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stringlengths 7
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"""
One way of improving the memory efficiency of the NaiveStack would be to recognise that:
[]
[1]
[1,2]
[1,2,3]
Holds the same information as:
[1, 2, 3]
(on the assumption that there have been no pops)
So rather than creating a new version for every push and every pop, we could create a new version only on pops,
since it is easy to see what the previous version of a stack that has been pushed to was.
This does mean that finding a particular version would no longer be a simple index look-up. You'd need
to iterate through each version until you found the right one.
Rather than storing a copy of each version, perhaps it would be more memory efficient to store
the sequence of update operations. And when a particular version is asked for, we could then
re-create that particular version from scratch? This would come at a cost for reading.
Each read would require all the update operations to be re-run first.
One solution to this might be to store a) the most recently accessed version r, and
b) the sequence of update operations, and c) to make sure all update operations are reversible.
Then, if we want to read from version v, rather than iterating through update operations
from 0 to v, we could find the 'fastest path' either forwards or backwards from r to v.
A stack is readily reversible. The reverse of a push is a pop. And the reverse of a pop is to push its return value.
If we know the sequence of pushes and pops we can start at any point in that sequence and go back and forth in it.
Let's implement that as ReversibleStack.
"""
class NaiveStack:
""" A partially persistent stack that makes no effort to save space or time. """
def __init__(self):
self.stacks = [[]]
def push(self, value):
new_stack = self.stacks[-1].copy()
new_stack.append(value)
self.stacks.append(new_stack)
def pop(self):
new_stack = self.stacks[-1].copy()
value = new_stack.pop()
self.stacks.append(new_stack)
return value
def read(self, version, index):
return self.stacks[version][index]
def show(self):
for stack in self.stacks:
print(stack)
class SequenceStack:
""" A partially persistent stack that iterates through a subsequence of update operations
to return a given version. Saves space but slows down read operations."""
def __init__(self):
self.sequence = [] # the complete sequence of pushes and pops
def push(self, value):
"""Append a push operation to end of update sequence."""
self.sequence.append(lambda stack: stack.append(value))
def pop(self):
"""Append a pop operation to end of update sequence."""
self.sequence.append(lambda stack: stack.pop())
def read_version(self, version):
"""Return the stack as it was at version."""
stack = []
for update_operation in self.sequence[:version]:
update_operation(stack)
return stack
def read(self, version, index):
return self.read_version(version)[index]
def show(self):
""" Print all versions of the stack. """
for v in range(len(self.sequence)):
print("version {}: ".format(v), self.read_version(v))
class ReversibleSequenceStack:
""" A partially persistent stack that stores the most recently read version and
iterates either forwards or backwards through the sequence of update operations
to return a requested version. This saves on space (although doubles the space
requirements for storing update operations because we are saving both the original
and its reverse), and tries to make up for the slow reading operation by reducing
how many update operations must be applied to reach the desired version."""
def __init__(self):
self.sequence = [] # the complete sequence of pushes and pops
self.stack = [] # most recently read version of the stack
self.version = 0 # most recently read version
def push(self, value):
"""Append a tuple of push and pop operation to end of update sequence."""
# the second value of the tuple is the opposite and can be used to iterate backwards
op = lambda stack: stack.append(value)
rev_op = lambda stack: stack.pop()
self.sequence.append((op, rev_op))
def pop(self):
"""Append a tuple of pop and push operation to end of update sequence."""
# the second value of the tuple is the opposite and can be used to iterate backwards
value = self.read_version(len(self.sequence))[-1]
op = lambda stack: stack.pop()
rev_op = lambda stack: stack.append(value)
self.sequence.append((op, rev_op))
def read_version(self, version):
"""Return the stack as it was at version."""
if version == self.version: return self.stack
while self.version < version:
update_operation = self.sequence[self.version][0]
self.version += 1
update_operation(self.stack)
while self.version > version:
update_operation = self.sequence[self.version-1][1]
self.version -= 1
update_operation(self.stack)
return self.stack
def read(self, version, index):
return self.read_version(version)[index]
rs = ReversibleSequenceStack()
rs.push(1)
rs.push(2)
rs.push(3)
rs.pop()
rs.pop()
rs.push(7)
for i in range(0, 7):
print(i, rs.read_version(i))
for i in range(6, -1, -1):
print(i, rs.read_version(i))
|
"""
One way of improving the memory efficiency of the NaiveStack would be to recognise that:
[]
[1]
[1,2]
[1,2,3]
Holds the same information as:
[1, 2, 3]
(on the assumption that there have been no pops)
So rather than creating a new version for every push and every pop, we could create a new version only on pops,
since it is easy to see what the previous version of a stack that has been pushed to was.
This does mean that finding a particular version would no longer be a simple index look-up. You'd need
to iterate through each version until you found the right one.
Rather than storing a copy of each version, perhaps it would be more memory efficient to store
the sequence of update operations. And when a particular version is asked for, we could then
re-create that particular version from scratch? This would come at a cost for reading.
Each read would require all the update operations to be re-run first.
One solution to this might be to store a) the most recently accessed version r, and
b) the sequence of update operations, and c) to make sure all update operations are reversible.
Then, if we want to read from version v, rather than iterating through update operations
from 0 to v, we could find the 'fastest path' either forwards or backwards from r to v.
A stack is readily reversible. The reverse of a push is a pop. And the reverse of a pop is to push its return value.
If we know the sequence of pushes and pops we can start at any point in that sequence and go back and forth in it.
Let's implement that as ReversibleStack.
"""
class Naivestack:
""" A partially persistent stack that makes no effort to save space or time. """
def __init__(self):
self.stacks = [[]]
def push(self, value):
new_stack = self.stacks[-1].copy()
new_stack.append(value)
self.stacks.append(new_stack)
def pop(self):
new_stack = self.stacks[-1].copy()
value = new_stack.pop()
self.stacks.append(new_stack)
return value
def read(self, version, index):
return self.stacks[version][index]
def show(self):
for stack in self.stacks:
print(stack)
class Sequencestack:
""" A partially persistent stack that iterates through a subsequence of update operations
to return a given version. Saves space but slows down read operations."""
def __init__(self):
self.sequence = []
def push(self, value):
"""Append a push operation to end of update sequence."""
self.sequence.append(lambda stack: stack.append(value))
def pop(self):
"""Append a pop operation to end of update sequence."""
self.sequence.append(lambda stack: stack.pop())
def read_version(self, version):
"""Return the stack as it was at version."""
stack = []
for update_operation in self.sequence[:version]:
update_operation(stack)
return stack
def read(self, version, index):
return self.read_version(version)[index]
def show(self):
""" Print all versions of the stack. """
for v in range(len(self.sequence)):
print('version {}: '.format(v), self.read_version(v))
class Reversiblesequencestack:
""" A partially persistent stack that stores the most recently read version and
iterates either forwards or backwards through the sequence of update operations
to return a requested version. This saves on space (although doubles the space
requirements for storing update operations because we are saving both the original
and its reverse), and tries to make up for the slow reading operation by reducing
how many update operations must be applied to reach the desired version."""
def __init__(self):
self.sequence = []
self.stack = []
self.version = 0
def push(self, value):
"""Append a tuple of push and pop operation to end of update sequence."""
op = lambda stack: stack.append(value)
rev_op = lambda stack: stack.pop()
self.sequence.append((op, rev_op))
def pop(self):
"""Append a tuple of pop and push operation to end of update sequence."""
value = self.read_version(len(self.sequence))[-1]
op = lambda stack: stack.pop()
rev_op = lambda stack: stack.append(value)
self.sequence.append((op, rev_op))
def read_version(self, version):
"""Return the stack as it was at version."""
if version == self.version:
return self.stack
while self.version < version:
update_operation = self.sequence[self.version][0]
self.version += 1
update_operation(self.stack)
while self.version > version:
update_operation = self.sequence[self.version - 1][1]
self.version -= 1
update_operation(self.stack)
return self.stack
def read(self, version, index):
return self.read_version(version)[index]
rs = reversible_sequence_stack()
rs.push(1)
rs.push(2)
rs.push(3)
rs.pop()
rs.pop()
rs.push(7)
for i in range(0, 7):
print(i, rs.read_version(i))
for i in range(6, -1, -1):
print(i, rs.read_version(i))
|
__all__ = ("Values", )
class Data(object):
def __init__(
self,
plugin_instance=None,
meta=None,
plugin=None,
host=None,
type=None,
type_instance=None,
interval=None,
time=None,
values=None,
):
self.plugin = plugin
self.plugin_instance = plugin_instance,
self.meta = meta
self.host = host
self.type = type
self.type_instance = type_instance
self.dstypes = dstypes
self.values = values
self.interval = interval
self.time = time
def dispatch(self):
pass
def mk_values(
plugin_instance=None,
meta=None,
plugin=None,
host=None,
type=None,
type_instance=None,
interval=None,
time=None,
values=None,
):
return Data(
plugin_instance=plugin_instance,
meta=meta,
plugin=plugin,
host=host,
type=type,
type_instance=type_instance,
interval=interval,
time=time,
values=values,
)
Values = mk_values
|
__all__ = ('Values',)
class Data(object):
def __init__(self, plugin_instance=None, meta=None, plugin=None, host=None, type=None, type_instance=None, interval=None, time=None, values=None):
self.plugin = plugin
self.plugin_instance = (plugin_instance,)
self.meta = meta
self.host = host
self.type = type
self.type_instance = type_instance
self.dstypes = dstypes
self.values = values
self.interval = interval
self.time = time
def dispatch(self):
pass
def mk_values(plugin_instance=None, meta=None, plugin=None, host=None, type=None, type_instance=None, interval=None, time=None, values=None):
return data(plugin_instance=plugin_instance, meta=meta, plugin=plugin, host=host, type=type, type_instance=type_instance, interval=interval, time=time, values=values)
values = mk_values
|
age = 6
if age < 1:
print("baby")
elif age < 3:
print("toddler")
elif age < 5:
print("preschool")
elif age < 12:
print("gradeschooler")
elif age < 19:
print("teen")
elif age > 20:
print("old")
else:
print("integer error")
|
age = 6
if age < 1:
print('baby')
elif age < 3:
print('toddler')
elif age < 5:
print('preschool')
elif age < 12:
print('gradeschooler')
elif age < 19:
print('teen')
elif age > 20:
print('old')
else:
print('integer error')
|
def main():
# input
H, W = map(int, input().split())
sss = [input() for _ in range(H)]
# compute
cnt = 0
for h in range(1,H-1):
for w in range(1,W-1):
if sss[h][w]=='#' and sss[h-1][w]!='#' and sss[h+1][w]!='#' and sss[h][w-1]!='#' and sss[h][w+1]!='#':
cnt += 1
# output
if cnt == 0:
print('Yes')
else:
print('No')
if __name__ == '__main__':
main()
|
def main():
(h, w) = map(int, input().split())
sss = [input() for _ in range(H)]
cnt = 0
for h in range(1, H - 1):
for w in range(1, W - 1):
if sss[h][w] == '#' and sss[h - 1][w] != '#' and (sss[h + 1][w] != '#') and (sss[h][w - 1] != '#') and (sss[h][w + 1] != '#'):
cnt += 1
if cnt == 0:
print('Yes')
else:
print('No')
if __name__ == '__main__':
main()
|
class Solution:
def getModifiedArray(self, length: int, updates: List[List[int]]) -> List[int]:
arr = [0] * (length + 1)
for s, e, i in updates:
arr[s] += i
arr[e+1] -= i
for i in range(1, length):
arr[i] += arr[i-1]
return arr[:-1]
|
class Solution:
def get_modified_array(self, length: int, updates: List[List[int]]) -> List[int]:
arr = [0] * (length + 1)
for (s, e, i) in updates:
arr[s] += i
arr[e + 1] -= i
for i in range(1, length):
arr[i] += arr[i - 1]
return arr[:-1]
|
nerdle_len = 8
nerd_num_list = [str(x) for x in range(nerdle_len+2)]
nerd_op_list = ['+','-','*','/','==']
nerd_list = nerd_num_list+nerd_op_list
|
nerdle_len = 8
nerd_num_list = [str(x) for x in range(nerdle_len + 2)]
nerd_op_list = ['+', '-', '*', '/', '==']
nerd_list = nerd_num_list + nerd_op_list
|
def assert_raises(excClass, callableObj, *args, **kwargs):
"""
Like unittest.TestCase.assertRaises, but returns the exception.
"""
try:
callableObj(*args, **kwargs)
except excClass as e:
return e
else:
if hasattr(excClass,'__name__'): excName = excClass.__name__
else: excName = str(excClass)
raise AssertionError("%s not raised" % excName)
|
def assert_raises(excClass, callableObj, *args, **kwargs):
"""
Like unittest.TestCase.assertRaises, but returns the exception.
"""
try:
callable_obj(*args, **kwargs)
except excClass as e:
return e
else:
if hasattr(excClass, '__name__'):
exc_name = excClass.__name__
else:
exc_name = str(excClass)
raise assertion_error('%s not raised' % excName)
|
'''
As is can shift max '1111' -> 15 on one command...
So a call like shift(20) would need to be split up...
Thinking the user should do this when coding... or
could be stdlib fx that does this...
If want to do shift(16) in one cycle, can add s4 support
(and correspoinding 16muxes) to hardware... revisit as needed
'''
def shiftRight16_( x, y ):
''' 16 bit barrel shifter (right) '''
N = 16
t0 = [ None ] * N
t1 = [ None ] * N
t2 = [ None ] * N
t3 = [ None ] * N
y = y[::-1] # make life simpler by matching array access to MSB-to-LSB format
#
for i in range( N - 1, 0, -1 ):
t0[i] = mux_( x[ i - 1 ], x[i], y[0] )
t0[0] = mux_( 0, x[0], y[0] )
#
for i in range( N - 1, 1, -1 ):
t1[i] = mux_( t0[ i - 2 ], t0[i], y[1] )
t1[1] = mux_( 0, t0[1], y[1] )
t1[0] = mux_( 0, t0[0], y[1] )
#
for i in range( N - 1, 3, -1 ):
t2[i] = mux_( t1[ i - 4 ], t1[i], y[2] )
t2[3] = mux_( 0, t1[3], y[2] )
t2[2] = mux_( 0, t1[2], y[2] )
t2[1] = mux_( 0, t1[1], y[2] )
t2[0] = mux_( 0, t1[0], y[2] )
#
for i in range( N - 1, 7, -1 ):
t3[i] = mux_( t2[ i - 8 ], t2[i], y[3] )
t3[7] = mux_( 0, t2[7], y[3] )
t3[6] = mux_( 0, t2[6], y[3] )
t3[5] = mux_( 0, t2[5], y[3] )
t3[4] = mux_( 0, t2[4], y[3] )
t3[3] = mux_( 0, t2[3], y[3] )
t3[2] = mux_( 0, t2[2], y[3] )
t3[1] = mux_( 0, t2[1], y[3] )
t3[0] = mux_( 0, t2[0], y[3] )
#
return t3
def shiftLeft16_( x, y ):
''' 16 bit barrel shifter (left) '''
N = 16
t0 = [ None ] * N
t1 = [ None ] * N
t2 = [ None ] * N
t3 = [ None ] * N
y = y[::-1] # make life simpler by matching array access to MSB-to-LSB format
#
t0[N - 1] = mux_( 0, x[N - 1], y[0] )
for i in range( N - 2, -1, -1 ):
t0[i] = mux_( x[ i + 1 ], x[i], y[0] )
#
t1[ N - 1 ] = mux_( 0, t0[ N - 1 ], y[1] )
t1[ N - 2 ] = mux_( 0, t0[ N - 2 ], y[1] )
for i in range( N - 3, -1, -1 ):
t1[i] = mux_( t0[ i + 2 ], t0[i], y[1] )
#
t2[ N - 1 ] = mux_( 0, t1[ N - 1 ], y[2] )
t2[ N - 2 ] = mux_( 0, t1[ N - 2 ], y[2] )
t2[ N - 3 ] = mux_( 0, t1[ N - 3 ], y[2] )
t2[ N - 4 ] = mux_( 0, t1[ N - 4 ], y[2] )
for i in range( N - 5, -1, -1 ):
t2[i] = mux_( t1[ i + 4 ], t1[i], y[2] )
#
t3[ N - 1 ] = mux_( 0, t2[ N - 1 ], y[3] )
t3[ N - 2 ] = mux_( 0, t2[ N - 2 ], y[3] )
t3[ N - 3 ] = mux_( 0, t2[ N - 3 ], y[3] )
t3[ N - 4 ] = mux_( 0, t2[ N - 4 ], y[3] )
t3[ N - 5 ] = mux_( 0, t2[ N - 5 ], y[3] )
t3[ N - 6 ] = mux_( 0, t2[ N - 6 ], y[3] )
t3[ N - 7 ] = mux_( 0, t2[ N - 7 ], y[3] )
t3[ N - 8 ] = mux_( 0, t2[ N - 8 ], y[3] )
for i in range( N - 9, -1, -1 ):
t3[i] = mux_( t2[ i + 8 ], t2[i], y[3] )
#
return t3
|
"""
As is can shift max '1111' -> 15 on one command...
So a call like shift(20) would need to be split up...
Thinking the user should do this when coding... or
could be stdlib fx that does this...
If want to do shift(16) in one cycle, can add s4 support
(and correspoinding 16muxes) to hardware... revisit as needed
"""
def shift_right16_(x, y):
""" 16 bit barrel shifter (right) """
n = 16
t0 = [None] * N
t1 = [None] * N
t2 = [None] * N
t3 = [None] * N
y = y[::-1]
for i in range(N - 1, 0, -1):
t0[i] = mux_(x[i - 1], x[i], y[0])
t0[0] = mux_(0, x[0], y[0])
for i in range(N - 1, 1, -1):
t1[i] = mux_(t0[i - 2], t0[i], y[1])
t1[1] = mux_(0, t0[1], y[1])
t1[0] = mux_(0, t0[0], y[1])
for i in range(N - 1, 3, -1):
t2[i] = mux_(t1[i - 4], t1[i], y[2])
t2[3] = mux_(0, t1[3], y[2])
t2[2] = mux_(0, t1[2], y[2])
t2[1] = mux_(0, t1[1], y[2])
t2[0] = mux_(0, t1[0], y[2])
for i in range(N - 1, 7, -1):
t3[i] = mux_(t2[i - 8], t2[i], y[3])
t3[7] = mux_(0, t2[7], y[3])
t3[6] = mux_(0, t2[6], y[3])
t3[5] = mux_(0, t2[5], y[3])
t3[4] = mux_(0, t2[4], y[3])
t3[3] = mux_(0, t2[3], y[3])
t3[2] = mux_(0, t2[2], y[3])
t3[1] = mux_(0, t2[1], y[3])
t3[0] = mux_(0, t2[0], y[3])
return t3
def shift_left16_(x, y):
""" 16 bit barrel shifter (left) """
n = 16
t0 = [None] * N
t1 = [None] * N
t2 = [None] * N
t3 = [None] * N
y = y[::-1]
t0[N - 1] = mux_(0, x[N - 1], y[0])
for i in range(N - 2, -1, -1):
t0[i] = mux_(x[i + 1], x[i], y[0])
t1[N - 1] = mux_(0, t0[N - 1], y[1])
t1[N - 2] = mux_(0, t0[N - 2], y[1])
for i in range(N - 3, -1, -1):
t1[i] = mux_(t0[i + 2], t0[i], y[1])
t2[N - 1] = mux_(0, t1[N - 1], y[2])
t2[N - 2] = mux_(0, t1[N - 2], y[2])
t2[N - 3] = mux_(0, t1[N - 3], y[2])
t2[N - 4] = mux_(0, t1[N - 4], y[2])
for i in range(N - 5, -1, -1):
t2[i] = mux_(t1[i + 4], t1[i], y[2])
t3[N - 1] = mux_(0, t2[N - 1], y[3])
t3[N - 2] = mux_(0, t2[N - 2], y[3])
t3[N - 3] = mux_(0, t2[N - 3], y[3])
t3[N - 4] = mux_(0, t2[N - 4], y[3])
t3[N - 5] = mux_(0, t2[N - 5], y[3])
t3[N - 6] = mux_(0, t2[N - 6], y[3])
t3[N - 7] = mux_(0, t2[N - 7], y[3])
t3[N - 8] = mux_(0, t2[N - 8], y[3])
for i in range(N - 9, -1, -1):
t3[i] = mux_(t2[i + 8], t2[i], y[3])
return t3
|
# coding: utf-8
SECRET_KEY = 'foo'
EMAIL_BACKEND = 'postmarker.django.EmailBackend'
POSTMARK = {
'TOKEN': '<YOUR POSTMARK SERVER TOKEN>'
}
|
secret_key = 'foo'
email_backend = 'postmarker.django.EmailBackend'
postmark = {'TOKEN': '<YOUR POSTMARK SERVER TOKEN>'}
|
def is_prime(num, primes):
for prime in primes:
if prime == num:
return True
if not num % prime:
return False
return True
def get_primes(num):
limit = (num // 2) + 1
candidates = list()
primes = list()
for i in range(2, limit):
if is_prime(i, primes):
primes.append(i)
candidates.append((i, num - i))
new_candidates = list()
for first, second in candidates[::-1]:
if is_prime(second, primes):
primes.append(second)
new_candidates.append((first, second))
return new_candidates[-1]
assert get_primes(4) == (2, 2)
assert get_primes(10) == (3, 7)
assert get_primes(100) == (3, 97)
|
def is_prime(num, primes):
for prime in primes:
if prime == num:
return True
if not num % prime:
return False
return True
def get_primes(num):
limit = num // 2 + 1
candidates = list()
primes = list()
for i in range(2, limit):
if is_prime(i, primes):
primes.append(i)
candidates.append((i, num - i))
new_candidates = list()
for (first, second) in candidates[::-1]:
if is_prime(second, primes):
primes.append(second)
new_candidates.append((first, second))
return new_candidates[-1]
assert get_primes(4) == (2, 2)
assert get_primes(10) == (3, 7)
assert get_primes(100) == (3, 97)
|
#program to remove two duplicate numbers from a given number of list.
def two_unique_nums(nums):
return [i for i in nums if nums.count(i)==1]
print(two_unique_nums([1,2,3,2,3,4,5]))
print(two_unique_nums([1,2,3,2,4,5]))
print(two_unique_nums([1,2,3,4,5]))
|
def two_unique_nums(nums):
return [i for i in nums if nums.count(i) == 1]
print(two_unique_nums([1, 2, 3, 2, 3, 4, 5]))
print(two_unique_nums([1, 2, 3, 2, 4, 5]))
print(two_unique_nums([1, 2, 3, 4, 5]))
|
types = [
{
'name': 'RNAExpression',
'item_type': 'rna-expression',
'schema': {
'title': 'RNAExpression',
'description': 'Schema for RNA-seq expression',
'properties': {
'uuid': {
'title': 'UUID',
},
'expression': {
'type': 'object',
'properties': {
'gene_id': {
'title': 'Gene ID',
'type': 'string'
},
'transcript_ids': {
'title': 'Transcript ID',
'type': 'string'
},
'tpm': {
'title': 'TPM',
'type': 'float'
},
'fpkm': {
'title': 'FPKM',
'type': 'float'
}
}
},
'file': {
'type': 'object',
'properties': {
'@id': {
'type': 'string'
},
'assay_title': {
'title': 'Assay title',
'type': 'string'
},
'assembly': {
'title': 'Assembly',
'type': 'string'
},
'biosample_ontology': {
'type': 'object',
'properties': {
'organ_slims': {
'type': 'string'
},
'term_name': {
'type': 'string'
},
'synonyms': {
'type': 'string'
},
'name': {
'type': 'string'
},
'term_id': {
'type': 'string'
},
'classification': {
'type': 'string'
}
}
},
'dataset': {
'type': 'string'
},
'donors': {
'type': 'string'
},
'genome_annotation': {
'type': 'string'
}
}
},
'dataset': {
'type': 'object',
'properties': {
'@id': {
'type': 'string'
},
'biosample_summary': {
'type': 'string'
},
'replicates': {
'type': 'object',
'properties': {
'library': {
'type': 'object',
'properties': {
'biosample': {
'type': 'object',
'properties': {
'age_units': {
'type': 'string'
},
'sex': {
'type': 'string'
},
'age': {
'type': 'string'
},
'donor': {
'type': 'object',
'properties': {
'organism': {
'type': 'object',
'properties': {
'scientific_name': {
'type': 'string'
}
}
}
}
}
}
}
}
}
}
}
}
},
'gene': {
'type': 'object',
'properties': {
'geneid': {
'type': 'string'
},
'symbol': {
'type': 'string'
},
'name': {
'type': 'string'
},
'synonyms': {
'type': 'string'
},
'@id': {
'type': 'string'
},
'title': {
'type': 'string'
}
}
},
'@id': {
'title': 'ID',
'type': 'string',
},
'@type': {
'title': 'Type',
'type': 'array',
'items': {
'type': 'string'
},
}
},
'columns': {
'expression.gene_id': {
'title': 'Feature ID'
},
'expression.tpm': {
'title': 'TPM'
},
'expression.fpkm': {
'title': 'FPKM'
},
'gene.symbol': {
'title': 'Gene symbol'
},
'gene.name': {
'title': 'Gene name'
},
'gene.title': {
'title': 'Gene title'
},
'file.biosample_ontology.term_name': {
'title': 'Biosample term name'
},
'file.assay_title': {
'title': 'Assay title'
},
'file.assembly': {
'title': 'Assembly'
},
'file.biosample_ontology.classification': {
'title': 'Biosample classification'
},
'file.biosample_ontology.organ_slims': {
'title': 'Biosample organ'
},
'dataset.replicates.library.biosample.sex': {
'title': 'Biosample sex'
},
'dataset.replicates.library.biosample.donor.organism.scientific_name': {
'title': 'Organism'
},
'dataset.biosample_summary': {
'title': 'Biosample summary'
},
'file.genome_annotation': {
'title': 'Genome annotation'
},
'file.donors': {
'title': 'Donors'
},
'file.@id': {
'title': 'File'
},
'dataset.@id': {
'title': 'Experiment'
}
},
'facets': {
'file.assay_title': {
'title': 'Assay title',
'open_on_load': True
},
'file.biosample_ontology.classification': {
'title': 'Biosample classification',
'open_on_load': True
},
'file.biosample_ontology.term_name': {
'title': 'Biosample term name',
'open_on_load': True,
'type': 'typeahead',
'length': 'long'
},
'file.assembly': {
'title': 'Assembly',
'open_on_load': True
},
'dataset.replicates.library.biosample.donor.organism.scientific_name': {
'title': 'Organism',
'open_on_load': True
},
'dataset.replicates.library.biosample.sex': {
'title': 'Biosample sex'
}
},
}
}
]
|
types = [{'name': 'RNAExpression', 'item_type': 'rna-expression', 'schema': {'title': 'RNAExpression', 'description': 'Schema for RNA-seq expression', 'properties': {'uuid': {'title': 'UUID'}, 'expression': {'type': 'object', 'properties': {'gene_id': {'title': 'Gene ID', 'type': 'string'}, 'transcript_ids': {'title': 'Transcript ID', 'type': 'string'}, 'tpm': {'title': 'TPM', 'type': 'float'}, 'fpkm': {'title': 'FPKM', 'type': 'float'}}}, 'file': {'type': 'object', 'properties': {'@id': {'type': 'string'}, 'assay_title': {'title': 'Assay title', 'type': 'string'}, 'assembly': {'title': 'Assembly', 'type': 'string'}, 'biosample_ontology': {'type': 'object', 'properties': {'organ_slims': {'type': 'string'}, 'term_name': {'type': 'string'}, 'synonyms': {'type': 'string'}, 'name': {'type': 'string'}, 'term_id': {'type': 'string'}, 'classification': {'type': 'string'}}}, 'dataset': {'type': 'string'}, 'donors': {'type': 'string'}, 'genome_annotation': {'type': 'string'}}}, 'dataset': {'type': 'object', 'properties': {'@id': {'type': 'string'}, 'biosample_summary': {'type': 'string'}, 'replicates': {'type': 'object', 'properties': {'library': {'type': 'object', 'properties': {'biosample': {'type': 'object', 'properties': {'age_units': {'type': 'string'}, 'sex': {'type': 'string'}, 'age': {'type': 'string'}, 'donor': {'type': 'object', 'properties': {'organism': {'type': 'object', 'properties': {'scientific_name': {'type': 'string'}}}}}}}}}}}}}, 'gene': {'type': 'object', 'properties': {'geneid': {'type': 'string'}, 'symbol': {'type': 'string'}, 'name': {'type': 'string'}, 'synonyms': {'type': 'string'}, '@id': {'type': 'string'}, 'title': {'type': 'string'}}}, '@id': {'title': 'ID', 'type': 'string'}, '@type': {'title': 'Type', 'type': 'array', 'items': {'type': 'string'}}}, 'columns': {'expression.gene_id': {'title': 'Feature ID'}, 'expression.tpm': {'title': 'TPM'}, 'expression.fpkm': {'title': 'FPKM'}, 'gene.symbol': {'title': 'Gene symbol'}, 'gene.name': {'title': 'Gene name'}, 'gene.title': {'title': 'Gene title'}, 'file.biosample_ontology.term_name': {'title': 'Biosample term name'}, 'file.assay_title': {'title': 'Assay title'}, 'file.assembly': {'title': 'Assembly'}, 'file.biosample_ontology.classification': {'title': 'Biosample classification'}, 'file.biosample_ontology.organ_slims': {'title': 'Biosample organ'}, 'dataset.replicates.library.biosample.sex': {'title': 'Biosample sex'}, 'dataset.replicates.library.biosample.donor.organism.scientific_name': {'title': 'Organism'}, 'dataset.biosample_summary': {'title': 'Biosample summary'}, 'file.genome_annotation': {'title': 'Genome annotation'}, 'file.donors': {'title': 'Donors'}, 'file.@id': {'title': 'File'}, 'dataset.@id': {'title': 'Experiment'}}, 'facets': {'file.assay_title': {'title': 'Assay title', 'open_on_load': True}, 'file.biosample_ontology.classification': {'title': 'Biosample classification', 'open_on_load': True}, 'file.biosample_ontology.term_name': {'title': 'Biosample term name', 'open_on_load': True, 'type': 'typeahead', 'length': 'long'}, 'file.assembly': {'title': 'Assembly', 'open_on_load': True}, 'dataset.replicates.library.biosample.donor.organism.scientific_name': {'title': 'Organism', 'open_on_load': True}, 'dataset.replicates.library.biosample.sex': {'title': 'Biosample sex'}}}}]
|
def square(x):
return x * x
def launch_missiles():
print('missiles launched')
def even_or_odd(n):
if n % 2 == 0:
print('even')
return
print('odd')
|
def square(x):
return x * x
def launch_missiles():
print('missiles launched')
def even_or_odd(n):
if n % 2 == 0:
print('even')
return
print('odd')
|
n = 1
for i in range(1, 10 + 1):
print(n)
n *= i
|
n = 1
for i in range(1, 10 + 1):
print(n)
n *= i
|
#!/usr/bin/env python
# coding: utf-8
# # Hill Cipher
# Below is the code to implement the Hill Cipher, which is an example of a **polyalphabetic cryptosystem**, that is, it does
# not assign a single ciphertext letter to a single plaintext letter, but rather a ciphertext letter may represent more than
# one plaintext letter. This example is from Judson's [Abstract Algebra](http://abstract.ups.edu/sage-aata.html) textbook,
# example 7.4. The encryption is based on the matrix
# \begin{equation*}
# A=\left(\begin{array}{cc}
# 3 & 5 \\
# 1 & 2
# \end{array}\right)
# \end{equation*}
# and encryptes pairs of letters at a time, rather than one letter at a time.
#
# The digitize and alphabetize functions are rather similar to the ones found in the CeasarCipher document, the bigest change
# being that these pair the numbers up so as to form matrices for encryption and decryption.
# In[ ]:
def digitize(string):
cipher_text = []
holder = []
for i in string:
if i == 'A' or i == 'a': holder.append(0)
if i == 'B' or i == 'b': holder.append(1)
if i == 'C' or i == 'c': holder.append(2)
if i == 'D' or i == 'd': holder.append(3)
if i == 'E' or i == 'e': holder.append(4)
if i == 'F' or i == 'f': holder.append(5)
if i == 'G' or i == 'g': holder.append(6)
if i == 'H' or i == 'h': holder.append(7)
if i == 'I' or i == 'i': holder.append(8)
if i == 'J' or i == 'j': holder.append(9)
if i == 'K' or i == 'k': holder.append(10)
if i == 'L' or i == 'l': holder.append(11)
if i == 'M' or i == 'm': holder.append(12)
if i == 'N' or i == 'n': holder.append(13)
if i == 'O' or i == 'o': holder.append(14)
if i == 'P' or i == 'p': holder.append(15)
if i == 'Q' or i == 'q': holder.append(16)
if i == 'R' or i == 'r': holder.append(17)
if i == 'S' or i == 's': holder.append(18)
if i == 'T' or i == 't': holder.append(19)
if i == 'U' or i == 'u': holder.append(20)
if i == 'V' or i == 'v': holder.append(21)
if i == 'W' or i == 'w': holder.append(22)
if i == 'X' or i == 'x': holder.append(23)
if i == 'Y' or i == 'y': holder.append(24)
if i == 'Z' or i == 'z': holder.append(25)
if len(holder)==2:
cipher_text.append(matrix(holder))
holder = []
if len(holder)==1:
holder.append(23)
cipher_text.append(matrix(holder))
return cipher_text
# In[ ]:
def alphabetize(digits):
plain_text = ""
comparison = MatrixSpace(IntegerModRing(26),1,1)
for number in digits:
for i in number:
if i == comparison([0])[0]: plain_text = plain_text + "A"
if i == comparison([1])[0]: plain_text = plain_text + "B"
if i == comparison([2])[0]: plain_text = plain_text + "C"
if i == comparison([3])[0]: plain_text = plain_text + "D"
if i == comparison([4])[0]: plain_text = plain_text + "E"
if i == comparison([5])[0]: plain_text = plain_text + "F"
if i == comparison([6])[0]: plain_text = plain_text + "G"
if i == comparison([7])[0]: plain_text = plain_text + "H"
if i == comparison([8])[0]: plain_text = plain_text + "I"
if i == comparison([9])[0]: plain_text = plain_text + "J"
if i == comparison([10])[0]: plain_text = plain_text + "K"
if i == comparison([11])[0]: plain_text = plain_text + "L"
if i == comparison([12])[0]: plain_text = plain_text + "M"
if i == comparison([13])[0]: plain_text = plain_text + "N"
if i == comparison([14])[0]: plain_text = plain_text + "O"
if i == comparison([15])[0]: plain_text = plain_text + "P"
if i == comparison([16])[0]: plain_text = plain_text + "Q"
if i == comparison([17])[0]: plain_text = plain_text + "R"
if i == comparison([18])[0]: plain_text = plain_text + "S"
if i == comparison([19])[0]: plain_text = plain_text + "T"
if i == comparison([20])[0]: plain_text = plain_text + "U"
if i == comparison([21])[0]: plain_text = plain_text + "V"
if i == comparison([22])[0]: plain_text = plain_text + "W"
if i == comparison([23])[0]: plain_text = plain_text + "X"
if i == comparison([24])[0]: plain_text = plain_text + "Y"
if i == comparison([25])[0]: plain_text = plain_text + "Z"
return plain_text
# Here we define the HillEncrypt and HillDecrypt functions, which take in strings, and encrypt or decrypt them according
# to the matrices passed into them as parameters.
# In[ ]:
def HillEncrypt(message, A, b):
encoded = digitize(message)
cipher_text = []
for item in encoded:
cipher_text.append(A*item.transpose()+b)
return alphabetize(cipher_text)
def HillDecrypt(message, A, b):
A = A.inverse()
encoded = digitize(message)
plain_text = []
for item in encoded:
plain_text.append(A*item.transpose()-A*b)
return alphabetize(plain_text)
# Here we use MatrixSpaces over the Ring of integers mod 26, to define the matrices used for encryption and decryption.
# We use MatrixSpaces rather than ordinary matrices to ensure that the inverse of $A$ is calculated correctly.
# In[ ]:
Z22_26 = MatrixSpace(IntegerModRing(26),2,2)
Z21_26 = MatrixSpace(IntegerModRing(26),2,1)
# these are the matrices used in the example in the book.
A = Z22_26([[3,5],[1,2]])
b = Z21_26([2,2])
# Here we go through our first example, which is the example in the book, encrypting the message "help".
# In[ ]:
message = "help"
encrypted = HillEncrypt(message,A,b)
print(encrypted)
decrypted = HillDecrypt(encrypted,A,b)
print(decrypted)
|
def digitize(string):
cipher_text = []
holder = []
for i in string:
if i == 'A' or i == 'a':
holder.append(0)
if i == 'B' or i == 'b':
holder.append(1)
if i == 'C' or i == 'c':
holder.append(2)
if i == 'D' or i == 'd':
holder.append(3)
if i == 'E' or i == 'e':
holder.append(4)
if i == 'F' or i == 'f':
holder.append(5)
if i == 'G' or i == 'g':
holder.append(6)
if i == 'H' or i == 'h':
holder.append(7)
if i == 'I' or i == 'i':
holder.append(8)
if i == 'J' or i == 'j':
holder.append(9)
if i == 'K' or i == 'k':
holder.append(10)
if i == 'L' or i == 'l':
holder.append(11)
if i == 'M' or i == 'm':
holder.append(12)
if i == 'N' or i == 'n':
holder.append(13)
if i == 'O' or i == 'o':
holder.append(14)
if i == 'P' or i == 'p':
holder.append(15)
if i == 'Q' or i == 'q':
holder.append(16)
if i == 'R' or i == 'r':
holder.append(17)
if i == 'S' or i == 's':
holder.append(18)
if i == 'T' or i == 't':
holder.append(19)
if i == 'U' or i == 'u':
holder.append(20)
if i == 'V' or i == 'v':
holder.append(21)
if i == 'W' or i == 'w':
holder.append(22)
if i == 'X' or i == 'x':
holder.append(23)
if i == 'Y' or i == 'y':
holder.append(24)
if i == 'Z' or i == 'z':
holder.append(25)
if len(holder) == 2:
cipher_text.append(matrix(holder))
holder = []
if len(holder) == 1:
holder.append(23)
cipher_text.append(matrix(holder))
return cipher_text
def alphabetize(digits):
plain_text = ''
comparison = matrix_space(integer_mod_ring(26), 1, 1)
for number in digits:
for i in number:
if i == comparison([0])[0]:
plain_text = plain_text + 'A'
if i == comparison([1])[0]:
plain_text = plain_text + 'B'
if i == comparison([2])[0]:
plain_text = plain_text + 'C'
if i == comparison([3])[0]:
plain_text = plain_text + 'D'
if i == comparison([4])[0]:
plain_text = plain_text + 'E'
if i == comparison([5])[0]:
plain_text = plain_text + 'F'
if i == comparison([6])[0]:
plain_text = plain_text + 'G'
if i == comparison([7])[0]:
plain_text = plain_text + 'H'
if i == comparison([8])[0]:
plain_text = plain_text + 'I'
if i == comparison([9])[0]:
plain_text = plain_text + 'J'
if i == comparison([10])[0]:
plain_text = plain_text + 'K'
if i == comparison([11])[0]:
plain_text = plain_text + 'L'
if i == comparison([12])[0]:
plain_text = plain_text + 'M'
if i == comparison([13])[0]:
plain_text = plain_text + 'N'
if i == comparison([14])[0]:
plain_text = plain_text + 'O'
if i == comparison([15])[0]:
plain_text = plain_text + 'P'
if i == comparison([16])[0]:
plain_text = plain_text + 'Q'
if i == comparison([17])[0]:
plain_text = plain_text + 'R'
if i == comparison([18])[0]:
plain_text = plain_text + 'S'
if i == comparison([19])[0]:
plain_text = plain_text + 'T'
if i == comparison([20])[0]:
plain_text = plain_text + 'U'
if i == comparison([21])[0]:
plain_text = plain_text + 'V'
if i == comparison([22])[0]:
plain_text = plain_text + 'W'
if i == comparison([23])[0]:
plain_text = plain_text + 'X'
if i == comparison([24])[0]:
plain_text = plain_text + 'Y'
if i == comparison([25])[0]:
plain_text = plain_text + 'Z'
return plain_text
def hill_encrypt(message, A, b):
encoded = digitize(message)
cipher_text = []
for item in encoded:
cipher_text.append(A * item.transpose() + b)
return alphabetize(cipher_text)
def hill_decrypt(message, A, b):
a = A.inverse()
encoded = digitize(message)
plain_text = []
for item in encoded:
plain_text.append(A * item.transpose() - A * b)
return alphabetize(plain_text)
z22_26 = matrix_space(integer_mod_ring(26), 2, 2)
z21_26 = matrix_space(integer_mod_ring(26), 2, 1)
a = z22_26([[3, 5], [1, 2]])
b = z21_26([2, 2])
message = 'help'
encrypted = hill_encrypt(message, A, b)
print(encrypted)
decrypted = hill_decrypt(encrypted, A, b)
print(decrypted)
|
file = open('Advent-of-Code-2021\\Day 13\\Day 13 input.txt')
points = []
folds = []
for line in file:
line = line.strip()
if (line.find(',') != -1):
pointparse = line.split(',')
points.append([int(pointparse[0]),int(pointparse[1])])
elif (line.find('=') != -1):
foldparse = line.split('=')
folds.append([foldparse[0][len(foldparse[0])-1], int(foldparse[1])])
else:
"Do nothing"
for thisfold in folds:
newpoints = []
for point in points:
if (thisfold[0] == 'x'):
if (point[0] > thisfold[1]):
checkpoint = [thisfold[1]-(point[0]-thisfold[1]),point[1]]
if (checkpoint not in newpoints):
newpoints.append(checkpoint)
elif (point not in newpoints):
newpoints.append(point)
else:
"Do Nothing"
else:
if (point[1] > thisfold[1]):
checkpoint = [point[0],thisfold[1]-(point[1]-thisfold[1])]
if (checkpoint not in newpoints):
newpoints.append(checkpoint)
elif (point not in newpoints):
newpoints.append(point)
else:
"Do Nothing"
points = newpoints
maxX = 0
maxY = 0
for point in points:
if (point[0] > maxX):
maxX = point[0]
if (point[1] > maxY):
maxY = point[1]
outstring = []
for y in range(maxY+1):
row = ''
for x in range(maxX+1):
if ([x,y] in points):
row += '#'
else:
row += '.'
outstring.append(row)
for row in outstring:
print(row)
|
file = open('Advent-of-Code-2021\\Day 13\\Day 13 input.txt')
points = []
folds = []
for line in file:
line = line.strip()
if line.find(',') != -1:
pointparse = line.split(',')
points.append([int(pointparse[0]), int(pointparse[1])])
elif line.find('=') != -1:
foldparse = line.split('=')
folds.append([foldparse[0][len(foldparse[0]) - 1], int(foldparse[1])])
else:
'Do nothing'
for thisfold in folds:
newpoints = []
for point in points:
if thisfold[0] == 'x':
if point[0] > thisfold[1]:
checkpoint = [thisfold[1] - (point[0] - thisfold[1]), point[1]]
if checkpoint not in newpoints:
newpoints.append(checkpoint)
elif point not in newpoints:
newpoints.append(point)
else:
'Do Nothing'
elif point[1] > thisfold[1]:
checkpoint = [point[0], thisfold[1] - (point[1] - thisfold[1])]
if checkpoint not in newpoints:
newpoints.append(checkpoint)
elif point not in newpoints:
newpoints.append(point)
else:
'Do Nothing'
points = newpoints
max_x = 0
max_y = 0
for point in points:
if point[0] > maxX:
max_x = point[0]
if point[1] > maxY:
max_y = point[1]
outstring = []
for y in range(maxY + 1):
row = ''
for x in range(maxX + 1):
if [x, y] in points:
row += '#'
else:
row += '.'
outstring.append(row)
for row in outstring:
print(row)
|
dummy1_iface_cfg = {
'INTERFACE': {
'MODULE': 'daq.interface.interface',
'CLASS': 'DummyInterface',
},
'IFCONFIG': {
'LABEL': 'Dummy1',
'ADDRESS': 'DummyAddress',
'SerialNumber': '1234',
}
}
dummycpc_inst_cfg = {
'INSTRUMENT': {
'MODULE': 'daq.instrument.instrument',
'CLASS': 'DummyInstrument',
},
'INSTCONFIG': {
'DESCRIPTION': {
'LABEL': 'DummyCPC',
'SERIAL_NUMBER': '0001',
'PROPERTY_NUMBER': 'CD0000001',
},
'IFACE_LIST': {
'DUMMY1': {
'IFACE_CONFIG': dummy1_iface_cfg,
'OPERATION': {
'POLLED': False,
'SAMPLE_FREQ_SEC': 1,
},
},
},
},
# could be IFACE_LIST to allow for multiple iface
}
dummy_controller_cfg = {
'CONTROLLER': {
'MODULE': 'daq.controller.controller',
'CLASS': 'Controller',
}
}
|
dummy1_iface_cfg = {'INTERFACE': {'MODULE': 'daq.interface.interface', 'CLASS': 'DummyInterface'}, 'IFCONFIG': {'LABEL': 'Dummy1', 'ADDRESS': 'DummyAddress', 'SerialNumber': '1234'}}
dummycpc_inst_cfg = {'INSTRUMENT': {'MODULE': 'daq.instrument.instrument', 'CLASS': 'DummyInstrument'}, 'INSTCONFIG': {'DESCRIPTION': {'LABEL': 'DummyCPC', 'SERIAL_NUMBER': '0001', 'PROPERTY_NUMBER': 'CD0000001'}, 'IFACE_LIST': {'DUMMY1': {'IFACE_CONFIG': dummy1_iface_cfg, 'OPERATION': {'POLLED': False, 'SAMPLE_FREQ_SEC': 1}}}}}
dummy_controller_cfg = {'CONTROLLER': {'MODULE': 'daq.controller.controller', 'CLASS': 'Controller'}}
|
print(dir(str))
nome = 'Flavio'
print(nome)
print(nome[:3])
texto = 'marca d\' agua'
print(texto)
texto = "marca d' agua"
print(texto)
texto = ''' texto
... texto
'''
print(texto)
texto = ' texto\n\t ...texto'
print(texto)
print(str.__add__('a', 'b'))
nome = 'Flavio Garcia Fernandes'
print(nome)
print(nome[-9:])
print(nome[::-1])
numeros = '0123456789'
print(numeros[1::2])
print(numeros[::2])
|
print(dir(str))
nome = 'Flavio'
print(nome)
print(nome[:3])
texto = "marca d' agua"
print(texto)
texto = "marca d' agua"
print(texto)
texto = ' texto\n ... texto\n'
print(texto)
texto = ' texto\n\t ...texto'
print(texto)
print(str.__add__('a', 'b'))
nome = 'Flavio Garcia Fernandes'
print(nome)
print(nome[-9:])
print(nome[::-1])
numeros = '0123456789'
print(numeros[1::2])
print(numeros[::2])
|
with open('in') as f:
data = list(map(lambda l: list(l.strip().replace(' ', '')), f.readlines()))
def evaluate(e):
value = None
operation = None
i = 0
while i < len(e):
c = e[i]
if c in '+*':
operation = c
elif c in '0123456789':
c = int(c)
if operation is None:
value = c
else:
if operation == '+':
value += c
else:
value *= c
elif c == '(':
tmp_e = []
i += 1
level = 1
while True:
if e[i] == '(':
level += 1
elif e[i] == ')':
level -= 1
if level == 0:
break
else:
tmp_e.append(e[i])
i += 1
b = evaluate(tmp_e)
if operation is None:
value = b
else:
if operation == '+':
value += b
else:
value *= b
else:
assert False
i += 1
return value
def evaluate_2(e):
i = 0
while i < len(e):
if e[i] == '+':
level = 0
index = -1
for j in range(i - 1, -1, -1):
if e[j] == ')':
level += 1
elif e[j] == '(':
level -= 1
if (level == 0 and e[j] in '+*') or (level < 0 and e[j] in '()'):
index = j
break
e.insert(index + 1, '(')
i += 1
level = 0
index = len(e)
for j in range(i + 1, len(e)):
if e[j] == '(':
level += 1
elif e[j] == ')':
level -= 1
if (level == 0 and e[j] in '+*') or (level < 0 and e[j] in '()'):
index = j
break
e.insert(index, ')')
i += 1
return evaluate(e)
def part_one():
return sum(map(evaluate, data))
def part_two():
return sum(map(evaluate_2, data))
if __name__ == '__main__':
print(f'Part One: {part_one()}')
print(f'Part Two: {part_two()}')
|
with open('in') as f:
data = list(map(lambda l: list(l.strip().replace(' ', '')), f.readlines()))
def evaluate(e):
value = None
operation = None
i = 0
while i < len(e):
c = e[i]
if c in '+*':
operation = c
elif c in '0123456789':
c = int(c)
if operation is None:
value = c
elif operation == '+':
value += c
else:
value *= c
elif c == '(':
tmp_e = []
i += 1
level = 1
while True:
if e[i] == '(':
level += 1
elif e[i] == ')':
level -= 1
if level == 0:
break
else:
tmp_e.append(e[i])
i += 1
b = evaluate(tmp_e)
if operation is None:
value = b
elif operation == '+':
value += b
else:
value *= b
else:
assert False
i += 1
return value
def evaluate_2(e):
i = 0
while i < len(e):
if e[i] == '+':
level = 0
index = -1
for j in range(i - 1, -1, -1):
if e[j] == ')':
level += 1
elif e[j] == '(':
level -= 1
if level == 0 and e[j] in '+*' or (level < 0 and e[j] in '()'):
index = j
break
e.insert(index + 1, '(')
i += 1
level = 0
index = len(e)
for j in range(i + 1, len(e)):
if e[j] == '(':
level += 1
elif e[j] == ')':
level -= 1
if level == 0 and e[j] in '+*' or (level < 0 and e[j] in '()'):
index = j
break
e.insert(index, ')')
i += 1
return evaluate(e)
def part_one():
return sum(map(evaluate, data))
def part_two():
return sum(map(evaluate_2, data))
if __name__ == '__main__':
print(f'Part One: {part_one()}')
print(f'Part Two: {part_two()}')
|
# just keep this as-is
def not_an_activity():
print("boom")
|
def not_an_activity():
print('boom')
|
label_data = open("label", encoding='utf-8').readlines()
label_data = [x.strip() for x in label_data]
print(len(label_data))
label_kinds = set(label_data)
print(label_kinds)
|
label_data = open('label', encoding='utf-8').readlines()
label_data = [x.strip() for x in label_data]
print(len(label_data))
label_kinds = set(label_data)
print(label_kinds)
|
class NotFoundError(Exception):
"""
Thrown during :meth:`get` when the requested object could not be found.
"""
pass
class ValidationError(Exception):
"""
Thrown by :class:`Field` subclasses when setting attributes that are
invalid.
"""
pass
|
class Notfounderror(Exception):
"""
Thrown during :meth:`get` when the requested object could not be found.
"""
pass
class Validationerror(Exception):
"""
Thrown by :class:`Field` subclasses when setting attributes that are
invalid.
"""
pass
|
def tupler(atuple):
print(f"{atuple=}")
return (1, 2, 3)
print(f"{type(tupler((10, 11)))=}")
|
def tupler(atuple):
print(f'atuple={atuple!r}')
return (1, 2, 3)
print(f'type(tupler((10, 11)))={type(tupler((10, 11)))!r}')
|
n1 = int (input())
s1 = set(map(int,input().split()))
n2 = int (input())
s2 = set(map(int,input().split()))
print(len(s1.intersection(s2)))
|
n1 = int(input())
s1 = set(map(int, input().split()))
n2 = int(input())
s2 = set(map(int, input().split()))
print(len(s1.intersection(s2)))
|
raio = int(input())
pi = 3.14159
volume = float(4.0 * pi * (raio* raio * raio) / 3)
print("VOLUME = %0.3f" %volume)
|
raio = int(input())
pi = 3.14159
volume = float(4.0 * pi * (raio * raio * raio) / 3)
print('VOLUME = %0.3f' % volume)
|
#!/usr/bin/env python
# encoding: utf-8
GRADES_FILENAME = 'grades.csv'
GRADING_SLASH_DELIMINATOR = '/'
SUBMISSIONS_FILENAME = 'Submissions'
GRADING_URL_EXTENSION = '&action=grading'
SUBMISSION_LISTING_DELIMINATOR = '-_submission_-'
GRADING_BLANK_GRADE = '-'
GRADING_HEADER_NAME = 'Name'
GRADING_HEADER_EMAIL = 'Email'
GRADING_HEADER_GRADE = 'Grade'
|
grades_filename = 'grades.csv'
grading_slash_deliminator = '/'
submissions_filename = 'Submissions'
grading_url_extension = '&action=grading'
submission_listing_deliminator = '-_submission_-'
grading_blank_grade = '-'
grading_header_name = 'Name'
grading_header_email = 'Email'
grading_header_grade = 'Grade'
|
#print("for loop")
#word = ["this", "is","roshan"]
# for w in word: print(w, len(w))
#give range of each word for w in range(len(word)): print(w, word[w])
#get odd or even
"""
for x in range(0,5):
x+=1
#print(x)
if x % 2 == 0:
print(f"{x}::Even No")
else:
print(f"{x}::Odd No")
print("PRime No's")
for n in range(1,10):
for x in range(2,n):
if n % x ==0:
print(f"{n} get by multiple of {x} and is divisible of {x}, So it is not a prime no")
break
else:
print(f"{n} is prime no")
"""
#Loop while for the printing numbers
def whileloop(x):
y=0
while(y<x):
print(y)
y=y+1
#print number using for loop
def forloop(x):
y=0
for i in range(y,x):
print(i)
#print even or odd based on the condition
def printodd(x):
y=0
for i in range(y,x):
if(i%2 != 0): continue
print("Even No: ",i)
for i in range(y,x):
if(i%2 == 0): continue
print("Odd No: ",i)
printodd(10)
#whileloop(10)
#forloop(10)
|
"""
for x in range(0,5):
x+=1
#print(x)
if x % 2 == 0:
print(f"{x}::Even No")
else:
print(f"{x}::Odd No")
print("PRime No's")
for n in range(1,10):
for x in range(2,n):
if n % x ==0:
print(f"{n} get by multiple of {x} and is divisible of {x}, So it is not a prime no")
break
else:
print(f"{n} is prime no")
"""
def whileloop(x):
y = 0
while y < x:
print(y)
y = y + 1
def forloop(x):
y = 0
for i in range(y, x):
print(i)
def printodd(x):
y = 0
for i in range(y, x):
if i % 2 != 0:
continue
print('Even No: ', i)
for i in range(y, x):
if i % 2 == 0:
continue
print('Odd No: ', i)
printodd(10)
|
# Time: O(n)
# Space: O(n)
class UnionFind(object):
def __init__(self, n):
self.set = range(n)
def find_set(self, x):
if self.set[x] != x:
self.set[x] = self.find_set(self.set[x]) # path compression.
return self.set[x]
def union_set(self, x, y):
x_root, y_root = map(self.find_set, (x, y))
if x_root == y_root:
return False
self.set[min(x_root, y_root)] = max(x_root, y_root)
return True
class Solution(object):
def removeStones(self, stones):
"""
:type stones: List[List[int]]
:rtype: int
"""
MAX_ROW = 10000
union_find = UnionFind(2*MAX_ROW)
for r, c in stones:
union_find.union_set(r, c+MAX_ROW)
return len(stones) - len({union_find.find_set(r) for r, _ in stones})
|
class Unionfind(object):
def __init__(self, n):
self.set = range(n)
def find_set(self, x):
if self.set[x] != x:
self.set[x] = self.find_set(self.set[x])
return self.set[x]
def union_set(self, x, y):
(x_root, y_root) = map(self.find_set, (x, y))
if x_root == y_root:
return False
self.set[min(x_root, y_root)] = max(x_root, y_root)
return True
class Solution(object):
def remove_stones(self, stones):
"""
:type stones: List[List[int]]
:rtype: int
"""
max_row = 10000
union_find = union_find(2 * MAX_ROW)
for (r, c) in stones:
union_find.union_set(r, c + MAX_ROW)
return len(stones) - len({union_find.find_set(r) for (r, _) in stones})
|
# IP and port to bind to.
bind = ['127.0.0.1:4000']
# Maximum number of pending connections.
backlog = 2048
# Number of worker processes to handle connections.
workers = 2
# Fork main process to background.
daemon = True
# PID file to write to.
pidfile = "web.gunicorn.pid"
# Allow connections from any frontend proxy.
# forwarded_allow_ips = '*'
# Logging configuration.
accesslog = "web.gunicorn.access.log"
errorlog = "web.gunicorn.error.log"
loglevel = "warning"
# Gunicorn process name.
proc_name = "rouly.net-gunicorn"
|
bind = ['127.0.0.1:4000']
backlog = 2048
workers = 2
daemon = True
pidfile = 'web.gunicorn.pid'
accesslog = 'web.gunicorn.access.log'
errorlog = 'web.gunicorn.error.log'
loglevel = 'warning'
proc_name = 'rouly.net-gunicorn'
|
i = 0
while(True):
if i+1<5:
i = i + 1
continue
print(i+1, end=" ")
if(i==50):
break #stop the loop
i = i+ 1
|
i = 0
while True:
if i + 1 < 5:
i = i + 1
continue
print(i + 1, end=' ')
if i == 50:
break
i = i + 1
|
#https://leetcode.com/problems/min-stack/
class MinStack(object):
def __init__(self):
self.stack = []
def push(self, x):
self.stack.append((x, min(x, self.getMin())))
def pop(self):
if len(self.stack)==0: return None
return self.stack.pop()[0]
def top(self):
if len(self.stack)==0: return None
return self.stack[-1][0]
def getMin(self):
if len(self.stack)==0: return float('inf')
return self.stack[-1][1]
# Your MinStack object will be instantiated and called as such:
# obj = MinStack()
# obj.push(x)
# obj.pop()
# param_3 = obj.top()
# param_4 = obj.getMin()
|
class Minstack(object):
def __init__(self):
self.stack = []
def push(self, x):
self.stack.append((x, min(x, self.getMin())))
def pop(self):
if len(self.stack) == 0:
return None
return self.stack.pop()[0]
def top(self):
if len(self.stack) == 0:
return None
return self.stack[-1][0]
def get_min(self):
if len(self.stack) == 0:
return float('inf')
return self.stack[-1][1]
|
# -*- coding: utf-8 -*-
"""
flybirds common error
"""
class FlybirdNotFoundException(Exception):
"""
not find flybirds
"""
def __init__(self, message, select_dic, error=None):
message = f"selectors={str(select_dic)} {message}"
if error is not None:
message = f"{message} innerErr:{error}"
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class PositionNotChangeException(Exception):
"""
position not change
"""
def __init__(self, message):
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class FlybirdCallMethodParamsException(Exception):
"""
params error
"""
def __init__(self, method, param_name):
message = f"call method:{method} has invalid params:{param_name}"
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class FlybirdEleExistsException(Exception):
"""
ele not exists
"""
def __init__(self, message):
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class FlybirdVerifyException(Exception):
"""
verify error
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
class FlybirdPositionChanging(Exception):
"""
position changing
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
class ScreenRecordException(Exception):
"""
screen record error
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
|
"""
flybirds common error
"""
class Flybirdnotfoundexception(Exception):
"""
not find flybirds
"""
def __init__(self, message, select_dic, error=None):
message = f'selectors={str(select_dic)} {message}'
if error is not None:
message = f'{message} innerErr:{error}'
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class Positionnotchangeexception(Exception):
"""
position not change
"""
def __init__(self, message):
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class Flybirdcallmethodparamsexception(Exception):
"""
params error
"""
def __init__(self, method, param_name):
message = f'call method:{method} has invalid params:{param_name}'
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class Flybirdeleexistsexception(Exception):
"""
ele not exists
"""
def __init__(self, message):
super().__init__(message)
self.message = message
def __str__(self):
return str(self.message)
class Flybirdverifyexception(Exception):
"""
verify error
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
class Flybirdpositionchanging(Exception):
"""
position changing
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
class Screenrecordexception(Exception):
"""
screen record error
"""
def __init__(self, message):
super().__init__()
self.message = message
def __str__(self):
return str(self.message)
|
class RaggedContiguous:
"""Mixin class for an underlying compressed ragged array.
.. versionadded:: (cfdm) 1.7.0
"""
def get_count(self, default=ValueError()):
"""Return the count variable for a compressed array.
.. versionadded:: (cfdm) 1.7.0
:Parameters:
default: optional
Return the value of the *default* parameter if the
count variable has not been set.
{{default Exception}}
:Returns:
The count variable.
**Examples:**
>>> c = d.get_count()
"""
out = self._get_component("count_variable", None)
if out is None:
return self._default(
default, f"{self.__class__.__name__!r} has no count variable"
)
return out
|
class Raggedcontiguous:
"""Mixin class for an underlying compressed ragged array.
.. versionadded:: (cfdm) 1.7.0
"""
def get_count(self, default=value_error()):
"""Return the count variable for a compressed array.
.. versionadded:: (cfdm) 1.7.0
:Parameters:
default: optional
Return the value of the *default* parameter if the
count variable has not been set.
{{default Exception}}
:Returns:
The count variable.
**Examples:**
>>> c = d.get_count()
"""
out = self._get_component('count_variable', None)
if out is None:
return self._default(default, f'{self.__class__.__name__!r} has no count variable')
return out
|
## This module deals with code regarding handling the double
## underscore separated keys
def dunderkey(*args):
"""Produces a nested key from multiple args separated by double
underscore
>>> dunderkey('a', 'b', 'c')
>>> 'a__b__c'
:param *args : *String
:rtype : String
"""
return '__'.join(args)
def dunder_partition(key):
"""Splits a dunderkey into 2 parts
The first part is everything before the final double underscore
The second part is after the final double underscore
>>> dunder_partition('a__b__c')
>>> ('a__b', 'c')
:param neskey : String
:rtype : 2 Tuple
"""
parts = key.rsplit('__', 1)
return tuple(parts) if len(parts) > 1 else (parts[0], None)
def dunder_init(key):
"""Returns the initial part of the dunder key
>>> dunder_init('a__b__c')
>>> 'a__b'
:param neskey : String
:rtype : String
"""
return dunder_partition(key)[0]
def dunder_last(key):
"""Returns the last part of the dunder key
>>> dunder_last('a__b__c')
>>> 'c'
:param neskey : String
:rtype : String
"""
return dunder_partition(key)[1]
def dunder_get(_dict, key):
"""Returns value for a specified dunderkey
A "dunderkey" is just a fieldname that may or may not contain
double underscores (dunderscores!) for referrencing nested keys in
a dict. eg::
>>> data = {'a': {'b': 1}}
>>> nesget(data, 'a__b')
1
key 'b' can be referrenced as 'a__b'
:param _dict : (dict)
:param key : (str) that represents a first level or nested key in the dict
:rtype : (mixed) value corresponding to the key
"""
parts = key.split('__', 1)
key = parts[0]
try:
result = _dict[key]
except KeyError:
return None
except TypeError:
try:
result = getattr(_dict, key)
except AttributeError:
return None
return result if len(parts) == 1 else dunder_get(result, parts[1])
def undunder_keys(_dict):
"""Returns dict with the dunder keys converted back to nested dicts
eg::
>>> undunder_keys({'a': 'hello', 'b__c': 'world'})
{'a': 'hello', 'b': {'c': 'world'}}
:param _dict : (dict) flat dict
:rtype : (dict) nested dict
"""
def f(key, value):
parts = key.split('__')
return {
parts[0]: value if len(parts) == 1 else f(parts[1], value)
}
result = {}
for r in [f(k, v) for k, v in _dict.items()]:
rk = list(r.keys())[0]
if rk not in result:
result.update(r)
else:
result[rk].update(r[rk])
return result
def dunder_truncate(_dict):
"""Returns dict with dunder keys truncated to only the last part
In other words, replaces the dunder keys with just last part of
it. In case many identical last parts are encountered, they are
not truncated further
eg::
>>> dunder_truncate({'a__p': 3, 'b__c': 'no'})
{'c': 'no', 'p': 3}
>>> dunder_truncate({'a__p': 'yay', 'b__p': 'no', 'c__z': 'dunno'})
{'a__p': 'yay', 'b__p': 'no', 'z': 'dunno'}
:param _dict : (dict) to flatten
:rtype : (dict) flattened result
"""
keylist = list(_dict.keys())
def decide_key(k, klist):
newkey = dunder_last(k)
return newkey if list(map(dunder_last, klist)).count(newkey) == 1 else k
original_keys = [decide_key(key, keylist) for key in keylist]
return dict(zip(original_keys, _dict.values()))
|
def dunderkey(*args):
"""Produces a nested key from multiple args separated by double
underscore
>>> dunderkey('a', 'b', 'c')
>>> 'a__b__c'
:param *args : *String
:rtype : String
"""
return '__'.join(args)
def dunder_partition(key):
"""Splits a dunderkey into 2 parts
The first part is everything before the final double underscore
The second part is after the final double underscore
>>> dunder_partition('a__b__c')
>>> ('a__b', 'c')
:param neskey : String
:rtype : 2 Tuple
"""
parts = key.rsplit('__', 1)
return tuple(parts) if len(parts) > 1 else (parts[0], None)
def dunder_init(key):
"""Returns the initial part of the dunder key
>>> dunder_init('a__b__c')
>>> 'a__b'
:param neskey : String
:rtype : String
"""
return dunder_partition(key)[0]
def dunder_last(key):
"""Returns the last part of the dunder key
>>> dunder_last('a__b__c')
>>> 'c'
:param neskey : String
:rtype : String
"""
return dunder_partition(key)[1]
def dunder_get(_dict, key):
"""Returns value for a specified dunderkey
A "dunderkey" is just a fieldname that may or may not contain
double underscores (dunderscores!) for referrencing nested keys in
a dict. eg::
>>> data = {'a': {'b': 1}}
>>> nesget(data, 'a__b')
1
key 'b' can be referrenced as 'a__b'
:param _dict : (dict)
:param key : (str) that represents a first level or nested key in the dict
:rtype : (mixed) value corresponding to the key
"""
parts = key.split('__', 1)
key = parts[0]
try:
result = _dict[key]
except KeyError:
return None
except TypeError:
try:
result = getattr(_dict, key)
except AttributeError:
return None
return result if len(parts) == 1 else dunder_get(result, parts[1])
def undunder_keys(_dict):
"""Returns dict with the dunder keys converted back to nested dicts
eg::
>>> undunder_keys({'a': 'hello', 'b__c': 'world'})
{'a': 'hello', 'b': {'c': 'world'}}
:param _dict : (dict) flat dict
:rtype : (dict) nested dict
"""
def f(key, value):
parts = key.split('__')
return {parts[0]: value if len(parts) == 1 else f(parts[1], value)}
result = {}
for r in [f(k, v) for (k, v) in _dict.items()]:
rk = list(r.keys())[0]
if rk not in result:
result.update(r)
else:
result[rk].update(r[rk])
return result
def dunder_truncate(_dict):
"""Returns dict with dunder keys truncated to only the last part
In other words, replaces the dunder keys with just last part of
it. In case many identical last parts are encountered, they are
not truncated further
eg::
>>> dunder_truncate({'a__p': 3, 'b__c': 'no'})
{'c': 'no', 'p': 3}
>>> dunder_truncate({'a__p': 'yay', 'b__p': 'no', 'c__z': 'dunno'})
{'a__p': 'yay', 'b__p': 'no', 'z': 'dunno'}
:param _dict : (dict) to flatten
:rtype : (dict) flattened result
"""
keylist = list(_dict.keys())
def decide_key(k, klist):
newkey = dunder_last(k)
return newkey if list(map(dunder_last, klist)).count(newkey) == 1 else k
original_keys = [decide_key(key, keylist) for key in keylist]
return dict(zip(original_keys, _dict.values()))
|
def insert_newlines(string, every=64):
return '\n'.join(string[i:i+every] for i in range(0, len(string), every))
for __ in range(int(input())):
n = int(input())
o = "O"
x = "X"
a = ["X" for i in range(64)]
for i in range(n):
a[i] = "."
a[0]=o
print(insert_newlines("".join(a),8))
|
def insert_newlines(string, every=64):
return '\n'.join((string[i:i + every] for i in range(0, len(string), every)))
for __ in range(int(input())):
n = int(input())
o = 'O'
x = 'X'
a = ['X' for i in range(64)]
for i in range(n):
a[i] = '.'
a[0] = o
print(insert_newlines(''.join(a), 8))
|
## Set Configs
print('Set configs..')
sns.set()
pd.options.display.max_columns = None
RANDOM_SEED = 42
fig_path = os.path.join(os.getcwd(), 'figs')
model_path = os.path.join(os.getcwd(), 'models')
model_bib_path = os.path.join(model_path,'model_bib')
data_path = os.path.join(os.getcwd(), 'data')
## read the data
print('Read the data..')
data_fn = os.path.join(data_path, 'simulation_data_y_2020_2021_reduced.h5')
df_data = pd.read_hdf(data_fn, key='df')
print('Shape of normal data (X_sim): {}'.format(df_data.shape))
data_fn_anormal = os.path.join(data_path, 'anomalous_data_y_2022_reduced.h5')
df_data_anormal = pd.read_hdf(data_fn_anormal, key='df')
print('Shape of anormal data (X_test): {}'.format(df_data_anormal.shape))
data_fn_drifted = os.path.join(data_path, 'drifted_data_y_2023_reduced_more_cos_phi.h5')
df_data_drifted = pd.read_hdf(data_fn_drifted, key='df')
print('Shape of drifted data (X_drifted): {}'.format(df_data_drifted.shape))
data_fn_drifted_anormal = os.path.join(data_path, 'anomalous_drifted_data_y_2023_reduced_more_cos_phi.h5')
df_data_drifted_anormal = pd.read_hdf(data_fn_drifted_anormal, key='df')
print('Shape of drifted anormal data (X_drifted,anormal): {}'.format(df_data_drifted_anormal.shape))
## save label
print('Save label..')
s_labels = df_data_anormal['label']
df_data_anormal.drop('label', axis=1, inplace=True)
print('Shape of anormal data (X_test): {}'.format(df_data_anormal.shape))
s_drift_labels = df_data_drifted['drift_labels']
df_data_drifted.drop('drift_labels',axis=1,inplace=True)
print('Shape of drifted data (X_drifted): {}'.format(df_data_drifted.shape))
s_drift_labels_drifted_ano = df_data_drifted_anormal['drift_labels']
df_data_drifted_anormal.drop('drift_labels', axis=1, inplace=True)
s_ano_labels_drifted_ano = df_data_drifted_anormal['anomaly_labels']
df_data_drifted_anormal.drop('anomaly_labels', axis=1, inplace=True)
print('Shape of drifted anormal data (X_drifted,anormal): {}'.format(df_data_drifted_anormal.shape))
### Scale data
print('Scale data..')
scaler_train = MinMaxScaler((-1,1))
scaler_train = scaler_train.fit(df_data)
scaled_anormal = scaler_train.transform(df_data_anormal.to_numpy())
scaled_normal = scaler_train.transform(df_data.to_numpy())
scaled_drifted = scaler_train.transform(df_data_drifted.to_numpy())
scaled_drifted_anormal = scaler_train.transform(df_data_drifted_anormal.to_numpy())
## prepare for PyTorch
print('Prepare data for PyTorch..')
# build tensor from numpy
anormal_torch_tensor = torch.from_numpy(scaled_anormal).type(torch.FloatTensor)
normal_torch_tensor = torch.from_numpy(scaled_normal).type(torch.FloatTensor)
drifted_torch_tensor = torch.from_numpy(scaled_drifted).type(torch.FloatTensor)
drifted_anormal_torch_tensor = torch.from_numpy(scaled_drifted_anormal).type(torch.FloatTensor)
# build TensorDataset from Tensor
anormal_dataset = TensorDataset(anormal_torch_tensor, anormal_torch_tensor)
normal_dataset = TensorDataset(normal_torch_tensor, normal_torch_tensor)
drifted_dataset = TensorDataset(drifted_torch_tensor, drifted_torch_tensor)
drifted_anormal_dataset = TensorDataset(drifted_anormal_torch_tensor, drifted_anormal_torch_tensor)
# build DataLoader from TensorDataset
anormal_dataloader = torch.utils.data.DataLoader(anormal_dataset,batch_size=128,shuffle=False, num_workers=0)
normal_dataloader = torch.utils.data.DataLoader(normal_dataset,batch_size=128,shuffle=False, num_workers=0)
drifted_dataloader = torch.utils.data.DataLoader(drifted_dataset,batch_size=128,shuffle=False, num_workers=0)
drifted_anormal_dataloader = torch.utils.data.DataLoader(drifted_anormal_dataset, batch_size=128, shuffle=False, num_workers=0)
|
print('Set configs..')
sns.set()
pd.options.display.max_columns = None
random_seed = 42
fig_path = os.path.join(os.getcwd(), 'figs')
model_path = os.path.join(os.getcwd(), 'models')
model_bib_path = os.path.join(model_path, 'model_bib')
data_path = os.path.join(os.getcwd(), 'data')
print('Read the data..')
data_fn = os.path.join(data_path, 'simulation_data_y_2020_2021_reduced.h5')
df_data = pd.read_hdf(data_fn, key='df')
print('Shape of normal data (X_sim): {}'.format(df_data.shape))
data_fn_anormal = os.path.join(data_path, 'anomalous_data_y_2022_reduced.h5')
df_data_anormal = pd.read_hdf(data_fn_anormal, key='df')
print('Shape of anormal data (X_test): {}'.format(df_data_anormal.shape))
data_fn_drifted = os.path.join(data_path, 'drifted_data_y_2023_reduced_more_cos_phi.h5')
df_data_drifted = pd.read_hdf(data_fn_drifted, key='df')
print('Shape of drifted data (X_drifted): {}'.format(df_data_drifted.shape))
data_fn_drifted_anormal = os.path.join(data_path, 'anomalous_drifted_data_y_2023_reduced_more_cos_phi.h5')
df_data_drifted_anormal = pd.read_hdf(data_fn_drifted_anormal, key='df')
print('Shape of drifted anormal data (X_drifted,anormal): {}'.format(df_data_drifted_anormal.shape))
print('Save label..')
s_labels = df_data_anormal['label']
df_data_anormal.drop('label', axis=1, inplace=True)
print('Shape of anormal data (X_test): {}'.format(df_data_anormal.shape))
s_drift_labels = df_data_drifted['drift_labels']
df_data_drifted.drop('drift_labels', axis=1, inplace=True)
print('Shape of drifted data (X_drifted): {}'.format(df_data_drifted.shape))
s_drift_labels_drifted_ano = df_data_drifted_anormal['drift_labels']
df_data_drifted_anormal.drop('drift_labels', axis=1, inplace=True)
s_ano_labels_drifted_ano = df_data_drifted_anormal['anomaly_labels']
df_data_drifted_anormal.drop('anomaly_labels', axis=1, inplace=True)
print('Shape of drifted anormal data (X_drifted,anormal): {}'.format(df_data_drifted_anormal.shape))
print('Scale data..')
scaler_train = min_max_scaler((-1, 1))
scaler_train = scaler_train.fit(df_data)
scaled_anormal = scaler_train.transform(df_data_anormal.to_numpy())
scaled_normal = scaler_train.transform(df_data.to_numpy())
scaled_drifted = scaler_train.transform(df_data_drifted.to_numpy())
scaled_drifted_anormal = scaler_train.transform(df_data_drifted_anormal.to_numpy())
print('Prepare data for PyTorch..')
anormal_torch_tensor = torch.from_numpy(scaled_anormal).type(torch.FloatTensor)
normal_torch_tensor = torch.from_numpy(scaled_normal).type(torch.FloatTensor)
drifted_torch_tensor = torch.from_numpy(scaled_drifted).type(torch.FloatTensor)
drifted_anormal_torch_tensor = torch.from_numpy(scaled_drifted_anormal).type(torch.FloatTensor)
anormal_dataset = tensor_dataset(anormal_torch_tensor, anormal_torch_tensor)
normal_dataset = tensor_dataset(normal_torch_tensor, normal_torch_tensor)
drifted_dataset = tensor_dataset(drifted_torch_tensor, drifted_torch_tensor)
drifted_anormal_dataset = tensor_dataset(drifted_anormal_torch_tensor, drifted_anormal_torch_tensor)
anormal_dataloader = torch.utils.data.DataLoader(anormal_dataset, batch_size=128, shuffle=False, num_workers=0)
normal_dataloader = torch.utils.data.DataLoader(normal_dataset, batch_size=128, shuffle=False, num_workers=0)
drifted_dataloader = torch.utils.data.DataLoader(drifted_dataset, batch_size=128, shuffle=False, num_workers=0)
drifted_anormal_dataloader = torch.utils.data.DataLoader(drifted_anormal_dataset, batch_size=128, shuffle=False, num_workers=0)
|
a = [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
# dumb way
# for i in range(0,len(a),1):
# if a[i]%2 == 0:
# print(str(a[i]),end=" ")
b = [i for i in a if i % 2 == 0]
print(b)
|
a = [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
b = [i for i in a if i % 2 == 0]
print(b)
|
'''
Roman numerals are represented by seven different symbols: I, V, X, L, C, D and M.
Symbol Value
I 1
V 5
X 10
L 50
C 100
D 500
M 1000
For example, 2 is written as II in Roman numeral, just two one's added together. 12 is written as XII, which is simply X + II. The number 27 is written as XXVII, which is XX + V + II.
Roman numerals are usually written largest to smallest from left to right. However, the numeral for four is not IIII. Instead, the number four is written as IV. Because the one is before the five we subtract it making four. The same principle applies to the number nine, which is written as IX. There are six instances where subtraction is used:
I can be placed before V (5) and X (10) to make 4 and 9.
X can be placed before L (50) and C (100) to make 40 and 90.
C can be placed before D (500) and M (1000) to make 400 and 900.
Given a roman numeral, convert it to an integer.
'''
class Solution:
def romanToInt(self, s: str) -> int:
roman = {'I' : 1,
'V' : 5,
'X' : 10,
'L' : 50,
'C' : 100,
'D' : 500,
'M' : 1000 }
ans = 0
for i in range(len(s)):
if i < len(s) - 1 and roman[s[i]] < roman[s[i + 1]]:
ans -= roman[s[i]]
else:
ans += roman[s[i]]
return ans
|
"""
Roman numerals are represented by seven different symbols: I, V, X, L, C, D and M.
Symbol Value
I 1
V 5
X 10
L 50
C 100
D 500
M 1000
For example, 2 is written as II in Roman numeral, just two one's added together. 12 is written as XII, which is simply X + II. The number 27 is written as XXVII, which is XX + V + II.
Roman numerals are usually written largest to smallest from left to right. However, the numeral for four is not IIII. Instead, the number four is written as IV. Because the one is before the five we subtract it making four. The same principle applies to the number nine, which is written as IX. There are six instances where subtraction is used:
I can be placed before V (5) and X (10) to make 4 and 9.
X can be placed before L (50) and C (100) to make 40 and 90.
C can be placed before D (500) and M (1000) to make 400 and 900.
Given a roman numeral, convert it to an integer.
"""
class Solution:
def roman_to_int(self, s: str) -> int:
roman = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
ans = 0
for i in range(len(s)):
if i < len(s) - 1 and roman[s[i]] < roman[s[i + 1]]:
ans -= roman[s[i]]
else:
ans += roman[s[i]]
return ans
|
# https://www.codewars.com/kata/55a243393fb3e87021000198/train/python
# My solution
def remember(text):
counter = {}
result = []
for ch in text:
counter[ch] = counter.get(ch, 0) + 1
if counter[ch] == 2:
result.append(ch)
return result
# ...
def remember(str_):
seen = set()
res = []
for i in str_:
res.append(i) if i in seen and i not in res else seen.add(i)
return res
|
def remember(text):
counter = {}
result = []
for ch in text:
counter[ch] = counter.get(ch, 0) + 1
if counter[ch] == 2:
result.append(ch)
return result
def remember(str_):
seen = set()
res = []
for i in str_:
res.append(i) if i in seen and i not in res else seen.add(i)
return res
|
directory_map = {
"abilene": "directed-abilene-zhang-5min-over-6months-ALL",
"geant": "directed-geant-uhlig-15min-over-4months-ALL",
"germany50": "directed-germany50-DFN-aggregated-1day-over-1month",
}
|
directory_map = {'abilene': 'directed-abilene-zhang-5min-over-6months-ALL', 'geant': 'directed-geant-uhlig-15min-over-4months-ALL', 'germany50': 'directed-germany50-DFN-aggregated-1day-over-1month'}
|
class Math1():
def __init__(self):
self.my_num1 = 10
self.my_num2 = 20
def addition(self):
return self.my_num1 + self.my_num2
def subtraction(self):
return self.my_num1 - self.my_num2
class Math_Plus(Math1):
def __init__(self, my_num1=40, my_num2=90):
self.my_num1 = my_num1
self.my_num2 = my_num2
def multiplication(self):
return self.my_num1 * self.my_num2
def division(self):
return self.my_num1 / self.my_num2
if __name__ == "__main__":
math1 = Math1()
print(math1.addition()) #30
print(math1.subtraction()) #-10
math_plus = Math_Plus()
print(math_plus.addition()) #130
print(math_plus.subtraction()) #-50
print(math_plus.multiplication()) #3600
print(math_plus.division()) #0.-44444444
|
class Math1:
def __init__(self):
self.my_num1 = 10
self.my_num2 = 20
def addition(self):
return self.my_num1 + self.my_num2
def subtraction(self):
return self.my_num1 - self.my_num2
class Math_Plus(Math1):
def __init__(self, my_num1=40, my_num2=90):
self.my_num1 = my_num1
self.my_num2 = my_num2
def multiplication(self):
return self.my_num1 * self.my_num2
def division(self):
return self.my_num1 / self.my_num2
if __name__ == '__main__':
math1 = math1()
print(math1.addition())
print(math1.subtraction())
math_plus = math__plus()
print(math_plus.addition())
print(math_plus.subtraction())
print(math_plus.multiplication())
print(math_plus.division())
|
# single source of truth for package version,
# see https://packaging.python.org/en/latest/single_source_version/
__version__ = "0.6.0"
# app name to send as part of SDK requests
app_name = "DLHub CLI v{}".format(__version__)
|
__version__ = '0.6.0'
app_name = 'DLHub CLI v{}'.format(__version__)
|
# coding: utf8
# try something like
def index(): return plugin_flatpage()
def rfp(): return plugin_flatpage()
|
def index():
return plugin_flatpage()
def rfp():
return plugin_flatpage()
|
"""
MicroPython driver for MLX90615 IR temperature I2C sensor :
https://github.com/rcolistete/MicroPython_MLX90615_driver
Version with simple read functions : 0.2.1 @ 2020/05/05
Author: Roberto Colistete Jr. (roberto.colistete at gmail.com)
License: MIT License (https://opensource.org/licenses/MIT)
"""
__version__ = '0.2.1'
MLX90615_I2C_DEFAULT_ADDR = const(0x5B)
_REG_ID_LOW = const(0x1E) # EEPROM register - ID number low
_REG_ID_HIGH = const(0x1F) # EEPROM register - ID number high
_REG_AMBIENT_TEMP = const(0x26) # RAM register - ambient temperature register
_REG_OBJECT_TEMP = const(0x27) # RAM register - object temperature register
class MLX90615:
def __init__(self, i2c, address=MLX90615_I2C_DEFAULT_ADDR):
self.i2c = i2c
self.address = address
self.buf = bytearray(3)
def _crc8(self, icrc, data):
crc = icrc ^ data
for _ in range(8):
crc <<= 1
if crc & 0x0100:
crc ^= 0x07
crc &= 0xFF
return crc
def read16(self, register, crc_check=True):
self.i2c.readfrom_mem_into(self.address, register, self.buf)
lsb = self.buf[0]
msb = self.buf[1]
pec = self.buf[2]
crc = 0
if crc_check:
crc = self._crc8(crc, self.address << 1)
crc = self._crc8(crc, register)
crc = self._crc8(crc, (self.address << 1) + 1)
crc = self._crc8(crc, lsb)
crc = self._crc8(crc, msb)
if (not crc_check) or (pec == crc):
return lsb | (msb << 8)
else:
raise Exception("PEC != CRC8 error in reading register {:02x}.".format(register))
def read_ambient_temp(self, pec_check=True):
try:
t = self.read16(_REG_AMBIENT_TEMP, crc_check=pec_check)
except Exception as err:
raise Exception("Error reading ambient temperature.\n{}".format(err))
else:
if (t > 0x7FFF):
raise Exception("Invalid ambient temperature error.")
else:
return t*2 - 27315
def read_object_temp(self, pec_check=True):
try:
t = self.read16(_REG_OBJECT_TEMP, crc_check=pec_check)
except Exception as err:
raise Exception("Error reading object temperature.\n{}".format(err))
else:
if (t > 0x7FFF):
raise Exception("Invalid object temperature error.")
else:
return t*2 - 27315
def read_id(self, pec_check=True):
try:
return self.read16(_REG_ID_LOW, crc_check=pec_check) | (self.read16(_REG_ID_HIGH, crc_check=pec_check) << 16)
except Exception as err:
raise Exception("Error reading sensor ID.\n{}".format(err))
def read_eeprom(self, pec_check=True):
eeprom_data = [0]*0x10
for register in range(0x10, 0x20):
try:
eeprom_data[register - 0x10] = self.read16(register, crc_check=pec_check)
except Exception as err:
raise Exception("Error reading EEPROM.\n{}".format(err))
return eeprom_data
|
"""
MicroPython driver for MLX90615 IR temperature I2C sensor :
https://github.com/rcolistete/MicroPython_MLX90615_driver
Version with simple read functions : 0.2.1 @ 2020/05/05
Author: Roberto Colistete Jr. (roberto.colistete at gmail.com)
License: MIT License (https://opensource.org/licenses/MIT)
"""
__version__ = '0.2.1'
mlx90615_i2_c_default_addr = const(91)
_reg_id_low = const(30)
_reg_id_high = const(31)
_reg_ambient_temp = const(38)
_reg_object_temp = const(39)
class Mlx90615:
def __init__(self, i2c, address=MLX90615_I2C_DEFAULT_ADDR):
self.i2c = i2c
self.address = address
self.buf = bytearray(3)
def _crc8(self, icrc, data):
crc = icrc ^ data
for _ in range(8):
crc <<= 1
if crc & 256:
crc ^= 7
crc &= 255
return crc
def read16(self, register, crc_check=True):
self.i2c.readfrom_mem_into(self.address, register, self.buf)
lsb = self.buf[0]
msb = self.buf[1]
pec = self.buf[2]
crc = 0
if crc_check:
crc = self._crc8(crc, self.address << 1)
crc = self._crc8(crc, register)
crc = self._crc8(crc, (self.address << 1) + 1)
crc = self._crc8(crc, lsb)
crc = self._crc8(crc, msb)
if not crc_check or pec == crc:
return lsb | msb << 8
else:
raise exception('PEC != CRC8 error in reading register {:02x}.'.format(register))
def read_ambient_temp(self, pec_check=True):
try:
t = self.read16(_REG_AMBIENT_TEMP, crc_check=pec_check)
except Exception as err:
raise exception('Error reading ambient temperature.\n{}'.format(err))
else:
if t > 32767:
raise exception('Invalid ambient temperature error.')
else:
return t * 2 - 27315
def read_object_temp(self, pec_check=True):
try:
t = self.read16(_REG_OBJECT_TEMP, crc_check=pec_check)
except Exception as err:
raise exception('Error reading object temperature.\n{}'.format(err))
else:
if t > 32767:
raise exception('Invalid object temperature error.')
else:
return t * 2 - 27315
def read_id(self, pec_check=True):
try:
return self.read16(_REG_ID_LOW, crc_check=pec_check) | self.read16(_REG_ID_HIGH, crc_check=pec_check) << 16
except Exception as err:
raise exception('Error reading sensor ID.\n{}'.format(err))
def read_eeprom(self, pec_check=True):
eeprom_data = [0] * 16
for register in range(16, 32):
try:
eeprom_data[register - 16] = self.read16(register, crc_check=pec_check)
except Exception as err:
raise exception('Error reading EEPROM.\n{}'.format(err))
return eeprom_data
|
# -*- coding: utf-8 -*-
"""Contains version information"""
__version__ = "0.7.9"
|
"""Contains version information"""
__version__ = '0.7.9'
|
'''
PyTorch implementation of the RetinaNet object detector:
Lin, Tsung-Yi, et al. "Focal loss for dense object detection." Proceedings of the IEEE international conference on computer vision. 2017.
Basic implementation forked and adapted from: https://github.com/kuangliu/pytorch-retinanet
2019 Benjamin Kellenberger
'''
# default options for the model, may be overridden in the custom configuration loaded at runtime
DEFAULT_OPTIONS = {
"general": {
"image_size": [800, 600],
"device": "cuda",
"seed": 1234
},
"model": {
"kwargs": {
"backbone": "resnet50",
"pretrained": False,
"out_planes": 256,
"convertToInstanceNorm": False
}
},
"train": {
"dataLoader": {
"kwargs": {
"shuffle": True,
"batch_size": 32
}
},
"optim": {
"class": "torch.optim.Adam",
"kwargs": {
"lr": 1e-7,
"weight_decay": 0.0
}
},
"transform": {
"class": "ai.models.pytorch.boundingBoxes.Compose",
"kwargs": {
"transforms": [{
"class": "ai.models.pytorch.boundingBoxes.Resize",
"kwargs": {
"size": [800, 600]
}
},
{
"class": "ai.models.pytorch.boundingBoxes.RandomHorizontalFlip",
"kwargs": {
"p": 0.5
}
},
{
"class": "ai.models.pytorch.boundingBoxes.DefaultTransform",
"kwargs": {
"transform": {
"class": "torchvision.transforms.ColorJitter",
"kwargs": {
"brightness": 0.25,
"contrast": 0.25,
"saturation": 0.25,
"hue": 0.01
}
}
}
},
{
"class": "ai.models.pytorch.boundingBoxes.DefaultTransform",
"kwargs": {
"transform": {
"class": "torchvision.transforms.ToTensor"
}
}
},
{
"class": "ai.models.pytorch.boundingBoxes.DefaultTransform",
"kwargs": {
"transform": {
"class": "torchvision.transforms.Normalize",
"kwargs": {
"mean": [0.485, 0.456, 0.406],
"std": [0.229, 0.224, 0.225]
}
}
}
}
]
}
},
"criterion": {
"class": "ai.models.pytorch.functional._retinanet.loss.FocalLoss",
"kwargs": {
"gamma": 2.0,
"alpha": 0.25,
"background_weight": 1.0
}
},
"ignore_unsure": True
},
"inference": {
"transform": {
"class": "ai.models.pytorch.boundingBoxes.Compose",
"kwargs": {
"transforms": [{
"class": "ai.models.pytorch.boundingBoxes.Resize",
"kwargs": {
"size": [800, 600]
}
},
{
"class": "ai.models.pytorch.boundingBoxes.DefaultTransform",
"kwargs": {
"transform": {
"class": "torchvision.transforms.ToTensor"
}
}
},
{
"class": "ai.models.pytorch.boundingBoxes.DefaultTransform",
"kwargs": {
"transform": {
"class": "torchvision.transforms.Normalize",
"kwargs": {
"mean": [0.485, 0.456, 0.406],
"std": [0.229, 0.224, 0.225]
}
}
}
}
]
}
},
"dataLoader": {
"kwargs": {
"shuffle": False,
"batch_size": 32
}
}
}
}
|
"""
PyTorch implementation of the RetinaNet object detector:
Lin, Tsung-Yi, et al. "Focal loss for dense object detection." Proceedings of the IEEE international conference on computer vision. 2017.
Basic implementation forked and adapted from: https://github.com/kuangliu/pytorch-retinanet
2019 Benjamin Kellenberger
"""
default_options = {'general': {'image_size': [800, 600], 'device': 'cuda', 'seed': 1234}, 'model': {'kwargs': {'backbone': 'resnet50', 'pretrained': False, 'out_planes': 256, 'convertToInstanceNorm': False}}, 'train': {'dataLoader': {'kwargs': {'shuffle': True, 'batch_size': 32}}, 'optim': {'class': 'torch.optim.Adam', 'kwargs': {'lr': 1e-07, 'weight_decay': 0.0}}, 'transform': {'class': 'ai.models.pytorch.boundingBoxes.Compose', 'kwargs': {'transforms': [{'class': 'ai.models.pytorch.boundingBoxes.Resize', 'kwargs': {'size': [800, 600]}}, {'class': 'ai.models.pytorch.boundingBoxes.RandomHorizontalFlip', 'kwargs': {'p': 0.5}}, {'class': 'ai.models.pytorch.boundingBoxes.DefaultTransform', 'kwargs': {'transform': {'class': 'torchvision.transforms.ColorJitter', 'kwargs': {'brightness': 0.25, 'contrast': 0.25, 'saturation': 0.25, 'hue': 0.01}}}}, {'class': 'ai.models.pytorch.boundingBoxes.DefaultTransform', 'kwargs': {'transform': {'class': 'torchvision.transforms.ToTensor'}}}, {'class': 'ai.models.pytorch.boundingBoxes.DefaultTransform', 'kwargs': {'transform': {'class': 'torchvision.transforms.Normalize', 'kwargs': {'mean': [0.485, 0.456, 0.406], 'std': [0.229, 0.224, 0.225]}}}}]}}, 'criterion': {'class': 'ai.models.pytorch.functional._retinanet.loss.FocalLoss', 'kwargs': {'gamma': 2.0, 'alpha': 0.25, 'background_weight': 1.0}}, 'ignore_unsure': True}, 'inference': {'transform': {'class': 'ai.models.pytorch.boundingBoxes.Compose', 'kwargs': {'transforms': [{'class': 'ai.models.pytorch.boundingBoxes.Resize', 'kwargs': {'size': [800, 600]}}, {'class': 'ai.models.pytorch.boundingBoxes.DefaultTransform', 'kwargs': {'transform': {'class': 'torchvision.transforms.ToTensor'}}}, {'class': 'ai.models.pytorch.boundingBoxes.DefaultTransform', 'kwargs': {'transform': {'class': 'torchvision.transforms.Normalize', 'kwargs': {'mean': [0.485, 0.456, 0.406], 'std': [0.229, 0.224, 0.225]}}}}]}}, 'dataLoader': {'kwargs': {'shuffle': False, 'batch_size': 32}}}}
|
#import gui.gui as gui
# Python3 program to find number
# of bins required using
# First Fit algorithm.
# Returns number of bins required
# using first fit
# online algorithm
def firstFit(weight, n, c):
# Initialize result (Count of bins)
res = 0
# Create an array to store
# remaining space in bins
# there can be at most n bins
bin_rem = [0]*n
# Place items one by one
for i in range(n):
# Find the first bin that
# can accommodate
# weight[i]
j = 0
# Initialize minimum space
# left and index
# of best bin
min = c + 1
bi = 0
for j in range(res):
if (bin_rem[j] >= weight[i] and bin_rem[j] -
weight[i] < min):
bi = j
min = bin_rem[j] - weight[i]
# If no bin could accommodate weight[i],
# create a new bin
if (min == c + 1):
bin_rem[res] = c - weight[i]
res += 1
else: # Assign the item to best bin
bin_rem[bi] -= weight[i]
return res
# Driver code
if __name__ == '__main__':
weight = [ 10, 5, 10, 7, 1, 10, 10 ]
c = 10
n = len(weight)
print("Number of bins required in First Fit : ",
firstFit(weight, n, c))
|
def first_fit(weight, n, c):
res = 0
bin_rem = [0] * n
for i in range(n):
j = 0
min = c + 1
bi = 0
for j in range(res):
if bin_rem[j] >= weight[i] and bin_rem[j] - weight[i] < min:
bi = j
min = bin_rem[j] - weight[i]
if min == c + 1:
bin_rem[res] = c - weight[i]
res += 1
else:
bin_rem[bi] -= weight[i]
return res
if __name__ == '__main__':
weight = [10, 5, 10, 7, 1, 10, 10]
c = 10
n = len(weight)
print('Number of bins required in First Fit : ', first_fit(weight, n, c))
|
# mapping for AWS IAM user_name to slack ID accross all AWS accounts
#
# Fill in "<aws_IAM_user_id>:<slack_id>" here. Seperate each entry by a comma, and leave the last one without a comma
# Example:
# mapping = {
# "IAM_user_id1":"slack_id1",
# "IAM_user_id2":"slack_id2",
# "IAM_user_id3":"slack_id3"
# }
mapping = {
"IAM_user_id1":"slack_id1",
"IAM_user_id2":"slack_id2",
"IAM_user_id3":"slack_id3"
}
|
mapping = {'IAM_user_id1': 'slack_id1', 'IAM_user_id2': 'slack_id2', 'IAM_user_id3': 'slack_id3'}
|
vents = """964,133 -> 596,133
920,215 -> 920,976
123,528 -> 123,661
613,13 -> 407,13
373,876 -> 424,876
616,326 -> 120,326
486,335 -> 539,388
104,947 -> 54,947
319,241 -> 282,204
453,175 -> 453,438
485,187 -> 915,617
863,605 -> 603,605
870,524 -> 342,524
967,395 -> 634,62
405,181 -> 807,181
961,363 -> 419,905
89,586 -> 214,461
545,481 -> 731,295
407,678 -> 626,678
421,642 -> 91,312
11,22 -> 935,946
770,208 -> 76,902
668,858 -> 668,890
568,451 -> 574,451
233,56 -> 371,56
233,932 -> 44,932
404,81 -> 796,81
520,77 -> 403,194
296,736 -> 447,887
210,909 -> 16,909
692,483 -> 877,668
777,289 -> 744,289
22,760 -> 652,130
96,360 -> 626,360
101,267 -> 101,783
47,667 -> 660,667
805,682 -> 563,440
112,15 -> 463,366
406,808 -> 430,808
793,767 -> 107,81
560,534 -> 958,534
722,429 -> 722,459
646,889 -> 646,195
433,942 -> 449,958
716,503 -> 716,99
266,450 -> 266,780
316,81 -> 565,81
760,452 -> 687,452
976,983 -> 15,22
499,564 -> 499,909
839,913 -> 38,112
707,333 -> 438,333
47,644 -> 352,644
807,309 -> 807,706
434,686 -> 812,308
559,572 -> 63,76
493,352 -> 581,352
94,88 -> 928,88
898,738 -> 106,738
201,10 -> 564,10
976,914 -> 976,472
836,153 -> 585,153
178,43 -> 17,204
784,967 -> 738,967
370,359 -> 449,359
13,526 -> 637,526
399,158 -> 10,158
572,293 -> 289,293
627,674 -> 895,674
921,402 -> 984,402
907,667 -> 944,704
574,877 -> 882,569
977,977 -> 121,121
550,584 -> 862,584
396,556 -> 396,289
391,33 -> 532,174
12,988 -> 989,11
48,787 -> 48,637
476,638 -> 113,638
985,985 -> 13,13
838,784 -> 198,784
567,195 -> 677,305
174,251 -> 577,654
296,801 -> 53,558
983,899 -> 983,380
507,230 -> 507,929
264,516 -> 668,920
865,952 -> 865,768
522,290 -> 744,512
936,958 -> 936,115
527,871 -> 527,519
944,972 -> 21,49
880,380 -> 695,565
471,374 -> 446,349
503,597 -> 127,221
471,514 -> 30,73
890,232 -> 890,511
14,461 -> 14,853
167,676 -> 148,676
987,230 -> 754,230
797,725 -> 797,847
347,21 -> 84,21
839,274 -> 964,274
607,456 -> 894,456
335,949 -> 301,949
167,236 -> 820,889
87,558 -> 87,917
318,788 -> 622,484
699,583 -> 699,321
971,967 -> 35,31
420,44 -> 420,36
29,484 -> 458,484
768,157 -> 768,30
690,839 -> 317,839
870,578 -> 560,578
697,195 -> 70,822
689,45 -> 689,223
790,724 -> 341,724
694,291 -> 694,507
43,339 -> 43,987
590,733 -> 590,179
751,361 -> 945,361
99,820 -> 450,469
460,696 -> 942,696
783,940 -> 487,644
630,537 -> 48,537
643,856 -> 643,396
558,733 -> 257,432
16,972 -> 570,418
636,188 -> 636,610
868,138 -> 868,407
85,424 -> 85,919
710,932 -> 354,576
356,505 -> 783,505
606,876 -> 606,62
577,431 -> 749,431
108,262 -> 108,145
615,455 -> 264,104
205,754 -> 866,754
189,182 -> 855,848
10,43 -> 925,958
293,773 -> 293,534
746,313 -> 802,369
607,174 -> 211,570
860,840 -> 260,240
879,78 -> 595,78
11,143 -> 449,143
190,983 -> 267,983
912,92 -> 76,928
744,364 -> 744,258
436,417 -> 46,807
629,592 -> 517,592
113,893 -> 113,959
714,213 -> 786,285
868,165 -> 868,731
349,69 -> 491,69
278,430 -> 111,263
593,849 -> 593,203
156,860 -> 876,860
169,615 -> 169,984
983,93 -> 139,937
94,548 -> 18,548
623,72 -> 106,589
530,334 -> 473,334
384,746 -> 925,205
711,74 -> 28,757
850,728 -> 629,949
378,801 -> 228,651
347,968 -> 201,822
82,578 -> 82,555
149,405 -> 707,963
254,169 -> 793,169
443,454 -> 331,454
460,659 -> 608,807
838,807 -> 31,807
561,952 -> 290,952
755,626 -> 204,75
550,424 -> 550,81
772,115 -> 772,600
40,517 -> 40,232
277,841 -> 317,841
899,150 -> 128,921
735,332 -> 465,332
839,254 -> 915,330
959,616 -> 182,616
729,723 -> 487,965
64,838 -> 953,838
689,830 -> 689,982
191,83 -> 191,879
522,833 -> 942,833
877,785 -> 877,346
255,95 -> 556,95
782,491 -> 475,798
268,815 -> 812,271
119,181 -> 905,181
445,457 -> 742,160
973,30 -> 27,976
356,681 -> 356,289
882,279 -> 914,279
672,162 -> 672,153
180,729 -> 357,729
985,716 -> 985,313
191,618 -> 191,963
949,749 -> 636,749
289,902 -> 142,902
923,615 -> 123,615
710,929 -> 541,760
211,402 -> 211,433
515,178 -> 533,178
525,869 -> 525,578
201,569 -> 17,569
629,848 -> 882,848
152,512 -> 152,189
914,723 -> 764,723
218,231 -> 721,734
438,382 -> 846,382
582,475 -> 582,559
529,943 -> 529,683
330,312 -> 59,312
242,900 -> 862,900
271,220 -> 271,118
182,459 -> 182,673
513,265 -> 513,420
918,942 -> 378,942
277,765 -> 812,230
625,874 -> 219,874
737,533 -> 644,626
647,975 -> 152,480
638,284 -> 785,284
549,680 -> 549,877
886,278 -> 372,792
130,560 -> 516,174
186,741 -> 186,555
208,536 -> 469,536
674,906 -> 312,906
934,156 -> 934,322
568,412 -> 214,412
243,19 -> 243,814
861,230 -> 104,987
683,891 -> 683,533
545,740 -> 545,980
343,320 -> 796,320
821,220 -> 821,302
578,741 -> 578,141
633,405 -> 27,405
645,975 -> 225,555
25,527 -> 412,527
378,817 -> 378,913
352,741 -> 352,293
48,986 -> 925,109
506,231 -> 491,231
854,883 -> 48,77
261,221 -> 895,855
902,240 -> 902,943
145,338 -> 770,963
832,216 -> 832,869
480,385 -> 324,385
644,202 -> 433,202
202,176 -> 190,176
668,693 -> 668,349
95,230 -> 143,230
873,144 -> 67,950
232,509 -> 238,509
963,43 -> 133,873
527,631 -> 641,517
363,61 -> 849,61
72,326 -> 72,861
542,801 -> 233,492
247,48 -> 247,785
972,563 -> 480,71
362,870 -> 932,300
263,811 -> 263,584
556,157 -> 417,157
946,900 -> 175,129
790,542 -> 530,542
777,195 -> 154,818
71,764 -> 71,193
197,13 -> 453,13
664,714 -> 158,714
257,819 -> 257,730
796,927 -> 688,927
124,53 -> 954,883
30,16 -> 980,966
84,151 -> 597,151
840,776 -> 684,776
548,460 -> 718,630
291,635 -> 291,151
948,43 -> 58,933
373,483 -> 373,591
309,81 -> 259,81
692,808 -> 692,835
737,112 -> 215,634
808,595 -> 808,115
160,912 -> 973,99
494,191 -> 494,475
713,925 -> 43,255
736,580 -> 290,134
257,679 -> 725,211
464,81 -> 712,81
35,147 -> 35,420
372,159 -> 372,548
508,228 -> 682,402
120,491 -> 518,889
139,948 -> 272,815
398,523 -> 398,818
935,50 -> 40,945
415,959 -> 195,739
250,868 -> 250,930
77,60 -> 917,900
584,389 -> 493,298
362,163 -> 362,704
670,740 -> 670,703
689,297 -> 689,388
988,572 -> 988,340
238,248 -> 238,916
748,753 -> 29,34
184,565 -> 184,486
812,217 -> 812,34
60,140 -> 96,104
826,673 -> 230,673
221,221 -> 207,235
449,483 -> 270,304
805,810 -> 805,564
952,52 -> 139,865
428,967 -> 312,851
854,673 -> 661,673
985,209 -> 853,209
523,365 -> 54,365
492,171 -> 646,171
908,853 -> 69,14
38,698 -> 724,12
400,479 -> 167,479
948,313 -> 948,976
280,145 -> 37,145
206,858 -> 683,381
203,413 -> 545,413
726,173 -> 673,173
30,954 -> 150,954
319,592 -> 870,41
808,91 -> 180,719
845,612 -> 972,485
160,430 -> 160,780
19,339 -> 379,339
476,550 -> 476,291
341,785 -> 229,673
371,476 -> 371,663
509,836 -> 412,933
980,20 -> 31,969
822,526 -> 328,32
859,314 -> 425,314
963,961 -> 963,100
984,978 -> 31,25
659,251 -> 619,211
649,477 -> 846,477
32,259 -> 724,951
468,753 -> 468,91
690,301 -> 690,652
436,912 -> 845,503
32,123 -> 576,667
142,79 -> 741,678
610,228 -> 468,370
172,667 -> 172,736
961,700 -> 132,700
804,875 -> 804,213
71,970 -> 340,970
171,52 -> 149,30
754,604 -> 226,604
485,941 -> 27,941
126,383 -> 328,181
41,39 -> 987,985
128,62 -> 896,830
414,278 -> 923,787
712,15 -> 712,859
794,35 -> 200,629
516,147 -> 402,261
526,862 -> 905,862
721,407 -> 721,887
728,920 -> 339,920
117,417 -> 203,417
291,561 -> 17,835
171,359 -> 837,359
93,125 -> 136,125
220,226 -> 220,177
75,434 -> 75,407
235,664 -> 141,664
553,490 -> 566,477
487,651 -> 487,877
699,150 -> 933,384
73,556 -> 453,556
363,371 -> 363,984
905,106 -> 668,106
139,271 -> 139,125
466,379 -> 466,420
12,935 -> 625,935
89,892 -> 779,892
119,701 -> 270,852
354,886 -> 80,886
917,376 -> 440,376
23,182 -> 794,953
451,718 -> 121,718
62,251 -> 62,451
642,74 -> 642,698
425,200 -> 442,200
828,175 -> 828,405
751,743 -> 591,743
569,681 -> 574,681
329,187 -> 329,837
302,592 -> 302,230
359,135 -> 386,108
44,234 -> 44,731
836,305 -> 836,574
170,512 -> 367,512
576,699 -> 576,44
398,185 -> 821,185
733,78 -> 733,747
141,183 -> 141,787
65,360 -> 65,691
828,780 -> 828,98
776,744 -> 776,751
881,74 -> 481,474
438,642 -> 438,399
676,972 -> 175,972
60,318 -> 56,314
312,169 -> 341,169
736,472 -> 392,128
225,281 -> 164,281
407,799 -> 341,799
458,826 -> 983,301
12,988 -> 987,13
23,854 -> 662,215
82,863 -> 82,416
542,708 -> 542,44
659,51 -> 520,51
353,246 -> 353,90
985,976 -> 77,68
628,493 -> 628,510
51,48 -> 635,48
97,814 -> 828,83
14,44 -> 773,44
603,178 -> 597,178
11,220 -> 783,220
613,39 -> 613,719
68,303 -> 690,925
121,974 -> 896,199
343,54 -> 343,837
744,303 -> 744,942
678,370 -> 246,370
937,134 -> 84,987
357,333 -> 357,516
848,212 -> 429,631
909,244 -> 138,244
122,794 -> 786,130
274,611 -> 57,611
66,337 -> 385,18
847,356 -> 831,356
740,480 -> 740,359
194,443 -> 194,301
50,564 -> 572,42
86,587 -> 774,587
708,258 -> 49,917
420,530 -> 277,387
509,580 -> 509,71
237,196 -> 479,196
442,287 -> 850,287
830,393 -> 532,393
274,720 -> 501,493
610,565 -> 218,957
380,393 -> 380,800
237,847 -> 155,847
267,791 -> 52,791
275,772 -> 275,794
239,238 -> 419,418
200,785 -> 884,101
185,980 -> 185,284
47,46 -> 750,749
724,661 -> 724,337
630,349 -> 666,349
21,911 -> 21,569
661,562 -> 661,925
41,898 -> 41,104
988,67 -> 105,67
739,65 -> 868,65
187,973 -> 809,973
730,211 -> 255,686
254,445 -> 254,872
622,364 -> 235,751
402,980 -> 761,621
46,488 -> 960,488
799,708 -> 799,862
909,181 -> 909,189
450,266 -> 450,304
631,584 -> 631,455
164,830 -> 744,250
679,755 -> 690,744
949,26 -> 190,785
695,783 -> 218,783
269,151 -> 40,151
166,152 -> 22,152
281,819 -> 922,178
956,649 -> 956,593"""
vents2="""0,9 -> 5,9
8,0 -> 0,8
9,4 -> 3,4
2,2 -> 2,1
7,0 -> 7,4
6,4 -> 2,0
0,9 -> 2,9
3,4 -> 1,4
0,0 -> 8,8
5,5 -> 8,2"""
size=1000
map = [[0 for x in range(size)] for y in range(size)]
#print(map)
for vent in vents.splitlines():
line = vent.split(" -> ")
x1, y1 = [int(digit) for digit in line[0].split(",")]
x2, y2 = [int(digit) for digit in line[1].split(",")]
if x1 == x2:
y_min = min(y1, y2)
y_max = max(y1, y2)
#print(x1, y_min, y_max)
for y in range(y_min, y_max + 1):
map[y][x1] += 1
elif y1 == y2:
x_min = min(x1, x2)
x_max = max(x1, x2)
#print(y1, x_min, x_max)
for x in range(x_min, x_max + 1):
map[y1][x] += 1
else:
dx = 1 if x2 > x1 else -1
dy = 1 if y2 > y1 else -1
range_x = range(x1, x2 + dx, dx)
range_y = range(y1, y2 + dy, dy)
for y, x in zip(range_y, range_x):
map[y][x] += 1
overlap = 0
for row in map:
for cell in row:
#print(cell)
if cell > 1:
overlap += 1
print("\n".join([",".join([str(digit) for digit in line]) for line in map]))
print(overlap)
|
vents = '964,133 -> 596,133\n920,215 -> 920,976\n123,528 -> 123,661\n613,13 -> 407,13\n373,876 -> 424,876\n616,326 -> 120,326\n486,335 -> 539,388\n104,947 -> 54,947\n319,241 -> 282,204\n453,175 -> 453,438\n485,187 -> 915,617\n863,605 -> 603,605\n870,524 -> 342,524\n967,395 -> 634,62\n405,181 -> 807,181\n961,363 -> 419,905\n89,586 -> 214,461\n545,481 -> 731,295\n407,678 -> 626,678\n421,642 -> 91,312\n11,22 -> 935,946\n770,208 -> 76,902\n668,858 -> 668,890\n568,451 -> 574,451\n233,56 -> 371,56\n233,932 -> 44,932\n404,81 -> 796,81\n520,77 -> 403,194\n296,736 -> 447,887\n210,909 -> 16,909\n692,483 -> 877,668\n777,289 -> 744,289\n22,760 -> 652,130\n96,360 -> 626,360\n101,267 -> 101,783\n47,667 -> 660,667\n805,682 -> 563,440\n112,15 -> 463,366\n406,808 -> 430,808\n793,767 -> 107,81\n560,534 -> 958,534\n722,429 -> 722,459\n646,889 -> 646,195\n433,942 -> 449,958\n716,503 -> 716,99\n266,450 -> 266,780\n316,81 -> 565,81\n760,452 -> 687,452\n976,983 -> 15,22\n499,564 -> 499,909\n839,913 -> 38,112\n707,333 -> 438,333\n47,644 -> 352,644\n807,309 -> 807,706\n434,686 -> 812,308\n559,572 -> 63,76\n493,352 -> 581,352\n94,88 -> 928,88\n898,738 -> 106,738\n201,10 -> 564,10\n976,914 -> 976,472\n836,153 -> 585,153\n178,43 -> 17,204\n784,967 -> 738,967\n370,359 -> 449,359\n13,526 -> 637,526\n399,158 -> 10,158\n572,293 -> 289,293\n627,674 -> 895,674\n921,402 -> 984,402\n907,667 -> 944,704\n574,877 -> 882,569\n977,977 -> 121,121\n550,584 -> 862,584\n396,556 -> 396,289\n391,33 -> 532,174\n12,988 -> 989,11\n48,787 -> 48,637\n476,638 -> 113,638\n985,985 -> 13,13\n838,784 -> 198,784\n567,195 -> 677,305\n174,251 -> 577,654\n296,801 -> 53,558\n983,899 -> 983,380\n507,230 -> 507,929\n264,516 -> 668,920\n865,952 -> 865,768\n522,290 -> 744,512\n936,958 -> 936,115\n527,871 -> 527,519\n944,972 -> 21,49\n880,380 -> 695,565\n471,374 -> 446,349\n503,597 -> 127,221\n471,514 -> 30,73\n890,232 -> 890,511\n14,461 -> 14,853\n167,676 -> 148,676\n987,230 -> 754,230\n797,725 -> 797,847\n347,21 -> 84,21\n839,274 -> 964,274\n607,456 -> 894,456\n335,949 -> 301,949\n167,236 -> 820,889\n87,558 -> 87,917\n318,788 -> 622,484\n699,583 -> 699,321\n971,967 -> 35,31\n420,44 -> 420,36\n29,484 -> 458,484\n768,157 -> 768,30\n690,839 -> 317,839\n870,578 -> 560,578\n697,195 -> 70,822\n689,45 -> 689,223\n790,724 -> 341,724\n694,291 -> 694,507\n43,339 -> 43,987\n590,733 -> 590,179\n751,361 -> 945,361\n99,820 -> 450,469\n460,696 -> 942,696\n783,940 -> 487,644\n630,537 -> 48,537\n643,856 -> 643,396\n558,733 -> 257,432\n16,972 -> 570,418\n636,188 -> 636,610\n868,138 -> 868,407\n85,424 -> 85,919\n710,932 -> 354,576\n356,505 -> 783,505\n606,876 -> 606,62\n577,431 -> 749,431\n108,262 -> 108,145\n615,455 -> 264,104\n205,754 -> 866,754\n189,182 -> 855,848\n10,43 -> 925,958\n293,773 -> 293,534\n746,313 -> 802,369\n607,174 -> 211,570\n860,840 -> 260,240\n879,78 -> 595,78\n11,143 -> 449,143\n190,983 -> 267,983\n912,92 -> 76,928\n744,364 -> 744,258\n436,417 -> 46,807\n629,592 -> 517,592\n113,893 -> 113,959\n714,213 -> 786,285\n868,165 -> 868,731\n349,69 -> 491,69\n278,430 -> 111,263\n593,849 -> 593,203\n156,860 -> 876,860\n169,615 -> 169,984\n983,93 -> 139,937\n94,548 -> 18,548\n623,72 -> 106,589\n530,334 -> 473,334\n384,746 -> 925,205\n711,74 -> 28,757\n850,728 -> 629,949\n378,801 -> 228,651\n347,968 -> 201,822\n82,578 -> 82,555\n149,405 -> 707,963\n254,169 -> 793,169\n443,454 -> 331,454\n460,659 -> 608,807\n838,807 -> 31,807\n561,952 -> 290,952\n755,626 -> 204,75\n550,424 -> 550,81\n772,115 -> 772,600\n40,517 -> 40,232\n277,841 -> 317,841\n899,150 -> 128,921\n735,332 -> 465,332\n839,254 -> 915,330\n959,616 -> 182,616\n729,723 -> 487,965\n64,838 -> 953,838\n689,830 -> 689,982\n191,83 -> 191,879\n522,833 -> 942,833\n877,785 -> 877,346\n255,95 -> 556,95\n782,491 -> 475,798\n268,815 -> 812,271\n119,181 -> 905,181\n445,457 -> 742,160\n973,30 -> 27,976\n356,681 -> 356,289\n882,279 -> 914,279\n672,162 -> 672,153\n180,729 -> 357,729\n985,716 -> 985,313\n191,618 -> 191,963\n949,749 -> 636,749\n289,902 -> 142,902\n923,615 -> 123,615\n710,929 -> 541,760\n211,402 -> 211,433\n515,178 -> 533,178\n525,869 -> 525,578\n201,569 -> 17,569\n629,848 -> 882,848\n152,512 -> 152,189\n914,723 -> 764,723\n218,231 -> 721,734\n438,382 -> 846,382\n582,475 -> 582,559\n529,943 -> 529,683\n330,312 -> 59,312\n242,900 -> 862,900\n271,220 -> 271,118\n182,459 -> 182,673\n513,265 -> 513,420\n918,942 -> 378,942\n277,765 -> 812,230\n625,874 -> 219,874\n737,533 -> 644,626\n647,975 -> 152,480\n638,284 -> 785,284\n549,680 -> 549,877\n886,278 -> 372,792\n130,560 -> 516,174\n186,741 -> 186,555\n208,536 -> 469,536\n674,906 -> 312,906\n934,156 -> 934,322\n568,412 -> 214,412\n243,19 -> 243,814\n861,230 -> 104,987\n683,891 -> 683,533\n545,740 -> 545,980\n343,320 -> 796,320\n821,220 -> 821,302\n578,741 -> 578,141\n633,405 -> 27,405\n645,975 -> 225,555\n25,527 -> 412,527\n378,817 -> 378,913\n352,741 -> 352,293\n48,986 -> 925,109\n506,231 -> 491,231\n854,883 -> 48,77\n261,221 -> 895,855\n902,240 -> 902,943\n145,338 -> 770,963\n832,216 -> 832,869\n480,385 -> 324,385\n644,202 -> 433,202\n202,176 -> 190,176\n668,693 -> 668,349\n95,230 -> 143,230\n873,144 -> 67,950\n232,509 -> 238,509\n963,43 -> 133,873\n527,631 -> 641,517\n363,61 -> 849,61\n72,326 -> 72,861\n542,801 -> 233,492\n247,48 -> 247,785\n972,563 -> 480,71\n362,870 -> 932,300\n263,811 -> 263,584\n556,157 -> 417,157\n946,900 -> 175,129\n790,542 -> 530,542\n777,195 -> 154,818\n71,764 -> 71,193\n197,13 -> 453,13\n664,714 -> 158,714\n257,819 -> 257,730\n796,927 -> 688,927\n124,53 -> 954,883\n30,16 -> 980,966\n84,151 -> 597,151\n840,776 -> 684,776\n548,460 -> 718,630\n291,635 -> 291,151\n948,43 -> 58,933\n373,483 -> 373,591\n309,81 -> 259,81\n692,808 -> 692,835\n737,112 -> 215,634\n808,595 -> 808,115\n160,912 -> 973,99\n494,191 -> 494,475\n713,925 -> 43,255\n736,580 -> 290,134\n257,679 -> 725,211\n464,81 -> 712,81\n35,147 -> 35,420\n372,159 -> 372,548\n508,228 -> 682,402\n120,491 -> 518,889\n139,948 -> 272,815\n398,523 -> 398,818\n935,50 -> 40,945\n415,959 -> 195,739\n250,868 -> 250,930\n77,60 -> 917,900\n584,389 -> 493,298\n362,163 -> 362,704\n670,740 -> 670,703\n689,297 -> 689,388\n988,572 -> 988,340\n238,248 -> 238,916\n748,753 -> 29,34\n184,565 -> 184,486\n812,217 -> 812,34\n60,140 -> 96,104\n826,673 -> 230,673\n221,221 -> 207,235\n449,483 -> 270,304\n805,810 -> 805,564\n952,52 -> 139,865\n428,967 -> 312,851\n854,673 -> 661,673\n985,209 -> 853,209\n523,365 -> 54,365\n492,171 -> 646,171\n908,853 -> 69,14\n38,698 -> 724,12\n400,479 -> 167,479\n948,313 -> 948,976\n280,145 -> 37,145\n206,858 -> 683,381\n203,413 -> 545,413\n726,173 -> 673,173\n30,954 -> 150,954\n319,592 -> 870,41\n808,91 -> 180,719\n845,612 -> 972,485\n160,430 -> 160,780\n19,339 -> 379,339\n476,550 -> 476,291\n341,785 -> 229,673\n371,476 -> 371,663\n509,836 -> 412,933\n980,20 -> 31,969\n822,526 -> 328,32\n859,314 -> 425,314\n963,961 -> 963,100\n984,978 -> 31,25\n659,251 -> 619,211\n649,477 -> 846,477\n32,259 -> 724,951\n468,753 -> 468,91\n690,301 -> 690,652\n436,912 -> 845,503\n32,123 -> 576,667\n142,79 -> 741,678\n610,228 -> 468,370\n172,667 -> 172,736\n961,700 -> 132,700\n804,875 -> 804,213\n71,970 -> 340,970\n171,52 -> 149,30\n754,604 -> 226,604\n485,941 -> 27,941\n126,383 -> 328,181\n41,39 -> 987,985\n128,62 -> 896,830\n414,278 -> 923,787\n712,15 -> 712,859\n794,35 -> 200,629\n516,147 -> 402,261\n526,862 -> 905,862\n721,407 -> 721,887\n728,920 -> 339,920\n117,417 -> 203,417\n291,561 -> 17,835\n171,359 -> 837,359\n93,125 -> 136,125\n220,226 -> 220,177\n75,434 -> 75,407\n235,664 -> 141,664\n553,490 -> 566,477\n487,651 -> 487,877\n699,150 -> 933,384\n73,556 -> 453,556\n363,371 -> 363,984\n905,106 -> 668,106\n139,271 -> 139,125\n466,379 -> 466,420\n12,935 -> 625,935\n89,892 -> 779,892\n119,701 -> 270,852\n354,886 -> 80,886\n917,376 -> 440,376\n23,182 -> 794,953\n451,718 -> 121,718\n62,251 -> 62,451\n642,74 -> 642,698\n425,200 -> 442,200\n828,175 -> 828,405\n751,743 -> 591,743\n569,681 -> 574,681\n329,187 -> 329,837\n302,592 -> 302,230\n359,135 -> 386,108\n44,234 -> 44,731\n836,305 -> 836,574\n170,512 -> 367,512\n576,699 -> 576,44\n398,185 -> 821,185\n733,78 -> 733,747\n141,183 -> 141,787\n65,360 -> 65,691\n828,780 -> 828,98\n776,744 -> 776,751\n881,74 -> 481,474\n438,642 -> 438,399\n676,972 -> 175,972\n60,318 -> 56,314\n312,169 -> 341,169\n736,472 -> 392,128\n225,281 -> 164,281\n407,799 -> 341,799\n458,826 -> 983,301\n12,988 -> 987,13\n23,854 -> 662,215\n82,863 -> 82,416\n542,708 -> 542,44\n659,51 -> 520,51\n353,246 -> 353,90\n985,976 -> 77,68\n628,493 -> 628,510\n51,48 -> 635,48\n97,814 -> 828,83\n14,44 -> 773,44\n603,178 -> 597,178\n11,220 -> 783,220\n613,39 -> 613,719\n68,303 -> 690,925\n121,974 -> 896,199\n343,54 -> 343,837\n744,303 -> 744,942\n678,370 -> 246,370\n937,134 -> 84,987\n357,333 -> 357,516\n848,212 -> 429,631\n909,244 -> 138,244\n122,794 -> 786,130\n274,611 -> 57,611\n66,337 -> 385,18\n847,356 -> 831,356\n740,480 -> 740,359\n194,443 -> 194,301\n50,564 -> 572,42\n86,587 -> 774,587\n708,258 -> 49,917\n420,530 -> 277,387\n509,580 -> 509,71\n237,196 -> 479,196\n442,287 -> 850,287\n830,393 -> 532,393\n274,720 -> 501,493\n610,565 -> 218,957\n380,393 -> 380,800\n237,847 -> 155,847\n267,791 -> 52,791\n275,772 -> 275,794\n239,238 -> 419,418\n200,785 -> 884,101\n185,980 -> 185,284\n47,46 -> 750,749\n724,661 -> 724,337\n630,349 -> 666,349\n21,911 -> 21,569\n661,562 -> 661,925\n41,898 -> 41,104\n988,67 -> 105,67\n739,65 -> 868,65\n187,973 -> 809,973\n730,211 -> 255,686\n254,445 -> 254,872\n622,364 -> 235,751\n402,980 -> 761,621\n46,488 -> 960,488\n799,708 -> 799,862\n909,181 -> 909,189\n450,266 -> 450,304\n631,584 -> 631,455\n164,830 -> 744,250\n679,755 -> 690,744\n949,26 -> 190,785\n695,783 -> 218,783\n269,151 -> 40,151\n166,152 -> 22,152\n281,819 -> 922,178\n956,649 -> 956,593'
vents2 = '0,9 -> 5,9\n8,0 -> 0,8\n9,4 -> 3,4\n2,2 -> 2,1\n7,0 -> 7,4\n6,4 -> 2,0\n0,9 -> 2,9\n3,4 -> 1,4\n0,0 -> 8,8\n5,5 -> 8,2'
size = 1000
map = [[0 for x in range(size)] for y in range(size)]
for vent in vents.splitlines():
line = vent.split(' -> ')
(x1, y1) = [int(digit) for digit in line[0].split(',')]
(x2, y2) = [int(digit) for digit in line[1].split(',')]
if x1 == x2:
y_min = min(y1, y2)
y_max = max(y1, y2)
for y in range(y_min, y_max + 1):
map[y][x1] += 1
elif y1 == y2:
x_min = min(x1, x2)
x_max = max(x1, x2)
for x in range(x_min, x_max + 1):
map[y1][x] += 1
else:
dx = 1 if x2 > x1 else -1
dy = 1 if y2 > y1 else -1
range_x = range(x1, x2 + dx, dx)
range_y = range(y1, y2 + dy, dy)
for (y, x) in zip(range_y, range_x):
map[y][x] += 1
overlap = 0
for row in map:
for cell in row:
if cell > 1:
overlap += 1
print('\n'.join([','.join([str(digit) for digit in line]) for line in map]))
print(overlap)
|
# Bot's version number
__version__ = "0.1.0"
# Authorized guild
GUILD_ID = 952941520867196958
|
__version__ = '0.1.0'
guild_id = 952941520867196958
|
#Rep of loops
numbers = [2, 3, 4, 45]
l = len(numbers)
for i in range(l):
print(numbers[i]) # each iteration the i takes on a different
#value according to len of numbers (4)
for i in range(8):
print(i) # prints numbers 0 through 7
for el in numbers:
print(el)
# using a loop to change elements within a list
items = ['yellow', 'red', 'green', 'purple', 'blue'] #list of colours
for i in range(5):
print('Before item ', i , 'is', items[i])
items[i] = 'different'
print('After item ', i , 'is', items[i])
items = ['yellow', 'red', 'green', 'purple', 'blue'] #list of colours
for index_of_enumerate, colors in enumerate(items):
print(index_of_enumerate, colors)
# while:
months = ['june', 'august', 'july', 'may']
i = 0
month = 'a'
while month != 'august':
month = months[i]
print(month)
i += 1
# Write your code below and press Shift+Enter to execute
# Write a while loop to display the values of the Rating of an album playlist stored in the list PlayListRatings. If the score is less than 6, exit the loop. The list PlayListRatings is given by: PlayListRatings = [10, 9.5, 10, 8, 7.5, 5, 10, 10]
PlayListRatings = [10, 9.5, 10, 8, 7.5, 5, 10, 10]
i = 0
score = PlayListRatings[i]
#print(score)
while score >= 6:
score = PlayListRatings[i]
print(score)
i += 1
|
numbers = [2, 3, 4, 45]
l = len(numbers)
for i in range(l):
print(numbers[i])
for i in range(8):
print(i)
for el in numbers:
print(el)
items = ['yellow', 'red', 'green', 'purple', 'blue']
for i in range(5):
print('Before item ', i, 'is', items[i])
items[i] = 'different'
print('After item ', i, 'is', items[i])
items = ['yellow', 'red', 'green', 'purple', 'blue']
for (index_of_enumerate, colors) in enumerate(items):
print(index_of_enumerate, colors)
months = ['june', 'august', 'july', 'may']
i = 0
month = 'a'
while month != 'august':
month = months[i]
print(month)
i += 1
play_list_ratings = [10, 9.5, 10, 8, 7.5, 5, 10, 10]
i = 0
score = PlayListRatings[i]
while score >= 6:
score = PlayListRatings[i]
print(score)
i += 1
|
"""
cheesyutils - A number of utility packages and functions
"""
__title__ = "cheesyutils"
__author__ = "CheesyGamer77"
__copyright__ = "Copyright 2021-present CheesyGamer77"
__version__ = "0.0.30"
|
"""
cheesyutils - A number of utility packages and functions
"""
__title__ = 'cheesyutils'
__author__ = 'CheesyGamer77'
__copyright__ = 'Copyright 2021-present CheesyGamer77'
__version__ = '0.0.30'
|
def append_text(new_text):
'''
Write the code instruction to be exported later on
Args.
new_text (str): the text that will be appended to the base string
'''
global code_base_text
code_base_text = code_base_text + new_text
|
def append_text(new_text):
"""
Write the code instruction to be exported later on
Args.
new_text (str): the text that will be appended to the base string
"""
global code_base_text
code_base_text = code_base_text + new_text
|
"""
Given an unsorted array of integers, find the length of the longest consecutive elements sequence.
Your algorithm should run in O(n) complexity.
Example:
Input: [100, 4, 200, 1, 3, 2]
Output: 4
Explanation: The longest consecutive elements sequence is [1, 2, 3, 4]. Therefore its length is 4.
Solution:
1. Sort
2. Hashset
"""
# Sort
# TLE: while loop too slow
# Time: O(NlogN)
# Space: O(1)
class Solution(object):
def longestConsecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l == 0:
return 0
nums.sort()
max_len = 0
for i in range(l):
cur_len = 1
j = i + 1
while j < l:
if nums[j] == nums[j-1] + 1:
cur_len += 1
j += 1
elif nums[j] == nums[j-1]:
j += 1
else:
break
if cur_len > max_len:
max_len = cur_len
i = j
return max_len
# Sort
# Time: O(NlogN)
# Space: O(1)
class Solution(object):
def longestConsecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l == 0:
return 0
nums.sort()
max_len = 0
cur_len = 1
for i in range(1, l):
if nums[i] != nums[i-1]:
# jump duplicates
if nums[i] == nums[i-1] + 1:
cur_len += 1
else:
max_len = max(max_len, cur_len)
cur_len = 1
# in case of the last number is in the longest consecutive numbers
max_len = max(max_len, cur_len)
return max_len
# Sort
# Time: O(NlogN)
# Space: O(1)
class Solution(object):
def longestConsecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l < 2 :
return l
res = 0
cur_len = 1
nums = list(set(nums))
nums.sort()
for i in range(1, len(nums)) :
if nums[i] == nums[i-1]+1 :
cur_len += 1
else:
res = max(res, cur_len)
cur_len = 1
res = max(res, cur_len)
return res
# Set
# Time: O(N), since we visit each number once
# Space: O(1)
class Solution(object):
def longestConsecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
# for each num I will check whether num-1 exists
# if yes, then I ignore this num
# Otherwise if num-1 doesn't exist, then I will go till I can find num+1
# so in a way I am only checking each number max once and once in set.
s = set(nums)
res = 0
for num in s:
cur_len = 1
if num - 1 not in s:
while num + 1 in s:
cur_len += 1
num += 1
res = max(res, cur_len)
return res
|
"""
Given an unsorted array of integers, find the length of the longest consecutive elements sequence.
Your algorithm should run in O(n) complexity.
Example:
Input: [100, 4, 200, 1, 3, 2]
Output: 4
Explanation: The longest consecutive elements sequence is [1, 2, 3, 4]. Therefore its length is 4.
Solution:
1. Sort
2. Hashset
"""
class Solution(object):
def longest_consecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l == 0:
return 0
nums.sort()
max_len = 0
for i in range(l):
cur_len = 1
j = i + 1
while j < l:
if nums[j] == nums[j - 1] + 1:
cur_len += 1
j += 1
elif nums[j] == nums[j - 1]:
j += 1
else:
break
if cur_len > max_len:
max_len = cur_len
i = j
return max_len
class Solution(object):
def longest_consecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l == 0:
return 0
nums.sort()
max_len = 0
cur_len = 1
for i in range(1, l):
if nums[i] != nums[i - 1]:
if nums[i] == nums[i - 1] + 1:
cur_len += 1
else:
max_len = max(max_len, cur_len)
cur_len = 1
max_len = max(max_len, cur_len)
return max_len
class Solution(object):
def longest_consecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = len(nums)
if l < 2:
return l
res = 0
cur_len = 1
nums = list(set(nums))
nums.sort()
for i in range(1, len(nums)):
if nums[i] == nums[i - 1] + 1:
cur_len += 1
else:
res = max(res, cur_len)
cur_len = 1
res = max(res, cur_len)
return res
class Solution(object):
def longest_consecutive(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
s = set(nums)
res = 0
for num in s:
cur_len = 1
if num - 1 not in s:
while num + 1 in s:
cur_len += 1
num += 1
res = max(res, cur_len)
return res
|
SHORT_DESCRIPTION = "Sorter organises/sorts files using a customised search function to group those that have similar characteristics into a single folder. Similar characteristics include file type, file name or part of the name and file category. You can put all letters documents into one folder, all images with the word home into another, all music by one artist in yet another folder, etc."
SOURCE_DESCRIPTION = "SOURCE (required)\nThis is the folder in which the sorting should be done i.e the folder containing the disorganised files."
DESTINATION_DESCRIPTION = "DESTINATION (optional)\nAn optional destination (a folder) where the user would want the sorted files/folders to be moved to."
RECURSIVE_DESCRIPTION = "LOOK INTO SUB-FOLDERS (optional)\nChecks into every child folder, starting from the source folder, and groups/sorts the files accordingly."
TYPES_DESCRIPTION = "SELECT FILE TYPES (optional)\nSelect the specific file types/formats to be sorted."
SEARCH_DESCRIPTION = "SEARCH FOR (optional)\nDirects Sorter to search and only group files with names containing this value. If this is enabled then, by default, Sort Folders option is enabled to enable the sorted files to be moved to a folder whose name will be the value provided here. The search is case-insensitive but the final folder will adopt the case styles."
GROUP_FOLDER_DESCRIPTION = "GROUP INTO FOLDER (optional)\nMoves all files (and folders) fitting the search descriptions into a folder named by the value provided in this option."
BY_EXTENSION_DESCRIPTION = "GROUP BY FILE TYPE (optional)\nGroups files in the destination and according to their file type. That is, all JPGs different from PDFs different from DOCXs."
CLEANUP_DESCRIPTION = "PERFORM CLEANUP (optional)\nLooks into the child folders of the source folder and removes those which are empty."
NOTE = "Note:\nIf you want a folder and its contents to be left as is (i.e. not to be sorted or affected in any way), just add a file named `.signore` (no extension) into the folder."
HELP_MESSAGE = "How it Works \n" + SHORT_DESCRIPTION + "\n\nBelow is a description of the fields required to achieve results using Sorter:\n\n" + SOURCE_DESCRIPTION + "\n\n" + DESTINATION_DESCRIPTION + \
"\n\n" + SEARCH_DESCRIPTION + "\n\n" + RECURSIVE_DESCRIPTION + \
"\n\n" + TYPES_DESCRIPTION + "\n\n" + \
GROUP_FOLDER_DESCRIPTION + "\n\n" + BY_EXTENSION_DESCRIPTION + "\n\n" + CLEANUP_DESCRIPTION + \
"\n\n" + NOTE
COPYRIGHT_MESSAGE = "Copyright \u00a9 2017\n\nAswa Paul\nAll rights reserved.\n\n"
HOMEPAGE = "https://giantas.github.io/sorter"
SOURCE_CODE = "https://github.com/giantas/sorter"
LICENSE = """BSD 3-Clause License
Copyright (c) 2017, Aswa Paul
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
|
short_description = 'Sorter organises/sorts files using a customised search function to group those that have similar characteristics into a single folder. Similar characteristics include file type, file name or part of the name and file category. You can put all letters documents into one folder, all images with the word home into another, all music by one artist in yet another folder, etc.'
source_description = 'SOURCE (required)\nThis is the folder in which the sorting should be done i.e the folder containing the disorganised files.'
destination_description = 'DESTINATION (optional)\nAn optional destination (a folder) where the user would want the sorted files/folders to be moved to.'
recursive_description = 'LOOK INTO SUB-FOLDERS (optional)\nChecks into every child folder, starting from the source folder, and groups/sorts the files accordingly.'
types_description = 'SELECT FILE TYPES (optional)\nSelect the specific file types/formats to be sorted.'
search_description = 'SEARCH FOR (optional)\nDirects Sorter to search and only group files with names containing this value. If this is enabled then, by default, Sort Folders option is enabled to enable the sorted files to be moved to a folder whose name will be the value provided here. The search is case-insensitive but the final folder will adopt the case styles.'
group_folder_description = 'GROUP INTO FOLDER (optional)\nMoves all files (and folders) fitting the search descriptions into a folder named by the value provided in this option.'
by_extension_description = 'GROUP BY FILE TYPE (optional)\nGroups files in the destination and according to their file type. That is, all JPGs different from PDFs different from DOCXs.'
cleanup_description = 'PERFORM CLEANUP (optional)\nLooks into the child folders of the source folder and removes those which are empty.'
note = 'Note:\nIf you want a folder and its contents to be left as is (i.e. not to be sorted or affected in any way), just add a file named `.signore` (no extension) into the folder.'
help_message = 'How it Works \n' + SHORT_DESCRIPTION + '\n\nBelow is a description of the fields required to achieve results using Sorter:\n\n' + SOURCE_DESCRIPTION + '\n\n' + DESTINATION_DESCRIPTION + '\n\n' + SEARCH_DESCRIPTION + '\n\n' + RECURSIVE_DESCRIPTION + '\n\n' + TYPES_DESCRIPTION + '\n\n' + GROUP_FOLDER_DESCRIPTION + '\n\n' + BY_EXTENSION_DESCRIPTION + '\n\n' + CLEANUP_DESCRIPTION + '\n\n' + NOTE
copyright_message = 'Copyright © 2017\n\nAswa Paul\nAll rights reserved.\n\n'
homepage = 'https://giantas.github.io/sorter'
source_code = 'https://github.com/giantas/sorter'
license = 'BSD 3-Clause License\n\nCopyright (c) 2017, Aswa Paul\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n* Redistributions of source code must retain the above copyright notice, this\n list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n\n* Neither the name of the copyright holder nor the names of its\n contributors may be used to endorse or promote products derived from\n this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n'
|
n=int(input ('veverite'))
if n %2==0: print ('par')
else: print ('impar')
print('par' if n%2==0 else 'impar')
|
n = int(input('veverite'))
if n % 2 == 0:
print('par')
else:
print('impar')
print('par' if n % 2 == 0 else 'impar')
|
# pylint: disable=missing-class-docstring, disable=missing-function-docstring, missing-module-docstring/
#$ header class Point(public)
#$ header method __init__(Point, double, double)
#$ header method __del__(Point)
#$ header method translate(Point, double, double)
class Point(object):
def __init__(self, x, y):
self.x = x
self.y = y
def __del__(self):
pass
def translate(self, a, b):
self.x = self.x + a
self.y = self.y + b
if __name__ == '__main__':
p = Point(0.0, 0.0)
x=p.x
p.x=x
a = p.x
a = p.x - 2
a = 2 * p.x - 2
a = 2 * (p.x + 6) - 2
p.y = a + 5
p.y = p.x + 5
p.translate(1.0, 2.0)
print(p.x, p.y)
print(a)
del p
|
class Point(object):
def __init__(self, x, y):
self.x = x
self.y = y
def __del__(self):
pass
def translate(self, a, b):
self.x = self.x + a
self.y = self.y + b
if __name__ == '__main__':
p = point(0.0, 0.0)
x = p.x
p.x = x
a = p.x
a = p.x - 2
a = 2 * p.x - 2
a = 2 * (p.x + 6) - 2
p.y = a + 5
p.y = p.x + 5
p.translate(1.0, 2.0)
print(p.x, p.y)
print(a)
del p
|
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'leftPLUSMINUSleftTIMESDIVIDEleftPOWERrightUMINUSCOMMA DATA DEF DIM DIVIDE END EQUALS FLOAT FOR GE GOSUB GOTO GT ID IF INTEGER LE LET LIST LPAREN LT MINUS NE NEW NEWLINE NEXT PLUS POWER PRINT READ REM RETURN RPAREN RUN SEMI STEP STOP STRING THEN TIMES TOprogram : program statement\n | statementprogram : errorstatement : INTEGER command NEWLINEstatement : RUN NEWLINE\n | LIST NEWLINE\n | NEW NEWLINEstatement : INTEGER NEWLINEstatement : INTEGER error NEWLINEstatement : NEWLINEcommand : LET variable EQUALS exprcommand : LET variable EQUALS errorcommand : READ varlistcommand : READ errorcommand : DATA numlistcommand : DATA errorcommand : PRINT plist optendcommand : PRINT erroroptend : COMMA \n | SEMI\n |command : PRINTcommand : GOTO INTEGERcommand : GOTO errorcommand : IF relexpr THEN INTEGERcommand : IF error THEN INTEGERcommand : IF relexpr THEN errorcommand : FOR ID EQUALS expr TO expr optstepcommand : FOR ID EQUALS error TO expr optstepcommand : FOR ID EQUALS expr TO error optstepcommand : FOR ID EQUALS expr TO expr STEP erroroptstep : STEP expr\n | emptycommand : NEXT IDcommand : NEXT errorcommand : ENDcommand : REMcommand : STOPcommand : DEF ID LPAREN ID RPAREN EQUALS exprcommand : DEF ID LPAREN ID RPAREN EQUALS errorcommand : DEF ID LPAREN error RPAREN EQUALS exprcommand : GOSUB INTEGERcommand : GOSUB errorcommand : RETURNcommand : DIM dimlistcommand : DIM errordimlist : dimlist COMMA dimitem\n | dimitemdimitem : ID LPAREN INTEGER RPARENdimitem : ID LPAREN INTEGER COMMA INTEGER RPARENexpr : expr PLUS expr\n | expr MINUS expr\n | expr TIMES expr\n | expr DIVIDE expr\n | expr POWER exprexpr : INTEGER\n | FLOATexpr : variableexpr : LPAREN expr RPARENexpr : MINUS expr %prec UMINUSrelexpr : expr LT expr\n | expr LE expr\n | expr GT expr\n | expr GE expr\n | expr EQUALS expr\n | expr NE exprvariable : ID\n | ID LPAREN expr RPAREN\n | ID LPAREN expr COMMA expr RPARENvarlist : varlist COMMA variable\n | variablenumlist : numlist COMMA number\n | numbernumber : INTEGER\n | FLOATnumber : MINUS INTEGER\n | MINUS FLOATplist : plist COMMA pitem\n | pitempitem : STRINGpitem : STRING exprpitem : exprempty : '
_lr_action_items = {'error':([0,4,14,15,16,17,18,20,25,27,69,86,94,95,127,137,142,],[3,12,36,39,45,55,57,61,64,66,99,111,120,122,135,148,152,]),'INTEGER':([0,1,2,3,5,9,11,15,16,17,18,25,28,29,30,31,32,43,47,49,53,69,70,72,76,79,80,81,82,83,86,87,88,89,90,91,92,93,94,97,126,127,128,132,137,138,142,145,],[4,4,-2,-3,-10,-1,-8,41,50,54,50,63,-5,-6,-7,-4,-9,73,50,50,50,50,50,41,50,50,50,50,50,50,110,112,50,50,50,50,50,50,50,124,50,50,50,139,50,50,50,50,]),'RUN':([0,1,2,3,5,9,11,28,29,30,31,32,],[6,6,-2,-3,-10,-1,-8,-5,-6,-7,-4,-9,]),'LIST':([0,1,2,3,5,9,11,28,29,30,31,32,],[7,7,-2,-3,-10,-1,-8,-5,-6,-7,-4,-9,]),'NEW':([0,1,2,3,5,9,11,28,29,30,31,32,],[8,8,-2,-3,-10,-1,-8,-5,-6,-7,-4,-9,]),'NEWLINE':([0,1,2,3,4,5,6,7,8,9,10,11,12,16,21,22,23,26,28,29,30,31,32,34,35,36,37,38,39,40,41,42,44,45,46,47,48,50,51,52,54,55,60,61,63,64,65,66,67,73,74,75,76,77,78,84,98,99,101,102,103,104,105,106,107,108,109,110,111,112,123,125,131,134,135,136,140,141,143,144,146,147,148,149,150,151,152,],[5,5,-2,-3,11,-10,28,29,30,-1,31,-8,32,-22,-36,-37,-38,-44,-5,-6,-7,-4,-9,-67,-13,-14,-71,-15,-16,-73,-74,-75,-21,-18,-79,-80,-82,-56,-57,-58,-23,-24,-34,-35,-42,-43,-45,-46,-48,-76,-77,-17,-19,-20,-81,-60,-11,-12,-70,-72,-78,-51,-52,-53,-54,-55,-59,-25,-27,-26,-47,-68,-49,-83,-83,-83,-69,-28,-33,-30,-29,-39,-40,-41,-50,-32,-31,]),'$end':([1,2,3,5,9,11,28,29,30,31,32,],[0,-2,-3,-10,-1,-8,-5,-6,-7,-4,-9,]),'LET':([4,],[13,]),'READ':([4,],[14,]),'DATA':([4,],[15,]),'PRINT':([4,],[16,]),'GOTO':([4,],[17,]),'IF':([4,],[18,]),'FOR':([4,],[19,]),'NEXT':([4,],[20,]),'END':([4,],[21,]),'REM':([4,],[22,]),'STOP':([4,],[23,]),'DEF':([4,],[24,]),'GOSUB':([4,],[25,]),'RETURN':([4,],[26,]),'DIM':([4,],[27,]),'ID':([13,14,16,18,19,20,24,27,47,49,53,69,70,71,76,79,80,81,82,83,88,89,90,91,92,93,94,95,96,126,127,128,137,138,142,145,],[34,34,34,34,59,60,62,68,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,121,68,34,34,34,34,34,34,34,]),'FLOAT':([15,16,18,43,47,49,53,69,70,72,76,79,80,81,82,83,88,89,90,91,92,93,94,126,127,128,137,138,142,145,],[42,51,51,74,51,51,51,51,51,42,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,51,]),'MINUS':([15,16,18,34,47,48,49,50,51,52,53,58,69,70,72,76,78,79,80,81,82,83,84,85,88,89,90,91,92,93,94,98,100,104,105,106,107,108,109,113,114,115,116,117,118,119,125,126,127,128,133,134,136,137,138,140,142,145,147,149,151,],[43,49,49,-67,49,80,49,-56,-57,-58,49,80,49,49,43,49,80,49,49,49,49,49,-60,80,49,49,49,49,49,49,49,80,80,-51,-52,-53,-54,-55,-59,80,80,80,80,80,80,80,-68,49,49,49,80,80,80,49,49,-69,49,49,80,80,80,]),'STRING':([16,76,],[47,47,]),'LPAREN':([16,18,34,47,49,53,62,68,69,70,76,79,80,81,82,83,88,89,90,91,92,93,94,126,127,128,137,138,142,145,],[53,53,70,53,53,53,95,97,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,53,]),'EQUALS':([33,34,50,51,52,58,59,84,104,105,106,107,108,109,125,129,130,140,],[69,-67,-56,-57,-58,92,94,-60,-51,-52,-53,-54,-55,-59,-68,137,138,-69,]),'COMMA':([34,35,37,38,40,41,42,44,46,47,48,50,51,52,65,67,73,74,78,84,100,101,102,103,104,105,106,107,108,109,123,124,125,131,140,150,],[-67,71,-71,72,-73,-74,-75,76,-79,-80,-82,-56,-57,-58,96,-48,-76,-77,-81,-60,126,-70,-72,-78,-51,-52,-53,-54,-55,-59,-47,132,-68,-49,-69,-50,]),'PLUS':([34,48,50,51,52,58,78,84,85,98,100,104,105,106,107,108,109,113,114,115,116,117,118,119,125,133,134,136,140,147,149,151,],[-67,79,-56,-57,-58,79,79,-60,79,79,79,-51,-52,-53,-54,-55,-59,79,79,79,79,79,79,79,-68,79,79,79,-69,79,79,79,]),'TIMES':([34,48,50,51,52,58,78,84,85,98,100,104,105,106,107,108,109,113,114,115,116,117,118,119,125,133,134,136,140,147,149,151,],[-67,81,-56,-57,-58,81,81,-60,81,81,81,81,81,-53,-54,-55,-59,81,81,81,81,81,81,81,-68,81,81,81,-69,81,81,81,]),'DIVIDE':([34,48,50,51,52,58,78,84,85,98,100,104,105,106,107,108,109,113,114,115,116,117,118,119,125,133,134,136,140,147,149,151,],[-67,82,-56,-57,-58,82,82,-60,82,82,82,82,82,-53,-54,-55,-59,82,82,82,82,82,82,82,-68,82,82,82,-69,82,82,82,]),'POWER':([34,48,50,51,52,58,78,84,85,98,100,104,105,106,107,108,109,113,114,115,116,117,118,119,125,133,134,136,140,147,149,151,],[-67,83,-56,-57,-58,83,83,-60,83,83,83,83,83,83,83,-55,-59,83,83,83,83,83,83,83,-68,83,83,83,-69,83,83,83,]),'SEMI':([34,44,46,47,48,50,51,52,78,84,103,104,105,106,107,108,109,125,140,],[-67,77,-79,-80,-82,-56,-57,-58,-81,-60,-78,-51,-52,-53,-54,-55,-59,-68,-69,]),'LT':([34,50,51,52,58,84,104,105,106,107,108,109,125,140,],[-67,-56,-57,-58,88,-60,-51,-52,-53,-54,-55,-59,-68,-69,]),'LE':([34,50,51,52,58,84,104,105,106,107,108,109,125,140,],[-67,-56,-57,-58,89,-60,-51,-52,-53,-54,-55,-59,-68,-69,]),'GT':([34,50,51,52,58,84,104,105,106,107,108,109,125,140,],[-67,-56,-57,-58,90,-60,-51,-52,-53,-54,-55,-59,-68,-69,]),'GE':([34,50,51,52,58,84,104,105,106,107,108,109,125,140,],[-67,-56,-57,-58,91,-60,-51,-52,-53,-54,-55,-59,-68,-69,]),'NE':([34,50,51,52,58,84,104,105,106,107,108,109,125,140,],[-67,-56,-57,-58,93,-60,-51,-52,-53,-54,-55,-59,-68,-69,]),'RPAREN':([34,50,51,52,84,85,100,104,105,106,107,108,109,121,122,124,125,133,139,140,],[-67,-56,-57,-58,-60,109,125,-51,-52,-53,-54,-55,-59,129,130,131,-68,140,150,-69,]),'THEN':([34,50,51,52,56,57,84,104,105,106,107,108,109,113,114,115,116,117,118,125,140,],[-67,-56,-57,-58,86,87,-60,-51,-52,-53,-54,-55,-59,-61,-62,-63,-64,-65,-66,-68,-69,]),'TO':([34,50,51,52,84,104,105,106,107,108,109,119,120,125,140,],[-67,-56,-57,-58,-60,-51,-52,-53,-54,-55,-59,127,128,-68,-69,]),'STEP':([34,50,51,52,84,104,105,106,107,108,109,125,134,135,136,140,],[-67,-56,-57,-58,-60,-51,-52,-53,-54,-55,-59,-68,142,145,145,-69,]),}
_lr_action = {}
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'program':([0,],[1,]),'statement':([0,1,],[2,9,]),'command':([4,],[10,]),'variable':([13,14,16,18,47,49,53,69,70,71,76,79,80,81,82,83,88,89,90,91,92,93,94,126,127,128,137,138,142,145,],[33,37,52,52,52,52,52,52,52,101,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,52,]),'varlist':([14,],[35,]),'numlist':([15,],[38,]),'number':([15,72,],[40,102,]),'plist':([16,],[44,]),'pitem':([16,76,],[46,103,]),'expr':([16,18,47,49,53,69,70,76,79,80,81,82,83,88,89,90,91,92,93,94,126,127,128,137,138,142,145,],[48,58,78,84,85,98,100,48,104,105,106,107,108,113,114,115,116,117,118,119,133,134,136,147,149,151,151,]),'relexpr':([18,],[56,]),'dimlist':([27,],[65,]),'dimitem':([27,96,],[67,123,]),'optend':([44,],[75,]),'optstep':([134,135,136,],[141,144,146,]),'empty':([134,135,136,],[143,143,143,]),}
_lr_goto = {}
for _k, _v in _lr_goto_items.items():
for _x, _y in zip(_v[0], _v[1]):
if not _x in _lr_goto: _lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> program","S'",1,None,None,None),
('program -> program statement','program',2,'p_program','basparse.py',21),
('program -> statement','program',1,'p_program','basparse.py',22),
('program -> error','program',1,'p_program_error','basparse.py',41),
('statement -> INTEGER command NEWLINE','statement',3,'p_statement','basparse.py',49),
('statement -> RUN NEWLINE','statement',2,'p_statement_interactive','basparse.py',62),
('statement -> LIST NEWLINE','statement',2,'p_statement_interactive','basparse.py',63),
('statement -> NEW NEWLINE','statement',2,'p_statement_interactive','basparse.py',64),
('statement -> INTEGER NEWLINE','statement',2,'p_statement_blank','basparse.py',71),
('statement -> INTEGER error NEWLINE','statement',3,'p_statement_bad','basparse.py',78),
('statement -> NEWLINE','statement',1,'p_statement_newline','basparse.py',87),
('command -> LET variable EQUALS expr','command',4,'p_command_let','basparse.py',94),
('command -> LET variable EQUALS error','command',4,'p_command_let_bad','basparse.py',99),
('command -> READ varlist','command',2,'p_command_read','basparse.py',106),
('command -> READ error','command',2,'p_command_read_bad','basparse.py',111),
('command -> DATA numlist','command',2,'p_command_data','basparse.py',118),
('command -> DATA error','command',2,'p_command_data_bad','basparse.py',123),
('command -> PRINT plist optend','command',3,'p_command_print','basparse.py',130),
('command -> PRINT error','command',2,'p_command_print_bad','basparse.py',135),
('optend -> COMMA','optend',1,'p_optend','basparse.py',142),
('optend -> SEMI','optend',1,'p_optend','basparse.py',143),
('optend -> <empty>','optend',0,'p_optend','basparse.py',144),
('command -> PRINT','command',1,'p_command_print_empty','basparse.py',154),
('command -> GOTO INTEGER','command',2,'p_command_goto','basparse.py',161),
('command -> GOTO error','command',2,'p_command_goto_bad','basparse.py',166),
('command -> IF relexpr THEN INTEGER','command',4,'p_command_if','basparse.py',173),
('command -> IF error THEN INTEGER','command',4,'p_command_if_bad','basparse.py',178),
('command -> IF relexpr THEN error','command',4,'p_command_if_bad2','basparse.py',183),
('command -> FOR ID EQUALS expr TO expr optstep','command',7,'p_command_for','basparse.py',190),
('command -> FOR ID EQUALS error TO expr optstep','command',7,'p_command_for_bad_initial','basparse.py',195),
('command -> FOR ID EQUALS expr TO error optstep','command',7,'p_command_for_bad_final','basparse.py',200),
('command -> FOR ID EQUALS expr TO expr STEP error','command',8,'p_command_for_bad_step','basparse.py',205),
('optstep -> STEP expr','optstep',2,'p_optstep','basparse.py',212),
('optstep -> empty','optstep',1,'p_optstep','basparse.py',213),
('command -> NEXT ID','command',2,'p_command_next','basparse.py',223),
('command -> NEXT error','command',2,'p_command_next_bad','basparse.py',229),
('command -> END','command',1,'p_command_end','basparse.py',236),
('command -> REM','command',1,'p_command_rem','basparse.py',243),
('command -> STOP','command',1,'p_command_stop','basparse.py',250),
('command -> DEF ID LPAREN ID RPAREN EQUALS expr','command',7,'p_command_def','basparse.py',257),
('command -> DEF ID LPAREN ID RPAREN EQUALS error','command',7,'p_command_def_bad_rhs','basparse.py',262),
('command -> DEF ID LPAREN error RPAREN EQUALS expr','command',7,'p_command_def_bad_arg','basparse.py',267),
('command -> GOSUB INTEGER','command',2,'p_command_gosub','basparse.py',274),
('command -> GOSUB error','command',2,'p_command_gosub_bad','basparse.py',279),
('command -> RETURN','command',1,'p_command_return','basparse.py',286),
('command -> DIM dimlist','command',2,'p_command_dim','basparse.py',293),
('command -> DIM error','command',2,'p_command_dim_bad','basparse.py',298),
('dimlist -> dimlist COMMA dimitem','dimlist',3,'p_dimlist','basparse.py',305),
('dimlist -> dimitem','dimlist',1,'p_dimlist','basparse.py',306),
('dimitem -> ID LPAREN INTEGER RPAREN','dimitem',4,'p_dimitem_single','basparse.py',317),
('dimitem -> ID LPAREN INTEGER COMMA INTEGER RPAREN','dimitem',6,'p_dimitem_double','basparse.py',322),
('expr -> expr PLUS expr','expr',3,'p_expr_binary','basparse.py',329),
('expr -> expr MINUS expr','expr',3,'p_expr_binary','basparse.py',330),
('expr -> expr TIMES expr','expr',3,'p_expr_binary','basparse.py',331),
('expr -> expr DIVIDE expr','expr',3,'p_expr_binary','basparse.py',332),
('expr -> expr POWER expr','expr',3,'p_expr_binary','basparse.py',333),
('expr -> INTEGER','expr',1,'p_expr_number','basparse.py',339),
('expr -> FLOAT','expr',1,'p_expr_number','basparse.py',340),
('expr -> variable','expr',1,'p_expr_variable','basparse.py',345),
('expr -> LPAREN expr RPAREN','expr',3,'p_expr_group','basparse.py',350),
('expr -> MINUS expr','expr',2,'p_expr_unary','basparse.py',355),
('relexpr -> expr LT expr','relexpr',3,'p_relexpr','basparse.py',362),
('relexpr -> expr LE expr','relexpr',3,'p_relexpr','basparse.py',363),
('relexpr -> expr GT expr','relexpr',3,'p_relexpr','basparse.py',364),
('relexpr -> expr GE expr','relexpr',3,'p_relexpr','basparse.py',365),
('relexpr -> expr EQUALS expr','relexpr',3,'p_relexpr','basparse.py',366),
('relexpr -> expr NE expr','relexpr',3,'p_relexpr','basparse.py',367),
('variable -> ID','variable',1,'p_variable','basparse.py',374),
('variable -> ID LPAREN expr RPAREN','variable',4,'p_variable','basparse.py',375),
('variable -> ID LPAREN expr COMMA expr RPAREN','variable',6,'p_variable','basparse.py',376),
('varlist -> varlist COMMA variable','varlist',3,'p_varlist','basparse.py',388),
('varlist -> variable','varlist',1,'p_varlist','basparse.py',389),
('numlist -> numlist COMMA number','numlist',3,'p_numlist','basparse.py',400),
('numlist -> number','numlist',1,'p_numlist','basparse.py',401),
('number -> INTEGER','number',1,'p_number','basparse.py',413),
('number -> FLOAT','number',1,'p_number','basparse.py',414),
('number -> MINUS INTEGER','number',2,'p_number_signed','basparse.py',421),
('number -> MINUS FLOAT','number',2,'p_number_signed','basparse.py',422),
('plist -> plist COMMA pitem','plist',3,'p_plist','basparse.py',430),
('plist -> pitem','plist',1,'p_plist','basparse.py',431),
('pitem -> STRING','pitem',1,'p_item_string','basparse.py',440),
('pitem -> STRING expr','pitem',2,'p_item_string_expr','basparse.py',445),
('pitem -> expr','pitem',1,'p_item_expr','basparse.py',450),
('empty -> <empty>','empty',0,'p_empty','basparse.py',457),
]
|
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'leftPLUSMINUSleftTIMESDIVIDEleftPOWERrightUMINUSCOMMA DATA DEF DIM DIVIDE END EQUALS FLOAT FOR GE GOSUB GOTO GT ID IF INTEGER LE LET LIST LPAREN LT MINUS NE NEW NEWLINE NEXT PLUS POWER PRINT READ REM RETURN RPAREN RUN SEMI STEP STOP STRING THEN TIMES TOprogram : program statement\n | statementprogram : errorstatement : INTEGER command NEWLINEstatement : RUN NEWLINE\n | LIST NEWLINE\n | NEW NEWLINEstatement : INTEGER NEWLINEstatement : INTEGER error NEWLINEstatement : NEWLINEcommand : LET variable EQUALS exprcommand : LET variable EQUALS errorcommand : READ varlistcommand : READ errorcommand : DATA numlistcommand : DATA errorcommand : PRINT plist optendcommand : PRINT erroroptend : COMMA \n | SEMI\n |command : PRINTcommand : GOTO INTEGERcommand : GOTO errorcommand : IF relexpr THEN INTEGERcommand : IF error THEN INTEGERcommand : IF relexpr THEN errorcommand : FOR ID EQUALS expr TO expr optstepcommand : FOR ID EQUALS error TO expr optstepcommand : FOR ID EQUALS expr TO error optstepcommand : FOR ID EQUALS expr TO expr STEP erroroptstep : STEP expr\n | emptycommand : NEXT IDcommand : NEXT errorcommand : ENDcommand : REMcommand : STOPcommand : DEF ID LPAREN ID RPAREN EQUALS exprcommand : DEF ID LPAREN ID RPAREN EQUALS errorcommand : DEF ID LPAREN error RPAREN EQUALS exprcommand : GOSUB INTEGERcommand : GOSUB errorcommand : RETURNcommand : DIM dimlistcommand : DIM errordimlist : dimlist COMMA dimitem\n | dimitemdimitem : ID LPAREN INTEGER RPARENdimitem : ID LPAREN INTEGER COMMA INTEGER RPARENexpr : expr PLUS expr\n | expr MINUS expr\n | expr TIMES expr\n | expr DIVIDE expr\n | expr POWER exprexpr : INTEGER\n | FLOATexpr : variableexpr : LPAREN expr RPARENexpr : MINUS expr %prec UMINUSrelexpr : expr LT expr\n | expr LE expr\n | expr GT expr\n | expr GE expr\n | expr EQUALS expr\n | expr NE exprvariable : ID\n | ID LPAREN expr RPAREN\n | ID LPAREN expr COMMA expr RPARENvarlist : varlist COMMA variable\n | variablenumlist : numlist COMMA number\n | numbernumber : INTEGER\n | FLOATnumber : MINUS INTEGER\n | MINUS FLOATplist : plist COMMA pitem\n | pitempitem : STRINGpitem : STRING exprpitem : exprempty : '
_lr_action_items = {'error': ([0, 4, 14, 15, 16, 17, 18, 20, 25, 27, 69, 86, 94, 95, 127, 137, 142], [3, 12, 36, 39, 45, 55, 57, 61, 64, 66, 99, 111, 120, 122, 135, 148, 152]), 'INTEGER': ([0, 1, 2, 3, 5, 9, 11, 15, 16, 17, 18, 25, 28, 29, 30, 31, 32, 43, 47, 49, 53, 69, 70, 72, 76, 79, 80, 81, 82, 83, 86, 87, 88, 89, 90, 91, 92, 93, 94, 97, 126, 127, 128, 132, 137, 138, 142, 145], [4, 4, -2, -3, -10, -1, -8, 41, 50, 54, 50, 63, -5, -6, -7, -4, -9, 73, 50, 50, 50, 50, 50, 41, 50, 50, 50, 50, 50, 50, 110, 112, 50, 50, 50, 50, 50, 50, 50, 124, 50, 50, 50, 139, 50, 50, 50, 50]), 'RUN': ([0, 1, 2, 3, 5, 9, 11, 28, 29, 30, 31, 32], [6, 6, -2, -3, -10, -1, -8, -5, -6, -7, -4, -9]), 'LIST': ([0, 1, 2, 3, 5, 9, 11, 28, 29, 30, 31, 32], [7, 7, -2, -3, -10, -1, -8, -5, -6, -7, -4, -9]), 'NEW': ([0, 1, 2, 3, 5, 9, 11, 28, 29, 30, 31, 32], [8, 8, -2, -3, -10, -1, -8, -5, -6, -7, -4, -9]), 'NEWLINE': ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 21, 22, 23, 26, 28, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 50, 51, 52, 54, 55, 60, 61, 63, 64, 65, 66, 67, 73, 74, 75, 76, 77, 78, 84, 98, 99, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 123, 125, 131, 134, 135, 136, 140, 141, 143, 144, 146, 147, 148, 149, 150, 151, 152], [5, 5, -2, -3, 11, -10, 28, 29, 30, -1, 31, -8, 32, -22, -36, -37, -38, -44, -5, -6, -7, -4, -9, -67, -13, -14, -71, -15, -16, -73, -74, -75, -21, -18, -79, -80, -82, -56, -57, -58, -23, -24, -34, -35, -42, -43, -45, -46, -48, -76, -77, -17, -19, -20, -81, -60, -11, -12, -70, -72, -78, -51, -52, -53, -54, -55, -59, -25, -27, -26, -47, -68, -49, -83, -83, -83, -69, -28, -33, -30, -29, -39, -40, -41, -50, -32, -31]), '$end': ([1, 2, 3, 5, 9, 11, 28, 29, 30, 31, 32], [0, -2, -3, -10, -1, -8, -5, -6, -7, -4, -9]), 'LET': ([4], [13]), 'READ': ([4], [14]), 'DATA': ([4], [15]), 'PRINT': ([4], [16]), 'GOTO': ([4], [17]), 'IF': ([4], [18]), 'FOR': ([4], [19]), 'NEXT': ([4], [20]), 'END': ([4], [21]), 'REM': ([4], [22]), 'STOP': ([4], [23]), 'DEF': ([4], [24]), 'GOSUB': ([4], [25]), 'RETURN': ([4], [26]), 'DIM': ([4], [27]), 'ID': ([13, 14, 16, 18, 19, 20, 24, 27, 47, 49, 53, 69, 70, 71, 76, 79, 80, 81, 82, 83, 88, 89, 90, 91, 92, 93, 94, 95, 96, 126, 127, 128, 137, 138, 142, 145], [34, 34, 34, 34, 59, 60, 62, 68, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 121, 68, 34, 34, 34, 34, 34, 34, 34]), 'FLOAT': ([15, 16, 18, 43, 47, 49, 53, 69, 70, 72, 76, 79, 80, 81, 82, 83, 88, 89, 90, 91, 92, 93, 94, 126, 127, 128, 137, 138, 142, 145], [42, 51, 51, 74, 51, 51, 51, 51, 51, 42, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51]), 'MINUS': ([15, 16, 18, 34, 47, 48, 49, 50, 51, 52, 53, 58, 69, 70, 72, 76, 78, 79, 80, 81, 82, 83, 84, 85, 88, 89, 90, 91, 92, 93, 94, 98, 100, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 119, 125, 126, 127, 128, 133, 134, 136, 137, 138, 140, 142, 145, 147, 149, 151], [43, 49, 49, -67, 49, 80, 49, -56, -57, -58, 49, 80, 49, 49, 43, 49, 80, 49, 49, 49, 49, 49, -60, 80, 49, 49, 49, 49, 49, 49, 49, 80, 80, -51, -52, -53, -54, -55, -59, 80, 80, 80, 80, 80, 80, 80, -68, 49, 49, 49, 80, 80, 80, 49, 49, -69, 49, 49, 80, 80, 80]), 'STRING': ([16, 76], [47, 47]), 'LPAREN': ([16, 18, 34, 47, 49, 53, 62, 68, 69, 70, 76, 79, 80, 81, 82, 83, 88, 89, 90, 91, 92, 93, 94, 126, 127, 128, 137, 138, 142, 145], [53, 53, 70, 53, 53, 53, 95, 97, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53]), 'EQUALS': ([33, 34, 50, 51, 52, 58, 59, 84, 104, 105, 106, 107, 108, 109, 125, 129, 130, 140], [69, -67, -56, -57, -58, 92, 94, -60, -51, -52, -53, -54, -55, -59, -68, 137, 138, -69]), 'COMMA': ([34, 35, 37, 38, 40, 41, 42, 44, 46, 47, 48, 50, 51, 52, 65, 67, 73, 74, 78, 84, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 123, 124, 125, 131, 140, 150], [-67, 71, -71, 72, -73, -74, -75, 76, -79, -80, -82, -56, -57, -58, 96, -48, -76, -77, -81, -60, 126, -70, -72, -78, -51, -52, -53, -54, -55, -59, -47, 132, -68, -49, -69, -50]), 'PLUS': ([34, 48, 50, 51, 52, 58, 78, 84, 85, 98, 100, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 119, 125, 133, 134, 136, 140, 147, 149, 151], [-67, 79, -56, -57, -58, 79, 79, -60, 79, 79, 79, -51, -52, -53, -54, -55, -59, 79, 79, 79, 79, 79, 79, 79, -68, 79, 79, 79, -69, 79, 79, 79]), 'TIMES': ([34, 48, 50, 51, 52, 58, 78, 84, 85, 98, 100, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 119, 125, 133, 134, 136, 140, 147, 149, 151], [-67, 81, -56, -57, -58, 81, 81, -60, 81, 81, 81, 81, 81, -53, -54, -55, -59, 81, 81, 81, 81, 81, 81, 81, -68, 81, 81, 81, -69, 81, 81, 81]), 'DIVIDE': ([34, 48, 50, 51, 52, 58, 78, 84, 85, 98, 100, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 119, 125, 133, 134, 136, 140, 147, 149, 151], [-67, 82, -56, -57, -58, 82, 82, -60, 82, 82, 82, 82, 82, -53, -54, -55, -59, 82, 82, 82, 82, 82, 82, 82, -68, 82, 82, 82, -69, 82, 82, 82]), 'POWER': ([34, 48, 50, 51, 52, 58, 78, 84, 85, 98, 100, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 119, 125, 133, 134, 136, 140, 147, 149, 151], [-67, 83, -56, -57, -58, 83, 83, -60, 83, 83, 83, 83, 83, 83, 83, -55, -59, 83, 83, 83, 83, 83, 83, 83, -68, 83, 83, 83, -69, 83, 83, 83]), 'SEMI': ([34, 44, 46, 47, 48, 50, 51, 52, 78, 84, 103, 104, 105, 106, 107, 108, 109, 125, 140], [-67, 77, -79, -80, -82, -56, -57, -58, -81, -60, -78, -51, -52, -53, -54, -55, -59, -68, -69]), 'LT': ([34, 50, 51, 52, 58, 84, 104, 105, 106, 107, 108, 109, 125, 140], [-67, -56, -57, -58, 88, -60, -51, -52, -53, -54, -55, -59, -68, -69]), 'LE': ([34, 50, 51, 52, 58, 84, 104, 105, 106, 107, 108, 109, 125, 140], [-67, -56, -57, -58, 89, -60, -51, -52, -53, -54, -55, -59, -68, -69]), 'GT': ([34, 50, 51, 52, 58, 84, 104, 105, 106, 107, 108, 109, 125, 140], [-67, -56, -57, -58, 90, -60, -51, -52, -53, -54, -55, -59, -68, -69]), 'GE': ([34, 50, 51, 52, 58, 84, 104, 105, 106, 107, 108, 109, 125, 140], [-67, -56, -57, -58, 91, -60, -51, -52, -53, -54, -55, -59, -68, -69]), 'NE': ([34, 50, 51, 52, 58, 84, 104, 105, 106, 107, 108, 109, 125, 140], [-67, -56, -57, -58, 93, -60, -51, -52, -53, -54, -55, -59, -68, -69]), 'RPAREN': ([34, 50, 51, 52, 84, 85, 100, 104, 105, 106, 107, 108, 109, 121, 122, 124, 125, 133, 139, 140], [-67, -56, -57, -58, -60, 109, 125, -51, -52, -53, -54, -55, -59, 129, 130, 131, -68, 140, 150, -69]), 'THEN': ([34, 50, 51, 52, 56, 57, 84, 104, 105, 106, 107, 108, 109, 113, 114, 115, 116, 117, 118, 125, 140], [-67, -56, -57, -58, 86, 87, -60, -51, -52, -53, -54, -55, -59, -61, -62, -63, -64, -65, -66, -68, -69]), 'TO': ([34, 50, 51, 52, 84, 104, 105, 106, 107, 108, 109, 119, 120, 125, 140], [-67, -56, -57, -58, -60, -51, -52, -53, -54, -55, -59, 127, 128, -68, -69]), 'STEP': ([34, 50, 51, 52, 84, 104, 105, 106, 107, 108, 109, 125, 134, 135, 136, 140], [-67, -56, -57, -58, -60, -51, -52, -53, -54, -55, -59, -68, 142, 145, 145, -69])}
_lr_action = {}
for (_k, _v) in _lr_action_items.items():
for (_x, _y) in zip(_v[0], _v[1]):
if not _x in _lr_action:
_lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'program': ([0], [1]), 'statement': ([0, 1], [2, 9]), 'command': ([4], [10]), 'variable': ([13, 14, 16, 18, 47, 49, 53, 69, 70, 71, 76, 79, 80, 81, 82, 83, 88, 89, 90, 91, 92, 93, 94, 126, 127, 128, 137, 138, 142, 145], [33, 37, 52, 52, 52, 52, 52, 52, 52, 101, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52]), 'varlist': ([14], [35]), 'numlist': ([15], [38]), 'number': ([15, 72], [40, 102]), 'plist': ([16], [44]), 'pitem': ([16, 76], [46, 103]), 'expr': ([16, 18, 47, 49, 53, 69, 70, 76, 79, 80, 81, 82, 83, 88, 89, 90, 91, 92, 93, 94, 126, 127, 128, 137, 138, 142, 145], [48, 58, 78, 84, 85, 98, 100, 48, 104, 105, 106, 107, 108, 113, 114, 115, 116, 117, 118, 119, 133, 134, 136, 147, 149, 151, 151]), 'relexpr': ([18], [56]), 'dimlist': ([27], [65]), 'dimitem': ([27, 96], [67, 123]), 'optend': ([44], [75]), 'optstep': ([134, 135, 136], [141, 144, 146]), 'empty': ([134, 135, 136], [143, 143, 143])}
_lr_goto = {}
for (_k, _v) in _lr_goto_items.items():
for (_x, _y) in zip(_v[0], _v[1]):
if not _x in _lr_goto:
_lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [("S' -> program", "S'", 1, None, None, None), ('program -> program statement', 'program', 2, 'p_program', 'basparse.py', 21), ('program -> statement', 'program', 1, 'p_program', 'basparse.py', 22), ('program -> error', 'program', 1, 'p_program_error', 'basparse.py', 41), ('statement -> INTEGER command NEWLINE', 'statement', 3, 'p_statement', 'basparse.py', 49), ('statement -> RUN NEWLINE', 'statement', 2, 'p_statement_interactive', 'basparse.py', 62), ('statement -> LIST NEWLINE', 'statement', 2, 'p_statement_interactive', 'basparse.py', 63), ('statement -> NEW NEWLINE', 'statement', 2, 'p_statement_interactive', 'basparse.py', 64), ('statement -> INTEGER NEWLINE', 'statement', 2, 'p_statement_blank', 'basparse.py', 71), ('statement -> INTEGER error NEWLINE', 'statement', 3, 'p_statement_bad', 'basparse.py', 78), ('statement -> NEWLINE', 'statement', 1, 'p_statement_newline', 'basparse.py', 87), ('command -> LET variable EQUALS expr', 'command', 4, 'p_command_let', 'basparse.py', 94), ('command -> LET variable EQUALS error', 'command', 4, 'p_command_let_bad', 'basparse.py', 99), ('command -> READ varlist', 'command', 2, 'p_command_read', 'basparse.py', 106), ('command -> READ error', 'command', 2, 'p_command_read_bad', 'basparse.py', 111), ('command -> DATA numlist', 'command', 2, 'p_command_data', 'basparse.py', 118), ('command -> DATA error', 'command', 2, 'p_command_data_bad', 'basparse.py', 123), ('command -> PRINT plist optend', 'command', 3, 'p_command_print', 'basparse.py', 130), ('command -> PRINT error', 'command', 2, 'p_command_print_bad', 'basparse.py', 135), ('optend -> COMMA', 'optend', 1, 'p_optend', 'basparse.py', 142), ('optend -> SEMI', 'optend', 1, 'p_optend', 'basparse.py', 143), ('optend -> <empty>', 'optend', 0, 'p_optend', 'basparse.py', 144), ('command -> PRINT', 'command', 1, 'p_command_print_empty', 'basparse.py', 154), ('command -> GOTO INTEGER', 'command', 2, 'p_command_goto', 'basparse.py', 161), ('command -> GOTO error', 'command', 2, 'p_command_goto_bad', 'basparse.py', 166), ('command -> IF relexpr THEN INTEGER', 'command', 4, 'p_command_if', 'basparse.py', 173), ('command -> IF error THEN INTEGER', 'command', 4, 'p_command_if_bad', 'basparse.py', 178), ('command -> IF relexpr THEN error', 'command', 4, 'p_command_if_bad2', 'basparse.py', 183), ('command -> FOR ID EQUALS expr TO expr optstep', 'command', 7, 'p_command_for', 'basparse.py', 190), ('command -> FOR ID EQUALS error TO expr optstep', 'command', 7, 'p_command_for_bad_initial', 'basparse.py', 195), ('command -> FOR ID EQUALS expr TO error optstep', 'command', 7, 'p_command_for_bad_final', 'basparse.py', 200), ('command -> FOR ID EQUALS expr TO expr STEP error', 'command', 8, 'p_command_for_bad_step', 'basparse.py', 205), ('optstep -> STEP expr', 'optstep', 2, 'p_optstep', 'basparse.py', 212), ('optstep -> empty', 'optstep', 1, 'p_optstep', 'basparse.py', 213), ('command -> NEXT ID', 'command', 2, 'p_command_next', 'basparse.py', 223), ('command -> NEXT error', 'command', 2, 'p_command_next_bad', 'basparse.py', 229), ('command -> END', 'command', 1, 'p_command_end', 'basparse.py', 236), ('command -> REM', 'command', 1, 'p_command_rem', 'basparse.py', 243), ('command -> STOP', 'command', 1, 'p_command_stop', 'basparse.py', 250), ('command -> DEF ID LPAREN ID RPAREN EQUALS expr', 'command', 7, 'p_command_def', 'basparse.py', 257), ('command -> DEF ID LPAREN ID RPAREN EQUALS error', 'command', 7, 'p_command_def_bad_rhs', 'basparse.py', 262), ('command -> DEF ID LPAREN error RPAREN EQUALS expr', 'command', 7, 'p_command_def_bad_arg', 'basparse.py', 267), ('command -> GOSUB INTEGER', 'command', 2, 'p_command_gosub', 'basparse.py', 274), ('command -> GOSUB error', 'command', 2, 'p_command_gosub_bad', 'basparse.py', 279), ('command -> RETURN', 'command', 1, 'p_command_return', 'basparse.py', 286), ('command -> DIM dimlist', 'command', 2, 'p_command_dim', 'basparse.py', 293), ('command -> DIM error', 'command', 2, 'p_command_dim_bad', 'basparse.py', 298), ('dimlist -> dimlist COMMA dimitem', 'dimlist', 3, 'p_dimlist', 'basparse.py', 305), ('dimlist -> dimitem', 'dimlist', 1, 'p_dimlist', 'basparse.py', 306), ('dimitem -> ID LPAREN INTEGER RPAREN', 'dimitem', 4, 'p_dimitem_single', 'basparse.py', 317), ('dimitem -> ID LPAREN INTEGER COMMA INTEGER RPAREN', 'dimitem', 6, 'p_dimitem_double', 'basparse.py', 322), ('expr -> expr PLUS expr', 'expr', 3, 'p_expr_binary', 'basparse.py', 329), ('expr -> expr MINUS expr', 'expr', 3, 'p_expr_binary', 'basparse.py', 330), ('expr -> expr TIMES expr', 'expr', 3, 'p_expr_binary', 'basparse.py', 331), ('expr -> expr DIVIDE expr', 'expr', 3, 'p_expr_binary', 'basparse.py', 332), ('expr -> expr POWER expr', 'expr', 3, 'p_expr_binary', 'basparse.py', 333), ('expr -> INTEGER', 'expr', 1, 'p_expr_number', 'basparse.py', 339), ('expr -> FLOAT', 'expr', 1, 'p_expr_number', 'basparse.py', 340), ('expr -> variable', 'expr', 1, 'p_expr_variable', 'basparse.py', 345), ('expr -> LPAREN expr RPAREN', 'expr', 3, 'p_expr_group', 'basparse.py', 350), ('expr -> MINUS expr', 'expr', 2, 'p_expr_unary', 'basparse.py', 355), ('relexpr -> expr LT expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 362), ('relexpr -> expr LE expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 363), ('relexpr -> expr GT expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 364), ('relexpr -> expr GE expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 365), ('relexpr -> expr EQUALS expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 366), ('relexpr -> expr NE expr', 'relexpr', 3, 'p_relexpr', 'basparse.py', 367), ('variable -> ID', 'variable', 1, 'p_variable', 'basparse.py', 374), ('variable -> ID LPAREN expr RPAREN', 'variable', 4, 'p_variable', 'basparse.py', 375), ('variable -> ID LPAREN expr COMMA expr RPAREN', 'variable', 6, 'p_variable', 'basparse.py', 376), ('varlist -> varlist COMMA variable', 'varlist', 3, 'p_varlist', 'basparse.py', 388), ('varlist -> variable', 'varlist', 1, 'p_varlist', 'basparse.py', 389), ('numlist -> numlist COMMA number', 'numlist', 3, 'p_numlist', 'basparse.py', 400), ('numlist -> number', 'numlist', 1, 'p_numlist', 'basparse.py', 401), ('number -> INTEGER', 'number', 1, 'p_number', 'basparse.py', 413), ('number -> FLOAT', 'number', 1, 'p_number', 'basparse.py', 414), ('number -> MINUS INTEGER', 'number', 2, 'p_number_signed', 'basparse.py', 421), ('number -> MINUS FLOAT', 'number', 2, 'p_number_signed', 'basparse.py', 422), ('plist -> plist COMMA pitem', 'plist', 3, 'p_plist', 'basparse.py', 430), ('plist -> pitem', 'plist', 1, 'p_plist', 'basparse.py', 431), ('pitem -> STRING', 'pitem', 1, 'p_item_string', 'basparse.py', 440), ('pitem -> STRING expr', 'pitem', 2, 'p_item_string_expr', 'basparse.py', 445), ('pitem -> expr', 'pitem', 1, 'p_item_expr', 'basparse.py', 450), ('empty -> <empty>', 'empty', 0, 'p_empty', 'basparse.py', 457)]
|
#-*- coding: utf8 -*-
class P3PMiddleware(object):
def process_response(self, request, response):
response['P3P'] = 'CP="CAO PSA OUR"'
return response
|
class P3Pmiddleware(object):
def process_response(self, request, response):
response['P3P'] = 'CP="CAO PSA OUR"'
return response
|
# Copyright 2018 Databricks, Inc.
VERSION = '0.7.0.dev'
|
version = '0.7.0.dev'
|
#!/usr/bin/env python
'''
This script prints Hello World!
'''
print('Hello, World!')
|
"""
This script prints Hello World!
"""
print('Hello, World!')
|
__all__ = ["InvalidECFGFormatException"]
class InvalidECFGFormatException(Exception):
pass
|
__all__ = ['InvalidECFGFormatException']
class Invalidecfgformatexception(Exception):
pass
|
r=int(input('banyaknya angka:'))
data=[]
for i in range (r): #v
n=int(input("Enter Integer {}:".format(i+1))) #v
data.append(n) #v
m=10**(r-1)
for i in range (r):
y=int(data[i]*m)
print(y)
m=m/10
#print(r);
|
r = int(input('banyaknya angka:'))
data = []
for i in range(r):
n = int(input('Enter Integer {}:'.format(i + 1)))
data.append(n)
m = 10 ** (r - 1)
for i in range(r):
y = int(data[i] * m)
print(y)
m = m / 10
|
def define_display_nodes(tree,nodemap,unscoped_vectors=False,looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> display_nodes;\n'
display_nodes = tree.findall('.//Display')
for dn in display_nodes:
node_id = str(nodemap[dn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap))+'*i+'+node_id
s += '\t\t\tdisplay_nodes.push_back('+ node_id + ');\n'
s += '\n'
return s
def define_rate_nodes(tree, nodemap,unscoped_vectors=False,looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> rate_nodes;\n'
s += '\t\t\tstd::vector<MPILib::Time> rate_node_intervals;\n'
rate_nodes = tree.findall('.//Rate')
for rn in rate_nodes:
node_id = str(nodemap[rn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap))+'*i+'+node_id
t_interval = rn.attrib['t_interval']
s += '\t\t\trate_nodes.push_back('+ node_id + ');\n'
s += '\t\t\trate_node_intervals.push_back('+ t_interval + ');\n'
s += '\n'
return s
def define_density_nodes(tree,nodemap,unscoped_vectors=False,looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> density_nodes;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_start_times;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_end_times;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_intervals;\n'
density_nodes = tree.findall('.//Density')
for dn in density_nodes:
node_id = str(nodemap[dn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap))+'*i+'+node_id
t_start = dn.attrib['t_start']
t_end = dn.attrib['t_end']
t_interval = dn.attrib['t_interval']
s += '\t\t\tdensity_nodes.push_back('+ node_id + ');\n'
s += '\t\t\tdensity_node_start_times.push_back('+ t_start + ');\n'
s += '\t\t\tdensity_node_end_times.push_back('+ t_end + ');\n'
s += '\t\t\tdensity_node_intervals.push_back('+ t_interval + ');\n'
s += '\n'
return s
|
def define_display_nodes(tree, nodemap, unscoped_vectors=False, looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> display_nodes;\n'
display_nodes = tree.findall('.//Display')
for dn in display_nodes:
node_id = str(nodemap[dn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap)) + '*i+' + node_id
s += '\t\t\tdisplay_nodes.push_back(' + node_id + ');\n'
s += '\n'
return s
def define_rate_nodes(tree, nodemap, unscoped_vectors=False, looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> rate_nodes;\n'
s += '\t\t\tstd::vector<MPILib::Time> rate_node_intervals;\n'
rate_nodes = tree.findall('.//Rate')
for rn in rate_nodes:
node_id = str(nodemap[rn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap)) + '*i+' + node_id
t_interval = rn.attrib['t_interval']
s += '\t\t\trate_nodes.push_back(' + node_id + ');\n'
s += '\t\t\trate_node_intervals.push_back(' + t_interval + ');\n'
s += '\n'
return s
def define_density_nodes(tree, nodemap, unscoped_vectors=False, looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> density_nodes;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_start_times;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_end_times;\n'
s += '\t\t\tstd::vector<MPILib::Time> density_node_intervals;\n'
density_nodes = tree.findall('.//Density')
for dn in density_nodes:
node_id = str(nodemap[dn.attrib['node']])
if looped_definition:
node_id = str(len(nodemap)) + '*i+' + node_id
t_start = dn.attrib['t_start']
t_end = dn.attrib['t_end']
t_interval = dn.attrib['t_interval']
s += '\t\t\tdensity_nodes.push_back(' + node_id + ');\n'
s += '\t\t\tdensity_node_start_times.push_back(' + t_start + ');\n'
s += '\t\t\tdensity_node_end_times.push_back(' + t_end + ');\n'
s += '\t\t\tdensity_node_intervals.push_back(' + t_interval + ');\n'
s += '\n'
return s
|
def factorial(n):
if n==0:
return 1
else:
return factorial(n-1)*n
print(factorial(80))
|
def factorial(n):
if n == 0:
return 1
else:
return factorial(n - 1) * n
print(factorial(80))
|
# two_tasks.py
def task_reformat_temperature_data():
"""Reformats the raw temperature data file for easier analysis"""
return {
'file_dep': ['UK_Tmean_data.txt'],
'targets': ['UK_Tmean_data.reformatted.txt'],
'actions': ['python reformat_weather_data.py UK_Tmean_data.txt > UK_Tmean_data.reformatted.txt'],
}
def task_reformat_sunshine_data():
"""Reformats the raw sunshine data file for easier analysis"""
return {
'file_dep': ['UK_Sunshine_data.txt'],
'targets': ['UK_Sunshine_data.reformatted.txt'],
'actions': ['python reformat_weather_data.py UK_Sunshine_data.txt > UK_Sunshine_data.reformatted.txt'],
}
|
def task_reformat_temperature_data():
"""Reformats the raw temperature data file for easier analysis"""
return {'file_dep': ['UK_Tmean_data.txt'], 'targets': ['UK_Tmean_data.reformatted.txt'], 'actions': ['python reformat_weather_data.py UK_Tmean_data.txt > UK_Tmean_data.reformatted.txt']}
def task_reformat_sunshine_data():
"""Reformats the raw sunshine data file for easier analysis"""
return {'file_dep': ['UK_Sunshine_data.txt'], 'targets': ['UK_Sunshine_data.reformatted.txt'], 'actions': ['python reformat_weather_data.py UK_Sunshine_data.txt > UK_Sunshine_data.reformatted.txt']}
|
#Make sure that we handle keyword-only arguments correctly
def f(a, *varargs, kw1, kw2="has-default"):
pass
#OK
f(1, 2, 3, kw1=1)
f(1, 2, kw1=1, kw2=2)
#Not OK
f(1, 2, 3, kw1=1, kw3=3)
f(1, 2, 3, kw3=3)
#ODASA-5897
def analyze_member_access(msg, *, original, override, chk: 'default' = None):
pass
def ok():
return analyze_member_access(msg, original=original, chk=chk)
def bad():
return analyze_member_access(msg, original, chk=chk)
|
def f(a, *varargs, kw1, kw2='has-default'):
pass
f(1, 2, 3, kw1=1)
f(1, 2, kw1=1, kw2=2)
f(1, 2, 3, kw1=1, kw3=3)
f(1, 2, 3, kw3=3)
def analyze_member_access(msg, *, original, override, chk: 'default'=None):
pass
def ok():
return analyze_member_access(msg, original=original, chk=chk)
def bad():
return analyze_member_access(msg, original, chk=chk)
|
class Parser():
def __init__(self, config):
self._config_args = config
@property
def experiment_args(self):
return self._config_args["Experiment"]
@property
def train_dataset_args(self):
return self._config_args["Dataset - metatrain"]
@property
def valid_dataset_args(self):
return self._config_args["Dataset - metatest"]
@property
def model_args(self):
return self._config_args["Model"]
@property
def maml_args(self):
return self._config_args["MAML"]
@property
def training_args(self):
return self._config_args["training"]
def parse(self):
return self.experiment_args, self.train_dataset_args, self.valid_dataset_args, self.model_args, self.maml_args, self.training_args
|
class Parser:
def __init__(self, config):
self._config_args = config
@property
def experiment_args(self):
return self._config_args['Experiment']
@property
def train_dataset_args(self):
return self._config_args['Dataset - metatrain']
@property
def valid_dataset_args(self):
return self._config_args['Dataset - metatest']
@property
def model_args(self):
return self._config_args['Model']
@property
def maml_args(self):
return self._config_args['MAML']
@property
def training_args(self):
return self._config_args['training']
def parse(self):
return (self.experiment_args, self.train_dataset_args, self.valid_dataset_args, self.model_args, self.maml_args, self.training_args)
|
'''
According to the Wikipedia's article: "The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970."
Given a board with m by n cells, each cell has an initial state live (1) or dead (0). Each cell interacts with its eight neighbors (horizontal, vertical, diagonal) using the following four rules (taken from the above Wikipedia article):
Any live cell with fewer than two live neighbors dies, as if caused by under-population.
Any live cell with two or three live neighbors lives on to the next generation.
Any live cell with more than three live neighbors dies, as if by over-population..
Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.
Write a function to compute the next state (after one update) of the board given its current state.
Follow up:
Could you solve it in-place? Remember that the board needs to be updated at the same time: You cannot update some cells first and then use their updated values to update other cells.
In this question, we represent the board using a 2D array. In principle, the board is infinite, which would cause problems when the active area encroaches the border of the array. How would you address these problems?
Credits:
Special thanks to @jianchao.li.fighter for adding this problem and creating all test cases.
'''
class Solution(object):
def gameOfLife(self, board):
"""
:type board: List[List[int]]
:rtype: void Do not return anything, modify board in-place instead.
"""
if not board:
return
n = len(board)
m = len(board[0])
copy_board = [[board[i][j] for j in xrange(m)] for i in xrange(n)]
for i in xrange(n):
for j in xrange(m):
live_neighbors = 0
for x, y in [(1, 0), (-1, 0), (0, 1), (0, -1), (-1, -1), (-1, 1), (1, -1), (1, 1)]:
ii = i + x
jj = j + y
if 0 <= ii < n and 0 <= jj < m:
if copy_board[ii][jj] == 1:
live_neighbors += 1
if copy_board[i][j] == 1:
if live_neighbors < 2:
board[i][j] = 0
elif live_neighbors < 4:
board[i][j] = 1
else:
board[i][j] = 0
elif copy_board[i][j] == 0:
if live_neighbors == 3:
board[i][j] = 1
else:
board[i][j] = 0
|
"""
According to the Wikipedia's article: "The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970."
Given a board with m by n cells, each cell has an initial state live (1) or dead (0). Each cell interacts with its eight neighbors (horizontal, vertical, diagonal) using the following four rules (taken from the above Wikipedia article):
Any live cell with fewer than two live neighbors dies, as if caused by under-population.
Any live cell with two or three live neighbors lives on to the next generation.
Any live cell with more than three live neighbors dies, as if by over-population..
Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.
Write a function to compute the next state (after one update) of the board given its current state.
Follow up:
Could you solve it in-place? Remember that the board needs to be updated at the same time: You cannot update some cells first and then use their updated values to update other cells.
In this question, we represent the board using a 2D array. In principle, the board is infinite, which would cause problems when the active area encroaches the border of the array. How would you address these problems?
Credits:
Special thanks to @jianchao.li.fighter for adding this problem and creating all test cases.
"""
class Solution(object):
def game_of_life(self, board):
"""
:type board: List[List[int]]
:rtype: void Do not return anything, modify board in-place instead.
"""
if not board:
return
n = len(board)
m = len(board[0])
copy_board = [[board[i][j] for j in xrange(m)] for i in xrange(n)]
for i in xrange(n):
for j in xrange(m):
live_neighbors = 0
for (x, y) in [(1, 0), (-1, 0), (0, 1), (0, -1), (-1, -1), (-1, 1), (1, -1), (1, 1)]:
ii = i + x
jj = j + y
if 0 <= ii < n and 0 <= jj < m:
if copy_board[ii][jj] == 1:
live_neighbors += 1
if copy_board[i][j] == 1:
if live_neighbors < 2:
board[i][j] = 0
elif live_neighbors < 4:
board[i][j] = 1
else:
board[i][j] = 0
elif copy_board[i][j] == 0:
if live_neighbors == 3:
board[i][j] = 1
else:
board[i][j] = 0
|
class X:
def __init__(self,x):
print("Inside X ", x)
class Y:
def __init__(self):
print("Inside Y")
class Z(X,Y):
def __init__(self):
super().__init__(10)
print("Inside Z")
obj = Z()
|
class X:
def __init__(self, x):
print('Inside X ', x)
class Y:
def __init__(self):
print('Inside Y')
class Z(X, Y):
def __init__(self):
super().__init__(10)
print('Inside Z')
obj = z()
|
# -*- coding: utf-8 -*-
valor = float(input())
if 0 < valor <= 25:
print('Intervalo [0, 25]')
elif 25 < valor <= 50:
print('Intervalo (25, 50]')
elif 50 < valor <= 75:
print('Intervalo (50, 75]')
elif 75 < valor <= 100:
print('Intervalo (75, 100]')
else:
print('Fora de intervalo')
|
valor = float(input())
if 0 < valor <= 25:
print('Intervalo [0, 25]')
elif 25 < valor <= 50:
print('Intervalo (25, 50]')
elif 50 < valor <= 75:
print('Intervalo (50, 75]')
elif 75 < valor <= 100:
print('Intervalo (75, 100]')
else:
print('Fora de intervalo')
|
"""
Consider the following:
A string,
, of length where
.
An integer,
, where is a factor of
.
We can split
into subsegments where each subsegment, , consists of a contiguous block of characters in . Then, use each to create string
such that:
The characters in
are a subsequence of the characters in
.
Any repeat occurrence of a character is removed from the string such that each character in
occurs exactly once. In other words, if the character at some index in occurs at a previous index in , then do not include the character in string
.
Given
and , print lines where each line denotes string
.
Input Format
The first line contains a single string denoting
.
The second line contains an integer,
, denoting the length of each subsegment.
Constraints
, where is the length of It is guaranteed that is a multiple of
.
Output Format
Print
lines where each line contains string
.
Sample Input
AABCAAADA
3
Sample Output
AB
CA
AD
Explanation
String
is split into equal parts of length . We convert each to by removing any subsequent occurrences non-distinct characters in
:
We then print each on a new line.
"""
S, N = input(), int(input())
for part in zip(*[iter(S)] * N):
d = dict()
print(''.join([d.setdefault(c, c) for c in part if c not in d]))
|
"""
Consider the following:
A string,
, of length where
.
An integer,
, where is a factor of
.
We can split
into subsegments where each subsegment, , consists of a contiguous block of characters in . Then, use each to create string
such that:
The characters in
are a subsequence of the characters in
.
Any repeat occurrence of a character is removed from the string such that each character in
occurs exactly once. In other words, if the character at some index in occurs at a previous index in , then do not include the character in string
.
Given
and , print lines where each line denotes string
.
Input Format
The first line contains a single string denoting
.
The second line contains an integer,
, denoting the length of each subsegment.
Constraints
, where is the length of It is guaranteed that is a multiple of
.
Output Format
Print
lines where each line contains string
.
Sample Input
AABCAAADA
3
Sample Output
AB
CA
AD
Explanation
String
is split into equal parts of length . We convert each to by removing any subsequent occurrences non-distinct characters in
:
We then print each on a new line.
"""
(s, n) = (input(), int(input()))
for part in zip(*[iter(S)] * N):
d = dict()
print(''.join([d.setdefault(c, c) for c in part if c not in d]))
|
# SPDX-FileCopyrightText: Copyright (C) 2020-2021 Ryan Finnie
# SPDX-License-Identifier: MIT
def numfmt(
num,
fmt="{num.real:0.02f} {num.prefix}",
binary=False,
rollover=1.0,
limit=0,
prefixes=None,
):
"""Formats a number with decimal or binary prefixes
num: Input number
fmt: Format string of default repr/str output
binary: If True, use divide by 1024 and use IEC binary prefixes
rollover: Threshold to roll over to the next prefix
limit: Stop after a specified number of rollovers
prefixes: List of (decimal, binary) prefix strings, ascending
"""
# SPDX-SnippetComment: Originally from https://github.com/rfinnie/rf-pymods
# SPDX-SnippetCopyrightText: Copyright (C) 2020-2021 Ryan Finnie
# SPDX-LicenseInfoInSnippet: MIT
class NumberFormat(float):
prefix = ""
fmt = "{num.real:0.02f} {num.prefix}"
def __str__(self):
return self.fmt.format(num=self)
def __repr__(self):
return str(self)
if prefixes is None:
prefixes = [
("k", "Ki"),
("M", "Mi"),
("G", "Gi"),
("T", "Ti"),
("P", "Pi"),
("E", "Ei"),
("Z", "Zi"),
("Y", "Yi"),
]
divisor = 1024 if binary else 1000
if limit <= 0 or limit > len(prefixes):
limit = len(prefixes)
count = 0
p = ""
for prefix in prefixes:
if num < (divisor * rollover):
break
if count >= limit:
break
count += 1
num = num / float(divisor)
p = prefix[1] if binary else prefix[0]
ret = NumberFormat(num)
ret.fmt = fmt
ret.prefix = p
return ret
|
def numfmt(num, fmt='{num.real:0.02f} {num.prefix}', binary=False, rollover=1.0, limit=0, prefixes=None):
"""Formats a number with decimal or binary prefixes
num: Input number
fmt: Format string of default repr/str output
binary: If True, use divide by 1024 and use IEC binary prefixes
rollover: Threshold to roll over to the next prefix
limit: Stop after a specified number of rollovers
prefixes: List of (decimal, binary) prefix strings, ascending
"""
class Numberformat(float):
prefix = ''
fmt = '{num.real:0.02f} {num.prefix}'
def __str__(self):
return self.fmt.format(num=self)
def __repr__(self):
return str(self)
if prefixes is None:
prefixes = [('k', 'Ki'), ('M', 'Mi'), ('G', 'Gi'), ('T', 'Ti'), ('P', 'Pi'), ('E', 'Ei'), ('Z', 'Zi'), ('Y', 'Yi')]
divisor = 1024 if binary else 1000
if limit <= 0 or limit > len(prefixes):
limit = len(prefixes)
count = 0
p = ''
for prefix in prefixes:
if num < divisor * rollover:
break
if count >= limit:
break
count += 1
num = num / float(divisor)
p = prefix[1] if binary else prefix[0]
ret = number_format(num)
ret.fmt = fmt
ret.prefix = p
return ret
|
# Aula 13 - Desafio 47: Contagem de numeros pares
# Mostrar na tela todos os numeros pares entre 1 e 50
print('Entre 1 e 50, sao numeros pares:')
for n in range(2, 51, 2):
print(n, end=' ')
|
print('Entre 1 e 50, sao numeros pares:')
for n in range(2, 51, 2):
print(n, end=' ')
|
word1=input()
word2=input()
dict={}
alphabet="abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
for char in alphabet:
dict[char]=0
for ch in word1:
dict[ch]+=1
for ch in word2:
dict[ch]-=1
flag=False
sum=0
for char in dict:
count=dict[char]
sum+=count
if count == 1:
flag=True
if flag and count>1:
flag=False
break
if flag and sum==0:
print("Yes")
else:
print("No")
|
word1 = input()
word2 = input()
dict = {}
alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
for char in alphabet:
dict[char] = 0
for ch in word1:
dict[ch] += 1
for ch in word2:
dict[ch] -= 1
flag = False
sum = 0
for char in dict:
count = dict[char]
sum += count
if count == 1:
flag = True
if flag and count > 1:
flag = False
break
if flag and sum == 0:
print('Yes')
else:
print('No')
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Source code meta data
__author__ = 'Dalwar Hossain'
__email__ = 'dalwar.hossain@protonmail.com'
|
__author__ = 'Dalwar Hossain'
__email__ = 'dalwar.hossain@protonmail.com'
|
tm20 = toi = h = 0
print('-' * 25)
print(' CADASTRANDO PESSOAS ')
print('-' * 25)
while True:
id = int(input('digite a idade '))
sex = ' '
while sex not in 'MF':
sex = str(input('digite o sexo')).upper()
if id >= 18:
toi += 1
if sex == 'M':
h += 1
if sex == 'f' and id < 18:
tm20 += 1
r = ' '
while r not in "SN":
r = str(input('quer continuar?[s/n]')).upper()
if r == 'N':
break
print(f' {toi} pessoas tem mais de 18 anos')
print(f'o total de homens foi {h}')
print(f'total de mulheres com menos de 20 anos {tm20}')
|
tm20 = toi = h = 0
print('-' * 25)
print(' CADASTRANDO PESSOAS ')
print('-' * 25)
while True:
id = int(input('digite a idade '))
sex = ' '
while sex not in 'MF':
sex = str(input('digite o sexo')).upper()
if id >= 18:
toi += 1
if sex == 'M':
h += 1
if sex == 'f' and id < 18:
tm20 += 1
r = ' '
while r not in 'SN':
r = str(input('quer continuar?[s/n]')).upper()
if r == 'N':
break
print(f' {toi} pessoas tem mais de 18 anos')
print(f'o total de homens foi {h}')
print(f'total de mulheres com menos de 20 anos {tm20}')
|
# De uitwerking van 4-autoencoder.py moet hiervoor gedraaid worden!
voorspeller = tf.keras.models.Sequential([
tf.keras.layers.Dense(200, activation=tf.nn.relu),
tf.keras.layers.Dense(50, activation=tf.nn.relu),
tf.keras.layers.Dense(50, activation=tf.nn.relu),
tf.keras.layers.Dense(10, activation=tf.nn.softmax)
])
voorspeller.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
voorspeller.fit(xtr, ytr, epochs=10)
print(voorspeller.evaluate(xtr, ytr))
print("Performance op ruizige getallen:")
print(voorspeller.evaluate(xruis, y))
print("Performance van hetzelfde netwerk op door auto-encoder gereconstrueerde getallen:")
print(voorspeller.evaluate(reconstructed, y))
print("Als het goed is, flinke winst!")
|
voorspeller = tf.keras.models.Sequential([tf.keras.layers.Dense(200, activation=tf.nn.relu), tf.keras.layers.Dense(50, activation=tf.nn.relu), tf.keras.layers.Dense(50, activation=tf.nn.relu), tf.keras.layers.Dense(10, activation=tf.nn.softmax)])
voorspeller.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
voorspeller.fit(xtr, ytr, epochs=10)
print(voorspeller.evaluate(xtr, ytr))
print('Performance op ruizige getallen:')
print(voorspeller.evaluate(xruis, y))
print('Performance van hetzelfde netwerk op door auto-encoder gereconstrueerde getallen:')
print(voorspeller.evaluate(reconstructed, y))
print('Als het goed is, flinke winst!')
|
# Time: O(logn)
# Space: O(1)
class Solution(object):
def fixedPoint(self, A):
"""
:type A: List[int]
:rtype: int
"""
left, right = 0, len(A)-1
while left <= right:
mid = left + (right-left)//2
if A[mid] >= mid:
right = mid-1
else:
left = mid+1
return left if A[left] == left else -1
|
class Solution(object):
def fixed_point(self, A):
"""
:type A: List[int]
:rtype: int
"""
(left, right) = (0, len(A) - 1)
while left <= right:
mid = left + (right - left) // 2
if A[mid] >= mid:
right = mid - 1
else:
left = mid + 1
return left if A[left] == left else -1
|
# model settings
model = dict(
type='ImageClassifier',
pretrained=None,
backbone=dict(
type='OmzBackboneCls',
mode='train',
model_path='public/mobilenet-v2/FP32/mobilenet-v2.xml',
last_layer_name='relu6_4',
normalized_img_input=True
),
neck=dict(
type='GlobalAveragePooling'),
head=dict(
type='LinearClsHead',
num_classes=1000,
in_channels=1280,
loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
))
|
model = dict(type='ImageClassifier', pretrained=None, backbone=dict(type='OmzBackboneCls', mode='train', model_path='public/mobilenet-v2/FP32/mobilenet-v2.xml', last_layer_name='relu6_4', normalized_img_input=True), neck=dict(type='GlobalAveragePooling'), head=dict(type='LinearClsHead', num_classes=1000, in_channels=1280, loss=dict(type='CrossEntropyLoss', loss_weight=1.0)))
|
class Environment(object):
def __init__(self):
pass
def act(self, state, action):
pass
def end_state(self, state):
return True
def reset(self):
pass
def available_actions(self):
return None
|
class Environment(object):
def __init__(self):
pass
def act(self, state, action):
pass
def end_state(self, state):
return True
def reset(self):
pass
def available_actions(self):
return None
|
class NodeCalculator:
@staticmethod
def calculate_node_size(node, relationships):
linked_tables = list()
size = 0
for table_key, table_value in relationships.items():
if table_key == node:
for table in relationships[table_key]:
linked_tables.append(table)
if len(linked_tables) == 0:
size = 1
return size
else:
if node in linked_tables:
linked_tables = [table for table in linked_tables if table != node]
for table in linked_tables:
for table_key, table_value in relationships.items():
if table_key == table:
for table in relationships[table_key]:
if table not in linked_tables:
linked_tables.append(table)
size = size + len(linked_tables)
return size
@staticmethod
def calculate_usage_score(node, relationships):
linked_nodes = list()
for node_key, node_value in relationships.items():
if node in node_value:
linked_nodes.append(node_key)
used_keys = list()
for node_source in linked_nodes:
for node_key, node_value in relationships.items():
if node_source in node_value and node_key not in used_keys:
linked_nodes.append(node_key)
used_keys.append(node_key)
score = len(linked_nodes)
return score
@staticmethod
def calculate_root_score_level_0(root_scores, levels, grouped_weights):
for node_level_0 in levels[0]:
for weight in grouped_weights.keys():
if node_level_0 in grouped_weights[weight]:
root_scores[node_level_0] = weight
return root_scores
@staticmethod
def list_unique_nodes(relationships):
unique_nodes = list()
for node in relationships:
unique_nodes.append(node)
for relationship in relationships:
for node in relationships[relationship]:
if node not in unique_nodes:
unique_nodes.append(node)
return unique_nodes
@staticmethod
def calculate_root_score_remaining_levels(levels, root_scores, relationships, grouped_weights):
level = 1
max_level = NodeCalculator.find_max_level(levels=levels) - 1
unique_nodes = NodeCalculator.list_unique_nodes(relationships=relationships)
while level <= max_level:
if level in levels:
for node in levels[level]:
if node in unique_nodes:
node_weight = 0
for weight in grouped_weights.keys():
if node in grouped_weights[weight]:
node_weight = weight
all_present = 1
if node in relationships:
for source in relationships[node]:
if source not in root_scores:
all_present = 0
if all_present == 1:
if node in relationships:
for source in relationships[node]:
node_weight += root_scores[source]
root_scores[node] = node_weight
level += 1
return root_scores
@staticmethod
def calculate_root_scores(levels, relationships, grouped_weights):
root_scores = dict()
root_scores = NodeCalculator.calculate_root_score_level_0(root_scores=root_scores,
grouped_weights=grouped_weights, levels=levels)
root_scores = NodeCalculator.calculate_root_score_remaining_levels(root_scores=root_scores,
grouped_weights=grouped_weights,
relationships=relationships, levels=levels)
return root_scores
@staticmethod
def undouble_list(list_objects):
list_objects = list(set(list_objects))
return list_objects
@staticmethod
def check_level(levels, level):
if len(levels[level]) > 0:
level += 1
return level
@staticmethod
def list_max_level_nodes(nodes, relationships):
max_nodes = list()
to_do_nodes = list()
for node in nodes:
present = 0
for key in relationships.keys():
if node in relationships[key]:
present = 1
if present == 0:
max_nodes.append(node)
else:
to_do_nodes.append(node)
max_nodes = NodeCalculator.undouble_list(list_objects=max_nodes)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
return to_do_nodes, max_nodes
@staticmethod
def list_level_0(level, levels, golden_sources, nodes):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
if node in golden_sources:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return to_do_nodes, levels
@staticmethod
def list_level_1(level, levels, nodes, relationships, golden_sources):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
if node not in relationships and node not in golden_sources:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return to_do_nodes, levels
@staticmethod
def list_level_2(level, levels, nodes, relationships):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
present = 0
for key in relationships.keys():
for source in relationships[key]:
if source in nodes:
present = 1
if present == 0:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return to_do_nodes, levels
@staticmethod
def dict_remaining_levels(nodes, level, relationships):
to_do_levels = dict()
for node in nodes:
check_level = level
level_up_nodes = list()
for source in relationships[node]:
if source in nodes:
level_up_nodes.append(source)
for level_up_node in level_up_nodes:
check_level += 1
for source in relationships[level_up_node]:
if source in nodes and source not in level_up_nodes:
level_up_nodes.append(source)
# else:
# check_level -= 1
if check_level in to_do_levels:
to_do_levels[check_level].append(node)
else:
to_do_levels[check_level] = [node]
test = list()
for key in to_do_levels.keys():
test.append(key)
test.sort()
return to_do_levels
@staticmethod
def combine_levels(levels, to_do_levels):
levels = {**levels, **to_do_levels}
return levels
@staticmethod
def find_max_level(levels):
max_level = 0
for key in levels.keys():
if key > max_level:
max_level = key
max_level += 1
return max_level
@staticmethod
def add_max_level(levels, level, max_nodes):
levels[level] = max_nodes
return levels
@staticmethod
def calculate_levels(golden_sources, nodes, relationships):
levels = dict()
level = 0
# On level 0 only the golden sources will be placed. The golden sources are the absolute primitive of the
# hierarchy, and should thus be placed on the absolute bottom of the hierarchy.
nodes, levels = NodeCalculator.list_level_0(level=level, levels=levels, golden_sources=golden_sources,
nodes=nodes)
level = NodeCalculator.check_level(levels=levels, level=level)
# Now we first check if we can also spot the absolute root objects. An absolute root object follows these
# conditions:
# [*] Not a Golden Source
# [*] Is a key in the relationships dictionary
# [*] Is not present as a source for any of the keys in the relationships dictionary
nodes, max_nodes = NodeCalculator.list_max_level_nodes(nodes=nodes, relationships=relationships)
# On level 1, we will place all the object that follow these conditions:
# [*] Not a Golden Source
# [*] Not a key in the relationships dictionary
nodes, levels = NodeCalculator.list_level_1(level=level, levels=levels, golden_sources=golden_sources,
nodes=nodes, relationships=relationships)
level = NodeCalculator.check_level(levels=levels, level=level)
# On level 2, we will place all the object that follow these conditions:
# [*] Not a Golden Source
# [*] Is a key in the relationships dictionary
# [*] No connection with other objects, except for the objects in level 0 & 1
nodes, levels = NodeCalculator.list_level_2(level=level, levels=levels, nodes=nodes,
relationships=relationships)
level = NodeCalculator.check_level(levels=levels, level=level)
# For the remaining levels, we take the following steps for each remaining node:
# [1] Check for the remaining node's sources, if any of these sources are also present in the list of the
# remaining networkers
# [2] If former is the case, we append this source to a checklist.
# [3] We iterate over every node of this list and up the level's value by one.
# [4] During this iteration, we check if this node also has any sources that is in the first list.
# [5] If former is the case, we check if this node is not already present in the checklist. If this is not the
# case, we add it to the checklist
# [6] After all the iterations have ended, we put the level as a key to a dictionary, append the node to a list
# of this key
to_do_levels = NodeCalculator.dict_remaining_levels(nodes=nodes, level=level, relationships=relationships)
levels = NodeCalculator.combine_levels(levels=levels, to_do_levels=to_do_levels)
level = NodeCalculator.find_max_level(levels=levels)
levels = NodeCalculator.add_max_level(levels=levels, level=level, max_nodes=max_nodes)
"""
EXAMPLE:
5 'test_db_1.example_table_a'
4 'test_db_1.example_table_b'
3 'test_db_2.example_table_b'
2 'test_db_2.example_table_a', 'test_db_4.example_table_a'
1 'test_db_3.example_table_c', 'test_db_3.example_table_b', 'test_db_2.example_table_c', 'test_db_3.example_table_a'
0 'golden_source.example_table_a', 'golden_source.example_table_b'
"""
return levels
|
class Nodecalculator:
@staticmethod
def calculate_node_size(node, relationships):
linked_tables = list()
size = 0
for (table_key, table_value) in relationships.items():
if table_key == node:
for table in relationships[table_key]:
linked_tables.append(table)
if len(linked_tables) == 0:
size = 1
return size
else:
if node in linked_tables:
linked_tables = [table for table in linked_tables if table != node]
for table in linked_tables:
for (table_key, table_value) in relationships.items():
if table_key == table:
for table in relationships[table_key]:
if table not in linked_tables:
linked_tables.append(table)
size = size + len(linked_tables)
return size
@staticmethod
def calculate_usage_score(node, relationships):
linked_nodes = list()
for (node_key, node_value) in relationships.items():
if node in node_value:
linked_nodes.append(node_key)
used_keys = list()
for node_source in linked_nodes:
for (node_key, node_value) in relationships.items():
if node_source in node_value and node_key not in used_keys:
linked_nodes.append(node_key)
used_keys.append(node_key)
score = len(linked_nodes)
return score
@staticmethod
def calculate_root_score_level_0(root_scores, levels, grouped_weights):
for node_level_0 in levels[0]:
for weight in grouped_weights.keys():
if node_level_0 in grouped_weights[weight]:
root_scores[node_level_0] = weight
return root_scores
@staticmethod
def list_unique_nodes(relationships):
unique_nodes = list()
for node in relationships:
unique_nodes.append(node)
for relationship in relationships:
for node in relationships[relationship]:
if node not in unique_nodes:
unique_nodes.append(node)
return unique_nodes
@staticmethod
def calculate_root_score_remaining_levels(levels, root_scores, relationships, grouped_weights):
level = 1
max_level = NodeCalculator.find_max_level(levels=levels) - 1
unique_nodes = NodeCalculator.list_unique_nodes(relationships=relationships)
while level <= max_level:
if level in levels:
for node in levels[level]:
if node in unique_nodes:
node_weight = 0
for weight in grouped_weights.keys():
if node in grouped_weights[weight]:
node_weight = weight
all_present = 1
if node in relationships:
for source in relationships[node]:
if source not in root_scores:
all_present = 0
if all_present == 1:
if node in relationships:
for source in relationships[node]:
node_weight += root_scores[source]
root_scores[node] = node_weight
level += 1
return root_scores
@staticmethod
def calculate_root_scores(levels, relationships, grouped_weights):
root_scores = dict()
root_scores = NodeCalculator.calculate_root_score_level_0(root_scores=root_scores, grouped_weights=grouped_weights, levels=levels)
root_scores = NodeCalculator.calculate_root_score_remaining_levels(root_scores=root_scores, grouped_weights=grouped_weights, relationships=relationships, levels=levels)
return root_scores
@staticmethod
def undouble_list(list_objects):
list_objects = list(set(list_objects))
return list_objects
@staticmethod
def check_level(levels, level):
if len(levels[level]) > 0:
level += 1
return level
@staticmethod
def list_max_level_nodes(nodes, relationships):
max_nodes = list()
to_do_nodes = list()
for node in nodes:
present = 0
for key in relationships.keys():
if node in relationships[key]:
present = 1
if present == 0:
max_nodes.append(node)
else:
to_do_nodes.append(node)
max_nodes = NodeCalculator.undouble_list(list_objects=max_nodes)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
return (to_do_nodes, max_nodes)
@staticmethod
def list_level_0(level, levels, golden_sources, nodes):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
if node in golden_sources:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return (to_do_nodes, levels)
@staticmethod
def list_level_1(level, levels, nodes, relationships, golden_sources):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
if node not in relationships and node not in golden_sources:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return (to_do_nodes, levels)
@staticmethod
def list_level_2(level, levels, nodes, relationships):
levels[level] = list()
to_do_nodes = list()
for node in nodes:
present = 0
for key in relationships.keys():
for source in relationships[key]:
if source in nodes:
present = 1
if present == 0:
levels[level].append(node)
else:
to_do_nodes.append(node)
to_do_nodes = NodeCalculator.undouble_list(list_objects=to_do_nodes)
levels[level] = NodeCalculator.undouble_list(list_objects=levels[level])
return (to_do_nodes, levels)
@staticmethod
def dict_remaining_levels(nodes, level, relationships):
to_do_levels = dict()
for node in nodes:
check_level = level
level_up_nodes = list()
for source in relationships[node]:
if source in nodes:
level_up_nodes.append(source)
for level_up_node in level_up_nodes:
check_level += 1
for source in relationships[level_up_node]:
if source in nodes and source not in level_up_nodes:
level_up_nodes.append(source)
if check_level in to_do_levels:
to_do_levels[check_level].append(node)
else:
to_do_levels[check_level] = [node]
test = list()
for key in to_do_levels.keys():
test.append(key)
test.sort()
return to_do_levels
@staticmethod
def combine_levels(levels, to_do_levels):
levels = {**levels, **to_do_levels}
return levels
@staticmethod
def find_max_level(levels):
max_level = 0
for key in levels.keys():
if key > max_level:
max_level = key
max_level += 1
return max_level
@staticmethod
def add_max_level(levels, level, max_nodes):
levels[level] = max_nodes
return levels
@staticmethod
def calculate_levels(golden_sources, nodes, relationships):
levels = dict()
level = 0
(nodes, levels) = NodeCalculator.list_level_0(level=level, levels=levels, golden_sources=golden_sources, nodes=nodes)
level = NodeCalculator.check_level(levels=levels, level=level)
(nodes, max_nodes) = NodeCalculator.list_max_level_nodes(nodes=nodes, relationships=relationships)
(nodes, levels) = NodeCalculator.list_level_1(level=level, levels=levels, golden_sources=golden_sources, nodes=nodes, relationships=relationships)
level = NodeCalculator.check_level(levels=levels, level=level)
(nodes, levels) = NodeCalculator.list_level_2(level=level, levels=levels, nodes=nodes, relationships=relationships)
level = NodeCalculator.check_level(levels=levels, level=level)
to_do_levels = NodeCalculator.dict_remaining_levels(nodes=nodes, level=level, relationships=relationships)
levels = NodeCalculator.combine_levels(levels=levels, to_do_levels=to_do_levels)
level = NodeCalculator.find_max_level(levels=levels)
levels = NodeCalculator.add_max_level(levels=levels, level=level, max_nodes=max_nodes)
"\n EXAMPLE:\n \n 5 'test_db_1.example_table_a' \n 4 'test_db_1.example_table_b'\n 3 'test_db_2.example_table_b'\n 2 'test_db_2.example_table_a', 'test_db_4.example_table_a'\n 1 'test_db_3.example_table_c', 'test_db_3.example_table_b', 'test_db_2.example_table_c', 'test_db_3.example_table_a'\n 0 'golden_source.example_table_a', 'golden_source.example_table_b'\n "
return levels
|
# Question(#1143): Given two strings text1 and text2, return the length of their longest common subsequence.
# Solution: Use the longest common susequence dynamic programming algorithm
def longestCommonSubsequence(text1: str, text2: str) -> int:
grid = [[0 for _ in range(len(text2)+1)] for _ in range(len(text1)+1)]
for i in range(1, len(text1)+1):
for j in range(1, len(text2)+1):
if text1[i-1] == text2[j-1]:
grid[i][j] = 1 + grid[i-1][j-1]
else:
grid[i][j] = max(grid[i][j-1], grid[i-1][j])
return grid[-1][-1]
|
def longest_common_subsequence(text1: str, text2: str) -> int:
grid = [[0 for _ in range(len(text2) + 1)] for _ in range(len(text1) + 1)]
for i in range(1, len(text1) + 1):
for j in range(1, len(text2) + 1):
if text1[i - 1] == text2[j - 1]:
grid[i][j] = 1 + grid[i - 1][j - 1]
else:
grid[i][j] = max(grid[i][j - 1], grid[i - 1][j])
return grid[-1][-1]
|
"""
gnmi_tools - Basic GNMI operations on a device
"""
__copyright__ = "Copyright (c) 2020 Cisco Systems, Inc. and/or its affiliates"
__version__ = "0.1"
__author__ = "Marcelo Reis"
__email__ = "mareis@cisco.com"
__url__ = "https://github.com/reismarcelo/gnmi_hello"
|
"""
gnmi_tools - Basic GNMI operations on a device
"""
__copyright__ = 'Copyright (c) 2020 Cisco Systems, Inc. and/or its affiliates'
__version__ = '0.1'
__author__ = 'Marcelo Reis'
__email__ = 'mareis@cisco.com'
__url__ = 'https://github.com/reismarcelo/gnmi_hello'
|
print("Let's do Factorial") #printing the operation what we are performing
def factorial(number): #defining the factorial method
result = 1 # result is intially defined with 1. if we define initially with 0 the factorial will be 0.
if number == 0: # if number is equals to 0, it prints 1.
print("The factorial of 0 is 1")
elif number < 0: # if number is negative number , it prints error message
print("Error..Enter only whole numbers")
else:
for i in range(1, number+1): # we are using range function for multiplication of numbers
result = result * i # multiplication of numbers is factorial. result is stored in result variable
print("The Factorial of" ,number, "is : ", result) # result will be printed
number = int(input("Enter the number: ")) # Input is taken from user
factorial(number) # Function is called
|
print("Let's do Factorial")
def factorial(number):
result = 1
if number == 0:
print('The factorial of 0 is 1')
elif number < 0:
print('Error..Enter only whole numbers')
else:
for i in range(1, number + 1):
result = result * i
print('The Factorial of', number, 'is : ', result)
number = int(input('Enter the number: '))
factorial(number)
|
name = "glew"
version = "2.1.0"
authors = [
"Milan Ikits",
"Marcelo Magallon",
"Nigel Stewart"
]
description = \
"""
The OpenGL Extension Wrangler Library (GLEW) is a cross-platform open-source C/C++ extension loading library.
"""
requires = [
"cmake-3+",
"gcc-6+"
]
variants = [
["platform-linux"]
]
tools = [
"glewinfo",
"visualinfo"
]
build_system = "cmake"
with scope("config") as config:
config.build_thread_count = "logical_cores"
uuid = "glew-{version}".format(version=str(version))
def commands():
env.PATH.prepend("{root}/bin")
env.LD_LIBRARY_PATH.prepend("{root}/lib64")
env.PKG_CONFIG_PATH.prepend("{root}/lib64/pkgconfig")
env.CMAKE_MODULE_PATH.prepend("{root}/lib64/cmake/glew")
# Helper environment variables.
env.GLEW_BINARY_PATH.set("{root}/bin")
env.GLEW_INCLUDE_PATH.set("{root}/include")
env.GLEW_LIBRARY_PATH.set("{root}/lib64")
|
name = 'glew'
version = '2.1.0'
authors = ['Milan Ikits', 'Marcelo Magallon', 'Nigel Stewart']
description = '\n The OpenGL Extension Wrangler Library (GLEW) is a cross-platform open-source C/C++ extension loading library.\n '
requires = ['cmake-3+', 'gcc-6+']
variants = [['platform-linux']]
tools = ['glewinfo', 'visualinfo']
build_system = 'cmake'
with scope('config') as config:
config.build_thread_count = 'logical_cores'
uuid = 'glew-{version}'.format(version=str(version))
def commands():
env.PATH.prepend('{root}/bin')
env.LD_LIBRARY_PATH.prepend('{root}/lib64')
env.PKG_CONFIG_PATH.prepend('{root}/lib64/pkgconfig')
env.CMAKE_MODULE_PATH.prepend('{root}/lib64/cmake/glew')
env.GLEW_BINARY_PATH.set('{root}/bin')
env.GLEW_INCLUDE_PATH.set('{root}/include')
env.GLEW_LIBRARY_PATH.set('{root}/lib64')
|
#!/usr/bin/env python
include = "$chrs".replace("[", "").replace("]", "").replace(" ", "").split(",")
ref = "$reference"
with open(ref) as ifh, open("include.bed", "w") as ofh:
for line in ifh:
toks = line.strip().split("\\t")
if toks[0] in include:
print(toks[0], 0, toks[1], sep="\\t", file=ofh)
|
include = '$chrs'.replace('[', '').replace(']', '').replace(' ', '').split(',')
ref = '$reference'
with open(ref) as ifh, open('include.bed', 'w') as ofh:
for line in ifh:
toks = line.strip().split('\\t')
if toks[0] in include:
print(toks[0], 0, toks[1], sep='\\t', file=ofh)
|
# Modify the program to show the numbers from 50 to 100
x=50
while x<=100:
print(x)
x=x+1
|
x = 50
while x <= 100:
print(x)
x = x + 1
|
# Number of queens
print("Enter the number of queens")
N = int(input())
# chessboard
# NxN matrix with all elements 0
board = [[0]*N for _ in range(N)]
def is_attack(i, j):
# checking if there is a queen in row or column
for k in range(0, N):
if board[i][k] == 1 or board[k][j] == 1:
return True
# checking diagonals
for k in range(0, N):
for l in range(0, N):
if (k+l == i+j) or (k-l == i-j):
if board[k][l] == 1:
return True
return False
def N_queen(n):
# if n is 0, solution found
if n == 0:
return True
for i in range(0, N):
for j in range(0, N):
'''checking if we can place a queen here or not
queen will not be placed if the place is being attacked
or already occupied'''
if (not(is_attack(i, j))) and (board[i][j] != 1):
board[i][j] = 1
# recursion
# wether we can put the next queen with this arrangment or not
if N_queen(n-1) == True:
return True
board[i][j] = 0
return False
N_queen(N)
for i in board:
print(i)
|
print('Enter the number of queens')
n = int(input())
board = [[0] * N for _ in range(N)]
def is_attack(i, j):
for k in range(0, N):
if board[i][k] == 1 or board[k][j] == 1:
return True
for k in range(0, N):
for l in range(0, N):
if k + l == i + j or k - l == i - j:
if board[k][l] == 1:
return True
return False
def n_queen(n):
if n == 0:
return True
for i in range(0, N):
for j in range(0, N):
'checking if we can place a queen here or not\n queen will not be placed if the place is being attacked\n or already occupied'
if not is_attack(i, j) and board[i][j] != 1:
board[i][j] = 1
if n_queen(n - 1) == True:
return True
board[i][j] = 0
return False
n_queen(N)
for i in board:
print(i)
|
class Device(object):
"""Device.
:param id: Unique identifier for the device.
:type id: str
:param name: The name of the device.
:type name: str
"""
def __init__(self, data=None):
if data is None:
data = {}
self.id = data.get('id', None)
self.name = data.get('name', None)
|
class Device(object):
"""Device.
:param id: Unique identifier for the device.
:type id: str
:param name: The name of the device.
:type name: str
"""
def __init__(self, data=None):
if data is None:
data = {}
self.id = data.get('id', None)
self.name = data.get('name', None)
|
start_inventory = 20
num_items = start_inventory
while num_items > 0:
print("We have " + str(num_items) + " items in inventory.")
user_purchase = input("How many would you like to buy? ")
if int(user_purchase) > num_items:
print("Not Enough Stock")
else:
num_items = num_items - int(user_purchase)
print("All out!")
|
start_inventory = 20
num_items = start_inventory
while num_items > 0:
print('We have ' + str(num_items) + ' items in inventory.')
user_purchase = input('How many would you like to buy? ')
if int(user_purchase) > num_items:
print('Not Enough Stock')
else:
num_items = num_items - int(user_purchase)
print('All out!')
|
first_list = range(11)
second_list = range(1,12)
ziplist = list(zip(first_list, second_list))
def square(a, b):
return (a*a) + (b*b) + 2 * a * b
# output = [square(item[0], item[1]) for item in ziplist]
output = [square(a, b) for a, b in ziplist]
print(output)
def square2(pair):
a = pair[0]
b = pair[1]
return (a*a) + (b*b) + 2 * a * b
map_list = list(map(square2, ziplist))
print(map_list)
|
first_list = range(11)
second_list = range(1, 12)
ziplist = list(zip(first_list, second_list))
def square(a, b):
return a * a + b * b + 2 * a * b
output = [square(a, b) for (a, b) in ziplist]
print(output)
def square2(pair):
a = pair[0]
b = pair[1]
return a * a + b * b + 2 * a * b
map_list = list(map(square2, ziplist))
print(map_list)
|
class Quest:
def __init__(self, dbRow):
self.id = dbRow[0]
self.name = dbRow[1]
self.description = dbRow[2]
self.objective = dbRow[3]
self.questType = dbRow[4]
self.category = dbRow[5]
self.location = dbRow[6]
self.stars = dbRow[7]
self.zenny = dbRow[8]
def __repr__(self):
return f"{self.__dict__!r}"
|
class Quest:
def __init__(self, dbRow):
self.id = dbRow[0]
self.name = dbRow[1]
self.description = dbRow[2]
self.objective = dbRow[3]
self.questType = dbRow[4]
self.category = dbRow[5]
self.location = dbRow[6]
self.stars = dbRow[7]
self.zenny = dbRow[8]
def __repr__(self):
return f'{self.__dict__!r}'
|
r"""
cgtasknet is a library for training spiking neural
networks with cognitive tasks
"""
|
"""
cgtasknet is a library for training spiking neural
networks with cognitive tasks
"""
|
termination = 4000000
previous = 1
current = 2
total = 2
while(True):
new = current+ previous
previous = current
current = new
if(current >= termination):
break
if(current % 2 == 0):
total = total + current
print(total)
|
termination = 4000000
previous = 1
current = 2
total = 2
while True:
new = current + previous
previous = current
current = new
if current >= termination:
break
if current % 2 == 0:
total = total + current
print(total)
|
power = {'BUSES': {'Area': 1.33155,
'Bus/Area': 1.33155,
'Bus/Gate Leakage': 0.00662954,
'Bus/Peak Dynamic': 0.0,
'Bus/Runtime Dynamic': 0.0,
'Bus/Subthreshold Leakage': 0.0691322,
'Bus/Subthreshold Leakage with power gating': 0.0259246,
'Gate Leakage': 0.00662954,
'Peak Dynamic': 0.0,
'Runtime Dynamic': 0.0,
'Subthreshold Leakage': 0.0691322,
'Subthreshold Leakage with power gating': 0.0259246},
'Core': [{'Area': 32.6082,
'Execution Unit/Area': 8.2042,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0980777,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279723,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.394,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.122718,
'Execution Unit/Instruction Scheduler/Area': 2.17927,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.148207,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.256641,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.147191,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.55204,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.0860909,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.81603,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0744351,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00537263,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0810849,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0397339,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.15552,
'Execution Unit/Register Files/Runtime Dynamic': 0.0451065,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.222804,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.402293,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155,
'Execution Unit/Runtime Dynamic': 1.68454,
'Execution Unit/Subthreshold Leakage': 1.83518,
'Execution Unit/Subthreshold Leakage with power gating': 0.709678,
'Gate Leakage': 0.372997,
'Instruction Fetch Unit/Area': 5.86007,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000225002,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000225002,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000194444,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 7.44341e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000570781,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00121523,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00221206,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0590479,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0381972,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.42967,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.0551552,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.129735,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 4.76791,
'Instruction Fetch Unit/Runtime Dynamic': 0.226515,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932587,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0140516,
'L2/Runtime Dynamic': 0.00517116,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80969,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 1.57809,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.182297,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0351387,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0110311,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0110311,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 1.63039,
'Load Store Unit/Runtime Dynamic': 0.247729,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.0272009,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.0544015,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591622,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283406,
'Memory Management Unit/Area': 0.434579,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0096537,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.00986453,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00813591,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.151068,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.00904231,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.326256,
'Memory Management Unit/Runtime Dynamic': 0.0189068,
'Memory Management Unit/Subthreshold Leakage': 0.0769113,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462,
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'Renaming Unit/Area': 0.369768,
'Renaming Unit/FP Front End RAT/Area': 0.168486,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731,
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'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.259687,
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'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925,
'Renaming Unit/Free List/Area': 0.0414755,
'Renaming Unit/Free List/Gate Leakage': 4.15911e-05,
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'Renaming Unit/Free List/Runtime Dynamic': 0.0107034,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987,
'Renaming Unit/Gate Leakage': 0.00863632,
'Renaming Unit/Int Front End RAT/Area': 0.114751,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0719334,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781,
'Renaming Unit/Peak Dynamic': 4.56169,
'Renaming Unit/Runtime Dynamic': 0.342324,
'Renaming Unit/Subthreshold Leakage': 0.070483,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779,
'Runtime Dynamic': 2.52519,
'Subthreshold Leakage': 6.21877,
'Subthreshold Leakage with power gating': 2.58311},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0982865,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279887,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.394843,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.123408,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.199053,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.100475,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.422937,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.0806077,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.75412,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0745942,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0051763,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0797547,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0382819,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.154349,
'Execution Unit/Register Files/Runtime Dynamic': 0.0434582,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.192598,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.345046,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.49671,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
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'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000196117,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000196117,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000169484,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 6.48802e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000549923,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00111164,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00192802,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0368014,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.34089,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.0552637,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.124994,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 4.67301,
'Instruction Fetch Unit/Runtime Dynamic': 0.220099,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0129726,
'L2/Runtime Dynamic': 0.00485966,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 1.53514,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.160709,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.00964176,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.00964166,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 1.58067,
'Load Store Unit/Runtime Dynamic': 0.2179,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.0237749,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.0475494,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0084378,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.00863242,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.145548,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.00906,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.316151,
'Memory Management Unit/Runtime Dynamic': 0.0176924,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 14.9264,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.196223,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.00795584,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0588229,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.263002,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 2.22026,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0978179,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279519,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.392958,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.123829,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.199732,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.100818,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.424379,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.081378,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.75194,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0742381,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00519396,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0796807,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0384125,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.153919,
'Execution Unit/Register Files/Runtime Dynamic': 0.0436065,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.192325,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.345489,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.49837,
'Execution Unit/Subthreshold Leakage': 1.79543,
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'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000199387,
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'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
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'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000551799,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00112288,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0019602,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0369269,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
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'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.34887,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.0549932,
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'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
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'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 4.68138,
'Instruction Fetch Unit/Runtime Dynamic': 0.220424,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
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'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.013049,
'L2/Runtime Dynamic': 0.0049262,
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'Load Store Unit/Data Cache/Area': 6.84535,
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'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
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'Load Store Unit/LoadQ/Peak Dynamic': 0.00990766,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.00990762,
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'Load Store Unit/Peak Dynamic': 1.59015,
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'Load Store Unit/Subthreshold Leakage': 0.591321,
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'Memory Management Unit/Gate Leakage': 0.00808595,
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'Subthreshold Leakage with power gating': 2.55328},
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'Execution Unit/Area': 7.68434,
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'Execution Unit/Floating Point Units/Area': 4.6585,
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'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
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'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
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'Execution Unit/Peak Dynamic': 4.75278,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.074361,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00518958,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
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'Execution Unit/Register Files/Peak Dynamic': 0.15408,
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'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
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'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
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'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.498,
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'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000170604,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
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'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00111677,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
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'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00194081,
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'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
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'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
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'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
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'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
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'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
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'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 4.6793,
'Instruction Fetch Unit/Runtime Dynamic': 0.22033,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0131558,
'L2/Runtime Dynamic': 0.0049838,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
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'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
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'Load Store Unit/LoadQ/Runtime Dynamic': 0.0098409,
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'Load Store Unit/StoreQ/Area': 0.322079,
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'Peak Dynamic': 1.2868175454447888,
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'Peak Dynamic': 0.0451325,
'Runtime Dynamic': 0.0231622,
'Subthreshold Leakage': 6.80085,
'Subthreshold Leakage with power gating': 3.32364}],
'Processor': {'Area': 191.908,
'Gate Leakage': 1.53485,
'Peak Dynamic': 61.9702,
'Peak Power': 95.0824,
'Runtime Dynamic': 9.22203,
'Subthreshold Leakage': 31.5774,
'Subthreshold Leakage with power gating': 13.9484,
'Total Cores/Area': 128.669,
'Total Cores/Gate Leakage': 1.4798,
'Total Cores/Peak Dynamic': 61.9251,
'Total Cores/Runtime Dynamic': 9.19887,
'Total Cores/Subthreshold Leakage': 24.7074,
'Total Cores/Subthreshold Leakage with power gating': 10.2429,
'Total L3s/Area': 61.9075,
'Total L3s/Gate Leakage': 0.0484137,
'Total L3s/Peak Dynamic': 0.0451325,
'Total L3s/Runtime Dynamic': 0.0231622,
'Total L3s/Subthreshold Leakage': 6.80085,
'Total L3s/Subthreshold Leakage with power gating': 3.32364,
'Total Leakage': 33.1122,
'Total NoCs/Area': 1.33155,
'Total NoCs/Gate Leakage': 0.00662954,
'Total NoCs/Peak Dynamic': 0.0,
'Total NoCs/Runtime Dynamic': 0.0,
'Total NoCs/Subthreshold Leakage': 0.0691322,
'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}
|
power = {'BUSES': {'Area': 1.33155, 'Bus/Area': 1.33155, 'Bus/Gate Leakage': 0.00662954, 'Bus/Peak Dynamic': 0.0, 'Bus/Runtime Dynamic': 0.0, 'Bus/Subthreshold Leakage': 0.0691322, 'Bus/Subthreshold Leakage with power gating': 0.0259246, 'Gate Leakage': 0.00662954, 'Peak Dynamic': 0.0, 'Runtime Dynamic': 0.0, 'Subthreshold Leakage': 0.0691322, 'Subthreshold Leakage with power gating': 0.0259246}, 'Core': [{'Area': 32.6082, 'Execution Unit/Area': 8.2042, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0980777, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279723, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.394, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.122718, 'Execution Unit/Instruction Scheduler/Area': 2.17927, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.148207, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.256641, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.147191, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.55204, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.0860909, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 5.81603, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0744351, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00537263, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0810849, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0397339, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.15552, 'Execution Unit/Register Files/Runtime Dynamic': 0.0451065, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.222804, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.402293, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155, 'Execution Unit/Runtime Dynamic': 1.68454, 'Execution Unit/Subthreshold Leakage': 1.83518, 'Execution Unit/Subthreshold Leakage with power gating': 0.709678, 'Gate Leakage': 0.372997, 'Instruction Fetch Unit/Area': 5.86007, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000225002, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000225002, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000194444, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 7.44341e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000570781, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00121523, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00221206, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0590479, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0381972, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.42967, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.0551552, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.129735, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 4.76791, 'Instruction Fetch Unit/Runtime Dynamic': 0.226515, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932587, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.0140516, 'L2/Runtime Dynamic': 0.00517116, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80969, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 1.57809, 'Load Store Unit/Data Cache/Runtime Dynamic': 0.182297, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0351387, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.0110311, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.0110311, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 1.63039, 'Load Store Unit/Runtime Dynamic': 0.247729, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.0272009, 'Load Store Unit/StoreQ/Runtime Dynamic': 0.0544015, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591622, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283406, 'Memory Management Unit/Area': 0.434579, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729, 'Memory Management Unit/Dtlb/Peak Dynamic': 0.0096537, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.00986453, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00813591, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.151068, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.00904231, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.326256, 'Memory Management Unit/Runtime Dynamic': 0.0189068, 'Memory Management Unit/Subthreshold Leakage': 0.0769113, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462, 'Peak Dynamic': 17.1163, 'Renaming Unit/Area': 0.369768, 'Renaming Unit/FP Front End RAT/Area': 0.168486, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.259687, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0437281, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925, 'Renaming Unit/Free List/Area': 0.0414755, 'Renaming Unit/Free List/Gate Leakage': 4.15911e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0401324, 'Renaming Unit/Free List/Runtime Dynamic': 0.0107034, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987, 'Renaming Unit/Gate Leakage': 0.00863632, 'Renaming Unit/Int Front End RAT/Area': 0.114751, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0719334, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781, 'Renaming Unit/Peak Dynamic': 4.56169, 'Renaming Unit/Runtime Dynamic': 0.342324, 'Renaming Unit/Subthreshold Leakage': 0.070483, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779, 'Runtime Dynamic': 2.52519, 'Subthreshold Leakage': 6.21877, 'Subthreshold Leakage with power gating': 2.58311}, {'Area': 32.0201, 'Execution Unit/Area': 7.68434, 'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0982865, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279887, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.394843, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.123408, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519, 'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913, 'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223, 'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562, 'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763, 'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.199053, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755, 'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964, 'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262, 'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388, 'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608, 'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451, 'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.100475, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853, 'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446, 'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.422937, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892, 'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346, 'Execution Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.0806077, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 4.75412, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0745942, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0051763, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0797547, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0382819, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.154349, 'Execution Unit/Register Files/Runtime Dynamic': 0.0434582, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.192598, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.345046, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543, 'Execution Unit/Runtime Dynamic': 1.49671, 'Execution Unit/Subthreshold Leakage': 1.79543, 'Execution Unit/Subthreshold Leakage with power gating': 0.688821, 'Gate Leakage': 0.368936, 'Instruction Fetch Unit/Area': 5.85939, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000196117, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000196117, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000169484, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 6.48802e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000549923, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00111164, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00192802, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0368014, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.34089, 'Instruction Fetch Unit/Instruction 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'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80901, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 1.53514, 'Load Store Unit/Data Cache/Runtime Dynamic': 0.160709, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0350888, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.00964176, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.00964166, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 1.58067, 'Load Store Unit/Runtime Dynamic': 0.2179, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate 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'Execution Unit/Complex ALUs/Area': 0.235435, 'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646, 'Execution Unit/Complex ALUs/Peak Dynamic': 0.0978179, 'Execution Unit/Complex ALUs/Runtime Dynamic': 0.279519, 'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111, 'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163, 'Execution Unit/Floating Point Units/Area': 4.6585, 'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156, 'Execution Unit/Floating Point Units/Peak Dynamic': 0.392958, 'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033, 'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829, 'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061, 'Execution Unit/Gate Leakage': 0.120359, 'Execution Unit/Instruction Scheduler/Area': 1.66526, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653, 'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate 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'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0019602, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0369269, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction 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Unit/Integer ALUs/Area': 0.47087, 'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291, 'Execution Unit/Integer ALUs/Peak Dynamic': 0.0811593, 'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344, 'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222, 'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833, 'Execution Unit/Peak Dynamic': 4.75278, 'Execution Unit/Register Files/Area': 0.570804, 'Execution Unit/Register Files/Floating Point RF/Area': 0.208131, 'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788, 'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.074361, 'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00518958, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698, 'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968, 'Execution Unit/Register Files/Gate Leakage': 0.000622708, 'Execution Unit/Register Files/Integer RF/Area': 0.362673, 'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992, 'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0797187, 'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0383801, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175, 'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675, 'Execution Unit/Register Files/Peak Dynamic': 0.15408, 'Execution Unit/Register Files/Runtime Dynamic': 0.0435697, 'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387, 'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643, 'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912, 'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402, 'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.192445, 'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.345389, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478, 'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543, 'Execution Unit/Runtime Dynamic': 1.498, 'Execution Unit/Subthreshold Leakage': 1.79543, 'Execution Unit/Subthreshold Leakage with power gating': 0.688821, 'Gate Leakage': 0.368936, 'Instruction Fetch Unit/Area': 5.85939, 'Instruction Fetch Unit/Branch Predictor/Area': 0.138516, 'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000197415, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000197415, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719, 'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000170604, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344, 'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 6.53086e-05, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347, 'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045, 'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838, 'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732, 'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05, 'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602, 'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000551334, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505, 'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733, 'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00111677, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703, 'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282, 'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954, 'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758, 'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867, 'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00194081, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682, 'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357, 'Instruction Fetch Unit/Gate Leakage': 0.0589979, 'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323, 'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05, 'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827, 'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0368958, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885, 'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682, 'Instruction Fetch Unit/Instruction Cache/Area': 3.14635, 'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931, 'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 2.34689, 'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.0550619, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022, 'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386, 'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799, 'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493, 'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404, 'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.125315, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943, 'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104, 'Instruction Fetch Unit/Peak Dynamic': 4.6793, 'Instruction Fetch Unit/Runtime Dynamic': 0.22033, 'Instruction Fetch Unit/Subthreshold Leakage': 0.932286, 'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843, 'L2/Area': 4.53318, 'L2/Gate Leakage': 0.015464, 'L2/Peak Dynamic': 0.0131558, 'L2/Runtime Dynamic': 0.0049838, 'L2/Subthreshold Leakage': 0.834142, 'L2/Subthreshold Leakage with power gating': 0.401066, 'Load Store Unit/Area': 8.80901, 'Load Store Unit/Data Cache/Area': 6.84535, 'Load Store Unit/Data Cache/Gate Leakage': 0.0279261, 'Load Store Unit/Data Cache/Peak Dynamic': 1.5413, 'Load Store Unit/Data Cache/Runtime Dynamic': 0.163934, 'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675, 'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085, 'Load Store Unit/Gate Leakage': 0.0350888, 'Load Store Unit/LoadQ/Area': 0.0836782, 'Load Store Unit/LoadQ/Gate Leakage': 0.00059896, 'Load Store Unit/LoadQ/Peak Dynamic': 0.00984081, 'Load Store Unit/LoadQ/Runtime Dynamic': 0.0098409, 'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961, 'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918, 'Load Store Unit/Peak Dynamic': 1.58777, 'Load Store Unit/Runtime Dynamic': 0.222306, 'Load Store Unit/StoreQ/Area': 0.322079, 'Load Store Unit/StoreQ/Gate Leakage': 0.00329971, 'Load Store Unit/StoreQ/Peak Dynamic': 0.0242658, 'Load Store Unit/StoreQ/Runtime Dynamic': 0.048532, 'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621, 'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004, 'Load Store Unit/Subthreshold Leakage': 0.591321, 'Load Store Unit/Subthreshold Leakage with power gating': 0.283293, 'Memory Management Unit/Area': 0.4339, 'Memory Management Unit/Dtlb/Area': 0.0879726, 'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729, 'Memory Management Unit/Dtlb/Peak Dynamic': 0.008612, 'Memory Management Unit/Dtlb/Runtime Dynamic': 0.00880954, 'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699, 'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485, 'Memory Management Unit/Gate Leakage': 0.00808595, 'Memory Management Unit/Itlb/Area': 0.301552, 'Memory Management Unit/Itlb/Gate Leakage': 0.00393464, 'Memory Management Unit/Itlb/Peak Dynamic': 0.145921, 'Memory Management Unit/Itlb/Runtime Dynamic': 0.00902684, 'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758, 'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842, 'Memory Management Unit/Peak Dynamic': 0.316824, 'Memory Management Unit/Runtime Dynamic': 0.0178364, 'Memory Management Unit/Subthreshold Leakage': 0.0766103, 'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333, 'Peak Dynamic': 14.9393, 'Renaming Unit/Area': 0.303608, 'Renaming Unit/FP Front End RAT/Area': 0.131045, 'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123, 'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468, 'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.195609, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571, 'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885, 'Renaming Unit/Free List/Area': 0.0340654, 'Renaming Unit/Free List/Gate Leakage': 2.5481e-05, 'Renaming Unit/Free List/Peak Dynamic': 0.0306032, 'Renaming Unit/Free List/Runtime Dynamic': 0.00796266, 'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144, 'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064, 'Renaming Unit/Gate Leakage': 0.00708398, 'Renaming Unit/Int Front End RAT/Area': 0.0941223, 'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242, 'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965, 'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0590131, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488, 'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228, 'Renaming Unit/Peak Dynamic': 3.58947, 'Renaming Unit/Runtime Dynamic': 0.262585, 'Renaming Unit/Subthreshold Leakage': 0.0552466, 'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461, 'Runtime Dynamic': 2.22605, 'Subthreshold Leakage': 6.16288, 'Subthreshold Leakage with power gating': 2.55328}], 'DRAM': {'Area': 0, 'Gate Leakage': 0, 'Peak Dynamic': 1.2868175454447888, 'Runtime Dynamic': 1.2868175454447888, 'Subthreshold Leakage': 4.252, 'Subthreshold Leakage with power gating': 4.252}, 'L3': [{'Area': 61.9075, 'Gate Leakage': 0.0484137, 'Peak Dynamic': 0.0451325, 'Runtime Dynamic': 0.0231622, 'Subthreshold Leakage': 6.80085, 'Subthreshold Leakage with power gating': 3.32364}], 'Processor': {'Area': 191.908, 'Gate Leakage': 1.53485, 'Peak Dynamic': 61.9702, 'Peak Power': 95.0824, 'Runtime Dynamic': 9.22203, 'Subthreshold Leakage': 31.5774, 'Subthreshold Leakage with power gating': 13.9484, 'Total Cores/Area': 128.669, 'Total Cores/Gate Leakage': 1.4798, 'Total Cores/Peak Dynamic': 61.9251, 'Total Cores/Runtime Dynamic': 9.19887, 'Total Cores/Subthreshold Leakage': 24.7074, 'Total Cores/Subthreshold Leakage with power gating': 10.2429, 'Total L3s/Area': 61.9075, 'Total L3s/Gate Leakage': 0.0484137, 'Total L3s/Peak Dynamic': 0.0451325, 'Total L3s/Runtime Dynamic': 0.0231622, 'Total L3s/Subthreshold Leakage': 6.80085, 'Total L3s/Subthreshold Leakage with power gating': 3.32364, 'Total Leakage': 33.1122, 'Total NoCs/Area': 1.33155, 'Total NoCs/Gate Leakage': 0.00662954, 'Total NoCs/Peak Dynamic': 0.0, 'Total NoCs/Runtime Dynamic': 0.0, 'Total NoCs/Subthreshold Leakage': 0.0691322, 'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}
|
def assign_ROSCO_values(wt_opt, modeling_options, control):
# ROSCO tuning parameters
wt_opt['tune_rosco_ivc.PC_omega'] = control['pitch']['PC_omega']
wt_opt['tune_rosco_ivc.PC_zeta'] = control['pitch']['PC_zeta']
wt_opt['tune_rosco_ivc.VS_omega'] = control['torque']['VS_omega']
wt_opt['tune_rosco_ivc.VS_zeta'] = control['torque']['VS_zeta']
if modeling_options['Level3']['ROSCO']['Flp_Mode'] > 0:
wt_opt['tune_rosco_ivc.Flp_omega'] = control['dac']['Flp_omega']
wt_opt['tune_rosco_ivc.Flp_zeta'] = control['dac']['Flp_zeta']
if 'IPC' in control.keys():
wt_opt['tune_rosco_ivc.IPC_KI'] = control['IPC']['IPC_gain_1P']
# # other optional parameters
wt_opt['tune_rosco_ivc.max_pitch'] = control['pitch']['max_pitch']
wt_opt['tune_rosco_ivc.min_pitch'] = control['pitch']['min_pitch']
wt_opt['tune_rosco_ivc.vs_minspd'] = control['torque']['VS_minspd']
wt_opt['tune_rosco_ivc.ss_vsgain'] = control['setpoint_smooth']['ss_vsgain']
wt_opt['tune_rosco_ivc.ss_pcgain'] = control['setpoint_smooth']['ss_pcgain']
wt_opt['tune_rosco_ivc.ps_percent'] = control['pitch']['ps_percent']
# Check for proper Flp_Mode, print warning
if modeling_options['WISDEM']['RotorSE']['n_tab'] > 1 and modeling_options['Level3']['ROSCO']['Flp_Mode'] == 0:
raise Exception('A distributed aerodynamic control device is specified in the geometry yaml, but Flp_Mode is zero in the modeling options.')
if modeling_options['WISDEM']['RotorSE']['n_tab'] == 1 and modeling_options['Level3']['ROSCO']['Flp_Mode'] > 0:
raise Exception('Flp_Mode is non zero in the modeling options, but no distributed aerodynamic control device is specified in the geometry yaml.')
return wt_opt
|
def assign_rosco_values(wt_opt, modeling_options, control):
wt_opt['tune_rosco_ivc.PC_omega'] = control['pitch']['PC_omega']
wt_opt['tune_rosco_ivc.PC_zeta'] = control['pitch']['PC_zeta']
wt_opt['tune_rosco_ivc.VS_omega'] = control['torque']['VS_omega']
wt_opt['tune_rosco_ivc.VS_zeta'] = control['torque']['VS_zeta']
if modeling_options['Level3']['ROSCO']['Flp_Mode'] > 0:
wt_opt['tune_rosco_ivc.Flp_omega'] = control['dac']['Flp_omega']
wt_opt['tune_rosco_ivc.Flp_zeta'] = control['dac']['Flp_zeta']
if 'IPC' in control.keys():
wt_opt['tune_rosco_ivc.IPC_KI'] = control['IPC']['IPC_gain_1P']
wt_opt['tune_rosco_ivc.max_pitch'] = control['pitch']['max_pitch']
wt_opt['tune_rosco_ivc.min_pitch'] = control['pitch']['min_pitch']
wt_opt['tune_rosco_ivc.vs_minspd'] = control['torque']['VS_minspd']
wt_opt['tune_rosco_ivc.ss_vsgain'] = control['setpoint_smooth']['ss_vsgain']
wt_opt['tune_rosco_ivc.ss_pcgain'] = control['setpoint_smooth']['ss_pcgain']
wt_opt['tune_rosco_ivc.ps_percent'] = control['pitch']['ps_percent']
if modeling_options['WISDEM']['RotorSE']['n_tab'] > 1 and modeling_options['Level3']['ROSCO']['Flp_Mode'] == 0:
raise exception('A distributed aerodynamic control device is specified in the geometry yaml, but Flp_Mode is zero in the modeling options.')
if modeling_options['WISDEM']['RotorSE']['n_tab'] == 1 and modeling_options['Level3']['ROSCO']['Flp_Mode'] > 0:
raise exception('Flp_Mode is non zero in the modeling options, but no distributed aerodynamic control device is specified in the geometry yaml.')
return wt_opt
|
# Tuples
# Assignment 1
tuple_numbers = (1, 2, 3, 4, 5)
tuple_groceries = ('coconuts', 'bananas', 'onions', 'spinach', 'tomatoes', 'cilantro', 'milk')
groceries_inventory = ('coconuts', 'tomatoes', 'onions', 'coconuts', 'bananas', 'onions', 'spinach', 'tomatoes', 'cilantro', 'milk', 'spinach', 'tomatoes', 'cilantro', 'tomatoes')
tuple_nested =((1, 2, 3), ["Python", "Database", "System"], 'Coding')
tuple_numbers_100s = (100, 200, 300, 400, 500)
# Print 3rd item from tuple_groceries
print("*" * 50)
print("The 3rd item of tuple_groceries :", tuple_groceries[2])
# Print the length of tuple_groceries
print("*" * 50)
print("The length of tuple_groceries :", len(tuple_groceries))
# Print the reverse of tuple_numbers & tuples_names
print("*" * 50)
tuple_groceries_rev = tuple(reversed(tuple_groceries))
print("Reverse of tuple_groceries :", tuple_groceries_rev)
# Print "Python" from "tuple_nested"
print("*" * 50)
print(tuple_nested[1][0])
# Unpack tuple_groceries tuple and print them
print("*" * 50)
print("Unpacking...")
g1, g2, g3, g4, g5, g6, g7, = tuple_groceries
print(g1)
print(g1)
print(g2)
print(g3)
print(g4)
print(g5)
print(g6)
print(g7)
# Swap tuple_numbers and tuple_numbers_100s
print("*" * 50)
print("Swapping...")
tuple_numbers, tuple_numbers_100s = tuple_numbers_100s, tuple_numbers
print("tuple_numbers_100s :", tuple_numbers_100s)
print("tuple_numbers :", tuple_numbers)
# Construct a new tuple "tuples_a" by extracting
# bananas, onions, spinach from tuples_groceries
print("*" * 50)
print("Subset items.... bananas, onions, spinach")
tuples_a = tuple_groceries[1:4]
print("tuples_a :", tuples_a)
# Count the number of times coconuts is listed in groceries_inventory tuple
print("*" * 50)
print("Count the number of times coconuts...")
coconut_count = groceries_inventory.count("coconuts")
print("coconuts :", coconut_count)
|
tuple_numbers = (1, 2, 3, 4, 5)
tuple_groceries = ('coconuts', 'bananas', 'onions', 'spinach', 'tomatoes', 'cilantro', 'milk')
groceries_inventory = ('coconuts', 'tomatoes', 'onions', 'coconuts', 'bananas', 'onions', 'spinach', 'tomatoes', 'cilantro', 'milk', 'spinach', 'tomatoes', 'cilantro', 'tomatoes')
tuple_nested = ((1, 2, 3), ['Python', 'Database', 'System'], 'Coding')
tuple_numbers_100s = (100, 200, 300, 400, 500)
print('*' * 50)
print('The 3rd item of tuple_groceries :', tuple_groceries[2])
print('*' * 50)
print('The length of tuple_groceries :', len(tuple_groceries))
print('*' * 50)
tuple_groceries_rev = tuple(reversed(tuple_groceries))
print('Reverse of tuple_groceries :', tuple_groceries_rev)
print('*' * 50)
print(tuple_nested[1][0])
print('*' * 50)
print('Unpacking...')
(g1, g2, g3, g4, g5, g6, g7) = tuple_groceries
print(g1)
print(g1)
print(g2)
print(g3)
print(g4)
print(g5)
print(g6)
print(g7)
print('*' * 50)
print('Swapping...')
(tuple_numbers, tuple_numbers_100s) = (tuple_numbers_100s, tuple_numbers)
print('tuple_numbers_100s :', tuple_numbers_100s)
print('tuple_numbers :', tuple_numbers)
print('*' * 50)
print('Subset items.... bananas, onions, spinach')
tuples_a = tuple_groceries[1:4]
print('tuples_a :', tuples_a)
print('*' * 50)
print('Count the number of times coconuts...')
coconut_count = groceries_inventory.count('coconuts')
print('coconuts :', coconut_count)
|
class QueryToken:
"""A placeholder token for dry-run query output"""
def __str__(self) -> str:
return "?"
def __repr__(self) -> str:
return "?"
|
class Querytoken:
"""A placeholder token for dry-run query output"""
def __str__(self) -> str:
return '?'
def __repr__(self) -> str:
return '?'
|
class Solution:
def minMeetingRooms(self, intervals: list[list[int]]) -> int:
start = sorted([i[0] for i in intervals])
end = sorted(i[1] for i in intervals)
result = count = 0
s, e = 0, 0
while s < len(intervals):
if start[s] < end[e]:
s += 1
count += 1
else:
e += 1
count -= 1
result = max(result, count)
return result
|
class Solution:
def min_meeting_rooms(self, intervals: list[list[int]]) -> int:
start = sorted([i[0] for i in intervals])
end = sorted((i[1] for i in intervals))
result = count = 0
(s, e) = (0, 0)
while s < len(intervals):
if start[s] < end[e]:
s += 1
count += 1
else:
e += 1
count -= 1
result = max(result, count)
return result
|
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