Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364 values |
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PB-DFS | PB-DFS-master/PySCIPOpt/examples/finished/transp.py | ##@file transp.py
#@brief a model for the transportation problem
"""
Model for solving a transportation problem:
minimize the total transportation cost for satisfying demand at
customers, from capacitated facilities.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def transp(I,J,c,d,M):
"""transp -- model for solving the transportation problem
Parameters:
I - set of customers
J - set of facilities
c[i,j] - unit transportation cost on arc (i,j)
d[i] - demand at node i
M[j] - capacity
Returns a model, ready to be solved.
"""
model = Model("transportation")
# Create variables
x = {}
for i in I:
for j in J:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)" % (i, j))
# Demand constraints
for i in I:
model.addCons(quicksum(x[i,j] for j in J if (i,j) in x) == d[i], name="Demand(%s)" % i)
# Capacity constraints
for j in J:
model.addCons(quicksum(x[i,j] for i in I if (i,j) in x) <= M[j], name="Capacity(%s)" % j)
# Objective
model.setObjective(quicksum(c[i,j]*x[i,j] for (i,j) in x), "minimize")
model.optimize()
model.data = x
return model
def make_inst1():
"""creates example data set 1"""
I,d = multidict({1:80, 2:270, 3:250 , 4:160, 5:180}) # demand
J,M = multidict({1:500, 2:500, 3:500}) # capacity
c = {(1,1):4, (1,2):6, (1,3):9, # cost
(2,1):5, (2,2):4, (2,3):7,
(3,1):6, (3,2):3, (3,3):4,
(4,1):8, (4,2):5, (4,3):3,
(5,1):10, (5,2):8, (5,3):4,
}
return I,J,c,d,M
def make_inst2():
"""creates example data set 2"""
I,d = multidict({1:45, 2:20, 3:30 , 4:30}) # demand
J,M = multidict({1:35, 2:50, 3:40}) # capacity
c = {(1,1):8, (1,2):9, (1,3):14 , # {(customer,factory) : cost<float>}
(2,1):6, (2,2):12, (2,3):9 ,
(3,1):10, (3,2):13, (3,3):16 ,
(4,1):9, (4,2):7, (4,3):5 ,
}
return I,J,c,d,M
if __name__ == "__main__":
I,J,c,d,M = make_inst1();
# I,J,c,d,M = make_inst2();
model = transp(I,J,c,d,M)
model.optimize()
print("Optimal value:", model.getObjVal())
EPS = 1.e-6
x = model.data
for (i,j) in x:
if model.getVal(x[i,j]) > EPS:
print("sending quantity %10s from factory %3s to customer %3s" % (model.getVal(x[i,j]),j,i))
| 2,515 | 27.590909 | 104 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/finished/transp_nofn.py | ##@file transp_nofn.py
#@brief a model for the transportation problem
"""
Model for solving a transportation problem:
minimize the total transportation cost for satisfying demand at
customers, from capacitated facilities.
Data:
I - set of customers
J - set of facilities
c[i,j] - unit transportation cost on arc (i,j)
d[i] - demand at node i
M[j] - capacity
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
d = {1:80, 2:270, 3:250 , 4:160, 5:180} # demand
I = d.keys()
M = {1:500, 2:500, 3:500} # capacity
J = M.keys()
c = {(1,1):4, (1,2):6, (1,3):9, # cost
(2,1):5, (2,2):4, (2,3):7,
(3,1):6, (3,2):3, (3,3):4,
(4,1):8, (4,2):5, (4,3):3,
(5,1):10, (5,2):8, (5,3):4,
}
model = Model("transportation")
# Create variables
x = {}
for i in I:
for j in J:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)" % (i,j))
# Demand constraints
for i in I:
model.addCons(sum(x[i,j] for j in J if (i,j) in x) == d[i], name="Demand(%s)" % i)
# Capacity constraints
for j in J:
model.addCons(sum(x[i,j] for i in I if (i,j) in x) <= M[j], name="Capacity(%s)" % j)
# Objective
model.setObjective(quicksum(c[i,j]*x[i,j] for (i,j) in x), "minimize")
model.optimize()
print("Optimal value:", model.getObjVal())
EPS = 1.e-6
for (i,j) in x:
if model.getVal(x[i,j]) > EPS:
print("sending quantity %10s from factory %3s to customer %3s" % (model.getVal(x[i,j]),j,i))
| 1,527 | 23.645161 | 100 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/finished/tsp.py | ##@file tsp.py
#@brief solve the traveling salesman problem
"""
minimize the travel cost for visiting n customers exactly once
approach:
- start with assignment model
- add cuts until there are no sub-cycles
- two cutting plane possibilities (called inside "solve_tsp"):
- addcut: limit the number of edges in a connected component S to |S|-1
- addcut2: require the number of edges between two connected component to be >= 2
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
import networkx
from pyscipopt import Model, quicksum
def solve_tsp(V,c):
"""solve_tsp -- solve the traveling salesman problem
- start with assignment model
- add cuts until there are no sub-cycles
Parameters:
- V: set/list of nodes in the graph
- c[i,j]: cost for traversing edge (i,j)
Returns the optimum objective value and the list of edges used.
"""
def addcut(cut_edges):
G = networkx.Graph()
G.add_edges_from(cut_edges)
Components = list(networkx.connected_components(G))
if len(Components) == 1:
return False
model.freeTransform()
for S in Components:
model.addCons(quicksum(x[i,j] for i in S for j in S if j>i) <= len(S)-1)
print("cut: len(%s) <= %s" % (S,len(S)-1))
return True
def addcut2(cut_edges):
G = networkx.Graph()
G.add_edges_from(cut_edges)
Components = list(networkx.connected_components(G))
if len(Components) == 1:
return False
model.freeTransform()
for S in Components:
T = set(V) - set(S)
print("S:",S)
print("T:",T)
model.addCons(quicksum(x[i,j] for i in S for j in T if j>i) +
quicksum(x[i,j] for i in T for j in S if j>i) >= 2)
print("cut: %s >= 2" % "+".join([("x[%s,%s]" % (i,j)) for i in S for j in T if j>i]))
return True
# main part of the solution process:
model = Model("tsp")
model.hideOutput() # silent/verbose mode
x = {}
for i in V:
for j in V:
if j > i:
x[i,j] = model.addVar(ub=1, name="x(%s,%s)"%(i,j))
for i in V:
model.addCons(quicksum(x[j,i] for j in V if j < i) + \
quicksum(x[i,j] for j in V if j > i) == 2, "Degree(%s)"%i)
model.setObjective(quicksum(c[i,j]*x[i,j] for i in V for j in V if j > i), "minimize")
EPS = 1.e-6
isMIP = False
while True:
model.optimize()
edges = []
for (i,j) in x:
if model.getVal(x[i,j]) > EPS:
edges.append( (i,j) )
if addcut(edges) == False:
if isMIP: # integer variables, components connected: solution found
break
model.freeTransform()
for (i,j) in x: # all components connected, switch to integer model
model.chgVarType(x[i,j], "B")
isMIP = True
return model.getObjVal(),edges
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n):
"""make_data: compute matrix distance based on euclidean distance"""
V = range(1,n+1)
x = dict([(i,random.random()) for i in V])
y = dict([(i,random.random()) for i in V])
c = {}
for i in V:
for j in V:
if j > i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return V,c
if __name__ == "__main__":
import sys
# Parse argument
if len(sys.argv) < 2:
print("Usage: %s instance" % sys.argv[0])
print("Using randomized example instead")
n = 200
seed = 1
random.seed(seed)
V,c = make_data(n)
else:
from read_tsplib import read_tsplib
try:
V,c,x,y = read_tsplib(sys.argv[1])
except:
print("Cannot read TSPLIB file",sys.argv[1])
exit(1)
obj,edges = solve_tsp(V,c)
print("\nOptimal tour:",edges)
print("Optimal cost:",obj)
| 4,147 | 29.725926 | 97 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/finished/weber_soco.py | ##@file weber_soco.py
#@brief model for solving the weber problem using soco.
"""
Copyright (c) by Joao Pedro PEDROSO, Masahiro MURAMATSU and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def weber(I,x,y,w):
"""weber: model for solving the single source weber problem using soco.
Parameters:
- I: set of customers
- x[i]: x position of customer i
- y[i]: y position of customer i
- w[i]: weight of customer i
Returns a model, ready to be solved.
"""
model = Model("weber")
X,Y,z,xaux,yaux = {},{},{},{},{}
X = model.addVar(lb=-model.infinity(), vtype="C", name="X")
Y = model.addVar(lb=-model.infinity(), vtype="C", name="Y")
for i in I:
z[i] = model.addVar(vtype="C", name="z(%s)"%(i))
xaux[i] = model.addVar(lb=-model.infinity(), vtype="C", name="xaux(%s)"%(i))
yaux[i] = model.addVar(lb=-model.infinity(), vtype="C", name="yaux(%s)"%(i))
for i in I:
model.addCons(xaux[i]*xaux[i] + yaux[i]*yaux[i] <= z[i]*z[i], "MinDist(%s)"%(i))
model.addCons(xaux[i] == (x[i]-X), "xAux(%s)"%(i))
model.addCons(yaux[i] == (y[i]-Y), "yAux(%s)"%(i))
model.setObjective(quicksum(w[i]*z[i] for i in I), "minimize")
model.data = X,Y,z
return model
import random
def make_data(n,m):
"""creates example data set"""
I = range(1,n+1)
J = range(1,m+1)
x,y,w = {},{},{}
for i in I:
x[i] = random.randint(0,100)
y[i] = random.randint(0,100)
w[i] = random.randint(1,5)
return I,J,x,y,w
if __name__ == "__main__":
import sys
random.seed(3)
n = 7
m = 1
I,J,x,y,w = make_data(n,m)
print("data:")
print("%s\t%8s\t%8s\t%8s" % ("i","x[i]","y[i]","w[i]"))
for i in I:
print("%s\t%8g\t%8g\t%8g" % (i,x[i],y[i],w[i]))
print
model = weber(I,x,y,w)
model.optimize()
X,Y,z = model.data
print("Optimal value=",model.getObjVal())
print("Selected position:",)
print("\t",(round(model.getVal(X)),round(model.getVal(Y))))
print
print("Solution:")
print("%s\t%8s" % ("i","z[i]"))
for i in I:
print("%s\t%8g" % (i,model.getVal(z[i])))
print
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
G.add_nodes_from(I)
G.add_nodes_from(["D"])
position = {}
for i in I:
position[i] = (x[i],y[i])
position["D"] = (round(model.getVal(X)),round(model.getVal(Y)))
NX.draw(G,pos=position,node_size=200,node_color="g",nodelist=I)
NX.draw(G,pos=position,node_size=400,node_color="w",nodelist=["D"],alpha=0.5)
#P.savefig("weber.pdf",format="pdf",dpi=300)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
def weber_MS(I,J,x,y,w):
"""weber -- model for solving the weber problem using soco (multiple source version).
Parameters:
- I: set of customers
- J: set of potential facilities
- x[i]: x position of customer i
- y[i]: y position of customer i
- w[i]: weight of customer i
Returns a model, ready to be solved.
"""
M = max([((x[i]-x[j])**2 + (y[i]-y[j])**2) for i in I for j in I])
model = Model("weber - multiple source")
X,Y,v,u = {},{},{},{}
xaux,yaux,uaux = {},{},{}
for j in J:
X[j] = model.addVar(lb=-model.infinity(), vtype="C", name="X(%s)"%j)
Y[j] = model.addVar(lb=-model.infinity(), vtype="C", name="Y(%s)"%j)
for i in I:
v[i,j] = model.addVar(vtype="C", name="v(%s,%s)"%(i,j))
u[i,j] = model.addVar(vtype="B", name="u(%s,%s)"%(i,j))
xaux[i,j] = model.addVar(lb=-model.infinity(), vtype="C", name="xaux(%s,%s)"%(i,j))
yaux[i,j] = model.addVar(lb=-model.infinity(), vtype="C", name="yaux(%s,%s)"%(i,j))
uaux[i,j] = model.addVar(vtype="C", name="uaux(%s,%s)"%(i,j))
for i in I:
model.addCons(quicksum(u[i,j] for j in J) == 1, "Assign(%s)"%i)
for j in J:
model.addCons(xaux[i,j]*xaux[i,j] + yaux[i,j]*yaux[i,j] <= v[i,j]*v[i,j], "MinDist(%s,%s)"%(i,j))
model.addCons(xaux[i,j] == (x[i]-X[j]), "xAux(%s,%s)"%(i,j))
model.addCons(yaux[i,j] == (y[i]-Y[j]), "yAux(%s,%s)"%(i,j))
model.addCons(uaux[i,j] >= v[i,j] - M*(1-u[i,j]), "uAux(%s,%s)"%(i,j))
model.setObjective(quicksum(w[i]*uaux[i,j] for i in I for j in J), "minimize")
model.data = X,Y,v,u
return model
if __name__ == "__main__":
random.seed(3)
n = 7
m = 1
I,J,x,y,w = make_data(n,m)
model = weber_MS(I,J,x,y,w)
model.optimize()
X,Y,w,z = model.data
print("Optimal value:",model.getObjVal())
print("Selected positions:")
for j in J:
print("\t",(model.getVal(X[j]),model.getVal(Y[j])))
for (i,j) in sorted(w.keys()):
print("\t",(i,j),model.getVal(w[i,j]),model.getVal(z[i,j]))
EPS = 1.e-4
edges = [(i,j) for (i,j) in z if model.getVal(z[i,j]) > EPS]
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
G.add_nodes_from(I)
G.add_nodes_from("%s"%j for j in J) # for distinguishing J from I, make nodes as strings
for (i,j) in edges:
G.add_edge(i,"%s"%j)
position = {}
for i in I:
position[i] = (x[i],y[i])
for j in J:
position["%s"%j] = (model.getVal(X[j]),model.getVal(Y[j]))
print(position)
NX.draw(G,position,node_color="g",nodelist=I)
NX.draw(G,position,node_color="w",nodelist=["%s"%j for j in J])
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
| 5,924 | 31.554945 | 109 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/tutorial/even.py | ##@file tutorial/even.py
#@brief Tutorial example to check whether values are even or odd
"""
Public Domain, WTFNMFPL Public Licence
"""
from pyscipopt import Model
from pprint import pformat as pfmt
example_values = [
0,
1,
1.5,
"helloworld",
20,
25,
-101,
-15.,
-10,
-2**31,
-int(2**31),
"2**31-1",
int(2**31-1),
int(2**63)-1
]
verbose = False
#verbose = True # uncomment for additional info on variables!
sdic = {0: "even", 1: "odd"} # remainder to 2
def parity(number):
"""
Prints if a value is even/odd/neither per each value in a example list
This example is made for newcomers and motivated by:
- modulus is unsupported for pyscipopt.scip.Variable and int
- variables are non-integer by default
Based on this: #172#issuecomment-394644046
Args:
number: value which parity is checked
Returns:
sval: 1 if number is odd, 0 if number is even, -1 if neither
"""
sval = -1
if verbose:
print(80*"*")
try:
assert number == int(round(number))
m = Model()
m.hideOutput()
# x and n are integer, s is binary
# Irrespective to their type, variables are non-negative by default
# since 0 is the default lb. To allow for negative values, give None
# as lower bound.
# (None means -infinity as lower bound and +infinity as upper bound)
x = m.addVar("x", vtype="I", lb=None, ub=None) #ub=None is default
n = m.addVar("n", vtype="I", lb=None)
s = m.addVar("s", vtype="B")
# CAVEAT: if number is negative, x's lower bound must be None
# if x is set by default as non-negative and number is negative:
# there is no feasible solution (trivial) but the program
# does not highlight which constraints conflict.
m.addCons(x==number)
# minimize the difference between the number and twice a natural number
m.addCons(s == x-2*n)
m.setObjective(s)
m.optimize()
assert m.getStatus() == "optimal"
boolmod = m.getVal(s) == m.getVal(x)%2
if verbose:
for v in m.getVars():
print("%*s: %d" % (fmtlen, v,m.getVal(v)))
print("%*d%%2 == %d?" % (fmtlen, m.getVal(x), m.getVal(s)))
print("%*s" % (fmtlen, boolmod))
xval = m.getVal(x)
sval = m.getVal(s)
sstr = sdic[sval]
print("%*d is %s" % (fmtlen, xval, sstr))
except (AssertionError, TypeError):
print("%*s is neither even nor odd!" % (fmtlen, number.__repr__()))
finally:
if verbose:
print(80*"*")
print("")
return sval
if __name__ == "__main__":
"""
If positional arguments are given:
the parity check is performed on each of them
Else:
the parity check is performed on each of the default example values
"""
import sys
from ast import literal_eval as leval
try:
# check parity for each positional arguments
sys.argv[1]
values = sys.argv[1:]
except IndexError:
# check parity for each default example value
values = example_values
# format lenght, cosmetics
fmtlen = max([len(fmt) for fmt in pfmt(values,width=1).split('\n')])
for value in values:
try:
n = leval(value)
except (ValueError, SyntaxError): # for numbers or str w/ spaces
n = value
parity(n)
| 3,583 | 29.632479 | 79 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/tutorial/logical.py | ##@file tutorial/logical.py
#@brief Tutorial example on how to use AND/OR/XOR constraints.
"""
N.B.: standard SCIP XOR constraint works differently from AND/OR by design.
The constraint is set with a boolean rhs instead of an integer resultant.
cf. http://listserv.zib.de/pipermail/scip/2018-May/003392.html
A workaround to get the resultant as variable is here proposed.
Public Domain, WTFNMFPL Public Licence
"""
from pyscipopt import Model
from pyscipopt import quicksum
def _init():
model = Model()
model.hideOutput()
x = model.addVar("x","B")
y = model.addVar("y","B")
z = model.addVar("z","B")
return model, x, y, z
def _optimize(name, m):
m.optimize()
print("* %s constraint *" % name)
objSet = bool(m.getObjective().terms.keys())
print("* Is objective set? %s" % objSet)
if objSet:
print("* Sense: %s" % m.getObjectiveSense())
status = m.getStatus()
print("* Model status: %s" % status)
if status == 'optimal':
for v in m.getVars():
if v.name != "n":
print("%s: %d" % (v, round(m.getVal(v))))
else:
print("* No variable is printed if model status is not optimal")
print("")
def and_constraint(v=1, sense="minimize"):
""" AND constraint """
assert v in [0,1], "v must be 0 or 1 instead of %s" % v.__repr__()
model, x, y, z = _init()
r = model.addVar("r", "B")
model.addConsAnd([x,y,z], r)
model.addCons(x==v)
model.setObjective(r, sense=sense)
_optimize("AND", model)
def or_constraint(v=0, sense="maximize"):
""" OR constraint"""
assert v in [0,1], "v must be 0 or 1 instead of %s" % v.__repr__()
model, x, y, z = _init()
r = model.addVar("r", "B")
model.addConsOr([x,y,z], r)
model.addCons(x==v)
model.setObjective(r, sense=sense)
_optimize("OR", model)
def xors_constraint(v=1):
""" XOR (r as boolean) standard constraint"""
assert v in [0,1], "v must be 0 or 1 instead of %s" % v.__repr__()
model, x, y, z = _init()
r = True
model.addConsXor([x,y,z], r)
model.addCons(x==v)
_optimize("Standard XOR (as boolean)", model)
def xorc_constraint(v=0, sense="maximize"):
""" XOR (r as variable) custom constraint"""
assert v in [0,1], "v must be 0 or 1 instead of %s" % v.__repr__()
model, x, y, z = _init()
r = model.addVar("r", "B")
n = model.addVar("n", "I") # auxiliary
model.addCons(r+quicksum([x,y,z]) == 2*n)
model.addCons(x==v)
model.setObjective(r, sense=sense)
_optimize("Custom XOR (as variable)", model)
if __name__ == "__main__":
and_constraint()
or_constraint()
xors_constraint()
xorc_constraint()
| 2,686 | 30.244186 | 75 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/tutorial/puzzle.py | ##@file tutorial/puzzle.py
#@brief solve a simple puzzle using SCIP
"""
On a beach there are octopuses, turtles and cranes.
The total number of legs of all animals is 80, while the number of heads is 32.
What are the minimum numbers of turtles and octopuses, respectively?
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model
model = Model("puzzle")
x = model.addVar(vtype="I", name="octopusses")
y = model.addVar(vtype="I", name="turtles")
z = model.addVar(vtype="I", name="cranes")
# Set up constraint for number of heads
model.addCons(x + y + z == 32, name="Heads")
# Set up constraint for number of legs
model.addCons(8*x + 4*y + 2*z == 80, name="Legs")
# Set objective function
model.setObjective(x + y, "minimize")
model.hideOutput()
model.optimize()
#solution = model.getBestSol()
print("Optimal value:", model.getObjVal())
print((x.name, y.name, z.name), " = ", (model.getVal(x), model.getVal(y), model.getVal(z)))
| 967 | 28.333333 | 91 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/cutstock.py | #todo relax function needed
"""
cutstock.py: use SCIP for solving the cutting stock problem.
The instance of the cutting stock problem is represented by the two
lists of m items of size w=(w_i) and and quantity q=(q_i).
The roll size is B.
Given packing patterns t_1, ...,t_k,...t_K where t_k is a vector of
the numbers of items cut from a roll, the problem is reduced to the
following LP:
minimize sum_{k} x_k
subject to sum_{k} t_k(i) x_k >= q_i for all i
x_k >=0 for all k.
We apply a column generation approch (Gilmore-Gomory approach) in
which we generate cutting patterns by solving a knapsack sub-problem.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
LOG = True
EPS = 1.e-6
def solveCuttingStock(w,q,B):
"""solveCuttingStock: use column generation (Gilmore-Gomory approach).
Parameters:
- w: list of item's widths
- q: number of items of a width
- B: bin/roll capacity
Returns a solution: list of lists, each of which with the cuts of a roll.
"""
t = [] # patterns
m = len(w)
# Generate initial patterns with one size for each item width
for (i,width) in enumerate(w):
pat = [0]*m # vector of number of orders to be packed into one roll (bin)
pat[i] = int(B/width)
t.append(pat)
# if LOG:
# print "sizes of orders=",w
# print "quantities of orders=",q
# print "roll size=",B
# print "initial patterns",t
K = len(t)
master = Model("master LP") # master LP problem
x = {}
for k in range(K):
x[k] = master.addVar(vtype="I", name="x(%s)"%k)
orders = {}
for i in range(m):
orders[i] = master.addCons(
quicksum(t[k][i]*x[k] for k in range(K) if t[k][i] > 0) >= q[i], "Order(%s)"%i)
master.setObjective(quicksum(x[k] for k in range(K)), "minimize")
# master.Params.OutputFlag = 0 # silent mode
# iter = 0
while True:
# print "current patterns:"
# for ti in t:
# print ti
# print
# iter += 1
relax = master.relax()
relax.optimize()
pi = [relax.getDualsolLinear(c) for c in relax.getConss()] # keep dual variables
knapsack = Model("KP") # knapsack sub-problem
knapsack.setMaximize # maximize
y = {}
for i in range(m):
y[i] = knapsack.addVar(lb=0, ub=q[i], vtype="I", name="y(%s)"%i)
knapsack.addCons(quicksum(w[i]*y[i] for i in range(m)) <= B, "Width")
knapsack.setObjective(quicksum(pi[i]*y[i] for i in range(m)), "maximize")
knapsack.hideOutput() # silent mode
knapsack.optimize()
# if LOG:
# print "objective of knapsack problem:", knapsack.ObjVal
if knapsack.getObjVal() < 1+EPS: # break if no more columns
break
pat = [int(y[i].X+0.5) for i in y] # new pattern
t.append(pat)
# if LOG:
# print "shadow prices and new pattern:"
# for (i,d) in enumerate(pi):
# print "\t%5s%12s%7s" % (i,d,pat[i])
# print
# add new column to the master problem
col = Column()
for i in range(m):
if t[K][i] > 0:
col.addTerms(t[K][i], orders[i])
x[K] = master.addVar(obj=1, vtype="I", name="x(%s)"%K, column=col)
# master.write("MP" + str(iter) + ".lp")
K += 1
# Finally, solve the IP
# if LOG:
# master.Params.OutputFlag = 1 # verbose mode
master.optimize()
# if LOG:
# print
# print "final solution (integer master problem): objective =", master.ObjVal
# print "patterns:"
# for k in x:
# if x[k].X > EPS:
# print "pattern",k,
# print "\tsizes:",
# print [w[i] for i in range(m) if t[k][i]>0 for j in range(t[k][i]) ],
# print "--> %s rolls" % int(x[k].X+.5)
rolls = []
for k in x:
for j in range(int(x[k].X + .5)):
rolls.append(sorted([w[i] for i in range(m) if t[k][i]>0 for j in range(t[k][i])]))
rolls.sort()
return rolls
def CuttingStockExample1():
"""CuttingStockExample1: create toy instance for the cutting stock problem."""
B = 110 # roll width (bin size)
w = [20,45,50,55,75] # width (size) of orders (items)
q = [48,35,24,10,8] # quantitiy of orders
return w,q,B
def CuttingStockExample2():
"""CuttingStockExample2: create toy instance for the cutting stock problem."""
B = 9 # roll width (bin size)
w = [2,3,4,5,6,7,8] # width (size) of orders (items)
q = [4,2,6,6,2,2,2] # quantitiy of orders
return w,q,B
def mkCuttingStock(s):
"""mkCuttingStock: convert a bin packing instance into cutting stock format"""
w,q = [],[] # list of different widths (sizes) of items, their quantities
for item in sorted(s):
if w == [] or item != w[-1]:
w.append(item)
q.append(1)
else:
q[-1] += 1
return w,q
def mkBinPacking(w,q):
"""mkBinPacking: convert a cutting stock instance into bin packing format"""
s = []
for j in range(len(w)):
for i in range(q[j]):
s.append(w[j])
return s
if __name__ == "__main__":
from bpp import FFD,solveBinPacking
w,q,B = CuttingStockExample1()
# w,q,B = CuttingStockExample2()
# n = 500
# B = 100
# s,B = DiscreteUniform(n,18,50,B)
s = mkBinPacking(w,q)
ffd = FFD(s,B)
print("\n\n\nSolution of FFD:")
print(ffd)
print(len(ffd), "bins")
print("\n\n\nCutting stock problem, column generation:")
rolls = solveCuttingStock(w,q,B)
print(len(rolls), "rolls:")
print(rolls)
print("\n\n\nBin packing problem:")
bins = solveBinPacking(s,B)
print(len(bins), "bins:")
print(bins)
| 6,000 | 28.561576 | 95 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/diet_std.py | """
diet.py: model for the modern diet problem
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def diet(F,N,a,b,c,d):
"""diet -- model for the modern diet problem
Parameters:
F - set of foods
N - set of nutrients
a[i] - minimum intake of nutrient i
b[i] - maximum intake of nutrient i
c[j] - cost of food j
d[j][i] - amount of nutrient i in food j
Returns a model, ready to be solved.
"""
model = Model("modern diet")
# Create variables
x,y,z = {},{},{}
for j in F:
x[j] = model.addVar(vtype="I", name="x(%s)" % j)
for i in N:
z[i] = model.addVar(lb=a[i], ub=b[i], vtype="C", name="z(%s)" % i)
# Constraints:
for i in N:
model.addCons(quicksum(d[j][i]*x[j] for j in F) == z[i], name="Nutr(%s)" % i)
model.setObjective(quicksum(c[j]*x[j] for j in F), "minimize")
model.data = x,y,z
return model
def make_inst():
"""make_inst: prepare data for the diet model"""
F,c,d = multidict({ # cost # composition
"CQPounder": [ 360, {"Cal":556, "Carbo":39, "Protein":30,
"VitA":147,"VitC": 10, "Calc":221, "Iron":2.4}],
"Big Mac" : [ 320, {"Cal":556, "Carbo":46, "Protein":26,
"VitA":97, "VitC": 9, "Calc":142, "Iron":2.4}],
"FFilet" : [ 270, {"Cal":356, "Carbo":42, "Protein":14,
"VitA":28, "VitC": 1, "Calc": 76, "Iron":0.7}],
"Chicken" : [ 290, {"Cal":431, "Carbo":45, "Protein":20,
"VitA": 9, "VitC": 2, "Calc": 37, "Iron":0.9}],
"Fries" : [ 190, {"Cal":249, "Carbo":30, "Protein": 3,
"VitA": 0, "VitC": 5, "Calc": 7, "Iron":0.6}],
"Milk" : [ 170, {"Cal":138, "Carbo":10, "Protein": 7,
"VitA":80, "VitC": 2, "Calc":227, "Iron": 0}],
"VegJuice" : [ 100, {"Cal": 69, "Carbo":17, "Protein": 1,
"VitA":750,"VitC": 2, "Calc":18, "Iron": 0}],
})
N,a,b = multidict({ # min,max intake
"Cal" : [ 2000, 3000],
"Carbo" : [ 300, 375 ],
"Protein" : [ 50, 60 ],
"VitA" : [ 500, 750 ],
"VitC" : [ 85, 100 ],
"Calc" : [ 660, 900 ],
"Iron" : [ 6.0, 7.5 ],
})
return F,N,a,b,c,d
if __name__ == "__main__":
F,N,a,b,c,d = make_inst()
model = diet(F,N,a,b,c,d)
model.optimize()
status = model.getStatus()
if status == "optimal":
print("Optimal value:",model.getObjVal())
x,y,z = model.data
for j in x:
if model.getVal(x[j]) > 0:
print((j,model.getVal(x[j])))
print("amount of nutrients:")
for i in z:
print((i,model.getVal(z[i])))
exit(0)
if status == "unbounded" or status == "infeasible":
model.setObjective(0, "maximize")
model.optimize()
status = model.getStatus()
if status == "optimal":
print("Instance unbounded")
elif status == "infeasible":
print("Infeasible instance")
# model.computeIIS()
# model.writeProblem("diet.lp")
# for c in model.getConss():
# if c.IISConstr:
# print(c.name)
# model.feasRelaxS(1,False,False,True)
# model.optimize()
# model.writeProblem("diet-feasiblity.lp")
# status = model.Status
# if status == "optimal":
# print("Optimal Value=",model.getObjVal())
# for v in model.getVars():
# print(v.name,"=",model.getVal(v))
# exit(0)
| 3,753 | 33.440367 | 85 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/eld.py | """
eld.py: economic load dispatching in electricity generation
Approach: use an SOS2 constraints for modeling non-linear functions.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
import math
import random
from piecewise import convex_comb_sos
def cost(a,b,c,e,f,p_min,p):
"""cost: fuel cost based on "standard" parameters
(with valve-point loading effect)
"""
return a + b*p + c*p*p + abs(e*math.sin(f*(p_min-p)))
def lower_brkpts(a,b,c,e,f,p_min,p_max,n):
"""lower_brkpts: lower approximation of the cost function
Parameters:
- a,...,p_max: cost parameters
- n: number of breakpoints' intervals to insert between valve points
Returns: list of breakpoints in the form [(x0,y0),...,(xK,yK)]
"""
EPS = 1.e-12 # for avoiding round-off errors
if f == 0: f = math.pi/(p_max-p_min)
brk = []
nvalve = int(math.ceil(f*(p_max-p_min)/math.pi))
for i in range(nvalve+1):
p0 = p_min + i*math.pi/f
if p0 >= p_max-EPS:
brk.append((p_max,cost(a,b,c,e,f,p_min,p_max)))
break
for j in range(n):
p = p0 + j*math.pi/f/n
if p >= p_max:
break
brk.append((p,cost(a,b,c,e,f,p_min,p)))
return brk
def eld_complete(U,p_min,p_max,d,brk):
"""eld -- economic load dispatching in electricity generation
Parameters:
- U: set of generators (units)
- p_min[u]: minimum operating power for unit u
- p_max[u]: maximum operating power for unit u
- d: demand
- brk[k]: (x,y) coordinates of breakpoint k, k=0,...,K
Returns a model, ready to be solved.
"""
model = Model("Economic load dispatching")
p,F = {},{}
for u in U:
p[u] = model.addVar(lb=p_min[u], ub=p_max[u], name="p(%s)"%u) # capacity
F[u] = model.addVar(lb=0,name="fuel(%s)"%u)
# set fuel costs based on piecewise linear approximation
for u in U:
abrk = [X for (X,Y) in brk[u]]
bbrk = [Y for (X,Y) in brk[u]]
# convex combination part:
K = len(brk[u])-1
z = {}
for k in range(K+1):
z[k] = model.addVar(ub=1) # do not name variables for avoiding clash
model.addCons(p[u] == quicksum(abrk[k]*z[k] for k in range(K+1)))
model.addCons(F[u] == quicksum(bbrk[k]*z[k] for k in range(K+1)))
model.addCons(quicksum(z[k] for k in range(K+1)) == 1)
model.addConsSOS2([z[k] for k in range(K+1)])
# demand satisfaction
model.addCons(quicksum(p[u] for u in U) == d, "demand")
# objective
model.setObjective(quicksum(F[u] for u in U), "minimize")
model.data = p
return model
def eld_another(U,p_min,p_max,d,brk):
"""eld -- economic load dispatching in electricity generation
Parameters:
- U: set of generators (units)
- p_min[u]: minimum operating power for unit u
- p_max[u]: maximum operating power for unit u
- d: demand
- brk[u][k]: (x,y) coordinates of breakpoint k, k=0,...,K for unit u
Returns a model, ready to be solved.
"""
model = Model("Economic load dispatching")
# set objective based on piecewise linear approximation
p,F,z = {},{},{}
for u in U:
abrk = [X for (X,Y) in brk[u]]
bbrk = [Y for (X,Y) in brk[u]]
p[u],F[u],z[u] = convex_comb_sos(model,abrk,bbrk)
p[u].lb = p_min[u]
p[u].ub = p_max[u]
# demand satisfaction
model.addCons(quicksum(p[u] for u in U) == d, "demand")
# objective
model.setObjective(quicksum(F[u] for u in U), "minimize")
model.data = p
return model
def eld13():
U, a, b, c, e, f, p_min, p_max = multidict({
1 : [ 550, 8.1, 0.00028, 300, 0.035, 0, 680 ],
2 : [ 309, 8.1, 0.00056, 200, 0.042, 0, 360 ],
3 : [ 307, 8.1, 0.00056, 200, 0.042, 0, 360 ],
4 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
5 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
6 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
7 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
8 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
9 : [ 240, 7.74, 0.00324, 150, 0.063, 60, 180 ],
10 : [ 126, 8.6, 0.00284, 100, 0.084, 40, 120 ],
11 : [ 126, 8.6, 0.00284, 100, 0.084, 40, 120 ],
12 : [ 126, 8.6, 0.00284, 100, 0.084, 55, 120 ],
13 : [ 126, 8.6, 0.00284, 100, 0.084, 55, 120 ],
})
return U, a, b, c, e, f, p_min, p_max
def eld40():
U, a, b, c, e, f, p_min, p_max = multidict({
1 : [ 94.705, 6.73, 0.00690, 100, 0.084, 36, 114],
2 : [ 94.705, 6.73, 0.00690, 100, 0.084, 36, 114],
3 : [ 309.54, 7.07, 0.02028, 100, 0.084, 60, 120],
4 : [ 369.03, 8.18, 0.00942, 150, 0.063, 80, 190],
5 : [ 148.89, 5.35, 0.01140, 120, 0.077, 47, 97],
6 : [ 222.33, 8.05, 0.01142, 100, 0.084, 68, 140],
7 : [ 287.71, 8.03, 0.00357, 200, 0.042, 110, 300],
8 : [ 391.98, 6.99, 0.00492, 200, 0.042, 135, 300],
9 : [ 455.76, 6.60, 0.00573, 200, 0.042, 135, 300],
10 : [ 722.82, 12.9, 0.00605, 200, 0.042, 130, 300],
11 : [ 635.20, 12.9, 0.00515, 200, 0.042, 94, 375],
12 : [ 654.69, 12.8, 0.00569, 200, 0.042, 94, 375],
13 : [ 913.40, 12.5, 0.00421, 300, 0.035, 125, 500],
14 : [ 1760.4, 8.84, 0.00752, 300, 0.035, 125, 500],
15 : [ 1728.3, 9.15, 0.00708, 300, 0.035, 125, 500],
16 : [ 1728.3, 9.15, 0.00708, 300, 0.035, 125, 500],
17 : [ 647.85, 7.97, 0.00313, 300, 0.035, 220, 500],
18 : [ 649.69, 7.95, 0.00313, 300, 0.035, 220, 500],
19 : [ 647.83, 7.97, 0.00313, 300, 0.035, 242, 550],
20 : [ 647.81, 7.97, 0.00313, 300, 0.035, 242, 550],
21 : [ 785.96, 6.63, 0.00298, 300, 0.035, 254, 550],
22 : [ 785.96, 6.63, 0.00298, 300, 0.035, 254, 550],
23 : [ 794.53, 6.66, 0.00284, 300, 0.035, 254, 550],
24 : [ 794.53, 6.66, 0.00284, 300, 0.035, 254, 550],
25 : [ 801.32, 7.10, 0.00277, 300, 0.035, 254, 550],
26 : [ 801.32, 7.10, 0.00277, 300, 0.035, 254, 550],
27 : [ 1055.1, 3.33, 0.52124, 120, 0.077, 10, 150],
28 : [ 1055.1, 3.33, 0.52124, 120, 0.077, 10, 150],
29 : [ 1055.1, 3.33, 0.52124, 120, 0.077, 10, 150],
30 : [ 148.89, 5.35, 0.01140, 120, 0.077, 47, 97],
31 : [ 222.92, 6.43, 0.00160, 150, 0.063, 60, 190],
32 : [ 222.92, 6.43, 0.00160, 150, 0.063, 60, 190],
33 : [ 222.92, 6.43, 0.00160, 150, 0.063, 60, 190],
34 : [ 107.87, 8.95, 0.00010, 200, 0.042, 90, 200],
35 : [ 116.58, 8.62, 0.00010, 200, 0.042, 90, 200],
36 : [ 116.58, 8.62, 0.00010, 200, 0.042, 90, 200],
37 : [ 307.45, 5.88, 0.01610, 80, 0.098, 25, 110],
38 : [ 307.45, 5.88, 0.01610, 80, 0.098, 25, 110],
39 : [ 307.45, 5.88, 0.01610, 80, 0.098, 25, 110],
40 : [ 647.83, 7.97, 0.00313, 300, 0.035, 242, 550],
})
U = list(a.keys())
return U,a,b,c,e,f,p_min,p_max,d
if __name__ == "__main__":
# U,a,b,c,e,f,p_min,p_max = eld13(); d=1800
U,a,b,c,e,f,p_min,p_max = eld13(); d=2520
# U,a,b,c,e,f,p_min,p_max = eld40(); d=10500
n = 100 # number of breakpoints between valve points
brk = {}
for u in U:
brk[u] = lower_brkpts(a[u],b[u],c[u],e[u],f[u],p_min[u],p_max[u],n)
lower = eld_complete(U,p_min,p_max,d,brk)
# lower = eld_another(U,p_min,p_max,d,brk)
lower.setRealParam("limits/gap", 1e-12)
lower.setRealParam("limits/absgap", 1e-12)
lower.setRealParam("numerics/feastol", 1e-9)
lower.optimize()
p = lower.data
print("Lower bound:",lower.ObjBound)
UB = sum(cost(a[u],b[u],c[u],e[u],f[u],p_min[u],lower.getVal(p[u])) for u in U)
print("Upper bound:",UB)
print("Solution:")
for u in p:
print(u,lower.getVal(p[u]))
| 8,669 | 40.090047 | 83 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/eoq_soco.py | """
eoq_soco.py: model to the multi-item economic ordering quantity problem.
Approach: use second-order cone optimization.
Copyright (c) by Joao Pedro PEDROSO, Masahiro MURAMATSU and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def eoq_soco(I,F,h,d,w,W):
"""eoq_soco -- multi-item capacitated economic ordering quantity model using soco
Parameters:
- I: set of items
- F[i]: ordering cost for item i
- h[i]: holding cost for item i
- d[i]: demand for item i
- w[i]: unit weight for item i
- W: capacity (limit on order quantity)
Returns a model, ready to be solved.
"""
model = Model("EOQ model using SOCO")
T,c = {},{}
for i in I:
T[i] = model.addVar(vtype="C", name="T(%s)"%i) # cycle time for item i
c[i] = model.addVar(vtype="C", name="c(%s)"%i) # total cost for item i
for i in I:
model.addCons(F[i] <= c[i]*T[i])
model.addCons(quicksum(w[i]*d[i]*T[i] for i in I) <= W)
model.setObjective(quicksum(c[i] + h[i]*d[i]*T[i]*0.5 for i in I), "minimize")
model.data = T,c
return model
if __name__ == "__main__":
# multiple item EOQ
I,F,h,d,w = multidict(
{1:[300,10,10,20],
2:[300,10,30,40],
3:[300,10,50,10]}
)
W = 2000
model = eoq_soco(I,F,h,d,w,W)
model.optimize()
T,c = model.data
EPS = 1.e-6
print("%5s\t%8s\t%8s" % ("i","T[i]","c[i]"))
for i in I:
print("%5s\t%8g\t%8g" % (i,model.getVal(T[i]),model.getVal(c[i])))
print
print("Optimal value:", model.getObjVal())
| 1,616 | 26.87931 | 86 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/flp_nonlinear.py | # todo
"""
flp_nonlinear.py: piecewise linear model for the capacitated facility location problem
minimize the total (weighted) travel cost from n customers to a
given set of facilities, with fixed costs and limited capacities;
costs are nonlinear (square root of the total quantity serviced
by a facility).
Approaches: use
- convex combination
- multiple selection
formulations defined in 'piecewise.py'.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
from pyscipopt import Model, quicksum, multidict
from piecewise import *
def flp_nonlinear_mselect(I,J,d,M,f,c,K):
"""flp_nonlinear_mselect -- use multiple selection model
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- piecewise linear version with multiple selection")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,z = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],z[j] = mult_selection(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * z[j][k] for k in range(K)),\
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_cc_dis_strong(I,J,d,M,f,c,K):
"""flp_nonlinear_bin -- use convex combination model, with binary variables
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- piecewise linear version with convex combination")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,z = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],z[j] = convex_comb_dis(model,a[j],b[j])
X[j].ub = M[j]
for i in I:
model.addCons(
x[i,j] <= \
quicksum(min(d[i],a[j][k+1]) * z[j][k] for k in range(K)),\
"Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_cc_dis(I,J,d,M,f,c,K):
"""flp_nonlinear_bin -- use convex combination model, with binary variables
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- piecewise linear version with convex combination")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,z = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],z[j] = convex_comb_dis(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * z[j][k] for k in range(K)),\
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_cc_dis_log(I,J,d,M,f,c,K):
"""flp_nonlinear_cc_dis_log -- convex combination model with logarithmic number of binary variables
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- convex combination model with logarithmic number of binary variables")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,yL,yR = {},{},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],yL[j],yR[j] = convex_comb_dis_log(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * (yL[j][k]+yR[j][k]) for k in range(K)),\
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_cc_agg(I,J,d,M,f,c,K):
"""flp_nonlinear_cc_agg -- aggregated convex combination model
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- piecewise linear aggregated convex combination")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,z = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],z[j] = convex_comb_agg(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * z[j][k] for k in range(K)),\
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_cc_agg_log(I,J,d,M,f,c,K):
"""flp_nonlinear_cc_agg_logg -- aggregated convex combination model, with log. binary variables
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- piecewise linear version with convex combination")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,y = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],y[j] = convex_comb_agg_log(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * (y[j][k]+y[j][k+1]) for k in range(K)),\
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def flp_nonlinear_sos(I,J,d,M,f,c,K):
"""flp_nonlinear_sos -- use model with SOS constraints
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
- K: number of linear pieces for approximation of non-linear cost function
Returns a model, ready to be solved.
"""
a,b = {},{}
for j in J:
U = M[j]
L = 0
width = U/float(K)
a[j] = [k*width for k in range(K+1)]
b[j] = [f[j]*math.sqrt(value) for value in a[j]]
model = Model("nonlinear flp -- use model with SOS constraints")
x = {}
for j in J:
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# total volume transported from plant j, corresponding (linearized) cost, selection variable:
X,F,z = {},{},{}
for j in J:
# add constraints for linking piecewise linear part:
X[j],F[j],z[j] = convex_comb_sos(model,a[j],b[j])
X[j].ub = M[j]
# for i in I:
# model.addCons(
# x[i,j] <= \
# quicksum(min(d[i],a[j][k+1]) * (z[j][k] + z[j][k+1])\
# for k in range(len(a[j])-1)),
# "Strong(%s,%s)"%(i,j))
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.setObjective(quicksum(F[j] for j in J) +\
quicksum(c[i,j]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,X,F
return model
def distance(x1,y1,x2,y2):
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n,m,same=True):
x,y = {},{}
if same == True:
I = range(1,n+1)
J = range(1,m+1)
for i in range(1,1+max(m,n)): # positions of the points in the plane
x[i] = random.random()
y[i] = random.random()
else:
I = range(1,n+1)
J = range(n+1,n+m+1)
for i in I: # positions of the points in the plane
x[i] = random.random()
y[i] = random.random()
for j in J: # positions of the points in the plane
x[j] = random.random()
y[j] = random.random()
f,c,d,M = {},{},{},{}
total_demand = 0.
for i in I:
for j in J:
c[i,j] = int(100*distance(x[i],y[i],x[j],y[j])) + 1
d[i] = random.randint(1,10)
total_demand += d[i]
total_cap = 0.
r = {}
for j in J:
r[j] = random.randint(0,m)
f[j] = random.randint(100,100+r[j]*m)
M[j] = 1 + 100+r[j]*m - f[j]
# M[j] = int(total_demand/m) + random.randint(1,m)
total_cap += M[j]
for j in J:
M[j] = int(M[j] * total_demand / total_cap + 1) + random.randint(0,r[j])
# print("%s\t%s\t%s" % (j,f[j],M[j])
# print("demand:",total_demand
# print("capacity:",sum([M[j] for j in J])
return I,J,d,M,f,c,x,y
def example():
I,d = multidict({1:80, 2:270, 3:250, 4:160, 5:180}) # demand
J,M,f = multidict({10:[500,100], 11:[500,100], 12:[500,100]}) # capacity, fixed costs
c = {(1,10):4, (1,11):6, (1,12):9, # transportation costs
(2,10):5, (2,11):4, (2,12):7,
(3,10):6, (3,11):3, (3,12):4,
(4,10):8, (4,11):5, (4,12):3,
(5,10):10, (5,11):8, (5,12):4,
}
x_pos = {1:0, 2:0, 3:0, 4:0, 5:0, 10:2, 11:2, 12:2} # positions of the points in the plane
y_pos = {1:2, 2:1, 3:0, 4:-1, 5:-2, 10:1, 11:0, 12:-1}
return I,J,d,M,f,c,x_pos,y_pos
if __name__ == "__main__":
# I,J,d,M,f,c,x_pos,y_pos = example()
random.seed(1)
n = 25
m = 5
I,J,d,M,f,c,x_pos,y_pos = make_data(n,m,same=False)
# from flp_make_data import read_orlib,read_cortinhal
# I,J,d,M,f,c,x_pos,y_pos = read_orlib("DATA/ORLIB/cap101.txt.gz")
# I,J,d,M,f,c,x_pos,y_pos = read_cortinhal("DATA/8_25/A8_25_11.DAT")
# I,J,d,M,f,c,x_pos,y_pos = example()
K = 4
print("demand:",d)
print("cost:",c)
print("fixed:",f)
print("capacity:",M)
# print("x:",x_pos
# print("y:",y_pos
print("number of intervals:",K)
print("\n\n\nflp: multiple selection")
model = flp_nonlinear_mselect(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objMS = model.getObjVal()
print("Obj.",objMS)
print("\n\n\nflp: convex combination with binary variables")
model = flp_nonlinear_cc_dis(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objCC = model.getObjVal()
print("Obj.",objCC)
print("\n\n\nflp: convex combination with logarithmic number of binary variables")
model = flp_nonlinear_cc_dis_log(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objLOG = model.getObjVal()
print("Obj.",objLOG)
print("\n\n\nflp: model with SOS constraints")
model = flp_nonlinear_sos(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objSOS = model.getObjVal()
print("Obj.",objSOS)
print("\n\n\nflp: aggregated CC model")
model = flp_nonlinear_cc_agg(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objND = model.getObjVal()
print("Obj.",objND)
print("\n\n\nflp: aggregated CC model, log number variables")
model = flp_nonlinear_cc_agg_log(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput() # silent/verbose mode
model.optimize()
objNDlog = model.getObjVal()
print("Obj.",objNDlog)
EPS = 1.e-4
assert abs(objCC-objMS)<EPS and abs(objLOG-objMS)<EPS and abs(objSOS-objMS)<EPS\
and abs(objSOS-objND)<EPS and abs(objSOS-objNDlog)<EPS
edges = []
flow = {}
for (i,j) in sorted(x):
if model.getVal(x[i,j]) > EPS:
edges.append((i,j))
flow[(i,j)] = model.getVal(x[i,j])
print("\n\n\nflp: model with piecewise linear approximation of cost function")
print("Obj.",model.getObjVal(),"\nedges",sorted(edges))
print("flows:",flow)
if x_pos == None:
exit(0)
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
facilities = J
client = I
G.add_nodes_from(facilities)
G.add_nodes_from(client)
for (i,j) in edges:
G.add_edge(i,j)
position = {}
for i in I + J:
position[i] = (x_pos[i],y_pos[i])
NX.draw(G,position,node_color="g",nodelist=client)
NX.draw(G,position,node_color="y",nodelist=facilities)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
| 19,258 | 32.262522 | 106 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/flp_nonlinear_soco.py | # todo
"""
flp_nonlinear.py: soco approach to the capacitated facility location problem
minimize the total (weighted) travel cost from n customers to a
given set of facilities, with fixed costs and limited capacities;
costs are nonlinear (square root of the total quantity serviced
by a facility).
Approach: use a second-order cone optimization formulation.
Copyright (c) by Joao Pedro PEDROSO, Masahiro MURAMATSU and Mikio KUBO, 2012
"""
import math
import random
from pyscipopt import Model, quicksum, multidict
def flp_nonlinear_soco(I,J,d,M,f,c):
"""flp_nonlinear_soco -- use
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for product i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
Returns a model, ready to be solved.
"""
model = Model("nonlinear flp -- soco formulation")
x,X,u = {},{},{}
for j in J:
X[j] = model.addVar(ub=M[j], vtype="C", name="X(%s)"%j) # for sum_i x_ij
u[j] = model.addVar(vtype="C", name="u(%s)"%j) # for replacing sqrt sum_i x_ij in soco
for i in I:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j)) # i's demand satisfied from j
# constraints for customer's demand satisfaction
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == 1, "Demand(%s)"%i)
for j in J:
model.addCons(quicksum(d[i]*x[i,j] for i in I) == X[j], "Capacity(%s)"%j)
model.addQConstr(quicksum(f[j]**2*d[i]*x[i,j]*x[i,j] for i in I) <= u[j]*u[j], "SOC(%s)"%j)
model.setObjective(quicksum(u[j] for j in J) +\
quicksum(c[i,j]*d[i]*x[i,j] for j in J for i in I),\
"minimize")
model.data = x,u
return model
if __name__ == "__main__":
from flp_nonlinear import distance,make_data,example,read_orlib,read_cortinhal
# I,J,d,M,f,c,x_pos,y_pos = example()
K = 100
random.seed(1)
n = 25
m = 5
I,J,d,M,f,c,x_pos,y_pos = make_data(n,m)
# I,J,d,M,f,c,x_pos,y_pos = read_orlib("DATA/cap41.txt.gz")
# I,J,d,M,f,c,x_pos,y_pos = read_cortinhal("DATA/8_25/A8_25_11.DAT.gz")
print("demand:",d)
print("cost:",c)
print("fixed:",f)
print("capacity:",M)
print("x:",x_pos)
print("y:",y_pos)
print("number of intervals:",K)
from flp_nonlinear import flp_nonlinear_sos
print("\n\n\nflp: model with SOS constraints")
model = flp_nonlinear_sos(I,J,d,M,f,c,K)
x,X,F = model.data
model.hideOutput = 1 # silent/verbose mode
model.optimize()
objSOS = model.getObjVal()
print("obj:",objSOS)
EPS = 1.e-4
# assert abs(objSOS-objSOCO) < EPS
edges = []
for (i,j) in sorted(x):
if model.getVal(x[i,j]) > EPS:
edges.append((i,j))
print("\n\n\nflp: model with piecewise linear approximation of cost function")
print("obj:",model.getObjVal(),"\nedges",sorted(edges))
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
facilities = J
client = I
G.add_nodes_from(facilities)
G.add_nodes_from(client)
for (i,j) in edges:
G.add_edge(i,j)
position = {}
for i in I + J:
position[i] = (x_pos[i],y_pos[i])
NX.draw(G,position,node_color="g",nodelist=client)
NX.draw(G,position,node_color="y",nodelist=facilities)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
print("\n\n\nflp: soco model")
model = flp_nonlinear_soco(I,J,d,M,f,c)
x,u = model.data
model.hideOutput = 1 # silent/verbose mode
model.optimize()
objSOCO = model.getObjVal()
print("obj:",objSOCO)
EPS = 1.e-4
# assert abs(objSOS-objSOCO) < EPS
edges = []
for (i,j) in sorted(x):
if model.getVal(x[i,j]) > EPS:
edges.append((i,j))
print("\n\n\nflp: model with piecewise linear approximation of cost function")
print("obj:",model.getObjVal(),"\nedges",sorted(edges))
if x_pos == None:
exit(0)
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
facilities = J
client = I
G.add_nodes_from(facilities)
G.add_nodes_from(client)
for (i,j) in edges:
G.add_edge(i,j)
position = {}
for i in I + J:
position[i] = (x_pos[i],y_pos[i])
NX.draw(G,position,node_color="g",nodelist=client)
NX.draw(G,position,node_color="y",nodelist=facilities)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
| 4,919 | 30.33758 | 99 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/kcenter.py | """
kcenter.py: model for solving the k-center problem.
select k facility positions such that the maximum distance
of each vertex in the graph to a facility is minimum
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def kcenter(I,J,c,k):
"""kcenter -- minimize the maximum travel cost from customers to k facilities.
Parameters:
- I: set of customers
- J: set of potential facilities
- c[i,j]: cost of servicing customer i from facility j
- k: number of facilities to be used
Returns a model, ready to be solved.
"""
model = Model("k-center")
z = model.addVar(vtype="C", name="z")
x,y = {},{}
for j in J:
y[j] = model.addVar(vtype="B", name="y(%s)"%j)
for i in I:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j))
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == 1, "Assign(%s)"%i)
for j in J:
model.addCons(x[i,j] <= y[j], "Strong(%s,%s)"%(i,j))
model.addCons(c[i,j]*x[i,j] <= z, "Max_x(%s,%s)"%(i,j))
model.addCons(quicksum(y[j] for j in J) == k, "Facilities")
model.setObjective(z, "minimize")
model.data = x,y
return model
import math
import random
def distance(x1,y1,x2,y2):
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n,m,same=True):
if same == True:
I = range(n)
J = range(m)
x = [random.random() for i in range(max(m,n))] # positions of the points in the plane
y = [random.random() for i in range(max(m,n))]
else:
I = range(n)
J = range(n,n+m)
x = [random.random() for i in range(n+m)] # positions of the points in the plane
y = [random.random() for i in range(n+m)]
c = {}
for i in I:
for j in J:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return I,J,c,x,y
if __name__ == "__main__":
random.seed(67)
n = 100
m = n
I,J,c,x_pos,y_pos = make_data(n,m,same=True)
k = 10
model = kcenter(I,J,c,k)
model.optimize()
EPS = 1.e-6
x,y = model.data
edges = [(i,j) for (i,j) in x if model.getVal(x[i,j]) > EPS]
facilities = [j for j in y if model.getVal(y[j]) > EPS]
print("Optimal value:", model.getObjVal())
print("Selected facilities:", facilities)
print("Edges:", edges)
print("max c:", max([c[i,j] for (i,j) in edges]))
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
facilities = set(j for j in J if model.getVal(y[j]) > EPS)
other = set(j for j in J if j not in facilities)
client = set(i for i in I if i not in facilities and i not in other)
G.add_nodes_from(facilities)
G.add_nodes_from(client)
G.add_nodes_from(other)
for (i,j) in edges:
G.add_edge(i,j)
position = {}
for i in range(len(x_pos)):
position[i] = (x_pos[i],y_pos[i])
NX.draw(G,position,with_labels=False,node_color="w",nodelist=facilities)
NX.draw(G,position,with_labels=False,node_color="c",nodelist=other,node_size=50)
NX.draw(G,position,with_labels=False,node_color="g",nodelist=client,node_size=50)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
| 3,449 | 29.263158 | 96 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/kcenter_binary_search.py | """
kcenter_binary_search.py: use bisection for solving the k-center problem
bisects the interval [0, max facility-customer distance] until finding a
distance such that all customers are covered, but decreasing that distance
by a small amount delta would leave some uncovered.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def kcover(I,J,c,k):
"""kcover -- minimize the number of uncovered customers from k facilities.
Parameters:
- I: set of customers
- J: set of potential facilities
- c[i,j]: cost of servicing customer i from facility j
- k: number of facilities to be used
Returns a model, ready to be solved.
"""
model = Model("k-center")
z,y,x = {},{},{}
for i in I:
z[i] = model.addVar(vtype="B", name="z(%s)"%i, obj=1)
for j in J:
y[j] = model.addVar(vtype="B", name="y(%s)"%j)
for i in I:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j))
for i in I:
model.addCons(quicksum(x[i,j] for j in J) + z[i] == 1, "Assign(%s)"%i)
for j in J:
model.addCons(x[i,j] <= y[j], "Strong(%s,%s)"%(i,j))
model.addCons(sum(y[j] for j in J) == k, "k_center")
model.data = x,y,z
return model
def solve_kcenter(I,J,c,k,delta):
"""solve_kcenter -- locate k facilities minimizing distance of most distant customer.
Parameters:
I - set of customers
J - set of potential facilities
c[i,j] - cost of servicing customer i from facility j
k - number of facilities to be used
delta - tolerance for terminating bisection
Returns:
- list of facilities to be used
- edges linking them to customers
"""
model = kcover(I,J,c,k)
x,y,z = model.data
facilities,edges = [],[]
LB = 0
UB = max(c[i,j] for (i,j) in c)
model.setObjlimit(0.1)
while UB-LB > delta:
theta = (UB+LB) / 2.
# print "\n\ncurrent theta:", theta
for j in J:
for i in I:
if c[i,j]>theta:
model.chgVarUb(x[i,j], 0.0)
else:
model.chgVarUb(x[i,j], 1.0)
# model.Params.OutputFlag = 0 # silent mode
model.setObjlimit(.1)
model.optimize()
if model.getStatus == "optimal":
# infeasibility = sum([z[i].X for i in I])
# print "infeasibility=",infeasibility
UB = theta
facilities = [j for j in y if model.getVal(y[j]) > .5]
edges = [(i,j) for (i,j) in x if model.getVal(x[i,j]) > .5]
# print "updated solution:"
# print "facilities",facilities
# print "edges",edges
else: # infeasibility > 0:
LB = theta
return facilities,edges
import math
import random
def distance(x1,y1,x2,y2):
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n,m,same=True):
if same == True:
I = range(n)
J = range(m)
x = [random.random() for i in range(max(m,n))] # positions of the points in the plane
y = [random.random() for i in range(max(m,n))]
else:
I = range(n)
J = range(n,n+m)
x = [random.random() for i in range(n+m)] # positions of the points in the plane
y = [random.random() for i in range(n+m)]
c = {}
for i in I:
for j in J:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return I,J,c,x,y
if __name__ == "__main__":
random.seed(67)
n = 200
m = n
I,J,c,x_pos,y_pos = make_data(n,m,same=True)
k = 20
delta = 1.e-4
facilities,edges = solve_kcenter(I,J,c,k,delta)
print("Selected facilities:", facilities)
print("Edges:", edges)
print("Max distance from a facility to a customer: ", max([c[i,j] for (i,j) in edges]))
try: # plot the result using networkx and matplotlib
import networkx as NX
import matplotlib.pyplot as P
P.clf()
G = NX.Graph()
facilities = set(facilities)
unused = set(j for j in J if j not in facilities)
client = set(i for i in I if i not in facilities and i not in unused)
G.add_nodes_from(facilities)
G.add_nodes_from(client)
G.add_nodes_from(unused)
for (i,j) in edges:
G.add_edge(i,j)
position = {}
for i in range(len(x_pos)):
position[i] = (x_pos[i],y_pos[i])
NX.draw(G,position,with_labels=False,node_color="w",nodelist=facilities)
NX.draw(G,position,with_labels=False,node_color="c",nodelist=unused,node_size=50)
NX.draw(G,position,with_labels=False,node_color="g",nodelist=client,node_size=50)
P.show()
except ImportError:
print("install 'networkx' and 'matplotlib' for plotting")
| 4,857 | 30.141026 | 96 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/lotsizing.py | """
lotsizing.py: solve the multi-item lot-sizing problem.
Approaches:
- mils: solve the problem using the standard formulation
- mils_fl: solve the problem using the facility location (tighten) formulation
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import random
from pyscipopt import Model, quicksum
def mils(T,P,f,g,c,d,h,M):
"""
mils: standard formulation for the multi-item lot-sizing problem
Parameters:
- T: number of periods
- P: set of products
- f[t,p]: set-up costs (on period t, for product p)
- g[t,p]: set-up times
- c[t,p]: variable costs
- d[t,p]: demand values
- h[t,p]: holding costs
- M[t]: resource upper bound on period t
Returns a model, ready to be solved.
"""
def mils_callback(model,where):
# remember to set model.params.DualReductions = 0 before using!
if where != GRB.Callback.MIPSOL and where != GRB.Callback.MIPNODE:
return
for p in P:
for ell in Ts:
lhs = 0
S,L = [],[]
for t in range(1,ell+1):
yt = model.cbGetSolution(y[t,p])
xt = model.cbGetSolution(x[t,p])
if D[t,ell,p]*yt < xt:
S.append(t)
lhs += D[t,ell,p]*yt
else:
L.append(t)
lhs += xt
if lhs < D[1,ell,p]:
# add cutting plane constraint
model.cbLazy(quicksum(x[t,p] for t in L) +\
quicksum(D[t,ell,p] * y[t,p] for t in S)
>= D[1,ell,p])
return
model = Model("standard multi-item lotsizing")
y,x,I = {},{},{}
Ts = range(1,T+1)
for p in P:
for t in Ts:
y[t,p] = model.addVar(vtype="B", name="y(%s,%s)"%(t,p))
x[t,p] = model.addVar(vtype="C", name="x(%s,%s)"%(t,p))
I[t,p] = model.addVar(vtype="C", name="I(%s,%s)"%(t,p))
I[0,p] = 0
for t in Ts:
# time capacity constraints
model.addCons(quicksum(g[t,p]*y[t,p] + x[t,p] for p in P) <= M[t], "TimeUB(%s)"%(t))
for p in P:
# flow conservation constraints
model.addCons(I[t-1,p] + x[t,p] == I[t,p] + d[t,p], "FlowCons(%s,%s)"%(t,p))
# capacity connection constraints
model.addCons(x[t,p] <= (M[t]-g[t,p])*y[t,p], "ConstrUB(%s,%s)"%(t,p))
# tighten constraints
model.addCons(x[t,p] <= d[t,p]*y[t,p] + I[t,p], "Tighten(%s,%s)"%(t,p))
model.setObjective(\
quicksum(f[t,p]*y[t,p] + c[t,p]*x[t,p] + h[t,p]*I[t,p] for t in Ts for p in P),\
"minimize")
# compute D[i,j,p] = sum_{t=i}^j d[t,p]
D = {}
for p in P:
for t in Ts:
s = 0
for j in range(t,T+1):
s += d[j,p]
D[t,j,p] = s
model.data = y,x,I
return model,mils_callback
def mils_fl(T,P,f,g,c,d,h,M):
"""
mils_fl: facility location formulation for the multi-item lot-sizing problem
Requires more variables, but gives a better solution because LB is
better than the standard formulation. It can be used as a
heuristic method that is sometimes better than relax-and-fix.
Parameters:
- T: number of periods
- P: set of products
- f[t,p]: set-up costs (on period t, for product p)
- g[t,p]: set-up times
- c[t,p]: variable costs
- d[t,p]: demand values
- h[t,p]: holding costs
- M[t]: resource upper bound on period t
Returns a model, ready to be solved.
"""
Ts = range(1,T+1)
model = Model("multi-item lotsizing -- facility location formulation")
y,X = {},{}
for p in P:
for t in Ts:
y[t,p] = model.addVar(vtype="B", name="y(%s,%s)"%(t,p))
for s in range(1,t+1):
X[s,t,p] = model.addVar(name="X(%s,%s,%s)"%(s,t,p))
for t in Ts:
# capacity constraints
model.addCons(quicksum(X[t,s,p] for s in range(t,T+1) for p in P) + \
quicksum(g[t,p]*y[t,p] for p in P) <= M[t],
"Capacity(%s)"%(t))
for p in P:
# demand satisfaction constraints
model.addCons(quicksum(X[s,t,p] for s in range(1,t+1)) == d[t,p], "Demand(%s,%s)"%(t,p))
# connection constraints
for s in range(1,t+1):
model.addCons(X[s,t,p] <= d[t,p] * y[s,p], "Connect(%s,%s,%s)"%(s,t,p))
C = {} # variable costs plus holding costs
for p in P:
for s in Ts:
sumC = 0
for t in range(s,T+1):
C[s,t,p] = (c[s,p] + sumC)
sumC += h[t,p]
model.setObjective(quicksum(f[t,p]*y[t,p] for t in Ts for p in P) + \
quicksum(C[s,t,p]*X[s,t,p] for t in Ts for p in P for s in range(1,t+1)),
"minimize")
model.data = y,X
model.write("tmp.lp")
return model
def trigeiro(T,N,factor):
"""
Data generator for the multi-item lot-sizing problem
it uses a simular algorithm for generating the standard benchmarks in:
"Capacitated Lot Sizing with Setup Times" by
William W. Trigeiro, L. Joseph Thomas, John O. McClain
MANAGEMENT SCIENCE
Vol. 35, No. 3, March 1989, pp. 353-366
Parameters:
- T: number of periods
- N: number of products
- factor: value for controlling constraining factor of capacity:
- 0.75: lightly-constrained instances
- 1.10: constrained instances
"""
P = range(1,N+1)
f,g,c,d,h,M = {},{},{},{},{},{}
sumT = 0
for t in range(1,T+1):
for p in P:
# capacity used per unit production: 1, except for
# except for specific instances with random value in [0.5, 1.5]
# (not tackled in our model)
# setup times
g[t,p] = 10 * random.randint(1,5) # 10, 50: trigeiro's values
# set-up costs
f[t,p] = 100 * random.randint(1,10) # checked from Wolsey's instances
c[t,p] = 0 # variable costs
# demands
d[t,p] = 100+random.randint(-25,25) # checked from Wolsey's instances
if t <= 4:
if random.random() < .25: # trigeiro's parameter
d[t,p] = 0
sumT += g[t,p] + d[t,p] # sumT is the total capacity usage in the lot-for-lot solution
h[t,p] = random.randint(1,5) # holding costs; checked from Wolsey's instances
for t in range(1,T+1):
M[t] = int(float(sumT)/float(T)/factor)
return P,f,g,c,d,h,M
if __name__ == "__main__":
# test only a subset of instances
T,N,factor = 15,6,0.75
P,f,g,c,d,h,M = trigeiro(T,N,factor)
print("\n\n\nStandard formulation + cutting plane ======================")
model,mils_callback = mils(T,P,f,g,c,d,h,M)
model.setBoolParam("misc/allowdualreds", 0)
model.optimize(mils_callback)
y,x,I = model.data
print("Optimal value:",model.getObjVal())
standard = model.getObjVal()
print("%7s%7s%7s%7s%12s%12s" % ("prod","t","dem","y","x","I"))
for p in P:
for t in range(1,T+1):
print("%7s%7s%7s%7s%12s%12s" % \
(p,t,d[t,p],int(y[t,p].X+0.5),round(x[t,p].X,5),round(I[t,p].X,5)))
exit(0)
# to test all instances: remove 'exit' above
# sizes: 4 to 36 items, 15 to 30 time periods; table 2: T = 15, 30, N = 6, 12, 24
# all costs constant over time
for T in [15,30]:
for N in [6,12,24]:
for factor in [0.75,1.0,1.1]:
# 0.75: lightly-constrained instances
# 1.1: constrained instances
random.seed(1)
# T,P = 10,5 # number of periods and number of products
# # T,P = 30,24 # number of periods and number of products
# P,f,g,c,d,h,M = make_data(T,P)
P,f,g,c,d,h,M = trigeiro(T,N,factor)
#for i in d:
# d[i] = 100
# print("f",f
# print("g",g
# print("c",c
# print("d",d
# print("h",h
# print("M",M
print("\n\n\n*** Trigeiros instance for %s periods, %s products, %s capacity factor" %\
(T,N,factor))
# standard formulation
print("\n\n\nStandard formulation======================")
model,_ = mils(T,P,f,g,c,d,h,M)
model.optimize()
y,x,I = model.data
status = model.getStatus()
if status == "unbounded":
print("Unbounded instance")
elif status == "optimal":
print("Optimal value:",model.getObjVal())
standard = model.getObjVal()
print("%7s%7s%7s%7s%12s%12s" % ("prod","t","dem","y","x","I"))
for p in P:
for t in range(1,T+1):
print("%7s%7s%7s%7s%12s%12s" % \
(p,t,d[t,p],int(y[t,p].X+0.5),round(x[t,p].X,5),round(I[t,p].X,5)))
elif status != "unbounded" and status != "infeasible":
print("Optimization stopped with status",status)
else:
print("Instance infeasible")
# standard formulation + cutting plane
print("\n\n\nStandard formulation + cutting plane ======================")
model,mils_callback = mils(T,P,f,g,c,d,h,M)
model.params.DualReductions = 0
model.optimize(mils_callback)
y,x,I = model.data
status = model.getStatus()
if status == "unbounded":
print("Unbounded instance")
elif status == "optimal":
print("Optimal value:",model.getObjVal())
standard = model.getObjVal()
print("%7s%7s%7s%7s%12s%12s" % ("prod","t","dem","y","x","I"))
for p in P:
for t in range(1,T+1):
print("%7s%7s%7s%7s%12s%12s" % \
(p,t,d[t,p],int(y[t,p].X+0.5),round(x[t,p].X,5),round(I[t,p].X,5)))
assert abs(model.objval - standard) < 1.e-6
elif status != "unbounded" and status != "infeasible":
print("Optimization stopped with status",status)
else:
print("Instance infeasible")
# facility location formulation
print("\n\n\nFacility location formulation======================")
model = mils_fl(T,P,f,g,c,d,h,M)
model.optimize()
y,X = model.data
status = model.getStatus()
if status == "unbounded":
print("Unbounded instance")
elif status == "optimal":
print("Optimal value:",model.getObjVal())
print("%7s%7s%7s%7s%12s%12s" % ("prod","t","dem","y","sum(X)","inv.mov"))
for p in P:
for t in range(1,T+1):
xd = sum(X[t,s,p].X for s in range(t,T+1))
I = xd - d[t,p]
print("%7s%7s%7s%7s%12s%12s" % \
(p,t,d[t,p],int(y[t,p].X+0.5),round(xd,5),round(I)))
assert abs(model.objval - standard) < 1.e-6
elif status != "unbounded" and status != "infeasible":
print("Optimization stopped with status",status)
else:
print("Instance infeasible")
| 12,056 | 36.444099 | 110 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/lotsizing_cut.py | """
lotsizing_cut.py: solve the single-item lot-sizing problem.
Approaches:
- sils: solve the problem using the standard formulation
- sils_cut: solve the problem using cutting planes
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def sils(T,f,c,d,h):
"""sils -- LP lotsizing for the single item lot sizing problem
Parameters:
- T: number of periods
- P: set of products
- f[t]: set-up costs (on period t)
- c[t]: variable costs
- d[t]: demand values
- h[t]: holding costs
Returns a model, ready to be solved.
"""
model = Model("single item lotsizing")
Ts = range(1,T+1)
M = sum(d[t] for t in Ts)
y,x,I = {},{},{}
for t in Ts:
y[t] = model.addVar(vtype="I", ub=1, name="y(%s)"%t)
x[t] = model.addVar(vtype="C", ub=M, name="x(%s)"%t)
I[t] = model.addVar(vtype="C", name="I(%s)"%t)
I[0] = 0
for t in Ts:
model.addCons(x[t] <= M*y[t], "ConstrUB(%s)"%t)
model.addCons(I[t-1] + x[t] == I[t] + d[t], "FlowCons(%s)"%t)
model.setObjective(\
quicksum(f[t]*y[t] + c[t]*x[t] + h[t]*I[t] for t in Ts),\
"minimize")
model.data = y,x,I
return model
def sils_cut(T,f,c,d,h):
"""solve_sils -- solve the lot sizing problem with cutting planes
- start with a relaxed model
- add cuts until there are no fractional setup variables
Parameters:
- T: number of periods
- P: set of products
- f[t]: set-up costs (on period t)
- c[t]: variable costs
- d[t]: demand values
- h[t]: holding costs
Returns the final model solved, with all necessary cuts added.
"""
Ts = range(1,T+1)
model = sils(T,f,c,d,h)
y,x,I = model.data
# relax integer variables
for t in Ts:
y[t].vtype = "C"
# compute D[i,j] = sum_{t=i}^j d[t]
D = {}
for t in Ts:
s = 0
for j in range(t,T+1):
s += d[j]
D[t,j] = s
EPS = 1.e-6
cuts = True
while cuts:
model.optimize()
cuts = False
for ell in Ts:
lhs = 0
S,L = [],[]
for t in range(1,ell+1):
yt = model.getVal(y[t])
xt = model.getVal(x[t])
if D[t,ell]*yt < xt:
S.append(t)
lhs += D[t,ell]*yt
else:
L.append(t)
lhs += xt
if lhs < D[1,ell]:
# add cutting plane constraint
model.addCons(quicksum([x[t] for t in L]) +\
quicksum(D[t,ell] * y[t] for t in S)
>= D[1,ell])
cuts = True
model.data = y,x,I
return model
def mk_example():
"""mk_example: book example for the single item lot sizing"""
T = 5
_,f,c,d,h = multidict({
1 : [3,1,5,1],
2 : [3,1,7,1],
3 : [3,3,3,1],
4 : [3,3,6,1],
5 : [3,3,4,1],
})
return T,f,c,d,h
if __name__ == "__main__":
T,f,c,d,h = mk_example()
model = sils(T,f,c,d,h)
y,x,I = model.data
model.optimize()
print("\nOptimal value [standard]=",model.getObjVal())
print("%8s%8s%8s%8s%8s%8s%12s%12s" % ("t","fix","var","h","dem","y","x","I"))
for t in range(1,T+1):
print("%8s%8s%8s%8s%8s%8s%12s%12s" % (t,f[t],c[t],h[t],d[t],model.getVal(y[t]),model.getVal(x[t]),model.getVal(I[t])))
model = sils_cut(T,f,c,d,h)
y,x,I = model.data
print("\nnOptimal value [cutting planes]=",model.getObjVal())
print("%8s%8s%8s%8s%8s%8s%12s%12s" % ("t","fix","var","h","dem","y","x","I"))
for t in range(1,T+1):
print("%8s%8s%8s%8s%8s%8s%12s%12s" % (t,f[t],c[t],h[t],d[t],model.getVal(y[t]),model.getVal(x[t]),model.getVal(I[t])))
| 3,915 | 28.223881 | 126 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/lotsizing_echelon.py | """
lotsizing.py: solve the multi-item, multi-stage lot-sizing problem.
Approaches:
- mils_standard: standard formulation
- mils_echelon: echelon formulation
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import random
from pyscipopt import Model, quicksum, multidict
def mils_standard(T,K,P,f,g,c,d,h,a,M,UB,phi):
"""
mils_standard: standard formulation for the multi-item, multi-stage lot-sizing problem
Parameters:
- T: number of periods
- K: set of resources
- P: set of items
- f[t,p]: set-up costs (on period t, for product p)
- g[t,p]: set-up times
- c[t,p]: variable costs
- d[t,p]: demand values
- h[t,p]: holding costs
- a[t,k,p]: amount of resource k for producing p in period t
- M[t,k]: resource k upper bound on period t
- UB[t,p]: upper bound of production time of product p in period t
- phi[(i,j)]: units of i required to produce a unit of j (j parent of i)
"""
model = Model("multi-stage lotsizing -- standard formulation")
y,x,I = {},{},{}
Ts = range(1,T+1)
for p in P:
for t in Ts:
y[t,p] = model.addVar(vtype="B", name="y(%s,%s)"%(t,p))
x[t,p] = model.addVar(vtype="C",name="x(%s,%s)"%(t,p))
I[t,p] = model.addVar(vtype="C",name="I(%s,%s)"%(t,p))
I[0,p] = model.addVar(name="I(%s,%s)"%(0,p))
for t in Ts:
for p in P:
# flow conservation constraints
model.addCons(I[t-1,p] + x[t,p] == \
quicksum(phi[p,q]*x[t,q] for (p2,q) in phi if p2 == p) \
+ I[t,p] + d[t,p],
"FlowCons(%s,%s)"%(t,p))
# capacity connection constraints
model.addCons(x[t,p] <= UB[t,p]*y[t,p], "ConstrUB(%s,%s)"%(t,p))
# time capacity constraints
for k in K:
model.addCons(quicksum(a[t,k,p]*x[t,p] + g[t,p]*y[t,p] for p in P) <= M[t,k],
"TimeUB(%s,%s)"%(t,k))
# initial inventory quantities
for p in P:
model.addCons(I[0,p] == 0, "InventInit(%s)"%(p))
model.setObjective(\
quicksum(f[t,p]*y[t,p] + c[t,p]*x[t,p] + h[t,p]*I[t,p] for t in Ts for p in P), \
"minimize")
model.data = y,x,I
return model
def sum_phi(k,rho,pred,phi):
for j in pred[k]:
if (j,k) in rho:
continue
rho[j,k] = phi[j,k]
sum_phi(j,rho,pred,phi)
for i in pred[j]:
if (i,k) in rho:
rho[i,k] += rho[i,j] * phi[j,k]
else:
rho[i,k] = rho[i,j] * phi[j,k]
return
def calc_rho(phi):
v = set()
for (i,j) in phi:
v.add(i)
v.add(j)
pred,succ = {},{}
for i in v:
pred[i] = set()
succ[i] = set()
for (i,j) in phi:
pred[j].add(i)
succ[i].add(j)
# set of vertices corresponding to end products:
final = set(i for i in v if len(succ[i]) == 0)
rho = {}
for j in final:
sum_phi(j,rho,pred,phi)
return rho
def mils_echelon(T,K,P,f,g,c,d,h,a,M,UB,phi):
"""
mils_echelon: echelon formulation for the multi-item, multi-stage lot-sizing problem
Parameters:
- T: number of periods
- K: set of resources
- P: set of items
- f[t,p]: set-up costs (on period t, for product p)
- g[t,p]: set-up times
- c[t,p]: variable costs
- d[t,p]: demand values
- h[t,p]: holding costs
- a[t,k,p]: amount of resource k for producing p in period t
- M[t,k]: resource k upper bound on period t
- UB[t,p]: upper bound of production time of product p in period t
- phi[(i,j)]: units of i required to produce a unit of j (j parent of i)
"""
rho = calc_rho(phi) # rho[(i,j)]: units of i required to produce a unit of j (j ancestor of i)
model = Model("multi-stage lotsizing -- echelon formulation")
y,x,E,H = {},{},{},{}
Ts = range(1,T+1)
for p in P:
for t in Ts:
y[t,p] = model.addVar(vtype="B", name="y(%s,%s)"%(t,p))
x[t,p] = model.addVar(vtype="C", name="x(%s,%s)"%(t,p))
H[t,p] = h[t,p] - sum([h[t,q]*phi[q,p] for (q,p2) in phi if p2 == p])
E[t,p] = model.addVar(vtype="C", name="E(%s,%s)"%(t,p)) # echelon inventory
E[0,p] = model.addVar(vtype="C", name="E(%s,%s)"%(0,p)) # echelon inventory
for t in Ts:
for p in P:
# flow conservation constraints
dsum = d[t,p] + sum([rho[p,q]*d[t,q] for (p2,q) in rho if p2 == p])
model.addCons(E[t-1,p] + x[t,p] == E[t,p] + dsum, "FlowCons(%s,%s)"%(t,p))
# capacity connection constraints
model.addCons(x[t,p] <= UB[t,p]*y[t,p], "ConstrUB(%s,%s)"%(t,p))
# time capacity constraints
for k in K:
model.addCons(quicksum(a[t,k,p]*x[t,p] + g[t,p]*y[t,p] for p in P) <= M[t,k],
"TimeUB(%s,%s)"%(t,k))
# calculate echelon quantities
for p in P:
model.addCons(E[0,p] == 0, "EchelonInit(%s)"%(p))
for t in Ts:
model.addCons(E[t,p] >= quicksum(phi[p,q]*E[t,q] for (p2,q) in phi if p2 == p),
"EchelonLB(%s,%s)"%(t,p))
model.setObjective(\
quicksum(f[t,p]*y[t,p] + c[t,p]*x[t,p] + H[t,p]*E[t,p] for t in Ts for p in P), \
"minimize")
model.data = y,x,E
return model
def make_data():
"""
1..T: set of periods
K: set of resources
P: set of items
f[t,p]: set-up costs
g[t,p]: set-up times
c[t,p]: variable costs
d[t,p]: demand values
h[t,p]: holding costs
a[t,k,p]: amount of resource k for producing product p in period. t
M[t,k]: resource upper bounds
UB[t,p]: upper bound of production time of product p in period t
phi[(i,j)] : units of i required to produce a unit of j (j parent of i)
"""
T = 5
K = [1]
P = [1,2,3,4,5]
_,f,g,c,d,h,UB = multidict({
(1,1): [10, 1, 2, 0, 0.5, 24],
(1,2): [10, 1, 2, 0, 0.5, 24],
(1,3): [10, 1, 2, 0, 0.5, 24],
(1,4): [10, 1, 2, 0, 0.5, 24],
(1,5): [10, 1, 2, 0, 0.5, 24],
(2,1): [10, 1, 2, 0, 0.5, 24],
(2,2): [10, 1, 2, 0, 0.5, 24],
(2,3): [10, 1, 2, 0, 0.5, 24],
(2,4): [10, 1, 2, 0, 0.5, 24],
(2,5): [10, 1, 2, 0, 0.5, 24],
(3,1): [10, 1, 2, 0, 0.5, 24],
(3,2): [10, 1, 2, 0, 0.5, 24],
(3,3): [10, 1, 2, 0, 0.5, 24],
(3,4): [10, 1, 2, 0, 0.5, 24],
(3,5): [10, 1, 2, 0, 0.5, 24],
(4,1): [10, 1, 2, 0, 0.5, 24],
(4,2): [10, 1, 2, 0, 0.5, 24],
(4,3): [10, 1, 2, 0, 0.5, 24],
(4,4): [10, 1, 2, 0, 0.5, 24],
(4,5): [10, 1, 2, 0, 0.5, 24],
(5,1): [10, 1, 2, 0, 0.5, 24],
(5,2): [10, 1, 2, 0, 0.5, 24],
(5,3): [10, 1, 2, 0, 0.5, 24],
(5,4): [10, 1, 2, 0, 0.5, 24],
(5,5): [10, 1, 2, 5, 0.5, 24],
})
a = {
(1,1,1): 1,
(1,1,2): 1,
(1,1,3): 1,
(1,1,4): 1,
(1,1,5): 1,
(2,1,1): 1,
(2,1,2): 1,
(2,1,3): 1,
(2,1,4): 1,
(2,1,5): 1,
(3,1,1): 1,
(3,1,2): 1,
(3,1,3): 1,
(3,1,4): 1,
(3,1,5): 1,
(4,1,1): 1,
(4,1,2): 1,
(4,1,3): 1,
(4,1,4): 1,
(4,1,5): 1,
(5,1,1): 1,
(5,1,2): 1,
(5,1,3): 1,
(5,1,4): 1,
(5,1,5): 1,
}
M = {
(1,1): 15,
(2,1): 15,
(3,1): 15,
(4,1): 15,
(5,1): 15,
}
phi = { # phi[(i,j)] : units of i required to produce a unit of j (j parent of i)
(1,3):2,
(2,3):3,
(2,4):3/2.,
(3,5):1/2.,
(4,5):3
}
return T,K,P,f,g,c,d,h,a,M,UB,phi
def make_data_10():
"""
1..T: set of periods
K: set of resources
P: set of items
f[t,p]: set-up costs
g[t,p]: set-up times
c[t,p]: variable costs
d[t,p]: demand values
h[t,p]: holding costs
a[t,k,p]: amount of resource k for producing product p in period. t
M[t,k]: resource upper bounds
UB[t,p]: upper bound of production time of product p in period t
phi[(i,j)] : units of i required to produce a unit of j (j parent of i)
"""
T = 5
K = [1]
P = [1,2,3,4,5,6,7,8,9,10]
_, f, g, c, d, h, UB = multidict({
(1,1): [10, 1, 2, 0, 0.5, 24],
(1,2): [10, 1, 2, 0, 0.5, 24],
(1,3): [10, 1, 2, 0, 0.5, 24],
(1,4): [10, 1, 2, 0, 0.5, 24],
(1,5): [10, 1, 2, 0, 0.5, 24],
(1,6): [10, 1, 2, 0, 0.5, 24],
(1,7): [10, 1, 2, 0, 0.5, 24],
(1,8): [10, 1, 2, 0, 0.5, 24],
(1,9): [10, 1, 2, 0, 0.5, 24],
(1,10):[10, 1, 2, 0, 0.5, 24],
(2,1): [10, 1, 2, 0, 0.5, 24],
(2,2): [10, 1, 2, 0, 0.5, 24],
(2,3): [10, 1, 2, 0, 0.5, 24],
(2,4): [10, 1, 2, 0, 0.5, 24],
(2,5): [10, 1, 2, 0, 0.5, 24],
(2,6): [10, 1, 2, 0, 0.5, 24],
(2,7): [10, 1, 2, 0, 0.5, 24],
(2,8): [10, 1, 2, 0, 0.5, 24],
(2,9): [10, 1, 2, 0, 0.5, 24],
(2,10):[10, 1, 2, 0, 0.5, 24],
(3,1): [10, 1, 2, 0, 0.5, 24],
(3,2): [10, 1, 2, 0, 0.5, 24],
(3,3): [10, 1, 2, 0, 0.5, 24],
(3,4): [10, 1, 2, 0, 0.5, 24],
(3,5): [10, 1, 2, 0, 0.5, 24],
(3,6): [10, 1, 2, 0, 0.5, 24],
(3,7): [10, 1, 2, 0, 0.5, 24],
(3,8): [10, 1, 2, 0, 0.5, 24],
(3,9): [10, 1, 2, 0, 0.5, 24],
(3,10):[10, 1, 2, 0, 0.5, 24],
(4,1): [10, 1, 2, 0, 0.5, 24],
(4,2): [10, 1, 2, 0, 0.5, 24],
(4,3): [10, 1, 2, 0, 0.5, 24],
(4,4): [10, 1, 2, 0, 0.5, 24],
(4,5): [10, 1, 2, 0, 0.5, 24],
(4,6): [10, 1, 2, 0, 0.5, 24],
(4,7): [10, 1, 2, 0, 0.5, 24],
(4,8): [10, 1, 2, 0, 0.5, 24],
(4,9): [10, 1, 2, 0, 0.5, 24],
(4,10):[10, 1, 2, 0, 0.5, 24],
(5,1): [10, 1, 2, 0, 0.5, 24],
(5,2): [10, 1, 2, 0, 0.5, 24],
(5,3): [10, 1, 2, 0, 0.5, 24],
(5,4): [10, 1, 2, 0, 0.5, 24],
(5,5): [10, 1, 2, 0, 0.5, 24],
(5,6): [10, 1, 2, 0, 0.5, 24],
(5,7): [10, 1, 2, 0, 0.5, 24],
(5,8): [10, 1, 2, 0, 0.5, 24],
(5,9): [10, 1, 2, 0, 0.5, 24],
(5,10):[10, 1, 2, 5, 0.5, 24],
})
a = {
(1,1,1): 1, (1,1,2): 1, (1,1,3): 1, (1,1,4): 1, (1,1,5): 1, (1,1,6): 1, (1,1,7): 1, (1,1,8): 1, (1,1,9): 1, (1,1,10): 1,
(2,1,1): 1, (2,1,2): 1, (2,1,3): 1, (2,1,4): 1, (2,1,5): 1, (2,1,6): 1, (2,1,7): 1, (2,1,8): 1, (2,1,9): 1, (2,1,10): 1,
(3,1,1): 1, (3,1,2): 1, (3,1,3): 1, (3,1,4): 1, (3,1,5): 1, (3,1,6): 1, (3,1,7): 1, (3,1,8): 1, (3,1,9): 1, (3,1,10): 1,
(4,1,1): 1, (4,1,2): 1, (4,1,3): 1, (4,1,4): 1, (4,1,5): 1, (4,1,6): 1, (4,1,7): 1, (4,1,8): 1, (4,1,9): 1, (4,1,10): 1,
(5,1,1): 1, (5,1,2): 1, (5,1,3): 1, (5,1,4): 1, (5,1,5): 1, (5,1,6): 1, (5,1,7): 1, (5,1,8): 1, (5,1,9): 1, (5,1,10): 1,
}
M = {
(1,1): 25,
(2,1): 25,
(3,1): 25,
(4,1): 25,
(5,1): 25,
(6,1): 25,
(7,1): 25,
(8,1): 25,
(9,1): 25,
(10,1):25,
}
phi = { # phi[(i,j)] : units of i required to produce a unit of j (j parent of i)
(1,2):1,
(2,5):2,
(3,4):3,
(4,5):1,
(5,6):1,
(6,10):1/2.,
(3,7):1,
(7,8):3/2.,
(8,9):3,
(9,10):1
}
return T,K,P,f,g,c,d,h,a,M,UB,phi
if __name__ == "__main__":
random.seed(1)
# T,K,P,f,g,c,d,h,a,M,UB,phi = make_data()
T,K,P,f,g,c,d,h,a,M,UB,phi = make_data_10()
# print("periods",T
# print("products:",P
# print("resources:",K
# print("demand",d
# print("a (resource used)",a
# print("g (setup time)",g
# print("M",M
# print("UB",UB
# print("phi",phi
# print("rho",calc_rho(phi)
print("\n\nstandard model")
model = mils_standard(T,K,P,f,g,c,d,h,a,M,UB,phi)
# model.setParam("MIPGap",0.0)
# model.write("lotsize_standard.lp")
model.optimize()
status = model.getStatus()
if status == "unbounded":
print("The model cannot be solved because it is unbounded")
elif status == "optimal":
print("Optimal value:", model.getObjVal())
standard = model.getObjVal()
y,x,I = model.data
print("%7s%7s%7s%7s%12s%12s" % ("prod","t","dem","y","x","I"))
for p in P:
print("%7s%7s%7s%7s%12s%12s" % (p,0,"-","-","-",round(model.getVal(I[0,p]),5)))
for t in range(1,T+1):
print("%7s%7s%7s%7s%12s%12s" % (p,t,d[t,p],int(model.getVal(y[t,p])+0.5),round(model.getVal(x[t,p]),5),round(model.getVal(I[t,p]),5)))
print("\n")
for k in K:
for t in range(1,T+1):
print("resource %3s used in period %s: %12s / %-9s" % (k,t,sum(a[t,k,p]*model.getVal(x[t,p])+g[t,p]*model.getVal(y[t,p]) for p in P),M[t,k]))
elif status != "unbounded" and status != "infeasible":
print("Optimization was stopped with status",status)
else:
print("The model is infeasible")
# model.computeIIS()
# print("\nThe following constraint(s) cannot be satisfied:")
# for cnstr in model.getConstrs():
# if cnstr.IISConstr:
# print(cnstr.ConstrName)
print("\n\nechelon model")
model = mils_echelon(T,K,P,f,g,c,d,h,a,M,UB,phi)
model.setRealParam("limits/gap", 0.0)
# model.write("lotsize_echelon.lp")
model.optimize()
status = model.getStatus()
if status == "unbounded":
print("The model cannot be solved because it is unbounded")
elif status == "optimal":
print("Opt.value=",model.getObjVal())
y,x,E = model.data
print("%7s%7s%7s%7s%12s%12s" % ("t","prod","dem","y","x","E"))
for p in P:
print("%7s%7s%7s%7s%12s%12s" % ("t",p,"-","-","-",round(model.getVal(E[0,p]),5)))
for t in range(1,T+1):
print("%7s%7s%7s%7s%12s%12s" %\
(t,p,d[t,p],int(model.getVal(y[t,p])+0.5),round(model.getVal(x[t,p]),5),round(model.getVal(E[t,p]),5)))
print("\n")
for k in K:
for t in range(1,T+1):
print("resource %3s used in period %s: %12s / %-9s" % \
(k,t,sum(a[t,k,p]*model.getVal(x[t,p]) + g[t,p]*model.getVal(y[t,p]) for p in P),M[t,k]))
print(model.getObjVal() - standard)
assert abs(model.getObjVal() - standard) < 1.e-6
elif status != "unbounded" and status != "infeasible":
print("Optimization was stopped with status",status)
else:
print("The model is infeasible")
# model.computeIIS()
# print("\nThe following constraint(s) cannot be satisfied:")
# for cnstr in model.getConstrs():
# if cnstr.IISConstr:
# print(cnstr.ConstrName)
| 15,109 | 32.135965 | 157 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/mctransp_tuplelist.py | """
transp.py: a model for the multi-commodity transportation problem
Model for solving the multi-commodity transportation problem:
minimize the total transportation cost for satisfying demand at
customers, from capacitated facilities.
Use tuplelist for selecting arcs.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model
def mctransp(I,J,K,c,d,M):
"""mctransp -- model for solving the Multi-commodity Transportation Problem
Parameters:
- I: set of customers
- J: set of facilities
- K: set of commodities
- c[i,j,k]: unit transportation cost on arc (i,j) for commodity k
- d[i][k]: demand for commodity k at node i
- M[j]: capacity
Returns a model, ready to be solved.
"""
model = Model("multi-commodity transportation")
# Create variables
x = {}
for (i,j,k) in c:
x[i,j,k] = model.addVar(vtype="C", name="x(%s,%s,%s)" % (i,j,k), obj=c[i,j,k])
# tuplelist is a Gurobi data structure to manage lists of equal sized tuples - try itertools as alternative
arcs = tuplelist([(i,j,k) for (i,j,k) in x])
# Demand constraints
for i in I:
for k in K:
model.addCons(sum(x[i,j,k] for (i,j,k) in arcs.select(i,"*",k)) == d[i,k], "Demand(%s,%s)" % (i,k))
# Capacity constraints
for j in J:
model.addCons(sum(x[i,j,k] for (i,j,k) in arcs.select("*",j,"*")) <= M[j], "Capacity(%s)" % j)
model.data = x
return model
def make_inst1():
d = {(1,1):80, (1,2):85, (1,3):300, (1,4):6, # {customer: {commodity:demand <float>}}
(2,1):270, (2,2):160, (2,3):400, (2,4):7,
(3,1):250, (3,2):130, (3,3):350, (3,4):4,
(4,1):160, (4,2):60, (4,3):200, (4,4):3,
(5,1):180, (5,2):40, (5,3):150, (5,4):5
}
I = set([i for (i,k) in d])
K = set([k for (i,k) in d])
M = {1:3000, 2:3000, 3:3000} # capacity
J = M.keys()
produce = {1:[2,4], 2:[1,2,3], 3:[2,3,4]} # products that can be produced in each facility
weight = {1:5, 2:2, 3:3, 4:4} # {commodity: weight<float>}
cost = {(1,1):4, (1,2):6, (1,3):9, # {(customer,factory): cost<float>}
(2,1):5, (2,2):4, (2,3):7,
(3,1):6, (3,2):3, (3,3):4,
(4,1):8, (4,2):5, (4,3):3,
(5,1):10, (5,2):8, (5,3):4
}
c = {}
for i in I:
for j in J:
for k in produce[j]:
c[i,j,k] = cost[i,j] * weight[k]
return I,J,K,c,d,M
def make_inst2():
d = {(1,1):45, # {customer: {commodity:demand <float>}}
(2,1):20,
(3,1):30,
(4,1):30,
}
I = set([i for (i,k) in d])
K = set([k for (i,k) in d])
M = {1:35, 2:50, 3:40} # {factory: capacity<float>}}
J = M.keys()
produce = {1:[1], 2:[1], 3:[1]} # products that can be produced in each facility
weight = {1:1} # {commodity: weight<float>}
cost = {(1,1):8, (1,2):9, (1,3):14, # {(customer,factory): cost<float>}
(2,1):6, (2,2):12, (2,3):9 ,
(3,1):10, (3,2):13, (3,3):16,
(4,1):9, (4,2):7, (4,3):5 ,
}
c = {}
for i in I:
for j in J:
for k in produce[j]:
c[i,j,k] = cost[i,j] * weight[k]
return I,J,K,c,d,M
if __name__ == "__main__":
I,J,K,c,d,M = make_inst1();
model = mctransp(I,J,K,c,d,M)
model.writeProblem("transp.lp")
model.optimize()
print("Optimal value:",model.getObjVal())
EPS = 1.e-6
x = model.data
for (i,j,k) in x:
if model.getVal(x[i,j,k]) > EPS:
print("sending %10s units of %3s from plant %3s to customer %3s" % (model.getVal(x[i,j,k]),k,j,i))
| 3,806 | 30.46281 | 111 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/pareto_front.py | """
pareto_front.py: tools for building a pareto front in multi-objective optimization
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
def dominates(a,b):
dominating = False
for i in range(len(a)):
if a[i] > b[i]:
return False
if a[i] < b[i]:
dominating = True
return dominating
def is_dominated(a,front):
for b in front:
if dominates(b,a):
return True
return False
def pareto_front(cand):
front = set([])
for i in cand:
add_i = True
for j in list(front):
if dominates(i,j):
front.remove(j)
if dominates(j,i):
add_i = False
if add_i:
front.add(i)
front = list(front)
front.sort()
return front
if __name__ == "__main__":
import random
# random.seed(1)
cand = [(random.random()**.25,random.random()**.25) for i in range(100)]
import matplotlib.pyplot as plt
for (x,y) in cand:
plt.plot(x,y,"bo")
front = pareto_front(cand)
plt.plot([x for (x,y) in front], [y for (x,y) in front])
plt.show()
| 1,143 | 21.88 | 83 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/portfolio_soco.py | """
portfolio_soco.py: modified markowitz model for portfolio optimization.
Approach: use second-order cone optimization.
Copyright (c) by Joao Pedro PEDROSO, Masahiro MURAMATSU and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
import math
def phi_inv(p):
"""phi_inv: inverse of gaussian (normal) CDF
Source:
Handbook of Mathematical Functions
Dover Books on Mathematics
Milton Abramowitz and Irene A. Stegun (Editors)
Formula 26.2.23.
"""
if p < 0.5:
t = math.sqrt(-2.0*math.log(p))
return ((0.010328*t + 0.802853)*t + 2.515517)/(((0.001308*t + 0.189269)*t + 1.432788)*t + 1.0) - t
else:
t = math.sqrt(-2.0*math.log(1.0-p))
return t - ((0.010328*t + 0.802853)*t + 2.515517)/(((0.001308*t + 0.189269)*t + 1.432788)*t + 1.0)
def p_portfolio(I,sigma,r,alpha,beta):
"""p_portfolio -- modified markowitz model for portfolio optimization.
Parameters:
- I: set of items
- sigma[i]: standard deviation of item i
- r[i]: revenue of item i
- alpha: acceptance threshold
- beta: desired confidence level
Returns a model, ready to be solved.
"""
model = Model("p_portfolio")
x = {}
for i in I:
x[i] = model.addVar(vtype="C", name="x(%s)"%i) # quantity of i to buy
rho = model.addVar(vtype="C", name="rho")
rhoaux = model.addVar(vtype="C", name="rhoaux")
model.addCons(rho == quicksum(r[i]*x[i] for i in I))
model.addCons(quicksum(x[i] for i in I) == 1)
model.addCons(rhoaux == (alpha - rho)*(1/phi_inv(beta))) #todo
model.addCons(quicksum(sigma[i]**2 * x[i] * x[i] for i in I) <= rhoaux * rhoaux)
model.setObjective(rho, "maximize")
model.data = x
return model
if __name__ == "__main__":
# portfolio
I,sigma,r = multidict(
{1:[0.07,1.01],
2:[0.09,1.05],
3:[0.1,1.08],
4:[0.2,1.10],
5:[0.3,1.20]}
)
alpha = 0.95
# beta = 0.1
for beta in [0.1, 0.05, 0.02, 0.01]:
print("\n\n\nbeta:",beta,"phi inv:",phi_inv(beta))
model = p_portfolio(I,sigma,r,alpha,beta)
model.optimize()
x = model.data
EPS = 1.e-6
print("Investment:")
print("%5s\t%8s" % ("i","x[i]"))
for i in I:
print("%5s\t%8g" % (i,model.getVal(x[i])))
print("Objective:",model.getObjVal())
| 2,434 | 27.988095 | 106 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/read_tsplib.py | """
tsp.py: read standard instances of the traveling salesman problem
Functions provided:
* read_tsplib - read a symmetric tsp instance
* read_atsplib - asymmetric
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import gzip
import math
def distL2(x1,y1,x2,y2):
"""Compute the L2-norm (Euclidean) distance between two points.
The distance is rounded to the closest integer, for compatibility
with the TSPLIB convention.
The two points are located on coordinates (x1,y1) and (x2,y2),
sent as parameters"""
xdiff = x2 - x1
ydiff = y2 - y1
return int(math.sqrt(xdiff*xdiff + ydiff*ydiff) + .5)
def distL1(x1,y1,x2,y2):
"""Compute the L1-norm (Manhattan) distance between two points.
The distance is rounded to the closest integer, for compatibility
with the TSPLIB convention.
The two points are located on coordinates (x1,y1) and (x2,y2),
sent as parameters"""
return int(abs(x2-x1) + abs(y2-y1)+.5)
def distLinf(x1,y1,x2,y2):
"""Compute the Linfty distance between two points (see TSPLIB documentation)"""
return int(max(abs(x2-x1),abs(y2-y1)))
def distATT(x1,y1,x2,y2):
"""Compute the ATT distance between two points (see TSPLIB documentation)"""
xd = x2 - x1
yd = y2 - y1
rij = math.sqrt((xd*xd + yd*yd) /10.)
tij = int(rij + .5)
if tij < rij:
return tij + 1
else:
return tij
def distCEIL2D(x1,y1,x2,y2):
xdiff = x2 - x1
ydiff = y2 - y1
return int(math.ceil(math.sqrt(xdiff*xdiff + ydiff*ydiff)))
def distGEO(x1,y1,x2,y2):
print("Implementation is wrong")
assert False
PI = 3.141592
deg = int(x1 + .5)
min_ = x1 - deg
lat1 = PI * (deg + 5.*min_/3)/180.
deg = int(y1 + .5)
min_ = y1 - deg
long1 = PI * (deg + 5.*min_/3)/180.
deg = int(x2 + .5)
min_ = x2 - deg
lat2 = PI * (deg + 5.*min_/3)/180.
deg = int(y2 + .5)
min_ = y2 - deg
long2 = PI * (deg + 5.*min_/3)/180.
RRR = 6378.388
q1 = math.cos( long1 - long2 );
q2 = math.cos( lat1 - lat2 );
q3 = math.cos( lat1 + lat2 );
return int(RRR * math.acos(.5*((1.+q1)*q2 - (1.-q1)*q3)) + 1.)
def read_explicit_lowerdiag(f,n):
c = {}
i,j = 1,1
while True:
line = f.readline()
for data in line.split():
c[j,i] = int(data)
j += 1
if j>i:
i += 1
j = 1
if i > n:
return range(1,n+1),c,None,None
def read_explicit_upper(f,n):
c = {}
i,j = 1,2
while True:
line = f.readline()
for data in line.split():
c[i,j] = int(data)
j += 1
if j>n:
i += 1
j = i+1
if i == n:
return range(1,n+1),c,None,None
def read_explicit_upperdiag(f,n):
c = {}
i,j = 1,1
while True:
line = f.readline()
for data in line.split():
c[i,j] = int(data)
j += 1
if j>n:
i += 1
j = i
if i == n:
return range(1,n+1),c,None,None
def read_explicit_matrix(f,n):
c = {}
i,j = 1,1
while True:
line = f.readline()
for data in line.split():
if j>i:
c[i,j] = int(data)
j += 1
if j>n:
i += 1
j = 1
if i == n:
return range(1,n+1),c,None,None
def read_tsplib(filename):
"basic function for reading a symmetric problem in the TSPLIB format"
"data is stored in an upper triangular matrix"
"NOTE: some distance types are not handled yet"
if filename[-3:] == ".gz":
f = gzip.open(filename, "rt")
else:
f = open(filename)
line = f.readline()
while line.find("DIMENSION") == -1:
line = f.readline()
n = int(line.split()[-1])
while line.find("EDGE_WEIGHT_TYPE") == -1:
line = f.readline()
if line.find("EUC_2D") != -1:
dist = distL2
elif line.find("MAN_2D") != -1:
dist = distL1
elif line.find("MAX_2D") != -1:
dist = distLinf
elif line.find("ATT") != -1:
dist = distATT
elif line.find("CEIL_2D") != -1:
dist = distCEIL2D
# elif line.find("GEO") != -1:
# print("geographic"
# dist = distGEO
elif line.find("EXPLICIT") != -1:
while line.find("EDGE_WEIGHT_FORMAT") == -1:
line = f.readline()
if line.find("LOWER_DIAG_ROW") != -1:
while line.find("EDGE_WEIGHT_SECTION") == -1:
line = f.readline()
return read_explicit_lowerdiag(f,n)
if line.find("UPPER_ROW") != -1:
while line.find("EDGE_WEIGHT_SECTION") == -1:
line = f.readline()
return read_explicit_upper(f,n)
if line.find("UPPER_DIAG_ROW") != -1:
while line.find("EDGE_WEIGHT_SECTION") == -1:
line = f.readline()
return read_explicit_upperdiag(f,n)
if line.find("FULL_MATRIX") != -1:
while line.find("EDGE_WEIGHT_SECTION") == -1:
line = f.readline()
return read_explicit_matrix(f,n)
print("error reading line " + line)
raise(Exception)
else:
print("cannot deal with '%s' distances" % line)
raise Exception
while line.find("NODE_COORD_SECTION") == -1:
line = f.readline()
x,y = {},{}
while 1:
line = f.readline()
if line.find("EOF") != -1 or not line: break
(i,xi,yi) = line.split()
x[i] = float(xi)
y[i] = float(yi)
V = x.keys()
c = {} # dictionary to hold n times n matrix
for i in V:
for j in V:
c[i,j] = dist(x[i],y[i],x[j],y[j])
return V,c,x,y
def read_atsplib(filename):
"basic function for reading a ATSP problem on the TSPLIB format"
"NOTE: only works for explicit matrices"
if filename[-3:] == ".gz":
f = gzip.open(filename, 'r')
data = f.readlines()
else:
f = open(filename, 'r')
data = f.readlines()
for line in data:
if line.find("DIMENSION") >= 0:
n = int(line.split()[1])
break
else:
raise IOError("'DIMENSION' keyword not found in file '%s'" % filename)
for line in data:
if line.find("EDGE_WEIGHT_TYPE") >= 0:
if line.split()[1] == "EXPLICIT":
break
else:
raise IOError("'EDGE_WEIGHT_TYPE' is not 'EXPLICIT' in file '%s'" % filename)
for k,line in enumerate(data):
if line.find("EDGE_WEIGHT_SECTION") >= 0:
break
else:
raise IOError("'EDGE_WEIGHT_SECTION' not found in file '%s'" % filename)
c = {}
# flatten list of distances
dist = []
for line in data[k+1:]:
if line.find("EOF") >= 0:
break
for val in line.split():
dist.append(int(val))
k = 0
for i in range(n):
for j in range(n):
c[i+1,j+1] = dist[k]
k += 1
return n,c
if __name__ == "__main__":
import sys
# Parse argument
if len(sys.argv) < 2:
print('Usage: %s instance' % sys.argv[0])
exit(1)
from read_tsplib import read_tsplib
V,c,x,y = read_tsplib(sys.argv[1])
print(len(V), "vertices,", len(c), "arcs")
print("distance matrix:")
for i in V:
for j in V:
if j > i:
print(c[i,j],)
elif j < i:
print(c[j,i],)
else:
print(0,)
print
print
| 7,667 | 25.811189 | 85 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/scheduling.py | """
scheduling.py: solve the one machine scheduling problem.
approaches:
- linear ordering formulation
- time-index formulation
- disjunctive formulation
- heuristics using cutting plane
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict
def scheduling_linear_ordering(J,p,d,w):
"""
scheduling_linear_ordering: model for the one machine total weighted tardiness problem
Model for the one machine total weighted tardiness problem
using the linear ordering formulation
Parameters:
- J: set of jobs
- p[j]: processing time of job j
- d[j]: latest non-tardy time for job j
- w[j]: weighted of job j; the objective is the sum of the weighted completion time
Returns a model, ready to be solved.
"""
model = Model("scheduling: linear ordering")
T,x = {},{} # tardiness variable; x[j,k] =1 if job j precedes job k, =0 otherwise
for j in J:
T[j] = model.addVar(vtype="C", name="T(%s)"%(j))
for k in J:
if j != k:
x[j,k] = model.addVar(vtype="B", name="x(%s,%s)"%(j,k))
for j in J:
model.addCons(quicksum(p[k]*x[k,j] for k in J if k != j) - T[j] <= d[j]-p[j], "Tardiness(%r)"%(j))
for k in J:
if k <= j:
continue
model.addCons(x[j,k] + x[k,j] == 1, "Disjunctive(%s,%s)"%(j,k))
for ell in J:
if ell > k:
model.addCons(x[j,k] + x[k,ell] + x[ell,j] <= 2, "Triangle(%s,%s,%s)"%(j,k,ell))
model.setObjective(quicksum(w[j]*T[j] for j in J), "minimize")
model.data = x,T
return model
def scheduling_time_index(J,p,r,w):
"""
scheduling_time_index: model for the one machine total weighted tardiness problem
Model for the one machine total weighted tardiness problem
using the time index formulation
Parameters:
- J: set of jobs
- p[j]: processing time of job j
- r[j]: earliest start time of job j
- w[j]: weighted of job j; the objective is the sum of the weighted completion time
Returns a model, ready to be solved.
"""
model = Model("scheduling: time index")
T = max(r.values()) + sum(p.values())
X = {} # X[j,t]=1 if job j starts processing at time t, 0 otherwise
for j in J:
for t in range(r[j], T-p[j]+2):
X[j,t] = model.addVar(vtype="B", name="x(%s,%s)"%(j,t))
for j in J:
model.addCons(quicksum(X[j,t] for t in range(1,T+1) if (j,t) in X) == 1, "JobExecution(%s)"%(j))
for t in range(1,T+1):
ind = [(j,t2) for j in J for t2 in range(t-p[j]+1,t+1) if (j,t2) in X]
if ind != []:
model.addCons(quicksum(X[j,t2] for (j,t2) in ind) <= 1, "MachineUB(%s)"%t)
model.setObjective(quicksum((w[j] * (t - 1 + p[j])) * X[j,t] for (j,t) in X), "minimize")
model.data = X
return model
def scheduling_disjunctive(J,p,r,w):
"""
scheduling_disjunctive: model for the one machine total weighted completion time problem
Disjunctive optimization model for the one machine total weighted
completion time problem with release times.
Parameters:
- J: set of jobs
- p[j]: processing time of job j
- r[j]: earliest start time of job j
- w[j]: weighted of job j; the objective is the sum of the weighted completion time
Returns a model, ready to be solved.
"""
model = Model("scheduling: disjunctive")
M = max(r.values()) + sum(p.values()) # big M
s,x = {},{} # start time variable, x[j,k] = 1 if job j precedes job k, 0 otherwise
for j in J:
s[j] = model.addVar(lb=r[j], vtype="C", name="s(%s)"%j)
for k in J:
if j != k:
x[j,k] = model.addVar(vtype="B", name="x(%s,%s)"%(j,k))
for j in J:
for k in J:
if j != k:
model.addCons(s[j] - s[k] + M*x[j,k] <= (M-p[j]), "Bound(%s,%s)"%(j,k))
if j < k:
model.addCons(x[j,k] + x[k,j] == 1, "Disjunctive(%s,%s)"%(j,k))
model.setObjective(quicksum(w[j]*s[j] for j in J), "minimize")
model.data = s,x
return model
def scheduling_cutting_plane(J,p,r,w):
"""
scheduling_cutting_plane: heuristic to one machine weighted completion time based on cutting planes
Use a cutting-plane method as a heuristics for solving the
one-machine total weighted completion time problem with release
times.
Parameters:
- J: set of jobs
- p[j]: processing time of job j
- r[j]: earliest start time of job j
- w[j]: weighted of job j; the objective is the sum of the weighted completion time
Returns a tuple with values of:
- bestC: corresponding completion time of the best found solution
- bestobj: best, best, hobj
"""
model = Model("scheduling: cutting plane")
C = {} # completion time variable
for j in J:
C[j] = model.addVar(lb=r[j]+p[j], obj=w[j], vtype="C", name="C(%s)"%j)
sumP = sum([p[j] for j in J])
sumP2 = sum([p[j]**2 for j in J])
model.addCons(C[j]*p[j] >= sumP2*0.5 + (sumP**2)*0.5, "AllJobs")
model.setObjective(quicksum(w[j]*C[j] for j in J), "minimize")
cut = 0
bestobj = float("inf")
while True:
model.optimize()
sol = sorted([(model.getVal(C[j]),j) for j in C])
seq = [j for (completion,j) in sol]
# print("Opt.value=",model.getObjVal()
# print("current solution:", seq
hC,hobj = evaluate(seq,p,r,w)
if hobj < bestobj:
# print("\t*** updating best found solution:", bestobj, "--->", hobj, "***"
bestC = hC
bestobj = hobj
best = list(seq)
S,S_ = [],[]
sumP,sumP2,f = 0,0,0
for (C_,j) in sol:
pj = p[j]
delta = pj**2 + ((sumP+pj)**2 - sumP**2) - 2*pj*C_
if f > 0 and delta <= 0:
S = S_
break
f += delta/2.
sumP2 += pj**2
sumP += pj
S_.append(j)
if S == []:
break
cut += 1
model.addCons(quicksum(C[j]*p[j] for j in S) >= sumP2*0.5 + (sumP**2)*0.5, "Cut(%s)"%cut)
return bestC,bestobj,best
def evaluate(seq,p,r,w):
C = 0 # completion time of previous job
obj = 0
for j in seq:
s = max(r[j],C)
C = max(r[j],C) + p[j]
obj += w[j]*C
return C,obj
def printsol(seq,p,r,w):
print("Solution:",seq)
C = 0 # completion time of previous job
print("%12s%12s%12s%12s%12s%12s%12s" % ("job","p","r","w","start","completion","obj"))
obj = 0
for j in seq:
s = max(r[j],C)
C = max(r[j],C) + p[j]
obj += w[j]*C
print("%12s%12s%12s%12s%12s%12s%12s" % (j,p[j],r[j],w[j],s,C,w[j]*C))
print("completion time:",C)
print("objective:",obj)
print
return C
import random
def make_data(n):
"""
Data generator for the one machine scheduling problem.
"""
p,r,d,w = {},{},{},{}
J = range(1,n+1)
for j in J:
p[j] = random.randint(1,4)
w[j] = random.randint(1,3)
T = sum(p)
for j in J:
r[j] = random.randint(0,5)
d[j] = r[j] + random.randint(0,5)
return J,p,r,d,w
def example(n):
"""
Data generator for the one machine scheduling problem.
"""
J,p,r,d,w = multidict({
1:[1,4,0,3],
2:[4,0,0,1],
3:[2,2,0,2],
4:[3,4,0,3],
5:[1,1,0,1],
6:[4,5,0,2],
})
return J,p,r,d,w
if __name__ == "__main__":
random.seed(1)
n = 5 # number of jobs
# J,p,r,d,w = make_data(n)
J,p,r,d,w = example(n)
print("Linear ordering formulation")
model = scheduling_linear_ordering(J,p,d,w)
# model.write("scheduling-lo.lp")
model.optimize()
z = model.getObjVal()
x,T = model.data
for (i,j) in x:
if model.getVal(x[i,j]) > .5:
print("x(%s) = %s" % ((i,j), int(model.getVal(x[i,j])+.5)))
for i in T:
print("T(%s) = %s" % (i, int(model.getVal(T[i])+.5)))
print("Opt.value by the linear ordering formulation=",z)
print("Time index formulation")
model = scheduling_time_index(J,p,r,w)
model.optimize()
X = model.data
z = model.getObjVal() + sum([w[j]*p[j] for j in J])
print("Optimal value by Time Index Formulation:",z)
seq = [j for (t,j) in sorted([(t,j) for (j,t) in X if model.getVal(X[j,t]) > .5])]
C1 = printsol(seq,p,r,w)
print("Disjunctive formulation")
model = scheduling_disjunctive(J,p,r,w)
model.optimize()
s,x = model.data
z = model.getObjVal() + sum([w[j]*p[j] for j in J])
print("Optimal value by Disjunctive Formulation:",z)
seq = [j for (t,j) in sorted([(int(model.getVal(s[j])+.5),j) for j in s])]
C2 = printsol(seq,p,r,w)
assert C2 == C1
print("Earliest start time rule:")
tmp = sorted([(r[i],i) for i in J])
seq = [i for (dummy,i) in sorted(tmp)]
printsol(seq,p,r,w)
print("Smith's rule: decreasing order of w/p")
tmp = [(float(w[i])/p[i],i) for i in J]
seq = [i for (dummy,i) in sorted(tmp,reverse=True)]
printsol(seq,p,r,w)
print("Scheduling heuristics with cutting planes")
C,obj,seq = scheduling_cutting_plane(J,p,r,w)
printsol(seq,p,r,w)
| 9,424 | 28.270186 | 106 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/staff_sched.py | """
staff_sched.py: model for staff scheduling
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import random
from pyscipopt import Model, quicksum, multidict
def staff(I,T,N,J,S,c,b):
"""
staff: staff scheduling
Parameters:
- I: set of members in the staff
- T: number of periods in a cycle
- N: number of working periods required for staff's elements in a cycle
- J: set of shifts in each period (shift 0 == rest)
- S: subset of shifts that must be kept at least consecutive days
- c[i,t,j]: cost of a shift j of staff's element i on period t
- b[t,j]: number of staff elements required in period t, shift j
Returns a model, ready to be solved.
"""
Ts = range(1,T+1)
model = Model("staff scheduling")
x = {}
for t in Ts:
for j in J:
for i in I:
x[i,t,j] = model.addVar(vtype="B", name="x(%s,%s,%s)" % (i,t,j))
model.setObjective(quicksum(c[i,t,j]*x[i,t,j] for i in I for t in Ts for j in J if j != 0),
"minimize")
for t in Ts:
for j in J:
if j == 0:
continue
model.addCons(quicksum(x[i,t,j] for i in I) >= b[t,j], "Cover(%s,%s)" % (t,j))
for i in I:
model.addCons(quicksum(x[i,t,j] for t in Ts for j in J if j != 0) == N, "Work(%s)"%i)
for t in Ts:
model.addCons(quicksum(x[i,t,j] for j in J) == 1, "Assign(%s,%s)" % (i,t))
for j in J:
if j != 0:
model.addCons(x[i,t,j] + quicksum(x[i,t,k] for k in J if k != j and k != 0) <= 1,\
"Require(%s,%s,%s)" % (i,t,j))
for t in range(2,T):
for j in S:
model.addCons(x[i,t-1,j] + x[i,t+1,j] >= x[i,t,j], "SameShift(%s,%s,%s)" % (i,t,j))
model.data = x
return model
def make_data():
T = 7 # number of periods
N = 5 # number of working periods of each staff element in a cycle
J = range(4) # shift set; 0 == rest
S = [2,3] # subset of shifts that must be kept at least consecutive days
# staff set, base cost
I,c_base = multidict({1:8000, 2:9000, 3:10000, 4:11000, 5:12000, 6:13000, 7:14000, 8:15000})
c = {}
for i in I:
for t in range(1,T+1):
for j in J:
if j == 0:
continue
c[i,t,j] = c_base[i]
if j == 3: # night shift, more expensive
c[i,t,j] *= 2
if t == T-1 or t == T: # weekend, more expensive
c[i,t,j] *= 1.5
b = {
(1,1):2, (1,2):3, (1,3):1,
(2,1):2, (2,2):3, (2,3):1,
(3,1):2, (3,2):2, (3,3):1,
(4,1):1, (4,2):1, (4,3):1,
(5,1):3, (5,2):3, (5,3):1,
(6,1):4, (6,2):4, (6,3):2,
(7,1):5, (7,2):5, (7,3):2,
}
return I,T,N,J,S,c,b
def make_data_trick():
T = 7 # number of periods
N = 5 # number of working periods of each staff element in a cycle
J = range(4) # shift set; 0 == rest
S = [2,3] # subset of shifts that must be kept at least consecutive days
# staff set, base cost
I,c_base = multidict({1:8000, 2:9000, 3:10000, 4:11000, 5:12000, 6:13000, 7:14000, 8:15000})
c = {}
for i in I:
for t in range(1,T+1):
for j in J:
if j == 0:
continue
c[i,t,j] = c_base[i]
if j == 3: # night shift, more expensive
c[i,t,j] *= 2
if t == T-1 or t == T: # weekend, more expensive
c[i,t,j] *= 1.5
b = {
(1,1):2, (1,2):2, (1,3):2,
(2,1):2, (2,2):2, (2,3):2,
(3,1):2, (3,2):2, (3,3):2,
(4,1):2, (4,2):2, (4,3):2,
(5,1):2, (5,2):2, (5,3):2,
(6,1):2, (6,2):2, (6,3):2,
(7,1):2, (7,2):2, (7,3):2,
}
return I,T,N,J,S,c,b
if __name__ == "__main__":
I,T,N,J,S,c,b = make_data_trick()
# I,T,N,J,S,c,b = make_data()
model = staff(I,T,N,J,S,c,b)
model.optimize()
status = model.getStatus()
if status == "optimal":
x = model.data
print("Optimum solution found")
print("\n\nstaff schedule: (shift on each day)")
for i in I:
s = "worker %s:\t" % i
for t in range(1,T+1):
for j in J:
if model.getVal(x[i,t,j]) > .5:
s += str(j)
print(s)
print("\n\nuncovered shifts:")
# for t in range(1,T+1):
# s = "day %s:\t" % t
# for j in J:
# if y[t,j].X > .5:
# s += "%s:%s, " % (j,int(y[t,j].X+.5))
# print(s)
elif status == "infeasible":
print("Infeasible instance...")
# model.computeIIS()
# for c in model.getConss():
# if c.IISConstr:
# print(c.ConstrName)
elif status == "unbounded" or status == "infeasible":
print("Unbounded instance")
else:
print("Error: Solver finished with non-optimal status",status)
| 5,242 | 32.825806 | 102 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/staff_sched_mo.py | """
staff_sched_mo.py: multiobjective model for staff scheduling
Objectives:
- minimize cost
- minimize uncovered shifts
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import random
from pyscipopt import Model, quicksum, multidict
def staff_mo(I,T,N,J,S,c,b):
"""
staff: staff scheduling
Parameters:
- I: set of members in the staff
- T: number of periods in a cycle
- N: number of working periods required for staff's elements in a cycle
- J: set of shifts in each period (shift 0 == rest)
- S: subset of shifts that must be kept at least consecutive days
- c[i,t,j]: cost of a shit j of staff's element i on period t
- b[t,j]: number of staff elements required in period t, shift j
Returns a model with no objective function.
"""
Ts = range(1,T+1)
model = Model("staff scheduling -- multiobjective version")
x,y = {},{}
for t in Ts:
for j in J:
for i in I:
x[i,t,j] = model.addVar(vtype="B", name="x(%s,%s,%s)" % (i,t,j))
y[t,j] = model.addVar(vtype="C", name="y(%s,%s)" % (t,j))
C = model.addVar(vtype="C", name="cost")
U = model.addVar(vtype="C", name="uncovered")
model.addCons(C >= quicksum(c[i,t,j]*x[i,t,j] for i in I for t in Ts for j in J if j != 0), "Cost")
model.addCons(U >= quicksum(y[t,j] for t in Ts for j in J if j != 0), "Uncovered")
for t in Ts:
for j in J:
if j == 0:
continue
model.addCons(quicksum(x[i,t,j] for i in I) >= b[t,j] - y[t,j], "Cover(%s,%s)" % (t,j))
for i in I:
model.addCons(quicksum(x[i,t,j] for t in Ts for j in J if j != 0) == N, "Work(%s)"%i)
for t in Ts:
model.addCons(quicksum(x[i,t,j] for j in J) == 1, "Assign(%s,%s)" % (i,t))
for j in J:
if j != 0:
model.addCons(x[i,t,j] + quicksum(x[i,t,k] for k in J if k != j and k != 0) <= 1,\
"Require(%s,%s,%s)" % (i,t,j))
for t in range(2,T):
for j in S:
model.addCons(x[i,t-1,j] + x[i,t+1,j] >= x[i,t,j], "SameShift(%s,%s,%s)" % (i,t,j))
model.data = x,y,C,U
return model
def optimize(model,cand,obj):
"""optimize: function for solving the model, updating candidate solutions' list
Parameters:
- model: Gurobi model object
- cand: list of pairs of objective functions (for appending more solutions)
- obj: name of a model's variable to setup as objective
Returns the solver's exit status
"""
# model.Params.OutputFlag = 0 # silent mode
model.setObjective(obj,"minimize")
model.optimize()
x,y,C,U = model.data
status = model.getStatus()
if status == "optimal" or status == "bestsollimit": # todo GRB.Status.SUBOPTIMAL:
sols = model.getSols()
for sol in sols:
cand.append((model.getVal(var=U,solution=sol),model.getVal(var=C,solution=sol)))
# for k in range(model.SolCount):
# model.Params.SolutionNumber = k
# cand.append(model.getVal(U),model.getVal(C))
return status
def solve_segment(I,T,N,J,S,c,b):
"""
solve_segment: segmentation for finding set of solutions for two-objective TSP
Parameters:
- I: set of members in the staff
- T: number of periods in a cycle
- N: number of working periods required for staff's elements in a cycle
- J: set of shifts in each period (shift 0 == rest)
- S: subset of shifts that must be kept at least consecutive days
- c[i,t,j]: cost of a shit j of staff's element i on period t
- b[t,j]: number of staff elements required in period t, shift j
Returns list of candidate solutions
"""
model = staff_mo(I,T,N,J,S,c,b) # model for minimizing time
x,y,C,U = model.data
model.setRealParam("limits/time", 60)
# store the set of solutions for plotting
cand = []
# first objective: cost
stat1 = optimize(model,cand,C)
stat2 = optimize(model,cand,U)
if stat1 != "optimal" or stat2 != "optimal":
return []
ulist = [int(ui+.5) for (ui,ci) in cand]
max_u = max(ulist)
min_u = min(ulist)
# add a time upper bound constraint, moving between min and max values
UConstr = model.addCons(U <= max_u, "UConstr")
for u_lim in range(max_u-1, min_u, -1):
print("limiting u to",u_lim)
UConstr.setAttr("RHS",u_lim)
optimize(model,cand,C)
return cand
if __name__ == "__main__":
from pareto_front import pareto_front
from staff_sched import make_data,make_data_trick
# I,T,N,J,S,c,b = make_data()
I,T,N,J,S,c,b = make_data_trick()
cand_seg = solve_segment(I,T,N,J,S,c,b)
print("candidate solutions:")
for cand in cand_seg:
print("\t",cand)
front_seg = pareto_front(cand_seg)
print("pareto front:",len(front_seg),"points out of",len(cand_seg))
for cand in front_seg:
print("\t",cand)
try:
import matplotlib.pyplot as P
except:
print("for graphics, install matplotlib")
exit(0)
P.clf()
P.xlabel("uncovered shifts")
P.ylabel("cost")
P.title("Pareto front")
### # plot pareto front - scaling
### x = [xi for (xi,yi) in cand_seg]
### y = [yi for (xi,yi) in cand_seg]
### P.plot(x,y,"bo",c="grey")
# plot pareto front - scaling
x = [xi for (xi,yi) in front_seg]
y = [yi for (xi,yi) in front_seg]
P.plot(x,y,"bo",c="black")
x = [xi for (xi,yi) in front_seg]
y = [yi for (xi,yi) in front_seg]
P.plot(x,y,c="black",lw=3,label="segmentation")
P.legend()
P.savefig("tsp_mo_pareto_staff.pdf",format="pdf")
P.show()
| 5,790 | 31.172222 | 103 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/tsp_flow.py | """
tsp_flow.py: solve the traveling salesman problem using flow formulation
minimize the travel cost for visiting n customers exactly once
approach:
- start with assignment model
- check flow from a source to every other node;
- if no flow, a sub-cycle has been found --> add cut
- otherwise, the solution is optimal
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
#import networkx todo
from pyscipopt import Model, quicksum, multidict
EPS = 1.e-6
def maxflow(V,M,source,sink):
"""maxflow: maximize flow from source to sink, taking into account arc capacities M
Parameters:
- V: set of vertices
- M[i,j]: dictionary or capacity for arcs (i,j)
- source: flow origin
- sink: flow target
Returns a model, ready to be solved.
"""
# create max-flow underlying model, on which to find cuts
model = Model("maxflow")
f = {} # flow variable
for (i,j) in M:
f[i,j] = model.addVar(lb=-M[i,j], ub=M[i,j], name="flow(%s,%s)"%(i,j))
cons = {}
for i in V:
if i != source and i != sink:
cons[i] = model.addCons(
quicksum(f[i,j] for j in V if i<j and (i,j) in M) - \
quicksum(f[j,i] for j in V if i>j and (j,i) in M) == 0,
"FlowCons(%s)"%i)
model.setObjective(quicksum(f[i,j] for (i,j) in M if i==source), "maximize")
# model.write("tmp.lp")
model.data = f,cons
return model
def solve_tsp(V,c):
"""solve_tsp -- solve the traveling salesman problem
- start with assignment model
- check flow from a source to every other node;
- if no flow, a sub-cycle has been found --> add cut
- otherwise, the solution is optimal
Parameters:
- V: set/list of nodes in the graph
- c[i,j]: cost for traversing edge (i,j)
Returns the optimum objective value and the list of edges used.
"""
def addcut(X):
for sink in V[1:]:
mflow = maxflow(V,X,V[0],sink)
mflow.optimize()
f,cons = mflow.data
if mflow.ObjVal < 2-EPS: # no flow to sink, can add cut
break
else:
return False
#add a cut/constraint
CutA = set([V[0]])
for i in cons:
if cons[i].Pi <= -1+EPS:
CutA.add(i)
CutB = set(V) - CutA
main.addCons(
quicksum(x[i,j] for i in CutA for j in CutB if j>i) + \
quicksum(x[j,i] for i in CutA for j in CutB if j<i) >= 2)
print("mflow:",mflow.getObjVal(),"cut:",CutA,"+",CutB,">= 2")
print("mflow:",mflow.getObjVal(),"cut:",[(i,j) for i in CutA for j in CutB if j>i],"+",[(j,i) for i in CutA for j in CutB if j<i],">= 2")
return True
def isMIP(x):
for var in x:
if var.vtype == "CONTINUOUS":
return False
return True
# main part of the solution process:
main = Model("tsp")
x = {}
for i in V:
for j in V:
if j > i:
x[i,j] = main.addVar(ub=1, vtype="C", name="x(%s,%s)"%(i,j))
for i in V:
main.addCons(quicksum(x[j,i] for j in V if j < i) + \
quicksum(x[i,j] for j in V if j > i) == 2, "Degree(%s)"%i)
main.setObjective(quicksum(c[i,j]*x[i,j] for i in V for j in V if j > i), "minimize")
while True:
main.optimize()
z = main.getObjVal()
X = {}
for (i,j) in x:
if main.getVal(x[i,j]) > EPS:
X[i,j] = main.getVal(x[i,j])
if addcut(X) == False: # i.e., components are connected
if isMIP(): # integer variables, components connected: solution found
break
for (i,j) in x: # all components connected, switch to integer model
main.chgVarType(x[i,j], "BINARY")
# process solution
edges = []
for (i,j) in x:
if main.getVal(x[i,j]) > EPS:
edges.append((i,j))
return main.getObjVal(),edges
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n):
"""make_data: compute matrix distance based on euclidean distance"""
V = range(1,n+1)
x = dict([(i,random.random()) for i in V])
y = dict([(i,random.random()) for i in V])
c = {}
for i in V:
for j in V:
if j > i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return V,c
if __name__ == "__main__":
import sys
# Parse argument
if len(sys.argv) < 2:
print("Usage: %s instance" % sys.argv[0])
exit(1)
# n = 200
# seed = 1
# random.seed(seed)
# V,c = make_data(n)
from read_tsplib import read_tsplib
try:
V,c,x,y = read_tsplib(sys.argv[1])
except:
print("Cannot read TSPLIB file",sys.argv[1])
exit(1)
obj,edges = solve_tsp(V,c)
print
print("Optimal tour:",edges)
print("Optimal cost:",obj)
print
| 5,113 | 29.082353 | 145 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/tsp_lazy.py | """
tsp.py: solve the traveling salesman problem
minimize the travel cost for visiting n customers exactly once
approach:
- start with assignment model
- add cuts until there are no sub-cycles
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
import networkx
from pyscipopt import Model, Conshdlr, quicksum, SCIP_RESULT, SCIP_PRESOLTIMING, SCIP_PROPTIMING, SCIP_PARAMSETTING
class TSPconshdlr(Conshdlr):
def findSubtours(self, checkonly, sol):
EPS = 1.e-6
edges = []
x = self.model.data
for (i, j) in x:
if self.model.getSolVal(sol, x[i, j]) > EPS:
edges.append((i,j))
G = networkx.Graph()
G.add_edges_from(edges)
Components = list(networkx.connected_components(G))
if len(Components) == 1:
return False
elif checkonly:
return True
for S in Components:
self.model.addCons(quicksum(x[i, j] for i in S for j in S if j > i) <= len(S) - 1)
print("cut: len(%s) <= %s" % (S, len(S) - 1))
return True
def conscheck(self, constraints, solution, checkintegrality, checklprows, printreason):
if self.findSubtours(checkonly = True, sol = solution):
return {"result": SCIP_RESULT.INFEASIBLE}
else:
return {"result": SCIP_RESULT.FEASIBLE}
def consenfolp(self, constraints, nusefulconss, solinfeasible):
if self.findSubtours(checkonly = False, sol = None):
return {"result": SCIP_RESULT.CONSADDED}
else:
return {"result": SCIP_RESULT.FEASIBLE}
def conslock(self, constraint, nlockspos, nlocksneg):
pass
def tsp(V,c):
"""tsp -- model for solving the traveling salesman problem with callbacks
- start with assignment model
- add cuts until there are no sub-cycles
Parameters:
- V: set/list of nodes in the graph
- c[i,j]: cost for traversing edge (i,j)
Returns the optimum objective value and the list of edges used.
"""
model = Model("TSP_lazy")
conshdlr = TSPconshdlr()
x = {}
for i in V:
for j in V:
if j > i:
x[i,j] = model.addVar(vtype = "B",name = "x(%s,%s)" % (i,j))
for i in V:
model.addCons(quicksum(x[j, i] for j in V if j < i) +
quicksum(x[i, j] for j in V if j > i) == 2, "Degree(%s)" % i)
model.setObjective(quicksum(c[i, j] * x[i, j] for i in V for j in V if j > i), "minimize")
model.data = x
return model, conshdlr
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def make_data(n):
"""make_data: compute matrix distance based on euclidean distance"""
V = range(1,n + 1)
x = dict([(i,random.random()) for i in V])
y = dict([(i,random.random()) for i in V])
c = {}
for i in V:
for j in V:
if j > i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return V,c,x,y
def solve_tsp(V,c):
model, conshdlr = tsp(V, c)
model.includeConshdlr(conshdlr, "TSP", "TSP subtour eliminator",
sepapriority = -1, enfopriority = -1, chckpriority = -1, sepafreq = -1, propfreq = -1,
eagerfreq = -1, maxprerounds = 0, delaysepa = False, delayprop = False, needscons = False,
presoltiming = SCIP_PRESOLTIMING.FAST, proptiming = SCIP_PROPTIMING.BEFORELP)
model.setBoolParam("misc/allowdualreds", 0)
model.writeProblem("tsp.cip")
model.optimize()
x = model.data
EPS = 1.e-6
edges = []
for (i,j) in x:
if model.getVal(x[i, j]) > EPS:
edges.append((i, j))
return model.getObjVal(), edges
if __name__ == "__main__":
import sys
if len(sys.argv) < 2:
print("Usage: %s instance" % sys.argv[0])
print("using randomly generated TSP instance")
n = 200
seed = 1
random.seed(seed)
V,c,x,y = make_data(n)
else:
from read_tsplib import read_tsplib
try:
V, c, x, y = read_tsplib(sys.argv[1])
except:
print("Cannot read TSPLIB file", sys.argv[1])
exit(1)
obj, edges = solve_tsp(V, c)
print("")
print("Optimal tour:", edges)
print("Optimal cost:", obj)
print("")
| 4,435 | 30.239437 | 116 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/tsp_mo.py | """
tsp-mp.py: solve the multi-objective traveling salesman problem
Approaches:
- segmentation
- ideal point
- scalarization
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
from pyscipopt import Model, quicksum, multidict
def optimize(model,cand):
"""optimize: function for solving the model, updating candidate solutions' list
Will add to cand all the intermediate solutions found, as well as the optimum
Parameters:
- model: Gurobi model object
- cand: list of pairs of objective functions (for appending more solutions)
Returns the solver's exit status
"""
model.hideOutput()
model.optimize()
x,y,C,T = model.data
status = model.getStatus()
if status == "optimal":
# collect suboptimal solutions
solutions = model.getSols()
for sol in solutions:
cand.append((model.getSolVal(T, sol), model.getSolVal(C)))
return status
def base_model(n,c,t):
"""base_model: mtz model for the atsp, prepared for two objectives
Loads two additional variables/constraints to the mtz model:
- C: sum of travel costs
- T: sum of travel times
Parameters:
- n: number of cities
- c,t: alternative edge weights, to compute two objective functions
Returns list of candidate solutions
"""
from atsp import mtz_strong
model = mtz_strong(n,c) # model for minimizing cost
x,u = model.data
# some auxiliary information
C = model.addVar(vtype="C", name="C") # for computing solution cost
T = model.addVar(vtype="C", name="T") # for computing solution time
model.addCons(T == quicksum(t[i,j]*x[i,j] for (i,j) in x), "Time")
model.addCons(C == quicksum(c[i,j]*x[i,j] for (i,j) in x), "Cost")
model.data = x,u,C,T
return model
def solve_segment_time(n,c,t,segments):
"""solve_segment: segmentation for finding set of solutions for two-objective TSP
Parameters:
- n: number of cities
- c,t: alternative edge weights, to compute two objective functions
- segments: number of segments for finding various non-dominated solutions
Returns list of candidate solutions
"""
model = base_model(n,c,t) # base model for minimizing cost or time
x,u,C,T = model.data
# store the set of solutions for plotting
cand = []
# print("optimizing time"
model.setObjective(T, "minimize")
stat1 = optimize(model,cand)
# print("optimizing cost"
model.setObjective(C, "minimize")
stat2 = optimize(model,cand)
if stat1 != "optimal" or stat2 != "optimal":
return []
times = [ti for (ti,ci) in cand]
max_time = max(times)
min_time = min(times)
delta = (max_time-min_time)/segments
# print("making time range from",min_time,"to",max_time
# add a time upper bound constraint, moving between min and max values
TimeCons = model.addCons(T <= max_time, "TimeCons")
for i in range(segments+1):
time_ub = max_time - delta*i
model.chgRhs(TimeCons, time_ub)
# print("optimizing cost subject to time <=",time_ub
optimize(model,cand)
return cand
def solve_ideal(n,c,t,segments):
"""solve_ideal: use ideal point for finding set of solutions for two-objective TSP
Parameters:
- n: number of cities
- c,t: alternative edge weights, to compute two objective functions
- segments: number of segments for finding various non-dominated solutions
Returns list of candidate solutions
"""
model = base_model(n,c,t) # base model for minimizing cost or time
x,u,C,T = model.data
# store the set of solutions for plotting
cand = []
# print("optimizing time"
model.setObjective(T, "minimize")
stat1 = optimize(model,cand)
# print("optimizing cost"
model.setObjective(C, "minimize")
stat2 = optimize(model,cand) #find the minimum cost routes
if stat1 != "optimal" or stat2 != "optimal":
return []
times = [ti for (ti,ci) in cand]
costs = [ci for (ti,ci) in cand]
min_time = min(times)
min_cost = min(costs)
# print("ideal point:",min_time,",",min_cost
#===============================================================
# Objective function is f1^2 + f2^2 where f=Sum tx-min_time and g=Sum cx-min_cost
f1 = model.addVar(vtype="C", name="f1")
f2 = model.addVar(vtype="C", name="f2")
model.addCons(f1 == T - min_time, "obj1")
model.addCons(f2 == C - min_cost, "obj2")
# print("optimizing distance to ideal point:"
for i in range(segments+1):
lambda_ = float(i)/segments
# print(lambda_
z = model.addVar(name="z")
Obj = model.addCons(lambda_*f1*f1 + (1-lambda_)*f2*f2 == z)
model.setObjective(z, "minimize")
optimize(model, cand) # find the minimum cost routes
return cand
def solve_scalarization(n,c,t):
"""solve_scalarization: scale objective function to find new point
Parameters:
- n: number of cities
- c,t: alternative edge weights, to compute two objective functions
Returns list of candidate solutions
"""
model = base_model(n,c,t) # base model for minimizing cost or time
x,u,C,T = model.data
def explore(C1,T1,C2,T2,front):
"""explore: recursively try to find new non-dominated solutions with a scaled objective
Parameters:
- C1,T1: cost and time of leftmost point
- C1,T1: cost and time of rightmost point
- front: current set of non-dominated solutions
Returns the updated front
"""
alpha = float(C1 - C2)/(T2 - T1)
# print("%s,%s -- %s,%s (%s)..." % (C1,T1,C2,T2,alpha)
init = list(front)
model.setObjective(quicksum((c[i,j] + alpha*t[i,j])*x[i,j] for (i,j) in x), "minimize")
optimize(model,front)
front = pareto_front(front)
# print("... added %s points" % (len(front)-len(init))
if front == init:
# print("no points added, returning"
return front
CM = model.getVal(C)
TM = model.getVal(T)
# print("will explore %s,%s -- %s,%s and %s,%s -- %s,%s" % (C1,T1,CM,TM,CM,TM,C2,T2)
if TM > T1:
front = explore(C1,T1,CM,TM,front)
if T2 > TM:
front = explore(CM,TM,C2,T2,front)
return front
# store the set of solutions for plotting
cand = [] # to store the set of solutions for plotting
model.setObjective(T, "minimize")
stat = optimize(model,cand)
if stat != "optimal":
return []
C1 = model.getVal(C)
T1 = model.getVal(T)
# change the objective function to minimize the travel cost
model.setObjective(C, "minimize")
stat = optimize(model,cand)
if stat != "optimal":
return []
C2 = model.getVal(C)
T2 = model.getVal(T)
front = pareto_front(cand)
return explore(C1,T1,C2,T2,front)
def distance(x1,y1,x2,y2):
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n):
x,y = {},{} # positions in the plane
c,t = {},{} # cost, time
for i in range(1,n+1):
x[i] = random.random()
y[i] = random.random()
for i in range(1,n+1):
for j in range(1,n+1):
c[i,j] = distance(x[i],y[i],x[j],y[j])
t[i,j] = 1/(c[i,j]+1.0)+0.3*random.random()
return c,t,x,y
if __name__ == "__main__":
from pareto_front import pareto_front
random.seed(7)
n = 20
c,t,x,y = make_data(n)
print("\n\n\nmultiobjective optimization: segmentation with additional (time) constraint")
segments = 6
cand_seg_time = solve_segment_time(n,c,t,segments)
print("candidate solutions:")
for cand in cand_seg_time:
print("\t",cand)
front_seg_time = pareto_front(cand_seg_time)
print("pareto front:",len(front_seg_time),"points out of",len(cand_seg_time))
for cand in front_seg_time:
print("\t",cand)
print("\n\n\nmultiobjective optimization: min distance to ideal point")
cand_ideal = solve_ideal(n,c,t,segments)
print("candidate solutions:")
for cand in cand_ideal:
print("\t",cand)
front_ideal = pareto_front(cand_ideal)
print("pareto front:",len(front_ideal),"points out of",len(cand_ideal))
for cand in front_ideal:
print("\t",cand)
print("\n\n\nmultiobjective optimization: scalarization strategy")
front_scalarization = solve_scalarization(n,c,t)
front_scalarization.sort()
print("front solutions:")
for cand in front_scalarization:
print("\t",cand)
assert front_scalarization == pareto_front(front_scalarization)
try:
import matplotlib.pyplot as P
except:
print("for graphics, install matplotlib")
exit(0)
P.clf()
P.xlabel("cost")
P.ylabel("time")
P.title("Pareto front")
# plot pareto front - scalarization
t = [ti for (ti,ci) in front_scalarization]
c = [ci for (ti,ci) in front_scalarization]
P.plot(t,c,"bo",c="black")
t = [ti for (ti,ci) in front_scalarization]
c = [ci for (ti,ci) in front_scalarization]
P.plot(t,c,c="black",lw=3,label="scalarization")
# plot pareto front - segmentation (time)
t = [ti for (ti,ci) in cand_seg_time]
c = [ci for (ti,ci) in cand_seg_time]
P.plot(t,c,"bo",c="cyan")
allpoints = [(ti,ci) for (ti,ci) in cand_seg_time]
t = [ti for (ti,ci) in front_seg_time]
c = [ci for (ti,ci) in front_seg_time]
P.plot(t,c,c="cyan",lw=3,label="segmentation (time)")
# plot pareto front - -ideal point
t = [ti for (ti,ci) in cand_ideal]
c = [ci for (ti,ci) in cand_ideal]
P.plot(t,c,"bo",c="red")
allpoints = [(ti,ci) for (ti,ci) in cand_ideal]
t = [ti for (ti,ci) in front_ideal]
c = [ci for (ti,ci) in front_ideal]
P.plot(t,c,c="red",lw=3,label="ideal point")
P.legend()
P.savefig("tsp_mo_pareto_ideal.pdf",format="pdf")
P.show()
| 10,031 | 30.54717 | 95 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/tsptw.py | """
tsptw.py: solve the asymmetric traveling salesman problem with time window constraints
minimize the travel cost for visiting n customers exactly once;
each customer has a time window within which the salesman must visit him
formulations based on Miller-Tucker-Zemlin's formulation, for the atsp;
one- and two-index potential variants
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
from pyscipopt import Model, quicksum, multidict
def mtztw(n,c,e,l):
"""mtzts: model for the traveling salesman problem with time windows
(based on Miller-Tucker-Zemlin's one-index potential formulation)
Parameters:
- n: number of nodes
- c[i,j]: cost for traversing arc (i,j)
- e[i]: earliest date for visiting node i
- l[i]: latest date for visiting node i
Returns a model, ready to be solved.
"""
model = Model("tsptw - mtz")
x,u = {},{}
for i in range(1,n+1):
u[i] = model.addVar(lb=e[i], ub=l[i], vtype="C", name="u(%s)"%i)
for j in range(1,n+1):
if i != j:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j))
for i in range(1,n+1):
model.addCons(quicksum(x[i,j] for j in range(1,n+1) if j != i) == 1, "Out(%s)"%i)
model.addCons(quicksum(x[j,i] for j in range(1,n+1) if j != i) == 1, "In(%s)"%i)
for i in range(1,n+1):
for j in range(2,n+1):
if i != j:
M = max(l[i] + c[i,j] - e[j], 0)
model.addCons(u[i] - u[j] + M*x[i,j] <= M-c[i,j], "MTZ(%s,%s)"%(i,j))
model.setObjective(quicksum(c[i,j]*x[i,j] for (i,j) in x), "minimize")
model.data = x,u
return model
def mtz2tw(n,c,e,l):
"""mtz: model for the traveling salesman problem with time windows
(based on Miller-Tucker-Zemlin's one-index potential formulation, stronger constraints)
Parameters:
- n: number of nodes
- c[i,j]: cost for traversing arc (i,j)
- e[i]: earliest date for visiting node i
- l[i]: latest date for visiting node i
Returns a model, ready to be solved.
"""
model = Model("tsptw - mtz-strong")
x,u = {},{}
for i in range(1,n+1):
u[i] = model.addVar(lb=e[i], ub=l[i], vtype="C", name="u(%s)"%i)
for j in range(1,n+1):
if i != j:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j))
for i in range(1,n+1):
model.addCons(quicksum(x[i,j] for j in range(1,n+1) if j != i) == 1, "Out(%s)"%i)
model.addCons(quicksum(x[j,i] for j in range(1,n+1) if j != i) == 1, "In(%s)"%i)
for j in range(2,n+1):
if i != j:
M1 = max(l[i] + c[i,j] - e[j], 0)
M2 = max(l[i] + min(-c[j,i], e[j]-e[i]) - e[j], 0)
model.addCons(u[i] + c[i,j] - M1*(1-x[i,j]) + M2*x[j,i] <= u[j], "LiftedMTZ(%s,%s)"%(i,j))
for i in range(2,n+1):
model.addCons(e[i] + quicksum(max(e[j]+c[j,i]-e[i],0) * x[j,i] for j in range(1,n+1) if i != j) \
<= u[i], "LiftedLB(%s)"%i)
model.addCons(u[i] <= l[i] - \
quicksum(max(l[i]-l[j]+c[i,j],0) * x[i,j] for j in range(2,n+1) if i != j), \
"LiftedUB(%s)"%i)
model.setObjective(quicksum(c[i,j]*x[i,j] for (i,j) in x), "minimize")
model.data = x,u
return model
def tsptw2(n,c,e,l):
"""tsptw2: model for the traveling salesman problem with time windows
(based on Miller-Tucker-Zemlin's formulation, two-index potential)
Parameters:
- n: number of nodes
- c[i,j]: cost for traversing arc (i,j)
- e[i]: earliest date for visiting node i
- l[i]: latest date for visiting node i
Returns a model, ready to be solved.
"""
model = Model("tsptw2")
x,u = {},{}
for i in range(1,n+1):
for j in range(1,n+1):
if i != j:
x[i,j] = model.addVar(vtype="B", name="x(%s,%s)"%(i,j))
u[i,j] = model.addVar(vtype="C", name="u(%s,%s)"%(i,j))
for i in range(1,n+1):
model.addCons(quicksum(x[i,j] for j in range(1,n+1) if j != i) == 1, "Out(%s)"%i)
model.addCons(quicksum(x[j,i] for j in range(1,n+1) if j != i) == 1, "In(%s)"%i)
for j in range(2,n+1):
model.addCons(quicksum(u[i,j] + c[i,j]*x[i,j] for i in range(1,n+1) if i != j) -
quicksum(u[j,k] for k in range(1,n+1) if k != j) <= 0, "Relate(%s)"%j)
for i in range(1,n+1):
for j in range(1,n+1):
if i != j:
model.addCons(e[i]*x[i,j] <= u[i,j], "LB(%s,%s)"%(i,j))
model.addCons(u[i,j] <= l[i]*x[i,j], "UB(%s,%s)"%(i,j))
model.setObjective(quicksum(c[i,j]*x[i,j] for (i,j) in x), "minimize")
model.data = x,u
return model
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n,width):
"""make_data: compute matrix distance and time windows."""
x = dict([(i,100*random.random()) for i in range(1,n+1)])
y = dict([(i,100*random.random()) for i in range(1,n+1)])
c = {}
for i in range(1,n+1):
for j in range(1,n+1):
if j != i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
e = {1:0}
l = {1:0}
start = 0
delta = int(76.*math.sqrt(n)/n * width)+1
for i in range(1,n):
j = i+1
start += c[i,j]
e[j] = max(start-delta,0)
l[j] = start + delta
return c,x,y,e,l
if __name__ == "__main__":
EPS = 1.e-6
# n = 10
# width = 10
# c,x,y,e,l = make_data(n,width)
n = 5
c = { (1,1):0, (1,2):9, (1,3):10, (1,4):10, (1,5):10,
(2,1):10, (2,2):0, (2,3):9, (2,4):10, (2,5):10,
(3,1):10, (3,2):10, (3,3):0, (3,4):9, (3,5):10,
(4,1):10, (4,2):10, (4,3):10, (4,4):0, (4,5):9,
(5,1):9, (5,2):10, (5,3):10, (5,4):10, (5,5):0,
}
e = {1:0, 2:0, 3:0, 4:0, 5:0}
l = {1:100, 2:100, 3:10, 4:100, 5:100}
print(c)
print(e)
print(l)
model = mtztw(n,c,e,l)
model.optimize()
x,u = model.data
sol = [i for (v,i) in sorted([(model.getVal(u[i]),i) for i in u])]
print("mtz:")
print(sol)
print("Optimal value:", model.getObjVal())
model = mtz2tw(n,c,e,l)
model.optimize()
x,u = model.data
sol = [i for (v,i) in sorted([(model.getVal(u[i]),i) for i in u])]
print("mtz2:")
print(sol)
print("Optimal value:", model.getObjVal())
# ### import networkx as NX
# ### import matplotlib.pyplot as P
# ### P.clf()
# ### G = NX.Graph()
# ### G.add_nodes_from(range(1,n+1))
# ### position = {}
# ### for i in range(1,n+1):
# ### position[i] = (x[i],y[i])
# ###
# ### for i in range(n-1):
# ### G.add_edge(perm[i], perm[i+1])
# ### G.add_edge(perm[n-1],perm[0])
# ### NX.draw(G,position)
# ### P.show()
print("TWO INDEX MODEL")
model = tsptw2(n,c,e,l)
model.optimize()
print("Optimal value:", model.getObjVal())
x,u = model.data
for (i,j) in x:
if model.getVal(x[i,j]) > EPS:
print(x[i,j].name,i,j,model.getVal(x[i,j]))
start_time = [0]*(n+1)
for (i,j) in u:
if model.getVal(u[i,j]) > EPS:
print(u[i,j].name,i,j,model.getVal(u[i,j]))
start_time[j] += model.getVal(u[i,j])
start = [i for v,i in sorted([(start_time[i],i) for i in range(1,n+1)])]
print(start)
| 7,537 | 31.491379 | 106 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/vrp.py | """
vrp.py: solve the vehicle routing problem.
approach:
- start with assignment model
- add cuts until all components of the graph are connected
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
import networkx
from pyscipopt import Model, quicksum, multidict
def solve_vrp(V,c,m,q,Q):
"""solve_vrp -- solve the vehicle routing problem.
- start with assignment model (depot has a special status)
- add cuts until all components of the graph are connected
Parameters:
- V: set/list of nodes in the graph
- c[i,j]: cost for traversing edge (i,j)
- m: number of vehicles available
- q[i]: demand for customer i
- Q: vehicle capacity
Returns the optimum objective value and the list of edges used.
"""
def addcut(cut_edges):
"""addcut: add constraint to eliminate infeasible solutions
Parameters:
- cut_edges: list of edges in the current solution, except connections to depot
Returns True if a cut was added, False otherwise
"""
G = networkx.Graph()
G.add_edges_from(cut_edges)
Components = networkx.connected_components(G)
cut = False
for S in Components:
S_card = len(S)
q_sum = sum(q[i] for i in S)
NS = int(math.ceil(float(q_sum)/Q))
S_edges = [(i,j) for i in S for j in S if i<j and (i,j) in cut_edges]
if S_card >= 3 and (len(S_edges) >= S_card or NS > 1):
add = model.addCons(quicksum(x[i,j] for i in S for j in S if j > i) <= S_card-NS)
cut = True
return cut
model = Model("vrp")
x = {}
for i in V:
for j in V:
if j > i and i == V[0]: # depot
x[i,j] = model.addVar(ub=2, vtype="I", name="x(%s,%s)"%(i,j))
elif j > i:
x[i,j] = model.addVar(ub=1, vtype="I", name="x(%s,%s)"%(i,j))
model.addCons(quicksum(x[V[0],j] for j in V[1:]) == 2*m, "DegreeDepot")
for i in V[1:]:
model.addCons(quicksum(x[j,i] for j in V if j < i) +
quicksum(x[i,j] for j in V if j > i) == 2, "Degree(%s)"%i)
model.setObjective(quicksum(c[i,j]*x[i,j] for i in V for j in V if j>i), "minimize")
model.hideOutput()
EPS = 1.e-6
while True:
model.optimize()
edges = []
for (i,j) in x:
if model.getVal(x[i,j]) > EPS:
if i != V[0] and j != V[0]:
edges.append((i,j))
if addcut(edges) == False:
break
return model.getObjVal(),edges
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2-x1)**2 + (y2-y1)**2)
def make_data(n):
"""make_data: compute matrix distance based on euclidean distance"""
V = range(1,n+1)
x = dict([(i,random.random()) for i in V])
y = dict([(i,random.random()) for i in V])
c,q = {},{}
Q = 100
for i in V:
q[i] = random.randint(10,20)
for j in V:
if j > i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return V,c,q,Q
if __name__ == "__main__":
import sys
n = 19
m = 3
seed = 1
random.seed(seed)
V,c,q,Q = make_data(n)
z,edges = solve_vrp(V,c,m,q,Q)
print("Optimal solution:",z)
print("Edges in the solution:")
print(sorted(edges))
| 3,456 | 29.866071 | 97 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/examples/unfinished/vrp_lazy.py | """
vrp.py: model for the vehicle routing problem using callback for adding cuts.
approach:
- start with assignment model
- add cuts until all components of the graph are connected
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
import math
import random
import networkx
from pyscipopt import Model, Conshdlr, quicksum, multidict, SCIP_RESULT, SCIP_PRESOLTIMING, SCIP_PROPTIMING
class VRPconshdlr(Conshdlr):
def addCuts(self, checkonly):
"""add cuts if necessary and return whether model is feasible"""
cutsadded = False
edges = []
x = self.model.data
for (i, j) in x:
if self.model.getVal(x[i, j]) > .5:
if i != V[0] and j != V[0]:
edges.append((i, j))
G = networkx.Graph()
G.add_edges_from(edges)
Components = list(networkx.connected_components(G))
for S in Components:
S_card = len(S)
q_sum = sum(q[i] for i in S)
NS = int(math.ceil(float(q_sum) / Q))
S_edges = [(i, j) for i in S for j in S if i < j and (i, j) in edges]
if S_card >= 3 and (len(S_edges) >= S_card or NS > 1):
cutsadded = True
if checkonly:
break
else:
self.model.addCons(quicksum(x[i, j] for i in S for j in S if j > i) <= S_card - NS)
print("adding cut for", S_edges)
return cutsadded
def conscheck(self, constraints, solution, checkintegrality, checklprows, printreason):
if self.addCuts(checkonly = True):
return {"result": SCIP_RESULT.INFEASIBLE}
else:
return {"result": SCIP_RESULT.FEASIBLE}
def consenfolp(self, constraints, nusefulconss, solinfeasible):
if self.addCuts(checkonly = False):
return {"result": SCIP_RESULT.CONSADDED}
else:
return {"result": SCIP_RESULT.FEASIBLE}
def conslock(self, constraint, nlockspos, nlocksneg):
pass
def vrp(V, c, m, q, Q):
"""solve_vrp -- solve the vehicle routing problem.
- start with assignment model (depot has a special status)
- add cuts until all components of the graph are connected
Parameters:
- V: set/list of nodes in the graph
- c[i,j]: cost for traversing edge (i,j)
- m: number of vehicles available
- q[i]: demand for customer i
- Q: vehicle capacity
Returns the optimum objective value and the list of edges used.
"""
model = Model("vrp")
vrp_conshdlr = VRPconshdlr()
x = {}
for i in V:
for j in V:
if j > i and i == V[0]: # depot
x[i,j] = model.addVar(ub=2, vtype="I", name="x(%s,%s)"%(i,j))
elif j > i:
x[i,j] = model.addVar(ub=1, vtype="I", name="x(%s,%s)"%(i,j))
model.addCons(quicksum(x[V[0],j] for j in V[1:]) == 2*m, "DegreeDepot")
for i in V[1:]:
model.addCons(quicksum(x[j,i] for j in V if j < i) +
quicksum(x[i,j] for j in V if j > i) == 2, "Degree(%s)"%i)
model.setObjective(quicksum(c[i,j]*x[i,j] for i in V for j in V if j>i), "minimize")
model.data = x
return model, vrp_conshdlr
def distance(x1,y1,x2,y2):
"""distance: euclidean distance between (x1,y1) and (x2,y2)"""
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def make_data(n):
"""make_data: compute matrix distance based on euclidean distance"""
V = range(1,n+1)
x = dict([(i, random.random()) for i in V])
y = dict([(i, random.random()) for i in V])
c, q = {}, {}
Q = 100
for i in V:
q[i] = random.randint(10, 20)
for j in V:
if j > i:
c[i, j] = distance(x[i], y[i], x[j], y[j])
return V, c, q, Q
if __name__ == "__main__":
n = 19
m = 3
seed = 1
random.seed(seed)
V,c,q,Q = make_data(n)
model, conshdlr = vrp(V, c, m, q, Q)
model.setBoolParam("misc/allowdualreds", 0)
model.includeConshdlr(conshdlr, "VRP", "VRP constraint handler",
sepapriority = 0, enfopriority = 1, chckpriority = 1, sepafreq = -1, propfreq = -1,
eagerfreq = -1, maxprerounds = 0, delaysepa = False, delayprop = False, needscons = False,
presoltiming = SCIP_PRESOLTIMING.FAST, proptiming = SCIP_PROPTIMING.BEFORELP)
model.optimize()
x = model.data
edges = []
for (i, j) in x:
if model.getVal(x[i, j]) > .5:
if i != V[0] and j != V[0]:
edges.append((i, j))
print("Optimal solution:", model.getObjVal())
print("Edges in the solution:")
print(sorted(edges))
| 4,744 | 33.136691 | 116 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/src/pyscipopt/Multidict.py | ##@file Multidict.py
#@brief Implementation of Multidictionaries
def multidict(D):
'''creates a multidictionary'''
keys = list(D.keys())
if len(keys) == 0:
return [[]]
try:
N = len(D[keys[0]])
islist = True
except:
N = 1
islist = False
dlist = [dict() for d in range(N)]
for k in keys:
if islist:
for i in range(N):
dlist[i][k] = D[k][i]
else:
dlist[0][k] = D[k]
return [keys]+dlist
| 511 | 22.272727 | 43 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/src/pyscipopt/__init__.py | __version__ = '2.1.5'
# export user-relevant objects:
from pyscipopt.Multidict import multidict
from pyscipopt.scip import Model
from pyscipopt.scip import Benders
from pyscipopt.scip import Benderscut
from pyscipopt.scip import Branchrule
from pyscipopt.scip import Nodesel
from pyscipopt.scip import Conshdlr
from pyscipopt.scip import Eventhdlr
from pyscipopt.scip import Heur
from pyscipopt.scip import Presol
from pyscipopt.scip import Pricer
from pyscipopt.scip import Prop
from pyscipopt.scip import Sepa
from pyscipopt.scip import LP
from pyscipopt.scip import Expr
from pyscipopt.scip import quicksum
from pyscipopt.scip import quickprod
from pyscipopt.scip import exp
from pyscipopt.scip import log
from pyscipopt.scip import sqrt
from pyscipopt.scip import PY_SCIP_RESULT as SCIP_RESULT
from pyscipopt.scip import PY_SCIP_PARAMSETTING as SCIP_PARAMSETTING
from pyscipopt.scip import PY_SCIP_PARAMEMPHASIS as SCIP_PARAMEMPHASIS
from pyscipopt.scip import PY_SCIP_STATUS as SCIP_STATUS
from pyscipopt.scip import PY_SCIP_STAGE as SCIP_STAGE
from pyscipopt.scip import PY_SCIP_PROPTIMING as SCIP_PROPTIMING
from pyscipopt.scip import PY_SCIP_PRESOLTIMING as SCIP_PRESOLTIMING
from pyscipopt.scip import PY_SCIP_HEURTIMING as SCIP_HEURTIMING
from pyscipopt.scip import PY_SCIP_EVENTTYPE as SCIP_EVENTTYPE
from pyscipopt.scip import PY_SCIP_LPSOLSTAT as SCIP_LPSOLSTAT
from pyscipopt.scip import PY_SCIP_BRANCHDIR as SCIP_BRANCHDIR
from pyscipopt.scip import PY_SCIP_BENDERSENFOTYPE as SCIP_BENDERSENFOTYPE
| 1,701 | 46.277778 | 79 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/src/pyscipopt/scip.c | /* Generated by Cython 0.29.24 */
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#define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
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#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash)
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#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name)
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#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
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#define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u))
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#define CYTHON_PEP393_ENABLED 0
#define PyUnicode_1BYTE_KIND 1
#define PyUnicode_2BYTE_KIND 2
#define PyUnicode_4BYTE_KIND 4
#define __Pyx_PyUnicode_READY(op) (0)
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
#define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111)
#define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
#define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
#define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
#define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch)
#define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u))
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#define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
#else
#define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\
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#define PyUnicode_Contains(u, s) PySequence_Contains(u, s)
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#define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type)
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#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format)
#define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt)
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#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
#else
#define __Pyx_PyString_Format(a, b) PyString_Format(a, b)
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#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII)
#define PyObject_ASCII(o) PyObject_Repr(o)
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBaseString_Type PyUnicode_Type
#define PyStringObject PyUnicodeObject
#define PyString_Type PyUnicode_Type
#define PyString_Check PyUnicode_Check
#define PyString_CheckExact PyUnicode_CheckExact
#ifndef PyObject_Unicode
#define PyObject_Unicode PyObject_Str
#endif
#endif
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
#define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
#else
#define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
#define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
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#define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
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#if PY_VERSION_HEX >= 0x030900A4
#define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt)
#define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size)
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#define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt)
#define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size)
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#if CYTHON_ASSUME_SAFE_MACROS
#define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq)
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#if PY_MAJOR_VERSION >= 3
#define PyIntObject PyLongObject
#define PyInt_Type PyLong_Type
#define PyInt_Check(op) PyLong_Check(op)
#define PyInt_CheckExact(op) PyLong_CheckExact(op)
#define PyInt_FromString PyLong_FromString
#define PyInt_FromUnicode PyLong_FromUnicode
#define PyInt_FromLong PyLong_FromLong
#define PyInt_FromSize_t PyLong_FromSize_t
#define PyInt_FromSsize_t PyLong_FromSsize_t
#define PyInt_AsLong PyLong_AsLong
#define PyInt_AS_LONG PyLong_AS_LONG
#define PyInt_AsSsize_t PyLong_AsSsize_t
#define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
#define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
#define PyNumber_Int PyNumber_Long
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBoolObject PyLongObject
#endif
#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
#ifndef PyUnicode_InternFromString
#define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
#endif
#endif
#if PY_VERSION_HEX < 0x030200A4
typedef long Py_hash_t;
#define __Pyx_PyInt_FromHash_t PyInt_FromLong
#define __Pyx_PyInt_AsHash_t PyInt_AsLong
#else
#define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
#define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
#endif
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func))
#else
#define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
#endif
#if CYTHON_USE_ASYNC_SLOTS
#if PY_VERSION_HEX >= 0x030500B1
#define __Pyx_PyAsyncMethodsStruct PyAsyncMethods
#define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async)
#else
#define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved))
#endif
#else
#define __Pyx_PyType_AsAsync(obj) NULL
#endif
#ifndef __Pyx_PyAsyncMethodsStruct
typedef struct {
unaryfunc am_await;
unaryfunc am_aiter;
unaryfunc am_anext;
} __Pyx_PyAsyncMethodsStruct;
#endif
#if defined(WIN32) || defined(MS_WINDOWS)
#define _USE_MATH_DEFINES
#endif
#include <math.h>
#ifdef NAN
#define __PYX_NAN() ((float) NAN)
#else
static CYTHON_INLINE float __PYX_NAN() {
float value;
memset(&value, 0xFF, sizeof(value));
return value;
}
#endif
#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL)
#define __Pyx_truncl trunc
#else
#define __Pyx_truncl truncl
#endif
#define __PYX_MARK_ERR_POS(f_index, lineno) \
{ __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; }
#define __PYX_ERR(f_index, lineno, Ln_error) \
{ __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; }
#ifndef __PYX_EXTERN_C
#ifdef __cplusplus
#define __PYX_EXTERN_C extern "C"
#else
#define __PYX_EXTERN_C extern
#endif
#endif
#define __PYX_HAVE__pyscipopt__scip
#define __PYX_HAVE_API__pyscipopt__scip
/* Early includes */
#include "scip/scip.h"
#include "scip/tree.h"
#include "scip/scipdefplugins.h"
#include "scip/cons_linear.h"
#include "scip/cons_quadratic.h"
#include "scip/cons_sos1.h"
#include "scip/cons_sos2.h"
#include "scip/cons_and.h"
#include "scip/cons_or.h"
#include "scip/cons_xor.h"
#include "blockmemshell/memory.h"
#include "nlpi/pub_expr.h"
#include "scip/pub_nlp.h"
#include "scip/cons_nonlinear.h"
#include "scip/cons_cardinality.h"
#include "scip/cons_indicator.h"
#include "scip/cons_countsols.h"
#include "scip/paramset.h"
#include "scip/pub_lp.h"
#include "scip/lp.h"
#include "scip/def.h"
#include "scip/struct_branch.h"
#include "scip/type_misc.h"
#include "time.h"
#include "scip/struct_clock.h"
#include "scip/type_history.h"
#include "scip/struct_stat.h"
#include <string.h>
#include <stdio.h>
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
/* NumPy API declarations from "numpy/__init__.pxd" */
#include "pythread.h"
#include <stdlib.h>
#include "numpy/npy_math.h"
#include <math.h>
#ifdef _OPENMP
#include <omp.h>
#endif /* _OPENMP */
#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS)
#define CYTHON_WITHOUT_ASSERTIONS
#endif
typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding;
const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0
#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8)
#define __PYX_DEFAULT_STRING_ENCODING ""
#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#define __Pyx_uchar_cast(c) ((unsigned char)c)
#define __Pyx_long_cast(x) ((long)x)
#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\
(sizeof(type) < sizeof(Py_ssize_t)) ||\
(sizeof(type) > sizeof(Py_ssize_t) &&\
likely(v < (type)PY_SSIZE_T_MAX ||\
v == (type)PY_SSIZE_T_MAX) &&\
(!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\
v == (type)PY_SSIZE_T_MIN))) ||\
(sizeof(type) == sizeof(Py_ssize_t) &&\
(is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\
v == (type)PY_SSIZE_T_MAX))) )
static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) {
return (size_t) i < (size_t) limit;
}
#if defined (__cplusplus) && __cplusplus >= 201103L
#include <cstdlib>
#define __Pyx_sst_abs(value) std::abs(value)
#elif SIZEOF_INT >= SIZEOF_SIZE_T
#define __Pyx_sst_abs(value) abs(value)
#elif SIZEOF_LONG >= SIZEOF_SIZE_T
#define __Pyx_sst_abs(value) labs(value)
#elif defined (_MSC_VER)
#define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value))
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
#define __Pyx_sst_abs(value) llabs(value)
#elif defined (__GNUC__)
#define __Pyx_sst_abs(value) __builtin_llabs(value)
#else
#define __Pyx_sst_abs(value) ((value<0) ? -value : value)
#endif
static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*);
static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
#define __Pyx_PyBytes_FromString PyBytes_FromString
#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
#if PY_MAJOR_VERSION < 3
#define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#else
#define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
#endif
#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s))
#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s))
#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s))
#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s))
#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s))
#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s))
#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s)
#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s)
#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s)
#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s)
#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) {
const Py_UNICODE *u_end = u;
while (*u_end++) ;
return (size_t)(u_end - u - 1);
}
#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj)
#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b);
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x);
#define __Pyx_PySequence_Tuple(obj)\
(likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj))
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
#if CYTHON_ASSUME_SAFE_MACROS
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
#else
#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
#endif
#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x))
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
static int __Pyx_sys_getdefaultencoding_not_ascii;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
PyObject* ascii_chars_u = NULL;
PyObject* ascii_chars_b = NULL;
const char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
if (strcmp(default_encoding_c, "ascii") == 0) {
__Pyx_sys_getdefaultencoding_not_ascii = 0;
} else {
char ascii_chars[128];
int c;
for (c = 0; c < 128; c++) {
ascii_chars[c] = c;
}
__Pyx_sys_getdefaultencoding_not_ascii = 1;
ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
if (!ascii_chars_u) goto bad;
ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
PyErr_Format(
PyExc_ValueError,
"This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
default_encoding_c);
goto bad;
}
Py_DECREF(ascii_chars_u);
Py_DECREF(ascii_chars_b);
}
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
Py_XDECREF(ascii_chars_u);
Py_XDECREF(ascii_chars_b);
return -1;
}
#endif
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
#else
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
static char* __PYX_DEFAULT_STRING_ENCODING;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
__PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1);
if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
return -1;
}
#endif
#endif
/* Test for GCC > 2.95 */
#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
#else /* !__GNUC__ or GCC < 2.95 */
#define likely(x) (x)
#define unlikely(x) (x)
#endif /* __GNUC__ */
static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; }
static PyObject *__pyx_m = NULL;
static PyObject *__pyx_d;
static PyObject *__pyx_b;
static PyObject *__pyx_cython_runtime = NULL;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static PyObject *__pyx_empty_unicode;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;
/* Header.proto */
#if !defined(CYTHON_CCOMPLEX)
#if defined(__cplusplus)
#define CYTHON_CCOMPLEX 1
#elif defined(_Complex_I)
#define CYTHON_CCOMPLEX 1
#else
#define CYTHON_CCOMPLEX 0
#endif
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
#include <complex>
#else
#include <complex.h>
#endif
#endif
#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__)
#undef _Complex_I
#define _Complex_I 1.0fj
#endif
static const char *__pyx_f[] = {
"src/pyscipopt/expr.pxi",
"src/pyscipopt/lp.pxi",
"src/pyscipopt/benders.pxi",
"src/pyscipopt/scip.pyx",
"stringsource",
"src/pyscipopt/benderscut.pxi",
"src/pyscipopt/branchrule.pxi",
"src/pyscipopt/conshdlr.pxi",
"src/pyscipopt/event.pxi",
"src/pyscipopt/heuristic.pxi",
"src/pyscipopt/presol.pxi",
"src/pyscipopt/pricer.pxi",
"src/pyscipopt/propagator.pxi",
"src/pyscipopt/sepa.pxi",
"src/pyscipopt/relax.pxi",
"src/pyscipopt/nodesel.pxi",
"__init__.pxd",
"type.pxd",
"bool.pxd",
"complex.pxd",
};
/* BufferFormatStructs.proto */
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
const char* name;
struct __Pyx_StructField_* fields;
size_t size;
size_t arraysize[8];
int ndim;
char typegroup;
char is_unsigned;
int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
__Pyx_TypeInfo* type;
const char* name;
size_t offset;
} __Pyx_StructField;
typedef struct {
__Pyx_StructField* field;
size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
__Pyx_StructField root;
__Pyx_BufFmt_StackElem* head;
size_t fmt_offset;
size_t new_count, enc_count;
size_t struct_alignment;
int is_complex;
char enc_type;
char new_packmode;
char enc_packmode;
char is_valid_array;
} __Pyx_BufFmt_Context;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":689
* # in Cython to enable them only on the right systems.
*
* ctypedef npy_int8 int8_t # <<<<<<<<<<<<<<
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t
*/
typedef npy_int8 __pyx_t_5numpy_int8_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":690
*
* ctypedef npy_int8 int8_t
* ctypedef npy_int16 int16_t # <<<<<<<<<<<<<<
* ctypedef npy_int32 int32_t
* ctypedef npy_int64 int64_t
*/
typedef npy_int16 __pyx_t_5numpy_int16_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":691
* ctypedef npy_int8 int8_t
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t # <<<<<<<<<<<<<<
* ctypedef npy_int64 int64_t
* #ctypedef npy_int96 int96_t
*/
typedef npy_int32 __pyx_t_5numpy_int32_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":692
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t
* ctypedef npy_int64 int64_t # <<<<<<<<<<<<<<
* #ctypedef npy_int96 int96_t
* #ctypedef npy_int128 int128_t
*/
typedef npy_int64 __pyx_t_5numpy_int64_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":696
* #ctypedef npy_int128 int128_t
*
* ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<<
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t
*/
typedef npy_uint8 __pyx_t_5numpy_uint8_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":697
*
* ctypedef npy_uint8 uint8_t
* ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<<
* ctypedef npy_uint32 uint32_t
* ctypedef npy_uint64 uint64_t
*/
typedef npy_uint16 __pyx_t_5numpy_uint16_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":698
* ctypedef npy_uint8 uint8_t
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<<
* ctypedef npy_uint64 uint64_t
* #ctypedef npy_uint96 uint96_t
*/
typedef npy_uint32 __pyx_t_5numpy_uint32_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":699
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t
* ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<<
* #ctypedef npy_uint96 uint96_t
* #ctypedef npy_uint128 uint128_t
*/
typedef npy_uint64 __pyx_t_5numpy_uint64_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":703
* #ctypedef npy_uint128 uint128_t
*
* ctypedef npy_float32 float32_t # <<<<<<<<<<<<<<
* ctypedef npy_float64 float64_t
* #ctypedef npy_float80 float80_t
*/
typedef npy_float32 __pyx_t_5numpy_float32_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":704
*
* ctypedef npy_float32 float32_t
* ctypedef npy_float64 float64_t # <<<<<<<<<<<<<<
* #ctypedef npy_float80 float80_t
* #ctypedef npy_float128 float128_t
*/
typedef npy_float64 __pyx_t_5numpy_float64_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":713
* # The int types are mapped a bit surprising --
* # numpy.int corresponds to 'l' and numpy.long to 'q'
* ctypedef npy_long int_t # <<<<<<<<<<<<<<
* ctypedef npy_longlong long_t
* ctypedef npy_longlong longlong_t
*/
typedef npy_long __pyx_t_5numpy_int_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":714
* # numpy.int corresponds to 'l' and numpy.long to 'q'
* ctypedef npy_long int_t
* ctypedef npy_longlong long_t # <<<<<<<<<<<<<<
* ctypedef npy_longlong longlong_t
*
*/
typedef npy_longlong __pyx_t_5numpy_long_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":715
* ctypedef npy_long int_t
* ctypedef npy_longlong long_t
* ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<<
*
* ctypedef npy_ulong uint_t
*/
typedef npy_longlong __pyx_t_5numpy_longlong_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":717
* ctypedef npy_longlong longlong_t
*
* ctypedef npy_ulong uint_t # <<<<<<<<<<<<<<
* ctypedef npy_ulonglong ulong_t
* ctypedef npy_ulonglong ulonglong_t
*/
typedef npy_ulong __pyx_t_5numpy_uint_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":718
*
* ctypedef npy_ulong uint_t
* ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<<
* ctypedef npy_ulonglong ulonglong_t
*
*/
typedef npy_ulonglong __pyx_t_5numpy_ulong_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":719
* ctypedef npy_ulong uint_t
* ctypedef npy_ulonglong ulong_t
* ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<<
*
* ctypedef npy_intp intp_t
*/
typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":721
* ctypedef npy_ulonglong ulonglong_t
*
* ctypedef npy_intp intp_t # <<<<<<<<<<<<<<
* ctypedef npy_uintp uintp_t
*
*/
typedef npy_intp __pyx_t_5numpy_intp_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":722
*
* ctypedef npy_intp intp_t
* ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<<
*
* ctypedef npy_double float_t
*/
typedef npy_uintp __pyx_t_5numpy_uintp_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":724
* ctypedef npy_uintp uintp_t
*
* ctypedef npy_double float_t # <<<<<<<<<<<<<<
* ctypedef npy_double double_t
* ctypedef npy_longdouble longdouble_t
*/
typedef npy_double __pyx_t_5numpy_float_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":725
*
* ctypedef npy_double float_t
* ctypedef npy_double double_t # <<<<<<<<<<<<<<
* ctypedef npy_longdouble longdouble_t
*
*/
typedef npy_double __pyx_t_5numpy_double_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":726
* ctypedef npy_double float_t
* ctypedef npy_double double_t
* ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<<
*
* ctypedef npy_cfloat cfloat_t
*/
typedef npy_longdouble __pyx_t_5numpy_longdouble_t;
/* Declarations.proto */
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
typedef ::std::complex< float > __pyx_t_float_complex;
#else
typedef float _Complex __pyx_t_float_complex;
#endif
#else
typedef struct { float real, imag; } __pyx_t_float_complex;
#endif
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float);
/* Declarations.proto */
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
typedef ::std::complex< double > __pyx_t_double_complex;
#else
typedef double _Complex __pyx_t_double_complex;
#endif
#else
typedef struct { double real, imag; } __pyx_t_double_complex;
#endif
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double);
/*--- Type declarations ---*/
struct __pyx_obj_9pyscipopt_4scip_Expr;
struct __pyx_obj_9pyscipopt_4scip_ExprCons;
struct __pyx_obj_9pyscipopt_4scip_GenExpr;
struct __pyx_obj_9pyscipopt_4scip_SumExpr;
struct __pyx_obj_9pyscipopt_4scip_ProdExpr;
struct __pyx_obj_9pyscipopt_4scip_VarExpr;
struct __pyx_obj_9pyscipopt_4scip_PowExpr;
struct __pyx_obj_9pyscipopt_4scip_UnaryExpr;
struct __pyx_obj_9pyscipopt_4scip_Constant;
struct __pyx_obj_9pyscipopt_4scip_LP;
struct __pyx_obj_9pyscipopt_4scip_Benders;
struct __pyx_obj_9pyscipopt_4scip_Benderscut;
struct __pyx_obj_9pyscipopt_4scip_Branchrule;
struct __pyx_obj_9pyscipopt_4scip_Conshdlr;
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr;
struct __pyx_obj_9pyscipopt_4scip_Heur;
struct __pyx_obj_9pyscipopt_4scip_Presol;
struct __pyx_obj_9pyscipopt_4scip_Pricer;
struct __pyx_obj_9pyscipopt_4scip_Prop;
struct __pyx_obj_9pyscipopt_4scip_Sepa;
struct __pyx_obj_9pyscipopt_4scip_Relax;
struct __pyx_obj_9pyscipopt_4scip_Nodesel;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR;
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE;
struct __pyx_obj_9pyscipopt_4scip_Event;
struct __pyx_obj_9pyscipopt_4scip_Column;
struct __pyx_obj_9pyscipopt_4scip_Row;
struct __pyx_obj_9pyscipopt_4scip_Solution;
struct __pyx_obj_9pyscipopt_4scip_Node;
struct __pyx_obj_9pyscipopt_4scip_Variable;
struct __pyx_obj_9pyscipopt_4scip_Constraint;
struct __pyx_obj_9pyscipopt_4scip_Model;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_3_genexpr;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_5_genexpr;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_6_addRows;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_7_genexpr;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":728
* ctypedef npy_longdouble longdouble_t
*
* ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<<
* ctypedef npy_cdouble cdouble_t
* ctypedef npy_clongdouble clongdouble_t
*/
typedef npy_cfloat __pyx_t_5numpy_cfloat_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":729
*
* ctypedef npy_cfloat cfloat_t
* ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<<
* ctypedef npy_clongdouble clongdouble_t
*
*/
typedef npy_cdouble __pyx_t_5numpy_cdouble_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":730
* ctypedef npy_cfloat cfloat_t
* ctypedef npy_cdouble cdouble_t
* ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<<
*
* ctypedef npy_cdouble complex_t
*/
typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t;
/* "../../../py-venv-test/lib/python3.6/site-packages/numpy/__init__.pxd":732
* ctypedef npy_clongdouble clongdouble_t
*
* ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew1(a):
*/
typedef npy_cdouble __pyx_t_5numpy_complex_t;
/* "src/pyscipopt/expr.pxi":143
* ##@details Polynomial expressions of variables with operator overloading. \n
* #See also the @ref ExprDetails "description" in the expr.pxi.
* cdef class Expr: # <<<<<<<<<<<<<<
* cdef public terms
*
*/
struct __pyx_obj_9pyscipopt_4scip_Expr {
PyObject_HEAD
PyObject *terms;
};
/* "src/pyscipopt/expr.pxi":303
*
*
* cdef class ExprCons: # <<<<<<<<<<<<<<
* '''Constraints with a polynomial expressions and lower/upper bounds.'''
* cdef public expr
*/
struct __pyx_obj_9pyscipopt_4scip_ExprCons {
PyObject_HEAD
PyObject *expr;
PyObject *_lhs;
PyObject *_rhs;
};
/* "src/pyscipopt/expr.pxi":429
* #
* #See also the @ref ExprDetails "description" in the expr.pxi.
* cdef class GenExpr: # <<<<<<<<<<<<<<
* cdef public operatorIndex
* cdef public _op
*/
struct __pyx_obj_9pyscipopt_4scip_GenExpr {
PyObject_HEAD
PyObject *operatorIndex;
PyObject *_op;
PyObject *children;
};
/* "src/pyscipopt/expr.pxi":609
*
* # Sum Expressions
* cdef class SumExpr(GenExpr): # <<<<<<<<<<<<<<
*
* cdef public constant
*/
struct __pyx_obj_9pyscipopt_4scip_SumExpr {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
PyObject *constant;
PyObject *coefs;
};
/* "src/pyscipopt/expr.pxi":624
*
* # Prod Expressions
* cdef class ProdExpr(GenExpr): # <<<<<<<<<<<<<<
* cdef public constant
* def __init__(self):
*/
struct __pyx_obj_9pyscipopt_4scip_ProdExpr {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
PyObject *constant;
};
/* "src/pyscipopt/expr.pxi":635
*
* # Var Expressions
* cdef class VarExpr(GenExpr): # <<<<<<<<<<<<<<
* cdef public var
* def __init__(self, var):
*/
struct __pyx_obj_9pyscipopt_4scip_VarExpr {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
PyObject *var;
};
/* "src/pyscipopt/expr.pxi":645
*
* # Pow Expressions
* cdef class PowExpr(GenExpr): # <<<<<<<<<<<<<<
* cdef public expo
* def __init__(self):
*/
struct __pyx_obj_9pyscipopt_4scip_PowExpr {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
PyObject *expo;
};
/* "src/pyscipopt/expr.pxi":656
*
* # Exp, Log, Sqrt Expressions
* cdef class UnaryExpr(GenExpr): # <<<<<<<<<<<<<<
* def __init__(self, op, expr):
* self.children = []
*/
struct __pyx_obj_9pyscipopt_4scip_UnaryExpr {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
};
/* "src/pyscipopt/expr.pxi":666
*
* # class for constant expressions
* cdef class Constant(GenExpr): # <<<<<<<<<<<<<<
* cdef public number
* def __init__(self,number):
*/
struct __pyx_obj_9pyscipopt_4scip_Constant {
struct __pyx_obj_9pyscipopt_4scip_GenExpr __pyx_base;
PyObject *number;
};
/* "src/pyscipopt/lp.pxi":3
* ##@file lp.pxi
* #@brief Base class of the LP Plugin
* cdef class LP: # <<<<<<<<<<<<<<
* cdef SCIP_LPI* lpi
* cdef readonly str name
*/
struct __pyx_obj_9pyscipopt_4scip_LP {
PyObject_HEAD
SCIP_LPI *lpi;
PyObject *name;
};
/* "src/pyscipopt/benders.pxi":3
* ##@file benders.pxi
* #@brief Base class of the Benders decomposition Plugin
* cdef class Benders: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Benders {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/benderscut.pxi":3
* ##@file benderscut.pxi
* #@brief Base class of the Benderscut Plugin
* cdef class Benderscut: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public Benders benders
*/
struct __pyx_obj_9pyscipopt_4scip_Benderscut {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
struct __pyx_obj_9pyscipopt_4scip_Benders *benders;
PyObject *name;
};
/* "src/pyscipopt/branchrule.pxi":3
* ##@file branchrule.pxi
* #@brief Base class of the Branchrule Plugin
* cdef class Branchrule: # <<<<<<<<<<<<<<
* cdef public Model model
*
*/
struct __pyx_obj_9pyscipopt_4scip_Branchrule {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
};
/* "src/pyscipopt/conshdlr.pxi":4
* #@brief base class of the Constraint Handler plugin
*
* cdef class Conshdlr: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Conshdlr {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/event.pxi":3
* ##@file event.pxi
* #@brief Base class of the Event Handler Plugin
* cdef class Eventhdlr: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/heuristic.pxi":3
* ##@file heuristic.pxi
* #@brief Base class of the Heuristics Plugin
* cdef class Heur: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Heur {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/presol.pxi":3
* ##@file presol.pxi
* #@brief Base class of the Presolver Plugin
* cdef class Presol: # <<<<<<<<<<<<<<
* cdef public Model model
*
*/
struct __pyx_obj_9pyscipopt_4scip_Presol {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
};
/* "src/pyscipopt/pricer.pxi":3
* ##@file pricer.pxi
* #@brief Base class of the Pricers Plugin
* cdef class Pricer: # <<<<<<<<<<<<<<
* cdef public Model model
*
*/
struct __pyx_obj_9pyscipopt_4scip_Pricer {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
};
/* "src/pyscipopt/propagator.pxi":3
* ##@file propagator.pxi
* #@brief Base class of the Propagators Plugin
* cdef class Prop: # <<<<<<<<<<<<<<
* cdef public Model model
*
*/
struct __pyx_obj_9pyscipopt_4scip_Prop {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
};
/* "src/pyscipopt/sepa.pxi":3
* ##@file sepa.pxi
* #@brief Base class of the Separator Plugin
* cdef class Sepa: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Sepa {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/relax.pxi":3
* ##@file relax.pxi
* #@brief Base class of the Relaxator Plugin
* cdef class Relax: # <<<<<<<<<<<<<<
* cdef public Model model
* cdef public str name
*/
struct __pyx_obj_9pyscipopt_4scip_Relax {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
PyObject *name;
};
/* "src/pyscipopt/nodesel.pxi":3
* ##@file nodesel.pxi
* #@brief Base class of the Nodesel Plugin
* cdef class Nodesel: # <<<<<<<<<<<<<<
* cdef public Model model
*
*/
struct __pyx_obj_9pyscipopt_4scip_Nodesel {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Model *model;
};
/* "pyscipopt/scip.pyx":50
* # In __init__.py this is imported as SCIP_RESULT to keep the
* # original naming scheme using capital letters
* cdef class PY_SCIP_RESULT: # <<<<<<<<<<<<<<
* DIDNOTRUN = SCIP_DIDNOTRUN
* DELAYED = SCIP_DELAYED
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":69
* SUCCESS = SCIP_SUCCESS
*
* cdef class PY_SCIP_PARAMSETTING: # <<<<<<<<<<<<<<
* DEFAULT = SCIP_PARAMSETTING_DEFAULT
* AGGRESSIVE = SCIP_PARAMSETTING_AGGRESSIVE
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":75
* OFF = SCIP_PARAMSETTING_OFF
*
* cdef class PY_SCIP_PARAMEMPHASIS: # <<<<<<<<<<<<<<
* DEFAULT = SCIP_PARAMEMPHASIS_DEFAULT
* CPSOLVER = SCIP_PARAMEMPHASIS_CPSOLVER
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":87
* PHASEPROOF = SCIP_PARAMEMPHASIS_PHASEPROOF
*
* cdef class PY_SCIP_STATUS: # <<<<<<<<<<<<<<
* UNKNOWN = SCIP_STATUS_UNKNOWN
* USERINTERRUPT = SCIP_STATUS_USERINTERRUPT
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":104
* INFORUNBD = SCIP_STATUS_INFORUNBD
*
* cdef class PY_SCIP_STAGE: # <<<<<<<<<<<<<<
* INIT = SCIP_STAGE_INIT
* PROBLEM = SCIP_STAGE_PROBLEM
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":120
* FREE = SCIP_STAGE_FREE
*
* cdef class PY_SCIP_NODETYPE: # <<<<<<<<<<<<<<
* FOCUSNODE = SCIP_NODETYPE_FOCUSNODE
* PROBINGNODE = SCIP_NODETYPE_PROBINGNODE
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":134
*
*
* cdef class PY_SCIP_PROPTIMING: # <<<<<<<<<<<<<<
* BEFORELP = SCIP_PROPTIMING_BEFORELP
* DURINGLPLOOP = SCIP_PROPTIMING_DURINGLPLOOP
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":140
* AFTERLPNODE = SCIP_PROPTIMING_AFTERLPNODE
*
* cdef class PY_SCIP_PRESOLTIMING: # <<<<<<<<<<<<<<
* NONE = SCIP_PRESOLTIMING_NONE
* FAST = SCIP_PRESOLTIMING_FAST
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":146
* EXHAUSTIVE = SCIP_PRESOLTIMING_EXHAUSTIVE
*
* cdef class PY_SCIP_HEURTIMING: # <<<<<<<<<<<<<<
* BEFORENODE = SCIP_HEURTIMING_BEFORENODE
* DURINGLPLOOP = SCIP_HEURTIMING_DURINGLPLOOP
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":159
* AFTERPROPLOOP = SCIP_HEURTIMING_AFTERPROPLOOP
*
* cdef class PY_SCIP_EVENTTYPE: # <<<<<<<<<<<<<<
* DISABLED = SCIP_EVENTTYPE_DISABLED
* VARADDED = SCIP_EVENTTYPE_VARADDED
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":196
* SYNC = SCIP_EVENTTYPE_SYNC
*
* cdef class PY_SCIP_LPSOLSTAT: # <<<<<<<<<<<<<<
* NOTSOLVED = SCIP_LPSOLSTAT_NOTSOLVED
* OPTIMAL = SCIP_LPSOLSTAT_OPTIMAL
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":206
* ERROR = SCIP_LPSOLSTAT_ERROR
*
* cdef class PY_SCIP_BRANCHDIR: # <<<<<<<<<<<<<<
* DOWNWARDS = SCIP_BRANCHDIR_DOWNWARDS
* UPWARDS = SCIP_BRANCHDIR_UPWARDS
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":212
* AUTO = SCIP_BRANCHDIR_AUTO
*
* cdef class PY_SCIP_BENDERSENFOTYPE: # <<<<<<<<<<<<<<
* LP = SCIP_BENDERSENFOTYPE_LP
* RELAX = SCIP_BENDERSENFOTYPE_RELAX
*/
struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE {
PyObject_HEAD
};
/* "pyscipopt/scip.pyx":260
* raise Exception('SCIP: unknown return code!')
*
* cdef class Event: # <<<<<<<<<<<<<<
* cdef SCIP_EVENT* event
* # can be used to store problem data
*/
struct __pyx_obj_9pyscipopt_4scip_Event {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Event *__pyx_vtab;
SCIP_EVENT *event;
PyObject *data;
};
/* "pyscipopt/scip.pyx":296
* return Node.create(node)
*
* cdef class Column: # <<<<<<<<<<<<<<
* """Base class holding a pointer to corresponding SCIP_COL"""
* cdef SCIP_COL* scip_col
*/
struct __pyx_obj_9pyscipopt_4scip_Column {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Column *__pyx_vtab;
SCIP_COL *scip_col;
PyObject *data;
};
/* "pyscipopt/scip.pyx":347
* return SCIPcolGetUb(self.scip_col)
*
* cdef class Row: # <<<<<<<<<<<<<<
* """Base class holding a pointer to corresponding SCIP_ROW"""
* cdef SCIP_ROW* scip_row
*/
struct __pyx_obj_9pyscipopt_4scip_Row {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Row *__pyx_vtab;
SCIP_ROW *scip_row;
PyObject *data;
};
/* "pyscipopt/scip.pyx":416
* return [vals[i] for i in range(self.getNNonz())]
*
* cdef class Solution: # <<<<<<<<<<<<<<
* """Base class holding a pointer to corresponding SCIP_SOL"""
* cdef SCIP_SOL* sol
*/
struct __pyx_obj_9pyscipopt_4scip_Solution {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Solution *__pyx_vtab;
SCIP_SOL *sol;
PyObject *data;
};
/* "pyscipopt/scip.pyx":428
* return sol
*
* cdef class Node: # <<<<<<<<<<<<<<
* """Base class holding a pointer to corresponding SCIP_NODE"""
* cdef SCIP_NODE* scip_node
*/
struct __pyx_obj_9pyscipopt_4scip_Node {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Node *__pyx_vtab;
SCIP_NODE *scip_node;
PyObject *data;
};
/* "pyscipopt/scip.pyx":492
*
*
* cdef class Variable(Expr): # <<<<<<<<<<<<<<
* """Is a linear expression and has SCIP_VAR*"""
* cdef SCIP_VAR* scip_var
*/
struct __pyx_obj_9pyscipopt_4scip_Variable {
struct __pyx_obj_9pyscipopt_4scip_Expr __pyx_base;
struct __pyx_vtabstruct_9pyscipopt_4scip_Variable *__pyx_vtab;
SCIP_VAR *scip_var;
PyObject *data;
};
/* "pyscipopt/scip.pyx":577
*
*
* cdef class Constraint: # <<<<<<<<<<<<<<
* cdef SCIP_CONS* scip_cons
* # can be used to store problem data
*/
struct __pyx_obj_9pyscipopt_4scip_Constraint {
PyObject_HEAD
struct __pyx_vtabstruct_9pyscipopt_4scip_Constraint *__pyx_vtab;
SCIP_CONS *scip_cons;
PyObject *data;
};
/* "pyscipopt/scip.pyx":665
* #@anchor Model
* ##
* cdef class Model: # <<<<<<<<<<<<<<
* cdef SCIP* _scip
* cdef SCIP_Bool* _valid
*/
struct __pyx_obj_9pyscipopt_4scip_Model {
PyObject_HEAD
SCIP *_scip;
SCIP_Bool *_valid;
struct __pyx_obj_9pyscipopt_4scip_Solution *_bestSol;
PyObject *data;
PyObject *__weakref__;
};
/* "src/pyscipopt/expr.pxi":88
* __slots__ = ('vartuple', 'ptrtuple', 'hashval')
*
* def __init__(self, *vartuple): # <<<<<<<<<<<<<<
* self.vartuple = tuple(sorted(vartuple, key=lambda v: v.ptr()))
* self.ptrtuple = tuple(v.ptr() for v in self.vartuple)
*/
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PyObject_HEAD
PyObject *__pyx_v_self;
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/* "src/pyscipopt/expr.pxi":90
* def __init__(self, *vartuple):
* self.vartuple = tuple(sorted(vartuple, key=lambda v: v.ptr()))
* self.ptrtuple = tuple(v.ptr() for v in self.vartuple) # <<<<<<<<<<<<<<
* self.hashval = sum(self.ptrtuple)
*
*/
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr {
PyObject_HEAD
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PyObject *(*__pyx_t_2)(PyObject *);
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/* "src/pyscipopt/expr.pxi":295
* return 'Expr(%s)' % repr(self.terms)
*
* def degree(self): # <<<<<<<<<<<<<<
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*/
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PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self;
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/* "src/pyscipopt/expr.pxi":300
* return 0
* else:
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*
*
*/
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_3_genexpr {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree *__pyx_outer_scope;
PyObject *__pyx_v_v;
PyObject *__pyx_t_0;
Py_ssize_t __pyx_t_1;
PyObject *(*__pyx_t_2)(PyObject *);
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/* "src/pyscipopt/lp.pxi":89
* free(c_inds)
*
* def addCols(self, entrieslist, objs = None, lbs = None, ubs = None): # <<<<<<<<<<<<<<
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*
*/
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols {
PyObject_HEAD
PyObject *__pyx_v_entrieslist;
};
/* "src/pyscipopt/lp.pxi":100
*
* ncols = len(entrieslist)
* nnonz = sum(len(entries) for entries in entrieslist) # <<<<<<<<<<<<<<
*
* cdef SCIP_Real* c_objs = <SCIP_Real*> malloc(ncols * sizeof(SCIP_Real))
*/
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_5_genexpr {
PyObject_HEAD
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols *__pyx_outer_scope;
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PyObject *__pyx_t_0;
Py_ssize_t __pyx_t_1;
PyObject *(*__pyx_t_2)(PyObject *);
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/* "src/pyscipopt/lp.pxi":183
* free(c_inds)
*
* def addRows(self, entrieslist, lhss = None, rhss = None): # <<<<<<<<<<<<<<
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*
*/
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_6_addRows {
PyObject_HEAD
PyObject *__pyx_v_entrieslist;
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/* "src/pyscipopt/lp.pxi":192
* """
* nrows = len(entrieslist)
* nnonz = sum(len(entries) for entries in entrieslist) # <<<<<<<<<<<<<<
*
* cdef SCIP_Real* c_lhss = <SCIP_Real*> malloc(nrows * sizeof(SCIP_Real))
*/
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PyObject_HEAD
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/* "pyscipopt/scip.pyx":260
* raise Exception('SCIP: unknown return code!')
*
* cdef class Event: # <<<<<<<<<<<<<<
* cdef SCIP_EVENT* event
* # can be used to store problem data
*/
struct __pyx_vtabstruct_9pyscipopt_4scip_Event {
PyObject *(*create)(SCIP_EVENT *);
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/* "pyscipopt/scip.pyx":296
* return Node.create(node)
*
* cdef class Column: # <<<<<<<<<<<<<<
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PyObject *(*create)(SCIP_COL *);
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/* "pyscipopt/scip.pyx":347
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*
* cdef class Row: # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":416
* return [vals[i] for i in range(self.getNNonz())]
*
* cdef class Solution: # <<<<<<<<<<<<<<
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*
* cdef class Node: # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":492
*
*
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/* "pyscipopt/scip.pyx":577
*
*
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static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
/* RaiseDoubleKeywords.proto */
static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
/* ParseKeywords.proto */
static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\
PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\
const char* function_name);
/* PyIntCompare.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, long intval, long inplace);
/* PyDictVersioning.proto */
#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS
#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1)
#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag)
#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\
(version_var) = __PYX_GET_DICT_VERSION(dict);\
(cache_var) = (value);
#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\
static PY_UINT64_T __pyx_dict_version = 0;\
static PyObject *__pyx_dict_cached_value = NULL;\
if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\
(VAR) = __pyx_dict_cached_value;\
} else {\
(VAR) = __pyx_dict_cached_value = (LOOKUP);\
__pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\
}\
}
static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj);
static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj);
static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version);
#else
#define __PYX_GET_DICT_VERSION(dict) (0)
#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)
#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP);
#endif
/* GetModuleGlobalName.proto */
#if CYTHON_USE_DICT_VERSIONS
#define __Pyx_GetModuleGlobalName(var, name) {\
static PY_UINT64_T __pyx_dict_version = 0;\
static PyObject *__pyx_dict_cached_value = NULL;\
(var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\
(likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\
__Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\
}
#define __Pyx_GetModuleGlobalNameUncached(var, name) {\
PY_UINT64_T __pyx_dict_version;\
PyObject *__pyx_dict_cached_value;\
(var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\
}
static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value);
#else
#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name)
#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name)
static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name);
#endif
/* PyCFunctionFastCall.proto */
#if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs);
#else
#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL)
#endif
/* PyFunctionFastCall.proto */
#if CYTHON_FAST_PYCALL
#define __Pyx_PyFunction_FastCall(func, args, nargs)\
__Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL)
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs);
#else
#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs)
#endif
#define __Pyx_BUILD_ASSERT_EXPR(cond)\
(sizeof(char [1 - 2*!(cond)]) - 1)
#ifndef Py_MEMBER_SIZE
#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member)
#endif
static size_t __pyx_pyframe_localsplus_offset = 0;
#include "frameobject.h"
#define __Pxy_PyFrame_Initialize_Offsets()\
((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\
(void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus)))
#define __Pyx_PyFrame_GetLocalsplus(frame)\
(assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset))
#endif
/* PyObjectCall2Args.proto */
static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2);
/* PyObjectCallMethO.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
#endif
/* PyObjectCallOneArg.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
/* PyErrFetchRestore.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL)
#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#if CYTHON_COMPILING_IN_CPYTHON
#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL))
#else
#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc)
#endif
#else
#define __Pyx_PyErr_Clear() PyErr_Clear()
#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc)
#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb)
#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb)
#endif
/* RaiseException.proto */
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
/* PyFloatBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_EqObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyFloat_EqObjC(op1, op2, floatval, inplace, zerodivision_check)\
(PyObject_RichCompare(op1, op2, Py_EQ))
#endif
/* PyObjectCallNoArg.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
#else
#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL)
#endif
/* None.proto */
static CYTHON_INLINE void __Pyx_RaiseClosureNameError(const char *varname);
/* FetchCommonType.proto */
static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type);
/* CythonFunctionShared.proto */
#define __Pyx_CyFunction_USED 1
#define __Pyx_CYFUNCTION_STATICMETHOD 0x01
#define __Pyx_CYFUNCTION_CLASSMETHOD 0x02
#define __Pyx_CYFUNCTION_CCLASS 0x04
#define __Pyx_CyFunction_GetClosure(f)\
(((__pyx_CyFunctionObject *) (f))->func_closure)
#define __Pyx_CyFunction_GetClassObj(f)\
(((__pyx_CyFunctionObject *) (f))->func_classobj)
#define __Pyx_CyFunction_Defaults(type, f)\
((type *)(((__pyx_CyFunctionObject *) (f))->defaults))
#define __Pyx_CyFunction_SetDefaultsGetter(f, g)\
((__pyx_CyFunctionObject *) (f))->defaults_getter = (g)
typedef struct {
PyCFunctionObject func;
#if PY_VERSION_HEX < 0x030500A0
PyObject *func_weakreflist;
#endif
PyObject *func_dict;
PyObject *func_name;
PyObject *func_qualname;
PyObject *func_doc;
PyObject *func_globals;
PyObject *func_code;
PyObject *func_closure;
PyObject *func_classobj;
void *defaults;
int defaults_pyobjects;
size_t defaults_size; // used by FusedFunction for copying defaults
int flags;
PyObject *defaults_tuple;
PyObject *defaults_kwdict;
PyObject *(*defaults_getter)(PyObject *);
PyObject *func_annotations;
} __pyx_CyFunctionObject;
static PyTypeObject *__pyx_CyFunctionType = 0;
#define __Pyx_CyFunction_Check(obj) (__Pyx_TypeCheck(obj, __pyx_CyFunctionType))
static PyObject *__Pyx_CyFunction_Init(__pyx_CyFunctionObject* op, PyMethodDef *ml,
int flags, PyObject* qualname,
PyObject *self,
PyObject *module, PyObject *globals,
PyObject* code);
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *m,
size_t size,
int pyobjects);
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *m,
PyObject *tuple);
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *m,
PyObject *dict);
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *m,
PyObject *dict);
static int __pyx_CyFunction_init(void);
/* CythonFunction.proto */
static PyObject *__Pyx_CyFunction_New(PyMethodDef *ml,
int flags, PyObject* qualname,
PyObject *closure,
PyObject *module, PyObject *globals,
PyObject* code);
/* PyObjectSetAttrStr.proto */
#if CYTHON_USE_TYPE_SLOTS
#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_SetAttrStr(o, n, NULL)
static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value);
#else
#define __Pyx_PyObject_DelAttrStr(o,n) PyObject_DelAttr(o,n)
#define __Pyx_PyObject_SetAttrStr(o,n,v) PyObject_SetAttr(o,n,v)
#endif
/* GetItemInt.proto */
#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\
(is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\
__Pyx_GetItemInt_Generic(o, to_py_func(i))))
#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
int is_list, int wraparound, int boundscheck);
/* ObjectGetItem.proto */
#if CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key);
#else
#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key)
#endif
/* ListCompAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len)) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
__Pyx_SET_SIZE(list, len + 1);
return 0;
}
return PyList_Append(list, x);
}
#else
#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
#endif
/* IterFinish.proto */
static CYTHON_INLINE int __Pyx_IterFinish(void);
/* PyObjectGetMethod.proto */
static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method);
/* PyObjectCallMethod0.proto */
static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name);
/* RaiseNeedMoreValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
/* RaiseTooManyValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
/* UnpackItemEndCheck.proto */
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected);
/* RaiseNoneIterError.proto */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
/* UnpackTupleError.proto */
static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index);
/* UnpackTuple2.proto */
#define __Pyx_unpack_tuple2(tuple, value1, value2, is_tuple, has_known_size, decref_tuple)\
(likely(is_tuple || PyTuple_Check(tuple)) ?\
(likely(has_known_size || PyTuple_GET_SIZE(tuple) == 2) ?\
__Pyx_unpack_tuple2_exact(tuple, value1, value2, decref_tuple) :\
(__Pyx_UnpackTupleError(tuple, 2), -1)) :\
__Pyx_unpack_tuple2_generic(tuple, value1, value2, has_known_size, decref_tuple))
static CYTHON_INLINE int __Pyx_unpack_tuple2_exact(
PyObject* tuple, PyObject** value1, PyObject** value2, int decref_tuple);
static int __Pyx_unpack_tuple2_generic(
PyObject* tuple, PyObject** value1, PyObject** value2, int has_known_size, int decref_tuple);
/* dict_iter.proto */
static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* dict, int is_dict, PyObject* method_name,
Py_ssize_t* p_orig_length, int* p_is_dict);
static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos,
PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict);
/* IterNext.proto */
#define __Pyx_PyIter_Next(obj) __Pyx_PyIter_Next2(obj, NULL)
static CYTHON_INLINE PyObject *__Pyx_PyIter_Next2(PyObject *, PyObject *);
/* py_abs.proto */
#if CYTHON_USE_PYLONG_INTERNALS
static PyObject *__Pyx_PyLong_AbsNeg(PyObject *num);
#define __Pyx_PyNumber_Absolute(x)\
((likely(PyLong_CheckExact(x))) ?\
(likely(Py_SIZE(x) >= 0) ? (Py_INCREF(x), (x)) : __Pyx_PyLong_AbsNeg(x)) :\
PyNumber_Absolute(x))
#else
#define __Pyx_PyNumber_Absolute(x) PyNumber_Absolute(x)
#endif
/* dict_getitem_default.proto */
static PyObject* __Pyx_PyDict_GetItemDefault(PyObject* d, PyObject* key, PyObject* default_value);
/* UnpackUnboundCMethod.proto */
typedef struct {
PyObject *type;
PyObject **method_name;
PyCFunction func;
PyObject *method;
int flag;
} __Pyx_CachedCFunction;
/* CallUnboundCMethod1.proto */
static PyObject* __Pyx__CallUnboundCMethod1(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg);
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_CallUnboundCMethod1(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg);
#else
#define __Pyx_CallUnboundCMethod1(cfunc, self, arg) __Pyx__CallUnboundCMethod1(cfunc, self, arg)
#endif
/* CallUnboundCMethod2.proto */
static PyObject* __Pyx__CallUnboundCMethod2(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg1, PyObject* arg2);
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030600B1
static CYTHON_INLINE PyObject *__Pyx_CallUnboundCMethod2(__Pyx_CachedCFunction *cfunc, PyObject *self, PyObject *arg1, PyObject *arg2);
#else
#define __Pyx_CallUnboundCMethod2(cfunc, self, arg1, arg2) __Pyx__CallUnboundCMethod2(cfunc, self, arg1, arg2)
#endif
/* PyFloatBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_NeObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyFloat_NeObjC(op1, op2, floatval, inplace, zerodivision_check)\
(PyObject_RichCompare(op1, op2, Py_NE))
#endif
/* GetAttr.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
/* GetAttr3.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *);
/* PyObjectFormatAndDecref.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatSimpleAndDecref(PyObject* s, PyObject* f);
static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatAndDecref(PyObject* s, PyObject* f);
/* IncludeStringH.proto */
#include <string.h>
/* JoinPyUnicode.proto */
static PyObject* __Pyx_PyUnicode_Join(PyObject* value_tuple, Py_ssize_t value_count, Py_ssize_t result_ulength,
Py_UCS4 max_char);
/* KeywordStringCheck.proto */
static int __Pyx_CheckKeywordStrings(PyObject *kwdict, const char* function_name, int kw_allowed);
/* ListAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
__Pyx_SET_SIZE(list, len + 1);
return 0;
}
return PyList_Append(list, x);
}
#else
#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
#endif
/* PyObjectCallMethod1.proto */
static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg);
/* append.proto */
static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x);
/* BytesEquals.proto */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
/* UnicodeEquals.proto */
static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
/* WriteUnraisableException.proto */
static void __Pyx_WriteUnraisable(const char *name, int clineno,
int lineno, const char *filename,
int full_traceback, int nogil);
/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\
(inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2))
#endif
/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyInt_SubtractObjC(op1, op2, intval, inplace, zerodivision_check)\
(inplace ? PyNumber_InPlaceSubtract(op1, op2) : PyNumber_Subtract(op1, op2))
#endif
/* ExtTypeTest.proto */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
/* PySequenceContains.proto */
static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) {
int result = PySequence_Contains(seq, item);
return unlikely(result < 0) ? result : (result == (eq == Py_EQ));
}
/* DictGetItem.proto */
#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY
static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key);
#define __Pyx_PyObject_Dict_GetItem(obj, name)\
(likely(PyDict_CheckExact(obj)) ?\
__Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name))
#else
#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key)
#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name)
#endif
/* decode_c_string_utf16.proto */
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) {
int byteorder = 0;
return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) {
int byteorder = -1;
return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) {
int byteorder = 1;
return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}
/* decode_c_bytes.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_c_bytes(
const char* cstring, Py_ssize_t length, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
/* decode_bytes.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_bytes(
PyObject* string, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
return __Pyx_decode_c_bytes(
PyBytes_AS_STRING(string), PyBytes_GET_SIZE(string),
start, stop, encoding, errors, decode_func);
}
/* decode_c_string.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
/* ArgTypeTest.proto */
#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\
((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\
__Pyx__ArgTypeTest(obj, type, name, exact))
static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact);
/* PyFloatBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_TrueDivideObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyFloat_TrueDivideObjC(op1, op2, floatval, inplace, zerodivision_check)\
(inplace ? PyNumber_InPlaceTrueDivide(op1, op2) : PyNumber_TrueDivide(op1, op2))
#endif
/* PyIntCompare.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, long intval, long inplace);
/* SliceObject.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(
PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop,
PyObject** py_start, PyObject** py_stop, PyObject** py_slice,
int has_cstart, int has_cstop, int wraparound);
/* UnicodeAsUCS4.proto */
static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject*);
/* object_ord.proto */
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyObject_Ord(c)\
(likely(PyUnicode_Check(c)) ? (long)__Pyx_PyUnicode_AsPy_UCS4(c) : __Pyx__PyObject_Ord(c))
#else
#define __Pyx_PyObject_Ord(c) __Pyx__PyObject_Ord(c)
#endif
static long __Pyx__PyObject_Ord(PyObject* c);
/* PyObjectLookupSpecial.proto */
#if CYTHON_USE_PYTYPE_LOOKUP && CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE PyObject* __Pyx_PyObject_LookupSpecial(PyObject* obj, PyObject* attr_name) {
PyObject *res;
PyTypeObject *tp = Py_TYPE(obj);
#if PY_MAJOR_VERSION < 3
if (unlikely(PyInstance_Check(obj)))
return __Pyx_PyObject_GetAttrStr(obj, attr_name);
#endif
res = _PyType_Lookup(tp, attr_name);
if (likely(res)) {
descrgetfunc f = Py_TYPE(res)->tp_descr_get;
if (!f) {
Py_INCREF(res);
} else {
res = f(res, obj, (PyObject *)tp);
}
} else {
PyErr_SetObject(PyExc_AttributeError, attr_name);
}
return res;
}
#else
#define __Pyx_PyObject_LookupSpecial(o,n) __Pyx_PyObject_GetAttrStr(o,n)
#endif
/* IsLittleEndian.proto */
static CYTHON_INLINE int __Pyx_Is_Little_Endian(void);
/* BufferFormatCheck.proto */
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts);
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type);
/* BufferGetAndValidate.proto */
#define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\
((obj == Py_None || obj == NULL) ?\
(__Pyx_ZeroBuffer(buf), 0) :\
__Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack))
static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
__Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static void __Pyx_ZeroBuffer(Py_buffer* buf);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 };
static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 };
/* BufferFallbackError.proto */
static void __Pyx_RaiseBufferFallbackError(void);
/* BufferIndexError.proto */
static void __Pyx_RaiseBufferIndexError(int axis);
#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0)
/* SetItemInt.proto */
#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) :\
(is_list ? (PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) :\
__Pyx_SetItemInt_Generic(o, to_py_func(i), v)))
static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v);
static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v,
int is_list, int wraparound, int boundscheck);
#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1)
/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractCObj(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check);
#else
#define __Pyx_PyInt_SubtractCObj(op1, op2, intval, inplace, zerodivision_check)\
(inplace ? PyNumber_InPlaceSubtract(op1, op2) : PyNumber_Subtract(op1, op2))
#endif
/* Import.proto */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
/* ImportFrom.proto */
static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);
/* HasAttr.proto */
static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *);
/* PyObject_GenericGetAttrNoDict.proto */
#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name);
#else
#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr
#endif
/* PyObject_GenericGetAttr.proto */
#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name);
#else
#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr
#endif
/* PyObjectGetAttrStrNoError.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name);
/* SetupReduce.proto */
static int __Pyx_setup_reduce(PyObject* type_obj);
/* SetVTable.proto */
static int __Pyx_SetVtable(PyObject *dict, void *vtable);
/* TypeImport.proto */
#ifndef __PYX_HAVE_RT_ImportType_proto
#define __PYX_HAVE_RT_ImportType_proto
enum __Pyx_ImportType_CheckSize {
__Pyx_ImportType_CheckSize_Error = 0,
__Pyx_ImportType_CheckSize_Warn = 1,
__Pyx_ImportType_CheckSize_Ignore = 2
};
static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size);
#endif
/* SetNameInClass.proto */
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1
#define __Pyx_SetNameInClass(ns, name, value)\
(likely(PyDict_CheckExact(ns)) ? _PyDict_SetItem_KnownHash(ns, name, value, ((PyASCIIObject *) name)->hash) : PyObject_SetItem(ns, name, value))
#elif CYTHON_COMPILING_IN_CPYTHON
#define __Pyx_SetNameInClass(ns, name, value)\
(likely(PyDict_CheckExact(ns)) ? PyDict_SetItem(ns, name, value) : PyObject_SetItem(ns, name, value))
#else
#define __Pyx_SetNameInClass(ns, name, value) PyObject_SetItem(ns, name, value)
#endif
/* CalculateMetaclass.proto */
static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases);
/* Py3ClassCreate.proto */
static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, PyObject *qualname,
PyObject *mkw, PyObject *modname, PyObject *doc);
static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, PyObject *dict,
PyObject *mkw, int calculate_metaclass, int allow_py2_metaclass);
/* CLineInTraceback.proto */
#ifdef CYTHON_CLINE_IN_TRACEBACK
#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0)
#else
static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line);
#endif
/* CodeObjectCache.proto */
typedef struct {
PyCodeObject* code_object;
int code_line;
} __Pyx_CodeObjectCacheEntry;
struct __Pyx_CodeObjectCache {
int count;
int max_count;
__Pyx_CodeObjectCacheEntry* entries;
};
static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
/* AddTraceback.proto */
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename);
/* BufferStructDeclare.proto */
typedef struct {
Py_ssize_t shape, strides, suboffsets;
} __Pyx_Buf_DimInfo;
typedef struct {
size_t refcount;
Py_buffer pybuffer;
} __Pyx_Buffer;
typedef struct {
__Pyx_Buffer *rcbuffer;
char *data;
__Pyx_Buf_DimInfo diminfo[8];
} __Pyx_LocalBuf_ND;
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
static void __Pyx_ReleaseBuffer(Py_buffer *view);
#else
#define __Pyx_GetBuffer PyObject_GetBuffer
#define __Pyx_ReleaseBuffer PyBuffer_Release
#endif
/* GCCDiagnostics.proto */
#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6))
#define __Pyx_HAS_GCC_DIAGNOSTIC
#endif
/* RealImag.proto */
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
#define __Pyx_CREAL(z) ((z).real())
#define __Pyx_CIMAG(z) ((z).imag())
#else
#define __Pyx_CREAL(z) (__real__(z))
#define __Pyx_CIMAG(z) (__imag__(z))
#endif
#else
#define __Pyx_CREAL(z) ((z).real)
#define __Pyx_CIMAG(z) ((z).imag)
#endif
#if defined(__cplusplus) && CYTHON_CCOMPLEX\
&& (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103)
#define __Pyx_SET_CREAL(z,x) ((z).real(x))
#define __Pyx_SET_CIMAG(z,y) ((z).imag(y))
#else
#define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x)
#define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y)
#endif
/* Arithmetic.proto */
#if CYTHON_CCOMPLEX
#define __Pyx_c_eq_float(a, b) ((a)==(b))
#define __Pyx_c_sum_float(a, b) ((a)+(b))
#define __Pyx_c_diff_float(a, b) ((a)-(b))
#define __Pyx_c_prod_float(a, b) ((a)*(b))
#define __Pyx_c_quot_float(a, b) ((a)/(b))
#define __Pyx_c_neg_float(a) (-(a))
#ifdef __cplusplus
#define __Pyx_c_is_zero_float(z) ((z)==(float)0)
#define __Pyx_c_conj_float(z) (::std::conj(z))
#if 1
#define __Pyx_c_abs_float(z) (::std::abs(z))
#define __Pyx_c_pow_float(a, b) (::std::pow(a, b))
#endif
#else
#define __Pyx_c_is_zero_float(z) ((z)==0)
#define __Pyx_c_conj_float(z) (conjf(z))
#if 1
#define __Pyx_c_abs_float(z) (cabsf(z))
#define __Pyx_c_pow_float(a, b) (cpowf(a, b))
#endif
#endif
#else
static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex);
static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex);
#if 1
static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex);
#endif
#endif
/* Arithmetic.proto */
#if CYTHON_CCOMPLEX
#define __Pyx_c_eq_double(a, b) ((a)==(b))
#define __Pyx_c_sum_double(a, b) ((a)+(b))
#define __Pyx_c_diff_double(a, b) ((a)-(b))
#define __Pyx_c_prod_double(a, b) ((a)*(b))
#define __Pyx_c_quot_double(a, b) ((a)/(b))
#define __Pyx_c_neg_double(a) (-(a))
#ifdef __cplusplus
#define __Pyx_c_is_zero_double(z) ((z)==(double)0)
#define __Pyx_c_conj_double(z) (::std::conj(z))
#if 1
#define __Pyx_c_abs_double(z) (::std::abs(z))
#define __Pyx_c_pow_double(a, b) (::std::pow(a, b))
#endif
#else
#define __Pyx_c_is_zero_double(z) ((z)==0)
#define __Pyx_c_conj_double(z) (conj(z))
#if 1
#define __Pyx_c_abs_double(z) (cabs(z))
#define __Pyx_c_pow_double(a, b) (cpow(a, b))
#endif
#endif
#else
static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex);
static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex);
#if 1
static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex);
#endif
#endif
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_EXPROP(SCIP_EXPROP value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_RESULT(SCIP_RESULT value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PARAMSETTING(SCIP_PARAMSETTING value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PARAMEMPHASIS(SCIP_PARAMEMPHASIS value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_STATUS(SCIP_STATUS value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_STAGE(SCIP_STAGE value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_NODETYPE(SCIP_NODETYPE value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PROPTIMING(SCIP_PROPTIMING value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PRESOLTIMING(SCIP_PRESOLTIMING value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_HEURTIMING(SCIP_HEURTIMING value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_EVENTTYPE(SCIP_EVENTTYPE value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_LPSOLSTAT(SCIP_LPSOLSTAT value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BRANCHDIR(SCIP_BRANCHDIR value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BENDERSENFOTYPE(SCIP_BENDERSENFOTYPE value);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_RETCODE __Pyx_PyInt_As_SCIP_RETCODE(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_RETCODE(SCIP_RETCODE value);
/* CIntFromPy.proto */
static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_RESULT __Pyx_PyInt_As_SCIP_RESULT(PyObject *);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_LOCKTYPE(SCIP_LOCKTYPE value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BOUNDTYPE(SCIP_BOUNDTYPE value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_Longint(SCIP_Longint value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BOUNDCHGTYPE(SCIP_BOUNDCHGTYPE value);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_PARAMSETTING __Pyx_PyInt_As_SCIP_PARAMSETTING(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_EXPROP __Pyx_PyInt_As_SCIP_EXPROP(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_BENDERSENFOTYPE __Pyx_PyInt_As_SCIP_BENDERSENFOTYPE(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_PROPTIMING __Pyx_PyInt_As_SCIP_PROPTIMING(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_PRESOLTIMING __Pyx_PyInt_As_SCIP_PRESOLTIMING(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_BRANCHDIR __Pyx_PyInt_As_SCIP_BRANCHDIR(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_EVENTTYPE __Pyx_PyInt_As_SCIP_EVENTTYPE(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_Longint __Pyx_PyInt_As_SCIP_Longint(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_char(char value);
/* CIntFromPy.proto */
static CYTHON_INLINE SCIP_PARAMEMPHASIS __Pyx_PyInt_As_SCIP_PARAMEMPHASIS(PyObject *);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value);
/* CIntFromPy.proto */
static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *);
/* FastTypeChecks.proto */
#if CYTHON_COMPILING_IN_CPYTHON
#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type)
static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b);
static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type);
static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2);
#else
#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type)
#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2))
#endif
#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception)
/* SwapException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
#endif
/* CoroutineBase.proto */
typedef PyObject *(*__pyx_coroutine_body_t)(PyObject *, PyThreadState *, PyObject *);
#if CYTHON_USE_EXC_INFO_STACK
#define __Pyx_ExcInfoStruct _PyErr_StackItem
#else
typedef struct {
PyObject *exc_type;
PyObject *exc_value;
PyObject *exc_traceback;
} __Pyx_ExcInfoStruct;
#endif
typedef struct {
PyObject_HEAD
__pyx_coroutine_body_t body;
PyObject *closure;
__Pyx_ExcInfoStruct gi_exc_state;
PyObject *gi_weakreflist;
PyObject *classobj;
PyObject *yieldfrom;
PyObject *gi_name;
PyObject *gi_qualname;
PyObject *gi_modulename;
PyObject *gi_code;
PyObject *gi_frame;
int resume_label;
char is_running;
} __pyx_CoroutineObject;
static __pyx_CoroutineObject *__Pyx__Coroutine_New(
PyTypeObject *type, __pyx_coroutine_body_t body, PyObject *code, PyObject *closure,
PyObject *name, PyObject *qualname, PyObject *module_name);
static __pyx_CoroutineObject *__Pyx__Coroutine_NewInit(
__pyx_CoroutineObject *gen, __pyx_coroutine_body_t body, PyObject *code, PyObject *closure,
PyObject *name, PyObject *qualname, PyObject *module_name);
static CYTHON_INLINE void __Pyx_Coroutine_ExceptionClear(__Pyx_ExcInfoStruct *self);
static int __Pyx_Coroutine_clear(PyObject *self);
static PyObject *__Pyx_Coroutine_Send(PyObject *self, PyObject *value);
static PyObject *__Pyx_Coroutine_Close(PyObject *self);
static PyObject *__Pyx_Coroutine_Throw(PyObject *gen, PyObject *args);
#if CYTHON_USE_EXC_INFO_STACK
#define __Pyx_Coroutine_SwapException(self)
#define __Pyx_Coroutine_ResetAndClearException(self) __Pyx_Coroutine_ExceptionClear(&(self)->gi_exc_state)
#else
#define __Pyx_Coroutine_SwapException(self) {\
__Pyx_ExceptionSwap(&(self)->gi_exc_state.exc_type, &(self)->gi_exc_state.exc_value, &(self)->gi_exc_state.exc_traceback);\
__Pyx_Coroutine_ResetFrameBackpointer(&(self)->gi_exc_state);\
}
#define __Pyx_Coroutine_ResetAndClearException(self) {\
__Pyx_ExceptionReset((self)->gi_exc_state.exc_type, (self)->gi_exc_state.exc_value, (self)->gi_exc_state.exc_traceback);\
(self)->gi_exc_state.exc_type = (self)->gi_exc_state.exc_value = (self)->gi_exc_state.exc_traceback = NULL;\
}
#endif
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyGen_FetchStopIterationValue(pvalue)\
__Pyx_PyGen__FetchStopIterationValue(__pyx_tstate, pvalue)
#else
#define __Pyx_PyGen_FetchStopIterationValue(pvalue)\
__Pyx_PyGen__FetchStopIterationValue(__Pyx_PyThreadState_Current, pvalue)
#endif
static int __Pyx_PyGen__FetchStopIterationValue(PyThreadState *tstate, PyObject **pvalue);
static CYTHON_INLINE void __Pyx_Coroutine_ResetFrameBackpointer(__Pyx_ExcInfoStruct *exc_state);
/* PatchModuleWithCoroutine.proto */
static PyObject* __Pyx_Coroutine_patch_module(PyObject* module, const char* py_code);
/* PatchGeneratorABC.proto */
static int __Pyx_patch_abc(void);
/* Generator.proto */
#define __Pyx_Generator_USED
static PyTypeObject *__pyx_GeneratorType = 0;
#define __Pyx_Generator_CheckExact(obj) (Py_TYPE(obj) == __pyx_GeneratorType)
#define __Pyx_Generator_New(body, code, closure, name, qualname, module_name)\
__Pyx__Coroutine_New(__pyx_GeneratorType, body, code, closure, name, qualname, module_name)
static PyObject *__Pyx_Generator_Next(PyObject *self);
static int __pyx_Generator_init(void);
/* CheckBinaryVersion.proto */
static int __Pyx_check_binary_version(void);
/* InitStrings.proto */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
static PyObject *__pyx_f_9pyscipopt_4scip_5Event_create(SCIP_EVENT *__pyx_v_scip_event); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_6Column_create(SCIP_COL *__pyx_v_scipcol); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_3Row_create(SCIP_ROW *__pyx_v_sciprow); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_8Solution_create(SCIP_SOL *__pyx_v_scip_sol); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_4Node_create(SCIP_NODE *__pyx_v_scipnode); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_8Variable_create(SCIP_VAR *__pyx_v_scipvar); /* proto*/
static PyObject *__pyx_f_9pyscipopt_4scip_10Constraint_create(SCIP_CONS *__pyx_v_scipcons); /* proto*/
/* Module declarations from 'cpython.buffer' */
/* Module declarations from 'libc.string' */
/* Module declarations from 'libc.stdio' */
/* Module declarations from '__builtin__' */
/* Module declarations from 'cpython.type' */
static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0;
/* Module declarations from 'cpython.version' */
/* Module declarations from 'cpython.exc' */
/* Module declarations from 'cpython.module' */
/* Module declarations from 'cpython.mem' */
/* Module declarations from 'cpython.tuple' */
/* Module declarations from 'cpython.list' */
/* Module declarations from 'cpython.sequence' */
/* Module declarations from 'cpython.mapping' */
/* Module declarations from 'cpython.iterator' */
/* Module declarations from 'cpython.number' */
/* Module declarations from 'cpython.int' */
/* Module declarations from '__builtin__' */
/* Module declarations from 'cpython.bool' */
static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0;
/* Module declarations from 'cpython.long' */
/* Module declarations from 'cpython.float' */
/* Module declarations from '__builtin__' */
/* Module declarations from 'cpython.complex' */
static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0;
/* Module declarations from 'cpython.string' */
/* Module declarations from 'cpython.unicode' */
/* Module declarations from 'cpython.dict' */
/* Module declarations from 'cpython.instance' */
/* Module declarations from 'cpython.function' */
/* Module declarations from 'cpython.method' */
/* Module declarations from 'cpython.weakref' */
/* Module declarations from 'cpython.getargs' */
/* Module declarations from 'cpython.pythread' */
/* Module declarations from 'cpython.pystate' */
/* Module declarations from 'cpython.cobject' */
/* Module declarations from 'cpython.oldbuffer' */
/* Module declarations from 'cpython.set' */
/* Module declarations from 'cpython.bytes' */
/* Module declarations from 'cpython.pycapsule' */
/* Module declarations from 'cpython' */
/* Module declarations from 'cpython.object' */
/* Module declarations from 'cpython.ref' */
/* Module declarations from 'numpy' */
/* Module declarations from 'numpy' */
static PyTypeObject *__pyx_ptype_5numpy_dtype = 0;
static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0;
static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0;
static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0;
static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0;
/* Module declarations from 'libc.stdlib' */
/* Module declarations from 'numpy.math' */
/* Module declarations from 'libc.math' */
/* Module declarations from 'pyscipopt.scip' */
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Expr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_ExprCons = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_GenExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_SumExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_ProdExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_VarExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PowExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_UnaryExpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Constant = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_LP = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Benders = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Benderscut = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Branchrule = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Conshdlr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Eventhdlr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Heur = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Presol = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Pricer = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Prop = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Sepa = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Relax = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Nodesel = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_RESULT = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_PARAMSETTING = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_STATUS = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_STAGE = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_NODETYPE = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_PROPTIMING = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_HEURTIMING = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_EVENTTYPE = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_BRANCHDIR = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Event = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Column = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Row = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Solution = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Node = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Variable = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Constraint = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip_Model = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct____init__ = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_1_genexpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_2_degree = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_3_genexpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_4_addCols = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_5_genexpr = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_6_addRows = 0;
static PyTypeObject *__pyx_ptype_9pyscipopt_4scip___pyx_scope_struct_7_genexpr = 0;
static struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_f_9pyscipopt_4scip_getPyVar(SCIP_VAR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersCopy(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersFree(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersInit(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersExit(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersInitpre(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersExitpre(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersInitsol(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersExitsol(SCIP *, SCIP_BENDERS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersCreatesub(SCIP *, SCIP_BENDERS *, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersPresubsolve(SCIP *, SCIP_BENDERS *, SCIP_SOL *, SCIP_BENDERSENFOTYPE, SCIP_Bool, SCIP_Bool *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersSolvesubconvex(SCIP *, SCIP_BENDERS *, SCIP_SOL *, int, SCIP_Bool, SCIP_Real *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersSolvesub(SCIP *, SCIP_BENDERS *, SCIP_SOL *, int, SCIP_Real *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersPostsolve(SCIP *, SCIP_BENDERS *, SCIP_SOL *, SCIP_BENDERSENFOTYPE, int *, int, int, SCIP_Bool, SCIP_Bool, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersFreesub(SCIP *, SCIP_BENDERS *, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBendersGetvar(SCIP *, SCIP_BENDERS *, SCIP_VAR *, SCIP_VAR **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutCopy(SCIP *, SCIP_BENDERS *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutFree(SCIP *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutInit(SCIP *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutExit(SCIP *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutInitsol(SCIP *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutExitsol(SCIP *, SCIP_BENDERSCUT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBenderscutExec(SCIP *, SCIP_BENDERS *, SCIP_BENDERSCUT *, SCIP_SOL *, int, SCIP_BENDERSENFOTYPE, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleCopy(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleFree(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleInit(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleExit(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleInitsol(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleExitsol(SCIP *, SCIP_BRANCHRULE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleExeclp(SCIP *, SCIP_BRANCHRULE *, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleExecext(SCIP *, SCIP_BRANCHRULE *, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyBranchruleExecps(SCIP *, SCIP_BRANCHRULE *, SCIP_Bool, SCIP_RESULT *); /*proto*/
static struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_f_9pyscipopt_4scip_getPyConshdlr(SCIP_CONSHDLR *); /*proto*/
static struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_f_9pyscipopt_4scip_getPyCons(SCIP_CONS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConshdlrCopy(SCIP *, SCIP_CONSHDLR *, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsFree(SCIP *, SCIP_CONSHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsInit(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsExit(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsInitpre(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsExitpre(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsInitsol(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsExitsol(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, SCIP_Bool); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsDelete(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_CONSDATA **); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsTrans(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_CONS **); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsInitlp(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsSepalp(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsSepasol(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_SOL *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsEnfolp(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsEnforelax(SCIP *, SCIP_SOL *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsEnfops(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_Bool, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsCheck(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, SCIP_SOL *, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsProp(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, int, SCIP_PROPTIMING, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsPresol(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int, int, SCIP_PRESOLTIMING, int, int, int, int, int, int, int, int, int, int, int *, int *, int *, int *, int *, int *, int *, int *, int *, int *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsResprop(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_VAR *, int, SCIP_BOUNDTYPE, SCIP_BDCHGIDX *, SCIP_Real, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsLock(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_LOCKTYPE, int, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsActive(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsDeactive(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsEnable(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsDisable(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsDelvars(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsPrint(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, FILE *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsCopy(SCIP *, SCIP_CONS **, char const *, SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_HASHMAP *, SCIP_HASHMAP *, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsParse(SCIP *, SCIP_CONSHDLR *, SCIP_CONS **, char const *, char const *, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsGetvars(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, SCIP_VAR **, int, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsGetnvars(SCIP *, SCIP_CONSHDLR *, SCIP_CONS *, int *, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyConsGetdivebdchgs(SCIP *, SCIP_CONSHDLR *, SCIP_DIVESET *, SCIP_SOL *, SCIP_Bool *, SCIP_Bool *); /*proto*/
static struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_f_9pyscipopt_4scip_getPyEventhdlr(SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventCopy(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventFree(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventInit(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventExit(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventInitsol(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventExitsol(SCIP *, SCIP_EVENTHDLR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventDelete(SCIP *, SCIP_EVENTHDLR *, SCIP_EVENTDATA **); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyEventExec(SCIP *, SCIP_EVENTHDLR *, SCIP_EVENT *, SCIP_EVENTDATA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurCopy(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurFree(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurInit(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurExit(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurInitsol(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurExitsol(SCIP *, SCIP_HEUR *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyHeurExec(SCIP *, SCIP_HEUR *, SCIP_HEURTIMING, SCIP_Bool, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolCopy(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolFree(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolInit(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolExit(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolInitpre(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolExitpre(SCIP *, SCIP_PRESOL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPresolExec(SCIP *, SCIP_PRESOL *, int, SCIP_PRESOLTIMING, int, int, int, int, int, int, int, int, int, int, int *, int *, int *, int *, int *, int *, int *, int *, int *, int *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerCopy(SCIP *, SCIP_PRICER *, SCIP_Bool *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerFree(SCIP *, SCIP_PRICER *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerInit(SCIP *, SCIP_PRICER *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerExit(SCIP *, SCIP_PRICER *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerInitsol(SCIP *, SCIP_PRICER *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerExitsol(SCIP *, SCIP_PRICER *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerRedcost(SCIP *, SCIP_PRICER *, SCIP_Real *, SCIP_Bool *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPricerFarkas(SCIP *, SCIP_PRICER *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropCopy(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropFree(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropInit(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropExit(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropInitpre(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropExitpre(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropInitsol(SCIP *, SCIP_PROP *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropExitsol(SCIP *, SCIP_PROP *, SCIP_Bool); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropPresol(SCIP *, SCIP_PROP *, int, SCIP_PRESOLTIMING, int, int, int, int, int, int, int, int, int, int, int *, int *, int *, int *, int *, int *, int *, int *, int *, int *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropExec(SCIP *, SCIP_PROP *, SCIP_PROPTIMING, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyPropResProp(SCIP *, SCIP_PROP *, SCIP_VAR *, int, SCIP_BOUNDTYPE, SCIP_BDCHGIDX *, SCIP_Real, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaCopy(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaFree(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaInit(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaExit(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaInitsol(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaExitsol(SCIP *, SCIP_SEPA *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaExeclp(SCIP *, SCIP_SEPA *, SCIP_RESULT *, unsigned int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PySepaExecsol(SCIP *, SCIP_SEPA *, SCIP_SOL *, SCIP_RESULT *, unsigned int); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxCopy(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxFree(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxInit(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxExit(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxInitsol(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxExitsol(SCIP *, SCIP_RELAX *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyRelaxExec(SCIP *, SCIP_RELAX *, SCIP_Real *, SCIP_RESULT *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselCopy(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselFree(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselInit(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselExit(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselInitsol(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselExitsol(SCIP *, SCIP_NODESEL *); /*proto*/
static SCIP_RETCODE __pyx_f_9pyscipopt_4scip_PyNodeselSelect(SCIP *, SCIP_NODESEL *, SCIP_NODE **); /*proto*/
static int __pyx_f_9pyscipopt_4scip_PyNodeselComp(SCIP *, SCIP_NODESEL *, SCIP_NODE *, SCIP_NODE *); /*proto*/
static void __pyx_f_9pyscipopt_4scip_relayMessage(SCIP_MESSAGEHDLR *, FILE *, char const *); /*proto*/
static void __pyx_f_9pyscipopt_4scip_relayErrorMessage(void *, FILE *, char const *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Expr__set_state(struct __pyx_obj_9pyscipopt_4scip_Expr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_ExprCons__set_state(struct __pyx_obj_9pyscipopt_4scip_ExprCons *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_GenExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_GenExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_SumExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_SumExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_ProdExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_VarExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_VarExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PowExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_PowExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_UnaryExpr__set_state(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Constant__set_state(struct __pyx_obj_9pyscipopt_4scip_Constant *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Benders__set_state(struct __pyx_obj_9pyscipopt_4scip_Benders *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Benderscut__set_state(struct __pyx_obj_9pyscipopt_4scip_Benderscut *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Branchrule__set_state(struct __pyx_obj_9pyscipopt_4scip_Branchrule *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Conshdlr__set_state(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Eventhdlr__set_state(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Heur__set_state(struct __pyx_obj_9pyscipopt_4scip_Heur *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Presol__set_state(struct __pyx_obj_9pyscipopt_4scip_Presol *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Pricer__set_state(struct __pyx_obj_9pyscipopt_4scip_Pricer *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Prop__set_state(struct __pyx_obj_9pyscipopt_4scip_Prop *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Sepa__set_state(struct __pyx_obj_9pyscipopt_4scip_Sepa *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Relax__set_state(struct __pyx_obj_9pyscipopt_4scip_Relax *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_Nodesel__set_state(struct __pyx_obj_9pyscipopt_4scip_Nodesel *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_RESULT__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_PARAMSETTING__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_PARAMEMPHASIS__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_STATUS__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_STAGE__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_NODETYPE__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_PROPTIMING__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_PRESOLTIMING__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_HEURTIMING__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_EVENTTYPE__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_LPSOLSTAT__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_BRANCHDIR__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR *, PyObject *); /*proto*/
static PyObject *__pyx_f_9pyscipopt_4scip___pyx_unpickle_PY_SCIP_BENDERSENFOTYPE__set_state(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE *, PyObject *); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_int32_t = { "int32_t", NULL, sizeof(__pyx_t_5numpy_int32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5numpy_int32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5numpy_int32_t), 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t = { "float32_t", NULL, sizeof(__pyx_t_5numpy_float32_t), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float_t = { "float_t", NULL, sizeof(__pyx_t_5numpy_float_t), { 0 }, 0, 'R', 0, 0 };
#define __Pyx_MODULE_NAME "pyscipopt.scip"
extern int __pyx_module_is_main_pyscipopt__scip;
int __pyx_module_is_main_pyscipopt__scip = 0;
/* Implementation of 'pyscipopt.scip' */
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_TypeError;
static PyObject *__pyx_builtin_NotImplementedError;
static PyObject *__pyx_builtin_sorted;
static PyObject *__pyx_builtin_sum;
static PyObject *__pyx_builtin_StopIteration;
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_max;
static PyObject *__pyx_builtin_ZeroDivisionError;
static PyObject *__pyx_builtin_map;
static PyObject *__pyx_builtin_Warning;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_print;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_IOError;
static PyObject *__pyx_builtin_KeyError;
static PyObject *__pyx_builtin_LookupError;
static PyObject *__pyx_builtin_open;
static PyObject *__pyx_builtin_chr;
static PyObject *__pyx_builtin_ImportError;
static const char __pyx_k_[] = ", ";
static const char __pyx_k_B[] = "B";
static const char __pyx_k_C[] = "C";
static const char __pyx_k_I[] = "I";
static const char __pyx_k_c[] = "c";
static const char __pyx_k_e[] = "e";
static const char __pyx_k_f[] = "f";
static const char __pyx_k_v[] = "v";
static const char __pyx_k_w[] = "w";
static const char __pyx_k_x[] = "x";
static const char __pyx_k_LP[] = "LP";
static const char __pyx_k_Op[] = "Op";
static const char __pyx_k__5[] = ")";
static const char __pyx_k__8[] = "(";
static const char __pyx_k__9[] = ",";
static const char __pyx_k_eq[] = "__eq__";
static const char __pyx_k_lb[] = "lb";
static const char __pyx_k_np[] = "np";
static const char __pyx_k_op[] = "op";
static const char __pyx_k_or[] = "or";
static const char __pyx_k_rc[] = "rc";
static const char __pyx_k_ub[] = "ub";
static const char __pyx_k_OFF[] = "OFF";
static const char __pyx_k_Row[] = "Row";
static const char __pyx_k__84[] = "";
static const char __pyx_k_abs[] = "abs";
static const char __pyx_k_add[] = "__add__";
static const char __pyx_k_and[] = "and";
static const char __pyx_k_chr[] = "chr";
static const char __pyx_k_cip[] = ".cip";
static const char __pyx_k_col[] = "col";
static const char __pyx_k_cut[] = "cut";
static const char __pyx_k_div[] = "__div__";
static const char __pyx_k_doc[] = "__doc__";
static const char __pyx_k_exp[] = "exp";
static const char __pyx_k_gap[] = "gap";
static const char __pyx_k_get[] = "get";
static const char __pyx_k_idx[] = "idx";
static const char __pyx_k_inf[] = "inf";
static const char __pyx_k_key[] = "key";
static const char __pyx_k_lbs[] = "lbs";
static const char __pyx_k_len[] = "__len__";
static const char __pyx_k_lhs[] = "lhs";
static const char __pyx_k_log[] = "log";
static const char __pyx_k_map[] = "map";
static const char __pyx_k_max[] = "max";
static const char __pyx_k_mul[] = "__mul__";
static const char __pyx_k_new[] = "__new__";
static const char __pyx_k_obj[] = "obj";
static const char __pyx_k_pos[] = "pos";
static const char __pyx_k_ptr[] = "ptr";
static const char __pyx_k_rhs[] = "rhs";
static const char __pyx_k_row[] = "row";
static const char __pyx_k_sol[] = "sol";
static const char __pyx_k_sum[] = "sum";
static const char __pyx_k_sys[] = "sys";
static const char __pyx_k_ubs[] = "ubs";
static const char __pyx_k_val[] = "val";
static const char __pyx_k_var[] = "var";
static const char __pyx_k_xor[] = "xor";
static const char __pyx_k_AUTO[] = "AUTO";
static const char __pyx_k_Expr[] = "Expr";
static const char __pyx_k_FAST[] = "FAST";
static const char __pyx_k_FORK[] = "FORK";
static const char __pyx_k_FREE[] = "FREE";
static const char __pyx_k_Heur[] = "Heur";
static const char __pyx_k_INIT[] = "INIT";
static const char __pyx_k_LEAF[] = "LEAF";
static const char __pyx_k_NONE[] = "NONE";
static const char __pyx_k_Node[] = "Node";
static const char __pyx_k_Prop[] = "Prop";
static const char __pyx_k_SYNC[] = "SYNC";
static const char __pyx_k_Sepa[] = "Sepa";
static const char __pyx_k_Term[] = "Term";
static const char __pyx_k__132[] = "+";
static const char __pyx_k__133[] = "-";
static const char __pyx_k__134[] = "*";
static const char __pyx_k__135[] = "/";
static const char __pyx_k__136[] = "**";
static const char __pyx_k_ages[] = "ages";
static const char __pyx_k_args[] = "args";
static const char __pyx_k_both[] = "both";
static const char __pyx_k_ceil[] = "ceil";
static const char __pyx_k_coef[] = "coef";
static const char __pyx_k_cons[] = "cons";
static const char __pyx_k_copy[] = "copy";
static const char __pyx_k_desc[] = "desc";
static const char __pyx_k_dict[] = "__dict__";
static const char __pyx_k_dual[] = "dual";
static const char __pyx_k_exit[] = "__exit__";
static const char __pyx_k_expo[] = "expo";
static const char __pyx_k_expr[] = "expr";
static const char __pyx_k_fabs[] = "fabs";
static const char __pyx_k_file[] = "file";
static const char __pyx_k_flag[] = "flag";
static const char __pyx_k_free[] = "free";
static const char __pyx_k_freq[] = "freq";
static const char __pyx_k_hash[] = "__hash__";
static const char __pyx_k_heur[] = "heur";
static const char __pyx_k_init[] = "__init__";
static const char __pyx_k_keys[] = "keys";
static const char __pyx_k_lhss[] = "lhss";
static const char __pyx_k_main[] = "__main__";
static const char __pyx_k_math[] = "math";
static const char __pyx_k_name[] = "name";
static const char __pyx_k_nlps[] = "nlps";
static const char __pyx_k_nnzs[] = "nnzs";
static const char __pyx_k_node[] = "node";
static const char __pyx_k_objs[] = "objs";
static const char __pyx_k_op_2[] = "_op";
static const char __pyx_k_open[] = "open";
static const char __pyx_k_plus[] = "plus";
static const char __pyx_k_prod[] = "prod";
static const char __pyx_k_prop[] = "prop";
static const char __pyx_k_repr[] = "__repr__";
static const char __pyx_k_rhss[] = "rhss";
static const char __pyx_k_self[] = "self";
static const char __pyx_k_send[] = "send";
static const char __pyx_k_sepa[] = "sepa";
static const char __pyx_k_side[] = "side";
static const char __pyx_k_sqrt[] = "sqrt";
static const char __pyx_k_term[] = "term";
static const char __pyx_k_test[] = "__test__";
static const char __pyx_k_true[] = "true";
static const char __pyx_k_val1[] = "val1";
static const char __pyx_k_val2[] = "val2";
static const char __pyx_k_vals[] = "vals";
static const char __pyx_k_vars[] = "vars";
static const char __pyx_k_warn[] = "warn";
static const char __pyx_k_zero[] = "zero";
static const char __pyx_k_CHECK[] = "CHECK";
static const char __pyx_k_CHILD[] = "CHILD";
static const char __pyx_k_CONST[] = "CONST";
static const char __pyx_k_ERROR[] = "ERROR";
static const char __pyx_k_Event[] = "Event";
static const char __pyx_k_FIXED[] = "FIXED";
static const char __pyx_k_MAJOR[] = "MAJOR";
static const char __pyx_k_MINOR[] = "MINOR";
static const char __pyx_k_Model[] = "Model";
static const char __pyx_k_PATCH[] = "PATCH";
static const char __pyx_k_RELAX[] = "RELAX";
static const char __pyx_k_Relax[] = "Relax";
static const char __pyx_k_add_2[] = "add";
static const char __pyx_k_basic[] = "basic";
static const char __pyx_k_check[] = "check";
static const char __pyx_k_child[] = "child";
static const char __pyx_k_class[] = "__class__";
static const char __pyx_k_clear[] = "clear";
static const char __pyx_k_close[] = "close";
static const char __pyx_k_coeff[] = "coeff";
static const char __pyx_k_coefs[] = "coefs";
static const char __pyx_k_const[] = "const";
static const char __pyx_k_cutlp[] = "cutlp";
static const char __pyx_k_delay[] = "delay";
static const char __pyx_k_depth[] = "depth";
static const char __pyx_k_div_2[] = "div";
static const char __pyx_k_dtype[] = "dtype";
static const char __pyx_k_empty[] = "empty";
static const char __pyx_k_enter[] = "__enter__";
static const char __pyx_k_exact[] = "exact";
static const char __pyx_k_float[] = "float";
static const char __pyx_k_floor[] = "floor";
static const char __pyx_k_force[] = "force";
static const char __pyx_k_getOp[] = "getOp";
static const char __pyx_k_int32[] = "int32";
static const char __pyx_k_items[] = "items";
static const char __pyx_k_itlim[] = "itlim";
static const char __pyx_k_lhs_2[] = "_lhs";
static const char __pyx_k_local[] = "local";
static const char __pyx_k_lower[] = "lower";
static const char __pyx_k_minus[] = "minus";
static const char __pyx_k_model[] = "model";
static const char __pyx_k_mul_2[] = "mul";
static const char __pyx_k_ncols[] = "ncols";
static const char __pyx_k_nnzrs[] = "nnzrs";
static const char __pyx_k_node1[] = "node1";
static const char __pyx_k_node2[] = "node2";
static const char __pyx_k_nodes[] = "nodes";
static const char __pyx_k_norms[] = "norms";
static const char __pyx_k_nrows[] = "nrows";
static const char __pyx_k_nruns[] = "nruns";
static const char __pyx_k_numpy[] = "numpy";
static const char __pyx_k_nvars[] = "nvars";
static const char __pyx_k_other[] = "other";
static const char __pyx_k_power[] = "power";
static const char __pyx_k_print[] = "print";
static const char __pyx_k_proxy[] = "proxy";
static const char __pyx_k_ps_up[] = "ps_up";
static const char __pyx_k_quiet[] = "quiet";
static const char __pyx_k_range[] = "range";
static const char __pyx_k_relax[] = "relax";
static const char __pyx_k_rhs_2[] = "_rhs";
static const char __pyx_k_sense[] = "sense";
static const char __pyx_k_shape[] = "shape";
static const char __pyx_k_slack[] = "slack";
static const char __pyx_k_slots[] = "__slots__";
static const char __pyx_k_stats[] = "stats";
static const char __pyx_k_terms[] = "terms";
static const char __pyx_k_throw[] = "throw";
static const char __pyx_k_trans[] = "trans";
static const char __pyx_k_types[] = "types";
static const char __pyx_k_upper[] = "upper";
static const char __pyx_k_utf_8[] = "utf-8";
static const char __pyx_k_value[] = "value";
static const char __pyx_k_vtype[] = "vtype";
static const char __pyx_k_write[] = "write";
static const char __pyx_k_zeros[] = "zeros";
static const char __pyx_k_BINARY[] = "BINARY";
static const char __pyx_k_CUTOFF[] = "CUTOFF";
static const char __pyx_k_Column[] = "Column";
static const char __pyx_k_Expr_s[] = "Expr(%s)";
static const char __pyx_k_HARDLP[] = "HARDLP";
static const char __pyx_k_MEDIUM[] = "MEDIUM";
static const char __pyx_k_ORcons[] = "ORcons";
static const char __pyx_k_PSEUDO[] = "PSEUDO";
static const char __pyx_k_Presol[] = "Presol";
static const char __pyx_k_Pricer[] = "Pricer";
static const char __pyx_k_SOLVED[] = "SOLVED";
static const char __pyx_k_Term_s[] = "Term(%s)";
static const char __pyx_k_append[] = "append";
static const char __pyx_k_bdtype[] = "bdtype";
static const char __pyx_k_binvar[] = "binvar";
static const char __pyx_k_coeffs[] = "coeffs";
static const char __pyx_k_create[] = "create";
static const char __pyx_k_degree[] = "degree";
static const char __pyx_k_extend[] = "extend";
static const char __pyx_k_fileno[] = "fileno";
static const char __pyx_k_format[] = "format";
static const char __pyx_k_getObj[] = "getObj";
static const char __pyx_k_import[] = "__import__";
static const char __pyx_k_lambda[] = "<lambda>";
static const char __pyx_k_linear[] = "linear";
static const char __pyx_k_lp_obj[] = "lp_obj";
static const char __pyx_k_merged[] = "merged";
static const char __pyx_k_module[] = "__module__";
static const char __pyx_k_name_2[] = "__name__";
static const char __pyx_k_newEnf[] = "newEnf";
static const char __pyx_k_newRem[] = "newRem";
static const char __pyx_k_newlhs[] = "newlhs";
static const char __pyx_k_newobj[] = "newobj";
static const char __pyx_k_newrhs[] = "newrhs";
static const char __pyx_k_newval[] = "newval";
static const char __pyx_k_nnodes[] = "nnodes";
static const char __pyx_k_number[] = "number";
static const char __pyx_k_offset[] = "offset";
static const char __pyx_k_pickle[] = "pickle";
static const char __pyx_k_presol[] = "presol";
static const char __pyx_k_pricer[] = "pricer";
static const char __pyx_k_ps_sum[] = "ps_sum";
static const char __pyx_k_reduce[] = "__reduce__";
static const char __pyx_k_result[] = "result";
static const char __pyx_k_resvar[] = "resvar";
static const char __pyx_k_rhsvar[] = "rhsvar";
static const char __pyx_k_sorted[] = "sorted";
static const char __pyx_k_stderr[] = "stderr";
static const char __pyx_k_stdout[] = "stdout";
static const char __pyx_k_timing[] = "timing";
static const char __pyx_k_update[] = "update";
static const char __pyx_k_values[] = "values";
static const char __pyx_k_varidx[] = "varidx";
static const char __pyx_k_weight[] = "weight";
static const char __pyx_k_ANDcons[] = "ANDcons";
static const char __pyx_k_Benders[] = "Benders";
static const char __pyx_k_COUNTER[] = "COUNTER";
static const char __pyx_k_DEADEND[] = "DEADEND";
static const char __pyx_k_DEFAULT[] = "DEFAULT";
static const char __pyx_k_DELAYED[] = "DELAYED";
static const char __pyx_k_EASYCIP[] = "EASYCIP";
static const char __pyx_k_GenExpr[] = "GenExpr";
static const char __pyx_k_INTEGER[] = "INTEGER";
static const char __pyx_k_IOError[] = "IOError";
static const char __pyx_k_LPEVENT[] = "LPEVENT";
static const char __pyx_k_Nodesel[] = "Nodesel";
static const char __pyx_k_OPTIMAL[] = "OPTIMAL";
static const char __pyx_k_PROBLEM[] = "PROBLEM";
static const char __pyx_k_PowExpr[] = "PowExpr";
static const char __pyx_k_SIBLING[] = "SIBLING";
static const char __pyx_k_SOLVELP[] = "SOLVELP";
static const char __pyx_k_SOLVING[] = "SOLVING";
static const char __pyx_k_SUBROOT[] = "SUBROOT";
static const char __pyx_k_SUCCESS[] = "SUCCESS";
static const char __pyx_k_SumExpr[] = "SumExpr";
static const char __pyx_k_UNKNOWN[] = "UNKNOWN";
static const char __pyx_k_UPWARDS[] = "UPWARDS";
static const char __pyx_k_VarExpr[] = "VarExpr";
static const char __pyx_k_Warning[] = "Warning";
static const char __pyx_k_XORcons[] = "XORcons";
static const char __pyx_k_abspath[] = "abspath";
static const char __pyx_k_benders[] = "benders";
static const char __pyx_k_cardval[] = "cardval";
static const char __pyx_k_col_lbs[] = "col_lbs";
static const char __pyx_k_col_ubs[] = "col_ubs";
static const char __pyx_k_colidxs[] = "colidxs";
static const char __pyx_k_confvar[] = "confvar";
static const char __pyx_k_dynamic[] = "dynamic";
static const char __pyx_k_enforce[] = "enforce";
static const char __pyx_k_entries[] = "entries";
static const char __pyx_k_float32[] = "float32";
static const char __pyx_k_freqofs[] = "freqofs";
static const char __pyx_k_genexpr[] = "genexpr";
static const char __pyx_k_getType[] = "getType";
static const char __pyx_k_getVars[] = "getVars";
static const char __pyx_k_getitem[] = "__getitem__";
static const char __pyx_k_hashval[] = "hashval";
static const char __pyx_k_incvals[] = "incvals";
static const char __pyx_k_indices[] = "indices";
static const char __pyx_k_indvars[] = "indvars";
static const char __pyx_k_initial[] = "initial";
static const char __pyx_k_isLocal[] = "isLocal";
static const char __pyx_k_islpcut[] = "islpcut";
static const char __pyx_k_lastcol[] = "lastcol";
static const char __pyx_k_lastrow[] = "lastrow";
static const char __pyx_k_lhs_vec[] = "lhs_vec";
static const char __pyx_k_lincons[] = "lincons";
static const char __pyx_k_linking[] = "linking";
static const char __pyx_k_logicor[] = "logicor";
static const char __pyx_k_nchgbds[] = "nchgbds";
static const char __pyx_k_newInit[] = "newInit";
static const char __pyx_k_nleaves[] = "nleaves";
static const char __pyx_k_nodesel[] = "nodesel";
static const char __pyx_k_nrounds[] = "nrounds";
static const char __pyx_k_nzrcoef[] = "nzrcoef";
static const char __pyx_k_optimal[] = "optimal";
static const char __pyx_k_os_path[] = "os.path";
static const char __pyx_k_prepare[] = "__prepare__";
static const char __pyx_k_ps_down[] = "ps_down";
static const char __pyx_k_restart[] = "restart";
static const char __pyx_k_rhs_vec[] = "rhs_vec";
static const char __pyx_k_rowidxs[] = "rowidxs";
static const char __pyx_k_selnode[] = "selnode";
static const char __pyx_k_solvals[] = "solvals";
static const char __pyx_k_success[] = "success";
static const char __pyx_k_sumexpr[] = "sumexpr";
static const char __pyx_k_truediv[] = "__truediv__";
static const char __pyx_k_unknown[] = "unknown";
static const char __pyx_k_varexpr[] = "varexpr";
static const char __pyx_k_version[] = "version";
static const char __pyx_k_weakref[] = "weakref";
static const char __pyx_k_weights[] = "weights";
static const char __pyx_k_BEFORELP[] = "BEFORELP";
static const char __pyx_k_BRANCHED[] = "BRANCHED";
static const char __pyx_k_CPSOLVER[] = "CPSOLVER";
static const char __pyx_k_Conshdlr[] = "Conshdlr";
static const char __pyx_k_Constant[] = "Constant";
static const char __pyx_k_DISABLED[] = "DISABLED";
static const char __pyx_k_ExprCons[] = "ExprCons(";
static const char __pyx_k_FEASIBLE[] = "FEASIBLE";
static const char __pyx_k_FOUNDSOL[] = "FOUNDSOL";
static const char __pyx_k_GAPLIMIT[] = "GAPLIMIT";
static const char __pyx_k_JUNCTION[] = "JUNCTION";
static const char __pyx_k_KeyError[] = "KeyError";
static const char __pyx_k_LPSOLVED[] = "LPSOLVED";
static const char __pyx_k_MEMLIMIT[] = "MEMLIMIT";
static const char __pyx_k_NEWROUND[] = "NEWROUND";
static const char __pyx_k_OBJLIMIT[] = "OBJLIMIT";
static const char __pyx_k_Operator[] = "Operator";
static const char __pyx_k_ProdExpr[] = "ProdExpr";
static const char __pyx_k_SOLLIMIT[] = "SOLLIMIT";
static const char __pyx_k_SOS1cons[] = "SOS1cons";
static const char __pyx_k_SOS2cons[] = "SOS2cons";
static const char __pyx_k_Solution[] = "Solution";
static const char __pyx_k_VARADDED[] = "VARADDED";
static const char __pyx_k_VARFIXED[] = "VARFIXED";
static const char __pyx_k_Variable[] = "Variable";
static const char __pyx_k_cdeg_max[] = "cdeg_max";
static const char __pyx_k_cdeg_min[] = "cdeg_min";
static const char __pyx_k_cdeg_var[] = "cdeg_var";
static const char __pyx_k_checkint[] = "checkint";
static const char __pyx_k_children[] = "children";
static const char __pyx_k_comments[] = "comments";
static const char __pyx_k_cons_lhs[] = "cons_lhs";
static const char __pyx_k_cons_rhs[] = "cons_rhs";
static const char __pyx_k_conscopy[] = "conscopy";
static const char __pyx_k_consexit[] = "consexit";
static const char __pyx_k_consfree[] = "consfree";
static const char __pyx_k_conshdlr[] = "conshdlr";
static const char __pyx_k_consinit[] = "consinit";
static const char __pyx_k_conslock[] = "conslock";
static const char __pyx_k_consprop[] = "consprop";
static const char __pyx_k_constant[] = "constant";
static const char __pyx_k_consvars[] = "consvars";
static const char __pyx_k_cutrelax[] = "cutrelax";
static const char __pyx_k_dispchar[] = "dispchar";
static const char __pyx_k_dualsols[] = "dualsols";
static const char __pyx_k_enfotype[] = "enfotype";
static const char __pyx_k_estimate[] = "estimate";
static const char __pyx_k_filename[] = "filename";
static const char __pyx_k_firstcol[] = "firstcol";
static const char __pyx_k_firstrow[] = "firstrow";
static const char __pyx_k_fixedval[] = "fixedval";
static const char __pyx_k_forcecut[] = "forcecut";
static const char __pyx_k_getNNonz[] = "getNNonz";
static const char __pyx_k_getStage[] = "getStage";
static const char __pyx_k_getstate[] = "__getstate__";
static const char __pyx_k_heurexec[] = "heurexec";
static const char __pyx_k_heurexit[] = "heurexit";
static const char __pyx_k_heurfree[] = "heurfree";
static const char __pyx_k_heurinit[] = "heurinit";
static const char __pyx_k_infinity[] = "infinity";
static const char __pyx_k_is_local[] = "is_local";
static const char __pyx_k_knapsack[] = "knapsack";
static const char __pyx_k_locktype[] = "locktype";
static const char __pyx_k_maxdepth[] = "maxdepth";
static const char __pyx_k_maximize[] = "maximize";
static const char __pyx_k_minimize[] = "minimize";
static const char __pyx_k_nduallps[] = "nduallps";
static const char __pyx_k_newCheck[] = "newCheck";
static const char __pyx_k_newbound[] = "newbound";
static const char __pyx_k_nlocksup[] = "nlocksup";
static const char __pyx_k_nnodelps[] = "nnodelps";
static const char __pyx_k_nodecomp[] = "nodecomp";
static const char __pyx_k_nodeexit[] = "nodeexit";
static const char __pyx_k_nodefree[] = "nodefree";
static const char __pyx_k_nodeinit[] = "nodeinit";
static const char __pyx_k_onlyroot[] = "onlyroot";
static const char __pyx_k_origcopy[] = "origcopy";
static const char __pyx_k_original[] = "original";
static const char __pyx_k_priority[] = "priority";
static const char __pyx_k_prodexpr[] = "prodexpr";
static const char __pyx_k_propexec[] = "propexec";
static const char __pyx_k_propexit[] = "propexit";
static const char __pyx_k_propfree[] = "propfree";
static const char __pyx_k_propfreq[] = "propfreq";
static const char __pyx_k_propinit[] = "propinit";
static const char __pyx_k_ps_ratio[] = "ps_ratio";
static const char __pyx_k_ptrtuple[] = "ptrtuple";
static const char __pyx_k_pyx_type[] = "__pyx_type";
static const char __pyx_k_quadcons[] = "quadcons";
static const char __pyx_k_qualname[] = "__qualname__";
static const char __pyx_k_quicksum[] = "quicksum";
static const char __pyx_k_redcosts[] = "redcosts";
static const char __pyx_k_sepaexit[] = "sepaexit";
static const char __pyx_k_sepafree[] = "sepafree";
static const char __pyx_k_sepafreq[] = "sepafreq";
static const char __pyx_k_sepainit[] = "sepainit";
static const char __pyx_k_separate[] = "separate";
static const char __pyx_k_setstate[] = "__setstate__";
static const char __pyx_k_shareaux[] = "shareaux";
static const char __pyx_k_solfracs[] = "solfracs";
static const char __pyx_k_solution[] = "solution";
static const char __pyx_k_solvecip[] = "solvecip";
static const char __pyx_k_splitext[] = "splitext";
static const char __pyx_k_termlist[] = "termlist";
static const char __pyx_k_transgap[] = "transgap";
static const char __pyx_k_varbound[] = "varbound";
static const char __pyx_k_variable[] = "variable";
static const char __pyx_k_vartuple[] = "vartuple";
static const char __pyx_k_warnings[] = "warnings";
static const char __pyx_k_CONSADDED[] = "CONSADDED";
static const char __pyx_k_DIDNOTRUN[] = "DIDNOTRUN";
static const char __pyx_k_DOWNWARDS[] = "DOWNWARDS";
static const char __pyx_k_EXITSOLVE[] = "EXITSOLVE";
static const char __pyx_k_Eventhdlr[] = "Eventhdlr";
static const char __pyx_k_FOCUSNODE[] = "FOCUSNODE";
static const char __pyx_k_FREETRANS[] = "FREETRANS";
static const char __pyx_k_IMPLADDED[] = "IMPLADDED";
static const char __pyx_k_INFORUNBD[] = "INFORUNBD";
static const char __pyx_k_INITSOLVE[] = "INITSOLVE";
static const char __pyx_k_ITERLIMIT[] = "ITERLIMIT";
static const char __pyx_k_LBRELAXED[] = "LBRELAXED";
static const char __pyx_k_NODELIMIT[] = "NODELIMIT";
static const char __pyx_k_NOTSOLVED[] = "NOTSOLVED";
static const char __pyx_k_PHASEFEAS[] = "PHASEFEAS";
static const char __pyx_k_PRESOLVED[] = "PRESOLVED";
static const char __pyx_k_SEPARATED[] = "SEPARATED";
static const char __pyx_k_SUSPENDED[] = "SUSPENDED";
static const char __pyx_k_TIMELIMIT[] = "TIMELIMIT";
static const char __pyx_k_Term___eq[] = "Term.__eq__";
static const char __pyx_k_TypeError[] = "TypeError";
static const char __pyx_k_UBRELAXED[] = "UBRELAXED";
static const char __pyx_k_UNBOUNDED[] = "UNBOUNDED";
static const char __pyx_k_UnaryExpr[] = "UnaryExpr";
static const char __pyx_k_acons_nb1[] = "acons_nb1";
static const char __pyx_k_acons_nb2[] = "acons_nb2";
static const char __pyx_k_acons_nb3[] = "acons_nb3";
static const char __pyx_k_acons_nb4[] = "acons_nb4";
static const char __pyx_k_basestats[] = "basestats";
static const char __pyx_k_branchdir[] = "branchdir";
static const char __pyx_k_cdeg_mean[] = "cdeg_mean";
static const char __pyx_k_coefs_neg[] = "coefs_neg";
static const char __pyx_k_coefs_pos[] = "coefs_pos";
static const char __pyx_k_col_coefs[] = "col_coefs";
static const char __pyx_k_col_nnzrs[] = "col_nnzrs";
static const char __pyx_k_col_ps_up[] = "col_ps_up";
static const char __pyx_k_cons_nneg[] = "cons_nneg";
static const char __pyx_k_cons_npos[] = "cons_npos";
static const char __pyx_k_conscheck[] = "conscheck";
static const char __pyx_k_consparse[] = "consparse";
static const char __pyx_k_consprint[] = "consprint";
static const char __pyx_k_constrans[] = "constrans";
static const char __pyx_k_createSol[] = "createSol";
static const char __pyx_k_cutpseudo[] = "cutpseudo";
static const char __pyx_k_delayprop[] = "delayprop";
static const char __pyx_k_delaysepa[] = "delaysepa";
static const char __pyx_k_dualbound[] = "dualbound";
static const char __pyx_k_eagerfreq[] = "eagerfreq";
static const char __pyx_k_enumerate[] = "enumerate";
static const char __pyx_k_eventcopy[] = "eventcopy";
static const char __pyx_k_eventexec[] = "eventexec";
static const char __pyx_k_eventexit[] = "eventexit";
static const char __pyx_k_eventfree[] = "eventfree";
static const char __pyx_k_eventhdlr[] = "eventhdlr";
static const char __pyx_k_eventinit[] = "eventinit";
static const char __pyx_k_eventtype[] = "eventtype";
static const char __pyx_k_extension[] = "extension";
static const char __pyx_k_getSolVal[] = "getSolVal";
static const char __pyx_k_inferinfo[] = "inferinfo";
static const char __pyx_k_isChecked[] = "isChecked";
static const char __pyx_k_isDynamic[] = "isDynamic";
static const char __pyx_k_isInitial[] = "isInitial";
static const char __pyx_k_is_at_lhs[] = "is_at_lhs";
static const char __pyx_k_is_at_rhs[] = "is_at_rhs";
static const char __pyx_k_is_number[] = "_is_number";
static const char __pyx_k_mappedvar[] = "mappedvar";
static const char __pyx_k_maxrounds[] = "maxrounds";
static const char __pyx_k_metaclass[] = "__metaclass__";
static const char __pyx_k_model_cip[] = "model.cip";
static const char __pyx_k_naddconss[] = "naddconss";
static const char __pyx_k_naddholes[] = "naddholes";
static const char __pyx_k_naggrvars[] = "naggrvars";
static const char __pyx_k_nchgcoefs[] = "nchgcoefs";
static const char __pyx_k_nchgsides[] = "nchgsides";
static const char __pyx_k_nchildren[] = "nchildren";
static const char __pyx_k_ndelconss[] = "ndelconss";
static const char __pyx_k_needscons[] = "needscons";
static const char __pyx_k_nlocksneg[] = "nlocksneg";
static const char __pyx_k_nlockspos[] = "nlockspos";
static const char __pyx_k_nnewholes[] = "nnewholes";
static const char __pyx_k_normalize[] = "normalize";
static const char __pyx_k_objective[] = "objective";
static const char __pyx_k_param_set[] = "param.set";
static const char __pyx_k_pricedVar[] = "pricedVar";
static const char __pyx_k_propagate[] = "propagate";
static const char __pyx_k_pyx_state[] = "__pyx_state";
static const char __pyx_k_quadratic[] = "quadratic";
static const char __pyx_k_quickprod[] = "quickprod";
static const char __pyx_k_reduce_ex[] = "__reduce_ex__";
static const char __pyx_k_relaxedbd[] = "relaxedbd";
static const char __pyx_k_relaxexec[] = "relaxexec";
static const char __pyx_k_relaxexit[] = "relaxexit";
static const char __pyx_k_relaxfree[] = "relaxfree";
static const char __pyx_k_relaxinit[] = "relaxinit";
static const char __pyx_k_removable[] = "removable";
static const char __pyx_k_root_info[] = "root_info";
static const char __pyx_k_skipsolve[] = "skipsolve";
static const char __pyx_k_solutions[] = "solutions";
static const char __pyx_k_stopearly[] = "stopearly";
static const char __pyx_k_timelimit[] = "timelimit";
static const char __pyx_k_unbounded[] = "unbounded";
static const char __pyx_k_validnode[] = "validnode";
static const char __pyx_k_AGGRESSIVE[] = "AGGRESSIVE";
static const char __pyx_k_BEFORENODE[] = "BEFORENODE";
static const char __pyx_k_Benderscut[] = "Benderscut";
static const char __pyx_k_Branchrule[] = "Branchrule";
static const char __pyx_k_CONTINUOUS[] = "CONTINUOUS";
static const char __pyx_k_Constraint[] = "Constraint";
static const char __pyx_k_DIDNOTFIND[] = "DIDNOTFIND";
static const char __pyx_k_EXHAUSTIVE[] = "EXHAUSTIVE";
static const char __pyx_k_ExprCons_2[] = "ExprCons";
static const char __pyx_k_GHOLEADDED[] = "GHOLEADDED";
static const char __pyx_k_GLBCHANGED[] = "GLBCHANGED";
static const char __pyx_k_GUBCHANGED[] = "GUBCHANGED";
static const char __pyx_k_INFEASIBLE[] = "INFEASIBLE";
static const char __pyx_k_LHOLEADDED[] = "LHOLEADDED";
static const char __pyx_k_OBJCHANGED[] = "OBJCHANGED";
static const char __pyx_k_OPTIMALITY[] = "OPTIMALITY";
static const char __pyx_k_PHASEPROOF[] = "PHASEPROOF";
static const char __pyx_k_PRESOLVING[] = "PRESOLVING";
static const char __pyx_k_PSEUDOFORK[] = "PSEUDOFORK";
static const char __pyx_k_REDUCEDDOM[] = "REDUCEDDOM";
static const char __pyx_k_ROWADDEDLP[] = "ROWADDEDLP";
static const char __pyx_k_Term___add[] = "Term.__add__";
static const char __pyx_k_Term___len[] = "Term.__len__";
static const char __pyx_k_VARDELETED[] = "VARDELETED";
static const char __pyx_k_ValueError[] = "ValueError";
static const char __pyx_k_acons_max1[] = "acons_max1";
static const char __pyx_k_acons_max2[] = "acons_max2";
static const char __pyx_k_acons_max3[] = "acons_max3";
static const char __pyx_k_acons_max4[] = "acons_max4";
static const char __pyx_k_acons_min1[] = "acons_min1";
static const char __pyx_k_acons_min2[] = "acons_min2";
static const char __pyx_k_acons_min3[] = "acons_min3";
static const char __pyx_k_acons_min4[] = "acons_min4";
static const char __pyx_k_acons_sum1[] = "acons_sum1";
static const char __pyx_k_acons_sum2[] = "acons_sum2";
static const char __pyx_k_acons_sum3[] = "acons_sum3";
static const char __pyx_k_acons_sum4[] = "acons_sum4";
static const char __pyx_k_acons_var1[] = "acons_var1";
static const char __pyx_k_acons_var2[] = "acons_var2";
static const char __pyx_k_acons_var3[] = "acons_var3";
static const char __pyx_k_acons_var4[] = "acons_var4";
static const char __pyx_k_activities[] = "activities";
static const char __pyx_k_addLinCons[] = "_addLinCons";
static const char __pyx_k_avgincvals[] = "avgincvals";
static const char __pyx_k_benderscut[] = "benderscut";
static const char __pyx_k_branchexit[] = "branchexit";
static const char __pyx_k_branchfree[] = "branchfree";
static const char __pyx_k_branchinit[] = "branchinit";
static const char __pyx_k_branchrule[] = "branchrule";
static const char __pyx_k_candidates[] = "candidates";
static const char __pyx_k_col_ps_sum[] = "col_ps_sum";
static const char __pyx_k_completely[] = "completely";
static const char __pyx_k_cons_is_OR[] = "cons_is_OR";
static const char __pyx_k_cons_nnzrs[] = "cons_nnzrs";
static const char __pyx_k_consactive[] = "consactive";
static const char __pyx_k_consdelete[] = "consdelete";
static const char __pyx_k_consenable[] = "consenable";
static const char __pyx_k_consenfolp[] = "consenfolp";
static const char __pyx_k_consenfops[] = "consenfops";
static const char __pyx_k_consinitlp[] = "consinitlp";
static const char __pyx_k_conspresol[] = "conspresol";
static const char __pyx_k_conssepalp[] = "conssepalp";
static const char __pyx_k_constraint[] = "constraint";
static const char __pyx_k_cumulative[] = "cumulative";
static const char __pyx_k_focusdepth[] = "focusdepth";
static const char __pyx_k_getOpIndex[] = "getOpIndex";
static const char __pyx_k_globalcopy[] = "globalcopy";
static const char __pyx_k_heurtiming[] = "heurtiming";
static const char __pyx_k_infeasible[] = "infeasible";
static const char __pyx_k_isEnforced[] = "isEnforced";
static const char __pyx_k_isOriginal[] = "isOriginal";
static const char __pyx_k_is_integer[] = "is_integer";
static const char __pyx_k_lowerbound[] = "lowerbound";
static const char __pyx_k_modifiable[] = "modifiable";
static const char __pyx_k_ncutsfound[] = "ncutsfound";
static const char __pyx_k_ndivinglps[] = "ndivinglps";
static const char __pyx_k_nfixedvars[] = "nfixedvars";
static const char __pyx_k_nlocksdown[] = "nlocksdown";
static const char __pyx_k_nnewchgbds[] = "nnewchgbds";
static const char __pyx_k_nnodesleft[] = "nnodesleft";
static const char __pyx_k_nodeselect[] = "nodeselect";
static const char __pyx_k_npricevars[] = "npricevars";
static const char __pyx_k_nprimallps[] = "nprimallps";
static const char __pyx_k_nreoptruns[] = "nreoptruns";
static const char __pyx_k_nsolsfound[] = "nsolsfound";
static const char __pyx_k_nupgdconss[] = "nupgdconss";
static const char __pyx_k_objcossims[] = "objcossims";
static const char __pyx_k_onlyconvex[] = "onlyconvex";
static const char __pyx_k_ota_nn_max[] = "ota_nn_max";
static const char __pyx_k_ota_nn_min[] = "ota_nn_min";
static const char __pyx_k_ota_np_max[] = "ota_np_max";
static const char __pyx_k_ota_np_min[] = "ota_np_min";
static const char __pyx_k_ota_pn_max[] = "ota_pn_max";
static const char __pyx_k_ota_pn_min[] = "ota_pn_min";
static const char __pyx_k_ota_pp_max[] = "ota_pp_max";
static const char __pyx_k_ota_pp_min[] = "ota_pp_min";
static const char __pyx_k_percentile[] = "percentile";
static const char __pyx_k_presolexec[] = "presolexec";
static const char __pyx_k_presolexit[] = "presolexit";
static const char __pyx_k_presolfree[] = "presolfree";
static const char __pyx_k_presolinit[] = "presolinit";
static const char __pyx_k_prev_state[] = "prev_state";
static const char __pyx_k_pricerexit[] = "pricerexit";
static const char __pyx_k_pricerfree[] = "pricerfree";
static const char __pyx_k_pricerinit[] = "pricerinit";
static const char __pyx_k_probnumber[] = "probnumber";
static const char __pyx_k_proppresol[] = "proppresol";
static const char __pyx_k_proptiming[] = "proptiming";
static const char __pyx_k_ps_product[] = "ps_product";
static const char __pyx_k_pyx_result[] = "__pyx_result";
static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
static const char __pyx_k_sepaexeclp[] = "sepaexeclp";
static const char __pyx_k_subproblem[] = "subproblem";
static const char __pyx_k_targetcons[] = "targetcons";
static const char __pyx_k_timingmask[] = "timingmask";
static const char __pyx_k_upperbound[] = "upperbound";
static const char __pyx_k_AFTERLPLOOP[] = "AFTERLPLOOP";
static const char __pyx_k_AFTERLPNODE[] = "AFTERLPNODE";
static const char __pyx_k_CONSCHANGED[] = "CONSCHANGED";
static const char __pyx_k_FEASIBILITY[] = "FEASIBILITY";
static const char __pyx_k_ImportError[] = "ImportError";
static const char __pyx_k_LBTIGHTENED[] = "LBTIGHTENED";
static const char __pyx_k_LookupError[] = "LookupError";
static const char __pyx_k_MemoryError[] = "MemoryError";
static const char __pyx_k_NODEFOCUSED[] = "NODEFOCUSED";
static const char __pyx_k_PROBINGNODE[] = "PROBINGNODE";
static const char __pyx_k_PickleError[] = "PickleError";
static const char __pyx_k_REFOCUSNODE[] = "REFOCUSNODE";
static const char __pyx_k_TRANSFORMED[] = "TRANSFORMED";
static const char __pyx_k_Term___hash[] = "Term.__hash__";
static const char __pyx_k_Term___init[] = "Term.__init__";
static const char __pyx_k_Term___repr[] = "Term.__repr__";
static const char __pyx_k_UBTIGHTENED[] = "UBTIGHTENED";
static const char __pyx_k_VARUNLOCKED[] = "VARUNLOCKED";
static const char __pyx_k_acons_mean1[] = "acons_mean1";
static const char __pyx_k_acons_mean2[] = "acons_mean2";
static const char __pyx_k_acons_mean3[] = "acons_mean3";
static const char __pyx_k_acons_mean4[] = "acons_mean4";
static const char __pyx_k_addQuadCons[] = "_addQuadCons";
static const char __pyx_k_bendersexit[] = "bendersexit";
static const char __pyx_k_bendersfree[] = "bendersfree";
static const char __pyx_k_bendersinit[] = "bendersinit";
static const char __pyx_k_cardinality[] = "cardinality";
static const char __pyx_k_checkbounds[] = "checkbounds";
static const char __pyx_k_checklprows[] = "checklprows";
static const char __pyx_k_col_ps_down[] = "col_ps_down";
static const char __pyx_k_col_solvals[] = "col_solvals";
static const char __pyx_k_cons_is_AND[] = "cons_is_AND";
static const char __pyx_k_cons_is_XOR[] = "cons_is_XOR";
static const char __pyx_k_cons_matrix[] = "cons_matrix";
static const char __pyx_k_consdelvars[] = "consdelvars";
static const char __pyx_k_consdisable[] = "consdisable";
static const char __pyx_k_consexitpre[] = "consexitpre";
static const char __pyx_k_consexitsol[] = "consexitsol";
static const char __pyx_k_consgetvars[] = "consgetvars";
static const char __pyx_k_consinitpre[] = "consinitpre";
static const char __pyx_k_consinitsol[] = "consinitsol";
static const char __pyx_k_consresprop[] = "consresprop";
static const char __pyx_k_conssepasol[] = "conssepasol";
static const char __pyx_k_constraints[] = "constraints";
static const char __pyx_k_cutoffbound[] = "cutoffbound";
static const char __pyx_k_cutoffdepth[] = "cutoffdepth";
static const char __pyx_k_entrieslist[] = "entrieslist";
static const char __pyx_k_eventdelete[] = "eventdelete";
static const char __pyx_k_heurexitsol[] = "heurexitsol";
static const char __pyx_k_heurinitsol[] = "heurinitsol";
static const char __pyx_k_isQuadratic[] = "isQuadratic";
static const char __pyx_k_isRemovable[] = "isRemovable";
static const char __pyx_k_isSeparated[] = "isSeparated";
static const char __pyx_k_lowerbounds[] = "lowerbounds";
static const char __pyx_k_nbacktracks[] = "nbacktracks";
static const char __pyx_k_nbarrierlps[] = "nbarrierlps";
static const char __pyx_k_nodeexitsol[] = "nodeexitsol";
static const char __pyx_k_nodeinitsol[] = "nodeinitsol";
static const char __pyx_k_nodeselprio[] = "nodeselprio";
static const char __pyx_k_nresolvelps[] = "nresolvelps";
static const char __pyx_k_nseparounds[] = "nseparounds";
static const char __pyx_k_ntotalnodes[] = "ntotalnodes";
static const char __pyx_k_onlychanged[] = "onlychanged";
static const char __pyx_k_plungedepth[] = "plungedepth";
static const char __pyx_k_primalbound[] = "primalbound";
static const char __pyx_k_printreason[] = "printreason";
static const char __pyx_k_problemName[] = "problemName";
static const char __pyx_k_propexitpre[] = "propexitpre";
static const char __pyx_k_propexitsol[] = "propexitsol";
static const char __pyx_k_propinitpre[] = "propinitpre";
static const char __pyx_k_propinitsol[] = "propinitsol";
static const char __pyx_k_propresprop[] = "propresprop";
static const char __pyx_k_repropdepth[] = "repropdepth";
static const char __pyx_k_result_dict[] = "result_dict";
static const char __pyx_k_sepaexecsol[] = "sepaexecsol";
static const char __pyx_k_sepaexitsol[] = "sepaexitsol";
static const char __pyx_k_sepainitsol[] = "sepainitsol";
static const char __pyx_k_setIntParam[] = "setIntParam";
static const char __pyx_k_setMaximize[] = "setMaximize";
static const char __pyx_k_setMinimize[] = "setMinimize";
static const char __pyx_k_solvingtime[] = "solvingtime";
static const char __pyx_k_sourceModel[] = "sourceModel";
static const char __pyx_k_stdpriority[] = "stdpriority";
static const char __pyx_k_targetvalue[] = "targetvalue";
static const char __pyx_k_transformed[] = "transformed";
static const char __pyx_k_usessubscip[] = "usessubscip";
static const char __pyx_k_write_zeros[] = "write_zeros";
static const char __pyx_k_BEFOREPRESOL[] = "BEFOREPRESOL";
static const char __pyx_k_BESTSOLFOUND[] = "BESTSOLFOUND";
static const char __pyx_k_BESTSOLLIMIT[] = "BESTSOLLIMIT";
static const char __pyx_k_DURINGLPLOOP[] = "DURINGLPLOOP";
static const char __pyx_k_EXITPRESOLVE[] = "EXITPRESOLVE";
static const char __pyx_k_GHOLEREMOVED[] = "GHOLEREMOVED";
static const char __pyx_k_INITPRESOLVE[] = "INITPRESOLVE";
static const char __pyx_k_LHOLEREMOVED[] = "LHOLEREMOVED";
static const char __pyx_k_NODEBRANCHED[] = "NODEBRANCHED";
static const char __pyx_k_NODEFEASIBLE[] = "NODEFEASIBLE";
static const char __pyx_k_PHASEIMPROVE[] = "PHASEIMPROVE";
static const char __pyx_k_POORSOLFOUND[] = "POORSOLFOUND";
static const char __pyx_k_PY_SCIP_CALL[] = "PY_SCIP_CALL";
static const char __pyx_k_RESTARTLIMIT[] = "RESTARTLIMIT";
static const char __pyx_k_ROWADDEDSEPA[] = "ROWADDEDSEPA";
static const char __pyx_k_ROWDELETEDLP[] = "ROWDELETEDLP";
static const char __pyx_k_TRANSFORMING[] = "TRANSFORMING";
static const char __pyx_k_UNBOUNDEDRAY[] = "UNBOUNDEDRAY";
static const char __pyx_k_addObjoffset[] = "addObjoffset";
static const char __pyx_k_allowaddcons[] = "allowaddcons";
static const char __pyx_k_avgdualbound[] = "avgdualbound";
static const char __pyx_k_branchexeclp[] = "branchexeclp";
static const char __pyx_k_branchexecps[] = "branchexecps";
static const char __pyx_k_chckpriority[] = "chckpriority";
static const char __pyx_k_col_cdeg_max[] = "col_cdeg_max";
static const char __pyx_k_col_cdeg_min[] = "col_cdeg_min";
static const char __pyx_k_col_cdeg_std[] = "col_cdeg_std";
static const char __pyx_k_col_ps_ratio[] = "col_ps_ratio";
static const char __pyx_k_col_type_int[] = "col_type_int";
static const char __pyx_k_cons_sum_abs[] = "cons_sum_abs";
static const char __pyx_k_cons_sum_neg[] = "cons_sum_neg";
static const char __pyx_k_cons_sum_pos[] = "cons_sum_pos";
static const char __pyx_k_consdeactive[] = "consdeactive";
static const char __pyx_k_consgetnvars[] = "consgetnvars";
static const char __pyx_k_enfopriority[] = "enfopriority";
static const char __pyx_k_eventexitsol[] = "eventexitsol";
static const char __pyx_k_eventinitsol[] = "eventinitsol";
static const char __pyx_k_expr_richcmp[] = "_expr_richcmp";
static const char __pyx_k_getSolObjVal[] = "getSolObjVal";
static const char __pyx_k_isModifiable[] = "isModifiable";
static const char __pyx_k_isPropagated[] = "isPropagated";
static const char __pyx_k_is_removable[] = "is_removable";
static const char __pyx_k_maxbounddist[] = "maxbounddist";
static const char __pyx_k_maxprerounds[] = "maxprerounds";
static const char __pyx_k_nactivesonss[] = "nactivesonss";
static const char __pyx_k_nb_up_infeas[] = "nb_up_infeas";
static const char __pyx_k_nchgvartypes[] = "nchgvartypes";
static const char __pyx_k_ncutsapplied[] = "ncutsapplied";
static const char __pyx_k_nmarkedconss[] = "nmarkedconss";
static const char __pyx_k_nnewaddconss[] = "nnewaddconss";
static const char __pyx_k_nnewaddholes[] = "nnewaddholes";
static const char __pyx_k_nnewaggrvars[] = "nnewaggrvars";
static const char __pyx_k_nnewchgcoefs[] = "nnewchgcoefs";
static const char __pyx_k_nnewchgsides[] = "nnewchgsides";
static const char __pyx_k_nnewdelconss[] = "nnewdelconss";
static const char __pyx_k_nnodeinitlps[] = "nnodeinitlps";
static const char __pyx_k_npricerounds[] = "npricerounds";
static const char __pyx_k_nsubproblems[] = "nsubproblems";
static const char __pyx_k_nusefulconss[] = "nusefulconss";
static const char __pyx_k_origprob_sol[] = "origprob.sol";
static const char __pyx_k_paraemphasis[] = "paraemphasis";
static const char __pyx_k_presoltiming[] = "presoltiming";
static const char __pyx_k_pricerfarkas[] = "pricerfarkas";
static const char __pyx_k_pyx_checksum[] = "__pyx_checksum";
static const char __pyx_k_relaxexitsol[] = "relaxexitsol";
static const char __pyx_k_relaxinitsol[] = "relaxinitsol";
static const char __pyx_k_sepapriority[] = "sepapriority";
static const char __pyx_k_setBoolParam[] = "setBoolParam";
static const char __pyx_k_sol_is_at_lb[] = "sol_is_at_lb";
static const char __pyx_k_sol_is_at_ub[] = "sol_is_at_ub";
static const char __pyx_k_stringsource[] = "stringsource";
static const char __pyx_k_version_info[] = "version_info";
static const char __pyx_k_AFTERLPPLUNGE[] = "AFTERLPPLUNGE";
static const char __pyx_k_AFTERPROPLOOP[] = "AFTERPROPLOOP";
static const char __pyx_k_FIRSTLPSOLVED[] = "FIRSTLPSOLVED";
static const char __pyx_k_IndicatorCons[] = "IndicatorCons";
static const char __pyx_k_Op_getOpIndex[] = "Op.getOpIndex";
static const char __pyx_k_PRESOLVEROUND[] = "PRESOLVEROUND";
static const char __pyx_k_PY_SCIP_STAGE[] = "PY_SCIP_STAGE";
static const char __pyx_k_StopIteration[] = "StopIteration";
static const char __pyx_k_USERINTERRUPT[] = "USERINTERRUPT";
static const char __pyx_k_avglowerbound[] = "avglowerbound";
static const char __pyx_k_bendersgetvar[] = "bendersgetvar";
static const char __pyx_k_branchexecext[] = "branchexecext";
static const char __pyx_k_branchexitsol[] = "branchexitsol";
static const char __pyx_k_branchinitsol[] = "branchinitsol";
static const char __pyx_k_col_cdeg_mean[] = "col_cdeg_mean";
static const char __pyx_k_col_coefs_neg[] = "col_coefs_neg";
static const char __pyx_k_col_coefs_pos[] = "col_coefs_pos";
static const char __pyx_k_col_nup_locks[] = "col_nup_locks";
static const char __pyx_k_col_red_costs[] = "col_red_costs";
static const char __pyx_k_cons_coef_max[] = "cons_coef_max";
static const char __pyx_k_cons_coef_min[] = "cons_coef_min";
static const char __pyx_k_cons_dual_sol[] = "cons_dual_sol";
static const char __pyx_k_consenforelax[] = "consenforelax";
static const char __pyx_k_dualboundroot[] = "dualboundroot";
static const char __pyx_k_enablepricing[] = "enablepricing";
static const char __pyx_k_expr_to_array[] = "expr_to_array";
static const char __pyx_k_expr_to_nodes[] = "expr_to_nodes";
static const char __pyx_k_indicator_arr[] = "indicator_arr";
static const char __pyx_k_interpolation[] = "interpolation";
static const char __pyx_k_is_modifiable[] = "is_modifiable";
static const char __pyx_k_maxtotaldepth[] = "maxtotaldepth";
static const char __pyx_k_ncreatednodes[] = "ncreatednodes";
static const char __pyx_k_nenabledconss[] = "nenabledconss";
static const char __pyx_k_nlimsolsfound[] = "nlimsolsfound";
static const char __pyx_k_nlpiterations[] = "nlpiterations";
static const char __pyx_k_nnewfixedvars[] = "nnewfixedvars";
static const char __pyx_k_nnewupgdconss[] = "nnewupgdconss";
static const char __pyx_k_nobjlimleaves[] = "nobjlimleaves";
static const char __pyx_k_objinfeasible[] = "objinfeasible";
static const char __pyx_k_presolexitpre[] = "presolexitpre";
static const char __pyx_k_presolinitpre[] = "presolinitpre";
static const char __pyx_k_pricerexitsol[] = "pricerexitsol";
static const char __pyx_k_pricerinitsol[] = "pricerinitsol";
static const char __pyx_k_pricerredcost[] = "pricerredcost";
static const char __pyx_k_reduce_cython[] = "__reduce_cython__";
static const char __pyx_k_root_cdeg_max[] = "root_cdeg_max";
static const char __pyx_k_root_cdeg_min[] = "root_cdeg_min";
static const char __pyx_k_root_cdeg_var[] = "root_cdeg_var";
static const char __pyx_k_solinfeasible[] = "solinfeasible";
static const char __pyx_k_userinterrupt[] = "userinterrupt";
static const char __pyx_k_NODEINFEASIBLE[] = "NODEINFEASIBLE";
static const char __pyx_k_PY_SCIP_RESULT[] = "PY_SCIP_RESULT";
static const char __pyx_k_PY_SCIP_STATUS[] = "PY_SCIP_STATUS";
static const char __pyx_k_ROWCOEFCHANGED[] = "ROWCOEFCHANGED";
static const char __pyx_k_ROWDELETEDSEPA[] = "ROWDELETEDSEPA";
static const char __pyx_k_ROWSIDECHANGED[] = "ROWSIDECHANGED";
static const char __pyx_k_STALLNODELIMIT[] = "STALLNODELIMIT";
static const char __pyx_k_TOTALNODELIMIT[] = "TOTALNODELIMIT";
static const char __pyx_k_Term___getitem[] = "Term.__getitem__";
static const char __pyx_k_avgcutoffscore[] = "avgcutoffscore";
static const char __pyx_k_benderscutexec[] = "benderscutexec";
static const char __pyx_k_benderscutexit[] = "benderscutexit";
static const char __pyx_k_benderscutfree[] = "benderscutfree";
static const char __pyx_k_benderscutinit[] = "benderscutinit";
static const char __pyx_k_bendersexitpre[] = "bendersexitpre";
static const char __pyx_k_bendersexitsol[] = "bendersexitsol";
static const char __pyx_k_bendersfreesub[] = "bendersfreesub";
static const char __pyx_k_bendersinitpre[] = "bendersinitpre";
static const char __pyx_k_bendersinitsol[] = "bendersinitsol";
static const char __pyx_k_cdeg_max_ratio[] = "cdeg_max_ratio";
static const char __pyx_k_cdeg_min_ratio[] = "cdeg_min_ratio";
static const char __pyx_k_col_ncoefs_max[] = "col_ncoefs_max";
static const char __pyx_k_col_ncoefs_min[] = "col_ncoefs_min";
static const char __pyx_k_col_ncoefs_std[] = "col_ncoefs_std";
static const char __pyx_k_col_ncoefs_sum[] = "col_ncoefs_sum";
static const char __pyx_k_col_pcoefs_max[] = "col_pcoefs_max";
static const char __pyx_k_col_pcoefs_min[] = "col_pcoefs_min";
static const char __pyx_k_col_pcoefs_std[] = "col_pcoefs_std";
static const char __pyx_k_col_pcoefs_sum[] = "col_pcoefs_sum";
static const char __pyx_k_col_ps_product[] = "col_ps_product";
static const char __pyx_k_col_sol_isfrac[] = "col_sol_isfrac";
static const char __pyx_k_cons_coef_mean[] = "cons_coef_mean";
static const char __pyx_k_defaultPlugins[] = "defaultPlugins";
static const char __pyx_k_frac_up_infeas[] = "frac_up_infeas";
static const char __pyx_k_lowerboundroot[] = "lowerboundroot";
static const char __pyx_k_nb_down_infeas[] = "nb_down_infeas";
static const char __pyx_k_nbestsolsfound[] = "nbestsolsfound";
static const char __pyx_k_ninternalnodes[] = "ninternalnodes";
static const char __pyx_k_nodeinfeasible[] = "nodeinfeasible";
static const char __pyx_k_nrhs_ratio_max[] = "nrhs_ratio_max";
static const char __pyx_k_nrhs_ratio_min[] = "nrhs_ratio_min";
static const char __pyx_k_nstrongbranchs[] = "nstrongbranchs";
static const char __pyx_k_origprob_stats[] = "origprob.stats";
static const char __pyx_k_presolpriority[] = "presolpriority";
static const char __pyx_k_prhs_ratio_max[] = "prhs_ratio_max";
static const char __pyx_k_prhs_ratio_min[] = "prhs_ratio_min";
static const char __pyx_k_pyscipopt_scip[] = "pyscipopt.scip";
static const char __pyx_k_root_cdeg_mean[] = "root_cdeg_mean";
static const char __pyx_k_stickingatnode[] = "stickingatnode";
static const char __pyx_k_str_conversion[] = "str_conversion";
static const char __pyx_k_value_to_array[] = "value_to_array";
static const char __pyx_k_AFTERPSEUDONODE[] = "AFTERPSEUDONODE";
static const char __pyx_k_CardinalityCons[] = "CardinalityCons";
static const char __pyx_k_ROWCONSTCHANGED[] = "ROWCONSTCHANGED";
static const char __pyx_k_SCIP_read_error[] = "SCIP: read error!";
static const char __pyx_k_benderssolvesub[] = "benderssolvesub";
static const char __pyx_k_buildGenExprObj[] = "buildGenExprObj";
static const char __pyx_k_cdeg_mean_ratio[] = "cdeg_mean_ratio";
static const char __pyx_k_col_ncoefs_mean[] = "col_ncoefs_mean";
static const char __pyx_k_col_ndown_locks[] = "col_ndown_locks";
static const char __pyx_k_col_pcoefs_mean[] = "col_pcoefs_mean";
static const char __pyx_k_col_sol_frac_up[] = "col_sol_frac_up";
static const char __pyx_k_col_type_binary[] = "col_type_binary";
static const char __pyx_k_cons_coef_stdev[] = "cons_coef_stdev";
static const char __pyx_k_cons_is_linking[] = "cons_is_linking";
static const char __pyx_k_cons_is_logicor[] = "cons_is_logicor";
static const char __pyx_k_createProbBasic[] = "createProbBasic";
static const char __pyx_k_inrepropagation[] = "inrepropagation";
static const char __pyx_k_is_memory_freed[] = "is_memory_freed";
static const char __pyx_k_memsavepriority[] = "memsavepriority";
static const char __pyx_k_mergecandidates[] = "mergecandidates";
static const char __pyx_k_nactivatednodes[] = "nactivatednodes";
static const char __pyx_k_ncutsfoundround[] = "ncutsfoundround";
static const char __pyx_k_ndelayedcutoffs[] = "ndelayedcutoffs";
static const char __pyx_k_ndualresolvelps[] = "ndualresolvelps";
static const char __pyx_k_nfeasibleleaves[] = "nfeasibleleaves";
static const char __pyx_k_nnewchgvartypes[] = "nnewchgvartypes";
static const char __pyx_k_npricevarsfound[] = "npricevarsfound";
static const char __pyx_k_npriomergecands[] = "npriomergecands";
static const char __pyx_k_overwrite_input[] = "overwrite_input";
static const char __pyx_k_presolmaxrounds[] = "presolmaxrounds";
static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError";
static const char __pyx_k_root_ncoefs_max[] = "root_ncoefs_max";
static const char __pyx_k_root_ncoefs_min[] = "root_ncoefs_min";
static const char __pyx_k_root_ncoefs_var[] = "root_ncoefs_var";
static const char __pyx_k_root_pcoefs_max[] = "root_pcoefs_max";
static const char __pyx_k_root_pcoefs_min[] = "root_pcoefs_min";
static const char __pyx_k_root_pcoefs_var[] = "root_pcoefs_var";
static const char __pyx_k_setstate_cython[] = "__setstate_cython__";
static const char __pyx_k_DURINGPRESOLLOOP[] = "DURINGPRESOLLOOP";
static const char __pyx_k_PY_SCIP_NODETYPE[] = "PY_SCIP_NODETYPE";
static const char __pyx_k_SCIP_write_error[] = "SCIP: write error!";
static const char __pyx_k_addNonlinearCons[] = "_addNonlinearCons";
static const char __pyx_k_avgconflictscore[] = "avgconflictscore";
static const char __pyx_k_benderscreatesub[] = "benderscreatesub";
static const char __pyx_k_benderspostsolve[] = "benderspostsolve";
static const char __pyx_k_checkintegrality[] = "checkintegrality";
static const char __pyx_k_cons_is_knapsack[] = "cons_is_knapsack";
static const char __pyx_k_firstprimalbound[] = "firstprimalbound";
static const char __pyx_k_frac_down_infeas[] = "frac_down_infeas";
static const char __pyx_k_isStickingAtNode[] = "isStickingAtNode";
static const char __pyx_k_isprimalboundsol[] = "isprimalboundsol";
static const char __pyx_k_ncreatednodesrun[] = "ncreatednodesrun";
static const char __pyx_k_operatorIndexDic[] = "operatorIndexDic";
static const char __pyx_k_root_ncoefs_mean[] = "root_ncoefs_mean";
static const char __pyx_k_root_pcoefs_mean[] = "root_pcoefs_mean";
static const char __pyx_k_AFTERPSEUDOPLUNGE[] = "AFTERPSEUDOPLUNGE";
static const char __pyx_k_DURINGPRICINGLOOP[] = "DURINGPRICINGLOOP";
static const char __pyx_k_PY_SCIP_BRANCHDIR[] = "PY_SCIP_BRANCHDIR";
static const char __pyx_k_PY_SCIP_EVENTTYPE[] = "PY_SCIP_EVENTTYPE";
static const char __pyx_k_PY_SCIP_LPSOLSTAT[] = "PY_SCIP_LPSOLSTAT";
static const char __pyx_k_ZeroDivisionError[] = "ZeroDivisionError";
static const char __pyx_k_avginferencescore[] = "avginferencescore";
static const char __pyx_k_benderscutexitsol[] = "benderscutexitsol";
static const char __pyx_k_benderscutinitsol[] = "benderscutinitsol";
static const char __pyx_k_col_sol_frac_down[] = "col_sol_frac_down";
static const char __pyx_k_cons_basis_status[] = "cons_basis_status";
static const char __pyx_k_cons_is_singleton[] = "cons_is_singleton";
static const char __pyx_k_consgetdivebdchgs[] = "consgetdivebdchgs";
static const char __pyx_k_deterministictime[] = "deterministictime";
static const char __pyx_k_getObjectiveSense[] = "getObjectiveSense";
static const char __pyx_k_ndeactivatednodes[] = "ndeactivatednodes";
static const char __pyx_k_nduallpiterations[] = "nduallpiterations";
static const char __pyx_k_ninfeasibleleaves[] = "ninfeasibleleaves";
static const char __pyx_k_nnodelpiterations[] = "nnodelpiterations";
static const char __pyx_k_npricevarsapplied[] = "npricevarsapplied";
static const char __pyx_k_nprimalresolvelps[] = "nprimalresolvelps";
static const char __pyx_k_nrootlpiterations[] = "nrootlpiterations";
static const char __pyx_k_opennodes_10quant[] = "opennodes_10quant";
static const char __pyx_k_opennodes_25quant[] = "opennodes_25quant";
static const char __pyx_k_opennodes_50quant[] = "opennodes_50quant";
static const char __pyx_k_opennodes_75quant[] = "opennodes_75quant";
static const char __pyx_k_opennodes_90quant[] = "opennodes_90quant";
static const char __pyx_k_pyx_unpickle_Expr[] = "__pyx_unpickle_Expr";
static const char __pyx_k_pyx_unpickle_Heur[] = "__pyx_unpickle_Heur";
static const char __pyx_k_pyx_unpickle_Prop[] = "__pyx_unpickle_Prop";
static const char __pyx_k_pyx_unpickle_Sepa[] = "__pyx_unpickle_Sepa";
static const char __pyx_k_root_ncoefs_count[] = "root_ncoefs_count";
static const char __pyx_k_root_pcoefs_count[] = "root_pcoefs_count";
static const char __pyx_k_PY_SCIP_HEURTIMING[] = "PY_SCIP_HEURTIMING";
static const char __pyx_k_PY_SCIP_PROPTIMING[] = "PY_SCIP_PROPTIMING";
static const char __pyx_k_avgpseudocostscore[] = "avgpseudocostscore";
static const char __pyx_k_benderspresubsolve[] = "benderspresubsolve";
static const char __pyx_k_cannot_divide_by_0[] = "cannot divide by 0";
static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback";
static const char __pyx_k_col_nlhs_ratio_max[] = "col_nlhs_ratio_max";
static const char __pyx_k_col_nlhs_ratio_min[] = "col_nlhs_ratio_min";
static const char __pyx_k_col_nrhs_ratio_max[] = "col_nrhs_ratio_max";
static const char __pyx_k_col_nrhs_ratio_min[] = "col_nrhs_ratio_min";
static const char __pyx_k_col_plhs_ratio_max[] = "col_plhs_ratio_max";
static const char __pyx_k_col_plhs_ratio_min[] = "col_plhs_ratio_min";
static const char __pyx_k_col_prhs_ratio_max[] = "col_prhs_ratio_max";
static const char __pyx_k_col_prhs_ratio_min[] = "col_prhs_ratio_min";
static const char __pyx_k_cons_is_precedence[] = "cons_is_precedence";
static const char __pyx_k_effectiverootdepth[] = "effectiverootdepth";
static const char __pyx_k_getTransformedCons[] = "getTransformedCons";
static const char __pyx_k_nrootstrongbranchs[] = "nrootstrongbranchs";
static const char __pyx_k_pyx_unpickle_Relax[] = "__pyx_unpickle_Relax";
static const char __pyx_k_NotImplementedError[] = "NotImplementedError";
static const char __pyx_k_addGenNonlinearCons[] = "_addGenNonlinearCons";
static const char __pyx_k_cons_is_aggregation[] = "cons_is_aggregation";
static const char __pyx_k_cons_is_cardinality[] = "cons_is_cardinality";
static const char __pyx_k_nconflictconssfound[] = "nconflictconssfound";
static const char __pyx_k_ndivinglpiterations[] = "ndivinglpiterations";
static const char __pyx_k_nprimallpiterations[] = "nprimallpiterations";
static const char __pyx_k_print_memory_in_use[] = "print_memory_in_use";
static const char __pyx_k_pyx_unpickle_Presol[] = "__pyx_unpickle_Presol";
static const char __pyx_k_pyx_unpickle_Pricer[] = "__pyx_unpickle_Pricer";
static const char __pyx_k_PY_SCIP_PARAMSETTING[] = "PY_SCIP_PARAMSETTING";
static const char __pyx_k_PY_SCIP_PRESOLTIMING[] = "PY_SCIP_PRESOLTIMING";
static const char __pyx_k_firstlpdualboundroot[] = "firstlpdualboundroot";
static const char __pyx_k_nbarrierlpiterations[] = "nbarrierlpiterations";
static const char __pyx_k_nresolvelpiterations[] = "nresolvelpiterations";
static const char __pyx_k_pyx_unpickle_Benders[] = "__pyx_unpickle_Benders";
static const char __pyx_k_pyx_unpickle_GenExpr[] = "__pyx_unpickle_GenExpr";
static const char __pyx_k_pyx_unpickle_Nodesel[] = "__pyx_unpickle_Nodesel";
static const char __pyx_k_pyx_unpickle_PowExpr[] = "__pyx_unpickle_PowExpr";
static const char __pyx_k_pyx_unpickle_SumExpr[] = "__pyx_unpickle_SumExpr";
static const char __pyx_k_pyx_unpickle_VarExpr[] = "__pyx_unpickle_VarExpr";
static const char __pyx_k_repr___locals_lambda[] = "__repr__.<locals>.<lambda>";
static const char __pyx_k_PY_SCIP_PARAMEMPHASIS[] = "PY_SCIP_PARAMEMPHASIS";
static const char __pyx_k_avgconfliclengthscore[] = "avgconfliclengthscore";
static const char __pyx_k_benderssolvesubconvex[] = "benderssolvesubconvex";
static const char __pyx_k_degree_locals_genexpr[] = "degree.<locals>.genexpr";
static const char __pyx_k_firstlplowerboundroot[] = "firstlplowerboundroot";
static const char __pyx_k_includeDefaultPlugins[] = "includeDefaultPlugins";
static const char __pyx_k_nconflictconssapplied[] = "nconflictconssapplied";
static const char __pyx_k_nnodeinitlpiterations[] = "nnodeinitlpiterations";
static const char __pyx_k_propagating_maxrounds[] = "propagating/maxrounds";
static const char __pyx_k_pyx_unpickle_Conshdlr[] = "__pyx_unpickle_Conshdlr";
static const char __pyx_k_pyx_unpickle_Constant[] = "__pyx_unpickle_Constant";
static const char __pyx_k_pyx_unpickle_ExprCons[] = "__pyx_unpickle_ExprCons";
static const char __pyx_k_pyx_unpickle_ProdExpr[] = "__pyx_unpickle_ProdExpr";
static const char __pyx_k_wrote_problem_to_file[] = "wrote problem to file ";
static const char __pyx_k_SCIP_no_problem_exists[] = "SCIP: no problem exists!";
static const char __pyx_k_SCIP_unspecified_error[] = "SCIP: unspecified error!";
static const char __pyx_k_addCols_locals_genexpr[] = "addCols.<locals>.genexpr";
static const char __pyx_k_addRows_locals_genexpr[] = "addRows.<locals>.genexpr";
static const char __pyx_k_cons_is_general_linear[] = "cons_is_general_linear";
static const char __pyx_k_cons_is_variable_bound[] = "cons_is_variable_bound";
static const char __pyx_k_nrootfirstlpiterations[] = "nrootfirstlpiterations";
static const char __pyx_k_pyx_unpickle_Eventhdlr[] = "__pyx_unpickle_Eventhdlr";
static const char __pyx_k_pyx_unpickle_UnaryExpr[] = "__pyx_unpickle_UnaryExpr";
static const char __pyx_k_src_pyscipopt_expr_pxi[] = "src/pyscipopt/expr.pxi";
static const char __pyx_k_src_pyscipopt_scip_pyx[] = "src/pyscipopt/scip.pyx";
static const char __pyx_k_PY_SCIP_BENDERSENFOTYPE[] = "PY_SCIP_BENDERSENFOTYPE";
static const char __pyx_k_SCIP_cannot_create_file[] = "SCIP: cannot create file!";
static const char __pyx_k_SCIP_error_in_LP_solver[] = "SCIP: error in LP solver!";
static const char __pyx_k_This_is_a_monomial_term[] = "This is a monomial term";
static const char __pyx_k_col_coef_max3_dual_cost[] = "col_coef_max3_dual_cost";
static const char __pyx_k_col_coef_min3_dual_cost[] = "col_coef_min3_dual_cost";
static const char __pyx_k_col_coef_std3_dual_cost[] = "col_coef_std3_dual_cost";
static const char __pyx_k_col_coef_sum3_dual_cost[] = "col_coef_sum3_dual_cost";
static const char __pyx_k_event_handler_not_found[] = "event handler not found";
static const char __pyx_k_nconflictconssfoundnode[] = "nconflictconssfoundnode";
static const char __pyx_k_pyx_unpickle_Benderscut[] = "__pyx_unpickle_Benderscut";
static const char __pyx_k_pyx_unpickle_Branchrule[] = "__pyx_unpickle_Branchrule";
static const char __pyx_k_SCIP_error_in_input_data[] = "SCIP: error in input data!";
static const char __pyx_k_SCIP_unknown_return_code[] = "SCIP: unknown return code!";
static const char __pyx_k_avgcuroffscorecurrentrun[] = "avgcuroffscorecurrentrun";
static const char __pyx_k_col_coef_mean3_dual_cost[] = "col_coef_mean3_dual_cost";
static const char __pyx_k_ndualresolvelpiterations[] = "ndualresolvelpiterations";
static const char __pyx_k_SCIP_file_not_found_error[] = "SCIP: file not found error!";
static const char __pyx_k_col_coef_max1_unit_weight[] = "col_coef_max1_unit_weight";
static const char __pyx_k_col_coef_max2_inverse_sum[] = "col_coef_max2_inverse_sum";
static const char __pyx_k_col_coef_min1_unit_weight[] = "col_coef_min1_unit_weight";
static const char __pyx_k_col_coef_min2_inverse_sum[] = "col_coef_min2_inverse_sum";
static const char __pyx_k_col_coef_std1_unit_weight[] = "col_coef_std1_unit_weight";
static const char __pyx_k_col_coef_std2_inverse_sum[] = "col_coef_std2_inverse_sum";
static const char __pyx_k_col_coef_sum1_unit_weight[] = "col_coef_sum1_unit_weight";
static const char __pyx_k_col_coef_sum2_inverse_sum[] = "col_coef_sum2_inverse_sum";
static const char __pyx_k_exponents_must_be_numbers[] = "exponents must be numbers";
static const char __pyx_k_nstrongbranchlpiterations[] = "nstrongbranchlpiterations";
static const char __pyx_k_propagating_maxroundsroot[] = "propagating/maxroundsroot";
static const char __pyx_k_Not_a_valid_parameter_name[] = "Not a valid parameter name";
static const char __pyx_k_avgconflictscorecurrentrun[] = "avgconflictscorecurrentrun";
static const char __pyx_k_col_coef_mean1_unit_weight[] = "col_coef_mean1_unit_weight";
static const char __pyx_k_col_coef_mean2_inverse_sum[] = "col_coef_mean2_inverse_sum";
static const char __pyx_k_constraints_benders_active[] = "constraints/benders/active";
static const char __pyx_k_nprimalresolvelpiterations[] = "nprimalresolvelpiterations";
static const char __pyx_k_pyx_unpickle_PY_SCIP_STAGE[] = "__pyx_unpickle_PY_SCIP_STAGE";
static const char __pyx_k_unrecognized_variable_type[] = "unrecognized variable type";
static const char __pyx_k_Term___init___locals_lambda[] = "Term.__init__.<locals>.<lambda>";
static const char __pyx_k_avginferencescorecurrentrun[] = "avginferencescorecurrentrun";
static const char __pyx_k_constraint_is_not_quadratic[] = "constraint is not quadratic";
static const char __pyx_k_pyx_unpickle_PY_SCIP_RESULT[] = "__pyx_unpickle_PY_SCIP_RESULT";
static const char __pyx_k_pyx_unpickle_PY_SCIP_STATUS[] = "__pyx_unpickle_PY_SCIP_STATUS";
static const char __pyx_k_Term___init___locals_genexpr[] = "Term.__init__.<locals>.genexpr";
static const char __pyx_k_avgpseudocostscorecurrentrun[] = "avgpseudocostscorecurrentrun";
static const char __pyx_k_constraints_benderslp_active[] = "constraints/benderslp/active";
static const char __pyx_k_unrecognized_objective_sense[] = "unrecognized objective sense";
static const char __pyx_k_nrootstrongbranchlpiterations[] = "nrootstrongbranchlpiterations";
static const char __pyx_k_pyx_unpickle_PY_SCIP_NODETYPE[] = "__pyx_unpickle_PY_SCIP_NODETYPE";
static const char __pyx_k_Error_branching_rule_not_found[] = "Error, branching rule not found!";
static const char __pyx_k_SCIP_insufficient_memory_error[] = "SCIP: insufficient memory error!";
static const char __pyx_k_pyx_unpickle_PY_SCIP_BENDERSEN[] = "__pyx_unpickle_PY_SCIP_BENDERSENFOTYPE";
static const char __pyx_k_pyx_unpickle_PY_SCIP_BRANCHDIR[] = "__pyx_unpickle_PY_SCIP_BRANCHDIR";
static const char __pyx_k_pyx_unpickle_PY_SCIP_EVENTTYPE[] = "__pyx_unpickle_PY_SCIP_EVENTTYPE";
static const char __pyx_k_pyx_unpickle_PY_SCIP_HEURTIMIN[] = "__pyx_unpickle_PY_SCIP_HEURTIMING";
static const char __pyx_k_pyx_unpickle_PY_SCIP_LPSOLSTAT[] = "__pyx_unpickle_PY_SCIP_LPSOLSTAT";
static const char __pyx_k_pyx_unpickle_PY_SCIP_PARAMEMPH[] = "__pyx_unpickle_PY_SCIP_PARAMEMPHASIS";
static const char __pyx_k_pyx_unpickle_PY_SCIP_PARAMSETT[] = "__pyx_unpickle_PY_SCIP_PARAMSETTING";
static const char __pyx_k_pyx_unpickle_PY_SCIP_PRESOLTIM[] = "__pyx_unpickle_PY_SCIP_PRESOLTIMING";
static const char __pyx_k_pyx_unpickle_PY_SCIP_PROPTIMIN[] = "__pyx_unpickle_PY_SCIP_PROPTIMING";
static const char __pyx_k_Provide_BOOLEAN_value_as_rhsvar[] = "Provide BOOLEAN value as rhsvar, you gave %s.";
static const char __pyx_k_SCIP_method_cannot_be_called_at[] = "SCIP: method cannot be called at this time in solution process!";
static const char __pyx_k_SCIP_method_returned_an_invalid[] = "SCIP: method returned an invalid result code!";
static const char __pyx_k_SCIP_reading_solution_from_file[] = "SCIP: reading solution from file failed!";
static const char __pyx_k_avgconfliclengthscorecurrentrun[] = "avgconfliclengthscorecurrentrun";
static const char __pyx_k_given_coefficients_are_not_Expr[] = "given coefficients are not Expr but %s";
static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import";
static const char __pyx_k_python_error_in_consenfolp_this[] = "python error in consenfolp: this method needs to be implemented";
static const char __pyx_k_python_error_in_consenfops_this[] = "python error in consenfops: this method needs to be implemented";
static const char __pyx_k_python_error_in_presolexec_this[] = "python error in presolexec: this method needs to be implemented";
static const char __pyx_k_self_lpi_cannot_be_converted_to[] = "self.lpi cannot be converted to a Python object for pickling";
static const char __pyx_k_self_sol_cannot_be_converted_to[] = "self.sol cannot be converted to a Python object for pickling";
static const char __pyx_k_total_number_of_solutions_found[] = "total number of solutions found is not valid!";
static const char __pyx_k_unrecognized_optimization_sense[] = "unrecognized optimization sense: %s";
static const char __pyx_k_Can_t_evaluate_constraints_as_bo[] = "Can't evaluate constraints as booleans.\n\nIf you want to add a ranged constraint of the form\n lhs <= expression <= rhs\nyou have to use parenthesis to break the Python syntax for chained comparisons:\n lhs <= (expression <= rhs)\n";
static const char __pyx_k_Constant_offsets_in_objective_ar[] = "Constant offsets in objective are not supported!";
static const char __pyx_k_ExprCons_already_has_lower_bound[] = "ExprCons already has lower bound";
static const char __pyx_k_ExprCons_already_has_upper_bound[] = "ExprCons already has upper bound";
static const char __pyx_k_Incompatible_checksums_s_vs_0x20[] = "Incompatible checksums (%s vs 0x20f35e6 = (model))";
static const char __pyx_k_Incompatible_checksums_s_vs_0x6f[] = "Incompatible checksums (%s vs 0x6f493bf = (terms))";
static const char __pyx_k_Incompatible_checksums_s_vs_0x88[] = "Incompatible checksums (%s vs 0x8819c6a = (_op, children, coefs, constant, operatorIndex))";
static const char __pyx_k_Incompatible_checksums_s_vs_0x8f[] = "Incompatible checksums (%s vs 0x8f4795b = (_lhs, _rhs, expr))";
static const char __pyx_k_Incompatible_checksums_s_vs_0x9b[] = "Incompatible checksums (%s vs 0x9b4da82 = (_op, children, constant, operatorIndex))";
static const char __pyx_k_Incompatible_checksums_s_vs_0xa0[] = "Incompatible checksums (%s vs 0xa0ceb6e = (_op, children, operatorIndex, var))";
static const char __pyx_k_Incompatible_checksums_s_vs_0xb3[] = "Incompatible checksums (%s vs 0xb3bb9c2 = (_op, children, expo, operatorIndex))";
static const char __pyx_k_Incompatible_checksums_s_vs_0xba[] = "Incompatible checksums (%s vs 0xbaa8c6e = (_op, children, operatorIndex))";
static const char __pyx_k_Incompatible_checksums_s_vs_0xd4[] = "Incompatible checksums (%s vs 0xd41d8cd = ())";
static const char __pyx_k_Incompatible_checksums_s_vs_0xec[] = "Incompatible checksums (%s vs 0xecd383d = (model, name))";
static const char __pyx_k_Incompatible_checksums_s_vs_0xfe[] = "Incompatible checksums (%s vs 0xfeb2b21 = (_op, children, number, operatorIndex))";
static const char __pyx_k_Nonlinear_objective_functions_ar[] = "Nonlinear objective functions are not supported!";
static const char __pyx_k_Ranged_ExprCons_is_not_well_defi[] = "Ranged ExprCons is not well defined!";
static const char __pyx_k_SCIP_a_required_plugin_was_not_f[] = "SCIP: a required plugin was not found !";
static const char __pyx_k_SCIP_maximal_branching_depth_lev[] = "SCIP: maximal branching depth level exceeded!";
static const char __pyx_k_SCIP_returned_base_status_zero_f[] = "SCIP returned base status zero for a row!";
static const char __pyx_k_SCIP_returned_unknown_base_statu[] = "SCIP returned unknown base status!";
static const char __pyx_k_SCIP_the_given_key_is_already_ex[] = "SCIP: the given key is already existing in table!";
static const char __pyx_k_SCIP_the_parameter_is_not_of_the[] = "SCIP: the parameter is not of the expected type!";
static const char __pyx_k_SCIP_the_parameter_with_the_give[] = "SCIP: the parameter with the given name was not found!";
static const char __pyx_k_SCIP_the_value_is_invalid_for_th[] = "SCIP: the value is invalid for the given parameter!";
static const char __pyx_k_cannot_create_Constraint_with_SC[] = "cannot create Constraint with SCIP_CONS* == NULL";
static const char __pyx_k_coefficients_not_available_for_c[] = "coefficients not available for constraints of type ";
static const char __pyx_k_could_not_change_variable_type_o[] = "could not change variable type of variable %s";
static const char __pyx_k_dual_solution_values_not_availab[] = "dual solution values not available for constraints of type ";
static const char __pyx_k_expected_inequality_that_has_eit[] = "expected inequality that has either only a left or right hand side";
static const char __pyx_k_expected_linear_inequality_expre[] = "expected linear inequality, expression has degree %d";
static const char __pyx_k_given_coefficients_are_neither_E[] = "given coefficients are neither Expr or number but %s";
static const char __pyx_k_given_constraint_is_not_ExprCons[] = "given constraint is not ExprCons but %s";
static const char __pyx_k_given_constraint_is_not_linear_d[] = "given constraint is not linear, degree == %d";
static const char __pyx_k_given_constraint_is_not_quadrati[] = "given constraint is not quadratic, degree == %d";
static const char __pyx_k_linked_SCIP_is_not_compatible_to[] = "linked SCIP is not compatible to this version of PySCIPOpt - use at least version";
static const char __pyx_k_linked_SCIP_is_not_recommended_f[] = "linked SCIP {} is not recommended for this version of PySCIPOpt - use version {}.{}.{}";
static const char __pyx_k_method_cannot_be_called_before_p[] = "method cannot be called before problem is solved";
static const char __pyx_k_method_cannot_be_called_for_cons[] = "method cannot be called for constraints of type ";
static const char __pyx_k_no_dual_solution_available_for_c[] = "no dual solution available for constraint ";
static const char __pyx_k_no_reduced_cost_available_for_va[] = "no reduced cost available for variable ";
static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import";
static const char __pyx_k_python_error_in_benderscreatesub[] = "python error in benderscreatesub: this method needs to be implemented";
static const char __pyx_k_python_error_in_benderscutexec_t[] = "python error in benderscutexec: this method needs to be implemented";
static const char __pyx_k_python_error_in_bendersgetvar_th[] = "python error in bendersgetvar: this method needs to be implemented";
static const char __pyx_k_python_error_in_conscheck_this_m[] = "python error in conscheck: this method needs to be implemented";
static const char __pyx_k_python_error_in_consenforelax_th[] = "python error in consenforelax: this method needs to be implemented";
static const char __pyx_k_python_error_in_conslock_this_me[] = "python error in conslock: this method needs to be implemented";
static const char __pyx_k_python_error_in_eventexec_this_m[] = "python error in eventexec: this method needs to be implemented";
static const char __pyx_k_python_error_in_heurexec_this_me[] = "python error in heurexec: this method needs to be implemented";
static const char __pyx_k_python_error_in_pricerredcost_th[] = "python error in pricerredcost: this method needs to be implemented";
static const char __pyx_k_python_error_in_propexec_this_me[] = "python error in propexec: this method needs to be implemented";
static const char __pyx_k_python_error_in_propresprop_this[] = "python error in propresprop: this method needs to be implemented";
static const char __pyx_k_python_error_in_relaxexec_this_m[] = "python error in relaxexec: this method needs to be implemented";
static const char __pyx_k_self__scip_self__valid_cannot_be[] = "self._scip,self._valid cannot be converted to a Python object for pickling";
static const char __pyx_k_self_event_cannot_be_converted_t[] = "self.event cannot be converted to a Python object for pickling";
static const char __pyx_k_self_scip_col_cannot_be_converte[] = "self.scip_col cannot be converted to a Python object for pickling";
static const char __pyx_k_self_scip_cons_cannot_be_convert[] = "self.scip_cons cannot be converted to a Python object for pickling";
static const char __pyx_k_self_scip_node_cannot_be_convert[] = "self.scip_node cannot be converted to a Python object for pickling";
static const char __pyx_k_self_scip_row_cannot_be_converte[] = "self.scip_row cannot be converted to a Python object for pickling";
static const char __pyx_k_self_scip_var_cannot_be_converte[] = "self.scip_var cannot be converted to a Python object for pickling";
static const char __pyx_k_term_length_must_be_1_or_2_but_i[] = "term length must be 1 or 2 but it is %s";
static const char __pyx_k_wrote_parameter_settings_to_file[] = "wrote parameter settings to file ";
static const char __pyx_k_Incompatible_checksums_s_vs_0xfe_2[] = "Incompatible checksums (%s vs 0xfef88e0 = (benders, model, name))";
static PyObject *__pyx_kp_u_;
static PyObject *__pyx_n_s_AFTERLPLOOP;
static PyObject *__pyx_n_s_AFTERLPNODE;
static PyObject *__pyx_n_s_AFTERLPPLUNGE;
static PyObject *__pyx_n_s_AFTERPROPLOOP;
static PyObject *__pyx_n_s_AFTERPSEUDONODE;
static PyObject *__pyx_n_s_AFTERPSEUDOPLUNGE;
static PyObject *__pyx_n_s_AGGRESSIVE;
static PyObject *__pyx_n_u_ANDcons;
static PyObject *__pyx_n_s_AUTO;
static PyObject *__pyx_n_u_B;
static PyObject *__pyx_n_s_BEFORELP;
static PyObject *__pyx_n_s_BEFORENODE;
static PyObject *__pyx_n_s_BEFOREPRESOL;
static PyObject *__pyx_n_s_BESTSOLFOUND;
static PyObject *__pyx_n_s_BESTSOLLIMIT;
static PyObject *__pyx_n_u_BINARY;
static PyObject *__pyx_n_s_BRANCHED;
static PyObject *__pyx_n_s_Benders;
static PyObject *__pyx_n_s_Benderscut;
static PyObject *__pyx_n_s_Branchrule;
static PyObject *__pyx_n_u_C;
static PyObject *__pyx_n_s_CHECK;
static PyObject *__pyx_n_s_CHILD;
static PyObject *__pyx_n_s_CONSADDED;
static PyObject *__pyx_n_s_CONSCHANGED;
static PyObject *__pyx_n_s_CONST;
static PyObject *__pyx_n_u_CONTINUOUS;
static PyObject *__pyx_n_s_COUNTER;
static PyObject *__pyx_n_s_CPSOLVER;
static PyObject *__pyx_n_s_CUTOFF;
static PyObject *__pyx_kp_u_Can_t_evaluate_constraints_as_bo;
static PyObject *__pyx_n_u_CardinalityCons;
static PyObject *__pyx_n_s_Column;
static PyObject *__pyx_n_s_Conshdlr;
static PyObject *__pyx_n_s_Constant;
static PyObject *__pyx_kp_u_Constant_offsets_in_objective_ar;
static PyObject *__pyx_n_s_Constraint;
static PyObject *__pyx_n_s_DEADEND;
static PyObject *__pyx_n_s_DEFAULT;
static PyObject *__pyx_n_s_DELAYED;
static PyObject *__pyx_n_s_DIDNOTFIND;
static PyObject *__pyx_n_s_DIDNOTRUN;
static PyObject *__pyx_n_s_DISABLED;
static PyObject *__pyx_n_s_DOWNWARDS;
static PyObject *__pyx_n_s_DURINGLPLOOP;
static PyObject *__pyx_n_s_DURINGPRESOLLOOP;
static PyObject *__pyx_n_s_DURINGPRICINGLOOP;
static PyObject *__pyx_n_s_EASYCIP;
static PyObject *__pyx_n_s_ERROR;
static PyObject *__pyx_n_s_EXHAUSTIVE;
static PyObject *__pyx_n_s_EXITPRESOLVE;
static PyObject *__pyx_n_s_EXITSOLVE;
static PyObject *__pyx_kp_u_Error_branching_rule_not_found;
static PyObject *__pyx_n_s_Event;
static PyObject *__pyx_n_s_Eventhdlr;
static PyObject *__pyx_n_s_Expr;
static PyObject *__pyx_kp_u_ExprCons;
static PyObject *__pyx_n_s_ExprCons_2;
static PyObject *__pyx_kp_u_ExprCons_already_has_lower_bound;
static PyObject *__pyx_kp_u_ExprCons_already_has_upper_bound;
static PyObject *__pyx_kp_u_Expr_s;
static PyObject *__pyx_n_s_FAST;
static PyObject *__pyx_n_s_FEASIBILITY;
static PyObject *__pyx_n_s_FEASIBLE;
static PyObject *__pyx_n_s_FIRSTLPSOLVED;
static PyObject *__pyx_n_s_FIXED;
static PyObject *__pyx_n_s_FOCUSNODE;
static PyObject *__pyx_n_s_FORK;
static PyObject *__pyx_n_s_FOUNDSOL;
static PyObject *__pyx_n_s_FREE;
static PyObject *__pyx_n_s_FREETRANS;
static PyObject *__pyx_n_s_GAPLIMIT;
static PyObject *__pyx_n_s_GHOLEADDED;
static PyObject *__pyx_n_s_GHOLEREMOVED;
static PyObject *__pyx_n_s_GLBCHANGED;
static PyObject *__pyx_n_s_GUBCHANGED;
static PyObject *__pyx_n_s_GenExpr;
static PyObject *__pyx_n_s_HARDLP;
static PyObject *__pyx_n_s_Heur;
static PyObject *__pyx_n_u_I;
static PyObject *__pyx_n_s_IMPLADDED;
static PyObject *__pyx_n_s_INFEASIBLE;
static PyObject *__pyx_n_s_INFORUNBD;
static PyObject *__pyx_n_s_INIT;
static PyObject *__pyx_n_s_INITPRESOLVE;
static PyObject *__pyx_n_s_INITSOLVE;
static PyObject *__pyx_n_u_INTEGER;
static PyObject *__pyx_n_s_IOError;
static PyObject *__pyx_n_s_ITERLIMIT;
static PyObject *__pyx_n_s_ImportError;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x20;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x6f;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x88;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x8f;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x9b;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xa0;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb3;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xba;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xd4;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xec;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xfe;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xfe_2;
static PyObject *__pyx_n_u_IndicatorCons;
static PyObject *__pyx_n_s_JUNCTION;
static PyObject *__pyx_n_s_KeyError;
static PyObject *__pyx_n_s_LBRELAXED;
static PyObject *__pyx_n_s_LBTIGHTENED;
static PyObject *__pyx_n_s_LEAF;
static PyObject *__pyx_n_s_LHOLEADDED;
static PyObject *__pyx_n_s_LHOLEREMOVED;
static PyObject *__pyx_n_s_LP;
static PyObject *__pyx_n_u_LP;
static PyObject *__pyx_n_s_LPEVENT;
static PyObject *__pyx_n_s_LPSOLVED;
static PyObject *__pyx_n_s_LookupError;
static PyObject *__pyx_n_s_MAJOR;
static PyObject *__pyx_n_s_MEDIUM;
static PyObject *__pyx_n_s_MEMLIMIT;
static PyObject *__pyx_n_s_MINOR;
static PyObject *__pyx_n_s_MemoryError;
static PyObject *__pyx_n_s_Model;
static PyObject *__pyx_n_s_NEWROUND;
static PyObject *__pyx_n_s_NODEBRANCHED;
static PyObject *__pyx_n_s_NODEFEASIBLE;
static PyObject *__pyx_n_s_NODEFOCUSED;
static PyObject *__pyx_n_s_NODEINFEASIBLE;
static PyObject *__pyx_n_s_NODELIMIT;
static PyObject *__pyx_n_s_NONE;
static PyObject *__pyx_n_s_NOTSOLVED;
static PyObject *__pyx_n_s_Node;
static PyObject *__pyx_n_s_Nodesel;
static PyObject *__pyx_kp_u_Nonlinear_objective_functions_ar;
static PyObject *__pyx_n_s_NotImplementedError;
static PyObject *__pyx_kp_u_Not_a_valid_parameter_name;
static PyObject *__pyx_n_s_OBJCHANGED;
static PyObject *__pyx_n_s_OBJLIMIT;
static PyObject *__pyx_n_s_OFF;
static PyObject *__pyx_n_s_OPTIMAL;
static PyObject *__pyx_n_s_OPTIMALITY;
static PyObject *__pyx_n_u_ORcons;
static PyObject *__pyx_n_s_Op;
static PyObject *__pyx_n_s_Op_getOpIndex;
static PyObject *__pyx_n_s_Operator;
static PyObject *__pyx_n_s_PATCH;
static PyObject *__pyx_n_s_PHASEFEAS;
static PyObject *__pyx_n_s_PHASEIMPROVE;
static PyObject *__pyx_n_s_PHASEPROOF;
static PyObject *__pyx_n_s_POORSOLFOUND;
static PyObject *__pyx_n_s_PRESOLVED;
static PyObject *__pyx_n_s_PRESOLVEROUND;
static PyObject *__pyx_n_s_PRESOLVING;
static PyObject *__pyx_n_s_PROBINGNODE;
static PyObject *__pyx_n_s_PROBLEM;
static PyObject *__pyx_n_s_PSEUDO;
static PyObject *__pyx_n_s_PSEUDOFORK;
static PyObject *__pyx_n_s_PY_SCIP_BENDERSENFOTYPE;
static PyObject *__pyx_n_s_PY_SCIP_BRANCHDIR;
static PyObject *__pyx_n_s_PY_SCIP_CALL;
static PyObject *__pyx_n_s_PY_SCIP_EVENTTYPE;
static PyObject *__pyx_n_s_PY_SCIP_HEURTIMING;
static PyObject *__pyx_n_s_PY_SCIP_LPSOLSTAT;
static PyObject *__pyx_n_s_PY_SCIP_NODETYPE;
static PyObject *__pyx_n_s_PY_SCIP_PARAMEMPHASIS;
static PyObject *__pyx_n_s_PY_SCIP_PARAMSETTING;
static PyObject *__pyx_n_s_PY_SCIP_PRESOLTIMING;
static PyObject *__pyx_n_s_PY_SCIP_PROPTIMING;
static PyObject *__pyx_n_s_PY_SCIP_RESULT;
static PyObject *__pyx_n_s_PY_SCIP_STAGE;
static PyObject *__pyx_n_s_PY_SCIP_STATUS;
static PyObject *__pyx_n_s_PickleError;
static PyObject *__pyx_n_s_PowExpr;
static PyObject *__pyx_n_s_Presol;
static PyObject *__pyx_n_s_Pricer;
static PyObject *__pyx_n_s_ProdExpr;
static PyObject *__pyx_n_s_Prop;
static PyObject *__pyx_kp_u_Provide_BOOLEAN_value_as_rhsvar;
static PyObject *__pyx_n_s_REDUCEDDOM;
static PyObject *__pyx_n_s_REFOCUSNODE;
static PyObject *__pyx_n_s_RELAX;
static PyObject *__pyx_n_s_RESTARTLIMIT;
static PyObject *__pyx_n_s_ROWADDEDLP;
static PyObject *__pyx_n_s_ROWADDEDSEPA;
static PyObject *__pyx_n_s_ROWCOEFCHANGED;
static PyObject *__pyx_n_s_ROWCONSTCHANGED;
static PyObject *__pyx_n_s_ROWDELETEDLP;
static PyObject *__pyx_n_s_ROWDELETEDSEPA;
static PyObject *__pyx_n_s_ROWSIDECHANGED;
static PyObject *__pyx_kp_u_Ranged_ExprCons_is_not_well_defi;
static PyObject *__pyx_n_s_Relax;
static PyObject *__pyx_n_s_Row;
static PyObject *__pyx_kp_u_SCIP_a_required_plugin_was_not_f;
static PyObject *__pyx_kp_u_SCIP_cannot_create_file;
static PyObject *__pyx_kp_u_SCIP_error_in_LP_solver;
static PyObject *__pyx_kp_u_SCIP_error_in_input_data;
static PyObject *__pyx_kp_u_SCIP_file_not_found_error;
static PyObject *__pyx_kp_u_SCIP_insufficient_memory_error;
static PyObject *__pyx_kp_u_SCIP_maximal_branching_depth_lev;
static PyObject *__pyx_kp_u_SCIP_method_cannot_be_called_at;
static PyObject *__pyx_kp_u_SCIP_method_returned_an_invalid;
static PyObject *__pyx_kp_u_SCIP_no_problem_exists;
static PyObject *__pyx_kp_u_SCIP_read_error;
static PyObject *__pyx_kp_u_SCIP_reading_solution_from_file;
static PyObject *__pyx_kp_u_SCIP_returned_base_status_zero_f;
static PyObject *__pyx_kp_u_SCIP_returned_unknown_base_statu;
static PyObject *__pyx_kp_u_SCIP_the_given_key_is_already_ex;
static PyObject *__pyx_kp_u_SCIP_the_parameter_is_not_of_the;
static PyObject *__pyx_kp_u_SCIP_the_parameter_with_the_give;
static PyObject *__pyx_kp_u_SCIP_the_value_is_invalid_for_th;
static PyObject *__pyx_kp_u_SCIP_unknown_return_code;
static PyObject *__pyx_kp_u_SCIP_unspecified_error;
static PyObject *__pyx_kp_u_SCIP_write_error;
static PyObject *__pyx_n_s_SEPARATED;
static PyObject *__pyx_n_s_SIBLING;
static PyObject *__pyx_n_s_SOLLIMIT;
static PyObject *__pyx_n_s_SOLVED;
static PyObject *__pyx_n_s_SOLVELP;
static PyObject *__pyx_n_s_SOLVING;
static PyObject *__pyx_n_u_SOS1cons;
static PyObject *__pyx_n_u_SOS2cons;
static PyObject *__pyx_n_s_STALLNODELIMIT;
static PyObject *__pyx_n_s_SUBROOT;
static PyObject *__pyx_n_s_SUCCESS;
static PyObject *__pyx_n_s_SUSPENDED;
static PyObject *__pyx_n_s_SYNC;
static PyObject *__pyx_n_s_Sepa;
static PyObject *__pyx_n_s_Solution;
static PyObject *__pyx_n_s_StopIteration;
static PyObject *__pyx_n_s_SumExpr;
static PyObject *__pyx_n_s_TIMELIMIT;
static PyObject *__pyx_n_s_TOTALNODELIMIT;
static PyObject *__pyx_n_s_TRANSFORMED;
static PyObject *__pyx_n_s_TRANSFORMING;
static PyObject *__pyx_n_s_Term;
static PyObject *__pyx_n_s_Term___add;
static PyObject *__pyx_n_s_Term___eq;
static PyObject *__pyx_n_s_Term___getitem;
static PyObject *__pyx_n_s_Term___hash;
static PyObject *__pyx_n_s_Term___init;
static PyObject *__pyx_n_s_Term___init___locals_genexpr;
static PyObject *__pyx_n_s_Term___init___locals_lambda;
static PyObject *__pyx_n_s_Term___len;
static PyObject *__pyx_n_s_Term___repr;
static PyObject *__pyx_kp_u_Term_s;
static PyObject *__pyx_kp_s_This_is_a_monomial_term;
static PyObject *__pyx_n_s_TypeError;
static PyObject *__pyx_n_s_UBRELAXED;
static PyObject *__pyx_n_s_UBTIGHTENED;
static PyObject *__pyx_n_s_UNBOUNDED;
static PyObject *__pyx_n_s_UNBOUNDEDRAY;
static PyObject *__pyx_n_s_UNKNOWN;
static PyObject *__pyx_n_s_UPWARDS;
static PyObject *__pyx_n_s_USERINTERRUPT;
static PyObject *__pyx_n_s_UnaryExpr;
static PyObject *__pyx_n_s_VARADDED;
static PyObject *__pyx_n_s_VARDELETED;
static PyObject *__pyx_n_s_VARFIXED;
static PyObject *__pyx_n_s_VARUNLOCKED;
static PyObject *__pyx_n_s_ValueError;
static PyObject *__pyx_n_s_VarExpr;
static PyObject *__pyx_n_s_Variable;
static PyObject *__pyx_n_s_Warning;
static PyObject *__pyx_n_u_XORcons;
static PyObject *__pyx_n_s_ZeroDivisionError;
static PyObject *__pyx_kp_u__132;
static PyObject *__pyx_kp_u__133;
static PyObject *__pyx_kp_u__134;
static PyObject *__pyx_kp_u__135;
static PyObject *__pyx_kp_u__136;
static PyObject *__pyx_kp_u__5;
static PyObject *__pyx_kp_u__8;
static PyObject *__pyx_kp_u__84;
static PyObject *__pyx_kp_u__9;
static PyObject *__pyx_n_u_abs;
static PyObject *__pyx_n_s_abspath;
static PyObject *__pyx_n_u_acons_max1;
static PyObject *__pyx_n_u_acons_max2;
static PyObject *__pyx_n_u_acons_max3;
static PyObject *__pyx_n_u_acons_max4;
static PyObject *__pyx_n_u_acons_mean1;
static PyObject *__pyx_n_u_acons_mean2;
static PyObject *__pyx_n_u_acons_mean3;
static PyObject *__pyx_n_u_acons_mean4;
static PyObject *__pyx_n_u_acons_min1;
static PyObject *__pyx_n_u_acons_min2;
static PyObject *__pyx_n_u_acons_min3;
static PyObject *__pyx_n_u_acons_min4;
static PyObject *__pyx_n_u_acons_nb1;
static PyObject *__pyx_n_u_acons_nb2;
static PyObject *__pyx_n_u_acons_nb3;
static PyObject *__pyx_n_u_acons_nb4;
static PyObject *__pyx_n_u_acons_sum1;
static PyObject *__pyx_n_u_acons_sum2;
static PyObject *__pyx_n_u_acons_sum3;
static PyObject *__pyx_n_u_acons_sum4;
static PyObject *__pyx_n_u_acons_var1;
static PyObject *__pyx_n_u_acons_var2;
static PyObject *__pyx_n_u_acons_var3;
static PyObject *__pyx_n_u_acons_var4;
static PyObject *__pyx_n_u_activities;
static PyObject *__pyx_n_s_add;
static PyObject *__pyx_n_s_addCols_locals_genexpr;
static PyObject *__pyx_n_s_addGenNonlinearCons;
static PyObject *__pyx_n_s_addLinCons;
static PyObject *__pyx_n_s_addNonlinearCons;
static PyObject *__pyx_n_s_addObjoffset;
static PyObject *__pyx_n_s_addQuadCons;
static PyObject *__pyx_n_s_addRows_locals_genexpr;
static PyObject *__pyx_n_s_add_2;
static PyObject *__pyx_n_u_ages;
static PyObject *__pyx_n_s_allowaddcons;
static PyObject *__pyx_n_u_and;
static PyObject *__pyx_n_s_append;
static PyObject *__pyx_n_s_args;
static PyObject *__pyx_n_u_avgconfliclengthscore;
static PyObject *__pyx_n_u_avgconfliclengthscorecurrentrun;
static PyObject *__pyx_n_u_avgconflictscore;
static PyObject *__pyx_n_u_avgconflictscorecurrentrun;
static PyObject *__pyx_n_u_avgcuroffscorecurrentrun;
static PyObject *__pyx_n_u_avgcutoffscore;
static PyObject *__pyx_n_u_avgdualbound;
static PyObject *__pyx_n_u_avgincvals;
static PyObject *__pyx_n_u_avginferencescore;
static PyObject *__pyx_n_u_avginferencescorecurrentrun;
static PyObject *__pyx_n_u_avglowerbound;
static PyObject *__pyx_n_u_avgpseudocostscore;
static PyObject *__pyx_n_u_avgpseudocostscorecurrentrun;
static PyObject *__pyx_n_u_basestats;
static PyObject *__pyx_n_u_basic;
static PyObject *__pyx_n_s_bdtype;
static PyObject *__pyx_n_s_benders;
static PyObject *__pyx_n_s_benderscreatesub;
static PyObject *__pyx_n_s_benderscut;
static PyObject *__pyx_n_s_benderscutexec;
static PyObject *__pyx_n_s_benderscutexit;
static PyObject *__pyx_n_s_benderscutexitsol;
static PyObject *__pyx_n_s_benderscutfree;
static PyObject *__pyx_n_s_benderscutinit;
static PyObject *__pyx_n_s_benderscutinitsol;
static PyObject *__pyx_n_s_bendersexit;
static PyObject *__pyx_n_s_bendersexitpre;
static PyObject *__pyx_n_s_bendersexitsol;
static PyObject *__pyx_n_s_bendersfree;
static PyObject *__pyx_n_s_bendersfreesub;
static PyObject *__pyx_n_s_bendersgetvar;
static PyObject *__pyx_n_s_bendersinit;
static PyObject *__pyx_n_s_bendersinitpre;
static PyObject *__pyx_n_s_bendersinitsol;
static PyObject *__pyx_n_s_benderspostsolve;
static PyObject *__pyx_n_s_benderspresubsolve;
static PyObject *__pyx_n_s_benderssolvesub;
static PyObject *__pyx_n_s_benderssolvesubconvex;
static PyObject *__pyx_n_s_binvar;
static PyObject *__pyx_n_s_both;
static PyObject *__pyx_n_s_branchdir;
static PyObject *__pyx_n_s_branchexecext;
static PyObject *__pyx_n_s_branchexeclp;
static PyObject *__pyx_n_s_branchexecps;
static PyObject *__pyx_n_s_branchexit;
static PyObject *__pyx_n_s_branchexitsol;
static PyObject *__pyx_n_s_branchfree;
static PyObject *__pyx_n_s_branchinit;
static PyObject *__pyx_n_s_branchinitsol;
static PyObject *__pyx_n_s_branchrule;
static PyObject *__pyx_n_s_buildGenExprObj;
static PyObject *__pyx_n_u_c;
static PyObject *__pyx_n_s_candidates;
static PyObject *__pyx_kp_u_cannot_create_Constraint_with_SC;
static PyObject *__pyx_kp_u_cannot_divide_by_0;
static PyObject *__pyx_n_u_cardinality;
static PyObject *__pyx_n_s_cardval;
static PyObject *__pyx_n_u_cdeg_max;
static PyObject *__pyx_n_u_cdeg_max_ratio;
static PyObject *__pyx_n_u_cdeg_mean;
static PyObject *__pyx_n_u_cdeg_mean_ratio;
static PyObject *__pyx_n_u_cdeg_min;
static PyObject *__pyx_n_u_cdeg_min_ratio;
static PyObject *__pyx_n_u_cdeg_var;
static PyObject *__pyx_n_s_ceil;
static PyObject *__pyx_n_s_chckpriority;
static PyObject *__pyx_n_s_check;
static PyObject *__pyx_n_u_check;
static PyObject *__pyx_n_s_checkbounds;
static PyObject *__pyx_n_s_checkint;
static PyObject *__pyx_n_s_checkintegrality;
static PyObject *__pyx_n_s_checklprows;
static PyObject *__pyx_n_s_child;
static PyObject *__pyx_n_s_children;
static PyObject *__pyx_n_s_chr;
static PyObject *__pyx_kp_u_cip;
static PyObject *__pyx_n_s_class;
static PyObject *__pyx_n_s_clear;
static PyObject *__pyx_n_s_cline_in_traceback;
static PyObject *__pyx_n_s_close;
static PyObject *__pyx_n_s_coef;
static PyObject *__pyx_n_s_coeff;
static PyObject *__pyx_kp_u_coefficients_not_available_for_c;
static PyObject *__pyx_n_s_coeffs;
static PyObject *__pyx_n_s_coefs;
static PyObject *__pyx_n_u_coefs;
static PyObject *__pyx_n_u_coefs_neg;
static PyObject *__pyx_n_u_coefs_pos;
static PyObject *__pyx_n_s_col;
static PyObject *__pyx_n_u_col;
static PyObject *__pyx_n_u_col_cdeg_max;
static PyObject *__pyx_n_u_col_cdeg_mean;
static PyObject *__pyx_n_u_col_cdeg_min;
static PyObject *__pyx_n_u_col_cdeg_std;
static PyObject *__pyx_n_u_col_coef_max1_unit_weight;
static PyObject *__pyx_n_u_col_coef_max2_inverse_sum;
static PyObject *__pyx_n_u_col_coef_max3_dual_cost;
static PyObject *__pyx_n_u_col_coef_mean1_unit_weight;
static PyObject *__pyx_n_u_col_coef_mean2_inverse_sum;
static PyObject *__pyx_n_u_col_coef_mean3_dual_cost;
static PyObject *__pyx_n_u_col_coef_min1_unit_weight;
static PyObject *__pyx_n_u_col_coef_min2_inverse_sum;
static PyObject *__pyx_n_u_col_coef_min3_dual_cost;
static PyObject *__pyx_n_u_col_coef_std1_unit_weight;
static PyObject *__pyx_n_u_col_coef_std2_inverse_sum;
static PyObject *__pyx_n_u_col_coef_std3_dual_cost;
static PyObject *__pyx_n_u_col_coef_sum1_unit_weight;
static PyObject *__pyx_n_u_col_coef_sum2_inverse_sum;
static PyObject *__pyx_n_u_col_coef_sum3_dual_cost;
static PyObject *__pyx_n_u_col_coefs;
static PyObject *__pyx_n_u_col_coefs_neg;
static PyObject *__pyx_n_u_col_coefs_pos;
static PyObject *__pyx_n_u_col_lbs;
static PyObject *__pyx_n_u_col_ncoefs_max;
static PyObject *__pyx_n_u_col_ncoefs_mean;
static PyObject *__pyx_n_u_col_ncoefs_min;
static PyObject *__pyx_n_u_col_ncoefs_std;
static PyObject *__pyx_n_u_col_ncoefs_sum;
static PyObject *__pyx_n_u_col_ndown_locks;
static PyObject *__pyx_n_u_col_nlhs_ratio_max;
static PyObject *__pyx_n_u_col_nlhs_ratio_min;
static PyObject *__pyx_n_u_col_nnzrs;
static PyObject *__pyx_n_u_col_nrhs_ratio_max;
static PyObject *__pyx_n_u_col_nrhs_ratio_min;
static PyObject *__pyx_n_u_col_nup_locks;
static PyObject *__pyx_n_u_col_pcoefs_max;
static PyObject *__pyx_n_u_col_pcoefs_mean;
static PyObject *__pyx_n_u_col_pcoefs_min;
static PyObject *__pyx_n_u_col_pcoefs_std;
static PyObject *__pyx_n_u_col_pcoefs_sum;
static PyObject *__pyx_n_u_col_plhs_ratio_max;
static PyObject *__pyx_n_u_col_plhs_ratio_min;
static PyObject *__pyx_n_u_col_prhs_ratio_max;
static PyObject *__pyx_n_u_col_prhs_ratio_min;
static PyObject *__pyx_n_u_col_ps_down;
static PyObject *__pyx_n_u_col_ps_product;
static PyObject *__pyx_n_u_col_ps_ratio;
static PyObject *__pyx_n_u_col_ps_sum;
static PyObject *__pyx_n_u_col_ps_up;
static PyObject *__pyx_n_u_col_red_costs;
static PyObject *__pyx_n_u_col_sol_frac_down;
static PyObject *__pyx_n_u_col_sol_frac_up;
static PyObject *__pyx_n_u_col_sol_isfrac;
static PyObject *__pyx_n_u_col_solvals;
static PyObject *__pyx_n_u_col_type_binary;
static PyObject *__pyx_n_u_col_type_int;
static PyObject *__pyx_n_u_col_ubs;
static PyObject *__pyx_n_u_colidxs;
static PyObject *__pyx_n_s_comments;
static PyObject *__pyx_n_s_completely;
static PyObject *__pyx_n_s_confvar;
static PyObject *__pyx_n_s_cons;
static PyObject *__pyx_n_u_cons_basis_status;
static PyObject *__pyx_n_u_cons_coef_max;
static PyObject *__pyx_n_u_cons_coef_mean;
static PyObject *__pyx_n_u_cons_coef_min;
static PyObject *__pyx_n_u_cons_coef_stdev;
static PyObject *__pyx_n_u_cons_dual_sol;
static PyObject *__pyx_n_u_cons_is_AND;
static PyObject *__pyx_n_u_cons_is_OR;
static PyObject *__pyx_n_u_cons_is_XOR;
static PyObject *__pyx_n_u_cons_is_aggregation;
static PyObject *__pyx_n_u_cons_is_cardinality;
static PyObject *__pyx_n_u_cons_is_general_linear;
static PyObject *__pyx_n_u_cons_is_knapsack;
static PyObject *__pyx_n_u_cons_is_linking;
static PyObject *__pyx_n_u_cons_is_logicor;
static PyObject *__pyx_n_u_cons_is_precedence;
static PyObject *__pyx_n_u_cons_is_singleton;
static PyObject *__pyx_n_u_cons_is_variable_bound;
static PyObject *__pyx_n_u_cons_lhs;
static PyObject *__pyx_n_u_cons_matrix;
static PyObject *__pyx_n_u_cons_nneg;
static PyObject *__pyx_n_u_cons_nnzrs;
static PyObject *__pyx_n_u_cons_npos;
static PyObject *__pyx_n_u_cons_rhs;
static PyObject *__pyx_n_u_cons_sum_abs;
static PyObject *__pyx_n_u_cons_sum_neg;
static PyObject *__pyx_n_u_cons_sum_pos;
static PyObject *__pyx_n_s_consactive;
static PyObject *__pyx_n_s_conscheck;
static PyObject *__pyx_n_s_conscopy;
static PyObject *__pyx_n_s_consdeactive;
static PyObject *__pyx_n_s_consdelete;
static PyObject *__pyx_n_s_consdelvars;
static PyObject *__pyx_n_s_consdisable;
static PyObject *__pyx_n_s_consenable;
static PyObject *__pyx_n_s_consenfolp;
static PyObject *__pyx_n_s_consenfops;
static PyObject *__pyx_n_s_consenforelax;
static PyObject *__pyx_n_s_consexit;
static PyObject *__pyx_n_s_consexitpre;
static PyObject *__pyx_n_s_consexitsol;
static PyObject *__pyx_n_s_consfree;
static PyObject *__pyx_n_s_consgetdivebdchgs;
static PyObject *__pyx_n_s_consgetnvars;
static PyObject *__pyx_n_s_consgetvars;
static PyObject *__pyx_n_s_conshdlr;
static PyObject *__pyx_n_s_consinit;
static PyObject *__pyx_n_s_consinitlp;
static PyObject *__pyx_n_s_consinitpre;
static PyObject *__pyx_n_s_consinitsol;
static PyObject *__pyx_n_s_conslock;
static PyObject *__pyx_n_s_consparse;
static PyObject *__pyx_n_s_conspresol;
static PyObject *__pyx_n_s_consprint;
static PyObject *__pyx_n_s_consprop;
static PyObject *__pyx_n_s_consresprop;
static PyObject *__pyx_n_s_conssepalp;
static PyObject *__pyx_n_s_conssepasol;
static PyObject *__pyx_n_s_const;
static PyObject *__pyx_n_u_const;
static PyObject *__pyx_n_s_constant;
static PyObject *__pyx_n_s_constraint;
static PyObject *__pyx_kp_u_constraint_is_not_quadratic;
static PyObject *__pyx_n_s_constraints;
static PyObject *__pyx_kp_u_constraints_benders_active;
static PyObject *__pyx_kp_u_constraints_benderslp_active;
static PyObject *__pyx_n_s_constrans;
static PyObject *__pyx_n_s_consvars;
static PyObject *__pyx_n_s_copy;
static PyObject *__pyx_kp_u_could_not_change_variable_type_o;
static PyObject *__pyx_n_s_create;
static PyObject *__pyx_n_s_createProbBasic;
static PyObject *__pyx_n_s_createSol;
static PyObject *__pyx_n_u_cumulative;
static PyObject *__pyx_n_s_cut;
static PyObject *__pyx_n_s_cutlp;
static PyObject *__pyx_n_u_cutoffbound;
static PyObject *__pyx_n_u_cutoffdepth;
static PyObject *__pyx_n_s_cutpseudo;
static PyObject *__pyx_n_s_cutrelax;
static PyObject *__pyx_n_s_defaultPlugins;
static PyObject *__pyx_n_s_degree;
static PyObject *__pyx_n_s_degree_locals_genexpr;
static PyObject *__pyx_n_s_delay;
static PyObject *__pyx_n_s_delayprop;
static PyObject *__pyx_n_s_delaysepa;
static PyObject *__pyx_n_u_depth;
static PyObject *__pyx_n_s_desc;
static PyObject *__pyx_n_u_deterministictime;
static PyObject *__pyx_n_s_dict;
static PyObject *__pyx_n_s_dispchar;
static PyObject *__pyx_n_s_div;
static PyObject *__pyx_n_s_div_2;
static PyObject *__pyx_n_s_doc;
static PyObject *__pyx_n_s_dtype;
static PyObject *__pyx_n_s_dual;
static PyObject *__pyx_kp_u_dual_solution_values_not_availab;
static PyObject *__pyx_n_u_dualbound;
static PyObject *__pyx_n_u_dualboundroot;
static PyObject *__pyx_n_u_dualsols;
static PyObject *__pyx_n_s_dynamic;
static PyObject *__pyx_n_u_dynamic;
static PyObject *__pyx_n_s_e;
static PyObject *__pyx_n_s_eagerfreq;
static PyObject *__pyx_n_u_effectiverootdepth;
static PyObject *__pyx_n_s_empty;
static PyObject *__pyx_n_s_enablepricing;
static PyObject *__pyx_n_s_enfopriority;
static PyObject *__pyx_n_s_enforce;
static PyObject *__pyx_n_u_enforce;
static PyObject *__pyx_n_s_enfotype;
static PyObject *__pyx_n_s_enter;
static PyObject *__pyx_n_s_entries;
static PyObject *__pyx_n_s_entrieslist;
static PyObject *__pyx_n_s_enumerate;
static PyObject *__pyx_n_s_eq;
static PyObject *__pyx_n_s_estimate;
static PyObject *__pyx_kp_u_event_handler_not_found;
static PyObject *__pyx_n_s_eventcopy;
static PyObject *__pyx_n_s_eventdelete;
static PyObject *__pyx_n_s_eventexec;
static PyObject *__pyx_n_s_eventexit;
static PyObject *__pyx_n_s_eventexitsol;
static PyObject *__pyx_n_s_eventfree;
static PyObject *__pyx_n_s_eventhdlr;
static PyObject *__pyx_n_s_eventinit;
static PyObject *__pyx_n_s_eventinitsol;
static PyObject *__pyx_n_s_eventtype;
static PyObject *__pyx_n_s_exact;
static PyObject *__pyx_n_s_exit;
static PyObject *__pyx_n_s_exp;
static PyObject *__pyx_n_u_exp;
static PyObject *__pyx_kp_u_expected_inequality_that_has_eit;
static PyObject *__pyx_kp_u_expected_linear_inequality_expre;
static PyObject *__pyx_n_s_expo;
static PyObject *__pyx_kp_u_exponents_must_be_numbers;
static PyObject *__pyx_n_s_expr;
static PyObject *__pyx_n_s_expr_richcmp;
static PyObject *__pyx_n_s_expr_to_array;
static PyObject *__pyx_n_s_expr_to_nodes;
static PyObject *__pyx_n_s_extend;
static PyObject *__pyx_n_s_extension;
static PyObject *__pyx_n_s_f;
static PyObject *__pyx_n_s_fabs;
static PyObject *__pyx_n_s_file;
static PyObject *__pyx_n_s_filename;
static PyObject *__pyx_n_s_fileno;
static PyObject *__pyx_n_s_firstcol;
static PyObject *__pyx_n_u_firstlpdualboundroot;
static PyObject *__pyx_n_u_firstlplowerboundroot;
static PyObject *__pyx_n_u_firstprimalbound;
static PyObject *__pyx_n_s_firstrow;
static PyObject *__pyx_n_s_fixedval;
static PyObject *__pyx_n_s_flag;
static PyObject *__pyx_n_s_float;
static PyObject *__pyx_n_s_float32;
static PyObject *__pyx_n_s_floor;
static PyObject *__pyx_n_u_focusdepth;
static PyObject *__pyx_n_s_force;
static PyObject *__pyx_n_s_forcecut;
static PyObject *__pyx_n_s_format;
static PyObject *__pyx_n_u_frac_down_infeas;
static PyObject *__pyx_n_u_frac_up_infeas;
static PyObject *__pyx_n_s_free;
static PyObject *__pyx_n_s_freq;
static PyObject *__pyx_n_s_freqofs;
static PyObject *__pyx_n_u_gap;
static PyObject *__pyx_n_s_genexpr;
static PyObject *__pyx_n_s_get;
static PyObject *__pyx_n_s_getNNonz;
static PyObject *__pyx_n_s_getObj;
static PyObject *__pyx_n_s_getObjectiveSense;
static PyObject *__pyx_n_s_getOp;
static PyObject *__pyx_n_s_getOpIndex;
static PyObject *__pyx_n_s_getSolObjVal;
static PyObject *__pyx_n_s_getSolVal;
static PyObject *__pyx_n_s_getStage;
static PyObject *__pyx_n_s_getTransformedCons;
static PyObject *__pyx_n_s_getType;
static PyObject *__pyx_n_s_getVars;
static PyObject *__pyx_n_s_getitem;
static PyObject *__pyx_n_s_getstate;
static PyObject *__pyx_kp_u_given_coefficients_are_neither_E;
static PyObject *__pyx_kp_u_given_coefficients_are_not_Expr;
static PyObject *__pyx_kp_u_given_constraint_is_not_ExprCons;
static PyObject *__pyx_kp_u_given_constraint_is_not_linear_d;
static PyObject *__pyx_kp_u_given_constraint_is_not_quadrati;
static PyObject *__pyx_n_s_globalcopy;
static PyObject *__pyx_n_s_hash;
static PyObject *__pyx_n_s_hashval;
static PyObject *__pyx_n_u_hashval;
static PyObject *__pyx_n_s_heur;
static PyObject *__pyx_n_s_heurexec;
static PyObject *__pyx_n_s_heurexit;
static PyObject *__pyx_n_s_heurexitsol;
static PyObject *__pyx_n_s_heurfree;
static PyObject *__pyx_n_s_heurinit;
static PyObject *__pyx_n_s_heurinitsol;
static PyObject *__pyx_n_s_heurtiming;
static PyObject *__pyx_n_s_idx;
static PyObject *__pyx_n_s_import;
static PyObject *__pyx_n_s_includeDefaultPlugins;
static PyObject *__pyx_n_u_incvals;
static PyObject *__pyx_n_s_indicator_arr;
static PyObject *__pyx_n_s_indices;
static PyObject *__pyx_n_s_indvars;
static PyObject *__pyx_n_u_inf;
static PyObject *__pyx_n_s_infeasible;
static PyObject *__pyx_n_u_infeasible;
static PyObject *__pyx_n_s_inferinfo;
static PyObject *__pyx_n_s_infinity;
static PyObject *__pyx_n_s_init;
static PyObject *__pyx_n_s_initial;
static PyObject *__pyx_n_u_initial;
static PyObject *__pyx_n_u_inrepropagation;
static PyObject *__pyx_n_s_int32;
static PyObject *__pyx_n_s_interpolation;
static PyObject *__pyx_n_s_isChecked;
static PyObject *__pyx_n_s_isDynamic;
static PyObject *__pyx_n_s_isEnforced;
static PyObject *__pyx_n_s_isInitial;
static PyObject *__pyx_n_s_isLocal;
static PyObject *__pyx_n_s_isModifiable;
static PyObject *__pyx_n_s_isOriginal;
static PyObject *__pyx_n_s_isPropagated;
static PyObject *__pyx_n_s_isQuadratic;
static PyObject *__pyx_n_s_isRemovable;
static PyObject *__pyx_n_s_isSeparated;
static PyObject *__pyx_n_s_isStickingAtNode;
static PyObject *__pyx_n_u_is_at_lhs;
static PyObject *__pyx_n_u_is_at_rhs;
static PyObject *__pyx_n_s_is_integer;
static PyObject *__pyx_n_u_is_local;
static PyObject *__pyx_n_s_is_memory_freed;
static PyObject *__pyx_n_u_is_modifiable;
static PyObject *__pyx_n_s_is_number;
static PyObject *__pyx_n_u_is_removable;
static PyObject *__pyx_n_s_islpcut;
static PyObject *__pyx_n_u_isprimalboundsol;
static PyObject *__pyx_n_s_items;
static PyObject *__pyx_n_s_itlim;
static PyObject *__pyx_n_s_key;
static PyObject *__pyx_n_s_keys;
static PyObject *__pyx_n_u_knapsack;
static PyObject *__pyx_n_s_lambda;
static PyObject *__pyx_n_s_lastcol;
static PyObject *__pyx_n_s_lastrow;
static PyObject *__pyx_n_s_lb;
static PyObject *__pyx_n_s_lbs;
static PyObject *__pyx_n_u_lbs;
static PyObject *__pyx_n_s_len;
static PyObject *__pyx_n_s_lhs;
static PyObject *__pyx_n_u_lhs;
static PyObject *__pyx_n_s_lhs_2;
static PyObject *__pyx_n_u_lhs_vec;
static PyObject *__pyx_n_s_lhss;
static PyObject *__pyx_n_u_lhss;
static PyObject *__pyx_n_s_lincons;
static PyObject *__pyx_n_u_linear;
static PyObject *__pyx_kp_u_linked_SCIP_is_not_compatible_to;
static PyObject *__pyx_kp_u_linked_SCIP_is_not_recommended_f;
static PyObject *__pyx_n_u_linking;
static PyObject *__pyx_n_s_local;
static PyObject *__pyx_n_u_local;
static PyObject *__pyx_n_s_locktype;
static PyObject *__pyx_n_s_log;
static PyObject *__pyx_n_u_log;
static PyObject *__pyx_n_u_logicor;
static PyObject *__pyx_n_u_lower;
static PyObject *__pyx_n_u_lowerbound;
static PyObject *__pyx_n_u_lowerboundroot;
static PyObject *__pyx_n_s_lowerbounds;
static PyObject *__pyx_n_u_lp_obj;
static PyObject *__pyx_n_s_main;
static PyObject *__pyx_n_s_map;
static PyObject *__pyx_n_u_mappedvar;
static PyObject *__pyx_n_s_math;
static PyObject *__pyx_n_s_max;
static PyObject *__pyx_n_s_maxbounddist;
static PyObject *__pyx_n_s_maxdepth;
static PyObject *__pyx_n_u_maxdepth;
static PyObject *__pyx_n_u_maximize;
static PyObject *__pyx_n_s_maxprerounds;
static PyObject *__pyx_n_s_maxrounds;
static PyObject *__pyx_n_u_maxtotaldepth;
static PyObject *__pyx_n_s_memsavepriority;
static PyObject *__pyx_n_s_mergecandidates;
static PyObject *__pyx_n_u_merged;
static PyObject *__pyx_n_s_metaclass;
static PyObject *__pyx_kp_u_method_cannot_be_called_before_p;
static PyObject *__pyx_kp_u_method_cannot_be_called_for_cons;
static PyObject *__pyx_n_u_minimize;
static PyObject *__pyx_n_s_minus;
static PyObject *__pyx_n_u_model;
static PyObject *__pyx_kp_u_model_cip;
static PyObject *__pyx_n_s_modifiable;
static PyObject *__pyx_n_u_modifiable;
static PyObject *__pyx_n_s_module;
static PyObject *__pyx_n_s_mul;
static PyObject *__pyx_n_s_mul_2;
static PyObject *__pyx_n_u_nactivatednodes;
static PyObject *__pyx_n_u_nactivesonss;
static PyObject *__pyx_n_u_naddconss;
static PyObject *__pyx_n_u_naddholes;
static PyObject *__pyx_n_u_naggrvars;
static PyObject *__pyx_n_s_name;
static PyObject *__pyx_n_u_name;
static PyObject *__pyx_n_s_name_2;
static PyObject *__pyx_n_u_nb_down_infeas;
static PyObject *__pyx_n_u_nb_up_infeas;
static PyObject *__pyx_n_u_nbacktracks;
static PyObject *__pyx_n_u_nbarrierlpiterations;
static PyObject *__pyx_n_u_nbarrierlps;
static PyObject *__pyx_n_u_nbestsolsfound;
static PyObject *__pyx_n_u_nchgbds;
static PyObject *__pyx_n_u_nchgcoefs;
static PyObject *__pyx_n_u_nchgsides;
static PyObject *__pyx_n_u_nchgvartypes;
static PyObject *__pyx_n_s_nchildren;
static PyObject *__pyx_n_s_ncols;
static PyObject *__pyx_n_u_nconflictconssapplied;
static PyObject *__pyx_n_u_nconflictconssfound;
static PyObject *__pyx_n_u_nconflictconssfoundnode;
static PyObject *__pyx_n_u_ncreatednodes;
static PyObject *__pyx_n_u_ncreatednodesrun;
static PyObject *__pyx_n_u_ncutsapplied;
static PyObject *__pyx_n_u_ncutsfound;
static PyObject *__pyx_n_u_ncutsfoundround;
static PyObject *__pyx_n_u_ndeactivatednodes;
static PyObject *__pyx_n_u_ndelayedcutoffs;
static PyObject *__pyx_n_u_ndelconss;
static PyObject *__pyx_n_u_ndivinglpiterations;
static PyObject *__pyx_n_u_ndivinglps;
static PyObject *__pyx_n_u_nduallpiterations;
static PyObject *__pyx_n_u_nduallps;
static PyObject *__pyx_n_u_ndualresolvelpiterations;
static PyObject *__pyx_n_u_ndualresolvelps;
static PyObject *__pyx_n_s_needscons;
static PyObject *__pyx_n_u_nenabledconss;
static PyObject *__pyx_n_s_new;
static PyObject *__pyx_n_s_newCheck;
static PyObject *__pyx_n_s_newEnf;
static PyObject *__pyx_n_s_newInit;
static PyObject *__pyx_n_s_newRem;
static PyObject *__pyx_n_s_newbound;
static PyObject *__pyx_n_s_newlhs;
static PyObject *__pyx_n_s_newobj;
static PyObject *__pyx_n_s_newrhs;
static PyObject *__pyx_n_s_newval;
static PyObject *__pyx_n_u_nfeasibleleaves;
static PyObject *__pyx_n_u_nfixedvars;
static PyObject *__pyx_n_u_ninfeasibleleaves;
static PyObject *__pyx_n_u_ninternalnodes;
static PyObject *__pyx_n_u_nleaves;
static PyObject *__pyx_n_u_nlimsolsfound;
static PyObject *__pyx_n_s_nlocksdown;
static PyObject *__pyx_n_s_nlocksneg;
static PyObject *__pyx_n_s_nlockspos;
static PyObject *__pyx_n_s_nlocksup;
static PyObject *__pyx_n_u_nlpiterations;
static PyObject *__pyx_n_u_nlps;
static PyObject *__pyx_n_s_nmarkedconss;
static PyObject *__pyx_n_s_nnewaddconss;
static PyObject *__pyx_n_u_nnewaddconss;
static PyObject *__pyx_n_u_nnewaddholes;
static PyObject *__pyx_n_s_nnewaggrvars;
static PyObject *__pyx_n_u_nnewaggrvars;
static PyObject *__pyx_n_s_nnewchgbds;
static PyObject *__pyx_n_u_nnewchgbds;
static PyObject *__pyx_n_s_nnewchgcoefs;
static PyObject *__pyx_n_u_nnewchgcoefs;
static PyObject *__pyx_n_s_nnewchgsides;
static PyObject *__pyx_n_u_nnewchgsides;
static PyObject *__pyx_n_s_nnewchgvartypes;
static PyObject *__pyx_n_u_nnewchgvartypes;
static PyObject *__pyx_n_s_nnewdelconss;
static PyObject *__pyx_n_u_nnewdelconss;
static PyObject *__pyx_n_s_nnewfixedvars;
static PyObject *__pyx_n_u_nnewfixedvars;
static PyObject *__pyx_n_s_nnewholes;
static PyObject *__pyx_n_s_nnewupgdconss;
static PyObject *__pyx_n_u_nnewupgdconss;
static PyObject *__pyx_n_u_nnodeinitlpiterations;
static PyObject *__pyx_n_u_nnodeinitlps;
static PyObject *__pyx_n_u_nnodelpiterations;
static PyObject *__pyx_n_u_nnodelps;
static PyObject *__pyx_n_u_nnodes;
static PyObject *__pyx_n_u_nnodesleft;
static PyObject *__pyx_n_u_nnzrs;
static PyObject *__pyx_n_u_nnzs;
static PyObject *__pyx_kp_u_no_dual_solution_available_for_c;
static PyObject *__pyx_kp_u_no_reduced_cost_available_for_va;
static PyObject *__pyx_n_u_nobjlimleaves;
static PyObject *__pyx_n_s_node;
static PyObject *__pyx_n_s_node1;
static PyObject *__pyx_n_s_node2;
static PyObject *__pyx_n_s_nodecomp;
static PyObject *__pyx_n_s_nodeexit;
static PyObject *__pyx_n_s_nodeexitsol;
static PyObject *__pyx_n_s_nodefree;
static PyObject *__pyx_n_s_nodeinfeasible;
static PyObject *__pyx_n_s_nodeinit;
static PyObject *__pyx_n_s_nodeinitsol;
static PyObject *__pyx_n_s_nodes;
static PyObject *__pyx_n_s_nodesel;
static PyObject *__pyx_n_s_nodeselect;
static PyObject *__pyx_n_s_nodeselprio;
static PyObject *__pyx_n_s_normalize;
static PyObject *__pyx_n_u_norms;
static PyObject *__pyx_n_s_np;
static PyObject *__pyx_n_u_npricerounds;
static PyObject *__pyx_n_u_npricevars;
static PyObject *__pyx_n_u_npricevarsapplied;
static PyObject *__pyx_n_u_npricevarsfound;
static PyObject *__pyx_n_u_nprimallpiterations;
static PyObject *__pyx_n_u_nprimallps;
static PyObject *__pyx_n_u_nprimalresolvelpiterations;
static PyObject *__pyx_n_u_nprimalresolvelps;
static PyObject *__pyx_n_s_npriomergecands;
static PyObject *__pyx_n_u_nreoptruns;
static PyObject *__pyx_n_u_nresolvelpiterations;
static PyObject *__pyx_n_u_nresolvelps;
static PyObject *__pyx_n_u_nrhs_ratio_max;
static PyObject *__pyx_n_u_nrhs_ratio_min;
static PyObject *__pyx_n_u_nrootfirstlpiterations;
static PyObject *__pyx_n_u_nrootlpiterations;
static PyObject *__pyx_n_u_nrootstrongbranchlpiterations;
static PyObject *__pyx_n_u_nrootstrongbranchs;
static PyObject *__pyx_n_s_nrounds;
static PyObject *__pyx_n_s_nrows;
static PyObject *__pyx_n_u_nruns;
static PyObject *__pyx_n_u_nseparounds;
static PyObject *__pyx_n_u_nsolsfound;
static PyObject *__pyx_n_u_nstrongbranchlpiterations;
static PyObject *__pyx_n_u_nstrongbranchs;
static PyObject *__pyx_n_s_nsubproblems;
static PyObject *__pyx_n_u_ntotalnodes;
static PyObject *__pyx_n_s_number;
static PyObject *__pyx_n_s_numpy;
static PyObject *__pyx_kp_u_numpy_core_multiarray_failed_to;
static PyObject *__pyx_kp_u_numpy_core_umath_failed_to_impor;
static PyObject *__pyx_n_u_nupgdconss;
static PyObject *__pyx_n_s_nusefulconss;
static PyObject *__pyx_n_u_nvars;
static PyObject *__pyx_n_u_nzrcoef;
static PyObject *__pyx_n_s_obj;
static PyObject *__pyx_n_u_objcossims;
static PyObject *__pyx_n_u_objective;
static PyObject *__pyx_n_s_objinfeasible;
static PyObject *__pyx_n_s_objs;
static PyObject *__pyx_n_s_offset;
static PyObject *__pyx_n_s_onlychanged;
static PyObject *__pyx_n_s_onlyconvex;
static PyObject *__pyx_n_s_onlyroot;
static PyObject *__pyx_n_s_op;
static PyObject *__pyx_n_s_op_2;
static PyObject *__pyx_n_s_open;
static PyObject *__pyx_n_u_opennodes_10quant;
static PyObject *__pyx_n_u_opennodes_25quant;
static PyObject *__pyx_n_u_opennodes_50quant;
static PyObject *__pyx_n_u_opennodes_75quant;
static PyObject *__pyx_n_u_opennodes_90quant;
static PyObject *__pyx_n_s_operatorIndexDic;
static PyObject *__pyx_n_u_optimal;
static PyObject *__pyx_n_u_or;
static PyObject *__pyx_n_s_origcopy;
static PyObject *__pyx_n_s_original;
static PyObject *__pyx_kp_u_origprob_sol;
static PyObject *__pyx_kp_u_origprob_stats;
static PyObject *__pyx_n_s_os_path;
static PyObject *__pyx_n_u_ota_nn_max;
static PyObject *__pyx_n_u_ota_nn_min;
static PyObject *__pyx_n_u_ota_np_max;
static PyObject *__pyx_n_u_ota_np_min;
static PyObject *__pyx_n_u_ota_pn_max;
static PyObject *__pyx_n_u_ota_pn_min;
static PyObject *__pyx_n_u_ota_pp_max;
static PyObject *__pyx_n_u_ota_pp_min;
static PyObject *__pyx_n_s_other;
static PyObject *__pyx_n_s_overwrite_input;
static PyObject *__pyx_n_s_paraemphasis;
static PyObject *__pyx_kp_u_param_set;
static PyObject *__pyx_n_s_percentile;
static PyObject *__pyx_n_s_pickle;
static PyObject *__pyx_n_u_plungedepth;
static PyObject *__pyx_n_s_plus;
static PyObject *__pyx_n_s_pos;
static PyObject *__pyx_n_s_power;
static PyObject *__pyx_n_s_prepare;
static PyObject *__pyx_n_s_presol;
static PyObject *__pyx_n_s_presolexec;
static PyObject *__pyx_n_s_presolexit;
static PyObject *__pyx_n_s_presolexitpre;
static PyObject *__pyx_n_s_presolfree;
static PyObject *__pyx_n_s_presolinit;
static PyObject *__pyx_n_s_presolinitpre;
static PyObject *__pyx_n_s_presolmaxrounds;
static PyObject *__pyx_n_s_presolpriority;
static PyObject *__pyx_n_s_presoltiming;
static PyObject *__pyx_n_s_prev_state;
static PyObject *__pyx_n_u_prhs_ratio_max;
static PyObject *__pyx_n_u_prhs_ratio_min;
static PyObject *__pyx_n_s_pricedVar;
static PyObject *__pyx_n_s_pricer;
static PyObject *__pyx_n_s_pricerexit;
static PyObject *__pyx_n_s_pricerexitsol;
static PyObject *__pyx_n_s_pricerfarkas;
static PyObject *__pyx_n_s_pricerfree;
static PyObject *__pyx_n_s_pricerinit;
static PyObject *__pyx_n_s_pricerinitsol;
static PyObject *__pyx_n_s_pricerredcost;
static PyObject *__pyx_n_u_primalbound;
static PyObject *__pyx_n_s_print;
static PyObject *__pyx_n_s_print_memory_in_use;
static PyObject *__pyx_n_s_printreason;
static PyObject *__pyx_n_s_priority;
static PyObject *__pyx_n_s_problemName;
static PyObject *__pyx_n_s_probnumber;
static PyObject *__pyx_n_s_prod;
static PyObject *__pyx_n_u_prod;
static PyObject *__pyx_n_s_prodexpr;
static PyObject *__pyx_n_s_prop;
static PyObject *__pyx_n_s_propagate;
static PyObject *__pyx_n_u_propagate;
static PyObject *__pyx_kp_u_propagating_maxrounds;
static PyObject *__pyx_kp_u_propagating_maxroundsroot;
static PyObject *__pyx_n_s_propexec;
static PyObject *__pyx_n_s_propexit;
static PyObject *__pyx_n_s_propexitpre;
static PyObject *__pyx_n_s_propexitsol;
static PyObject *__pyx_n_s_propfree;
static PyObject *__pyx_n_s_propfreq;
static PyObject *__pyx_n_s_propinit;
static PyObject *__pyx_n_s_propinitpre;
static PyObject *__pyx_n_s_propinitsol;
static PyObject *__pyx_n_s_proppresol;
static PyObject *__pyx_n_s_propresprop;
static PyObject *__pyx_n_s_proptiming;
static PyObject *__pyx_n_s_proxy;
static PyObject *__pyx_n_u_ps_down;
static PyObject *__pyx_n_u_ps_product;
static PyObject *__pyx_n_u_ps_ratio;
static PyObject *__pyx_n_u_ps_sum;
static PyObject *__pyx_n_u_ps_up;
static PyObject *__pyx_n_s_ptr;
static PyObject *__pyx_n_s_ptrtuple;
static PyObject *__pyx_n_u_ptrtuple;
static PyObject *__pyx_n_s_pyscipopt_scip;
static PyObject *__pyx_kp_u_python_error_in_benderscreatesub;
static PyObject *__pyx_kp_u_python_error_in_benderscutexec_t;
static PyObject *__pyx_kp_u_python_error_in_bendersgetvar_th;
static PyObject *__pyx_kp_u_python_error_in_conscheck_this_m;
static PyObject *__pyx_kp_u_python_error_in_consenfolp_this;
static PyObject *__pyx_kp_u_python_error_in_consenfops_this;
static PyObject *__pyx_kp_u_python_error_in_consenforelax_th;
static PyObject *__pyx_kp_u_python_error_in_conslock_this_me;
static PyObject *__pyx_kp_u_python_error_in_eventexec_this_m;
static PyObject *__pyx_kp_u_python_error_in_heurexec_this_me;
static PyObject *__pyx_kp_u_python_error_in_presolexec_this;
static PyObject *__pyx_kp_u_python_error_in_pricerredcost_th;
static PyObject *__pyx_kp_u_python_error_in_propexec_this_me;
static PyObject *__pyx_kp_u_python_error_in_propresprop_this;
static PyObject *__pyx_kp_u_python_error_in_relaxexec_this_m;
static PyObject *__pyx_n_s_pyx_PickleError;
static PyObject *__pyx_n_s_pyx_checksum;
static PyObject *__pyx_n_s_pyx_result;
static PyObject *__pyx_n_s_pyx_state;
static PyObject *__pyx_n_s_pyx_type;
static PyObject *__pyx_n_s_pyx_unpickle_Benders;
static PyObject *__pyx_n_s_pyx_unpickle_Benderscut;
static PyObject *__pyx_n_s_pyx_unpickle_Branchrule;
static PyObject *__pyx_n_s_pyx_unpickle_Conshdlr;
static PyObject *__pyx_n_s_pyx_unpickle_Constant;
static PyObject *__pyx_n_s_pyx_unpickle_Eventhdlr;
static PyObject *__pyx_n_s_pyx_unpickle_Expr;
static PyObject *__pyx_n_s_pyx_unpickle_ExprCons;
static PyObject *__pyx_n_s_pyx_unpickle_GenExpr;
static PyObject *__pyx_n_s_pyx_unpickle_Heur;
static PyObject *__pyx_n_s_pyx_unpickle_Nodesel;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_BENDERSEN;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_BRANCHDIR;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_EVENTTYPE;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_HEURTIMIN;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_LPSOLSTAT;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_NODETYPE;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_PARAMEMPH;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_PARAMSETT;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_PRESOLTIM;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_PROPTIMIN;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_RESULT;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_STAGE;
static PyObject *__pyx_n_s_pyx_unpickle_PY_SCIP_STATUS;
static PyObject *__pyx_n_s_pyx_unpickle_PowExpr;
static PyObject *__pyx_n_s_pyx_unpickle_Presol;
static PyObject *__pyx_n_s_pyx_unpickle_Pricer;
static PyObject *__pyx_n_s_pyx_unpickle_ProdExpr;
static PyObject *__pyx_n_s_pyx_unpickle_Prop;
static PyObject *__pyx_n_s_pyx_unpickle_Relax;
static PyObject *__pyx_n_s_pyx_unpickle_Sepa;
static PyObject *__pyx_n_s_pyx_unpickle_SumExpr;
static PyObject *__pyx_n_s_pyx_unpickle_UnaryExpr;
static PyObject *__pyx_n_s_pyx_unpickle_VarExpr;
static PyObject *__pyx_n_s_pyx_vtable;
static PyObject *__pyx_n_s_quadcons;
static PyObject *__pyx_n_u_quadratic;
static PyObject *__pyx_n_s_qualname;
static PyObject *__pyx_n_s_quickprod;
static PyObject *__pyx_n_s_quicksum;
static PyObject *__pyx_n_s_quiet;
static PyObject *__pyx_n_s_range;
static PyObject *__pyx_n_s_rc;
static PyObject *__pyx_n_u_redcosts;
static PyObject *__pyx_n_s_reduce;
static PyObject *__pyx_n_s_reduce_cython;
static PyObject *__pyx_n_s_reduce_ex;
static PyObject *__pyx_n_s_relax;
static PyObject *__pyx_n_s_relaxedbd;
static PyObject *__pyx_n_s_relaxexec;
static PyObject *__pyx_n_s_relaxexit;
static PyObject *__pyx_n_s_relaxexitsol;
static PyObject *__pyx_n_s_relaxfree;
static PyObject *__pyx_n_s_relaxinit;
static PyObject *__pyx_n_s_relaxinitsol;
static PyObject *__pyx_n_s_removable;
static PyObject *__pyx_n_u_removable;
static PyObject *__pyx_n_s_repr;
static PyObject *__pyx_n_s_repr___locals_lambda;
static PyObject *__pyx_n_u_repropdepth;
static PyObject *__pyx_n_s_restart;
static PyObject *__pyx_n_s_result;
static PyObject *__pyx_n_u_result;
static PyObject *__pyx_n_s_result_dict;
static PyObject *__pyx_n_s_resvar;
static PyObject *__pyx_n_s_rhs;
static PyObject *__pyx_n_u_rhs;
static PyObject *__pyx_n_s_rhs_2;
static PyObject *__pyx_n_u_rhs_vec;
static PyObject *__pyx_n_s_rhss;
static PyObject *__pyx_n_u_rhss;
static PyObject *__pyx_n_s_rhsvar;
static PyObject *__pyx_n_u_root_cdeg_max;
static PyObject *__pyx_n_u_root_cdeg_mean;
static PyObject *__pyx_n_u_root_cdeg_min;
static PyObject *__pyx_n_u_root_cdeg_var;
static PyObject *__pyx_n_s_root_info;
static PyObject *__pyx_n_u_root_ncoefs_count;
static PyObject *__pyx_n_u_root_ncoefs_max;
static PyObject *__pyx_n_u_root_ncoefs_mean;
static PyObject *__pyx_n_u_root_ncoefs_min;
static PyObject *__pyx_n_u_root_ncoefs_var;
static PyObject *__pyx_n_u_root_pcoefs_count;
static PyObject *__pyx_n_u_root_pcoefs_max;
static PyObject *__pyx_n_u_root_pcoefs_mean;
static PyObject *__pyx_n_u_root_pcoefs_min;
static PyObject *__pyx_n_u_root_pcoefs_var;
static PyObject *__pyx_n_s_row;
static PyObject *__pyx_n_u_row;
static PyObject *__pyx_n_u_rowidxs;
static PyObject *__pyx_n_s_self;
static PyObject *__pyx_kp_s_self__scip_self__valid_cannot_be;
static PyObject *__pyx_kp_s_self_event_cannot_be_converted_t;
static PyObject *__pyx_kp_s_self_lpi_cannot_be_converted_to;
static PyObject *__pyx_kp_s_self_scip_col_cannot_be_converte;
static PyObject *__pyx_kp_s_self_scip_cons_cannot_be_convert;
static PyObject *__pyx_kp_s_self_scip_node_cannot_be_convert;
static PyObject *__pyx_kp_s_self_scip_row_cannot_be_converte;
static PyObject *__pyx_kp_s_self_scip_var_cannot_be_converte;
static PyObject *__pyx_kp_s_self_sol_cannot_be_converted_to;
static PyObject *__pyx_n_u_selnode;
static PyObject *__pyx_n_s_send;
static PyObject *__pyx_n_s_sense;
static PyObject *__pyx_n_s_sepa;
static PyObject *__pyx_n_s_sepaexeclp;
static PyObject *__pyx_n_s_sepaexecsol;
static PyObject *__pyx_n_s_sepaexit;
static PyObject *__pyx_n_s_sepaexitsol;
static PyObject *__pyx_n_s_sepafree;
static PyObject *__pyx_n_s_sepafreq;
static PyObject *__pyx_n_s_sepainit;
static PyObject *__pyx_n_s_sepainitsol;
static PyObject *__pyx_n_s_sepapriority;
static PyObject *__pyx_n_s_separate;
static PyObject *__pyx_n_u_separate;
static PyObject *__pyx_n_s_setBoolParam;
static PyObject *__pyx_n_s_setIntParam;
static PyObject *__pyx_n_s_setMaximize;
static PyObject *__pyx_n_s_setMinimize;
static PyObject *__pyx_n_s_setstate;
static PyObject *__pyx_n_s_setstate_cython;
static PyObject *__pyx_n_s_shape;
static PyObject *__pyx_n_s_shareaux;
static PyObject *__pyx_n_s_side;
static PyObject *__pyx_n_u_skipsolve;
static PyObject *__pyx_n_u_slack;
static PyObject *__pyx_n_s_slots;
static PyObject *__pyx_n_s_sol;
static PyObject *__pyx_n_u_sol_is_at_lb;
static PyObject *__pyx_n_u_sol_is_at_ub;
static PyObject *__pyx_n_u_solfracs;
static PyObject *__pyx_n_s_solinfeasible;
static PyObject *__pyx_n_s_solution;
static PyObject *__pyx_n_s_solutions;
static PyObject *__pyx_n_u_solvals;
static PyObject *__pyx_n_s_solvecip;
static PyObject *__pyx_n_u_solvingtime;
static PyObject *__pyx_n_s_sorted;
static PyObject *__pyx_n_s_sourceModel;
static PyObject *__pyx_n_s_splitext;
static PyObject *__pyx_n_s_sqrt;
static PyObject *__pyx_n_u_sqrt;
static PyObject *__pyx_kp_s_src_pyscipopt_expr_pxi;
static PyObject *__pyx_kp_s_src_pyscipopt_scip_pyx;
static PyObject *__pyx_n_u_stats;
static PyObject *__pyx_n_s_stderr;
static PyObject *__pyx_n_s_stdout;
static PyObject *__pyx_n_s_stdpriority;
static PyObject *__pyx_n_s_stickingatnode;
static PyObject *__pyx_n_u_stickingatnode;
static PyObject *__pyx_n_u_stopearly;
static PyObject *__pyx_n_s_str_conversion;
static PyObject *__pyx_kp_s_stringsource;
static PyObject *__pyx_n_s_subproblem;
static PyObject *__pyx_n_u_success;
static PyObject *__pyx_n_s_sum;
static PyObject *__pyx_n_u_sum;
static PyObject *__pyx_n_s_sumexpr;
static PyObject *__pyx_n_s_sys;
static PyObject *__pyx_n_u_targetcons;
static PyObject *__pyx_n_s_targetvalue;
static PyObject *__pyx_n_s_term;
static PyObject *__pyx_kp_u_term_length_must_be_1_or_2_but_i;
static PyObject *__pyx_n_s_termlist;
static PyObject *__pyx_n_s_terms;
static PyObject *__pyx_n_s_test;
static PyObject *__pyx_n_s_throw;
static PyObject *__pyx_n_u_timelimit;
static PyObject *__pyx_n_s_timing;
static PyObject *__pyx_n_s_timingmask;
static PyObject *__pyx_kp_u_total_number_of_solutions_found;
static PyObject *__pyx_n_s_trans;
static PyObject *__pyx_n_s_transformed;
static PyObject *__pyx_n_u_transgap;
static PyObject *__pyx_n_u_true;
static PyObject *__pyx_n_s_truediv;
static PyObject *__pyx_n_u_types;
static PyObject *__pyx_n_s_ub;
static PyObject *__pyx_n_s_ubs;
static PyObject *__pyx_n_u_ubs;
static PyObject *__pyx_n_u_unbounded;
static PyObject *__pyx_n_u_unknown;
static PyObject *__pyx_kp_u_unrecognized_objective_sense;
static PyObject *__pyx_kp_u_unrecognized_optimization_sense;
static PyObject *__pyx_kp_u_unrecognized_variable_type;
static PyObject *__pyx_n_s_update;
static PyObject *__pyx_n_s_upper;
static PyObject *__pyx_n_u_upper;
static PyObject *__pyx_n_u_upperbound;
static PyObject *__pyx_n_u_userinterrupt;
static PyObject *__pyx_n_s_usessubscip;
static PyObject *__pyx_kp_u_utf_8;
static PyObject *__pyx_n_s_v;
static PyObject *__pyx_n_s_val;
static PyObject *__pyx_n_s_val1;
static PyObject *__pyx_n_s_val2;
static PyObject *__pyx_n_s_validnode;
static PyObject *__pyx_n_u_vals;
static PyObject *__pyx_n_s_value;
static PyObject *__pyx_n_s_value_to_array;
static PyObject *__pyx_n_s_values;
static PyObject *__pyx_n_s_var;
static PyObject *__pyx_n_u_var;
static PyObject *__pyx_n_u_varbound;
static PyObject *__pyx_n_s_varexpr;
static PyObject *__pyx_n_s_variable;
static PyObject *__pyx_n_s_varidx;
static PyObject *__pyx_n_s_vars;
static PyObject *__pyx_n_s_vartuple;
static PyObject *__pyx_n_u_vartuple;
static PyObject *__pyx_n_s_version;
static PyObject *__pyx_n_s_version_info;
static PyObject *__pyx_n_s_vtype;
static PyObject *__pyx_n_u_w;
static PyObject *__pyx_n_s_warn;
static PyObject *__pyx_n_s_warnings;
static PyObject *__pyx_n_s_weakref;
static PyObject *__pyx_n_s_weight;
static PyObject *__pyx_n_s_weights;
static PyObject *__pyx_n_s_write;
static PyObject *__pyx_n_s_write_zeros;
static PyObject *__pyx_kp_u_wrote_parameter_settings_to_file;
static PyObject *__pyx_kp_u_wrote_problem_to_file;
static PyObject *__pyx_n_u_x;
static PyObject *__pyx_n_u_xor;
static PyObject *__pyx_n_u_zero;
static PyObject *__pyx_n_s_zeros;
static PyObject *__pyx_lambda_funcdef_9pyscipopt_4scip_lambda7(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x); /* proto */
static PyObject *__pyx_lambda_funcdef_9pyscipopt_4scip_lambda8(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip__is_number(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_e); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2_expr_richcmp(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_other, PyObject *__pyx_v_op); /* proto */
static PyObject *__pyx_lambda_funcdef_lambda(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_v); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_8__init___1genexpr(PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term___init__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_vartuple); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_2__getitem__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_idx); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_4__hash__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_6__eq__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_8__len__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_10__add__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Term_12__repr__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4buildGenExprObj(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Expr___init__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_terms); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_2__getitem__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_key); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_4__iter__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_6__next__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_8__abs__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_10__add__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_12__iadd__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_14__mul__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_16__div__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
#endif
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_18__rdiv__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_20__truediv__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_22__rtruediv__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_24__pow__(PyObject *__pyx_v_self, PyObject *__pyx_v_other, CYTHON_UNUSED PyObject *__pyx_v_modulo); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_26__neg__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_28__sub__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_30__radd__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_32__rmul__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_34__rsub__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_36__richcmp__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_other, PyObject *__pyx_v_op); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_38normalize(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_40__repr__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_6degree_genexpr(PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_42degree(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_5terms___get__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Expr_5terms_2__set__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Expr_5terms_4__del__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_44__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Expr_46__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Expr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons___init__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v_expr, PyObject *__pyx_v_lhs, PyObject *__pyx_v_rhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_2normalize(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_4__richcmp__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v_other, PyObject *__pyx_v_op); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_6__repr__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_8__nonzero__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_4expr___get__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4expr_2__set__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4expr_4__del__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_4_lhs___get__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4_lhs_2__set__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4_lhs_4__del__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_4_rhs___get__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4_rhs_2__set__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ExprCons_4_rhs_4__del__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_10__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ExprCons_12__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6quicksum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_termlist); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8quickprod(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_termlist); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2Op_getOpIndex(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED PyObject *__pyx_v_self, PyObject *__pyx_v_op); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr___init__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_2__abs__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_4__add__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_6__mul__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_8__pow__(PyObject *__pyx_v_self, PyObject *__pyx_v_other, CYTHON_UNUSED PyObject *__pyx_v_modulo); /* proto */
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_10__div__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
#endif
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_12__rdiv__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_14__truediv__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_16__rtruediv__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_18__neg__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_20__sub__(PyObject *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_22__radd__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_24__rmul__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_26__rsub__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_28__richcmp__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_other, PyObject *__pyx_v_op); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_30degree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_32getOp(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_13operatorIndex___get__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_13operatorIndex_2__set__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_13operatorIndex_4__del__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_3_op___get__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_3_op_2__set__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_3_op_4__del__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_8children___get__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_8children_2__set__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7GenExpr_8children_4__del__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_34__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7GenExpr_36__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_GenExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7SumExpr___init__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_lambda_funcdef_lambda3(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_child); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7SumExpr_2__repr__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7SumExpr_8constant___get__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7SumExpr_8constant_2__set__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7SumExpr_8constant_4__del__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7SumExpr_5coefs___get__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7SumExpr_5coefs_2__set__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7SumExpr_5coefs_4__del__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7SumExpr_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7SumExpr_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_SumExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ProdExpr___init__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_lambda_funcdef_lambda4(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_child); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ProdExpr_2__repr__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ProdExpr_8constant___get__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ProdExpr_8constant_2__set__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8ProdExpr_8constant_4__del__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ProdExpr_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8ProdExpr_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_ProdExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7VarExpr___init__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self, PyObject *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7VarExpr_2__repr__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7VarExpr_3var___get__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7VarExpr_3var_2__set__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7VarExpr_3var_4__del__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7VarExpr_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7VarExpr_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_VarExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7PowExpr___init__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7PowExpr_2__repr__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7PowExpr_4expo___get__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7PowExpr_4expo_2__set__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7PowExpr_4expo_4__del__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7PowExpr_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7PowExpr_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PowExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_9UnaryExpr___init__(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr *__pyx_v_self, PyObject *__pyx_v_op, PyObject *__pyx_v_expr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9UnaryExpr_2__repr__(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9UnaryExpr_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9UnaryExpr_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Constant___init__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self, PyObject *__pyx_v_number); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Constant_2__repr__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Constant_6number___get__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Constant_6number_2__set__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Constant_6number_4__del__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Constant_4__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Constant_6__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Constant *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10exp(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_12log(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_14sqrt(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_16expr_to_nodes(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_18value_to_array(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_val, PyObject *__pyx_v_nodes); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_20expr_to_array(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_expr, PyObject *__pyx_v_nodes); /* proto */
static int __pyx_pf_9pyscipopt_4scip_2LP___init__(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_sense); /* proto */
static void __pyx_pf_9pyscipopt_4scip_2LP_2__dealloc__(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_4__repr__(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_6writeLP(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_filename); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_8readLP(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_filename); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_10infinity(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_12isInfinity(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_val); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_14addCol(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_entries, PyObject *__pyx_v_obj, PyObject *__pyx_v_lb, PyObject *__pyx_v_ub); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_7addCols_genexpr(PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_16addCols(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_entrieslist, PyObject *__pyx_v_objs, PyObject *__pyx_v_lbs, PyObject *__pyx_v_ubs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_18delCols(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_firstcol, PyObject *__pyx_v_lastcol); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_20addRow(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_entries, PyObject *__pyx_v_lhs, PyObject *__pyx_v_rhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_7addRows_genexpr(PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_22addRows(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_entrieslist, PyObject *__pyx_v_lhss, PyObject *__pyx_v_rhss); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_24delRows(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_firstrow, PyObject *__pyx_v_lastrow); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_26getBounds(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_firstcol, PyObject *__pyx_v_lastcol); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_28getSides(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_firstrow, PyObject *__pyx_v_lastrow); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_30chgObj(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_col, PyObject *__pyx_v_obj); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_32chgCoef(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_row, PyObject *__pyx_v_col, PyObject *__pyx_v_newval); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_34chgBound(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_col, PyObject *__pyx_v_lb, PyObject *__pyx_v_ub); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_36chgSide(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_row, PyObject *__pyx_v_lhs, PyObject *__pyx_v_rhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_38clear(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_40nrows(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_42ncols(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_44solve(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, PyObject *__pyx_v_dual); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_46getPrimal(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_48isPrimalFeasible(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_50getDual(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_52isDualFeasible(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_54getPrimalRay(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_56getDualRay(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_58getNIterations(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_60getRedcost(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_62getBasisInds(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_4name___get__(struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_64__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_2LP_66__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_LP *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_bendersfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_2bendersinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_4bendersexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_6bendersinitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_8bendersexitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_10bendersinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_12bendersexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_14benderscreatesub(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_probnumber); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_16benderspresubsolve(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_enfotype, CYTHON_UNUSED PyObject *__pyx_v_checkint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_18benderssolvesubconvex(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_probnumber, CYTHON_UNUSED PyObject *__pyx_v_onlyconvex); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_20benderssolvesub(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_probnumber); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_22benderspostsolve(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_enfotype, CYTHON_UNUSED PyObject *__pyx_v_mergecandidates, CYTHON_UNUSED PyObject *__pyx_v_npriomergecands, CYTHON_UNUSED PyObject *__pyx_v_checkint, CYTHON_UNUSED PyObject *__pyx_v_infeasible); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_24bendersfreesub(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_probnumber); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_26bendersgetvar(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_variable, CYTHON_UNUSED PyObject *__pyx_v_probnumber); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Benders_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Benders_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Benders_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Benders_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_28__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Benders_30__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_benderscutfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_2benderscutinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_4benderscutexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_6benderscutinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_8benderscutexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_10benderscutexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_probnumber, CYTHON_UNUSED PyObject *__pyx_v_enfotype); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_7benders___get__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_7benders_2__set__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_7benders_4__del__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Benderscut_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_12__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Benderscut_14__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_branchfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_2branchinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_4branchexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_6branchinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_8branchexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_10branchexeclp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_allowaddcons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_12branchexecext(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_allowaddcons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_14branchexecps(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_allowaddcons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Branchrule_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Branchrule_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_16__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Branchrule_18__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_consfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_2consinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_4consexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_6consinitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_8consexitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_10consinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_12consexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_restart); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_14consdelete(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_16constrans(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_sourceconstraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_18consinitlp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_20conssepalp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_22conssepasol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss, CYTHON_UNUSED PyObject *__pyx_v_solution); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_24consenfolp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss, CYTHON_UNUSED PyObject *__pyx_v_solinfeasible); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_26consenforelax(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss, CYTHON_UNUSED PyObject *__pyx_v_solinfeasible); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_28consenfops(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss, CYTHON_UNUSED PyObject *__pyx_v_solinfeasible, CYTHON_UNUSED PyObject *__pyx_v_objinfeasible); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_30conscheck(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_solution, CYTHON_UNUSED PyObject *__pyx_v_checkintegrality, CYTHON_UNUSED PyObject *__pyx_v_checklprows, CYTHON_UNUSED PyObject *__pyx_v_printreason, CYTHON_UNUSED PyObject *__pyx_v_completely); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_32consprop(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nusefulconss, CYTHON_UNUSED PyObject *__pyx_v_nmarkedconss, CYTHON_UNUSED PyObject *__pyx_v_proptiming); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_34conspresol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints, CYTHON_UNUSED PyObject *__pyx_v_nrounds, CYTHON_UNUSED PyObject *__pyx_v_presoltiming, CYTHON_UNUSED PyObject *__pyx_v_nnewfixedvars, CYTHON_UNUSED PyObject *__pyx_v_nnewaggrvars, CYTHON_UNUSED PyObject *__pyx_v_nnewchgvartypes, CYTHON_UNUSED PyObject *__pyx_v_nnewchgbds, CYTHON_UNUSED PyObject *__pyx_v_nnewholes, CYTHON_UNUSED PyObject *__pyx_v_nnewdelconss, CYTHON_UNUSED PyObject *__pyx_v_nnewaddconss, CYTHON_UNUSED PyObject *__pyx_v_nnewupgdconss, CYTHON_UNUSED PyObject *__pyx_v_nnewchgcoefs, CYTHON_UNUSED PyObject *__pyx_v_nnewchgsides, PyObject *__pyx_v_result_dict); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_36consresprop(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_38conslock(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint, CYTHON_UNUSED PyObject *__pyx_v_locktype, CYTHON_UNUSED PyObject *__pyx_v_nlockspos, CYTHON_UNUSED PyObject *__pyx_v_nlocksneg); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_40consactive(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_42consdeactive(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_44consenable(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_46consdisable(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_48consdelvars(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraints); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_50consprint(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_52conscopy(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_54consparse(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_56consgetvars(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_58consgetnvars(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_constraint); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_60consgetdivebdchgs(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Conshdlr_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Conshdlr_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Conshdlr_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Conshdlr_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_62__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Conshdlr_64__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_eventcopy(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_2eventfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_4eventinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_6eventexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_8eventinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_10eventexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_12eventdelete(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_14eventexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_event); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_9Eventhdlr_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_9Eventhdlr_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_9Eventhdlr_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_9Eventhdlr_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_16__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_9Eventhdlr_18__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_heurfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_2heurinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_4heurexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_6heurinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_8heurexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_10heurexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_heurtiming, CYTHON_UNUSED PyObject *__pyx_v_nodeinfeasible); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Heur_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Heur_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Heur_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Heur_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_12__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Heur_14__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_presolfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_2presolinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_4presolexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_6presolinitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_8presolexitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_10presolexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_nrounds, CYTHON_UNUSED PyObject *__pyx_v_presoltiming); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Presol_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Presol_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_12__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Presol_14__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_pricerfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_2pricerinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_4pricerexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_6pricerinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_8pricerexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_10pricerredcost(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_12pricerfarkas(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Pricer_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Pricer_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_14__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Pricer_16__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_propfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_2propinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_4propexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_6propinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_8propexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_restart); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_10propinitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_12propexitpre(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_14proppresol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_nrounds, CYTHON_UNUSED PyObject *__pyx_v_presoltiming, CYTHON_UNUSED PyObject *__pyx_v_result_dict); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_16propexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_proptiming); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_18propresprop(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_confvar, CYTHON_UNUSED PyObject *__pyx_v_inferinfo, CYTHON_UNUSED PyObject *__pyx_v_bdtype, CYTHON_UNUSED PyObject *__pyx_v_relaxedbd); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Prop_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Prop_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_20__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Prop_22__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_sepafree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_2sepainit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_4sepaexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_6sepainitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_8sepaexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_10sepaexeclp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_12sepaexecsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_solution); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Sepa_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Sepa_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Sepa_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Sepa_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_14__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Sepa_16__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_relaxfree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_2relaxinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_4relaxexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_6relaxinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_8relaxexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_10relaxexec(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Relax_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Relax_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Relax_4name_2__set__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Relax_4name_4__del__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_12__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Relax_14__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_nodefree(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_2nodeinit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_4nodeexit(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_6nodeinitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_8nodeexitsol(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_10nodeselect(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_12nodecomp(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_node1, CYTHON_UNUSED PyObject *__pyx_v_node2); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_5model___get__(struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Nodesel_5model_2__set__(struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_7Nodesel_5model_4__del__(struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_14__reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_7Nodesel_16__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_14PY_SCIP_RESULT___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_14PY_SCIP_RESULT_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_20PY_SCIP_PARAMSETTING___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_20PY_SCIP_PARAMSETTING_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_21PY_SCIP_PARAMEMPHASIS___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_21PY_SCIP_PARAMEMPHASIS_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_14PY_SCIP_STATUS___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_14PY_SCIP_STATUS_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_13PY_SCIP_STAGE___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_13PY_SCIP_STAGE_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_16PY_SCIP_NODETYPE___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_16PY_SCIP_NODETYPE_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_18PY_SCIP_PROPTIMING___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_18PY_SCIP_PROPTIMING_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_20PY_SCIP_PRESOLTIMING___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_20PY_SCIP_PRESOLTIMING_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_18PY_SCIP_HEURTIMING___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_18PY_SCIP_HEURTIMING_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_EVENTTYPE___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_EVENTTYPE_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_LPSOLSTAT___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_LPSOLSTAT_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_BRANCHDIR___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_17PY_SCIP_BRANCHDIR_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_23PY_SCIP_BENDERSENFOTYPE___reduce_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_23PY_SCIP_BENDERSENFOTYPE_2__setstate_cython__(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_22PY_SCIP_CALL(CYTHON_UNUSED PyObject *__pyx_self, SCIP_RETCODE __pyx_v_rc); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_getType(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_2__repr__(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_4getNewBound(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_6getOldBound(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_8getVar(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_10getNode(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Event_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Event_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_12__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Event_14__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Event *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_getLPPos(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_2getBasisStatus(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_4isIntegral(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_6getVar(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_8getPrimsol(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_10getLb(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_12getUb(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Column_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_6Column_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_14__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_6Column_16__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Column *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_getLhs(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_2getRhs(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_4getConstant(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_6getLPPos(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_8getBasisStatus(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_10isIntegral(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_12isModifiable(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_14getNNonz(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_16getNLPNonz(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_18getCols(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_20getVals(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_3Row_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_3Row_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_22__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_3Row_24__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Solution_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Solution_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Solution_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Solution___reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Solution_2__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_getParent(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_2getNumber(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_4getDepth(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_6getType(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_8getLowerbound(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_10getEstimate(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_12getNAddedConss(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_14isActive(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_16isPropagatedAgain(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_18getBranchInfos(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Node_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_4Node_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_20__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_4Node_22__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_ptr(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_2__repr__(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_4vtype(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_6isOriginal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_8isInLP(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_10getIndex(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_12getCol(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_14getLbOriginal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_16getUbOriginal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_18getLbGlobal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_20getUbGlobal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_22getLbLocal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_24getUbLocal(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_26getObj(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_28getLPSol(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Variable_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_8Variable_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_30__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_8Variable_32__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_4name___get__(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint___repr__(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_2isOriginal(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_4isInitial(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_6isSeparated(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_8isEnforced(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_10isChecked(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_12isPropagated(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_14isLocal(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_16isModifiable(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_18isDynamic(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_20isRemovable(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_22isStickingAtNode(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_24isLinear(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_26isQuadratic(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Constraint_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_10Constraint_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_28__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_10Constraint_30__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Model___init__(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_problemName, PyObject *__pyx_v_defaultPlugins, struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_sourceModel, PyObject *__pyx_v_origcopy, PyObject *__pyx_v_globalcopy, PyObject *__pyx_v_enablepricing); /* proto */
static void __pyx_pf_9pyscipopt_4scip_5Model_2__dealloc__(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_4create(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_6includeDefaultPlugins(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_8createProbBasic(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_problemName); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_10freeProb(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_12freeTransform(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_14version(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_16printVersion(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_18getProbName(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_20getTotalTime(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_22getSolvingTime(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_24getReadingTime(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_26getPresolvingTime(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_28getNNodes(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_30getUpperbound(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_32getLowerbound(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_34getCurrentNode(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_36getNLPIterations(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_38getGap(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_40getDepth(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_42infinity(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_44epsilon(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_46feastol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_48feasFrac(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_50frac(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_52isZero(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_54isFeasZero(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_56isInfinity(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_58isFeasNegative(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_60isFeasIntegral(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_62isLE(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_val1, PyObject *__pyx_v_val2); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_64isLT(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_val1, PyObject *__pyx_v_val2); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_66isGE(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_val1, PyObject *__pyx_v_val2); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_68isGT(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_val1, PyObject *__pyx_v_val2); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_70getCondition(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_exact); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_72setMinimize(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_74setMaximize(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_76setObjlimit(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_objlimit); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_78getObjlimit(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_80setObjective(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_coeffs, PyObject *__pyx_v_sense, PyObject *__pyx_v_clear); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_82getObjective(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_84addObjoffset(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_offset, PyObject *__pyx_v_solutions); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_86getObjoffset(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_original); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_88setPresolve(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_setting); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_90setProbName(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_92setSeparating(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_setting); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_94setHeuristics(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_setting); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_96disablePropagation(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_onlyroot); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_98writeProblem(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename, PyObject *__pyx_v_trans); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_100addVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_vtype, PyObject *__pyx_v_lb, PyObject *__pyx_v_ub, PyObject *__pyx_v_obj, PyObject *__pyx_v_pricedVar); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_102releaseVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_104getTransformedVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_106addVarLocks(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_nlocksdown, PyObject *__pyx_v_nlocksup); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_108fixVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_val); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_110delVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_112tightenVarLb(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_lb, PyObject *__pyx_v_force); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_114tightenVarUb(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_ub, PyObject *__pyx_v_force); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_116tightenVarUbGlobal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_ub, PyObject *__pyx_v_force); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_118tightenVarLbGlobal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_lb, PyObject *__pyx_v_force); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_120chgVarLb(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_lb); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_122chgVarUb(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_ub); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_124chgVarLbGlobal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_lb); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_126chgVarUbGlobal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_ub); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_128chgVarLbNode(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_node, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_lb); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_130chgVarUbNode(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_node, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_ub); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_132chgVarType(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_vtype); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_134getVars(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_transformed); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_136getNVars(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_138getNConss(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_140updateNodeLowerbound(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_node, PyObject *__pyx_v_lb); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_142getLPSolstat(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_144constructLP(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_146getLPObjVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_148getLPColsData(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_150getLPRowsData(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_152getNLPRows(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_154getNLPCols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_156getLPBasisInd(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_158getLPBInvRow(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_160getLPBInvARow(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_162isLPSolBasic(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_164createEmptyRowSepa(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_sepa, PyObject *__pyx_v_name, PyObject *__pyx_v_lhs, PyObject *__pyx_v_rhs, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_removable); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_166createEmptyRowUnspec(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_lhs, PyObject *__pyx_v_rhs, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_removable); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_168getRowActivity(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_170getRowLPActivity(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_172releaseRow(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_174cacheRowExtensions(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_176flushRowExtensions(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_178addVarToRow(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_180printRow(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_182addPoolCut(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_184getCutEfficacy(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_cut, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_186isCutEfficacious(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_cut, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_188addCut(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_cut, PyObject *__pyx_v_forcecut); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_190getNCuts(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_192getNCutsApplied(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_194addCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_cons, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_196_addLinCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_lincons, PyObject *__pyx_v_kwargs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_198_addQuadCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_quadcons, PyObject *__pyx_v_kwargs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_200_addNonlinearCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_cons, PyObject *__pyx_v_kwargs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_202_addGenNonlinearCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_ExprCons *__pyx_v_cons, PyObject *__pyx_v_kwargs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_204addConsCoeff(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_coeff); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_206addConsNode(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_node, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_validnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_208addConsLocal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Node *__pyx_v_validnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_210addConsSOS1(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_vars, PyObject *__pyx_v_weights, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_212addConsSOS2(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_vars, PyObject *__pyx_v_weights, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_214addConsAnd(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_vars, PyObject *__pyx_v_resvar, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_216addConsOr(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_vars, PyObject *__pyx_v_resvar, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_218addConsXor(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_vars, PyObject *__pyx_v_rhsvar, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_220addConsCardinality(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_consvars, PyObject *__pyx_v_cardval, PyObject *__pyx_v_indvars, PyObject *__pyx_v_weights, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_222addConsIndicator(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_cons, PyObject *__pyx_v_binvar, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_224addPyCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_226addVarSOS1(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_weight); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_228appendVarSOS1(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_230addVarSOS2(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_weight); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_232appendVarSOS2(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_234setInitial(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_newInit); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_236setRemovable(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_newRem); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_238setEnforced(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_newEnf); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_240setCheck(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_newCheck); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_242chgRhs(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_rhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_244chgLhs(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, PyObject *__pyx_v_lhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_246getRhs(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_248getLhs(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_250getActivity(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_252getSlack(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol, PyObject *__pyx_v_side); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_254getTransformedCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_256getTermsQuadratic(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_258setRelaxSolVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_val); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_260getConss(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_262getNConss(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_264delCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_266delConsLocal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_268getValsLinear(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_270getDualMultiplier(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_272getDualsolLinear(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_274getDualfarkasLinear(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Constraint *__pyx_v_cons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_276getVarRedcost(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_278optimize(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_280presolve(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_282initBendersDefault(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_subproblems); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_284computeBestSolSubproblems(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_286freeBendersSubproblems(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_288updateBendersLowerbounds(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_lowerbounds, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_290activateBenders(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, int __pyx_v_nsubproblems); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_292addBendersSubproblem(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_subproblem); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_294setupBendersSubproblem(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_probnumber, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_296solveBendersSubproblem(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_probnumber, PyObject *__pyx_v_enfotype, PyObject *__pyx_v_solvecip, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_298getBendersVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders, PyObject *__pyx_v_probnumber); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_300includeEventhdlr(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr, PyObject *__pyx_v_name, PyObject *__pyx_v_desc); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_302includePricer(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Pricer *__pyx_v_pricer, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_delay); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_304includeConshdlr(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_conshdlr, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_sepapriority, PyObject *__pyx_v_enfopriority, PyObject *__pyx_v_chckpriority, PyObject *__pyx_v_sepafreq, PyObject *__pyx_v_propfreq, PyObject *__pyx_v_eagerfreq, PyObject *__pyx_v_maxprerounds, PyObject *__pyx_v_delaysepa, PyObject *__pyx_v_delayprop, PyObject *__pyx_v_needscons, PyObject *__pyx_v_proptiming, PyObject *__pyx_v_presoltiming); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_306createCons(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Conshdlr *__pyx_v_conshdlr, PyObject *__pyx_v_name, PyObject *__pyx_v_initial, PyObject *__pyx_v_separate, PyObject *__pyx_v_enforce, PyObject *__pyx_v_check, PyObject *__pyx_v_propagate, PyObject *__pyx_v_local, PyObject *__pyx_v_modifiable, PyObject *__pyx_v_dynamic, PyObject *__pyx_v_removable, PyObject *__pyx_v_stickingatnode); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_308includePresol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Presol *__pyx_v_presol, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_maxrounds, PyObject *__pyx_v_timing); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_310includeSepa(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Sepa *__pyx_v_sepa, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_freq, PyObject *__pyx_v_maxbounddist, PyObject *__pyx_v_usessubscip, PyObject *__pyx_v_delay); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_312includeProp(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Prop *__pyx_v_prop, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_presolpriority, PyObject *__pyx_v_presolmaxrounds, PyObject *__pyx_v_proptiming, PyObject *__pyx_v_presoltiming, PyObject *__pyx_v_priority, PyObject *__pyx_v_freq, PyObject *__pyx_v_delay); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_314includeHeur(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_heur, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_dispchar, PyObject *__pyx_v_priority, PyObject *__pyx_v_freq, PyObject *__pyx_v_freqofs, PyObject *__pyx_v_maxdepth, PyObject *__pyx_v_timingmask, PyObject *__pyx_v_usessubscip); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_316includeRelax(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Relax *__pyx_v_relax, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_freq); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_318includeBranchrule(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Branchrule *__pyx_v_branchrule, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_maxdepth, PyObject *__pyx_v_maxbounddist); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_320getChildren(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_322includeBenders(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_cutlp, PyObject *__pyx_v_cutpseudo, PyObject *__pyx_v_cutrelax, PyObject *__pyx_v_shareaux); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_324includeBenderscut(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Benders *__pyx_v_benders, struct __pyx_obj_9pyscipopt_4scip_Benderscut *__pyx_v_benderscut, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_priority, PyObject *__pyx_v_islpcut); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_326getLPBranchCands(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_328getPseudoBranchCands(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_330branchVar(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_variable); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_332branchVarVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_variable, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_334calcNodeselPriority(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_variable, PyObject *__pyx_v_branchdir, PyObject *__pyx_v_targetvalue); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_336calcChildEstimate(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_variable, PyObject *__pyx_v_targetvalue); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_338createChild(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_nodeselprio, PyObject *__pyx_v_estimate); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_340startDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_342endDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_344chgVarObjDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_newobj); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_346chgVarLbDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_newbound); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_348chgVarUbDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_newbound); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_350getVarLbDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_352getVarUbDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_354chgRowLhsDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row, PyObject *__pyx_v_newlhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_356chgRowRhsDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row, PyObject *__pyx_v_newrhs); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_358addRowDive(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_360solveDiveLP(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_itlim); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_362inRepropagation(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_364startProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_366endProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_368chgVarObjProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_newobj); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_370fixVarProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_fixedval); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_372isObjChangedProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_374inProbing(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_376solveProbingLP(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_itlim); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_378interruptSolve(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_380createSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Heur *__pyx_v_heur); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_382printBestSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_write_zeros); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_384printSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, PyObject *__pyx_v_write_zeros); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_386writeBestSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename, PyObject *__pyx_v_write_zeros); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_388writeSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, PyObject *__pyx_v_filename, PyObject *__pyx_v_write_zeros); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_390readSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_392readSolFile(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_394setSolVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_val); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_396trySol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, PyObject *__pyx_v_printreason, PyObject *__pyx_v_completely, PyObject *__pyx_v_checkbounds, PyObject *__pyx_v_checkintegrality, PyObject *__pyx_v_checklprows, PyObject *__pyx_v_free); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_398checkSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, PyObject *__pyx_v_printreason, PyObject *__pyx_v_completely, PyObject *__pyx_v_checkbounds, PyObject *__pyx_v_checkintegrality, PyObject *__pyx_v_checklprows, PyObject *__pyx_v_original); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_400addSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution, PyObject *__pyx_v_free); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_402freeSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_solution); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_404getSols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_406getBestSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_408getSolObjVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol, PyObject *__pyx_v_original); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_410getObjVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_original); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_412getSolVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Solution *__pyx_v_sol, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_414getVal(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_416getPrimalbound(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_418getDualbound(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_420getDualboundRoot(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_422writeName(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_424getStage(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_426getStatus(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_428getObjectiveSense(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_430catchEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_432dropEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_434catchVarEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_436dropVarEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Variable *__pyx_v_var, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_438catchRowEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_440dropRowEvent(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Row *__pyx_v_row, PyObject *__pyx_v_eventtype, struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *__pyx_v_eventhdlr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_442printStatistics(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_444writeStatistics(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_446getNLPs(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_448hideOutput(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_quiet); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_450redirectOutput(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_452setBoolParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_454setIntParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_456setLongintParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_458setRealParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_460setCharParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_462setStringParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_464setParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_466getParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_468readParams(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_file); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_470writeParams(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_filename, PyObject *__pyx_v_comments, PyObject *__pyx_v_onlychanged); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_472resetParam(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_474resetParams(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_476setEmphasis(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_paraemphasis, PyObject *__pyx_v_quiet); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_478readProblem(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_file, PyObject *__pyx_v_extension); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_480count(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_482getNCountedSols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_484setParamsCountsols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_486freeReoptSolve(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_488chgReoptObjective(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_coeffs, PyObject *__pyx_v_sense); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_490getVariablePseudocost(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_variable); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_492includeNodesel(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, struct __pyx_obj_9pyscipopt_4scip_Nodesel *__pyx_v_nodesel, PyObject *__pyx_v_name, PyObject *__pyx_v_desc, PyObject *__pyx_v_stdpriority, PyObject *__pyx_v_memsavepriority); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_494getMapping(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_496getTimeSol(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_498getNPrimalSols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_500setup_ml_nodelsel(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_flag, CYTHON_UNUSED PyObject *__pyx_v_indicator_arr); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_502getState(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_prev_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_504getDingStateRows(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_506getDingStateLPgraph(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_508getDingStateCols(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_510getKhalilState(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_root_info, PyObject *__pyx_v_candidates); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_512getSolvingStats(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_514executeBranchRule(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_allowaddcons); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_516getConsVals(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_4data___get__(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Model_4data_2__set__(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_9pyscipopt_4scip_5Model_4data_4__del__(struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_518__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_5Model_520__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9pyscipopt_4scip_Model *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_24is_memory_freed(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_26print_memory_in_use(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_28__pyx_unpickle_Expr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_30__pyx_unpickle_ExprCons(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_32__pyx_unpickle_GenExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_34__pyx_unpickle_SumExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_36__pyx_unpickle_ProdExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_38__pyx_unpickle_VarExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_40__pyx_unpickle_PowExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_42__pyx_unpickle_UnaryExpr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_44__pyx_unpickle_Constant(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_46__pyx_unpickle_Benders(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_48__pyx_unpickle_Benderscut(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_50__pyx_unpickle_Branchrule(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_52__pyx_unpickle_Conshdlr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_54__pyx_unpickle_Eventhdlr(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_56__pyx_unpickle_Heur(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_58__pyx_unpickle_Presol(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_60__pyx_unpickle_Pricer(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_62__pyx_unpickle_Prop(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_64__pyx_unpickle_Sepa(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_66__pyx_unpickle_Relax(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_9pyscipopt_4scip_68__pyx_unpickle_Nodesel(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
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*
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* # number of coefficients
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*
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/* "pyscipopt/scip.pyx":4179
*
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*
*/
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*
*
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*/
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*
* vals = SCIProwGetVals(row)
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__pyx_v_npos = 0;
__pyx_v_nneg = 0;
__pyx_v_abs_sum_norm = 0.0;
__pyx_v_pos_sum_norm = 0.0;
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* vals = SCIProwGetVals(row)
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*/
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for (__pyx_t_44 = 0; __pyx_t_44 < __pyx_t_43; __pyx_t_44+=1) {
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/* "pyscipopt/scip.pyx":4366
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* min1 = min(min1, vals[i])
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goto __pyx_L9;
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/* "pyscipopt/scip.pyx":4373
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/* "pyscipopt/scip.pyx":4374
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for (__pyx_t_44 = 0; __pyx_t_44 < __pyx_t_43; __pyx_t_44+=1) {
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/* "pyscipopt/scip.pyx":4379
*
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* stdev = SQRT(stdev / nnzrs) if nnzrs != 0 else 0
*
* cons_npos[row_i] = npos # <<<<<<<<<<<<<<
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*/
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/* "pyscipopt/scip.pyx":4383
*
* cons_npos[row_i] = npos
* cons_nneg[row_i] = nneg # <<<<<<<<<<<<<<
* cons_sum_abs[row_i] = abs_sum_norm
* cons_sum_pos[row_i] = pos_sum_norm
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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/* "pyscipopt/scip.pyx":4384
* cons_npos[row_i] = npos
* cons_nneg[row_i] = nneg
* cons_sum_abs[row_i] = abs_sum_norm # <<<<<<<<<<<<<<
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__pyx_t_40 = -1;
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4385
* cons_nneg[row_i] = nneg
* cons_sum_abs[row_i] = abs_sum_norm
* cons_sum_pos[row_i] = pos_sum_norm # <<<<<<<<<<<<<<
* cons_sum_neg[row_i] = neg_sum_norm
* cons_coef_mean[row_i] = mean
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4386
* cons_sum_abs[row_i] = abs_sum_norm
* cons_sum_pos[row_i] = pos_sum_norm
* cons_sum_neg[row_i] = neg_sum_norm # <<<<<<<<<<<<<<
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* cons_coef_stdev[row_i] = stdev
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4387
* cons_sum_pos[row_i] = pos_sum_norm
* cons_sum_neg[row_i] = neg_sum_norm
* cons_coef_mean[row_i] = mean # <<<<<<<<<<<<<<
* cons_coef_stdev[row_i] = stdev
* cons_coef_min[row_i] = min1
*/
__pyx_t_39 = __pyx_v_row_i;
__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_coef_mean.diminfo[0].shape)) __pyx_t_40 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4388
* cons_sum_neg[row_i] = neg_sum_norm
* cons_coef_mean[row_i] = mean
* cons_coef_stdev[row_i] = stdev # <<<<<<<<<<<<<<
* cons_coef_min[row_i] = min1
* cons_coef_max[row_i] = max1
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_coef_stdev.diminfo[0].shape)) __pyx_t_40 = 0;
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/* "pyscipopt/scip.pyx":4389
* cons_coef_mean[row_i] = mean
* cons_coef_stdev[row_i] = stdev
* cons_coef_min[row_i] = min1 # <<<<<<<<<<<<<<
* cons_coef_max[row_i] = max1
*
*/
__pyx_t_39 = __pyx_v_row_i;
__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_coef_min.diminfo[0].shape)) __pyx_t_40 = 0;
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/* "pyscipopt/scip.pyx":4390
* cons_coef_stdev[row_i] = stdev
* cons_coef_min[row_i] = min1
* cons_coef_max[row_i] = max1 # <<<<<<<<<<<<<<
*
* cons_dual_sol[row_i] = SCIProwGetDualsol(row)
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_coef_max.diminfo[0].shape)) __pyx_t_40 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4392
* cons_coef_max[row_i] = max1
*
* cons_dual_sol[row_i] = SCIProwGetDualsol(row) # <<<<<<<<<<<<<<
* stat = SCIProwGetBasisStatus(row)
* if stat == SCIP_BASESTAT_LOWER:
*/
__pyx_t_39 = __pyx_v_row_i;
__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_dual_sol.diminfo[0].shape)) __pyx_t_40 = 0;
if (unlikely(__pyx_t_40 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4393
*
* cons_dual_sol[row_i] = SCIProwGetDualsol(row)
* stat = SCIProwGetBasisStatus(row) # <<<<<<<<<<<<<<
* if stat == SCIP_BASESTAT_LOWER:
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*/
__pyx_v_stat = SCIProwGetBasisStatus(__pyx_v_row);
/* "pyscipopt/scip.pyx":4394
* cons_dual_sol[row_i] = SCIProwGetDualsol(row)
* stat = SCIProwGetBasisStatus(row)
* if stat == SCIP_BASESTAT_LOWER: # <<<<<<<<<<<<<<
* cons_basis_status[row_i] = 0
* elif stat == SCIP_BASESTAT_BASIC:
*/
switch (__pyx_v_stat) {
case SCIP_BASESTAT_LOWER:
/* "pyscipopt/scip.pyx":4395
* stat = SCIProwGetBasisStatus(row)
* if stat == SCIP_BASESTAT_LOWER:
* cons_basis_status[row_i] = 0 # <<<<<<<<<<<<<<
* elif stat == SCIP_BASESTAT_BASIC:
* cons_basis_status[row_i] = 1
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_basis_status.diminfo[0].shape)) __pyx_t_40 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t *, __pyx_pybuffernd_cons_basis_status.rcbuffer->pybuffer.buf, __pyx_t_39, __pyx_pybuffernd_cons_basis_status.diminfo[0].strides) = 0;
/* "pyscipopt/scip.pyx":4394
* cons_dual_sol[row_i] = SCIProwGetDualsol(row)
* stat = SCIProwGetBasisStatus(row)
* if stat == SCIP_BASESTAT_LOWER: # <<<<<<<<<<<<<<
* cons_basis_status[row_i] = 0
* elif stat == SCIP_BASESTAT_BASIC:
*/
break;
case SCIP_BASESTAT_BASIC:
/* "pyscipopt/scip.pyx":4397
* cons_basis_status[row_i] = 0
* elif stat == SCIP_BASESTAT_BASIC:
* cons_basis_status[row_i] = 1 # <<<<<<<<<<<<<<
* elif stat == SCIP_BASESTAT_UPPER:
* cons_basis_status[row_i] = 2
*/
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__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_basis_status.diminfo[0].shape)) __pyx_t_40 = 0;
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/* "pyscipopt/scip.pyx":4396
* if stat == SCIP_BASESTAT_LOWER:
* cons_basis_status[row_i] = 0
* elif stat == SCIP_BASESTAT_BASIC: # <<<<<<<<<<<<<<
* cons_basis_status[row_i] = 1
* elif stat == SCIP_BASESTAT_UPPER:
*/
break;
case SCIP_BASESTAT_UPPER:
/* "pyscipopt/scip.pyx":4399
* cons_basis_status[row_i] = 1
* elif stat == SCIP_BASESTAT_UPPER:
* cons_basis_status[row_i] = 2 # <<<<<<<<<<<<<<
* else:
* cons_basis_status[row_i] = 3
*/
__pyx_t_39 = __pyx_v_row_i;
__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_basis_status.diminfo[0].shape)) __pyx_t_40 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_40);
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/* "pyscipopt/scip.pyx":4398
* elif stat == SCIP_BASESTAT_BASIC:
* cons_basis_status[row_i] = 1
* elif stat == SCIP_BASESTAT_UPPER: # <<<<<<<<<<<<<<
* cons_basis_status[row_i] = 2
* else:
*/
break;
default:
/* "pyscipopt/scip.pyx":4401
* cons_basis_status[row_i] = 2
* else:
* cons_basis_status[row_i] = 3 # <<<<<<<<<<<<<<
*
* return {
*/
__pyx_t_39 = __pyx_v_row_i;
__pyx_t_40 = -1;
if (__pyx_t_39 < 0) {
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if (unlikely(__pyx_t_39 < 0)) __pyx_t_40 = 0;
} else if (unlikely(__pyx_t_39 >= __pyx_pybuffernd_cons_basis_status.diminfo[0].shape)) __pyx_t_40 = 0;
if (unlikely(__pyx_t_40 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_40);
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*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t *, __pyx_pybuffernd_cons_basis_status.rcbuffer->pybuffer.buf, __pyx_t_39, __pyx_pybuffernd_cons_basis_status.diminfo[0].strides) = 3;
break;
}
}
/* "pyscipopt/scip.pyx":4403
* cons_basis_status[row_i] = 3
*
* return { # <<<<<<<<<<<<<<
* # basic features
* 'cons_is_singleton': cons_is_singleton,
*/
__Pyx_XDECREF(__pyx_r);
/* "pyscipopt/scip.pyx":4405
* return {
* # basic features
* 'cons_is_singleton': cons_is_singleton, # <<<<<<<<<<<<<<
* 'cons_is_aggregation': cons_is_aggregation,
* 'cons_is_precedence': cons_is_precedence,
*/
__pyx_t_3 = __Pyx_PyDict_NewPresized(26); if (unlikely(!__pyx_t_3)) __PYX_ERR(3, 4405, __pyx_L1_error)
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if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_singleton, ((PyObject *)__pyx_v_cons_is_singleton)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4406
* # basic features
* 'cons_is_singleton': cons_is_singleton,
* 'cons_is_aggregation': cons_is_aggregation, # <<<<<<<<<<<<<<
* 'cons_is_precedence': cons_is_precedence,
* 'cons_is_knapsack': cons_is_knapsack,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_aggregation, ((PyObject *)__pyx_v_cons_is_aggregation)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4407
* 'cons_is_singleton': cons_is_singleton,
* 'cons_is_aggregation': cons_is_aggregation,
* 'cons_is_precedence': cons_is_precedence, # <<<<<<<<<<<<<<
* 'cons_is_knapsack': cons_is_knapsack,
* 'cons_is_logicor': cons_is_logicor,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_precedence, ((PyObject *)__pyx_v_cons_is_precedence)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4408
* 'cons_is_aggregation': cons_is_aggregation,
* 'cons_is_precedence': cons_is_precedence,
* 'cons_is_knapsack': cons_is_knapsack, # <<<<<<<<<<<<<<
* 'cons_is_logicor': cons_is_logicor,
* 'cons_is_general_linear': cons_is_general_linear,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_knapsack, ((PyObject *)__pyx_v_cons_is_knapsack)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4409
* 'cons_is_precedence': cons_is_precedence,
* 'cons_is_knapsack': cons_is_knapsack,
* 'cons_is_logicor': cons_is_logicor, # <<<<<<<<<<<<<<
* 'cons_is_general_linear': cons_is_general_linear,
* 'cons_is_AND': cons_is_AND,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_logicor, ((PyObject *)__pyx_v_cons_is_logicor)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4410
* 'cons_is_knapsack': cons_is_knapsack,
* 'cons_is_logicor': cons_is_logicor,
* 'cons_is_general_linear': cons_is_general_linear, # <<<<<<<<<<<<<<
* 'cons_is_AND': cons_is_AND,
* 'cons_is_OR': cons_is_OR,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_general_linear, ((PyObject *)__pyx_v_cons_is_general_linear)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4411
* 'cons_is_logicor': cons_is_logicor,
* 'cons_is_general_linear': cons_is_general_linear,
* 'cons_is_AND': cons_is_AND, # <<<<<<<<<<<<<<
* 'cons_is_OR': cons_is_OR,
* 'cons_is_XOR': cons_is_XOR,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cons_is_AND, ((PyObject *)__pyx_v_cons_is_AND)) < 0) __PYX_ERR(3, 4405, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4412
* 'cons_is_general_linear': cons_is_general_linear,
* 'cons_is_AND': cons_is_AND,
* 'cons_is_OR': cons_is_OR, # <<<<<<<<<<<<<<
* 'cons_is_XOR': cons_is_XOR,
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* 'col_pcoefs_sum': col_pcoefs_sum,
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_nlhs_ratio_min, ((PyObject *)__pyx_v_col_nlhs_ratio_min)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
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* 'col_nlhs_ratio_max': col_nlhs_ratio_max,
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* 'col_pcoefs_sum': col_pcoefs_sum, # <<<<<<<<<<<<<<
* 'col_pcoefs_mean': col_pcoefs_mean,
* 'col_pcoefs_std': col_pcoefs_std,
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_pcoefs_sum, ((PyObject *)__pyx_v_col_pcoefs_sum)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4930
* 'col_nlhs_ratio_min': col_nlhs_ratio_min,
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* 'col_pcoefs_mean': col_pcoefs_mean, # <<<<<<<<<<<<<<
* 'col_pcoefs_std': col_pcoefs_std,
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_pcoefs_mean, ((PyObject *)__pyx_v_col_pcoefs_mean)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
/* "pyscipopt/scip.pyx":4931
* 'col_pcoefs_sum': col_pcoefs_sum,
* 'col_pcoefs_mean': col_pcoefs_mean,
* 'col_pcoefs_std': col_pcoefs_std, # <<<<<<<<<<<<<<
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_pcoefs_std, ((PyObject *)__pyx_v_col_pcoefs_std)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
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* 'col_pcoefs_min': col_pcoefs_min, # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":4933
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* 'col_pcoefs_max': col_pcoefs_max, # <<<<<<<<<<<<<<
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_pcoefs_max, ((PyObject *)__pyx_v_col_pcoefs_max)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
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if (PyDict_SetItem(__pyx_t_4, __pyx_n_u_col_ncoefs_sum, ((PyObject *)__pyx_v_col_ncoefs_sum)) < 0) __PYX_ERR(3, 4893, __pyx_L1_error)
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* 'col_ncoefs_mean': col_ncoefs_mean, # <<<<<<<<<<<<<<
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* 'col_ncoefs_std': col_ncoefs_std, # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":4940
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/* "pyscipopt/scip.pyx":4941
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/* "pyscipopt/scip.pyx":4942
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/* "pyscipopt/scip.pyx":4946
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/* "pyscipopt/scip.pyx":4947
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/* "pyscipopt/scip.pyx":4948
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/* "pyscipopt/scip.pyx":4949
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* # (count, mean, stdev., min, max)
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* pcoefs_var, pcoefs_mean, pcoefs_min, pcoefs_max = 0, 0, 0, 0.
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* ncoefs_var, ncoefs_mean, ncoefs_min, ncoefs_max = 0, 0, 0, 0.
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* pcoefs_count, ncoefs_count = 0, 0
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* pcoefs_mean = coef
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* pcoefs_max = coef if pcoefs_count == 1 else max(pcoefs_max, coef)
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* ncoefs_count += 1
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* ncoefs_mean += coef
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* pcoefs_min = coef if pcoefs_count == 1 else min(pcoefs_min, coef)
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* ncoefs_min = coef if ncoefs_count == 1 else min(ncoefs_min, coef)
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* var = (<Variable>candidates[cand_i]).scip_var
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* cand_ps_sum[cand_i] = cand_ps_up[cand_i] + cand_ps_down[cand_i]
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*
* # Infeasibility statistics (4)
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/* "pyscipopt/scip.pyx":5284
* # infeasible children (during data collection)
* # N.B. replaced by left, right infeasibility
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* cand_nb_down_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_DOWNWARDS)
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_UPWARDS)
*/
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/* "pyscipopt/scip.pyx":5285
* # N.B. replaced by left, right infeasibility
* cand_nb_up_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_UPWARDS)
* cand_nb_down_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_DOWNWARDS) # <<<<<<<<<<<<<<
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_UPWARDS)
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*/
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/* "pyscipopt/scip.pyx":5286
* cand_nb_up_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_UPWARDS)
* cand_nb_down_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_DOWNWARDS)
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_UPWARDS) # <<<<<<<<<<<<<<
* cand_frac_up_infeas[cand_i] = 0 if nbranchings == 0 else cand_nb_up_infeas[cand_i] / nbranchings
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*/
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* cand_nb_down_infeas[cand_i] = SCIPvarGetCutoffSum(var, SCIP_BRANCHDIR_DOWNWARDS)
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_UPWARDS)
* cand_frac_up_infeas[cand_i] = 0 if nbranchings == 0 else cand_nb_up_infeas[cand_i] / nbranchings # <<<<<<<<<<<<<<
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_DOWNWARDS)
* cand_frac_down_infeas[cand_i] = 0 if nbranchings == 0 else cand_nb_down_infeas[cand_i] / nbranchings
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* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_UPWARDS)
* cand_frac_up_infeas[cand_i] = 0 if nbranchings == 0 else cand_nb_up_infeas[cand_i] / nbranchings
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_DOWNWARDS) # <<<<<<<<<<<<<<
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*
*/
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* cand_frac_up_infeas[cand_i] = 0 if nbranchings == 0 else cand_nb_up_infeas[cand_i] / nbranchings
* nbranchings = SCIPvarGetNBranchings(var, SCIP_BRANCHDIR_DOWNWARDS)
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*
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/* "pyscipopt/scip.pyx":5295
* # on the current nodes LP.The ratios of the static mean, maximum and minimum to
* # their dynamic counterparts are also features
* cdeg_var, cdeg_mean, cdeg_min, cdeg_max = 0, 0, 0, 0 # <<<<<<<<<<<<<<
* if nb_neighbors > 0:
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/* "pyscipopt/scip.pyx":5296
* # their dynamic counterparts are also features
* cdeg_var, cdeg_mean, cdeg_min, cdeg_max = 0, 0, 0, 0
* if nb_neighbors > 0: # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
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*/
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/* "pyscipopt/scip.pyx":5297
* cdeg_var, cdeg_mean, cdeg_min, cdeg_max = 0, 0, 0, 0
* if nb_neighbors > 0:
* for neighbor_index in range(nb_neighbors): # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":5298
* if nb_neighbors > 0:
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*/
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/* "pyscipopt/scip.pyx":5299
* for neighbor_index in range(nb_neighbors):
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
* cdeg_mean += cdeg # <<<<<<<<<<<<<<
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* cdeg_min = cdeg if neighbor_index == 0 else min(cdeg_min, cdeg)
*/
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/* "pyscipopt/scip.pyx":5300
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
* cdeg_mean += cdeg
* cdeg_max = cdeg if neighbor_index == 0 else max(cdeg_max, cdeg) # <<<<<<<<<<<<<<
* cdeg_min = cdeg if neighbor_index == 0 else min(cdeg_min, cdeg)
* cdeg_mean /= nb_neighbors
*/
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} else {
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/* "pyscipopt/scip.pyx":5301
* cdeg_mean += cdeg
* cdeg_max = cdeg if neighbor_index == 0 else max(cdeg_max, cdeg)
* cdeg_min = cdeg if neighbor_index == 0 else min(cdeg_min, cdeg) # <<<<<<<<<<<<<<
* cdeg_mean /= nb_neighbors
* for neighbor_index in range(nb_neighbors):
*/
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} else {
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if (((__pyx_t_90 < __pyx_t_91) != 0)) {
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} else {
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}
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}
/* "pyscipopt/scip.pyx":5302
* cdeg_max = cdeg if neighbor_index == 0 else max(cdeg_max, cdeg)
* cdeg_min = cdeg if neighbor_index == 0 else min(cdeg_min, cdeg)
* cdeg_mean /= nb_neighbors # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
*/
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/* "pyscipopt/scip.pyx":5303
* cdeg_min = cdeg if neighbor_index == 0 else min(cdeg_min, cdeg)
* cdeg_mean /= nb_neighbors
* for neighbor_index in range(nb_neighbors): # <<<<<<<<<<<<<<
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
* cdeg_var += (cdeg - cdeg_mean)**2
*/
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__pyx_t_86 = __pyx_t_87;
for (__pyx_t_88 = 0; __pyx_t_88 < __pyx_t_86; __pyx_t_88+=1) {
__pyx_v_neighbor_index = __pyx_t_88;
/* "pyscipopt/scip.pyx":5304
* cdeg_mean /= nb_neighbors
* for neighbor_index in range(nb_neighbors):
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* cdeg_var += (cdeg - cdeg_mean)**2
* cdeg_var /= nb_neighbors
*/
__pyx_v_cdeg = SCIProwGetNLPNonz((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5305
* for neighbor_index in range(nb_neighbors):
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
* cdeg_var += (cdeg - cdeg_mean)**2 # <<<<<<<<<<<<<<
* cdeg_var /= nb_neighbors
* cand_cdeg_mean[cand_i] = cdeg_mean
*/
__pyx_v_cdeg_var = (__pyx_v_cdeg_var + powf((__pyx_v_cdeg - __pyx_v_cdeg_mean), 2.0));
}
/* "pyscipopt/scip.pyx":5306
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
* cdeg_var += (cdeg - cdeg_mean)**2
* cdeg_var /= nb_neighbors # <<<<<<<<<<<<<<
* cand_cdeg_mean[cand_i] = cdeg_mean
* cand_cdeg_var[cand_i] = cdeg_var
*/
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PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5306, __pyx_L1_error)
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__pyx_v_cdeg_var = (__pyx_v_cdeg_var / __pyx_v_nb_neighbors);
/* "pyscipopt/scip.pyx":5296
* # their dynamic counterparts are also features
* cdeg_var, cdeg_mean, cdeg_min, cdeg_max = 0, 0, 0, 0
* if nb_neighbors > 0: # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
* cdeg = SCIProwGetNLPNonz(neighbors[neighbor_index])
*/
}
/* "pyscipopt/scip.pyx":5307
* cdeg_var += (cdeg - cdeg_mean)**2
* cdeg_var /= nb_neighbors
* cand_cdeg_mean[cand_i] = cdeg_mean # <<<<<<<<<<<<<<
* cand_cdeg_var[cand_i] = cdeg_var
* cand_cdeg_min[cand_i] = cdeg_min
*/
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__pyx_t_87 = -1;
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/* "pyscipopt/scip.pyx":5308
* cdeg_var /= nb_neighbors
* cand_cdeg_mean[cand_i] = cdeg_mean
* cand_cdeg_var[cand_i] = cdeg_var # <<<<<<<<<<<<<<
* cand_cdeg_min[cand_i] = cdeg_min
* cand_cdeg_max[cand_i] = cdeg_max
*/
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/* "pyscipopt/scip.pyx":5309
* cand_cdeg_mean[cand_i] = cdeg_mean
* cand_cdeg_var[cand_i] = cdeg_var
* cand_cdeg_min[cand_i] = cdeg_min # <<<<<<<<<<<<<<
* cand_cdeg_max[cand_i] = cdeg_max
* cand_cdeg_mean_ratio[cand_i] = 0 if cdeg_mean == 0 else cdeg_mean / (cand_root_cdeg_mean[cand_i] + cdeg_mean)
*/
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__pyx_t_87 = -1;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5310
* cand_cdeg_var[cand_i] = cdeg_var
* cand_cdeg_min[cand_i] = cdeg_min
* cand_cdeg_max[cand_i] = cdeg_max # <<<<<<<<<<<<<<
* cand_cdeg_mean_ratio[cand_i] = 0 if cdeg_mean == 0 else cdeg_mean / (cand_root_cdeg_mean[cand_i] + cdeg_mean)
* cand_cdeg_min_ratio[cand_i] = 0 if cdeg_min == 0 else cdeg_min / (cand_root_cdeg_min[cand_i] + cdeg_min)
*/
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__pyx_t_87 = -1;
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__pyx_t_100 += __pyx_pybuffernd_cand_cdeg_max.diminfo[0].shape;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5311
* cand_cdeg_min[cand_i] = cdeg_min
* cand_cdeg_max[cand_i] = cdeg_max
* cand_cdeg_mean_ratio[cand_i] = 0 if cdeg_mean == 0 else cdeg_mean / (cand_root_cdeg_mean[cand_i] + cdeg_mean) # <<<<<<<<<<<<<<
* cand_cdeg_min_ratio[cand_i] = 0 if cdeg_min == 0 else cdeg_min / (cand_root_cdeg_min[cand_i] + cdeg_min)
* cand_cdeg_max_ratio[cand_i] = 0 if cdeg_max == 0 else cdeg_max / (cand_root_cdeg_max[cand_i] + cdeg_max)
*/
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__pyx_t_99 = 0.0;
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__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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PyErr_SetString(PyExc_ZeroDivisionError, "float division");
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}
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_cdeg_mean_ratio.diminfo[0].shape;
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/* "pyscipopt/scip.pyx":5312
* cand_cdeg_max[cand_i] = cdeg_max
* cand_cdeg_mean_ratio[cand_i] = 0 if cdeg_mean == 0 else cdeg_mean / (cand_root_cdeg_mean[cand_i] + cdeg_mean)
* cand_cdeg_min_ratio[cand_i] = 0 if cdeg_min == 0 else cdeg_min / (cand_root_cdeg_min[cand_i] + cdeg_min) # <<<<<<<<<<<<<<
* cand_cdeg_max_ratio[cand_i] = 0 if cdeg_max == 0 else cdeg_max / (cand_root_cdeg_max[cand_i] + cdeg_max)
*
*/
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__pyx_t_94 = 0.0;
} else {
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_root_cdeg_min.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_root_cdeg_min.diminfo[0].shape)) __pyx_t_87 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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if (unlikely(__pyx_t_101 == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5312, __pyx_L1_error)
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}
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_cdeg_min_ratio.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_cdeg_min_ratio.diminfo[0].shape)) __pyx_t_87 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5313
* cand_cdeg_mean_ratio[cand_i] = 0 if cdeg_mean == 0 else cdeg_mean / (cand_root_cdeg_mean[cand_i] + cdeg_mean)
* cand_cdeg_min_ratio[cand_i] = 0 if cdeg_min == 0 else cdeg_min / (cand_root_cdeg_min[cand_i] + cdeg_min)
* cand_cdeg_max_ratio[cand_i] = 0 if cdeg_max == 0 else cdeg_max / (cand_root_cdeg_max[cand_i] + cdeg_max) # <<<<<<<<<<<<<<
*
* # Min/max for ratios of constraint coeffs. to RHS (4)
*/
if (((__pyx_v_cdeg_max == 0) != 0)) {
__pyx_t_94 = 0.0;
} else {
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_root_cdeg_max.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_root_cdeg_max.diminfo[0].shape)) __pyx_t_87 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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PyErr_SetString(PyExc_ZeroDivisionError, "float division");
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}
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_cdeg_max_ratio.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_cdeg_max_ratio.diminfo[0].shape)) __pyx_t_87 = 0;
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/* "pyscipopt/scip.pyx":5317
* # Min/max for ratios of constraint coeffs. to RHS (4)
* # Minimum and maximum ratios across positive and negative right-hand-sides (RHS)
* prhs_ratio_max, prhs_ratio_min = -1, 1 # <<<<<<<<<<<<<<
* nrhs_ratio_max, nrhs_ratio_min = -1, 1
* for neighbor_index in range(nb_neighbors):
*/
__pyx_t_84 = -1.0;
__pyx_t_85 = 1.0;
__pyx_v_prhs_ratio_max = __pyx_t_84;
__pyx_v_prhs_ratio_min = __pyx_t_85;
/* "pyscipopt/scip.pyx":5318
* # Minimum and maximum ratios across positive and negative right-hand-sides (RHS)
* prhs_ratio_max, prhs_ratio_min = -1, 1
* nrhs_ratio_max, nrhs_ratio_min = -1, 1 # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
* coef = nonzero_coefs_raw[neighbor_index]
*/
__pyx_t_85 = -1.0;
__pyx_t_84 = 1.0;
__pyx_v_nrhs_ratio_max = __pyx_t_85;
__pyx_v_nrhs_ratio_min = __pyx_t_84;
/* "pyscipopt/scip.pyx":5319
* prhs_ratio_max, prhs_ratio_min = -1, 1
* nrhs_ratio_max, nrhs_ratio_min = -1, 1
* for neighbor_index in range(nb_neighbors): # <<<<<<<<<<<<<<
* coef = nonzero_coefs_raw[neighbor_index]
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
*/
__pyx_t_87 = __pyx_v_nb_neighbors;
__pyx_t_86 = __pyx_t_87;
for (__pyx_t_88 = 0; __pyx_t_88 < __pyx_t_86; __pyx_t_88+=1) {
__pyx_v_neighbor_index = __pyx_t_88;
/* "pyscipopt/scip.pyx":5320
* nrhs_ratio_max, nrhs_ratio_min = -1, 1
* for neighbor_index in range(nb_neighbors):
* coef = nonzero_coefs_raw[neighbor_index] # <<<<<<<<<<<<<<
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
*/
__pyx_v_coef = (__pyx_v_nonzero_coefs_raw[__pyx_v_neighbor_index]);
/* "pyscipopt/scip.pyx":5321
* for neighbor_index in range(nb_neighbors):
* coef = nonzero_coefs_raw[neighbor_index]
* rhs = SCIProwGetRhs(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* if not SCIPisInfinity(scip, REALABS(rhs)):
*/
__pyx_v_rhs = SCIProwGetRhs((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5322
* coef = nonzero_coefs_raw[neighbor_index]
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* if not SCIPisInfinity(scip, REALABS(rhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
*/
__pyx_v_lhs = SCIProwGetLhs((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5323
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* if not SCIPisInfinity(scip, REALABS(rhs)): # <<<<<<<<<<<<<<
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
* if rhs >= 0:
*/
__pyx_t_80 = ((!(SCIPisInfinity(__pyx_v_scip, REALABS(__pyx_v_rhs)) != 0)) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5324
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* if not SCIPisInfinity(scip, REALABS(rhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs)) # <<<<<<<<<<<<<<
* if rhs >= 0:
* rhs_ratio_max = max(prhs_ratio_max, value)
*/
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}
__pyx_v_value = __pyx_t_95;
/* "pyscipopt/scip.pyx":5325
* if not SCIPisInfinity(scip, REALABS(rhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
* if rhs >= 0: # <<<<<<<<<<<<<<
* rhs_ratio_max = max(prhs_ratio_max, value)
* rhs_ratio_min = min(prhs_ratio_min, value)
*/
__pyx_t_80 = ((__pyx_v_rhs >= 0.0) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5326
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
* if rhs >= 0:
* rhs_ratio_max = max(prhs_ratio_max, value) # <<<<<<<<<<<<<<
* rhs_ratio_min = min(prhs_ratio_min, value)
* else:
*/
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}
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__Pyx_GOTREF(__pyx_t_4);
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__pyx_t_4 = 0;
/* "pyscipopt/scip.pyx":5327
* if rhs >= 0:
* rhs_ratio_max = max(prhs_ratio_max, value)
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*/
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__pyx_t_84 = __pyx_v_prhs_ratio_min;
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/* "pyscipopt/scip.pyx":5325
* if not SCIPisInfinity(scip, REALABS(rhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
* if rhs >= 0: # <<<<<<<<<<<<<<
* rhs_ratio_max = max(prhs_ratio_max, value)
* rhs_ratio_min = min(prhs_ratio_min, value)
*/
goto __pyx_L35;
}
/* "pyscipopt/scip.pyx":5329
* rhs_ratio_min = min(prhs_ratio_min, value)
* else:
* nrhs_ratio_max = max(nrhs_ratio_max, value) # <<<<<<<<<<<<<<
* nrhs_ratio_min = min(nrhs_ratio_min, value)
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__pyx_t_93 = __pyx_v_nrhs_ratio_max;
if (((__pyx_t_85 > __pyx_t_93) != 0)) {
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} else {
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}
__pyx_v_nrhs_ratio_max = __pyx_t_84;
/* "pyscipopt/scip.pyx":5330
* else:
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* nrhs_ratio_min = min(nrhs_ratio_min, value) # <<<<<<<<<<<<<<
* if not SCIPisInfinity(scip, REALABS(lhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
*/
__pyx_t_84 = __pyx_v_value;
__pyx_t_85 = __pyx_v_nrhs_ratio_min;
if (((__pyx_t_84 < __pyx_t_85) != 0)) {
__pyx_t_93 = __pyx_t_84;
} else {
__pyx_t_93 = __pyx_t_85;
}
__pyx_v_nrhs_ratio_min = __pyx_t_93;
}
__pyx_L35:;
/* "pyscipopt/scip.pyx":5323
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* if not SCIPisInfinity(scip, REALABS(rhs)): # <<<<<<<<<<<<<<
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(rhs))
* if rhs >= 0:
*/
}
/* "pyscipopt/scip.pyx":5331
* nrhs_ratio_max = max(nrhs_ratio_max, value)
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* if not SCIPisInfinity(scip, REALABS(lhs)): # <<<<<<<<<<<<<<
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
* if -lhs >= 0:
*/
__pyx_t_80 = ((!(SCIPisInfinity(__pyx_v_scip, REALABS(__pyx_v_lhs)) != 0)) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5332
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* if not SCIPisInfinity(scip, REALABS(lhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs)) # <<<<<<<<<<<<<<
* if -lhs >= 0:
* prhs_ratio_max = max(prhs_ratio_max, value)
*/
if (((__pyx_v_coef == 0.0) != 0)) {
__pyx_t_95 = 0.0;
} else {
__pyx_t_96 = (REALABS(__pyx_v_coef) + REALABS(__pyx_v_lhs));
if (unlikely(__pyx_t_96 == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5332, __pyx_L1_error)
}
__pyx_t_95 = (__pyx_v_coef / __pyx_t_96);
}
__pyx_v_value = __pyx_t_95;
/* "pyscipopt/scip.pyx":5333
* if not SCIPisInfinity(scip, REALABS(lhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
* if -lhs >= 0: # <<<<<<<<<<<<<<
* prhs_ratio_max = max(prhs_ratio_max, value)
* prhs_ratio_min = min(prhs_ratio_min, value)
*/
__pyx_t_80 = (((-__pyx_v_lhs) >= 0.0) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5334
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
* if -lhs >= 0:
* prhs_ratio_max = max(prhs_ratio_max, value) # <<<<<<<<<<<<<<
* prhs_ratio_min = min(prhs_ratio_min, value)
* else:
*/
__pyx_t_93 = __pyx_v_value;
__pyx_t_84 = __pyx_v_prhs_ratio_max;
if (((__pyx_t_93 > __pyx_t_84) != 0)) {
__pyx_t_85 = __pyx_t_93;
} else {
__pyx_t_85 = __pyx_t_84;
}
__pyx_v_prhs_ratio_max = __pyx_t_85;
/* "pyscipopt/scip.pyx":5335
* if -lhs >= 0:
* prhs_ratio_max = max(prhs_ratio_max, value)
* prhs_ratio_min = min(prhs_ratio_min, value) # <<<<<<<<<<<<<<
* else:
* nrhs_ratio_max = max(nrhs_ratio_max, value)
*/
__pyx_t_85 = __pyx_v_value;
__pyx_t_93 = __pyx_v_prhs_ratio_min;
if (((__pyx_t_85 < __pyx_t_93) != 0)) {
__pyx_t_84 = __pyx_t_85;
} else {
__pyx_t_84 = __pyx_t_93;
}
__pyx_v_prhs_ratio_min = __pyx_t_84;
/* "pyscipopt/scip.pyx":5333
* if not SCIPisInfinity(scip, REALABS(lhs)):
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
* if -lhs >= 0: # <<<<<<<<<<<<<<
* prhs_ratio_max = max(prhs_ratio_max, value)
* prhs_ratio_min = min(prhs_ratio_min, value)
*/
goto __pyx_L37;
}
/* "pyscipopt/scip.pyx":5337
* prhs_ratio_min = min(prhs_ratio_min, value)
* else:
* nrhs_ratio_max = max(nrhs_ratio_max, value) # <<<<<<<<<<<<<<
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* cand_prhs_ratio_max[cand_i] = prhs_ratio_max
*/
/*else*/ {
__pyx_t_84 = __pyx_v_value;
__pyx_t_85 = __pyx_v_nrhs_ratio_max;
if (((__pyx_t_84 > __pyx_t_85) != 0)) {
__pyx_t_93 = __pyx_t_84;
} else {
__pyx_t_93 = __pyx_t_85;
}
__pyx_v_nrhs_ratio_max = __pyx_t_93;
/* "pyscipopt/scip.pyx":5338
* else:
* nrhs_ratio_max = max(nrhs_ratio_max, value)
* nrhs_ratio_min = min(nrhs_ratio_min, value) # <<<<<<<<<<<<<<
* cand_prhs_ratio_max[cand_i] = prhs_ratio_max
* cand_prhs_ratio_min[cand_i] = prhs_ratio_min
*/
__pyx_t_93 = __pyx_v_value;
__pyx_t_84 = __pyx_v_nrhs_ratio_min;
if (((__pyx_t_93 < __pyx_t_84) != 0)) {
__pyx_t_85 = __pyx_t_93;
} else {
__pyx_t_85 = __pyx_t_84;
}
__pyx_v_nrhs_ratio_min = __pyx_t_85;
}
__pyx_L37:;
/* "pyscipopt/scip.pyx":5331
* nrhs_ratio_max = max(nrhs_ratio_max, value)
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* if not SCIPisInfinity(scip, REALABS(lhs)): # <<<<<<<<<<<<<<
* value = 0 if coef == 0 else coef / (REALABS(coef) + REALABS(lhs))
* if -lhs >= 0:
*/
}
}
/* "pyscipopt/scip.pyx":5339
* nrhs_ratio_max = max(nrhs_ratio_max, value)
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* cand_prhs_ratio_max[cand_i] = prhs_ratio_max # <<<<<<<<<<<<<<
* cand_prhs_ratio_min[cand_i] = prhs_ratio_min
* cand_nrhs_ratio_max[cand_i] = nrhs_ratio_max
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_prhs_ratio_max.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_prhs_ratio_max.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5339, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_prhs_ratio_max.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_prhs_ratio_max.diminfo[0].strides) = __pyx_v_prhs_ratio_max;
/* "pyscipopt/scip.pyx":5340
* nrhs_ratio_min = min(nrhs_ratio_min, value)
* cand_prhs_ratio_max[cand_i] = prhs_ratio_max
* cand_prhs_ratio_min[cand_i] = prhs_ratio_min # <<<<<<<<<<<<<<
* cand_nrhs_ratio_max[cand_i] = nrhs_ratio_max
* cand_nrhs_ratio_min[cand_i] = nrhs_ratio_min
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_prhs_ratio_min.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_prhs_ratio_min.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5340, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_prhs_ratio_min.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_prhs_ratio_min.diminfo[0].strides) = __pyx_v_prhs_ratio_min;
/* "pyscipopt/scip.pyx":5341
* cand_prhs_ratio_max[cand_i] = prhs_ratio_max
* cand_prhs_ratio_min[cand_i] = prhs_ratio_min
* cand_nrhs_ratio_max[cand_i] = nrhs_ratio_max # <<<<<<<<<<<<<<
* cand_nrhs_ratio_min[cand_i] = nrhs_ratio_min
*
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_nrhs_ratio_max.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_nrhs_ratio_max.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5341, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_nrhs_ratio_max.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_nrhs_ratio_max.diminfo[0].strides) = __pyx_v_nrhs_ratio_max;
/* "pyscipopt/scip.pyx":5342
* cand_prhs_ratio_min[cand_i] = prhs_ratio_min
* cand_nrhs_ratio_max[cand_i] = nrhs_ratio_max
* cand_nrhs_ratio_min[cand_i] = nrhs_ratio_min # <<<<<<<<<<<<<<
*
* # Min/max for one-to-all coefficient ratios (8)
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_nrhs_ratio_min.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_nrhs_ratio_min.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5342, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_nrhs_ratio_min.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_nrhs_ratio_min.diminfo[0].strides) = __pyx_v_nrhs_ratio_min;
/* "pyscipopt/scip.pyx":5348
* # other variables coefficients, for a given constraint. Four versions of these ratios
* # are considered: positive (negative) coefficient to sum of positive (negative) coefficients
* ota_pp_max, ota_pp_min, ota_pn_max, ota_pn_min = 0, 1, 0, 1 # <<<<<<<<<<<<<<
* ota_np_max, ota_np_min, ota_nn_max, ota_nn_min = 0, 1, 0, 1
* for neighbor_index in range(nb_neighbors):
*/
__pyx_t_85 = 0.0;
__pyx_t_93 = 1.0;
__pyx_t_84 = 0.0;
__pyx_t_106 = 1.0;
__pyx_v_ota_pp_max = __pyx_t_85;
__pyx_v_ota_pp_min = __pyx_t_93;
__pyx_v_ota_pn_max = __pyx_t_84;
__pyx_v_ota_pn_min = __pyx_t_106;
/* "pyscipopt/scip.pyx":5349
* # are considered: positive (negative) coefficient to sum of positive (negative) coefficients
* ota_pp_max, ota_pp_min, ota_pn_max, ota_pn_min = 0, 1, 0, 1
* ota_np_max, ota_np_min, ota_nn_max, ota_nn_min = 0, 1, 0, 1 # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
* all_coefs_raw = SCIProwGetVals(neighbors[neighbor_index])
*/
__pyx_t_106 = 0.0;
__pyx_t_84 = 1.0;
__pyx_t_93 = 0.0;
__pyx_t_85 = 1.0;
__pyx_v_ota_np_max = __pyx_t_106;
__pyx_v_ota_np_min = __pyx_t_84;
__pyx_v_ota_nn_max = __pyx_t_93;
__pyx_v_ota_nn_min = __pyx_t_85;
/* "pyscipopt/scip.pyx":5350
* ota_pp_max, ota_pp_min, ota_pn_max, ota_pn_min = 0, 1, 0, 1
* ota_np_max, ota_np_min, ota_nn_max, ota_nn_min = 0, 1, 0, 1
* for neighbor_index in range(nb_neighbors): # <<<<<<<<<<<<<<
* all_coefs_raw = SCIProwGetVals(neighbors[neighbor_index])
* neighbor_ncolumns = SCIProwGetNNonz(neighbors[neighbor_index])
*/
__pyx_t_87 = __pyx_v_nb_neighbors;
__pyx_t_86 = __pyx_t_87;
for (__pyx_t_88 = 0; __pyx_t_88 < __pyx_t_86; __pyx_t_88+=1) {
__pyx_v_neighbor_index = __pyx_t_88;
/* "pyscipopt/scip.pyx":5351
* ota_np_max, ota_np_min, ota_nn_max, ota_nn_min = 0, 1, 0, 1
* for neighbor_index in range(nb_neighbors):
* all_coefs_raw = SCIProwGetVals(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* neighbor_ncolumns = SCIProwGetNNonz(neighbors[neighbor_index])
* pos_coef_sum, neg_coef_sum = 0, 0
*/
__pyx_v_all_coefs_raw = SCIProwGetVals((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5352
* for neighbor_index in range(nb_neighbors):
* all_coefs_raw = SCIProwGetVals(neighbors[neighbor_index])
* neighbor_ncolumns = SCIProwGetNNonz(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* pos_coef_sum, neg_coef_sum = 0, 0
* for neighbor_column_index in range(neighbor_ncolumns):
*/
__pyx_v_neighbor_ncolumns = SCIProwGetNNonz((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5353
* all_coefs_raw = SCIProwGetVals(neighbors[neighbor_index])
* neighbor_ncolumns = SCIProwGetNNonz(neighbors[neighbor_index])
* pos_coef_sum, neg_coef_sum = 0, 0 # <<<<<<<<<<<<<<
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_coef = all_coefs_raw[neighbor_column_index]
*/
__pyx_t_85 = 0.0;
__pyx_t_93 = 0.0;
__pyx_v_pos_coef_sum = __pyx_t_85;
__pyx_v_neg_coef_sum = __pyx_t_93;
/* "pyscipopt/scip.pyx":5354
* neighbor_ncolumns = SCIProwGetNNonz(neighbors[neighbor_index])
* pos_coef_sum, neg_coef_sum = 0, 0
* for neighbor_column_index in range(neighbor_ncolumns): # <<<<<<<<<<<<<<
* neighbor_coef = all_coefs_raw[neighbor_column_index]
* if neighbor_coef > 0:
*/
__pyx_t_89 = __pyx_v_neighbor_ncolumns;
__pyx_t_92 = __pyx_t_89;
for (__pyx_t_90 = 0; __pyx_t_90 < __pyx_t_92; __pyx_t_90+=1) {
__pyx_v_neighbor_column_index = __pyx_t_90;
/* "pyscipopt/scip.pyx":5355
* pos_coef_sum, neg_coef_sum = 0, 0
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_coef = all_coefs_raw[neighbor_column_index] # <<<<<<<<<<<<<<
* if neighbor_coef > 0:
* pos_coef_sum += neighbor_coef
*/
__pyx_v_neighbor_coef = (__pyx_v_all_coefs_raw[__pyx_v_neighbor_column_index]);
/* "pyscipopt/scip.pyx":5356
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_coef = all_coefs_raw[neighbor_column_index]
* if neighbor_coef > 0: # <<<<<<<<<<<<<<
* pos_coef_sum += neighbor_coef
* else:
*/
__pyx_t_80 = ((__pyx_v_neighbor_coef > 0.0) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5357
* neighbor_coef = all_coefs_raw[neighbor_column_index]
* if neighbor_coef > 0:
* pos_coef_sum += neighbor_coef # <<<<<<<<<<<<<<
* else:
* neg_coef_sum += neighbor_coef
*/
__pyx_v_pos_coef_sum = (__pyx_v_pos_coef_sum + __pyx_v_neighbor_coef);
/* "pyscipopt/scip.pyx":5356
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_coef = all_coefs_raw[neighbor_column_index]
* if neighbor_coef > 0: # <<<<<<<<<<<<<<
* pos_coef_sum += neighbor_coef
* else:
*/
goto __pyx_L42;
}
/* "pyscipopt/scip.pyx":5359
* pos_coef_sum += neighbor_coef
* else:
* neg_coef_sum += neighbor_coef # <<<<<<<<<<<<<<
* coef = nonzero_coefs_raw[neighbor_index]
* if coef > 0:
*/
/*else*/ {
__pyx_v_neg_coef_sum = (__pyx_v_neg_coef_sum + __pyx_v_neighbor_coef);
}
__pyx_L42:;
}
/* "pyscipopt/scip.pyx":5360
* else:
* neg_coef_sum += neighbor_coef
* coef = nonzero_coefs_raw[neighbor_index] # <<<<<<<<<<<<<<
* if coef > 0:
* pratio = coef / pos_coef_sum
*/
__pyx_v_coef = (__pyx_v_nonzero_coefs_raw[__pyx_v_neighbor_index]);
/* "pyscipopt/scip.pyx":5361
* neg_coef_sum += neighbor_coef
* coef = nonzero_coefs_raw[neighbor_index]
* if coef > 0: # <<<<<<<<<<<<<<
* pratio = coef / pos_coef_sum
* nratio = coef / (coef - neg_coef_sum)
*/
__pyx_t_80 = ((__pyx_v_coef > 0.0) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5362
* coef = nonzero_coefs_raw[neighbor_index]
* if coef > 0:
* pratio = coef / pos_coef_sum # <<<<<<<<<<<<<<
* nratio = coef / (coef - neg_coef_sum)
* ota_pp_max = max(ota_pp_max, pratio)
*/
if (unlikely(__pyx_v_pos_coef_sum == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5362, __pyx_L1_error)
}
__pyx_v_pratio = (__pyx_v_coef / ((SCIP_Real)__pyx_v_pos_coef_sum));
/* "pyscipopt/scip.pyx":5363
* if coef > 0:
* pratio = coef / pos_coef_sum
* nratio = coef / (coef - neg_coef_sum) # <<<<<<<<<<<<<<
* ota_pp_max = max(ota_pp_max, pratio)
* ota_pp_min = min(ota_pp_min, pratio)
*/
__pyx_t_95 = (__pyx_v_coef - __pyx_v_neg_coef_sum);
if (unlikely(__pyx_t_95 == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5363, __pyx_L1_error)
}
__pyx_v_nratio = (__pyx_v_coef / __pyx_t_95);
/* "pyscipopt/scip.pyx":5364
* pratio = coef / pos_coef_sum
* nratio = coef / (coef - neg_coef_sum)
* ota_pp_max = max(ota_pp_max, pratio) # <<<<<<<<<<<<<<
* ota_pp_min = min(ota_pp_min, pratio)
* ota_pn_max = max(ota_pn_max, nratio)
*/
__pyx_t_93 = __pyx_v_pratio;
__pyx_t_85 = __pyx_v_ota_pp_max;
if (((__pyx_t_93 > __pyx_t_85) != 0)) {
__pyx_t_84 = __pyx_t_93;
} else {
__pyx_t_84 = __pyx_t_85;
}
__pyx_v_ota_pp_max = __pyx_t_84;
/* "pyscipopt/scip.pyx":5365
* nratio = coef / (coef - neg_coef_sum)
* ota_pp_max = max(ota_pp_max, pratio)
* ota_pp_min = min(ota_pp_min, pratio) # <<<<<<<<<<<<<<
* ota_pn_max = max(ota_pn_max, nratio)
* ota_pn_min = min(ota_pn_min, nratio)
*/
__pyx_t_84 = __pyx_v_pratio;
__pyx_t_93 = __pyx_v_ota_pp_min;
if (((__pyx_t_84 < __pyx_t_93) != 0)) {
__pyx_t_85 = __pyx_t_84;
} else {
__pyx_t_85 = __pyx_t_93;
}
__pyx_v_ota_pp_min = __pyx_t_85;
/* "pyscipopt/scip.pyx":5366
* ota_pp_max = max(ota_pp_max, pratio)
* ota_pp_min = min(ota_pp_min, pratio)
* ota_pn_max = max(ota_pn_max, nratio) # <<<<<<<<<<<<<<
* ota_pn_min = min(ota_pn_min, nratio)
* if coef < 0:
*/
__pyx_t_85 = __pyx_v_nratio;
__pyx_t_84 = __pyx_v_ota_pn_max;
if (((__pyx_t_85 > __pyx_t_84) != 0)) {
__pyx_t_93 = __pyx_t_85;
} else {
__pyx_t_93 = __pyx_t_84;
}
__pyx_v_ota_pn_max = __pyx_t_93;
/* "pyscipopt/scip.pyx":5367
* ota_pp_min = min(ota_pp_min, pratio)
* ota_pn_max = max(ota_pn_max, nratio)
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} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5432, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w2.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w2.diminfo[0].strides) = __pyx_t_99;
/* "pyscipopt/scip.pyx":5436
* # weight no. 3
* # inverse of the sum of the coefficients of only candidate variables in constraint
* constraint_sum = 0 # <<<<<<<<<<<<<<
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_var = SCIPcolGetVar(neighbor_columns[neighbor_column_index])
*/
__pyx_v_constraint_sum = 0.0;
/* "pyscipopt/scip.pyx":5437
* # inverse of the sum of the coefficients of only candidate variables in constraint
* constraint_sum = 0
* for neighbor_column_index in range(neighbor_ncolumns): # <<<<<<<<<<<<<<
* neighbor_var = SCIPcolGetVar(neighbor_columns[neighbor_column_index])
* neighbor_var_index = SCIPvarGetIndex(neighbor_var)
*/
__pyx_t_87 = __pyx_v_neighbor_ncolumns;
__pyx_t_86 = __pyx_t_87;
for (__pyx_t_88 = 0; __pyx_t_88 < __pyx_t_86; __pyx_t_88+=1) {
__pyx_v_neighbor_column_index = __pyx_t_88;
/* "pyscipopt/scip.pyx":5438
* constraint_sum = 0
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_var = SCIPcolGetVar(neighbor_columns[neighbor_column_index]) # <<<<<<<<<<<<<<
* neighbor_var_index = SCIPvarGetIndex(neighbor_var)
* for cand_i in range(ncands):
*/
__pyx_v_neighbor_var = SCIPcolGetVar((__pyx_v_neighbor_columns[__pyx_v_neighbor_column_index]));
/* "pyscipopt/scip.pyx":5439
* for neighbor_column_index in range(neighbor_ncolumns):
* neighbor_var = SCIPcolGetVar(neighbor_columns[neighbor_column_index])
* neighbor_var_index = SCIPvarGetIndex(neighbor_var) # <<<<<<<<<<<<<<
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var
*/
__pyx_v_neighbor_var_index = SCIPvarGetIndex(__pyx_v_neighbor_var);
/* "pyscipopt/scip.pyx":5440
* neighbor_var = SCIPcolGetVar(neighbor_columns[neighbor_column_index])
* neighbor_var_index = SCIPvarGetIndex(neighbor_var)
* for cand_i in range(ncands): # <<<<<<<<<<<<<<
* var = (<Variable>candidates[cand_i]).scip_var
* if SCIPvarGetIndex(var) == neighbor_var_index:
*/
__pyx_t_89 = __pyx_v_ncands;
__pyx_t_92 = __pyx_t_89;
for (__pyx_t_90 = 0; __pyx_t_90 < __pyx_t_92; __pyx_t_90+=1) {
__pyx_v_cand_i = __pyx_t_90;
/* "pyscipopt/scip.pyx":5441
* neighbor_var_index = SCIPvarGetIndex(neighbor_var)
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var # <<<<<<<<<<<<<<
* if SCIPvarGetIndex(var) == neighbor_var_index:
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index])
*/
__pyx_t_3 = __Pyx_GetItemInt(__pyx_v_candidates, __pyx_v_cand_i, int, 1, __Pyx_PyInt_From_int, 0, 1, 1); if (unlikely(!__pyx_t_3)) __PYX_ERR(3, 5441, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_98 = ((struct __pyx_obj_9pyscipopt_4scip_Variable *)__pyx_t_3)->scip_var;
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_v_var = __pyx_t_98;
/* "pyscipopt/scip.pyx":5442
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var
* if SCIPvarGetIndex(var) == neighbor_var_index: # <<<<<<<<<<<<<<
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index])
* break
*/
__pyx_t_80 = ((SCIPvarGetIndex(__pyx_v_var) == __pyx_v_neighbor_var_index) != 0);
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5443
* var = (<Variable>candidates[cand_i]).scip_var
* if SCIPvarGetIndex(var) == neighbor_var_index:
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index]) # <<<<<<<<<<<<<<
* break
* act_cons_w3[row_index] = 1 if constraint_sum == 0 else 1 / constraint_sum
*/
__pyx_v_constraint_sum = (__pyx_v_constraint_sum + REALABS((__pyx_v_neighbor_columns_values[__pyx_v_neighbor_column_index])));
/* "pyscipopt/scip.pyx":5444
* if SCIPvarGetIndex(var) == neighbor_var_index:
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index])
* break # <<<<<<<<<<<<<<
* act_cons_w3[row_index] = 1 if constraint_sum == 0 else 1 / constraint_sum
*
*/
goto __pyx_L55_break;
/* "pyscipopt/scip.pyx":5442
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var
* if SCIPvarGetIndex(var) == neighbor_var_index: # <<<<<<<<<<<<<<
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index])
* break
*/
}
}
__pyx_L55_break:;
}
/* "pyscipopt/scip.pyx":5445
* constraint_sum += REALABS(neighbor_columns_values[neighbor_column_index])
* break
* act_cons_w3[row_index] = 1 if constraint_sum == 0 else 1 / constraint_sum # <<<<<<<<<<<<<<
*
* # weight no. 4
*/
if (((__pyx_v_constraint_sum == 0.0) != 0)) {
__pyx_t_99 = 1.0;
} else {
if (unlikely(__pyx_v_constraint_sum == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5445, __pyx_L1_error)
}
__pyx_t_99 = (1.0 / __pyx_v_constraint_sum);
}
__pyx_t_100 = __pyx_v_row_index;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5445, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w3.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w3.diminfo[0].strides) = __pyx_t_99;
/* "pyscipopt/scip.pyx":5449
* # weight no. 4
* # dual cost of the constraint
* act_cons_w4[row_index] = REALABS(SCIProwGetDualsol(row)) # <<<<<<<<<<<<<<
*
* for cand_i in range(ncands):
*/
__pyx_t_100 = __pyx_v_row_index;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5449, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w4.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w4.diminfo[0].strides) = REALABS(SCIProwGetDualsol(__pyx_v_row));
/* "pyscipopt/scip.pyx":5418
* activity = SCIPgetRowActivity(scip, row)
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs): # <<<<<<<<<<<<<<
* neighbor_columns = SCIProwGetCols(row)
* neighbor_ncolumns = SCIProwGetNNonz(row)
*/
}
}
/* "pyscipopt/scip.pyx":5451
* act_cons_w4[row_index] = REALABS(SCIProwGetDualsol(row))
*
* for cand_i in range(ncands): # <<<<<<<<<<<<<<
* var = (<Variable>candidates[cand_i]).scip_var
* col = SCIPvarGetCol(var)
*/
__pyx_t_8 = __pyx_v_ncands;
__pyx_t_81 = __pyx_t_8;
for (__pyx_t_82 = 0; __pyx_t_82 < __pyx_t_81; __pyx_t_82+=1) {
__pyx_v_cand_i = __pyx_t_82;
/* "pyscipopt/scip.pyx":5452
*
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var # <<<<<<<<<<<<<<
* col = SCIPvarGetCol(var)
* neighbors = SCIPcolGetRows(col)
*/
__pyx_t_3 = __Pyx_GetItemInt(__pyx_v_candidates, __pyx_v_cand_i, int, 1, __Pyx_PyInt_From_int, 0, 1, 1); if (unlikely(!__pyx_t_3)) __PYX_ERR(3, 5452, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_98 = ((struct __pyx_obj_9pyscipopt_4scip_Variable *)__pyx_t_3)->scip_var;
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_v_var = __pyx_t_98;
/* "pyscipopt/scip.pyx":5453
* for cand_i in range(ncands):
* var = (<Variable>candidates[cand_i]).scip_var
* col = SCIPvarGetCol(var) # <<<<<<<<<<<<<<
* neighbors = SCIPcolGetRows(col)
* nb_neighbors = SCIPcolGetNNonz(col)
*/
__pyx_v_col = SCIPvarGetCol(__pyx_v_var);
/* "pyscipopt/scip.pyx":5454
* var = (<Variable>candidates[cand_i]).scip_var
* col = SCIPvarGetCol(var)
* neighbors = SCIPcolGetRows(col) # <<<<<<<<<<<<<<
* nb_neighbors = SCIPcolGetNNonz(col)
* nonzero_coefs_raw = SCIPcolGetVals(col)
*/
__pyx_v_neighbors = SCIPcolGetRows(__pyx_v_col);
/* "pyscipopt/scip.pyx":5455
* col = SCIPvarGetCol(var)
* neighbors = SCIPcolGetRows(col)
* nb_neighbors = SCIPcolGetNNonz(col) # <<<<<<<<<<<<<<
* nonzero_coefs_raw = SCIPcolGetVals(col)
*
*/
__pyx_v_nb_neighbors = SCIPcolGetNNonz(__pyx_v_col);
/* "pyscipopt/scip.pyx":5456
* neighbors = SCIPcolGetRows(col)
* nb_neighbors = SCIPcolGetNNonz(col)
* nonzero_coefs_raw = SCIPcolGetVals(col) # <<<<<<<<<<<<<<
*
* acons_sum1, acons_mean1, acons_var1, acons_max1, acons_min1 = 0, 0, 0, 0, 0
*/
__pyx_v_nonzero_coefs_raw = SCIPcolGetVals(__pyx_v_col);
/* "pyscipopt/scip.pyx":5458
* nonzero_coefs_raw = SCIPcolGetVals(col)
*
* acons_sum1, acons_mean1, acons_var1, acons_max1, acons_min1 = 0, 0, 0, 0, 0 # <<<<<<<<<<<<<<
* acons_sum2, acons_mean2, acons_var2, acons_max2, acons_min2 = 0, 0, 0, 0, 0
* acons_sum3, acons_mean3, acons_var3, acons_max3, acons_min3 = 0, 0, 0, 0, 0
*/
__pyx_t_85 = 0.0;
__pyx_t_84 = 0.0;
__pyx_t_93 = 0.0;
__pyx_t_106 = 0.0;
__pyx_t_109 = 0.0;
__pyx_v_acons_sum1 = __pyx_t_85;
__pyx_v_acons_mean1 = __pyx_t_84;
__pyx_v_acons_var1 = __pyx_t_93;
__pyx_v_acons_max1 = __pyx_t_106;
__pyx_v_acons_min1 = __pyx_t_109;
/* "pyscipopt/scip.pyx":5459
*
* acons_sum1, acons_mean1, acons_var1, acons_max1, acons_min1 = 0, 0, 0, 0, 0
* acons_sum2, acons_mean2, acons_var2, acons_max2, acons_min2 = 0, 0, 0, 0, 0 # <<<<<<<<<<<<<<
* acons_sum3, acons_mean3, acons_var3, acons_max3, acons_min3 = 0, 0, 0, 0, 0
* acons_sum4, acons_mean4, acons_var4, acons_max4, acons_min4 = 0, 0, 0, 0, 0
*/
__pyx_t_109 = 0.0;
__pyx_t_106 = 0.0;
__pyx_t_93 = 0.0;
__pyx_t_84 = 0.0;
__pyx_t_85 = 0.0;
__pyx_v_acons_sum2 = __pyx_t_109;
__pyx_v_acons_mean2 = __pyx_t_106;
__pyx_v_acons_var2 = __pyx_t_93;
__pyx_v_acons_max2 = __pyx_t_84;
__pyx_v_acons_min2 = __pyx_t_85;
/* "pyscipopt/scip.pyx":5460
* acons_sum1, acons_mean1, acons_var1, acons_max1, acons_min1 = 0, 0, 0, 0, 0
* acons_sum2, acons_mean2, acons_var2, acons_max2, acons_min2 = 0, 0, 0, 0, 0
* acons_sum3, acons_mean3, acons_var3, acons_max3, acons_min3 = 0, 0, 0, 0, 0 # <<<<<<<<<<<<<<
* acons_sum4, acons_mean4, acons_var4, acons_max4, acons_min4 = 0, 0, 0, 0, 0
* acons_nb1, acons_nb2, acons_nb3, acons_nb4 = 0, 0, 0, 0
*/
__pyx_t_85 = 0.0;
__pyx_t_84 = 0.0;
__pyx_t_93 = 0.0;
__pyx_t_106 = 0.0;
__pyx_t_109 = 0.0;
__pyx_v_acons_sum3 = __pyx_t_85;
__pyx_v_acons_mean3 = __pyx_t_84;
__pyx_v_acons_var3 = __pyx_t_93;
__pyx_v_acons_max3 = __pyx_t_106;
__pyx_v_acons_min3 = __pyx_t_109;
/* "pyscipopt/scip.pyx":5461
* acons_sum2, acons_mean2, acons_var2, acons_max2, acons_min2 = 0, 0, 0, 0, 0
* acons_sum3, acons_mean3, acons_var3, acons_max3, acons_min3 = 0, 0, 0, 0, 0
* acons_sum4, acons_mean4, acons_var4, acons_max4, acons_min4 = 0, 0, 0, 0, 0 # <<<<<<<<<<<<<<
* acons_nb1, acons_nb2, acons_nb3, acons_nb4 = 0, 0, 0, 0
* active_count = 0
*/
__pyx_t_109 = 0.0;
__pyx_t_106 = 0.0;
__pyx_t_93 = 0.0;
__pyx_t_84 = 0.0;
__pyx_t_85 = 0.0;
__pyx_v_acons_sum4 = __pyx_t_109;
__pyx_v_acons_mean4 = __pyx_t_106;
__pyx_v_acons_var4 = __pyx_t_93;
__pyx_v_acons_max4 = __pyx_t_84;
__pyx_v_acons_min4 = __pyx_t_85;
/* "pyscipopt/scip.pyx":5462
* acons_sum3, acons_mean3, acons_var3, acons_max3, acons_min3 = 0, 0, 0, 0, 0
* acons_sum4, acons_mean4, acons_var4, acons_max4, acons_min4 = 0, 0, 0, 0, 0
* acons_nb1, acons_nb2, acons_nb3, acons_nb4 = 0, 0, 0, 0 # <<<<<<<<<<<<<<
* active_count = 0
* for neighbor_index in range(nb_neighbors):
*/
__pyx_t_85 = 0.0;
__pyx_t_84 = 0.0;
__pyx_t_93 = 0.0;
__pyx_t_106 = 0.0;
__pyx_v_acons_nb1 = __pyx_t_85;
__pyx_v_acons_nb2 = __pyx_t_84;
__pyx_v_acons_nb3 = __pyx_t_93;
__pyx_v_acons_nb4 = __pyx_t_106;
/* "pyscipopt/scip.pyx":5463
* acons_sum4, acons_mean4, acons_var4, acons_max4, acons_min4 = 0, 0, 0, 0, 0
* acons_nb1, acons_nb2, acons_nb3, acons_nb4 = 0, 0, 0, 0
* active_count = 0 # <<<<<<<<<<<<<<
* for neighbor_index in range(nb_neighbors):
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
*/
__pyx_v_active_count = 0;
/* "pyscipopt/scip.pyx":5464
* acons_nb1, acons_nb2, acons_nb3, acons_nb4 = 0, 0, 0, 0
* active_count = 0
* for neighbor_index in range(nb_neighbors): # <<<<<<<<<<<<<<
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
*/
__pyx_t_87 = __pyx_v_nb_neighbors;
__pyx_t_86 = __pyx_t_87;
for (__pyx_t_88 = 0; __pyx_t_88 < __pyx_t_86; __pyx_t_88+=1) {
__pyx_v_neighbor_index = __pyx_t_88;
/* "pyscipopt/scip.pyx":5465
* active_count = 0
* for neighbor_index in range(nb_neighbors):
* rhs = SCIProwGetRhs(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index])
*/
__pyx_v_rhs = SCIProwGetRhs((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5466
* for neighbor_index in range(nb_neighbors):
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index])
* # N.B. active if activity = lhs or rhs
*/
__pyx_v_lhs = SCIProwGetLhs((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5467
* rhs = SCIProwGetRhs(neighbors[neighbor_index])
* lhs = SCIProwGetLhs(neighbors[neighbor_index])
* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs):
*/
__pyx_v_activity = SCIPgetRowActivity(__pyx_v_scip, (__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5469
* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index])
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs): # <<<<<<<<<<<<<<
* active_count += 1
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
*/
__pyx_t_108 = (SCIPisEQ(__pyx_v_scip, __pyx_v_activity, __pyx_v_rhs) != 0);
if (!__pyx_t_108) {
} else {
__pyx_t_80 = __pyx_t_108;
goto __pyx_L62_bool_binop_done;
}
__pyx_t_108 = (SCIPisEQ(__pyx_v_scip, __pyx_v_activity, __pyx_v_lhs) != 0);
__pyx_t_80 = __pyx_t_108;
__pyx_L62_bool_binop_done:;
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5470
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs):
* active_count += 1 # <<<<<<<<<<<<<<
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*/
__pyx_v_active_count = (__pyx_v_active_count + 1);
/* "pyscipopt/scip.pyx":5471
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs):
* active_count += 1
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*
*/
__pyx_v_neighbor_row_index = SCIProwGetLPPos((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5472
* active_count += 1
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index]) # <<<<<<<<<<<<<<
*
* acons_nb1 += act_cons_w1[neighbor_row_index]
*/
__pyx_v_abs_coef = REALABS((__pyx_v_nonzero_coefs_raw[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5474
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*
* acons_nb1 += act_cons_w1[neighbor_row_index] # <<<<<<<<<<<<<<
* value = act_cons_w1[neighbor_row_index] * abs_coef
* acons_sum1 += value
*/
__pyx_t_100 = __pyx_v_neighbor_row_index;
__pyx_t_89 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_89 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w1.diminfo[0].shape)) __pyx_t_89 = 0;
if (unlikely(__pyx_t_89 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_89);
__PYX_ERR(3, 5474, __pyx_L1_error)
}
__pyx_v_acons_nb1 = (__pyx_v_acons_nb1 + (*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w1.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w1.diminfo[0].strides)));
/* "pyscipopt/scip.pyx":5475
*
* acons_nb1 += act_cons_w1[neighbor_row_index]
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* acons_mean4 = acons_sum4 / active_count
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* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index])
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs): # <<<<<<<<<<<<<<
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*/
__pyx_t_108 = (SCIPisEQ(__pyx_v_scip, __pyx_v_activity, __pyx_v_rhs) != 0);
if (!__pyx_t_108) {
} else {
__pyx_t_80 = __pyx_t_108;
goto __pyx_L68_bool_binop_done;
}
__pyx_t_108 = (SCIPisEQ(__pyx_v_scip, __pyx_v_activity, __pyx_v_lhs) != 0);
__pyx_t_80 = __pyx_t_108;
__pyx_L68_bool_binop_done:;
if (__pyx_t_80) {
/* "pyscipopt/scip.pyx":5509
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs):
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index]) # <<<<<<<<<<<<<<
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*
*/
__pyx_v_neighbor_row_index = SCIProwGetLPPos((__pyx_v_neighbors[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5510
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs):
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index]) # <<<<<<<<<<<<<<
*
* value = act_cons_w1[neighbor_row_index] * abs_coef
*/
__pyx_v_abs_coef = REALABS((__pyx_v_nonzero_coefs_raw[__pyx_v_neighbor_index]));
/* "pyscipopt/scip.pyx":5512
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*
* value = act_cons_w1[neighbor_row_index] * abs_coef # <<<<<<<<<<<<<<
* acons_var1 += (value - acons_mean1)**2
*
*/
__pyx_t_100 = __pyx_v_neighbor_row_index;
__pyx_t_89 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_89 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w1.diminfo[0].shape)) __pyx_t_89 = 0;
if (unlikely(__pyx_t_89 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_89);
__PYX_ERR(3, 5512, __pyx_L1_error)
}
__pyx_v_value = ((*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w1.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w1.diminfo[0].strides)) * __pyx_v_abs_coef);
/* "pyscipopt/scip.pyx":5513
*
* value = act_cons_w1[neighbor_row_index] * abs_coef
* acons_var1 += (value - acons_mean1)**2 # <<<<<<<<<<<<<<
*
* value = act_cons_w2[neighbor_row_index] * abs_coef
*/
__pyx_v_acons_var1 = (__pyx_v_acons_var1 + powf((__pyx_v_value - __pyx_v_acons_mean1), 2.0));
/* "pyscipopt/scip.pyx":5515
* acons_var1 += (value - acons_mean1)**2
*
* value = act_cons_w2[neighbor_row_index] * abs_coef # <<<<<<<<<<<<<<
* acons_var2 += (value - acons_mean2)**2
*
*/
__pyx_t_100 = __pyx_v_neighbor_row_index;
__pyx_t_89 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w2.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_89 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w2.diminfo[0].shape)) __pyx_t_89 = 0;
if (unlikely(__pyx_t_89 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_89);
__PYX_ERR(3, 5515, __pyx_L1_error)
}
__pyx_v_value = ((*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w2.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w2.diminfo[0].strides)) * __pyx_v_abs_coef);
/* "pyscipopt/scip.pyx":5516
*
* value = act_cons_w2[neighbor_row_index] * abs_coef
* acons_var2 += (value - acons_mean2)**2 # <<<<<<<<<<<<<<
*
* value = act_cons_w3[neighbor_row_index] * abs_coef
*/
__pyx_v_acons_var2 = (__pyx_v_acons_var2 + powf((__pyx_v_value - __pyx_v_acons_mean2), 2.0));
/* "pyscipopt/scip.pyx":5518
* acons_var2 += (value - acons_mean2)**2
*
* value = act_cons_w3[neighbor_row_index] * abs_coef # <<<<<<<<<<<<<<
* acons_var3 += (value - acons_mean3)**2
*
*/
__pyx_t_100 = __pyx_v_neighbor_row_index;
__pyx_t_89 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_89 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w3.diminfo[0].shape)) __pyx_t_89 = 0;
if (unlikely(__pyx_t_89 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_89);
__PYX_ERR(3, 5518, __pyx_L1_error)
}
__pyx_v_value = ((*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w3.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w3.diminfo[0].strides)) * __pyx_v_abs_coef);
/* "pyscipopt/scip.pyx":5519
*
* value = act_cons_w3[neighbor_row_index] * abs_coef
* acons_var3 += (value - acons_mean3)**2 # <<<<<<<<<<<<<<
*
* value = act_cons_w4[neighbor_row_index] * abs_coef
*/
__pyx_v_acons_var3 = (__pyx_v_acons_var3 + powf((__pyx_v_value - __pyx_v_acons_mean3), 2.0));
/* "pyscipopt/scip.pyx":5521
* acons_var3 += (value - acons_mean3)**2
*
* value = act_cons_w4[neighbor_row_index] * abs_coef # <<<<<<<<<<<<<<
* acons_var4 += (value - acons_mean4)**2
* acons_var1 /= active_count
*/
__pyx_t_100 = __pyx_v_neighbor_row_index;
__pyx_t_89 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_act_cons_w4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_89 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_act_cons_w4.diminfo[0].shape)) __pyx_t_89 = 0;
if (unlikely(__pyx_t_89 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_89);
__PYX_ERR(3, 5521, __pyx_L1_error)
}
__pyx_v_value = ((*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_act_cons_w4.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_act_cons_w4.diminfo[0].strides)) * __pyx_v_abs_coef);
/* "pyscipopt/scip.pyx":5522
*
* value = act_cons_w4[neighbor_row_index] * abs_coef
* acons_var4 += (value - acons_mean4)**2 # <<<<<<<<<<<<<<
* acons_var1 /= active_count
* acons_var2 /= active_count
*/
__pyx_v_acons_var4 = (__pyx_v_acons_var4 + powf((__pyx_v_value - __pyx_v_acons_mean4), 2.0));
/* "pyscipopt/scip.pyx":5508
* activity = SCIPgetRowActivity(scip, neighbors[neighbor_index])
* # N.B. active if activity = lhs or rhs
* if SCIPisEQ(scip, activity, rhs) or SCIPisEQ(scip, activity, lhs): # <<<<<<<<<<<<<<
* neighbor_row_index = SCIProwGetLPPos(neighbors[neighbor_index])
* abs_coef = REALABS(nonzero_coefs_raw[neighbor_index])
*/
}
}
/* "pyscipopt/scip.pyx":5523
* value = act_cons_w4[neighbor_row_index] * abs_coef
* acons_var4 += (value - acons_mean4)**2
* acons_var1 /= active_count # <<<<<<<<<<<<<<
* acons_var2 /= active_count
* acons_var3 /= active_count
*/
if (unlikely(__pyx_v_active_count == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5523, __pyx_L1_error)
}
__pyx_v_acons_var1 = (__pyx_v_acons_var1 / __pyx_v_active_count);
/* "pyscipopt/scip.pyx":5524
* acons_var4 += (value - acons_mean4)**2
* acons_var1 /= active_count
* acons_var2 /= active_count # <<<<<<<<<<<<<<
* acons_var3 /= active_count
* acons_var4 /= active_count
*/
if (unlikely(__pyx_v_active_count == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5524, __pyx_L1_error)
}
__pyx_v_acons_var2 = (__pyx_v_acons_var2 / __pyx_v_active_count);
/* "pyscipopt/scip.pyx":5525
* acons_var1 /= active_count
* acons_var2 /= active_count
* acons_var3 /= active_count # <<<<<<<<<<<<<<
* acons_var4 /= active_count
*
*/
if (unlikely(__pyx_v_active_count == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5525, __pyx_L1_error)
}
__pyx_v_acons_var3 = (__pyx_v_acons_var3 / __pyx_v_active_count);
/* "pyscipopt/scip.pyx":5526
* acons_var2 /= active_count
* acons_var3 /= active_count
* acons_var4 /= active_count # <<<<<<<<<<<<<<
*
* cand_acons_sum1[cand_i] = acons_sum1
*/
if (unlikely(__pyx_v_active_count == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(3, 5526, __pyx_L1_error)
}
__pyx_v_acons_var4 = (__pyx_v_acons_var4 / __pyx_v_active_count);
/* "pyscipopt/scip.pyx":5498
* acons_min4 = value if active_count == 1 else min(acons_min4, value)
*
* if active_count > 0: # <<<<<<<<<<<<<<
* acons_mean1 = acons_sum1 / active_count
* acons_mean2 = acons_sum2 / active_count
*/
}
/* "pyscipopt/scip.pyx":5528
* acons_var4 /= active_count
*
* cand_acons_sum1[cand_i] = acons_sum1 # <<<<<<<<<<<<<<
* cand_acons_sum2[cand_i] = acons_sum2
* cand_acons_sum3[cand_i] = acons_sum3
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_sum1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_sum1.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5528, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_sum1.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_sum1.diminfo[0].strides) = __pyx_v_acons_sum1;
/* "pyscipopt/scip.pyx":5529
*
* cand_acons_sum1[cand_i] = acons_sum1
* cand_acons_sum2[cand_i] = acons_sum2 # <<<<<<<<<<<<<<
* cand_acons_sum3[cand_i] = acons_sum3
* cand_acons_sum4[cand_i] = acons_sum4
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_sum2.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_sum2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5529, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_sum2.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_sum2.diminfo[0].strides) = __pyx_v_acons_sum2;
/* "pyscipopt/scip.pyx":5530
* cand_acons_sum1[cand_i] = acons_sum1
* cand_acons_sum2[cand_i] = acons_sum2
* cand_acons_sum3[cand_i] = acons_sum3 # <<<<<<<<<<<<<<
* cand_acons_sum4[cand_i] = acons_sum4
* cand_acons_mean1[cand_i] = acons_mean1
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_sum3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_sum3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5530, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_sum3.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_sum3.diminfo[0].strides) = __pyx_v_acons_sum3;
/* "pyscipopt/scip.pyx":5531
* cand_acons_sum2[cand_i] = acons_sum2
* cand_acons_sum3[cand_i] = acons_sum3
* cand_acons_sum4[cand_i] = acons_sum4 # <<<<<<<<<<<<<<
* cand_acons_mean1[cand_i] = acons_mean1
* cand_acons_mean2[cand_i] = acons_mean2
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_sum4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_sum4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5531, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_sum4.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_sum4.diminfo[0].strides) = __pyx_v_acons_sum4;
/* "pyscipopt/scip.pyx":5532
* cand_acons_sum3[cand_i] = acons_sum3
* cand_acons_sum4[cand_i] = acons_sum4
* cand_acons_mean1[cand_i] = acons_mean1 # <<<<<<<<<<<<<<
* cand_acons_mean2[cand_i] = acons_mean2
* cand_acons_mean3[cand_i] = acons_mean3
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_mean1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_mean1.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5532, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_mean1.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_mean1.diminfo[0].strides) = __pyx_v_acons_mean1;
/* "pyscipopt/scip.pyx":5533
* cand_acons_sum4[cand_i] = acons_sum4
* cand_acons_mean1[cand_i] = acons_mean1
* cand_acons_mean2[cand_i] = acons_mean2 # <<<<<<<<<<<<<<
* cand_acons_mean3[cand_i] = acons_mean3
* cand_acons_mean4[cand_i] = acons_mean4
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_mean2.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_mean2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5533, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_mean2.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_mean2.diminfo[0].strides) = __pyx_v_acons_mean2;
/* "pyscipopt/scip.pyx":5534
* cand_acons_mean1[cand_i] = acons_mean1
* cand_acons_mean2[cand_i] = acons_mean2
* cand_acons_mean3[cand_i] = acons_mean3 # <<<<<<<<<<<<<<
* cand_acons_mean4[cand_i] = acons_mean4
* cand_acons_max1[cand_i] = acons_max1
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_mean3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_mean3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5534, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_mean3.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_mean3.diminfo[0].strides) = __pyx_v_acons_mean3;
/* "pyscipopt/scip.pyx":5535
* cand_acons_mean2[cand_i] = acons_mean2
* cand_acons_mean3[cand_i] = acons_mean3
* cand_acons_mean4[cand_i] = acons_mean4 # <<<<<<<<<<<<<<
* cand_acons_max1[cand_i] = acons_max1
* cand_acons_max2[cand_i] = acons_max2
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_mean4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_mean4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5535, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_mean4.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_mean4.diminfo[0].strides) = __pyx_v_acons_mean4;
/* "pyscipopt/scip.pyx":5536
* cand_acons_mean3[cand_i] = acons_mean3
* cand_acons_mean4[cand_i] = acons_mean4
* cand_acons_max1[cand_i] = acons_max1 # <<<<<<<<<<<<<<
* cand_acons_max2[cand_i] = acons_max2
* cand_acons_max3[cand_i] = acons_max3
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_max1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_max1.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5536, __pyx_L1_error)
}
*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_max1.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_max1.diminfo[0].strides) = __pyx_v_acons_max1;
/* "pyscipopt/scip.pyx":5537
* cand_acons_mean4[cand_i] = acons_mean4
* cand_acons_max1[cand_i] = acons_max1
* cand_acons_max2[cand_i] = acons_max2 # <<<<<<<<<<<<<<
* cand_acons_max3[cand_i] = acons_max3
* cand_acons_max4[cand_i] = acons_max4
*/
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__pyx_t_87 = -1;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5538
* cand_acons_max1[cand_i] = acons_max1
* cand_acons_max2[cand_i] = acons_max2
* cand_acons_max3[cand_i] = acons_max3 # <<<<<<<<<<<<<<
* cand_acons_max4[cand_i] = acons_max4
* cand_acons_min1[cand_i] = acons_min1
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_max3.diminfo[0].shape;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5539
* cand_acons_max2[cand_i] = acons_max2
* cand_acons_max3[cand_i] = acons_max3
* cand_acons_max4[cand_i] = acons_max4 # <<<<<<<<<<<<<<
* cand_acons_min1[cand_i] = acons_min1
* cand_acons_min2[cand_i] = acons_min2
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_max4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_max4.diminfo[0].shape)) __pyx_t_87 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5540
* cand_acons_max3[cand_i] = acons_max3
* cand_acons_max4[cand_i] = acons_max4
* cand_acons_min1[cand_i] = acons_min1 # <<<<<<<<<<<<<<
* cand_acons_min2[cand_i] = acons_min2
* cand_acons_min3[cand_i] = acons_min3
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_min1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_min1.diminfo[0].shape)) __pyx_t_87 = 0;
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__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5541
* cand_acons_max4[cand_i] = acons_max4
* cand_acons_min1[cand_i] = acons_min1
* cand_acons_min2[cand_i] = acons_min2 # <<<<<<<<<<<<<<
* cand_acons_min3[cand_i] = acons_min3
* cand_acons_min4[cand_i] = acons_min4
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_min2.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_min2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5542
* cand_acons_min1[cand_i] = acons_min1
* cand_acons_min2[cand_i] = acons_min2
* cand_acons_min3[cand_i] = acons_min3 # <<<<<<<<<<<<<<
* cand_acons_min4[cand_i] = acons_min4
* cand_acons_var1[cand_i] = acons_var1
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_min3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_min3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_float32_t *, __pyx_pybuffernd_cand_acons_min3.rcbuffer->pybuffer.buf, __pyx_t_100, __pyx_pybuffernd_cand_acons_min3.diminfo[0].strides) = __pyx_v_acons_min3;
/* "pyscipopt/scip.pyx":5543
* cand_acons_min2[cand_i] = acons_min2
* cand_acons_min3[cand_i] = acons_min3
* cand_acons_min4[cand_i] = acons_min4 # <<<<<<<<<<<<<<
* cand_acons_var1[cand_i] = acons_var1
* cand_acons_var2[cand_i] = acons_var2
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_min4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_min4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5544
* cand_acons_min3[cand_i] = acons_min3
* cand_acons_min4[cand_i] = acons_min4
* cand_acons_var1[cand_i] = acons_var1 # <<<<<<<<<<<<<<
* cand_acons_var2[cand_i] = acons_var2
* cand_acons_var3[cand_i] = acons_var3
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_var1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_var1.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5545
* cand_acons_min4[cand_i] = acons_min4
* cand_acons_var1[cand_i] = acons_var1
* cand_acons_var2[cand_i] = acons_var2 # <<<<<<<<<<<<<<
* cand_acons_var3[cand_i] = acons_var3
* cand_acons_var4[cand_i] = acons_var4
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
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if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_var2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5546
* cand_acons_var1[cand_i] = acons_var1
* cand_acons_var2[cand_i] = acons_var2
* cand_acons_var3[cand_i] = acons_var3 # <<<<<<<<<<<<<<
* cand_acons_var4[cand_i] = acons_var4
* cand_acons_nb1[cand_i] = acons_nb1
*/
__pyx_t_100 = __pyx_v_cand_i;
__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_var3.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_var3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5547
* cand_acons_var2[cand_i] = acons_var2
* cand_acons_var3[cand_i] = acons_var3
* cand_acons_var4[cand_i] = acons_var4 # <<<<<<<<<<<<<<
* cand_acons_nb1[cand_i] = acons_nb1
* cand_acons_nb2[cand_i] = acons_nb2
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_var4.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_var4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5548
* cand_acons_var3[cand_i] = acons_var3
* cand_acons_var4[cand_i] = acons_var4
* cand_acons_nb1[cand_i] = acons_nb1 # <<<<<<<<<<<<<<
* cand_acons_nb2[cand_i] = acons_nb2
* cand_acons_nb3[cand_i] = acons_nb3
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_nb1.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_nb1.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5548, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5549
* cand_acons_var4[cand_i] = acons_var4
* cand_acons_nb1[cand_i] = acons_nb1
* cand_acons_nb2[cand_i] = acons_nb2 # <<<<<<<<<<<<<<
* cand_acons_nb3[cand_i] = acons_nb3
* cand_acons_nb4[cand_i] = acons_nb4
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
__pyx_t_100 += __pyx_pybuffernd_cand_acons_nb2.diminfo[0].shape;
if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_nb2.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
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/* "pyscipopt/scip.pyx":5550
* cand_acons_nb1[cand_i] = acons_nb1
* cand_acons_nb2[cand_i] = acons_nb2
* cand_acons_nb3[cand_i] = acons_nb3 # <<<<<<<<<<<<<<
* cand_acons_nb4[cand_i] = acons_nb4
*
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
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if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_nb3.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5550, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5551
* cand_acons_nb2[cand_i] = acons_nb2
* cand_acons_nb3[cand_i] = acons_nb3
* cand_acons_nb4[cand_i] = acons_nb4 # <<<<<<<<<<<<<<
*
* return {
*/
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__pyx_t_87 = -1;
if (__pyx_t_100 < 0) {
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if (unlikely(__pyx_t_100 < 0)) __pyx_t_87 = 0;
} else if (unlikely(__pyx_t_100 >= __pyx_pybuffernd_cand_acons_nb4.diminfo[0].shape)) __pyx_t_87 = 0;
if (unlikely(__pyx_t_87 != -1)) {
__Pyx_RaiseBufferIndexError(__pyx_t_87);
__PYX_ERR(3, 5551, __pyx_L1_error)
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}
/* "pyscipopt/scip.pyx":5553
* cand_acons_nb4[cand_i] = acons_nb4
*
* return { # <<<<<<<<<<<<<<
* 'coefs': cand_coefs,
* 'coefs_pos': cand_coefs_pos,
*/
__Pyx_XDECREF(__pyx_r);
/* "pyscipopt/scip.pyx":5554
*
* return {
* 'coefs': cand_coefs, # <<<<<<<<<<<<<<
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* 'coefs_neg': cand_coefs_neg,
*/
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/* "pyscipopt/scip.pyx":5555
* return {
* 'coefs': cand_coefs,
* 'coefs_pos': cand_coefs_pos, # <<<<<<<<<<<<<<
* 'coefs_neg': cand_coefs_neg,
* 'nnzrs': cand_nnzrs,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_coefs_pos, ((PyObject *)__pyx_v_cand_coefs_pos)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5556
* 'coefs': cand_coefs,
* 'coefs_pos': cand_coefs_pos,
* 'coefs_neg': cand_coefs_neg, # <<<<<<<<<<<<<<
* 'nnzrs': cand_nnzrs,
* 'root_cdeg_mean': cand_root_cdeg_mean,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_coefs_neg, ((PyObject *)__pyx_v_cand_coefs_neg)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5557
* 'coefs_pos': cand_coefs_pos,
* 'coefs_neg': cand_coefs_neg,
* 'nnzrs': cand_nnzrs, # <<<<<<<<<<<<<<
* 'root_cdeg_mean': cand_root_cdeg_mean,
* 'root_cdeg_var': cand_root_cdeg_var,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nnzrs, ((PyObject *)__pyx_v_cand_nnzrs)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5558
* 'coefs_neg': cand_coefs_neg,
* 'nnzrs': cand_nnzrs,
* 'root_cdeg_mean': cand_root_cdeg_mean, # <<<<<<<<<<<<<<
* 'root_cdeg_var': cand_root_cdeg_var,
* 'root_cdeg_min': cand_root_cdeg_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_cdeg_mean, ((PyObject *)__pyx_v_cand_root_cdeg_mean)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5559
* 'nnzrs': cand_nnzrs,
* 'root_cdeg_mean': cand_root_cdeg_mean,
* 'root_cdeg_var': cand_root_cdeg_var, # <<<<<<<<<<<<<<
* 'root_cdeg_min': cand_root_cdeg_min,
* 'root_cdeg_max': cand_root_cdeg_max,
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if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_cdeg_var, ((PyObject *)__pyx_v_cand_root_cdeg_var)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5560
* 'root_cdeg_mean': cand_root_cdeg_mean,
* 'root_cdeg_var': cand_root_cdeg_var,
* 'root_cdeg_min': cand_root_cdeg_min, # <<<<<<<<<<<<<<
* 'root_cdeg_max': cand_root_cdeg_max,
* 'root_pcoefs_count': cand_root_pcoefs_count,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_cdeg_min, ((PyObject *)__pyx_v_cand_root_cdeg_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5561
* 'root_cdeg_var': cand_root_cdeg_var,
* 'root_cdeg_min': cand_root_cdeg_min,
* 'root_cdeg_max': cand_root_cdeg_max, # <<<<<<<<<<<<<<
* 'root_pcoefs_count': cand_root_pcoefs_count,
* 'root_pcoefs_mean': cand_root_pcoefs_mean,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_cdeg_max, ((PyObject *)__pyx_v_cand_root_cdeg_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5562
* 'root_cdeg_min': cand_root_cdeg_min,
* 'root_cdeg_max': cand_root_cdeg_max,
* 'root_pcoefs_count': cand_root_pcoefs_count, # <<<<<<<<<<<<<<
* 'root_pcoefs_mean': cand_root_pcoefs_mean,
* 'root_pcoefs_var': cand_root_pcoefs_var,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_pcoefs_count, ((PyObject *)__pyx_v_cand_root_pcoefs_count)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5563
* 'root_cdeg_max': cand_root_cdeg_max,
* 'root_pcoefs_count': cand_root_pcoefs_count,
* 'root_pcoefs_mean': cand_root_pcoefs_mean, # <<<<<<<<<<<<<<
* 'root_pcoefs_var': cand_root_pcoefs_var,
* 'root_pcoefs_min': cand_root_pcoefs_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_pcoefs_mean, ((PyObject *)__pyx_v_cand_root_pcoefs_mean)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5564
* 'root_pcoefs_count': cand_root_pcoefs_count,
* 'root_pcoefs_mean': cand_root_pcoefs_mean,
* 'root_pcoefs_var': cand_root_pcoefs_var, # <<<<<<<<<<<<<<
* 'root_pcoefs_min': cand_root_pcoefs_min,
* 'root_pcoefs_max': cand_root_pcoefs_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_pcoefs_var, ((PyObject *)__pyx_v_cand_root_pcoefs_var)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5565
* 'root_pcoefs_mean': cand_root_pcoefs_mean,
* 'root_pcoefs_var': cand_root_pcoefs_var,
* 'root_pcoefs_min': cand_root_pcoefs_min, # <<<<<<<<<<<<<<
* 'root_pcoefs_max': cand_root_pcoefs_max,
* 'root_ncoefs_count': cand_root_ncoefs_count,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_pcoefs_min, ((PyObject *)__pyx_v_cand_root_pcoefs_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5566
* 'root_pcoefs_var': cand_root_pcoefs_var,
* 'root_pcoefs_min': cand_root_pcoefs_min,
* 'root_pcoefs_max': cand_root_pcoefs_max, # <<<<<<<<<<<<<<
* 'root_ncoefs_count': cand_root_ncoefs_count,
* 'root_ncoefs_mean': cand_root_ncoefs_mean,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_pcoefs_max, ((PyObject *)__pyx_v_cand_root_pcoefs_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5567
* 'root_pcoefs_min': cand_root_pcoefs_min,
* 'root_pcoefs_max': cand_root_pcoefs_max,
* 'root_ncoefs_count': cand_root_ncoefs_count, # <<<<<<<<<<<<<<
* 'root_ncoefs_mean': cand_root_ncoefs_mean,
* 'root_ncoefs_var': cand_root_ncoefs_var,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_ncoefs_count, ((PyObject *)__pyx_v_cand_root_ncoefs_count)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5568
* 'root_pcoefs_max': cand_root_pcoefs_max,
* 'root_ncoefs_count': cand_root_ncoefs_count,
* 'root_ncoefs_mean': cand_root_ncoefs_mean, # <<<<<<<<<<<<<<
* 'root_ncoefs_var': cand_root_ncoefs_var,
* 'root_ncoefs_min': cand_root_ncoefs_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_ncoefs_mean, ((PyObject *)__pyx_v_cand_root_ncoefs_mean)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5569
* 'root_ncoefs_count': cand_root_ncoefs_count,
* 'root_ncoefs_mean': cand_root_ncoefs_mean,
* 'root_ncoefs_var': cand_root_ncoefs_var, # <<<<<<<<<<<<<<
* 'root_ncoefs_min': cand_root_ncoefs_min,
* 'root_ncoefs_max': cand_root_ncoefs_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_ncoefs_var, ((PyObject *)__pyx_v_cand_root_ncoefs_var)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5570
* 'root_ncoefs_mean': cand_root_ncoefs_mean,
* 'root_ncoefs_var': cand_root_ncoefs_var,
* 'root_ncoefs_min': cand_root_ncoefs_min, # <<<<<<<<<<<<<<
* 'root_ncoefs_max': cand_root_ncoefs_max,
* 'solfracs': cand_solfracs,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_ncoefs_min, ((PyObject *)__pyx_v_cand_root_ncoefs_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5571
* 'root_ncoefs_var': cand_root_ncoefs_var,
* 'root_ncoefs_min': cand_root_ncoefs_min,
* 'root_ncoefs_max': cand_root_ncoefs_max, # <<<<<<<<<<<<<<
* 'solfracs': cand_solfracs,
* 'slack': cand_slack,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_root_ncoefs_max, ((PyObject *)__pyx_v_cand_root_ncoefs_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5572
* 'root_ncoefs_min': cand_root_ncoefs_min,
* 'root_ncoefs_max': cand_root_ncoefs_max,
* 'solfracs': cand_solfracs, # <<<<<<<<<<<<<<
* 'slack': cand_slack,
* 'ps_up': cand_ps_up,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_solfracs, __pyx_v_cand_solfracs) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5573
* 'root_ncoefs_max': cand_root_ncoefs_max,
* 'solfracs': cand_solfracs,
* 'slack': cand_slack, # <<<<<<<<<<<<<<
* 'ps_up': cand_ps_up,
* 'ps_down': cand_ps_down,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_slack, ((PyObject *)__pyx_v_cand_slack)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5574
* 'solfracs': cand_solfracs,
* 'slack': cand_slack,
* 'ps_up': cand_ps_up, # <<<<<<<<<<<<<<
* 'ps_down': cand_ps_down,
* 'ps_ratio': cand_ps_ratio,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ps_up, ((PyObject *)__pyx_v_cand_ps_up)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5575
* 'slack': cand_slack,
* 'ps_up': cand_ps_up,
* 'ps_down': cand_ps_down, # <<<<<<<<<<<<<<
* 'ps_ratio': cand_ps_ratio,
* 'ps_sum': cand_ps_sum,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ps_down, ((PyObject *)__pyx_v_cand_ps_down)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5576
* 'ps_up': cand_ps_up,
* 'ps_down': cand_ps_down,
* 'ps_ratio': cand_ps_ratio, # <<<<<<<<<<<<<<
* 'ps_sum': cand_ps_sum,
* 'ps_product': cand_ps_product,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ps_ratio, ((PyObject *)__pyx_v_cand_ps_ratio)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5577
* 'ps_down': cand_ps_down,
* 'ps_ratio': cand_ps_ratio,
* 'ps_sum': cand_ps_sum, # <<<<<<<<<<<<<<
* 'ps_product': cand_ps_product,
* 'nb_up_infeas': cand_nb_up_infeas,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ps_sum, ((PyObject *)__pyx_v_cand_ps_sum)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5578
* 'ps_ratio': cand_ps_ratio,
* 'ps_sum': cand_ps_sum,
* 'ps_product': cand_ps_product, # <<<<<<<<<<<<<<
* 'nb_up_infeas': cand_nb_up_infeas,
* 'nb_down_infeas': cand_nb_down_infeas,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ps_product, ((PyObject *)__pyx_v_cand_ps_product)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5579
* 'ps_sum': cand_ps_sum,
* 'ps_product': cand_ps_product,
* 'nb_up_infeas': cand_nb_up_infeas, # <<<<<<<<<<<<<<
* 'nb_down_infeas': cand_nb_down_infeas,
* 'frac_up_infeas': cand_frac_up_infeas,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nb_up_infeas, ((PyObject *)__pyx_v_cand_nb_up_infeas)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5580
* 'ps_product': cand_ps_product,
* 'nb_up_infeas': cand_nb_up_infeas,
* 'nb_down_infeas': cand_nb_down_infeas, # <<<<<<<<<<<<<<
* 'frac_up_infeas': cand_frac_up_infeas,
* 'frac_down_infeas': cand_frac_down_infeas,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nb_down_infeas, ((PyObject *)__pyx_v_cand_nb_down_infeas)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5581
* 'nb_up_infeas': cand_nb_up_infeas,
* 'nb_down_infeas': cand_nb_down_infeas,
* 'frac_up_infeas': cand_frac_up_infeas, # <<<<<<<<<<<<<<
* 'frac_down_infeas': cand_frac_down_infeas,
* 'cdeg_mean': cand_cdeg_mean,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_frac_up_infeas, __pyx_v_cand_frac_up_infeas) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5582
* 'nb_down_infeas': cand_nb_down_infeas,
* 'frac_up_infeas': cand_frac_up_infeas,
* 'frac_down_infeas': cand_frac_down_infeas, # <<<<<<<<<<<<<<
* 'cdeg_mean': cand_cdeg_mean,
* 'cdeg_var': cand_cdeg_var,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_frac_down_infeas, __pyx_v_cand_frac_down_infeas) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5583
* 'frac_up_infeas': cand_frac_up_infeas,
* 'frac_down_infeas': cand_frac_down_infeas,
* 'cdeg_mean': cand_cdeg_mean, # <<<<<<<<<<<<<<
* 'cdeg_var': cand_cdeg_var,
* 'cdeg_min': cand_cdeg_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_mean, ((PyObject *)__pyx_v_cand_cdeg_mean)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5584
* 'frac_down_infeas': cand_frac_down_infeas,
* 'cdeg_mean': cand_cdeg_mean,
* 'cdeg_var': cand_cdeg_var, # <<<<<<<<<<<<<<
* 'cdeg_min': cand_cdeg_min,
* 'cdeg_max': cand_cdeg_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_var, ((PyObject *)__pyx_v_cand_cdeg_var)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5585
* 'cdeg_mean': cand_cdeg_mean,
* 'cdeg_var': cand_cdeg_var,
* 'cdeg_min': cand_cdeg_min, # <<<<<<<<<<<<<<
* 'cdeg_max': cand_cdeg_max,
* 'cdeg_mean_ratio': cand_cdeg_mean_ratio,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_min, ((PyObject *)__pyx_v_cand_cdeg_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5586
* 'cdeg_var': cand_cdeg_var,
* 'cdeg_min': cand_cdeg_min,
* 'cdeg_max': cand_cdeg_max, # <<<<<<<<<<<<<<
* 'cdeg_mean_ratio': cand_cdeg_mean_ratio,
* 'cdeg_min_ratio': cand_cdeg_min_ratio,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_max, ((PyObject *)__pyx_v_cand_cdeg_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5587
* 'cdeg_min': cand_cdeg_min,
* 'cdeg_max': cand_cdeg_max,
* 'cdeg_mean_ratio': cand_cdeg_mean_ratio, # <<<<<<<<<<<<<<
* 'cdeg_min_ratio': cand_cdeg_min_ratio,
* 'cdeg_max_ratio': cand_cdeg_max_ratio,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_mean_ratio, ((PyObject *)__pyx_v_cand_cdeg_mean_ratio)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5588
* 'cdeg_max': cand_cdeg_max,
* 'cdeg_mean_ratio': cand_cdeg_mean_ratio,
* 'cdeg_min_ratio': cand_cdeg_min_ratio, # <<<<<<<<<<<<<<
* 'cdeg_max_ratio': cand_cdeg_max_ratio,
* 'prhs_ratio_max': cand_prhs_ratio_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_min_ratio, ((PyObject *)__pyx_v_cand_cdeg_min_ratio)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5589
* 'cdeg_mean_ratio': cand_cdeg_mean_ratio,
* 'cdeg_min_ratio': cand_cdeg_min_ratio,
* 'cdeg_max_ratio': cand_cdeg_max_ratio, # <<<<<<<<<<<<<<
* 'prhs_ratio_max': cand_prhs_ratio_max,
* 'prhs_ratio_min': cand_prhs_ratio_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cdeg_max_ratio, ((PyObject *)__pyx_v_cand_cdeg_max_ratio)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5590
* 'cdeg_min_ratio': cand_cdeg_min_ratio,
* 'cdeg_max_ratio': cand_cdeg_max_ratio,
* 'prhs_ratio_max': cand_prhs_ratio_max, # <<<<<<<<<<<<<<
* 'prhs_ratio_min': cand_prhs_ratio_min,
* 'nrhs_ratio_max': cand_nrhs_ratio_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_prhs_ratio_max, ((PyObject *)__pyx_v_cand_prhs_ratio_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5591
* 'cdeg_max_ratio': cand_cdeg_max_ratio,
* 'prhs_ratio_max': cand_prhs_ratio_max,
* 'prhs_ratio_min': cand_prhs_ratio_min, # <<<<<<<<<<<<<<
* 'nrhs_ratio_max': cand_nrhs_ratio_max,
* 'nrhs_ratio_min': cand_nrhs_ratio_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_prhs_ratio_min, ((PyObject *)__pyx_v_cand_prhs_ratio_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5592
* 'prhs_ratio_max': cand_prhs_ratio_max,
* 'prhs_ratio_min': cand_prhs_ratio_min,
* 'nrhs_ratio_max': cand_nrhs_ratio_max, # <<<<<<<<<<<<<<
* 'nrhs_ratio_min': cand_nrhs_ratio_min,
* 'ota_pp_max': cand_ota_pp_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nrhs_ratio_max, ((PyObject *)__pyx_v_cand_nrhs_ratio_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5593
* 'prhs_ratio_min': cand_prhs_ratio_min,
* 'nrhs_ratio_max': cand_nrhs_ratio_max,
* 'nrhs_ratio_min': cand_nrhs_ratio_min, # <<<<<<<<<<<<<<
* 'ota_pp_max': cand_ota_pp_max,
* 'ota_pp_min': cand_ota_pp_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nrhs_ratio_min, ((PyObject *)__pyx_v_cand_nrhs_ratio_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5594
* 'nrhs_ratio_max': cand_nrhs_ratio_max,
* 'nrhs_ratio_min': cand_nrhs_ratio_min,
* 'ota_pp_max': cand_ota_pp_max, # <<<<<<<<<<<<<<
* 'ota_pp_min': cand_ota_pp_min,
* 'ota_pn_max': cand_ota_pn_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_pp_max, ((PyObject *)__pyx_v_cand_ota_pp_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5595
* 'nrhs_ratio_min': cand_nrhs_ratio_min,
* 'ota_pp_max': cand_ota_pp_max,
* 'ota_pp_min': cand_ota_pp_min, # <<<<<<<<<<<<<<
* 'ota_pn_max': cand_ota_pn_max,
* 'ota_pn_min': cand_ota_pn_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_pp_min, ((PyObject *)__pyx_v_cand_ota_pp_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5596
* 'ota_pp_max': cand_ota_pp_max,
* 'ota_pp_min': cand_ota_pp_min,
* 'ota_pn_max': cand_ota_pn_max, # <<<<<<<<<<<<<<
* 'ota_pn_min': cand_ota_pn_min,
* 'ota_np_max': cand_ota_np_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_pn_max, ((PyObject *)__pyx_v_cand_ota_pn_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5597
* 'ota_pp_min': cand_ota_pp_min,
* 'ota_pn_max': cand_ota_pn_max,
* 'ota_pn_min': cand_ota_pn_min, # <<<<<<<<<<<<<<
* 'ota_np_max': cand_ota_np_max,
* 'ota_np_min': cand_ota_np_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_pn_min, ((PyObject *)__pyx_v_cand_ota_pn_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5598
* 'ota_pn_max': cand_ota_pn_max,
* 'ota_pn_min': cand_ota_pn_min,
* 'ota_np_max': cand_ota_np_max, # <<<<<<<<<<<<<<
* 'ota_np_min': cand_ota_np_min,
* 'ota_nn_max': cand_ota_nn_max,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_np_max, ((PyObject *)__pyx_v_cand_ota_np_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5599
* 'ota_pn_min': cand_ota_pn_min,
* 'ota_np_max': cand_ota_np_max,
* 'ota_np_min': cand_ota_np_min, # <<<<<<<<<<<<<<
* 'ota_nn_max': cand_ota_nn_max,
* 'ota_nn_min': cand_ota_nn_min,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_np_min, ((PyObject *)__pyx_v_cand_ota_np_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5600
* 'ota_np_max': cand_ota_np_max,
* 'ota_np_min': cand_ota_np_min,
* 'ota_nn_max': cand_ota_nn_max, # <<<<<<<<<<<<<<
* 'ota_nn_min': cand_ota_nn_min,
* 'acons_sum1': cand_acons_sum1,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_nn_max, ((PyObject *)__pyx_v_cand_ota_nn_max)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5601
* 'ota_np_min': cand_ota_np_min,
* 'ota_nn_max': cand_ota_nn_max,
* 'ota_nn_min': cand_ota_nn_min, # <<<<<<<<<<<<<<
* 'acons_sum1': cand_acons_sum1,
* 'acons_mean1': cand_acons_mean1,
*/
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_ota_nn_min, ((PyObject *)__pyx_v_cand_ota_nn_min)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5602
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* 'acons_sum1': cand_acons_sum1, # <<<<<<<<<<<<<<
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if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_acons_sum1, ((PyObject *)__pyx_v_cand_acons_sum1)) < 0) __PYX_ERR(3, 5554, __pyx_L1_error)
/* "pyscipopt/scip.pyx":5603
* 'ota_nn_min': cand_ota_nn_min,
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* 'acons_sum1': cand_acons_sum1,
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* 'acons_var1': cand_acons_var1, # <<<<<<<<<<<<<<
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* 'acons_min1': cand_acons_min1, # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":5607
* 'acons_max1': cand_acons_max1,
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/* "pyscipopt/scip.pyx":5608
* 'acons_min1': cand_acons_min1,
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* 'acons_mean2': cand_acons_mean2, # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":5609
* 'acons_sum2': cand_acons_sum2,
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* 'acons_var2': cand_acons_var2, # <<<<<<<<<<<<<<
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/* "pyscipopt/scip.pyx":5610
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/* "pyscipopt/scip.pyx":5611
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/* "pyscipopt/scip.pyx":5615
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/* "pyscipopt/scip.pyx":5616
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/* "pyscipopt/scip.pyx":5618
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/* "pyscipopt/scip.pyx":5619
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/* "pyscipopt/scip.pyx":5620
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/* "pyscipopt/scip.pyx":5621
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/* "pyscipopt/scip.pyx":5622
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* 'maxdepth': SCIPgetMaxDepth(scip), # maximal depth of all processed nodes in current branch and bound run (excluding probing nodes)
* 'maxtotaldepth': SCIPgetMaxTotalDepth(scip),
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* 'nactivesonss': SCIPgetNActiveConss(scip),
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/* "pyscipopt/scip.pyx":5740
* 'maxtotaldepth': SCIPgetMaxTotalDepth(scip),
* 'nbacktracks': SCIPgetNBacktracks(scip), # total number of backtracks, i.e. number of times, the new node was selected from the leaves queue
* 'nactivesonss': SCIPgetNActiveConss(scip), # <<<<<<<<<<<<<<
* 'nenabledconss': SCIPgetNEnabledConss(scip),
* 'avgdualbound': SCIPgetAvgDualbound(scip), # average dual bound of all unprocessed nodes for original problem
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/* "pyscipopt/scip.pyx":5741
* 'nbacktracks': SCIPgetNBacktracks(scip), # total number of backtracks, i.e. number of times, the new node was selected from the leaves queue
* 'nactivesonss': SCIPgetNActiveConss(scip),
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* 'avgdualbound': SCIPgetAvgDualbound(scip), # average dual bound of all unprocessed nodes for original problem
* 'avglowerbound': SCIPgetAvgLowerbound(scip), # average lower (dual) bound of all unprocessed nodes in transformed problem
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/* "pyscipopt/scip.pyx":5742
* 'nactivesonss': SCIPgetNActiveConss(scip),
* 'nenabledconss': SCIPgetNEnabledConss(scip),
* 'avgdualbound': SCIPgetAvgDualbound(scip), # average dual bound of all unprocessed nodes for original problem # <<<<<<<<<<<<<<
* 'avglowerbound': SCIPgetAvgLowerbound(scip), # average lower (dual) bound of all unprocessed nodes in transformed problem
* 'dualbound': SCIPgetDualbound(scip), # global dual bound
*/
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/* "pyscipopt/scip.pyx":5743
* 'nenabledconss': SCIPgetNEnabledConss(scip),
* 'avgdualbound': SCIPgetAvgDualbound(scip), # average dual bound of all unprocessed nodes for original problem
* 'avglowerbound': SCIPgetAvgLowerbound(scip), # average lower (dual) bound of all unprocessed nodes in transformed problem # <<<<<<<<<<<<<<
* 'dualbound': SCIPgetDualbound(scip), # global dual bound
* 'lowerbound': SCIPgetLowerbound(scip), # global lower (dual) bound in transformed problem
*/
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/* "pyscipopt/scip.pyx":5744
* 'avgdualbound': SCIPgetAvgDualbound(scip), # average dual bound of all unprocessed nodes for original problem
* 'avglowerbound': SCIPgetAvgLowerbound(scip), # average lower (dual) bound of all unprocessed nodes in transformed problem
* 'dualbound': SCIPgetDualbound(scip), # global dual bound # <<<<<<<<<<<<<<
* 'lowerbound': SCIPgetLowerbound(scip), # global lower (dual) bound in transformed problem
* 'dualboundroot': SCIPgetDualboundRoot(scip), # gets dual bound of the root node for the original problem
*/
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/* "pyscipopt/scip.pyx":5745
* 'avglowerbound': SCIPgetAvgLowerbound(scip), # average lower (dual) bound of all unprocessed nodes in transformed problem
* 'dualbound': SCIPgetDualbound(scip), # global dual bound
* 'lowerbound': SCIPgetLowerbound(scip), # global lower (dual) bound in transformed problem # <<<<<<<<<<<<<<
* 'dualboundroot': SCIPgetDualboundRoot(scip), # gets dual bound of the root node for the original problem
* 'lowerboundroot': SCIPgetLowerboundRoot(scip), # gets lower (dual) bound in transformed problem of the root node
*/
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/* "pyscipopt/scip.pyx":5746
* 'dualbound': SCIPgetDualbound(scip), # global dual bound
* 'lowerbound': SCIPgetLowerbound(scip), # global lower (dual) bound in transformed problem
* 'dualboundroot': SCIPgetDualboundRoot(scip), # gets dual bound of the root node for the original problem # <<<<<<<<<<<<<<
* 'lowerboundroot': SCIPgetLowerboundRoot(scip), # gets lower (dual) bound in transformed problem of the root node
* 'firstlpdualboundroot': SCIPgetFirstLPDualboundRoot(scip), # gets dual bound for the original problem obtained by the first LP solve at the root node
*/
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/* "pyscipopt/scip.pyx":5747
* 'lowerbound': SCIPgetLowerbound(scip), # global lower (dual) bound in transformed problem
* 'dualboundroot': SCIPgetDualboundRoot(scip), # gets dual bound of the root node for the original problem
* 'lowerboundroot': SCIPgetLowerboundRoot(scip), # gets lower (dual) bound in transformed problem of the root node # <<<<<<<<<<<<<<
* 'firstlpdualboundroot': SCIPgetFirstLPDualboundRoot(scip), # gets dual bound for the original problem obtained by the first LP solve at the root node
* 'firstlplowerboundroot': SCIPgetFirstLPLowerboundRoot(scip), # gets lower (dual) bound in transformed problem obtained by the first LP solve at the root node
*/
__pyx_t_2 = PyFloat_FromDouble(SCIPgetLowerboundRoot(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5747, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5748
* 'dualboundroot': SCIPgetDualboundRoot(scip), # gets dual bound of the root node for the original problem
* 'lowerboundroot': SCIPgetLowerboundRoot(scip), # gets lower (dual) bound in transformed problem of the root node
* 'firstlpdualboundroot': SCIPgetFirstLPDualboundRoot(scip), # gets dual bound for the original problem obtained by the first LP solve at the root node # <<<<<<<<<<<<<<
* 'firstlplowerboundroot': SCIPgetFirstLPLowerboundRoot(scip), # gets lower (dual) bound in transformed problem obtained by the first LP solve at the root node
* 'firstprimalbound': SCIPgetFirstPrimalBound(scip), # the primal bound of the very first solution
*/
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/* "pyscipopt/scip.pyx":5749
* 'lowerboundroot': SCIPgetLowerboundRoot(scip), # gets lower (dual) bound in transformed problem of the root node
* 'firstlpdualboundroot': SCIPgetFirstLPDualboundRoot(scip), # gets dual bound for the original problem obtained by the first LP solve at the root node
* 'firstlplowerboundroot': SCIPgetFirstLPLowerboundRoot(scip), # gets lower (dual) bound in transformed problem obtained by the first LP solve at the root node # <<<<<<<<<<<<<<
* 'firstprimalbound': SCIPgetFirstPrimalBound(scip), # the primal bound of the very first solution
* 'primalbound': SCIPgetPrimalbound(scip), # gets global primal bound (objective value of best solution or user objective limit) for the original problem
*/
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/* "pyscipopt/scip.pyx":5750
* 'firstlpdualboundroot': SCIPgetFirstLPDualboundRoot(scip), # gets dual bound for the original problem obtained by the first LP solve at the root node
* 'firstlplowerboundroot': SCIPgetFirstLPLowerboundRoot(scip), # gets lower (dual) bound in transformed problem obtained by the first LP solve at the root node
* 'firstprimalbound': SCIPgetFirstPrimalBound(scip), # the primal bound of the very first solution # <<<<<<<<<<<<<<
* 'primalbound': SCIPgetPrimalbound(scip), # gets global primal bound (objective value of best solution or user objective limit) for the original problem
* 'upperbound': SCIPgetUpperbound(scip), # gets global upper (primal) bound in transformed problem (objective value of best solution or user objective limit)
*/
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/* "pyscipopt/scip.pyx":5751
* 'firstlplowerboundroot': SCIPgetFirstLPLowerboundRoot(scip), # gets lower (dual) bound in transformed problem obtained by the first LP solve at the root node
* 'firstprimalbound': SCIPgetFirstPrimalBound(scip), # the primal bound of the very first solution
* 'primalbound': SCIPgetPrimalbound(scip), # gets global primal bound (objective value of best solution or user objective limit) for the original problem # <<<<<<<<<<<<<<
* 'upperbound': SCIPgetUpperbound(scip), # gets global upper (primal) bound in transformed problem (objective value of best solution or user objective limit)
* 'cutoffbound': SCIPgetCutoffbound(scip),
*/
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if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_primalbound, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5752
* 'firstprimalbound': SCIPgetFirstPrimalBound(scip), # the primal bound of the very first solution
* 'primalbound': SCIPgetPrimalbound(scip), # gets global primal bound (objective value of best solution or user objective limit) for the original problem
* 'upperbound': SCIPgetUpperbound(scip), # gets global upper (primal) bound in transformed problem (objective value of best solution or user objective limit) # <<<<<<<<<<<<<<
* 'cutoffbound': SCIPgetCutoffbound(scip),
* 'isprimalboundsol': SCIPisPrimalboundSol(scip),
*/
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/* "pyscipopt/scip.pyx":5753
* 'primalbound': SCIPgetPrimalbound(scip), # gets global primal bound (objective value of best solution or user objective limit) for the original problem
* 'upperbound': SCIPgetUpperbound(scip), # gets global upper (primal) bound in transformed problem (objective value of best solution or user objective limit)
* 'cutoffbound': SCIPgetCutoffbound(scip), # <<<<<<<<<<<<<<
* 'isprimalboundsol': SCIPisPrimalboundSol(scip),
* 'gap': SCIPgetGap(scip),
*/
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__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_cutoffbound, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5754
* 'upperbound': SCIPgetUpperbound(scip), # gets global upper (primal) bound in transformed problem (objective value of best solution or user objective limit)
* 'cutoffbound': SCIPgetCutoffbound(scip),
* 'isprimalboundsol': SCIPisPrimalboundSol(scip), # <<<<<<<<<<<<<<
* 'gap': SCIPgetGap(scip),
* 'transgap': SCIPgetTransGap(scip),
*/
__pyx_t_2 = __Pyx_PyBool_FromLong(SCIPisPrimalboundSol(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5754, __pyx_L1_error)
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if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_isprimalboundsol, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5755
* 'cutoffbound': SCIPgetCutoffbound(scip),
* 'isprimalboundsol': SCIPisPrimalboundSol(scip),
* 'gap': SCIPgetGap(scip), # <<<<<<<<<<<<<<
* 'transgap': SCIPgetTransGap(scip),
* 'nsolsfound': SCIPgetNSolsFound(scip),
*/
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__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_gap, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5756
* 'isprimalboundsol': SCIPisPrimalboundSol(scip),
* 'gap': SCIPgetGap(scip),
* 'transgap': SCIPgetTransGap(scip), # <<<<<<<<<<<<<<
* 'nsolsfound': SCIPgetNSolsFound(scip),
* 'nlimsolsfound': SCIPgetNLimSolsFound(scip),
*/
__pyx_t_2 = PyFloat_FromDouble(SCIPgetTransGap(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5756, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_transgap, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5757
* 'gap': SCIPgetGap(scip),
* 'transgap': SCIPgetTransGap(scip),
* 'nsolsfound': SCIPgetNSolsFound(scip), # <<<<<<<<<<<<<<
* 'nlimsolsfound': SCIPgetNLimSolsFound(scip),
* 'nbestsolsfound': SCIPgetNBestSolsFound(scip),
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__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nsolsfound, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5758
* 'transgap': SCIPgetTransGap(scip),
* 'nsolsfound': SCIPgetNSolsFound(scip),
* 'nlimsolsfound': SCIPgetNLimSolsFound(scip), # <<<<<<<<<<<<<<
* 'nbestsolsfound': SCIPgetNBestSolsFound(scip),
* # SCIPgetAvgPseudocost(scip, SCIP_Real solvaldelta)
*/
__pyx_t_2 = __Pyx_PyInt_From_SCIP_Longint(SCIPgetNLimSolsFound(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5758, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nlimsolsfound, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":5759
* 'nsolsfound': SCIPgetNSolsFound(scip),
* 'nlimsolsfound': SCIPgetNLimSolsFound(scip),
* 'nbestsolsfound': SCIPgetNBestSolsFound(scip), # <<<<<<<<<<<<<<
* # SCIPgetAvgPseudocost(scip, SCIP_Real solvaldelta)
* # SCIPgetAvgPseudocostCurrentRun(scip, SCIP_Real solvaldelta)
*/
__pyx_t_2 = __Pyx_PyInt_From_SCIP_Longint(SCIPgetNBestSolsFound(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5759, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_nbestsolsfound, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
/* "pyscipopt/scip.pyx":5765
* # SCIPgetAvgPseudocostCountCurrentRun(scip, SCIP_BRANCHDIR dir)
* # SCIPgetPseudocostCount(scip, SCIP_BRANCHDIR dir, SCIP_Bool onlycurrentrun)
* 'avgpseudocostscore': SCIPgetAvgPseudocostScore(scip), # <<<<<<<<<<<<<<
* # SCIPgetPseudocostVariance(scip, SCIP_BRANCHDIR branchdir, SCIP_Bool onlycurrentrun)
* 'avgpseudocostscorecurrentrun': SCIPgetAvgPseudocostScoreCurrentRun(scip),
*/
__pyx_t_2 = PyFloat_FromDouble(SCIPgetAvgPseudocostScore(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5765, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_avgpseudocostscore, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
/* "pyscipopt/scip.pyx":5767
* 'avgpseudocostscore': SCIPgetAvgPseudocostScore(scip),
* # SCIPgetPseudocostVariance(scip, SCIP_BRANCHDIR branchdir, SCIP_Bool onlycurrentrun)
* 'avgpseudocostscorecurrentrun': SCIPgetAvgPseudocostScoreCurrentRun(scip), # <<<<<<<<<<<<<<
* 'avgconflictscore': SCIPgetAvgConflictScore(scip),
* 'avgconflictscorecurrentrun': SCIPgetAvgConflictScoreCurrentRun(scip),
*/
__pyx_t_2 = PyFloat_FromDouble(SCIPgetAvgPseudocostScoreCurrentRun(__pyx_v_scip)); if (unlikely(!__pyx_t_2)) __PYX_ERR(3, 5767, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_2);
if (PyDict_SetItem(__pyx_t_3, __pyx_n_u_avgpseudocostscorecurrentrun, __pyx_t_2) < 0) __PYX_ERR(3, 5660, __pyx_L1_error)
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
/* "pyscipopt/scip.pyx":5768
* # SCIPgetPseudocostVariance(scip, SCIP_BRANCHDIR branchdir, SCIP_Bool onlycurrentrun)
* 'avgpseudocostscorecurrentrun': SCIPgetAvgPseudocostScoreCurrentRun(scip),
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__pyx_pw_9pyscipopt_4scip_4Expr_13__iadd__, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
__pyx_pw_9pyscipopt_4scip_4Expr_21__truediv__, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
0, /*nb_index*/
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_matrix_multiply*/
#endif
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_inplace_matrix_multiply*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Expr = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
__pyx_sq_item_9pyscipopt_4scip_Expr, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Expr = {
0, /*mp_length*/
__pyx_pw_9pyscipopt_4scip_4Expr_3__getitem__, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Expr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Expr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Expr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Expr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_4Expr_41__repr__, /*tp_repr*/
&__pyx_tp_as_number_Expr, /*tp_as_number*/
&__pyx_tp_as_sequence_Expr, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Expr, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Expr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Expr, /*tp_clear*/
__pyx_pw_9pyscipopt_4scip_4Expr_37__richcmp__, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
__pyx_pw_9pyscipopt_4scip_4Expr_5__iter__, /*tp_iter*/
__pyx_pw_9pyscipopt_4scip_4Expr_7__next__, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Expr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Expr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_4Expr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Expr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_ExprCons(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_ExprCons *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_ExprCons *)o);
p->expr = Py_None; Py_INCREF(Py_None);
p->_lhs = Py_None; Py_INCREF(Py_None);
p->_rhs = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_ExprCons(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_ExprCons *p = (struct __pyx_obj_9pyscipopt_4scip_ExprCons *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->expr);
Py_CLEAR(p->_lhs);
Py_CLEAR(p->_rhs);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_ExprCons(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_ExprCons *p = (struct __pyx_obj_9pyscipopt_4scip_ExprCons *)o;
if (p->expr) {
e = (*v)(p->expr, a); if (e) return e;
}
if (p->_lhs) {
e = (*v)(p->_lhs, a); if (e) return e;
}
if (p->_rhs) {
e = (*v)(p->_rhs, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_ExprCons(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_ExprCons *p = (struct __pyx_obj_9pyscipopt_4scip_ExprCons *)o;
tmp = ((PyObject*)p->expr);
p->expr = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_lhs);
p->_lhs = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_rhs);
p->_rhs = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8ExprCons_expr(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4expr_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8ExprCons_expr(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4expr_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4expr_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8ExprCons__lhs(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_lhs_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8ExprCons__lhs(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_lhs_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_lhs_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8ExprCons__rhs(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_rhs_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8ExprCons__rhs(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_rhs_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8ExprCons_4_rhs_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_ExprCons[] = {
{"normalize", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8ExprCons_3normalize, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8ExprCons_2normalize},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8ExprCons_11__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8ExprCons_13__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_ExprCons[] = {
{(char *)"expr", __pyx_getprop_9pyscipopt_4scip_8ExprCons_expr, __pyx_setprop_9pyscipopt_4scip_8ExprCons_expr, (char *)0, 0},
{(char *)"_lhs", __pyx_getprop_9pyscipopt_4scip_8ExprCons__lhs, __pyx_setprop_9pyscipopt_4scip_8ExprCons__lhs, (char *)0, 0},
{(char *)"_rhs", __pyx_getprop_9pyscipopt_4scip_8ExprCons__rhs, __pyx_setprop_9pyscipopt_4scip_8ExprCons__rhs, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_ExprCons = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
__pyx_pw_9pyscipopt_4scip_8ExprCons_9__nonzero__, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
0, /*nb_index*/
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_matrix_multiply*/
#endif
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_inplace_matrix_multiply*/
#endif
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_ExprCons = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.ExprCons", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_ExprCons), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_ExprCons, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_8ExprCons_7__repr__, /*tp_repr*/
&__pyx_tp_as_number_ExprCons, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Constraints with a polynomial expressions and lower/upper bounds.", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_ExprCons, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_ExprCons, /*tp_clear*/
__pyx_pw_9pyscipopt_4scip_8ExprCons_5__richcmp__, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_ExprCons, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_ExprCons, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_8ExprCons_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_ExprCons, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_GenExpr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_GenExpr *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_GenExpr *)o);
p->operatorIndex = Py_None; Py_INCREF(Py_None);
p->_op = Py_None; Py_INCREF(Py_None);
p->children = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_GenExpr *p = (struct __pyx_obj_9pyscipopt_4scip_GenExpr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->operatorIndex);
Py_CLEAR(p->_op);
Py_CLEAR(p->children);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_GenExpr *p = (struct __pyx_obj_9pyscipopt_4scip_GenExpr *)o;
if (p->operatorIndex) {
e = (*v)(p->operatorIndex, a); if (e) return e;
}
if (p->_op) {
e = (*v)(p->_op, a); if (e) return e;
}
if (p->children) {
e = (*v)(p->children, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_GenExpr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_GenExpr *p = (struct __pyx_obj_9pyscipopt_4scip_GenExpr *)o;
tmp = ((PyObject*)p->operatorIndex);
p->operatorIndex = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_op);
p->_op = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->children);
p->children = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7GenExpr_operatorIndex(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_13operatorIndex_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7GenExpr_operatorIndex(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_13operatorIndex_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_13operatorIndex_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7GenExpr__op(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_3_op_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7GenExpr__op(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_3_op_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_3_op_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7GenExpr_children(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_8children_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7GenExpr_children(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_8children_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7GenExpr_8children_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_GenExpr[] = {
{"__rdiv__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_13__rdiv__, METH_O, __pyx_doc_9pyscipopt_4scip_7GenExpr_12__rdiv__},
{"__rtruediv__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_17__rtruediv__, METH_O, __pyx_doc_9pyscipopt_4scip_7GenExpr_16__rtruediv__},
{"__radd__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_23__radd__, METH_O, 0},
{"__rmul__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_25__rmul__, METH_O, 0},
{"__rsub__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_27__rsub__, METH_O, 0},
{"degree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_31degree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7GenExpr_30degree},
{"getOp", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_33getOp, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7GenExpr_32getOp},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_35__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7GenExpr_37__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_GenExpr[] = {
{(char *)"operatorIndex", __pyx_getprop_9pyscipopt_4scip_7GenExpr_operatorIndex, __pyx_setprop_9pyscipopt_4scip_7GenExpr_operatorIndex, (char *)0, 0},
{(char *)"_op", __pyx_getprop_9pyscipopt_4scip_7GenExpr__op, __pyx_setprop_9pyscipopt_4scip_7GenExpr__op, (char *)0, 0},
{(char *)"children", __pyx_getprop_9pyscipopt_4scip_7GenExpr_children, __pyx_setprop_9pyscipopt_4scip_7GenExpr_children, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_GenExpr = {
__pyx_pw_9pyscipopt_4scip_7GenExpr_5__add__, /*nb_add*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_21__sub__, /*nb_subtract*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_7__mul__, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
__pyx_pw_9pyscipopt_4scip_7GenExpr_11__div__, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_9__pow__, /*nb_power*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_19__neg__, /*nb_negative*/
0, /*nb_positive*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_3__abs__, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3 || (CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x03050000)
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_15__truediv__, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
0, /*nb_index*/
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_matrix_multiply*/
#endif
#if PY_VERSION_HEX >= 0x03050000
0, /*nb_inplace_matrix_multiply*/
#endif
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_GenExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.GenExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_GenExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_GenExpr, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_GenExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_GenExpr, /*tp_clear*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_29__richcmp__, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_GenExpr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_GenExpr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_7GenExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_GenExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_SumExpr(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_SumExpr *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_SumExpr *)o);
p->constant = Py_None; Py_INCREF(Py_None);
p->coefs = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_SumExpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_SumExpr *p = (struct __pyx_obj_9pyscipopt_4scip_SumExpr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->constant);
Py_CLEAR(p->coefs);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_SumExpr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_SumExpr *p = (struct __pyx_obj_9pyscipopt_4scip_SumExpr *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(o, v, a); if (e) return e;
if (p->constant) {
e = (*v)(p->constant, a); if (e) return e;
}
if (p->coefs) {
e = (*v)(p->coefs, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_SumExpr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_SumExpr *p = (struct __pyx_obj_9pyscipopt_4scip_SumExpr *)o;
__pyx_tp_clear_9pyscipopt_4scip_GenExpr(o);
tmp = ((PyObject*)p->constant);
p->constant = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->coefs);
p->coefs = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7SumExpr_constant(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_8constant_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7SumExpr_constant(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_8constant_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_8constant_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7SumExpr_coefs(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_5coefs_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7SumExpr_coefs(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_5coefs_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7SumExpr_5coefs_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_SumExpr[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7SumExpr_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7SumExpr_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_SumExpr[] = {
{(char *)"constant", __pyx_getprop_9pyscipopt_4scip_7SumExpr_constant, __pyx_setprop_9pyscipopt_4scip_7SumExpr_constant, (char *)0, 0},
{(char *)"coefs", __pyx_getprop_9pyscipopt_4scip_7SumExpr_coefs, __pyx_setprop_9pyscipopt_4scip_7SumExpr_coefs, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_SumExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.SumExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_SumExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_SumExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_7SumExpr_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_SumExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_SumExpr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_SumExpr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_SumExpr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_7SumExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_SumExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
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0, /*tp_del*/
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0, /*tp_finalize*/
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0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_ProdExpr(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_ProdExpr *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_ProdExpr *)o);
p->constant = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_ProdExpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_ProdExpr *p = (struct __pyx_obj_9pyscipopt_4scip_ProdExpr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->constant);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_ProdExpr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_ProdExpr *p = (struct __pyx_obj_9pyscipopt_4scip_ProdExpr *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(o, v, a); if (e) return e;
if (p->constant) {
e = (*v)(p->constant, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_ProdExpr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_ProdExpr *p = (struct __pyx_obj_9pyscipopt_4scip_ProdExpr *)o;
__pyx_tp_clear_9pyscipopt_4scip_GenExpr(o);
tmp = ((PyObject*)p->constant);
p->constant = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8ProdExpr_constant(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8ProdExpr_8constant_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8ProdExpr_constant(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8ProdExpr_8constant_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8ProdExpr_8constant_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_ProdExpr[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8ProdExpr_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8ProdExpr_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_ProdExpr[] = {
{(char *)"constant", __pyx_getprop_9pyscipopt_4scip_8ProdExpr_constant, __pyx_setprop_9pyscipopt_4scip_8ProdExpr_constant, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_ProdExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.ProdExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_ProdExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_ProdExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_8ProdExpr_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_ProdExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_ProdExpr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_ProdExpr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_ProdExpr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_8ProdExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_ProdExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_VarExpr(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_VarExpr *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_VarExpr *)o);
p->var = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_VarExpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_VarExpr *p = (struct __pyx_obj_9pyscipopt_4scip_VarExpr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->var);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_VarExpr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_VarExpr *p = (struct __pyx_obj_9pyscipopt_4scip_VarExpr *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(o, v, a); if (e) return e;
if (p->var) {
e = (*v)(p->var, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_VarExpr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_VarExpr *p = (struct __pyx_obj_9pyscipopt_4scip_VarExpr *)o;
__pyx_tp_clear_9pyscipopt_4scip_GenExpr(o);
tmp = ((PyObject*)p->var);
p->var = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7VarExpr_var(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7VarExpr_3var_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7VarExpr_var(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7VarExpr_3var_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7VarExpr_3var_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_VarExpr[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7VarExpr_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7VarExpr_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_VarExpr[] = {
{(char *)"var", __pyx_getprop_9pyscipopt_4scip_7VarExpr_var, __pyx_setprop_9pyscipopt_4scip_7VarExpr_var, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_VarExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.VarExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_VarExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_VarExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_7VarExpr_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_VarExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_VarExpr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_VarExpr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_VarExpr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_7VarExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_VarExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PowExpr(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_PowExpr *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_PowExpr *)o);
p->expo = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PowExpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_PowExpr *p = (struct __pyx_obj_9pyscipopt_4scip_PowExpr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->expo);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_PowExpr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_PowExpr *p = (struct __pyx_obj_9pyscipopt_4scip_PowExpr *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(o, v, a); if (e) return e;
if (p->expo) {
e = (*v)(p->expo, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_PowExpr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_PowExpr *p = (struct __pyx_obj_9pyscipopt_4scip_PowExpr *)o;
__pyx_tp_clear_9pyscipopt_4scip_GenExpr(o);
tmp = ((PyObject*)p->expo);
p->expo = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7PowExpr_expo(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7PowExpr_4expo_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7PowExpr_expo(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7PowExpr_4expo_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7PowExpr_4expo_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PowExpr[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7PowExpr_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7PowExpr_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_PowExpr[] = {
{(char *)"expo", __pyx_getprop_9pyscipopt_4scip_7PowExpr_expo, __pyx_setprop_9pyscipopt_4scip_7PowExpr_expo, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PowExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PowExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PowExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PowExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_7PowExpr_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_PowExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_PowExpr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PowExpr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_PowExpr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_7PowExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PowExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_UnaryExpr(PyTypeObject *t, PyObject *a, PyObject *k) {
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
return o;
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_UnaryExpr[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9UnaryExpr_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9UnaryExpr_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_UnaryExpr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.UnaryExpr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_UnaryExpr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_9UnaryExpr_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_GenExpr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_GenExpr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_UnaryExpr, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_9UnaryExpr_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_UnaryExpr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Constant(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Constant *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_GenExpr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Constant *)o);
p->number = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Constant(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Constant *p = (struct __pyx_obj_9pyscipopt_4scip_Constant *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->number);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_GenExpr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Constant(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Constant *p = (struct __pyx_obj_9pyscipopt_4scip_Constant *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_GenExpr(o, v, a); if (e) return e;
if (p->number) {
e = (*v)(p->number, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Constant(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Constant *p = (struct __pyx_obj_9pyscipopt_4scip_Constant *)o;
__pyx_tp_clear_9pyscipopt_4scip_GenExpr(o);
tmp = ((PyObject*)p->number);
p->number = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Constant_number(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Constant_6number_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8Constant_number(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8Constant_6number_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8Constant_6number_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Constant[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Constant_5__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Constant_7__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Constant[] = {
{(char *)"number", __pyx_getprop_9pyscipopt_4scip_8Constant_number, __pyx_setprop_9pyscipopt_4scip_8Constant_number, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Constant = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Constant", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Constant), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Constant, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_8Constant_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Constant, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Constant, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Constant, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Constant, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_8Constant_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Constant, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_LP(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_LP *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_LP *)o);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_LP(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_LP *p = (struct __pyx_obj_9pyscipopt_4scip_LP *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
__Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1);
__pyx_pw_9pyscipopt_4scip_2LP_3__dealloc__(o);
__Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1);
PyErr_Restore(etype, eval, etb);
}
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_2LP_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_2LP_4name_1__get__(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_LP[] = {
{"writeLP", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_7writeLP, METH_O, __pyx_doc_9pyscipopt_4scip_2LP_6writeLP},
{"readLP", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_9readLP, METH_O, __pyx_doc_9pyscipopt_4scip_2LP_8readLP},
{"infinity", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_11infinity, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_10infinity},
{"isInfinity", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_13isInfinity, METH_O, __pyx_doc_9pyscipopt_4scip_2LP_12isInfinity},
{"addCol", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_15addCol, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_14addCol},
{"addCols", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_17addCols, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_16addCols},
{"delCols", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_19delCols, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_18delCols},
{"addRow", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_21addRow, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_20addRow},
{"addRows", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_23addRows, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_22addRows},
{"delRows", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_25delRows, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_24delRows},
{"getBounds", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_27getBounds, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_26getBounds},
{"getSides", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_29getSides, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_28getSides},
{"chgObj", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_31chgObj, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_30chgObj},
{"chgCoef", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_33chgCoef, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_32chgCoef},
{"chgBound", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_35chgBound, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_34chgBound},
{"chgSide", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_37chgSide, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_36chgSide},
{"clear", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_39clear, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_38clear},
{"nrows", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_41nrows, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_40nrows},
{"ncols", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_43ncols, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_42ncols},
{"solve", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_2LP_45solve, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_2LP_44solve},
{"getPrimal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_47getPrimal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_46getPrimal},
{"isPrimalFeasible", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_49isPrimalFeasible, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_48isPrimalFeasible},
{"getDual", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_51getDual, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_50getDual},
{"isDualFeasible", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_53isDualFeasible, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_52isDualFeasible},
{"getPrimalRay", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_55getPrimalRay, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_54getPrimalRay},
{"getDualRay", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_57getDualRay, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_56getDualRay},
{"getNIterations", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_59getNIterations, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_58getNIterations},
{"getRedcost", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_61getRedcost, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_60getRedcost},
{"getBasisInds", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_63getBasisInds, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_2LP_62getBasisInds},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_65__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_2LP_67__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_LP[] = {
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_2LP_name, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_LP = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.LP", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_LP), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_LP, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_2LP_5__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_LP, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_LP, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_9pyscipopt_4scip_2LP_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_LP, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Benders(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Benders *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Benders *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Benders(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Benders *p = (struct __pyx_obj_9pyscipopt_4scip_Benders *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Benders(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Benders *p = (struct __pyx_obj_9pyscipopt_4scip_Benders *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Benders(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Benders *p = (struct __pyx_obj_9pyscipopt_4scip_Benders *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7Benders_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7Benders_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7Benders_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7Benders_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7Benders_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7Benders_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7Benders_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7Benders_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7Benders_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7Benders_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Benders[] = {
{"bendersfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_1bendersfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_bendersfree},
{"bendersinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_3bendersinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_2bendersinit},
{"bendersexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_5bendersexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_4bendersexit},
{"bendersinitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_7bendersinitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_6bendersinitpre},
{"bendersexitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_9bendersexitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_8bendersexitpre},
{"bendersinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_11bendersinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_10bendersinitsol},
{"bendersexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_13bendersexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Benders_12bendersexitsol},
{"benderscreatesub", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_15benderscreatesub, METH_O, __pyx_doc_9pyscipopt_4scip_7Benders_14benderscreatesub},
{"benderspresubsolve", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Benders_17benderspresubsolve, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Benders_16benderspresubsolve},
{"benderssolvesubconvex", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Benders_19benderssolvesubconvex, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Benders_18benderssolvesubconvex},
{"benderssolvesub", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Benders_21benderssolvesub, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Benders_20benderssolvesub},
{"benderspostsolve", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Benders_23benderspostsolve, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Benders_22benderspostsolve},
{"bendersfreesub", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_25bendersfreesub, METH_O, __pyx_doc_9pyscipopt_4scip_7Benders_24bendersfreesub},
{"bendersgetvar", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Benders_27bendersgetvar, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Benders_26bendersgetvar},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_29__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Benders_31__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Benders[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_7Benders_model, __pyx_setprop_9pyscipopt_4scip_7Benders_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_7Benders_name, __pyx_setprop_9pyscipopt_4scip_7Benders_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Benders = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Benders", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Benders), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Benders, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Benders, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Benders, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Benders, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Benders, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Benders, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Benderscut(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Benderscut *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Benderscut *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->benders = ((struct __pyx_obj_9pyscipopt_4scip_Benders *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Benderscut(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Benderscut *p = (struct __pyx_obj_9pyscipopt_4scip_Benderscut *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->benders);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Benderscut(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Benderscut *p = (struct __pyx_obj_9pyscipopt_4scip_Benderscut *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
if (p->benders) {
e = (*v)(((PyObject *)p->benders), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Benderscut(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Benderscut *p = (struct __pyx_obj_9pyscipopt_4scip_Benderscut *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->benders);
p->benders = ((struct __pyx_obj_9pyscipopt_4scip_Benders *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Benderscut_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_10Benderscut_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Benderscut_benders(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_7benders_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_10Benderscut_benders(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_7benders_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_7benders_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Benderscut_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_10Benderscut_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_10Benderscut_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Benderscut[] = {
{"benderscutfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_1benderscutfree, METH_NOARGS, 0},
{"benderscutinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_3benderscutinit, METH_NOARGS, 0},
{"benderscutexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_5benderscutexit, METH_NOARGS, 0},
{"benderscutinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_7benderscutinitsol, METH_NOARGS, 0},
{"benderscutexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_9benderscutexitsol, METH_NOARGS, 0},
{"benderscutexec", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_10Benderscut_11benderscutexec, METH_VARARGS|METH_KEYWORDS, 0},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_13__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Benderscut_15__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Benderscut[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_10Benderscut_model, __pyx_setprop_9pyscipopt_4scip_10Benderscut_model, (char *)0, 0},
{(char *)"benders", __pyx_getprop_9pyscipopt_4scip_10Benderscut_benders, __pyx_setprop_9pyscipopt_4scip_10Benderscut_benders, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_10Benderscut_name, __pyx_setprop_9pyscipopt_4scip_10Benderscut_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Benderscut = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Benderscut", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Benderscut), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Benderscut, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Benderscut, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Benderscut, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Benderscut, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Benderscut, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Benderscut, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Branchrule(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Branchrule *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Branchrule *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Branchrule(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Branchrule *p = (struct __pyx_obj_9pyscipopt_4scip_Branchrule *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Branchrule(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Branchrule *p = (struct __pyx_obj_9pyscipopt_4scip_Branchrule *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Branchrule(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Branchrule *p = (struct __pyx_obj_9pyscipopt_4scip_Branchrule *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Branchrule_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Branchrule_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_10Branchrule_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_10Branchrule_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_10Branchrule_5model_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Branchrule[] = {
{"branchfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_1branchfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Branchrule_branchfree},
{"branchinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_3branchinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Branchrule_2branchinit},
{"branchexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_5branchexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Branchrule_4branchexit},
{"branchinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_7branchinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Branchrule_6branchinitsol},
{"branchexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_9branchexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Branchrule_8branchexitsol},
{"branchexeclp", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_11branchexeclp, METH_O, __pyx_doc_9pyscipopt_4scip_10Branchrule_10branchexeclp},
{"branchexecext", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_13branchexecext, METH_O, __pyx_doc_9pyscipopt_4scip_10Branchrule_12branchexecext},
{"branchexecps", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_15branchexecps, METH_O, __pyx_doc_9pyscipopt_4scip_10Branchrule_14branchexecps},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_17__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Branchrule_19__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Branchrule[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_10Branchrule_model, __pyx_setprop_9pyscipopt_4scip_10Branchrule_model, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Branchrule = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Branchrule", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Branchrule), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Branchrule, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Branchrule, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Branchrule, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Branchrule, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Branchrule, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Branchrule, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Conshdlr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Conshdlr *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Conshdlr *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Conshdlr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Conshdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Conshdlr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Conshdlr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Conshdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Conshdlr *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Conshdlr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Conshdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Conshdlr *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Conshdlr_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8Conshdlr_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Conshdlr_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8Conshdlr_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8Conshdlr_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Conshdlr[] = {
{"consfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_1consfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_consfree},
{"consinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_3consinit, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_2consinit},
{"consexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_5consexit, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_4consexit},
{"consinitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_7consinitpre, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_6consinitpre},
{"consexitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_9consexitpre, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_8consexitpre},
{"consinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_11consinitsol, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_10consinitsol},
{"consexitsol", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_13consexitsol, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_12consexitsol},
{"consdelete", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_15consdelete, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_14consdelete},
{"constrans", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_17constrans, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_16constrans},
{"consinitlp", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_19consinitlp, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_18consinitlp},
{"conssepalp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_21conssepalp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_20conssepalp},
{"conssepasol", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_23conssepasol, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_22conssepasol},
{"consenfolp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_25consenfolp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_24consenfolp},
{"consenforelax", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_27consenforelax, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_26consenforelax},
{"consenfops", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_29consenfops, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_28consenfops},
{"conscheck", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_31conscheck, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_30conscheck},
{"consprop", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_33consprop, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_32consprop},
{"conspresol", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_35conspresol, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_34conspresol},
{"consresprop", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_37consresprop, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_36consresprop},
{"conslock", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_8Conshdlr_39conslock, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_38conslock},
{"consactive", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_41consactive, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_40consactive},
{"consdeactive", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_43consdeactive, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_42consdeactive},
{"consenable", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_45consenable, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_44consenable},
{"consdisable", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_47consdisable, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_46consdisable},
{"consdelvars", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_49consdelvars, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_48consdelvars},
{"consprint", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_51consprint, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_50consprint},
{"conscopy", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_53conscopy, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_52conscopy},
{"consparse", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_55consparse, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_54consparse},
{"consgetvars", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_57consgetvars, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_56consgetvars},
{"consgetnvars", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_59consgetnvars, METH_O, __pyx_doc_9pyscipopt_4scip_8Conshdlr_58consgetnvars},
{"consgetdivebdchgs", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_61consgetdivebdchgs, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Conshdlr_60consgetdivebdchgs},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_63__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Conshdlr_65__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Conshdlr[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_8Conshdlr_model, __pyx_setprop_9pyscipopt_4scip_8Conshdlr_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_8Conshdlr_name, __pyx_setprop_9pyscipopt_4scip_8Conshdlr_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Conshdlr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Conshdlr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Conshdlr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Conshdlr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Conshdlr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Conshdlr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Conshdlr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Conshdlr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Conshdlr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Eventhdlr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Eventhdlr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Eventhdlr(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Eventhdlr(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *p = (struct __pyx_obj_9pyscipopt_4scip_Eventhdlr *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_9Eventhdlr_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_9Eventhdlr_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_9Eventhdlr_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_9Eventhdlr_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_9Eventhdlr_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Eventhdlr[] = {
{"eventcopy", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_1eventcopy, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_eventcopy},
{"eventfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_3eventfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_2eventfree},
{"eventinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_5eventinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_4eventinit},
{"eventexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_7eventexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_6eventexit},
{"eventinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_9eventinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_8eventinitsol},
{"eventexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_11eventexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_10eventexitsol},
{"eventdelete", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_13eventdelete, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_12eventdelete},
{"eventexec", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_15eventexec, METH_O, __pyx_doc_9pyscipopt_4scip_9Eventhdlr_14eventexec},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_17__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_9Eventhdlr_19__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Eventhdlr[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_9Eventhdlr_model, __pyx_setprop_9pyscipopt_4scip_9Eventhdlr_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_9Eventhdlr_name, __pyx_setprop_9pyscipopt_4scip_9Eventhdlr_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Eventhdlr = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Eventhdlr", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Eventhdlr), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Eventhdlr, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Eventhdlr, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Eventhdlr, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Eventhdlr, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Eventhdlr, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Eventhdlr, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Heur(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Heur *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Heur *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Heur(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Heur *p = (struct __pyx_obj_9pyscipopt_4scip_Heur *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Heur(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Heur *p = (struct __pyx_obj_9pyscipopt_4scip_Heur *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Heur(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Heur *p = (struct __pyx_obj_9pyscipopt_4scip_Heur *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Heur_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Heur_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Heur_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Heur_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Heur_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Heur_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Heur_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Heur_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Heur_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Heur_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Heur[] = {
{"heurfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_1heurfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Heur_heurfree},
{"heurinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_3heurinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Heur_2heurinit},
{"heurexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_5heurexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Heur_4heurexit},
{"heurinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_7heurinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Heur_6heurinitsol},
{"heurexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_9heurexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Heur_8heurexitsol},
{"heurexec", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_4Heur_11heurexec, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_4Heur_10heurexec},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_13__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Heur_15__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Heur[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_4Heur_model, __pyx_setprop_9pyscipopt_4scip_4Heur_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_4Heur_name, __pyx_setprop_9pyscipopt_4scip_4Heur_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Heur = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Heur", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Heur), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Heur, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Heur, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Heur, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Heur, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Heur, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Heur, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Presol(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Presol *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Presol *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Presol(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Presol *p = (struct __pyx_obj_9pyscipopt_4scip_Presol *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Presol(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Presol *p = (struct __pyx_obj_9pyscipopt_4scip_Presol *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Presol(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Presol *p = (struct __pyx_obj_9pyscipopt_4scip_Presol *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_6Presol_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_6Presol_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_6Presol_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_6Presol_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_6Presol_5model_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Presol[] = {
{"presolfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_1presolfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Presol_presolfree},
{"presolinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_3presolinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Presol_2presolinit},
{"presolexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_5presolexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Presol_4presolexit},
{"presolinitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_7presolinitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Presol_6presolinitpre},
{"presolexitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_9presolexitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Presol_8presolexitpre},
{"presolexec", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_6Presol_11presolexec, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_6Presol_10presolexec},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_13__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Presol_15__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Presol[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_6Presol_model, __pyx_setprop_9pyscipopt_4scip_6Presol_model, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Presol = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Presol", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Presol), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Presol, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Presol, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Presol, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Presol, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Presol, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Presol, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Pricer(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Pricer *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Pricer *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Pricer(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Pricer *p = (struct __pyx_obj_9pyscipopt_4scip_Pricer *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Pricer(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Pricer *p = (struct __pyx_obj_9pyscipopt_4scip_Pricer *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Pricer(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Pricer *p = (struct __pyx_obj_9pyscipopt_4scip_Pricer *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_6Pricer_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_6Pricer_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_6Pricer_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_6Pricer_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_6Pricer_5model_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Pricer[] = {
{"pricerfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_1pricerfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_pricerfree},
{"pricerinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_3pricerinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_2pricerinit},
{"pricerexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_5pricerexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_4pricerexit},
{"pricerinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_7pricerinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_6pricerinitsol},
{"pricerexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_9pricerexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_8pricerexitsol},
{"pricerredcost", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_11pricerredcost, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_10pricerredcost},
{"pricerfarkas", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_13pricerfarkas, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Pricer_12pricerfarkas},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_15__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Pricer_17__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Pricer[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_6Pricer_model, __pyx_setprop_9pyscipopt_4scip_6Pricer_model, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Pricer = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Pricer", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Pricer), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Pricer, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Pricer, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Pricer, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Pricer, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Pricer, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Pricer, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Prop(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Prop *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Prop *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Prop(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Prop *p = (struct __pyx_obj_9pyscipopt_4scip_Prop *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Prop(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Prop *p = (struct __pyx_obj_9pyscipopt_4scip_Prop *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Prop(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Prop *p = (struct __pyx_obj_9pyscipopt_4scip_Prop *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Prop_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Prop_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Prop_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Prop_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Prop_5model_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Prop[] = {
{"propfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_1propfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_propfree},
{"propinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_3propinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_2propinit},
{"propexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_5propexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_4propexit},
{"propinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_7propinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_6propinitsol},
{"propexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_9propexitsol, METH_O, __pyx_doc_9pyscipopt_4scip_4Prop_8propexitsol},
{"propinitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_11propinitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_10propinitpre},
{"propexitpre", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_13propexitpre, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Prop_12propexitpre},
{"proppresol", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_4Prop_15proppresol, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_4Prop_14proppresol},
{"propexec", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_17propexec, METH_O, __pyx_doc_9pyscipopt_4scip_4Prop_16propexec},
{"propresprop", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_4Prop_19propresprop, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_4Prop_18propresprop},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_21__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Prop_23__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Prop[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_4Prop_model, __pyx_setprop_9pyscipopt_4scip_4Prop_model, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Prop = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Prop", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Prop), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Prop, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Prop, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Prop, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Prop, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Prop, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Prop, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Sepa(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Sepa *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Sepa *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Sepa(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Sepa *p = (struct __pyx_obj_9pyscipopt_4scip_Sepa *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Sepa(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Sepa *p = (struct __pyx_obj_9pyscipopt_4scip_Sepa *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Sepa(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Sepa *p = (struct __pyx_obj_9pyscipopt_4scip_Sepa *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Sepa_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Sepa_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Sepa_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Sepa_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Sepa_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Sepa_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Sepa_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Sepa_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Sepa_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Sepa_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Sepa[] = {
{"sepafree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_1sepafree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_sepafree},
{"sepainit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_3sepainit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_2sepainit},
{"sepaexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_5sepaexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_4sepaexit},
{"sepainitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_7sepainitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_6sepainitsol},
{"sepaexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_9sepaexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_8sepaexitsol},
{"sepaexeclp", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_11sepaexeclp, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Sepa_10sepaexeclp},
{"sepaexecsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_13sepaexecsol, METH_O, __pyx_doc_9pyscipopt_4scip_4Sepa_12sepaexecsol},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_15__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Sepa_17__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Sepa[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_4Sepa_model, __pyx_setprop_9pyscipopt_4scip_4Sepa_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_4Sepa_name, __pyx_setprop_9pyscipopt_4scip_4Sepa_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Sepa = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Sepa", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Sepa), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Sepa, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Sepa, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Sepa, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Sepa, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Sepa, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Sepa, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Relax(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Relax *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Relax *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
p->name = ((PyObject*)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Relax(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Relax *p = (struct __pyx_obj_9pyscipopt_4scip_Relax *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Relax(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Relax *p = (struct __pyx_obj_9pyscipopt_4scip_Relax *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Relax(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Relax *p = (struct __pyx_obj_9pyscipopt_4scip_Relax *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_5Relax_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_5Relax_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_5Relax_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_5Relax_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_5Relax_5model_5__del__(o);
}
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_5Relax_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_5Relax_4name_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_5Relax_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_5Relax_4name_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_5Relax_4name_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Relax[] = {
{"relaxfree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_1relaxfree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_relaxfree},
{"relaxinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_3relaxinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_2relaxinit},
{"relaxexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_5relaxexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_4relaxexit},
{"relaxinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_7relaxinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_6relaxinitsol},
{"relaxexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_9relaxexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_8relaxexitsol},
{"relaxexec", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_11relaxexec, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Relax_10relaxexec},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_13__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Relax_15__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Relax[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_5Relax_model, __pyx_setprop_9pyscipopt_4scip_5Relax_model, (char *)0, 0},
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_5Relax_name, __pyx_setprop_9pyscipopt_4scip_5Relax_name, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Relax = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Relax", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Relax), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Relax, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Relax, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Relax, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Relax, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Relax, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Relax, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Nodesel(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Nodesel *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Nodesel *)o);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Nodesel(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Nodesel *p = (struct __pyx_obj_9pyscipopt_4scip_Nodesel *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->model);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Nodesel(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Nodesel *p = (struct __pyx_obj_9pyscipopt_4scip_Nodesel *)o;
if (p->model) {
e = (*v)(((PyObject *)p->model), a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Nodesel(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Nodesel *p = (struct __pyx_obj_9pyscipopt_4scip_Nodesel *)o;
tmp = ((PyObject*)p->model);
p->model = ((struct __pyx_obj_9pyscipopt_4scip_Model *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_7Nodesel_model(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_7Nodesel_5model_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_7Nodesel_model(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_7Nodesel_5model_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_7Nodesel_5model_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Nodesel[] = {
{"nodefree", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_1nodefree, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_nodefree},
{"nodeinit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_3nodeinit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_2nodeinit},
{"nodeexit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_5nodeexit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_4nodeexit},
{"nodeinitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_7nodeinitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_6nodeinitsol},
{"nodeexitsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_9nodeexitsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_8nodeexitsol},
{"nodeselect", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_11nodeselect, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_7Nodesel_10nodeselect},
{"nodecomp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_7Nodesel_13nodecomp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_7Nodesel_12nodecomp},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_15__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_7Nodesel_17__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Nodesel[] = {
{(char *)"model", __pyx_getprop_9pyscipopt_4scip_7Nodesel_model, __pyx_setprop_9pyscipopt_4scip_7Nodesel_model, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Nodesel = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Nodesel", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Nodesel), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Nodesel, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Nodesel, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Nodesel, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Nodesel, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Nodesel, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Nodesel, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_RESULT(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_RESULT(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_RESULT[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_14PY_SCIP_RESULT_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_14PY_SCIP_RESULT_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_RESULT = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_RESULT", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_RESULT), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_RESULT, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_RESULT, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_RESULT, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PARAMSETTING(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PARAMSETTING(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_PARAMSETTING[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_20PY_SCIP_PARAMSETTING_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_20PY_SCIP_PARAMSETTING_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_PARAMSETTING = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_PARAMSETTING", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMSETTING), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PARAMSETTING, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
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__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PARAMSETTING, /*tp_new*/
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0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_21PY_SCIP_PARAMEMPHASIS_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_21PY_SCIP_PARAMEMPHASIS_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS = {
PyVarObject_HEAD_INIT(0, 0)
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sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
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__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PARAMEMPHASIS, /*tp_new*/
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0, /*tp_finalize*/
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0, /*tp_vectorcall*/
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#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_STATUS(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_STATUS(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_STATUS[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_14PY_SCIP_STATUS_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_14PY_SCIP_STATUS_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_STATUS = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_STATUS", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STATUS), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_STATUS, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
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__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_STATUS, /*tp_new*/
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0, /*tp_vectorcall*/
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#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_STAGE(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_STAGE(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_STAGE[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_13PY_SCIP_STAGE_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_13PY_SCIP_STAGE_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_STAGE = {
PyVarObject_HEAD_INIT(0, 0)
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sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_STAGE), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_STAGE, /*tp_dealloc*/
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0, /*tp_print*/
#endif
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_NODETYPE(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_NODETYPE(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_NODETYPE[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_16PY_SCIP_NODETYPE_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_16PY_SCIP_NODETYPE_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_NODETYPE = {
PyVarObject_HEAD_INIT(0, 0)
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sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_NODETYPE), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_NODETYPE, /*tp_dealloc*/
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0, /*tp_print*/
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__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_NODETYPE, /*tp_new*/
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PROPTIMING(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PROPTIMING(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_PROPTIMING[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_18PY_SCIP_PROPTIMING_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_18PY_SCIP_PROPTIMING_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_PROPTIMING = {
PyVarObject_HEAD_INIT(0, 0)
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sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PROPTIMING), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PROPTIMING, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
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static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_20PY_SCIP_PRESOLTIMING_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_20PY_SCIP_PRESOLTIMING_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_PRESOLTIMING", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
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0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_PRESOLTIMING, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_HEURTIMING(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_HEURTIMING(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_HEURTIMING[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_18PY_SCIP_HEURTIMING_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_18PY_SCIP_HEURTIMING_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_HEURTIMING = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_HEURTIMING", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_HEURTIMING), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_HEURTIMING, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_HEURTIMING, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_HEURTIMING, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_EVENTTYPE(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_EVENTTYPE(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_EVENTTYPE[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_EVENTTYPE_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_EVENTTYPE_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_EVENTTYPE = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_EVENTTYPE", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_EVENTTYPE), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_EVENTTYPE, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_EVENTTYPE, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_EVENTTYPE, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_LPSOLSTAT_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_LPSOLSTAT_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_LPSOLSTAT", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_LPSOLSTAT, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_BRANCHDIR(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_BRANCHDIR(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_BRANCHDIR[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_BRANCHDIR_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_17PY_SCIP_BRANCHDIR_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_BRANCHDIR = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_BRANCHDIR", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BRANCHDIR), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_BRANCHDIR, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_BRANCHDIR, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_BRANCHDIR, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE(PyObject *o) {
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_23PY_SCIP_BENDERSENFOTYPE_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_23PY_SCIP_BENDERSENFOTYPE_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.PY_SCIP_BENDERSENFOTYPE", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_PY_SCIP_BENDERSENFOTYPE, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Event __pyx_vtable_9pyscipopt_4scip_Event;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Event(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Event *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Event *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Event;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Event(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Event *p = (struct __pyx_obj_9pyscipopt_4scip_Event *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Event(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Event *p = (struct __pyx_obj_9pyscipopt_4scip_Event *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Event(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Event *p = (struct __pyx_obj_9pyscipopt_4scip_Event *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_5Event_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_5Event_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_5Event_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_5Event_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_5Event_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Event[] = {
{"getType", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_1getType, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Event_getType},
{"getNewBound", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_5getNewBound, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Event_4getNewBound},
{"getOldBound", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_7getOldBound, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Event_6getOldBound},
{"getVar", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_9getVar, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Event_8getVar},
{"getNode", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_11getNode, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Event_10getNode},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_13__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Event_15__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Event[] = {
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_5Event_data, __pyx_setprop_9pyscipopt_4scip_5Event_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Event = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Event", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Event), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Event, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_5Event_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Event, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Event, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Event, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Event, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Event, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Column __pyx_vtable_9pyscipopt_4scip_Column;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Column(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Column *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Column *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Column;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Column(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Column *p = (struct __pyx_obj_9pyscipopt_4scip_Column *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Column(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Column *p = (struct __pyx_obj_9pyscipopt_4scip_Column *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Column(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Column *p = (struct __pyx_obj_9pyscipopt_4scip_Column *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_6Column_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_6Column_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_6Column_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_6Column_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_6Column_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Column[] = {
{"getLPPos", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_1getLPPos, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_getLPPos},
{"getBasisStatus", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_3getBasisStatus, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_2getBasisStatus},
{"isIntegral", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_5isIntegral, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_4isIntegral},
{"getVar", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_7getVar, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_6getVar},
{"getPrimsol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_9getPrimsol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_8getPrimsol},
{"getLb", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_11getLb, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_10getLb},
{"getUb", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_13getUb, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_6Column_12getUb},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_15__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_6Column_17__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Column[] = {
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_6Column_data, __pyx_setprop_9pyscipopt_4scip_6Column_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Column = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Column", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Column), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Column, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Base class holding a pointer to corresponding SCIP_COL", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Column, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Column, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Column, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Column, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Column, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Row __pyx_vtable_9pyscipopt_4scip_Row;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Row(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Row *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Row *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Row;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Row(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Row *p = (struct __pyx_obj_9pyscipopt_4scip_Row *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Row(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Row *p = (struct __pyx_obj_9pyscipopt_4scip_Row *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Row(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Row *p = (struct __pyx_obj_9pyscipopt_4scip_Row *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_3Row_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_3Row_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_3Row_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_3Row_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_3Row_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Row[] = {
{"getLhs", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_1getLhs, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_getLhs},
{"getRhs", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_3getRhs, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_2getRhs},
{"getConstant", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_5getConstant, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_4getConstant},
{"getLPPos", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_7getLPPos, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_6getLPPos},
{"getBasisStatus", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_9getBasisStatus, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_8getBasisStatus},
{"isIntegral", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_11isIntegral, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_10isIntegral},
{"isModifiable", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_13isModifiable, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_12isModifiable},
{"getNNonz", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_15getNNonz, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_14getNNonz},
{"getNLPNonz", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_17getNLPNonz, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_16getNLPNonz},
{"getCols", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_19getCols, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_18getCols},
{"getVals", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_21getVals, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_3Row_20getVals},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_23__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_3Row_25__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Row[] = {
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_3Row_data, __pyx_setprop_9pyscipopt_4scip_3Row_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Row = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Row", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Row), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Row, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Base class holding a pointer to corresponding SCIP_ROW", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Row, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Row, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Row, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Row, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Row, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Solution __pyx_vtable_9pyscipopt_4scip_Solution;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Solution(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Solution *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Solution *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Solution;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Solution(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Solution *p = (struct __pyx_obj_9pyscipopt_4scip_Solution *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Solution(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Solution *p = (struct __pyx_obj_9pyscipopt_4scip_Solution *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Solution(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Solution *p = (struct __pyx_obj_9pyscipopt_4scip_Solution *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Solution_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Solution_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8Solution_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8Solution_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8Solution_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Solution[] = {
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Solution_1__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Solution_3__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Solution[] = {
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_8Solution_data, __pyx_setprop_9pyscipopt_4scip_8Solution_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Solution = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Solution", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Solution), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Solution, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Base class holding a pointer to corresponding SCIP_SOL", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Solution, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Solution, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Solution, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Solution, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Solution, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Node __pyx_vtable_9pyscipopt_4scip_Node;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Node(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Node *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Node *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Node;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Node(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Node *p = (struct __pyx_obj_9pyscipopt_4scip_Node *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Node(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Node *p = (struct __pyx_obj_9pyscipopt_4scip_Node *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Node(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Node *p = (struct __pyx_obj_9pyscipopt_4scip_Node *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_4Node_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_4Node_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_4Node_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_4Node_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_4Node_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Node[] = {
{"getParent", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_1getParent, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_getParent},
{"getNumber", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_3getNumber, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_2getNumber},
{"getDepth", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_5getDepth, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_4getDepth},
{"getType", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_7getType, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_6getType},
{"getLowerbound", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_9getLowerbound, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_8getLowerbound},
{"getEstimate", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_11getEstimate, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_10getEstimate},
{"getNAddedConss", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_13getNAddedConss, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_12getNAddedConss},
{"isActive", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_15isActive, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_14isActive},
{"isPropagatedAgain", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_17isPropagatedAgain, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_16isPropagatedAgain},
{"getBranchInfos", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_19getBranchInfos, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_4Node_18getBranchInfos},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_21__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_4Node_23__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Node[] = {
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_4Node_data, __pyx_setprop_9pyscipopt_4scip_4Node_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Node = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Node", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Node), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Node, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Base class holding a pointer to corresponding SCIP_NODE", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Node, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Node, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Node, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Node, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Node, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Variable __pyx_vtable_9pyscipopt_4scip_Variable;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Variable(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Variable *p;
PyObject *o = __pyx_tp_new_9pyscipopt_4scip_Expr(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Variable *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Variable;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Variable(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Variable *p = (struct __pyx_obj_9pyscipopt_4scip_Variable *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
PyObject_GC_Track(o);
__pyx_tp_dealloc_9pyscipopt_4scip_Expr(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Variable(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Variable *p = (struct __pyx_obj_9pyscipopt_4scip_Variable *)o;
e = __pyx_tp_traverse_9pyscipopt_4scip_Expr(o, v, a); if (e) return e;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Variable(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Variable *p = (struct __pyx_obj_9pyscipopt_4scip_Variable *)o;
__pyx_tp_clear_9pyscipopt_4scip_Expr(o);
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Variable_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Variable_4name_1__get__(o);
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_8Variable_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_8Variable_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_8Variable_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_8Variable_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_8Variable_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Variable[] = {
{"ptr", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_1ptr, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_ptr},
{"vtype", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_5vtype, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_4vtype},
{"isOriginal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_7isOriginal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_6isOriginal},
{"isInLP", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_9isInLP, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_8isInLP},
{"getIndex", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_11getIndex, METH_NOARGS, 0},
{"getCol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_13getCol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_12getCol},
{"getLbOriginal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_15getLbOriginal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_14getLbOriginal},
{"getUbOriginal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_17getUbOriginal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_16getUbOriginal},
{"getLbGlobal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_19getLbGlobal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_18getLbGlobal},
{"getUbGlobal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_21getUbGlobal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_20getUbGlobal},
{"getLbLocal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_23getLbLocal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_22getLbLocal},
{"getUbLocal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_25getUbLocal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_24getUbLocal},
{"getObj", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_27getObj, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_26getObj},
{"getLPSol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_29getLPSol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_8Variable_28getLPSol},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_31__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_8Variable_33__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Variable[] = {
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_8Variable_name, 0, (char *)0, 0},
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_8Variable_data, __pyx_setprop_9pyscipopt_4scip_8Variable_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Variable = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Variable", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Variable), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Variable, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_8Variable_3__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Is a linear expression and has SCIP_VAR*", /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Variable, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Variable, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
#if CYTHON_COMPILING_IN_PYPY
__pyx_pw_9pyscipopt_4scip_4Expr_5__iter__, /*tp_iter*/
#else
0, /*tp_iter*/
#endif
#if CYTHON_COMPILING_IN_PYPY
__pyx_pw_9pyscipopt_4scip_4Expr_7__next__, /*tp_iternext*/
#else
0, /*tp_iternext*/
#endif
__pyx_methods_9pyscipopt_4scip_Variable, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Variable, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
#if CYTHON_COMPILING_IN_PYPY
__pyx_pw_9pyscipopt_4scip_4Expr_1__init__, /*tp_init*/
#else
0, /*tp_init*/
#endif
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Variable, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static struct __pyx_vtabstruct_9pyscipopt_4scip_Constraint __pyx_vtable_9pyscipopt_4scip_Constraint;
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Constraint(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Constraint *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Constraint *)o);
p->__pyx_vtab = __pyx_vtabptr_9pyscipopt_4scip_Constraint;
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Constraint(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Constraint *p = (struct __pyx_obj_9pyscipopt_4scip_Constraint *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Constraint(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Constraint *p = (struct __pyx_obj_9pyscipopt_4scip_Constraint *)o;
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Constraint(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Constraint *p = (struct __pyx_obj_9pyscipopt_4scip_Constraint *)o;
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Constraint_name(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Constraint_4name_1__get__(o);
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_10Constraint_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_10Constraint_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_10Constraint_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_10Constraint_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_10Constraint_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Constraint[] = {
{"isOriginal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_3isOriginal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_2isOriginal},
{"isInitial", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_5isInitial, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_4isInitial},
{"isSeparated", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_7isSeparated, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_6isSeparated},
{"isEnforced", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_9isEnforced, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_8isEnforced},
{"isChecked", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_11isChecked, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_10isChecked},
{"isPropagated", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_13isPropagated, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_12isPropagated},
{"isLocal", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_15isLocal, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_14isLocal},
{"isModifiable", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_17isModifiable, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_16isModifiable},
{"isDynamic", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_19isDynamic, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_18isDynamic},
{"isRemovable", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_21isRemovable, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_20isRemovable},
{"isStickingAtNode", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_23isStickingAtNode, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_22isStickingAtNode},
{"isLinear", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_25isLinear, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_24isLinear},
{"isQuadratic", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_27isQuadratic, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_10Constraint_26isQuadratic},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_29__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_10Constraint_31__setstate_cython__, METH_O, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Constraint[] = {
{(char *)"name", __pyx_getprop_9pyscipopt_4scip_10Constraint_name, 0, (char *)0, 0},
{(char *)"data", __pyx_getprop_9pyscipopt_4scip_10Constraint_data, __pyx_setprop_9pyscipopt_4scip_10Constraint_data, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type_9pyscipopt_4scip_Constraint = {
PyVarObject_HEAD_INIT(0, 0)
"pyscipopt.scip.Constraint", /*tp_name*/
sizeof(struct __pyx_obj_9pyscipopt_4scip_Constraint), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_9pyscipopt_4scip_Constraint, /*tp_dealloc*/
#if PY_VERSION_HEX < 0x030800b4
0, /*tp_print*/
#endif
#if PY_VERSION_HEX >= 0x030800b4
0, /*tp_vectorcall_offset*/
#endif
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_pw_9pyscipopt_4scip_10Constraint_1__repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_9pyscipopt_4scip_Constraint, /*tp_traverse*/
__pyx_tp_clear_9pyscipopt_4scip_Constraint, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_9pyscipopt_4scip_Constraint, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_9pyscipopt_4scip_Constraint, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_9pyscipopt_4scip_Constraint, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
#if PY_VERSION_HEX >= 0x030800b1
0, /*tp_vectorcall*/
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0, /*tp_print*/
#endif
};
static PyObject *__pyx_tp_new_9pyscipopt_4scip_Model(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_9pyscipopt_4scip_Model *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_obj_9pyscipopt_4scip_Model *)o);
p->_bestSol = ((struct __pyx_obj_9pyscipopt_4scip_Solution *)Py_None); Py_INCREF(Py_None);
p->data = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_9pyscipopt_4scip_Model(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip_Model *p = (struct __pyx_obj_9pyscipopt_4scip_Model *)o;
#if CYTHON_USE_TP_FINALIZE
if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
__Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1);
__pyx_pw_9pyscipopt_4scip_5Model_3__dealloc__(o);
__Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1);
PyErr_Restore(etype, eval, etb);
}
if (p->__weakref__) PyObject_ClearWeakRefs(o);
Py_CLEAR(p->_bestSol);
Py_CLEAR(p->data);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_9pyscipopt_4scip_Model(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_obj_9pyscipopt_4scip_Model *p = (struct __pyx_obj_9pyscipopt_4scip_Model *)o;
if (p->_bestSol) {
e = (*v)(((PyObject *)p->_bestSol), a); if (e) return e;
}
if (p->data) {
e = (*v)(p->data, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_9pyscipopt_4scip_Model(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip_Model *p = (struct __pyx_obj_9pyscipopt_4scip_Model *)o;
tmp = ((PyObject*)p->_bestSol);
p->_bestSol = ((struct __pyx_obj_9pyscipopt_4scip_Solution *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->data);
p->data = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyObject *__pyx_getprop_9pyscipopt_4scip_5Model_data(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_9pyscipopt_4scip_5Model_4data_1__get__(o);
}
static int __pyx_setprop_9pyscipopt_4scip_5Model_data(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
if (v) {
return __pyx_pw_9pyscipopt_4scip_5Model_4data_3__set__(o, v);
}
else {
return __pyx_pw_9pyscipopt_4scip_5Model_4data_5__del__(o);
}
}
static PyMethodDef __pyx_methods_9pyscipopt_4scip_Model[] = {
{"create", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_5create, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_4create},
{"includeDefaultPlugins", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_7includeDefaultPlugins, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_6includeDefaultPlugins},
{"createProbBasic", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_9createProbBasic, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_8createProbBasic},
{"freeProb", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_11freeProb, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_10freeProb},
{"freeTransform", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_13freeTransform, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_12freeTransform},
{"version", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_15version, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_14version},
{"printVersion", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_17printVersion, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_16printVersion},
{"getProbName", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_19getProbName, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_18getProbName},
{"getTotalTime", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_21getTotalTime, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_20getTotalTime},
{"getSolvingTime", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_23getSolvingTime, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_22getSolvingTime},
{"getReadingTime", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_25getReadingTime, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_24getReadingTime},
{"getPresolvingTime", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_27getPresolvingTime, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_26getPresolvingTime},
{"getNNodes", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_29getNNodes, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_28getNNodes},
{"getUpperbound", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_31getUpperbound, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_30getUpperbound},
{"getLowerbound", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_33getLowerbound, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_32getLowerbound},
{"getCurrentNode", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_35getCurrentNode, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_34getCurrentNode},
{"getNLPIterations", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_37getNLPIterations, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_36getNLPIterations},
{"getGap", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_39getGap, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_38getGap},
{"getDepth", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_41getDepth, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_40getDepth},
{"infinity", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_43infinity, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_42infinity},
{"epsilon", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_45epsilon, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_44epsilon},
{"feastol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_47feastol, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_46feastol},
{"feasFrac", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_49feasFrac, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_48feasFrac},
{"frac", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_51frac, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_50frac},
{"isZero", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_53isZero, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_52isZero},
{"isFeasZero", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_55isFeasZero, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_54isFeasZero},
{"isInfinity", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_57isInfinity, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_56isInfinity},
{"isFeasNegative", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_59isFeasNegative, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_58isFeasNegative},
{"isFeasIntegral", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_61isFeasIntegral, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_60isFeasIntegral},
{"isLE", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_63isLE, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_62isLE},
{"isLT", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_65isLT, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_64isLT},
{"isGE", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_67isGE, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_66isGE},
{"isGT", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_69isGT, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_68isGT},
{"getCondition", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_71getCondition, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_70getCondition},
{"setMinimize", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_73setMinimize, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_72setMinimize},
{"setMaximize", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_75setMaximize, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_74setMaximize},
{"setObjlimit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_77setObjlimit, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_76setObjlimit},
{"getObjlimit", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_79getObjlimit, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_78getObjlimit},
{"setObjective", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_81setObjective, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_80setObjective},
{"getObjective", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_83getObjective, METH_NOARGS, __pyx_doc_9pyscipopt_4scip_5Model_82getObjective},
{"addObjoffset", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_85addObjoffset, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_84addObjoffset},
{"getObjoffset", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_87getObjoffset, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_86getObjoffset},
{"setPresolve", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_89setPresolve, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_88setPresolve},
{"setProbName", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_91setProbName, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_90setProbName},
{"setSeparating", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_93setSeparating, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_92setSeparating},
{"setHeuristics", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_95setHeuristics, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_94setHeuristics},
{"disablePropagation", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_97disablePropagation, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_96disablePropagation},
{"writeProblem", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_99writeProblem, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_98writeProblem},
{"addVar", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_101addVar, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_100addVar},
{"releaseVar", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_103releaseVar, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_102releaseVar},
{"getTransformedVar", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_105getTransformedVar, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_104getTransformedVar},
{"addVarLocks", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_107addVarLocks, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_106addVarLocks},
{"fixVar", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_109fixVar, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_108fixVar},
{"delVar", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_111delVar, METH_O, __pyx_doc_9pyscipopt_4scip_5Model_110delVar},
{"tightenVarLb", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_113tightenVarLb, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_112tightenVarLb},
{"tightenVarUb", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_115tightenVarUb, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_114tightenVarUb},
{"tightenVarUbGlobal", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_117tightenVarUbGlobal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_116tightenVarUbGlobal},
{"tightenVarLbGlobal", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_119tightenVarLbGlobal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_118tightenVarLbGlobal},
{"chgVarLb", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_121chgVarLb, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_120chgVarLb},
{"chgVarUb", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_123chgVarUb, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_122chgVarUb},
{"chgVarLbGlobal", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_125chgVarLbGlobal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_124chgVarLbGlobal},
{"chgVarUbGlobal", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_127chgVarUbGlobal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_126chgVarUbGlobal},
{"chgVarLbNode", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_129chgVarLbNode, METH_VARARGS|METH_KEYWORDS, __pyx_doc_9pyscipopt_4scip_5Model_128chgVarLbNode},
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{"getTimeSol", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_497getTimeSol, METH_NOARGS, 0},
{"getNPrimalSols", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_499getNPrimalSols, METH_NOARGS, 0},
{"setup_ml_nodelsel", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_501setup_ml_nodelsel, METH_VARARGS|METH_KEYWORDS, 0},
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{"getDingStateLPgraph", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_507getDingStateLPgraph, METH_NOARGS, 0},
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{"executeBranchRule", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_9pyscipopt_4scip_5Model_515executeBranchRule, METH_VARARGS|METH_KEYWORDS, 0},
{"getConsVals", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_517getConsVals, METH_NOARGS, 0},
{"__reduce_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_519__reduce_cython__, METH_NOARGS, 0},
{"__setstate_cython__", (PyCFunction)__pyx_pw_9pyscipopt_4scip_5Model_521__setstate_cython__, METH_O, 0},
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static struct PyGetSetDef __pyx_getsets_9pyscipopt_4scip_Model[] = {
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{0, 0, 0, 0, 0}
};
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__pyx_tp_dealloc_9pyscipopt_4scip_Model, /*tp_dealloc*/
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0, /*tp_print*/
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__pyx_tp_clear_9pyscipopt_4scip_Model, /*tp_clear*/
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0, /*tp_print*/
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static struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__ *__pyx_freelist_9pyscipopt_4scip___pyx_scope_struct____init__[8];
static int __pyx_freecount_9pyscipopt_4scip___pyx_scope_struct____init__ = 0;
static PyObject *__pyx_tp_new_9pyscipopt_4scip___pyx_scope_struct____init__(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
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o = (PyObject*)__pyx_freelist_9pyscipopt_4scip___pyx_scope_struct____init__[--__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct____init__];
memset(o, 0, sizeof(struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__));
(void) PyObject_INIT(o, t);
PyObject_GC_Track(o);
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if (unlikely(!o)) return 0;
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struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__ *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__ *)o;
PyObject_GC_UnTrack(o);
Py_CLEAR(p->__pyx_v_self);
if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct____init__ < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct____init__)))) {
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(*Py_TYPE(o)->tp_free)(o);
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static int __pyx_tp_traverse_9pyscipopt_4scip___pyx_scope_struct____init__(PyObject *o, visitproc v, void *a) {
int e;
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PyObject* tmp;
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tmp = ((PyObject*)p->__pyx_v_self);
p->__pyx_v_self = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
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static PyObject *__pyx_tp_new_9pyscipopt_4scip___pyx_scope_struct_1_genexpr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
PyObject *o;
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o = (PyObject*)__pyx_freelist_9pyscipopt_4scip___pyx_scope_struct_1_genexpr[--__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct_1_genexpr];
memset(o, 0, sizeof(struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr));
(void) PyObject_INIT(o, t);
PyObject_GC_Track(o);
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o = (*t->tp_alloc)(t, 0);
if (unlikely(!o)) return 0;
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return o;
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static void __pyx_tp_dealloc_9pyscipopt_4scip___pyx_scope_struct_1_genexpr(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr *)o;
PyObject_GC_UnTrack(o);
Py_CLEAR(p->__pyx_outer_scope);
Py_CLEAR(p->__pyx_v_v);
Py_CLEAR(p->__pyx_t_0);
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__pyx_freelist_9pyscipopt_4scip___pyx_scope_struct_1_genexpr[__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct_1_genexpr++] = ((struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_1_genexpr *)o);
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(*Py_TYPE(o)->tp_free)(o);
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static int __pyx_tp_traverse_9pyscipopt_4scip___pyx_scope_struct_1_genexpr(PyObject *o, visitproc v, void *a) {
int e;
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o = (PyObject*)__pyx_freelist_9pyscipopt_4scip___pyx_scope_struct_2_degree[--__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct_2_degree];
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(void) PyObject_INIT(o, t);
PyObject_GC_Track(o);
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if (unlikely(!o)) return 0;
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return o;
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static void __pyx_tp_dealloc_9pyscipopt_4scip___pyx_scope_struct_2_degree(PyObject *o) {
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree *)o;
PyObject_GC_UnTrack(o);
Py_CLEAR(p->__pyx_v_self);
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(*Py_TYPE(o)->tp_free)(o);
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static int __pyx_tp_traverse_9pyscipopt_4scip___pyx_scope_struct_2_degree(PyObject *o, visitproc v, void *a) {
int e;
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e = (*v)(((PyObject *)p->__pyx_v_self), a); if (e) return e;
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return 0;
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static int __pyx_tp_clear_9pyscipopt_4scip___pyx_scope_struct_2_degree(PyObject *o) {
PyObject* tmp;
struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_2_degree *)o;
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p->__pyx_v_self = ((struct __pyx_obj_9pyscipopt_4scip_Expr *)Py_None); Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
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PyObject_GC_Track(o);
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PyObject_GC_UnTrack(o);
Py_CLEAR(p->__pyx_outer_scope);
Py_CLEAR(p->__pyx_v_v);
Py_CLEAR(p->__pyx_t_0);
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static PyObject *__pyx_tp_new_9pyscipopt_4scip___pyx_scope_struct_4_addCols(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
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PyObject_GC_Track(o);
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struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols *)o;
PyObject_GC_UnTrack(o);
Py_CLEAR(p->__pyx_v_entrieslist);
if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_9pyscipopt_4scip___pyx_scope_struct_4_addCols < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_4_addCols)))) {
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(*Py_TYPE(o)->tp_free)(o);
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static int __pyx_tp_traverse_9pyscipopt_4scip___pyx_scope_struct_4_addCols(PyObject *o, visitproc v, void *a) {
int e;
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e = (*v)(p->__pyx_v_entrieslist, a); if (e) return e;
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PyObject* tmp;
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p->__pyx_v_entrieslist = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
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PyObject *o;
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memset(o, 0, sizeof(struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_5_genexpr));
(void) PyObject_INIT(o, t);
PyObject_GC_Track(o);
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struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_5_genexpr *p = (struct __pyx_obj_9pyscipopt_4scip___pyx_scope_struct_5_genexpr *)o;
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Py_CLEAR(p->__pyx_outer_scope);
Py_CLEAR(p->__pyx_v_entries);
Py_CLEAR(p->__pyx_t_0);
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int e;
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Py_CLEAR(p->__pyx_v_entrieslist);
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int e;
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__Pyx_GOTREF(__pyx_tuple__11);
__Pyx_GIVEREF(__pyx_tuple__11);
/* "(tree fragment)":4
* raise TypeError("self.lpi cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.lpi cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
__pyx_tuple__12 = PyTuple_Pack(1, __pyx_kp_s_self_lpi_cannot_be_converted_to); if (unlikely(!__pyx_tuple__12)) __PYX_ERR(4, 4, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__12);
__Pyx_GIVEREF(__pyx_tuple__12);
/* "src/pyscipopt/benders.pxi":37
* def benderscreatesub(self, probnumber):
* '''creates the subproblems and registers it with the Benders decomposition struct '''
* print("python error in benderscreatesub: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__13 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_benderscreatesub); if (unlikely(!__pyx_tuple__13)) __PYX_ERR(2, 37, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__13);
__Pyx_GIVEREF(__pyx_tuple__13);
/* "src/pyscipopt/benders.pxi":62
* def bendersgetvar(self, variable, probnumber):
* '''Returns the corresponding master or subproblem variable for the given variable. This provides a call back for the variable mapping between the master and subproblems. '''
* print("python error in bendersgetvar: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__14 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_bendersgetvar_th); if (unlikely(!__pyx_tuple__14)) __PYX_ERR(2, 62, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__14);
__Pyx_GIVEREF(__pyx_tuple__14);
/* "src/pyscipopt/benders.pxi":142
* enfotype = type
* result_dict = PyBenders.benderspresubsolve(solution, enfotype, checkint)
* skipsolve[0] = result_dict.get("skipsolve", False) # <<<<<<<<<<<<<<
* result[0] = result_dict.get("result", <SCIP_RESULT>result[0])
* return SCIP_OKAY
*/
__pyx_tuple__15 = PyTuple_Pack(2, __pyx_n_u_skipsolve, Py_False); if (unlikely(!__pyx_tuple__15)) __PYX_ERR(2, 142, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__15);
__Pyx_GIVEREF(__pyx_tuple__15);
/* "src/pyscipopt/benders.pxi":155
* solution = Solution.create(sol)
* result_dict = PyBenders.benderssolvesubconvex(solution, probnumber, onlyconvex)
* objective[0] = result_dict.get("objective", 1e+20) # <<<<<<<<<<<<<<
* result[0] = result_dict.get("result", <SCIP_RESULT>result[0])
* return SCIP_OKAY
*/
__pyx_tuple__16 = PyTuple_Pack(2, __pyx_n_u_objective, __pyx_float_1e_20); if (unlikely(!__pyx_tuple__16)) __PYX_ERR(2, 155, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__16);
__Pyx_GIVEREF(__pyx_tuple__16);
/* "src/pyscipopt/benders.pxi":187
* mergecandidates.append(mergecands[i])
* result_dict = PyBenders.benderspostsolve(solution, enfotype, mergecandidates, npriomergecands, checkint, infeasible)
* merged[0] = result_dict.get("merged", False) # <<<<<<<<<<<<<<
* return SCIP_OKAY
*
*/
__pyx_tuple__17 = PyTuple_Pack(2, __pyx_n_u_merged, Py_False); if (unlikely(!__pyx_tuple__17)) __PYX_ERR(2, 187, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__17);
__Pyx_GIVEREF(__pyx_tuple__17);
/* "src/pyscipopt/benders.pxi":204
* PyVar = getPyVar(var)
* result_dict = PyBenders.bendersgetvar(PyVar, probnumber)
* mappedvariable = <Variable>(result_dict.get("mappedvar", None)) # <<<<<<<<<<<<<<
* if mappedvariable is None:
* mappedvar[0] = NULL
*/
__pyx_tuple__18 = PyTuple_Pack(2, __pyx_n_u_mappedvar, Py_None); if (unlikely(!__pyx_tuple__18)) __PYX_ERR(2, 204, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__18);
__Pyx_GIVEREF(__pyx_tuple__18);
/* "src/pyscipopt/benderscut.pxi":24
*
* def benderscutexec(self, solution, probnumber, enfotype):
* print("python error in benderscutexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__19 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_benderscutexec_t); if (unlikely(!__pyx_tuple__19)) __PYX_ERR(5, 24, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__19);
__Pyx_GIVEREF(__pyx_tuple__19);
/* "src/pyscipopt/conshdlr.pxi":58
* def consenfolp(self, constraints, nusefulconss, solinfeasible):
* '''calls enforcing method of constraint handler for LP solution for all constraints added'''
* print("python error in consenfolp: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__20 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_consenfolp_this); if (unlikely(!__pyx_tuple__20)) __PYX_ERR(7, 58, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__20);
__Pyx_GIVEREF(__pyx_tuple__20);
/* "src/pyscipopt/conshdlr.pxi":63
* def consenforelax(self, solution, constraints, nusefulconss, solinfeasible):
* '''calls enforcing method of constraint handler for a relaxation solution for all constraints added'''
* print("python error in consenforelax: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__21 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_consenforelax_th); if (unlikely(!__pyx_tuple__21)) __PYX_ERR(7, 63, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__21);
__Pyx_GIVEREF(__pyx_tuple__21);
/* "src/pyscipopt/conshdlr.pxi":68
* def consenfops(self, constraints, nusefulconss, solinfeasible, objinfeasible):
* '''calls enforcing method of constraint handler for pseudo solution for all constraints added'''
* print("python error in consenfops: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__22 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_consenfops_this); if (unlikely(!__pyx_tuple__22)) __PYX_ERR(7, 68, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__22);
__Pyx_GIVEREF(__pyx_tuple__22);
/* "src/pyscipopt/conshdlr.pxi":73
* def conscheck(self, constraints, solution, checkintegrality, checklprows, printreason, completely):
* '''calls feasibility check method of constraint handler '''
* print("python error in conscheck: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__23 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_conscheck_this_m); if (unlikely(!__pyx_tuple__23)) __PYX_ERR(7, 73, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__23);
__Pyx_GIVEREF(__pyx_tuple__23);
/* "src/pyscipopt/conshdlr.pxi":92
* def conslock(self, constraint, locktype, nlockspos, nlocksneg):
* '''variable rounding lock method of constraint handler'''
* print("python error in conslock: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__24 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_conslock_this_me); if (unlikely(!__pyx_tuple__24)) __PYX_ERR(7, 92, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__24);
__Pyx_GIVEREF(__pyx_tuple__24);
/* "src/pyscipopt/conshdlr.pxi":446
* PyCons = getPyCons(cons)
* result_dict = PyConshdlr.consgetnvars(PyCons)
* nvars[0] = result_dict.get("nvars", 0) # <<<<<<<<<<<<<<
* success[0] = result_dict.get("success", False)
* return SCIP_OKAY
*/
__pyx_tuple__25 = PyTuple_Pack(2, __pyx_n_u_nvars, __pyx_int_0); if (unlikely(!__pyx_tuple__25)) __PYX_ERR(7, 446, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__25);
__Pyx_GIVEREF(__pyx_tuple__25);
/* "src/pyscipopt/conshdlr.pxi":447
* result_dict = PyConshdlr.consgetnvars(PyCons)
* nvars[0] = result_dict.get("nvars", 0)
* success[0] = result_dict.get("success", False) # <<<<<<<<<<<<<<
* return SCIP_OKAY
*
*/
__pyx_tuple__26 = PyTuple_Pack(2, __pyx_n_u_success, Py_False); if (unlikely(!__pyx_tuple__26)) __PYX_ERR(7, 447, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__26);
__Pyx_GIVEREF(__pyx_tuple__26);
/* "src/pyscipopt/event.pxi":37
* def eventexec(self, event):
* '''calls execution method of event handler '''
* print("python error in eventexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__27 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_eventexec_this_m); if (unlikely(!__pyx_tuple__27)) __PYX_ERR(8, 37, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__27);
__Pyx_GIVEREF(__pyx_tuple__27);
/* "src/pyscipopt/heuristic.pxi":29
* def heurexec(self, heurtiming, nodeinfeasible):
* '''should the heuristic the executed at the given depth, frequency, timing,...'''
* print("python error in heurexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__28 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_heurexec_this_me); if (unlikely(!__pyx_tuple__28)) __PYX_ERR(9, 29, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__28);
__Pyx_GIVEREF(__pyx_tuple__28);
/* "src/pyscipopt/presol.pxi":28
* def presolexec(self, nrounds, presoltiming):
* '''executes presolver'''
* print("python error in presolexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__29 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_presolexec_this); if (unlikely(!__pyx_tuple__29)) __PYX_ERR(10, 28, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__29);
__Pyx_GIVEREF(__pyx_tuple__29);
/* "src/pyscipopt/presol.pxi":83
* result_dict = PyPresol.presolexec(nrounds, presoltiming)
* result[0] = result_dict.get("result", <SCIP_RESULT>result[0])
* nfixedvars[0] += result_dict.get("nnewfixedvars", 0) # <<<<<<<<<<<<<<
* naggrvars[0] += result_dict.get("nnewaggrvars", 0)
* nchgvartypes[0] += result_dict.get("nnewchgvartypes", 0)
*/
__pyx_tuple__30 = PyTuple_Pack(2, __pyx_n_u_nnewfixedvars, __pyx_int_0); if (unlikely(!__pyx_tuple__30)) __PYX_ERR(10, 83, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__30);
__Pyx_GIVEREF(__pyx_tuple__30);
/* "src/pyscipopt/presol.pxi":84
* result[0] = result_dict.get("result", <SCIP_RESULT>result[0])
* nfixedvars[0] += result_dict.get("nnewfixedvars", 0)
* naggrvars[0] += result_dict.get("nnewaggrvars", 0) # <<<<<<<<<<<<<<
* nchgvartypes[0] += result_dict.get("nnewchgvartypes", 0)
* nchgbds[0] += result_dict.get("nnewchgbds", 0)
*/
__pyx_tuple__31 = PyTuple_Pack(2, __pyx_n_u_nnewaggrvars, __pyx_int_0); if (unlikely(!__pyx_tuple__31)) __PYX_ERR(10, 84, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__31);
__Pyx_GIVEREF(__pyx_tuple__31);
/* "src/pyscipopt/presol.pxi":85
* nfixedvars[0] += result_dict.get("nnewfixedvars", 0)
* naggrvars[0] += result_dict.get("nnewaggrvars", 0)
* nchgvartypes[0] += result_dict.get("nnewchgvartypes", 0) # <<<<<<<<<<<<<<
* nchgbds[0] += result_dict.get("nnewchgbds", 0)
* naddholes[0] += result_dict.get("nnewaddholes", 0)
*/
__pyx_tuple__32 = PyTuple_Pack(2, __pyx_n_u_nnewchgvartypes, __pyx_int_0); if (unlikely(!__pyx_tuple__32)) __PYX_ERR(10, 85, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__32);
__Pyx_GIVEREF(__pyx_tuple__32);
/* "src/pyscipopt/presol.pxi":86
* naggrvars[0] += result_dict.get("nnewaggrvars", 0)
* nchgvartypes[0] += result_dict.get("nnewchgvartypes", 0)
* nchgbds[0] += result_dict.get("nnewchgbds", 0) # <<<<<<<<<<<<<<
* naddholes[0] += result_dict.get("nnewaddholes", 0)
* ndelconss[0] += result_dict.get("nnewdelconss", 0)
*/
__pyx_tuple__33 = PyTuple_Pack(2, __pyx_n_u_nnewchgbds, __pyx_int_0); if (unlikely(!__pyx_tuple__33)) __PYX_ERR(10, 86, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__33);
__Pyx_GIVEREF(__pyx_tuple__33);
/* "src/pyscipopt/presol.pxi":87
* nchgvartypes[0] += result_dict.get("nnewchgvartypes", 0)
* nchgbds[0] += result_dict.get("nnewchgbds", 0)
* naddholes[0] += result_dict.get("nnewaddholes", 0) # <<<<<<<<<<<<<<
* ndelconss[0] += result_dict.get("nnewdelconss", 0)
* naddconss[0] += result_dict.get("nnewaddconss", 0)
*/
__pyx_tuple__34 = PyTuple_Pack(2, __pyx_n_u_nnewaddholes, __pyx_int_0); if (unlikely(!__pyx_tuple__34)) __PYX_ERR(10, 87, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__34);
__Pyx_GIVEREF(__pyx_tuple__34);
/* "src/pyscipopt/presol.pxi":88
* nchgbds[0] += result_dict.get("nnewchgbds", 0)
* naddholes[0] += result_dict.get("nnewaddholes", 0)
* ndelconss[0] += result_dict.get("nnewdelconss", 0) # <<<<<<<<<<<<<<
* naddconss[0] += result_dict.get("nnewaddconss", 0)
* nupgdconss[0] += result_dict.get("nnewupgdconss", 0)
*/
__pyx_tuple__35 = PyTuple_Pack(2, __pyx_n_u_nnewdelconss, __pyx_int_0); if (unlikely(!__pyx_tuple__35)) __PYX_ERR(10, 88, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__35);
__Pyx_GIVEREF(__pyx_tuple__35);
/* "src/pyscipopt/presol.pxi":89
* naddholes[0] += result_dict.get("nnewaddholes", 0)
* ndelconss[0] += result_dict.get("nnewdelconss", 0)
* naddconss[0] += result_dict.get("nnewaddconss", 0) # <<<<<<<<<<<<<<
* nupgdconss[0] += result_dict.get("nnewupgdconss", 0)
* nchgcoefs[0] += result_dict.get("nnewchgcoefs", 0)
*/
__pyx_tuple__36 = PyTuple_Pack(2, __pyx_n_u_nnewaddconss, __pyx_int_0); if (unlikely(!__pyx_tuple__36)) __PYX_ERR(10, 89, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__36);
__Pyx_GIVEREF(__pyx_tuple__36);
/* "src/pyscipopt/presol.pxi":90
* ndelconss[0] += result_dict.get("nnewdelconss", 0)
* naddconss[0] += result_dict.get("nnewaddconss", 0)
* nupgdconss[0] += result_dict.get("nnewupgdconss", 0) # <<<<<<<<<<<<<<
* nchgcoefs[0] += result_dict.get("nnewchgcoefs", 0)
* nchgsides[0] += result_dict.get("nnewchgsides", 0)
*/
__pyx_tuple__37 = PyTuple_Pack(2, __pyx_n_u_nnewupgdconss, __pyx_int_0); if (unlikely(!__pyx_tuple__37)) __PYX_ERR(10, 90, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__37);
__Pyx_GIVEREF(__pyx_tuple__37);
/* "src/pyscipopt/presol.pxi":91
* naddconss[0] += result_dict.get("nnewaddconss", 0)
* nupgdconss[0] += result_dict.get("nnewupgdconss", 0)
* nchgcoefs[0] += result_dict.get("nnewchgcoefs", 0) # <<<<<<<<<<<<<<
* nchgsides[0] += result_dict.get("nnewchgsides", 0)
* return SCIP_OKAY
*/
__pyx_tuple__38 = PyTuple_Pack(2, __pyx_n_u_nnewchgcoefs, __pyx_int_0); if (unlikely(!__pyx_tuple__38)) __PYX_ERR(10, 91, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__38);
__Pyx_GIVEREF(__pyx_tuple__38);
/* "src/pyscipopt/presol.pxi":92
* nupgdconss[0] += result_dict.get("nnewupgdconss", 0)
* nchgcoefs[0] += result_dict.get("nnewchgcoefs", 0)
* nchgsides[0] += result_dict.get("nnewchgsides", 0) # <<<<<<<<<<<<<<
* return SCIP_OKAY
*/
__pyx_tuple__39 = PyTuple_Pack(2, __pyx_n_u_nnewchgsides, __pyx_int_0); if (unlikely(!__pyx_tuple__39)) __PYX_ERR(10, 92, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__39);
__Pyx_GIVEREF(__pyx_tuple__39);
/* "src/pyscipopt/pricer.pxi":28
* def pricerredcost(self):
* '''calls reduced cost pricing method of variable pricer'''
* print("python error in pricerredcost: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__40 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_pricerredcost_th); if (unlikely(!__pyx_tuple__40)) __PYX_ERR(11, 28, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__40);
__Pyx_GIVEREF(__pyx_tuple__40);
/* "src/pyscipopt/propagator.pxi":40
* def propexec(self, proptiming):
* '''calls execution method of propagator'''
* print("python error in propexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__41 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_propexec_this_me); if (unlikely(!__pyx_tuple__41)) __PYX_ERR(12, 40, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__41);
__Pyx_GIVEREF(__pyx_tuple__41);
/* "src/pyscipopt/propagator.pxi":45
* def propresprop(self, confvar, inferinfo, bdtype, relaxedbd):
* '''resolves the given conflicting bound, that was reduced by the given propagator'''
* print("python error in propresprop: this method needs to be implemented") # <<<<<<<<<<<<<<
* return {}
*
*/
__pyx_tuple__42 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_propresprop_this); if (unlikely(!__pyx_tuple__42)) __PYX_ERR(12, 45, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__42);
__Pyx_GIVEREF(__pyx_tuple__42);
/* "src/pyscipopt/relax.pxi":29
* def relaxexec(self):
* '''callls execution method of relaxation handler'''
* print("python error in relaxexec: this method needs to be implemented") # <<<<<<<<<<<<<<
* return{}
*
*/
__pyx_tuple__43 = PyTuple_Pack(1, __pyx_kp_u_python_error_in_relaxexec_this_m); if (unlikely(!__pyx_tuple__43)) __PYX_ERR(14, 29, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__43);
__Pyx_GIVEREF(__pyx_tuple__43);
/* "src/pyscipopt/nodesel.pxi":88
* PyNodesel = <Nodesel>nodeseldata
* result_dict = PyNodesel.nodeselect()
* selected_node = <Node>(result_dict.get("selnode", None)) # <<<<<<<<<<<<<<
* selnode[0] = selected_node.scip_node
* return SCIP_OKAY
*/
__pyx_tuple__44 = PyTuple_Pack(2, __pyx_n_u_selnode, Py_None); if (unlikely(!__pyx_tuple__44)) __PYX_ERR(15, 88, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__44);
__Pyx_GIVEREF(__pyx_tuple__44);
/* "pyscipopt/scip.pyx":223
* pass
* elif rc == SCIP_ERROR:
* raise Exception('SCIP: unspecified error!') # <<<<<<<<<<<<<<
* elif rc == SCIP_NOMEMORY:
* raise MemoryError('SCIP: insufficient memory error!')
*/
__pyx_tuple__45 = PyTuple_Pack(1, __pyx_kp_u_SCIP_unspecified_error); if (unlikely(!__pyx_tuple__45)) __PYX_ERR(3, 223, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__45);
__Pyx_GIVEREF(__pyx_tuple__45);
/* "pyscipopt/scip.pyx":225
* raise Exception('SCIP: unspecified error!')
* elif rc == SCIP_NOMEMORY:
* raise MemoryError('SCIP: insufficient memory error!') # <<<<<<<<<<<<<<
* elif rc == SCIP_READERROR:
* raise IOError('SCIP: read error!')
*/
__pyx_tuple__46 = PyTuple_Pack(1, __pyx_kp_u_SCIP_insufficient_memory_error); if (unlikely(!__pyx_tuple__46)) __PYX_ERR(3, 225, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__46);
__Pyx_GIVEREF(__pyx_tuple__46);
/* "pyscipopt/scip.pyx":227
* raise MemoryError('SCIP: insufficient memory error!')
* elif rc == SCIP_READERROR:
* raise IOError('SCIP: read error!') # <<<<<<<<<<<<<<
* elif rc == SCIP_WRITEERROR:
* raise IOError('SCIP: write error!')
*/
__pyx_tuple__47 = PyTuple_Pack(1, __pyx_kp_u_SCIP_read_error); if (unlikely(!__pyx_tuple__47)) __PYX_ERR(3, 227, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__47);
__Pyx_GIVEREF(__pyx_tuple__47);
/* "pyscipopt/scip.pyx":229
* raise IOError('SCIP: read error!')
* elif rc == SCIP_WRITEERROR:
* raise IOError('SCIP: write error!') # <<<<<<<<<<<<<<
* elif rc == SCIP_NOFILE:
* raise IOError('SCIP: file not found error!')
*/
__pyx_tuple__48 = PyTuple_Pack(1, __pyx_kp_u_SCIP_write_error); if (unlikely(!__pyx_tuple__48)) __PYX_ERR(3, 229, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__48);
__Pyx_GIVEREF(__pyx_tuple__48);
/* "pyscipopt/scip.pyx":231
* raise IOError('SCIP: write error!')
* elif rc == SCIP_NOFILE:
* raise IOError('SCIP: file not found error!') # <<<<<<<<<<<<<<
* elif rc == SCIP_FILECREATEERROR:
* raise IOError('SCIP: cannot create file!')
*/
__pyx_tuple__49 = PyTuple_Pack(1, __pyx_kp_u_SCIP_file_not_found_error); if (unlikely(!__pyx_tuple__49)) __PYX_ERR(3, 231, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__49);
__Pyx_GIVEREF(__pyx_tuple__49);
/* "pyscipopt/scip.pyx":233
* raise IOError('SCIP: file not found error!')
* elif rc == SCIP_FILECREATEERROR:
* raise IOError('SCIP: cannot create file!') # <<<<<<<<<<<<<<
* elif rc == SCIP_LPERROR:
* raise Exception('SCIP: error in LP solver!')
*/
__pyx_tuple__50 = PyTuple_Pack(1, __pyx_kp_u_SCIP_cannot_create_file); if (unlikely(!__pyx_tuple__50)) __PYX_ERR(3, 233, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__50);
__Pyx_GIVEREF(__pyx_tuple__50);
/* "pyscipopt/scip.pyx":235
* raise IOError('SCIP: cannot create file!')
* elif rc == SCIP_LPERROR:
* raise Exception('SCIP: error in LP solver!') # <<<<<<<<<<<<<<
* elif rc == SCIP_NOPROBLEM:
* raise Exception('SCIP: no problem exists!')
*/
__pyx_tuple__51 = PyTuple_Pack(1, __pyx_kp_u_SCIP_error_in_LP_solver); if (unlikely(!__pyx_tuple__51)) __PYX_ERR(3, 235, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_tuple__51);
/* "pyscipopt/scip.pyx":237
* raise Exception('SCIP: error in LP solver!')
* elif rc == SCIP_NOPROBLEM:
* raise Exception('SCIP: no problem exists!') # <<<<<<<<<<<<<<
* elif rc == SCIP_INVALIDCALL:
* raise Exception('SCIP: method cannot be called at this time'
*/
__pyx_tuple__52 = PyTuple_Pack(1, __pyx_kp_u_SCIP_no_problem_exists); if (unlikely(!__pyx_tuple__52)) __PYX_ERR(3, 237, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__52);
__Pyx_GIVEREF(__pyx_tuple__52);
/* "pyscipopt/scip.pyx":239
* raise Exception('SCIP: no problem exists!')
* elif rc == SCIP_INVALIDCALL:
* raise Exception('SCIP: method cannot be called at this time' # <<<<<<<<<<<<<<
* + ' in solution process!')
* elif rc == SCIP_INVALIDDATA:
*/
__pyx_tuple__53 = PyTuple_Pack(1, __pyx_kp_u_SCIP_method_cannot_be_called_at); if (unlikely(!__pyx_tuple__53)) __PYX_ERR(3, 239, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__53);
__Pyx_GIVEREF(__pyx_tuple__53);
/* "pyscipopt/scip.pyx":242
* + ' in solution process!')
* elif rc == SCIP_INVALIDDATA:
* raise Exception('SCIP: error in input data!') # <<<<<<<<<<<<<<
* elif rc == SCIP_INVALIDRESULT:
* raise Exception('SCIP: method returned an invalid result code!')
*/
__pyx_tuple__54 = PyTuple_Pack(1, __pyx_kp_u_SCIP_error_in_input_data); if (unlikely(!__pyx_tuple__54)) __PYX_ERR(3, 242, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__54);
__Pyx_GIVEREF(__pyx_tuple__54);
/* "pyscipopt/scip.pyx":244
* raise Exception('SCIP: error in input data!')
* elif rc == SCIP_INVALIDRESULT:
* raise Exception('SCIP: method returned an invalid result code!') # <<<<<<<<<<<<<<
* elif rc == SCIP_PLUGINNOTFOUND:
* raise Exception('SCIP: a required plugin was not found !')
*/
__pyx_tuple__55 = PyTuple_Pack(1, __pyx_kp_u_SCIP_method_returned_an_invalid); if (unlikely(!__pyx_tuple__55)) __PYX_ERR(3, 244, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__55);
__Pyx_GIVEREF(__pyx_tuple__55);
/* "pyscipopt/scip.pyx":246
* raise Exception('SCIP: method returned an invalid result code!')
* elif rc == SCIP_PLUGINNOTFOUND:
* raise Exception('SCIP: a required plugin was not found !') # <<<<<<<<<<<<<<
* elif rc == SCIP_PARAMETERUNKNOWN:
* raise KeyError('SCIP: the parameter with the given name was not found!')
*/
__pyx_tuple__56 = PyTuple_Pack(1, __pyx_kp_u_SCIP_a_required_plugin_was_not_f); if (unlikely(!__pyx_tuple__56)) __PYX_ERR(3, 246, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__56);
__Pyx_GIVEREF(__pyx_tuple__56);
/* "pyscipopt/scip.pyx":248
* raise Exception('SCIP: a required plugin was not found !')
* elif rc == SCIP_PARAMETERUNKNOWN:
* raise KeyError('SCIP: the parameter with the given name was not found!') # <<<<<<<<<<<<<<
* elif rc == SCIP_PARAMETERWRONGTYPE:
* raise LookupError('SCIP: the parameter is not of the expected type!')
*/
__pyx_tuple__57 = PyTuple_Pack(1, __pyx_kp_u_SCIP_the_parameter_with_the_give); if (unlikely(!__pyx_tuple__57)) __PYX_ERR(3, 248, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__57);
__Pyx_GIVEREF(__pyx_tuple__57);
/* "pyscipopt/scip.pyx":250
* raise KeyError('SCIP: the parameter with the given name was not found!')
* elif rc == SCIP_PARAMETERWRONGTYPE:
* raise LookupError('SCIP: the parameter is not of the expected type!') # <<<<<<<<<<<<<<
* elif rc == SCIP_PARAMETERWRONGVAL:
* raise ValueError('SCIP: the value is invalid for the given parameter!')
*/
__pyx_tuple__58 = PyTuple_Pack(1, __pyx_kp_u_SCIP_the_parameter_is_not_of_the); if (unlikely(!__pyx_tuple__58)) __PYX_ERR(3, 250, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__58);
__Pyx_GIVEREF(__pyx_tuple__58);
/* "pyscipopt/scip.pyx":252
* raise LookupError('SCIP: the parameter is not of the expected type!')
* elif rc == SCIP_PARAMETERWRONGVAL:
* raise ValueError('SCIP: the value is invalid for the given parameter!') # <<<<<<<<<<<<<<
* elif rc == SCIP_KEYALREADYEXISTING:
* raise KeyError('SCIP: the given key is already existing in table!')
*/
__pyx_tuple__59 = PyTuple_Pack(1, __pyx_kp_u_SCIP_the_value_is_invalid_for_th); if (unlikely(!__pyx_tuple__59)) __PYX_ERR(3, 252, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__59);
__Pyx_GIVEREF(__pyx_tuple__59);
/* "pyscipopt/scip.pyx":254
* raise ValueError('SCIP: the value is invalid for the given parameter!')
* elif rc == SCIP_KEYALREADYEXISTING:
* raise KeyError('SCIP: the given key is already existing in table!') # <<<<<<<<<<<<<<
* elif rc == SCIP_MAXDEPTHLEVEL:
* raise Exception('SCIP: maximal branching depth level exceeded!')
*/
__pyx_tuple__60 = PyTuple_Pack(1, __pyx_kp_u_SCIP_the_given_key_is_already_ex); if (unlikely(!__pyx_tuple__60)) __PYX_ERR(3, 254, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__60);
__Pyx_GIVEREF(__pyx_tuple__60);
/* "pyscipopt/scip.pyx":256
* raise KeyError('SCIP: the given key is already existing in table!')
* elif rc == SCIP_MAXDEPTHLEVEL:
* raise Exception('SCIP: maximal branching depth level exceeded!') # <<<<<<<<<<<<<<
* else:
* raise Exception('SCIP: unknown return code!')
*/
__pyx_tuple__61 = PyTuple_Pack(1, __pyx_kp_u_SCIP_maximal_branching_depth_lev); if (unlikely(!__pyx_tuple__61)) __PYX_ERR(3, 256, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__61);
__Pyx_GIVEREF(__pyx_tuple__61);
/* "pyscipopt/scip.pyx":258
* raise Exception('SCIP: maximal branching depth level exceeded!')
* else:
* raise Exception('SCIP: unknown return code!') # <<<<<<<<<<<<<<
*
* cdef class Event:
*/
__pyx_tuple__62 = PyTuple_Pack(1, __pyx_kp_u_SCIP_unknown_return_code); if (unlikely(!__pyx_tuple__62)) __PYX_ERR(3, 258, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__62);
__Pyx_GIVEREF(__pyx_tuple__62);
/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.event cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.event cannot be converted to a Python object for pickling")
*/
__pyx_tuple__63 = PyTuple_Pack(1, __pyx_kp_s_self_event_cannot_be_converted_t); if (unlikely(!__pyx_tuple__63)) __PYX_ERR(4, 2, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__63);
__Pyx_GIVEREF(__pyx_tuple__63);
/* "(tree fragment)":4
* raise TypeError("self.event cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.event cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
__pyx_tuple__64 = PyTuple_Pack(1, __pyx_kp_s_self_event_cannot_be_converted_t); if (unlikely(!__pyx_tuple__64)) __PYX_ERR(4, 4, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__64);
__Pyx_GIVEREF(__pyx_tuple__64);
/* "pyscipopt/scip.pyx":324
* return "zero"
* else:
* raise Exception('SCIP returned unknown base status!') # <<<<<<<<<<<<<<
*
* def isIntegral(self):
*/
__pyx_tuple__65 = PyTuple_Pack(1, __pyx_kp_u_SCIP_returned_unknown_base_statu); if (unlikely(!__pyx_tuple__65)) __PYX_ERR(3, 324, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__65);
__Pyx_GIVEREF(__pyx_tuple__65);
/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.scip_col cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_col cannot be converted to a Python object for pickling")
*/
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__Pyx_GOTREF(__pyx_tuple__66);
__Pyx_GIVEREF(__pyx_tuple__66);
/* "(tree fragment)":4
* raise TypeError("self.scip_col cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_col cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
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__Pyx_GOTREF(__pyx_tuple__67);
__Pyx_GIVEREF(__pyx_tuple__67);
/* "pyscipopt/scip.pyx":386
* elif stat == SCIP_BASESTAT_ZERO:
* # this shouldn't happen!
* raise Exception('SCIP returned base status zero for a row!') # <<<<<<<<<<<<<<
* else:
* raise Exception('SCIP returned unknown base status!')
*/
__pyx_tuple__68 = PyTuple_Pack(1, __pyx_kp_u_SCIP_returned_base_status_zero_f); if (unlikely(!__pyx_tuple__68)) __PYX_ERR(3, 386, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_tuple__68);
/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.scip_row cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_row cannot be converted to a Python object for pickling")
*/
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__Pyx_GOTREF(__pyx_tuple__69);
__Pyx_GIVEREF(__pyx_tuple__69);
/* "(tree fragment)":4
* raise TypeError("self.scip_row cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_row cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
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/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.sol cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.sol cannot be converted to a Python object for pickling")
*/
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/* "(tree fragment)":4
* raise TypeError("self.sol cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.sol cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
__pyx_tuple__72 = PyTuple_Pack(1, __pyx_kp_s_self_sol_cannot_be_converted_to); if (unlikely(!__pyx_tuple__72)) __PYX_ERR(4, 4, __pyx_L1_error)
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/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.scip_node cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_node cannot be converted to a Python object for pickling")
*/
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/* "(tree fragment)":4
* raise TypeError("self.scip_node cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_node cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
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__Pyx_GIVEREF(__pyx_tuple__74);
/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.scip_var cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_var cannot be converted to a Python object for pickling")
*/
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__Pyx_GOTREF(__pyx_tuple__75);
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/* "(tree fragment)":4
* raise TypeError("self.scip_var cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_var cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
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/* "pyscipopt/scip.pyx":585
* cdef create(SCIP_CONS* scipcons):
* if scipcons == NULL:
* raise Warning("cannot create Constraint with SCIP_CONS* == NULL") # <<<<<<<<<<<<<<
* cons = Constraint()
* cons.scip_cons = scipcons
*/
__pyx_tuple__77 = PyTuple_Pack(1, __pyx_kp_u_cannot_create_Constraint_with_SC); if (unlikely(!__pyx_tuple__77)) __PYX_ERR(3, 585, __pyx_L1_error)
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/* "(tree fragment)":2
* def __reduce_cython__(self):
* raise TypeError("self.scip_cons cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_cons cannot be converted to a Python object for pickling")
*/
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/* "(tree fragment)":4
* raise TypeError("self.scip_cons cannot be converted to a Python object for pickling")
* def __setstate_cython__(self, __pyx_state):
* raise TypeError("self.scip_cons cannot be converted to a Python object for pickling") # <<<<<<<<<<<<<<
*/
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/* "pyscipopt/scip.pyx":901
*
* if coeffs.degree() > 1:
* raise ValueError("Nonlinear objective functions are not supported!") # <<<<<<<<<<<<<<
* if coeffs[CONST] != 0.0:
* self.addObjoffset(coeffs[CONST])
*/
__pyx_tuple__80 = PyTuple_Pack(1, __pyx_kp_u_Nonlinear_objective_functions_ar); if (unlikely(!__pyx_tuple__80)) __PYX_ERR(3, 901, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":996
*
* """
* self.setIntParam("propagating/maxroundsroot", 0) # <<<<<<<<<<<<<<
* if not onlyroot:
* self.setIntParam("propagating/maxrounds", 0)
*/
__pyx_tuple__81 = PyTuple_Pack(2, __pyx_kp_u_propagating_maxroundsroot, __pyx_int_0); if (unlikely(!__pyx_tuple__81)) __PYX_ERR(3, 996, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":998
* self.setIntParam("propagating/maxroundsroot", 0)
* if not onlyroot:
* self.setIntParam("propagating/maxrounds", 0) # <<<<<<<<<<<<<<
*
* def writeProblem(self, filename='model.cip', trans=False):
*/
__pyx_tuple__82 = PyTuple_Pack(2, __pyx_kp_u_propagating_maxrounds, __pyx_int_0); if (unlikely(!__pyx_tuple__82)) __PYX_ERR(3, 998, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":1012
* ext = str_conversion('.cip')
* fn = fn + ext
* ext = ext[1:] # <<<<<<<<<<<<<<
* if trans:
* PY_SCIP_CALL(SCIPwriteTransProblem(self._scip, fn, ext, False))
*/
__pyx_slice__83 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__83)) __PYX_ERR(3, 1012, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":1053
* PY_SCIP_CALL(SCIPcreateVarBasic(self._scip, &scip_var, cname, lb, ub, obj, SCIP_VARTYPE_INTEGER))
* else:
* raise Warning("unrecognized variable type") # <<<<<<<<<<<<<<
*
* if pricedVar:
*/
__pyx_tuple__85 = PyTuple_Pack(1, __pyx_kp_u_unrecognized_variable_type); if (unlikely(!__pyx_tuple__85)) __PYX_ERR(3, 1053, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_tuple__85);
/* "pyscipopt/scip.pyx":2051
* cdef SCIP_VAR* _binVar
* if cons._lhs is not None and cons._rhs is not None:
* raise ValueError("expected inequality that has either only a left or right hand side") # <<<<<<<<<<<<<<
*
* if cons.expr.degree() > 1:
*/
__pyx_tuple__86 = PyTuple_Pack(1, __pyx_kp_u_expected_inequality_that_has_eit); if (unlikely(!__pyx_tuple__86)) __PYX_ERR(3, 2051, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_tuple__86);
/* "pyscipopt/scip.pyx":2244
*
* if not self.getStage() >= SCIP_STAGE_SOLVING:
* raise Warning("method cannot be called before problem is solved") # <<<<<<<<<<<<<<
*
* if isinstance(sol, Solution):
*/
__pyx_tuple__87 = PyTuple_Pack(1, __pyx_kp_u_method_cannot_be_called_before_p); if (unlikely(!__pyx_tuple__87)) __PYX_ERR(3, 2244, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":2549
*
* # activating the Benders' decomposition constraint handlers
* self.setBoolParam("constraints/benderslp/active", True) # <<<<<<<<<<<<<<
* self.setBoolParam("constraints/benders/active", True)
* #self.setIntParam("limits/maxorigsol", 0)
*/
__pyx_tuple__88 = PyTuple_Pack(2, __pyx_kp_u_constraints_benderslp_active, Py_True); if (unlikely(!__pyx_tuple__88)) __PYX_ERR(3, 2549, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_tuple__88);
/* "pyscipopt/scip.pyx":2550
* # activating the Benders' decomposition constraint handlers
* self.setBoolParam("constraints/benderslp/active", True)
* self.setBoolParam("constraints/benders/active", True) # <<<<<<<<<<<<<<
* #self.setIntParam("limits/maxorigsol", 0)
*
*/
__pyx_tuple__89 = PyTuple_Pack(2, __pyx_kp_u_constraints_benders_active, Py_True); if (unlikely(!__pyx_tuple__89)) __PYX_ERR(3, 2550, __pyx_L1_error)
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/* "pyscipopt/scip.pyx":3318
* # use this doubled opening pattern to ensure that IOErrors are
* # triggered early and in Python not in C,Cython or SCIP.
* with open(filename, "w") as f: # <<<<<<<<<<<<<<
* cfile = fdopen(f.fileno(), "w")
* PY_SCIP_CALL(SCIPprintBestSol(self._scip, cfile, write_zeros))
*/
__pyx_tuple__95 = PyTuple_Pack(3, Py_None, Py_None, Py_None); if (unlikely(!__pyx_tuple__95)) __PYX_ERR(3, 3318, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__95);
__Pyx_GIVEREF(__pyx_tuple__95);
/* "pyscipopt/scip.pyx":3365
* PY_SCIP_CALL(SCIPreadSolFile(self._scip, fn, solution.sol, False, &partial, &error))
* if error:
* raise Exception("SCIP: reading solution from file failed!") # <<<<<<<<<<<<<<
*
* return solution
*/
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*
*/
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*
* if param == NULL:
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*
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*/
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/* "pyscipopt/scip.pyx":3854
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*
*/
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* raise ValueError("Nonlinear objective functions are not supported!")
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* raise ValueError("Constant offsets in objective are not supported!") # <<<<<<<<<<<<<<
*
* cdef SCIP_VAR** _vars
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* return PY_SCIP_RESULT.DIDNOTFIND
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*
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*
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*
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*
* def __init__(self, *vartuple): # <<<<<<<<<<<<<<
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* return self.hashval
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*
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*/
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*
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/* "src/pyscipopt/expr.pxi":373
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while (argname != first_kw_arg) {
int cmp = (**argname == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 :
#endif
PyUnicode_Compare(**argname, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) goto arg_passed_twice;
argname++;
}
}
} else
goto invalid_keyword_type;
if (kwds2) {
if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
} else {
goto invalid_keyword;
}
}
return 0;
arg_passed_twice:
__Pyx_RaiseDoubleKeywordsError(function_name, key);
goto bad;
invalid_keyword_type:
PyErr_Format(PyExc_TypeError,
"%.200s() keywords must be strings", function_name);
goto bad;
invalid_keyword:
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION < 3
"%.200s() got an unexpected keyword argument '%.200s'",
function_name, PyString_AsString(key));
#else
"%s() got an unexpected keyword argument '%U'",
function_name, key);
#endif
bad:
return -1;
}
/* PyIntCompare */
static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) {
if (op1 == op2) {
Py_RETURN_TRUE;
}
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long a = PyInt_AS_LONG(op1);
if (a == b) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
int unequal;
unsigned long uintval;
Py_ssize_t size = Py_SIZE(op1);
const digit* digits = ((PyLongObject*)op1)->ob_digit;
if (intval == 0) {
if (size == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE;
} else if (intval < 0) {
if (size >= 0)
Py_RETURN_FALSE;
intval = -intval;
size = -size;
} else {
if (size <= 0)
Py_RETURN_FALSE;
}
uintval = (unsigned long) intval;
#if PyLong_SHIFT * 4 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 4)) {
unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 3 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 3)) {
unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 2 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 2)) {
unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 1 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 1)) {
unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK));
if (unequal == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
if ((double)a == (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
return (
PyObject_RichCompare(op1, op2, Py_EQ));
}
/* PyDictVersioning */
#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) {
PyObject *dict = Py_TYPE(obj)->tp_dict;
return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0;
}
static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) {
PyObject **dictptr = NULL;
Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset;
if (offset) {
#if CYTHON_COMPILING_IN_CPYTHON
dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj);
#else
dictptr = _PyObject_GetDictPtr(obj);
#endif
}
return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0;
}
static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) {
PyObject *dict = Py_TYPE(obj)->tp_dict;
if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict)))
return 0;
return obj_dict_version == __Pyx_get_object_dict_version(obj);
}
#endif
/* GetModuleGlobalName */
#if CYTHON_USE_DICT_VERSIONS
static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value)
#else
static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name)
#endif
{
PyObject *result;
#if !CYTHON_AVOID_BORROWED_REFS
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1
result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash);
__PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
if (likely(result)) {
return __Pyx_NewRef(result);
} else if (unlikely(PyErr_Occurred())) {
return NULL;
}
#else
result = PyDict_GetItem(__pyx_d, name);
__PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
if (likely(result)) {
return __Pyx_NewRef(result);
}
#endif
#else
result = PyObject_GetItem(__pyx_d, name);
__PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
if (likely(result)) {
return __Pyx_NewRef(result);
}
PyErr_Clear();
#endif
return __Pyx_GetBuiltinName(name);
}
/* PyCFunctionFastCall */
#if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) {
PyCFunctionObject *func = (PyCFunctionObject*)func_obj;
PyCFunction meth = PyCFunction_GET_FUNCTION(func);
PyObject *self = PyCFunction_GET_SELF(func);
int flags = PyCFunction_GET_FLAGS(func);
assert(PyCFunction_Check(func));
assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS)));
assert(nargs >= 0);
assert(nargs == 0 || args != NULL);
/* _PyCFunction_FastCallDict() must not be called with an exception set,
because it may clear it (directly or indirectly) and so the
caller loses its exception */
assert(!PyErr_Occurred());
if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) {
return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL);
} else {
return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs);
}
}
#endif
/* PyFunctionFastCall */
#if CYTHON_FAST_PYCALL
static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na,
PyObject *globals) {
PyFrameObject *f;
PyThreadState *tstate = __Pyx_PyThreadState_Current;
PyObject **fastlocals;
Py_ssize_t i;
PyObject *result;
assert(globals != NULL);
/* XXX Perhaps we should create a specialized
PyFrame_New() that doesn't take locals, but does
take builtins without sanity checking them.
*/
assert(tstate != NULL);
f = PyFrame_New(tstate, co, globals, NULL);
if (f == NULL) {
return NULL;
}
fastlocals = __Pyx_PyFrame_GetLocalsplus(f);
for (i = 0; i < na; i++) {
Py_INCREF(*args);
fastlocals[i] = *args++;
}
result = PyEval_EvalFrameEx(f,0);
++tstate->recursion_depth;
Py_DECREF(f);
--tstate->recursion_depth;
return result;
}
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) {
PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func);
PyObject *globals = PyFunction_GET_GLOBALS(func);
PyObject *argdefs = PyFunction_GET_DEFAULTS(func);
PyObject *closure;
#if PY_MAJOR_VERSION >= 3
PyObject *kwdefs;
#endif
PyObject *kwtuple, **k;
PyObject **d;
Py_ssize_t nd;
Py_ssize_t nk;
PyObject *result;
assert(kwargs == NULL || PyDict_Check(kwargs));
nk = kwargs ? PyDict_Size(kwargs) : 0;
if (Py_EnterRecursiveCall((char*)" while calling a Python object")) {
return NULL;
}
if (
#if PY_MAJOR_VERSION >= 3
co->co_kwonlyargcount == 0 &&
#endif
likely(kwargs == NULL || nk == 0) &&
co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) {
if (argdefs == NULL && co->co_argcount == nargs) {
result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals);
goto done;
}
else if (nargs == 0 && argdefs != NULL
&& co->co_argcount == Py_SIZE(argdefs)) {
/* function called with no arguments, but all parameters have
a default value: use default values as arguments .*/
args = &PyTuple_GET_ITEM(argdefs, 0);
result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals);
goto done;
}
}
if (kwargs != NULL) {
Py_ssize_t pos, i;
kwtuple = PyTuple_New(2 * nk);
if (kwtuple == NULL) {
result = NULL;
goto done;
}
k = &PyTuple_GET_ITEM(kwtuple, 0);
pos = i = 0;
while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) {
Py_INCREF(k[i]);
Py_INCREF(k[i+1]);
i += 2;
}
nk = i / 2;
}
else {
kwtuple = NULL;
k = NULL;
}
closure = PyFunction_GET_CLOSURE(func);
#if PY_MAJOR_VERSION >= 3
kwdefs = PyFunction_GET_KW_DEFAULTS(func);
#endif
if (argdefs != NULL) {
d = &PyTuple_GET_ITEM(argdefs, 0);
nd = Py_SIZE(argdefs);
}
else {
d = NULL;
nd = 0;
}
#if PY_MAJOR_VERSION >= 3
result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL,
args, (int)nargs,
k, (int)nk,
d, (int)nd, kwdefs, closure);
#else
result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL,
args, (int)nargs,
k, (int)nk,
d, (int)nd, closure);
#endif
Py_XDECREF(kwtuple);
done:
Py_LeaveRecursiveCall();
return result;
}
#endif
#endif
/* PyObjectCall2Args */
static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) {
PyObject *args, *result = NULL;
#if CYTHON_FAST_PYCALL
if (PyFunction_Check(function)) {
PyObject *args[2] = {arg1, arg2};
return __Pyx_PyFunction_FastCall(function, args, 2);
}
#endif
#if CYTHON_FAST_PYCCALL
if (__Pyx_PyFastCFunction_Check(function)) {
PyObject *args[2] = {arg1, arg2};
return __Pyx_PyCFunction_FastCall(function, args, 2);
}
#endif
args = PyTuple_New(2);
if (unlikely(!args)) goto done;
Py_INCREF(arg1);
PyTuple_SET_ITEM(args, 0, arg1);
Py_INCREF(arg2);
PyTuple_SET_ITEM(args, 1, arg2);
Py_INCREF(function);
result = __Pyx_PyObject_Call(function, args, NULL);
Py_DECREF(args);
Py_DECREF(function);
done:
return result;
}
/* PyObjectCallMethO */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
PyObject *self, *result;
PyCFunction cfunc;
cfunc = PyCFunction_GET_FUNCTION(func);
self = PyCFunction_GET_SELF(func);
if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
return NULL;
result = cfunc(self, arg);
Py_LeaveRecursiveCall();
if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
PyErr_SetString(
PyExc_SystemError,
"NULL result without error in PyObject_Call");
}
return result;
}
#endif
/* PyObjectCallOneArg */
#if CYTHON_COMPILING_IN_CPYTHON
static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
PyObject *result;
PyObject *args = PyTuple_New(1);
if (unlikely(!args)) return NULL;
Py_INCREF(arg);
PyTuple_SET_ITEM(args, 0, arg);
result = __Pyx_PyObject_Call(func, args, NULL);
Py_DECREF(args);
return result;
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
#if CYTHON_FAST_PYCALL
if (PyFunction_Check(func)) {
return __Pyx_PyFunction_FastCall(func, &arg, 1);
}
#endif
if (likely(PyCFunction_Check(func))) {
if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
return __Pyx_PyObject_CallMethO(func, arg);
#if CYTHON_FAST_PYCCALL
} else if (__Pyx_PyFastCFunction_Check(func)) {
return __Pyx_PyCFunction_FastCall(func, &arg, 1);
#endif
}
}
return __Pyx__PyObject_CallOneArg(func, arg);
}
#else
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
PyObject *result;
PyObject *args = PyTuple_Pack(1, arg);
if (unlikely(!args)) return NULL;
result = __Pyx_PyObject_Call(func, args, NULL);
Py_DECREF(args);
return result;
}
#endif
/* PyErrFetchRestore */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->curexc_type;
tmp_value = tstate->curexc_value;
tmp_tb = tstate->curexc_traceback;
tstate->curexc_type = type;
tstate->curexc_value = value;
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
*type = tstate->curexc_type;
*value = tstate->curexc_value;
*tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
}
#endif
/* RaiseException */
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
CYTHON_UNUSED PyObject *cause) {
__Pyx_PyThreadState_declare
Py_XINCREF(type);
if (!value || value == Py_None)
value = NULL;
else
Py_INCREF(value);
if (!tb || tb == Py_None)
tb = NULL;
else {
Py_INCREF(tb);
if (!PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto raise_error;
}
}
if (PyType_Check(type)) {
#if CYTHON_COMPILING_IN_PYPY
if (!value) {
Py_INCREF(Py_None);
value = Py_None;
}
#endif
PyErr_NormalizeException(&type, &value, &tb);
} else {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto raise_error;
}
value = type;
type = (PyObject*) Py_TYPE(type);
Py_INCREF(type);
if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto raise_error;
}
}
__Pyx_PyThreadState_assign
__Pyx_ErrRestore(type, value, tb);
return;
raise_error:
Py_XDECREF(value);
Py_XDECREF(type);
Py_XDECREF(tb);
return;
}
#else
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
PyObject* owned_instance = NULL;
if (tb == Py_None) {
tb = 0;
} else if (tb && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto bad;
}
if (value == Py_None)
value = 0;
if (PyExceptionInstance_Check(type)) {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto bad;
}
value = type;
type = (PyObject*) Py_TYPE(value);
} else if (PyExceptionClass_Check(type)) {
PyObject *instance_class = NULL;
if (value && PyExceptionInstance_Check(value)) {
instance_class = (PyObject*) Py_TYPE(value);
if (instance_class != type) {
int is_subclass = PyObject_IsSubclass(instance_class, type);
if (!is_subclass) {
instance_class = NULL;
} else if (unlikely(is_subclass == -1)) {
goto bad;
} else {
type = instance_class;
}
}
}
if (!instance_class) {
PyObject *args;
if (!value)
args = PyTuple_New(0);
else if (PyTuple_Check(value)) {
Py_INCREF(value);
args = value;
} else
args = PyTuple_Pack(1, value);
if (!args)
goto bad;
owned_instance = PyObject_Call(type, args, NULL);
Py_DECREF(args);
if (!owned_instance)
goto bad;
value = owned_instance;
if (!PyExceptionInstance_Check(value)) {
PyErr_Format(PyExc_TypeError,
"calling %R should have returned an instance of "
"BaseException, not %R",
type, Py_TYPE(value));
goto bad;
}
}
} else {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto bad;
}
if (cause) {
PyObject *fixed_cause;
if (cause == Py_None) {
fixed_cause = NULL;
} else if (PyExceptionClass_Check(cause)) {
fixed_cause = PyObject_CallObject(cause, NULL);
if (fixed_cause == NULL)
goto bad;
} else if (PyExceptionInstance_Check(cause)) {
fixed_cause = cause;
Py_INCREF(fixed_cause);
} else {
PyErr_SetString(PyExc_TypeError,
"exception causes must derive from "
"BaseException");
goto bad;
}
PyException_SetCause(value, fixed_cause);
}
PyErr_SetObject(type, value);
if (tb) {
#if CYTHON_COMPILING_IN_PYPY
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
Py_INCREF(tb);
PyErr_Restore(tmp_type, tmp_value, tb);
Py_XDECREF(tmp_tb);
#else
PyThreadState *tstate = __Pyx_PyThreadState_Current;
PyObject* tmp_tb = tstate->curexc_traceback;
if (tb != tmp_tb) {
Py_INCREF(tb);
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_tb);
}
#endif
}
bad:
Py_XDECREF(owned_instance);
return;
}
#endif
/* PyFloatBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_EqObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) {
const double b = floatval;
double a;
(void)inplace;
(void)zerodivision_check;
if (op1 == op2) {
Py_RETURN_TRUE;
}
if (likely(PyFloat_CheckExact(op1))) {
a = PyFloat_AS_DOUBLE(op1);
} else
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
a = (double) PyInt_AS_LONG(op1);
} else
#endif
if (likely(PyLong_CheckExact(op1))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
switch (size) {
case 0: a = 0.0; break;
case -1: a = -(double) digits[0]; break;
case 1: a = (double) digits[0]; break;
case -2:
case 2:
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) {
a = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -2)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -3:
case 3:
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) {
a = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -3)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -4:
case 4:
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) {
a = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -4)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
default:
#else
{
#endif
return (
PyFloat_Type.tp_richcompare(op2, op1, Py_EQ));
}
} else {
return (
PyObject_RichCompare(op1, op2, Py_EQ));
}
if (a == b) {
Py_RETURN_TRUE;
} else {
Py_RETURN_FALSE;
}
}
#endif
/* PyObjectCallNoArg */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
#if CYTHON_FAST_PYCALL
if (PyFunction_Check(func)) {
return __Pyx_PyFunction_FastCall(func, NULL, 0);
}
#endif
#ifdef __Pyx_CyFunction_USED
if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func)))
#else
if (likely(PyCFunction_Check(func)))
#endif
{
if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
return __Pyx_PyObject_CallMethO(func, NULL);
}
}
return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
}
#endif
/* None */
static CYTHON_INLINE void __Pyx_RaiseClosureNameError(const char *varname) {
PyErr_Format(PyExc_NameError, "free variable '%s' referenced before assignment in enclosing scope", varname);
}
/* FetchCommonType */
static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type) {
PyObject* fake_module;
PyTypeObject* cached_type = NULL;
fake_module = PyImport_AddModule((char*) "_cython_" CYTHON_ABI);
if (!fake_module) return NULL;
Py_INCREF(fake_module);
cached_type = (PyTypeObject*) PyObject_GetAttrString(fake_module, type->tp_name);
if (cached_type) {
if (!PyType_Check((PyObject*)cached_type)) {
PyErr_Format(PyExc_TypeError,
"Shared Cython type %.200s is not a type object",
type->tp_name);
goto bad;
}
if (cached_type->tp_basicsize != type->tp_basicsize) {
PyErr_Format(PyExc_TypeError,
"Shared Cython type %.200s has the wrong size, try recompiling",
type->tp_name);
goto bad;
}
} else {
if (!PyErr_ExceptionMatches(PyExc_AttributeError)) goto bad;
PyErr_Clear();
if (PyType_Ready(type) < 0) goto bad;
if (PyObject_SetAttrString(fake_module, type->tp_name, (PyObject*) type) < 0)
goto bad;
Py_INCREF(type);
cached_type = type;
}
done:
Py_DECREF(fake_module);
return cached_type;
bad:
Py_XDECREF(cached_type);
cached_type = NULL;
goto done;
}
/* CythonFunctionShared */
#include <structmember.h>
static PyObject *
__Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *closure)
{
if (unlikely(op->func_doc == NULL)) {
if (op->func.m_ml->ml_doc) {
#if PY_MAJOR_VERSION >= 3
op->func_doc = PyUnicode_FromString(op->func.m_ml->ml_doc);
#else
op->func_doc = PyString_FromString(op->func.m_ml->ml_doc);
#endif
if (unlikely(op->func_doc == NULL))
return NULL;
} else {
Py_INCREF(Py_None);
return Py_None;
}
}
Py_INCREF(op->func_doc);
return op->func_doc;
}
static int
__Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp = op->func_doc;
if (value == NULL) {
value = Py_None;
}
Py_INCREF(value);
op->func_doc = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
if (unlikely(op->func_name == NULL)) {
#if PY_MAJOR_VERSION >= 3
op->func_name = PyUnicode_InternFromString(op->func.m_ml->ml_name);
#else
op->func_name = PyString_InternFromString(op->func.m_ml->ml_name);
#endif
if (unlikely(op->func_name == NULL))
return NULL;
}
Py_INCREF(op->func_name);
return op->func_name;
}
static int
__Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
if (unlikely(value == NULL || !PyUnicode_Check(value)))
#else
if (unlikely(value == NULL || !PyString_Check(value)))
#endif
{
PyErr_SetString(PyExc_TypeError,
"__name__ must be set to a string object");
return -1;
}
tmp = op->func_name;
Py_INCREF(value);
op->func_name = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
Py_INCREF(op->func_qualname);
return op->func_qualname;
}
static int
__Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
if (unlikely(value == NULL || !PyUnicode_Check(value)))
#else
if (unlikely(value == NULL || !PyString_Check(value)))
#endif
{
PyErr_SetString(PyExc_TypeError,
"__qualname__ must be set to a string object");
return -1;
}
tmp = op->func_qualname;
Py_INCREF(value);
op->func_qualname = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_self(__pyx_CyFunctionObject *m, CYTHON_UNUSED void *closure)
{
PyObject *self;
self = m->func_closure;
if (self == NULL)
self = Py_None;
Py_INCREF(self);
return self;
}
static PyObject *
__Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
if (unlikely(op->func_dict == NULL)) {
op->func_dict = PyDict_New();
if (unlikely(op->func_dict == NULL))
return NULL;
}
Py_INCREF(op->func_dict);
return op->func_dict;
}
static int
__Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp;
if (unlikely(value == NULL)) {
PyErr_SetString(PyExc_TypeError,
"function's dictionary may not be deleted");
return -1;
}
if (unlikely(!PyDict_Check(value))) {
PyErr_SetString(PyExc_TypeError,
"setting function's dictionary to a non-dict");
return -1;
}
tmp = op->func_dict;
Py_INCREF(value);
op->func_dict = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
Py_INCREF(op->func_globals);
return op->func_globals;
}
static PyObject *
__Pyx_CyFunction_get_closure(CYTHON_UNUSED __pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
Py_INCREF(Py_None);
return Py_None;
}
static PyObject *
__Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context)
{
PyObject* result = (op->func_code) ? op->func_code : Py_None;
Py_INCREF(result);
return result;
}
static int
__Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) {
int result = 0;
PyObject *res = op->defaults_getter((PyObject *) op);
if (unlikely(!res))
return -1;
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
op->defaults_tuple = PyTuple_GET_ITEM(res, 0);
Py_INCREF(op->defaults_tuple);
op->defaults_kwdict = PyTuple_GET_ITEM(res, 1);
Py_INCREF(op->defaults_kwdict);
#else
op->defaults_tuple = PySequence_ITEM(res, 0);
if (unlikely(!op->defaults_tuple)) result = -1;
else {
op->defaults_kwdict = PySequence_ITEM(res, 1);
if (unlikely(!op->defaults_kwdict)) result = -1;
}
#endif
Py_DECREF(res);
return result;
}
static int
__Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) {
PyObject* tmp;
if (!value) {
value = Py_None;
} else if (value != Py_None && !PyTuple_Check(value)) {
PyErr_SetString(PyExc_TypeError,
"__defaults__ must be set to a tuple object");
return -1;
}
Py_INCREF(value);
tmp = op->defaults_tuple;
op->defaults_tuple = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) {
PyObject* result = op->defaults_tuple;
if (unlikely(!result)) {
if (op->defaults_getter) {
if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL;
result = op->defaults_tuple;
} else {
result = Py_None;
}
}
Py_INCREF(result);
return result;
}
static int
__Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) {
PyObject* tmp;
if (!value) {
value = Py_None;
} else if (value != Py_None && !PyDict_Check(value)) {
PyErr_SetString(PyExc_TypeError,
"__kwdefaults__ must be set to a dict object");
return -1;
}
Py_INCREF(value);
tmp = op->defaults_kwdict;
op->defaults_kwdict = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) {
PyObject* result = op->defaults_kwdict;
if (unlikely(!result)) {
if (op->defaults_getter) {
if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL;
result = op->defaults_kwdict;
} else {
result = Py_None;
}
}
Py_INCREF(result);
return result;
}
static int
__Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) {
PyObject* tmp;
if (!value || value == Py_None) {
value = NULL;
} else if (!PyDict_Check(value)) {
PyErr_SetString(PyExc_TypeError,
"__annotations__ must be set to a dict object");
return -1;
}
Py_XINCREF(value);
tmp = op->func_annotations;
op->func_annotations = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) {
PyObject* result = op->func_annotations;
if (unlikely(!result)) {
result = PyDict_New();
if (unlikely(!result)) return NULL;
op->func_annotations = result;
}
Py_INCREF(result);
return result;
}
static PyGetSetDef __pyx_CyFunction_getsets[] = {
{(char *) "func_doc", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0},
{(char *) "__doc__", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0},
{(char *) "func_name", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0},
{(char *) "__name__", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0},
{(char *) "__qualname__", (getter)__Pyx_CyFunction_get_qualname, (setter)__Pyx_CyFunction_set_qualname, 0, 0},
{(char *) "__self__", (getter)__Pyx_CyFunction_get_self, 0, 0, 0},
{(char *) "func_dict", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0},
{(char *) "__dict__", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0},
{(char *) "func_globals", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0},
{(char *) "__globals__", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0},
{(char *) "func_closure", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0},
{(char *) "__closure__", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0},
{(char *) "func_code", (getter)__Pyx_CyFunction_get_code, 0, 0, 0},
{(char *) "__code__", (getter)__Pyx_CyFunction_get_code, 0, 0, 0},
{(char *) "func_defaults", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0},
{(char *) "__defaults__", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0},
{(char *) "__kwdefaults__", (getter)__Pyx_CyFunction_get_kwdefaults, (setter)__Pyx_CyFunction_set_kwdefaults, 0, 0},
{(char *) "__annotations__", (getter)__Pyx_CyFunction_get_annotations, (setter)__Pyx_CyFunction_set_annotations, 0, 0},
{0, 0, 0, 0, 0}
};
static PyMemberDef __pyx_CyFunction_members[] = {
{(char *) "__module__", T_OBJECT, offsetof(PyCFunctionObject, m_module), PY_WRITE_RESTRICTED, 0},
{0, 0, 0, 0, 0}
};
static PyObject *
__Pyx_CyFunction_reduce(__pyx_CyFunctionObject *m, CYTHON_UNUSED PyObject *args)
{
#if PY_MAJOR_VERSION >= 3
Py_INCREF(m->func_qualname);
return m->func_qualname;
#else
return PyString_FromString(m->func.m_ml->ml_name);
#endif
}
static PyMethodDef __pyx_CyFunction_methods[] = {
{"__reduce__", (PyCFunction)__Pyx_CyFunction_reduce, METH_VARARGS, 0},
{0, 0, 0, 0}
};
#if PY_VERSION_HEX < 0x030500A0
#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func_weakreflist)
#else
#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func.m_weakreflist)
#endif
static PyObject *__Pyx_CyFunction_Init(__pyx_CyFunctionObject *op, PyMethodDef *ml, int flags, PyObject* qualname,
PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) {
if (unlikely(op == NULL))
return NULL;
op->flags = flags;
__Pyx_CyFunction_weakreflist(op) = NULL;
op->func.m_ml = ml;
op->func.m_self = (PyObject *) op;
Py_XINCREF(closure);
op->func_closure = closure;
Py_XINCREF(module);
op->func.m_module = module;
op->func_dict = NULL;
op->func_name = NULL;
Py_INCREF(qualname);
op->func_qualname = qualname;
op->func_doc = NULL;
op->func_classobj = NULL;
op->func_globals = globals;
Py_INCREF(op->func_globals);
Py_XINCREF(code);
op->func_code = code;
op->defaults_pyobjects = 0;
op->defaults_size = 0;
op->defaults = NULL;
op->defaults_tuple = NULL;
op->defaults_kwdict = NULL;
op->defaults_getter = NULL;
op->func_annotations = NULL;
return (PyObject *) op;
}
static int
__Pyx_CyFunction_clear(__pyx_CyFunctionObject *m)
{
Py_CLEAR(m->func_closure);
Py_CLEAR(m->func.m_module);
Py_CLEAR(m->func_dict);
Py_CLEAR(m->func_name);
Py_CLEAR(m->func_qualname);
Py_CLEAR(m->func_doc);
Py_CLEAR(m->func_globals);
Py_CLEAR(m->func_code);
Py_CLEAR(m->func_classobj);
Py_CLEAR(m->defaults_tuple);
Py_CLEAR(m->defaults_kwdict);
Py_CLEAR(m->func_annotations);
if (m->defaults) {
PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m);
int i;
for (i = 0; i < m->defaults_pyobjects; i++)
Py_XDECREF(pydefaults[i]);
PyObject_Free(m->defaults);
m->defaults = NULL;
}
return 0;
}
static void __Pyx__CyFunction_dealloc(__pyx_CyFunctionObject *m)
{
if (__Pyx_CyFunction_weakreflist(m) != NULL)
PyObject_ClearWeakRefs((PyObject *) m);
__Pyx_CyFunction_clear(m);
PyObject_GC_Del(m);
}
static void __Pyx_CyFunction_dealloc(__pyx_CyFunctionObject *m)
{
PyObject_GC_UnTrack(m);
__Pyx__CyFunction_dealloc(m);
}
static int __Pyx_CyFunction_traverse(__pyx_CyFunctionObject *m, visitproc visit, void *arg)
{
Py_VISIT(m->func_closure);
Py_VISIT(m->func.m_module);
Py_VISIT(m->func_dict);
Py_VISIT(m->func_name);
Py_VISIT(m->func_qualname);
Py_VISIT(m->func_doc);
Py_VISIT(m->func_globals);
Py_VISIT(m->func_code);
Py_VISIT(m->func_classobj);
Py_VISIT(m->defaults_tuple);
Py_VISIT(m->defaults_kwdict);
if (m->defaults) {
PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m);
int i;
for (i = 0; i < m->defaults_pyobjects; i++)
Py_VISIT(pydefaults[i]);
}
return 0;
}
static PyObject *__Pyx_CyFunction_descr_get(PyObject *func, PyObject *obj, PyObject *type)
{
#if PY_MAJOR_VERSION < 3
__pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
if (m->flags & __Pyx_CYFUNCTION_STATICMETHOD) {
Py_INCREF(func);
return func;
}
if (m->flags & __Pyx_CYFUNCTION_CLASSMETHOD) {
if (type == NULL)
type = (PyObject *)(Py_TYPE(obj));
return __Pyx_PyMethod_New(func, type, (PyObject *)(Py_TYPE(type)));
}
if (obj == Py_None)
obj = NULL;
#endif
return __Pyx_PyMethod_New(func, obj, type);
}
static PyObject*
__Pyx_CyFunction_repr(__pyx_CyFunctionObject *op)
{
#if PY_MAJOR_VERSION >= 3
return PyUnicode_FromFormat("<cyfunction %U at %p>",
op->func_qualname, (void *)op);
#else
return PyString_FromFormat("<cyfunction %s at %p>",
PyString_AsString(op->func_qualname), (void *)op);
#endif
}
static PyObject * __Pyx_CyFunction_CallMethod(PyObject *func, PyObject *self, PyObject *arg, PyObject *kw) {
PyCFunctionObject* f = (PyCFunctionObject*)func;
PyCFunction meth = f->m_ml->ml_meth;
Py_ssize_t size;
switch (f->m_ml->ml_flags & (METH_VARARGS | METH_KEYWORDS | METH_NOARGS | METH_O)) {
case METH_VARARGS:
if (likely(kw == NULL || PyDict_Size(kw) == 0))
return (*meth)(self, arg);
break;
case METH_VARARGS | METH_KEYWORDS:
return (*(PyCFunctionWithKeywords)(void*)meth)(self, arg, kw);
case METH_NOARGS:
if (likely(kw == NULL || PyDict_Size(kw) == 0)) {
size = PyTuple_GET_SIZE(arg);
if (likely(size == 0))
return (*meth)(self, NULL);
PyErr_Format(PyExc_TypeError,
"%.200s() takes no arguments (%" CYTHON_FORMAT_SSIZE_T "d given)",
f->m_ml->ml_name, size);
return NULL;
}
break;
case METH_O:
if (likely(kw == NULL || PyDict_Size(kw) == 0)) {
size = PyTuple_GET_SIZE(arg);
if (likely(size == 1)) {
PyObject *result, *arg0;
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
arg0 = PyTuple_GET_ITEM(arg, 0);
#else
arg0 = PySequence_ITEM(arg, 0); if (unlikely(!arg0)) return NULL;
#endif
result = (*meth)(self, arg0);
#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS)
Py_DECREF(arg0);
#endif
return result;
}
PyErr_Format(PyExc_TypeError,
"%.200s() takes exactly one argument (%" CYTHON_FORMAT_SSIZE_T "d given)",
f->m_ml->ml_name, size);
return NULL;
}
break;
default:
PyErr_SetString(PyExc_SystemError, "Bad call flags in "
"__Pyx_CyFunction_Call. METH_OLDARGS is no "
"longer supported!");
return NULL;
}
PyErr_Format(PyExc_TypeError, "%.200s() takes no keyword arguments",
f->m_ml->ml_name);
return NULL;
}
static CYTHON_INLINE PyObject *__Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) {
return __Pyx_CyFunction_CallMethod(func, ((PyCFunctionObject*)func)->m_self, arg, kw);
}
static PyObject *__Pyx_CyFunction_CallAsMethod(PyObject *func, PyObject *args, PyObject *kw) {
PyObject *result;
__pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func;
if ((cyfunc->flags & __Pyx_CYFUNCTION_CCLASS) && !(cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD)) {
Py_ssize_t argc;
PyObject *new_args;
PyObject *self;
argc = PyTuple_GET_SIZE(args);
new_args = PyTuple_GetSlice(args, 1, argc);
if (unlikely(!new_args))
return NULL;
self = PyTuple_GetItem(args, 0);
if (unlikely(!self)) {
Py_DECREF(new_args);
return NULL;
}
result = __Pyx_CyFunction_CallMethod(func, self, new_args, kw);
Py_DECREF(new_args);
} else {
result = __Pyx_CyFunction_Call(func, args, kw);
}
return result;
}
static PyTypeObject __pyx_CyFunctionType_type = {
PyVarObject_HEAD_INIT(0, 0)
"cython_function_or_method",
sizeof(__pyx_CyFunctionObject),
0,
(destructor) __Pyx_CyFunction_dealloc,
0,
0,
0,
#if PY_MAJOR_VERSION < 3
0,
#else
0,
#endif
(reprfunc) __Pyx_CyFunction_repr,
0,
0,
0,
0,
__Pyx_CyFunction_CallAsMethod,
0,
0,
0,
0,
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC,
0,
(traverseproc) __Pyx_CyFunction_traverse,
(inquiry) __Pyx_CyFunction_clear,
0,
#if PY_VERSION_HEX < 0x030500A0
offsetof(__pyx_CyFunctionObject, func_weakreflist),
#else
offsetof(PyCFunctionObject, m_weakreflist),
#endif
0,
0,
__pyx_CyFunction_methods,
__pyx_CyFunction_members,
__pyx_CyFunction_getsets,
0,
0,
__Pyx_CyFunction_descr_get,
0,
offsetof(__pyx_CyFunctionObject, func_dict),
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
#if PY_VERSION_HEX >= 0x030400a1
0,
#endif
#if PY_VERSION_HEX >= 0x030800b1
0,
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0,
#endif
};
static int __pyx_CyFunction_init(void) {
__pyx_CyFunctionType = __Pyx_FetchCommonType(&__pyx_CyFunctionType_type);
if (unlikely(__pyx_CyFunctionType == NULL)) {
return -1;
}
return 0;
}
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) {
__pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
m->defaults = PyObject_Malloc(size);
if (unlikely(!m->defaults))
return PyErr_NoMemory();
memset(m->defaults, 0, size);
m->defaults_pyobjects = pyobjects;
m->defaults_size = size;
return m->defaults;
}
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) {
__pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
m->defaults_tuple = tuple;
Py_INCREF(tuple);
}
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) {
__pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
m->defaults_kwdict = dict;
Py_INCREF(dict);
}
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) {
__pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
m->func_annotations = dict;
Py_INCREF(dict);
}
/* CythonFunction */
static PyObject *__Pyx_CyFunction_New(PyMethodDef *ml, int flags, PyObject* qualname,
PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) {
PyObject *op = __Pyx_CyFunction_Init(
PyObject_GC_New(__pyx_CyFunctionObject, __pyx_CyFunctionType),
ml, flags, qualname, closure, module, globals, code
);
if (likely(op)) {
PyObject_GC_Track(op);
}
return op;
}
/* PyObjectSetAttrStr */
#if CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) {
PyTypeObject* tp = Py_TYPE(obj);
if (likely(tp->tp_setattro))
return tp->tp_setattro(obj, attr_name, value);
#if PY_MAJOR_VERSION < 3
if (likely(tp->tp_setattr))
return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value);
#endif
return PyObject_SetAttr(obj, attr_name, value);
}
#endif
/* GetItemInt */
static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
PyObject *r;
if (!j) return NULL;
r = PyObject_GetItem(o, j);
Py_DECREF(j);
return r;
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
Py_ssize_t wrapped_i = i;
if (wraparound & unlikely(i < 0)) {
wrapped_i += PyList_GET_SIZE(o);
}
if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) {
PyObject *r = PyList_GET_ITEM(o, wrapped_i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
Py_ssize_t wrapped_i = i;
if (wraparound & unlikely(i < 0)) {
wrapped_i += PyTuple_GET_SIZE(o);
}
if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, wrapped_i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
if (is_list || PyList_CheckExact(o)) {
Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) {
PyObject *r = PyList_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
}
else if (PyTuple_CheckExact(o)) {
Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
} else {
PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
if (likely(m && m->sq_item)) {
if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
Py_ssize_t l = m->sq_length(o);
if (likely(l >= 0)) {
i += l;
} else {
if (!PyErr_ExceptionMatches(PyExc_OverflowError))
return NULL;
PyErr_Clear();
}
}
return m->sq_item(o, i);
}
}
#else
if (is_list || PySequence_Check(o)) {
return PySequence_GetItem(o, i);
}
#endif
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
}
/* ObjectGetItem */
#if CYTHON_USE_TYPE_SLOTS
static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) {
PyObject *runerr;
Py_ssize_t key_value;
PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence;
if (unlikely(!(m && m->sq_item))) {
PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name);
return NULL;
}
key_value = __Pyx_PyIndex_AsSsize_t(index);
if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) {
return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1);
}
if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) {
PyErr_Clear();
PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name);
}
return NULL;
}
static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) {
PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping;
if (likely(m && m->mp_subscript)) {
return m->mp_subscript(obj, key);
}
return __Pyx_PyObject_GetIndex(obj, key);
}
#endif
/* IterFinish */
static CYTHON_INLINE int __Pyx_IterFinish(void) {
#if CYTHON_FAST_THREAD_STATE
PyThreadState *tstate = __Pyx_PyThreadState_Current;
PyObject* exc_type = tstate->curexc_type;
if (unlikely(exc_type)) {
if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) {
PyObject *exc_value, *exc_tb;
exc_value = tstate->curexc_value;
exc_tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
Py_DECREF(exc_type);
Py_XDECREF(exc_value);
Py_XDECREF(exc_tb);
return 0;
} else {
return -1;
}
}
return 0;
#else
if (unlikely(PyErr_Occurred())) {
if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) {
PyErr_Clear();
return 0;
} else {
return -1;
}
}
return 0;
#endif
}
/* PyObjectGetMethod */
static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) {
PyObject *attr;
#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP
PyTypeObject *tp = Py_TYPE(obj);
PyObject *descr;
descrgetfunc f = NULL;
PyObject **dictptr, *dict;
int meth_found = 0;
assert (*method == NULL);
if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) {
attr = __Pyx_PyObject_GetAttrStr(obj, name);
goto try_unpack;
}
if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) {
return 0;
}
descr = _PyType_Lookup(tp, name);
if (likely(descr != NULL)) {
Py_INCREF(descr);
#if PY_MAJOR_VERSION >= 3
#ifdef __Pyx_CyFunction_USED
if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr)))
#else
if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type)))
#endif
#else
#ifdef __Pyx_CyFunction_USED
if (likely(PyFunction_Check(descr) || __Pyx_CyFunction_Check(descr)))
#else
if (likely(PyFunction_Check(descr)))
#endif
#endif
{
meth_found = 1;
} else {
f = Py_TYPE(descr)->tp_descr_get;
if (f != NULL && PyDescr_IsData(descr)) {
attr = f(descr, obj, (PyObject *)Py_TYPE(obj));
Py_DECREF(descr);
goto try_unpack;
}
}
}
dictptr = _PyObject_GetDictPtr(obj);
if (dictptr != NULL && (dict = *dictptr) != NULL) {
Py_INCREF(dict);
attr = __Pyx_PyDict_GetItemStr(dict, name);
if (attr != NULL) {
Py_INCREF(attr);
Py_DECREF(dict);
Py_XDECREF(descr);
goto try_unpack;
}
Py_DECREF(dict);
}
if (meth_found) {
*method = descr;
return 1;
}
if (f != NULL) {
attr = f(descr, obj, (PyObject *)Py_TYPE(obj));
Py_DECREF(descr);
goto try_unpack;
}
if (descr != NULL) {
*method = descr;
return 0;
}
PyErr_Format(PyExc_AttributeError,
#if PY_MAJOR_VERSION >= 3
"'%.50s' object has no attribute '%U'",
tp->tp_name, name);
#else
"'%.50s' object has no attribute '%.400s'",
tp->tp_name, PyString_AS_STRING(name));
#endif
return 0;
#else
attr = __Pyx_PyObject_GetAttrStr(obj, name);
goto try_unpack;
#endif
try_unpack:
#if CYTHON_UNPACK_METHODS
if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) {
PyObject *function = PyMethod_GET_FUNCTION(attr);
Py_INCREF(function);
Py_DECREF(attr);
*method = function;
return 1;
}
#endif
*method = attr;
return 0;
}
/* PyObjectCallMethod0 */
static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) {
PyObject *method = NULL, *result = NULL;
int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method);
if (likely(is_method)) {
result = __Pyx_PyObject_CallOneArg(method, obj);
Py_DECREF(method);
return result;
}
if (unlikely(!method)) goto bad;
result = __Pyx_PyObject_CallNoArg(method);
Py_DECREF(method);
bad:
return result;
}
/* RaiseNeedMoreValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
PyErr_Format(PyExc_ValueError,
"need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
index, (index == 1) ? "" : "s");
}
/* RaiseTooManyValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
PyErr_Format(PyExc_ValueError,
"too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}
/* UnpackItemEndCheck */
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) {
if (unlikely(retval)) {
Py_DECREF(retval);
__Pyx_RaiseTooManyValuesError(expected);
return -1;
} else {
return __Pyx_IterFinish();
}
return 0;
}
/* RaiseNoneIterError */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}
/* UnpackTupleError */
static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) {
if (t == Py_None) {
__Pyx_RaiseNoneNotIterableError();
} else if (PyTuple_GET_SIZE(t) < index) {
__Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t));
} else {
__Pyx_RaiseTooManyValuesError(index);
}
}
/* UnpackTuple2 */
static CYTHON_INLINE int __Pyx_unpack_tuple2_exact(
PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int decref_tuple) {
PyObject *value1 = NULL, *value2 = NULL;
#if CYTHON_COMPILING_IN_PYPY
value1 = PySequence_ITEM(tuple, 0); if (unlikely(!value1)) goto bad;
value2 = PySequence_ITEM(tuple, 1); if (unlikely(!value2)) goto bad;
#else
value1 = PyTuple_GET_ITEM(tuple, 0); Py_INCREF(value1);
value2 = PyTuple_GET_ITEM(tuple, 1); Py_INCREF(value2);
#endif
if (decref_tuple) {
Py_DECREF(tuple);
}
*pvalue1 = value1;
*pvalue2 = value2;
return 0;
#if CYTHON_COMPILING_IN_PYPY
bad:
Py_XDECREF(value1);
Py_XDECREF(value2);
if (decref_tuple) { Py_XDECREF(tuple); }
return -1;
#endif
}
static int __Pyx_unpack_tuple2_generic(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2,
int has_known_size, int decref_tuple) {
Py_ssize_t index;
PyObject *value1 = NULL, *value2 = NULL, *iter = NULL;
iternextfunc iternext;
iter = PyObject_GetIter(tuple);
if (unlikely(!iter)) goto bad;
if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; }
iternext = Py_TYPE(iter)->tp_iternext;
value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; }
value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; }
if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad;
Py_DECREF(iter);
*pvalue1 = value1;
*pvalue2 = value2;
return 0;
unpacking_failed:
if (!has_known_size && __Pyx_IterFinish() == 0)
__Pyx_RaiseNeedMoreValuesError(index);
bad:
Py_XDECREF(iter);
Py_XDECREF(value1);
Py_XDECREF(value2);
if (decref_tuple) { Py_XDECREF(tuple); }
return -1;
}
/* dict_iter */
static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name,
Py_ssize_t* p_orig_length, int* p_source_is_dict) {
is_dict = is_dict || likely(PyDict_CheckExact(iterable));
*p_source_is_dict = is_dict;
if (is_dict) {
#if !CYTHON_COMPILING_IN_PYPY
*p_orig_length = PyDict_Size(iterable);
Py_INCREF(iterable);
return iterable;
#elif PY_MAJOR_VERSION >= 3
static PyObject *py_items = NULL, *py_keys = NULL, *py_values = NULL;
PyObject **pp = NULL;
if (method_name) {
const char *name = PyUnicode_AsUTF8(method_name);
if (strcmp(name, "iteritems") == 0) pp = &py_items;
else if (strcmp(name, "iterkeys") == 0) pp = &py_keys;
else if (strcmp(name, "itervalues") == 0) pp = &py_values;
if (pp) {
if (!*pp) {
*pp = PyUnicode_FromString(name + 4);
if (!*pp)
return NULL;
}
method_name = *pp;
}
}
#endif
}
*p_orig_length = 0;
if (method_name) {
PyObject* iter;
iterable = __Pyx_PyObject_CallMethod0(iterable, method_name);
if (!iterable)
return NULL;
#if !CYTHON_COMPILING_IN_PYPY
if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable))
return iterable;
#endif
iter = PyObject_GetIter(iterable);
Py_DECREF(iterable);
return iter;
}
return PyObject_GetIter(iterable);
}
static CYTHON_INLINE int __Pyx_dict_iter_next(
PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos,
PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) {
PyObject* next_item;
#if !CYTHON_COMPILING_IN_PYPY
if (source_is_dict) {
PyObject *key, *value;
if (unlikely(orig_length != PyDict_Size(iter_obj))) {
PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration");
return -1;
}
if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) {
return 0;
}
if (pitem) {
PyObject* tuple = PyTuple_New(2);
if (unlikely(!tuple)) {
return -1;
}
Py_INCREF(key);
Py_INCREF(value);
PyTuple_SET_ITEM(tuple, 0, key);
PyTuple_SET_ITEM(tuple, 1, value);
*pitem = tuple;
} else {
if (pkey) {
Py_INCREF(key);
*pkey = key;
}
if (pvalue) {
Py_INCREF(value);
*pvalue = value;
}
}
return 1;
} else if (PyTuple_CheckExact(iter_obj)) {
Py_ssize_t pos = *ppos;
if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0;
*ppos = pos + 1;
next_item = PyTuple_GET_ITEM(iter_obj, pos);
Py_INCREF(next_item);
} else if (PyList_CheckExact(iter_obj)) {
Py_ssize_t pos = *ppos;
if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0;
*ppos = pos + 1;
next_item = PyList_GET_ITEM(iter_obj, pos);
Py_INCREF(next_item);
} else
#endif
{
next_item = PyIter_Next(iter_obj);
if (unlikely(!next_item)) {
return __Pyx_IterFinish();
}
}
if (pitem) {
*pitem = next_item;
} else if (pkey && pvalue) {
if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1))
return -1;
} else if (pkey) {
*pkey = next_item;
} else {
*pvalue = next_item;
}
return 1;
}
/* IterNext */
static PyObject *__Pyx_PyIter_Next2Default(PyObject* defval) {
PyObject* exc_type;
__Pyx_PyThreadState_declare
__Pyx_PyThreadState_assign
exc_type = __Pyx_PyErr_Occurred();
if (unlikely(exc_type)) {
if (!defval || unlikely(!__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)))
return NULL;
__Pyx_PyErr_Clear();
Py_INCREF(defval);
return defval;
}
if (defval) {
Py_INCREF(defval);
return defval;
}
__Pyx_PyErr_SetNone(PyExc_StopIteration);
return NULL;
}
static void __Pyx_PyIter_Next_ErrorNoIterator(PyObject *iterator) {
PyErr_Format(PyExc_TypeError,
"%.200s object is not an iterator", Py_TYPE(iterator)->tp_name);
}
static CYTHON_INLINE PyObject *__Pyx_PyIter_Next2(PyObject* iterator, PyObject* defval) {
PyObject* next;
iternextfunc iternext = Py_TYPE(iterator)->tp_iternext;
if (likely(iternext)) {
#if CYTHON_USE_TYPE_SLOTS
next = iternext(iterator);
if (likely(next))
return next;
#if PY_VERSION_HEX >= 0x02070000
if (unlikely(iternext == &_PyObject_NextNotImplemented))
return NULL;
#endif
#else
next = PyIter_Next(iterator);
if (likely(next))
return next;
#endif
} else if (CYTHON_USE_TYPE_SLOTS || unlikely(!PyIter_Check(iterator))) {
__Pyx_PyIter_Next_ErrorNoIterator(iterator);
return NULL;
}
#if !CYTHON_USE_TYPE_SLOTS
else {
next = PyIter_Next(iterator);
if (likely(next))
return next;
}
#endif
return __Pyx_PyIter_Next2Default(defval);
}
/* py_abs */
#if CYTHON_USE_PYLONG_INTERNALS
static PyObject *__Pyx_PyLong_AbsNeg(PyObject *n) {
if (likely(Py_SIZE(n) == -1)) {
return PyLong_FromLong(((PyLongObject*)n)->ob_digit[0]);
}
#if CYTHON_COMPILING_IN_CPYTHON
{
PyObject *copy = _PyLong_Copy((PyLongObject*)n);
if (likely(copy)) {
__Pyx_SET_SIZE(copy, -Py_SIZE(copy));
}
return copy;
}
#else
return PyNumber_Negative(n);
#endif
}
#endif
/* UnpackUnboundCMethod */
static int __Pyx_TryUnpackUnboundCMethod(__Pyx_CachedCFunction* target) {
PyObject *method;
method = __Pyx_PyObject_GetAttrStr(target->type, *target->method_name);
if (unlikely(!method))
return -1;
target->method = method;
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_MAJOR_VERSION >= 3
if (likely(__Pyx_TypeCheck(method, &PyMethodDescr_Type)))
#endif
{
PyMethodDescrObject *descr = (PyMethodDescrObject*) method;
target->func = descr->d_method->ml_meth;
target->flag = descr->d_method->ml_flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_STACKLESS);
}
#endif
return 0;
}
/* CallUnboundCMethod1 */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_CallUnboundCMethod1(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg) {
if (likely(cfunc->func)) {
int flag = cfunc->flag;
if (flag == METH_O) {
return (*(cfunc->func))(self, arg);
} else if (PY_VERSION_HEX >= 0x030600B1 && flag == METH_FASTCALL) {
if (PY_VERSION_HEX >= 0x030700A0) {
return (*(__Pyx_PyCFunctionFast)(void*)(PyCFunction)cfunc->func)(self, &arg, 1);
} else {
return (*(__Pyx_PyCFunctionFastWithKeywords)(void*)(PyCFunction)cfunc->func)(self, &arg, 1, NULL);
}
} else if (PY_VERSION_HEX >= 0x030700A0 && flag == (METH_FASTCALL | METH_KEYWORDS)) {
return (*(__Pyx_PyCFunctionFastWithKeywords)(void*)(PyCFunction)cfunc->func)(self, &arg, 1, NULL);
}
}
return __Pyx__CallUnboundCMethod1(cfunc, self, arg);
}
#endif
static PyObject* __Pyx__CallUnboundCMethod1(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg){
PyObject *args, *result = NULL;
if (unlikely(!cfunc->func && !cfunc->method) && unlikely(__Pyx_TryUnpackUnboundCMethod(cfunc) < 0)) return NULL;
#if CYTHON_COMPILING_IN_CPYTHON
if (cfunc->func && (cfunc->flag & METH_VARARGS)) {
args = PyTuple_New(1);
if (unlikely(!args)) goto bad;
Py_INCREF(arg);
PyTuple_SET_ITEM(args, 0, arg);
if (cfunc->flag & METH_KEYWORDS)
result = (*(PyCFunctionWithKeywords)(void*)(PyCFunction)cfunc->func)(self, args, NULL);
else
result = (*cfunc->func)(self, args);
} else {
args = PyTuple_New(2);
if (unlikely(!args)) goto bad;
Py_INCREF(self);
PyTuple_SET_ITEM(args, 0, self);
Py_INCREF(arg);
PyTuple_SET_ITEM(args, 1, arg);
result = __Pyx_PyObject_Call(cfunc->method, args, NULL);
}
#else
args = PyTuple_Pack(2, self, arg);
if (unlikely(!args)) goto bad;
result = __Pyx_PyObject_Call(cfunc->method, args, NULL);
#endif
bad:
Py_XDECREF(args);
return result;
}
/* CallUnboundCMethod2 */
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030600B1
static CYTHON_INLINE PyObject *__Pyx_CallUnboundCMethod2(__Pyx_CachedCFunction *cfunc, PyObject *self, PyObject *arg1, PyObject *arg2) {
if (likely(cfunc->func)) {
PyObject *args[2] = {arg1, arg2};
if (cfunc->flag == METH_FASTCALL) {
#if PY_VERSION_HEX >= 0x030700A0
return (*(__Pyx_PyCFunctionFast)(void*)(PyCFunction)cfunc->func)(self, args, 2);
#else
return (*(__Pyx_PyCFunctionFastWithKeywords)(void*)(PyCFunction)cfunc->func)(self, args, 2, NULL);
#endif
}
#if PY_VERSION_HEX >= 0x030700A0
if (cfunc->flag == (METH_FASTCALL | METH_KEYWORDS))
return (*(__Pyx_PyCFunctionFastWithKeywords)(void*)(PyCFunction)cfunc->func)(self, args, 2, NULL);
#endif
}
return __Pyx__CallUnboundCMethod2(cfunc, self, arg1, arg2);
}
#endif
static PyObject* __Pyx__CallUnboundCMethod2(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg1, PyObject* arg2){
PyObject *args, *result = NULL;
if (unlikely(!cfunc->func && !cfunc->method) && unlikely(__Pyx_TryUnpackUnboundCMethod(cfunc) < 0)) return NULL;
#if CYTHON_COMPILING_IN_CPYTHON
if (cfunc->func && (cfunc->flag & METH_VARARGS)) {
args = PyTuple_New(2);
if (unlikely(!args)) goto bad;
Py_INCREF(arg1);
PyTuple_SET_ITEM(args, 0, arg1);
Py_INCREF(arg2);
PyTuple_SET_ITEM(args, 1, arg2);
if (cfunc->flag & METH_KEYWORDS)
result = (*(PyCFunctionWithKeywords)(void*)(PyCFunction)cfunc->func)(self, args, NULL);
else
result = (*cfunc->func)(self, args);
} else {
args = PyTuple_New(3);
if (unlikely(!args)) goto bad;
Py_INCREF(self);
PyTuple_SET_ITEM(args, 0, self);
Py_INCREF(arg1);
PyTuple_SET_ITEM(args, 1, arg1);
Py_INCREF(arg2);
PyTuple_SET_ITEM(args, 2, arg2);
result = __Pyx_PyObject_Call(cfunc->method, args, NULL);
}
#else
args = PyTuple_Pack(3, self, arg1, arg2);
if (unlikely(!args)) goto bad;
result = __Pyx_PyObject_Call(cfunc->method, args, NULL);
#endif
bad:
Py_XDECREF(args);
return result;
}
/* dict_getitem_default */
static PyObject* __Pyx_PyDict_GetItemDefault(PyObject* d, PyObject* key, PyObject* default_value) {
PyObject* value;
#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY
value = PyDict_GetItemWithError(d, key);
if (unlikely(!value)) {
if (unlikely(PyErr_Occurred()))
return NULL;
value = default_value;
}
Py_INCREF(value);
if ((1));
#else
if (PyString_CheckExact(key) || PyUnicode_CheckExact(key) || PyInt_CheckExact(key)) {
value = PyDict_GetItem(d, key);
if (unlikely(!value)) {
value = default_value;
}
Py_INCREF(value);
}
#endif
else {
if (default_value == Py_None)
value = __Pyx_CallUnboundCMethod1(&__pyx_umethod_PyDict_Type_get, d, key);
else
value = __Pyx_CallUnboundCMethod2(&__pyx_umethod_PyDict_Type_get, d, key, default_value);
}
return value;
}
/* PyFloatBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_NeObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) {
const double b = floatval;
double a;
(void)inplace;
(void)zerodivision_check;
if (op1 == op2) {
Py_RETURN_FALSE;
}
if (likely(PyFloat_CheckExact(op1))) {
a = PyFloat_AS_DOUBLE(op1);
} else
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
a = (double) PyInt_AS_LONG(op1);
} else
#endif
if (likely(PyLong_CheckExact(op1))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
switch (size) {
case 0: a = 0.0; break;
case -1: a = -(double) digits[0]; break;
case 1: a = (double) digits[0]; break;
case -2:
case 2:
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) {
a = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -2)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -3:
case 3:
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) {
a = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -3)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -4:
case 4:
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) {
a = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -4)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
default:
#else
{
#endif
return (
PyFloat_Type.tp_richcompare(op2, op1, Py_NE));
}
} else {
return (
PyObject_RichCompare(op1, op2, Py_NE));
}
if (a != b) {
Py_RETURN_TRUE;
} else {
Py_RETURN_FALSE;
}
}
#endif
/* GetAttr */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
#if CYTHON_USE_TYPE_SLOTS
#if PY_MAJOR_VERSION >= 3
if (likely(PyUnicode_Check(n)))
#else
if (likely(PyString_Check(n)))
#endif
return __Pyx_PyObject_GetAttrStr(o, n);
#endif
return PyObject_GetAttr(o, n);
}
/* GetAttr3 */
static PyObject *__Pyx_GetAttr3Default(PyObject *d) {
__Pyx_PyThreadState_declare
__Pyx_PyThreadState_assign
if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
return NULL;
__Pyx_PyErr_Clear();
Py_INCREF(d);
return d;
}
static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) {
PyObject *r = __Pyx_GetAttr(o, n);
return (likely(r)) ? r : __Pyx_GetAttr3Default(d);
}
/* PyObjectFormatAndDecref */
static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatSimpleAndDecref(PyObject* s, PyObject* f) {
if (unlikely(!s)) return NULL;
if (likely(PyUnicode_CheckExact(s))) return s;
#if PY_MAJOR_VERSION < 3
if (likely(PyString_CheckExact(s))) {
PyObject *result = PyUnicode_FromEncodedObject(s, NULL, "strict");
Py_DECREF(s);
return result;
}
#endif
return __Pyx_PyObject_FormatAndDecref(s, f);
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatAndDecref(PyObject* s, PyObject* f) {
PyObject *result = PyObject_Format(s, f);
Py_DECREF(s);
return result;
}
/* JoinPyUnicode */
static PyObject* __Pyx_PyUnicode_Join(PyObject* value_tuple, Py_ssize_t value_count, Py_ssize_t result_ulength,
CYTHON_UNUSED Py_UCS4 max_char) {
#if CYTHON_USE_UNICODE_INTERNALS && CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
PyObject *result_uval;
int result_ukind;
Py_ssize_t i, char_pos;
void *result_udata;
#if CYTHON_PEP393_ENABLED
result_uval = PyUnicode_New(result_ulength, max_char);
if (unlikely(!result_uval)) return NULL;
result_ukind = (max_char <= 255) ? PyUnicode_1BYTE_KIND : (max_char <= 65535) ? PyUnicode_2BYTE_KIND : PyUnicode_4BYTE_KIND;
result_udata = PyUnicode_DATA(result_uval);
#else
result_uval = PyUnicode_FromUnicode(NULL, result_ulength);
if (unlikely(!result_uval)) return NULL;
result_ukind = sizeof(Py_UNICODE);
result_udata = PyUnicode_AS_UNICODE(result_uval);
#endif
char_pos = 0;
for (i=0; i < value_count; i++) {
int ukind;
Py_ssize_t ulength;
void *udata;
PyObject *uval = PyTuple_GET_ITEM(value_tuple, i);
if (unlikely(__Pyx_PyUnicode_READY(uval)))
goto bad;
ulength = __Pyx_PyUnicode_GET_LENGTH(uval);
if (unlikely(!ulength))
continue;
if (unlikely(char_pos + ulength < 0))
goto overflow;
ukind = __Pyx_PyUnicode_KIND(uval);
udata = __Pyx_PyUnicode_DATA(uval);
if (!CYTHON_PEP393_ENABLED || ukind == result_ukind) {
memcpy((char *)result_udata + char_pos * result_ukind, udata, (size_t) (ulength * result_ukind));
} else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030300F0 || defined(_PyUnicode_FastCopyCharacters)
_PyUnicode_FastCopyCharacters(result_uval, char_pos, uval, 0, ulength);
#else
Py_ssize_t j;
for (j=0; j < ulength; j++) {
Py_UCS4 uchar = __Pyx_PyUnicode_READ(ukind, udata, j);
__Pyx_PyUnicode_WRITE(result_ukind, result_udata, char_pos+j, uchar);
}
#endif
}
char_pos += ulength;
}
return result_uval;
overflow:
PyErr_SetString(PyExc_OverflowError, "join() result is too long for a Python string");
bad:
Py_DECREF(result_uval);
return NULL;
#else
result_ulength++;
value_count++;
return PyUnicode_Join(__pyx_empty_unicode, value_tuple);
#endif
}
/* KeywordStringCheck */
static int __Pyx_CheckKeywordStrings(
PyObject *kwdict,
const char* function_name,
int kw_allowed)
{
PyObject* key = 0;
Py_ssize_t pos = 0;
#if CYTHON_COMPILING_IN_PYPY
if (!kw_allowed && PyDict_Next(kwdict, &pos, &key, 0))
goto invalid_keyword;
return 1;
#else
while (PyDict_Next(kwdict, &pos, &key, 0)) {
#if PY_MAJOR_VERSION < 3
if (unlikely(!PyString_Check(key)))
#endif
if (unlikely(!PyUnicode_Check(key)))
goto invalid_keyword_type;
}
if ((!kw_allowed) && unlikely(key))
goto invalid_keyword;
return 1;
invalid_keyword_type:
PyErr_Format(PyExc_TypeError,
"%.200s() keywords must be strings", function_name);
return 0;
#endif
invalid_keyword:
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION < 3
"%.200s() got an unexpected keyword argument '%.200s'",
function_name, PyString_AsString(key));
#else
"%s() got an unexpected keyword argument '%U'",
function_name, key);
#endif
return 0;
}
/* PyObjectCallMethod1 */
static PyObject* __Pyx__PyObject_CallMethod1(PyObject* method, PyObject* arg) {
PyObject *result = __Pyx_PyObject_CallOneArg(method, arg);
Py_DECREF(method);
return result;
}
static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) {
PyObject *method = NULL, *result;
int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method);
if (likely(is_method)) {
result = __Pyx_PyObject_Call2Args(method, obj, arg);
Py_DECREF(method);
return result;
}
if (unlikely(!method)) return NULL;
return __Pyx__PyObject_CallMethod1(method, arg);
}
/* append */
static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x) {
if (likely(PyList_CheckExact(L))) {
if (unlikely(__Pyx_PyList_Append(L, x) < 0)) return -1;
} else {
PyObject* retval = __Pyx_PyObject_CallMethod1(L, __pyx_n_s_append, x);
if (unlikely(!retval))
return -1;
Py_DECREF(retval);
}
return 0;
}
/* BytesEquals */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
if (s1 == s2) {
return (equals == Py_EQ);
} else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
const char *ps1, *ps2;
Py_ssize_t length = PyBytes_GET_SIZE(s1);
if (length != PyBytes_GET_SIZE(s2))
return (equals == Py_NE);
ps1 = PyBytes_AS_STRING(s1);
ps2 = PyBytes_AS_STRING(s2);
if (ps1[0] != ps2[0]) {
return (equals == Py_NE);
} else if (length == 1) {
return (equals == Py_EQ);
} else {
int result;
#if CYTHON_USE_UNICODE_INTERNALS
Py_hash_t hash1, hash2;
hash1 = ((PyBytesObject*)s1)->ob_shash;
hash2 = ((PyBytesObject*)s2)->ob_shash;
if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
return (equals == Py_NE);
}
#endif
result = memcmp(ps1, ps2, (size_t)length);
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
return (equals == Py_NE);
} else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
return (equals == Py_NE);
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
#endif
}
/* UnicodeEquals */
static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
#if PY_MAJOR_VERSION < 3
PyObject* owned_ref = NULL;
#endif
int s1_is_unicode, s2_is_unicode;
if (s1 == s2) {
goto return_eq;
}
s1_is_unicode = PyUnicode_CheckExact(s1);
s2_is_unicode = PyUnicode_CheckExact(s2);
#if PY_MAJOR_VERSION < 3
if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
owned_ref = PyUnicode_FromObject(s2);
if (unlikely(!owned_ref))
return -1;
s2 = owned_ref;
s2_is_unicode = 1;
} else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
owned_ref = PyUnicode_FromObject(s1);
if (unlikely(!owned_ref))
return -1;
s1 = owned_ref;
s1_is_unicode = 1;
} else if (((!s2_is_unicode) & (!s1_is_unicode))) {
return __Pyx_PyBytes_Equals(s1, s2, equals);
}
#endif
if (s1_is_unicode & s2_is_unicode) {
Py_ssize_t length;
int kind;
void *data1, *data2;
if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
return -1;
length = __Pyx_PyUnicode_GET_LENGTH(s1);
if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
goto return_ne;
}
#if CYTHON_USE_UNICODE_INTERNALS
{
Py_hash_t hash1, hash2;
#if CYTHON_PEP393_ENABLED
hash1 = ((PyASCIIObject*)s1)->hash;
hash2 = ((PyASCIIObject*)s2)->hash;
#else
hash1 = ((PyUnicodeObject*)s1)->hash;
hash2 = ((PyUnicodeObject*)s2)->hash;
#endif
if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
goto return_ne;
}
}
#endif
kind = __Pyx_PyUnicode_KIND(s1);
if (kind != __Pyx_PyUnicode_KIND(s2)) {
goto return_ne;
}
data1 = __Pyx_PyUnicode_DATA(s1);
data2 = __Pyx_PyUnicode_DATA(s2);
if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
goto return_ne;
} else if (length == 1) {
goto return_eq;
} else {
int result = memcmp(data1, data2, (size_t)(length * kind));
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & s2_is_unicode) {
goto return_ne;
} else if ((s2 == Py_None) & s1_is_unicode) {
goto return_ne;
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
return_eq:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ);
return_ne:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_NE);
#endif
}
/* WriteUnraisableException */
static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
int full_traceback, CYTHON_UNUSED int nogil) {
PyObject *old_exc, *old_val, *old_tb;
PyObject *ctx;
__Pyx_PyThreadState_declare
#ifdef WITH_THREAD
PyGILState_STATE state;
if (nogil)
state = PyGILState_Ensure();
#ifdef _MSC_VER
else state = (PyGILState_STATE)-1;
#endif
#endif
__Pyx_PyThreadState_assign
__Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
if (full_traceback) {
Py_XINCREF(old_exc);
Py_XINCREF(old_val);
Py_XINCREF(old_tb);
__Pyx_ErrRestore(old_exc, old_val, old_tb);
PyErr_PrintEx(1);
}
#if PY_MAJOR_VERSION < 3
ctx = PyString_FromString(name);
#else
ctx = PyUnicode_FromString(name);
#endif
__Pyx_ErrRestore(old_exc, old_val, old_tb);
if (!ctx) {
PyErr_WriteUnraisable(Py_None);
} else {
PyErr_WriteUnraisable(ctx);
Py_DECREF(ctx);
}
#ifdef WITH_THREAD
if (nogil)
PyGILState_Release(state);
#endif
}
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) {
(void)inplace;
(void)zerodivision_check;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long x;
long a = PyInt_AS_LONG(op1);
x = (long)((unsigned long)a + b);
if (likely((x^a) >= 0 || (x^b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG llb = intval;
PY_LONG_LONG lla, llx;
#endif
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
}
x = a + b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla + llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
double result;
PyFPE_START_PROTECT("add", return NULL)
result = ((double)a) + (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
}
#endif
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) {
(void)inplace;
(void)zerodivision_check;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long x;
long a = PyInt_AS_LONG(op1);
x = (long)((unsigned long)a - b);
if (likely((x^a) >= 0 || (x^~b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG llb = intval;
PY_LONG_LONG lla, llx;
#endif
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
default: return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
}
x = a - b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla - llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
double result;
PyFPE_START_PROTECT("subtract", return NULL)
result = ((double)a) - (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceSubtract : PyNumber_Subtract)(op1, op2);
}
#endif
/* ExtTypeTest */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
if (likely(__Pyx_TypeCheck(obj, type)))
return 1;
PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
Py_TYPE(obj)->tp_name, type->tp_name);
return 0;
}
/* DictGetItem */
#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY
static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) {
PyObject *value;
value = PyDict_GetItemWithError(d, key);
if (unlikely(!value)) {
if (!PyErr_Occurred()) {
if (unlikely(PyTuple_Check(key))) {
PyObject* args = PyTuple_Pack(1, key);
if (likely(args)) {
PyErr_SetObject(PyExc_KeyError, args);
Py_DECREF(args);
}
} else {
PyErr_SetObject(PyExc_KeyError, key);
}
}
return NULL;
}
Py_INCREF(value);
return value;
}
#endif
/* decode_c_bytes */
static CYTHON_INLINE PyObject* __Pyx_decode_c_bytes(
const char* cstring, Py_ssize_t length, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
if (unlikely((start < 0) | (stop < 0))) {
if (start < 0) {
start += length;
if (start < 0)
start = 0;
}
if (stop < 0)
stop += length;
}
if (stop > length)
stop = length;
if (unlikely(stop <= start))
return __Pyx_NewRef(__pyx_empty_unicode);
length = stop - start;
cstring += start;
if (decode_func) {
return decode_func(cstring, length, errors);
} else {
return PyUnicode_Decode(cstring, length, encoding, errors);
}
}
/* decode_c_string */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
Py_ssize_t length;
if (unlikely((start < 0) | (stop < 0))) {
size_t slen = strlen(cstring);
if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) {
PyErr_SetString(PyExc_OverflowError,
"c-string too long to convert to Python");
return NULL;
}
length = (Py_ssize_t) slen;
if (start < 0) {
start += length;
if (start < 0)
start = 0;
}
if (stop < 0)
stop += length;
}
if (unlikely(stop <= start))
return __Pyx_NewRef(__pyx_empty_unicode);
length = stop - start;
cstring += start;
if (decode_func) {
return decode_func(cstring, length, errors);
} else {
return PyUnicode_Decode(cstring, length, encoding, errors);
}
}
/* ArgTypeTest */
static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact)
{
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
else if (exact) {
#if PY_MAJOR_VERSION == 2
if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
#endif
}
else {
if (likely(__Pyx_TypeCheck(obj, type))) return 1;
}
PyErr_Format(PyExc_TypeError,
"Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
name, type->tp_name, Py_TYPE(obj)->tp_name);
return 0;
}
/* PyFloatBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyFloat_TrueDivideObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) {
const double b = floatval;
double a, result;
(void)inplace;
(void)zerodivision_check;
if (likely(PyFloat_CheckExact(op1))) {
a = PyFloat_AS_DOUBLE(op1);
} else
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
a = (double) PyInt_AS_LONG(op1);
} else
#endif
if (likely(PyLong_CheckExact(op1))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
switch (size) {
case 0: a = 0.0; break;
case -1: a = -(double) digits[0]; break;
case 1: a = (double) digits[0]; break;
case -2:
case 2:
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) {
a = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -2)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -3:
case 3:
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) {
a = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -3)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
case -4:
case 4:
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) {
a = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) {
if (size == -4)
a = -a;
break;
}
}
CYTHON_FALLTHROUGH;
default:
#else
{
#endif
a = PyLong_AsDouble(op1);
if (unlikely(a == -1.0 && PyErr_Occurred())) return NULL;
}
} else {
return (inplace ? PyNumber_InPlaceTrueDivide : PyNumber_TrueDivide)(op1, op2);
}
PyFPE_START_PROTECT("divide", return NULL)
result = a / b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
#endif
/* PyIntCompare */
static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) {
if (op1 == op2) {
Py_RETURN_FALSE;
}
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long a = PyInt_AS_LONG(op1);
if (a != b) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
int unequal;
unsigned long uintval;
Py_ssize_t size = Py_SIZE(op1);
const digit* digits = ((PyLongObject*)op1)->ob_digit;
if (intval == 0) {
if (size != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE;
} else if (intval < 0) {
if (size >= 0)
Py_RETURN_TRUE;
intval = -intval;
size = -size;
} else {
if (size <= 0)
Py_RETURN_TRUE;
}
uintval = (unsigned long) intval;
#if PyLong_SHIFT * 4 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 4)) {
unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 3 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 3)) {
unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 2 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 2)) {
unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
#if PyLong_SHIFT * 1 < SIZEOF_LONG*8
if (uintval >> (PyLong_SHIFT * 1)) {
unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK))
| (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK));
} else
#endif
unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK));
if (unequal != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
if ((double)a != (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE;
}
return (
PyObject_RichCompare(op1, op2, Py_NE));
}
/* SliceObject */
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj,
Py_ssize_t cstart, Py_ssize_t cstop,
PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice,
int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) {
#if CYTHON_USE_TYPE_SLOTS
PyMappingMethods* mp;
#if PY_MAJOR_VERSION < 3
PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence;
if (likely(ms && ms->sq_slice)) {
if (!has_cstart) {
if (_py_start && (*_py_start != Py_None)) {
cstart = __Pyx_PyIndex_AsSsize_t(*_py_start);
if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
} else
cstart = 0;
}
if (!has_cstop) {
if (_py_stop && (*_py_stop != Py_None)) {
cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop);
if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
} else
cstop = PY_SSIZE_T_MAX;
}
if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) {
Py_ssize_t l = ms->sq_length(obj);
if (likely(l >= 0)) {
if (cstop < 0) {
cstop += l;
if (cstop < 0) cstop = 0;
}
if (cstart < 0) {
cstart += l;
if (cstart < 0) cstart = 0;
}
} else {
if (!PyErr_ExceptionMatches(PyExc_OverflowError))
goto bad;
PyErr_Clear();
}
}
return ms->sq_slice(obj, cstart, cstop);
}
#endif
mp = Py_TYPE(obj)->tp_as_mapping;
if (likely(mp && mp->mp_subscript))
#endif
{
PyObject* result;
PyObject *py_slice, *py_start, *py_stop;
if (_py_slice) {
py_slice = *_py_slice;
} else {
PyObject* owned_start = NULL;
PyObject* owned_stop = NULL;
if (_py_start) {
py_start = *_py_start;
} else {
if (has_cstart) {
owned_start = py_start = PyInt_FromSsize_t(cstart);
if (unlikely(!py_start)) goto bad;
} else
py_start = Py_None;
}
if (_py_stop) {
py_stop = *_py_stop;
} else {
if (has_cstop) {
owned_stop = py_stop = PyInt_FromSsize_t(cstop);
if (unlikely(!py_stop)) {
Py_XDECREF(owned_start);
goto bad;
}
} else
py_stop = Py_None;
}
py_slice = PySlice_New(py_start, py_stop, Py_None);
Py_XDECREF(owned_start);
Py_XDECREF(owned_stop);
if (unlikely(!py_slice)) goto bad;
}
#if CYTHON_USE_TYPE_SLOTS
result = mp->mp_subscript(obj, py_slice);
#else
result = PyObject_GetItem(obj, py_slice);
#endif
if (!_py_slice) {
Py_DECREF(py_slice);
}
return result;
}
PyErr_Format(PyExc_TypeError,
"'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name);
bad:
return NULL;
}
/* UnicodeAsUCS4 */
static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject* x) {
Py_ssize_t length;
#if CYTHON_PEP393_ENABLED
length = PyUnicode_GET_LENGTH(x);
if (likely(length == 1)) {
return PyUnicode_READ_CHAR(x, 0);
}
#else
length = PyUnicode_GET_SIZE(x);
if (likely(length == 1)) {
return PyUnicode_AS_UNICODE(x)[0];
}
#if Py_UNICODE_SIZE == 2
else if (PyUnicode_GET_SIZE(x) == 2) {
Py_UCS4 high_val = PyUnicode_AS_UNICODE(x)[0];
if (high_val >= 0xD800 && high_val <= 0xDBFF) {
Py_UCS4 low_val = PyUnicode_AS_UNICODE(x)[1];
if (low_val >= 0xDC00 && low_val <= 0xDFFF) {
return 0x10000 + (((high_val & ((1<<10)-1)) << 10) | (low_val & ((1<<10)-1)));
}
}
}
#endif
#endif
PyErr_Format(PyExc_ValueError,
"only single character unicode strings can be converted to Py_UCS4, "
"got length %" CYTHON_FORMAT_SSIZE_T "d", length);
return (Py_UCS4)-1;
}
/* object_ord */
static long __Pyx__PyObject_Ord(PyObject* c) {
Py_ssize_t size;
if (PyBytes_Check(c)) {
size = PyBytes_GET_SIZE(c);
if (likely(size == 1)) {
return (unsigned char) PyBytes_AS_STRING(c)[0];
}
#if PY_MAJOR_VERSION < 3
} else if (PyUnicode_Check(c)) {
return (long)__Pyx_PyUnicode_AsPy_UCS4(c);
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
} else if (PyByteArray_Check(c)) {
size = PyByteArray_GET_SIZE(c);
if (likely(size == 1)) {
return (unsigned char) PyByteArray_AS_STRING(c)[0];
}
#endif
} else {
PyErr_Format(PyExc_TypeError,
"ord() expected string of length 1, but %.200s found", Py_TYPE(c)->tp_name);
return (long)(Py_UCS4)-1;
}
PyErr_Format(PyExc_TypeError,
"ord() expected a character, but string of length %zd found", size);
return (long)(Py_UCS4)-1;
}
/* IsLittleEndian */
static CYTHON_INLINE int __Pyx_Is_Little_Endian(void)
{
union {
uint32_t u32;
uint8_t u8[4];
} S;
S.u32 = 0x01020304;
return S.u8[0] == 4;
}
/* BufferFormatCheck */
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type) {
stack[0].field = &ctx->root;
stack[0].parent_offset = 0;
ctx->root.type = type;
ctx->root.name = "buffer dtype";
ctx->root.offset = 0;
ctx->head = stack;
ctx->head->field = &ctx->root;
ctx->fmt_offset = 0;
ctx->head->parent_offset = 0;
ctx->new_packmode = '@';
ctx->enc_packmode = '@';
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->is_complex = 0;
ctx->is_valid_array = 0;
ctx->struct_alignment = 0;
while (type->typegroup == 'S') {
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = 0;
type = type->fields->type;
}
}
static int __Pyx_BufFmt_ParseNumber(const char** ts) {
int count;
const char* t = *ts;
if (*t < '0' || *t > '9') {
return -1;
} else {
count = *t++ - '0';
while (*t >= '0' && *t <= '9') {
count *= 10;
count += *t++ - '0';
}
}
*ts = t;
return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
int number = __Pyx_BufFmt_ParseNumber(ts);
if (number == -1)
PyErr_Format(PyExc_ValueError,\
"Does not understand character buffer dtype format string ('%c')", **ts);
return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
PyErr_Format(PyExc_ValueError,
"Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
switch (ch) {
case '?': return "'bool'";
case 'c': return "'char'";
case 'b': return "'signed char'";
case 'B': return "'unsigned char'";
case 'h': return "'short'";
case 'H': return "'unsigned short'";
case 'i': return "'int'";
case 'I': return "'unsigned int'";
case 'l': return "'long'";
case 'L': return "'unsigned long'";
case 'q': return "'long long'";
case 'Q': return "'unsigned long long'";
case 'f': return (is_complex ? "'complex float'" : "'float'");
case 'd': return (is_complex ? "'complex double'" : "'double'");
case 'g': return (is_complex ? "'complex long double'" : "'long double'");
case 'T': return "a struct";
case 'O': return "Python object";
case 'P': return "a pointer";
case 's': case 'p': return "a string";
case 0: return "end";
default: return "unparseable format string";
}
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return 2;
case 'i': case 'I': case 'l': case 'L': return 4;
case 'q': case 'Q': return 8;
case 'f': return (is_complex ? 8 : 4);
case 'd': return (is_complex ? 16 : 8);
case 'g': {
PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
return 0;
}
case 'O': case 'P': return sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(short);
case 'i': case 'I': return sizeof(int);
case 'l': case 'L': return sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(float) * (is_complex ? 2 : 1);
case 'd': return sizeof(double) * (is_complex ? 2 : 1);
case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
case 'O': case 'P': return sizeof(void*);
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
/* These are for computing the padding at the end of the struct to align
on the first member of the struct. This will probably the same as above,
but we don't have any guarantees.
*/
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
switch (ch) {
case 'c':
return 'H';
case 'b': case 'h': case 'i':
case 'l': case 'q': case 's': case 'p':
return 'I';
case '?': case 'B': case 'H': case 'I': case 'L': case 'Q':
return 'U';
case 'f': case 'd': case 'g':
return (is_complex ? 'C' : 'R');
case 'O':
return 'O';
case 'P':
return 'P';
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
if (ctx->head == NULL || ctx->head->field == &ctx->root) {
const char* expected;
const char* quote;
if (ctx->head == NULL) {
expected = "end";
quote = "";
} else {
expected = ctx->head->field->type->name;
quote = "'";
}
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected %s%s%s but got %s",
quote, expected, quote,
__Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
} else {
__Pyx_StructField* field = ctx->head->field;
__Pyx_StructField* parent = (ctx->head - 1)->field;
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
parent->type->name, field->name);
}
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
char group;
size_t size, offset, arraysize = 1;
if (ctx->enc_type == 0) return 0;
if (ctx->head->field->type->arraysize[0]) {
int i, ndim = 0;
if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
ctx->is_valid_array = ctx->head->field->type->ndim == 1;
ndim = 1;
if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %zu",
ctx->head->field->type->arraysize[0], ctx->enc_count);
return -1;
}
}
if (!ctx->is_valid_array) {
PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
ctx->head->field->type->ndim, ndim);
return -1;
}
for (i = 0; i < ctx->head->field->type->ndim; i++) {
arraysize *= ctx->head->field->type->arraysize[i];
}
ctx->is_valid_array = 0;
ctx->enc_count = 1;
}
group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
do {
__Pyx_StructField* field = ctx->head->field;
__Pyx_TypeInfo* type = field->type;
if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
} else {
size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
}
if (ctx->enc_packmode == '@') {
size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
size_t align_mod_offset;
if (align_at == 0) return -1;
align_mod_offset = ctx->fmt_offset % align_at;
if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
if (ctx->struct_alignment == 0)
ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
ctx->is_complex);
}
if (type->size != size || type->typegroup != group) {
if (type->typegroup == 'C' && type->fields != NULL) {
size_t parent_offset = ctx->head->parent_offset + field->offset;
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = parent_offset;
continue;
}
if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
} else {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
}
offset = ctx->head->parent_offset + field->offset;
if (ctx->fmt_offset != offset) {
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
(Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
return -1;
}
ctx->fmt_offset += size;
if (arraysize)
ctx->fmt_offset += (arraysize - 1) * size;
--ctx->enc_count;
while (1) {
if (field == &ctx->root) {
ctx->head = NULL;
if (ctx->enc_count != 0) {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
break;
}
ctx->head->field = ++field;
if (field->type == NULL) {
--ctx->head;
field = ctx->head->field;
continue;
} else if (field->type->typegroup == 'S') {
size_t parent_offset = ctx->head->parent_offset + field->offset;
if (field->type->fields->type == NULL) continue;
field = field->type->fields;
++ctx->head;
ctx->head->field = field;
ctx->head->parent_offset = parent_offset;
break;
} else {
break;
}
}
} while (ctx->enc_count);
ctx->enc_type = 0;
ctx->is_complex = 0;
return 0;
}
static PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
const char *ts = *tsp;
int i = 0, number, ndim;
++ts;
if (ctx->new_count != 1) {
PyErr_SetString(PyExc_ValueError,
"Cannot handle repeated arrays in format string");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ndim = ctx->head->field->type->ndim;
while (*ts && *ts != ')') {
switch (*ts) {
case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
default: break;
}
number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
return PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %d",
ctx->head->field->type->arraysize[i], number);
if (*ts != ',' && *ts != ')')
return PyErr_Format(PyExc_ValueError,
"Expected a comma in format string, got '%c'", *ts);
if (*ts == ',') ts++;
i++;
}
if (i != ndim)
return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
ctx->head->field->type->ndim, i);
if (!*ts) {
PyErr_SetString(PyExc_ValueError,
"Unexpected end of format string, expected ')'");
return NULL;
}
ctx->is_valid_array = 1;
ctx->new_count = 1;
*tsp = ++ts;
return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
int got_Z = 0;
while (1) {
switch(*ts) {
case 0:
if (ctx->enc_type != 0 && ctx->head == NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
if (ctx->head != NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
return ts;
case ' ':
case '\r':
case '\n':
++ts;
break;
case '<':
if (!__Pyx_Is_Little_Endian()) {
PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '>':
case '!':
if (__Pyx_Is_Little_Endian()) {
PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '=':
case '@':
case '^':
ctx->new_packmode = *ts++;
break;
case 'T':
{
const char* ts_after_sub;
size_t i, struct_count = ctx->new_count;
size_t struct_alignment = ctx->struct_alignment;
ctx->new_count = 1;
++ts;
if (*ts != '{') {
PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
ctx->enc_count = 0;
ctx->struct_alignment = 0;
++ts;
ts_after_sub = ts;
for (i = 0; i != struct_count; ++i) {
ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
if (!ts_after_sub) return NULL;
}
ts = ts_after_sub;
if (struct_alignment) ctx->struct_alignment = struct_alignment;
}
break;
case '}':
{
size_t alignment = ctx->struct_alignment;
++ts;
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
if (alignment && ctx->fmt_offset % alignment) {
ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
}
}
return ts;
case 'x':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->fmt_offset += ctx->new_count;
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->enc_packmode = ctx->new_packmode;
++ts;
break;
case 'Z':
got_Z = 1;
++ts;
if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
__Pyx_BufFmt_RaiseUnexpectedChar('Z');
return NULL;
}
CYTHON_FALLTHROUGH;
case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
case 'l': case 'L': case 'q': case 'Q':
case 'f': case 'd': case 'g':
case 'O': case 'p':
if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) &&
(ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) {
ctx->enc_count += ctx->new_count;
ctx->new_count = 1;
got_Z = 0;
++ts;
break;
}
CYTHON_FALLTHROUGH;
case 's':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_count = ctx->new_count;
ctx->enc_packmode = ctx->new_packmode;
ctx->enc_type = *ts;
ctx->is_complex = got_Z;
++ts;
ctx->new_count = 1;
got_Z = 0;
break;
case ':':
++ts;
while(*ts != ':') ++ts;
++ts;
break;
case '(':
if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
break;
default:
{
int number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
ctx->new_count = (size_t)number;
}
}
}
}
/* BufferGetAndValidate */
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
if (unlikely(info->buf == NULL)) return;
if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
__Pyx_ReleaseBuffer(info);
}
static void __Pyx_ZeroBuffer(Py_buffer* buf) {
buf->buf = NULL;
buf->obj = NULL;
buf->strides = __Pyx_zeros;
buf->shape = __Pyx_zeros;
buf->suboffsets = __Pyx_minusones;
}
static int __Pyx__GetBufferAndValidate(
Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
buf->buf = NULL;
if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) {
__Pyx_ZeroBuffer(buf);
return -1;
}
if (unlikely(buf->ndim != nd)) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
nd, buf->ndim);
goto fail;
}
if (!cast) {
__Pyx_BufFmt_Context ctx;
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if (unlikely((size_t)buf->itemsize != dtype->size)) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
buf->itemsize, (buf->itemsize > 1) ? "s" : "",
dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
goto fail;
}
if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
return 0;
fail:;
__Pyx_SafeReleaseBuffer(buf);
return -1;
}
/* BufferFallbackError */
static void __Pyx_RaiseBufferFallbackError(void) {
PyErr_SetString(PyExc_ValueError,
"Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!");
}
/* BufferIndexError */
static void __Pyx_RaiseBufferIndexError(int axis) {
PyErr_Format(PyExc_IndexError,
"Out of bounds on buffer access (axis %d)", axis);
}
/* SetItemInt */
static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) {
int r;
if (!j) return -1;
r = PyObject_SetItem(o, j, v);
Py_DECREF(j);
return r;
}
static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list,
CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
if (is_list || PyList_CheckExact(o)) {
Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o));
if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o)))) {
PyObject* old = PyList_GET_ITEM(o, n);
Py_INCREF(v);
PyList_SET_ITEM(o, n, v);
Py_DECREF(old);
return 1;
}
} else {
PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
if (likely(m && m->sq_ass_item)) {
if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
Py_ssize_t l = m->sq_length(o);
if (likely(l >= 0)) {
i += l;
} else {
if (!PyErr_ExceptionMatches(PyExc_OverflowError))
return -1;
PyErr_Clear();
}
}
return m->sq_ass_item(o, i, v);
}
}
#else
#if CYTHON_COMPILING_IN_PYPY
if (is_list || (PySequence_Check(o) && !PyDict_Check(o)))
#else
if (is_list || PySequence_Check(o))
#endif
{
return PySequence_SetItem(o, i, v);
}
#endif
return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v);
}
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractCObj(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) {
(void)inplace;
(void)zerodivision_check;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op2))) {
const long a = intval;
long x;
long b = PyInt_AS_LONG(op2);
x = (long)((unsigned long)a - b);
if (likely((x^a) >= 0 || (x^~b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op2))) {
const long a = intval;
long b, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG lla = intval;
PY_LONG_LONG llb, llx;
#endif
const digit* digits = ((PyLongObject*)op2)->ob_digit;
const Py_ssize_t size = Py_SIZE(op2);
if (likely(__Pyx_sst_abs(size) <= 1)) {
b = likely(size) ? digits[0] : 0;
if (size == -1) b = -b;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
b = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
llb = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
b = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
llb = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
b = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
llb = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
b = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
llb = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
b = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
llb = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
b = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
llb = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
CYTHON_FALLTHROUGH;
default: return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
}
x = a - b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla - llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op2)) {
const long a = intval;
double b = PyFloat_AS_DOUBLE(op2);
double result;
PyFPE_START_PROTECT("subtract", return NULL)
result = ((double)a) - (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceSubtract : PyNumber_Subtract)(op1, op2);
}
#endif
/* Import */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
PyObject *empty_list = 0;
PyObject *module = 0;
PyObject *global_dict = 0;
PyObject *empty_dict = 0;
PyObject *list;
#if PY_MAJOR_VERSION < 3
PyObject *py_import;
py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
if (!py_import)
goto bad;
#endif
if (from_list)
list = from_list;
else {
empty_list = PyList_New(0);
if (!empty_list)
goto bad;
list = empty_list;
}
global_dict = PyModule_GetDict(__pyx_m);
if (!global_dict)
goto bad;
empty_dict = PyDict_New();
if (!empty_dict)
goto bad;
{
#if PY_MAJOR_VERSION >= 3
if (level == -1) {
if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) {
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, 1);
if (!module) {
if (!PyErr_ExceptionMatches(PyExc_ImportError))
goto bad;
PyErr_Clear();
}
}
level = 0;
}
#endif
if (!module) {
#if PY_MAJOR_VERSION < 3
PyObject *py_level = PyInt_FromLong(level);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, (PyObject *)NULL);
Py_DECREF(py_level);
#else
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, level);
#endif
}
}
bad:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(py_import);
#endif
Py_XDECREF(empty_list);
Py_XDECREF(empty_dict);
return module;
}
/* ImportFrom */
static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
PyErr_Format(PyExc_ImportError,
#if PY_MAJOR_VERSION < 3
"cannot import name %.230s", PyString_AS_STRING(name));
#else
"cannot import name %S", name);
#endif
}
return value;
}
/* HasAttr */
static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) {
PyObject *r;
if (unlikely(!__Pyx_PyBaseString_Check(n))) {
PyErr_SetString(PyExc_TypeError,
"hasattr(): attribute name must be string");
return -1;
}
r = __Pyx_GetAttr(o, n);
if (unlikely(!r)) {
PyErr_Clear();
return 0;
} else {
Py_DECREF(r);
return 1;
}
}
/* PyObject_GenericGetAttrNoDict */
#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) {
PyErr_Format(PyExc_AttributeError,
#if PY_MAJOR_VERSION >= 3
"'%.50s' object has no attribute '%U'",
tp->tp_name, attr_name);
#else
"'%.50s' object has no attribute '%.400s'",
tp->tp_name, PyString_AS_STRING(attr_name));
#endif
return NULL;
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) {
PyObject *descr;
PyTypeObject *tp = Py_TYPE(obj);
if (unlikely(!PyString_Check(attr_name))) {
return PyObject_GenericGetAttr(obj, attr_name);
}
assert(!tp->tp_dictoffset);
descr = _PyType_Lookup(tp, attr_name);
if (unlikely(!descr)) {
return __Pyx_RaiseGenericGetAttributeError(tp, attr_name);
}
Py_INCREF(descr);
#if PY_MAJOR_VERSION < 3
if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS)))
#endif
{
descrgetfunc f = Py_TYPE(descr)->tp_descr_get;
if (unlikely(f)) {
PyObject *res = f(descr, obj, (PyObject *)tp);
Py_DECREF(descr);
return res;
}
}
return descr;
}
#endif
/* PyObject_GenericGetAttr */
#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) {
if (unlikely(Py_TYPE(obj)->tp_dictoffset)) {
return PyObject_GenericGetAttr(obj, attr_name);
}
return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name);
}
#endif
/* PyObjectGetAttrStrNoError */
static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) {
__Pyx_PyThreadState_declare
__Pyx_PyThreadState_assign
if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
__Pyx_PyErr_Clear();
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) {
PyObject *result;
#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1
PyTypeObject* tp = Py_TYPE(obj);
if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) {
return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1);
}
#endif
result = __Pyx_PyObject_GetAttrStr(obj, attr_name);
if (unlikely(!result)) {
__Pyx_PyObject_GetAttrStr_ClearAttributeError();
}
return result;
}
/* SetupReduce */
static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) {
int ret;
PyObject *name_attr;
name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2);
if (likely(name_attr)) {
ret = PyObject_RichCompareBool(name_attr, name, Py_EQ);
} else {
ret = -1;
}
if (unlikely(ret < 0)) {
PyErr_Clear();
ret = 0;
}
Py_XDECREF(name_attr);
return ret;
}
static int __Pyx_setup_reduce(PyObject* type_obj) {
int ret = 0;
PyObject *object_reduce = NULL;
PyObject *object_reduce_ex = NULL;
PyObject *reduce = NULL;
PyObject *reduce_ex = NULL;
PyObject *reduce_cython = NULL;
PyObject *setstate = NULL;
PyObject *setstate_cython = NULL;
#if CYTHON_USE_PYTYPE_LOOKUP
if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD;
#else
if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD;
#endif
#if CYTHON_USE_PYTYPE_LOOKUP
object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
#else
object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
#endif
reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD;
if (reduce_ex == object_reduce_ex) {
#if CYTHON_USE_PYTYPE_LOOKUP
object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
#else
object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
#endif
reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD;
if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) {
reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython);
if (likely(reduce_cython)) {
ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
} else if (reduce == object_reduce || PyErr_Occurred()) {
goto __PYX_BAD;
}
setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate);
if (!setstate) PyErr_Clear();
if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) {
setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython);
if (likely(setstate_cython)) {
ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
} else if (!setstate || PyErr_Occurred()) {
goto __PYX_BAD;
}
}
PyType_Modified((PyTypeObject*)type_obj);
}
}
goto __PYX_GOOD;
__PYX_BAD:
if (!PyErr_Occurred())
PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name);
ret = -1;
__PYX_GOOD:
#if !CYTHON_USE_PYTYPE_LOOKUP
Py_XDECREF(object_reduce);
Py_XDECREF(object_reduce_ex);
#endif
Py_XDECREF(reduce);
Py_XDECREF(reduce_ex);
Py_XDECREF(reduce_cython);
Py_XDECREF(setstate);
Py_XDECREF(setstate_cython);
return ret;
}
/* SetVTable */
static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000
PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
if (!ob)
goto bad;
if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
goto bad;
Py_DECREF(ob);
return 0;
bad:
Py_XDECREF(ob);
return -1;
}
/* TypeImport */
#ifndef __PYX_HAVE_RT_ImportType
#define __PYX_HAVE_RT_ImportType
static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name,
size_t size, enum __Pyx_ImportType_CheckSize check_size)
{
PyObject *result = 0;
char warning[200];
Py_ssize_t basicsize;
#ifdef Py_LIMITED_API
PyObject *py_basicsize;
#endif
result = PyObject_GetAttrString(module, class_name);
if (!result)
goto bad;
if (!PyType_Check(result)) {
PyErr_Format(PyExc_TypeError,
"%.200s.%.200s is not a type object",
module_name, class_name);
goto bad;
}
#ifndef Py_LIMITED_API
basicsize = ((PyTypeObject *)result)->tp_basicsize;
#else
py_basicsize = PyObject_GetAttrString(result, "__basicsize__");
if (!py_basicsize)
goto bad;
basicsize = PyLong_AsSsize_t(py_basicsize);
Py_DECREF(py_basicsize);
py_basicsize = 0;
if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred())
goto bad;
#endif
if ((size_t)basicsize < size) {
PyErr_Format(PyExc_ValueError,
"%.200s.%.200s size changed, may indicate binary incompatibility. "
"Expected %zd from C header, got %zd from PyObject",
module_name, class_name, size, basicsize);
goto bad;
}
if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) {
PyErr_Format(PyExc_ValueError,
"%.200s.%.200s size changed, may indicate binary incompatibility. "
"Expected %zd from C header, got %zd from PyObject",
module_name, class_name, size, basicsize);
goto bad;
}
else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) {
PyOS_snprintf(warning, sizeof(warning),
"%s.%s size changed, may indicate binary incompatibility. "
"Expected %zd from C header, got %zd from PyObject",
module_name, class_name, size, basicsize);
if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
}
return (PyTypeObject *)result;
bad:
Py_XDECREF(result);
return NULL;
}
#endif
/* CalculateMetaclass */
static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases) {
Py_ssize_t i, nbases = PyTuple_GET_SIZE(bases);
for (i=0; i < nbases; i++) {
PyTypeObject *tmptype;
PyObject *tmp = PyTuple_GET_ITEM(bases, i);
tmptype = Py_TYPE(tmp);
#if PY_MAJOR_VERSION < 3
if (tmptype == &PyClass_Type)
continue;
#endif
if (!metaclass) {
metaclass = tmptype;
continue;
}
if (PyType_IsSubtype(metaclass, tmptype))
continue;
if (PyType_IsSubtype(tmptype, metaclass)) {
metaclass = tmptype;
continue;
}
PyErr_SetString(PyExc_TypeError,
"metaclass conflict: "
"the metaclass of a derived class "
"must be a (non-strict) subclass "
"of the metaclasses of all its bases");
return NULL;
}
if (!metaclass) {
#if PY_MAJOR_VERSION < 3
metaclass = &PyClass_Type;
#else
metaclass = &PyType_Type;
#endif
}
Py_INCREF((PyObject*) metaclass);
return (PyObject*) metaclass;
}
/* Py3ClassCreate */
static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name,
PyObject *qualname, PyObject *mkw, PyObject *modname, PyObject *doc) {
PyObject *ns;
if (metaclass) {
PyObject *prep = __Pyx_PyObject_GetAttrStr(metaclass, __pyx_n_s_prepare);
if (prep) {
PyObject *pargs = PyTuple_Pack(2, name, bases);
if (unlikely(!pargs)) {
Py_DECREF(prep);
return NULL;
}
ns = PyObject_Call(prep, pargs, mkw);
Py_DECREF(prep);
Py_DECREF(pargs);
} else {
if (unlikely(!PyErr_ExceptionMatches(PyExc_AttributeError)))
return NULL;
PyErr_Clear();
ns = PyDict_New();
}
} else {
ns = PyDict_New();
}
if (unlikely(!ns))
return NULL;
if (unlikely(PyObject_SetItem(ns, __pyx_n_s_module, modname) < 0)) goto bad;
if (unlikely(PyObject_SetItem(ns, __pyx_n_s_qualname, qualname) < 0)) goto bad;
if (unlikely(doc && PyObject_SetItem(ns, __pyx_n_s_doc, doc) < 0)) goto bad;
return ns;
bad:
Py_DECREF(ns);
return NULL;
}
static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases,
PyObject *dict, PyObject *mkw,
int calculate_metaclass, int allow_py2_metaclass) {
PyObject *result, *margs;
PyObject *owned_metaclass = NULL;
if (allow_py2_metaclass) {
owned_metaclass = PyObject_GetItem(dict, __pyx_n_s_metaclass);
if (owned_metaclass) {
metaclass = owned_metaclass;
} else if (likely(PyErr_ExceptionMatches(PyExc_KeyError))) {
PyErr_Clear();
} else {
return NULL;
}
}
if (calculate_metaclass && (!metaclass || PyType_Check(metaclass))) {
metaclass = __Pyx_CalculateMetaclass((PyTypeObject*) metaclass, bases);
Py_XDECREF(owned_metaclass);
if (unlikely(!metaclass))
return NULL;
owned_metaclass = metaclass;
}
margs = PyTuple_Pack(3, name, bases, dict);
if (unlikely(!margs)) {
result = NULL;
} else {
result = PyObject_Call(metaclass, margs, mkw);
Py_DECREF(margs);
}
Py_XDECREF(owned_metaclass);
return result;
}
/* CLineInTraceback */
#ifndef CYTHON_CLINE_IN_TRACEBACK
static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) {
PyObject *use_cline;
PyObject *ptype, *pvalue, *ptraceback;
#if CYTHON_COMPILING_IN_CPYTHON
PyObject **cython_runtime_dict;
#endif
if (unlikely(!__pyx_cython_runtime)) {
return c_line;
}
__Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback);
#if CYTHON_COMPILING_IN_CPYTHON
cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime);
if (likely(cython_runtime_dict)) {
__PYX_PY_DICT_LOOKUP_IF_MODIFIED(
use_cline, *cython_runtime_dict,
__Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback))
} else
#endif
{
PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback);
if (use_cline_obj) {
use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True;
Py_DECREF(use_cline_obj);
} else {
PyErr_Clear();
use_cline = NULL;
}
}
if (!use_cline) {
c_line = 0;
PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False);
}
else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) {
c_line = 0;
}
__Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback);
return c_line;
}
#endif
/* CodeObjectCache */
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
int start = 0, mid = 0, end = count - 1;
if (end >= 0 && code_line > entries[end].code_line) {
return count;
}
while (start < end) {
mid = start + (end - start) / 2;
if (code_line < entries[mid].code_line) {
end = mid;
} else if (code_line > entries[mid].code_line) {
start = mid + 1;
} else {
return mid;
}
}
if (code_line <= entries[mid].code_line) {
return mid;
} else {
return mid + 1;
}
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
PyCodeObject* code_object;
int pos;
if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
return NULL;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
return NULL;
}
code_object = __pyx_code_cache.entries[pos].code_object;
Py_INCREF(code_object);
return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
int pos, i;
__Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
if (unlikely(!code_line)) {
return;
}
if (unlikely(!entries)) {
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
if (likely(entries)) {
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = 64;
__pyx_code_cache.count = 1;
entries[0].code_line = code_line;
entries[0].code_object = code_object;
Py_INCREF(code_object);
}
return;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
PyCodeObject* tmp = entries[pos].code_object;
entries[pos].code_object = code_object;
Py_DECREF(tmp);
return;
}
if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
int new_max = __pyx_code_cache.max_count + 64;
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
__pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry));
if (unlikely(!entries)) {
return;
}
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = new_max;
}
for (i=__pyx_code_cache.count; i>pos; i--) {
entries[i] = entries[i-1];
}
entries[pos].code_line = code_line;
entries[pos].code_object = code_object;
__pyx_code_cache.count++;
Py_INCREF(code_object);
}
/* AddTraceback */
#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyObject *py_srcfile = 0;
PyObject *py_funcname = 0;
#if PY_MAJOR_VERSION < 3
py_srcfile = PyString_FromString(filename);
#else
py_srcfile = PyUnicode_FromString(filename);
#endif
if (!py_srcfile) goto bad;
if (c_line) {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#else
py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#endif
}
else {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromString(funcname);
#else
py_funcname = PyUnicode_FromString(funcname);
#endif
}
if (!py_funcname) goto bad;
py_code = __Pyx_PyCode_New(
0,
0,
0,
0,
0,
__pyx_empty_bytes, /*PyObject *code,*/
__pyx_empty_tuple, /*PyObject *consts,*/
__pyx_empty_tuple, /*PyObject *names,*/
__pyx_empty_tuple, /*PyObject *varnames,*/
__pyx_empty_tuple, /*PyObject *freevars,*/
__pyx_empty_tuple, /*PyObject *cellvars,*/
py_srcfile, /*PyObject *filename,*/
py_funcname, /*PyObject *name,*/
py_line,
__pyx_empty_bytes /*PyObject *lnotab*/
);
Py_DECREF(py_srcfile);
Py_DECREF(py_funcname);
return py_code;
bad:
Py_XDECREF(py_srcfile);
Py_XDECREF(py_funcname);
return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyFrameObject *py_frame = 0;
PyThreadState *tstate = __Pyx_PyThreadState_Current;
if (c_line) {
c_line = __Pyx_CLineForTraceback(tstate, c_line);
}
py_code = __pyx_find_code_object(c_line ? -c_line : py_line);
if (!py_code) {
py_code = __Pyx_CreateCodeObjectForTraceback(
funcname, c_line, py_line, filename);
if (!py_code) goto bad;
__pyx_insert_code_object(c_line ? -c_line : py_line, py_code);
}
py_frame = PyFrame_New(
tstate, /*PyThreadState *tstate,*/
py_code, /*PyCodeObject *code,*/
__pyx_d, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (!py_frame) goto bad;
__Pyx_PyFrame_SetLineNumber(py_frame, py_line);
PyTraceBack_Here(py_frame);
bad:
Py_XDECREF(py_code);
Py_XDECREF(py_frame);
}
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
PyObject *obj = view->obj;
if (!obj) return;
if (PyObject_CheckBuffer(obj)) {
PyBuffer_Release(view);
return;
}
if ((0)) {}
view->obj = NULL;
Py_DECREF(obj);
}
#endif
/* CIntFromPyVerify */
#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
{\
func_type value = func_value;\
if (sizeof(target_type) < sizeof(func_type)) {\
if (unlikely(value != (func_type) (target_type) value)) {\
func_type zero = 0;\
if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
return (target_type) -1;\
if (is_unsigned && unlikely(value < zero))\
goto raise_neg_overflow;\
else\
goto raise_overflow;\
}\
}\
return (target_type) value;\
}
/* Declarations */
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return ::std::complex< float >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return x + y*(__pyx_t_float_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
__pyx_t_float_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
/* Arithmetic */
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
#if 1
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
if (b.imag == 0) {
return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real);
} else if (fabsf(b.real) >= fabsf(b.imag)) {
if (b.real == 0 && b.imag == 0) {
return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag);
} else {
float r = b.imag / b.real;
float s = (float)(1.0) / (b.real + b.imag * r);
return __pyx_t_float_complex_from_parts(
(a.real + a.imag * r) * s, (a.imag - a.real * r) * s);
}
} else {
float r = b.real / b.imag;
float s = (float)(1.0) / (b.imag + b.real * r);
return __pyx_t_float_complex_from_parts(
(a.real * r + a.imag) * s, (a.imag * r - a.real) * s);
}
}
#else
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
if (b.imag == 0) {
return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real);
} else {
float denom = b.real * b.real + b.imag * b.imag;
return __pyx_t_float_complex_from_parts(
(a.real * b.real + a.imag * b.imag) / denom,
(a.imag * b.real - a.real * b.imag) / denom);
}
}
#endif
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
#if 1
static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) {
#if !defined(HAVE_HYPOT) || defined(_MSC_VER)
return sqrtf(z.real*z.real + z.imag*z.imag);
#else
return hypotf(z.real, z.imag);
#endif
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
float r, lnr, theta, z_r, z_theta;
if (b.imag == 0 && b.real == (int)b.real) {
if (b.real < 0) {
float denom = a.real * a.real + a.imag * a.imag;
a.real = a.real / denom;
a.imag = -a.imag / denom;
b.real = -b.real;
}
switch ((int)b.real) {
case 0:
z.real = 1;
z.imag = 0;
return z;
case 1:
return a;
case 2:
return __Pyx_c_prod_float(a, a);
case 3:
z = __Pyx_c_prod_float(a, a);
return __Pyx_c_prod_float(z, a);
case 4:
z = __Pyx_c_prod_float(a, a);
return __Pyx_c_prod_float(z, z);
}
}
if (a.imag == 0) {
if (a.real == 0) {
return a;
} else if (b.imag == 0) {
z.real = powf(a.real, b.real);
z.imag = 0;
return z;
} else if (a.real > 0) {
r = a.real;
theta = 0;
} else {
r = -a.real;
theta = atan2f(0.0, -1.0);
}
} else {
r = __Pyx_c_abs_float(a);
theta = atan2f(a.imag, a.real);
}
lnr = logf(r);
z_r = expf(lnr * b.real - theta * b.imag);
z_theta = theta * b.real + lnr * b.imag;
z.real = z_r * cosf(z_theta);
z.imag = z_r * sinf(z_theta);
return z;
}
#endif
#endif
/* Declarations */
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return ::std::complex< double >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return x + y*(__pyx_t_double_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
__pyx_t_double_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
/* Arithmetic */
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
#if 1
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
if (b.imag == 0) {
return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real);
} else if (fabs(b.real) >= fabs(b.imag)) {
if (b.real == 0 && b.imag == 0) {
return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag);
} else {
double r = b.imag / b.real;
double s = (double)(1.0) / (b.real + b.imag * r);
return __pyx_t_double_complex_from_parts(
(a.real + a.imag * r) * s, (a.imag - a.real * r) * s);
}
} else {
double r = b.real / b.imag;
double s = (double)(1.0) / (b.imag + b.real * r);
return __pyx_t_double_complex_from_parts(
(a.real * r + a.imag) * s, (a.imag * r - a.real) * s);
}
}
#else
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
if (b.imag == 0) {
return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real);
} else {
double denom = b.real * b.real + b.imag * b.imag;
return __pyx_t_double_complex_from_parts(
(a.real * b.real + a.imag * b.imag) / denom,
(a.imag * b.real - a.real * b.imag) / denom);
}
}
#endif
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
#if 1
static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) {
#if !defined(HAVE_HYPOT) || defined(_MSC_VER)
return sqrt(z.real*z.real + z.imag*z.imag);
#else
return hypot(z.real, z.imag);
#endif
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
double r, lnr, theta, z_r, z_theta;
if (b.imag == 0 && b.real == (int)b.real) {
if (b.real < 0) {
double denom = a.real * a.real + a.imag * a.imag;
a.real = a.real / denom;
a.imag = -a.imag / denom;
b.real = -b.real;
}
switch ((int)b.real) {
case 0:
z.real = 1;
z.imag = 0;
return z;
case 1:
return a;
case 2:
return __Pyx_c_prod_double(a, a);
case 3:
z = __Pyx_c_prod_double(a, a);
return __Pyx_c_prod_double(z, a);
case 4:
z = __Pyx_c_prod_double(a, a);
return __Pyx_c_prod_double(z, z);
}
}
if (a.imag == 0) {
if (a.real == 0) {
return a;
} else if (b.imag == 0) {
z.real = pow(a.real, b.real);
z.imag = 0;
return z;
} else if (a.real > 0) {
r = a.real;
theta = 0;
} else {
r = -a.real;
theta = atan2(0.0, -1.0);
}
} else {
r = __Pyx_c_abs_double(a);
theta = atan2(a.imag, a.real);
}
lnr = log(r);
z_r = exp(lnr * b.real - theta * b.imag);
z_theta = theta * b.real + lnr * b.imag;
z.real = z_r * cos(z_theta);
z.imag = z_r * sin(z_theta);
return z;
}
#endif
#endif
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const int neg_one = (int) -1, const_zero = (int) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(int) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(int) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(int) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(int),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_EXPROP(SCIP_EXPROP value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_EXPROP neg_one = (SCIP_EXPROP) -1, const_zero = (SCIP_EXPROP) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_EXPROP) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_EXPROP) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EXPROP) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_EXPROP) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EXPROP) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_EXPROP),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_RESULT(SCIP_RESULT value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_RESULT neg_one = (SCIP_RESULT) -1, const_zero = (SCIP_RESULT) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_RESULT) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_RESULT) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RESULT) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_RESULT) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RESULT) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_RESULT),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PARAMSETTING(SCIP_PARAMSETTING value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PARAMSETTING neg_one = (SCIP_PARAMSETTING) -1, const_zero = (SCIP_PARAMSETTING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_PARAMSETTING) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_PARAMSETTING) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMSETTING) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_PARAMSETTING) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMSETTING) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_PARAMSETTING),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PARAMEMPHASIS(SCIP_PARAMEMPHASIS value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PARAMEMPHASIS neg_one = (SCIP_PARAMEMPHASIS) -1, const_zero = (SCIP_PARAMEMPHASIS) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_PARAMEMPHASIS) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_PARAMEMPHASIS),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_STATUS(SCIP_STATUS value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_STATUS neg_one = (SCIP_STATUS) -1, const_zero = (SCIP_STATUS) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_STATUS) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_STATUS) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_STATUS) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_STATUS) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_STATUS) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_STATUS),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_STAGE(SCIP_STAGE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_STAGE neg_one = (SCIP_STAGE) -1, const_zero = (SCIP_STAGE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_STAGE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_STAGE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_STAGE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_STAGE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_STAGE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_STAGE),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_NODETYPE(SCIP_NODETYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_NODETYPE neg_one = (SCIP_NODETYPE) -1, const_zero = (SCIP_NODETYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_NODETYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_NODETYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_NODETYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_NODETYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_NODETYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_NODETYPE),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PROPTIMING(SCIP_PROPTIMING value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PROPTIMING neg_one = (SCIP_PROPTIMING) -1, const_zero = (SCIP_PROPTIMING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_PROPTIMING) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_PROPTIMING) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PROPTIMING) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_PROPTIMING) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PROPTIMING) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_PROPTIMING),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_PRESOLTIMING(SCIP_PRESOLTIMING value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PRESOLTIMING neg_one = (SCIP_PRESOLTIMING) -1, const_zero = (SCIP_PRESOLTIMING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_PRESOLTIMING) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_PRESOLTIMING) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PRESOLTIMING) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_PRESOLTIMING) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PRESOLTIMING) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_PRESOLTIMING),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_HEURTIMING(SCIP_HEURTIMING value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_HEURTIMING neg_one = (SCIP_HEURTIMING) -1, const_zero = (SCIP_HEURTIMING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_HEURTIMING) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_HEURTIMING) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_HEURTIMING) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_HEURTIMING) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_HEURTIMING) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_HEURTIMING),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_EVENTTYPE(SCIP_EVENTTYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_EVENTTYPE neg_one = (SCIP_EVENTTYPE) -1, const_zero = (SCIP_EVENTTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_EVENTTYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_EVENTTYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EVENTTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_EVENTTYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EVENTTYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_EVENTTYPE),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_LPSOLSTAT(SCIP_LPSOLSTAT value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_LPSOLSTAT neg_one = (SCIP_LPSOLSTAT) -1, const_zero = (SCIP_LPSOLSTAT) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_LPSOLSTAT) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_LPSOLSTAT) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_LPSOLSTAT) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_LPSOLSTAT) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_LPSOLSTAT) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_LPSOLSTAT),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BRANCHDIR(SCIP_BRANCHDIR value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BRANCHDIR neg_one = (SCIP_BRANCHDIR) -1, const_zero = (SCIP_BRANCHDIR) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_BRANCHDIR) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_BRANCHDIR) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BRANCHDIR) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_BRANCHDIR) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BRANCHDIR) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_BRANCHDIR),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BENDERSENFOTYPE(SCIP_BENDERSENFOTYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BENDERSENFOTYPE neg_one = (SCIP_BENDERSENFOTYPE) -1, const_zero = (SCIP_BENDERSENFOTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_BENDERSENFOTYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_BENDERSENFOTYPE),
little, !is_unsigned);
}
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_RETCODE __Pyx_PyInt_As_SCIP_RETCODE(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_RETCODE neg_one = (SCIP_RETCODE) -1, const_zero = (SCIP_RETCODE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_RETCODE) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_RETCODE) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_RETCODE) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_RETCODE, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_RETCODE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) >= 2 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((((SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_RETCODE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) >= 3 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((((((SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_RETCODE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) >= 4 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((((((((SCIP_RETCODE)digits[3]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_RETCODE) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_RETCODE) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RETCODE, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RETCODE) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RETCODE, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_RETCODE) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_RETCODE, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_RETCODE, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_RETCODE) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((SCIP_RETCODE)-1)*(((((SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_RETCODE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_RETCODE) ((((((SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_RETCODE) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((SCIP_RETCODE)-1)*(((((((SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_RETCODE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_RETCODE) ((((((((SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_RETCODE) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_RETCODE) (((SCIP_RETCODE)-1)*(((((((((SCIP_RETCODE)digits[3]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_RETCODE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RETCODE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RETCODE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_RETCODE) ((((((((((SCIP_RETCODE)digits[3]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[2]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[1]) << PyLong_SHIFT) | (SCIP_RETCODE)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_RETCODE) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RETCODE, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RETCODE) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RETCODE, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_RETCODE val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_RETCODE) -1;
}
} else {
SCIP_RETCODE val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_RETCODE) -1;
val = __Pyx_PyInt_As_SCIP_RETCODE(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_RETCODE");
return (SCIP_RETCODE) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_RETCODE");
return (SCIP_RETCODE) -1;
}
/* CIntFromPy */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const int neg_one = (int) -1, const_zero = (int) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(int) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (int) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (int) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(int) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0])
case -2:
if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
}
#endif
if (sizeof(int) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
int val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (int) -1;
}
} else {
int val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (int) -1;
val = __Pyx_PyInt_As_int(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to int");
return (int) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to int");
return (int) -1;
}
/* CIntFromPy */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const long neg_one = (long) -1, const_zero = (long) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(long) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (long) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (long) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(long) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0])
case -2:
if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
}
#endif
if (sizeof(long) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
long val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (long) -1;
}
} else {
long val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (long) -1;
val = __Pyx_PyInt_As_long(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to long");
return (long) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long) -1;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const long neg_one = (long) -1, const_zero = (long) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(long) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(long) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(long) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(long),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_RETCODE(SCIP_RETCODE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_RETCODE neg_one = (SCIP_RETCODE) -1, const_zero = (SCIP_RETCODE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_RETCODE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_RETCODE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RETCODE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_RETCODE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RETCODE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_RETCODE),
little, !is_unsigned);
}
}
/* CIntFromPy */
static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const size_t neg_one = (size_t) -1, const_zero = (size_t) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(size_t) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(size_t, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (size_t) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (size_t) 0;
case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, digits[0])
case 2:
if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) >= 2 * PyLong_SHIFT) {
return (size_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) >= 3 * PyLong_SHIFT) {
return (size_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) >= 4 * PyLong_SHIFT) {
return (size_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (size_t) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(size_t) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(size_t) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (size_t) 0;
case -1: __PYX_VERIFY_RETURN_INT(size_t, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, +digits[0])
case -2:
if (8 * sizeof(size_t) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) {
return (size_t) (((size_t)-1)*(((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) {
return (size_t) ((((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) {
return (size_t) (((size_t)-1)*(((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) {
return (size_t) ((((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) {
return (size_t) (((size_t)-1)*(((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) {
return (size_t) ((((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])));
}
}
break;
}
#endif
if (sizeof(size_t) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(size_t, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(size_t) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(size_t, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
size_t val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (size_t) -1;
}
} else {
size_t val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (size_t) -1;
val = __Pyx_PyInt_As_size_t(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to size_t");
return (size_t) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to size_t");
return (size_t) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_RESULT __Pyx_PyInt_As_SCIP_RESULT(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_RESULT neg_one = (SCIP_RESULT) -1, const_zero = (SCIP_RESULT) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_RESULT) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_RESULT) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_RESULT) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_RESULT, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_RESULT) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) >= 2 * PyLong_SHIFT) {
return (SCIP_RESULT) (((((SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_RESULT) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) >= 3 * PyLong_SHIFT) {
return (SCIP_RESULT) (((((((SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_RESULT) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) >= 4 * PyLong_SHIFT) {
return (SCIP_RESULT) (((((((((SCIP_RESULT)digits[3]) << PyLong_SHIFT) | (SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_RESULT) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_RESULT) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RESULT, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RESULT) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RESULT, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_RESULT) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_RESULT, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_RESULT, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_RESULT) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_RESULT) (((SCIP_RESULT)-1)*(((((SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_RESULT) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_RESULT) ((((((SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_RESULT) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_RESULT) (((SCIP_RESULT)-1)*(((((((SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_RESULT) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_RESULT) ((((((((SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_RESULT) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_RESULT) (((SCIP_RESULT)-1)*(((((((((SCIP_RESULT)digits[3]) << PyLong_SHIFT) | (SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_RESULT) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_RESULT, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_RESULT) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_RESULT) ((((((((((SCIP_RESULT)digits[3]) << PyLong_SHIFT) | (SCIP_RESULT)digits[2]) << PyLong_SHIFT) | (SCIP_RESULT)digits[1]) << PyLong_SHIFT) | (SCIP_RESULT)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_RESULT) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RESULT, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_RESULT) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_RESULT, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_RESULT val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_RESULT) -1;
}
} else {
SCIP_RESULT val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_RESULT) -1;
val = __Pyx_PyInt_As_SCIP_RESULT(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_RESULT");
return (SCIP_RESULT) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_RESULT");
return (SCIP_RESULT) -1;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_LOCKTYPE(SCIP_LOCKTYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_LOCKTYPE neg_one = (SCIP_LOCKTYPE) -1, const_zero = (SCIP_LOCKTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_LOCKTYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_LOCKTYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_LOCKTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_LOCKTYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_LOCKTYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_LOCKTYPE),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BOUNDTYPE(SCIP_BOUNDTYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BOUNDTYPE neg_one = (SCIP_BOUNDTYPE) -1, const_zero = (SCIP_BOUNDTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_BOUNDTYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_BOUNDTYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BOUNDTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_BOUNDTYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BOUNDTYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_BOUNDTYPE),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_Longint(SCIP_Longint value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_Longint neg_one = (SCIP_Longint) -1, const_zero = (SCIP_Longint) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_Longint) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_Longint) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_Longint) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_Longint) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_Longint) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_Longint),
little, !is_unsigned);
}
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_SCIP_BOUNDCHGTYPE(SCIP_BOUNDCHGTYPE value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BOUNDCHGTYPE neg_one = (SCIP_BOUNDCHGTYPE) -1, const_zero = (SCIP_BOUNDCHGTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(SCIP_BOUNDCHGTYPE) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(SCIP_BOUNDCHGTYPE) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BOUNDCHGTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(SCIP_BOUNDCHGTYPE) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BOUNDCHGTYPE) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(SCIP_BOUNDCHGTYPE),
little, !is_unsigned);
}
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_PARAMSETTING __Pyx_PyInt_As_SCIP_PARAMSETTING(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PARAMSETTING neg_one = (SCIP_PARAMSETTING) -1, const_zero = (SCIP_PARAMSETTING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_PARAMSETTING) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_PARAMSETTING) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PARAMSETTING) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_PARAMSETTING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) >= 2 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((((SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PARAMSETTING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) >= 3 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((((((SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PARAMSETTING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) >= 4 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((((((((SCIP_PARAMSETTING)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_PARAMSETTING) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_PARAMSETTING) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMSETTING, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMSETTING) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMSETTING, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PARAMSETTING) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((SCIP_PARAMSETTING)-1)*(((((SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_PARAMSETTING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) ((((((SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((SCIP_PARAMSETTING)-1)*(((((((SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PARAMSETTING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) ((((((((SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) (((SCIP_PARAMSETTING)-1)*(((((((((SCIP_PARAMSETTING)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PARAMSETTING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMSETTING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMSETTING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PARAMSETTING) ((((((((((SCIP_PARAMSETTING)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMSETTING)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_PARAMSETTING) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMSETTING, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMSETTING) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMSETTING, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_PARAMSETTING val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_PARAMSETTING) -1;
}
} else {
SCIP_PARAMSETTING val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_PARAMSETTING) -1;
val = __Pyx_PyInt_As_SCIP_PARAMSETTING(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_PARAMSETTING");
return (SCIP_PARAMSETTING) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_PARAMSETTING");
return (SCIP_PARAMSETTING) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_EXPROP __Pyx_PyInt_As_SCIP_EXPROP(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_EXPROP neg_one = (SCIP_EXPROP) -1, const_zero = (SCIP_EXPROP) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_EXPROP) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_EXPROP) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_EXPROP) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_EXPROP, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_EXPROP) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) >= 2 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((((SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_EXPROP) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) >= 3 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((((((SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_EXPROP) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) >= 4 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((((((((SCIP_EXPROP)digits[3]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_EXPROP) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_EXPROP) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EXPROP, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EXPROP) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EXPROP, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_EXPROP) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_EXPROP, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_EXPROP, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_EXPROP) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((SCIP_EXPROP)-1)*(((((SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_EXPROP) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_EXPROP) ((((((SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_EXPROP) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((SCIP_EXPROP)-1)*(((((((SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_EXPROP) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_EXPROP) ((((((((SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_EXPROP) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_EXPROP) (((SCIP_EXPROP)-1)*(((((((((SCIP_EXPROP)digits[3]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_EXPROP) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EXPROP, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EXPROP) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_EXPROP) ((((((((((SCIP_EXPROP)digits[3]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[2]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[1]) << PyLong_SHIFT) | (SCIP_EXPROP)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_EXPROP) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EXPROP, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EXPROP) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EXPROP, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_EXPROP val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_EXPROP) -1;
}
} else {
SCIP_EXPROP val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_EXPROP) -1;
val = __Pyx_PyInt_As_SCIP_EXPROP(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_EXPROP");
return (SCIP_EXPROP) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_EXPROP");
return (SCIP_EXPROP) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_BENDERSENFOTYPE __Pyx_PyInt_As_SCIP_BENDERSENFOTYPE(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BENDERSENFOTYPE neg_one = (SCIP_BENDERSENFOTYPE) -1, const_zero = (SCIP_BENDERSENFOTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_BENDERSENFOTYPE) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_BENDERSENFOTYPE) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_BENDERSENFOTYPE) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) >= 2 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((((SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) >= 3 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((((((SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) >= 4 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((((((((SCIP_BENDERSENFOTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_BENDERSENFOTYPE) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BENDERSENFOTYPE, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BENDERSENFOTYPE, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_BENDERSENFOTYPE) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((SCIP_BENDERSENFOTYPE)-1)*(((((SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) ((((((SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((SCIP_BENDERSENFOTYPE)-1)*(((((((SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) ((((((((SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) (((SCIP_BENDERSENFOTYPE)-1)*(((((((((SCIP_BENDERSENFOTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_BENDERSENFOTYPE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BENDERSENFOTYPE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BENDERSENFOTYPE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_BENDERSENFOTYPE) ((((((((((SCIP_BENDERSENFOTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_BENDERSENFOTYPE)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BENDERSENFOTYPE, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BENDERSENFOTYPE) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BENDERSENFOTYPE, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_BENDERSENFOTYPE val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_BENDERSENFOTYPE) -1;
}
} else {
SCIP_BENDERSENFOTYPE val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_BENDERSENFOTYPE) -1;
val = __Pyx_PyInt_As_SCIP_BENDERSENFOTYPE(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_BENDERSENFOTYPE");
return (SCIP_BENDERSENFOTYPE) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_BENDERSENFOTYPE");
return (SCIP_BENDERSENFOTYPE) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_PROPTIMING __Pyx_PyInt_As_SCIP_PROPTIMING(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PROPTIMING neg_one = (SCIP_PROPTIMING) -1, const_zero = (SCIP_PROPTIMING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_PROPTIMING) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_PROPTIMING) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PROPTIMING) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_PROPTIMING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) >= 2 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((((SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PROPTIMING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) >= 3 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((((((SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PROPTIMING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) >= 4 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((((((((SCIP_PROPTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_PROPTIMING) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_PROPTIMING) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PROPTIMING, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PROPTIMING) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PROPTIMING, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PROPTIMING) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_PROPTIMING) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((SCIP_PROPTIMING)-1)*(((((SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_PROPTIMING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) ((((((SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_PROPTIMING) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((SCIP_PROPTIMING)-1)*(((((((SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PROPTIMING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) ((((((((SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_PROPTIMING) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) (((SCIP_PROPTIMING)-1)*(((((((((SCIP_PROPTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PROPTIMING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PROPTIMING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PROPTIMING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PROPTIMING) ((((((((((SCIP_PROPTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PROPTIMING)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_PROPTIMING) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PROPTIMING, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PROPTIMING) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PROPTIMING, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_PROPTIMING val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_PROPTIMING) -1;
}
} else {
SCIP_PROPTIMING val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_PROPTIMING) -1;
val = __Pyx_PyInt_As_SCIP_PROPTIMING(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_PROPTIMING");
return (SCIP_PROPTIMING) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_PROPTIMING");
return (SCIP_PROPTIMING) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_PRESOLTIMING __Pyx_PyInt_As_SCIP_PRESOLTIMING(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PRESOLTIMING neg_one = (SCIP_PRESOLTIMING) -1, const_zero = (SCIP_PRESOLTIMING) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_PRESOLTIMING) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_PRESOLTIMING) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PRESOLTIMING) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_PRESOLTIMING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) >= 2 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((((SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PRESOLTIMING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) >= 3 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((((((SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PRESOLTIMING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) >= 4 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((((((((SCIP_PRESOLTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_PRESOLTIMING) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_PRESOLTIMING) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PRESOLTIMING, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PRESOLTIMING) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PRESOLTIMING, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PRESOLTIMING) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((SCIP_PRESOLTIMING)-1)*(((((SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_PRESOLTIMING) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) ((((((SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((SCIP_PRESOLTIMING)-1)*(((((((SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PRESOLTIMING) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) ((((((((SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) (((SCIP_PRESOLTIMING)-1)*(((((((((SCIP_PRESOLTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PRESOLTIMING) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PRESOLTIMING, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PRESOLTIMING) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PRESOLTIMING) ((((((((((SCIP_PRESOLTIMING)digits[3]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[2]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[1]) << PyLong_SHIFT) | (SCIP_PRESOLTIMING)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_PRESOLTIMING) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PRESOLTIMING, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PRESOLTIMING) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PRESOLTIMING, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_PRESOLTIMING val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_PRESOLTIMING) -1;
}
} else {
SCIP_PRESOLTIMING val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_PRESOLTIMING) -1;
val = __Pyx_PyInt_As_SCIP_PRESOLTIMING(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_PRESOLTIMING");
return (SCIP_PRESOLTIMING) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_PRESOLTIMING");
return (SCIP_PRESOLTIMING) -1;
}
/* CIntFromPy */
static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(unsigned int) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(unsigned int, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (unsigned int) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (unsigned int) 0;
case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, digits[0])
case 2:
if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) >= 2 * PyLong_SHIFT) {
return (unsigned int) (((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) >= 3 * PyLong_SHIFT) {
return (unsigned int) (((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) >= 4 * PyLong_SHIFT) {
return (unsigned int) (((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (unsigned int) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(unsigned int) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (unsigned int) 0;
case -1: __PYX_VERIFY_RETURN_INT(unsigned int, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, +digits[0])
case -2:
if (8 * sizeof(unsigned int) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
return (unsigned int) (((unsigned int)-1)*(((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
return (unsigned int) ((((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
return (unsigned int) (((unsigned int)-1)*(((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
return (unsigned int) ((((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) {
return (unsigned int) (((unsigned int)-1)*(((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) {
return (unsigned int) ((((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
}
}
break;
}
#endif
if (sizeof(unsigned int) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(unsigned int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(unsigned int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
unsigned int val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (unsigned int) -1;
}
} else {
unsigned int val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (unsigned int) -1;
val = __Pyx_PyInt_As_unsigned_int(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to unsigned int");
return (unsigned int) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned int");
return (unsigned int) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_BRANCHDIR __Pyx_PyInt_As_SCIP_BRANCHDIR(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_BRANCHDIR neg_one = (SCIP_BRANCHDIR) -1, const_zero = (SCIP_BRANCHDIR) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_BRANCHDIR) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_BRANCHDIR) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_BRANCHDIR) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_BRANCHDIR) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) >= 2 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((((SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_BRANCHDIR) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) >= 3 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((((((SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_BRANCHDIR) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) >= 4 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((((((((SCIP_BRANCHDIR)digits[3]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_BRANCHDIR) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_BRANCHDIR) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BRANCHDIR, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BRANCHDIR) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BRANCHDIR, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_BRANCHDIR) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((SCIP_BRANCHDIR)-1)*(((((SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_BRANCHDIR) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) ((((((SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((SCIP_BRANCHDIR)-1)*(((((((SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_BRANCHDIR) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) ((((((((SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) (((SCIP_BRANCHDIR)-1)*(((((((((SCIP_BRANCHDIR)digits[3]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_BRANCHDIR) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_BRANCHDIR, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_BRANCHDIR) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_BRANCHDIR) ((((((((((SCIP_BRANCHDIR)digits[3]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[2]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[1]) << PyLong_SHIFT) | (SCIP_BRANCHDIR)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_BRANCHDIR) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BRANCHDIR, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_BRANCHDIR) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_BRANCHDIR, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_BRANCHDIR val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_BRANCHDIR) -1;
}
} else {
SCIP_BRANCHDIR val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_BRANCHDIR) -1;
val = __Pyx_PyInt_As_SCIP_BRANCHDIR(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_BRANCHDIR");
return (SCIP_BRANCHDIR) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_BRANCHDIR");
return (SCIP_BRANCHDIR) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_EVENTTYPE __Pyx_PyInt_As_SCIP_EVENTTYPE(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_EVENTTYPE neg_one = (SCIP_EVENTTYPE) -1, const_zero = (SCIP_EVENTTYPE) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_EVENTTYPE) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_EVENTTYPE) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_EVENTTYPE) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_EVENTTYPE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) >= 2 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((((SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_EVENTTYPE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) >= 3 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((((((SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_EVENTTYPE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) >= 4 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((((((((SCIP_EVENTTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_EVENTTYPE) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_EVENTTYPE) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EVENTTYPE, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EVENTTYPE) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EVENTTYPE, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_EVENTTYPE) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((SCIP_EVENTTYPE)-1)*(((((SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_EVENTTYPE) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) ((((((SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((SCIP_EVENTTYPE)-1)*(((((((SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_EVENTTYPE) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) ((((((((SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) (((SCIP_EVENTTYPE)-1)*(((((((((SCIP_EVENTTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_EVENTTYPE) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_EVENTTYPE, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_EVENTTYPE) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_EVENTTYPE) ((((((((((SCIP_EVENTTYPE)digits[3]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[2]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[1]) << PyLong_SHIFT) | (SCIP_EVENTTYPE)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_EVENTTYPE) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EVENTTYPE, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_EVENTTYPE) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_EVENTTYPE, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_EVENTTYPE val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_EVENTTYPE) -1;
}
} else {
SCIP_EVENTTYPE val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_EVENTTYPE) -1;
val = __Pyx_PyInt_As_SCIP_EVENTTYPE(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_EVENTTYPE");
return (SCIP_EVENTTYPE) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_EVENTTYPE");
return (SCIP_EVENTTYPE) -1;
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_Longint __Pyx_PyInt_As_SCIP_Longint(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_Longint neg_one = (SCIP_Longint) -1, const_zero = (SCIP_Longint) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_Longint) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_Longint) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_Longint) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_Longint, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_Longint) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) >= 2 * PyLong_SHIFT) {
return (SCIP_Longint) (((((SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_Longint) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) >= 3 * PyLong_SHIFT) {
return (SCIP_Longint) (((((((SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_Longint) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) >= 4 * PyLong_SHIFT) {
return (SCIP_Longint) (((((((((SCIP_Longint)digits[3]) << PyLong_SHIFT) | (SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_Longint) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_Longint) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_Longint, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_Longint) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_Longint, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_Longint) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_Longint, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_Longint, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_Longint) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_Longint) (((SCIP_Longint)-1)*(((((SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_Longint) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_Longint) ((((((SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_Longint) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_Longint) (((SCIP_Longint)-1)*(((((((SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_Longint) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_Longint) ((((((((SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_Longint) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_Longint) (((SCIP_Longint)-1)*(((((((((SCIP_Longint)digits[3]) << PyLong_SHIFT) | (SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_Longint) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_Longint, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_Longint) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_Longint) ((((((((((SCIP_Longint)digits[3]) << PyLong_SHIFT) | (SCIP_Longint)digits[2]) << PyLong_SHIFT) | (SCIP_Longint)digits[1]) << PyLong_SHIFT) | (SCIP_Longint)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_Longint) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_Longint, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_Longint) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_Longint, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_Longint val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_Longint) -1;
}
} else {
SCIP_Longint val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_Longint) -1;
val = __Pyx_PyInt_As_SCIP_Longint(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_Longint");
return (SCIP_Longint) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_Longint");
return (SCIP_Longint) -1;
}
/* CIntFromPy */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const char neg_one = (char) -1, const_zero = (char) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(char) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (char) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0])
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) {
return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) {
return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) {
return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (char) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(char) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0])
case -2:
if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
}
#endif
if (sizeof(char) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
char val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (char) -1;
}
} else {
char val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (char) -1;
val = __Pyx_PyInt_As_char(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to char");
return (char) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to char");
return (char) -1;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_char(char value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const char neg_one = (char) -1, const_zero = (char) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(char) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(char) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(char) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(char),
little, !is_unsigned);
}
}
/* CIntFromPy */
static CYTHON_INLINE SCIP_PARAMEMPHASIS __Pyx_PyInt_As_SCIP_PARAMEMPHASIS(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const SCIP_PARAMEMPHASIS neg_one = (SCIP_PARAMEMPHASIS) -1, const_zero = (SCIP_PARAMEMPHASIS) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(SCIP_PARAMEMPHASIS) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (SCIP_PARAMEMPHASIS) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PARAMEMPHASIS) 0;
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, digit, digits[0])
case 2:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) >= 2 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((((SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) >= 3 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((((((SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) >= 4 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((((((((SCIP_PARAMEMPHASIS)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (SCIP_PARAMEMPHASIS) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMEMPHASIS, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMEMPHASIS, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (SCIP_PARAMEMPHASIS) 0;
case -1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, digit, +digits[0])
case -2:
if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((SCIP_PARAMEMPHASIS)-1)*(((((SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 2 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) ((((((SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((SCIP_PARAMEMPHASIS)-1)*(((((((SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 3 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) ((((((((SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) (((SCIP_PARAMEMPHASIS)-1)*(((((((((SCIP_PARAMEMPHASIS)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(SCIP_PARAMEMPHASIS) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(SCIP_PARAMEMPHASIS, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(SCIP_PARAMEMPHASIS) - 1 > 4 * PyLong_SHIFT) {
return (SCIP_PARAMEMPHASIS) ((((((((((SCIP_PARAMEMPHASIS)digits[3]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[2]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[1]) << PyLong_SHIFT) | (SCIP_PARAMEMPHASIS)digits[0])));
}
}
break;
}
#endif
if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMEMPHASIS, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(SCIP_PARAMEMPHASIS) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(SCIP_PARAMEMPHASIS, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
SCIP_PARAMEMPHASIS val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (SCIP_PARAMEMPHASIS) -1;
}
} else {
SCIP_PARAMEMPHASIS val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (SCIP_PARAMEMPHASIS) -1;
val = __Pyx_PyInt_As_SCIP_PARAMEMPHASIS(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to SCIP_PARAMEMPHASIS");
return (SCIP_PARAMEMPHASIS) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to SCIP_PARAMEMPHASIS");
return (SCIP_PARAMEMPHASIS) -1;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(npy_int32) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(npy_int32) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(npy_int32) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(npy_int32),
little, !is_unsigned);
}
}
/* CIntFromPy */
static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) {
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wconversion"
#endif
const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0;
#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
#pragma GCC diagnostic pop
#endif
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(npy_int32) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (npy_int32) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (npy_int32) 0;
case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0])
case 2:
if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) {
return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) {
return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) {
return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (npy_int32) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(npy_int32) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (npy_int32) 0;
case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0])
case -2:
if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) {
return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) {
return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) {
return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) {
return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) {
return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) {
return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])));
}
}
break;
}
#endif
if (sizeof(npy_int32) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
npy_int32 val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (npy_int32) -1;
}
} else {
npy_int32 val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (npy_int32) -1;
val = __Pyx_PyInt_As_npy_int32(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to npy_int32");
return (npy_int32) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to npy_int32");
return (npy_int32) -1;
}
/* FastTypeChecks */
#if CYTHON_COMPILING_IN_CPYTHON
static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) {
while (a) {
a = a->tp_base;
if (a == b)
return 1;
}
return b == &PyBaseObject_Type;
}
static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) {
PyObject *mro;
if (a == b) return 1;
mro = a->tp_mro;
if (likely(mro)) {
Py_ssize_t i, n;
n = PyTuple_GET_SIZE(mro);
for (i = 0; i < n; i++) {
if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b)
return 1;
}
return 0;
}
return __Pyx_InBases(a, b);
}
#if PY_MAJOR_VERSION == 2
static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) {
PyObject *exception, *value, *tb;
int res;
__Pyx_PyThreadState_declare
__Pyx_PyThreadState_assign
__Pyx_ErrFetch(&exception, &value, &tb);
res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0;
if (unlikely(res == -1)) {
PyErr_WriteUnraisable(err);
res = 0;
}
if (!res) {
res = PyObject_IsSubclass(err, exc_type2);
if (unlikely(res == -1)) {
PyErr_WriteUnraisable(err);
res = 0;
}
}
__Pyx_ErrRestore(exception, value, tb);
return res;
}
#else
static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) {
int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0;
if (!res) {
res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2);
}
return res;
}
#endif
static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) {
Py_ssize_t i, n;
assert(PyExceptionClass_Check(exc_type));
n = PyTuple_GET_SIZE(tuple);
#if PY_MAJOR_VERSION >= 3
for (i=0; i<n; i++) {
if (exc_type == PyTuple_GET_ITEM(tuple, i)) return 1;
}
#endif
for (i=0; i<n; i++) {
PyObject *t = PyTuple_GET_ITEM(tuple, i);
#if PY_MAJOR_VERSION < 3
if (likely(exc_type == t)) return 1;
#endif
if (likely(PyExceptionClass_Check(t))) {
if (__Pyx_inner_PyErr_GivenExceptionMatches2(exc_type, NULL, t)) return 1;
} else {
}
}
return 0;
}
static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject* exc_type) {
if (likely(err == exc_type)) return 1;
if (likely(PyExceptionClass_Check(err))) {
if (likely(PyExceptionClass_Check(exc_type))) {
return __Pyx_inner_PyErr_GivenExceptionMatches2(err, NULL, exc_type);
} else if (likely(PyTuple_Check(exc_type))) {
return __Pyx_PyErr_GivenExceptionMatchesTuple(err, exc_type);
} else {
}
}
return PyErr_GivenExceptionMatches(err, exc_type);
}
static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *exc_type1, PyObject *exc_type2) {
assert(PyExceptionClass_Check(exc_type1));
assert(PyExceptionClass_Check(exc_type2));
if (likely(err == exc_type1 || err == exc_type2)) return 1;
if (likely(PyExceptionClass_Check(err))) {
return __Pyx_inner_PyErr_GivenExceptionMatches2(err, exc_type1, exc_type2);
}
return (PyErr_GivenExceptionMatches(err, exc_type1) || PyErr_GivenExceptionMatches(err, exc_type2));
}
#endif
/* SwapException */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
#if CYTHON_USE_EXC_INFO_STACK
_PyErr_StackItem *exc_info = tstate->exc_info;
tmp_type = exc_info->exc_type;
tmp_value = exc_info->exc_value;
tmp_tb = exc_info->exc_traceback;
exc_info->exc_type = *type;
exc_info->exc_value = *value;
exc_info->exc_traceback = *tb;
#else
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = *type;
tstate->exc_value = *value;
tstate->exc_traceback = *tb;
#endif
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
PyErr_SetExcInfo(*type, *value, *tb);
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#endif
/* CoroutineBase */
#include <structmember.h>
#include <frameobject.h>
#define __Pyx_Coroutine_Undelegate(gen) Py_CLEAR((gen)->yieldfrom)
static int __Pyx_PyGen__FetchStopIterationValue(CYTHON_UNUSED PyThreadState *__pyx_tstate, PyObject **pvalue) {
PyObject *et, *ev, *tb;
PyObject *value = NULL;
__Pyx_ErrFetch(&et, &ev, &tb);
if (!et) {
Py_XDECREF(tb);
Py_XDECREF(ev);
Py_INCREF(Py_None);
*pvalue = Py_None;
return 0;
}
if (likely(et == PyExc_StopIteration)) {
if (!ev) {
Py_INCREF(Py_None);
value = Py_None;
}
#if PY_VERSION_HEX >= 0x030300A0
else if (Py_TYPE(ev) == (PyTypeObject*)PyExc_StopIteration) {
value = ((PyStopIterationObject *)ev)->value;
Py_INCREF(value);
Py_DECREF(ev);
}
#endif
else if (unlikely(PyTuple_Check(ev))) {
if (PyTuple_GET_SIZE(ev) >= 1) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
value = PyTuple_GET_ITEM(ev, 0);
Py_INCREF(value);
#else
value = PySequence_ITEM(ev, 0);
#endif
} else {
Py_INCREF(Py_None);
value = Py_None;
}
Py_DECREF(ev);
}
else if (!__Pyx_TypeCheck(ev, (PyTypeObject*)PyExc_StopIteration)) {
value = ev;
}
if (likely(value)) {
Py_XDECREF(tb);
Py_DECREF(et);
*pvalue = value;
return 0;
}
} else if (!__Pyx_PyErr_GivenExceptionMatches(et, PyExc_StopIteration)) {
__Pyx_ErrRestore(et, ev, tb);
return -1;
}
PyErr_NormalizeException(&et, &ev, &tb);
if (unlikely(!PyObject_TypeCheck(ev, (PyTypeObject*)PyExc_StopIteration))) {
__Pyx_ErrRestore(et, ev, tb);
return -1;
}
Py_XDECREF(tb);
Py_DECREF(et);
#if PY_VERSION_HEX >= 0x030300A0
value = ((PyStopIterationObject *)ev)->value;
Py_INCREF(value);
Py_DECREF(ev);
#else
{
PyObject* args = __Pyx_PyObject_GetAttrStr(ev, __pyx_n_s_args);
Py_DECREF(ev);
if (likely(args)) {
value = PySequence_GetItem(args, 0);
Py_DECREF(args);
}
if (unlikely(!value)) {
__Pyx_ErrRestore(NULL, NULL, NULL);
Py_INCREF(Py_None);
value = Py_None;
}
}
#endif
*pvalue = value;
return 0;
}
static CYTHON_INLINE
void __Pyx_Coroutine_ExceptionClear(__Pyx_ExcInfoStruct *exc_state) {
PyObject *t, *v, *tb;
t = exc_state->exc_type;
v = exc_state->exc_value;
tb = exc_state->exc_traceback;
exc_state->exc_type = NULL;
exc_state->exc_value = NULL;
exc_state->exc_traceback = NULL;
Py_XDECREF(t);
Py_XDECREF(v);
Py_XDECREF(tb);
}
#define __Pyx_Coroutine_AlreadyRunningError(gen) (__Pyx__Coroutine_AlreadyRunningError(gen), (PyObject*)NULL)
static void __Pyx__Coroutine_AlreadyRunningError(CYTHON_UNUSED __pyx_CoroutineObject *gen) {
const char *msg;
if ((0)) {
#ifdef __Pyx_Coroutine_USED
} else if (__Pyx_Coroutine_Check((PyObject*)gen)) {
msg = "coroutine already executing";
#endif
#ifdef __Pyx_AsyncGen_USED
} else if (__Pyx_AsyncGen_CheckExact((PyObject*)gen)) {
msg = "async generator already executing";
#endif
} else {
msg = "generator already executing";
}
PyErr_SetString(PyExc_ValueError, msg);
}
#define __Pyx_Coroutine_NotStartedError(gen) (__Pyx__Coroutine_NotStartedError(gen), (PyObject*)NULL)
static void __Pyx__Coroutine_NotStartedError(CYTHON_UNUSED PyObject *gen) {
const char *msg;
if ((0)) {
#ifdef __Pyx_Coroutine_USED
} else if (__Pyx_Coroutine_Check(gen)) {
msg = "can't send non-None value to a just-started coroutine";
#endif
#ifdef __Pyx_AsyncGen_USED
} else if (__Pyx_AsyncGen_CheckExact(gen)) {
msg = "can't send non-None value to a just-started async generator";
#endif
} else {
msg = "can't send non-None value to a just-started generator";
}
PyErr_SetString(PyExc_TypeError, msg);
}
#define __Pyx_Coroutine_AlreadyTerminatedError(gen, value, closing) (__Pyx__Coroutine_AlreadyTerminatedError(gen, value, closing), (PyObject*)NULL)
static void __Pyx__Coroutine_AlreadyTerminatedError(CYTHON_UNUSED PyObject *gen, PyObject *value, CYTHON_UNUSED int closing) {
#ifdef __Pyx_Coroutine_USED
if (!closing && __Pyx_Coroutine_Check(gen)) {
PyErr_SetString(PyExc_RuntimeError, "cannot reuse already awaited coroutine");
} else
#endif
if (value) {
#ifdef __Pyx_AsyncGen_USED
if (__Pyx_AsyncGen_CheckExact(gen))
PyErr_SetNone(__Pyx_PyExc_StopAsyncIteration);
else
#endif
PyErr_SetNone(PyExc_StopIteration);
}
}
static
PyObject *__Pyx_Coroutine_SendEx(__pyx_CoroutineObject *self, PyObject *value, int closing) {
__Pyx_PyThreadState_declare
PyThreadState *tstate;
__Pyx_ExcInfoStruct *exc_state;
PyObject *retval;
assert(!self->is_running);
if (unlikely(self->resume_label == 0)) {
if (unlikely(value && value != Py_None)) {
return __Pyx_Coroutine_NotStartedError((PyObject*)self);
}
}
if (unlikely(self->resume_label == -1)) {
return __Pyx_Coroutine_AlreadyTerminatedError((PyObject*)self, value, closing);
}
#if CYTHON_FAST_THREAD_STATE
__Pyx_PyThreadState_assign
tstate = __pyx_tstate;
#else
tstate = __Pyx_PyThreadState_Current;
#endif
exc_state = &self->gi_exc_state;
if (exc_state->exc_type) {
#if CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_PYSTON
#else
if (exc_state->exc_traceback) {
PyTracebackObject *tb = (PyTracebackObject *) exc_state->exc_traceback;
PyFrameObject *f = tb->tb_frame;
Py_XINCREF(tstate->frame);
assert(f->f_back == NULL);
f->f_back = tstate->frame;
}
#endif
}
#if CYTHON_USE_EXC_INFO_STACK
exc_state->previous_item = tstate->exc_info;
tstate->exc_info = exc_state;
#else
if (exc_state->exc_type) {
__Pyx_ExceptionSwap(&exc_state->exc_type, &exc_state->exc_value, &exc_state->exc_traceback);
} else {
__Pyx_Coroutine_ExceptionClear(exc_state);
__Pyx_ExceptionSave(&exc_state->exc_type, &exc_state->exc_value, &exc_state->exc_traceback);
}
#endif
self->is_running = 1;
retval = self->body((PyObject *) self, tstate, value);
self->is_running = 0;
#if CYTHON_USE_EXC_INFO_STACK
exc_state = &self->gi_exc_state;
tstate->exc_info = exc_state->previous_item;
exc_state->previous_item = NULL;
__Pyx_Coroutine_ResetFrameBackpointer(exc_state);
#endif
return retval;
}
static CYTHON_INLINE void __Pyx_Coroutine_ResetFrameBackpointer(__Pyx_ExcInfoStruct *exc_state) {
PyObject *exc_tb = exc_state->exc_traceback;
if (likely(exc_tb)) {
#if CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_PYSTON
#else
PyTracebackObject *tb = (PyTracebackObject *) exc_tb;
PyFrameObject *f = tb->tb_frame;
Py_CLEAR(f->f_back);
#endif
}
}
static CYTHON_INLINE
PyObject *__Pyx_Coroutine_MethodReturn(CYTHON_UNUSED PyObject* gen, PyObject *retval) {
if (unlikely(!retval)) {
__Pyx_PyThreadState_declare
__Pyx_PyThreadState_assign
if (!__Pyx_PyErr_Occurred()) {
PyObject *exc = PyExc_StopIteration;
#ifdef __Pyx_AsyncGen_USED
if (__Pyx_AsyncGen_CheckExact(gen))
exc = __Pyx_PyExc_StopAsyncIteration;
#endif
__Pyx_PyErr_SetNone(exc);
}
}
return retval;
}
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03030000 && (defined(__linux__) || PY_VERSION_HEX >= 0x030600B3)
static CYTHON_INLINE
PyObject *__Pyx_PyGen_Send(PyGenObject *gen, PyObject *arg) {
#if PY_VERSION_HEX <= 0x030A00A1
return _PyGen_Send(gen, arg);
#else
PyObject *result;
if (PyIter_Send((PyObject*)gen, arg ? arg : Py_None, &result) == PYGEN_RETURN) {
if (PyAsyncGen_CheckExact(gen)) {
assert(result == Py_None);
PyErr_SetNone(PyExc_StopAsyncIteration);
}
else if (result == Py_None) {
PyErr_SetNone(PyExc_StopIteration);
}
else {
_PyGen_SetStopIterationValue(result);
}
Py_CLEAR(result);
}
return result;
#endif
}
#endif
static CYTHON_INLINE
PyObject *__Pyx_Coroutine_FinishDelegation(__pyx_CoroutineObject *gen) {
PyObject *ret;
PyObject *val = NULL;
__Pyx_Coroutine_Undelegate(gen);
__Pyx_PyGen__FetchStopIterationValue(__Pyx_PyThreadState_Current, &val);
ret = __Pyx_Coroutine_SendEx(gen, val, 0);
Py_XDECREF(val);
return ret;
}
static PyObject *__Pyx_Coroutine_Send(PyObject *self, PyObject *value) {
PyObject *retval;
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject*) self;
PyObject *yf = gen->yieldfrom;
if (unlikely(gen->is_running))
return __Pyx_Coroutine_AlreadyRunningError(gen);
if (yf) {
PyObject *ret;
gen->is_running = 1;
#ifdef __Pyx_Generator_USED
if (__Pyx_Generator_CheckExact(yf)) {
ret = __Pyx_Coroutine_Send(yf, value);
} else
#endif
#ifdef __Pyx_Coroutine_USED
if (__Pyx_Coroutine_Check(yf)) {
ret = __Pyx_Coroutine_Send(yf, value);
} else
#endif
#ifdef __Pyx_AsyncGen_USED
if (__pyx_PyAsyncGenASend_CheckExact(yf)) {
ret = __Pyx_async_gen_asend_send(yf, value);
} else
#endif
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03030000 && (defined(__linux__) || PY_VERSION_HEX >= 0x030600B3)
if (PyGen_CheckExact(yf)) {
ret = __Pyx_PyGen_Send((PyGenObject*)yf, value == Py_None ? NULL : value);
} else
#endif
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03050000 && defined(PyCoro_CheckExact) && (defined(__linux__) || PY_VERSION_HEX >= 0x030600B3)
if (PyCoro_CheckExact(yf)) {
ret = __Pyx_PyGen_Send((PyGenObject*)yf, value == Py_None ? NULL : value);
} else
#endif
{
if (value == Py_None)
ret = Py_TYPE(yf)->tp_iternext(yf);
else
ret = __Pyx_PyObject_CallMethod1(yf, __pyx_n_s_send, value);
}
gen->is_running = 0;
if (likely(ret)) {
return ret;
}
retval = __Pyx_Coroutine_FinishDelegation(gen);
} else {
retval = __Pyx_Coroutine_SendEx(gen, value, 0);
}
return __Pyx_Coroutine_MethodReturn(self, retval);
}
static int __Pyx_Coroutine_CloseIter(__pyx_CoroutineObject *gen, PyObject *yf) {
PyObject *retval = NULL;
int err = 0;
#ifdef __Pyx_Generator_USED
if (__Pyx_Generator_CheckExact(yf)) {
retval = __Pyx_Coroutine_Close(yf);
if (!retval)
return -1;
} else
#endif
#ifdef __Pyx_Coroutine_USED
if (__Pyx_Coroutine_Check(yf)) {
retval = __Pyx_Coroutine_Close(yf);
if (!retval)
return -1;
} else
if (__Pyx_CoroutineAwait_CheckExact(yf)) {
retval = __Pyx_CoroutineAwait_Close((__pyx_CoroutineAwaitObject*)yf, NULL);
if (!retval)
return -1;
} else
#endif
#ifdef __Pyx_AsyncGen_USED
if (__pyx_PyAsyncGenASend_CheckExact(yf)) {
retval = __Pyx_async_gen_asend_close(yf, NULL);
} else
if (__pyx_PyAsyncGenAThrow_CheckExact(yf)) {
retval = __Pyx_async_gen_athrow_close(yf, NULL);
} else
#endif
{
PyObject *meth;
gen->is_running = 1;
meth = __Pyx_PyObject_GetAttrStr(yf, __pyx_n_s_close);
if (unlikely(!meth)) {
if (!PyErr_ExceptionMatches(PyExc_AttributeError)) {
PyErr_WriteUnraisable(yf);
}
PyErr_Clear();
} else {
retval = PyObject_CallFunction(meth, NULL);
Py_DECREF(meth);
if (!retval)
err = -1;
}
gen->is_running = 0;
}
Py_XDECREF(retval);
return err;
}
static PyObject *__Pyx_Generator_Next(PyObject *self) {
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject*) self;
PyObject *yf = gen->yieldfrom;
if (unlikely(gen->is_running))
return __Pyx_Coroutine_AlreadyRunningError(gen);
if (yf) {
PyObject *ret;
gen->is_running = 1;
#ifdef __Pyx_Generator_USED
if (__Pyx_Generator_CheckExact(yf)) {
ret = __Pyx_Generator_Next(yf);
} else
#endif
#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03030000 && (defined(__linux__) || PY_VERSION_HEX >= 0x030600B3)
if (PyGen_CheckExact(yf)) {
ret = __Pyx_PyGen_Send((PyGenObject*)yf, NULL);
} else
#endif
#ifdef __Pyx_Coroutine_USED
if (__Pyx_Coroutine_Check(yf)) {
ret = __Pyx_Coroutine_Send(yf, Py_None);
} else
#endif
ret = Py_TYPE(yf)->tp_iternext(yf);
gen->is_running = 0;
if (likely(ret)) {
return ret;
}
return __Pyx_Coroutine_FinishDelegation(gen);
}
return __Pyx_Coroutine_SendEx(gen, Py_None, 0);
}
static PyObject *__Pyx_Coroutine_Close_Method(PyObject *self, CYTHON_UNUSED PyObject *arg) {
return __Pyx_Coroutine_Close(self);
}
static PyObject *__Pyx_Coroutine_Close(PyObject *self) {
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self;
PyObject *retval, *raised_exception;
PyObject *yf = gen->yieldfrom;
int err = 0;
if (unlikely(gen->is_running))
return __Pyx_Coroutine_AlreadyRunningError(gen);
if (yf) {
Py_INCREF(yf);
err = __Pyx_Coroutine_CloseIter(gen, yf);
__Pyx_Coroutine_Undelegate(gen);
Py_DECREF(yf);
}
if (err == 0)
PyErr_SetNone(PyExc_GeneratorExit);
retval = __Pyx_Coroutine_SendEx(gen, NULL, 1);
if (unlikely(retval)) {
const char *msg;
Py_DECREF(retval);
if ((0)) {
#ifdef __Pyx_Coroutine_USED
} else if (__Pyx_Coroutine_Check(self)) {
msg = "coroutine ignored GeneratorExit";
#endif
#ifdef __Pyx_AsyncGen_USED
} else if (__Pyx_AsyncGen_CheckExact(self)) {
#if PY_VERSION_HEX < 0x03060000
msg = "async generator ignored GeneratorExit - might require Python 3.6+ finalisation (PEP 525)";
#else
msg = "async generator ignored GeneratorExit";
#endif
#endif
} else {
msg = "generator ignored GeneratorExit";
}
PyErr_SetString(PyExc_RuntimeError, msg);
return NULL;
}
raised_exception = PyErr_Occurred();
if (likely(!raised_exception || __Pyx_PyErr_GivenExceptionMatches2(raised_exception, PyExc_GeneratorExit, PyExc_StopIteration))) {
if (raised_exception) PyErr_Clear();
Py_INCREF(Py_None);
return Py_None;
}
return NULL;
}
static PyObject *__Pyx__Coroutine_Throw(PyObject *self, PyObject *typ, PyObject *val, PyObject *tb,
PyObject *args, int close_on_genexit) {
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self;
PyObject *yf = gen->yieldfrom;
if (unlikely(gen->is_running))
return __Pyx_Coroutine_AlreadyRunningError(gen);
if (yf) {
PyObject *ret;
Py_INCREF(yf);
if (__Pyx_PyErr_GivenExceptionMatches(typ, PyExc_GeneratorExit) && close_on_genexit) {
int err = __Pyx_Coroutine_CloseIter(gen, yf);
Py_DECREF(yf);
__Pyx_Coroutine_Undelegate(gen);
if (err < 0)
return __Pyx_Coroutine_MethodReturn(self, __Pyx_Coroutine_SendEx(gen, NULL, 0));
goto throw_here;
}
gen->is_running = 1;
if (0
#ifdef __Pyx_Generator_USED
|| __Pyx_Generator_CheckExact(yf)
#endif
#ifdef __Pyx_Coroutine_USED
|| __Pyx_Coroutine_Check(yf)
#endif
) {
ret = __Pyx__Coroutine_Throw(yf, typ, val, tb, args, close_on_genexit);
#ifdef __Pyx_Coroutine_USED
} else if (__Pyx_CoroutineAwait_CheckExact(yf)) {
ret = __Pyx__Coroutine_Throw(((__pyx_CoroutineAwaitObject*)yf)->coroutine, typ, val, tb, args, close_on_genexit);
#endif
} else {
PyObject *meth = __Pyx_PyObject_GetAttrStr(yf, __pyx_n_s_throw);
if (unlikely(!meth)) {
Py_DECREF(yf);
if (!PyErr_ExceptionMatches(PyExc_AttributeError)) {
gen->is_running = 0;
return NULL;
}
PyErr_Clear();
__Pyx_Coroutine_Undelegate(gen);
gen->is_running = 0;
goto throw_here;
}
if (likely(args)) {
ret = PyObject_CallObject(meth, args);
} else {
ret = PyObject_CallFunctionObjArgs(meth, typ, val, tb, NULL);
}
Py_DECREF(meth);
}
gen->is_running = 0;
Py_DECREF(yf);
if (!ret) {
ret = __Pyx_Coroutine_FinishDelegation(gen);
}
return __Pyx_Coroutine_MethodReturn(self, ret);
}
throw_here:
__Pyx_Raise(typ, val, tb, NULL);
return __Pyx_Coroutine_MethodReturn(self, __Pyx_Coroutine_SendEx(gen, NULL, 0));
}
static PyObject *__Pyx_Coroutine_Throw(PyObject *self, PyObject *args) {
PyObject *typ;
PyObject *val = NULL;
PyObject *tb = NULL;
if (!PyArg_UnpackTuple(args, (char *)"throw", 1, 3, &typ, &val, &tb))
return NULL;
return __Pyx__Coroutine_Throw(self, typ, val, tb, args, 1);
}
static CYTHON_INLINE int __Pyx_Coroutine_traverse_excstate(__Pyx_ExcInfoStruct *exc_state, visitproc visit, void *arg) {
Py_VISIT(exc_state->exc_type);
Py_VISIT(exc_state->exc_value);
Py_VISIT(exc_state->exc_traceback);
return 0;
}
static int __Pyx_Coroutine_traverse(__pyx_CoroutineObject *gen, visitproc visit, void *arg) {
Py_VISIT(gen->closure);
Py_VISIT(gen->classobj);
Py_VISIT(gen->yieldfrom);
return __Pyx_Coroutine_traverse_excstate(&gen->gi_exc_state, visit, arg);
}
static int __Pyx_Coroutine_clear(PyObject *self) {
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self;
Py_CLEAR(gen->closure);
Py_CLEAR(gen->classobj);
Py_CLEAR(gen->yieldfrom);
__Pyx_Coroutine_ExceptionClear(&gen->gi_exc_state);
#ifdef __Pyx_AsyncGen_USED
if (__Pyx_AsyncGen_CheckExact(self)) {
Py_CLEAR(((__pyx_PyAsyncGenObject*)gen)->ag_finalizer);
}
#endif
Py_CLEAR(gen->gi_code);
Py_CLEAR(gen->gi_frame);
Py_CLEAR(gen->gi_name);
Py_CLEAR(gen->gi_qualname);
Py_CLEAR(gen->gi_modulename);
return 0;
}
static void __Pyx_Coroutine_dealloc(PyObject *self) {
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self;
PyObject_GC_UnTrack(gen);
if (gen->gi_weakreflist != NULL)
PyObject_ClearWeakRefs(self);
if (gen->resume_label >= 0) {
PyObject_GC_Track(self);
#if PY_VERSION_HEX >= 0x030400a1 && CYTHON_USE_TP_FINALIZE
if (PyObject_CallFinalizerFromDealloc(self))
#else
Py_TYPE(gen)->tp_del(self);
if (Py_REFCNT(self) > 0)
#endif
{
return;
}
PyObject_GC_UnTrack(self);
}
#ifdef __Pyx_AsyncGen_USED
if (__Pyx_AsyncGen_CheckExact(self)) {
/* We have to handle this case for asynchronous generators
right here, because this code has to be between UNTRACK
and GC_Del. */
Py_CLEAR(((__pyx_PyAsyncGenObject*)self)->ag_finalizer);
}
#endif
__Pyx_Coroutine_clear(self);
PyObject_GC_Del(gen);
}
static void __Pyx_Coroutine_del(PyObject *self) {
PyObject *error_type, *error_value, *error_traceback;
__pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self;
__Pyx_PyThreadState_declare
if (gen->resume_label < 0) {
return;
}
#if !CYTHON_USE_TP_FINALIZE
assert(self->ob_refcnt == 0);
__Pyx_SET_REFCNT(self, 1);
#endif
__Pyx_PyThreadState_assign
__Pyx_ErrFetch(&error_type, &error_value, &error_traceback);
#ifdef __Pyx_AsyncGen_USED
if (__Pyx_AsyncGen_CheckExact(self)) {
__pyx_PyAsyncGenObject *agen = (__pyx_PyAsyncGenObject*)self;
PyObject *finalizer = agen->ag_finalizer;
if (finalizer && !agen->ag_closed) {
PyObject *res = __Pyx_PyObject_CallOneArg(finalizer, self);
if (unlikely(!res)) {
PyErr_WriteUnraisable(self);
} else {
Py_DECREF(res);
}
__Pyx_ErrRestore(error_type, error_value, error_traceback);
return;
}
}
#endif
if (unlikely(gen->resume_label == 0 && !error_value)) {
#ifdef __Pyx_Coroutine_USED
#ifdef __Pyx_Generator_USED
if (!__Pyx_Generator_CheckExact(self))
#endif
{
PyObject_GC_UnTrack(self);
#if PY_MAJOR_VERSION >= 3 || defined(PyErr_WarnFormat)
if (unlikely(PyErr_WarnFormat(PyExc_RuntimeWarning, 1, "coroutine '%.50S' was never awaited", gen->gi_qualname) < 0))
PyErr_WriteUnraisable(self);
#else
{PyObject *msg;
char *cmsg;
#if CYTHON_COMPILING_IN_PYPY
msg = NULL;
cmsg = (char*) "coroutine was never awaited";
#else
char *cname;
PyObject *qualname;
qualname = gen->gi_qualname;
cname = PyString_AS_STRING(qualname);
msg = PyString_FromFormat("coroutine '%.50s' was never awaited", cname);
if (unlikely(!msg)) {
PyErr_Clear();
cmsg = (char*) "coroutine was never awaited";
} else {
cmsg = PyString_AS_STRING(msg);
}
#endif
if (unlikely(PyErr_WarnEx(PyExc_RuntimeWarning, cmsg, 1) < 0))
PyErr_WriteUnraisable(self);
Py_XDECREF(msg);}
#endif
PyObject_GC_Track(self);
}
#endif
} else {
PyObject *res = __Pyx_Coroutine_Close(self);
if (unlikely(!res)) {
if (PyErr_Occurred())
PyErr_WriteUnraisable(self);
} else {
Py_DECREF(res);
}
}
__Pyx_ErrRestore(error_type, error_value, error_traceback);
#if !CYTHON_USE_TP_FINALIZE
assert(Py_REFCNT(self) > 0);
if (--self->ob_refcnt == 0) {
return;
}
{
Py_ssize_t refcnt = Py_REFCNT(self);
_Py_NewReference(self);
__Pyx_SET_REFCNT(self, refcnt);
}
#if CYTHON_COMPILING_IN_CPYTHON
assert(PyType_IS_GC(Py_TYPE(self)) &&
_Py_AS_GC(self)->gc.gc_refs != _PyGC_REFS_UNTRACKED);
_Py_DEC_REFTOTAL;
#endif
#ifdef COUNT_ALLOCS
--Py_TYPE(self)->tp_frees;
--Py_TYPE(self)->tp_allocs;
#endif
#endif
}
static PyObject *
__Pyx_Coroutine_get_name(__pyx_CoroutineObject *self, CYTHON_UNUSED void *context)
{
PyObject *name = self->gi_name;
if (unlikely(!name)) name = Py_None;
Py_INCREF(name);
return name;
}
static int
__Pyx_Coroutine_set_name(__pyx_CoroutineObject *self, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
if (unlikely(value == NULL || !PyUnicode_Check(value)))
#else
if (unlikely(value == NULL || !PyString_Check(value)))
#endif
{
PyErr_SetString(PyExc_TypeError,
"__name__ must be set to a string object");
return -1;
}
tmp = self->gi_name;
Py_INCREF(value);
self->gi_name = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_Coroutine_get_qualname(__pyx_CoroutineObject *self, CYTHON_UNUSED void *context)
{
PyObject *name = self->gi_qualname;
if (unlikely(!name)) name = Py_None;
Py_INCREF(name);
return name;
}
static int
__Pyx_Coroutine_set_qualname(__pyx_CoroutineObject *self, PyObject *value, CYTHON_UNUSED void *context)
{
PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
if (unlikely(value == NULL || !PyUnicode_Check(value)))
#else
if (unlikely(value == NULL || !PyString_Check(value)))
#endif
{
PyErr_SetString(PyExc_TypeError,
"__qualname__ must be set to a string object");
return -1;
}
tmp = self->gi_qualname;
Py_INCREF(value);
self->gi_qualname = value;
Py_XDECREF(tmp);
return 0;
}
static PyObject *
__Pyx_Coroutine_get_frame(__pyx_CoroutineObject *self, CYTHON_UNUSED void *context)
{
PyObject *frame = self->gi_frame;
if (!frame) {
if (unlikely(!self->gi_code)) {
Py_RETURN_NONE;
}
frame = (PyObject *) PyFrame_New(
PyThreadState_Get(), /*PyThreadState *tstate,*/
(PyCodeObject*) self->gi_code, /*PyCodeObject *code,*/
__pyx_d, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (unlikely(!frame))
return NULL;
self->gi_frame = frame;
}
Py_INCREF(frame);
return frame;
}
static __pyx_CoroutineObject *__Pyx__Coroutine_New(
PyTypeObject* type, __pyx_coroutine_body_t body, PyObject *code, PyObject *closure,
PyObject *name, PyObject *qualname, PyObject *module_name) {
__pyx_CoroutineObject *gen = PyObject_GC_New(__pyx_CoroutineObject, type);
if (unlikely(!gen))
return NULL;
return __Pyx__Coroutine_NewInit(gen, body, code, closure, name, qualname, module_name);
}
static __pyx_CoroutineObject *__Pyx__Coroutine_NewInit(
__pyx_CoroutineObject *gen, __pyx_coroutine_body_t body, PyObject *code, PyObject *closure,
PyObject *name, PyObject *qualname, PyObject *module_name) {
gen->body = body;
gen->closure = closure;
Py_XINCREF(closure);
gen->is_running = 0;
gen->resume_label = 0;
gen->classobj = NULL;
gen->yieldfrom = NULL;
gen->gi_exc_state.exc_type = NULL;
gen->gi_exc_state.exc_value = NULL;
gen->gi_exc_state.exc_traceback = NULL;
#if CYTHON_USE_EXC_INFO_STACK
gen->gi_exc_state.previous_item = NULL;
#endif
gen->gi_weakreflist = NULL;
Py_XINCREF(qualname);
gen->gi_qualname = qualname;
Py_XINCREF(name);
gen->gi_name = name;
Py_XINCREF(module_name);
gen->gi_modulename = module_name;
Py_XINCREF(code);
gen->gi_code = code;
gen->gi_frame = NULL;
PyObject_GC_Track(gen);
return gen;
}
/* PatchModuleWithCoroutine */
static PyObject* __Pyx_Coroutine_patch_module(PyObject* module, const char* py_code) {
#if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED)
int result;
PyObject *globals, *result_obj;
globals = PyDict_New(); if (unlikely(!globals)) goto ignore;
result = PyDict_SetItemString(globals, "_cython_coroutine_type",
#ifdef __Pyx_Coroutine_USED
(PyObject*)__pyx_CoroutineType);
#else
Py_None);
#endif
if (unlikely(result < 0)) goto ignore;
result = PyDict_SetItemString(globals, "_cython_generator_type",
#ifdef __Pyx_Generator_USED
(PyObject*)__pyx_GeneratorType);
#else
Py_None);
#endif
if (unlikely(result < 0)) goto ignore;
if (unlikely(PyDict_SetItemString(globals, "_module", module) < 0)) goto ignore;
if (unlikely(PyDict_SetItemString(globals, "__builtins__", __pyx_b) < 0)) goto ignore;
result_obj = PyRun_String(py_code, Py_file_input, globals, globals);
if (unlikely(!result_obj)) goto ignore;
Py_DECREF(result_obj);
Py_DECREF(globals);
return module;
ignore:
Py_XDECREF(globals);
PyErr_WriteUnraisable(module);
if (unlikely(PyErr_WarnEx(PyExc_RuntimeWarning, "Cython module failed to patch module with custom type", 1) < 0)) {
Py_DECREF(module);
module = NULL;
}
#else
py_code++;
#endif
return module;
}
/* PatchGeneratorABC */
#ifndef CYTHON_REGISTER_ABCS
#define CYTHON_REGISTER_ABCS 1
#endif
#if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED)
static PyObject* __Pyx_patch_abc_module(PyObject *module);
static PyObject* __Pyx_patch_abc_module(PyObject *module) {
module = __Pyx_Coroutine_patch_module(
module, ""
"if _cython_generator_type is not None:\n"
" try: Generator = _module.Generator\n"
" except AttributeError: pass\n"
" else: Generator.register(_cython_generator_type)\n"
"if _cython_coroutine_type is not None:\n"
" try: Coroutine = _module.Coroutine\n"
" except AttributeError: pass\n"
" else: Coroutine.register(_cython_coroutine_type)\n"
);
return module;
}
#endif
static int __Pyx_patch_abc(void) {
#if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED)
static int abc_patched = 0;
if (CYTHON_REGISTER_ABCS && !abc_patched) {
PyObject *module;
module = PyImport_ImportModule((PY_MAJOR_VERSION >= 3) ? "collections.abc" : "collections");
if (!module) {
PyErr_WriteUnraisable(NULL);
if (unlikely(PyErr_WarnEx(PyExc_RuntimeWarning,
((PY_MAJOR_VERSION >= 3) ?
"Cython module failed to register with collections.abc module" :
"Cython module failed to register with collections module"), 1) < 0)) {
return -1;
}
} else {
module = __Pyx_patch_abc_module(module);
abc_patched = 1;
if (unlikely(!module))
return -1;
Py_DECREF(module);
}
module = PyImport_ImportModule("backports_abc");
if (module) {
module = __Pyx_patch_abc_module(module);
Py_XDECREF(module);
}
if (!module) {
PyErr_Clear();
}
}
#else
if ((0)) __Pyx_Coroutine_patch_module(NULL, NULL);
#endif
return 0;
}
/* Generator */
static PyMethodDef __pyx_Generator_methods[] = {
{"send", (PyCFunction) __Pyx_Coroutine_Send, METH_O,
(char*) PyDoc_STR("send(arg) -> send 'arg' into generator,\nreturn next yielded value or raise StopIteration.")},
{"throw", (PyCFunction) __Pyx_Coroutine_Throw, METH_VARARGS,
(char*) PyDoc_STR("throw(typ[,val[,tb]]) -> raise exception in generator,\nreturn next yielded value or raise StopIteration.")},
{"close", (PyCFunction) __Pyx_Coroutine_Close_Method, METH_NOARGS,
(char*) PyDoc_STR("close() -> raise GeneratorExit inside generator.")},
{0, 0, 0, 0}
};
static PyMemberDef __pyx_Generator_memberlist[] = {
{(char *) "gi_running", T_BOOL, offsetof(__pyx_CoroutineObject, is_running), READONLY, NULL},
{(char*) "gi_yieldfrom", T_OBJECT, offsetof(__pyx_CoroutineObject, yieldfrom), READONLY,
(char*) PyDoc_STR("object being iterated by 'yield from', or None")},
{(char*) "gi_code", T_OBJECT, offsetof(__pyx_CoroutineObject, gi_code), READONLY, NULL},
{0, 0, 0, 0, 0}
};
static PyGetSetDef __pyx_Generator_getsets[] = {
{(char *) "__name__", (getter)__Pyx_Coroutine_get_name, (setter)__Pyx_Coroutine_set_name,
(char*) PyDoc_STR("name of the generator"), 0},
{(char *) "__qualname__", (getter)__Pyx_Coroutine_get_qualname, (setter)__Pyx_Coroutine_set_qualname,
(char*) PyDoc_STR("qualified name of the generator"), 0},
{(char *) "gi_frame", (getter)__Pyx_Coroutine_get_frame, NULL,
(char*) PyDoc_STR("Frame of the generator"), 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_GeneratorType_type = {
PyVarObject_HEAD_INIT(0, 0)
"generator",
sizeof(__pyx_CoroutineObject),
0,
(destructor) __Pyx_Coroutine_dealloc,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_HAVE_FINALIZE,
0,
(traverseproc) __Pyx_Coroutine_traverse,
0,
0,
offsetof(__pyx_CoroutineObject, gi_weakreflist),
0,
(iternextfunc) __Pyx_Generator_Next,
__pyx_Generator_methods,
__pyx_Generator_memberlist,
__pyx_Generator_getsets,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
#if CYTHON_USE_TP_FINALIZE
0,
#else
__Pyx_Coroutine_del,
#endif
0,
#if CYTHON_USE_TP_FINALIZE
__Pyx_Coroutine_del,
#elif PY_VERSION_HEX >= 0x030400a1
0,
#endif
#if PY_VERSION_HEX >= 0x030800b1
0,
#endif
#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
0,
#endif
};
static int __pyx_Generator_init(void) {
__pyx_GeneratorType_type.tp_getattro = __Pyx_PyObject_GenericGetAttrNoDict;
__pyx_GeneratorType_type.tp_iter = PyObject_SelfIter;
__pyx_GeneratorType = __Pyx_FetchCommonType(&__pyx_GeneratorType_type);
if (unlikely(!__pyx_GeneratorType)) {
return -1;
}
return 0;
}
/* CheckBinaryVersion */
static int __Pyx_check_binary_version(void) {
char ctversion[4], rtversion[4];
PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
char message[200];
PyOS_snprintf(message, sizeof(message),
"compiletime version %s of module '%.100s' "
"does not match runtime version %s",
ctversion, __Pyx_MODULE_NAME, rtversion);
return PyErr_WarnEx(NULL, message, 1);
}
return 0;
}
/* InitStrings */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
while (t->p) {
#if PY_MAJOR_VERSION < 3
if (t->is_unicode) {
*t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
} else if (t->intern) {
*t->p = PyString_InternFromString(t->s);
} else {
*t->p = PyString_FromStringAndSize(t->s, t->n - 1);
}
#else
if (t->is_unicode | t->is_str) {
if (t->intern) {
*t->p = PyUnicode_InternFromString(t->s);
} else if (t->encoding) {
*t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
} else {
*t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
}
} else {
*t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
}
#endif
if (!*t->p)
return -1;
if (PyObject_Hash(*t->p) == -1)
return -1;
++t;
}
return 0;
}
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
}
static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) {
Py_ssize_t ignore;
return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
#if !CYTHON_PEP393_ENABLED
static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
char* defenc_c;
PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
if (!defenc) return NULL;
defenc_c = PyBytes_AS_STRING(defenc);
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
{
char* end = defenc_c + PyBytes_GET_SIZE(defenc);
char* c;
for (c = defenc_c; c < end; c++) {
if ((unsigned char) (*c) >= 128) {
PyUnicode_AsASCIIString(o);
return NULL;
}
}
}
#endif
*length = PyBytes_GET_SIZE(defenc);
return defenc_c;
}
#else
static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
if (likely(PyUnicode_IS_ASCII(o))) {
*length = PyUnicode_GET_LENGTH(o);
return PyUnicode_AsUTF8(o);
} else {
PyUnicode_AsASCIIString(o);
return NULL;
}
#else
return PyUnicode_AsUTF8AndSize(o, length);
#endif
}
#endif
#endif
static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
if (
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
__Pyx_sys_getdefaultencoding_not_ascii &&
#endif
PyUnicode_Check(o)) {
return __Pyx_PyUnicode_AsStringAndSize(o, length);
} else
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
if (PyByteArray_Check(o)) {
*length = PyByteArray_GET_SIZE(o);
return PyByteArray_AS_STRING(o);
} else
#endif
{
char* result;
int r = PyBytes_AsStringAndSize(o, &result, length);
if (unlikely(r < 0)) {
return NULL;
} else {
return result;
}
}
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
int is_true = x == Py_True;
if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
else return PyObject_IsTrue(x);
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) {
int retval;
if (unlikely(!x)) return -1;
retval = __Pyx_PyObject_IsTrue(x);
Py_DECREF(x);
return retval;
}
static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) {
#if PY_MAJOR_VERSION >= 3
if (PyLong_Check(result)) {
if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1,
"__int__ returned non-int (type %.200s). "
"The ability to return an instance of a strict subclass of int "
"is deprecated, and may be removed in a future version of Python.",
Py_TYPE(result)->tp_name)) {
Py_DECREF(result);
return NULL;
}
return result;
}
#endif
PyErr_Format(PyExc_TypeError,
"__%.4s__ returned non-%.4s (type %.200s)",
type_name, type_name, Py_TYPE(result)->tp_name);
Py_DECREF(result);
return NULL;
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) {
#if CYTHON_USE_TYPE_SLOTS
PyNumberMethods *m;
#endif
const char *name = NULL;
PyObject *res = NULL;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x) || PyLong_Check(x)))
#else
if (likely(PyLong_Check(x)))
#endif
return __Pyx_NewRef(x);
#if CYTHON_USE_TYPE_SLOTS
m = Py_TYPE(x)->tp_as_number;
#if PY_MAJOR_VERSION < 3
if (m && m->nb_int) {
name = "int";
res = m->nb_int(x);
}
else if (m && m->nb_long) {
name = "long";
res = m->nb_long(x);
}
#else
if (likely(m && m->nb_int)) {
name = "int";
res = m->nb_int(x);
}
#endif
#else
if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) {
res = PyNumber_Int(x);
}
#endif
if (likely(res)) {
#if PY_MAJOR_VERSION < 3
if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) {
#else
if (unlikely(!PyLong_CheckExact(res))) {
#endif
return __Pyx_PyNumber_IntOrLongWrongResultType(res, name);
}
}
else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_TypeError,
"an integer is required");
}
return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
Py_ssize_t ival;
PyObject *x;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(b))) {
if (sizeof(Py_ssize_t) >= sizeof(long))
return PyInt_AS_LONG(b);
else
return PyInt_AsSsize_t(b);
}
#endif
if (likely(PyLong_CheckExact(b))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)b)->ob_digit;
const Py_ssize_t size = Py_SIZE(b);
if (likely(__Pyx_sst_abs(size) <= 1)) {
ival = likely(size) ? digits[0] : 0;
if (size == -1) ival = -ival;
return ival;
} else {
switch (size) {
case 2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
}
}
#endif
return PyLong_AsSsize_t(b);
}
x = PyNumber_Index(b);
if (!x) return -1;
ival = PyInt_AsSsize_t(x);
Py_DECREF(x);
return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) {
return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False);
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
return PyInt_FromSize_t(ival);
}
#endif /* Py_PYTHON_H */
| 8,771,017 | 44.361078 | 1,743 | c |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_alldiff.py | import pytest
networkx = pytest.importorskip("networkx")
from pyscipopt import Model, Conshdlr, SCIP_RESULT, SCIP_PARAMEMPHASIS, SCIP_PARAMSETTING
try:
from types import SimpleNamespace
except:
class SimpleNamespace:
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def __repr__(self):
keys = sorted(self.__dict__)
items = ("{}={!r}".format(k, self.__dict__[k]) for k in keys)
return "{}({})".format(type(self).__name__, ", ".join(items))
def __eq__(self, other):
return self.__dict__ == other.__dict__
#initial Sudoku values
init = [5, 3, 0, 0, 7, 0, 0, 0, 0,
6, 0, 0, 1, 9, 5, 0, 0, 0,
0, 9, 8, 0, 0, 0, 0, 6, 0,
8, 0, 0, 0, 6, 0, 0, 0, 3,
4, 0, 0, 8, 0, 3, 0, 0, 1,
7, 0, 0, 0, 2, 0, 0, 0, 6,
0, 6, 0, 0, 0, 0, 2, 8, 0,
0, 0, 0, 4, 1, 9, 0, 0, 5,
0, 0, 0, 0, 8, 0, 0, 7, 9]
def plot_graph(G):
plt = pytest.importorskip("matplotlib.pyplot")
X,Y = networkx.bipartite.sets(G)
pos = dict()
pos.update( (n, (1, i)) for i, n in enumerate(X) ) # put nodes from X at x=1
pos.update( (n, (2, i)) for i, n in enumerate(Y) ) # put nodes from Y at x=2
networkx.draw(G, pos=pos, with_labels=False)
labels = {}
for node in G.nodes():
labels[node] = node
networkx.draw_networkx_labels(G, pos, labels)
plt.show()
# all different constraint handler
class ALLDIFFconshdlr(Conshdlr):
# value graph: bipartite graph between variables and the union of their domains
# an edge connects a variable and a value iff the value is in the variable's domain
def build_value_graph(self, vars, domains):
#print(domains)
vals = set([])
for var in vars:
#print("domain of var ", var.name, "is ", domains[var])
vals.update(domains[var.ptr()]) # vals = vals union domains[var]
G = networkx.Graph()
G.add_nodes_from((var.name for var in vars), bipartite = 0) # add vars names as nodes
G.add_nodes_from(vals, bipartite = 1) # add union of values as nodes
for var in vars:
for value in domains[var.ptr()]:
G.add_edge(var.name, value)
return G, vals
# propagates single constraint: uses Regin's Algorithm as described in
# https://www.ps.uni-saarland.de/courses/seminar-ws04/papers/anastasatos.pdf
# The idea is that every solution of an all different constraint corresponds to a maximal matching in
# a bipartite graph (see value graph). Furthermore, if an arc of this arc is in no maximal matching, then
# one can remove it. Removing and arc corresponds to remove a value in the domain of the variable.
# So what the algorithm does is to determine which arcs can be in a maximal matching. Graph theory help
# us build fast algorithm so that we don't have to compute all possible maximal matchings ;)
# That being said, the implementation is pretty naive and brute-force, so there is a lot of room for improvement
def propagate_cons(self, cons):
#print("propagating cons %s with id %d"%(cons.name, id(cons)))
vars = cons.data.vars
domains = cons.data.domains
# TODO: would be nice to have a flag to know whether we should propagate the constraint.
# We would need an event handler to let us know whenever a variable of our constraint changed its domain
# Currently we can't write event handlers in python.
G, vals = self.build_value_graph(vars, domains)
try:
M = networkx.bipartite.maximum_matching(G) # returns dict between nodes in matching
except:
top_nodes = {n for n, d in G.nodes(data=True) if d['bipartite'] == 0}
bottom_nodes = set(G) - top_nodes
M = networkx.bipartite.maximum_matching(G, top_nodes) # returns dict between nodes in matching
if( len(M)/2 < len(vars) ):
#print("it is infeasible: max matching of card ", len(M), " M: ", M)
#print("Its value graph:\nV = ", G.nodes(), "\nE = ", G.edges())
plot_graph(G)
return SCIP_RESULT.CUTOFF
# build auxiliary directed graph: direct var -> val if [var, val] is in matching, otherwise var <- val
# note that all vars are matched
D = networkx.DiGraph()
D.add_nodes_from(G) ## this seems to work
for var in vars:
D.add_edge(var.name, M[var.name])
for val in domains[var.ptr()]:
if val != M[var.name]:
D.add_edge(val, var.name)
# find arcs that *do not* need to be removed and *remove* them from G. All remaining edges of G
# should be use to remove values from the domain of variables
# get all free vertices
V = set(G.nodes())
V_matched = set(M)
V_free = V.difference(V_matched)
#print("matched nodes ", V_matched, "\nfree nodes ", V_free)
# TODO quit() << this produces an assertion
# no variable should be free!
for var in vars:
assert var.name not in V_free
# perform breadth first search starting from free vertices and mark all visited edges as useful
for v in V_free:
visited_edges = networkx.bfs_edges(D, v)
G.remove_edges_from(visited_edges)
# compute strongly connected components of D and mark edges on the cc as useful
for g in networkx.strongly_connected_components(D):
for e in D.subgraph(g).edges():
if G.has_edge(*e):
G.remove_edge(*e)
# cannot remove edges in matching!
for var in vars:
e = (var.name, M[var.name])
if G.has_edge(*e):
G.remove_edge(*e)
# check that there is something to remove
if G.size() == 0:
return SCIP_RESULT.DIDNOTFIND
#print("Edges to remove!", G.edges())
# remove values
for var in vars:
for val in domains[var.ptr()].copy():
if G.has_edge(var.name, val):
domains[var.ptr()].remove(val) # this asserts if value is not there and we shouldn't delete two times the same value
# "fix" variable when possible
for var in vars:
#print("domain of var ", var.name, "is ", domains[var])
minval = min(domains[var.ptr()])
maxval = max(domains[var.ptr()])
if var.getLbLocal() < minval:
self.model.chgVarLb(var, minval)
if var.getUbLocal() > maxval:
self.model.chgVarUb(var, maxval)
#print("bounds of ", var, "are (%d,%d)"%(minval,maxval))
return SCIP_RESULT.REDUCEDDOM
# propagator callback
def consprop(self, constraints, nusefulconss, nmarkedconss, proptiming): # I have no idea what to return, documentation?
result = SCIP_RESULT.DIDNOTFIND
for cons in constraints:
prop_result = self.propagate_cons(cons)
if prop_result == SCIP_RESULT.CUTOFF:
result = prop_result
break
if prop_result == SCIP_RESULT.REDUCEDDOM:
result = prop_result
return {"result": result}
def is_cons_feasible(self, cons, solution = None):
#print("checking feasibility of constraint %s id: %d"%(cons.name, id(cons)))
sol_values = set()
for var in cons.data.vars:
sol_values.add(round(self.model.getSolVal(solution, var)))
#print("sol_values = ", sol_values)
return len(sol_values) == len(cons.data.vars)
# checks whether solution is feasible, ie, if they are all different
# since the checkpriority is < 0, we are only called if the integrality
# constraint handler didn't find infeasibility, so solution is integral
def conscheck(self, constraints, solution, check_integrality, check_lp_rows, print_reason, completely):
for cons in constraints:
if not self.is_cons_feasible(cons, solution):
return {"result": SCIP_RESULT.INFEASIBLE}
return {"result": SCIP_RESULT.FEASIBLE}
# enforces LP solution
def consenfolp(self, constraints, n_useful_conss, sol_infeasible):
for cons in constraints:
if not self.is_cons_feasible(cons):
# TODO: suggest some value to branch on
return {"result": SCIP_RESULT.INFEASIBLE}
return {"result": SCIP_RESULT.FEASIBLE}
def conslock(self, constraint, locktype, nlockspos, nlocksneg):
for var in constraint.data.vars:
self.model.addVarLocks(var, nlockspos + nlocksneg , nlockspos + nlocksneg)
def constrans(self, constraint):
#print("CONSTRANS BEING CAAAAAAAAAAAAAAAAAAAALLLLLLED")
return {}
# builds sudoku model; adds variables and all diff constraints
def create_sudoku():
scip = Model("Sudoku")
x = {} # values of squares
for row in range(9):
for col in range(9):
# some variables are fix
if init[row*9 + col] != 0:
x[row,col] = scip.addVar(vtype = "I", lb = init[row*9 + col], ub = init[row*9 + col], name = "x(%s,%s)" % (row,col))
else:
x[row,col] = scip.addVar(vtype = "I", lb = 1, ub = 9, name = "x(%s,%s)" % (row,col))
var = x[row,col]
#print("built var ", var.name, " with bounds: (%d,%d)"%(var.getLbLocal(), var.getUbLocal()))
conshdlr = ALLDIFFconshdlr()
# hoping to get called when all vars have integer values
scip.includeConshdlr(conshdlr, "ALLDIFF", "All different constraint", propfreq = 1, enfopriority = -10, chckpriority = -10)
# row constraints; also we specify the domain of all variables here
# TODO/QUESTION: in principle domain is of course associated to the var and not the constraint. it should be "var.data"
# But ideally that information would be handle by SCIP itself... the reason we can't is because domain holes is not implemented, right?
domains = {}
for row in range(9):
vars = []
for col in range(9):
var = x[row,col]
vars.append(var)
vals = set(range(int(round(var.getLbLocal())), int(round(var.getUbLocal())) + 1))
domains[var.ptr()] = vals
# this is kind of ugly, isn't it?
cons = scip.createCons(conshdlr, "row_%d" % row)
#print("in test: received a constraint with id ", id(cons)) ### DELETE
cons.data = SimpleNamespace() # so that data behaves like an instance of a class (ie, cons.data.whatever is allowed)
cons.data.vars = vars
cons.data.domains = domains
scip.addPyCons(cons)
# col constraints
for col in range(9):
vars = []
for row in range(9):
var = x[row,col]
vars.append(var)
cons = scip.createCons(conshdlr, "col_%d"%col)
cons.data = SimpleNamespace()
cons.data.vars = vars
cons.data.domains = domains
scip.addPyCons(cons)
# square constraints
for idx1 in range(3):
for idx2 in range(3):
vars = []
for row in range(3):
for col in range(3):
var = x[3*idx1 + row, 3*idx2 + col]
vars.append(var)
cons = scip.createCons(conshdlr, "square_%d-%d"%(idx1, idx2))
cons.data = SimpleNamespace()
cons.data.vars = vars
cons.data.domains = domains
scip.addPyCons(cons)
#scip.setObjective()
return scip, x
def test_main():
scip, x = create_sudoku()
#scip.setBoolParam("misc/allowdualreds", False)
scip.setBoolParam("misc/allowdualreds", False)
scip.setEmphasis(SCIP_PARAMEMPHASIS.CPSOLVER)
scip.setPresolve(SCIP_PARAMSETTING.OFF)
scip.optimize()
if scip.getStatus() != 'optimal':
print('Sudoku is not feasible!')
else:
print('\nSudoku solution:\n')
for row in range(9):
out = ''
for col in range(9):
out += str(round(scip.getVal(x[row,col]))) + ' '
print(out)
if __name__ == "__main__":
test_main()
| 12,268 | 39.094771 | 139 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_benders.py | """
flp-benders.py: model for solving the capacitated facility location problem using Benders' decomposition
minimize the total (weighted) travel cost from n customers
to some facilities with fixed costs and capacities.
Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012
"""
from pyscipopt import Model, quicksum, multidict, SCIP_PARAMSETTING
import pdb
def flp(I,J,d,M,f,c):
"""flp -- model for the capacitated facility location problem
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
Returns a model, ready to be solved.
"""
master = Model("flp-master")
subprob = Model("flp-subprob")
# creating the problem
y = {}
for j in J:
y[j] = master.addVar(vtype="B", name="y(%s)"%j)
master.setObjective(
quicksum(f[j]*y[j] for j in J),
"minimize")
master.data = y
# creating the subproblem
x,y = {},{}
for j in J:
y[j] = subprob.addVar(vtype="B", name="y(%s)"%j)
for i in I:
x[i,j] = subprob.addVar(vtype="C", name="x(%s,%s)"%(i,j))
for i in I:
subprob.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in M:
subprob.addCons(quicksum(x[i,j] for i in I) <= M[j]*y[j], "Capacity(%s)"%i)
for (i,j) in x:
subprob.addCons(x[i,j] <= d[i]*y[j], "Strong(%s,%s)"%(i,j))
subprob.setObjective(
quicksum(c[i,j]*x[i,j] for i in I for j in J),
"minimize")
subprob.data = x,y
return master, subprob
def make_data():
I,d = multidict({1:80, 2:270, 3:250, 4:160, 5:180}) # demand
J,M,f = multidict({1:[500,1000], 2:[500,1000], 3:[500,1000]}) # capacity, fixed costs
c = {(1,1):4, (1,2):6, (1,3):9, # transportation costs
(2,1):5, (2,2):4, (2,3):7,
(3,1):6, (3,2):3, (3,3):4,
(4,1):8, (4,2):5, (4,3):3,
(5,1):10, (5,2):8, (5,3):4,
}
return I,J,d,M,f,c
def test_flpbenders():
'''
test the Benders' decomposition plugins with the facility location problem.
'''
I,J,d,M,f,c = make_data()
master, subprob = flp(I,J,d,M,f,c)
# initializing the default Benders' decomposition with the subproblem
master.setPresolve(SCIP_PARAMSETTING.OFF)
master.setBoolParam("misc/allowdualreds", False)
master.setBoolParam("benders/copybenders", False)
master.initBendersDefault(subprob)
# optimizing the problem using Benders' decomposition
master.optimize()
# solving the subproblems to get the best solution
master.computeBestSolSubproblems()
EPS = 1.e-6
y = master.data
facilities = [j for j in y if master.getVal(y[j]) > EPS]
x, suby = subprob.data
edges = [(i,j) for (i,j) in x if subprob.getVal(x[i,j]) > EPS]
print("Optimal value:", master.getObjVal())
print("Facilities at nodes:", facilities)
print("Edges:", edges)
master.printStatistics()
# since computeBestSolSubproblems() was called above, we need to free the
# subproblems. This must happen after the solution is extracted, otherwise
# the solution will be lost
master.freeBendersSubproblems()
assert master.getObjVal() == 5.61e+03
if __name__ == "__main__":
test_flpbenders()
| 3,451 | 29.280702 | 105 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_branch_probing_lp.py | from pyscipopt import Model, Branchrule, SCIP_RESULT, quicksum
class MyBranching(Branchrule):
def __init__(self, model, cont):
self.model = model
self.cont = cont
self.count = 0
self.was_called_val = False
self.was_called_int = False
def branchexeclp(self, allowaddcons):
self.count += 1
if self.count >= 2:
return {"result": SCIP_RESULT.DIDNOTRUN}
assert allowaddcons
assert not self.model.inRepropagation()
assert not self.model.inProbing()
self.model.startProbing()
assert not self.model.isObjChangedProbing()
self.model.fixVarProbing(self.cont, 2.0)
self.model.constructLP()
self.model.solveProbingLP()
self.model.getLPObjVal()
self.model.endProbing()
self.integral = self.model.getLPBranchCands()[0][0]
if self.count == 1:
down, eq, up = self.model.branchVarVal(self.cont, 1.3)
self.model.chgVarLbNode(down, self.cont, -1.5)
self.model.chgVarUbNode(up, self.cont, 3.0)
self.was_called_val = True
down2, eq2, up2 = self.model.branchVar(self.integral)
self.was_called_int = True
self.model.createChild(6, 7)
return {"result": SCIP_RESULT.BRANCHED}
m = Model()
m.setIntParam("presolving/maxrounds", 0)
#m.setLongintParam("lp/rootiterlim", 3)
m.setRealParam("limits/time", 60)
x0 = m.addVar(lb=-2, ub=4)
r1 = m.addVar()
r2 = m.addVar()
y0 = m.addVar(lb=3)
t = m.addVar(lb=None)
l = m.addVar(vtype="I", lb=-9, ub=18)
u = m.addVar(vtype="I", lb=-3, ub=99)
more_vars = []
for i in range(1000):
more_vars.append(m.addVar(vtype="I", lb= -12, ub=40))
m.addCons(quicksum(v for v in more_vars) <= (40 - i) * quicksum(v for v in more_vars[::2]))
for i in range(1000):
more_vars.append(m.addVar(vtype="I", lb= -52, ub=10))
m.addCons(quicksum(v for v in more_vars[50::2]) <= (40 - i) * quicksum(v for v in more_vars[405::2]))
m.addCons(r1 >= x0)
m.addCons(r2 >= -x0)
m.addCons(y0 == r1 +r2)
#m.addCons(t * l + l * u >= 4)
m.addCons(t + l + 7* u <= 300)
m.addCons(t >= quicksum(v for v in more_vars[::3]) - 10 * more_vars[5] + 5* more_vars[9])
m.addCons(more_vars[3] >= l + 2)
m.addCons(7 <= quicksum(v for v in more_vars[::4]) - x0)
m.addCons(quicksum(v for v in more_vars[::2]) + l <= quicksum(v for v in more_vars[::4]))
m.setObjective(t - quicksum(j*v for j, v in enumerate(more_vars[20:-40])))
#m.addCons(t >= r1 * (r1 - x0) + r2 * (r2 + x0))
my_branchrule = MyBranching(m, x0)
m.includeBranchrule(my_branchrule, "test branch", "test branching and probing and lp functions",
priority=10000000, maxdepth=3, maxbounddist=1)
m.optimize()
print("x0", m.getVal(x0))
print("r1", m.getVal(r1))
print("r2", m.getVal(r2))
print("y0", m.getVal(y0))
print("t", m.getVal(t))
assert my_branchrule.was_called_val
assert my_branchrule.was_called_int
| 2,957 | 29.494845 | 105 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_conshdlr.py | from pyscipopt import Model, Conshdlr, SCIP_RESULT, SCIP_PRESOLTIMING, SCIP_PROPTIMING
from sys import version_info
if version_info >= (3, 3):
from types import SimpleNamespace
else:
class SimpleNamespace:
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def __repr__(self):
keys = sorted(self.__dict__)
items = ("{}={!r}".format(k, self.__dict__[k]) for k in keys)
return "{}({})".format(type(self).__name__, ", ".join(items))
def __eq__(self, other):
return self.__dict__ == other.__dict__
## callbacks which are not implemented yet:
# PyConsGetdivebdchgs
# PyConsGetvars
# PyConsCopy
## callbacks which are not tested here are:
# consenfops
# consresprop
# conscopy
# consparse
# consgetvars
# consgetdivebdchgs
## callbacks which are not called are:
# conssepasol
# consdelvars
# consprint
ids = []
calls = set([])
class MyConshdlr(Conshdlr):
def __init__(self, shouldtrans, shouldcopy):
self.shouldtrans = shouldtrans
self.shouldcopy = shouldcopy
def createData(self, constraint, nvars, othername):
print("Creating data for my constraint: %s"%constraint.name)
constraint.data = SimpleNamespace()
constraint.data.nvars = nvars
constraint.data.myothername = othername
## fundamental callbacks ##
def consenfolp(self, constraints, nusefulconss, solinfeasible):
calls.add("consenfolp")
for constraint in constraints:
assert id(constraint) in ids
return {"result": SCIP_RESULT.FEASIBLE}
# consenfops
def conscheck(self, constraints, solution, checkintegrality, checklprows, printreason, completely):
calls.add("conscheck")
for constraint in constraints:
assert id(constraint) in ids
return {"result": SCIP_RESULT.FEASIBLE}
def conslock(self, constraint, locktype, nlockspos, nlocksneg):
calls.add("conslock")
assert id(constraint) in ids
## callbacks ##
def consfree(self):
calls.add("consfree")
def consinit(self, constraints):
calls.add("consinit")
for constraint in constraints:
assert id(constraint) in ids
def consexit(self, constraints):
calls.add("consexit")
for constraint in constraints:
assert id(constraint) in ids
def consinitpre(self, constraints):
calls.add("consinitpre")
for constraint in constraints:
assert id(constraint) in ids
def consexitpre(self, constraints):
calls.add("consexitpre")
for constraint in constraints:
assert id(constraint) in ids
def consinitsol(self, constraints):
calls.add("consinitsol")
for constraint in constraints:
assert id(constraint) in ids
def consexitsol(self, constraints, restart):
calls.add("consexitsol")
for constraint in constraints:
assert id(constraint) in ids
def consdelete(self, constraint):
calls.add("consdelete")
assert id(constraint) in ids
def constrans(self, sourceconstraint):
calls.add("constrans")
assert id(sourceconstraint) in ids
if self.shouldtrans:
transcons = self.model.createCons(self, "transformed_" + sourceconstraint.name)
ids.append(id(transcons))
return {"targetcons" : transcons}
return {}
def consinitlp(self, constraints):
calls.add("consinitlp")
for constraint in constraints:
assert id(constraint) in ids
return {}
def conssepalp(self, constraints, nusefulconss):
calls.add("conssepalp")
for constraint in constraints:
assert id(constraint) in ids
return {}
def conssepasol(self, constraints, nusefulconss, solution):
calls.add("conssepasol")
for constraint in constraints:
assert id(constraint) in ids
return {}
def consprop(self, constraints, nusefulconss, nmarkedconss, proptiming):
calls.add("consprop")
for constraint in constraints:
assert id(constraint) in ids
return {}
def conspresol(self, constraints, nrounds, presoltiming,
nnewfixedvars, nnewaggrvars, nnewchgvartypes, nnewchgbds, nnewholes,
nnewdelconss, nnewaddconss, nnewupgdconss, nnewchgcoefs, nnewchgsides, result_dict):
calls.add("conspresol")
return result_dict
# consresprop
def consactive(self, constraint):
calls.add("consactive")
assert id(constraint) in ids
def consdeactive(self, constraint):
calls.add("consdeactive")
assert id(constraint) in ids
def consenable(self, constraint):
calls.add("consenable")
assert id(constraint) in ids
def consdisable(self, constraint):
calls.add("consdisable")
assert id(constraint) in ids
def consdelvars(self, constraints):
calls.add("consdelvars")
for constraint in constraints:
assert id(constraint) in ids
def consprint(self, constraint):
calls.add("consprint")
assert id(constraint) in ids
# conscopy
# consparse
# consgetvars
def consgetnvars(self, constraint):
calls.add("consgetnvars")
assert id(constraint) in ids
return {"nvars": 1, "success": True}
# consgetdivebdchgs
def test_conshdlr():
def create_model():
# create solver instance
s = Model()
# add some variables
x = s.addVar("x", obj = -1.0, vtype = "I", lb=-10)
y = s.addVar("y", obj = 1.0, vtype = "I", lb=-1000)
z = s.addVar("z", obj = 1.0, vtype = "I", lb=-1000)
# add some constraint
s.addCons(314*x + 867*y + 860*z == 363)
s.addCons(87*x + 875*y - 695*z == 423)
# create conshdlr and include it to SCIP
conshdlr = MyConshdlr(shouldtrans=True, shouldcopy=False)
s.includeConshdlr(conshdlr, "PyCons", "custom constraint handler implemented in python",
sepapriority = 1, enfopriority = 1, chckpriority = 1, sepafreq = 10, propfreq = 50,
eagerfreq = 1, maxprerounds = -1, delaysepa = False, delayprop = False, needscons = True,
presoltiming = SCIP_PRESOLTIMING.FAST, proptiming = SCIP_PROPTIMING.BEFORELP)
cons1 = s.createCons(conshdlr, "cons1name")
ids.append(id(cons1))
cons2 = s.createCons(conshdlr, "cons2name")
ids.append(id(cons2))
conshdlr.createData(cons1, 10, "cons1_anothername")
conshdlr.createData(cons2, 12, "cons2_anothername")
# add these constraints
s.addPyCons(cons1)
s.addPyCons(cons2)
return s
s = create_model()
# solve problem
s.optimize()
# so that consfree gets called
del s
# check callbacks got called
assert "consenfolp" in calls
assert "conscheck" in calls
assert "conslock" in calls
assert "consfree" in calls
assert "consinit" in calls
assert "consexit" in calls
assert "consinitpre" in calls
assert "consexitpre" in calls
assert "consinitsol" in calls
assert "consexitsol" in calls
assert "consdelete" in calls
assert "constrans" in calls
assert "consinitlp" in calls
assert "conssepalp" in calls
#assert "conssepasol" in calls
assert "consprop" in calls
assert "conspresol" in calls
assert "consactive" in calls
assert "consdeactive" in calls
assert "consenable" in calls
assert "consdisable" in calls
#assert "consdelvars" in calls
#assert "consprint" in calls
assert "consgetnvars" in calls
if __name__ == "__main__":
test_conshdlr()
| 7,831 | 29.59375 | 115 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_copy.py | from pyscipopt import Model
def test_copy():
# create solver instance
s = Model()
# add some variables
x = s.addVar("x", vtype = 'C', obj = 1.0)
y = s.addVar("y", vtype = 'C', obj = 2.0)
s.setObjective(4.0 * y, clear = False)
c = s.addCons(x + 2 * y >= 1.0)
s2 = Model(sourceModel=s)
# solve problems
s.optimize()
s2.optimize()
assert s.getObjVal() == s2.getObjVal()
if __name__ == "__main__":
test_copy()
| 465 | 18.416667 | 45 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_event.py | import pytest
from pyscipopt import Model, Eventhdlr, SCIP_RESULT, SCIP_EVENTTYPE, SCIP_PARAMSETTING
calls = []
class MyEvent(Eventhdlr):
def eventinit(self):
calls.append('eventinit')
self.model.catchEvent(SCIP_EVENTTYPE.FIRSTLPSOLVED, self)
def eventexit(self):
calls.append('eventexit')
self.model.dropEvent(SCIP_EVENTTYPE.FIRSTLPSOLVED, self)
def eventexec(self, event):
calls.append('eventexec')
event.getNewBound()
event.getOldBound()
assert event.getNode().getNumber() == 1
def test_event():
# create solver instance
s = Model()
s.hideOutput()
s.setPresolve(SCIP_PARAMSETTING.OFF)
eventhdlr = MyEvent()
s.includeEventhdlr(eventhdlr, "TestFirstLPevent", "python event handler to catch FIRSTLPEVENT")
# add some variables
x = s.addVar("x", obj=1.0)
y = s.addVar("y", obj=2.0)
# add some constraint
s.addCons(x + 2*y >= 5)
# solve problem
s.optimize()
# print solution
assert round(s.getVal(x)) == 5.0
assert round(s.getVal(y)) == 0.0
del s
assert 'eventinit' in calls
assert 'eventexit' in calls
assert 'eventexec' in calls
assert len(calls) == 3
if __name__ == "__main__":
test_event()
| 1,270 | 22.537037 | 99 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_expr.py | import pytest
from pyscipopt import Model, sqrt, log, exp
from pyscipopt.scip import Expr, GenExpr, ExprCons, Term, quicksum
@pytest.fixture(scope="module")
def model():
m = Model()
x = m.addVar("x")
y = m.addVar("y")
z = m.addVar("z")
return m, x, y, z
CONST = Term()
def test_upgrade(model):
m, x, y, z = model
expr = x + y
assert isinstance(expr, Expr)
expr += exp(z)
assert isinstance(expr, GenExpr)
expr = x + y
assert isinstance(expr, Expr)
expr -= exp(z)
assert isinstance(expr, GenExpr)
expr = x + y
assert isinstance(expr, Expr)
expr /= x
assert isinstance(expr, GenExpr)
expr = x + y
assert isinstance(expr, Expr)
expr *= sqrt(x)
assert isinstance(expr, GenExpr)
expr = x + y
assert isinstance(expr, Expr)
expr **= 1.5
assert isinstance(expr, GenExpr)
expr = x + y
assert isinstance(expr, Expr)
assert isinstance(expr + exp(x), GenExpr)
assert isinstance(expr - exp(x), GenExpr)
assert isinstance(expr/x, GenExpr)
assert isinstance(expr * x**1.2, GenExpr)
assert isinstance(sqrt(expr), GenExpr)
assert isinstance(abs(expr), GenExpr)
assert isinstance(log(expr), GenExpr)
assert isinstance(exp(expr), GenExpr)
with pytest.raises(ZeroDivisionError):
expr /= 0.0
def test_genexpr_op_expr(model):
m, x, y, z = model
genexpr = x**1.5 + y
assert isinstance(genexpr, GenExpr)
genexpr += x**2
assert isinstance(genexpr, GenExpr)
genexpr += 1
assert isinstance(genexpr, GenExpr)
genexpr += x
assert isinstance(genexpr, GenExpr)
genexpr += 2 * y
assert isinstance(genexpr, GenExpr)
genexpr -= x**2
assert isinstance(genexpr, GenExpr)
genexpr -= 1
assert isinstance(genexpr, GenExpr)
genexpr -= x
assert isinstance(genexpr, GenExpr)
genexpr -= 2 * y
assert isinstance(genexpr, GenExpr)
genexpr *= x + y
assert isinstance(genexpr, GenExpr)
genexpr *= 2
assert isinstance(genexpr, GenExpr)
genexpr /= 2
assert isinstance(genexpr, GenExpr)
genexpr /= x + y
assert isinstance(genexpr, GenExpr)
assert isinstance(x**1.2 + x + y, GenExpr)
assert isinstance(x**1.2 - x, GenExpr)
assert isinstance(x**1.2 *(x+y), GenExpr)
def test_genexpr_op_genexpr(model):
m, x, y, z = model
genexpr = x**1.5 + y
assert isinstance(genexpr, GenExpr)
genexpr **= 2.2
assert isinstance(genexpr, GenExpr)
genexpr += exp(x)
assert isinstance(genexpr, GenExpr)
genexpr -= exp(x)
assert isinstance(genexpr, GenExpr)
genexpr /= log(x + 1)
assert isinstance(genexpr, GenExpr)
genexpr *= (x + y)**1.2
assert isinstance(genexpr, GenExpr)
genexpr /= exp(2)
assert isinstance(genexpr, GenExpr)
genexpr /= x + y
assert isinstance(genexpr, GenExpr)
genexpr = x**1.5 + y
assert isinstance(genexpr, GenExpr)
assert isinstance(sqrt(x) + genexpr, GenExpr)
assert isinstance(exp(x) + genexpr, GenExpr)
assert isinstance(1/x + genexpr, GenExpr)
assert isinstance(1/x**1.5 - genexpr, GenExpr)
assert isinstance(y/x - exp(genexpr), GenExpr)
# sqrt(2) is not a constant expression and
# we can only power to constant expressions!
with pytest.raises(NotImplementedError):
genexpr **= sqrt(2)
def test_degree(model):
m, x, y, z = model
expr = GenExpr()
assert expr.degree() == float('inf')
# In contrast to Expr inequalities, we can't expect much of the sides
def test_inequality(model):
m, x, y, z = model
expr = x + 2*y
assert isinstance(expr, Expr)
cons = expr <= x**1.2
assert isinstance(cons, ExprCons)
assert isinstance(cons.expr, GenExpr)
assert cons._lhs is None
assert cons._rhs == 0.0
assert isinstance(expr, Expr)
cons = expr >= x**1.2
assert isinstance(cons, ExprCons)
assert isinstance(cons.expr, GenExpr)
assert cons._lhs == 0.0
assert cons._rhs is None
assert isinstance(expr, Expr)
cons = expr >= 1 + x**1.2
assert isinstance(cons, ExprCons)
assert isinstance(cons.expr, GenExpr)
assert cons._lhs == 0.0 # NOTE: the 1 is pass the the other side because of the way GenExprs work
assert cons._rhs is None
assert isinstance(expr, Expr)
cons = exp(expr) <= 1 + x**1.2
assert isinstance(cons, ExprCons)
assert isinstance(cons.expr, GenExpr)
assert cons._rhs == 0.0
assert cons._lhs is None
def test_equation(model):
m, x, y, z = model
equat = 2*x**1.2 - 3*sqrt(y) == 1
assert isinstance(equat, ExprCons)
assert equat._lhs == equat._rhs
assert equat._lhs == 1.0
equat = exp(x+2*y) == 1 + x**1.2
assert isinstance(equat, ExprCons)
assert isinstance(equat.expr, GenExpr)
assert equat._lhs == equat._rhs
assert equat._lhs == 0.0
equat = x == 1 + x**1.2
assert isinstance(equat, ExprCons)
assert isinstance(equat.expr, GenExpr)
assert equat._lhs == equat._rhs
assert equat._lhs == 0.0
| 5,031 | 27.590909 | 101 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_gomory.py | import pytest
from pyscipopt import Model, Sepa, SCIP_RESULT, SCIP_PARAMSETTING
from pyscipopt.scip import is_memory_freed
class GMI(Sepa):
def __init__(self):
self.ncuts = 0
def getGMIFromRow(self, cols, rows, binvrow, binvarow, primsol):
""" Given the row (binvarow, binvrow) of the tableau, computes gomory cut
:param primsol: is the rhs of the tableau row.
:param cols: are the variables
:param rows: are the slack variables
:param binvrow: components of the tableau row associated to the basis inverse
:param binvarow: components of the tableau row associated to the basis inverse * A
The GMI is given by
sum(f_j x_j , j in J_I s.t. f_j <= f_0) +
sum((1-f_j)*f_0/(1 - f_0) x_j, j in J_I s.t. f_j > f_0) +
sum(a_j x_j, , j in J_C s.t. a_j >= 0) -
sum(a_j*f_0/(1-f_0) x_j , j in J_C s.t. a_j < 0) >= f_0.
where J_I are the integer non-basic variables and J_C are the continuous.
f_0 is the fractional part of primsol
a_j is the j-th coefficient of the row and f_j its fractional part
Note: we create -% <= -f_0 !!
Note: this formula is valid for a problem of the form Ax = b, x>= 0. Since we do not have
such problem structure in general, we have to (implicitely) transform whatever we are given
to that form. Specifically, non-basic variables at their lower bound are shifted so that the lower
bound is 0 and non-basic at their upper bound are complemented.
"""
# initialize
cutcoefs = [0] * len(cols)
cutrhs = 0
# get scip
scip = self.model
# Compute cut fractionality f0 and f0/(1-f0)
f0 = scip.frac(primsol)
ratiof0compl = f0/(1-f0)
# rhs of the cut is the fractional part of the LP solution for the basic variable
cutrhs = -f0
# Generate cut coefficients for the original variables
for c in range(len(cols)):
col = cols[c]
assert col is not None # is this the equivalent of col != NULL? does it even make sense to have this assert?
status = col.getBasisStatus()
# Get simplex tableau coefficient
if status == "lower":
# Take coefficient if nonbasic at lower bound
rowelem = binvarow[c]
elif status == "upper":
# Flip coefficient if nonbasic at upper bound: x --> u - x
rowelem = -binvarow[c]
else:
# variable is nonbasic free at zero -> cut coefficient is zero, skip OR
# variable is basic, skip
assert status == "zero" or status == "basic"
continue
# Integer variables
if col.isIntegral():
# warning: because of numerics cutelem < 0 is possible (though the fractional part is, mathematically, always positive)
# However, when cutelem < 0 it is also very close to 0, enough that isZero(cutelem) is true, so we ignore
# the coefficient (see below)
cutelem = scip.frac(rowelem)
if cutelem > f0:
# sum((1-f_j)*f_0/(1 - f_0) x_j, j in J_I s.t. f_j > f_0) +
cutelem = -((1.0 - cutelem) * ratiof0compl)
else:
# sum(f_j x_j , j in J_I s.t. f_j <= f_0) +
cutelem = -cutelem
else:
# Continuous variables
if rowelem < 0.0:
# -sum(a_j*f_0/(1-f_0) x_j , j in J_C s.t. a_j < 0) >= f_0.
cutelem = rowelem * ratiof0compl
else:
# sum(a_j x_j, , j in J_C s.t. a_j >= 0) -
cutelem = -rowelem
# cut is define when variables are in [0, infty). Translate to general bounds
if not scip.isZero(cutelem):
if col.getBasisStatus() == "upper":
cutelem = -cutelem
cutrhs += cutelem * col.getUb()
else:
cutrhs += cutelem * col.getLb()
# Add coefficient to cut in dense form
cutcoefs[col.getLPPos()] = cutelem
# Generate cut coefficients for the slack variables; skip basic ones
for c in range(len(rows)):
row = rows[c]
assert row != None
status = row.getBasisStatus()
# free slack variable shouldn't appear
assert status != "zero"
# Get simplex tableau coefficient
if status == "lower":
# Take coefficient if nonbasic at lower bound
rowelem = binvrow[row.getLPPos()]
# But if this is a >= or ranged constraint at the lower bound, we have to flip the row element
if not scip.isInfinity(-row.getLhs()):
rowelem = -rowelem
elif status == "upper":
# Take element if nonbasic at upper bound - see notes at beginning of file: only nonpositive slack variables
# can be nonbasic at upper, therefore they should be flipped twice and we can take the element directly.
rowelem = binvrow[row.getLPPos()]
else:
assert status == "basic"
continue
# if row is integral we can strengthen the cut coefficient
if row.isIntegral() and not row.isModifiable():
# warning: because of numerics cutelem < 0 is possible (though the fractional part is, mathematically, always positive)
# However, when cutelem < 0 it is also very close to 0, enough that isZero(cutelem) is true (see later)
cutelem = scip.frac(rowelem)
if cutelem > f0:
# sum((1-f_j)*f_0/(1 - f_0) x_j, j in J_I s.t. f_j > f_0) +
cutelem = -((1.0 - cutelem) * ratiof0compl)
else:
# sum(f_j x_j , j in J_I s.t. f_j <= f_0) +
cutelem = -cutelem
else:
# Continuous variables
if rowelem < 0.0:
# -sum(a_j*f_0/(1-f_0) x_j , j in J_C s.t. a_j < 0) >= f_0.
cutelem = rowelem * ratiof0compl
else:
# sum(a_j x_j, , j in J_C s.t. a_j >= 0) -
cutelem = -rowelem
# cut is define in original variables, so we replace slack by its definition
if not scip.isZero(cutelem):
# get lhs/rhs
rlhs = row.getLhs()
rrhs = row.getRhs()
assert scip.isLE(rlhs, rrhs)
assert not scip.isInfinity(rlhs) or not scip.isInfinity(rrhs)
# If the slack variable is fixed, we can ignore this cut coefficient
if scip.isFeasZero(rrhs - rlhs):
continue
# Unflip slack variable and adjust rhs if necessary: row at lower means the slack variable is at its upper bound.
# Since SCIP adds +1 slacks, this can only happen when constraints have a finite lhs
if row.getBasisStatus() == "lower":
assert not scip.isInfinity(-rlhs)
cutelem = -cutelem
rowcols = row.getCols()
rowvals = row.getVals()
assert len(rowcols) == len(rowvals)
# Eliminate slack variable: rowcols is sorted: [columns in LP, columns not in LP]
for i in range(row.getNLPNonz()):
cutcoefs[rowcols[i].getLPPos()] -= cutelem * rowvals[i]
act = scip.getRowLPActivity(row)
rhsslack = rrhs - act
if scip.isFeasZero(rhsslack):
assert row.getBasisStatus() == "upper" # cutelem != 0 and row active at upper bound -> slack at lower, row at upper
cutrhs -= cutelem * (rrhs - row.getConstant())
else:
assert scip.isFeasZero(act - rlhs)
cutrhs -= cutelem * (rlhs - row.getConstant())
return cutcoefs, cutrhs
def sepaexeclp(self):
result = SCIP_RESULT.DIDNOTRUN
scip = self.model
if not scip.isLPSolBasic():
return {"result": result}
#TODO: add SCIPgetNLPBranchCands
# get var data ---> this is the same as getVars!
vars = scip.getVars(transformed = True)
# get LP data
cols = scip.getLPColsData()
rows = scip.getLPRowsData()
# exit if LP is trivial
if len(cols) == 0 or len(rows) == 0:
return {"result": result}
result = SCIP_RESULT.DIDNOTFIND
# get basis indices
basisind = scip.getLPBasisInd()
# For all basic columns (not slacks) belonging to integer variables, try to generate a gomory cut
for i in range(len(rows)):
tryrow = False
c = basisind[i]
#primsol = SCIP_INVALID
#print("Row %d/%d basic index: %d"%(i, len(rows),c))
#print("Row %d with value %f"%(i, cols[c].getPrimsol() if c >=0 else scip.getRowActivity(rows[-c-1])))
if c >= 0:
assert c < len(cols)
var = cols[c].getVar()
if var.vtype() != "CONTINUOUS":
primsol = cols[c].getPrimsol()
assert scip.getSolVal(None, var) == primsol
#print("var ", var," is not continuous. primsol = ", primsol)
if 0.005 <= scip.frac(primsol) <= 1 - 0.005:
#print("####trying gomory cut for col <%s> [%g] row %i"%(var, primsol, i))
tryrow = True
# generate the cut!
if tryrow:
# get the row of B^-1 for this basic integer variable with fractional solution value
binvrow = scip.getLPBInvRow(i)
# get the tableau row for this basic integer variable with fractional solution value
binvarow = scip.getLPBInvARow(i)
# get cut's coefficients
cutcoefs, cutrhs = self.getGMIFromRow(cols, rows, binvrow, binvarow, primsol)
#########################################
#### This code is for testing only!! ####
# the first two cuts are -x1 + 2y <= 0 and -x2 +2y <= 0
# the next two (when both previous ones are added) are -2x1 + 6y <=0 and -2x2 + 6y <=0
assert scip.isZero(cutcoefs[0]) or scip.isZero(cutcoefs[1])
if self.ncuts < 2:
assert scip.isZero(cutcoefs[0] + 1) or scip.isZero(cutcoefs[1] + 1)
assert scip.isZero(cutcoefs[2] - 2)
else:
assert scip.isZero(cutcoefs[0] + 2) or scip.isZero(cutcoefs[1] + 2)
assert scip.isZero(cutcoefs[2] - 6)
##########################################
# add cut
# TODO: here it might make sense just to have a function `addCut` just like `addCons`. Or maybe better `createCut`
# so that then one can ask stuff about it, like its efficacy, etc. This function would receive all coefficients
# and basically do what we do here: cacheRowExtension etc up to releaseRow
cut = scip.createEmptyRowSepa(self, "gmi%d_x%d"%(self.ncuts,c if c >= 0 else -c-1), lhs = None, rhs = cutrhs)
scip.cacheRowExtensions(cut)
for j in range(len(cutcoefs)):
if scip.isZero(cutcoefs[j]): # maybe here we need isFeasZero
continue
#print("var : ", cols[j].getVar(), " coef: ", cutcoefs[j])
#print("cut.lhs : ", cut.getLhs(), " cut.rhs: ", cut.getRhs())
scip.addVarToRow(cut, cols[j].getVar(), cutcoefs[j])
if cut.getNNonz() == 0:
assert scip.isFeasNegative(cutrhs)
#print("Gomory cut is infeasible: 0 <= ", cutrhs)
return {"result": SCIP_RESULT.CUTOFF}
# Only take efficacious cuts, except for cuts with one non-zero coefficient (= bound changes)
# the latter cuts will be handeled internally in sepastore.
if cut.getNNonz() == 1 or scip.isCutEfficacious(cut):
#print(" -> gomory cut for <%s>: rhs=%f, eff=%f"%(cols[c].getVar() if c >= 0 else rows[-c-1].getName(),
# cutrhs, scip.getCutEfficacy(cut)))
#SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
# cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
# SCIPgetCutEfficacy(scip, NULL, cut),
# SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
# SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut))
# flush all changes before adding the cut
scip.flushRowExtensions(cut)
infeasible = scip.addCut(cut, forcecut=True)
self.ncuts += 1
if infeasible:
result = SCIP_RESULT.CUTOFF
else:
result = SCIP_RESULT.SEPARATED
scip.releaseRow(cut)
return {"result": result}
def model():
# create solver instance
s = Model()
# include separator
sepa = GMI()
s.includeSepa(sepa, "python_gmi", "generates gomory mixed integer cuts", priority = 1000, freq = 1)
# turn off presolve
s.setPresolve(SCIP_PARAMSETTING.OFF)
# turn off heuristics
s.setHeuristics(SCIP_PARAMSETTING.OFF)
# turn off propagation
s.setIntParam("propagating/maxrounds", 0)
s.setIntParam("propagating/maxroundsroot", 0)
# turn off some cuts
s.setIntParam("separating/strongcg/freq", -1)
s.setIntParam("separating/gomory/freq", -1)
s.setIntParam("separating/aggregation/freq", -1)
s.setIntParam("separating/mcf/freq", -1)
s.setIntParam("separating/closecuts/freq", -1)
s.setIntParam("separating/clique/freq", -1)
s.setIntParam("separating/zerohalf/freq", -1)
# only two rounds of cuts
s.setIntParam("separating/maxroundsroot", 2)
return s
# we use Cook Kannan and Schrijver's example
def test_CKS():
s = model()
# add variables
x1 = s.addVar("x1", vtype='I')
x2 = s.addVar("x2", vtype='I')
y = s.addVar("y", obj=-1, vtype='C')
# add constraint
s.addCons(-x1 + y <= 0)
s.addCons( - x2 + y <= 0)
s.addCons( x1 + x2 + y <= 2)
# solve problem
s.optimize()
s.printStatistics()
if __name__ == "__main__":
test_CKS()
| 15,199 | 42.930636 | 136 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_heur.py | import gc
import weakref
import pytest
from pyscipopt import Model, Heur, SCIP_RESULT, SCIP_PARAMSETTING, SCIP_HEURTIMING
from pyscipopt.scip import is_memory_freed
from util import is_optimized_mode
class MyHeur(Heur):
def heurexec(self, heurtiming, nodeinfeasible):
sol = self.model.createSol(self)
vars = self.model.getVars()
self.model.setSolVal(sol, vars[0], 5.0)
self.model.setSolVal(sol, vars[1], 0.0)
accepted = self.model.trySol(sol)
if accepted:
return {"result": SCIP_RESULT.FOUNDSOL}
else:
return {"result": SCIP_RESULT.DIDNOTFIND}
def test_heur():
# create solver instance
s = Model()
heuristic = MyHeur()
s.includeHeur(heuristic, "PyHeur", "custom heuristic implemented in python", "Y", timingmask=SCIP_HEURTIMING.BEFORENODE)
s.setPresolve(SCIP_PARAMSETTING.OFF)
# add some variables
x = s.addVar("x", obj=1.0)
y = s.addVar("y", obj=2.0)
# add some constraint
s.addCons(x + 2*y >= 5)
# solve problem
s.optimize()
# print solution
assert round(s.getVal(x)) == 5.0
assert round(s.getVal(y)) == 0.0
def test_heur_memory():
if is_optimized_mode():
pytest.skip()
def inner():
s = Model()
heuristic = MyHeur()
s.includeHeur(heuristic, "PyHeur", "custom heuristic implemented in python", "Y", timingmask=SCIP_HEURTIMING.BEFORENODE)
return weakref.proxy(heuristic)
heur_prox = inner()
gc.collect() # necessary?
with pytest.raises(ReferenceError):
heur_prox.name
assert is_memory_freed()
if __name__ == "__main__":
test_heur()
| 1,670 | 23.573529 | 128 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_knapsack.py | from pyscipopt import Model, quicksum
def test_knapsack():
# create solver instance
s = Model("Knapsack")
s.hideOutput()
# setting the objective sense to maximise
s.setMaximize()
# item weights
weights = [4, 2, 6, 3, 7, 5]
# item costs
costs = [7, 2, 5, 4, 3, 4]
assert len(weights) == len(costs)
# knapsack size
knapsackSize = 15
# adding the knapsack variables
knapsackVars = []
varNames = []
varBaseName = "Item"
for i in range(len(weights)):
varNames.append(varBaseName + "_" + str(i))
knapsackVars.append(s.addVar(varNames[i], vtype='I', obj=costs[i], ub=1.0))
# adding a linear constraint for the knapsack constraint
s.addCons(quicksum(w*v for (w, v) in zip(weights, knapsackVars)) <= knapsackSize)
# solve problem
s.optimize()
s.printStatistics()
# print solution
varSolutions = []
for i in range(len(weights)):
solValue = round(s.getVal(knapsackVars[i]))
varSolutions.append(solValue)
if solValue > 0:
print (varNames[i], "Times Selected:", solValue)
print ("\tIncluded Weight:", weights[i]*solValue, "\tItem Cost:", costs[i]*solValue)
includedWeight = sum([weights[i]*varSolutions[i] for i in range(len(weights))])
assert includedWeight > 0 and includedWeight <= knapsackSize
if __name__ == "__main__":
test_knapsack()
| 1,417 | 26.269231 | 96 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_linexpr.py | import pytest
from pyscipopt import Model
from pyscipopt.scip import Expr, ExprCons, Term, quicksum
@pytest.fixture(scope="module")
def model():
m = Model()
x = m.addVar("x")
y = m.addVar("y")
z = m.addVar("z")
return m, x, y, z
CONST = Term()
def test_term(model):
m, x, y, z = model
assert x[x] == 1.0
assert x[y] == 0.0
def test_operations_linear(model):
m, x, y, z = model
expr = x + y
assert isinstance(expr, Expr)
assert expr[x] == 1.0
assert expr[y] == 1.0
assert expr[z] == 0.0
expr = -x
assert isinstance(expr, Expr)
assert expr[x] == -1.0
assert expr[y] == 0.0
expr = x*4
assert isinstance(expr, Expr)
assert expr[x] == 4.0
assert expr[y] == 0.0
expr = 4*x
assert isinstance(expr, Expr)
assert expr[x] == 4.0
assert expr[y] == 0.0
expr = x + y + x
assert isinstance(expr, Expr)
assert expr[x] == 2.0
assert expr[y] == 1.0
expr = x + y - x
assert isinstance(expr, Expr)
assert expr[x] == 0.0
assert expr[y] == 1.0
expr = 3*x + 1.0
assert isinstance(expr, Expr)
assert expr[x] == 3.0
assert expr[y] == 0.0
assert expr[CONST] == 1.0
expr = 1.0 + 3*x
assert isinstance(expr, Expr)
assert expr[x] == 3.0
assert expr[y] == 0.0
assert expr[CONST] == 1.0
def test_operations_quadratic(model):
m, x, y, z = model
expr = x*x
assert isinstance(expr, Expr)
assert expr[x] == 0.0
assert expr[y] == 0.0
assert expr[CONST] == 0.0
assert expr[Term(x,x)] == 1.0
expr = x*y
assert isinstance(expr, Expr)
assert expr[x] == 0.0
assert expr[y] == 0.0
assert expr[CONST] == 0.0
assert expr[Term(x,y)] == 1.0
expr = (x - 1)*(y + 1)
assert isinstance(expr, Expr)
assert expr[x] == 1.0
assert expr[y] == -1.0
assert expr[CONST] == -1.0
assert expr[Term(x,y)] == 1.0
def test_power_for_quadratic(model):
m, x, y, z = model
expr = x**2 + x + 1
assert isinstance(expr, Expr)
assert expr[Term(x,x)] == 1.0
assert expr[x] == 1.0
assert expr[CONST] == 1.0
assert len(expr.terms) == 3
assert (x**2).terms == (x*x).terms
assert ((x + 3)**2).terms == (x**2 + 6*x + 9).terms
def test_operations_poly(model):
m, x, y, z = model
expr = x*x*x + 2*y*y
assert isinstance(expr, Expr)
assert expr[x] == 0.0
assert expr[y] == 0.0
assert expr[CONST] == 0.0
assert expr[Term(x,x,x)] == 1.0
assert expr[Term(y,y)] == 2.0
assert expr.terms == (x**3 + 2*y**2).terms
def test_degree(model):
m, x, y, z = model
expr = Expr()
assert expr.degree() == 0
expr = Expr() + 3.0
assert expr.degree() == 0
expr = x + 1
assert expr.degree() == 1
expr = x*x + y - 2
assert expr.degree() == 2
expr = (x + 1)*(y + 1)*(x - 1)
assert expr.degree() == 3
def test_inequality(model):
m, x, y, z = model
expr = x + 2*y
cons = expr <= 0
assert isinstance(cons, ExprCons)
assert cons._lhs is None
assert cons._rhs == 0.0
assert cons.expr[x] == 1.0
assert cons.expr[y] == 2.0
assert cons.expr[z] == 0.0
assert cons.expr[CONST] == 0.0
assert CONST not in cons.expr.terms
cons = expr >= 5
assert isinstance(cons, ExprCons)
assert cons._lhs == 5.0
assert cons._rhs is None
assert cons.expr[x] == 1.0
assert cons.expr[y] == 2.0
assert cons.expr[z] == 0.0
assert cons.expr[CONST] == 0.0
assert CONST not in cons.expr.terms
cons = 5 <= x + 2*y - 3
assert isinstance(cons, ExprCons)
assert cons._lhs == 8.0
assert cons._rhs is None
assert cons.expr[x] == 1.0
assert cons.expr[y] == 2.0
assert cons.expr[z] == 0.0
assert cons.expr[CONST] == 0.0
assert CONST not in cons.expr.terms
def test_ranged(model):
m, x, y, z = model
expr = x + 2*y
cons = expr >= 3
ranged = cons <= 5
assert isinstance(ranged, ExprCons)
assert ranged._lhs == 3.0
assert ranged._rhs == 5.0
assert ranged.expr[y] == 2.0
assert ranged.expr[CONST] == 0.0
# again, more or less directly:
ranged = 3 <= (x + 2*y <= 5)
assert isinstance(ranged, ExprCons)
assert ranged._lhs == 3.0
assert ranged._rhs == 5.0
assert ranged.expr[y] == 2.0
assert ranged.expr[CONST] == 0.0
# we must use the parenthesis, because
# x <= y <= z
# is a "chained comparison", which will be interpreted by Python
# to be equivalent to
# (x <= y) and (y <= z)
# where "and" can not be overloaded and the expressions in
# parenthesis are coerced to booleans.
with pytest.raises(TypeError):
ranged = (x + 2*y <= 5) <= 3
with pytest.raises(TypeError):
ranged = 3 >= (x + 2*y <= 5)
with pytest.raises(TypeError):
ranged = (1 <= x + 2*y <= 5)
def test_equation(model):
m, x, y, z = model
equat = 2*x - 3*y == 1
assert isinstance(equat, ExprCons)
assert equat._lhs == equat._rhs
assert equat._lhs == 1.0
assert equat.expr[x] == 2.0
assert equat.expr[y] == -3.0
assert equat.expr[CONST] == 0.0
def test_objective(model):
m, x, y, z = model
# setting linear objective
m.setObjective(x + y)
# using quicksum
m.setObjective(quicksum(2 * v for v in [x, y, z]))
# setting affine objective
m.setObjective(x + y + 1)
assert m.getObjoffset() == 1
# setting nonlinear objective
with pytest.raises(ValueError):
m.setObjective(x ** 2 - y * z)
| 5,534 | 23.709821 | 68 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_logical.py | from pyscipopt import Model
from pyscipopt import quicksum
try:
import pytest
itertools = pytest.importorskip("itertools")
except ImportError:
import itertools
product = itertools.product
# Testing AND/OR/XOR constraints
# check whether any error is raised
# see http://scip.zib.de/doc-5.0.1/html/cons__and_8c.php
# for resultant and operators definition
# CAVEAT: ONLY binary variables are allowed
# Integer and continous variables behave unexpectedly (due to SCIP?)
# TBI: automatic assertion of expected resultant VS optimal resultant
# (visual inspection at the moment)
verbose = True # py.test ignores this
# AUXILIARY FUNCTIONS
def setModel(vtype="B", name=None, imax=2):
"""initialize model and its variables.
imax (int): number of operators"""
if name is None:
name = "model"
m = Model(name)
m.hideOutput()
i = 0
r = m.addVar("r", vtype)
while i < imax:
m.addVar("v%s" % i, vtype)
i += 1
return m
def getVarByName(m, name):
try:
return [v for v in m.getVars() if name == v.name][0]
except IndexError:
return None
def getAllVarsByName(m, name):
try:
return [v for v in m.getVars() if name in v.name]
except IndexError:
return []
def setConss(m, vtype="B", val=0, imax=1):
"""set numeric constraints to the operators.
val (int): number to which the operators are constraint
imax (int): number of operators affected by the constraint"""
i = 0
while i < imax:
vi = getVarByName(m, "v%s" % i)
m.addCons(vi == val, vtype)
i += 1
return
def printOutput(m):
"""print status and values of variables AFTER optimization."""
status = m.getStatus()
r = getVarByName(m, "r")
rstr = "%d" % round(m.getVal(r))
vs = getAllVarsByName(m, "v")
vsstr = "".join(["%d" % round(m.getVal(v)) for v in vs])
print("Status: %s, resultant: %s, operators: %s" % (status, rstr, vsstr))
# MAIN FUNCTIONS
def main_variable(model, logical, sense="min"):
"""r is the BINARY resultant variable
v are BINARY operators
cf. http://scip.zib.de/doc-5.0.1/html/cons__and_8h.php"""
try:
r = getVarByName(model, "r")
vs = getAllVarsByName(model, "v")
# addConsAnd/Or method (Xor: TBI, custom) ###
method_name = "addCons%s" % logical.capitalize()
if method_name == "addConsXor":
n = model.addVar("n", "I")
model.addCons(r+quicksum(vs) == 2*n)
else:
try:
_model_addConsLogical = getattr(model, method_name)
_model_addConsLogical(vs, r)
except AttributeError as e:
raise AttributeError("%s not implemented" % method_name)
model.setObjective(r, sense="%simize" % sense)
model.optimize()
assert model.getStatus() == "optimal"
if verbose:
printOutput(model)
return True
except Exception as e:
if verbose:
print("%s: %s" % (e.__class__.__name__, e))
return False
def main_boolean(model, logical, value=False):
"""r is the BOOLEAN rhs (NOT a variable!)
v are BINARY operators
cf. http://scip.zib.de/doc-5.0.1/html/cons__xor_8h.php"""
try:
r = value
vs = getAllVarsByName(model, "v")
# addConsXor method (And/Or: TBI) ###
method_name = "addCons%s" % logical.capitalize()
try:
_model_addConsLogical = getattr(model, method_name)
_model_addConsLogical(vs, r)
except AttributeError as e:
raise AttributeError("%s not implemented" % method_name)
model.optimize()
assert model.getStatus() == "optimal"
if verbose:
printOutput(model)
return True
except Exception as e:
if verbose:
print("%s: %s" % (e.__class__.__name__, e))
return False
# TEST FUNCTIONS
@pytest.mark.parametrize("nconss", [1, 2, "all"])
@pytest.mark.parametrize("vconss", [0, 1])
@pytest.mark.parametrize("sense", ["min", "max"])
@pytest.mark.parametrize("logical", ["and", "or", "xor"])
@pytest.mark.parametrize("noperators", [2, 20, 51, 100])
@pytest.mark.parametrize("vtype", ["B"])
def test_variable(noperators, vtype, logical, sense, vconss, nconss):
if nconss == "all":
nconss = noperators
if vtype in ["I", "C"]:
pytest.skip("unsupported vtype \"%s\" may raise errors or unexpected results" % vtype)
m = setModel(vtype, logical, noperators)
setConss(m, vtype, vconss, nconss)
success = main_variable(m, logical, sense)
assert(success), "Status is not optimal"
@pytest.mark.parametrize("nconss", [1, 2, "all"])
@pytest.mark.parametrize("vconss", [0, 1])
@pytest.mark.parametrize("value", [False, True])
@pytest.mark.parametrize("logical", ["xor", "and", "or"])
@pytest.mark.parametrize("noperators", [2, 20, 51, 100])
@pytest.mark.parametrize("vtype", ["B"])
def test_boolean(noperators, vtype, logical, value, vconss, nconss):
if nconss == "all":
nconss = noperators
if vtype in ["I", "C"]:
pytest.skip("unsupported vtype \"%s\" may raise errors or unexpected results" % vtype)
if logical in ["and", "or"]:
pytest.skip("unsupported logical: %s" % vtype)
if logical == "xor" and nconss == noperators and noperators % 2 & vconss != value:
pytest.xfail("addConsXor cannot be %s if an %s number of variables are all constraint to %s" % (value, noperators, vconss))
m = setModel(vtype, logical, noperators)
setConss(m, vtype, vconss, nconss)
success = main_boolean(m, logical, value)
assert(success), "Test is not successful"
| 5,697 | 32.715976 | 131 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_lp.py | from pyscipopt import LP
def test_lp():
# create LP instance, minimizing by default
myLP = LP()
# create cols w/o coefficients, 0 objective coefficient and 0,\infty bounds
myLP.addCols(2 * [[]])
# create rows
myLP.addRow(entries = [(0,1),(1,2)] ,lhs = 5)
lhs, rhs = myLP.getSides()
assert lhs[0] == 5.0
assert rhs[0] == myLP.infinity()
assert(myLP.ncols() == 2)
myLP.chgObj(0, 1.0)
myLP.chgObj(1, 4.0)
solval = myLP.solve()
assert round(5.0 == solval)
if __name__ == "__main__":
test_lp()
| 556 | 20.423077 | 79 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_memory.py | import pytest
from pyscipopt.scip import Model, is_memory_freed
from util import is_optimized_mode
def test_not_freed():
if is_optimized_mode():
pytest.skip()
m = Model()
assert not is_memory_freed()
def test_freed():
if is_optimized_mode():
pytest.skip()
m = Model()
del m
assert is_memory_freed()
if __name__ == "__main__":
test_not_freed()
test_freed()
| 409 | 18.52381 | 49 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_model.py | from pyscipopt import Model
def test_model():
# create solver instance
s = Model()
# add some variables
x = s.addVar("x", vtype = 'C', obj = 1.0)
y = s.addVar("y", vtype = 'C', obj = 2.0)
assert x.getObj() == 1.0
assert y.getObj() == 2.0
s.setObjective(4.0 * y + 10.5, clear = False)
assert x.getObj() == 1.0
assert y.getObj() == 4.0
assert s.getObjoffset() == 10.5
# add some constraint
c = s.addCons(x + 2 * y >= 1.0)
assert c.isLinear()
s.chgLhs(c, 5.0)
s.chgRhs(c, 6.0)
assert s.getLhs(c) == 5.0
assert s.getRhs(c) == 6.0
# solve problem
s.optimize()
solution = s.getBestSol()
# print solution
assert (s.getVal(x) == s.getSolVal(solution, x))
assert (s.getVal(y) == s.getSolVal(solution, y))
assert round(s.getVal(x)) == 5.0
assert round(s.getVal(y)) == 0.0
assert s.getSlack(c, solution) == 0.0
assert s.getSlack(c, solution, 'lhs') == 0.0
assert s.getSlack(c, solution, 'rhs') == 1.0
assert s.getActivity(c, solution) == 5.0
s.writeProblem('model')
s.writeProblem('model.lp')
s.freeProb()
s = Model()
x = s.addVar("x", vtype = 'C', obj = 1.0)
y = s.addVar("y", vtype = 'C', obj = 2.0)
c = s.addCons(x + 2 * y <= 1.0)
s.setMaximize()
s.delCons(c)
s.optimize()
assert s.getStatus() == 'unbounded'
if __name__ == "__main__":
test_model()
| 1,424 | 22.360656 | 52 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_nonlinear.py | import pytest
from pyscipopt import Model, quicksum, sqrt
# test string with polynomial formulation (uses only Expr)
def test_string_poly():
PI = 3.141592653589793238462643
NWIRES = 11
DIAMETERS = [0.207, 0.225, 0.244, 0.263, 0.283, 0.307, 0.331, 0.362, 0.394, 0.4375, 0.500]
PRELOAD = 300.0
MAXWORKLOAD = 1000.0
MAXDEFLECT = 6.0
DEFLECTPRELOAD = 1.25
MAXFREELEN = 14.0
MAXCOILDIAM = 3.0
MAXSHEARSTRESS = 189000.0
SHEARMOD = 11500000.0
m = Model()
coil = m.addVar('coildiam')
wire = m.addVar('wirediam')
defl = m.addVar('deflection', lb=DEFLECTPRELOAD / (MAXWORKLOAD - PRELOAD), ub=MAXDEFLECT / PRELOAD)
ncoils = m.addVar('ncoils', vtype='I')
const1 = m.addVar('const1')
const2 = m.addVar('const2')
volume = m.addVar('volume')
y = [m.addVar('wire%d' % i, vtype='B') for i in range(NWIRES)]
obj = 1.0 * volume
m.setObjective(obj, 'minimize')
m.addCons(PI/2*(ncoils + 2)*coil*wire**2 - volume == 0, name='voldef')
# defconst1: coil / wire - const1 == 0.0
m.addCons(coil - const1*wire == 0, name='defconst1')
# defconst2: (4.0*const1 - 1.0) / (4.0*const1 - 4.0) + 0.615 / const1 - const2 == 0.0
d1 = (4.0*const1 - 4.0)
d2 = const1
m.addCons((4.0*const1 - 1.0)*d2 + 0.615*d1 - const2*d1*d2 == 0, name='defconst2')
m.addCons(8.0*MAXWORKLOAD/PI*const1*const2 - MAXSHEARSTRESS*wire**2 <= 0.0, name='shear')
# defdefl: 8.0/shearmod * ncoils * const1^3 / wire - defl == 0.0
m.addCons(8.0/SHEARMOD*ncoils*const1**3 - defl*wire == 0.0, name="defdefl")
m.addCons(MAXWORKLOAD*defl + 1.05*ncoils*wire + 2.1*wire <= MAXFREELEN, name='freel')
m.addCons(coil + wire <= MAXCOILDIAM, name='coilwidth')
m.addCons(quicksum(c*v for (c,v) in zip(DIAMETERS, y)) - wire == 0, name='defwire')
m.addCons(quicksum(y) == 1, name='selectwire')
m.optimize()
assert abs(m.getPrimalbound() - 1.6924910128) < 1.0e-5
# test string with original formulation (uses GenExpr)
def test_string():
PI = 3.141592653589793238462643
NWIRES = 11
DIAMETERS = [0.207, 0.225, 0.244, 0.263, 0.283, 0.307, 0.331, 0.362, 0.394, 0.4375, 0.500]
PRELOAD = 300.0
MAXWORKLOAD = 1000.0
MAXDEFLECT = 6.0
DEFLECTPRELOAD = 1.25
MAXFREELEN = 14.0
MAXCOILDIAM = 3.0
MAXSHEARSTRESS = 189000.0
SHEARMOD = 11500000.0
m = Model()
coil = m.addVar('coildiam')
wire = m.addVar('wirediam')
defl = m.addVar('deflection', lb=DEFLECTPRELOAD / (MAXWORKLOAD - PRELOAD), ub=MAXDEFLECT / PRELOAD)
ncoils = m.addVar('ncoils', vtype='I')
const1 = m.addVar('const1')
const2 = m.addVar('const2')
volume = m.addVar('volume')
y = [m.addVar('wire%d' % i, vtype='B') for i in range(NWIRES)]
obj = 1.0 * volume
m.setObjective(obj, 'minimize')
m.addCons(PI/2*(ncoils + 2)*coil*wire**2 - volume == 0, name='voldef')
m.addCons(coil / wire - const1 == 0, name='defconst1')
m.addCons((4.0*const1 - 1.0) / (4.0*const1 - 4.0) + 0.615 / const1 - const2 == 0, name='defconst2')
m.addCons(8.0*MAXWORKLOAD/PI*const1*const2 - MAXSHEARSTRESS*wire**2 <= 0.0, name='shear')
m.addCons(8.0/SHEARMOD*ncoils*const1**3 / wire - defl == 0.0, name="defdefl")
m.addCons(MAXWORKLOAD*defl + 1.05*ncoils*wire + 2.1*wire <= MAXFREELEN, name='freel')
m.addCons(coil + wire <= MAXCOILDIAM, name='coilwidth')
m.addCons(quicksum(c*v for (c,v) in zip(DIAMETERS, y)) - wire == 0, name='defwire')
m.addCons(quicksum(y) == 1, name='selectwire')
m.optimize()
assert abs(m.getPrimalbound() - 1.6924910128) < 1.0e-6
# test circle: find circle of smallest radius that encloses the given points
def test_circle():
points =[
(2.802686, 1.398947),
(4.719673, 4.792101),
(1.407758, 7.769566),
(2.253320, 2.373641),
(8.583144, 9.769102),
(3.022725, 5.470335),
(5.791380, 1.214782),
(8.304504, 8.196392),
(9.812677, 5.284600),
(9.445761, 9.541600)]
m = Model()
a = m.addVar('a', lb=None)
b = m.addVar('b', ub=None)
r = m.addVar('r')
# minimize radius
m.setObjective(r, 'minimize')
for i,p in enumerate(points):
# NOTE: SCIP will not identify this as SOC constraints!
m.addCons( sqrt((a - p[0])**2 + (b - p[1])**2) <= r, name = 'point_%d'%i)
m.optimize()
bestsol = m.getBestSol()
assert abs(m.getSolVal(bestsol, r) - 5.2543) < 1.0e-3
assert abs(m.getSolVal(bestsol, a) - 6.1242) < 1.0e-3
assert abs(m.getSolVal(bestsol, b) - 5.4702) < 1.0e-3
# test gastrans: see example in <scip path>/examples/CallableLibrary/src/gastrans.c
# of course there is a more pythonic/elegant way of implementing this, probably
# starting by using a proper graph structure
def test_gastrans():
GASTEMP = 281.15
RUGOSITY = 0.05
DENSITY = 0.616
COMPRESSIBILITY = 0.8
nodes = [
# name supplylo supplyup pressurelo pressureup cost
("Anderlues", 0.0, 1.2, 0.0, 66.2, 0.0 ), # 0
("Antwerpen", None, -4.034, 30.0, 80.0, 0.0 ), # 1
("Arlon", None, -0.222, 0.0, 66.2, 0.0 ), # 2
("Berneau", 0.0, 0.0, 0.0, 66.2, 0.0 ), # 3
("Blaregnies", None, -15.616, 50.0, 66.2, 0.0 ), # 4
("Brugge", None, -3.918, 30.0, 80.0, 0.0 ), # 5
("Dudzele", 0.0, 8.4, 0.0, 77.0, 2.28 ), # 6
("Gent", None, -5.256, 30.0, 80.0, 0.0 ), # 7
("Liege", None, -6.385, 30.0, 66.2, 0.0 ), # 8
("Loenhout", 0.0, 4.8, 0.0, 77.0, 2.28 ), # 9
("Mons", None, -6.848, 0.0, 66.2, 0.0 ), # 10
("Namur", None, -2.120, 0.0, 66.2, 0.0 ), # 11
("Petange", None, -1.919, 25.0, 66.2, 0.0 ), # 12
("Peronnes", 0.0, 0.96, 0.0, 66.2, 1.68 ), # 13
("Sinsin", 0.0, 0.0, 0.0, 63.0, 0.0 ), # 14
("Voeren", 20.344, 22.012, 50.0, 66.2, 1.68 ), # 15
("Wanze", 0.0, 0.0, 0.0, 66.2, 0.0 ), # 16
("Warnand", 0.0, 0.0, 0.0, 66.2, 0.0 ), # 17
("Zeebrugge", 8.87, 11.594, 0.0, 77.0, 2.28 ), # 18
("Zomergem", 0.0, 0.0, 0.0, 80.0, 0.0 ) # 19
]
arcs = [
# node1 node2 diameter length active */
( 18, 6, 890.0, 4.0, False ),
( 18, 6, 890.0, 4.0, False ),
( 6, 5, 890.0, 6.0, False ),
( 6, 5, 890.0, 6.0, False ),
( 5, 19, 890.0, 26.0, False ),
( 9, 1, 590.1, 43.0, False ),
( 1, 7, 590.1, 29.0, False ),
( 7, 19, 590.1, 19.0, False ),
( 19, 13, 890.0, 55.0, False ),
( 15, 3, 890.0, 5.0, True ),
( 15, 3, 395.0, 5.0, True ),
( 3, 8, 890.0, 20.0, False ),
( 3, 8, 395.0, 20.0, False ),
( 8, 17, 890.0, 25.0, False ),
( 8, 17, 395.0, 25.0, False ),
( 17, 11, 890.0, 42.0, False ),
( 11, 0, 890.0, 40.0, False ),
( 0, 13, 890.0, 5.0, False ),
( 13, 10, 890.0, 10.0, False ),
( 10, 4, 890.0, 25.0, False ),
( 17, 16, 395.5, 10.5, False ),
( 16, 14, 315.5, 26.0, True ),
( 14, 2, 315.5, 98.0, False ),
( 2, 12, 315.5, 6.0, False )
]
scip = Model()
# create flow variables
flow = {}
for arc in arcs:
flow[arc] = scip.addVar("flow_%s_%s"%(nodes[arc[0]][0],nodes[arc[1]][0]), # names of nodes in arc
lb = 0.0 if arc[4] else None) # no lower bound if not active
# pressure difference variables
pressurediff = {}
for arc in arcs:
pressurediff[arc] = scip.addVar("pressurediff_%s_%s"%(nodes[arc[0]][0],nodes[arc[1]][0]), # names of nodes in arc
lb = None)
# supply variables
supply = {}
for node in nodes:
supply[node] = scip.addVar("supply_%s"%(node[0]), lb = node[1], ub = node[2], obj = node[5])
# square pressure variables
pressure = {}
for node in nodes:
pressure[node] = scip.addVar("pressure_%s"%(node[0]), lb = node[3]**2, ub = node[4]**2)
# node balance constrains, for each node i: outflows - inflows = supply
for nid, node in enumerate(nodes):
# find arcs that go or end at this node
flowbalance = 0
for arc in arcs:
if arc[0] == nid: # arc is outgoing
flowbalance += flow[arc]
elif arc[1] == nid: # arc is incoming
flowbalance -= flow[arc]
else:
continue
scip.addCons(flowbalance == supply[node], name="flowbalance%s"%node[0])
# pressure difference constraints: pressurediff[node1 to node2] = pressure[node1] - pressure[node2]
for arc in arcs:
scip.addCons(pressurediff[arc] == pressure[nodes[arc[0]]] - pressure[nodes[arc[1]]], "pressurediffcons_%s_%s"%(nodes[arc[0]][0],nodes[arc[1]][0]))
# pressure loss constraints:
# active arc: flow[arc]^2 + coef * pressurediff[arc] <= 0.0
# regular pipes: flow[arc] * abs(flow[arc]) - coef * pressurediff[arc] == 0.0
# coef = 96.074830e-15*diameter(i)^5/(lambda*compressibility*temperatur*length(i)*density)
# lambda = (2*log10(3.7*diameter(i)/rugosity))^(-2)
from math import log10
for arc in arcs:
coef = 96.074830e-15 * arc[2]**5 * (2.0*log10(3.7*arc[2]/RUGOSITY))**2 / COMPRESSIBILITY / GASTEMP / arc[3] / DENSITY
if arc[4]: # active
scip.addCons(flow[arc]**2 + coef * pressurediff[arc] <= 0.0, "pressureloss_%s_%s"%(nodes[arc[0]][0],nodes[arc[1]][0]))
else:
scip.addCons(flow[arc]*abs(flow[arc]) - coef * pressurediff[arc] == 0.0, "pressureloss_%s_%s"%(nodes[arc[0]][0],nodes[arc[1]][0]))
scip.setRealParam('limits/time', 5)
scip.optimize()
if scip.getStatus() == 'timelimit':
pytest.skip()
assert abs(scip.getPrimalbound() - 89.08584) < 1.0e-9
def test_quad_coeffs():
"""test coefficient access method for quadratic constraints"""
scip = Model()
x = scip.addVar()
y = scip.addVar()
z = scip.addVar()
c = scip.addCons(2*x*y + 0.5*x**2 + 4*z >= 10)
assert c.isQuadratic()
bilinterms, quadterms, linterms = scip.getTermsQuadratic(c)
assert bilinterms[0][0].name == x.name
assert bilinterms[0][1].name == y.name
assert bilinterms[0][2] == 2
assert quadterms[0][0].name == x.name
assert quadterms[0][1] == 0.5
assert linterms[0][0].name == z.name
assert linterms[0][1] == 4
| 11,399 | 38.721254 | 154 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_pricer.py | from pyscipopt import Model, Pricer, SCIP_RESULT, SCIP_PARAMSETTING, quicksum
class CutPricer(Pricer):
# The reduced cost function for the variable pricer
def pricerredcost(self):
# Retrieving the dual solutions
dualSolutions = []
for i, c in enumerate(self.data['cons']):
dualSolutions.append(self.model.getDualMultiplier(c))
# Building a MIP to solve the subproblem
subMIP = Model("CuttingStock-Sub")
# Turning off presolve
subMIP.setPresolve(SCIP_PARAMSETTING.OFF)
# Setting the verbosity level to 0
subMIP.hideOutput()
cutWidthVars = []
varNames = []
varBaseName = "CutWidth"
# Variables for the subMIP
for i in range(len(dualSolutions)):
varNames.append(varBaseName + "_" + str(i))
cutWidthVars.append(subMIP.addVar(varNames[i], vtype = "I", obj = -1.0 * dualSolutions[i]))
# Adding the knapsack constraint
knapsackCons = subMIP.addCons(
quicksum(w*v for (w,v) in zip(self.data['widths'], cutWidthVars)) <= self.data['rollLength'])
# Solving the subMIP to generate the most negative reduced cost pattern
subMIP.optimize()
objval = 1 + subMIP.getObjVal()
# Adding the column to the master problem
if objval < -1e-08:
currentNumVar = len(self.data['var'])
# Creating new var; must set pricedVar to True
newVar = self.model.addVar("NewPattern_" + str(currentNumVar), vtype = "C", obj = 1.0, pricedVar = True)
# Adding the new variable to the constraints of the master problem
newPattern = []
for i, c in enumerate(self.data['cons']):
coeff = round(subMIP.getVal(cutWidthVars[i]))
self.model.addConsCoeff(c, newVar, coeff)
newPattern.append(coeff)
# Storing the new variable in the pricer data.
self.data['patterns'].append(newPattern)
self.data['var'].append(newVar)
return {'result':SCIP_RESULT.SUCCESS}
# The initialisation function for the variable pricer to retrieve the transformed constraints of the problem
def pricerinit(self):
for i, c in enumerate(self.data['cons']):
self.data['cons'][i] = self.model.getTransformedCons(c)
def test_cuttingstock():
# create solver instance
s = Model("CuttingStock")
s.setPresolve(0)
# creating a pricer
pricer = CutPricer()
s.includePricer(pricer, "CuttingStockPricer", "Pricer to identify new cutting stock patterns")
# item widths
widths = [14, 31, 36, 45]
# width demand
demand = [211, 395, 610, 97]
# roll length
rollLength = 100
assert len(widths) == len(demand)
# adding the initial variables
cutPatternVars = []
varNames = []
varBaseName = "Pattern"
patterns = []
initialCoeffs = []
for i in range(len(widths)):
varNames.append(varBaseName + "_" + str(i))
cutPatternVars.append(s.addVar(varNames[i], obj = 1.0))
# adding a linear constraint for the knapsack constraint
demandCons = []
for i in range(len(widths)):
numWidthsPerRoll = float(int(rollLength/widths[i]))
demandCons.append(s.addCons(numWidthsPerRoll*cutPatternVars[i] >= demand[i],
separate = False, modifiable = True))
newPattern = [0]*len(widths)
newPattern[i] = numWidthsPerRoll
patterns.append(newPattern)
# Setting the pricer_data for use in the init and redcost functions
pricer.data = {}
pricer.data['var'] = cutPatternVars
pricer.data['cons'] = demandCons
pricer.data['widths'] = widths
pricer.data['demand'] = demand
pricer.data['rollLength'] = rollLength
pricer.data['patterns'] = patterns
# solve problem
s.optimize()
# print original data
printWidths = '\t'.join(str(e) for e in widths)
print('\nInput Data')
print('==========')
print('Roll Length:', rollLength)
print('Widths:\t', printWidths)
print('Demand:\t', '\t'.join(str(e) for e in demand))
# print solution
widthOutput = [0]*len(widths)
print('\nResult')
print('======')
print('\t\tSol Value', '\tWidths\t', printWidths)
for i in range(len(pricer.data['var'])):
rollUsage = 0
solValue = round(s.getVal(pricer.data['var'][i]))
if solValue > 0:
outline = 'Pattern_' + str(i) + ':\t' + str(solValue) + '\t\tCuts:\t '
for j in range(len(widths)):
rollUsage += pricer.data['patterns'][i][j]*widths[j]
widthOutput[j] += pricer.data['patterns'][i][j]*solValue
outline += str(pricer.data['patterns'][i][j]) + '\t'
outline += 'Usage:' + str(rollUsage)
print(outline)
print('\t\t\tTotal Output:\t', '\t'.join(str(e) for e in widthOutput))
assert s.getObjVal() == 452.25
if __name__ == '__main__':
test_cuttingstock()
| 5,049 | 32.892617 | 116 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_quadcons.py | from pyscipopt import Model
def test_niceqp():
s = Model()
x = s.addVar("x")
y = s.addVar("y")
s.addCons(x >= 2)
s.addCons(x*x <= y)
s.setObjective(y, sense='minimize')
s.optimize()
assert round(s.getVal(x)) == 2.0
assert round(s.getVal(y)) == 4.0
def test_niceqcqp():
s = Model()
x = s.addVar("x")
y = s.addVar("y")
s.addCons(x*x + y*y <= 2)
s.setObjective(x + y, sense='maximize')
s.optimize()
assert round(s.getVal(x)) == 1.0
assert round(s.getVal(y)) == 1.0
if __name__ == "__main__":
test_niceqp()
test_niceqcqp()
| 604 | 17.333333 | 43 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_quickprod.py | from pyscipopt import Model, quickprod
from pyscipopt.scip import CONST
from operator import mul
import functools
def test_quickprod_model():
m = Model("quickprod")
x = m.addVar("x")
y = m.addVar("y")
z = m.addVar("z")
c = 2.3
q = quickprod([x,y,z,c]) == 0.0
s = functools.reduce(mul,[x,y,z,c],1) == 0.0
assert(q.expr.terms == s.expr.terms)
def test_quickprod():
empty = quickprod(1 for i in [])
assert len(empty.terms) == 1
assert CONST in empty.terms
def test_largequadratic():
# inspired from performance issue on
# http://stackoverflow.com/questions/38434300
m = Model("dense_quadratic")
dim = 20
x = [m.addVar("x_%d" % i) for i in range(dim)]
expr = quickprod((i+j+1)*x[i]*x[j]
for i in range(dim)
for j in range(dim))
cons = expr <= 1.0
# upper triangle, diagonal
assert cons.expr.degree() == 2*dim*dim
m.addCons(cons)
# TODO: what can we test beyond the lack of crashes?
if __name__ == "__main__":
test_quickprod()
test_quickprod_model()
test_largequadratic()
| 1,147 | 25.697674 | 63 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_quicksum.py | from pyscipopt import Model, quicksum
from pyscipopt.scip import CONST
def test_quicksum_model():
m = Model("quicksum")
x = m.addVar("x")
y = m.addVar("y")
z = m.addVar("z")
c = 2.3
q = quicksum([x,y,z,c]) == 0.0
s = sum([x,y,z,c]) == 0.0
assert(q.expr.terms == s.expr.terms)
def test_quicksum():
empty = quicksum(1 for i in [])
assert len(empty.terms) == 1
assert CONST in empty.terms
def test_largequadratic():
# inspired from performance issue on
# http://stackoverflow.com/questions/38434300
m = Model("dense_quadratic")
dim = 200
x = [m.addVar("x_%d" % i) for i in range(dim)]
expr = quicksum((i+j+1)*x[i]*x[j]
for i in range(dim)
for j in range(dim))
cons = expr <= 1.0
# upper triangle, diagonal
assert len(cons.expr.terms) == dim * (dim-1) / 2 + dim
m.addCons(cons)
# TODO: what can we test beyond the lack of crashes?
if __name__ == "__main__":
test_quicksum()
test_quicksum_model()
test_largequadratic()
| 1,099 | 25.829268 | 63 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_relax.py | from pyscipopt import Model
from pyscipopt.scip import Relax
calls = []
class SoncRelax(Relax):
def relaxexec(self):
calls.append('relaxexec')
def test_relax():
m = Model()
m.hideOutput()
#include relaxator
m.includeRelax(SoncRelax(),'testrelaxator','Test that relaxator gets included')
#add Variables
x0 = m.addVar(vtype = "C", name = "x0")
x1 = m.addVar(vtype = "C", name = "x1")
x2 = m.addVar(vtype = "C", name = "x2")
#addCons
m.addCons(x0 >= 2)
m.addCons(x0**2 <= x1)
m.addCons(x1 * x2 >= x0)
m.setObjective(x1 + x0)
m.optimize()
print(m.getVal(x0))
assert 'relaxexec' in calls
assert len(calls) == 1
if __name__ == "__main__":
test_relax()
| 767 | 20.333333 | 83 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_short.py | from pyscipopt import Model
import pytest
import os
# This test requires a directory link in tests/ to check/ in the main SCIP directory.
testset = []
primalsolutions = {}
dualsolutions = {}
tolerance = 1e-5
infinity = 1e20
testsetpath = 'check/testset/short.test'
solufilepath = 'check/testset/short.solu'
if not all(os.path.isfile(fn) for fn in [testsetpath, solufilepath]):
if pytest.__version__ < "3.0.0":
pytest.skip("Files for testset `short` not found (symlink missing?)")
else:
pytestmark = pytest.mark.skip
else:
with open(testsetpath, 'r') as f:
for line in f.readlines():
testset.append('check/' + line.rstrip('\n'))
with open(solufilepath, 'r') as f:
for line in f.readlines():
if len(line.split()) == 2:
[s, name] = line.split()
else:
[s, name, value] = line.split()
if s == '=opt=':
primalsolutions[name] = float(value)
dualsolutions[name] = float(value)
elif s == '=inf=':
primalsolutions[name] = infinity
dualsolutions[name] = infinity
elif s == '=best=':
primalsolutions[name] = float(value)
elif s == '=best dual=':
dualsolutions[name] = float(value)
# status =unkn= needs no data
def relGE(v1, v2, tol = tolerance):
if v1 is None or v2 is None:
return True
else:
reltol = tol * max(abs(v1), abs(v2), 1.0)
return (v1 - v2) >= -reltol
def relLE(v1, v2, tol = tolerance):
if v1 is None or v2 is None:
return True
else:
reltol = tol * max(abs(v1), abs(v2), 1.0)
return (v1 - v2) <= reltol
@pytest.mark.parametrize('instance', testset)
def test_instance(instance):
s = Model()
s.hideOutput()
s.readProblem(instance)
s.optimize()
name = os.path.split(instance)[1]
if name.rsplit('.',1)[1].lower() == 'gz':
name = name.rsplit('.',2)[0]
else:
name = name.rsplit('.',1)[0]
# we do not need the solution status
primalbound = s.getObjVal()
dualbound = s.getDualbound()
# get solution data from solu file
primalsolu = primalsolutions.get(name, None)
dualsolu = dualsolutions.get(name, None)
if s.getObjectiveSense() == 'minimize':
assert relGE(primalbound, dualsolu)
assert relLE(dualbound, primalsolu)
else:
if( primalsolu == infinity ): primalsolu = -infinity
if( dualsolu == infinity ): dualsolu = -infinity
assert relLE(primalbound, dualsolu)
assert relGE(dualbound, primalsolu)
| 2,667 | 28.644444 | 85 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_tsp.py | from pyscipopt import Model, Conshdlr, quicksum, SCIP_RESULT
import pytest
itertools = pytest.importorskip("itertools")
networkx = pytest.importorskip("networkx")
EPS = 1.e-6
# subtour elimination constraint handler
class TSPconshdlr(Conshdlr):
def __init__(self, variables):
self.variables = variables
# find subtours in the graph induced by the edges {i,j} for which x[i,j] is positive
# at the given solution; when solution is None, then the LP solution is used
def find_subtours(self, solution = None):
edges = []
x = self.variables
for (i, j) in x:
if self.model.getSolVal(solution, x[i, j]) > EPS:
edges.append((i, j))
G = networkx.Graph()
G.add_edges_from(edges)
components = list(networkx.connected_components(G))
if len(components) == 1:
return []
else:
return components
# checks whether solution is feasible, ie, if there are no subtours;
# since the checkpriority is < 0, we are only called if the integrality
# constraint handler didn't find infeasibility, so solution is integral
def conscheck(self, constraints, solution, check_integrality,
check_lp_rows, print_reason, completely, **results):
if self.find_subtours(solution):
return {"result": SCIP_RESULT.INFEASIBLE}
else:
return {"result": SCIP_RESULT.FEASIBLE}
# enforces LP solution
def consenfolp(self, constraints, n_useful_conss, sol_infeasible):
subtours = self.find_subtours()
if subtours:
x = self.variables
for subset in subtours:
self.model.addCons(quicksum(x[i, j] for(i, j) in pairs(subset))
<= len(subset) - 1)
print("cut: len(%s) <= %s" % (subset, len(subset) - 1))
return {"result": SCIP_RESULT.CONSADDED}
else:
return {"result": SCIP_RESULT.FEASIBLE}
def conslock(self, constraint, locktype, nlockspos, nlocksneg):
pass
# builds tsp model; adds variables, degree constraint and the subtour elimination constaint handler
def create_tsp(vertices, distance):
model = Model("TSP")
x = {} # binary variable to select edges
for (i, j) in pairs(vertices):
x[i, j] = model.addVar(vtype = "B", name = "x(%s,%s)" % (i, j))
for i in vertices:
model.addCons(quicksum(x[j, i] for j in vertices if j < i) +
quicksum(x[i, j] for j in vertices if j > i) == 2, "Degree(%s)" % i)
conshdlr = TSPconshdlr(x)
model.includeConshdlr(conshdlr, "TSP", "TSP subtour eliminator",
chckpriority = -10, needscons = False)
model.setBoolParam("misc/allowdualreds", False)
model.setObjective(quicksum(distance[i, j] * x[i, j] for (i, j) in pairs(vertices)),
"minimize")
return model, x
def solve_tsp(vertices, distance):
model, x = create_tsp(vertices, distance)
model.optimize()
edges = []
for (i, j) in x:
if model.getVal(x[i, j]) > EPS:
edges.append((i, j))
return model.getObjVal(), edges
# returns all undirected edges between vertices
def pairs(vertices):
return itertools.combinations(vertices, 2)
def test_main():
vertices = [1, 2, 3, 4, 5, 6]
distance = {(u, v):1 for (u, v) in pairs(vertices)}
for u in vertices[:3]:
for v in vertices[3:]:
distance[u, v] = 10
objective_value, edges = solve_tsp(vertices, distance)
print("Optimal tour:", edges)
print("Optimal cost:", objective_value)
if __name__ == "__main__":
test_main()
| 3,707 | 30.159664 | 99 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/test_variablebounds.py | from pyscipopt import Model
m = Model()
x0 = m.addVar(lb=-5, ub=8)
r1 = m.addVar()
r2 = m.addVar()
y0 = m.addVar(lb=3)
t = m.addVar(lb=None)
z = m.addVar()
m.chgVarLbGlobal(x0, -2)
m.chgVarUbGlobal(x0, 4)
infeas, tightened = m.tightenVarLb(x0, -5)
assert not infeas
assert not tightened
infeas, tightened = m.tightenVarLbGlobal(x0, -1)
assert not infeas
assert tightened
infeas, tightened = m.tightenVarUb(x0, 3)
assert not infeas
assert tightened
infeas, tightened = m.tightenVarUbGlobal(x0, 9)
assert not infeas
assert not tightened
infeas, fixed = m.fixVar(z, 7)
assert not infeas
assert fixed
assert m.delVar(z)
m.addCons(r1 >= x0)
m.addCons(r2 >= -x0)
m.addCons(y0 == r1 +r2)
m.setObjective(t)
m.addCons(t >= r1 * (r1 - x0) + r2 * (r2 + x0))
m.optimize()
print("x0", m.getVal(x0))
print("r1", m.getVal(r1))
print("r2", m.getVal(r2))
print("y0", m.getVal(y0))
print("t", m.getVal(t))
| 899 | 17.367347 | 48 | py |
PB-DFS | PB-DFS-master/PySCIPOpt/tests/util.py | from pyscipopt.scip import Model, is_memory_freed
def is_optimized_mode():
s = Model()
return is_memory_freed()
| 123 | 14.5 | 49 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/config.py | import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
'problem',
choices=['mis', 'ca', 'ds', 'vc'],
)
parser.add_argument('--learning_rate', default=0.01)
parser.add_argument('--epochs', default=200)
parser.add_argument('--hidden1', default=64)
parser.add_argument('--dropout', default=0)
parser.add_argument('--weight_decay', default=5e-4)
parser.add_argument('--early_stopping', default=10)
parser.add_argument('--max_degree', default=1)
parser.add_argument('--num_layers', default=20)
args = parser.parse_args()
| 544 | 29.277778 | 52 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/inits.py | import tensorflow as tf
import numpy as np
def uniform(shape, scale=0.05, name=None):
"""Uniform init."""
initial = tf.random.uniform(shape, minval=-scale, maxval=scale, dtype=tf.float32)
return tf.Variable(initial, name=name)
def glorot(shape, name=None):
"""Glorot & Bengio (AISTATS 2010) init."""
init_range = np.sqrt(6.0/(shape[0]+shape[1]))
initial = tf.random.uniform(shape, minval=-init_range, maxval=init_range, dtype=tf.float32)
return tf.Variable(initial, name=name)
def zeros(shape, name=None):
"""All zeros."""
initial = tf.zeros(shape, dtype=tf.float32)
return tf.Variable(initial, name=name)
def ones(shape, name=None):
"""All ones."""
initial = tf.ones(shape, dtype=tf.float32)
return tf.Variable(initial, name=name) | 791 | 28.333333 | 95 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/layers.py | from inits import *
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from config import args
keras.backend.set_floatx('float32')
import sys, os
# global unique layer ID dictionary for layer name assignment
_LAYER_UIDS = {}
def get_layer_uid(layer_name=''):
"""Helper function, assigns unique layer IDs."""
if layer_name not in _LAYER_UIDS:
_LAYER_UIDS[layer_name] = 1
return 1
else:
_LAYER_UIDS[layer_name] += 1
return _LAYER_UIDS[layer_name]
def sparse_dropout(x, rate, noise_shape):
"""
Dropout for sparse tensors.
"""
random_tensor = 1 - rate
random_tensor += tf.random.uniform(noise_shape)
dropout_mask = tf.cast(tf.floor(random_tensor), dtype=tf.bool)
pre_out = tf.sparse.retain(x, dropout_mask)
return pre_out * (1./(1 - rate))
def dot(x, y, sparse=False):
"""
Wrapper for tf.matmul (sparse vs dense).
"""
if sparse:
res = tf.sparse.sparse_dense_matmul(x, y)
else:
res = tf.matmul(x, y)
return res
class Dense(layers.Layer):
"""Dense layer."""
def __init__(self, input_dim, output_dim, wp='dense', act=tf.nn.relu, bias=True, **kwargs):
super(Dense, self).__init__(**kwargs)
self.act = act
self.bias = bias
self.wp = wp
self.vars={}
self.vars[f'{self.wp}_weights'] = self.add_weight(
f'{self.wp}_weights', [input_dim, output_dim])
if self.bias:
self.vars[f'{self.wp}_bias'] = self.add_weight(
f'{self.wp}_bias', [output_dim])
def call(self, inputs):
x = inputs
# transform
output = dot(x, self.vars[f'{self.wp}_weights'], sparse=False)
# bias
if self.bias:
output += self.vars[f'{self.wp}_bias']
return self.act(output)
class Attention(layers.Layer):
def __init__(self, input_dim, act=tf.nn.softmax, wp='attn_weights', **kwargs):
super(Attention, self).__init__(**kwargs)
self.vars={}
self.wp=wp
self.input_dim = input_dim
self.act = act
self.vars[self.wp] = self.add_weight(self.wp, [input_dim, 1])
def call(self, input):
logits = dot(input, self.vars[self.wp], sparse=False)
norms = self.act(logits, axis=0)
return norms
class GraphConvolution(layers.Layer):
"""
Graph convolution layer.
"""
def __init__(self, attn_dict, act=tf.nn.relu, wp='TRI_GCN', **kwargs):
super(GraphConvolution, self).__init__(**kwargs)
self.vars={}
self.wp = wp
self.args = args
self.weight_dim = args.hidden1*2
self.act = act
self.attn_dict = attn_dict
self.vars[f'{self.wp}_vc_weights'] = self.add_weight(
f'{self.wp}_vc_weights', [self.weight_dim, args.hidden1])
self.vars[f'{self.wp}_cv_weights'] = self.add_weight(
f'{self.wp}_cv_weights', [self.weight_dim, args.hidden1])
self.vars[f'{self.wp}_co_weights'] = self.add_weight(
f'{self.wp}_co_weights', [self.weight_dim, args.hidden1])
self.vars[f'{self.wp}_oc_weights'] = self.add_weight(
f'{self.wp}_oc_weights', [self.weight_dim, args.hidden1])
self.vars[f'{self.wp}_vo_weights'] = self.add_weight(
f'{self.wp}_vo_weights', [self.weight_dim, args.hidden1])
self.vars[f'{self.wp}_ov_weights'] = self.add_weight(
f'{self.wp}_ov_weights', [self.weight_dim, args.hidden1])
def call(self, inputs):
zero = tf.constant(0, dtype=tf.float32)
col_hidden, row_hidden, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp = inputs
ncols = col_hidden.shape[0]
nrows = row_hidden.shape[0]
if args.dropout != 0:
col_hidden = tf.nn.dropout(col_hidden, 1-args.dropout)
row_hidden = tf.nn.dropout(row_hidden, 1-args.dropout)
obj_hidden = tf.nn.dropout(obj_hidden, 1-args.dropout)
# convolve v -> o
attn_coefs = self.attn_dict['attn_vo'](tf.concat([col_hidden, vo_supp, tf.broadcast_to(input=obj_hidden, shape=[ncols, args.hidden1])], axis=1))
# v_o_out: (?, 1).T (?, 64) -> (1, 64)
v_o_out = dot(tf.transpose(attn_coefs), col_hidden)
# obj_hidden: (1, 128) (128, 64) -> (1, 64)
obj_hidden = self.act(dot( tf.concat([obj_hidden, v_o_out], axis=1), self.vars[f'{self.wp}_vo_weights']))
# convolve v,o -> c
row_hidden_next = []
for i in tf.range(nrows):
neighbor_cols_mask = tf.not_equal(cv_supp[0, i, :], zero)
attn_coefs = self.attn_dict['attn_cv'](tf.concat([
tf.boolean_mask(col_hidden, neighbor_cols_mask, axis=0),
tf.transpose(tf.boolean_mask(cv_supp[:, i, :], neighbor_cols_mask, axis=1)),
tf.broadcast_to(row_hidden[i], [tf.reduce_sum(tf.cast(neighbor_cols_mask, dtype=tf.float32)), args.hidden1])], axis=1))
# v_out: (?, 1).T (?, 64) -> (1, 64)
v_out = dot(tf.transpose(attn_coefs), tf.boolean_mask(col_hidden, neighbor_cols_mask, axis=0))
# o_c_out: (1, 64))
o_c_out = self.act( dot( tf.concat([obj_hidden, tf.expand_dims(row_hidden[i], 0)], axis=1), self.vars[f'{self.wp}_oc_weights']))
row_hidden_next.append(self.act(dot(tf.concat([o_c_out, v_out], axis=1), self.vars[f'{self.wp}_vc_weights'])))
row_hidden_next = tf.squeeze(tf.stack(row_hidden_next))
# convolve c -> o
attn_coefs = self.attn_dict['attn_co'](tf.concat([row_hidden_next, co_supp, tf.broadcast_to(obj_hidden, [nrows, args.hidden1])], axis=1))
c_o_out = dot(tf.transpose(attn_coefs), row_hidden_next)
obj_hidden = self.act(dot(tf.concat([obj_hidden, c_o_out], axis=1), self.vars[f'{self.wp}_co_weights']))
# convolve c,o -> v
col_hidden_next = []
for i in tf.range(ncols):
neighbor_rows_mask = tf.not_equal(vc_supp[0,i,:], zero)
attn_coefs = self.attn_dict['attn_vc'](tf.concat([
tf.boolean_mask(row_hidden_next, neighbor_rows_mask, axis=0),
tf.transpose(tf.boolean_mask(vc_supp[:, i, :], neighbor_rows_mask, axis=1)),
tf.broadcast_to(col_hidden[i], [tf.reduce_sum(tf.cast(neighbor_rows_mask, dtype=tf.float32)), args.hidden1])], axis=1))
c_out = dot(tf.transpose(attn_coefs), tf.boolean_mask(row_hidden_next, neighbor_rows_mask, axis=0))
o_v_out = self.act( dot( tf.concat([obj_hidden, tf.expand_dims(col_hidden[i], 0)], axis=1), self.vars[f'{self.wp}_ov_weights']))
col_hidden_next.append(self.act(dot(tf.concat([o_v_out, c_out], axis=1), self.vars[f'{self.wp}_cv_weights'])))
col_hidden_next = tf.squeeze(tf.stack(col_hidden_next))
return col_hidden_next, row_hidden_next, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp | 7,122 | 41.147929 | 152 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/metrics.py | import tensorflow as tf
def masked_softmax_cross_entropy(preds, labels, mask):
"""
Softmax cross-entropy loss with masking.
"""
loss = tf.nn.softmax_cross_entropy_with_logits(logits=preds, labels=labels)
mask = tf.cast(mask, dtype=tf.float32)
mask /= tf.reduce_mean(mask)
loss *= mask
return tf.reduce_mean(loss)
def masked_accuracy(preds, labels, mask):
"""
Accuracy with masking.
"""
correct_prediction = tf.equal(tf.argmax(preds, 1), tf.argmax(labels, 1))
accuracy_all = tf.cast(correct_prediction, tf.float32)
mask = tf.cast(mask, dtype=tf.float32)
mask /= tf.reduce_mean(mask)
accuracy_all *= mask
return tf.reduce_mean(accuracy_all)
| 711 | 27.48 | 79 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/models.py | import tensorflow as tf
from tensorflow import keras
from layers import *
from metrics import *
from config import args
class GCN(keras.Model):
def __init__(self, output_dim, **kwargs):
super(GCN, self).__init__(**kwargs)
self.output_dim = output_dim
self.col_feats_dim = 57
self.row_feats_dim = 26
# projection layers
self.col_embedding = Dense(input_dim=self.col_feats_dim,
output_dim=args.hidden1,
act=tf.nn.relu,
wp='col_emb')
self.row_embedding = Dense(input_dim=self.row_feats_dim,
output_dim=args.hidden1,
act=tf.nn.relu,
wp='row_emb')
# attention layers
self.attn_dim = args.hidden1*2+2
self.attn_vc = Attention(self.attn_dim, wp='attn_vc')
self.attn_cv = Attention(self.attn_dim, wp='attn_cv')
self.attn_vo = Attention(self.attn_dim, wp='attn_vo')
self.attn_co = Attention(self.attn_dim, wp='attn_co')
self.attn_dict = {
'attn_vc': self.attn_vc,
'attn_cv': self.attn_cv,
'attn_vo': self.attn_vo,
'attn_co': self.attn_co,
}
# tri-conv layers
self.conv = GraphConvolution(self.attn_dict, wp=f'tri_conv_0')
# 2 fully connected layers at the end of the gcn
self.out1 = Dense(input_dim=args.hidden1*2, output_dim=32, act=tf.nn.relu,wp='out1')
self.out2 = Dense(input_dim=32, output_dim=2, act=lambda x: x, wp='out2')
def call(self, inputs):
col_feats, row_feats, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp, label, mask = inputs
col_hidden_t0 = self.col_embedding(col_feats)
row_hidden = self.row_embedding(row_feats)
input = col_hidden_t0, row_hidden, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp
output = self.conv(input)
col_hidden_tn = output[0]
col_logits = self.out2(self.out1(tf.concat([col_hidden_t0, col_hidden_tn], axis=1)))
# Weight decay loss
loss = tf.zeros([])
for var in self.conv.trainable_variables:
loss += args.weight_decay * tf.nn.l2_loss(var)
# Cross entropy error
loss += masked_softmax_cross_entropy(col_logits, label, mask)
acc = masked_accuracy(col_logits, label, mask)
return loss, acc
def predict(self, inputs):
col_feats, row_feats, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp, label, mask = inputs
col_hidden_t0 = self.col_embedding(col_feats)
row_hidden = self.row_embedding(row_feats)
input = col_hidden_t0, row_hidden, obj_hidden, cv_supp, vc_supp, vo_supp, co_supp
output = self.conv(input)
col_hidden_tn = output[0]
col_logits = self.out2(self.out1(tf.concat([col_hidden_t0, col_hidden_tn], axis=1)))
return tf.nn.softmax(col_logits) | 3,032 | 37.884615 | 98 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/test.py | import time, sys, os
from utils import *
from models import GCN
from config import args
import scipy.io as sio
import numpy as np
from copy import deepcopy
import scipy.sparse as sp
import sklearn.metrics as metrics
from os.path import expanduser
import gzip
import pickle
import pathlib
import tensorflow as tf;
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
print('tf version:', tf.__version__)
assert tf.__version__.startswith('2.')
if __name__ == '__main__':
filedir = os.path.dirname(__file__)
model_dir = f'{filedir}/../trained_models/{args.problem}/TRIG-GCN'
model = GCN( output_dim=2)
model.load_weights(f'{model_dir}/model.ckpt')
####### data #######
for data_dir in ['test_small', 'test_medium']:
data_path = f'{filedir}/../datasets/{args.problem}/{data_dir}'
data_files = list(pathlib.Path(data_path).glob('sample_*.pkl'))
data_files = [str(data_file) for data_file in data_files][:100]
os.makedirs(f'{filedir}/../ret_model', exist_ok=True)
logfile = f'{filedir}/../ret_model/{args.problem}_{data_dir}_TRIG_GCN.txt'
nsamples = len(data_files)
log(f'test dataset: <{data_path}>, number of instances: {nsamples}', logfile)
log(f'log write to: <{logfile}>', logfile)
t1 = time.time()
ct=0
yss = []
yhss = []
ncands = []
for idd in range(nsamples):
ct+=1
data = read_data(data_files[idd])
col_state, row_state, cv, vo, co, ys = read_data(data_files[idd])
obj_state = np.zeros((1, args.hidden1), dtype=np.float32)
mask = np.ones((col_state.shape[0], ), dtype=int)
ncols = col_state.shape[0]; nrows = row_state.shape[0]
supp_cv = np.reshape( np.stack(preprocess_adj_lp_dense(cv)), (-1, nrows, ncols))
supp_vc = np.reshape( np.stack(preprocess_adj_lp_dense(cv.T)), (-1, ncols, nrows))
supp_vo = np.reshape( np.stack(preprocess_adj_lp_dense(vo)), (-1, 2))
supp_co = np.reshape( np.stack(preprocess_adj_lp_dense(co)), (-1, 2))
input = [col_state, row_state, obj_state, supp_cv, supp_vc, supp_vo, supp_co, ys, mask]
probs = model.predict(input)
# calcuate precision recall f1
y_pred = probs[:,1]
y_true = ys[:,1]
ncand = len(y_true)
yss.append(y_true); yhss.append(y_pred); ncands.append(ncand)
t2 = time.time()
log(f'time per instance: {(t2-t1)/nsamples}', logfile=logfile)
yss = np.concatenate(yss, axis=None)
yhss = np.concatenate(yhss, axis=None)
ncands = np.concatenate(ncands, axis=None)
line, stats = calc_classification_metrics(yss, yhss, ncands)
log(line, logfile)
line, stats = calc_classification_metrics_top(yss, yhss, ncands)
log(line, logfile)
sys.stdout.flush()
| 2,959 | 34.662651 | 99 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/train.py | import time, sys, os
from utils import *
from models import GCN
from config import args
import scipy.io as sio
import numpy as np
from copy import deepcopy
import scipy.sparse as sp
import sklearn.metrics as metrics
from os.path import expanduser
import gzip
import pickle
import pathlib
import tensorflow as tf;
from tensorflow.keras import optimizers
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
print('tf version:', tf.__version__)
assert tf.__version__.startswith('2.')
def log(line, f=None, stdout=True):
if stdout:
print(line)
sys.stdout.flush()
if f is not None:
f.write(f'{line}\n')
f.flush()
# set random seed
seed = 123
np.random.seed(seed)
tf.random.set_seed(seed)
if __name__ == '__main__':
filedir = os.path.dirname(__file__)
save_model_to = f'{filedir}/../trained_models/{args.problem}/TRIG-GCN'
os.makedirs(save_model_to, exist_ok=True)
####### model #######
col_dim = 57; row_dim = 26;
model = GCN( output_dim=2)
####### data #######
data_path = f'{filedir}/../datasets/{args.problem}/train'
data_files = list(pathlib.Path(data_path).glob('sample_*.pkl'))
data_files = [str(data_file) for data_file in data_files][:500]
####### Train model #######
log_file=open(f"{save_model_to}/score.txt",'w+')
samples_per_epoch = len(data_files)
samples_per_log = samples_per_epoch // 20
print(f'dataset size: {len(data_files)}, samples_per_log: {samples_per_log}')
best_loss = 1e9
optimizer = optimizers.Adam(lr=1e-2)
for epoch in range(args.epochs):
ct = 0
t1 = time.time()
all_loss = []
all_acc = []
for idd in range(samples_per_epoch):
ct += 1
t2 = time.time()
col_state, row_state, cv, vo, co, label = read_data(data_files[idd])
obj_state = np.zeros((1, args.hidden1), dtype=np.float32)
mask = np.ones((col_state.shape[0], ), dtype=int)
ncols = col_state.shape[0]; nrows = row_state.shape[0]
supp_cv = np.reshape( np.stack(preprocess_adj_lp_dense(cv)), (-1, nrows, ncols))
supp_vc = np.reshape( np.stack(preprocess_adj_lp_dense(cv.T)), (-1, ncols, nrows))
supp_vo = np.reshape( np.stack(preprocess_adj_lp_dense(vo)), (-1, 2))
supp_co = np.reshape( np.stack(preprocess_adj_lp_dense(co)), (-1, 2))
input = [col_state, row_state, obj_state, supp_cv, supp_vc, supp_vo, supp_co, label, mask]
with tf.GradientTape() as tape:
loss, acc = model(input)
grads = tape.gradient(loss, model.trainable_variables)
optimizer.apply_gradients(zip(grads, model.trainable_variables))
all_loss.append(loss)
all_acc.append(acc)
if ct % samples_per_log == 0:
line = '{} {} loss={:.4f} acc={:.4f} time_sample={:.1f}'.format(
epoch + 1, ct,
np.mean(all_loss[-samples_per_log:]), np.mean(all_acc[-samples_per_log:]),
time.time() - t2)
log(line, log_file)
loss_cur_epoch = np.mean(all_loss)
line = '[{} finished!] loss={:.4f} acc={:.4f} time_epoch={:.1f}'.format(
epoch + 1, loss_cur_epoch, np.mean(all_acc), time.time() - t1)
log(line, log_file)
if loss_cur_epoch < best_loss:
log(f'best model currently, save to {save_model_to}', log_file)
model.save_weights(f'{save_model_to}/model.ckpt')
best_loss = loss_cur_epoch
sys.stdout.flush()
log_file.flush(); log_file.close()
print("Optimization Finished!")
| 3,691 | 33.504673 | 102 | py |
PB-DFS | PB-DFS-master/TRIG-GCN/utils.py | import numpy as np
import pickle
import networkx as nx
import scipy.sparse as sp
from scipy.sparse.linalg.eigen.arpack import eigsh, eigs
import sys
import datetime
import scipy.io as sio
import sklearn.metrics as sk_metrics
import gzip
import math
def parse_index_file(filename):
"""Parse index file."""
index = []
for line in open(filename):
index.append(int(line.strip()))
return index
def sample_mask(idx, l):
"""Create mask."""
mask = np.zeros(l)
mask[idx] = 1
return np.array(mask, dtype=np.bool)
def sparse_to_tuple(sparse_mx):
"""Convert sparse matrix to tuple representation."""
def to_tuple(mx):
if not sp.isspmatrix_coo(mx):
mx = mx.tocoo()
coords = np.vstack((mx.row, mx.col)).transpose()
values = mx.data
shape = mx.shape
return coords, values, shape
if isinstance(sparse_mx, list):
for i in range(len(sparse_mx)):
sparse_mx[i] = to_tuple(sparse_mx[i])
else:
sparse_mx = to_tuple(sparse_mx)
return sparse_mx
def preprocess_features(features):
"""Row-normalize feature matrix and convert to tuple representation"""
rowsum = np.array(features.sum(1))
r_inv = np.power(rowsum, -1).flatten()
r_inv[np.isinf(r_inv)] = 0.
r_mat_inv = sp.diags(r_inv)
features = r_mat_inv.dot(features)
# features = features/features.shape[1]
return sparse_to_tuple(features)
def normalize_adj(adj):
"""Symmetrically normalize adjacency matrix."""
adj = sp.coo_matrix(adj)
rowsum = np.array(adj.sum(1))
with np.errstate(divide='ignore'):
d_inv_sqrt = np.power(rowsum, -0.5).flatten()
d_inv_sqrt[np.isinf(d_inv_sqrt)] = 0.
d_mat_inv_sqrt = sp.diags(d_inv_sqrt)
return adj.dot(d_mat_inv_sqrt).transpose().dot(d_mat_inv_sqrt).tocoo()
def preprocess_adj(adj):
"""Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation."""
# adj_normalized = normalize_adj(adj)
adj_normalized = normalize_adj(adj + sp.eye(adj.shape[0]))
# adj_normalized = sp.coo_matrix(adj)
return sparse_to_tuple(adj_normalized)
def preprocess_adj_lp_sparse(adj):
"""Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation."""
# adj_normalized = normalize_adj(adj)
adj_normalized = normalize_adj(adj + sp.eye(adj.shape[0]))
# adj_normalized = sp.coo_matrix(adj)
t_k = [adj, adj_normalized]
return sparse_to_tuple(t_k)
def preprocess_adj_lp_dense(adj):
def normalize(input):
input_min = np.min(input, axis=0, keepdims=True)
input_max = np.max(input, axis=0, keepdims=True)
input_delta = input_max - input_min
input_delta[input_delta==0] = 1
input = (input - input_min)/input_delta
return input
t_k = [adj, normalize(adj)]
return t_k
def simple_polynomials(adj, k):
"""Calculate polynomials up to order k. Return a list of sparse matrices (tuple representation)."""
# print("Calculating polynomials up to order {}...".format(k))
adj_normalized = normalize_adj(adj)
laplacian = sp.eye(adj.shape[0]) - adj_normalized
t_k = list()
t_k.append(sp.eye(adj.shape[0]))
t_k.append(laplacian)
for i in range(2, k+1):
t_new = t_k[-1]*laplacian
t_k.append(t_new)
return sparse_to_tuple(t_k)
def simple_polynomials_to_dense(adj, k):
"""Calculate polynomials up to order k. Return a list of sparse matrices (tuple representation)."""
adj_normalized = normalize_adj(adj)
laplacian = sp.eye(adj.shape[0]) - adj_normalized
t_k = list()
t_k.append(sp.eye(adj.shape[0]))
t_k.append(laplacian)
for i in range(2, k+1):
t_new = t_k[-1]*laplacian
t_k.append(t_new)
for i in range(len(t_k)):
t_k[i] = t_k[i].toarray()
return t_k
def log(line, logfile=None):
line = f'[{datetime.datetime.now()}] {line}' if line is not None else "\n\n\n\n"
print(line)
if logfile is not None:
with open(logfile, mode='a') as f:
print(line, file=f)
sys.stdout.flush()
def read_data(lp_path):
def normalize(input):
input_min = np.min(input, axis=0, keepdims=True)
input_max = np.max(input, axis=0, keepdims=True)
input_delta = input_max - input_min
input_delta[input_delta==0] = 1
input = (input - input_min)/input_delta
input[np.isnan(input)] = 0
return input
with gzip.open(lp_path, 'rb') as f:
sample = pickle.load(f)
state, label_cols, cand_cols, _ = sample['data']
col_state, row_state, cv, vo, co = state
label_cols = np.squeeze(label_cols)
cand_cols = np.squeeze(cand_cols)
ys = np.expand_dims(np.isin(cand_cols, label_cols), axis=1)
ys = np.concatenate([1-ys, ys],axis=1)
col_state = normalize(np.nan_to_num(col_state[cand_cols])).astype(np.float32)
row_state = normalize(np.nan_to_num(row_state)).astype(np.float32)
cv = np.take(cv, cand_cols, axis=1)
vo = vo[cand_cols]
return col_state, row_state, cv, vo, co, ys
def calc_classification_metrics_top(y_true, y_pred, ncands=None, top_percentages=[0.80, 0.90 ,0.95, 1], threshold=0.5):
def calc_single(y_true_single, y_pred_single):
test_yhats_roundings = (y_pred_single > threshold).astype(int)
acc = np.sum(y_true_single == test_yhats_roundings) / len(y_true_single)
precision, recall, f1_score, _ = sk_metrics.precision_recall_fscore_support(
y_true_single, test_yhats_roundings, labels=[0,1])
return acc, f1_score[0], f1_score[1], precision[0], precision[1]
if ncands is None:
ret = {}
y_pred_confidence = np.where( y_pred < threshold, y_pred, 1 - y_pred)
sortedargs = np.argsort(y_pred_confidence)
for cur_percentage in top_percentages:
num_vars_choosen = int(len(y_true)*cur_percentage)
sortedargs_cur_percentage = sortedargs[:num_vars_choosen]
stats = calc_single(y_true[sortedargs_cur_percentage], y_pred[sortedargs_cur_percentage])
ret[cur_percentage] = [[stats[i]] for i in range(len(stats))]
else:
ncands = np.insert(ncands, 0,0)
slices = np.cumsum(ncands)
mean_stats = {key: [] for key in top_percentages}
for i in range(len(slices)-1):
begin = slices[i]; end = slices[i+1]
y_true_sinlge = y_true[begin:end]; y_pred_single = y_pred[begin:end]
y_pred_confidence = np.where( y_pred_single < threshold, y_pred_single, 1 - y_pred_single)
sortedargs = np.argsort(y_pred_confidence)
for cur_percentage in top_percentages:
num_vars_choosen = int(len(y_true_sinlge)*cur_percentage)
# print(num_vars_choosen, len(y_true))
sortedargs_cur_percentage = sortedargs[:num_vars_choosen]
# print(len(sortedargs_cur_percentage), len(sortedargs))
stats = calc_single(y_true_sinlge[sortedargs_cur_percentage], y_pred_single[sortedargs_cur_percentage])
mean_stats[cur_percentage].append(stats)
ret = {key: [] for key in top_percentages}
for cur_percentage in top_percentages:
for stat in zip(*mean_stats[cur_percentage]):
ret[cur_percentage].append((np.mean(stat) * 100, np.std(stat) * 100))
line = ""
for p in top_percentages:
line += f'percentage vars: {p} mean - acc: {ret[p][0][0]:0.2f}, f1_0: {ret[p][1][0]:0.2f}, f1_1: {ret[p][2][0]:0.2f}, p_0: {ret[p][3][0]:0.2f}, p1: {ret[p][4][0]:0.2f}\n'
line += f'percentage vars: {p} std - acc: {ret[p][0][1]:0.2f}, f1_0: {ret[p][1][1]:0.2f}, f1_1: {ret[p][2][1]:0.2f}, p_0: {ret[p][3][1]:0.2f}, p1: {ret[p][4][1]:0.2f}\n\n'
return line, ret
def calc_classification_metrics(y_true, y_pred, ncands=None, threshold=0.5):
def calc_single(y_true_single, y_pred_single):
test_yhats_roundings = (y_pred_single > threshold).astype(int)
acc = np.sum(y_true_single == test_yhats_roundings) / len(y_true_single)
precision, recall, f1_score, _ = sk_metrics.precision_recall_fscore_support(
y_true_single, test_yhats_roundings, labels=[0,1])
avg_precision = sk_metrics.average_precision_score(y_true_single, y_pred_single)
return acc, np.nan_to_num(avg_precision), precision[0], recall[0], f1_score[0], precision[1], recall[1], f1_score[1]
if ncands is None:
mean_stats = calc_single(y_true, y_pred)
mean_stats = [[mean_stats[i]] for i in range(len(mean_stats))]
else:
ncands = np.insert(ncands, 0,0)
slices = np.cumsum(ncands)
metricss = []; APs = []
for i in range(len(slices)-1):
begin = slices[i]; end = slices[i+1]
metrics = calc_single(y_true[begin:end], y_pred[begin:end])
metricss.append(metrics)
APs.append(str(float(metrics[1])))
mean_stats = []
for stat in zip(*metricss):
mean_stats.append(np.mean(stat) * 100)
line = f'acc: {mean_stats[0]:0.2f}, ap: {mean_stats[1]:0.2f}\
\np_0: {mean_stats[2]:0.2f}, r_0: {mean_stats[3]:0.2f}, f1_0: {mean_stats[4]:0.2f},\
\np_1: {mean_stats[5]:0.2f}, r_1: {mean_stats[6]:0.2f}, f1_1: {mean_stats[7]:0.2f}'
line += f"\n APs: {','.join(APs)}"
return line, mean_stats | 9,448 | 37.884774 | 179 | py |
PB-DFS | PB-DFS-master/data_generator/utils.py | import numpy as np
import pyscipopt as scip
def init_scip_params(model, seed, heuristics=False, presolving=False, separating=False, conflict=True):
seed = seed % 2147483648 # SCIP seed range
# set up randomization
model.setBoolParam('randomization/permutevars', False)
model.setIntParam('randomization/permutationseed', seed)
model.setIntParam('randomization/randomseedshift', seed)
# separation only at root node
model.setIntParam('separating/maxrounds', 0)
# if asked, disable presolving
if not presolving:
model.setIntParam('presolving/maxrounds', 0)
model.setIntParam('presolving/maxrestarts', 0)
# if asked, disable separating (cuts)
if not separating:
model.setIntParam('separating/maxroundsroot', 0)
# if asked, disable conflict analysis (more cuts)
if not conflict:
model.setBoolParam('conflict/enable', False)
# if asked, disable primal heuristics
if not heuristics:
model.setHeuristics(scip.SCIP_PARAMSETTING.OFF)
def extract_ding_variable_features(model):
"""
Extract features following Khalil et al. (2016) Learning to Branch in Mixed Integer Programming.
Parameters
----------
model : pyscipopt.scip.Model
The current model.
candidates : list of pyscipopt.scip.Variable's
A list of variables for which to compute the variable features.
root_buffer : dict
A buffer to avoid re-extracting redundant root node information (None to deactivate buffering).
Returns
-------
variable_features : 2D np.ndarray
The features associated with the candidate variables.
"""
col_state = model.getDingStateCols()
col_feature_names = sorted(col_state)
for index, name in enumerate(col_feature_names):
if name == 'col_coefs':
break
col_state = np.stack([col_state[feature_name] for feature_name in col_feature_names], axis=1)
row_state = model.getDingStateRows()
row_feature_names = sorted(row_state)
row_state = np.stack([row_state[feature_name] for feature_name in row_feature_names], axis=1)
vc, vo, co = model.getDingStateLPgraph()
return (col_state, row_state, vc, vo, co), index | 2,228 | 32.268657 | 103 | py |
PB-DFS | PB-DFS-master/data_generator/ca/gen_inst_ca.py | import os, sys
import argparse
import numpy as np
import scipy.sparse
import scipy.io as sio
from itertools import combinations
from os.path import expanduser
from os import path
import re
from functools import cmp_to_key
import random
import gurobipy as gp
from gurobipy import *
def generate_ca(random, filename, n_items=100, n_bids=500, min_value=1, max_value=20,
value_deviation=0.5, add_item_prob=0.9, max_n_sub_bids=5,
additivity=0.2, budget_factor=1.5, resale_factor=0.5,
integers=False, warnings=False):
"""
Generate a Combinatorial Auction problem following the 'arbitrary' scheme found in section 4.3. of
Kevin Leyton-Brown, Mark Pearson, and Yoav Shoham. (2000).
Towards a universal test suite for combinatorial auction algorithms.
Proceedings of ACM Conference on Electronic Commerce (EC-00) 66-76.
Saves it as a CPLEX LP file.
Parameters
----------
random : numpy.random.RandomState
A random number generator.
filename : str
Path to the file to save.
n_items : int
The number of items.
n_bids : int
The number of bids.
min_value : int
The minimum resale value for an item.
max_value : int
The maximum resale value for an item.
value_deviation : int
The deviation allowed for each bidder's private value of an item, relative from max_value.
add_item_prob : float in [0, 1]
The probability of adding a new item to an existing bundle.
max_n_sub_bids : int
The maximum number of substitutable bids per bidder (+1 gives the maximum number of bids per bidder).
additivity : float
Additivity parameter for bundle prices. Note that additivity < 0 gives sub-additive bids, while additivity > 0 gives super-additive bids.
budget_factor : float
The budget factor for each bidder, relative to their initial bid's price.
resale_factor : float
The resale factor for each bidder, relative to their initial bid's resale value.
integers : logical
Should bid's prices be integral ?
warnings : logical
Should warnings be printed ?
"""
assert min_value >= 0 and max_value >= min_value
assert add_item_prob >= 0 and add_item_prob <= 1
def choose_next_item(bundle_mask, interests, compats, add_item_prob, random):
n_items = len(interests)
prob = (1 - bundle_mask) * interests * compats[bundle_mask, :].mean(axis=0)
prob /= prob.sum()
return random.choice(n_items, p=prob)
# common item values (resale price)
values = min_value + (max_value - min_value) * random.rand(n_items)
# item compatibilities
compats = np.triu(random.rand(n_items, n_items), k=1)
compats = compats + compats.transpose()
compats = compats / compats.sum(1)
bids = []
n_dummy_items = 0
# create bids, one bidder at a time
while len(bids) < n_bids:
# bidder item values (buy price) and interests
private_interests = random.rand(n_items)
private_values = values + max_value * value_deviation * (2 * private_interests - 1)
# substitutable bids of this bidder
bidder_bids = {}
# generate initial bundle, choose first item according to bidder interests
prob = private_interests / private_interests.sum()
item = random.choice(n_items, p=prob)
bundle_mask = np.full(n_items, 0)
bundle_mask[item] = 1
# add additional items, according to bidder interests and item compatibilities
while random.rand() < add_item_prob:
# stop when bundle full (no item left)
if bundle_mask.sum() == n_items:
break
item = choose_next_item(bundle_mask, private_interests, compats, add_item_prob, random)
bundle_mask[item] = 1
bundle = np.nonzero(bundle_mask)[0]
# compute bundle price with value additivity
price = private_values[bundle].sum() + np.power(len(bundle), 1 + additivity)
if integers:
price = int(price)
# drop negativaly priced bundles
if price < 0:
if warnings:
print("warning: negatively priced bundle avoided")
continue
# bid on initial bundle
bidder_bids[frozenset(bundle)] = price
# generate candidates substitutable bundles
sub_candidates = []
for item in bundle:
# at least one item must be shared with initial bundle
bundle_mask = np.full(n_items, 0)
bundle_mask[item] = 1
# add additional items, according to bidder interests and item compatibilities
while bundle_mask.sum() < len(bundle):
item = choose_next_item(bundle_mask, private_interests, compats, add_item_prob, random)
bundle_mask[item] = 1
sub_bundle = np.nonzero(bundle_mask)[0]
# compute bundle price with value additivity
sub_price = private_values[sub_bundle].sum() + np.power(len(sub_bundle), 1 + additivity)
if integers:
sub_price = int(sub_price)
sub_candidates.append((sub_bundle, sub_price))
# filter valid candidates, higher priced candidates first
budget = budget_factor * price
min_resale_value = resale_factor * values[bundle].sum()
for bundle, price in [
sub_candidates[i] for i in np.argsort([-price for bundle, price in sub_candidates])]:
if len(bidder_bids) >= max_n_sub_bids + 1 or len(bids) + len(bidder_bids) >= n_bids:
break
if price < 0:
if warnings:
print("warning: negatively priced substitutable bundle avoided")
continue
if price > budget:
if warnings:
print("warning: over priced substitutable bundle avoided")
continue
if values[bundle].sum() < min_resale_value:
if warnings:
print("warning: substitutable bundle below min resale value avoided")
continue
if frozenset(bundle) in bidder_bids:
if warnings:
print("warning: duplicated substitutable bundle avoided")
continue
bidder_bids[frozenset(bundle)] = price
# add XOR constraint if needed (dummy item)
if len(bidder_bids) > 2:
dummy_item = [n_items + n_dummy_items]
n_dummy_items += 1
else:
dummy_item = []
# place bids
for bundle, price in bidder_bids.items():
bids.append((list(bundle) + dummy_item, price))
# generate the LP file
with open(filename, 'w') as file:
bids_per_item = [[] for item in range(n_items + n_dummy_items)]
file.write("maximize\nOBJ:")
for i, bid in enumerate(bids):
bundle, price = bid
file.write(f" +{price} x{i+1}")
for item in bundle:
bids_per_item[item].append(i)
file.write("\n\nsubject to\n")
ctr=1
for item_bids in bids_per_item:
if item_bids:
file.write(f"C{ctr}:")
ctr+=1
for i in item_bids:
file.write(f" +1 x{i+1}")
file.write(f" <= 1\n")
file.write("\nbinary\n")
for i in range(len(bids)):
file.write(f" x{i+1}")
def solve_single(lp_path, sol_path, time_limit=200):
print(f'process lp: {lp_path}')
model = gp.read(lp_path)
model.setParam('TimeLimit', time_limit) # set a time limit
model.setParam('OutputFlag', 0) # disable logging
model.optimize()
if model.status != GRB.OPTIMAL:
print(f'problem is too hard to solve within {time_limit}, skipping!')
return
print(f'problem is solved with {round(model.runtime, 1)} seconds')
with open( sol_path, 'w+') as f:
# f.write('Obj: %f\n' % model.objVal)
for v in model.getVars():
if int(v.x) == 1 and v.varName[0] == 'x' :
f.write(f'{v.varName[1:]}\n')
def solve_ca(lp_path, time_limit=200):
sol_file_path = f'{lp_path[:-2]}sol'
if os.path.exists(sol_file_path):
print(f'{lp_path} has been processed, skipping!')
return
solve_single(lp_path, sol_file_path, time_limit=time_limit)
sys.stdout.flush()
def gen_ca(data_dir, ninst, nitems, nbids, nitems_upper=None, nbids_upper=None, solve=True):
os.makedirs(data_dir, exist_ok=True)
for i in range(ninst):
nitems = nitems if nitems_upper is None else random.randint(nitems, nitems_upper+1)
nbids = nbids if nbids_upper is None else random.randint(nbids, nbids_upper+1)
rng = np.random.RandomState(i)
lp_path = os.path.join(data_dir, f'{i}.lp')
print(f'generate {lp_path}')
generate_ca(rng, lp_path, nitems, nbids)
if solve:
sol_path = solve_ca(lp_path)
if __name__ == '__main__':
home = expanduser("~")
# data_dir = os.path.join(home, f'storage1/instances/ca/train_100-500-1.5')
# gen_ca(data_dir, 500, 100, 500, nitems_upper=150, nbids_upper=750, solve=True)
data_dir = os.path.join(home, f'storage1/instances/ca/time_100-500')
gen_ca(data_dir, 30, 100, 500, solve=False)
data_dir = os.path.join(home, f'storage1/instances/ca/time_200-1000')
gen_ca(data_dir, 30, 200, 1000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/ca/time_300-1500')
gen_ca(data_dir, 30, 300, 1500, solve=False)
data_dir = os.path.join(home, f'storage1/instances/ca/time_400-2000')
gen_ca(data_dir, 30, 400, 2000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/ca/time_500-2500')
gen_ca(data_dir, 30, 500, 2500, solve=False)
| 9,967 | 36.473684 | 145 | py |
PB-DFS | PB-DFS-master/data_generator/ca/make_sample_ca.py | import os
import sys
import os
sys.path.append( f'{os.path.dirname(os.path.realpath(__file__))}/../')
import argparse
import multiprocessing as mp
import pickle
import glob
import numpy as np
import shutil
import gzip
from os.path import expanduser
import pyscipopt as scip
import utils
def read_sol_file(filepath):
sol = set()
with open(filepath, 'r') as f:
lines = f.readlines()
for line in lines:
var_name = line.strip()
sol.add(var_name)
sol.add(f't_x{var_name}')
return sol
class SamplingAgent(scip.Branchrule):
def __init__(self, sol, write_to):
self.sol = sol
self.write_to = write_to
def branchexeclp(self, allowaddcons):
if self.model.getNNodes() == 1:
ys = []
cands = []
cands_dict = self.model.getMapping()
name_index_mapping = {}
for lp_col_idx, name in cands_dict.items():
cands.append(lp_col_idx)
if name in self.sol:
ys.append(lp_col_idx)
name_index_mapping[name] = lp_col_idx
state_ding, obj_coef_idx = utils.extract_ding_variable_features(self.model)
data = [state_ding, ys, cands, obj_coef_idx]
with gzip.open(self.write_to, 'wb') as f:
pickle.dump({
'data': data,
'mapping': name_index_mapping,
}, f)
print(f'write {self.write_to}\n')
# end the scip solving process
self.model.interruptSolve()
else:
self.model.interruptSolve()
# result = self.model.executeBranchRule('relpscost', False)
return {"result": scip.SCIP_RESULT.DIDNOTRUN}
def collect_samples(data_dir):
require_sol = 'eval' not in data_dir and 'time' not in data_dir
def collect_single(id, sol_path=None):
sample_file = os.path.join(data_dir, f'sample_{id}.pkl')
if os.path.exists(sample_file):
print(f"skipping {sample_file}")
sys.stdout.flush()
return
m = scip.Model()
m.setIntParam('display/verblevel', 0)
m.readProblem(os.path.join(data_dir, f'{id}.lp'))
utils.init_scip_params(m, presolving=False, seed=0)
print(f"begin collect {os.path.join(data_dir, f'sample_{id}.pkl')}")
sys.stdout.flush()
branchrule = SamplingAgent(
sol = read_sol_file(sol_path) if require_sol else set(),
write_to=os.path.join(data_dir, f'sample_{id}.pkl'))
m.includeBranchrule(
branchrule=branchrule,
name="Sampling branching rule", desc="",
priority=666666, maxdepth=-1, maxbounddist=1)
m.optimize()
m.freeProb()
if require_sol: # construct training and test data, must have .sol for each .lp
ids = []; sols = []
for i in range(0, 3000):
sol_filepath = os.path.join(data_dir, f'{i}.sol')
if os.path.exists(sol_filepath):
ids.append(i)
sols.append(sol_filepath)
for cur_id, cur_sol_path in zip(ids, sols):
collect_single(cur_id, cur_sol_path)
else: # construct training and test data, for all .lp files
for i in range(0, 30):
collect_single(i, None)
def remove_broken_sample(data_dir):
for i in range(0, 3000):
sample_file = os.path.join(data_dir, f'sample_{i}.pkl')
if os.path.exists(sample_file):
try:
with gzip.open(sample_file, 'rb') as f:
sample = pickle.load(f)
except:
print(f'<{sample_file}> is broken. removing...')
os.remove(sample_file)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
home = expanduser("~")
# data_dir = f'{home}/storage1/instances/ca/train_100-500-1.5'
# remove_broken_sample(data_dir)
# collect_samples(data_dir)
# data_dir = f'{home}/storage1/instances/ca/eval_300-1500'
# remove_broken_sample(data_dir)
# collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ca/time_100-500'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ca/time_200-1000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ca/time_300-1500'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ca/time_400-2000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ca/time_500-2500'
collect_samples(data_dir) | 4,648 | 31.739437 | 91 | py |
PB-DFS | PB-DFS-master/data_generator/ds/gen_inst_ds.py | import os, sys
import argparse
import numpy as np
import scipy.sparse
import scipy.io as sio
from itertools import combinations
from os.path import expanduser
from os import path
import re
from functools import cmp_to_key
import random
import gurobipy as gp
from gurobipy import *
class Graph:
"""
Container for a graph.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
edges : set of tuples (int, int)
The edges of the graph, where the integers refer to the nodes.
degrees : numpy array of integers
The degrees of the nodes in the graph.
neighbors : dictionary of type {int: set of ints}
The neighbors of each node in the graph.
"""
def __init__(self, number_of_nodes, edges, degrees, neighbors):
self.number_of_nodes = number_of_nodes
self.edges = edges
self.degrees = degrees
self.neighbors = neighbors
def __len__(self):
"""
The number of nodes in the graph.
"""
return self.number_of_nodes
@staticmethod
def barabasi_albert(number_of_nodes, affinity, random):
"""
Generate a Barabási-Albert random graph with a given edge probability.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
affinity : integer >= 1
The number of nodes each new node will be attached to, in the sampling scheme.
random : numpy.random.RandomState
A random number generator.
Returns
-------
Graph
The generated graph.
"""
assert affinity >= 1 and affinity < number_of_nodes
edges = set()
degrees = np.zeros(number_of_nodes, dtype=int)
neighbors = {node: set() for node in range(number_of_nodes)}
for new_node in range(affinity, number_of_nodes):
# first node is connected to all previous ones (star-shape)
if new_node == affinity:
neighborhood = np.arange(new_node)
# remaining nodes are picked stochastically
else:
neighbor_prob = degrees[:new_node] / (2*len(edges))
neighborhood = random.choice(new_node, affinity, replace=False, p=neighbor_prob)
for node in neighborhood:
edges.add((node, new_node))
degrees[node] += 1
degrees[new_node] += 1
neighbors[node].add(new_node)
neighbors[new_node].add(node)
graph = Graph(number_of_nodes, edges, degrees, neighbors)
return graph
def generate_ds(graph, filename):
"""
Generate a Maximum Independent Set (also known as Maximum Stable Set) instance
in CPLEX LP format from a previously generated graph.
Parameters
----------
graph : Graph
The graph from which to build the independent set problem.
filename : str
Path to the file to save.
"""
with open(filename, 'w') as lp_file:
lp_file.write("minimize\nOBJ:" + "".join([f" + 1 x{node+1}" for node in range(len(graph))]) + "\n")
lp_file.write("\nsubject to\n")
for count, node in enumerate(range(len(graph))):
neighbors = graph.neighbors[node]
cons = f"+1 x{node+1}" + "".join([f" +1 x{j+1}" for j in neighbors])
lp_file.write(f"C{count+1}: {cons} >= 1\n")
lp_file.write("\nbinary\n" + " ".join([f"x{node+1}" for node in range(len(graph))]) + "\n")
def solve_single(lp_path, sol_path, time_limit=500):
print(f'process lp: {lp_path}')
model = gp.read(lp_path)
model.setParam('TimeLimit', time_limit) # set a time limit
model.setParam('OutputFlag', 0) # disable logging
model.optimize()
if model.status != GRB.OPTIMAL:
print(f'problem is too hard to solve within {time_limit}, skipping!')
return
print(f'problem is solved with {round(model.runtime, 1)} seconds')
with open( sol_path, 'w+') as f:
# f.write('Obj: %f\n' % model.objVal)
for v in model.getVars():
if int(v.x) == 1 and v.varName[0] == 'x' :
f.write(f'{v.varName[1:]}\n')
def solve_ds(lp_path, time_limit=200):
sol_file_path = f'{lp_path[:-2]}sol'
if os.path.exists(sol_file_path):
print(f'{lp_path} has been processed, skipping!')
return
solve_single(lp_path, sol_file_path, time_limit=time_limit)
sys.stdout.flush()
def gen_ds(data_dir, ninst, scale_lower, scale_upper=None, solve=True):
os.makedirs(data_dir, exist_ok=True)
affinity = 4
for i in range(ninst):
nnodes = scale_lower if scale_upper is None else random.randint(scale_lower, scale_upper+1)
graph = Graph.barabasi_albert(nnodes, affinity, np.random.RandomState(i))
lp_path = os.path.join(data_dir, f'{i}.lp')
generate_ds(graph, lp_path)
if solve:
sol_path = solve_ds(lp_path)
if __name__ == '__main__':
home = expanduser("~")
# data_dir = os.path.join(home, f'storage1/instances/ds/train_500-1000')
# gen_ds(data_dir, 500, 500, 1000, solve=True)
# data_dir = os.path.join(home, f'storage1/instances/ds/time_1000')
# gen_ds(data_dir, 30, 1000, solve=False)
# data_dir = os.path.join(home, f'storage1/instances/ds/time_3000')
# gen_ds(data_dir, 30, 3000, solve=False)
# data_dir = os.path.join(home, f'storage1/instances/ds/time_5000')
# gen_ds(data_dir, 30, 5000, solve=False)
# data_dir = os.path.join(home, f'storage1/instances/ds/time_7000')
# gen_ds(data_dir, 30, 7000, solve=False)
# data_dir = os.path.join(home, f'storage1/instances/ds/time_9000')
# gen_ds(data_dir, 30, 9000, solve=False)
| 5,785 | 33.035294 | 107 | py |
PB-DFS | PB-DFS-master/data_generator/ds/make_sample_ds.py | import os
import sys
import os
sys.path.append( f'{os.path.dirname(os.path.realpath(__file__))}/../')
import argparse
import multiprocessing as mp
import pickle
import glob
import numpy as np
import shutil
import gzip
from os.path import expanduser
import pyscipopt as scip
import utils
def read_sol_file(filepath):
sol = set()
with open(filepath, 'r') as f:
lines = f.readlines()
for line in lines:
var_name = line.strip()
sol.add(var_name)
sol.add(f't_x{var_name}')
return sol
class SamplingAgent(scip.Branchrule):
def __init__(self, sol, write_to):
self.sol = sol
self.write_to = write_to
def branchexeclp(self, allowaddcons):
if self.model.getNNodes() == 1:
ys = []
cands = []
cands_dict = self.model.getMapping()
name_index_mapping = {}
for lp_col_idx, name in cands_dict.items():
cands.append(lp_col_idx)
if name in self.sol:
ys.append(lp_col_idx)
name_index_mapping[name] = lp_col_idx
state_ding, obj_coef_idx = utils.extract_ding_variable_features(self.model)
data = [state_ding, ys, cands, obj_coef_idx]
with gzip.open(self.write_to, 'wb') as f:
pickle.dump({
'data': data,
'mapping': name_index_mapping,
}, f)
print(f'write {self.write_to}\n')
# end the scip solving process
self.model.interruptSolve()
else:
self.model.interruptSolve()
# result = self.model.executeBranchRule('relpscost', False)
return {"result": scip.SCIP_RESULT.DIDNOTRUN}
def collect_samples(data_dir):
require_sol = 'eval' not in data_dir and 'time' not in data_dir
def collect_single(id, sol_path=None):
sample_file = os.path.join(data_dir, f'sample_{id}.pkl')
if os.path.exists(sample_file):
print(f"skipping {sample_file}")
sys.stdout.flush()
return
m = scip.Model()
m.setIntParam('display/verblevel', 0)
m.readProblem(os.path.join(data_dir, f'{id}.lp'))
utils.init_scip_params(m, presolving=False, seed=0)
print(f"begin collect {os.path.join(data_dir, f'sample_{id}.pkl')}")
sys.stdout.flush()
branchrule = SamplingAgent(
sol = read_sol_file(sol_path) if require_sol else set(),
write_to=os.path.join(data_dir, f'sample_{id}.pkl'))
m.includeBranchrule(
branchrule=branchrule,
name="Sampling branching rule", desc="",
priority=666666, maxdepth=-1, maxbounddist=1)
m.optimize()
m.freeProb()
if require_sol: # construct training and test data, must have .sol for each .lp
ids = []; sols = []
for i in range(0, 3000):
sol_filepath = os.path.join(data_dir, f'{i}.sol')
if os.path.exists(sol_filepath):
ids.append(i)
sols.append(sol_filepath)
for cur_id, cur_sol_path in zip(ids, sols):
collect_single(cur_id, cur_sol_path)
else: # construct training and test data, for all .lp files
for i in range(0, 30):
collect_single(i, None)
def remove_broken_sample(data_dir):
for i in range(0, 3000):
sample_file = os.path.join(data_dir, f'sample_{i}.pkl')
if os.path.exists(sample_file):
try:
with gzip.open(sample_file, 'rb') as f:
sample = pickle.load(f)
except:
print(f'<{sample_file}> is broken. removing...')
os.remove(sample_file)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
home = expanduser("~")
# data_dir = f'{home}/storage1/instances/ds/train_500-1000'
# remove_broken_sample(data_dir)
# collect_samples(data_dir)
# data_dir = f'{home}/storage1/instances/ds/test_1000'
# remove_broken_sample(data_dir)
# collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ds/time_1000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ds/time_3000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ds/time_5000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ds/time_7000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/ds/time_9000'
collect_samples(data_dir)
| 4,623 | 31.335664 | 91 | py |
PB-DFS | PB-DFS-master/data_generator/mis/gen_inst_mis.py | import os, sys
import argparse
import numpy as np
import scipy.sparse
import scipy.io as sio
from itertools import combinations
from os.path import expanduser
from os import path
import re
from functools import cmp_to_key
import random
class Graph:
"""
Container for a graph.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
edges : set of tuples (int, int)
The edges of the graph, where the integers refer to the nodes.
degrees : numpy array of integers
The degrees of the nodes in the graph.
neighbors : dictionary of type {int: set of ints}
The neighbors of each node in the graph.
"""
def __init__(self, number_of_nodes, edges, degrees, neighbors):
self.number_of_nodes = number_of_nodes
self.edges = edges
self.degrees = degrees
self.neighbors = neighbors
def __len__(self):
"""
The number of nodes in the graph.
"""
return self.number_of_nodes
def greedy_clique_partition(self):
"""
Partition the graph into cliques using a greedy algorithm.
Returns
-------
list of sets
The resulting clique partition.
"""
cliques = []
leftover_nodes = (-self.degrees).argsort().tolist()
while leftover_nodes:
clique_center, leftover_nodes = leftover_nodes[0], leftover_nodes[1:]
clique = {clique_center}
neighbors = self.neighbors[clique_center].intersection(leftover_nodes)
densest_neighbors = sorted(neighbors, key=lambda x: -self.degrees[x])
for neighbor in densest_neighbors:
# Can you add it to the clique, and maintain cliqueness?
if all([neighbor in self.neighbors[clique_node] for clique_node in clique]):
clique.add(neighbor)
cliques.append(clique)
leftover_nodes = [node for node in leftover_nodes if node not in clique]
return cliques
@staticmethod
def barabasi_albert(number_of_nodes, affinity, random):
"""
Generate a Barabási-Albert random graph with a given edge probability.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
affinity : integer >= 1
The number of nodes each new node will be attached to, in the sampling scheme.
random : numpy.random.RandomState
A random number generator.
Returns
-------
Graph
The generated graph.
"""
assert affinity >= 1 and affinity < number_of_nodes
edges = set()
degrees = np.zeros(number_of_nodes, dtype=int)
neighbors = {node: set() for node in range(number_of_nodes)}
for new_node in range(affinity, number_of_nodes):
# first node is connected to all previous ones (star-shape)
if new_node == affinity:
neighborhood = np.arange(new_node)
# remaining nodes are picked stochastically
else:
neighbor_prob = degrees[:new_node] / (2*len(edges))
neighborhood = random.choice(new_node, affinity, replace=False, p=neighbor_prob)
for node in neighborhood:
edges.add((node, new_node))
degrees[node] += 1
degrees[new_node] += 1
neighbors[node].add(new_node)
neighbors[new_node].add(node)
graph = Graph(number_of_nodes, edges, degrees, neighbors)
return graph
def generate_indset(graph, filename):
"""
Generate a Maximum Independent Set (also known as Maximum Stable Set) instance
in CPLEX LP format from a previously generated graph.
Parameters
----------
graph : Graph
The graph from which to build the independent set problem.
filename : str
Path to the file to save.
"""
cliques = graph.greedy_clique_partition()
inequalities = set(graph.edges)
for clique in cliques:
clique = tuple(sorted(clique))
for edge in combinations(clique, 2):
inequalities.remove(edge)
if len(clique) > 1:
inequalities.add(clique)
# Put trivial inequalities for nodes that didn't appear
# in the constraints, otherwise SCIP will complain
used_nodes = set()
for group in inequalities:
used_nodes.update(group)
for node in range(10):
if node not in used_nodes:
inequalities.add((node,))
with open(filename, 'w') as lp_file:
lp_file.write("maximize\nOBJ:" + "".join([f" + 1 x{node+1}" for node in range(len(graph))]) + "\n")
lp_file.write("\nsubject to\n")
for count, group in enumerate(inequalities):
lp_file.write(f"C{count+1}:" + "".join([f" + x{node+1}" for node in sorted(group)]) + " <= 1\n")
lp_file.write("\nbinary\n" + " ".join([f"x{node+1}" for node in range(len(graph))]) + "\n")
# mis graphs index from 1
def lp2mis(inst_name):
writeto = inst_name[:-2]+'mis'
# read problem
with open(inst_name, 'r') as f:
lines = f.readlines()
lines = [line.strip() for line in lines]
nnodes = int(lines[-1].split(' ')[-1][1:])
nconss = int(lines[-4].split(':')[0][1:])
conss = lines[4:-3]
assert(len(conss) == nconss)
print(f"\ncurrent graph: {inst_name}, {nnodes}, {nconss}")
lines = []
for cons in conss:
nodes = cons[:-5].split('+')[1:]
nodes = [node.strip()[1:] for node in nodes]
for i in range(len(nodes)):
for j in range(i+1, len(nodes)):
lines.append(f'e {nodes[i]} {nodes[j]}\n')
nedges = len(lines)
with open(writeto, 'w+') as f:
f.write(f'p edge {nnodes} {nedges}\n')
for line in lines:
f.write(line)
return writeto
# snap graphs index from 0
def mis2snap(fpath):
writeto = fpath[:-3]+'snap'
with open(fpath, 'r') as f:
lines = f.readlines()
lines = [line.strip() for line in lines]
nnodes = int(lines[0].split(' ')[2])
nedges = int(lines[0].split(' ')[3])
lines = lines[1:]
# sort
def compare(line1, line2):
from1, to1 = line1[2:].split(" ")
from1, to1 = int (from1), int(to1)
from2, to2 = line2[2:].split(" ")
from2, to2 = int(from2), int(to2)
if from1 != from2:
return from1 - from2
else:
return to1 - to2
print(f"\ncurrent graph: {fpath}, {nnodes}, {nedges}")
with open(writeto, 'w+') as f:
f.write('# Undirected graph (each unordered pair of nodes is saved once)\n')
f.write('# Undirected Erdos-Renyi random graph.\n')
f.write(f'# Nodes: {nnodes} Edges: {nedges}\n')
f.write(f'# NodeId NodeId\n')
numlines = len(lines)
for idx, line in enumerate(sorted(lines, key=cmp_to_key(compare))):
node1, node2 = line[2:].split(' ')
node1, node2 = int(node1), int(node2)
if idx + 1 == numlines:
f.write(f'{node1-1} {node2-1}')
else:
f.write(f'{node1-1} {node2-1}\n')
return writeto
# metis graphs index from 1
def mis2metis(mis_path):
writeto = mis_path[:-3]+'metis'
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [ atoi(c) for c in re.split('(\d+)', text) ]
number_nodes = 0
number_edges = 0
edges_counted = 0
adjacency = []
with open(mis_path) as f:
for line in f:
args = line.strip().split()
if args[0] == 'p':
number_nodes = args[2]
number_edges = args[3]
adjacency = [[] for _ in range(0, int(number_nodes) + 1)]
elif args[0] == 'e':
source = int(args[1])
target = int(args[2])
edge_added = False
if not target in adjacency[source]:
adjacency[source].append(target)
edge_added = True
if not source in adjacency[target]:
adjacency[target].append(source)
edge_added = True
if edge_added:
edges_counted += 1
else:
print ("Could not read line.\n")
adjacency[0].append(number_nodes)
# adjacency[0].append(number_edges)
adjacency[0].append(str(edges_counted))
with open(writeto, 'w') as f:
node = 0
for neighbors in adjacency:
if node != 0:
neighbors.sort()
if not neighbors:
f.write(' ')
else:
tmp = [str(i) for i in neighbors]
f.write(' '.join(tmp))
f.write('\n')
node += 1
return writeto
def solve_mis(metis_path):
writeto = f'{metis_path[:-5]}sol'
os.system(f'./redumis {metis_path} --output={writeto}')
with open(writeto, 'r') as f:
sol_content = f.readlines()
sol_content = [line.strip() for line in sol_content]
sol_arr = []
for idx, sol_val in enumerate(sol_content):
if int(sol_val) == 1:
sol_arr.append(idx+1)
with open(writeto, 'w') as f:
for opt_sol_idx in sol_arr:
f.write(f'{opt_sol_idx}\n')
return writeto
# should be snap graph
def save_adj(graph_path, writeto):
with open(graph_path, 'r') as f:
graph_content = f.readlines()
graph_content = [line.strip() for line in graph_content]
nnodes = int(graph_content[2].split(' ')[2])
graph_content = graph_content[4:]
adj_mat = np.zeros((nnodes,nnodes))
for edge in graph_content:
ver1, ver2 = edge.split(' ')
ver1, ver2 = int(ver1), int(ver2)
adj_mat[ver1, ver2] = 1
adj_mat[ver2, ver1] = 1
dic = {
'adj':adj_mat,
}
sio.savemat(writeto, dic)
def gen_mis(data_dir, ninst, scale_lower, scale_upper=None, solve=True):
os.makedirs(data_dir, exist_ok=True)
affinity = 4
for i in range(ninst):
nnodes = scale_lower if scale_upper is None else random.randint(scale_lower, scale_upper+1)
graph = Graph.barabasi_albert(nnodes, affinity, np.random.RandomState(i))
lp_path = os.path.join(data_dir, f'{i}.lp')
generate_indset(graph, lp_path)
mis_path = lp2mis(lp_path);
snap_path = mis2snap(mis_path)
metis_path = mis2metis(mis_path)
save_adj(snap_path, f'{lp_path[:-2]}adj')
# solve metis
if solve:
sol_path = solve_mis(metis_path)
os.remove(snap_path); os.remove(metis_path)
if __name__ == '__main__':
home = expanduser("~")
data_dir = os.path.join(home, f'storage1/instances/mis/test_2000')
gen_mis(data_dir, 50, 2000, solve=False) | 11,085 | 31.702065 | 108 | py |
PB-DFS | PB-DFS-master/data_generator/mis/make_sample_mis.py | import os
import sys
import os
sys.path.append( f'{os.path.dirname(os.path.realpath(__file__))}/../')
import argparse
import multiprocessing as mp
import pickle
import glob
import numpy as np
import shutil
import gzip
from os.path import expanduser
import pyscipopt as scip
import utils
def read_sol_file(filepath):
sol = set()
with open(filepath, 'r') as f:
lines = f.readlines()
for line in lines:
var_name = line.strip()
sol.add(var_name)
sol.add(f't_x{var_name}')
return sol
class SamplingAgent(scip.Branchrule):
def __init__(self, sol, write_to):
self.sol = sol
self.write_to = write_to
def branchexeclp(self, allowaddcons):
if self.model.getNNodes() == 1:
ys = []
cands = []
cands_dict = self.model.getMapping()
name_index_mapping = {}
for lp_col_idx, name in cands_dict.items():
cands.append(lp_col_idx)
if name in self.sol:
ys.append(lp_col_idx)
name_index_mapping[name] = lp_col_idx
state_ding, obj_coef_idx = utils.extract_ding_variable_features(self.model)
data = [state_ding, ys, cands, obj_coef_idx]
with gzip.open(self.write_to, 'wb') as f:
pickle.dump({
'data': data,
'mapping': name_index_mapping,
}, f)
print(f'write {self.write_to}\n')
# end the scip solving process
self.model.interruptSolve()
else:
self.model.interruptSolve()
# result = self.model.executeBranchRule('relpscost', False)
return {"result": scip.SCIP_RESULT.DIDNOTRUN}
def collect_samples(data_dir):
require_sol = 'eval' not in data_dir and 'time' not in data_dir
def collect_single(id, sol_path=None):
sample_file = os.path.join(data_dir, f'sample_{id}.pkl')
if os.path.exists(sample_file):
print(f"skipping {sample_file}")
sys.stdout.flush()
return
m = scip.Model()
m.setIntParam('display/verblevel', 0)
m.readProblem(os.path.join(data_dir, f'{id}.lp'))
utils.init_scip_params(m, presolving=False, seed=0)
print(f"begin collect {os.path.join(data_dir, f'sample_{id}.pkl')}")
sys.stdout.flush()
branchrule = SamplingAgent(
sol = read_sol_file(sol_path) if require_sol else set(),
write_to=os.path.join(data_dir, f'sample_{id}.pkl'))
m.includeBranchrule(
branchrule=branchrule,
name="Sampling branching rule", desc="",
priority=666666, maxdepth=-1, maxbounddist=1)
m.optimize()
m.freeProb()
if require_sol: # construct training and test data, must have .sol for each .lp
ids = []; sols = []
for i in range(0, 3000):
sol_filepath = os.path.join(data_dir, f'{i}.sol')
if os.path.exists(sol_filepath):
ids.append(i)
sols.append(sol_filepath)
for cur_id, cur_sol_path in zip(ids, sols):
collect_single(cur_id, cur_sol_path)
else: # construct training and test data, for all .lp files
for i in range(0, 30):
collect_single(i, None)
def remove_broken_sample(data_dir):
for i in range(0, 3000):
sample_file = os.path.join(data_dir, f'sample_{i}.pkl')
if os.path.exists(sample_file):
try:
with gzip.open(sample_file, 'rb') as f:
sample = pickle.load(f)
except:
print(f'<{sample_file}> is broken. removing...')
os.remove(sample_file)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
home = expanduser("~")
data_dir = f'{home}/storage1/instances/mis/time_1000'
remove_broken_sample(data_dir)
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/mis/time_3000'
remove_broken_sample(data_dir)
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/mis/time_5000'
remove_broken_sample(data_dir)
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/mis/time_7000'
remove_broken_sample(data_dir)
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/mis/time_9000'
remove_broken_sample(data_dir)
collect_samples(data_dir) | 4,541 | 31.212766 | 91 | py |
PB-DFS | PB-DFS-master/data_generator/vc/gen_inst_vc.py | import os, sys
import argparse
import numpy as np
import scipy.sparse
import scipy.io as sio
from itertools import combinations
from os.path import expanduser
from os import path
import re
from functools import cmp_to_key
import random
import gurobipy as gp
from gurobipy import *
class Graph:
"""
Container for a graph.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
edges : set of tuples (int, int)
The edges of the graph, where the integers refer to the nodes.
degrees : numpy array of integers
The degrees of the nodes in the graph.
neighbors : dictionary of type {int: set of ints}
The neighbors of each node in the graph.
"""
def __init__(self, number_of_nodes, edges, degrees, neighbors):
self.number_of_nodes = number_of_nodes
self.edges = edges
self.degrees = degrees
self.neighbors = neighbors
def __len__(self):
"""
The number of nodes in the graph.
"""
return self.number_of_nodes
@staticmethod
def barabasi_albert(number_of_nodes, affinity, random):
"""
Generate a Barabási-Albert random graph with a given edge probability.
Parameters
----------
number_of_nodes : int
The number of nodes in the graph.
affinity : integer >= 1
The number of nodes each new node will be attached to, in the sampling scheme.
random : numpy.random.RandomState
A random number generator.
Returns
-------
Graph
The generated graph.
"""
assert affinity >= 1 and affinity < number_of_nodes
edges = set()
degrees = np.zeros(number_of_nodes, dtype=int)
neighbors = {node: set() for node in range(number_of_nodes)}
for new_node in range(affinity, number_of_nodes):
# first node is connected to all previous ones (star-shape)
if new_node == affinity:
neighborhood = np.arange(new_node)
# remaining nodes are picked stochastically
else:
neighbor_prob = degrees[:new_node] / (2*len(edges))
neighborhood = random.choice(new_node, affinity, replace=False, p=neighbor_prob)
for node in neighborhood:
edges.add((node, new_node))
degrees[node] += 1
degrees[new_node] += 1
neighbors[node].add(new_node)
neighbors[new_node].add(node)
graph = Graph(number_of_nodes, edges, degrees, neighbors)
return graph
def generate_vc(graph, filename):
"""
Generate a Maximum Independent Set (also known as Maximum Stable Set) instance
in CPLEX LP format from a previously generated graph.
Parameters
----------
graph : Graph
The graph from which to build the independent set problem.
filename : str
Path to the file to save.
"""
with open(filename, 'w') as lp_file:
lp_file.write("minimize\nOBJ:" + "".join([f" + 1 x{node+1}" for node in range(len(graph))]) + "\n")
lp_file.write("\nsubject to\n")
for count, (n1, n2) in enumerate(sorted(list(graph.edges))):
lp_file.write(f"C{count+1}:" + f"x{n1+1} + x{n2+1} >= 1\n")
lp_file.write("\nbinary\n" + " ".join([f"x{node+1}" for node in range(len(graph))]) + "\n")
def solve_single(lp_path, sol_path, time_limit=500):
print(f'process lp: {lp_path}')
model = gp.read(lp_path)
model.setParam('TimeLimit', time_limit) # set a time limit
model.setParam('OutputFlag', 0) # disable logging
model.optimize()
if model.status != GRB.OPTIMAL:
print(f'problem is too hard to solve within {time_limit}, skipping!')
return
print(f'problem is solved with {round(model.runtime, 1)} seconds')
with open( sol_path, 'w+') as f:
# f.write('Obj: %f\n' % model.objVal)
for v in model.getVars():
if int(v.x) == 1 and v.varName[0] == 'x' :
f.write(f'{v.varName[1:]}\n')
def solve_vc(lp_path, time_limit=200):
sol_file_path = f'{lp_path[:-2]}sol'
if os.path.exists(sol_file_path):
print(f'{lp_path} has been processed, skipping!')
return
solve_single(lp_path, sol_file_path, time_limit=time_limit)
sys.stdout.flush()
def gen_vc(data_dir, ninst, scale_lower, scale_upper=None, solve=True):
os.makedirs(data_dir, exist_ok=True)
affinity = 4
for i in range(ninst):
nnodes = scale_lower if scale_upper is None else random.randint(scale_lower, scale_upper+1)
graph = Graph.barabasi_albert(nnodes, affinity, np.random.RandomState(i))
lp_path = os.path.join(data_dir, f'{i}.lp')
generate_vc(graph, lp_path)
if solve:
sol_path = solve_vc(lp_path)
if __name__ == '__main__':
home = expanduser("~")
# data_dir = os.path.join(home, f'storage1/instances/vc/train_500-1000')
# gen_vc(data_dir, 1000, 500, 1000, solve=True)
data_dir = os.path.join(home, f'storage1/instances/vc/time_1000')
gen_vc(data_dir, 30, 1000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/vc/time_3000')
gen_vc(data_dir, 30, 3000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/vc/time_5000')
gen_vc(data_dir, 30, 5000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/vc/time_7000')
gen_vc(data_dir, 30, 7000, solve=False)
data_dir = os.path.join(home, f'storage1/instances/vc/time_9000')
gen_vc(data_dir, 30, 9000, solve=False) | 5,666 | 32.934132 | 107 | py |
PB-DFS | PB-DFS-master/data_generator/vc/make_sample_vc.py | import os
import sys
import os
sys.path.append( f'{os.path.dirname(os.path.realpath(__file__))}/../')
import argparse
import multiprocessing as mp
import pickle
import glob
import numpy as np
import shutil
import gzip
from os.path import expanduser
import pyscipopt as scip
import utils
def read_sol_file(filepath):
sol = set()
with open(filepath, 'r') as f:
lines = f.readlines()
for line in lines:
var_name = line.strip()
sol.add(var_name)
sol.add(f't_x{var_name}')
return sol
class SamplingAgent(scip.Branchrule):
def __init__(self, sol, write_to):
self.sol = sol
self.write_to = write_to
def branchexeclp(self, allowaddcons):
if self.model.getNNodes() == 1:
ys = []
cands = []
cands_dict = self.model.getMapping()
name_index_mapping = {}
for lp_col_idx, name in cands_dict.items():
cands.append(lp_col_idx)
if name in self.sol:
ys.append(lp_col_idx)
name_index_mapping[name] = lp_col_idx
state_ding, obj_coef_idx = utils.extract_ding_variable_features(self.model)
data = [state_ding, ys, cands, obj_coef_idx]
with gzip.open(self.write_to, 'wb') as f:
pickle.dump({
'data': data,
'mapping': name_index_mapping,
}, f)
print(f'write {self.write_to}\n')
# end the scip solving process
self.model.interruptSolve()
else:
self.model.interruptSolve()
# result = self.model.executeBranchRule('relpscost', False)
return {"result": scip.SCIP_RESULT.DIDNOTRUN}
def collect_samples(data_dir):
require_sol = 'eval' not in data_dir and 'time' not in data_dir
def collect_single(id, sol_path=None):
sample_file = os.path.join(data_dir, f'sample_{id}.pkl')
if os.path.exists(sample_file):
print(f"skipping {sample_file}")
sys.stdout.flush()
return
m = scip.Model()
m.setIntParam('display/verblevel', 0)
m.readProblem(os.path.join(data_dir, f'{id}.lp'))
utils.init_scip_params(m, presolving=False, seed=0)
print(f"begin collect {os.path.join(data_dir, f'sample_{id}.pkl')}")
sys.stdout.flush()
branchrule = SamplingAgent(
sol = read_sol_file(sol_path) if require_sol else set(),
write_to=os.path.join(data_dir, f'sample_{id}.pkl'))
m.includeBranchrule(
branchrule=branchrule,
name="Sampling branching rule", desc="",
priority=666666, maxdepth=-1, maxbounddist=1)
m.optimize()
m.freeProb()
if require_sol: # construct training and test data, must have .sol for each .lp
ids = []; sols = []
for i in range(0, 3000):
sol_filepath = os.path.join(data_dir, f'{i}.sol')
if os.path.exists(sol_filepath):
ids.append(i)
sols.append(sol_filepath)
for cur_id, cur_sol_path in zip(ids, sols):
collect_single(cur_id, cur_sol_path)
else: # construct training and test data, for all .lp files
for i in range(0, 30):
collect_single(i, None)
def remove_broken_sample(data_dir):
for i in range(0, 3000):
sample_file = os.path.join(data_dir, f'sample_{i}.pkl')
if os.path.exists(sample_file):
try:
with gzip.open(sample_file, 'rb') as f:
sample = pickle.load(f)
except:
print(f'<{sample_file}> is broken. removing...')
os.remove(sample_file)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
home = expanduser("~")
data_dir = f'{home}/storage1/instances/vc/time_1000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/vc/time_3000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/vc/time_5000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/vc/time_7000'
collect_samples(data_dir)
data_dir = f'{home}/storage1/instances/vc/time_9000'
collect_samples(data_dir) | 4,361 | 31.073529 | 91 | py |
PB-DFS | PB-DFS-master/src/branching_ml_dfs.cpp | #include "branching_ml_dfs.hpp"
#include "utils.hpp"
#include <boost/algorithm/string.hpp>
#include <math.h>
/** branching rule data */
struct SCIP_BranchruleData
{
scip::ObjBranchrule *objbranchrule; /**< branching rule object */
SCIP_Bool deleteobject; /**< should the branching rule object be deleted when branching rule is freed? */
};
COML::Branching_dfs::Branching_dfs(
// ---------------------------------------------- SCIP parameters --------------------------------------------
SCIP *scip, /**< SCIP data structure */
const char *name, /**< name of branching rule */
const char *desc, /**< description of branching rule */
int priority, /**< priority of the branching rule */
int maxdepth, /**< maximal depth level, up to which this branching rule should be used (or -1) */
double maxbounddist /**< maximal relative distance from current node's dual bound to primal bound
* compared to best node's dual bound for applying branching rule
* (0.0: only on current best node, 1.0: on all nodes) */
// ---------------------------------------------- ml parameters --------------------------------------------
) : ObjBranchrule(scip, name, desc, priority, maxdepth, maxbounddist){};
SCIP_DECL_BRANCHEXECLP(COML::Branching_dfs::scip_execlp)
{
SCIP_BRANCHRULEDATA *branchruledata;
SCIP_VAR **tmplpcands;
SCIP_VAR **lpcands;
double *tmplpcandsfrac;
double *lpcandsfrac;
double bestdown;
double bestup;
double provedbound;
SCIP_Bool bestdownvalid;
SCIP_Bool bestupvalid;
int npriolpcands;
double *tmplpcandssol;
double *lpcandssol;
double bestscore;
int nlpcands;
int bestcand = -1;
assert(branchrule != NULL);
assert(strcmp(SCIPbranchruleGetName(branchrule), this->scip_name_) == 0);
assert(scip != NULL);
assert(scip == this->scip_);
assert(result != NULL);
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
*result = SCIP_DIDNOTRUN;
SCIP_CALL(SCIPgetLPBranchCands(scip, &tmplpcands, &tmplpcandssol, &tmplpcandsfrac, &nlpcands, &npriolpcands, NULL));
assert(nlpcands > 0);
assert(npriolpcands > 0);
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcands, tmplpcands, nlpcands));
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcandssol, tmplpcandssol, nlpcands));
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcandsfrac, tmplpcandsfrac, nlpcands));
SCIP_NODE* focus_node = SCIPgetFocusNode(scip);
long long cur_node_id = SCIPnodeGetNumber(focus_node);
if (nlpcands == 1)
{
bestcand = 0;
}
else
{
double cands_ml_score[nlpcands];
const char* var_name;
int var_idx;
char var_short_name[10];
int prefix_remove = gconf.prefix_size_remove + 2;
if (gconf.policy==Policy::ML_DFS_HEUR_SCORE1_GCN ||
gconf.policy==Policy::ML_DFS_HEUR_SCORE1_LR ||
gconf.policy == Policy::SCIP_DEF_PBDFS)
{
for (int i = 0; i < nlpcands; i++)
{
var_name = SCIPvarGetName(lpcands[i]);
strcpy(var_short_name, var_name + prefix_remove);
if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
{
cands_ml_score[i] = 0;
}
else
{
var_idx = gconf.var_mapper[var_short_name];
cands_ml_score[i] = gconf.ml_scores1[var_idx];
}
}
}
// else if (gconf.policy==Policy::ML_DFS_HEUR_SCORE3_GCN)
// {
// for (int i = 0; i < nlpcands; i++)
// {
// var_name = SCIPvarGetName(lpcands[i]);
// strcpy(var_short_name, var_name + prefix_remove);
// if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
// {
// cands_ml_score[i] = 0;
// }
// else
// {
// var_idx = gconf.var_mapper[var_short_name];
// cands_ml_score[i] = 1-gconf.ml_scores1[var_idx];
// }
// }
// }
else if (gconf.policy==Policy::ML_DFS_HEUR_SCORE2_GCN ||
gconf.policy==Policy::ML_DFS_HEUR_SCORE2_LR)
{
for (int i = 0; i < nlpcands; i++)
{
var_name = SCIPvarGetName(lpcands[i]);
strcpy(var_short_name, var_name + prefix_remove);
if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
{
cands_ml_score[i] = 0;
}
else
{
var_idx = gconf.var_mapper[var_short_name];
cands_ml_score[i] = gconf.ml_scores2[var_idx];
}
}
}
bestcand = COML::calc_argmax(cands_ml_score, nlpcands);
// printf("bestcand: %d, bestcand score: %f\n", bestcand, cands_ml_score[bestcand]);
}
assert(*result == SCIP_DIDNOTRUN);
if (0 > bestcand || bestcand >= nlpcands)
printf("bestcand: %d, nlpcands: %d\n", bestcand, nlpcands);
assert(0 <= bestcand && bestcand < nlpcands);
SCIP_NODE *downchild; SCIP_NODE *upchild;
SCIP_CALL(SCIPbranchVar(this->scip_, lpcands[bestcand], &downchild, NULL, &upchild));
if (downchild == NULL && upchild == NULL)
*result = SCIP_CUTOFF;
else
*result = SCIP_BRANCHED;
return SCIP_OKAY;
};
/*
* Callback methods of SCIP
* --------------------------------------------------------------------------------------------------------------
*/
extern "C"
{
/** copy method for branchrule plugins (called when SCIP copies plugins) */
static SCIP_DECL_BRANCHCOPY(branchCopyBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
assert(scip != NULL);
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ != scip);
if (branchruledata->objbranchrule->iscloneable())
{
scip::ObjBranchrule *newobjbranchrule;
newobjbranchrule = dynamic_cast<scip::ObjBranchrule *>(branchruledata->objbranchrule->clone(scip));
/* call include method of branchrule object */
SCIP_CALL(COML::SCIPincludeObjBranchrule_MLDFS(scip, newobjbranchrule, TRUE));
}
return SCIP_OKAY;
}
/** destructor of branching rule to free user data (called when SCIP is exiting) */
static SCIP_DECL_BRANCHFREE(branchFreeBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ == scip);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_free(scip, branchrule));
/* free branchrule object */
if (branchruledata->deleteobject)
delete branchruledata->objbranchrule;
/* free branchrule data */
delete branchruledata;
SCIPbranchruleSetData(branchrule, NULL); /*lint !e64*/
return SCIP_OKAY;
}
/** initialization method of branching rule (called after problem was transformed) */
static SCIP_DECL_BRANCHINIT(branchInitBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ == scip);
return SCIP_OKAY;
}
/** deinitialization method of branching rule (called before transformed problem is freed) */
static SCIP_DECL_BRANCHEXIT(branchExitBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_exit(scip, branchrule));
return SCIP_OKAY;
}
/** solving process initialization method of branching rule (called when branch and bound process is about to begin) */
static SCIP_DECL_BRANCHINITSOL(branchInitsolBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
return SCIP_OKAY;
}
/** solving process deinitialization method of branching rule (called before branch and bound process data is freed) */
static SCIP_DECL_BRANCHEXITSOL(branchExitsolBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_exitsol(scip, branchrule));
return SCIP_OKAY;
}
/** branching execution method for fractional LP solutions */
static SCIP_DECL_BRANCHEXECLP(branchExeclpBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata = NULL;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execlp(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
/** branching execution method for external candidates */
static SCIP_DECL_BRANCHEXECEXT(branchExecextBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execext(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
/** branching execution method for not completely fixed pseudo solutions */
static SCIP_DECL_BRANCHEXECPS(branchExecpsBranchingMLDFS)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execps(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
}
/** creates the branching rule for the given branching rule object and includes it in SCIP */
SCIP_RETCODE COML::SCIPincludeObjBranchrule_MLDFS(
SCIP *scip, /**< SCIP data structure */
scip::ObjBranchrule *objbranchrule, /**< branching rule object */
SCIP_Bool deleteobject /**< should the branching rule object be deleted when branching rule is freed? */
)
{
SCIP_BRANCHRULEDATA *branchruledata;
assert(scip != NULL);
assert(objbranchrule != NULL);
/* create branching rule data */
branchruledata = new SCIP_BRANCHRULEDATA;
branchruledata->objbranchrule = objbranchrule;
branchruledata->deleteobject = deleteobject;
/* include branching rule */
SCIP_CALL(SCIPincludeBranchrule(scip, objbranchrule->scip_name_, objbranchrule->scip_desc_,
objbranchrule->scip_priority_, objbranchrule->scip_maxdepth_, objbranchrule->scip_maxbounddist_,
branchCopyBranchingMLDFS,
branchFreeBranchingMLDFS, branchInitBranchingMLDFS, branchExitBranchingMLDFS, branchInitsolBranchingMLDFS, branchExitsolBranchingMLDFS,
branchExeclpBranchingMLDFS, branchExecextBranchingMLDFS, branchExecpsBranchingMLDFS,
branchruledata)); /*lint !e429*/
return SCIP_OKAY; /*lint !e429*/
} | 12,352 | 35.547337 | 168 | cpp |
PB-DFS | PB-DFS-master/src/branching_ml_dfs.hpp | #ifndef __SCIP_BRANCH_ML_DFS__
#define __SCIP_BRANCH_ML_DFS__
#include <vector>
#include <utility>
#include <cassert>
#include <unordered_map>
#include <chrono>
#include <random>
#include <stdio.h>
#include <algorithm>
#include <ctime>
#include <string>
#include <scip/scip.h>
#include <objscip/objscip.h>
#include <scip/struct_var.h>
#include <scip/type_stat.h>
#include <scip/struct_stat.h>
#include <scip/type_scip.h>
#include <scip/struct_scip.h>
#include <scip/struct_tree.h>
#include <scip/tree.h>
#include <scip/struct_var.h>
#include <scip/var.h>
#include "global_config.hpp"
#include <scip/scip_mem.h>
#include <scip/set.h>
#include <scip/struct_mem.h>
#include <scip/visual.h>
#include <scip/cons_linear.h>
#include <scip/type_cons.h>
#include <scip/struct_cons.h>
#include <scip/struct_nodesel.h>
namespace COML{
SCIP_RETCODE SCIPincludeObjBranchrule_MLDFS(
SCIP *scip, /**< SCIP data structure */
scip::ObjBranchrule *objbranchrule, /**< branching rule object */
SCIP_Bool deleteobject /**< should the branching rule object be deleted when branching rule is freed? */
);
class Branching_dfs : public scip::ObjBranchrule
{
public:
int num_vars;
Branching_dfs(
// ---------------------------------------------- SCIP parameters --------------------------------------------
SCIP* scip, /**< SCIP data structure */
const char* name, /**< name of branching rule */
const char* desc, /**< description of branching rule */
int priority, /**< priority of the branching rule */
int maxdepth, /**< maximal depth level, up to which this branching rule should be used (or -1) */
SCIP_Real maxbounddist /**< maximal relative distance from current node's dual bound to primal bound
* compared to best node's dual bound for applying branching rule
* (0.0: only on current best node, 1.0: on all nodes) */
// ---------------------------------------------- ml parameters --------------------------------------------
);
~Branching_dfs() {};
/** branching execution method for fractional LP solutions
*
* @see SCIP_DECL_BRANCHEXECLP(x) in @ref type_branch.h
*/
SCIP_DECL_BRANCHEXECLP(scip_execlp) override;
};
}
#endif | 2,515 | 34.942857 | 139 | hpp |
PB-DFS | PB-DFS-master/src/branching_policy.cpp |
#include "branching_policy.hpp"
#include "utils.hpp"
#define DEFAULT_REEVALAGE 10LL
#define DEFAULT_MAXPROPROUNDS -2
#define DEFAULT_PROBINGBOUNDS TRUE
#define SIMPLEX_ITERATION_LIMIT 500
#define DEFAULT_MAXLOOKAHEAD 9 /**< maximal number of further variables evaluated without better score */
#define DEFAULT_INITCAND 30 /**< maximal number of candidates initialized with strong branching per node */
/** branching rule data */
struct SCIP_BranchruleData
{
scip::ObjBranchrule *objbranchrule; /**< branching rule object */
SCIP_Bool deleteobject; /**< should the branching rule object be deleted when branching rule is freed? */
};
static SCIP_RETCODE printNodeRootPath(
SCIP *scip, /**< SCIP data structure */
SCIP_NODE *node, /**< node data */
FILE *file /**< output file (or NULL for standard output) */
);
/*
* actual methods that matters
* --------------------------------------------------------------------------------------------------------------
*/
/**
* called back from SCIP every branching decision
*
* arguments:
* SCIP* scip;
* SCIP_BRANCHRULE *branchrule;
* unsigned int allowaddcons;
* SCIP_RESULT *result;
* */
/**
* if current node depth less than the strong branching depth,
* we perform strong branching and update variable statistics.
* otherwise we train the model and let the model select branching variables.
*
*/
COML::Branching::Branching(
// ---------------------------------------------- SCIP parameters --------------------------------------------
SCIP *scip, /**< SCIP data structure */
const char *name, /**< name of branching rule */
const char *desc, /**< description of branching rule */
int priority, /**< priority of the branching rule */
int maxdepth, /**< maximal depth level, up to which this branching rule should be used (or -1) */
double maxbounddist /**< maximal relative distance from current node's dual bound to primal bound
* compared to best node's dual bound for applying branching rule
* (0.0: only on current best node, 1.0: on all nodes) */
// ---------------------------------------------- ml parameters --------------------------------------------
) : ObjBranchrule(scip, name, desc, priority, maxdepth, maxbounddist){};
SCIP_DECL_BRANCHINIT(COML::Branching::scip_init)
{
int num_vars;
int num_binary_vars;
int num_integral_vars;
int num_implicit_integral_vars;
int num_coutinous_vars;
SCIPgetVarsData(scip, NULL, &num_vars, &num_binary_vars,
&num_integral_vars, &num_implicit_integral_vars, &num_coutinous_vars);
printf("statistics of the transformed problem: \
num_vars: %d, num_binary_vars: %d, num_integral_vars: %d, \
num_implicit_integral_vars: %d, num_coutinous_vars: %d \n",
num_vars, num_binary_vars, num_integral_vars, num_implicit_integral_vars, num_coutinous_vars);
return SCIP_OKAY;
}
void COML::Branching::record_solving_curves(SCIP* scip)
{
// record primal info for curve plot
SCIP_SOL* sol = SCIPgetBestSol(scip);
double time = SCIPgetSolvingTime(scip);
if(sol != NULL)
{
SCIP_HEUR* h = SCIPsolGetHeur(sol);
double obj = SCIPgetSolOrigObj(scip, sol);
if (gconf.objs.empty())
{
gconf.objs.push_back(obj);
gconf.time.push_back(SCIPsolGetTime(sol));
gconf.first_sol_heur = h == NULL ? "none":SCIPheurGetName(h);
printf("first solution: %f %fs\n", obj, time);
if (h!=NULL)
printf("heuristic: %s\n", SCIPheurGetName(h));
else
printf("heuristic is None\n");
}else if (
(gconf.optimization_type == Optimization_Type::Maximization &&
obj > gconf.objs[gconf.objs.size()-1] + SCIPsetEpsilon(scip->set)) ||
(gconf.optimization_type == Optimization_Type::Minimization &&
obj < gconf.objs[gconf.objs.size()-1] - SCIPsetEpsilon(scip->set))
){
gconf.objs.push_back(obj);
gconf.time.push_back(time);
printf("better solution: %f %fs\n", obj, time);
if (h!=NULL)
printf("heuristic: %s\n", SCIPheurGetName(h));
else
printf("heuristic is None\n");
}
}
// record dual info for curve plot
double dualbound = SCIPgetDualbound(scip);
if (gconf.dual_bounds.empty())
{
gconf.dual_bounds.push_back(dualbound);
gconf.dual_time.push_back(time);
}else if (
(gconf.optimization_type == Optimization_Type::Maximization &&
dualbound < gconf.dual_bounds[gconf.dual_bounds.size()-1] - SCIPsetEpsilon(scip->set)) ||
(gconf.optimization_type == Optimization_Type::Minimization &&
dualbound > gconf.dual_bounds[gconf.dual_bounds.size()-1] + SCIPsetEpsilon(scip->set))
){
gconf.dual_bounds.push_back(dualbound);
gconf.dual_time.push_back(time);
}
// record gap info for curve plot
double optgap = SCIPgetGap(scip);
if (gconf.gaps.empty()){
gconf.gaps.push_back(optgap);
gconf.gap_time.push_back(time);
}else if (optgap < gconf.gaps[gconf.gaps.size()-1] - SCIPsetEpsilon(scip->set)){
gconf.gaps.push_back(optgap);
gconf.gap_time.push_back(time);
}
}
SCIP_DECL_BRANCHEXECLP(COML::Branching::scip_execlp)
{
if (gconf.record_solving_info)
record_solving_curves(scip);
SCIP_BRANCHRULEDATA *branchruledata;
SCIP_VAR **tmplpcands;
SCIP_VAR **lpcands;
double *tmplpcandsfrac;
double *lpcandsfrac;
double bestdown;
double bestup;
double provedbound;
SCIP_Bool bestdownvalid;
SCIP_Bool bestupvalid;
int npriolpcands;
double *tmplpcandssol;
double *lpcandssol;
double bestscore;
int nlpcands;
int bestcand = -1;
assert(branchrule != NULL);
assert(strcmp(SCIPbranchruleGetName(branchrule), this->scip_name_) == 0);
assert(scip != NULL);
assert(scip == this->scip_);
assert(result != NULL);
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
*result = SCIP_DIDNOTRUN;
SCIP_CALL(SCIPgetLPBranchCands(scip, &tmplpcands, &tmplpcandssol, &tmplpcandsfrac, &nlpcands, &npriolpcands, NULL));
assert(nlpcands > 0);
assert(npriolpcands > 0);
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcands, tmplpcands, nlpcands));
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcandssol, tmplpcandssol, nlpcands));
SCIP_CALL(SCIPduplicateBufferArray(scip, &lpcandsfrac, tmplpcandsfrac, nlpcands));
SCIP_NODE* focus_node = SCIPgetFocusNode(scip);
long long cur_node_id = SCIPnodeGetNumber(focus_node);
long long nnodes = SCIPgetNNodes(scip) - 1;
int nnodeLeft = SCIPgetNNodesLeft(scip);
// printf("cur_node_id: %lld\n", cur_node_id);
// printf("global_cut off bound: %f\n\n", SCIPgetCutoffbound(scip_));
// printf("is dual node: %d\n", gconf.is_dual_node(cur_node_id));
if (gconf.policy == Policy::ML_DING)
{
if (cur_node_id == 1)
{
SCIP_NODE* left_child_ptr; SCIP_NODE* right_child_ptr;
gconf.create_children_by_ml_local_cuts(scip, &left_child_ptr, &right_child_ptr, false);
(*result) = SCIP_BRANCHED;
}
else
{
SCIPexecRelpscostBranching(scip, lpcands, lpcandssol, lpcandsfrac, nlpcands,
TRUE, result);
}
}else if (gconf.policy == Policy::ML_DFS_EXACT_SCORE1_GCN ||
gconf.policy == Policy::ML_DFS_EXACT_SCORE2_GCN ||
gconf.policy == Policy::ML_DFS_EXACT_SCORE3_GCN){
double cands_ml_score[nlpcands];
const char* var_name;
int var_idx;
char var_short_name[10];
int prefix_remove = gconf.prefix_size_remove;
if (gconf.policy==Policy::ML_DFS_EXACT_SCORE1_GCN)
{
for (int i = 0; i < nlpcands; i++)
{
var_name = SCIPvarGetName(lpcands[i]);
strcpy(var_short_name, var_name + prefix_remove);
if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
{
cands_ml_score[i] = 0;
}
else
{
var_idx = gconf.var_mapper[var_short_name];
cands_ml_score[i] = gconf.ml_scores1[var_idx];
}
}
}
else if (gconf.policy==Policy::ML_DFS_EXACT_SCORE3_GCN)
{
for (int i = 0; i < nlpcands; i++)
{
var_name = SCIPvarGetName(lpcands[i]);
strcpy(var_short_name, var_name + prefix_remove);
if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
{
cands_ml_score[i] = 0;
}
else
{
var_idx = gconf.var_mapper[var_short_name];
cands_ml_score[i] = 1-gconf.ml_scores1[var_idx];
}
}
}
else if (gconf.policy==Policy::ML_DFS_EXACT_SCORE2_GCN )
{
for (int i = 0; i < nlpcands; i++)
{
var_name = SCIPvarGetName(lpcands[i]);
strcpy(var_short_name, var_name + prefix_remove);
if (gconf.var_mapper.find(var_short_name) == gconf.var_mapper.end())
{
cands_ml_score[i] = 0;
}
else
{
var_idx = gconf.var_mapper[var_short_name];
cands_ml_score[i] = gconf.ml_scores2[var_idx];
}
}
}
bestcand = COML::calc_argmax(cands_ml_score, nlpcands);
// printf("bestcand: %d, bestcand score: %f\n", bestcand, cands_ml_score[bestcand]);
assert(*result == SCIP_DIDNOTRUN);
if (0 > bestcand || bestcand >= nlpcands)
printf("bestcand: %d, nlpcands: %d\n", bestcand, nlpcands);
assert(0 <= bestcand && bestcand < nlpcands);
SCIP_NODE *downchild; SCIP_NODE *upchild;
SCIP_CALL(SCIPbranchVar(this->scip_, lpcands[bestcand], &downchild, NULL, &upchild));
if (downchild == NULL && upchild == NULL)
*result = SCIP_CUTOFF;
else
*result = SCIP_BRANCHED;
}
else {
SCIPexecRelpscostBranching(scip, lpcands, lpcandssol, lpcandsfrac, nlpcands,
TRUE, result);
}
// printf("result code: %d\n", *result);
SCIPfreeBufferArray(scip, &lpcandsfrac);
SCIPfreeBufferArray(scip, &lpcandssol);
SCIPfreeBufferArray(scip, &lpcands);
return SCIP_OKAY;
}
COML::Branching::~Branching()
{
}
/*
* Callback methods of SCIP
* --------------------------------------------------------------------------------------------------------------
*/
extern "C"
{
static SCIP_DECL_BRANCHCOPY(branchCopyDynamicBranching);
static SCIP_DECL_BRANCHFREE(branchFreeDynamicBranching);
static SCIP_DECL_BRANCHINIT(branchInitDynamicBranching);
static SCIP_DECL_BRANCHEXIT(branchExitDynamicBranching);
static SCIP_DECL_BRANCHINITSOL(branchInitsolDynamicBranching);
static SCIP_DECL_BRANCHEXITSOL(branchExitsolDynamicBranching);
static SCIP_DECL_BRANCHEXECLP(branchExeclpDynamicBranching);
static SCIP_DECL_BRANCHEXECEXT(branchExecextDynamicBranching);
static SCIP_DECL_BRANCHEXECPS(branchExecpsDynamicBranching);
}
/** creates the branching rule for the given branching rule object and includes it in SCIP */
SCIP_RETCODE COML::SCIPincludeObjBranchrule_DB(
SCIP *scip, /**< SCIP data structure */
scip::ObjBranchrule *objbranchrule, /**< branching rule object */
SCIP_Bool deleteobject /**< should the branching rule object be deleted when branching rule is freed? */
)
{
SCIP_BRANCHRULEDATA *branchruledata;
assert(scip != NULL);
assert(objbranchrule != NULL);
/* create branching rule data */
branchruledata = new SCIP_BRANCHRULEDATA;
branchruledata->objbranchrule = objbranchrule;
branchruledata->deleteobject = deleteobject;
/* include branching rule */
SCIP_CALL(SCIPincludeBranchrule(scip, objbranchrule->scip_name_, objbranchrule->scip_desc_,
objbranchrule->scip_priority_, objbranchrule->scip_maxdepth_, objbranchrule->scip_maxbounddist_,
branchCopyDynamicBranching,
branchFreeDynamicBranching, branchInitDynamicBranching, branchExitDynamicBranching, branchInitsolDynamicBranching, branchExitsolDynamicBranching,
branchExeclpDynamicBranching, branchExecextDynamicBranching, branchExecpsDynamicBranching,
branchruledata)); /*lint !e429*/
return SCIP_OKAY; /*lint !e429*/
}
extern "C"
{
/** copy method for branchrule plugins (called when SCIP copies plugins) */
static SCIP_DECL_BRANCHCOPY(branchCopyDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
assert(scip != NULL);
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ != scip);
if (branchruledata->objbranchrule->iscloneable())
{
scip::ObjBranchrule *newobjbranchrule;
newobjbranchrule = dynamic_cast<scip::ObjBranchrule *>(branchruledata->objbranchrule->clone(scip));
/* call include method of branchrule object */
SCIP_CALL(COML::SCIPincludeObjBranchrule_DB(scip, newobjbranchrule, TRUE));
}
return SCIP_OKAY;
}
/** destructor of branching rule to free user data (called when SCIP is exiting) */
static SCIP_DECL_BRANCHFREE(branchFreeDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ == scip);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_free(scip, branchrule));
/* free branchrule object */
if (branchruledata->deleteobject)
delete branchruledata->objbranchrule;
/* free branchrule data */
delete branchruledata;
SCIPbranchruleSetData(branchrule, NULL); /*lint !e64*/
return SCIP_OKAY;
}
/** initialization method of branching rule (called after problem was transformed) */
static SCIP_DECL_BRANCHINIT(branchInitDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
assert(branchruledata->objbranchrule->scip_ == scip);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_init(scip, branchrule));
return SCIP_OKAY;
}
/** deinitialization method of branching rule (called before transformed problem is freed) */
static SCIP_DECL_BRANCHEXIT(branchExitDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_exit(scip, branchrule));
return SCIP_OKAY;
}
/** solving process initialization method of branching rule (called when branch and bound process is about to begin) */
static SCIP_DECL_BRANCHINITSOL(branchInitsolDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_initsol(scip, branchrule));
return SCIP_OKAY;
}
/** solving process deinitialization method of branching rule (called before branch and bound process data is freed) */
static SCIP_DECL_BRANCHEXITSOL(branchExitsolDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_exitsol(scip, branchrule));
return SCIP_OKAY;
}
/** branching execution method for fractional LP solutions */
static SCIP_DECL_BRANCHEXECLP(branchExeclpDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execlp(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
/** branching execution method for external candidates */
static SCIP_DECL_BRANCHEXECEXT(branchExecextDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execext(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
/** branching execution method for not completely fixed pseudo solutions */
static SCIP_DECL_BRANCHEXECPS(branchExecpsDynamicBranching)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA *branchruledata;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
assert(branchruledata->objbranchrule != NULL);
/* call virtual method of branchrule object */
SCIP_CALL(branchruledata->objbranchrule->scip_execps(scip, branchrule, allowaddcons, result));
return SCIP_OKAY;
}
}
/*
* Callback methods of branching rule
* --------------------------------------------------------------------------------------------------------------
*/
static SCIP_RETCODE printNodeRootPath(
SCIP *scip, /**< SCIP data structure */
SCIP_NODE *node, /**< node data */
FILE *file /**< output file (or NULL for standard output) */
)
{
SCIP_VAR **branchvars; /* array of variables on which the branchings has been performed in all ancestors */
double *branchbounds; /* array of bounds which the branchings in all ancestors set */
SCIP_BOUNDTYPE *boundtypes; /* array of boundtypes which the branchings in all ancestors set */
int *nodeswitches; /* marks, where in the arrays the branching decisions of the next node on the path start
* branchings performed at the parent of node always start at position 0. For single variable branching,
* nodeswitches[i] = i holds */
int nbranchvars; /* number of variables on which branchings have been performed in all ancestors
* if this is larger than the array size, arrays should be reallocated and method should be called again */
int branchvarssize; /* available slots in arrays */
int nnodes; /* number of nodes in the nodeswitch array */
int nodeswitchsize; /* available slots in node switch array */
branchvarssize = SCIPnodeGetDepth(node);
nodeswitchsize = branchvarssize;
/* memory allocation */
SCIP_CALL(SCIPallocBufferArray(scip, &branchvars, branchvarssize));
SCIP_CALL(SCIPallocBufferArray(scip, &branchbounds, branchvarssize));
SCIP_CALL(SCIPallocBufferArray(scip, &boundtypes, branchvarssize));
SCIP_CALL(SCIPallocBufferArray(scip, &nodeswitches, nodeswitchsize));
SCIPnodeGetAncestorBranchingPath(node, branchvars, branchbounds, boundtypes, &nbranchvars, branchvarssize, nodeswitches, &nnodes, nodeswitchsize);
/* if the arrays were to small, we have to reallocate them and recall SCIPnodeGetAncestorBranchingPath */
if (nbranchvars > branchvarssize || nnodes > nodeswitchsize)
{
branchvarssize = nbranchvars;
nodeswitchsize = nnodes;
/* memory reallocation */
SCIP_CALL(SCIPreallocBufferArray(scip, &branchvars, branchvarssize));
SCIP_CALL(SCIPreallocBufferArray(scip, &branchbounds, branchvarssize));
SCIP_CALL(SCIPreallocBufferArray(scip, &boundtypes, branchvarssize));
SCIP_CALL(SCIPreallocBufferArray(scip, &nodeswitches, nodeswitchsize));
SCIPnodeGetAncestorBranchingPath(node, branchvars, branchbounds, boundtypes, &nbranchvars, branchvarssize, nodeswitches, &nnodes, nodeswitchsize);
assert(nbranchvars == branchvarssize);
}
/* we only want to create output, if branchings were performed */
if (nbranchvars >= 1)
{
int i;
int j;
/* print all nodes, starting from the root, which is last in the arrays */
for (j = nnodes - 1; j >= 0; --j)
{
int end;
if (j == nnodes - 1)
end = nbranchvars;
else
end = nodeswitches[j + 1];
for (i = nodeswitches[j]; i < end; ++i)
{
if (i > nodeswitches[j])
printf(" AND ");
printf("<%s> %s %.1f", SCIPvarGetName(branchvars[i]), boundtypes[i] == SCIP_BOUNDTYPE_LOWER ? ">=" : "<=", branchbounds[i]);
}
printf("\n");
if (j > 0)
{
if (nodeswitches[j] - nodeswitches[j - 1] != 1)
printf(" |\n |\n");
else if (boundtypes[i - 1] == SCIP_BOUNDTYPE_LOWER)
printf("\\ \n \\\n");
else
printf(" /\n/ \n");
}
}
}
/* free all local memory */
SCIPfreeBufferArray(scip, &nodeswitches);
SCIPfreeBufferArray(scip, &boundtypes);
SCIPfreeBufferArray(scip, &branchbounds);
SCIPfreeBufferArray(scip, &branchvars);
return SCIP_OKAY;
} | 22,522 | 36.475874 | 180 | cpp |
PB-DFS | PB-DFS-master/src/branching_policy.hpp | #ifndef __SCIP_BRANCH_DYNAMIC_H__
#define __SCIP_BRANCH_DYNAMIC_H__
#include <vector>
#include <utility>
#include <cassert>
#include <unordered_map>
#include <chrono>
#include <random>
#include <stdio.h>
#include <algorithm>
#include <ctime>
#include <string>
#include <scip/scip.h>
#include <objscip/objscip.h>
#include <scip/struct_var.h>
#include <scip/type_stat.h>
#include <scip/struct_stat.h>
#include <scip/type_scip.h>
#include <scip/struct_scip.h>
#include <scip/struct_tree.h>
#include <scip/tree.h>
#include <scip/struct_var.h>
#include <scip/var.h>
#include "global_config.hpp"
#include <scip/scip_mem.h>
#include <scip/set.h>
#include <scip/struct_mem.h>
#include <scip/visual.h>
#include <scip/cons_linear.h>
#include <scip/type_cons.h>
#include <scip/struct_cons.h>
#include <scip/struct_nodesel.h>
#include <boost/algorithm/string.hpp>
#include <math.h>
#include <scip/branch_relpscost.h>
namespace COML{
SCIP_RETCODE SCIPincludeObjBranchrule_DB(
SCIP* scip, /**< SCIP data structure */
scip::ObjBranchrule* objbranchrule, /**< branching rule object */
SCIP_Bool deleteobject /**< should the branching rule object be deleted when branching rule is freed? */
);
class Branching : public scip::ObjBranchrule
{
public:
int num_vars;
Branching(
// ---------------------------------------------- SCIP parameters --------------------------------------------
SCIP* scip, /**< SCIP data structure */
const char* name, /**< name of branching rule */
const char* desc, /**< description of branching rule */
int priority, /**< priority of the branching rule */
int maxdepth, /**< maximal depth level, up to which this branching rule should be used (or -1) */
SCIP_Real maxbounddist /**< maximal relative distance from current node's dual bound to primal bound
* compared to best node's dual bound for applying branching rule
* (0.0: only on current best node, 1.0: on all nodes) */
// ---------------------------------------------- ml parameters --------------------------------------------
);
~Branching();
void record_solving_curves(SCIP* scip);
/** branching execution method for fractional LP solutions
*
* @see SCIP_DECL_BRANCHEXECLP(x) in @ref type_branch.h
*/
SCIP_DECL_BRANCHEXECLP(scip_execlp) override;
SCIP_DECL_BRANCHINIT(scip_init) override;
};
}
#endif | 2,717 | 32.555556 | 139 | hpp |
PB-DFS | PB-DFS-master/src/global_config.cpp | #include "global_config.hpp"
#include "utils.hpp"
#include <time.h>
#include <unistd.h>
#include <sys/types.h>
#include <pwd.h>
#include <scip/struct_scip.h>
#include <scip/struct_tree.h>
#include <scip/struct_set.h>
#include <scip/struct_mem.h>
#include <scip/set.h>
#include <scip/tree.h>
#include <scip/cons_linear.h>
COML::Global_config::Global_config()
: solving_stats_logger(NULL), optimization_type(Optimization_Type::Maximization),
seed(0), cutoff(0), split_id(0), objs(), time(), ml_scores1(), ml_scores2(),
dual_bounds(), dual_time(), gaps(), gap_time(), prefix_size_remove(3)
{}
void COML::Global_config::init(Policy policy, int prob_type, double cutoff_time, int split_id)
{
const char *homedir;
if ((homedir = getenv("HOME")) == NULL)
homedir = getpwuid(getuid())->pw_dir;
this->home_dir = homedir;
this->start_time_clock = currentDateTime();
this->split_id = split_id;
this->cutoff = cutoff_time;
this->policy = policy;
this->prob = prob_type;
int _cutoff = cutoff_time;
std::string pname;
if (policy == Policy::SCIP_AGG) pname = "scip_agg";
else if (policy == Policy::SCIP_DEF) pname = "scip_def";
else if (policy == Policy::SCIP_DEF_PBDFS) pname = "scip_def_pbdfs";
else if (policy == Policy::ML_DING) pname = "ml_split";
else if (policy == Policy::ML_DFS_HEUR_SCORE1_GCN)
{
if (this->cutoff <= 100)
pname = "pbdfs1_gcn_" + std::to_string(_cutoff);
else
pname = "pbdfs1_gcn";
}
else if (policy == Policy::ML_DFS_HEUR_SCORE2_GCN){
if (this->cutoff <= 100)
pname = "pbdfs2_gcn_" + std::to_string(_cutoff);
else
pname = "pbdfs2_gcn";
}
else if (policy == Policy::ML_DFS_HEUR_SCORE1_LR){
if (this->cutoff <= 100)
pname = "pbdfs1_lr_" + std::to_string(_cutoff);
else
pname = "pbdfs1_lr";
} else if (policy == Policy::ML_DFS_EXACT_SCORE1_GCN)
{
if (this->cutoff <= 100)
pname = "pb_dfs1_gcn_exact_" + std::to_string(_cutoff);
else
pname = "pb_dfs1_gcn_exact";
}
else if (policy == Policy::ML_DFS_EXACT_SCORE2_GCN){
if (this->cutoff <= 100)
pname = "pb_dfs2_gcn_exact_" + std::to_string(_cutoff);
else
pname = "pb_dfs2_gcn_exact";
}
else if (policy == Policy::ML_DFS_EXACT_SCORE3_GCN){
if (this->cutoff <= 100)
pname = "pb_dfs3_gcn_exact_" + std::to_string(_cutoff);
else
pname = "pb_dfs3_gcn_exact";
}
else if (policy == Policy::ML_DFS_HEUR_SCORE2_LR){
if (this->cutoff <= 100)
pname = "pbdfs2_lr_" + std::to_string(_cutoff);
else
pname = "pbdfs2_lr";
}
else if (policy == Policy::SCIP_HEUR_ALL_ROUNDING) pname = "heur_all_rounding";
else if (policy == Policy::SCIP_HEUR_ALL_DIVING) pname = "heur_all_diving";
else if (policy == Policy::SCIP_HEUR_FEASPUMP) pname = "heur_feaspump";
else if (policy == Policy::SCIP_HEUR_RENS) pname = "heur_rens";
else throw std::runtime_error("unrecognized policy!\n");
switch (prob_type)
{
case 0: this->prob_str = "mis"; this->optimization_type = Maximization; break;
case 1: this->prob_str = "sc"; this->optimization_type = Minimization; break;
case 2: this->prob_str = "tsp"; this->optimization_type = Minimization; break;
case 3: this->prob_str = "vrp"; this->optimization_type = Minimization; break;
case 4: this->prob_str = "vc"; this->optimization_type = Minimization; break;
case 5: this->prob_str = "ds"; this->optimization_type = Minimization; break;
case 6: this->prob_str = "ca"; this->optimization_type = Maximization; break;
default: throw std::runtime_error("unrecognized problem type!\n");
}
this->DATA_BASE_DIR = ("./datasets/" + prob_str + "/");
this->LOG_DIR = "./ret_solver/" + prob_str + "/" + pname + "/";
COML::create_dir("./ret_solver/");
COML::create_dir("./ret_solver/" + prob_str);
COML::create_dir(this->LOG_DIR);
std::string info(
"problem type: " + prob_str + "\nevaluation policy: " + pname +
"\ndata read from: " + DATA_BASE_DIR + "\nlog write to: " + this->LOG_DIR + "\n\n");
printf("%s\n", info.c_str());
std::string tmp;
tmp = LOG_DIR + "solving_stats_" + std::to_string(this->split_id) + ".csv";
this->solving_stats_logger = new std::ofstream(tmp);
(*solving_stats_logger) << "instance_id,status,opt_gap,best_sol_obj,best_sol_time,best_sol_heur,best_heur_sol_obj,best_heur_sol_time,heur_ncalls,heur_tot_time\n";
(*solving_stats_logger).flush();
}
int comparator_decending1(const std::pair<std::string, double> &l, const std::pair<std::string, double> &r)
{
return l.second > r.second;
}
void COML::Global_config::cleanup()
{
objs.clear();
time.clear();
dual_bounds.clear();
dual_time.clear();
gaps.clear();
gap_time.clear();
first_sol_heur = "none";
this->ml_scores1.clear();
this->ml_scores2.clear();
this->var_mapper.clear();
}
void COML::Global_config::setup(int nvars, double* ml_scores1, double* ml_scores2, int seed)
{
this->seed = seed;
this->nprobvars = nvars;
for (int i = 0; i < nprobvars; i++){
this->ml_scores1.push_back(ml_scores1[i]);
this->ml_scores2.push_back(ml_scores2[i]);
}
}
COML::Global_config::~Global_config()
{
if (solving_stats_logger != NULL)
{
solving_stats_logger->flush();
solving_stats_logger->close();
delete solving_stats_logger;
}
}
SCIP_RETCODE COML::Global_config::create_children_by_ml_local_cuts(SCIP* scip,
SCIP_NODE** left_child_ptr, SCIP_NODE** right_child_ptr, bool left_child_only)
{
int nfixed_vars;
int rhs;
switch (this->prob)
{
case 0: // mis prob
case 4: // vc prob
case 6:
nfixed_vars = this->nprobvars * 0.9;
rhs = 10;
break;
case 1: // sc
case 5: // ds
nfixed_vars = this->nprobvars * 0.9;
rhs = 0;
break;
default:
throw std::runtime_error("problem not specify fixing vars\n");
break;
}
/* create mapping between var names and var */
SCIP_VAR* var; SCIP_VAR* var1; SCIP_VAR* var2;
int i; int j; int var_idx;
std::string var_name; std::string var_name1; std::string var_name2; std::string prefix;
std::vector<std::string> result;
SCIP_VAR** vars = SCIPgetVars(scip);
int nvars = SCIPgetNVars(scip);
printf("fixing variables: %d/%d\n", nfixed_vars, nvars);
std::unordered_map<std::string, SCIP_VAR*> dict;
for (i = 0; i < nvars; i++){
dict[SCIPvarGetName(vars[i])] = vars[i];
}
// create var prefix
var_name = SCIPvarGetName(vars[0]);
prefix = var_name.substr(0, this->prefix_size_remove);
SCIP_VAR* fixed_vars[nfixed_vars];
double fixed_var_coefs[nfixed_vars];
int subtract_to_rhs = 0;
std::vector<std::pair<std::string, double>> name_score;
for (i = 0; i < this->ml_scores2.size(); i++)
{
std::pair<std::string, double> p;
p.first = this->orderednames[i];
p.second = this->ml_scores2[i];
name_score.push_back(p);
}
std::sort(name_score.begin(), name_score.end(), comparator_decending1);
for (i = 0, j = 0; j < nfixed_vars; i++)
{
var_name = name_score[i].first;
var_idx = this->var_mapper[var_name];
if (dict.find( prefix + var_name ) != dict.end()){
var = dict[prefix + var_name];
var_idx = this->var_mapper[var_name];
fixed_vars[j] = var;
if (this->ml_scores1[var_idx] > 0.5)
{
subtract_to_rhs+=1;
fixed_var_coefs[j] = - 1.;
}
else
{
fixed_var_coefs[j] = 1.;
}
j++;
}
}
rhs = rhs - subtract_to_rhs;
printf("creating children by ml split!\n");
SCIP_NODE* focusnode = SCIPgetFocusNode(scip);
/* left */
SCIP_NODE* left_child; SCIP_CONS* cons_left;
SCIP_CALL( SCIPnodeCreateChild(&left_child, scip->mem->probmem, scip->set, scip->stat, scip->tree, 1, SCIPnodeGetEstimate(focusnode)));
SCIPcreateConsLinear(scip, &cons_left, "cons_left_cut", nfixed_vars, fixed_vars, fixed_var_coefs,
- SCIPsetInfinity(scip->set), rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE);
SCIPaddConsNode(scip, left_child, cons_left, NULL);
SCIPreleaseCons(scip, &cons_left);
*left_child_ptr = left_child;
// left child should be the new focus subtree root
if (left_child_only)
return SCIP_OKAY;
/* right */
SCIP_NODE* right_child; SCIP_CONS* cons_right;
SCIP_CALL( SCIPnodeCreateChild(&right_child, scip->mem->probmem, scip->set, scip->stat, scip->tree, 0, SCIPnodeGetEstimate(focusnode)));
SCIPcreateConsLinear(scip, &cons_right, "cons_left_cut", nfixed_vars, fixed_vars, fixed_var_coefs,
rhs+1 , SCIPsetInfinity(scip->set),
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE);
SCIPaddConsNode(scip, right_child, cons_right, NULL);
SCIPreleaseCons(scip, &cons_right);
*right_child_ptr = right_child;
}
COML::Global_config gconf;
| 9,444 | 33.345455 | 166 | cpp |
PB-DFS | PB-DFS-master/src/global_config.hpp | #ifndef __global__conf__
#define __global__conf__
#include <cstdlib>
#include <string>
#include <pwd.h>
#include <unistd.h>
#include <fstream>
#include <vector>
#include <unordered_map>
#include <unordered_set>
#include <queue>
#include <boost/algorithm/string.hpp>
#include <scip/type_retcode.h>
#include <scip/scip.h>
namespace COML{
typedef enum Optimization_Type
{
Maximization, Minimization
} Optimization_Type;
typedef enum Policy
{
// exact
SCIP_DEF_PBDFS,
SCIP_DEF,
SCIP_AGG,
ML_DING,
ML_DFS_HEUR_SCORE1_GCN,
ML_DFS_HEUR_SCORE2_GCN,
ML_DFS_HEUR_SCORE1_LR,
ML_DFS_HEUR_SCORE2_LR,
SCIP_HEUR_FEASPUMP,
SCIP_HEUR_RENS,
SCIP_HEUR_ALL_ROUNDING,
SCIP_HEUR_ALL_DIVING,
ML_DFS_EXACT_SCORE1_GCN,
ML_DFS_EXACT_SCORE2_GCN,
ML_DFS_EXACT_SCORE3_GCN,
STATS,
} Policy;
typedef struct Global_config
{
Global_config();
~Global_config();
public:
std::string prob_str;
Optimization_Type optimization_type;
int split_id;
std::string prob_lp_path;
int prefix_size_remove;
int nprobvars;
int prob;
std::unordered_map<std::string, int> var_mapper;
std::vector<std::string> orderednames;
std::vector<double> ml_scores1; // fn = p
std::vector<double> ml_scores2; // fn = max(1-p, p)
Policy policy;
std::string cur_prob;
double cutoff;
std::string start_time_clock;
std::string home_dir;
std::string DATA_BASE_DIR;
std::string LOG_DIR;
std::ofstream* solving_stats_logger;
bool record_solving_info = true;
std::string first_sol_heur;
// recorded information during solving
std::vector<double> objs;
std::vector<double> time;
std::vector<double> dual_bounds;
std::vector<double> dual_time;
std::vector<double> gaps;
std::vector<double> gap_time;
void init(Policy policy, int prob_type, double cutoff_time, int split_id);
void setup(int nnodes, double* ml_scores1, double* ml_scores2, int seed);
void cleanup(); // must be used at the end
SCIP_RETCODE create_children_by_ml_local_cuts(SCIP* scip,
SCIP_NODE** left_child_ptr, SCIP_NODE** right_child_ptr, bool left_child_only);
// --- scip param variables ---
int seed;
}Global_config;
}
extern COML::Global_config gconf;
#endif | 2,328 | 23.260417 | 111 | hpp |
PB-DFS | PB-DFS-master/src/heur_ml_subscip.cpp | /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/* */
/* This file is part of the program and library */
/* SCIP --- Solving Constraint Integer Programs */
/* */
/* Copyright (C) 2002-2019 Konrad-Zuse-Zentrum */
/* fuer Informationstechnik Berlin */
/* */
/* SCIP is distributed under the terms of the ZIB Academic License. */
/* */
/* You should have received a copy of the ZIB Academic License */
/* along with SCIP; see the file COPYING. If not visit scip.zib.de. */
/* */
/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/**@file heur_MLdfs.c
* @brief Local branching heuristic according to Fischetti and Lodi
* @author Timo Berthold
* @author Marc Pfetsch
*/
/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
#include <blockmemshell/memory.h>
#include <scip/cons_linear.h>
#include <scip/heuristics.h>
#include "heur_ml_subscip.hpp"
#include <scip/pub_event.h>
#include <scip/pub_heur.h>
#include <scip/pub_message.h>
#include <scip/pub_misc.h>
#include <scip/pub_sol.h>
#include <scip/pub_var.h>
#include <scip/scip_branch.h>
#include <scip/scip_cons.h>
#include <scip/scip_copy.h>
#include <scip/scip_event.h>
#include <scip/scip_general.h>
#include <scip/scip_heur.h>
#include <scip/scip_mem.h>
#include <scip/scip_message.h>
#include <scip/scip_nodesel.h>
#include <scip/scip_numerics.h>
#include <scip/scip_param.h>
#include <scip/scip_prob.h>
#include <scip/scip_sol.h>
#include <scip/scip_solve.h>
#include <scip/scip_solvingstats.h>
#include <string.h>
#include "branching_ml_dfs.hpp"
#include "nodesel_ml_dfs.hpp"
#define HEUR_NAME "mldfs"
#define HEUR_DESC "local branching heuristic by Fischetti and Lodi"
#define HEUR_DISPCHAR 'L'
#define HEUR_PRIORITY -1000000
#define HEUR_FREQ 100
#define HEUR_FREQOFS 0
#define HEUR_MAXDEPTH -1
#define HEUR_TIMING SCIP_HEURTIMING_BEFOREPRESOL
#define HEUR_USESSUBSCIP TRUE /**< does the heuristic use a secondary SCIP instance? */
#define DEFAULT_NEIGHBORHOODSIZE 18 /* radius of the incumbents neighborhood to be searched */
#define DEFAULT_NODESOFS 1000 /* number of nodes added to the contingent of the total nodes */
#define DEFAULT_MAXNODES 10000 /* maximum number of nodes to regard in the subproblem */
#define DEFAULT_MINIMPROVE 0.01 /* factor by which MLdfs should at least improve the incumbent */
#define DEFAULT_MINNODES 1000 /* minimum number of nodes required to start the subproblem */
#define DEFAULT_NODESQUOT 0.05 /* contingent of sub problem nodes in relation to original nodes */
#define DEFAULT_LPLIMFAC 1.5 /* factor by which the limit on the number of LP depends on the node limit */
#define DEFAULT_NWAITINGNODES 200 /* number of nodes without incumbent change that heuristic should wait */
#define DEFAULT_USELPROWS FALSE /* should subproblem be created out of the rows in the LP rows,
* otherwise, the copy constructors of the constraints handlers are used */
#define DEFAULT_COPYCUTS TRUE /* if DEFAULT_USELPROWS is FALSE, then should all active cuts from the cutpool
* of the original scip be copied to constraints of the subscip
*/
#define DEFAULT_BESTSOLLIMIT 3 /* limit on number of improving incumbent solutions in sub-CIP */
#define DEFAULT_USEUCT FALSE /* should uct node selection be used at the beginning of the search? */
/* event handler properties */
#define EVENTHDLR_NAME "MLdfs"
#define EVENTHDLR_DESC "LP event handler for " HEUR_NAME " heuristic"
#define EXECUTE 0
#define WAITFORNEWSOL 1
/*
* Data structures
*/
/** primal heuristic data */
struct SCIP_HeurData
{
int nwaitingnodes; /**< number of nodes without incumbent change that heuristic should wait */
int nodesofs; /**< number of nodes added to the contingent of the total nodes */
int minnodes; /**< minimum number of nodes required to start the subproblem */
int maxnodes; /**< maximum number of nodes to regard in the subproblem */
SCIP_Longint usednodes; /**< amount of nodes local branching used during all calls */
SCIP_Real nodesquot; /**< contingent of sub problem nodes in relation to original nodes */
SCIP_Real minimprove; /**< factor by which MLdfs should at least improve the incumbent */
SCIP_Real nodelimit; /**< the nodelimit employed in the current sub-SCIP, for the event handler*/
SCIP_Real lplimfac; /**< factor by which the limit on the number of LP depends on the node limit */
int neighborhoodsize; /**< radius of the incumbent's neighborhood to be searched */
int callstatus; /**< current status of MLdfs heuristic */
SCIP_SOL* lastsol; /**< the last incumbent MLdfs used as reference point */
int curneighborhoodsize;/**< current neighborhoodsize */
int curminnodes; /**< current minimal number of nodes required to start the subproblem */
int emptyneighborhoodsize;/**< size of neighborhood that was proven to be empty */
SCIP_Bool uselprows; /**< should subproblem be created out of the rows in the LP rows? */
SCIP_Bool copycuts; /**< if uselprows == FALSE, should all active cuts from cutpool be copied
* to constraints in subproblem?
*/
int bestsollimit; /**< limit on number of improving incumbent solutions in sub-CIP */
SCIP_Bool useuct; /**< should uct node selection be used at the beginning of the search? */
};
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< SCIP data structure of the original problem */
SCIP* subscip, /**< SCIP data structure of the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_HEUR* heur, /**< the MLdfs heuristic */
SCIP_SOL* subsol, /**< solution of the subproblem */
SCIP_Bool* success /**< pointer to store, whether new solution was found */
)
{
SCIP_VAR** vars;
int nvars;
SCIP_SOL* newsol;
SCIP_Real* subsolvals;
assert( scip != NULL );
assert( subscip != NULL );
assert( subvars != NULL );
assert( subsol != NULL );
/* copy the solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
* since constraint copying may have required the copy of variables that are fixed in the main SCIP
*/
assert(nvars <= SCIPgetNOrigVars(subscip));
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &subsolvals);
return SCIP_OKAY;
}
/* ---------------- Callback methods of event handler ---------------- */
/* exec the event handler
*
* we interrupt the solution process
*/
static
SCIP_DECL_EVENTEXEC(eventExecMLdfs)
{
SCIP_HEURDATA* heurdata;
assert(eventhdlr != NULL);
assert(eventdata != NULL);
assert(strcmp(SCIPeventhdlrGetName(eventhdlr), EVENTHDLR_NAME) == 0);
assert(event != NULL);
assert(SCIPeventGetType(event) & SCIP_EVENTTYPE_LPSOLVED);
heurdata = (SCIP_HEURDATA*)eventdata;
assert(heurdata != NULL);
/* interrupt solution process of sub-SCIP */
if( SCIPgetNLPs(scip) > heurdata->lplimfac * heurdata->nodelimit )
{
SCIPdebugMsg(scip, "interrupt after %" SCIP_LONGINT_FORMAT " LPs\n",SCIPgetNLPs(scip));
SCIP_CALL( SCIPinterruptSolve(scip) );
}
return SCIP_OKAY;
}
/*
* Callback methods of primal heuristic
*/
/** copy method for primal heuristic plugins (called when SCIP copies plugins) */
static
SCIP_DECL_HEURCOPY(heurCopyMLdfs)
{ /*lint --e{715}*/
assert(scip != NULL);
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
/* call inclusion method of primal heuristic */
SCIP_CALL( SCIPincludeHeurMLdfs(scip) );
return SCIP_OKAY;
}
/** destructor of primal heuristic to free user data (called when SCIP is exiting) */
static
SCIP_DECL_HEURFREE(heurFreeMLdfs)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
assert( heur != NULL );
assert( scip != NULL );
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* free heuristic data */
SCIPfreeBlockMemory(scip, &heurdata);
SCIPheurSetData(heur, NULL);
return SCIP_OKAY;
}
/** initialization method of primal heuristic (called after problem was transformed) */
static
SCIP_DECL_HEURINIT(heurInitMLdfs)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
assert( heur != NULL );
assert( scip != NULL );
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* with a little abuse we initialize the heurdata as if MLdfs would have finished its last step regularly */
heurdata->callstatus = WAITFORNEWSOL;
heurdata->lastsol = NULL;
heurdata->usednodes = 0;
heurdata->curneighborhoodsize = heurdata->neighborhoodsize;
heurdata->curminnodes = heurdata->minnodes;
heurdata->emptyneighborhoodsize = 0;
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMLdfs)
{ /*lint --e{715}*/
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
SCIP_HEURDATA* heurdata;
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars;
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real upperbound;
int nvars;
int i;
SCIP_Bool success;
SCIP* subscip;
SCIP_CALL( SCIPcreate(&subscip) );
printf("exe ml dfs heuristic\n");
/* get the data of the variables and the best solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), nvars) );
success = FALSE;
SCIPcopy(scip, subscip, varmapfw, NULL, "df", FALSE, FALSE, FALSE, 0, NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
for (i = 0; i < nvars; ++i)
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
assert(scip != NULL);
assert(subscip != NULL);
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
/* speed up the heuristic */
SCIPsetIntParam(subscip, "presolving/maxrounds", 0);
SCIPsetIntParam(subscip, "separating/maxrounds", 0);
SCIPsetIntParam(subscip, "presolving/maxrestarts", 0);
SCIPsetIntParam(subscip, "separating/maxroundsroot", 0);
SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE);
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* set termination condition */
// SCIPsetRealParam(subscip, "limits/time", 5);
SCIPsetIntParam(subscip, "limits/solutions", 1);
COML::Branching_dfs* branching_policy = new COML::Branching_dfs( subscip, "", "", 66666667, -1, 1);
COML::SCIPincludeObjBranchrule_MLDFS(subscip, branching_policy, false);
COML::Nodesel_ML_DFS* nodesel_policy = new COML::Nodesel_ML_DFS(subscip, "", "", 66666667, 66666667);
SCIPincludeObjNodesel_MLDFS(subscip, nodesel_policy, false);
SCIP_CALL( SCIPtransformProb(subscip) );
SCIP_CALL_ABORT( SCIPsolve(subscip) );
printf("endsolve\n");
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
if( success )
{
*result = SCIP_FOUNDSOL;
}
}
}
else
{
printf("heuristic did not find any feasible solution\n");
}
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/*
* primal heuristic specific interface methods
*/
/** creates the MLdfs primal heuristic and includes it in SCIP */
SCIP_RETCODE SCIPincludeHeurMLdfs(
SCIP* scip /**< SCIP data structure */
)
{
SCIP_HEURDATA* heurdata;
SCIP_HEUR* heur;
/* create MLdfs primal heuristic data */
SCIP_CALL( SCIPallocBlockMemory(scip, &heurdata) );
/* include primal heuristic */
SCIP_CALL( SCIPincludeHeurBasic(scip, &heur,
HEUR_NAME, HEUR_DESC, HEUR_DISPCHAR, HEUR_PRIORITY, HEUR_FREQ, HEUR_FREQOFS,
HEUR_MAXDEPTH, HEUR_TIMING, HEUR_USESSUBSCIP, heurExecMLdfs, heurdata) );
assert(heur != NULL);
/* set non-NULL pointers to callback methods */
SCIP_CALL( SCIPsetHeurCopy(scip, heur, heurCopyMLdfs) );
SCIP_CALL( SCIPsetHeurFree(scip, heur, heurFreeMLdfs) );
SCIP_CALL( SCIPsetHeurInit(scip, heur, heurInitMLdfs) );
return SCIP_OKAY;
}
| 15,415 | 40 | 124 | cpp |
PB-DFS | PB-DFS-master/src/heur_ml_subscip.hpp | /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/* */
/* This file is part of the program and library */
/* SCIP --- Solving Constraint Integer Programs */
/* */
/* Copyright (C) 2002-2019 Konrad-Zuse-Zentrum */
/* fuer Informationstechnik Berlin */
/* */
/* SCIP is distributed under the terms of the ZIB Academic License. */
/* */
/* You should have received a copy of the ZIB Academic License */
/* along with SCIP; see the file COPYING. If not visit scip.zib.de. */
/* */
/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/**@file heur_localbranching.h
* @ingroup PRIMALHEURISTICS
* @brief Local branching heuristic according to Fischetti and Lodi
* @author Timo Berthold
*/
/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
#ifndef __SCIP_HEUR_MLSUBSCIP_H__
#define __SCIP_HEUR_MLSUBSCIP_H__
#include <scip/def.h>
#include <scip/type_retcode.h>
#include <scip/type_scip.h>
/** creates local branching primal heuristic and includes it in SCIP
*
* @ingroup PrimalHeuristicIncludes
*/
SCIP_RETCODE SCIPincludeHeurMLdfs(
SCIP* scip /**< SCIP data structure */
);
#endif
| 1,795 | 41.761905 | 123 | hpp |
PB-DFS | PB-DFS-master/src/main.cpp | #include "preprocessor.hpp"
#include <iostream>
#include <time.h>
#include <sys/time.h>
#include "global_config.hpp"
#include "scip_solver.hpp"
double get_wall_time(){
struct timeval time;
if (gettimeofday(&time,NULL)){
return 0;
}
return (double)time.tv_sec + (double)time.tv_usec * .000001;
}
void exit_and_help(){
std::cout << "Usage: ./MIS [options] datafile" << std::endl;
std::cout << "options: " << std::endl;
std::cout << "-p : set the problem type" << std::endl;
std::cout << "-0 - mis problem" << std::endl;
std::cout << "-1 - sc problem" << std::endl;
std::cout << "-2 - tsp problem" << std::endl;
std::cout << "-3 - vrp problem" << std::endl;
std::cout << "-4 - vc problem" << std::endl;
std::cout << "-5 - ds problem" << std::endl;
std::cout << "-6 - ca problem" << std::endl;
std::cout << "-d : set the test dataset split" << std::endl;
std::cout << "total 3 splits: 0..2" << std::endl;
std::cout << "-b : set branching method to solve the problem (default 0)" << std::endl;
std::cout << "0 .. 6" << std::endl;
exit(1);
}
int main(int argc, char* argv[]) {
using namespace COML;
double param_cutoff = 1000; //cutoff time in seconds.
int param_prob_type = 0;
int branching_policy = 0;
int split_id = 0;
int span = 10;
// parse options (parameters)
for(int i = 1; i < argc; ++i){
if(argv[i][0] != '-'){
break;
}
if(++i >= argc){
exit_and_help();
}
switch(argv[i-1][1]){
case 't': param_cutoff = std::stod(argv[i]); break;
case 'h': branching_policy = std::atoi(argv[i]); break;
case 'p': param_prob_type = std::atoi(argv[i]); break;
case 'd': split_id = std::atoi(argv[i]); break;
default:
std::cout << "Unknown option: " << argv[i-1][1] << std::endl;
exit_and_help();
}
}
Policy p;
switch (branching_policy)
{
case 0: p = Policy::SCIP_DEF; break;
case 1: p = Policy::SCIP_AGG; break;
case 2: p = Policy::ML_DING; break;
case 3: p = Policy::ML_DFS_HEUR_SCORE1_GCN; break;
case 4: p = Policy::ML_DFS_HEUR_SCORE2_GCN; break;
case 5: p = Policy::ML_DFS_HEUR_SCORE1_LR; break;
case 6: p = Policy::ML_DFS_HEUR_SCORE2_LR; break;
case 7: p = Policy::SCIP_HEUR_FEASPUMP; break;
case 8: p = Policy::SCIP_HEUR_RENS; break;
case 9: p = Policy::SCIP_HEUR_ALL_ROUNDING; break;
case 10: p = Policy::SCIP_HEUR_ALL_DIVING; break;
case 11: p = Policy::ML_DFS_EXACT_SCORE1_GCN; break;
case 12: p = Policy::ML_DFS_EXACT_SCORE2_GCN; break;
case 13: p = Policy::ML_DFS_EXACT_SCORE3_GCN; break;
case 14: p = Policy::SCIP_DEF_PBDFS; break;
default: throw std::runtime_error("unknown branching_policy\n");
}
gconf.init(p, param_prob_type, param_cutoff, split_id);
// specify testing & training graphs; optimal solutions for the training graphs must be provided.
std::vector<std::string> test_files;
for (int i = 0; i < 30; i++){
test_files.push_back("eval_large/" + std::to_string(i));
}
for (auto test_file : test_files)
{
gconf.cur_prob = test_file;
Preprocessor preprocessor_ptr;
int nvars;
if (branching_policy == 2 || branching_policy == 3 || branching_policy == 4 ||
branching_policy == 5 || branching_policy == 6 || branching_policy == 11 ||
branching_policy == 12 || branching_policy == 13 || branching_policy == 14)
{
preprocessor_ptr.load_prob_map_gcn(gconf.var_mapper, branching_policy);
// get ml scores for each node
const std::vector<double>& predicted_real_values = preprocessor_ptr.predicted_real_value;
nvars = predicted_real_values.size();
double ml_scores1[nvars];
double ml_scores2[nvars];
for (auto i = 0u; i < nvars; ++i){
ml_scores1[i] = predicted_real_values[i]; // (scoring fn: p)
ml_scores2[i] = predicted_real_values[i]; // (scoring fn: max(p, 1-p))
if (ml_scores2[i] < 0.5) ml_scores2[i] = 1 - ml_scores2[i];
}
gconf.setup(nvars, ml_scores1, ml_scores2, 0);
}else
gconf.setup(0, NULL, NULL, 0);
COML::SCIP_Solver solver;
solver.solve();
double obj = solver.finalize();
gconf.cleanup();
}
return 0;
}
| 4,615 | 32.208633 | 108 | cpp |
PB-DFS | PB-DFS-master/src/nodesel_ml_dfs.cpp | #include <cassert>
#include "nodesel_ml_dfs.hpp"
#include "global_config.hpp"
#include <scip/type_var.h>
#include <scip/struct_var.h>
#include <scip/type_tree.h>
#include <scip/struct_tree.h>
#include <scip/type_lp.h>
/** node selector data */
struct SCIP_NodeselData
{
scip::ObjNodesel* objnodesel; /**< node selector object */
SCIP_Bool deleteobject; /**< should the node selector object be deleted when node selector is freed? */
};
SCIP_DECL_NODESELSELECT(COML::Nodesel_ML_DFS::scip_select)
{
assert(nodesel != NULL);
assert(strcmp(SCIPnodeselGetName(nodesel), scip_name_) == 0);
assert(scip != NULL);
assert(selnode != NULL);
*selnode = SCIPgetBestNode(scip);
return SCIP_OKAY;
};
SCIP_DECL_NODESELCOMP(COML::Nodesel_ML_DFS::scip_comp)
{
int depth1;
int depth2;
assert(nodesel != NULL);
assert(strcmp(SCIPnodeselGetName(nodesel), scip_name_) == 0);
assert(scip != NULL);
depth1 = SCIPnodeGetDepth(node1);
depth2 = SCIPnodeGetDepth(node2);
if( depth1 > depth2 )
return -1;
else if( depth1 < depth2 )
return +1;
else
{
unsigned int node1_bd_type = node1->domchg->domchgbound.boundchgs[0].boundtype;
unsigned int node2_bd_type = node2->domchg->domchgbound.boundchgs[0].boundtype;
if (gconf.policy==Policy::ML_DFS_HEUR_SCORE1_GCN ||
gconf.policy==Policy::ML_DFS_EXACT_SCORE1_GCN ||
gconf.policy==Policy::ML_DFS_HEUR_SCORE1_LR ||
gconf.policy == Policy::SCIP_DEF_PBDFS)
{
if (node1_bd_type == SCIP_BOUNDTYPE_LOWER)
return -1;
else if(node2_bd_type == SCIP_BOUNDTYPE_LOWER)
return +1;
else
return 0;
}
else if (gconf.policy==Policy::ML_DFS_EXACT_SCORE3_GCN)
{
if (node1_bd_type == SCIP_BOUNDTYPE_LOWER)
return +1;
else if(node2_bd_type == SCIP_BOUNDTYPE_LOWER)
return -1;
else
return 0;
}
else if (gconf.policy==Policy::ML_DFS_HEUR_SCORE2_GCN ||
gconf.policy==Policy::ML_DFS_EXACT_SCORE2_GCN ||
gconf.policy==Policy::ML_DFS_HEUR_SCORE2_LR)
{
const char* var_name;
int var_idx;
char var_short_name[10];
int prefix_remove;
if (gconf.policy==Policy::ML_DFS_EXACT_SCORE2_GCN)
prefix_remove = gconf.prefix_size_remove;
else
prefix_remove = gconf.prefix_size_remove + 2;
var_name = SCIPvarGetName(node1->domchg->domchgbound.boundchgs[0].var);
strcpy(var_short_name, var_name + prefix_remove);
var_idx = gconf.var_mapper[var_short_name];
if (gconf.ml_scores1[var_idx] > 0.5)
{
if (node1_bd_type == SCIP_BOUNDTYPE_LOWER)
return -1;
else if(node2_bd_type == SCIP_BOUNDTYPE_LOWER)
return +1;
else
return 0;
}
else
{
if (node1_bd_type == SCIP_BOUNDTYPE_LOWER)
return +1;
else if(node2_bd_type == SCIP_BOUNDTYPE_LOWER)
return -1;
}
}
}
};
/*
* Callback methods of node selector
*/
extern "C"
{
/** copy method for node selector plugins (called when SCIP copies plugins) */
static
SCIP_DECL_NODESELCOPY(nodeselCopyObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
assert(scip != NULL);
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
assert(nodeseldata->objnodesel->scip_ != scip);
if( nodeseldata->objnodesel->iscloneable() )
{
scip::ObjNodesel* newobjnodesel;
newobjnodesel = dynamic_cast<scip::ObjNodesel*> (nodeseldata->objnodesel->clone(scip));
/* call include method of node selector object */
SCIP_CALL( SCIPincludeObjNodesel(scip, newobjnodesel, TRUE) );
}
return SCIP_OKAY;
}
/** destructor of node selector to free user data (called when SCIP is exiting) */
static
SCIP_DECL_NODESELFREE(nodeselFreeObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
assert(nodeseldata->objnodesel->scip_ == scip);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_free(scip, nodesel) );
/* free nodesel object */
if( nodeseldata->deleteobject ){
delete nodeseldata->objnodesel;
nodeseldata->objnodesel = NULL;
}
/* free nodesel data */
delete nodeseldata;
SCIPnodeselSetData(nodesel, NULL); /*lint !e64*/
return SCIP_OKAY;
}
/** initialization method of node selector (called after problem was transformed) */
static
SCIP_DECL_NODESELINIT(nodeselInitObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
assert(nodeseldata->objnodesel->scip_ == scip);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_init(scip, nodesel) );
return SCIP_OKAY;
}
/** deinitialization method of node selector (called before transformed problem is freed) */
static
SCIP_DECL_NODESELEXIT(nodeselExitObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_exit(scip, nodesel) );
return SCIP_OKAY;
}
/** solving process initialization method of node selector (called when branch and bound process is about to begin) */
static
SCIP_DECL_NODESELINITSOL(nodeselInitsolObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_initsol(scip, nodesel) );
return SCIP_OKAY;
}
/** solving process deinitialization method of node selector (called before branch and bound process data is freed) */
static
SCIP_DECL_NODESELEXITSOL(nodeselExitsolObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_exitsol(scip, nodesel) );
return SCIP_OKAY;
}
/** node selection method of node selector */
static
SCIP_DECL_NODESELSELECT(nodeselSelectObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
/* call virtual method of nodesel object */
SCIP_CALL( nodeseldata->objnodesel->scip_select(scip, nodesel, selnode) );
return SCIP_OKAY;
}
/** node comparison method of node selector */
static
SCIP_DECL_NODESELCOMP(nodeselCompObj)
{ /*lint --e{715}*/
SCIP_NODESELDATA* nodeseldata;
nodeseldata = SCIPnodeselGetData(nodesel);
assert(nodeseldata != NULL);
assert(nodeseldata->objnodesel != NULL);
/* call virtual method of nodesel object */
return nodeseldata->objnodesel->scip_comp(scip, nodesel, node1, node2);
}
}
/*
* node selector specific interface methods
*/
/** creates the node selector for the given node selector object and includes it in SCIP */
SCIP_RETCODE SCIPincludeObjNodesel_MLDFS(
SCIP* scip, /**< SCIP data structure */
scip::ObjNodesel* objnodesel, /**< node selector object */
SCIP_Bool deleteobject /**< should the node selector object be deleted when node selector is freed? */
)
{
SCIP_NODESELDATA* nodeseldata;
assert(scip != NULL);
assert(objnodesel != NULL);
/* create node selector data */
nodeseldata = new SCIP_NODESELDATA;
nodeseldata->objnodesel = objnodesel;
nodeseldata->deleteobject = deleteobject;
/* include node selector */
SCIP_CALL( SCIPincludeNodesel(scip, objnodesel->scip_name_, objnodesel->scip_desc_,
objnodesel->scip_stdpriority_, objnodesel->scip_memsavepriority_,
nodeselCopyObj,
nodeselFreeObj, nodeselInitObj, nodeselExitObj,
nodeselInitsolObj, nodeselExitsolObj, nodeselSelectObj, nodeselCompObj,
nodeseldata) ); /*lint !e429*/
return SCIP_OKAY; /*lint !e429*/
}
| 8,658 | 27.483553 | 124 | cpp |
PB-DFS | PB-DFS-master/src/nodesel_ml_dfs.hpp | #ifndef __NODESEL_ML_DFS___
#define __NODESEL_ML_DFS___
#include <scip/scip.h>
#include <objscip/objscip.h>
namespace COML{
class Nodesel_ML_DFS: public scip::ObjNodesel
{
public:
/** default constructor */
Nodesel_ML_DFS(
SCIP* scip, /**< SCIP data structure */
const char* name, /**< name of node selector */
const char* desc, /**< description of node selector */
int stdpriority, /**< priority of the node selector in standard mode */
int memsavepriority /**< priority of the node selector in memory saving mode */
) : ObjNodesel (scip, name, desc, stdpriority, memsavepriority){};
SCIP_DECL_NODESELSELECT(scip_select) override;
SCIP_DECL_NODESELCOMP(scip_comp) override;
};
};
extern
SCIP_RETCODE SCIPincludeObjNodesel_MLDFS(
SCIP* scip, /**< SCIP data structure */
scip::ObjNodesel* objnodesel, /**< node selector object */
SCIP_Bool deleteobject /**< should the node selector object be deleted when node selector is freed? */
);
#endif | 1,180 | 32.742857 | 124 | hpp |
PB-DFS | PB-DFS-master/src/preprocessor.cpp | #include "preprocessor.hpp"
#include "global_config.hpp"
#include <cmath>
#include <limits>
#include <assert.h>
#include <set>
#include <boost/algorithm/string.hpp>
namespace COML {
Preprocessor::Preprocessor() : predicted_real_value() {}
void Preprocessor::load_prob_map_gcn(std::unordered_map<std::string, int>& mapper,
int branching_policy ){
std::ifstream predicted_file("tmp.prob");
if (! predicted_file){
std::cout << "fail to read the predicted file \n" << std::endl;
exit(-1);
}
std::string varname1;
std::string varname2;
double prob;
int idx = 0;
std::vector<std::string> result;
while (predicted_file >> varname1 >> prob){
//edge-based symetric
if (strcmp(gconf.prob_str.c_str(), "tsp") == 0 || strcmp(gconf.prob_str.c_str(), "vrp") == 0){
result.clear();
boost::split(result, varname1, boost::is_any_of("_"));
varname2 = result[1] + "_" + result[0];
mapper[varname1] = idx;
mapper[varname2] = idx;
}else{ //node-based
mapper[varname1] = idx;
}
predicted_real_value.push_back(prob);
gconf.orderednames.push_back(varname1);
idx++;
}
predicted_file.close();
}
}
| 1,431 | 28.833333 | 109 | cpp |
PB-DFS | PB-DFS-master/src/preprocessor.hpp | #ifndef PREPROCESSOR_H
#define PREPROCESSOR_H
#include <random>
#include <algorithm>
#include <iterator>
#include <iostream>
#include <numeric> // std::iota
#include <vector>
#include <cstring>
#include <string>
#include <time.h>
#include <sys/time.h>
#include <iomanip>
#include <unordered_map>
namespace COML {
class Preprocessor
{
public:
std::vector<double> predicted_real_value;
explicit Preprocessor();
void load_prob_map_gcn(std::unordered_map<std::string, int>& mapper,
int branching_policy );
};
}
#endif
| 561 | 17.733333 | 73 | hpp |
PB-DFS | PB-DFS-master/src/scip_exception.hpp | /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/* */
/* This file is part of the examples to */
/* An introduction to SCIP */
/* */
/* Copyright (C) 2007 Cornelius Schwarz */
/* */
/* 2007 University of Bayreuth */
/* */
/* */
/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/**@file scip_exception.hpp
* @brief exception handling for SCIP
* @author Cornelius Schwarz
*/
#ifndef SCIP_EXCEPTION
#define SCIP_EXCEPTION
#include<exception>
#include<string>
#include <scip/scip.h>
#include <scip/misc.h>
// unfortunately SCIP has no method to get the string of an error code, you can just print it to a file
// so we add such a method here, this has to be updated when SCIP Messages changes
// currently supporting SCIP-1.00
#define SCIP_MSG_MAX 100 ///< maximal number of characters in an error messages
/**
* @brief translates a SCIP_RETCODE into an error string
*
* @param[in] retcode SCIP_RETCODE you want to translate
* @param[in] buffersize size of buffer
* @param[out] buffer_str buffer to character array to store translated message, this must be at least of size SCIP_MSG_MAX
* @return buffer_str or NULL, if retcode could not be translated
*/
inline char* SCIPgetErrorString(SCIP_RETCODE retcode, char* buffer_str, int buffersize)
{
// the following was copied from SCIPprintError
switch(retcode)
{
case SCIP_OKAY:
(void) SCIPsnprintf(buffer_str, buffersize, "normal termination");
return buffer_str;
case SCIP_ERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "unspecified error");
return buffer_str;
case SCIP_NOMEMORY:
(void) SCIPsnprintf(buffer_str, buffersize, "insufficient memory error");
return buffer_str;
case SCIP_READERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "file read error");
return buffer_str;
case SCIP_WRITEERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "file write error");
return buffer_str;
case SCIP_BRANCHERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "branch error");
return buffer_str;
case SCIP_NOFILE:
(void) SCIPsnprintf(buffer_str, buffersize, "file not found error");
return buffer_str;
case SCIP_FILECREATEERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "cannot create file");
return buffer_str;
case SCIP_LPERROR:
(void) SCIPsnprintf(buffer_str, buffersize, "error in LP solver");
return buffer_str;
case SCIP_NOPROBLEM:
(void) SCIPsnprintf(buffer_str, buffersize, "no problem exists");
return buffer_str;
case SCIP_INVALIDCALL:
(void) SCIPsnprintf(buffer_str, buffersize, "method cannot be called at this time in solution process");
return buffer_str;
case SCIP_INVALIDDATA:
(void) SCIPsnprintf(buffer_str, buffersize, "method cannot be called with this type of data");
return buffer_str;
case SCIP_INVALIDRESULT:
(void) SCIPsnprintf(buffer_str, buffersize, "method returned an invalid result code");
return buffer_str;
case SCIP_PLUGINNOTFOUND:
(void) SCIPsnprintf(buffer_str, buffersize, "a required plugin was not found");
return buffer_str;
case SCIP_PARAMETERUNKNOWN:
(void) SCIPsnprintf(buffer_str, buffersize, "the parameter with the given name was not found");
return buffer_str;
case SCIP_PARAMETERWRONGTYPE:
(void) SCIPsnprintf(buffer_str, buffersize, "the parameter is not of the expected type");
return buffer_str;
case SCIP_PARAMETERWRONGVAL:
(void) SCIPsnprintf(buffer_str, buffersize, "the value is invalid for the given parameter");
return buffer_str;
case SCIP_KEYALREADYEXISTING:
(void) SCIPsnprintf(buffer_str, buffersize, "the given key is already existing in table");
return buffer_str;
case SCIP_MAXDEPTHLEVEL:
(void) SCIPsnprintf(buffer_str, buffersize, "maximal branching depth level exceeded");
return buffer_str;
}
return NULL;
}
/** @brief exception handling class for SCIP
*
* this class enables you to handle the return code of SCIP functions in a C++ way
*/
class SCIPException : public std::exception
{
private:
char _msg[SCIP_MSG_MAX]; ///< error message
SCIP_RETCODE _retcode; ///< SCIP error code
public:
/** @brief constructs a SCIPEexception from an error code
*
* this constructs a new SCIPException from given error code
* @param[in] retcode SCIP error code
*/
SCIPException(SCIP_RETCODE retcode) : _retcode(retcode)
{
if( SCIPgetErrorString(retcode, _msg, SCIP_MSG_MAX) == NULL )
(void) SCIPsnprintf(_msg, SCIP_MSG_MAX, "unknown SCIP retcode %d",retcode);
}
/** @brief returns the error message
*
* @return error message
*
* this overrides the corresponding method of std::exception in order to allow you to catch all of your exceptions as std::exception
*/
const char * what(void)const throw() {return _msg;}
/** @brief get method for @p _retcode
*
* @return stored SCIP_RETCODE
*/
SCIP_RETCODE getRetcode(void)const{return _retcode;}
/** destructor */
~SCIPException(void) throw(){}
}; /*lint !e1712*/
/** @brief macro to call scip function with exception handling
*
* this macro calls a SCIP function and throws an instance of SCIPException if anything went wrong
*
*/
#define SCIP_CALL_EXC(x) \
{ \
SCIP_RETCODE retcode; \
if( (retcode = (x)) != SCIP_OKAY) \
{ \
throw SCIPException(retcode); \
} \
}
#endif
| 6,106 | 35.568862 | 135 | hpp |
PB-DFS | PB-DFS-master/src/scip_solver.cpp | #include <string>
#include <algorithm>
#include <utility>
#include <iomanip>
#include <iostream>
#include <fstream>
#include <cmath>
#include <stdio.h>
#include <scip/debug.h>
#include <scip/struct_scip.h>
#include <scip/type_scip.h>
#include <scip/type_primal.h>
#include <scip/struct_primal.h>
#include <scip/type_stat.h>
#include <scip/struct_stat.h>
#include <scip/set.h>
#include <scip/struct_sol.h>
#include <scip/struct_misc.h>
#include <scip/type_sol.h>
#include <scip/type_misc.h>
#include <scip/type_retcode.h>
#include <scip/pub_message.h>
#include <boost/algorithm/string.hpp>
#include "scip_solver.hpp"
#include "scip_exception.hpp"
#include "global_config.hpp"
#include "utils.hpp"
#include "branching_policy.hpp"
#include "heur_ml_subscip.hpp"
static SCIP_RETCODE includeSCIPotherPlugins(
SCIP* scip /**< SCIP data structure */
);
static SCIP_RETCODE includeSCIPheuristicsDoRequireFeasibleSol(
SCIP* scip /**< SCIP data structure */
);
static SCIP_RETCODE includeSCIPheuristicsDoNotRequireFeasibleSol(
SCIP* scip /**< SCIP data structure */
);
// for data collection
COML::SCIP_Solver::SCIP_Solver()
: scip(NULL), nodesel_policy(NULL), branching_policy(NULL)
{
std::string prob_name = gconf.DATA_BASE_DIR + gconf.cur_prob + ".lp";
gconf.prob_lp_path = prob_name;
// initialize scip
SCIP_CALL_EXC(SCIPcreate(&scip));
assert(scip!=NULL);
branching_policy = new COML::Branching(
scip, "db", "", 1000000, -1, 1);
COML::SCIPincludeObjBranchrule_DB(scip, branching_policy, false);
includeSCIPotherPlugins(scip);
if (gconf.policy == Policy::ML_DFS_HEUR_SCORE1_GCN ||
gconf.policy == Policy::ML_DFS_HEUR_SCORE2_GCN ||
gconf.policy == Policy::ML_DFS_HEUR_SCORE1_LR ||
gconf.policy == Policy::ML_DFS_HEUR_SCORE2_LR)
{
SCIPincludeHeurMLdfs(scip);
}else if (gconf.policy == Policy::ML_DFS_EXACT_SCORE1_GCN ||
gconf.policy == Policy::ML_DFS_EXACT_SCORE2_GCN ||
gconf.policy == Policy::ML_DFS_EXACT_SCORE3_GCN)
{
nodesel_policy = new COML::Nodesel_ML_DFS(scip, "", "", 66666667, 66666667);
SCIPincludeObjNodesel_MLDFS(scip, nodesel_policy, false);
SCIPsetHeuristics(scip, SCIP_PARAMSETTING_OFF, TRUE);
}
else if (gconf.policy == Policy::SCIP_AGG ||
gconf.policy == Policy::SCIP_DEF)
{
includeSCIPheuristicsDoNotRequireFeasibleSol(scip);
includeSCIPheuristicsDoRequireFeasibleSol(scip);
if (gconf.policy == Policy::SCIP_AGG)
{
SCIPsetHeuristics(scip, SCIP_PARAMSETTING_AGGRESSIVE, TRUE);
}
}
else if (gconf.policy == Policy::SCIP_DEF_PBDFS)
{
includeSCIPheuristicsDoNotRequireFeasibleSol(scip);
includeSCIPheuristicsDoRequireFeasibleSol(scip);
SCIPincludeHeurMLdfs(scip);
}
else
{
if (gconf.policy == Policy::SCIP_HEUR_ALL_DIVING)
{
SCIPincludeHeurCoefdiving(scip);
SCIPincludeHeurDistributiondiving(scip);
SCIPincludeHeurFracdiving(scip);
SCIPincludeHeurIntdiving(scip);
SCIPincludeHeurLinesearchdiving(scip);
SCIPincludeHeurNlpdiving(scip);
SCIPincludeHeurObjpscostdiving(scip);
SCIPincludeHeurPscostdiving(scip);
SCIPincludeHeurRootsoldiving(scip);
SCIPincludeHeurVeclendiving(scip);
SCIPincludeHeurOctane(scip);
SCIPincludeHeurConflictdiving(scip);
SCIPincludeHeurFarkasdiving(scip);
SCIPincludeHeurActconsdiving(scip);
SCIPincludeHeurGuideddiving(scip);
}
else if (gconf.policy == Policy::SCIP_HEUR_ALL_ROUNDING)
{
SCIPincludeHeurIntshifting(scip);
SCIPincludeHeurRounding(scip);
SCIPincludeHeurRandrounding(scip);
SCIPincludeHeurSimplerounding(scip);
SCIPincludeHeurRounding(scip);
SCIPincludeHeurZirounding(scip);
SCIPincludeHeurShiftandpropagate(scip);
SCIPincludeHeurShifting(scip);
}
else if (gconf.policy == Policy::SCIP_HEUR_FEASPUMP)
SCIPincludeHeurFeaspump(scip); // SCIP_HEURTIMING_AFTERLPPLUNGE freq 20
else if (gconf.policy == Policy::SCIP_HEUR_RENS)
SCIPincludeHeurRens(scip); // SCIP_HEURTIMING_AFTERLPNODE freq 0
else if (gconf.policy != Policy::ML_DING)
throw std::runtime_error("unrecognized policy in scip_solver!\n");
}
// disable scip output to stdout
SCIPmessagehdlrSetQuiet(SCIPgetMessagehdlr(scip), TRUE);
scip_set_params();
printf("\nread problem from %s\n", prob_name.c_str());
SCIPreadProb(scip, prob_name.c_str(), NULL);
}
/* destructor */
COML::SCIP_Solver::~SCIP_Solver(void)
{
if (scip != NULL)
{
SCIP_CALL_EXC(SCIPfree(&scip));
scip = NULL;
}
if (branching_policy != NULL)
{
delete branching_policy;
branching_policy = NULL;
}
if (nodesel_policy != NULL)
{
delete nodesel_policy;
nodesel_policy = NULL;
}
}
void COML::SCIP_Solver::scip_set_params()
{
/**
some important scip parameters: -1 means unlimited, 0 means disabled
------------------------------------------------------------------------
*/
// time limit
SCIPsetRealParam(scip, "limits/time", gconf.cutoff);
SCIPsetIntParam(scip, "display/verblevel", 5);
SCIPsetIntParam(scip, "timing/clocktype", 2);
// random seed to break ties
SCIPsetBoolParam(scip, "randomization/permutevars", TRUE);
SCIPsetIntParam(scip, "randomization/permutationseed", gconf.seed);
SCIPsetIntParam(scip, "randomization/randomseedshift", gconf.seed);
SCIPsetIntParam(scip, "presolving/maxrestarts", 0);
if (gconf.cutoff <= 100)
{
SCIPsetIntParam(scip, "separating/maxrounds", 0);
SCIPsetIntParam(scip, "separating/maxroundsroot", 0);
}
// SCIPsetIntParam(scip, "presolving/maxrounds", 0);
}
/* display the solving statistics */
double COML::SCIP_Solver::finalize()
{
printf("nnodes left in finalize: %d\n", SCIPgetNNodesLeft(scip));
double solving_time = std::round(SCIPgetSolvingTime(scip));
long long num_nodes = SCIPgetNNodes(scip);
long long num_internal_nodes = scip->stat->ninternalnodes;
long long num_lps_sb = SCIPgetNStrongbranchLPIterations(scip);
long long num_lps_relax = SCIPgetNNodeLPIterations(scip);
double dual_bound = SCIPgetDualbound(scip);
//|(primalbound - dualbound)/min(|primalbound|,|dualbound|)|
double opt_gap = abs((SCIPgetPrimalbound(scip) - SCIPgetDualbound(scip))/(SCIPgetPrimalbound(scip) + SCIPsetEpsilon(scip->set)));
std::string status;
SCIP_STATUS _status = SCIPgetStatus(scip);
if (_status == SCIP_STATUS_OPTIMAL ||
_status == SCIP_STATUS_INFEASIBLE ||
_status == SCIP_STATUS_UNBOUNDED ||
_status == SCIP_STATUS_INFORUNBD)
status = "solved";
else
status = "unsolved";
double best_sol_obj = -1;
double best_sol_time = -1;
/**
* write primal bound plot
*/
int i;
std::vector<std::string> result;
boost::split(result, gconf.cur_prob, boost::is_any_of("/"));
COML::create_dir(gconf.LOG_DIR + result[0]);
std::string tmp = gconf.LOG_DIR + gconf.cur_prob + ".primal_plot";
std::ofstream fsol_logger(tmp);
fsol_logger << gconf.objs.size() << "\n";
printf("write primal curve to %s\n", tmp.c_str());
for (i = 0; i < gconf.objs.size(); i++)
fsol_logger << gconf.time[i] << " ";
fsol_logger << "\n";
for (i = 0; i < gconf.objs.size(); i++)
fsol_logger << gconf.objs[i] << " ";
fsol_logger.flush();
fsol_logger.close();
/**
* write dual bound plot
*/
tmp = gconf.LOG_DIR + gconf.cur_prob + ".dual_plot";
printf("write dual curve to %s\n", tmp.c_str());
std::ofstream fdual_logger(tmp);
fdual_logger << gconf.dual_bounds.size() << "\n";
for (i = 0; i < gconf.dual_bounds.size(); i++)
fdual_logger << gconf.dual_time[i] << " ";
fdual_logger << "\n";
for (i = 0; i < gconf.dual_bounds.size(); i++)
fdual_logger << gconf.dual_bounds[i] << " ";
fdual_logger.flush();
fdual_logger.close();
/**
* write gap plot
*/
tmp = gconf.LOG_DIR + gconf.cur_prob + ".gap_plot";
printf("write optgap curve to %s\n", tmp.c_str());
std::ofstream gap_logger(tmp);
gap_logger << gconf.gaps.size() << "\n";
for (i = 0; i < gconf.gaps.size(); i++)
gap_logger << gconf.gap_time[i] << " ";
gap_logger << "\n";
for (i = 0; i < gconf.gaps.size(); i++)
gap_logger << gconf.gaps[i] << " ";
gap_logger.flush();
gap_logger.close();
/**
* heuristic stats
*/
tmp = gconf.LOG_DIR + gconf.cur_prob + ".heur_stats";
std::ofstream heur_logger(tmp);
SCIP_HEUR** heuristics = SCIPgetHeurs(scip);
int nheuristics = SCIPgetNHeurs(scip);
SCIP_HEUR* heuristic = NULL;
heur_logger << "name,nbestsol,nsol,ncalls,time\n";
for (i = 0; i < nheuristics; i++)
{
heuristic = heuristics[i];
heur_logger << SCIPheurGetName(heuristic) << ",";
heur_logger << SCIPheurGetNBestSolsFound(heuristic) << ",";
heur_logger << SCIPheurGetNSolsFound(heuristic) << ",";
heur_logger << SCIPheurGetNCalls(heuristic) << ",";
heur_logger << SCIPheurGetTime(heuristic) << "\n";
}
heur_logger.flush();
heur_logger.close();
SCIP_SOL* best_solution = SCIPgetBestSol(scip);
SCIP_HEUR* best_sol_heur = NULL;
std::string best_sol_heur_name;
if (best_solution != NULL)
{
best_sol_obj = SCIPgetSolOrigObj(scip, best_solution);
best_sol_time = SCIPgetSolTime(scip, best_solution);
best_sol_heur = SCIPgetSolHeur(scip, best_solution);
if (best_sol_heur != NULL)
best_sol_heur_name = SCIPheurGetName(best_sol_heur);
else
best_sol_heur_name = "none";
}
double first_sol_time = gconf.time.size() == 0 ? -1 : gconf.time[0];
double first_sol_obj = gconf.objs.size() == 0 ? -1 : gconf.objs[0];
printf("status:%s,opt_gap:%f,best_sol_obj:%f,best_sol_time:%f,best_sol_heur:%s,first_sol_obj:%f,first_sol_time:%f,first_sol_heur:%s,global_dual_bound:%f\n",
status.c_str(), opt_gap, best_sol_obj, best_sol_time, best_sol_heur_name.c_str(), first_sol_obj, first_sol_time, gconf.first_sol_heur.c_str(), dual_bound);
int totalcalls = 0;
double heuristic_total_time = 0.;
for (i = 0; i < nheuristics; i++)
{
heuristic = heuristics[i];
totalcalls += SCIPheurGetNCalls(heuristic);
heuristic_total_time += SCIPheurGetTime(heuristic);
}
int nsols = SCIPgetNSols(scip);
SCIP_SOL** sols = SCIPgetSols(scip);
SCIP_HEUR* h;
double best_heur_sol_time = 0.;
double best_heur_sol_obj = 0.;
double obj;
for (i = 0; i < nsols; i++)
{
h = SCIPsolGetHeur(sols[i]);
obj = SCIPgetSolOrigObj(scip, sols[i]);
if (h!=NULL)
{
if (best_heur_sol_obj==0.)
{
best_heur_sol_obj = obj;
best_heur_sol_time = SCIPsolGetTime(sols[i]);
}
else if (
(gconf.optimization_type == Optimization_Type::Maximization &&
obj > best_heur_sol_obj + SCIPsetEpsilon(scip->set)) ||
(gconf.optimization_type == Optimization_Type::Minimization &&
obj < best_heur_sol_obj - SCIPsetEpsilon(scip->set))
)
{
best_heur_sol_obj = obj;
best_heur_sol_time = SCIPsolGetTime(sols[i]);
}
}
}
// instance_id,status,opt_gap,
// best_sol_obj,best_sol_time,best_sol_heur,
// best_heur_sol_obj,best_heur_sol_time,
// heur_ncalls,heur_tot_time
(*gconf.solving_stats_logger) << gconf.cur_prob << "," << status << "," << opt_gap << ","
<< best_sol_obj << "," << best_sol_time << "," << best_sol_heur_name << ","
<< best_heur_sol_obj << "," << best_heur_sol_time << ","
<< totalcalls << "," << heuristic_total_time << "\n";
(*gconf.solving_stats_logger).flush();
return best_sol_obj;
}
void COML::SCIP_Solver::solve(void)
{
// this tells scip to start the solution process
SCIP_CALL_EXC(SCIPsolve(scip));
}
static SCIP_RETCODE includeSCIPheuristicsDoNotRequireFeasibleSol(
SCIP* scip /**< SCIP data structure */
)
{
// heuristics do not require a feasible solution
SCIP_CALL( SCIPincludeHeurCoefdiving(scip) );
SCIP_CALL( SCIPincludeHeurDistributiondiving(scip) );
SCIP_CALL( SCIPincludeHeurFracdiving(scip) );
SCIP_CALL( SCIPincludeHeurIntdiving(scip) );
SCIP_CALL( SCIPincludeHeurLinesearchdiving(scip) );
SCIP_CALL( SCIPincludeHeurNlpdiving(scip) );
SCIP_CALL( SCIPincludeHeurObjpscostdiving(scip) );
SCIP_CALL( SCIPincludeHeurPscostdiving(scip) );
SCIP_CALL( SCIPincludeHeurRootsoldiving(scip) );
SCIP_CALL( SCIPincludeHeurVeclendiving(scip) );
SCIP_CALL( SCIPincludeHeurOctane(scip) );
SCIP_CALL( SCIPincludeHeurFeaspump(scip) );
SCIP_CALL( SCIPincludeHeurRens(scip) );
SCIP_CALL( SCIPincludeHeurIntshifting(scip) );
SCIP_CALL( SCIPincludeHeurActconsdiving(scip) );
SCIP_CALL( SCIPincludeHeurRandrounding(scip) );
SCIP_CALL( SCIPincludeHeurSimplerounding(scip) );
SCIP_CALL( SCIPincludeHeurRounding(scip) );
SCIP_CALL( SCIPincludeHeurZirounding(scip) );
SCIP_CALL( SCIPincludeHeurShiftandpropagate(scip) );
SCIP_CALL( SCIPincludeHeurShifting(scip) );
SCIP_CALL( SCIPincludeHeurConflictdiving(scip) );
SCIP_CALL( SCIPincludeHeurFarkasdiving(scip) );
}
static SCIP_RETCODE includeSCIPheuristicsDoRequireFeasibleSol(
SCIP* scip /**< SCIP data structure */
)
{
// heuristics do require a feasible solution
SCIP_CALL( SCIPincludeHeurGuideddiving(scip) );
SCIP_CALL( SCIPincludeHeurBound(scip) );
SCIP_CALL( SCIPincludeHeurClique(scip) );
SCIP_CALL( SCIPincludeHeurCompletesol(scip) );
SCIP_CALL( SCIPincludeHeurCrossover(scip) );
SCIP_CALL( SCIPincludeHeurDins(scip) );
SCIP_CALL( SCIPincludeHeurDualval(scip) );
SCIP_CALL( SCIPincludeHeurFixandinfer(scip) );
SCIP_CALL( SCIPincludeHeurGins(scip) );
SCIP_CALL( SCIPincludeHeurZeroobj(scip) );
SCIP_CALL( SCIPincludeHeurIndicator(scip) );
SCIP_CALL( SCIPincludeHeurLocalbranching(scip) );
SCIP_CALL( SCIPincludeHeurLocks(scip) );
SCIP_CALL( SCIPincludeHeurLpface(scip) );
SCIP_CALL( SCIPincludeHeurAlns(scip) );
SCIP_CALL( SCIPincludeHeurMutation(scip) );
SCIP_CALL( SCIPincludeHeurMultistart(scip) );
SCIP_CALL( SCIPincludeHeurMpec(scip) );
SCIP_CALL( SCIPincludeHeurOfins(scip) );
SCIP_CALL( SCIPincludeHeurOneopt(scip) );
SCIP_CALL( SCIPincludeHeurProximity(scip) );
SCIP_CALL( SCIPincludeHeurReoptsols(scip) );
SCIP_CALL( SCIPincludeHeurRepair(scip) );
SCIP_CALL( SCIPincludeHeurRins(scip) );
SCIP_CALL( SCIPincludeHeurSubNlp(scip) );
SCIP_CALL( SCIPincludeHeurTrivial(scip) );
SCIP_CALL( SCIPincludeHeurTrivialnegation(scip) );
SCIP_CALL( SCIPincludeHeurTrySol(scip) );
SCIP_CALL( SCIPincludeHeurTwoopt(scip) );
SCIP_CALL( SCIPincludeHeurUndercover(scip) );
SCIP_CALL( SCIPincludeHeurVbounds(scip) );
}
static SCIP_RETCODE includeSCIPotherPlugins(
SCIP* scip /**< SCIP data structure */
)
{
SCIP_CALL( SCIPincludeConshdlrNonlinear(scip) ); /* nonlinear must be before linear, quadratic, abspower, and and due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrQuadratic(scip) ); /* quadratic must be before linear due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrLinear(scip) ); /* linear must be before its specializations due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrAbspower(scip) ); /* absolute power needs to be after quadratic and nonlinear due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrAnd(scip) );
SCIP_CALL( SCIPincludeConshdlrBenders(scip) );
SCIP_CALL( SCIPincludeConshdlrBenderslp(scip) );
SCIP_CALL( SCIPincludeConshdlrBivariate(scip) ); /* bivariate needs to be after quadratic and nonlinear due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrBounddisjunction(scip) );
SCIP_CALL( SCIPincludeConshdlrCardinality(scip) );
SCIP_CALL( SCIPincludeConshdlrConjunction(scip) );
SCIP_CALL( SCIPincludeConshdlrCountsols(scip) );
SCIP_CALL( SCIPincludeConshdlrCumulative(scip) );
SCIP_CALL( SCIPincludeConshdlrDisjunction(scip) );
SCIP_CALL( SCIPincludeConshdlrIndicator(scip) );
SCIP_CALL( SCIPincludeConshdlrIntegral(scip) );
SCIP_CALL( SCIPincludeConshdlrKnapsack(scip) );
SCIP_CALL( SCIPincludeConshdlrLinking(scip) );
SCIP_CALL( SCIPincludeConshdlrLogicor(scip) );
SCIP_CALL( SCIPincludeConshdlrOr(scip) );
SCIP_CALL( SCIPincludeConshdlrOrbisack(scip) );
SCIP_CALL( SCIPincludeConshdlrOrbitope(scip) );
SCIP_CALL( SCIPincludeConshdlrPseudoboolean(scip) );
SCIP_CALL( SCIPincludeConshdlrSetppc(scip) );
SCIP_CALL( SCIPincludeConshdlrSOC(scip) ); /* SOC needs to be after quadratic due to constraint upgrading */
SCIP_CALL( SCIPincludeConshdlrSOS1(scip) );
SCIP_CALL( SCIPincludeConshdlrSOS2(scip) );
SCIP_CALL( SCIPincludeConshdlrSuperindicator(scip) );
SCIP_CALL( SCIPincludeConshdlrSymresack(scip) );
SCIP_CALL( SCIPincludeConshdlrVarbound(scip) );
SCIP_CALL( SCIPincludeConshdlrXor(scip) );
SCIP_CALL( SCIPincludeConshdlrComponents(scip) );
SCIP_CALL( SCIPincludeReaderBnd(scip) );
SCIP_CALL( SCIPincludeReaderCcg(scip) );
SCIP_CALL( SCIPincludeReaderCip(scip) );
SCIP_CALL( SCIPincludeReaderCnf(scip) );
SCIP_CALL( SCIPincludeReaderCor(scip) );
SCIP_CALL( SCIPincludeReaderDiff(scip) );
SCIP_CALL( SCIPincludeReaderFix(scip) );
SCIP_CALL( SCIPincludeReaderFzn(scip) );
SCIP_CALL( SCIPincludeReaderGms(scip) );
SCIP_CALL( SCIPincludeReaderLp(scip) );
SCIP_CALL( SCIPincludeReaderMps(scip) );
SCIP_CALL( SCIPincludeReaderMst(scip) );
SCIP_CALL( SCIPincludeReaderOpb(scip) );
SCIP_CALL( SCIPincludeReaderOsil(scip) );
SCIP_CALL( SCIPincludeReaderPip(scip) );
SCIP_CALL( SCIPincludeReaderPpm(scip) );
SCIP_CALL( SCIPincludeReaderPbm(scip) );
SCIP_CALL( SCIPincludeReaderRlp(scip) );
SCIP_CALL( SCIPincludeReaderSmps(scip) );
SCIP_CALL( SCIPincludeReaderSol(scip) );
SCIP_CALL( SCIPincludeReaderSto(scip) );
SCIP_CALL( SCIPincludeReaderTim(scip) );
SCIP_CALL( SCIPincludeReaderWbo(scip) );
SCIP_CALL( SCIPincludeReaderZpl(scip) );
SCIP_CALL( SCIPincludePresolBoundshift(scip) );
SCIP_CALL( SCIPincludePresolConvertinttobin(scip) );
SCIP_CALL( SCIPincludePresolDomcol(scip) );
SCIP_CALL( SCIPincludePresolDualagg(scip) );
SCIP_CALL( SCIPincludePresolDualcomp(scip) );
SCIP_CALL( SCIPincludePresolDualinfer(scip) );
SCIP_CALL( SCIPincludePresolGateextraction(scip) );
SCIP_CALL( SCIPincludePresolImplics(scip) );
SCIP_CALL( SCIPincludePresolInttobinary(scip) );
SCIP_CALL( SCIPincludePresolQPKKTref(scip) );
SCIP_CALL( SCIPincludePresolRedvub(scip) );
SCIP_CALL( SCIPincludePresolTrivial(scip) );
SCIP_CALL( SCIPincludePresolTworowbnd(scip) );
SCIP_CALL( SCIPincludePresolSparsify(scip) );
SCIP_CALL( SCIPincludePresolStuffing(scip) );
// SCIP_CALL( SCIPincludePresolSymmetry(scip) );
// SCIP_CALL( SCIPincludePresolSymbreak(scip) ); /* needs to be included after presol_symmetry */
SCIP_CALL( SCIPincludeNodeselBfs(scip) );
SCIP_CALL( SCIPincludeNodeselBreadthfirst(scip) );
SCIP_CALL( SCIPincludeNodeselDfs(scip) );
SCIP_CALL( SCIPincludeNodeselEstimate(scip) );
SCIP_CALL( SCIPincludeNodeselHybridestim(scip) );
SCIP_CALL( SCIPincludeNodeselRestartdfs(scip) );
SCIP_CALL( SCIPincludeNodeselUct(scip) );
SCIP_CALL( SCIPincludeBranchruleAllfullstrong(scip) );
SCIP_CALL( SCIPincludeBranchruleCloud(scip) );
SCIP_CALL( SCIPincludeBranchruleDistribution(scip) );
SCIP_CALL( SCIPincludeBranchruleFullstrong(scip) );
SCIP_CALL( SCIPincludeBranchruleInference(scip) );
SCIP_CALL( SCIPincludeBranchruleLeastinf(scip) );
SCIP_CALL( SCIPincludeBranchruleLookahead(scip) );
SCIP_CALL( SCIPincludeBranchruleMostinf(scip) );
SCIP_CALL( SCIPincludeBranchruleMultAggr(scip) );
SCIP_CALL( SCIPincludeBranchruleNodereopt(scip) );
SCIP_CALL( SCIPincludeBranchrulePscost(scip) );
SCIP_CALL( SCIPincludeBranchruleRandom(scip) );
SCIP_CALL( SCIPincludeBranchruleRelpscost(scip) );
SCIP_CALL( SCIPincludeEventHdlrSolvingphase(scip) );
SCIP_CALL( SCIPincludeComprLargestrepr(scip) );
SCIP_CALL( SCIPincludeComprWeakcompr(scip) );
SCIP_CALL( SCIPincludePropDualfix(scip) );
SCIP_CALL( SCIPincludePropGenvbounds(scip) );
SCIP_CALL( SCIPincludePropObbt(scip) );
// SCIP_CALL( SCIPincludePropOrbitalfixing(scip) );
SCIP_CALL( SCIPincludePropNlobbt(scip) );
SCIP_CALL( SCIPincludePropProbing(scip) );
SCIP_CALL( SCIPincludePropPseudoobj(scip) );
SCIP_CALL( SCIPincludePropRedcost(scip) );
SCIP_CALL( SCIPincludePropRootredcost(scip) );
SCIP_CALL( SCIPincludePropVbounds(scip) );
SCIP_CALL( SCIPincludeSepaCGMIP(scip) );
SCIP_CALL( SCIPincludeSepaClique(scip) );
SCIP_CALL( SCIPincludeSepaClosecuts(scip) );
SCIP_CALL( SCIPincludeSepaAggregation(scip) );
SCIP_CALL( SCIPincludeSepaConvexproj(scip) );
SCIP_CALL( SCIPincludeSepaDisjunctive(scip) );
SCIP_CALL( SCIPincludeSepaEccuts(scip) );
SCIP_CALL( SCIPincludeSepaGauge(scip) );
SCIP_CALL( SCIPincludeSepaGomory(scip) );
SCIP_CALL( SCIPincludeSepaImpliedbounds(scip) );
SCIP_CALL( SCIPincludeSepaIntobj(scip) );
SCIP_CALL( SCIPincludeSepaMcf(scip) );
SCIP_CALL( SCIPincludeSepaOddcycle(scip) );
SCIP_CALL( SCIPincludeSepaRapidlearning(scip) );
SCIP_CALL( SCIPincludeSepaStrongcg(scip) );
SCIP_CALL( SCIPincludeSepaZerohalf(scip) );
SCIP_CALL( SCIPincludeDispDefault(scip) );
SCIP_CALL( SCIPincludeTableDefault(scip) );
// SCIP_CALL( SCIPincludeEventHdlrSofttimelimit(scip) );
SCIP_CALL( SCIPincludeConcurrentScipSolvers(scip) );
SCIP_CALL( SCIPincludeBendersDefault(scip) );
} | 22,195 | 37.601739 | 167 | cpp |
PB-DFS | PB-DFS-master/src/scip_solver.hpp | #ifndef SOLVER
#define SOLVER
#include <vector>
#include <iostream>
#include <scip/scip.h>
#include <vector>
#include "fstream"
// headers of various plugins
#include "scip/branch_allfullstrong.h"
#include "scip/branch_cloud.h"
#include "scip/branch_distribution.h"
#include "scip/branch_fullstrong.h"
#include "scip/branch_inference.h"
#include "scip/branch_leastinf.h"
#include "scip/branch_lookahead.h"
#include "scip/branch_mostinf.h"
#include "scip/branch_multaggr.h"
#include "scip/branch_nodereopt.h"
#include "scip/branch_pscost.h"
#include "scip/branch_random.h"
#include "scip/branch_relpscost.h"
#include "scip/compr_largestrepr.h"
#include "scip/compr_weakcompr.h"
#include "scip/cons_abspower.h"
#include "scip/cons_and.h"
#include "scip/cons_benders.h"
#include "scip/cons_benderslp.h"
#include "scip/cons_bivariate.h"
#include "scip/cons_bounddisjunction.h"
#include "scip/cons_cardinality.h"
#include "scip/cons_conjunction.h"
#include "scip/cons_countsols.h"
#include "scip/cons_cumulative.h"
#include "scip/cons_disjunction.h"
#include "scip/cons_indicator.h"
#include "scip/cons_integral.h"
#include "scip/cons_knapsack.h"
#include "scip/cons_linear.h"
#include "scip/cons_linking.h"
#include "scip/cons_logicor.h"
#include "scip/cons_nonlinear.h"
#include "scip/cons_or.h"
#include "scip/cons_orbisack.h"
#include "scip/cons_orbitope.h"
#include "scip/cons_pseudoboolean.h"
#include "scip/cons_quadratic.h"
#include "scip/cons_setppc.h"
#include "scip/cons_soc.h"
#include "scip/cons_sos1.h"
#include "scip/cons_sos2.h"
#include "scip/cons_superindicator.h"
#include "scip/cons_symresack.h"
#include "scip/cons_varbound.h"
#include "scip/cons_xor.h"
#include "scip/cons_components.h"
#include "scip/disp_default.h"
#include "scip/event_solvingphase.h"
#include "scip/event_softtimelimit.h"
#include "scip/heur_actconsdiving.h"
#include "scip/heur_bound.h"
#include "scip/heur_clique.h"
#include "scip/heur_coefdiving.h"
#include "scip/heur_completesol.h"
#include "scip/heur_conflictdiving.h"
#include "scip/heur_crossover.h"
#include "scip/heur_dins.h"
#include "scip/heur_distributiondiving.h"
#include "scip/heur_dualval.h"
#include "scip/heur_farkasdiving.h"
#include "scip/heur_feaspump.h"
#include "scip/heur_fixandinfer.h"
#include "scip/heur_fracdiving.h"
#include "scip/heur_gins.h"
#include "scip/heur_guideddiving.h"
#include "scip/heur_indicator.h"
#include "scip/heur_intdiving.h"
#include "scip/heur_intshifting.h"
#include "scip/heur_linesearchdiving.h"
#include "scip/heur_localbranching.h"
#include "scip/heur_locks.h"
#include "scip/heur_lpface.h"
#include "scip/heur_alns.h"
#include "scip/heur_multistart.h"
#include "scip/heur_mutation.h"
#include "scip/heur_mpec.h"
#include "scip/heur_nlpdiving.h"
#include "scip/heur_objpscostdiving.h"
#include "scip/heur_octane.h"
#include "scip/heur_ofins.h"
#include "scip/heur_oneopt.h"
#include "scip/heur_pscostdiving.h"
#include "scip/heur_proximity.h"
#include "scip/heur_randrounding.h"
#include "scip/heur_rens.h"
#include "scip/heur_reoptsols.h"
#include "scip/heur_repair.h"
#include "scip/heur_rins.h"
#include "scip/heur_rootsoldiving.h"
#include "scip/heur_rounding.h"
#include "scip/heur_shiftandpropagate.h"
#include "scip/heur_shifting.h"
#include "scip/heur_simplerounding.h"
#include "scip/heur_subnlp.h"
#include "scip/heur_trivial.h"
#include "scip/heur_trivialnegation.h"
#include "scip/heur_trysol.h"
#include "scip/heur_twoopt.h"
#include "scip/heur_undercover.h"
#include "scip/heur_vbounds.h"
#include "scip/heur_veclendiving.h"
#include "scip/heur_zeroobj.h"
#include "scip/heur_zirounding.h"
#include "scip/nodesel_bfs.h"
#include "scip/nodesel_breadthfirst.h"
#include "scip/nodesel_dfs.h"
#include "scip/nodesel_estimate.h"
#include "scip/nodesel_hybridestim.h"
#include "scip/nodesel_uct.h"
#include "scip/nodesel_restartdfs.h"
#include "scip/presol_boundshift.h"
#include "scip/presol_convertinttobin.h"
#include "scip/presol_domcol.h"
#include "scip/presol_dualagg.h"
#include "scip/presol_dualcomp.h"
#include "scip/presol_dualinfer.h"
#include "scip/presol_gateextraction.h"
#include "scip/presol_implics.h"
#include "scip/presol_inttobinary.h"
#include "scip/presol_redvub.h"
#include "scip/presol_qpkktref.h"
#include "scip/presol_trivial.h"
#include "scip/presol_tworowbnd.h"
#include "scip/presol_sparsify.h"
#include "scip/presol_stuffing.h"
#include "scip/prop_dualfix.h"
#include "scip/prop_genvbounds.h"
#include "scip/prop_nlobbt.h"
#include "scip/prop_obbt.h"
#include "scip/prop_probing.h"
#include "scip/prop_pseudoobj.h"
#include "scip/prop_redcost.h"
#include "scip/prop_rootredcost.h"
#include "scip/prop_vbounds.h"
#include "scip/reader_bnd.h"
#include "scip/reader_ccg.h"
#include "scip/reader_cip.h"
#include "scip/reader_cnf.h"
#include "scip/reader_cor.h"
#include "scip/reader_diff.h"
#include "scip/reader_fix.h"
#include "scip/reader_fzn.h"
#include "scip/reader_gms.h"
#include "scip/reader_lp.h"
#include "scip/reader_mps.h"
#include "scip/reader_mst.h"
#include "scip/reader_opb.h"
#include "scip/reader_osil.h"
#include "scip/reader_pip.h"
#include "scip/reader_ppm.h"
#include "scip/reader_pbm.h"
#include "scip/reader_rlp.h"
#include "scip/reader_smps.h"
#include "scip/reader_sol.h"
#include "scip/reader_sto.h"
#include "scip/reader_tim.h"
#include "scip/reader_wbo.h"
#include "scip/reader_zpl.h"
#include "scip/sepa_eccuts.h"
#include "scip/sepa_cgmip.h"
#include "scip/sepa_clique.h"
#include "scip/sepa_closecuts.h"
#include "scip/sepa_aggregation.h"
#include "scip/sepa_convexproj.h"
#include "scip/sepa_disjunctive.h"
#include "scip/sepa_gauge.h"
#include "scip/sepa_gomory.h"
#include "scip/sepa_impliedbounds.h"
#include "scip/sepa_intobj.h"
#include "scip/sepa_mcf.h"
#include "scip/sepa_oddcycle.h"
#include "scip/sepa_rapidlearning.h"
#include "scip/sepa_strongcg.h"
#include "scip/sepa_zerohalf.h"
#include "scip/scipshell.h"
#include "scip/table_default.h"
#include "scip/concsolver_scip.h"
#include "scip/benders_default.h"
#include <objscip/objscip.h>
#include "nodesel_ml_dfs.hpp"
namespace COML{
class SCIP_Solver
{
private:
scip::ObjBranchrule* branching_policy;
SCIP* scip;
COML::Nodesel_ML_DFS* nodesel_policy;
void scip_set_params();
public:
SCIP_Solver();
~SCIP_Solver();
void solve();
double finalize();
};
}
#endif
| 6,362 | 28.733645 | 44 | hpp |
PB-DFS | PB-DFS-master/src/stats.cpp | #include "preprocessor.hpp"
#include <iostream>
#include <time.h>
#include <sys/time.h>
#include "global_config.hpp"
#include "scip_solver.hpp"
#include "scip/scip.h"
#include "scip/scipdefplugins.h"
void solve(std::string path)
{
}
int main0(int argc, char* argv[]) {
using namespace COML;
const char * _homedir;
if ((_homedir = getenv("HOME")) == NULL)
_homedir = getpwuid(getuid())->pw_dir;
std::string home_dir = _homedir;
std::string prob = "ca";
std::string data_dir = home_dir + "/storage1/instances/" + prob + "/";
std::string lp_path;
double nnzs;
int nvars;
int ncons;
double frac;
int nvars_max;
int nvars_min;
int ncons_max;
int ncons_min;
double frac_max;
double frac_min;
// mis problem
nvars_max = -1;
nvars_min = 1000000000;
ncons_max = -1;
ncons_min = 1000000000;
frac_max = 0;
frac_min = 1;
SCIP* scip;
for (int i = 0; i < 30; i++){
// lp_path = data_dir + "test_2000/" + std::to_string(i) + ".lp";
lp_path = data_dir + "eval_300-1500/" + std::to_string(i) + ".lp";
SCIPcreate(&scip);
assert(scip!=NULL);
SCIPincludeDefaultPlugins(scip);
printf("%s\n", lp_path.c_str());
SCIPreadProb(scip, lp_path.c_str(), NULL);
SCIPsetIntParam(scip, "presolving/maxrestarts", 0);
SCIPsetIntParam(scip, "separating/maxrounds", 0);
SCIPsetIntParam(scip, "separating/maxroundsroot", 0);
SCIPmessagehdlrSetQuiet(SCIPgetMessagehdlr(scip), TRUE);
SCIPtransformProb(scip);
// SCIPsolve(scip);
nvars = SCIPgetNOrigBinVars(scip);
ncons = SCIPgetNOrigConss(scip);
nnzs = SCIPgetNNZs(scip);
frac = nnzs / nvars / ncons;
SCIPfree(&scip);
if (nvars > nvars_max)
nvars_max = nvars;
if (nvars < nvars_min)
nvars_min = nvars;
if (ncons > ncons_max)
ncons_max = ncons;
if (ncons < ncons_min)
ncons_min = ncons;
if (frac > frac_max)
frac_max = frac;
if (frac < frac_min)
frac_min = frac;
}
printf("mis large: %d-%d %d-%d %f-%f\n", nvars_min, nvars_max, ncons_min, ncons_max, frac_min, frac_max);
// specify testing & training graphs; optimal solutions for the training graphs must be provided.
// std::vector<std::string> train_files; std::vector<std::string> test_files;
// switch (gconf.prob)
// {
// case 0: //MIS problem
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_3000/" + std::to_string(i));
// }
// break;
// case 1: // Setcover problem
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_2250_1750/" + std::to_string(i));
// }
// break;
// case 2: // TSP
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_150/" + std::to_string(i));
// }
// break;
// case 3: // vrp
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_50/" + std::to_string(i));
// }
// break;
// case 4: // vc
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_3000/" + std::to_string(i));
// }
// break;
// case 5: // dominate set
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_3000/" + std::to_string(i));
// }
// break;
// case 6: // ca
// for (int i = 0; i < 30; i++){
// test_files.push_back("eval_300-1500/" + std::to_string(i));
// }
// break;
// default: throw std::runtime_error("unknown problem\n");
// }
return 0;
}
| 3,797 | 27.556391 | 109 | cpp |
PB-DFS | PB-DFS-master/src/utils.cpp | #include "utils.hpp"
#include <stdio.h>
#include <string>
#include <sys/stat.h>
#include <dirent.h>
#include <stdlib.h>
#include <random>
#include "global_config.hpp"
#include <limits>
#include <unordered_set>
#include <sstream>
// Get current date/time, format is YYYY-MM-DD.HH:mm:ss
const std::string COML::currentDateTime() {
time_t now = time(0);
struct tm tstruct;
char buf[80];
tstruct = *localtime(&now);
strftime(buf, sizeof(buf), "%Y-%m-%d-%H-%M", &tstruct);
return buf;
}
int COML::list_filenames_under_dir(std::string dir_name, std::vector<int> *vec)
{
int max = -1;
if (auto dir = opendir(dir_name.c_str()))
{
while (auto f = readdir(dir))
{
if (f->d_name[0] == '.')
continue; // Skip everything that starts with a dot
int data_idx = std::stoi(f->d_name);
if (vec != NULL)
vec->push_back(data_idx);
if (max < data_idx)
max = data_idx;
}
closedir(dir);
return max;
}
else
{
printf("in utils.list_filenames_under_dir(), open dir %s failed\n", dir_name.c_str());
exit(EXIT_FAILURE);
}
}
void COML::create_dir(std::string path)
{
struct stat sb;
if (!(stat(path.c_str(), &sb) == 0 && S_ISDIR(sb.st_mode)))
mkdir(path.c_str(), S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
}
int COML::calc_argmax(const std::vector<double> &v)
{
double max_score = -std::numeric_limits<double>::infinity();
int arg_max = 0;
int vec_size = v.size();
//set true label index
double tmp_score;
for (int i = 0; i < vec_size; i++)
{
tmp_score = v.at(i);
if (max_score < tmp_score)
{
max_score = tmp_score;
arg_max = i;
}
}
return arg_max;
}
void COML::all_zeros(double *arr, int size)
{
for (int i = 0; i < size; i++)
{
arr[i] = 0;
}
}
void COML::all_zeros(int *arr, int size)
{
for (int i = 0; i < size; i++)
{
arr[i] = 0;
}
}
double *COML::calc_top10(const double *arr, const int arr_size)
{
std::vector<double> sb_scores_cp;
double *_top10 = new double[10];
sb_scores_cp.assign(arr, arr + arr_size);
std::sort(sb_scores_cp.begin(), sb_scores_cp.end(), std::greater<double>());
sb_scores_cp.resize(10);
for (int i = 0; i < 10; i++)
{
_top10[i] = sb_scores_cp[i];
}
return _top10;
}
double *COML::calc_top1_5_10_30(const double *arr, const int arr_size)
{
#ifdef DEBUG
printf("start calc_top1_5_10_30\n");
fflush(stdout);
#endif
std::vector<double> sb_scores_vec(arr, arr + arr_size);
double *_top_1_5_10_30 = new double[4];
#ifdef DEBUG
printf("after assign arr\n");
fflush(stdout);
#endif
std::sort(sb_scores_vec.begin(), sb_scores_vec.end(), std::greater<double>());
#ifdef DEBUG
printf("after sorting\n");
fflush(stdout);
#endif
_top_1_5_10_30[0] = sb_scores_vec[0];
#ifdef DEBUG
printf("after first assignment\n");
fflush(stdout);
#endif
if (arr_size >= 5)
_top_1_5_10_30[1] = sb_scores_vec[4];
else
_top_1_5_10_30[1] = sb_scores_vec[arr_size - 1];
#ifdef DEBUG
printf("after second assignment\n");
fflush(stdout);
#endif
if (arr_size >= 10)
_top_1_5_10_30[2] = sb_scores_vec[9];
else
_top_1_5_10_30[2] = sb_scores_vec[arr_size - 1];
#ifdef DEBUG
printf("after third assignment\n");
fflush(stdout);
#endif
if (arr_size >= 30)
_top_1_5_10_30[3] = sb_scores_vec[29];
else
_top_1_5_10_30[3] = sb_scores_vec[arr_size - 1];
#ifdef DEBUG
printf("done calc_top1_5_10_30\n");
fflush(stdout);
#endif
return _top_1_5_10_30;
}
int COML::calc_argmax(const double *arr, const int size)
{
double max_score = -std::numeric_limits<double>::infinity();
int arg_max = 0;
for (int i = 0; i < size; i++)
{
if (max_score < arr[i])
{
max_score = arr[i];
arg_max = i;
}
}
return arg_max;
}
int COML::calc_argmin(const double *arr, const int size)
{
double min_score = std::numeric_limits<double>::infinity();
int arg_min = 0;
for (int i = 0; i < size; i++)
{
if (min_score > arr[i])
{
min_score = arr[i];
arg_min = i;
}
}
return arg_min;
}
double COML::calc_max(const double *arr, const int arr_size)
{
double maxval = -std::numeric_limits<double>::infinity();
for (int i = 0; i < arr_size; i++)
{
if (arr[i] > maxval)
{
maxval = arr[i];
}
}
return maxval;
}
double COML::calc_min(const double *arr, const int arr_size)
{
double minval = std::numeric_limits<double>::infinity();
for (int i = 0; i < arr_size; i++)
{
if (arr[i] < minval)
{
minval = arr[i];
}
}
return minval;
}
double COML::calc_mean(const double *arr, const int arr_size)
{
double tot = 0.;
int i;
for (i = 0; i < arr_size; i++)
{
if (arr[i] == -100000000000000000000.)
break;
tot += arr[i];
}
return tot / (i);
}
double COML::calc_stdev(const double *arr, const int arr_size)
{
double mean = COML::calc_mean(arr, arr_size);
double variance = 0.;
int i;
for (i = 0; i < arr_size; i++)
{
if (arr[i] == -100000000000000000000.)
break;
variance += (arr[i] - mean) * (arr[i] - mean);
}
variance /= (i);
return std::sqrt(variance);
}
double COML::calc_zscore(const double val, const double mean, const double stddev)
{
double tmp = (val - mean) / stddev;
return tmp;
}
void COML::min_max_norm(double *arr, int arr_size)
{
double min = COML::calc_min(arr, arr_size);
double max = COML::calc_max(arr, arr_size);
double delta = max - min;
for (int i = 0; i < arr_size; i++)
{
arr[i] = (delta == 0) ? 0 : (arr[i] - min) / delta;
if (arr[i] < -1 || arr[i] > 1)
{
printf("%f\n", arr[i]);
}
}
}
void COML::arraycopy(double *src, double *dest, int num_elements)
{
for (int i = 0; i < num_elements; i++)
{
dest[i] = src[i];
}
}
int COML::read_problems(std::string prefix, std::string filename,
std::vector<std::string> &problems, std::vector<double> &objs)
{
// read problems from file
int num_problems = 0;
std::ifstream infile(filename);
if (infile.is_open())
{
std::string prob_name;
std::string objval;
while (getline(infile, prob_name))
{
if (!prob_name.empty() && prob_name[prob_name.length() - 1] == '\n')
prob_name.erase(prob_name.length() - 1);
getline(infile, objval);
if (!objval.empty() && objval[objval.length() - 1] == '\n')
objval.erase(objval.length() - 1);
problems.push_back(prefix + prob_name);
objs.push_back(std::stod(objval));
num_problems++;
}
infile.close();
}
else
{
printf("cannot find problem file: %s\n", filename.c_str());
assert(false);
}
printf("number of problems to solve: %d\n\n", num_problems);
return num_problems;
}
bool comparator_acending(const COML::mypair &l, const COML::mypair &r)
{
return l.second < r.second;
}
bool COML::comparator_decending(const mypair &l, const mypair &r)
{
return l.second > r.second;
}
void COML::argsort(const double *scores, int *sortedargs, int size)
{
std::vector<mypair> score_index;
for (int i = 0; i < size; i++)
{
mypair p;
p.first = i;
p.second = scores[i];
score_index.push_back(p);
}
std::sort(score_index.begin(), score_index.end(), comparator_decending);
for (int i = 0; i < size; i++)
{
sortedargs[i] = score_index[i].first;
}
}
bool COML::is_file_exist(const char *fileName)
{
std::ifstream infile(fileName);
return infile.good();
}
| 8,134 | 21.787115 | 94 | cpp |
PB-DFS | PB-DFS-master/src/utils.hpp |
#ifndef _MIPEXP_UTILS
#define _MIPEXP_UTILS
#include <vector>
#include <limits>
#include <cmath>
#include <algorithm>
#include <map>
#include <scip/scip.h>
#include <string>
#include <algorithm>
#include <cassert>
#include <fstream>
#include "global_config.hpp"
#include <time.h>
namespace COML
{
const std::string currentDateTime();
typedef std::pair<int,double> mypair;
bool comparator_decending ( const mypair& l, const mypair& r);
int list_filenames_under_dir(std::string dir_name, std::vector<int>* vec);
void create_dir(std::string path);
int read_problems(std::string prefix, std::string filename,
std::vector<std::string>& problems, std::vector<double> &objs);
int calc_argmax(const double* arr, const int size );
int calc_argmax(const std::vector<double>& v );
int calc_argmin(const double* arr, const int size );
double* calc_top10(const double* arr, const int arr_size);
double* calc_top1_5_10_30(const double* arr, const int arr_size);
double calc_max(const double* arr, const int arr_size);
double calc_min(const double* arr, const int arr_size);
double calc_mean(const double* arr, const int arr_size);
double calc_stdev(const double* arr, const int arr_size);
double calc_zscore(const double val, const double mean, const double stddev);
void min_max_norm(double * arr, const int arr_size);
void arraycopy(double* src, double* dest, int num_elements);
void argsort(const double* scores, int* sortedargs, int size);
void all_zeros(int* arr, int size);
void all_zeros(double* arr, int size);
bool is_file_exist(const char *fileName);
}
#endif | 1,674 | 34.638298 | 83 | hpp |
umap | umap-master/.pep8speaks.yml | pycodestyle: # Same as scanner.linter value. Other option is flake8
max-line-length: 88 # Default is 79 in PEP 8
| 119 | 39 | 68 | yml |
umap | umap-master/.travis.yml | language: python
cache:
apt: true
# We use three different cache directory
# to work around a Travis bug with multi-platform cache
directories:
- $HOME/.cache/pip
- $HOME/download
env:
global:
# Directory where tests are run from
- TEST_DIR=/tmp/test_dir/
- MODULE=umap
matrix:
include:
- python: 3.6
os: linux
- env: DISTRIB="conda" PYTHON_VERSION="3.7" NUMPY_VERSION="1.17" SCIPY_VERSION="1.3.1"
os: linux
- env: DISTRIB="conda" PYTHON_VERSION="3.8" NUMPY_VERSION="1.20.0" SCIPY_VERSION="1.6.0"
os: linux
- env: DISTRIB="conda" PYTHON_VERSION="3.8" COVERAGE="true" NUMPY_VERSION="1.20.0" SCIPY_VERSION="1.6.0"
os: linux
# - env: DISTRIB="conda" PYTHON_VERSION="3.7" NUMBA_VERSION="0.51.2"
# os: osx
# language: generic
# - env: DISTRIB="conda" PYTHON_VERSION="3.8" NUMBA_VERSION="0.51.2"
# os: osx
# language: generic
install: source ci_scripts/install.sh
script: travis_wait 90 bash ci_scripts/test.sh
after_success: source ci_scripts/success.sh
| 1,046 | 28.083333 | 108 | yml |
umap | umap-master/CODE_OF_CONDUCT.md | # Contributor Covenant Code of Conduct
## Our Pledge
In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
## Our Standards
Examples of behavior that contributes to creating a positive environment include:
* Using welcoming and inclusive language
* Being respectful of differing viewpoints and experiences
* Gracefully accepting constructive criticism
* Focusing on what is best for the community
* Showing empathy towards other community members
Examples of unacceptable behavior by participants include:
* The use of sexualized language or imagery and unwelcome sexual attention or advances
* Trolling, insulting/derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or electronic address, without explicit permission
* Other conduct which could reasonably be considered inappropriate in a professional setting
## Our Responsibilities
Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.
## Scope
This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at leland.mcinnes@gmail.com. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version]
[homepage]: http://contributor-covenant.org
[version]: http://contributor-covenant.org/version/1/4/
| 3,221 | 67.553191 | 455 | md |
umap | umap-master/CONTRIBUTING.md | # Contributing
Contributions of all kinds are welcome. In particular pull requests are appreciated.
The authors will endeavour to help walk you through any issues in the pull request
discussion, so please feel free to open a pull request even if you are new to such things.
## Issues
The easiest contribution to make is to [file an issue](https://github.com/lmcinnes/umap/issues/new).
It is beneficial if you check the [FAQ](https://umap-learn.readthedocs.io/en/latest/faq.html),
and do a cursory search of [existing issues](https://github.com/lmcinnes/umap/issues?utf8=%E2%9C%93&q=is%3Aissue).
It is also helpful, but not necessary, if you can provide clear instruction for
how to reproduce a problem. If you have resolved an issue yourself please consider
contributing to the FAQ to add your problem, and its resolution, so others can
benefit from your work.
## Documentation
Contributing to documentation is the easiest way to get started. Providing simple
clear or helpful documentation for new users is critical. Anything that *you* as
a new user found hard to understand, or difficult to work out, are excellent places
to begin. Contributions to more detailed and descriptive error messages is
especially appreciated. To contribute to the documentation please
[fork the project](https://github.com/lmcinnes/umap/issues#fork-destination-box)
into your own repository, make changes there, and then submit a pull request.
### Building the Documentation Locally
To build the docs locally, install the documentation tools requirements:
```bash
pip install -r docs_requirements.txt
```
Then run:
```bash
sphinx-build -b html doc doc/_build
```
This will build the documentation in HTML format. You will be able to find the output
in the `doc/_build` folder.
## Code
Code contributions are always welcome, from simple bug fixes, to new features. To
contribute code please
[fork the project](https://github.com/lmcinnes/umap/issues#fork-destination-box)
into your own repository, make changes there, and then submit a pull request. If
you are fixing a known issue please add the issue number to the PR message. If you
are fixing a new issue feel free to file an issue and then reference it in the PR.
You can [browse open issues](https://github.com/lmcinnes/umap/issues),
or consult the [project roadmap](https://github.com/lmcinnes/umap/issues/15), for potential code
contributions. Fixes for issues tagged with 'help wanted' are especially appreciated.
### Code formatting
If possible, install the [black code formatter](https://github.com/python/black) (e.g.
`pip install black`) and run it before submitting a pull request. This helps maintain consistency
across the code, but also there is a check in the Travis-CI continuous integration system which
will show up as a failure in the pull request if `black` detects that it hasn't been run.
Formatting is as simple as running:
```bash
black .
```
in the root of the project.
| 2,953 | 41.2 | 114 | md |
umap | umap-master/appveyor.yml | build: "off"
environment:
matrix:
- PYTHON_VERSION: "3.7"
MINICONDA: C:\Miniconda3-x64
- PYTHON_VERSION: "3.8"
MINICONDA: C:\Miniconda3-x64
init:
- "ECHO %PYTHON_VERSION% %MINICONDA%"
install:
- "set PATH=%MINICONDA%;%MINICONDA%\\Scripts;%PATH%"
- conda config --set always_yes yes --set changeps1 no
- conda update -q conda
- conda info -a
- "conda create -q -n test-environment python=%PYTHON_VERSION% numpy scipy scikit-learn numba pandas bokeh holoviews datashader scikit-image pytest"
- activate test-environment
- pip install "tensorflow>=2.1"
- pip install pytest-benchmark
- pip install -e .
test_script:
- pytest --show-capture=no -v --disable-warnings
| 712 | 26.423077 | 150 | yml |