content
stringlengths 7
1.05M
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stringlengths 1
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def process(record):
ids = (record.get('idsurface', '') or '').split(' ')
if len(ids) > 4:
return {'language': record['language'],
'longitude': float(record['longitude'] or 0),
'latitude': float(record['latitude'] or 0),
'idsurface': ids}
|
def process(record):
ids = (record.get('idsurface', '') or '').split(' ')
if len(ids) > 4:
return {'language': record['language'], 'longitude': float(record['longitude'] or 0), 'latitude': float(record['latitude'] or 0), 'idsurface': ids}
|
a = 2 ** 50
b = 2 ** 50 * 3
c = 2 ** 50 * 3 - 1000
d = 400 / 2 ** 50 + 50
print(a,b,c,d)
|
a = 2 ** 50
b = 2 ** 50 * 3
c = 2 ** 50 * 3 - 1000
d = 400 / 2 ** 50 + 50
print(a, b, c, d)
|
G = 6.67408e-11 # N-m2/kg2
#
# Normalize the constants such that m, r, t and v are of the order 10^1.
#
def get_normalization_constants_alphacentauri():
# Normalize the masses to the mass of our sun
m_nd = 1.989e+30 # kg
# Normalize distances to the distance between Alpha Centauri A and Alpha Centauri B
r_nd = 5.326e+12 # m
# Normalize velocities to the velocity of earth around the sun
v_nd = 30000 # m/s
# Normalize time to the orbital period of Alpha Centauri A and B
t_nd = 79.91 * 365 * 24 * 3600 * 0.51 # s
return m_nd, r_nd, v_nd, t_nd
def get_normalization_constants_earthsun():
# Normalize the masses to the mass of our sun
m_nd = 1.989e+30 # kg
# Normalize distances to the distance between Earth and Sun
r_nd = 149.47e9 # m
# Normalize velocities to the velocity of earth around the sun
v_nd = 29.78e3 # m/s
# Normalize time to the orbital period of Earth and Sun
t_nd = 365 * 24 * 3600 * 0.51 # s
return m_nd, r_nd, v_nd, t_nd
def normalization_constants_none():
return 1, 1, 1, 1
m_nd, r_nd, v_nd, t_nd = get_normalization_constants_alphacentauri()
|
g = 6.67408e-11
def get_normalization_constants_alphacentauri():
m_nd = 1.989e+30
r_nd = 5326000000000.0
v_nd = 30000
t_nd = 79.91 * 365 * 24 * 3600 * 0.51
return (m_nd, r_nd, v_nd, t_nd)
def get_normalization_constants_earthsun():
m_nd = 1.989e+30
r_nd = 149470000000.0
v_nd = 29780.0
t_nd = 365 * 24 * 3600 * 0.51
return (m_nd, r_nd, v_nd, t_nd)
def normalization_constants_none():
return (1, 1, 1, 1)
(m_nd, r_nd, v_nd, t_nd) = get_normalization_constants_alphacentauri()
|
"""
BFS
"""
class Solution909:
pass
|
"""
BFS
"""
class Solution909:
pass
|
# Time: 0.72 s
movies = []
for _ in range(int(input())):
movies.append(tuple(map(int, input().split())))
movies.sort(key=lambda x: x[1])
last_end_time = 0
movie_count = 0
for start_time, end_time in movies:
if start_time >= last_end_time:
last_end_time = end_time
movie_count += 1
print(movie_count)
|
movies = []
for _ in range(int(input())):
movies.append(tuple(map(int, input().split())))
movies.sort(key=lambda x: x[1])
last_end_time = 0
movie_count = 0
for (start_time, end_time) in movies:
if start_time >= last_end_time:
last_end_time = end_time
movie_count += 1
print(movie_count)
|
# 072220
# CodeSignal
# https://app.codesignal.com/arcade/intro/level-6/mCkmbxdMsMTjBc3Bm/solutions
def array_replace(inputArray, elemToReplace, substitutionElem):
# loop through input array
# if element = elemToReplace
# replace that element
for index,i in enumerate(inputArray):
if i == elemToReplace:
inputArray[index] = substitutionElem
return inputArray
|
def array_replace(inputArray, elemToReplace, substitutionElem):
for (index, i) in enumerate(inputArray):
if i == elemToReplace:
inputArray[index] = substitutionElem
return inputArray
|
while True:
print('\n--- MULTIPLICATION TABLE ---')
num = int(input('Type a number integer: '))
if num < 0:
break
for c in range(1, 11):
print(f'{c} X {num} = {c*num}')
print('END PROGRAM')
|
while True:
print('\n--- MULTIPLICATION TABLE ---')
num = int(input('Type a number integer: '))
if num < 0:
break
for c in range(1, 11):
print(f'{c} X {num} = {c * num}')
print('END PROGRAM')
|
def plot(width, height):
for j in range(height):
y = height - j - 1
print("y = {0:3} |".format(y), end="")
for x in range(width):
print("{0:3}".format(f(x,y)), end="")
print()
print(" +", end="")
for x in range(width):
print("---", end="")
print()
print(" ", end="")
for x in range(width):
print("{0:3}".format(x), end="")
print()
def f(x, y):
if x == y:
if x % 2 == 0:
return x + y
else:
return 1 + f(x-1, y-1)
elif x - 2 == y:
return f(x, y + 2) - 2
return ""
def test():
assert f(4, 2) == 6, "Test 1 failed"
assert f(6, 6) == 12, "Test 2 failed"
assert f(3, 4) == "", "Test 3 failed"
print("All tests passed")
if __name__ == '__main__':
lines = int(input())
for i in range(lines):
x, y = input().split()
n = f(int(x), int(y))
if n == "":
print("No Number")
else:
print(n)
#plot(20, 20)
|
def plot(width, height):
for j in range(height):
y = height - j - 1
print('y = {0:3} |'.format(y), end='')
for x in range(width):
print('{0:3}'.format(f(x, y)), end='')
print()
print(' +', end='')
for x in range(width):
print('---', end='')
print()
print(' ', end='')
for x in range(width):
print('{0:3}'.format(x), end='')
print()
def f(x, y):
if x == y:
if x % 2 == 0:
return x + y
else:
return 1 + f(x - 1, y - 1)
elif x - 2 == y:
return f(x, y + 2) - 2
return ''
def test():
assert f(4, 2) == 6, 'Test 1 failed'
assert f(6, 6) == 12, 'Test 2 failed'
assert f(3, 4) == '', 'Test 3 failed'
print('All tests passed')
if __name__ == '__main__':
lines = int(input())
for i in range(lines):
(x, y) = input().split()
n = f(int(x), int(y))
if n == '':
print('No Number')
else:
print(n)
|
'''
Psuedo-joystick object for playback of recorded macros
'''
class PlaybackJoystick():
def __init__(self, playback_data):
self.playback_data = playback_data
self.t = 0
def setTime(self, t=0):
self.t = t
def getRawAxis(self, axis):
#TODO fix me, get correct index for time t
# in the simulator it's called multiple times per millisecond, but the recorder only stores one per millisecond,
# so in the simulator index is usually the same as t.... but in the real bot it would be like every 50 ms or so
index = self.t
if(index < len(self.playback_data)):
return float(self.playback_data[index][axis + 2])
return 0
def getX(self, hand=None):
return self.getRawAxis(0)
def getY(self, hand=None):
return self.getRawAxis(1)
|
"""
Psuedo-joystick object for playback of recorded macros
"""
class Playbackjoystick:
def __init__(self, playback_data):
self.playback_data = playback_data
self.t = 0
def set_time(self, t=0):
self.t = t
def get_raw_axis(self, axis):
index = self.t
if index < len(self.playback_data):
return float(self.playback_data[index][axis + 2])
return 0
def get_x(self, hand=None):
return self.getRawAxis(0)
def get_y(self, hand=None):
return self.getRawAxis(1)
|
default_app_config = "freight.apps.FreightConfig"
__version__ = "1.5.1"
__title__ = "Freight"
|
default_app_config = 'freight.apps.FreightConfig'
__version__ = '1.5.1'
__title__ = 'Freight'
|
#
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
"""
Utility for monitoring collected data.
Author: Jeff Kinnison (jkinniso@nd.edu)
"""
# TODO: Add method to add handlers
# TODO: Add method to create PikaProducer
# TODO: Add method to use PikaProducer to respond to events
# TODO: Add method to deactivate monitor
class EventCheckerNotCallableException(Exception):
pass
class EventHandlerNotCallableException(Exception):
pass
class EventHandlerDoesNotExistException(Exception):
pass
class EventMonitor(object):
"""Checks data for user-defined bounds violations.
Instance variables:
handlers -- a dict of EventHandler objects indexed by name
"""
def __init__(self, event_check, handlers={}):
self._event_check = event_check
self.handlers = handlers
def __call__(self, val):
if not callable(self._event_check):
raise EventCheckerNotCallableException
self._run_handler(self.event_check(val))
def _run_handler(self, handler_names):
for name in handler_names:
if name not in self.handlers:
raise EventHandlerDoesNotExistException
if not callable(self.handlers[name]):
raise EventHandlerNotCallableException
self.handlers[name]()
|
"""
Utility for monitoring collected data.
Author: Jeff Kinnison (jkinniso@nd.edu)
"""
class Eventcheckernotcallableexception(Exception):
pass
class Eventhandlernotcallableexception(Exception):
pass
class Eventhandlerdoesnotexistexception(Exception):
pass
class Eventmonitor(object):
"""Checks data for user-defined bounds violations.
Instance variables:
handlers -- a dict of EventHandler objects indexed by name
"""
def __init__(self, event_check, handlers={}):
self._event_check = event_check
self.handlers = handlers
def __call__(self, val):
if not callable(self._event_check):
raise EventCheckerNotCallableException
self._run_handler(self.event_check(val))
def _run_handler(self, handler_names):
for name in handler_names:
if name not in self.handlers:
raise EventHandlerDoesNotExistException
if not callable(self.handlers[name]):
raise EventHandlerNotCallableException
self.handlers[name]()
|
words_file = open('wordlist.txt')
print("export const VALIDGUESSES6 = [")
for word in words_file.read().split('\n'):
word = word.strip()
if word.isalpha() and len(word) == 6:
print(' "%s",' % word.lower())
print("];")
|
words_file = open('wordlist.txt')
print('export const VALIDGUESSES6 = [')
for word in words_file.read().split('\n'):
word = word.strip()
if word.isalpha() and len(word) == 6:
print(' "%s",' % word.lower())
print('];')
|
graph = {}
n = input().split(' ')
node, edge, start = map(int, n)
for i in range(edge):
edge_number = input().split(' ')
n1, n2 = map(int, edge_number)
if n1 not in graph:
graph[n1] = [n2]
elif n2 not in graph[n1]:
graph[n1].append(n2)
if n2 not in graph:
graph[n2] = [n1]
elif n1 not in graph[n2]:
graph[n2].append(n1)
def DFS(graph, start):
visited = []
stack = [start]
while stack:
n = stack.pop()
if n not in visited:
visited.append(n)
if n in graph:
tmp = list(set(graph[n]) - set(visited))
tmp.sort(reverse=True)
stack += tmp
return " ".join(map(str, visited))
def BFS(graph, start):
visited = []
queue = [start]
while queue:
n = queue.pop(0)
if n not in visited:
visited.append(n)
if n in graph:
tmp = list(set(graph[n]) - set(visited))
tmp.sort()
queue += tmp
return " ".join(map(str, visited))
print(DFS(graph, start))
print(BFS(graph, start))
|
graph = {}
n = input().split(' ')
(node, edge, start) = map(int, n)
for i in range(edge):
edge_number = input().split(' ')
(n1, n2) = map(int, edge_number)
if n1 not in graph:
graph[n1] = [n2]
elif n2 not in graph[n1]:
graph[n1].append(n2)
if n2 not in graph:
graph[n2] = [n1]
elif n1 not in graph[n2]:
graph[n2].append(n1)
def dfs(graph, start):
visited = []
stack = [start]
while stack:
n = stack.pop()
if n not in visited:
visited.append(n)
if n in graph:
tmp = list(set(graph[n]) - set(visited))
tmp.sort(reverse=True)
stack += tmp
return ' '.join(map(str, visited))
def bfs(graph, start):
visited = []
queue = [start]
while queue:
n = queue.pop(0)
if n not in visited:
visited.append(n)
if n in graph:
tmp = list(set(graph[n]) - set(visited))
tmp.sort()
queue += tmp
return ' '.join(map(str, visited))
print(dfs(graph, start))
print(bfs(graph, start))
|
#
# PySNMP MIB module TPLINK-COMMANDER-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/TPLINK-COMMANDER-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 21:16:55 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
ObjectIdentifier, Integer, OctetString = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "Integer", "OctetString")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsUnion, ValueRangeConstraint, ConstraintsIntersection, ValueSizeConstraint, SingleValueConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "ValueRangeConstraint", "ConstraintsIntersection", "ValueSizeConstraint", "SingleValueConstraint")
ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "NotificationGroup")
NotificationType, Unsigned32, MibScalar, MibTable, MibTableRow, MibTableColumn, TimeTicks, MibIdentifier, iso, IpAddress, ModuleIdentity, ObjectIdentity, Counter64, Bits, Integer32, Counter32, Gauge32 = mibBuilder.importSymbols("SNMPv2-SMI", "NotificationType", "Unsigned32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "TimeTicks", "MibIdentifier", "iso", "IpAddress", "ModuleIdentity", "ObjectIdentity", "Counter64", "Bits", "Integer32", "Counter32", "Gauge32")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString")
clusterManage, = mibBuilder.importSymbols("TPLINK-CLUSTER-MIB", "clusterManage")
clusterConfig = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2))
commanderConfig = MibIdentifier((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4))
clusterName = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: clusterName.setStatus('current')
clusterHoldTime = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 255))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: clusterHoldTime.setStatus('current')
clusterIntervalTime = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 3), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 255))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: clusterIntervalTime.setStatus('current')
commanderClusterName = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 1), DisplayString().subtype(subtypeSpec=ValueSizeConstraint(1, 16))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: commanderClusterName.setStatus('current')
clusterIp = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 2), IpAddress()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: clusterIp.setStatus('current')
clusterIpMask = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 3), IpAddress()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: clusterIpMask.setStatus('current')
clusterCommit = MibScalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1))).clone(namedValues=NamedValues(("commit", 1)))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: clusterCommit.setStatus('current')
mibBuilder.exportSymbols("TPLINK-COMMANDER-MIB", commanderConfig=commanderConfig, clusterIntervalTime=clusterIntervalTime, clusterConfig=clusterConfig, clusterIp=clusterIp, clusterHoldTime=clusterHoldTime, clusterIpMask=clusterIpMask, clusterName=clusterName, clusterCommit=clusterCommit, commanderClusterName=commanderClusterName)
|
(object_identifier, integer, octet_string) = mibBuilder.importSymbols('ASN1', 'ObjectIdentifier', 'Integer', 'OctetString')
(named_values,) = mibBuilder.importSymbols('ASN1-ENUMERATION', 'NamedValues')
(constraints_union, value_range_constraint, constraints_intersection, value_size_constraint, single_value_constraint) = mibBuilder.importSymbols('ASN1-REFINEMENT', 'ConstraintsUnion', 'ValueRangeConstraint', 'ConstraintsIntersection', 'ValueSizeConstraint', 'SingleValueConstraint')
(module_compliance, notification_group) = mibBuilder.importSymbols('SNMPv2-CONF', 'ModuleCompliance', 'NotificationGroup')
(notification_type, unsigned32, mib_scalar, mib_table, mib_table_row, mib_table_column, time_ticks, mib_identifier, iso, ip_address, module_identity, object_identity, counter64, bits, integer32, counter32, gauge32) = mibBuilder.importSymbols('SNMPv2-SMI', 'NotificationType', 'Unsigned32', 'MibScalar', 'MibTable', 'MibTableRow', 'MibTableColumn', 'TimeTicks', 'MibIdentifier', 'iso', 'IpAddress', 'ModuleIdentity', 'ObjectIdentity', 'Counter64', 'Bits', 'Integer32', 'Counter32', 'Gauge32')
(textual_convention, display_string) = mibBuilder.importSymbols('SNMPv2-TC', 'TextualConvention', 'DisplayString')
(cluster_manage,) = mibBuilder.importSymbols('TPLINK-CLUSTER-MIB', 'clusterManage')
cluster_config = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2))
commander_config = mib_identifier((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4))
cluster_name = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 1), display_string().subtype(subtypeSpec=value_size_constraint(1, 16))).setMaxAccess('readonly')
if mibBuilder.loadTexts:
clusterName.setStatus('current')
cluster_hold_time = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 2), integer32().subtype(subtypeSpec=value_range_constraint(1, 255))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
clusterHoldTime.setStatus('current')
cluster_interval_time = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 3), integer32().subtype(subtypeSpec=value_range_constraint(1, 255))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
clusterIntervalTime.setStatus('current')
commander_cluster_name = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 1), display_string().subtype(subtypeSpec=value_size_constraint(1, 16))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
commanderClusterName.setStatus('current')
cluster_ip = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 2), ip_address()).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
clusterIp.setStatus('current')
cluster_ip_mask = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 3), ip_address()).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
clusterIpMask.setStatus('current')
cluster_commit = mib_scalar((1, 3, 6, 1, 4, 1, 11863, 6, 33, 1, 1, 3, 2, 4, 4), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1))).clone(namedValues=named_values(('commit', 1)))).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
clusterCommit.setStatus('current')
mibBuilder.exportSymbols('TPLINK-COMMANDER-MIB', commanderConfig=commanderConfig, clusterIntervalTime=clusterIntervalTime, clusterConfig=clusterConfig, clusterIp=clusterIp, clusterHoldTime=clusterHoldTime, clusterIpMask=clusterIpMask, clusterName=clusterName, clusterCommit=clusterCommit, commanderClusterName=commanderClusterName)
|
def hello(name):
return 'Hello ' + 'name'
def test_hello():
assert hello('name') == 'Hello name'
|
def hello(name):
return 'Hello ' + 'name'
def test_hello():
assert hello('name') == 'Hello name'
|
#!/usr/bin/env python
class MatrixUtil:
@classmethod
def allocateMatrix(cls, numRows, numCols):
rv = [0.0] * numRows
for i in range(numRows):
rv[i] = [0.0] * numCols
return rv
@classmethod
def allocateMatrixAsRowMajorArray(cls, numRows, numCols):
return [0.0] * numRows * numCols
@classmethod
def torben(cls, m, numRows, numCols):
n = numRows * numCols
midn = int((n + 1) / 2)
less = int()
greater = int()
equal = int()
min = float()
max = float()
guess = float()
maxltguess = float()
mingtguess = float()
min = max = m[0][0]
for i in range(numRows):
for j in range(numCols):
v = m[i][j]
if v < min:
min = v
if v > max:
max = v
while True:
guess = float((min + max) / 2)
less = 0
greater = 0
equal = 0
maxltguess = min
mingtguess = max
for _i in range(numRows):
for _j in range(numCols):
v = m[_i][_j]
if v < guess:
less += 1
if v > maxltguess:
maxltguess = v
elif v > guess:
greater += 1
if v < mingtguess:
mingtguess = v
else:
equal += 1
if less <= midn and greater <= midn:
break
elif less > greater:
max = maxltguess
else:
min = mingtguess
if less >= midn:
return maxltguess
elif less + equal >= midn:
return guess
else:
return mingtguess
|
class Matrixutil:
@classmethod
def allocate_matrix(cls, numRows, numCols):
rv = [0.0] * numRows
for i in range(numRows):
rv[i] = [0.0] * numCols
return rv
@classmethod
def allocate_matrix_as_row_major_array(cls, numRows, numCols):
return [0.0] * numRows * numCols
@classmethod
def torben(cls, m, numRows, numCols):
n = numRows * numCols
midn = int((n + 1) / 2)
less = int()
greater = int()
equal = int()
min = float()
max = float()
guess = float()
maxltguess = float()
mingtguess = float()
min = max = m[0][0]
for i in range(numRows):
for j in range(numCols):
v = m[i][j]
if v < min:
min = v
if v > max:
max = v
while True:
guess = float((min + max) / 2)
less = 0
greater = 0
equal = 0
maxltguess = min
mingtguess = max
for _i in range(numRows):
for _j in range(numCols):
v = m[_i][_j]
if v < guess:
less += 1
if v > maxltguess:
maxltguess = v
elif v > guess:
greater += 1
if v < mingtguess:
mingtguess = v
else:
equal += 1
if less <= midn and greater <= midn:
break
elif less > greater:
max = maxltguess
else:
min = mingtguess
if less >= midn:
return maxltguess
elif less + equal >= midn:
return guess
else:
return mingtguess
|
with open("input.txt") as input_file:
lines = input_file.readlines()
result = 0
for line in lines:
print(line.strip(), result)
result += int(line.strip())
print(result)
|
with open('input.txt') as input_file:
lines = input_file.readlines()
result = 0
for line in lines:
print(line.strip(), result)
result += int(line.strip())
print(result)
|
#License: https://bit.ly/3oLErEI
def test(strs):
return [*map(len, strs)]
strs = ['cat', 'car', 'fear', 'center']
print("Original strings:")
print(strs)
print("Lengths of the said list of non-empty strings:")
print(test(strs))
strs = ['cat', 'dog', 'shatter', 'donut', 'at', 'todo', '']
print("\nOriginal strings:")
print(strs)
print("Lengths of the said list of non-empty strings:")
print(test(strs))
|
def test(strs):
return [*map(len, strs)]
strs = ['cat', 'car', 'fear', 'center']
print('Original strings:')
print(strs)
print('Lengths of the said list of non-empty strings:')
print(test(strs))
strs = ['cat', 'dog', 'shatter', 'donut', 'at', 'todo', '']
print('\nOriginal strings:')
print(strs)
print('Lengths of the said list of non-empty strings:')
print(test(strs))
|
# Write a Python program to compute the greatest common divisor (GCD) of two positive integers.
n1 = int(input("Enter the first number: "))
n2 = int(input("Enter the second number: "))
a1 = []
a2 = []
a3 = []
for i in range(1, n1 + 1):
if n1 % i == 0:
a1.append(i)
for i in range(1, n2 + 1):
if n2 % i == 0:
a2.append(i)
for i in a1:
if i in a2:
a3.append(i)
print(max(a3))
|
n1 = int(input('Enter the first number: '))
n2 = int(input('Enter the second number: '))
a1 = []
a2 = []
a3 = []
for i in range(1, n1 + 1):
if n1 % i == 0:
a1.append(i)
for i in range(1, n2 + 1):
if n2 % i == 0:
a2.append(i)
for i in a1:
if i in a2:
a3.append(i)
print(max(a3))
|
# Only used for PyTorch open source BUCK build
IGNORED_ATTRIBUTE_PREFIX = [
"apple",
"fbobjc",
"windows",
"fbandroid",
"macosx",
]
IGNORED_ATTRIBUTES = [
"feature",
"platforms",
]
def filter_attributes(kwgs):
keys = list(kwgs.keys())
# drop unncessary attributes
for key in keys:
if key in IGNORED_ATTRIBUTES:
kwgs.pop(key)
else:
for invalid_prefix in IGNORED_ATTRIBUTE_PREFIX:
if key.startswith(invalid_prefix):
kwgs.pop(key)
return kwgs
|
ignored_attribute_prefix = ['apple', 'fbobjc', 'windows', 'fbandroid', 'macosx']
ignored_attributes = ['feature', 'platforms']
def filter_attributes(kwgs):
keys = list(kwgs.keys())
for key in keys:
if key in IGNORED_ATTRIBUTES:
kwgs.pop(key)
else:
for invalid_prefix in IGNORED_ATTRIBUTE_PREFIX:
if key.startswith(invalid_prefix):
kwgs.pop(key)
return kwgs
|
# -*- coding: utf-8 -*-
class Solution:
def crackSafe(self, n, k):
if k == 1:
return '0' * n
s = self.deBrujin(n, k)
return s + s[:n - 1]
def deBrujin(self, n, k):
"""See: https://en.wikipedia.org/wiki/De_Bruijn_sequence#Algorithm"""
def _deBrujin(t, p):
if t > n:
if n % p == 0:
sequence.extend(a[1:p + 1])
else:
a[t] = a[t - p]
_deBrujin(t + 1, p)
for j in range(a[t - p] + 1, k):
a[t] = j
_deBrujin(t + 1, t)
a = [0] * k * n
sequence = []
_deBrujin(1, 1)
return ''.join(str(el) for el in sequence)
if __name__ == '__main__':
solution = Solution()
assert '01' == solution.crackSafe(1, 2)
assert '00110' == solution.crackSafe(2, 2)
assert '0' == solution.crackSafe(1, 1)
assert '00' == solution.crackSafe(2, 1)
|
class Solution:
def crack_safe(self, n, k):
if k == 1:
return '0' * n
s = self.deBrujin(n, k)
return s + s[:n - 1]
def de_brujin(self, n, k):
"""See: https://en.wikipedia.org/wiki/De_Bruijn_sequence#Algorithm"""
def _de_brujin(t, p):
if t > n:
if n % p == 0:
sequence.extend(a[1:p + 1])
else:
a[t] = a[t - p]
_de_brujin(t + 1, p)
for j in range(a[t - p] + 1, k):
a[t] = j
_de_brujin(t + 1, t)
a = [0] * k * n
sequence = []
_de_brujin(1, 1)
return ''.join((str(el) for el in sequence))
if __name__ == '__main__':
solution = solution()
assert '01' == solution.crackSafe(1, 2)
assert '00110' == solution.crackSafe(2, 2)
assert '0' == solution.crackSafe(1, 1)
assert '00' == solution.crackSafe(2, 1)
|
def media_suicida (mediaProvas, mediaTrabalhos):
if mediaProvas >= 5 and mediaTrabalhos >= 5:
return mediaProvas * 0.6 + mediaTrabalhos * 0.4
return min(mediaProvas, mediaTrabalhos)
notasProva = []
notasTrabalho = []
quantidadeProva = int(input("Quantidade de provas: "))
for item in range(quantidadeProva):
n = float(input("Nota da prova {}: ".format(item + 1)))
notasProva.append(n)
quantidadeTrabalho = int(input("Quantidade de trabalhos: "))
for item in range(quantidadeTrabalho):
n = float(input("Nota do trabalho {}: ".format(item + 1)))
notasTrabalho.append((n))
mediaProva = sum(notasProva) / quantidadeProva
mediaTrabalho = sum(notasTrabalho) / quantidadeTrabalho
print("Media final = {}".format(media_suicida(mediaProva, mediaTrabalho)))
|
def media_suicida(mediaProvas, mediaTrabalhos):
if mediaProvas >= 5 and mediaTrabalhos >= 5:
return mediaProvas * 0.6 + mediaTrabalhos * 0.4
return min(mediaProvas, mediaTrabalhos)
notas_prova = []
notas_trabalho = []
quantidade_prova = int(input('Quantidade de provas: '))
for item in range(quantidadeProva):
n = float(input('Nota da prova {}: '.format(item + 1)))
notasProva.append(n)
quantidade_trabalho = int(input('Quantidade de trabalhos: '))
for item in range(quantidadeTrabalho):
n = float(input('Nota do trabalho {}: '.format(item + 1)))
notasTrabalho.append(n)
media_prova = sum(notasProva) / quantidadeProva
media_trabalho = sum(notasTrabalho) / quantidadeTrabalho
print('Media final = {}'.format(media_suicida(mediaProva, mediaTrabalho)))
|
print('Begin', __name__)
print('Defines fA')
def fA():
print('Inside fA')
if __name__ == "__main__":
print('Calls fA')
fA()
print('End', __name__)
|
print('Begin', __name__)
print('Defines fA')
def f_a():
print('Inside fA')
if __name__ == '__main__':
print('Calls fA')
f_a()
print('End', __name__)
|
def find_missing_number(sequence):
try:
numbers = sorted(int(word) for word in sequence.split(" ") if word)
except ValueError:
return 1
return next((i + 1 for i, n in enumerate(numbers) if i + 1 != n), 0)
|
def find_missing_number(sequence):
try:
numbers = sorted((int(word) for word in sequence.split(' ') if word))
except ValueError:
return 1
return next((i + 1 for (i, n) in enumerate(numbers) if i + 1 != n), 0)
|
# Lucas Reicher Prompt #3 - Coding Journal #1
def main():
# Uses formatted strings to output the required info (result & type)
# Adds floats
x = 1.342 # float
y = 3.433 # float
z = x + y # float
float_sum_string = "Addition: {0} + {1} = {2} with type = {3}".format(str(x),str(y),str(z),str(type(z)))
print(float_sum_string)
# Subtracts integers
x = 5 # int
y = 2 # int
z = x - y # int
float_difference_string = "Subtraction: {0} - {1} = {2} with type = {3}".format(str(x),str(y),str(z),str(type(z)))
print(float_difference_string)
# Multiplies float and int
x = 1.342 # float
y = 3 # int
z = x * y # float
float_product_string = "Multiplication: {0} * {1} = {2} with type = {3}".format(str(x),str(y),str(z),str(type(z)))
print(float_product_string)
if __name__ == "__main__":
main()
|
def main():
x = 1.342
y = 3.433
z = x + y
float_sum_string = 'Addition: {0} + {1} = {2} with type = {3}'.format(str(x), str(y), str(z), str(type(z)))
print(float_sum_string)
x = 5
y = 2
z = x - y
float_difference_string = 'Subtraction: {0} - {1} = {2} with type = {3}'.format(str(x), str(y), str(z), str(type(z)))
print(float_difference_string)
x = 1.342
y = 3
z = x * y
float_product_string = 'Multiplication: {0} * {1} = {2} with type = {3}'.format(str(x), str(y), str(z), str(type(z)))
print(float_product_string)
if __name__ == '__main__':
main()
|
"""
At infinite membrane resistance, the Neuron does not leak any current out,
and hence it starts firing with the slightest input current,
This shifts the transfer function towards 0, similar to ReLU activation (centered at 0).
Also, when there is minimal refractory time, the neuron can keep firing
at a high input current which avoids the saturation.
""";
|
"""
At infinite membrane resistance, the Neuron does not leak any current out,
and hence it starts firing with the slightest input current,
This shifts the transfer function towards 0, similar to ReLU activation (centered at 0).
Also, when there is minimal refractory time, the neuron can keep firing
at a high input current which avoids the saturation.
"""
|
class Solution:
"""
@param k: The k
@param a: The A
@param b: The B
@return: The answer
"""
def addition(self, k, a, b):
result = ""
i = len(a) - 1
j = len(b) - 1
carry = 0
while i >= 0 and j >= 0:
summ = carry + ord(a[i]) - ord('0') + ord(b[j]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
i -= 1
j -= 1
while i >= 0 :
summ = carry + ord(a[i]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
i -= 1
while j >= 0 :
summ = carry + ord(b[j]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
j -= 1
if carry > 0:
result += str(carry)
result = result[::-1]
# trim zeros
for i in range(len(result)):
if result[i] != "0":
return result[i:]
return "0"
|
class Solution:
"""
@param k: The k
@param a: The A
@param b: The B
@return: The answer
"""
def addition(self, k, a, b):
result = ''
i = len(a) - 1
j = len(b) - 1
carry = 0
while i >= 0 and j >= 0:
summ = carry + ord(a[i]) - ord('0') + ord(b[j]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
i -= 1
j -= 1
while i >= 0:
summ = carry + ord(a[i]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
i -= 1
while j >= 0:
summ = carry + ord(b[j]) - ord('0')
carry = int(summ / k)
result += str(summ % k)
j -= 1
if carry > 0:
result += str(carry)
result = result[::-1]
for i in range(len(result)):
if result[i] != '0':
return result[i:]
return '0'
|
# OpenWeatherMap API Key
weather_api_key = "e1067d92d6b631a16363bf4db3023b19"
# Google API Key
g_key = "AIzaSyA4RYdQ1nxoMTIW854C7wvVJMf0Qz5qjNk"
|
weather_api_key = 'e1067d92d6b631a16363bf4db3023b19'
g_key = 'AIzaSyA4RYdQ1nxoMTIW854C7wvVJMf0Qz5qjNk'
|
class DmsRequestError(Exception):
def __init__(self, error_message, status_code):
self.message = "Error requesting DMS API %s with code %s" \
% (error_message, status_code)
super(DmsRequestError, self).__init__(self.message)
|
class Dmsrequesterror(Exception):
def __init__(self, error_message, status_code):
self.message = 'Error requesting DMS API %s with code %s' % (error_message, status_code)
super(DmsRequestError, self).__init__(self.message)
|
class Keyword:
def __init__(self, keyword):
if keyword in ['add', 'find']:
self.value = keyword
else:
self.value = 'find'
|
class Keyword:
def __init__(self, keyword):
if keyword in ['add', 'find']:
self.value = keyword
else:
self.value = 'find'
|
"""Given a string containing only the characters x and y, find whether there are the same number of xs and ys.
balanced("xxxyyy") => true
balanced("yyyxxx") => true
balanced("xxxyyyy") => false
balanced("yyxyxxyxxyyyyxxxyxyx") => true
balanced("xyxxxxyyyxyxxyxxyy") => false
balanced("") => true
balanced("x") => false
"""
"""Optional bonus
Given a string containing only lowercase letters, find whether every letter that appears in the string appears the same number of times. Don't forget to handle the empty string ("") correctly!
balanced_bonus("xxxyyyzzz") => true
balanced_bonus("abccbaabccba") => true
balanced_bonus("xxxyyyzzzz") => false
balanced_bonus("abcdefghijklmnopqrstuvwxyz") => true
balanced_bonus("pqq") => false
balanced_bonus("fdedfdeffeddefeeeefddf") => false
balanced_bonus("www") => true
balanced_bonus("x") => true
balanced_bonus("") => true
Note that balanced_bonus behaves differently than balanced for a few inputs, e.g. "x".
"""
def balanced(string):
x_count, y_count = 0, 0
for char in string:
if char == 'x':
x_count = x_count + 1
elif char =='y':
y_count = y_count + 1
else:
print("Strings may only contain 'x' or 'y'. Exiting")
exit()
if x_count == y_count:
return True
else:
return False
# From reddit comments
def balanced_bonus(string):
if len(string) == 0:
return True
letters = {}
for letter in string:
try:
letters[letter] += 1
except:
letters[letter] = 1
return len(set(letters.values())) == 1
print("balanced(\"xxxyyy\"): ", balanced("xxxyyy"))
print("balanced(\"yyyxxx\"): ", balanced("yyyxxx"))
print("balanced(\"xxxyyyy\"): ", balanced("xxxyyyy"))
print("balanced(\"yyxyxxyxxyyyyxxxyxyx\"): ", balanced("yyxyxxyxxyyyyxxxyxyx"))
print("balanced(\"xyxxxxyyyxyxxyxxyy\"): ", balanced("xyxxxxyyyxyxxyxxyy"))
print("balanced(\"\"): ", balanced(""))
print("balanced(\"x\"): ", balanced("x"))
#print("balanced(\"xxxyyya\"): ", balanced("xxxyyya"))
print("balanced_bonus(\"xxxyyyzzz\"): ", balanced_bonus("xxxyyyzzz"))
print("balanced_bonus(\"abccbaabccba\"): ", balanced_bonus("abccbaabccba"))
print("balanced_bonus(\"xxxyyyzzzz\"): ", balanced_bonus("xxxyyyzzzz"))
print("balanced_bonus(\"abcdefghijklmnopqrstuvwxyz\"): ", balanced_bonus("abcdefghijklmnopqrstuvwxyz"))
print("balanced_bonus(\"pqq\"): ", balanced_bonus("pqq"))
print("balanced_bonus(\"fdedfdeffeddefeeeefddf\"): ", balanced_bonus("fdedfdeffeddefeeeefddf"))
print("balanced_bonus(\"www\"): ", balanced_bonus("www"))
print("balanced_bonus(\"\"): ", balanced_bonus(""))
print("balanced_bonus(\"x\"): ", balanced_bonus("x"))
# one line solution from reddit:
#def balanced(string):
# return string.lower().count("x") == string.lower().count("y")
|
"""Given a string containing only the characters x and y, find whether there are the same number of xs and ys.
balanced("xxxyyy") => true
balanced("yyyxxx") => true
balanced("xxxyyyy") => false
balanced("yyxyxxyxxyyyyxxxyxyx") => true
balanced("xyxxxxyyyxyxxyxxyy") => false
balanced("") => true
balanced("x") => false
"""
'Optional bonus\nGiven a string containing only lowercase letters, find whether every letter that appears in the string appears the same number of times. Don\'t forget to handle the empty string ("") correctly!\n\nbalanced_bonus("xxxyyyzzz") => true\nbalanced_bonus("abccbaabccba") => true\nbalanced_bonus("xxxyyyzzzz") => false\nbalanced_bonus("abcdefghijklmnopqrstuvwxyz") => true\nbalanced_bonus("pqq") => false\nbalanced_bonus("fdedfdeffeddefeeeefddf") => false\nbalanced_bonus("www") => true\nbalanced_bonus("x") => true\nbalanced_bonus("") => true\nNote that balanced_bonus behaves differently than balanced for a few inputs, e.g. "x".\n'
def balanced(string):
(x_count, y_count) = (0, 0)
for char in string:
if char == 'x':
x_count = x_count + 1
elif char == 'y':
y_count = y_count + 1
else:
print("Strings may only contain 'x' or 'y'. Exiting")
exit()
if x_count == y_count:
return True
else:
return False
def balanced_bonus(string):
if len(string) == 0:
return True
letters = {}
for letter in string:
try:
letters[letter] += 1
except:
letters[letter] = 1
return len(set(letters.values())) == 1
print('balanced("xxxyyy"): ', balanced('xxxyyy'))
print('balanced("yyyxxx"): ', balanced('yyyxxx'))
print('balanced("xxxyyyy"): ', balanced('xxxyyyy'))
print('balanced("yyxyxxyxxyyyyxxxyxyx"): ', balanced('yyxyxxyxxyyyyxxxyxyx'))
print('balanced("xyxxxxyyyxyxxyxxyy"): ', balanced('xyxxxxyyyxyxxyxxyy'))
print('balanced(""): ', balanced(''))
print('balanced("x"): ', balanced('x'))
print('balanced_bonus("xxxyyyzzz"): ', balanced_bonus('xxxyyyzzz'))
print('balanced_bonus("abccbaabccba"): ', balanced_bonus('abccbaabccba'))
print('balanced_bonus("xxxyyyzzzz"): ', balanced_bonus('xxxyyyzzzz'))
print('balanced_bonus("abcdefghijklmnopqrstuvwxyz"): ', balanced_bonus('abcdefghijklmnopqrstuvwxyz'))
print('balanced_bonus("pqq"): ', balanced_bonus('pqq'))
print('balanced_bonus("fdedfdeffeddefeeeefddf"): ', balanced_bonus('fdedfdeffeddefeeeefddf'))
print('balanced_bonus("www"): ', balanced_bonus('www'))
print('balanced_bonus(""): ', balanced_bonus(''))
print('balanced_bonus("x"): ', balanced_bonus('x'))
|
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 28 10:15:21 2021
@author: CC-SXF
"""
|
"""
Created on Sun Mar 28 10:15:21 2021
@author: CC-SXF
"""
|
# import datetime
# import logging
# logger = logging.getLogger(__name__)
# logger.setLevel(logging.INFO)
def run(event, context):
# current_time = datetime.datetime.now().time()
# name = context.function_name
# logger.info("Your cron function " + name + " ran at " + str(current_time))
return "hello world!"
|
def run(event, context):
return 'hello world!'
|
# coding: utf-8
class RurouniException(Exception):
pass
class ConfigException(RurouniException):
pass
class TokenBucketFull(RurouniException):
pass
class UnexpectedMetric(RurouniException):
pass
|
class Rurouniexception(Exception):
pass
class Configexception(RurouniException):
pass
class Tokenbucketfull(RurouniException):
pass
class Unexpectedmetric(RurouniException):
pass
|
class ControlStyles(Enum,IComparable,IFormattable,IConvertible):
"""
Specifies the style and behavior of a control.
enum (flags) ControlStyles,values: AllPaintingInWmPaint (8192),CacheText (16384),ContainerControl (1),DoubleBuffer (65536),EnableNotifyMessage (32768),FixedHeight (64),FixedWidth (32),Opaque (4),OptimizedDoubleBuffer (131072),ResizeRedraw (16),Selectable (512),StandardClick (256),StandardDoubleClick (4096),SupportsTransparentBackColor (2048),UserMouse (1024),UserPaint (2),UseTextForAccessibility (262144)
"""
def __eq__(self,*args):
""" x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """
pass
def __format__(self,*args):
""" __format__(formattable: IFormattable,format: str) -> str """
pass
def __ge__(self,*args):
pass
def __gt__(self,*args):
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
def __le__(self,*args):
pass
def __lt__(self,*args):
pass
def __ne__(self,*args):
pass
def __reduce_ex__(self,*args):
pass
def __str__(self,*args):
pass
AllPaintingInWmPaint=None
CacheText=None
ContainerControl=None
DoubleBuffer=None
EnableNotifyMessage=None
FixedHeight=None
FixedWidth=None
Opaque=None
OptimizedDoubleBuffer=None
ResizeRedraw=None
Selectable=None
StandardClick=None
StandardDoubleClick=None
SupportsTransparentBackColor=None
UserMouse=None
UserPaint=None
UseTextForAccessibility=None
value__=None
|
class Controlstyles(Enum, IComparable, IFormattable, IConvertible):
"""
Specifies the style and behavior of a control.
enum (flags) ControlStyles,values: AllPaintingInWmPaint (8192),CacheText (16384),ContainerControl (1),DoubleBuffer (65536),EnableNotifyMessage (32768),FixedHeight (64),FixedWidth (32),Opaque (4),OptimizedDoubleBuffer (131072),ResizeRedraw (16),Selectable (512),StandardClick (256),StandardDoubleClick (4096),SupportsTransparentBackColor (2048),UserMouse (1024),UserPaint (2),UseTextForAccessibility (262144)
"""
def __eq__(self, *args):
""" x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """
pass
def __format__(self, *args):
""" __format__(formattable: IFormattable,format: str) -> str """
pass
def __ge__(self, *args):
pass
def __gt__(self, *args):
pass
def __init__(self, *args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
def __le__(self, *args):
pass
def __lt__(self, *args):
pass
def __ne__(self, *args):
pass
def __reduce_ex__(self, *args):
pass
def __str__(self, *args):
pass
all_painting_in_wm_paint = None
cache_text = None
container_control = None
double_buffer = None
enable_notify_message = None
fixed_height = None
fixed_width = None
opaque = None
optimized_double_buffer = None
resize_redraw = None
selectable = None
standard_click = None
standard_double_click = None
supports_transparent_back_color = None
user_mouse = None
user_paint = None
use_text_for_accessibility = None
value__ = None
|
"""
how to create a class
a class is constructed through constructor
=> a class can be constructed through specific function called "__init__(self)"
"""
# let's create a Class
class Person:
"""
A class to create a person with the following attributes:
age, marks, phone, user_id, profession, goal
Have the following methods:
get_age()
get_marks()
get_phone()
get_user_id()
get_profession()
get_goal()
set_age(age)
set_marks(marks)
set_phone(phone)
set_user_id(user_id)
set_profession(profession)
set_goal(goal)
print_details()
"""
# now we have to define the shape of the class for that we use __init__
def __init__(self, age, marks, phone, user_id, profession, goal):
# this is a special function for the initialising the variables
# construct the shape
## to add new parameters we pass in init method
"""
this is a function to initialise the variables of the class
:param age: int
:param marks: int
:param phone: int
:param user_id: int
:param profession: string
:param goal: string
"""
self.age = age
self.marks = marks
self.phone = phone
self.user_id = user_id
self.profession = profession
self.goal = goal
def get_age(self):
"""
this is a function to get the age of the class
:return: int
"""
return self.age
def get_marks(self):
"""
this is a function to get the marks of the class
:return: int
"""
return self.marks
def get_phone(self):
"""
this is a function to get the phone of the class
:return: int
"""
return self.phone
def get_user_id(self):
"""
this is a function to get the user_id of the class
:return: int
"""
return self.user_id
def get_profession(self):
"""
this is a function to get the profession of the class
:return: string
"""
return self.profession
def get_goal(self):
"""
this is a function to get the goal of the class
:return: goal
"""
return self.goal
def set_age(self, age):
"""
this is a function to set the age of the class
:param age: int
:return: Age
"""
self.age = age
def set_marks(self, marks):
"""
this is a function to set the marks of the class
:param marks: int
:return: marks
"""
self.marks = marks
def set_phone(self, phone):
"""
this is a function to set the phone of the class
:param phone: int
:return: phone
"""
self.phone = phone
def set_user_id(self, user_id):
"""
this is a function to set the user_id of the class
:param user_id: int
:return: user_id
"""
self.user_id = user_id
def set_profession(self, profession):
"""
this is a function to set the profession of the class
:param profession: string
:return: Profession
"""
self.profession = profession
def set_goal(self, goal):
"""
this is a function to set the goal of the class
:param goal: string
:return: goal
"""
self.goal = goal
def print_details(self):
"""
this is a function to print the details of the class
:return: age , marks , phone , user_id , profession , goal
"""
print("age: ", self.age)
print("marks: ", self.marks)
print("phone: ", self.phone)
print("user_id: ", self.user_id)
print("profession: ", self.profession)
print("goal: ", self.goal)
abhishek = Person(21, 90, 31114111, 12345, "student", "to be a good programmer")
abhishek.set_age(20)
abhishek.set_marks(90)
abhishek.set_phone(9674144556) # yess this is a valid phone number of mine :)
abhishek.set_user_id(1)
abhishek.set_profession("student")
abhishek.set_goal("to be a good programmer")
print("the address is ")
print(abhishek) # this is the address of the object
print(abhishek.__dict__) # this is a dictionary of the class
print(abhishek.__doc__) # this is a special function to print the docstring of the class
abhishek.print_details() # this is to print the details of the class
profession = abhishek.get_profession() # this is to get the profession of the class
print("the profession is " + profession) # this is to print the profession of the class
|
"""
how to create a class
a class is constructed through constructor
=> a class can be constructed through specific function called "__init__(self)"
"""
class Person:
"""
A class to create a person with the following attributes:
age, marks, phone, user_id, profession, goal
Have the following methods:
get_age()
get_marks()
get_phone()
get_user_id()
get_profession()
get_goal()
set_age(age)
set_marks(marks)
set_phone(phone)
set_user_id(user_id)
set_profession(profession)
set_goal(goal)
print_details()
"""
def __init__(self, age, marks, phone, user_id, profession, goal):
"""
this is a function to initialise the variables of the class
:param age: int
:param marks: int
:param phone: int
:param user_id: int
:param profession: string
:param goal: string
"""
self.age = age
self.marks = marks
self.phone = phone
self.user_id = user_id
self.profession = profession
self.goal = goal
def get_age(self):
"""
this is a function to get the age of the class
:return: int
"""
return self.age
def get_marks(self):
"""
this is a function to get the marks of the class
:return: int
"""
return self.marks
def get_phone(self):
"""
this is a function to get the phone of the class
:return: int
"""
return self.phone
def get_user_id(self):
"""
this is a function to get the user_id of the class
:return: int
"""
return self.user_id
def get_profession(self):
"""
this is a function to get the profession of the class
:return: string
"""
return self.profession
def get_goal(self):
"""
this is a function to get the goal of the class
:return: goal
"""
return self.goal
def set_age(self, age):
"""
this is a function to set the age of the class
:param age: int
:return: Age
"""
self.age = age
def set_marks(self, marks):
"""
this is a function to set the marks of the class
:param marks: int
:return: marks
"""
self.marks = marks
def set_phone(self, phone):
"""
this is a function to set the phone of the class
:param phone: int
:return: phone
"""
self.phone = phone
def set_user_id(self, user_id):
"""
this is a function to set the user_id of the class
:param user_id: int
:return: user_id
"""
self.user_id = user_id
def set_profession(self, profession):
"""
this is a function to set the profession of the class
:param profession: string
:return: Profession
"""
self.profession = profession
def set_goal(self, goal):
"""
this is a function to set the goal of the class
:param goal: string
:return: goal
"""
self.goal = goal
def print_details(self):
"""
this is a function to print the details of the class
:return: age , marks , phone , user_id , profession , goal
"""
print('age: ', self.age)
print('marks: ', self.marks)
print('phone: ', self.phone)
print('user_id: ', self.user_id)
print('profession: ', self.profession)
print('goal: ', self.goal)
abhishek = person(21, 90, 31114111, 12345, 'student', 'to be a good programmer')
abhishek.set_age(20)
abhishek.set_marks(90)
abhishek.set_phone(9674144556)
abhishek.set_user_id(1)
abhishek.set_profession('student')
abhishek.set_goal('to be a good programmer')
print('the address is ')
print(abhishek)
print(abhishek.__dict__)
print(abhishek.__doc__)
abhishek.print_details()
profession = abhishek.get_profession()
print('the profession is ' + profession)
|
# Write a program that reads a word and prints all substrings, sorted by length. For
# example, if the user provides the input "rum" , the program prints
# r
# u
# m
# ru
# um
# rum
word = str(input("Enter a word: "))
wordLen = len(word)
subLen = 1
start = 0
for i in range(wordLen):
start = 0
while start + subLen <= wordLen:
print(word[start:start+subLen])
start += 1
subLen += 1
|
word = str(input('Enter a word: '))
word_len = len(word)
sub_len = 1
start = 0
for i in range(wordLen):
start = 0
while start + subLen <= wordLen:
print(word[start:start + subLen])
start += 1
sub_len += 1
|
x = 100
y = 50
print('x=', x, 'y=', y)
|
x = 100
y = 50
print('x=', x, 'y=', y)
|
BASE_CASE = {
"model": {
"random_seed": 495279142,
"default_age_grid": "0 0.01917808 0.07671233 1 5 10 20 30 40 50 60 70 80 90 100",
"default_time_grid": "1990 1995 2000 2005 2010 2015 2016",
"add_calc_emr": "from_both",
"birth_prev": 0,
"ode_step_size": 5,
"minimum_meas_cv": 0.2,
"rate_case": "iota_pos_rho_zero",
"data_density": "log_gaussian",
"constrain_omega": 1,
"modelable_entity_id": 2005,
"decomp_step_id": 3,
"research_area": 2,
"drill": "drill",
"drill_location_start": 70,
"bundle_id": 173,
"crosswalk_version_id": 5699,
"split_sex": "most_detailed",
"add_csmr_cause": 587,
"drill_sex": 2,
"model_version_id": 472515,
"title": "test diabetes australasia marlena -- 2",
"relabel_incidence": 2,
"description": "<p>diabetes<\/p>",
"addl_ode_stpes": "0.01917808 0.07671233 1.0",
"zero_sum_random": [
"iota"
],
"bound_frac_fixed": 1.0e-8,
"drill_location_end": [72],
"quasi_fixed": 0
},
"max_num_iter": {
"fixed": 200,
"random": 100
},
"print_level": {
"fixed": 5,
"random": 0
},
"accept_after_max_steps": {
"fixed": 5,
"random": 5
},
"students_dof": {
"priors": 5,
"data": 5
},
"log_students_dof": {
"priors": 5,
"data": 5
},
"eta": {
"priors": 1.0e-5,
"data": 1.0e-5
},
"config_version": "mnorwood",
"rate": [
{
"age_time_specific": 1,
"default": {
"value": {
"density": "gaussian",
"min": 1.0e-6,
"mean": 0.00015,
"max": 0.01,
"std": 1.5,
"eta": 1.0e-6
},
"dage": {
"density": "gaussian",
"min": -1,
"mean": 0,
"max": 1,
"std": 0.01
},
"dtime": {
"density": "gaussian",
"min": -1,
"mean": 0,
"max": 1,
"std": 0.01
}
},
"rate": "iota",
"age_grid": "0 5 10 50 100"
},
{
"age_time_specific": 1,
"default": {
"value": {
"density": "gaussian",
"min": 1.0e-6,
"mean": 0.0004,
"max": 0.01,
"std": 0.2
},
"dage": {
"density": "gaussian",
"min": -1,
"mean": 0,
"max": 1,
"std": 0.01
},
"dtime": {
"density": "gaussian",
"min": -1,
"mean": 0,
"max": 1,
"std": 0.01
}
},
"rate": "chi"
},
{
"age_time_specific": 0,
"default": {
"value": {
"density": "log_gaussian",
"min": 0,
"mean": 0.1,
"max": 0.2,
"std": 1,
"eta": 1.0e-6
},
"dage": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1
},
"dtime": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1
}
},
"rate": "pini"
}
],
"random_effect": [
{
"age_time_specific": 0,
"default": {
"value": {
"density": "gaussian",
"mean": 0,
"std": 1
},
"dage": {
"mean": 0,
"std": 1,
"density": "uniform"
},
"dtime": {
"mean": 0,
"std": 1,
"density": "uniform"
}
},
"rate": "iota"
}
],
"study_covariate": [
{
"age_time_specific": 0,
"mulcov_type": "rate_value",
"default": {
"value": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1
},
"dage": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1
},
"dtime": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1
}
},
"study_covariate_id": 0,
"transformation": 0,
"measure_id": 41
}
],
"country_covariate": [
{
"age_time_specific": 0,
"mulcov_type": "rate_value",
"measure_id": 41,
"country_covariate_id": 28,
"transformation": 0,
"default": {
"value": {
"density": "uniform",
"min": -1,
"mean": 0,
"max": 1,
"eta": 1.0e-5
}
}
}
],
"gbd_round_id": 6,
"csmr_cod_output_version_id": 84,
"csmr_mortality_output_version_id": 8003,
"location_set_version_id": 684,
"tolerance": {
"fixed": 1.0e-6,
"random": 1.0e-6
}
}
|
base_case = {'model': {'random_seed': 495279142, 'default_age_grid': '0 0.01917808 0.07671233 1 5 10 20 30 40 50 60 70 80 90 100', 'default_time_grid': '1990 1995 2000 2005 2010 2015 2016', 'add_calc_emr': 'from_both', 'birth_prev': 0, 'ode_step_size': 5, 'minimum_meas_cv': 0.2, 'rate_case': 'iota_pos_rho_zero', 'data_density': 'log_gaussian', 'constrain_omega': 1, 'modelable_entity_id': 2005, 'decomp_step_id': 3, 'research_area': 2, 'drill': 'drill', 'drill_location_start': 70, 'bundle_id': 173, 'crosswalk_version_id': 5699, 'split_sex': 'most_detailed', 'add_csmr_cause': 587, 'drill_sex': 2, 'model_version_id': 472515, 'title': 'test diabetes australasia marlena -- 2', 'relabel_incidence': 2, 'description': '<p>diabetes<\\/p>', 'addl_ode_stpes': '0.01917808 0.07671233 1.0', 'zero_sum_random': ['iota'], 'bound_frac_fixed': 1e-08, 'drill_location_end': [72], 'quasi_fixed': 0}, 'max_num_iter': {'fixed': 200, 'random': 100}, 'print_level': {'fixed': 5, 'random': 0}, 'accept_after_max_steps': {'fixed': 5, 'random': 5}, 'students_dof': {'priors': 5, 'data': 5}, 'log_students_dof': {'priors': 5, 'data': 5}, 'eta': {'priors': 1e-05, 'data': 1e-05}, 'config_version': 'mnorwood', 'rate': [{'age_time_specific': 1, 'default': {'value': {'density': 'gaussian', 'min': 1e-06, 'mean': 0.00015, 'max': 0.01, 'std': 1.5, 'eta': 1e-06}, 'dage': {'density': 'gaussian', 'min': -1, 'mean': 0, 'max': 1, 'std': 0.01}, 'dtime': {'density': 'gaussian', 'min': -1, 'mean': 0, 'max': 1, 'std': 0.01}}, 'rate': 'iota', 'age_grid': '0 5 10 50 100'}, {'age_time_specific': 1, 'default': {'value': {'density': 'gaussian', 'min': 1e-06, 'mean': 0.0004, 'max': 0.01, 'std': 0.2}, 'dage': {'density': 'gaussian', 'min': -1, 'mean': 0, 'max': 1, 'std': 0.01}, 'dtime': {'density': 'gaussian', 'min': -1, 'mean': 0, 'max': 1, 'std': 0.01}}, 'rate': 'chi'}, {'age_time_specific': 0, 'default': {'value': {'density': 'log_gaussian', 'min': 0, 'mean': 0.1, 'max': 0.2, 'std': 1, 'eta': 1e-06}, 'dage': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1}, 'dtime': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1}}, 'rate': 'pini'}], 'random_effect': [{'age_time_specific': 0, 'default': {'value': {'density': 'gaussian', 'mean': 0, 'std': 1}, 'dage': {'mean': 0, 'std': 1, 'density': 'uniform'}, 'dtime': {'mean': 0, 'std': 1, 'density': 'uniform'}}, 'rate': 'iota'}], 'study_covariate': [{'age_time_specific': 0, 'mulcov_type': 'rate_value', 'default': {'value': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1}, 'dage': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1}, 'dtime': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1}}, 'study_covariate_id': 0, 'transformation': 0, 'measure_id': 41}], 'country_covariate': [{'age_time_specific': 0, 'mulcov_type': 'rate_value', 'measure_id': 41, 'country_covariate_id': 28, 'transformation': 0, 'default': {'value': {'density': 'uniform', 'min': -1, 'mean': 0, 'max': 1, 'eta': 1e-05}}}], 'gbd_round_id': 6, 'csmr_cod_output_version_id': 84, 'csmr_mortality_output_version_id': 8003, 'location_set_version_id': 684, 'tolerance': {'fixed': 1e-06, 'random': 1e-06}}
|
#Write a function named "falling_distance" that accepts an object's falling time
#(in seconds) as an argument. The function should return the distance, in meters
#, that the object has fallen during the time interval.Write a program that
#calls the function in a loop that passes the values 1 through 10 as arguments
#and displays the return value.
def main():
print("This program shows an object's fall distance (in meters) with each")
print('passing second from 1 to 10.')
print()
print('Time(s)\tDistance(m)')
print('--------------------')
for time in range (10 + 1):
distance = falling_distance(time)
print(time, '\t', format(distance, ',.1f'))
def falling_distance(time):
g = 9.8
distance = 0.5*g*time**2 #I believe the formula is incorrect, i think it
return distance #means (1/2)gt^2
main()
|
def main():
print("This program shows an object's fall distance (in meters) with each")
print('passing second from 1 to 10.')
print()
print('Time(s)\tDistance(m)')
print('--------------------')
for time in range(10 + 1):
distance = falling_distance(time)
print(time, '\t', format(distance, ',.1f'))
def falling_distance(time):
g = 9.8
distance = 0.5 * g * time ** 2
return distance
main()
|
"""Represent the command parameter strings."""
ARG_COMMAND = 'command'
ARG_ARGUMENT = 'argument'
ARG_COUNT = 'count'
ARG_CHANNEL = 'channel'
ARG_CLIENT = 'client'
ARG_GUID = 'guid'
ARG_CHANGELIST = 'cl'
ARG_DEV_CHANNEL = 'dev_channel'
ARG_QUEUE_WORKER_NUMBER = 'worker_number'
ARG_CALLBACK = 'callback'
ARG_PAYLOAD = 'payload'
ARG_MESSAGE = 'message'
ARG_USER = 'user'
ARG_ERROR = 'error'
ARG_PATH = 'path'
ARG_ISO = 'iso'
ARG_DESCRIPTION = 'description'
ARG_SOURCE = 'source'
ARG_TARGET = 'target'
ARG_RESPONSE = 'response'
ARG_COMMAND_ID = 'command_id'
ARG_MESSAGE_TYPE = 'msg_status'
ARG_MODE = 'mode'
ARG_FOLDER = 'folder'
ARG_VERBOSE = 'verbose'
ARG_FORCE = 'force'
ARG_REBUILD = 'rebuild'
ARG_SHELVE = 'shelve'
ARG_CHECKOUT = 'co'
ARG_LOOP = 'loop'
ARG_SAVE = 'save'
ARG_SIMILARITY = 'sim'
ARG_UPLOAD = 'upload'
ARG_METADATA = 'metadata'
ARG_CONFIG = 'config'
ARG_RESET = 'reset'
ARG_NAME = 'name'
ARG_DOC = 'doc'
ARG_INDEX = 'index'
ARG_CQL = 'cql'
ARG_HEADERS = 'headers'
ARG_FILES = 'files'
ARG_FILE = 'file'
ARG_TXT = 'txt'
ARG_OUTPUT = 'output'
ARG_CDP = 'cdp' # create document placeholder : doc_app
ARG_CTP = 'ctp'
ARG_VERSION = 'version'
ARG_SPACE = 'space'
ARG_PREBUILD = 'prebuild'
ARG_OUT_OF_SERVICE = 'oos' # out of service
ARG_CID = 'cid' # represent the flag checking CID build
ARG_DB_ALIAS = 'db_alias'
ARG_COMMIT = 'commit'
ARG_DUPLICATE = 'dup' # duplicate (flag)
ARG_RENAME = 'rename'
ARG_COPY = 'copy'
ARG_ACTION = 'action'
ARG_COLOR = 'color'
ARG_OPTIMIZE = 'opt'
ARG_SYNC = 'sync'
ARG_DATA = 'data'
ARG_DIR = 'dir'
ARG_PARENT = 'parent'
ARG_POPULATE = 'populate'
ARG_PROJECT = 'project'
ARG_CLASS = 'cls'
ARG_OBJ = 'object'
ARG_CACHE = 'cache'
ARG_RESOURCE = 'resource'
ARG_DEBUG = 'debug'
ARG_QUEUE_WORKER_NUM = 'queue_worker_num'
ARG_SUBPROCESS_NUM = 'subprocess_num'
ARG_CLASSIFICATION = 'classification'
ARG_TEAM = 'team'
ARG_CONSOLE = 'console'
ARG_FILTER = 'filter'
ARG_PUSH = 'push'
ARG_ORIGINAL = 'original'
ARG_ORIGIN = 'origin'
ARG_DIRECTION = 'direction'
ARG_MAIN = 'main'
ARG_TRANSFORM = 'transform'
ARG_AXES = 'axes'
ARG_PATTERN = 'pattern'
ARG_REVERSE = 'reverse'
ARG_MESH = 'mesh'
ARG_OFFSET = 'offset'
ARG_FACTOR = 'factor'
ARG_SCALE = 'scale'
ARG_DENOISING = 'denoising'
ARG_MODEL = 'model'
ARG_DNN_MODELS = 'dnn_models'
ARG_REFORMAT = 'reformat'
ARG_SCENE = 'scene'
ARG_MATERIAL = 'material'
ARG_SIZE = 'size'
ARG_TEXTURE = 'texture'
ARG_TYPE = 'type'
ARG_FACES = 'faces'
ARG_SMOOTH_LEVEL = 'smooth_level'
ARG_MAX_FACES = 'max_faces'
ARG_DOMINANT = 'dominant'
ARG_SHOW = "show"
ARG_PREVIEW = "preview"
ARG_OPACITY = "opacity"
ARG_PADDING = 'padding'
ARG_CROP = 'crop'
ARG_DECIMATE = 'decimate'
ARG_RESAMPLE = 'resample'
ARG_LIMITS = 'limits'
# space names
ARG_SPACE_SAVOIA = 'savoia'
ARG_SPACE_HYPER = 'hyper'
ARG_SPACE_MARS = 'mars'
# values
ARG_FRAMES = 'frames'
ARG_FRAME = 'frame'
# Mars Project
ARG_LOCAL_DRIVE = 'local_drive'
ARG_SEGMENT = 'segment'
ARG_THRESHOLD = 'threshold'
ARG_TAGS = 'tags'
ARG_SPACING = 'spacing'
ARG_MODALITY = 'modality'
ARG_WORLDSPACE_OFFSET = 'worldspace_offset'
ARG_WINDOW_WIDTH = 'ww'
ARG_WINDOW_LEVEL = 'wl'
# server config
ARG_EXECUTABLE_TOOLS = 'executable_tools'
ARG_PYTHON_MODULES = 'python_modules'
# Channel Texture Maps
ARG_AMBIENTOCCLUSION_MAP = 'aomap'
ARG_EMISSION_MAP = 'emmap'
ARG_CHANNEL_MAP = 'chmap'
ARG_CHANNEL_TRANS_MAP = 'tchmap'
ARG_DIFFUSE_MAP = 'dcmap'
def parse_bool(value):
return str(value).lower() in ("yes", "true", "t", "1")
|
"""Represent the command parameter strings."""
arg_command = 'command'
arg_argument = 'argument'
arg_count = 'count'
arg_channel = 'channel'
arg_client = 'client'
arg_guid = 'guid'
arg_changelist = 'cl'
arg_dev_channel = 'dev_channel'
arg_queue_worker_number = 'worker_number'
arg_callback = 'callback'
arg_payload = 'payload'
arg_message = 'message'
arg_user = 'user'
arg_error = 'error'
arg_path = 'path'
arg_iso = 'iso'
arg_description = 'description'
arg_source = 'source'
arg_target = 'target'
arg_response = 'response'
arg_command_id = 'command_id'
arg_message_type = 'msg_status'
arg_mode = 'mode'
arg_folder = 'folder'
arg_verbose = 'verbose'
arg_force = 'force'
arg_rebuild = 'rebuild'
arg_shelve = 'shelve'
arg_checkout = 'co'
arg_loop = 'loop'
arg_save = 'save'
arg_similarity = 'sim'
arg_upload = 'upload'
arg_metadata = 'metadata'
arg_config = 'config'
arg_reset = 'reset'
arg_name = 'name'
arg_doc = 'doc'
arg_index = 'index'
arg_cql = 'cql'
arg_headers = 'headers'
arg_files = 'files'
arg_file = 'file'
arg_txt = 'txt'
arg_output = 'output'
arg_cdp = 'cdp'
arg_ctp = 'ctp'
arg_version = 'version'
arg_space = 'space'
arg_prebuild = 'prebuild'
arg_out_of_service = 'oos'
arg_cid = 'cid'
arg_db_alias = 'db_alias'
arg_commit = 'commit'
arg_duplicate = 'dup'
arg_rename = 'rename'
arg_copy = 'copy'
arg_action = 'action'
arg_color = 'color'
arg_optimize = 'opt'
arg_sync = 'sync'
arg_data = 'data'
arg_dir = 'dir'
arg_parent = 'parent'
arg_populate = 'populate'
arg_project = 'project'
arg_class = 'cls'
arg_obj = 'object'
arg_cache = 'cache'
arg_resource = 'resource'
arg_debug = 'debug'
arg_queue_worker_num = 'queue_worker_num'
arg_subprocess_num = 'subprocess_num'
arg_classification = 'classification'
arg_team = 'team'
arg_console = 'console'
arg_filter = 'filter'
arg_push = 'push'
arg_original = 'original'
arg_origin = 'origin'
arg_direction = 'direction'
arg_main = 'main'
arg_transform = 'transform'
arg_axes = 'axes'
arg_pattern = 'pattern'
arg_reverse = 'reverse'
arg_mesh = 'mesh'
arg_offset = 'offset'
arg_factor = 'factor'
arg_scale = 'scale'
arg_denoising = 'denoising'
arg_model = 'model'
arg_dnn_models = 'dnn_models'
arg_reformat = 'reformat'
arg_scene = 'scene'
arg_material = 'material'
arg_size = 'size'
arg_texture = 'texture'
arg_type = 'type'
arg_faces = 'faces'
arg_smooth_level = 'smooth_level'
arg_max_faces = 'max_faces'
arg_dominant = 'dominant'
arg_show = 'show'
arg_preview = 'preview'
arg_opacity = 'opacity'
arg_padding = 'padding'
arg_crop = 'crop'
arg_decimate = 'decimate'
arg_resample = 'resample'
arg_limits = 'limits'
arg_space_savoia = 'savoia'
arg_space_hyper = 'hyper'
arg_space_mars = 'mars'
arg_frames = 'frames'
arg_frame = 'frame'
arg_local_drive = 'local_drive'
arg_segment = 'segment'
arg_threshold = 'threshold'
arg_tags = 'tags'
arg_spacing = 'spacing'
arg_modality = 'modality'
arg_worldspace_offset = 'worldspace_offset'
arg_window_width = 'ww'
arg_window_level = 'wl'
arg_executable_tools = 'executable_tools'
arg_python_modules = 'python_modules'
arg_ambientocclusion_map = 'aomap'
arg_emission_map = 'emmap'
arg_channel_map = 'chmap'
arg_channel_trans_map = 'tchmap'
arg_diffuse_map = 'dcmap'
def parse_bool(value):
return str(value).lower() in ('yes', 'true', 't', '1')
|
a=list(input().split(','))
st,num=[],[]
for i in a:
s1,n=i.split(':')
st.append(s1)
num.append(n)
print(st)
print(num)
for i in range(len(num)):
for j in range(i):
print(st[j])
|
a = list(input().split(','))
(st, num) = ([], [])
for i in a:
(s1, n) = i.split(':')
st.append(s1)
num.append(n)
print(st)
print(num)
for i in range(len(num)):
for j in range(i):
print(st[j])
|
"""
Discussion:
Because we have a facilitatory synapses, as the input rate increases synaptic
resources released per spike also increase. Therefore, we expect that the synaptic
conductance will increase with input rate. However, total synaptic resources are
finite. And they recover in a finite time. Therefore, at high frequency inputs
synaptic resources are rapidly deleted at a higher rate than their recovery, so
after first few spikes, only a small number of synaptic resources are left. This
results in decrease in the steady-state synaptic conductance at high frequency inputs.
""";
|
"""
Discussion:
Because we have a facilitatory synapses, as the input rate increases synaptic
resources released per spike also increase. Therefore, we expect that the synaptic
conductance will increase with input rate. However, total synaptic resources are
finite. And they recover in a finite time. Therefore, at high frequency inputs
synaptic resources are rapidly deleted at a higher rate than their recovery, so
after first few spikes, only a small number of synaptic resources are left. This
results in decrease in the steady-state synaptic conductance at high frequency inputs.
"""
|
GitHubTarballPackage ('mono', 'mono-basic', '3.0', 'a74642af7f72d1012c87d82d7a12ac04a17858d5',
configure = './configure --prefix="%{prefix}"',
override_properties = { 'make': 'make' }
)
|
git_hub_tarball_package('mono', 'mono-basic', '3.0', 'a74642af7f72d1012c87d82d7a12ac04a17858d5', configure='./configure --prefix="%{prefix}"', override_properties={'make': 'make'})
|
# Asking for height and weight input
height = float(input("What is your height in meters: "))
weight = float(input("What is your weight in kilograms: "))
# Calculating BMI (formula is weight/height^2)
bmi = str(round(weight/(height ** 2), 2))
# Printing BMI
print("Your BMI is " + bmi)
|
height = float(input('What is your height in meters: '))
weight = float(input('What is your weight in kilograms: '))
bmi = str(round(weight / height ** 2, 2))
print('Your BMI is ' + bmi)
|
# IMAGES #
# UI NAVIGATION #
img_addFriend = "add_friend.png"
img_allow = "allow.png"
img_allowFlash = "enableflash_0.png"
img_allowFlash1 = "enableflash_1.png"
img_allowFlash2 = "enableflash_2.png"
img_alreadyStarted = "alreadystarted.png"
img_alreadyStarted1 = "alreadystarted1.png"
img_backButton = "back_button.png"
img_beginningGame = "beginninggame.png"
img_challengeFriend = "challenge_friend.png"
img_cheapButtonFriend = "cheap_button_friend.png"
img_cheapButton = "cheap_button.png"
img_cueUpdate = "cueUpdate.png"
img_cues = "cues.png"
img_collectCoins = "collectcoins.png"
img_collectCoins1 = "collectcoins_1.png"
img_defaultAcct = "defaultaccount.png"
img_eightBallSpinButton = "8ballspin_button.png"
img_emailArea = "email_area.png"
img_facebookLogo = "facebooklogo.png"
img_inviteFriend = "invite_friend.png"
img_isGameStart = "isgamestart.png"
img_loginButton3 = "login3_button.png"
img_loginWithMiniclip = "login_with_miniclip.png"
img_luckyShot = "luckyShot.png"
img_mainMenuBefore = "mainmenu_before.png"
img_passwordArea = "password_area.png"
img_playButtonGuest = "play_button_guest.png"
img_playButtonLogged = "play_button_logged.png"
img_playFree = "playFree.png"
img_playFriends = "playfriends.png"
img_playNow = "playnow.png"
img_poolChoice = "poolchoice.png"
img_poolChoice1 = "poolchoice1.png"
img_poolChoice200 = "poolchoice200.png"
img_poolChoice200_1 = "poolchoice200_1.png"
img_searchFriends = "search_friends.png"
img_searchFriends1 = "search_friends2.png"
img_searchFriends2 = "search_friends3.png"
img_signUpLogin = "signup_login_button.png"
img_spinWinCollect = "spinwin_collect.png"
img_spinWinIcon = "spinwinicon.png"
img_spinWinX = "spinwin_x.png"
img_topRightCorner = "top_right_corner.png"
img_topRightCornerLogged = "top_right_corner_logged.png"
img_turn = "turn.png"
img_turn1 = "turn1.png"
img_opponentTurn = "playertwoturn.png"
img_opponentTurn1 = "playertwoturn1.png"
img_url = "url.png"
img_url2 = "url2.png"
img_url3 = "url3.png"
img_urlBar = "urlbar.png"
img_unsecure = "unsecure.png"
img_xOut = "xout.png"
# UI NAVIGATION #
# GAME NAVIGATION #
img_1ball = "1ball.png"
img_2ball = "2ball.png"
img_3ball = "3ball.png"
img_4ball = "4ball.png"
img_5ball = "5ball.png"
img_6ball = "6ball.png"
img_7ball = "7ball.png"
img_8ball = "8ball.png"
img_9ball = "9ball.png"
img_10ball = "10ball.png"
img_11ball = "11ball.png"
img_12ball = "12ball.png"
img_13ball = "13ball.png"
img_14ball = "14ball.png"
img_15ball = "15ball.png"
img_1ballDark = "1ballDark.png"
img_2ballDark = "2ballDark.png"
img_3ballDark = "3ballDark.png"
img_4ballDark = "4ballDark.png"
img_5ballDark = "5ballDark.png"
img_6ballDark = "6ballDark.png"
img_7ballDark = "7ballDark.png"
img_8ballDark = "8ballDark.png"
img_9ballDark = "9ballDark.png"
img_10ballDark = "10ballDark.png"
img_11ballDark = "11ballDark.png"
img_12ballDark = "12ballDark.png"
img_13ballDark = "13ballDark.png"
img_14ballDark = "14ballDark.png"
img_15ballDark = "15ballDark.png"
img_cueball = "cueball.png"
img_eightball = "eightball.png"
img_ballPic1 = "ballpic1.png"
img_tlh = "tlh.png"
img_tmh = "tmh.png"
img_trh = "trh.png"
img_blh = "blh.png"
img_bmh = "bmh.png"
img_brh = "brh.png"
img_topRail = "toprail.png"
img_bottomRail = "bottomrail.png"
img_leftRail = "leftrail.png"
img_rightRail = "rightrail.png"
# GAME NAVIGATION #
# IMAGES #
debug = False
|
img_add_friend = 'add_friend.png'
img_allow = 'allow.png'
img_allow_flash = 'enableflash_0.png'
img_allow_flash1 = 'enableflash_1.png'
img_allow_flash2 = 'enableflash_2.png'
img_already_started = 'alreadystarted.png'
img_already_started1 = 'alreadystarted1.png'
img_back_button = 'back_button.png'
img_beginning_game = 'beginninggame.png'
img_challenge_friend = 'challenge_friend.png'
img_cheap_button_friend = 'cheap_button_friend.png'
img_cheap_button = 'cheap_button.png'
img_cue_update = 'cueUpdate.png'
img_cues = 'cues.png'
img_collect_coins = 'collectcoins.png'
img_collect_coins1 = 'collectcoins_1.png'
img_default_acct = 'defaultaccount.png'
img_eight_ball_spin_button = '8ballspin_button.png'
img_email_area = 'email_area.png'
img_facebook_logo = 'facebooklogo.png'
img_invite_friend = 'invite_friend.png'
img_is_game_start = 'isgamestart.png'
img_login_button3 = 'login3_button.png'
img_login_with_miniclip = 'login_with_miniclip.png'
img_lucky_shot = 'luckyShot.png'
img_main_menu_before = 'mainmenu_before.png'
img_password_area = 'password_area.png'
img_play_button_guest = 'play_button_guest.png'
img_play_button_logged = 'play_button_logged.png'
img_play_free = 'playFree.png'
img_play_friends = 'playfriends.png'
img_play_now = 'playnow.png'
img_pool_choice = 'poolchoice.png'
img_pool_choice1 = 'poolchoice1.png'
img_pool_choice200 = 'poolchoice200.png'
img_pool_choice200_1 = 'poolchoice200_1.png'
img_search_friends = 'search_friends.png'
img_search_friends1 = 'search_friends2.png'
img_search_friends2 = 'search_friends3.png'
img_sign_up_login = 'signup_login_button.png'
img_spin_win_collect = 'spinwin_collect.png'
img_spin_win_icon = 'spinwinicon.png'
img_spin_win_x = 'spinwin_x.png'
img_top_right_corner = 'top_right_corner.png'
img_top_right_corner_logged = 'top_right_corner_logged.png'
img_turn = 'turn.png'
img_turn1 = 'turn1.png'
img_opponent_turn = 'playertwoturn.png'
img_opponent_turn1 = 'playertwoturn1.png'
img_url = 'url.png'
img_url2 = 'url2.png'
img_url3 = 'url3.png'
img_url_bar = 'urlbar.png'
img_unsecure = 'unsecure.png'
img_x_out = 'xout.png'
img_1ball = '1ball.png'
img_2ball = '2ball.png'
img_3ball = '3ball.png'
img_4ball = '4ball.png'
img_5ball = '5ball.png'
img_6ball = '6ball.png'
img_7ball = '7ball.png'
img_8ball = '8ball.png'
img_9ball = '9ball.png'
img_10ball = '10ball.png'
img_11ball = '11ball.png'
img_12ball = '12ball.png'
img_13ball = '13ball.png'
img_14ball = '14ball.png'
img_15ball = '15ball.png'
img_1ball_dark = '1ballDark.png'
img_2ball_dark = '2ballDark.png'
img_3ball_dark = '3ballDark.png'
img_4ball_dark = '4ballDark.png'
img_5ball_dark = '5ballDark.png'
img_6ball_dark = '6ballDark.png'
img_7ball_dark = '7ballDark.png'
img_8ball_dark = '8ballDark.png'
img_9ball_dark = '9ballDark.png'
img_10ball_dark = '10ballDark.png'
img_11ball_dark = '11ballDark.png'
img_12ball_dark = '12ballDark.png'
img_13ball_dark = '13ballDark.png'
img_14ball_dark = '14ballDark.png'
img_15ball_dark = '15ballDark.png'
img_cueball = 'cueball.png'
img_eightball = 'eightball.png'
img_ball_pic1 = 'ballpic1.png'
img_tlh = 'tlh.png'
img_tmh = 'tmh.png'
img_trh = 'trh.png'
img_blh = 'blh.png'
img_bmh = 'bmh.png'
img_brh = 'brh.png'
img_top_rail = 'toprail.png'
img_bottom_rail = 'bottomrail.png'
img_left_rail = 'leftrail.png'
img_right_rail = 'rightrail.png'
debug = False
|
class EfficiencyMeasurement():
# input_voltage = None
# input_current = None
# output_voltage = None
# output_current = None
# input_power = None
# output_power = None
# loss_power = None
# efficiency = None
def __init__(self, input_voltage: float, input_current: float,
output_voltage: float, output_current: float):
self.input_voltage = input_voltage
self.input_current = input_current
self.output_voltage = output_voltage
self.output_current = output_current
self.input_power = calc_power(voltage = input_voltage, current = input_current)
self.output_power = calc_power(voltage = output_voltage, current = output_current)
self.loss_power = calc_loss_power(input_power=self.input_power, ouput_power=self.output_power)
class TsetPoint():
setup = None
measurement = None #EfficiencyMeasurement()
class TestSet_Efficiency():
def __init__(self, s: dict):
self.source_bias = s['source_bias']
self.dut = s['powertrain']
self.load = s['load']
|
class Efficiencymeasurement:
def __init__(self, input_voltage: float, input_current: float, output_voltage: float, output_current: float):
self.input_voltage = input_voltage
self.input_current = input_current
self.output_voltage = output_voltage
self.output_current = output_current
self.input_power = calc_power(voltage=input_voltage, current=input_current)
self.output_power = calc_power(voltage=output_voltage, current=output_current)
self.loss_power = calc_loss_power(input_power=self.input_power, ouput_power=self.output_power)
class Tsetpoint:
setup = None
measurement = None
class Testset_Efficiency:
def __init__(self, s: dict):
self.source_bias = s['source_bias']
self.dut = s['powertrain']
self.load = s['load']
|
class Y:
def __init__(self, v0):
self.v0 = v0
self.g = 9.81
def value(self, t):
return self.v0*t - 0.5*self.g*t**2
def formula(self):
return "v0*t - 0.5*g*t**2; v0=%g" % self.v0
|
class Y:
def __init__(self, v0):
self.v0 = v0
self.g = 9.81
def value(self, t):
return self.v0 * t - 0.5 * self.g * t ** 2
def formula(self):
return 'v0*t - 0.5*g*t**2; v0=%g' % self.v0
|
"""
* Problem Description
*Suppose you are a university student and you need to pay 1536 dollars as a tuition fee.
*The college is offering a 10% discount on the early payment. How much money do you have to pay if you make an early payment?
*Task
*Create a variable named fee and assign 1536 to it.
*Create another variable discount_percent and assign 10 to it.
*Compute discount and assign it to the discount variable.
*Compute and print the fee you have to pay by subtracting discount from fee.
"""
fee = 1536
discount_percent = 10
discount = fee - (fee * 0.1)
fee = discount
print(fee) # Output: 1382.4
|
"""
* Problem Description
*Suppose you are a university student and you need to pay 1536 dollars as a tuition fee.
*The college is offering a 10% discount on the early payment. How much money do you have to pay if you make an early payment?
*Task
*Create a variable named fee and assign 1536 to it.
*Create another variable discount_percent and assign 10 to it.
*Compute discount and assign it to the discount variable.
*Compute and print the fee you have to pay by subtracting discount from fee.
"""
fee = 1536
discount_percent = 10
discount = fee - fee * 0.1
fee = discount
print(fee)
|
"""
PASSENGERS
"""
numPassengers = 19216
passenger_arriving = (
(7, 4, 4, 3, 2, 1, 4, 2, 4, 2, 0, 0, 0, 7, 5, 8, 3, 7, 1, 3, 0, 1, 2, 1, 1, 0), # 0
(4, 7, 2, 3, 3, 1, 2, 5, 2, 1, 1, 0, 0, 6, 4, 4, 3, 2, 1, 5, 1, 1, 1, 0, 1, 0), # 1
(6, 4, 5, 6, 2, 1, 2, 4, 1, 1, 0, 0, 0, 11, 3, 6, 7, 7, 0, 3, 2, 1, 2, 0, 0, 0), # 2
(6, 3, 6, 7, 6, 1, 3, 3, 1, 2, 1, 0, 0, 7, 11, 8, 2, 4, 3, 0, 0, 2, 2, 0, 0, 0), # 3
(11, 5, 8, 3, 6, 1, 2, 2, 2, 0, 0, 0, 0, 6, 9, 5, 1, 5, 1, 2, 1, 1, 1, 0, 0, 0), # 4
(3, 5, 7, 7, 5, 2, 5, 3, 3, 2, 3, 0, 0, 9, 10, 3, 2, 7, 2, 1, 0, 3, 1, 1, 2, 0), # 5
(6, 4, 5, 5, 6, 2, 1, 3, 4, 1, 0, 2, 0, 7, 6, 2, 4, 4, 1, 3, 1, 3, 5, 0, 2, 0), # 6
(5, 8, 6, 4, 6, 0, 6, 4, 2, 1, 2, 0, 0, 9, 6, 2, 5, 3, 0, 1, 1, 3, 2, 2, 0, 0), # 7
(6, 3, 2, 11, 4, 2, 7, 4, 2, 1, 1, 0, 0, 4, 4, 4, 1, 4, 5, 1, 2, 2, 2, 4, 0, 0), # 8
(7, 5, 8, 5, 10, 0, 7, 2, 4, 2, 1, 1, 0, 8, 3, 4, 3, 8, 4, 1, 4, 4, 3, 2, 1, 0), # 9
(3, 4, 12, 6, 6, 4, 4, 0, 2, 1, 0, 0, 0, 15, 3, 9, 3, 0, 4, 2, 2, 4, 3, 2, 1, 0), # 10
(9, 11, 8, 8, 4, 3, 2, 0, 3, 2, 0, 1, 0, 6, 12, 7, 4, 7, 2, 5, 4, 3, 3, 2, 1, 0), # 11
(8, 3, 6, 9, 10, 2, 9, 2, 4, 1, 1, 1, 0, 6, 5, 7, 1, 5, 4, 3, 2, 4, 1, 0, 2, 0), # 12
(5, 11, 12, 7, 6, 3, 5, 4, 3, 2, 1, 3, 0, 16, 6, 8, 8, 8, 1, 2, 4, 2, 2, 2, 1, 0), # 13
(17, 12, 8, 14, 4, 2, 2, 5, 4, 0, 2, 1, 0, 11, 4, 9, 6, 10, 1, 2, 2, 4, 1, 1, 0, 0), # 14
(12, 11, 13, 8, 13, 2, 5, 3, 4, 0, 0, 0, 0, 16, 7, 2, 8, 6, 4, 4, 4, 3, 2, 1, 1, 0), # 15
(7, 5, 4, 7, 9, 1, 5, 4, 4, 4, 1, 1, 0, 11, 10, 4, 7, 8, 7, 5, 1, 3, 4, 0, 0, 0), # 16
(11, 7, 5, 6, 6, 6, 4, 1, 6, 0, 1, 1, 0, 9, 9, 6, 6, 7, 5, 2, 1, 1, 3, 0, 0, 0), # 17
(9, 12, 9, 3, 7, 4, 3, 2, 3, 2, 1, 2, 0, 12, 9, 6, 3, 7, 8, 4, 4, 5, 2, 2, 2, 0), # 18
(11, 15, 6, 8, 7, 6, 5, 6, 2, 1, 0, 1, 0, 11, 11, 3, 4, 9, 4, 6, 4, 4, 2, 3, 1, 0), # 19
(7, 11, 6, 10, 5, 4, 3, 2, 3, 2, 1, 0, 0, 7, 8, 8, 1, 11, 8, 6, 3, 4, 4, 3, 0, 0), # 20
(10, 9, 10, 11, 7, 3, 4, 3, 3, 1, 3, 2, 0, 10, 17, 12, 11, 6, 3, 2, 2, 5, 4, 2, 1, 0), # 21
(14, 8, 8, 11, 4, 6, 3, 3, 4, 1, 1, 0, 0, 11, 5, 6, 6, 15, 3, 1, 4, 5, 2, 1, 0, 0), # 22
(12, 17, 8, 14, 10, 2, 4, 2, 4, 3, 0, 1, 0, 11, 12, 7, 5, 9, 5, 2, 2, 1, 5, 2, 3, 0), # 23
(7, 12, 17, 16, 5, 3, 6, 4, 6, 1, 2, 0, 0, 13, 4, 5, 4, 14, 2, 3, 6, 5, 1, 1, 0, 0), # 24
(10, 11, 9, 7, 4, 6, 2, 1, 5, 3, 0, 3, 0, 5, 9, 8, 6, 8, 3, 4, 4, 3, 1, 4, 1, 0), # 25
(11, 7, 8, 8, 9, 5, 2, 5, 7, 3, 1, 1, 0, 10, 5, 11, 3, 11, 3, 7, 2, 3, 3, 3, 2, 0), # 26
(11, 8, 6, 7, 6, 5, 8, 0, 7, 0, 0, 0, 0, 11, 15, 8, 3, 9, 8, 5, 1, 4, 1, 1, 2, 0), # 27
(6, 15, 10, 15, 9, 2, 4, 5, 4, 4, 0, 0, 0, 16, 9, 7, 6, 7, 1, 6, 0, 7, 3, 0, 4, 0), # 28
(15, 3, 13, 9, 9, 6, 3, 3, 3, 1, 1, 0, 0, 6, 6, 8, 7, 13, 6, 5, 5, 5, 4, 0, 1, 0), # 29
(17, 12, 13, 7, 8, 3, 4, 3, 3, 1, 2, 1, 0, 14, 13, 3, 7, 11, 6, 6, 3, 6, 1, 2, 2, 0), # 30
(17, 10, 3, 9, 4, 3, 5, 2, 5, 3, 1, 1, 0, 12, 10, 4, 7, 12, 7, 5, 1, 3, 4, 1, 2, 0), # 31
(8, 10, 7, 8, 12, 1, 5, 4, 3, 0, 0, 3, 0, 8, 18, 7, 1, 13, 7, 6, 1, 3, 1, 1, 1, 0), # 32
(7, 5, 10, 8, 7, 4, 4, 8, 8, 5, 1, 0, 0, 8, 8, 5, 2, 4, 3, 6, 2, 4, 1, 3, 1, 0), # 33
(5, 10, 12, 11, 9, 7, 4, 4, 2, 1, 0, 1, 0, 9, 11, 6, 6, 11, 6, 5, 0, 1, 2, 2, 2, 0), # 34
(13, 11, 5, 8, 7, 4, 4, 4, 7, 2, 1, 0, 0, 13, 10, 5, 5, 11, 7, 3, 0, 1, 3, 0, 0, 0), # 35
(10, 12, 5, 7, 5, 5, 2, 6, 4, 2, 1, 3, 0, 10, 12, 15, 7, 11, 5, 6, 2, 2, 2, 0, 0, 0), # 36
(11, 11, 13, 9, 9, 4, 1, 1, 4, 2, 1, 1, 0, 13, 12, 6, 3, 7, 6, 5, 1, 4, 2, 2, 0, 0), # 37
(4, 7, 9, 5, 6, 3, 6, 1, 3, 2, 1, 1, 0, 13, 7, 4, 5, 14, 1, 4, 2, 1, 1, 1, 0, 0), # 38
(12, 8, 9, 11, 11, 4, 6, 8, 5, 5, 2, 1, 0, 6, 10, 6, 4, 11, 8, 6, 0, 8, 4, 4, 2, 0), # 39
(12, 14, 10, 9, 6, 2, 5, 0, 4, 2, 0, 2, 0, 10, 8, 5, 4, 7, 6, 3, 1, 3, 6, 1, 2, 0), # 40
(10, 13, 11, 10, 9, 5, 1, 5, 6, 4, 1, 0, 0, 11, 5, 7, 6, 8, 4, 4, 1, 4, 1, 1, 1, 0), # 41
(12, 9, 17, 9, 6, 6, 1, 3, 3, 3, 2, 0, 0, 13, 4, 7, 4, 4, 6, 3, 4, 2, 1, 2, 2, 0), # 42
(3, 14, 13, 6, 11, 5, 4, 3, 3, 2, 0, 3, 0, 13, 6, 8, 4, 6, 7, 9, 3, 2, 2, 3, 0, 0), # 43
(10, 12, 12, 8, 10, 3, 3, 10, 4, 2, 1, 1, 0, 8, 12, 10, 5, 9, 5, 6, 2, 5, 4, 2, 1, 0), # 44
(11, 11, 16, 8, 8, 2, 11, 5, 6, 1, 2, 2, 0, 10, 12, 7, 10, 8, 1, 6, 4, 4, 2, 2, 1, 0), # 45
(9, 10, 12, 14, 12, 5, 3, 2, 2, 1, 4, 0, 0, 12, 9, 8, 6, 13, 6, 3, 1, 4, 3, 3, 0, 0), # 46
(7, 8, 8, 4, 5, 2, 2, 2, 4, 4, 2, 0, 0, 17, 10, 9, 7, 9, 6, 3, 5, 4, 7, 5, 0, 0), # 47
(12, 8, 6, 14, 6, 1, 4, 2, 3, 0, 2, 0, 0, 19, 9, 7, 3, 7, 3, 4, 3, 3, 4, 1, 0, 0), # 48
(11, 8, 7, 8, 12, 5, 3, 2, 9, 1, 2, 0, 0, 14, 11, 8, 2, 4, 7, 3, 3, 7, 2, 1, 0, 0), # 49
(10, 10, 4, 7, 5, 3, 2, 1, 4, 2, 1, 0, 0, 14, 11, 3, 8, 5, 3, 7, 5, 3, 1, 1, 1, 0), # 50
(14, 11, 8, 14, 10, 3, 1, 2, 6, 1, 2, 0, 0, 12, 6, 2, 4, 7, 1, 5, 3, 5, 3, 1, 2, 0), # 51
(5, 16, 8, 10, 9, 6, 5, 7, 1, 3, 1, 2, 0, 14, 12, 4, 6, 8, 3, 3, 3, 5, 8, 2, 0, 0), # 52
(6, 9, 4, 13, 8, 2, 6, 4, 2, 1, 3, 2, 0, 13, 6, 6, 5, 15, 6, 4, 2, 5, 4, 0, 3, 0), # 53
(15, 15, 15, 12, 12, 2, 0, 3, 6, 0, 4, 1, 0, 10, 12, 8, 6, 5, 5, 4, 2, 6, 2, 2, 0, 0), # 54
(11, 8, 8, 6, 9, 4, 4, 1, 2, 4, 1, 1, 0, 3, 14, 5, 3, 7, 4, 4, 1, 1, 3, 3, 1, 0), # 55
(5, 10, 5, 12, 10, 3, 5, 5, 2, 1, 0, 0, 0, 10, 7, 11, 6, 8, 2, 6, 3, 1, 4, 6, 0, 0), # 56
(9, 11, 10, 13, 7, 4, 4, 2, 6, 3, 0, 1, 0, 11, 7, 9, 5, 7, 1, 6, 3, 1, 8, 1, 0, 0), # 57
(13, 12, 11, 6, 9, 1, 1, 5, 3, 4, 4, 0, 0, 14, 10, 9, 10, 10, 2, 6, 3, 3, 3, 1, 1, 0), # 58
(11, 11, 15, 9, 9, 5, 1, 3, 7, 3, 0, 2, 0, 11, 5, 7, 3, 6, 4, 3, 3, 2, 1, 1, 2, 0), # 59
(7, 12, 10, 11, 11, 4, 2, 5, 5, 0, 2, 0, 0, 5, 13, 13, 3, 11, 7, 6, 3, 2, 3, 2, 0, 0), # 60
(11, 5, 10, 12, 8, 1, 2, 0, 2, 1, 1, 0, 0, 4, 7, 4, 5, 13, 5, 3, 7, 3, 4, 2, 2, 0), # 61
(6, 4, 5, 10, 13, 1, 6, 3, 7, 1, 2, 2, 0, 9, 10, 3, 3, 8, 3, 6, 4, 8, 0, 0, 0, 0), # 62
(11, 11, 9, 5, 8, 3, 4, 2, 8, 4, 0, 1, 0, 12, 12, 11, 5, 8, 1, 5, 6, 7, 4, 1, 0, 0), # 63
(8, 11, 12, 7, 16, 3, 6, 4, 3, 1, 1, 2, 0, 14, 4, 6, 6, 7, 3, 4, 3, 2, 4, 1, 1, 0), # 64
(7, 11, 10, 10, 6, 5, 8, 1, 3, 2, 1, 2, 0, 12, 7, 8, 3, 11, 6, 4, 1, 5, 2, 1, 0, 0), # 65
(15, 6, 5, 11, 10, 2, 4, 7, 2, 1, 2, 1, 0, 14, 11, 7, 4, 9, 6, 4, 2, 2, 5, 4, 0, 0), # 66
(4, 7, 4, 10, 5, 4, 0, 4, 4, 3, 2, 0, 0, 14, 5, 11, 4, 6, 4, 5, 4, 3, 3, 2, 2, 0), # 67
(12, 10, 5, 8, 4, 1, 1, 5, 9, 2, 1, 1, 0, 13, 12, 4, 7, 8, 4, 4, 2, 3, 3, 2, 1, 0), # 68
(8, 9, 11, 8, 10, 4, 3, 5, 3, 1, 3, 1, 0, 11, 8, 8, 7, 8, 3, 1, 1, 1, 3, 3, 0, 0), # 69
(9, 6, 3, 11, 9, 3, 5, 2, 2, 3, 4, 1, 0, 11, 5, 7, 5, 9, 5, 4, 4, 5, 2, 0, 0, 0), # 70
(4, 7, 5, 5, 6, 5, 1, 3, 0, 4, 1, 0, 0, 9, 9, 9, 3, 10, 5, 5, 2, 5, 1, 3, 1, 0), # 71
(11, 6, 8, 11, 12, 3, 5, 1, 6, 4, 1, 2, 0, 16, 9, 4, 7, 8, 4, 9, 2, 5, 1, 2, 2, 0), # 72
(10, 10, 10, 5, 11, 5, 3, 3, 4, 0, 2, 1, 0, 15, 3, 8, 6, 8, 2, 6, 1, 4, 1, 0, 2, 0), # 73
(14, 8, 9, 8, 7, 6, 1, 1, 2, 1, 2, 0, 0, 13, 4, 4, 7, 5, 3, 9, 8, 5, 4, 1, 0, 0), # 74
(10, 11, 11, 9, 10, 1, 3, 2, 5, 1, 1, 0, 0, 14, 13, 7, 4, 8, 4, 4, 2, 7, 2, 3, 0, 0), # 75
(13, 10, 10, 12, 7, 6, 3, 3, 4, 3, 0, 1, 0, 12, 12, 9, 8, 4, 3, 3, 6, 2, 3, 2, 1, 0), # 76
(9, 7, 10, 7, 10, 5, 2, 4, 5, 2, 0, 2, 0, 11, 5, 6, 8, 12, 5, 6, 1, 3, 4, 1, 1, 0), # 77
(5, 7, 8, 5, 12, 2, 5, 1, 4, 1, 0, 1, 0, 8, 13, 6, 3, 6, 2, 4, 3, 3, 10, 3, 0, 0), # 78
(13, 11, 10, 3, 9, 4, 5, 3, 3, 0, 0, 0, 0, 10, 12, 8, 7, 5, 1, 4, 7, 5, 4, 0, 3, 0), # 79
(9, 9, 11, 11, 8, 1, 2, 1, 4, 4, 2, 1, 0, 10, 7, 2, 7, 8, 4, 3, 1, 3, 2, 2, 0, 0), # 80
(13, 4, 5, 11, 3, 3, 6, 4, 5, 0, 3, 0, 0, 8, 10, 3, 9, 4, 7, 3, 3, 4, 5, 0, 1, 0), # 81
(13, 9, 8, 4, 5, 3, 5, 3, 4, 1, 2, 1, 0, 12, 5, 7, 2, 7, 5, 0, 0, 2, 0, 2, 1, 0), # 82
(7, 9, 4, 5, 5, 2, 1, 2, 3, 1, 1, 0, 0, 10, 7, 5, 2, 9, 3, 1, 2, 3, 5, 1, 1, 0), # 83
(12, 6, 9, 7, 7, 6, 4, 2, 4, 1, 1, 0, 0, 10, 8, 3, 3, 6, 5, 4, 3, 1, 4, 2, 0, 0), # 84
(10, 10, 3, 7, 10, 4, 5, 3, 1, 1, 1, 2, 0, 9, 13, 3, 5, 5, 5, 3, 4, 5, 3, 1, 0, 0), # 85
(7, 10, 13, 11, 8, 3, 2, 2, 1, 3, 1, 0, 0, 5, 11, 7, 2, 6, 4, 5, 1, 3, 3, 1, 1, 0), # 86
(13, 10, 13, 12, 15, 4, 8, 2, 6, 0, 0, 1, 0, 9, 7, 6, 2, 9, 7, 8, 1, 6, 6, 2, 1, 0), # 87
(6, 10, 7, 12, 4, 4, 2, 2, 3, 4, 3, 1, 0, 11, 7, 9, 0, 2, 7, 4, 2, 4, 3, 0, 1, 0), # 88
(14, 10, 7, 11, 7, 2, 1, 1, 2, 1, 2, 1, 0, 6, 8, 5, 3, 9, 4, 5, 0, 4, 1, 3, 2, 0), # 89
(10, 6, 6, 13, 7, 2, 3, 2, 5, 1, 2, 1, 0, 11, 12, 7, 6, 9, 4, 5, 2, 1, 4, 0, 0, 0), # 90
(14, 8, 8, 7, 5, 3, 6, 1, 4, 3, 1, 0, 0, 12, 5, 4, 4, 9, 1, 5, 4, 0, 5, 3, 0, 0), # 91
(14, 7, 7, 7, 10, 6, 5, 1, 2, 1, 4, 0, 0, 10, 6, 5, 5, 11, 5, 2, 0, 5, 4, 0, 0, 0), # 92
(13, 10, 12, 7, 8, 3, 3, 3, 5, 1, 0, 1, 0, 14, 9, 8, 2, 12, 5, 3, 2, 3, 3, 5, 0, 0), # 93
(4, 4, 9, 7, 9, 3, 1, 3, 1, 1, 2, 0, 0, 12, 9, 3, 5, 10, 4, 3, 3, 2, 2, 2, 0, 0), # 94
(5, 9, 12, 10, 15, 4, 4, 6, 2, 2, 2, 0, 0, 13, 11, 0, 7, 7, 3, 1, 5, 3, 2, 0, 1, 0), # 95
(2, 6, 13, 9, 5, 2, 4, 5, 2, 0, 3, 0, 0, 12, 8, 3, 6, 7, 2, 3, 4, 3, 5, 3, 0, 0), # 96
(8, 6, 5, 6, 8, 4, 1, 2, 2, 0, 1, 1, 0, 9, 7, 4, 4, 7, 1, 4, 1, 2, 3, 1, 0, 0), # 97
(12, 12, 8, 7, 5, 2, 4, 5, 8, 0, 2, 1, 0, 10, 9, 5, 5, 9, 0, 4, 2, 6, 3, 1, 1, 0), # 98
(8, 9, 10, 6, 13, 7, 5, 4, 5, 2, 1, 3, 0, 12, 7, 7, 6, 6, 2, 3, 2, 8, 3, 4, 0, 0), # 99
(10, 12, 11, 4, 12, 3, 3, 4, 3, 2, 1, 0, 0, 8, 8, 4, 3, 5, 7, 2, 5, 5, 1, 1, 0, 0), # 100
(9, 8, 6, 4, 6, 1, 4, 3, 3, 3, 1, 1, 0, 11, 9, 4, 10, 11, 2, 1, 2, 3, 4, 2, 0, 0), # 101
(11, 8, 10, 10, 4, 5, 3, 0, 5, 2, 0, 0, 0, 13, 8, 3, 7, 10, 3, 1, 2, 6, 3, 2, 1, 0), # 102
(6, 9, 9, 7, 5, 5, 2, 2, 5, 0, 2, 2, 0, 14, 11, 5, 3, 8, 0, 2, 3, 5, 1, 0, 2, 0), # 103
(12, 8, 7, 5, 8, 4, 2, 2, 3, 3, 0, 0, 0, 9, 6, 5, 3, 7, 4, 0, 3, 3, 3, 2, 1, 0), # 104
(9, 6, 8, 14, 6, 4, 2, 2, 1, 1, 0, 1, 0, 6, 3, 6, 2, 5, 4, 6, 2, 1, 4, 2, 3, 0), # 105
(8, 13, 9, 7, 12, 6, 5, 4, 5, 1, 3, 0, 0, 13, 9, 7, 5, 6, 3, 1, 3, 3, 1, 1, 0, 0), # 106
(8, 8, 13, 8, 11, 0, 1, 4, 6, 1, 0, 0, 0, 9, 10, 4, 6, 5, 2, 3, 1, 1, 1, 0, 0, 0), # 107
(10, 8, 10, 13, 9, 5, 4, 1, 5, 1, 1, 0, 0, 9, 8, 4, 7, 10, 4, 0, 2, 3, 4, 0, 1, 0), # 108
(7, 8, 5, 7, 11, 7, 5, 4, 7, 1, 0, 1, 0, 14, 8, 8, 6, 10, 3, 1, 1, 3, 4, 1, 1, 0), # 109
(14, 8, 8, 7, 8, 2, 4, 1, 4, 2, 0, 0, 0, 10, 7, 2, 2, 4, 6, 2, 2, 2, 2, 3, 0, 0), # 110
(7, 13, 11, 4, 10, 2, 0, 0, 2, 1, 0, 0, 0, 13, 5, 6, 3, 3, 0, 4, 1, 0, 4, 2, 1, 0), # 111
(13, 5, 11, 8, 5, 4, 1, 2, 2, 2, 2, 0, 0, 7, 6, 10, 5, 7, 2, 3, 2, 2, 2, 0, 1, 0), # 112
(11, 8, 6, 6, 4, 6, 3, 2, 6, 0, 1, 1, 0, 2, 13, 5, 1, 13, 4, 5, 2, 2, 1, 1, 1, 0), # 113
(9, 9, 9, 8, 8, 6, 2, 3, 4, 2, 1, 2, 0, 7, 4, 9, 8, 7, 2, 2, 1, 3, 0, 3, 0, 0), # 114
(12, 10, 9, 8, 9, 4, 0, 0, 4, 0, 0, 0, 0, 6, 8, 1, 3, 7, 4, 1, 2, 3, 2, 2, 1, 0), # 115
(8, 10, 7, 10, 5, 7, 0, 3, 1, 1, 2, 1, 0, 14, 7, 2, 5, 3, 4, 6, 1, 3, 3, 1, 1, 0), # 116
(8, 13, 5, 10, 9, 0, 3, 0, 5, 1, 0, 1, 0, 10, 5, 6, 3, 5, 1, 0, 1, 4, 3, 2, 0, 0), # 117
(9, 6, 6, 13, 15, 3, 0, 7, 3, 1, 2, 0, 0, 7, 10, 5, 5, 6, 0, 2, 0, 2, 2, 1, 2, 0), # 118
(12, 8, 9, 9, 9, 5, 3, 3, 2, 1, 0, 3, 0, 10, 6, 3, 1, 8, 1, 4, 6, 2, 0, 1, 0, 0), # 119
(8, 7, 9, 7, 11, 3, 6, 1, 6, 2, 0, 1, 0, 6, 4, 4, 8, 3, 1, 3, 1, 1, 2, 0, 1, 0), # 120
(8, 6, 11, 6, 10, 6, 4, 1, 4, 3, 0, 2, 0, 5, 9, 6, 7, 8, 2, 3, 3, 5, 4, 0, 1, 0), # 121
(10, 4, 8, 11, 8, 5, 6, 7, 2, 0, 1, 0, 0, 5, 7, 7, 3, 8, 5, 3, 5, 2, 3, 1, 0, 0), # 122
(4, 11, 8, 2, 10, 2, 2, 2, 6, 1, 2, 0, 0, 7, 10, 8, 4, 6, 6, 4, 3, 3, 6, 1, 0, 0), # 123
(9, 4, 10, 11, 6, 4, 2, 0, 2, 2, 0, 0, 0, 10, 10, 6, 2, 10, 7, 2, 1, 3, 2, 1, 0, 0), # 124
(12, 10, 10, 3, 8, 5, 3, 2, 3, 2, 0, 3, 0, 8, 8, 3, 2, 9, 3, 3, 1, 4, 5, 0, 0, 0), # 125
(5, 4, 16, 6, 11, 3, 1, 2, 4, 1, 0, 1, 0, 11, 8, 7, 3, 10, 2, 9, 1, 3, 1, 0, 0, 0), # 126
(15, 8, 5, 8, 7, 2, 1, 4, 3, 1, 2, 0, 0, 9, 7, 2, 7, 7, 3, 2, 2, 3, 1, 1, 1, 0), # 127
(6, 9, 11, 7, 9, 8, 1, 2, 5, 2, 1, 0, 0, 13, 6, 8, 6, 5, 1, 1, 3, 5, 4, 1, 0, 0), # 128
(6, 6, 4, 10, 8, 7, 0, 2, 3, 0, 2, 0, 0, 9, 10, 3, 3, 4, 2, 3, 1, 2, 3, 3, 2, 0), # 129
(18, 5, 8, 10, 7, 3, 3, 5, 1, 2, 1, 0, 0, 12, 7, 6, 5, 4, 2, 4, 2, 4, 2, 1, 0, 0), # 130
(6, 10, 8, 12, 9, 3, 2, 2, 4, 2, 3, 1, 0, 9, 10, 5, 1, 4, 2, 4, 3, 5, 1, 4, 2, 0), # 131
(10, 6, 6, 5, 8, 3, 6, 1, 5, 3, 1, 0, 0, 12, 10, 3, 2, 11, 1, 4, 1, 5, 3, 0, 0, 0), # 132
(11, 7, 8, 3, 10, 4, 2, 2, 4, 1, 1, 1, 0, 11, 9, 4, 1, 5, 4, 3, 2, 3, 4, 2, 2, 0), # 133
(6, 10, 5, 7, 8, 2, 2, 3, 1, 3, 2, 1, 0, 9, 9, 3, 5, 6, 5, 3, 2, 4, 1, 2, 0, 0), # 134
(8, 6, 7, 7, 9, 2, 2, 4, 4, 0, 0, 0, 0, 12, 4, 8, 7, 8, 3, 3, 3, 4, 1, 2, 0, 0), # 135
(7, 8, 2, 11, 5, 1, 5, 2, 8, 0, 1, 2, 0, 5, 5, 9, 2, 5, 0, 4, 4, 7, 2, 2, 3, 0), # 136
(10, 9, 6, 6, 7, 5, 2, 5, 1, 2, 1, 1, 0, 7, 5, 3, 3, 15, 0, 3, 0, 3, 3, 1, 1, 0), # 137
(7, 7, 7, 5, 9, 4, 4, 1, 2, 0, 2, 0, 0, 4, 4, 8, 3, 6, 5, 8, 3, 4, 4, 3, 1, 0), # 138
(11, 5, 6, 6, 5, 3, 4, 3, 1, 0, 1, 0, 0, 11, 7, 5, 4, 4, 1, 3, 1, 4, 2, 1, 3, 0), # 139
(17, 9, 10, 8, 3, 3, 3, 1, 3, 1, 1, 0, 0, 10, 4, 3, 4, 8, 7, 4, 1, 4, 1, 1, 2, 0), # 140
(9, 6, 8, 1, 6, 1, 1, 0, 3, 2, 3, 0, 0, 7, 6, 4, 4, 6, 2, 2, 0, 0, 2, 3, 0, 0), # 141
(7, 6, 9, 8, 13, 4, 2, 6, 5, 2, 1, 0, 0, 7, 9, 6, 3, 11, 5, 5, 2, 6, 2, 0, 0, 0), # 142
(4, 6, 9, 10, 7, 3, 2, 0, 1, 0, 2, 0, 0, 6, 4, 6, 3, 3, 2, 2, 4, 1, 2, 0, 2, 0), # 143
(4, 6, 15, 8, 8, 5, 3, 2, 4, 0, 2, 2, 0, 6, 10, 3, 2, 7, 2, 1, 1, 2, 3, 3, 0, 0), # 144
(6, 5, 6, 6, 11, 3, 3, 0, 2, 1, 1, 1, 0, 9, 4, 3, 3, 6, 2, 1, 1, 0, 3, 1, 0, 0), # 145
(10, 5, 5, 10, 6, 2, 1, 1, 2, 1, 1, 0, 0, 11, 4, 7, 4, 9, 2, 1, 0, 8, 3, 3, 0, 0), # 146
(6, 5, 6, 5, 6, 2, 3, 2, 2, 1, 2, 1, 0, 10, 7, 9, 3, 8, 2, 2, 3, 3, 2, 1, 0, 0), # 147
(7, 4, 11, 10, 5, 1, 2, 2, 2, 0, 0, 0, 0, 11, 10, 2, 6, 6, 2, 1, 3, 6, 2, 0, 0, 0), # 148
(3, 6, 6, 8, 6, 3, 3, 5, 1, 0, 1, 0, 0, 8, 9, 8, 8, 6, 7, 2, 1, 2, 0, 3, 2, 0), # 149
(10, 8, 13, 10, 2, 3, 3, 2, 5, 1, 3, 0, 0, 5, 3, 5, 5, 6, 1, 1, 3, 4, 0, 2, 0, 0), # 150
(7, 2, 8, 12, 7, 5, 5, 4, 2, 4, 1, 1, 0, 8, 6, 7, 1, 8, 4, 0, 3, 2, 0, 0, 0, 0), # 151
(10, 7, 6, 6, 7, 1, 0, 5, 1, 2, 0, 2, 0, 10, 4, 5, 3, 8, 4, 2, 4, 1, 2, 3, 0, 0), # 152
(4, 9, 7, 1, 10, 4, 2, 3, 4, 1, 0, 1, 0, 12, 3, 6, 2, 5, 3, 5, 1, 3, 7, 0, 0, 0), # 153
(7, 8, 10, 6, 4, 1, 3, 2, 6, 3, 1, 1, 0, 7, 7, 1, 3, 10, 5, 1, 2, 3, 4, 3, 0, 0), # 154
(7, 6, 6, 7, 3, 6, 3, 3, 3, 2, 1, 1, 0, 7, 8, 5, 4, 5, 3, 0, 1, 3, 1, 1, 0, 0), # 155
(6, 5, 7, 3, 5, 4, 1, 5, 4, 3, 0, 0, 0, 9, 11, 1, 6, 11, 5, 4, 3, 3, 2, 3, 1, 0), # 156
(11, 5, 6, 15, 9, 4, 1, 1, 3, 0, 1, 0, 0, 6, 4, 7, 4, 14, 7, 4, 1, 3, 2, 2, 0, 0), # 157
(11, 4, 5, 4, 2, 5, 2, 1, 6, 0, 0, 0, 0, 11, 5, 6, 6, 4, 2, 2, 4, 2, 2, 1, 0, 0), # 158
(9, 2, 11, 7, 3, 0, 3, 1, 0, 0, 1, 0, 0, 4, 4, 6, 1, 6, 1, 4, 2, 1, 4, 0, 0, 0), # 159
(10, 9, 7, 5, 7, 4, 4, 0, 4, 3, 0, 0, 0, 4, 4, 6, 0, 5, 5, 2, 1, 5, 4, 0, 2, 0), # 160
(8, 12, 11, 12, 4, 3, 2, 5, 1, 2, 0, 0, 0, 7, 1, 3, 5, 9, 3, 1, 2, 3, 1, 2, 0, 0), # 161
(3, 4, 6, 7, 3, 3, 2, 0, 1, 1, 0, 0, 0, 9, 5, 2, 2, 4, 1, 2, 2, 2, 2, 0, 0, 0), # 162
(13, 7, 7, 10, 8, 3, 1, 6, 4, 0, 0, 0, 0, 9, 3, 4, 1, 6, 1, 2, 1, 7, 1, 2, 0, 0), # 163
(12, 5, 2, 5, 7, 4, 1, 1, 3, 1, 2, 1, 0, 8, 3, 7, 3, 8, 1, 2, 2, 2, 4, 0, 0, 0), # 164
(4, 6, 6, 8, 4, 1, 4, 3, 2, 1, 1, 1, 0, 9, 3, 2, 2, 9, 4, 1, 0, 4, 4, 1, 1, 0), # 165
(9, 4, 3, 5, 6, 1, 2, 4, 1, 1, 0, 0, 0, 10, 3, 4, 3, 8, 0, 0, 1, 4, 3, 2, 2, 0), # 166
(4, 3, 8, 2, 9, 1, 2, 1, 3, 0, 1, 0, 0, 5, 3, 4, 3, 7, 3, 3, 1, 2, 1, 4, 0, 0), # 167
(7, 3, 9, 9, 2, 5, 5, 1, 2, 1, 0, 0, 0, 6, 6, 2, 2, 6, 3, 1, 2, 2, 1, 1, 0, 0), # 168
(3, 4, 6, 4, 4, 5, 1, 2, 4, 0, 1, 0, 0, 8, 8, 3, 4, 5, 2, 2, 1, 4, 1, 2, 0, 0), # 169
(5, 5, 3, 5, 2, 5, 2, 0, 1, 2, 1, 1, 0, 4, 3, 5, 2, 1, 0, 2, 3, 2, 1, 0, 1, 0), # 170
(8, 4, 2, 8, 4, 3, 3, 2, 4, 1, 1, 0, 0, 7, 6, 3, 3, 6, 0, 0, 2, 3, 1, 0, 0, 0), # 171
(5, 4, 8, 4, 5, 0, 3, 0, 6, 0, 0, 1, 0, 4, 8, 2, 2, 2, 1, 1, 1, 3, 1, 1, 1, 0), # 172
(6, 2, 2, 5, 3, 0, 1, 1, 3, 1, 0, 0, 0, 7, 6, 2, 6, 3, 4, 1, 2, 1, 0, 0, 0, 0), # 173
(2, 9, 2, 5, 3, 2, 1, 1, 2, 2, 0, 0, 0, 5, 4, 2, 0, 3, 2, 1, 0, 3, 1, 1, 0, 0), # 174
(7, 6, 3, 2, 5, 3, 0, 3, 1, 1, 0, 0, 0, 2, 3, 3, 4, 5, 3, 3, 0, 4, 3, 0, 0, 0), # 175
(6, 4, 7, 1, 4, 3, 1, 1, 0, 0, 1, 0, 0, 5, 4, 3, 2, 4, 1, 1, 0, 0, 3, 0, 0, 0), # 176
(4, 1, 4, 6, 2, 1, 0, 0, 3, 1, 0, 1, 0, 5, 2, 3, 2, 8, 1, 1, 1, 3, 1, 1, 2, 0), # 177
(6, 2, 5, 1, 1, 1, 1, 0, 2, 1, 1, 0, 0, 4, 0, 4, 1, 4, 0, 1, 1, 4, 3, 0, 0, 0), # 178
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 179
)
station_arriving_intensity = (
(5.020865578371768, 5.525288559693166, 5.211283229612507, 6.214667773863432, 5.554685607609612, 3.1386549320373387, 4.146035615373915, 4.653176172979423, 6.090099062168007, 3.9580150155223697, 4.205265163885603, 4.897915078306173, 5.083880212578363), # 0
(5.354327152019974, 5.890060694144759, 5.555346591330152, 6.625144253276616, 5.922490337474237, 3.3459835840425556, 4.419468941263694, 4.959513722905708, 6.492245326332909, 4.21898069227715, 4.483096135956131, 5.221216660814354, 5.419791647439855), # 1
(5.686723008979731, 6.253385170890979, 5.8980422855474135, 7.033987704664794, 6.288962973749744, 3.5524851145124448, 4.691818507960704, 5.264625247904419, 6.892786806877549, 4.478913775020546, 4.759823148776313, 5.543232652053055, 5.75436482820969), # 2
(6.016757793146562, 6.613820501936447, 6.238010869319854, 7.439576407532074, 6.652661676001902, 3.757340622585113, 4.962003641647955, 5.567301157494507, 7.290135160921093, 4.736782698426181, 5.0343484118273825, 5.862685684930461, 6.086272806254225), # 3
(6.343136148415981, 6.9699251992857745, 6.573892899703036, 7.840288641382569, 7.012144603796492, 3.9597312073986677, 5.2289436685084585, 5.866331861194915, 7.682702045582707, 4.991555897167679, 5.305574134590575, 6.178298392354764, 6.414188632939817), # 4
(6.66456271868351, 7.320257774943588, 6.9043289337525175, 8.234502685720393, 7.36596991669928, 4.158837968091214, 5.491557914725224, 6.160507768524592, 8.068899117981559, 5.242201805918663, 5.572402526547132, 6.488793407234148, 6.736785359632827), # 5
(6.979742147844666, 7.663376740914501, 7.227959528523866, 8.620596820049652, 7.712695774276043, 4.353842003800864, 5.7487657064812625, 6.4486192890024885, 8.447138035236815, 5.487688859352758, 5.833735797178282, 6.792893362476808, 7.052736037699606), # 6
(7.2873790797949685, 7.997840609203132, 7.543425241072635, 8.996949323874462, 8.050880336092554, 4.543924413665721, 5.999486369959585, 6.729456832147552, 8.815830454467644, 5.726985492143586, 6.088476155965268, 7.089320890990929, 7.360713718506519), # 7
(7.586178158429934, 8.322207891814099, 7.849366628454396, 9.361938476698928, 8.379081761714586, 4.7282662968238895, 6.2426392313431975, 7.001810807478725, 9.173388032793206, 5.959060138964774, 6.335525812389321, 7.376798625684702, 7.659391453419917), # 8
(7.874844027645085, 8.635037100752022, 8.144424247724704, 9.713942558027169, 8.69585821070791, 4.906048752413484, 6.47714361681512, 7.264471624514963, 9.518222427332674, 6.182881234489941, 6.573786975931678, 7.654049199466313, 7.947442293806162), # 9
(8.152081331335932, 8.934886748021516, 8.427238655939124, 10.051339847363288, 8.9997678426383, 5.076452879572607, 6.701918852558355, 7.516229692775211, 9.848745295205214, 6.397417213392714, 6.802161856073574, 7.919795245243952, 8.22353929103161), # 10
(8.416594713398005, 9.220315345627206, 8.696450410153215, 10.372508624211397, 9.289368817071534, 5.238659777439368, 6.915884264755916, 7.7558754217784145, 10.163368293529993, 6.601636510346719, 7.019552662296249, 8.17275939592581, 8.486355496462611), # 11
(8.667088817726812, 9.489881405573698, 8.95070006742254, 10.675827168075612, 9.563219293573377, 5.391850545151869, 7.1179591795908115, 7.982199221043521, 10.460503079426179, 6.794507560025572, 7.224861604080934, 8.411664284420068, 8.734563961465534), # 12
(8.902268288217876, 9.74214343986562, 9.188628184802662, 10.959673758460044, 9.819877431709601, 5.5352062818482235, 7.307062923246056, 8.193991500089481, 10.738561310012932, 6.974998797102904, 7.416990890908869, 8.63523254363492, 8.966837737406735), # 13
(9.120837768766716, 9.975659960507588, 9.408875319349146, 11.222426674868792, 10.05790139104599, 5.667908086666534, 7.482114821904661, 8.390042668435246, 10.995954642409421, 7.142078656252334, 7.594842732261284, 8.84218680647856, 9.181849875652563), # 14
(9.321501903268855, 10.188989479504217, 9.610082028117542, 11.462464196805985, 10.275849331148308, 5.789137058744912, 7.642034201749626, 8.569143135599756, 11.23109473373482, 7.29471557214749, 7.757319337619419, 9.031249705859171, 9.37827342756938), # 15
(9.5029653356198, 10.380690508860132, 9.790888868163425, 11.678164603775716, 10.472279411582333, 5.898074297221459, 7.785740388963976, 8.73008331110196, 11.442393241108286, 7.431877979461996, 7.9033229164645125, 9.20114387468494, 9.554781444523545), # 16
(9.663932709715075, 10.549321560579946, 9.949936396542352, 11.867906175282112, 10.645749791913838, 5.993900901234285, 7.9121527097307105, 8.871653604460818, 11.628261821648984, 7.552534312869467, 8.031755678277799, 9.350591945864055, 9.710046977881415), # 17
(9.803108669450204, 10.693441146668274, 10.08586517030988, 12.030067190829278, 10.794818631708589, 6.075797969921503, 8.020190490232851, 8.99264442519526, 11.787112132476096, 7.6556530070435365, 8.141519832540508, 9.478316552304715, 9.842743079009345), # 18
(9.919197858720699, 10.811607779129744, 10.197315746521578, 12.163025929921314, 10.918044090532366, 6.142946602421208, 8.108773056653394, 9.091846182824245, 11.917355830708779, 7.740202496657828, 8.231517588733878, 9.583040326915096, 9.951542799273696), # 19
(10.010904921422082, 10.902379969968962, 10.282928682233003, 12.265160672062354, 11.013984327950944, 6.194527897871518, 8.176819735175362, 9.168049286866717, 12.017404573466198, 7.805151216385958, 8.30065115633915, 9.66348590260339, 10.035119190040824), # 20
(10.076934501449866, 10.964316231190558, 10.341344534499719, 12.334849696756486, 11.081197503530088, 6.229722955410535, 8.223249851981759, 9.220044146841623, 12.085670017867521, 7.849467600901555, 8.34782274483756, 9.718375912277793, 10.092145302677078), # 21
(10.115991242699579, 10.995975074799144, 10.371203860377285, 12.370471283507836, 11.118241776835575, 6.247712874176367, 8.2469827332556, 9.246621172267915, 12.120563821031915, 7.872120084878242, 8.37193456371034, 9.74643298884649, 10.121294188548827), # 22
(10.13039336334264, 10.999723593964335, 10.374923182441702, 12.374930812757203, 11.127732056032597, 6.25, 8.249804002259339, 9.249493827160494, 12.124926234567901, 7.874792272519433, 8.37495803716174, 9.749897576588934, 10.125), # 23
(10.141012413034153, 10.997537037037038, 10.374314814814815, 12.374381944444446, 11.133107613614852, 6.25, 8.248253812636166, 9.2455, 12.124341666666666, 7.87315061728395, 8.37462457912458, 9.749086419753086, 10.125), # 24
(10.15140723021158, 10.993227023319616, 10.373113854595337, 12.373296039094651, 11.138364945594503, 6.25, 8.24519890260631, 9.237654320987655, 12.123186728395062, 7.869918838591678, 8.373963399426362, 9.747485139460448, 10.125), # 25
(10.161577019048034, 10.986859396433472, 10.371336762688616, 12.37168544238683, 11.143503868421105, 6.25, 8.240686718308721, 9.226104938271606, 12.1214762345679, 7.865150708733425, 8.372980483850855, 9.745115683584821, 10.125), # 26
(10.171520983716636, 10.978499999999999, 10.369, 12.369562499999999, 11.148524198544214, 6.25, 8.234764705882354, 9.211, 12.119225, 7.858899999999999, 8.371681818181818, 9.742, 10.125), # 27
(10.181238328390501, 10.968214677640603, 10.366120027434842, 12.366939557613168, 11.153425752413401, 6.25, 8.22748031146615, 9.192487654320988, 12.116447839506172, 7.851220484682213, 8.370073388203018, 9.73816003657979, 10.125), # 28
(10.19072825724275, 10.95606927297668, 10.362713305898492, 12.36382896090535, 11.15820834647822, 6.25, 8.218880981199066, 9.170716049382715, 12.113159567901235, 7.842165935070874, 8.368161179698216, 9.733617741197987, 10.125), # 29
(10.199989974446497, 10.94212962962963, 10.358796296296296, 12.360243055555555, 11.162871797188236, 6.25, 8.209014161220043, 9.145833333333332, 12.109375, 7.83179012345679, 8.365951178451178, 9.728395061728394, 10.125), # 30
(10.209022684174858, 10.926461591220852, 10.354385459533608, 12.356194187242798, 11.167415920993008, 6.25, 8.19792729766804, 9.117987654320988, 12.105108950617284, 7.820146822130773, 8.363449370245666, 9.722513946044812, 10.125), # 31
(10.217825590600954, 10.909131001371742, 10.349497256515773, 12.35169470164609, 11.171840534342095, 6.25, 8.185667836681999, 9.087327160493828, 12.100376234567902, 7.807289803383631, 8.360661740865444, 9.715996342021034, 10.125), # 32
(10.226397897897897, 10.890203703703703, 10.344148148148149, 12.346756944444444, 11.176145453685063, 6.25, 8.172283224400871, 9.054, 12.095191666666667, 7.793272839506173, 8.357594276094275, 9.708864197530863, 10.125), # 33
(10.23473881023881, 10.869745541838133, 10.338354595336076, 12.341393261316872, 11.180330495471466, 6.25, 8.15782090696361, 9.018154320987653, 12.089570061728397, 7.778149702789209, 8.354252961715924, 9.701139460448102, 10.125), # 34
(10.242847531796807, 10.847822359396433, 10.332133058984912, 12.335615997942385, 11.18439547615087, 6.25, 8.142328330509159, 8.979938271604938, 12.083526234567902, 7.761974165523548, 8.350643783514153, 9.692844078646548, 10.125), # 35
(10.250723266745005, 10.824499999999999, 10.3255, 12.3294375, 11.188340212172836, 6.25, 8.12585294117647, 8.9395, 12.077074999999999, 7.7448, 8.346772727272727, 9.684000000000001, 10.125), # 36
(10.258365219256524, 10.799844307270233, 10.318471879286694, 12.322870113168724, 11.192164519986921, 6.25, 8.108442185104494, 8.896987654320988, 12.070231172839506, 7.726680978509374, 8.34264577877541, 9.674629172382259, 10.125), # 37
(10.265772593504476, 10.773921124828533, 10.311065157750342, 12.315926183127573, 11.19586821604269, 6.25, 8.09014350843218, 8.85254938271605, 12.063009567901235, 7.707670873342479, 8.33826892380596, 9.664753543667125, 10.125), # 38
(10.272944593661986, 10.746796296296296, 10.303296296296297, 12.308618055555556, 11.199451116789703, 6.25, 8.071004357298476, 8.806333333333333, 12.055425000000001, 7.687823456790124, 8.333648148148148, 9.654395061728394, 10.125), # 39
(10.279880423902163, 10.718535665294924, 10.295181755829903, 12.300958076131687, 11.202913038677519, 6.25, 8.05107217784233, 8.758487654320989, 12.047492283950618, 7.667192501143119, 8.328789437585733, 9.643575674439873, 10.125), # 40
(10.286579288398128, 10.689205075445816, 10.286737997256516, 12.29295859053498, 11.206253798155702, 6.25, 8.030394416202695, 8.709160493827161, 12.0392262345679, 7.645831778692272, 8.323698777902482, 9.632317329675354, 10.125), # 41
(10.293040391323, 10.658870370370371, 10.277981481481483, 12.284631944444445, 11.209473211673808, 6.25, 8.009018518518518, 8.6585, 12.030641666666668, 7.623795061728395, 8.318382154882155, 9.620641975308642, 10.125), # 42
(10.299262936849892, 10.627597393689987, 10.268928669410151, 12.275990483539095, 11.212571095681403, 6.25, 7.98699193092875, 8.606654320987655, 12.021753395061728, 7.601136122542296, 8.312845554308517, 9.608571559213535, 10.125), # 43
(10.305246129151927, 10.595451989026063, 10.259596021947875, 12.267046553497943, 11.215547266628045, 6.25, 7.964362099572339, 8.553771604938273, 12.0125762345679, 7.577908733424783, 8.307094961965332, 9.596128029263832, 10.125), # 44
(10.310989172402216, 10.5625, 10.25, 12.2578125, 11.218401540963296, 6.25, 7.9411764705882355, 8.5, 12.003124999999999, 7.554166666666667, 8.301136363636363, 9.583333333333332, 10.125), # 45
(10.31649127077388, 10.528807270233196, 10.240157064471878, 12.24830066872428, 11.221133735136716, 6.25, 7.917482490115388, 8.445487654320988, 11.993414506172838, 7.529963694558756, 8.294975745105374, 9.57020941929584, 10.125), # 46
(10.321751628440035, 10.49443964334705, 10.230083676268862, 12.238523405349794, 11.223743665597867, 6.25, 7.893327604292747, 8.390382716049382, 11.983459567901235, 7.505353589391861, 8.288619092156129, 9.55677823502515, 10.125), # 47
(10.326769449573796, 10.459462962962963, 10.219796296296296, 12.228493055555557, 11.22623114879631, 6.25, 7.868759259259259, 8.334833333333334, 11.973275000000001, 7.4803901234567896, 8.28207239057239, 9.543061728395061, 10.125), # 48
(10.331543938348286, 10.42394307270233, 10.209311385459534, 12.218221965020577, 11.228596001181607, 6.25, 7.8438249011538765, 8.278987654320987, 11.96287561728395, 7.455127069044353, 8.275341626137923, 9.529081847279379, 10.125), # 49
(10.336074298936616, 10.387945816186559, 10.198645404663925, 12.207722479423868, 11.230838039203315, 6.25, 7.81857197611555, 8.222993827160494, 11.9522762345679, 7.429618198445358, 8.268432784636488, 9.514860539551899, 10.125), # 50
(10.34035973551191, 10.351537037037037, 10.187814814814814, 12.197006944444444, 11.232957079310998, 6.25, 7.793047930283224, 8.167, 11.941491666666668, 7.403917283950617, 8.261351851851853, 9.50041975308642, 10.125), # 51
(10.344399452247279, 10.314782578875173, 10.176836076817558, 12.186087705761317, 11.234952937954214, 6.25, 7.767300209795852, 8.111154320987653, 11.930536728395062, 7.3780780978509375, 8.254104813567777, 9.485781435756746, 10.125), # 52
(10.348192653315843, 10.27774828532236, 10.165725651577505, 12.174977109053497, 11.23682543158253, 6.25, 7.741376260792383, 8.055604938271605, 11.919426234567903, 7.3521544124371285, 8.246697655568026, 9.470967535436671, 10.125), # 53
(10.351738542890716, 10.2405, 10.154499999999999, 12.1636875, 11.238574376645502, 6.25, 7.715323529411765, 8.000499999999999, 11.908175, 7.3262, 8.239136363636362, 9.456, 10.125), # 54
(10.355036325145022, 10.203103566529492, 10.143175582990398, 12.152231224279834, 11.24019958959269, 6.25, 7.689189461792948, 7.945987654320987, 11.896797839506172, 7.300268632830361, 8.231426923556553, 9.44090077732053, 10.125), # 55
(10.358085204251871, 10.165624828532236, 10.131768861454047, 12.140620627572016, 11.241700886873659, 6.25, 7.663021504074881, 7.892216049382716, 11.885309567901235, 7.274414083219022, 8.223575321112358, 9.425691815272062, 10.125), # 56
(10.360884384384383, 10.12812962962963, 10.120296296296297, 12.128868055555555, 11.243078084937967, 6.25, 7.636867102396514, 7.839333333333334, 11.873725, 7.24869012345679, 8.215587542087542, 9.410395061728394, 10.125), # 57
(10.36343306971568, 10.090683813443073, 10.108774348422497, 12.116985853909464, 11.244331000235174, 6.25, 7.610773702896797, 7.787487654320987, 11.862058950617284, 7.223150525834477, 8.20746957226587, 9.395032464563329, 10.125), # 58
(10.36573046441887, 10.053353223593964, 10.097219478737998, 12.104986368312757, 11.245459449214845, 6.25, 7.584788751714678, 7.736827160493827, 11.850326234567902, 7.197849062642891, 8.1992273974311, 9.379625971650663, 10.125), # 59
(10.367775772667077, 10.016203703703704, 10.085648148148147, 12.092881944444445, 11.246463248326537, 6.25, 7.558959694989106, 7.6875, 11.838541666666668, 7.172839506172839, 8.190867003367003, 9.364197530864198, 10.125), # 60
(10.369568198633415, 9.97930109739369, 10.0740768175583, 12.080684927983539, 11.247342214019811, 6.25, 7.533333978859033, 7.639654320987654, 11.826720061728395, 7.148175628715135, 8.182394375857339, 9.348769090077733, 10.125), # 61
(10.371106946491004, 9.942711248285322, 10.062521947873801, 12.068407664609055, 11.248096162744234, 6.25, 7.507959049463406, 7.5934382716049384, 11.814876234567901, 7.123911202560586, 8.17381550068587, 9.333362597165067, 10.125), # 62
(10.37239122041296, 9.9065, 10.051, 12.056062500000001, 11.248724910949356, 6.25, 7.482882352941176, 7.549, 11.803025, 7.100099999999999, 8.165136363636364, 9.318, 10.125), # 63
(10.373420224572397, 9.870733196159122, 10.039527434842249, 12.043661779835391, 11.249228275084748, 6.25, 7.458151335431292, 7.506487654320988, 11.791181172839506, 7.076795793324188, 8.156362950492579, 9.302703246456334, 10.125), # 64
(10.374193163142438, 9.835476680384087, 10.0281207133059, 12.031217849794238, 11.249606071599967, 6.25, 7.433813443072703, 7.466049382716049, 11.779359567901235, 7.054052354823959, 8.147501247038285, 9.287494284407863, 10.125), # 65
(10.374709240296196, 9.800796296296298, 10.016796296296297, 12.018743055555555, 11.249858116944573, 6.25, 7.409916122004357, 7.427833333333334, 11.767575, 7.031923456790123, 8.138557239057238, 9.272395061728396, 10.125), # 66
(10.374967660206792, 9.766757887517146, 10.005570644718793, 12.006249742798353, 11.24998422756813, 6.25, 7.386506818365206, 7.391987654320989, 11.755842283950617, 7.010462871513489, 8.12953691233321, 9.257427526291723, 10.125), # 67
(10.374791614480825, 9.733248639320323, 9.994405949931412, 11.993641740472357, 11.249877955297345, 6.2498840115836, 7.363515194829646, 7.358343850022862, 11.744087848651121, 6.989620441647166, 8.120285988540376, 9.242530021899743, 10.124875150034294), # 68
(10.373141706924315, 9.699245519713262, 9.982988425925925, 11.980283514492752, 11.248910675381262, 6.248967078189301, 7.340268181346613, 7.325098765432099, 11.731797839506173, 6.968806390704429, 8.10986283891547, 9.227218973359324, 10.12388599537037), # 69
(10.369885787558895, 9.664592459843355, 9.971268432784635, 11.966087124261943, 11.246999314128942, 6.247161255906112, 7.31666013456137, 7.291952446273434, 11.718902892089622, 6.947919524462734, 8.09814888652608, 9.211422761292809, 10.121932334533609), # 70
(10.365069660642929, 9.62931016859153, 9.959250085733881, 11.951073503757382, 11.244168078754136, 6.244495808565767, 7.292701659538988, 7.258915866483768, 11.705422210791038, 6.926960359342639, 8.085187370783862, 9.195152937212715, 10.119039887688615), # 71
(10.358739130434783, 9.593419354838709, 9.946937499999999, 11.935263586956522, 11.240441176470588, 6.2410000000000005, 7.268403361344538, 7.226, 11.691375, 6.905929411764705, 8.07102153110048, 9.17842105263158, 10.115234375), # 72
(10.35094000119282, 9.556940727465816, 9.934334790809327, 11.918678307836823, 11.23584281449205, 6.236703094040542, 7.243775845043092, 7.193215820759031, 11.676780464106082, 6.884827198149493, 8.055694606887588, 9.161238659061919, 10.110541516632374), # 73
(10.341718077175404, 9.519894995353777, 9.921446073388202, 11.901338600375738, 11.230397200032275, 6.231634354519128, 7.218829715699722, 7.160574302697759, 11.661657807498857, 6.863654234917561, 8.039249837556856, 9.143617308016267, 10.104987032750344), # 74
(10.331119162640901, 9.482302867383511, 9.908275462962962, 11.883265398550725, 11.224128540305012, 6.22582304526749, 7.1935755783795, 7.128086419753086, 11.6460262345679, 6.84241103848947, 8.021730462519935, 9.125568551007147, 10.098596643518519), # 75
(10.319189061847677, 9.44418505243595, 9.894827074759945, 11.864479636339238, 11.217061042524005, 6.219298430117361, 7.168024038147495, 7.095763145861912, 11.629904949702789, 6.821098125285779, 8.003179721188491, 9.107103939547082, 10.091396069101508), # 76
(10.305973579054093, 9.40556225939201, 9.881105024005485, 11.845002247718732, 11.209218913903008, 6.212089772900472, 7.142185700068779, 7.063615454961135, 11.613313157293096, 6.7997160117270505, 7.983640852974187, 9.088235025148606, 10.083411029663925), # 77
(10.291518518518519, 9.366455197132618, 9.867113425925925, 11.824854166666666, 11.200626361655774, 6.204226337448559, 7.116071169208425, 7.031654320987655, 11.596270061728394, 6.7782652142338415, 7.9631570972886765, 9.068973359324238, 10.074667245370371), # 78
(10.275869684499314, 9.326884574538697, 9.8528563957476, 11.804056327160493, 11.191307592996047, 6.195737387593354, 7.089691050631501, 6.9998907178783725, 11.578794867398262, 6.756746249226714, 7.941771693543622, 9.049330493586504, 10.065190436385459), # 79
(10.259072881254847, 9.286871100491172, 9.838338048696844, 11.782629663177671, 11.181286815137579, 6.18665218716659, 7.063055949403081, 6.968335619570188, 11.560906778692273, 6.7351596331262265, 7.919527881150688, 9.029317979447935, 10.0550063228738), # 80
(10.241173913043479, 9.246435483870968, 9.8235625, 11.760595108695654, 11.170588235294117, 6.177, 7.036176470588235, 6.937, 11.542625, 6.713505882352941, 7.8964688995215315, 9.008947368421053, 10.044140624999999), # 81
(10.222218584123576, 9.205598433559008, 9.808533864883403, 11.737973597691894, 11.159236060679415, 6.166810089925317, 7.009063219252036, 6.90589483310471, 11.52396873571102, 6.691785513327416, 7.872637988067813, 8.988230212018387, 10.03261906292867), # 82
(10.202252698753504, 9.164380658436214, 9.793256258573388, 11.714786064143853, 11.147254498507221, 6.156111720774272, 6.981726800459553, 6.875031092821216, 11.504957190214906, 6.669999042470211, 7.848078386201194, 8.967178061752461, 10.020467356824417), # 83
(10.181322061191626, 9.122802867383513, 9.777733796296296, 11.691053442028986, 11.134667755991286, 6.144934156378601, 6.954177819275858, 6.844419753086419, 11.485609567901234, 6.648146986201889, 7.822833333333333, 8.945802469135803, 10.007711226851852), # 84
(10.159472475696308, 9.080885769281826, 9.761970593278463, 11.666796665324746, 11.121500040345357, 6.133306660570035, 6.926426880766024, 6.814071787837221, 11.465945073159578, 6.626229860943005, 7.796946068875894, 8.924114985680937, 9.994376393175584), # 85
(10.136749746525913, 9.03865007301208, 9.745970764746229, 11.64203666800859, 11.107775558783183, 6.121258497180309, 6.89848458999512, 6.783998171010516, 11.445982910379517, 6.604248183114124, 7.770459832240534, 8.902127162900394, 9.98048857596022), # 86
(10.113199677938807, 8.996116487455197, 9.729738425925925, 11.61679438405797, 11.09351851851852, 6.108818930041152, 6.870361552028219, 6.75420987654321, 11.425742283950619, 6.582202469135802, 7.743417862838915, 8.879850552306692, 9.96607349537037), # 87
(10.088868074193357, 8.9533057214921, 9.713277692043896, 11.59109074745035, 11.07875312676511, 6.096017222984301, 6.842068371930391, 6.724717878372199, 11.40524239826246, 6.560093235428601, 7.715863400082698, 8.857296705412365, 9.951156871570646), # 88
(10.063800739547922, 8.910238484003717, 9.696592678326475, 11.564946692163177, 11.063503590736707, 6.082882639841488, 6.813615654766708, 6.695533150434385, 11.384502457704619, 6.537920998413083, 7.687839683383544, 8.834477173729935, 9.935764424725651), # 89
(10.03804347826087, 8.866935483870968, 9.6796875, 11.538383152173914, 11.04779411764706, 6.069444444444445, 6.785014005602241, 6.666666666666666, 11.363541666666668, 6.515686274509804, 7.65938995215311, 8.81140350877193, 9.919921875), # 90
(10.011642094590563, 8.823417429974777, 9.662566272290809, 11.511421061460013, 11.031648914709915, 6.055731900624904, 6.756274029502062, 6.638129401005944, 11.342379229538182, 6.4933895801393255, 7.63055744580306, 8.788087262050874, 9.903654942558298), # 91
(9.984642392795372, 8.779705031196071, 9.64523311042524, 11.484081353998926, 11.015092189139029, 6.041774272214601, 6.727406331531242, 6.609932327389118, 11.321034350708734, 6.471031431722209, 7.601385403745053, 8.764539985079297, 9.886989347565157), # 92
(9.957090177133654, 8.735818996415771, 9.62769212962963, 11.456384963768118, 10.998148148148148, 6.027600823045267, 6.69842151675485, 6.582086419753087, 11.299526234567901, 6.448612345679011, 7.57191706539075, 8.74077322936972, 9.869950810185184), # 93
(9.92903125186378, 8.691780034514801, 9.609947445130317, 11.428352824745035, 10.98084099895102, 6.0132408169486355, 6.669330190237961, 6.554602652034752, 11.277874085505259, 6.426132838430297, 7.54219567015181, 8.716798546434674, 9.85256505058299), # 94
(9.90051142124411, 8.647608854374088, 9.592003172153635, 11.400005870907139, 10.963194948761398, 5.9987235177564395, 6.640142957045644, 6.527491998171011, 11.25609710791038, 6.403593426396621, 7.512264457439896, 8.69262748778668, 9.834857788923182), # 95
(9.871576489533012, 8.603326164874554, 9.573863425925927, 11.371365036231884, 10.945234204793028, 5.984078189300411, 6.610870422242971, 6.500765432098766, 11.234214506172838, 6.3809946259985475, 7.482166666666667, 8.668271604938273, 9.816854745370371), # 96
(9.842272260988848, 8.558952674897121, 9.555532321673525, 11.342451254696725, 10.926982974259664, 5.969334095412284, 6.581523190895013, 6.474433927754916, 11.212245484682214, 6.358336953656634, 7.451945537243782, 8.64374244940197, 9.798581640089164), # 97
(9.812644539869984, 8.514509093322713, 9.53701397462277, 11.31328546027912, 10.908465464375052, 5.954520499923793, 6.552111868066842, 6.44850845907636, 11.190209247828074, 6.335620925791441, 7.421644308582906, 8.619051572690298, 9.78006419324417), # 98
(9.782739130434782, 8.470016129032258, 9.5183125, 11.283888586956522, 10.889705882352942, 5.939666666666667, 6.52264705882353, 6.423, 11.168125, 6.312847058823529, 7.391306220095694, 8.59421052631579, 9.761328125), # 99
(9.752601836941611, 8.425494490906676, 9.49943201303155, 11.254281568706388, 10.870728435407084, 5.924801859472641, 6.493139368230145, 6.3979195244627345, 11.146011945587563, 6.290015869173458, 7.36097451119381, 8.569230861790967, 9.742399155521262), # 100
(9.722278463648834, 8.380964887826895, 9.480376628943759, 11.224485339506174, 10.85155733075123, 5.909955342173449, 6.463599401351762, 6.3732780064014625, 11.123889288980338, 6.267127873261788, 7.330692421288912, 8.544124130628353, 9.723303004972564), # 101
(9.691814814814816, 8.336448028673836, 9.461150462962962, 11.194520833333334, 10.832216775599129, 5.895156378600824, 6.43403776325345, 6.349086419753086, 11.1017762345679, 6.244183587509078, 7.300503189792663, 8.518901884340481, 9.704065393518519), # 102
(9.661256694697919, 8.291964622328422, 9.4417576303155, 11.164408984165325, 10.812730977164529, 5.880434232586496, 6.40446505900028, 6.325355738454504, 11.079691986739826, 6.221183528335889, 7.270450056116723, 8.493575674439873, 9.68471204132373), # 103
(9.63064990755651, 8.247535377671579, 9.422202246227709, 11.134170725979603, 10.79312414266118, 5.865818167962201, 6.374891893657326, 6.302096936442616, 11.057655749885688, 6.19812821216278, 7.24057625967275, 8.468157052439054, 9.665268668552812), # 104
(9.600040257648953, 8.203181003584229, 9.402488425925926, 11.103826992753623, 10.773420479302832, 5.851337448559671, 6.345328872289658, 6.279320987654321, 11.035686728395062, 6.175018155410313, 7.210925039872408, 8.442657569850553, 9.64576099537037), # 105
(9.569473549233614, 8.158922208947299, 9.382620284636488, 11.073398718464842, 10.753644194303236, 5.837021338210638, 6.315786599962345, 6.25703886602652, 11.01380412665752, 6.151853874499045, 7.181539636127355, 8.417088778186894, 9.626214741941014), # 106
(9.538995586568856, 8.11477970264171, 9.362601937585735, 11.042906837090714, 10.733819494876139, 5.822899100746838, 6.286275681740461, 6.235261545496114, 10.992027149062643, 6.128635885849539, 7.152463287849252, 8.391462228960604, 9.606655628429355), # 107
(9.508652173913044, 8.070774193548388, 9.3424375, 11.012372282608696, 10.713970588235293, 5.809, 6.256806722689075, 6.214, 10.970375, 6.105364705882353, 7.1237392344497605, 8.365789473684211, 9.587109375), # 108
(9.478489115524543, 8.026926390548255, 9.322131087105625, 10.98181598899624, 10.69412168159445, 5.795353299801859, 6.227390327873262, 6.193265203475081, 10.948866883859168, 6.082040851018047, 7.09541071534054, 8.340082063870238, 9.567601701817559), # 109
(9.448552215661715, 7.983257002522237, 9.301686814128946, 10.951258890230811, 10.674296982167354, 5.7819882639841484, 6.198037102358089, 6.173068129858253, 10.92752200502972, 6.058664837677183, 7.06752096993325, 8.314351551031214, 9.54815832904664), # 110
(9.41888727858293, 7.9397867383512555, 9.281108796296298, 10.920721920289855, 10.654520697167756, 5.768934156378601, 6.168757651208631, 6.153419753086419, 10.906359567901236, 6.035237182280319, 7.040113237639553, 8.288609486679663, 9.528804976851852), # 111
(9.38954010854655, 7.896536306916234, 9.26040114883402, 10.890226013150832, 10.634817033809409, 5.756220240816949, 6.139562579489958, 6.134331047096479, 10.885398776863282, 6.011758401248016, 7.013230757871109, 8.26286742232811, 9.509567365397805), # 112
(9.360504223703044, 7.853598618785952, 9.239617828252069, 10.85983388249204, 10.615175680173705, 5.7438697692145135, 6.1105259636567695, 6.115852568780606, 10.86471281125862, 5.988304736612729, 6.9869239061528665, 8.237192936504428, 9.490443900843221), # 113
(9.331480897900065, 7.811397183525536, 9.219045675021619, 10.829789421277336, 10.595393354566326, 5.731854608529901, 6.082018208410579, 6.09821125950512, 10.84461903571306, 5.965315167912783, 6.961244337113197, 8.211912172112974, 9.471275414160035), # 114
(9.302384903003995, 7.769947198683046, 9.198696932707318, 10.800084505181779, 10.5754076778886, 5.7201435124987645, 6.054059650191562, 6.081402654278709, 10.82512497866879, 5.942825327988077, 6.936154511427094, 8.187037582558851, 9.452006631660376), # 115
(9.273179873237634, 7.729188281291702, 9.178532189983873, 10.770666150266404, 10.555188526383779, 5.708708877287098, 6.026604817527893, 6.065380312898993, 10.80618133922783, 5.920793358449547, 6.911605931271481, 8.162523197487346, 9.43260725975589), # 116
(9.243829442823772, 7.689060048384721, 9.158512035525986, 10.741481372592244, 10.53470577629511, 5.6975230990608905, 5.9996082389477525, 6.050097795163585, 10.787738816492203, 5.899177400908129, 6.887550098823283, 8.13832304654375, 9.413047004858225), # 117
(9.214297245985211, 7.649502116995324, 9.138597058008367, 10.712477188220333, 10.513929303865842, 5.686558573986138, 5.973024442979315, 6.0355086608700965, 10.769748109563935, 5.877935596974759, 6.863938516259424, 8.11439115937335, 9.393295573379024), # 118
(9.184546916944742, 7.610454104156729, 9.118747846105723, 10.683600613211706, 10.492828985339221, 5.675787698228833, 5.946807958150756, 6.021566469816145, 10.752159917545043, 5.857026088260372, 6.840722685756828, 8.090681565621434, 9.373322671729932), # 119
(9.154542089925162, 7.571855626902158, 9.098924988492762, 10.654798663627394, 10.471374696958497, 5.665182867954965, 5.920913312990253, 6.008224781799343, 10.734924939537558, 5.836407016375905, 6.817854109492416, 8.067148294933297, 9.353098006322597), # 120
(9.124246399149268, 7.533646302264829, 9.079089073844187, 10.626018355528434, 10.449536314966918, 5.6547164793305305, 5.89529503602598, 5.995437156617307, 10.717993874643499, 5.816036522932296, 6.795284289643116, 8.043745376954222, 9.33259128356866), # 121
(9.093623478839854, 7.495765747277961, 9.059200690834711, 10.597206704975855, 10.427283715607734, 5.644360928521519, 5.869907655786117, 5.983157154067649, 10.70131742196489, 5.795872749540477, 6.772964728385851, 8.0204268413295, 9.31177220987977), # 122
(9.062636963219719, 7.458153578974774, 9.039220428139036, 10.568310728030694, 10.40458677512419, 5.634088611693925, 5.844705700798839, 5.971338333947983, 10.684846280603754, 5.775873837811387, 6.750846927897544, 7.997146717704421, 9.290610491667572), # 123
(9.031250486511654, 7.420749414388487, 9.01910887443187, 10.539277440753986, 10.381415369759537, 5.623871925013739, 5.819643699592319, 5.959934256055926, 10.668531149662115, 5.755997929355961, 6.728882390355119, 7.973859035724275, 9.269075835343711), # 124
(8.999427682938459, 7.38349287055232, 8.998826618387923, 10.51005385920676, 10.357739375757022, 5.613683264646956, 5.794676180694739, 5.948898480189091, 10.652322728241993, 5.736203165785134, 6.707022617935501, 7.950517825034348, 9.247137947319828), # 125
(8.967132186722928, 7.346323564499494, 8.978334248681898, 10.480586999450054, 10.333528669359893, 5.603495026759568, 5.76975767263427, 5.938184566145092, 10.636171715445418, 5.7164476887098425, 6.685219112815613, 7.927077115279934, 9.224766534007578), # 126
(8.93432763208786, 7.309181113263224, 8.957592353988504, 10.450823877544899, 10.308753126811398, 5.593279607517565, 5.744842703939094, 5.927746073721545, 10.620028810374407, 5.696689639741024, 6.6634233771723785, 7.903490936106316, 9.201931301818599), # 127
(8.900977653256046, 7.272005133876735, 8.93656152298245, 10.420711509552332, 10.28338262435479, 5.583009403086944, 5.719885803137382, 5.917536562716062, 10.603844712130984, 5.6768871604896125, 6.641586913182724, 7.879713317158788, 9.178601957164537), # 128
(8.867045884450281, 7.234735243373241, 8.91520234433844, 10.390196911533382, 10.257387038233311, 5.572656809633695, 5.694841498757313, 5.90750959292626, 10.587570119817174, 5.656998392566545, 6.619661223023571, 7.855698288082636, 9.154748206457038), # 129
(8.832495959893366, 7.197311058785966, 8.893475406731179, 10.359227099549086, 10.230736244690213, 5.562194223323808, 5.669664319327063, 5.89761872414975, 10.571155732535, 5.636981477582757, 6.5975978088718445, 7.831399878523152, 9.130339756107748), # 130
(8.797291513808094, 7.159672197148127, 8.87134129883538, 10.327749089660475, 10.203400119968745, 5.55159404032328, 5.644308793374809, 5.88781751618415, 10.554552249386486, 5.616794557149185, 6.575348172904468, 7.806772118125624, 9.105346312528312), # 131
(8.76139618041726, 7.121758275492944, 8.848760609325746, 10.295709897928587, 10.175348540312154, 5.540828656798102, 5.618729449428725, 5.878059528827073, 10.537710369473654, 5.596395772876765, 6.552863817298364, 7.781769036535342, 9.079737582130376), # 132
(8.724773593943663, 7.083508910853635, 8.825693926876983, 10.263056540414452, 10.146551381963686, 5.529870468914266, 5.592880816016989, 5.868298321876132, 10.520580791898526, 5.575743266376432, 6.53009624423046, 7.756344663397592, 9.053483271325586), # 133
(8.687387388610095, 7.044863720263423, 8.802101840163804, 10.229736033179103, 10.116978521166592, 5.518691872837765, 5.566717421667779, 5.858487455128944, 10.503114215763128, 5.5547951792591235, 6.506996955877678, 7.730453028357666, 9.026553086525583), # 134
(8.649201198639354, 7.005762320755524, 8.777944937860909, 10.195695392283579, 10.08659983416412, 5.507265264734592, 5.540193794909268, 5.84858048838312, 10.48526134016948, 5.533509653135776, 6.483517454416942, 7.704048161060852, 8.99891673414202), # 135
(8.610178658254235, 6.966144329363159, 8.753183808643008, 10.160881633788906, 10.055385197199517, 5.495563040770739, 5.513264464269635, 5.838530981436277, 10.466972864219606, 5.511844829617322, 6.459609242025177, 7.677084091152441, 8.970543920586536), # 136
(8.570283401677534, 6.925949363119547, 8.72777904118481, 10.125241773756125, 10.023304486516034, 5.483557597112198, 5.485883958277055, 5.828292494086029, 10.448199487015533, 5.4897588503147015, 6.435223820879306, 7.649514848277719, 8.941404352270776), # 137
(8.529479063132047, 6.885117039057908, 8.701691224161017, 10.088722828246263, 9.990327578356919, 5.471221329924964, 5.458006805459704, 5.81781858612999, 10.428891907659281, 5.4672098568388465, 6.410312693156252, 7.621294462081978, 8.91146773560639), # 138
(8.487729276840568, 6.843586974211461, 8.67488094624634, 10.051271813320358, 9.956424348965415, 5.458526635375026, 5.429587534345759, 5.807062817365774, 10.409000825252871, 5.444155990800697, 6.38482736103294, 7.592376962210506, 8.880703777005019), # 139
(8.444997677025897, 6.801298785613425, 8.647308796115487, 10.012835745039444, 9.92156467458478, 5.445445909628379, 5.400580673463397, 5.795978747590996, 10.388476938898332, 5.420555393811186, 6.358719326686294, 7.562716378308592, 8.849082182878314), # 140
(8.40124789791083, 6.758192090297021, 8.61893536244316, 9.973361639464553, 9.885718431458253, 5.431951548851015, 5.370940751340795, 5.78451993660327, 10.36727094769768, 5.396366207481251, 6.331940092293238, 7.532266740021525, 8.816572659637913), # 141
(8.356443573718156, 6.714206505295466, 8.58972123390407, 9.93279651265672, 9.848855495829087, 5.418015949208927, 5.340622296506126, 5.772639944200211, 10.345333550752942, 5.371546573421828, 6.304441160030697, 7.500982076994594, 8.783144913695466), # 142
(8.310548338670674, 6.669281647641981, 8.559626999172925, 9.891087380676975, 9.810945743940529, 5.403611506868106, 5.3095798374875685, 5.760292330179432, 10.322615447166147, 5.3460546332438525, 6.276174032075593, 7.4688164188730894, 8.748768651462617), # 143
(8.263525826991184, 6.623357134369786, 8.528613246924428, 9.848181259586356, 9.771959052035829, 5.388710617994547, 5.277767902813299, 5.747430654338549, 10.29906733603931, 5.31984852855826, 6.247090210604851, 7.435723795302299, 8.713413579351014), # 144
(8.215339672902477, 6.576372582512099, 8.496640565833289, 9.804025165445895, 9.731865296358233, 5.3732856787542405, 5.245141021011493, 5.734008476475176, 10.274639916474454, 5.292886400975988, 6.217141197795395, 7.401658235927513, 8.6770494037723), # 145
(8.16595351062735, 6.528267609102142, 8.463669544574216, 9.758566114316626, 9.690634353150992, 5.35730908531318, 5.21165372061033, 5.719979356386927, 10.249283887573606, 5.2651263921079705, 6.186278495824149, 7.3665737703940195, 8.639645831138118), # 146
(8.1153309743886, 6.47898183117313, 8.42966077182191, 9.71175112225958, 9.648236098657351, 5.340753233837358, 5.177260530137981, 5.705296853871415, 10.22294994843879, 5.236526643565146, 6.154453606868036, 7.3304244283471105, 8.601172567860118), # 147
(8.063435698409021, 6.428454865758288, 8.394574836251083, 9.663527205335797, 9.604640409120561, 5.323590520492767, 5.1419159781226265, 5.689914528726257, 10.195588798172029, 5.207045296958447, 6.1216180331039824, 7.29316423943207, 8.561599320349941), # 148
(8.010231316911412, 6.37662632989083, 8.358372326536443, 9.613841379606303, 9.55981716078387, 5.3057933414453995, 5.105574593092441, 5.673785940749067, 10.167151135875338, 5.176640493898813, 6.08772327670891, 7.254747233294191, 8.520895795019237), # 149
(7.955681464118564, 6.323435840603979, 8.321013831352694, 9.562640661132138, 9.513736229890526, 5.287334092861249, 5.0681909035756005, 5.656864649737456, 10.137587660650752, 5.1452703759971765, 6.0527208398597425, 7.215127439578763, 8.479031698279647), # 150
(7.899749774253275, 6.268823014930954, 8.282459939374542, 9.50987206597433, 9.466367492683776, 5.268185170906305, 5.029719438100283, 5.639104215489043, 10.106849071600289, 5.112893084864478, 6.016562224733405, 7.174258887931072, 8.435976736542818), # 151
(7.842399881538343, 6.212727469904973, 8.242671239276701, 9.455482610193918, 9.417680825406869, 5.2483189717465635, 4.9901147251946645, 5.620458197801441, 10.07488606782597, 5.079466762111649, 5.979198933506821, 7.132095607996409, 8.391700616220398), # 152
(7.78359542019656, 6.155088822559256, 8.201608319733868, 9.399419309851933, 9.367646104303056, 5.2277078915480155, 4.949331293386919, 5.600880156472262, 10.041649348429823, 5.044949549349629, 5.940582468356916, 7.088591629420064, 8.346173043724027), # 153
(7.723300024450729, 6.095846689927024, 8.159231769420758, 9.34162918100941, 9.31623320561558, 5.206324326476654, 4.907323671205228, 5.580323651299123, 10.007089612513866, 5.009299588189353, 5.900664331460612, 7.043700981847325, 8.299363725465357), # 154
(7.6614773285236355, 6.034940689041495, 8.115502177012075, 9.282059239727378, 9.263412005587696, 5.184140672698471, 4.864046387177761, 5.558742242079636, 9.971157559180128, 4.972475020241754, 5.859396024994833, 6.997377694923482, 8.251242367856026), # 155
(7.598090966638081, 5.972310436935888, 8.070380131182526, 9.220656502066875, 9.209152380462648, 5.161129326379461, 4.8194539698327, 5.5360894886114185, 9.933803887530626, 4.934433987117773, 5.816729051136504, 6.949575798293822, 8.201778677307685), # 156
(7.533104573016862, 5.907895550643423, 8.023826220606818, 9.157367984088937, 9.153424206483685, 5.137262683685614, 4.773500947698219, 5.512318950692082, 9.894979296667389, 4.895134630428341, 5.772614912062549, 6.900249321603637, 8.150942360231976), # 157
(7.464680946405239, 5.840453120772258, 7.973591953902355, 9.089769581651243, 9.093681105870997, 5.11102447631711, 4.725106720927857, 5.485796952349372, 9.851662091599097, 4.8533659162911436, 5.7255957525389425, 6.847599564194339, 8.096485859415345), # 158
(7.382286766978402, 5.763065319599478, 7.906737818402988, 9.003977158788453, 9.015191309781628, 5.073689648007103, 4.668212763385716, 5.4472135327643825, 9.786427261222144, 4.802280994098745, 5.667416935618994, 6.781362523683108, 8.025427646920194), # 159
(7.284872094904309, 5.675096728540714, 7.821920957955888, 8.89857751040886, 8.916420131346795, 5.024341296047684, 4.602243748383784, 5.3955991895273465, 9.697425227228651, 4.741205651862893, 5.59725950860954, 6.700501948887847, 7.93642060889358), # 160
(7.17322205458596, 5.577120868080469, 7.720046971910309, 8.774572503756728, 8.798393124282113, 4.963577241570314, 4.527681446006876, 5.33160053310978, 9.585829766999018, 4.6706581931709374, 5.515741654599707, 6.605767468907571, 7.830374044819097), # 161
(7.048121770426357, 5.469711258703239, 7.602021459615496, 8.632964006076326, 8.662135842303204, 4.891995305706455, 4.445007626339809, 5.255864173983202, 9.452814657913637, 4.5911569216102315, 5.42348155667862, 6.497908712841293, 7.708197254180333), # 162
(6.9103563668284975, 5.353441420893524, 7.468750020420702, 8.474753884611934, 8.508673839125688, 4.810193309587572, 4.354704059467401, 5.169036722619125, 9.299553677352906, 4.503220140768125, 5.321097397935408, 6.3776753097880325, 7.570799536460879), # 163
(6.760710968195384, 5.228884875135821, 7.321138253675176, 8.300944006607818, 8.339032668465189, 4.718769074345129, 4.257252515474466, 5.071764789489069, 9.127220602697223, 4.407366154231968, 5.209207361459196, 6.245816888846803, 7.419090191144328), # 164
(6.599970698930017, 5.096615141914632, 7.160091758728169, 8.112536239308252, 8.154237884037324, 4.618320421110586, 4.153134764445822, 4.964694985064546, 8.93698921132698, 4.3041132655891134, 5.088429630339111, 6.10308307911662, 7.25397851771427), # 165
(6.428920683435397, 4.957205741714454, 6.9865161349289275, 7.910532449957501, 7.955315039557714, 4.509445171015408, 4.042832576466286, 4.848473919817077, 8.730033280622573, 4.193979778426912, 4.959382387664279, 5.950223509696501, 7.0763738156542955), # 166
(6.248346046114523, 4.811230195019787, 6.801316981626704, 7.695934505799843, 7.74328968874198, 4.392741145191058, 3.9268277216206746, 4.723748204218176, 8.5075265879644, 4.077483996332714, 4.822683816523827, 5.7879878096854585, 6.887185384447996), # 167
(6.059031911370395, 4.659262022315128, 6.605399898170748, 7.469744274079546, 7.519187385305742, 4.268806164768999, 3.805601969993804, 4.5911644487393595, 8.270642910732855, 3.955144222893872, 4.678952100006881, 5.617125608182511, 6.6873225235789615), # 168
(5.861763403606015, 4.501874744084979, 6.399670483910309, 7.232963622040883, 7.28403368296462, 4.138238050880695, 3.6796370916704917, 4.451369263852145, 8.020556026308338, 3.8274787616977366, 4.528805421202568, 5.438386534286672, 6.477694532530785), # 169
(5.657325647224384, 4.339641880813837, 6.185034338194635, 6.98659441692812, 7.038854135434233, 4.001634624657607, 3.549414856735553, 4.305009260028047, 7.7584397120712385, 3.6950059163316578, 4.372861963200016, 5.252520217096959, 6.259210710787055), # 170
(5.4465037666285, 4.173136952986201, 5.962397060372978, 6.731638525985535, 6.784674296430206, 3.8595937072311983, 3.4154170352738054, 4.152731047738583, 7.485467745401956, 3.5582439903829886, 4.211739909088348, 5.060276285712386, 6.032780357831365), # 171
(5.230082886221365, 4.002933481086569, 5.7326642497945866, 6.4690978164573965, 6.5225197196681535, 3.7127131197329337, 3.2781253973700655, 3.9951812374552707, 7.202813903680886, 3.41771128743908, 4.046057441956694, 4.862404369231971, 5.799312773147303), # 172
(5.00884813040598, 3.8296049855994423, 5.4967415058087115, 6.1999741555879755, 6.253415958863702, 3.5615906832942748, 3.1380217131091497, 3.8330064396496235, 6.911651964288422, 3.2739261110872815, 3.8764327448941778, 4.659654096754725, 5.5597172562184625), # 173
(4.783584623585344, 3.653724987009318, 5.2555344277646014, 5.9252694106215404, 5.978388567732466, 3.406824219046685, 2.9955877525758754, 3.6668532647931604, 6.613155704604964, 3.1274067649149466, 3.7034840009899277, 4.452775097379668, 5.314903106528433), # 174
(4.555077490162455, 3.4758670058006946, 5.009948615011508, 5.645985448802367, 5.698463099990069, 3.2490115481216284, 2.851305285855058, 3.497368323357396, 6.308498902010905, 2.9786715525094243, 3.5278293933330693, 4.242517000205814, 5.0657796235608075), # 175
(4.324111854540319, 3.296604562458073, 4.760889666898678, 5.363124137374725, 5.41466510935213, 3.0887504916505666, 2.705656083031515, 3.325198225813849, 5.998855333886642, 2.828238777458067, 3.35008710501273, 4.029629434332179, 4.813256106799174), # 176
(4.0914728411219325, 3.1165111774659513, 4.5092631827753635, 5.077687343582883, 5.128020149534273, 2.9266388707649633, 2.5591219141900625, 3.1509895826340326, 5.68539877761257, 2.6766267433482245, 3.1708753191180357, 3.8148620288577786, 4.5582418557271245), # 177
(3.8579455743102966, 2.9361603713088282, 4.255974761990814, 4.790676934671116, 4.8395537742521135, 2.7632745065962827, 2.4121845494155174, 2.9753890042894655, 5.3693030105690855, 2.52435375376725, 2.9908122187381125, 3.598964412881627, 4.301646169828252), # 178
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179
)
passenger_arriving_acc = (
(7, 4, 4, 3, 2, 1, 4, 2, 4, 2, 0, 0, 0, 7, 5, 8, 3, 7, 1, 3, 0, 1, 2, 1, 1, 0), # 0
(11, 11, 6, 6, 5, 2, 6, 7, 6, 3, 1, 0, 0, 13, 9, 12, 6, 9, 2, 8, 1, 2, 3, 1, 2, 0), # 1
(17, 15, 11, 12, 7, 3, 8, 11, 7, 4, 1, 0, 0, 24, 12, 18, 13, 16, 2, 11, 3, 3, 5, 1, 2, 0), # 2
(23, 18, 17, 19, 13, 4, 11, 14, 8, 6, 2, 0, 0, 31, 23, 26, 15, 20, 5, 11, 3, 5, 7, 1, 2, 0), # 3
(34, 23, 25, 22, 19, 5, 13, 16, 10, 6, 2, 0, 0, 37, 32, 31, 16, 25, 6, 13, 4, 6, 8, 1, 2, 0), # 4
(37, 28, 32, 29, 24, 7, 18, 19, 13, 8, 5, 0, 0, 46, 42, 34, 18, 32, 8, 14, 4, 9, 9, 2, 4, 0), # 5
(43, 32, 37, 34, 30, 9, 19, 22, 17, 9, 5, 2, 0, 53, 48, 36, 22, 36, 9, 17, 5, 12, 14, 2, 6, 0), # 6
(48, 40, 43, 38, 36, 9, 25, 26, 19, 10, 7, 2, 0, 62, 54, 38, 27, 39, 9, 18, 6, 15, 16, 4, 6, 0), # 7
(54, 43, 45, 49, 40, 11, 32, 30, 21, 11, 8, 2, 0, 66, 58, 42, 28, 43, 14, 19, 8, 17, 18, 8, 6, 0), # 8
(61, 48, 53, 54, 50, 11, 39, 32, 25, 13, 9, 3, 0, 74, 61, 46, 31, 51, 18, 20, 12, 21, 21, 10, 7, 0), # 9
(64, 52, 65, 60, 56, 15, 43, 32, 27, 14, 9, 3, 0, 89, 64, 55, 34, 51, 22, 22, 14, 25, 24, 12, 8, 0), # 10
(73, 63, 73, 68, 60, 18, 45, 32, 30, 16, 9, 4, 0, 95, 76, 62, 38, 58, 24, 27, 18, 28, 27, 14, 9, 0), # 11
(81, 66, 79, 77, 70, 20, 54, 34, 34, 17, 10, 5, 0, 101, 81, 69, 39, 63, 28, 30, 20, 32, 28, 14, 11, 0), # 12
(86, 77, 91, 84, 76, 23, 59, 38, 37, 19, 11, 8, 0, 117, 87, 77, 47, 71, 29, 32, 24, 34, 30, 16, 12, 0), # 13
(103, 89, 99, 98, 80, 25, 61, 43, 41, 19, 13, 9, 0, 128, 91, 86, 53, 81, 30, 34, 26, 38, 31, 17, 12, 0), # 14
(115, 100, 112, 106, 93, 27, 66, 46, 45, 19, 13, 9, 0, 144, 98, 88, 61, 87, 34, 38, 30, 41, 33, 18, 13, 0), # 15
(122, 105, 116, 113, 102, 28, 71, 50, 49, 23, 14, 10, 0, 155, 108, 92, 68, 95, 41, 43, 31, 44, 37, 18, 13, 0), # 16
(133, 112, 121, 119, 108, 34, 75, 51, 55, 23, 15, 11, 0, 164, 117, 98, 74, 102, 46, 45, 32, 45, 40, 18, 13, 0), # 17
(142, 124, 130, 122, 115, 38, 78, 53, 58, 25, 16, 13, 0, 176, 126, 104, 77, 109, 54, 49, 36, 50, 42, 20, 15, 0), # 18
(153, 139, 136, 130, 122, 44, 83, 59, 60, 26, 16, 14, 0, 187, 137, 107, 81, 118, 58, 55, 40, 54, 44, 23, 16, 0), # 19
(160, 150, 142, 140, 127, 48, 86, 61, 63, 28, 17, 14, 0, 194, 145, 115, 82, 129, 66, 61, 43, 58, 48, 26, 16, 0), # 20
(170, 159, 152, 151, 134, 51, 90, 64, 66, 29, 20, 16, 0, 204, 162, 127, 93, 135, 69, 63, 45, 63, 52, 28, 17, 0), # 21
(184, 167, 160, 162, 138, 57, 93, 67, 70, 30, 21, 16, 0, 215, 167, 133, 99, 150, 72, 64, 49, 68, 54, 29, 17, 0), # 22
(196, 184, 168, 176, 148, 59, 97, 69, 74, 33, 21, 17, 0, 226, 179, 140, 104, 159, 77, 66, 51, 69, 59, 31, 20, 0), # 23
(203, 196, 185, 192, 153, 62, 103, 73, 80, 34, 23, 17, 0, 239, 183, 145, 108, 173, 79, 69, 57, 74, 60, 32, 20, 0), # 24
(213, 207, 194, 199, 157, 68, 105, 74, 85, 37, 23, 20, 0, 244, 192, 153, 114, 181, 82, 73, 61, 77, 61, 36, 21, 0), # 25
(224, 214, 202, 207, 166, 73, 107, 79, 92, 40, 24, 21, 0, 254, 197, 164, 117, 192, 85, 80, 63, 80, 64, 39, 23, 0), # 26
(235, 222, 208, 214, 172, 78, 115, 79, 99, 40, 24, 21, 0, 265, 212, 172, 120, 201, 93, 85, 64, 84, 65, 40, 25, 0), # 27
(241, 237, 218, 229, 181, 80, 119, 84, 103, 44, 24, 21, 0, 281, 221, 179, 126, 208, 94, 91, 64, 91, 68, 40, 29, 0), # 28
(256, 240, 231, 238, 190, 86, 122, 87, 106, 45, 25, 21, 0, 287, 227, 187, 133, 221, 100, 96, 69, 96, 72, 40, 30, 0), # 29
(273, 252, 244, 245, 198, 89, 126, 90, 109, 46, 27, 22, 0, 301, 240, 190, 140, 232, 106, 102, 72, 102, 73, 42, 32, 0), # 30
(290, 262, 247, 254, 202, 92, 131, 92, 114, 49, 28, 23, 0, 313, 250, 194, 147, 244, 113, 107, 73, 105, 77, 43, 34, 0), # 31
(298, 272, 254, 262, 214, 93, 136, 96, 117, 49, 28, 26, 0, 321, 268, 201, 148, 257, 120, 113, 74, 108, 78, 44, 35, 0), # 32
(305, 277, 264, 270, 221, 97, 140, 104, 125, 54, 29, 26, 0, 329, 276, 206, 150, 261, 123, 119, 76, 112, 79, 47, 36, 0), # 33
(310, 287, 276, 281, 230, 104, 144, 108, 127, 55, 29, 27, 0, 338, 287, 212, 156, 272, 129, 124, 76, 113, 81, 49, 38, 0), # 34
(323, 298, 281, 289, 237, 108, 148, 112, 134, 57, 30, 27, 0, 351, 297, 217, 161, 283, 136, 127, 76, 114, 84, 49, 38, 0), # 35
(333, 310, 286, 296, 242, 113, 150, 118, 138, 59, 31, 30, 0, 361, 309, 232, 168, 294, 141, 133, 78, 116, 86, 49, 38, 0), # 36
(344, 321, 299, 305, 251, 117, 151, 119, 142, 61, 32, 31, 0, 374, 321, 238, 171, 301, 147, 138, 79, 120, 88, 51, 38, 0), # 37
(348, 328, 308, 310, 257, 120, 157, 120, 145, 63, 33, 32, 0, 387, 328, 242, 176, 315, 148, 142, 81, 121, 89, 52, 38, 0), # 38
(360, 336, 317, 321, 268, 124, 163, 128, 150, 68, 35, 33, 0, 393, 338, 248, 180, 326, 156, 148, 81, 129, 93, 56, 40, 0), # 39
(372, 350, 327, 330, 274, 126, 168, 128, 154, 70, 35, 35, 0, 403, 346, 253, 184, 333, 162, 151, 82, 132, 99, 57, 42, 0), # 40
(382, 363, 338, 340, 283, 131, 169, 133, 160, 74, 36, 35, 0, 414, 351, 260, 190, 341, 166, 155, 83, 136, 100, 58, 43, 0), # 41
(394, 372, 355, 349, 289, 137, 170, 136, 163, 77, 38, 35, 0, 427, 355, 267, 194, 345, 172, 158, 87, 138, 101, 60, 45, 0), # 42
(397, 386, 368, 355, 300, 142, 174, 139, 166, 79, 38, 38, 0, 440, 361, 275, 198, 351, 179, 167, 90, 140, 103, 63, 45, 0), # 43
(407, 398, 380, 363, 310, 145, 177, 149, 170, 81, 39, 39, 0, 448, 373, 285, 203, 360, 184, 173, 92, 145, 107, 65, 46, 0), # 44
(418, 409, 396, 371, 318, 147, 188, 154, 176, 82, 41, 41, 0, 458, 385, 292, 213, 368, 185, 179, 96, 149, 109, 67, 47, 0), # 45
(427, 419, 408, 385, 330, 152, 191, 156, 178, 83, 45, 41, 0, 470, 394, 300, 219, 381, 191, 182, 97, 153, 112, 70, 47, 0), # 46
(434, 427, 416, 389, 335, 154, 193, 158, 182, 87, 47, 41, 0, 487, 404, 309, 226, 390, 197, 185, 102, 157, 119, 75, 47, 0), # 47
(446, 435, 422, 403, 341, 155, 197, 160, 185, 87, 49, 41, 0, 506, 413, 316, 229, 397, 200, 189, 105, 160, 123, 76, 47, 0), # 48
(457, 443, 429, 411, 353, 160, 200, 162, 194, 88, 51, 41, 0, 520, 424, 324, 231, 401, 207, 192, 108, 167, 125, 77, 47, 0), # 49
(467, 453, 433, 418, 358, 163, 202, 163, 198, 90, 52, 41, 0, 534, 435, 327, 239, 406, 210, 199, 113, 170, 126, 78, 48, 0), # 50
(481, 464, 441, 432, 368, 166, 203, 165, 204, 91, 54, 41, 0, 546, 441, 329, 243, 413, 211, 204, 116, 175, 129, 79, 50, 0), # 51
(486, 480, 449, 442, 377, 172, 208, 172, 205, 94, 55, 43, 0, 560, 453, 333, 249, 421, 214, 207, 119, 180, 137, 81, 50, 0), # 52
(492, 489, 453, 455, 385, 174, 214, 176, 207, 95, 58, 45, 0, 573, 459, 339, 254, 436, 220, 211, 121, 185, 141, 81, 53, 0), # 53
(507, 504, 468, 467, 397, 176, 214, 179, 213, 95, 62, 46, 0, 583, 471, 347, 260, 441, 225, 215, 123, 191, 143, 83, 53, 0), # 54
(518, 512, 476, 473, 406, 180, 218, 180, 215, 99, 63, 47, 0, 586, 485, 352, 263, 448, 229, 219, 124, 192, 146, 86, 54, 0), # 55
(523, 522, 481, 485, 416, 183, 223, 185, 217, 100, 63, 47, 0, 596, 492, 363, 269, 456, 231, 225, 127, 193, 150, 92, 54, 0), # 56
(532, 533, 491, 498, 423, 187, 227, 187, 223, 103, 63, 48, 0, 607, 499, 372, 274, 463, 232, 231, 130, 194, 158, 93, 54, 0), # 57
(545, 545, 502, 504, 432, 188, 228, 192, 226, 107, 67, 48, 0, 621, 509, 381, 284, 473, 234, 237, 133, 197, 161, 94, 55, 0), # 58
(556, 556, 517, 513, 441, 193, 229, 195, 233, 110, 67, 50, 0, 632, 514, 388, 287, 479, 238, 240, 136, 199, 162, 95, 57, 0), # 59
(563, 568, 527, 524, 452, 197, 231, 200, 238, 110, 69, 50, 0, 637, 527, 401, 290, 490, 245, 246, 139, 201, 165, 97, 57, 0), # 60
(574, 573, 537, 536, 460, 198, 233, 200, 240, 111, 70, 50, 0, 641, 534, 405, 295, 503, 250, 249, 146, 204, 169, 99, 59, 0), # 61
(580, 577, 542, 546, 473, 199, 239, 203, 247, 112, 72, 52, 0, 650, 544, 408, 298, 511, 253, 255, 150, 212, 169, 99, 59, 0), # 62
(591, 588, 551, 551, 481, 202, 243, 205, 255, 116, 72, 53, 0, 662, 556, 419, 303, 519, 254, 260, 156, 219, 173, 100, 59, 0), # 63
(599, 599, 563, 558, 497, 205, 249, 209, 258, 117, 73, 55, 0, 676, 560, 425, 309, 526, 257, 264, 159, 221, 177, 101, 60, 0), # 64
(606, 610, 573, 568, 503, 210, 257, 210, 261, 119, 74, 57, 0, 688, 567, 433, 312, 537, 263, 268, 160, 226, 179, 102, 60, 0), # 65
(621, 616, 578, 579, 513, 212, 261, 217, 263, 120, 76, 58, 0, 702, 578, 440, 316, 546, 269, 272, 162, 228, 184, 106, 60, 0), # 66
(625, 623, 582, 589, 518, 216, 261, 221, 267, 123, 78, 58, 0, 716, 583, 451, 320, 552, 273, 277, 166, 231, 187, 108, 62, 0), # 67
(637, 633, 587, 597, 522, 217, 262, 226, 276, 125, 79, 59, 0, 729, 595, 455, 327, 560, 277, 281, 168, 234, 190, 110, 63, 0), # 68
(645, 642, 598, 605, 532, 221, 265, 231, 279, 126, 82, 60, 0, 740, 603, 463, 334, 568, 280, 282, 169, 235, 193, 113, 63, 0), # 69
(654, 648, 601, 616, 541, 224, 270, 233, 281, 129, 86, 61, 0, 751, 608, 470, 339, 577, 285, 286, 173, 240, 195, 113, 63, 0), # 70
(658, 655, 606, 621, 547, 229, 271, 236, 281, 133, 87, 61, 0, 760, 617, 479, 342, 587, 290, 291, 175, 245, 196, 116, 64, 0), # 71
(669, 661, 614, 632, 559, 232, 276, 237, 287, 137, 88, 63, 0, 776, 626, 483, 349, 595, 294, 300, 177, 250, 197, 118, 66, 0), # 72
(679, 671, 624, 637, 570, 237, 279, 240, 291, 137, 90, 64, 0, 791, 629, 491, 355, 603, 296, 306, 178, 254, 198, 118, 68, 0), # 73
(693, 679, 633, 645, 577, 243, 280, 241, 293, 138, 92, 64, 0, 804, 633, 495, 362, 608, 299, 315, 186, 259, 202, 119, 68, 0), # 74
(703, 690, 644, 654, 587, 244, 283, 243, 298, 139, 93, 64, 0, 818, 646, 502, 366, 616, 303, 319, 188, 266, 204, 122, 68, 0), # 75
(716, 700, 654, 666, 594, 250, 286, 246, 302, 142, 93, 65, 0, 830, 658, 511, 374, 620, 306, 322, 194, 268, 207, 124, 69, 0), # 76
(725, 707, 664, 673, 604, 255, 288, 250, 307, 144, 93, 67, 0, 841, 663, 517, 382, 632, 311, 328, 195, 271, 211, 125, 70, 0), # 77
(730, 714, 672, 678, 616, 257, 293, 251, 311, 145, 93, 68, 0, 849, 676, 523, 385, 638, 313, 332, 198, 274, 221, 128, 70, 0), # 78
(743, 725, 682, 681, 625, 261, 298, 254, 314, 145, 93, 68, 0, 859, 688, 531, 392, 643, 314, 336, 205, 279, 225, 128, 73, 0), # 79
(752, 734, 693, 692, 633, 262, 300, 255, 318, 149, 95, 69, 0, 869, 695, 533, 399, 651, 318, 339, 206, 282, 227, 130, 73, 0), # 80
(765, 738, 698, 703, 636, 265, 306, 259, 323, 149, 98, 69, 0, 877, 705, 536, 408, 655, 325, 342, 209, 286, 232, 130, 74, 0), # 81
(778, 747, 706, 707, 641, 268, 311, 262, 327, 150, 100, 70, 0, 889, 710, 543, 410, 662, 330, 342, 209, 288, 232, 132, 75, 0), # 82
(785, 756, 710, 712, 646, 270, 312, 264, 330, 151, 101, 70, 0, 899, 717, 548, 412, 671, 333, 343, 211, 291, 237, 133, 76, 0), # 83
(797, 762, 719, 719, 653, 276, 316, 266, 334, 152, 102, 70, 0, 909, 725, 551, 415, 677, 338, 347, 214, 292, 241, 135, 76, 0), # 84
(807, 772, 722, 726, 663, 280, 321, 269, 335, 153, 103, 72, 0, 918, 738, 554, 420, 682, 343, 350, 218, 297, 244, 136, 76, 0), # 85
(814, 782, 735, 737, 671, 283, 323, 271, 336, 156, 104, 72, 0, 923, 749, 561, 422, 688, 347, 355, 219, 300, 247, 137, 77, 0), # 86
(827, 792, 748, 749, 686, 287, 331, 273, 342, 156, 104, 73, 0, 932, 756, 567, 424, 697, 354, 363, 220, 306, 253, 139, 78, 0), # 87
(833, 802, 755, 761, 690, 291, 333, 275, 345, 160, 107, 74, 0, 943, 763, 576, 424, 699, 361, 367, 222, 310, 256, 139, 79, 0), # 88
(847, 812, 762, 772, 697, 293, 334, 276, 347, 161, 109, 75, 0, 949, 771, 581, 427, 708, 365, 372, 222, 314, 257, 142, 81, 0), # 89
(857, 818, 768, 785, 704, 295, 337, 278, 352, 162, 111, 76, 0, 960, 783, 588, 433, 717, 369, 377, 224, 315, 261, 142, 81, 0), # 90
(871, 826, 776, 792, 709, 298, 343, 279, 356, 165, 112, 76, 0, 972, 788, 592, 437, 726, 370, 382, 228, 315, 266, 145, 81, 0), # 91
(885, 833, 783, 799, 719, 304, 348, 280, 358, 166, 116, 76, 0, 982, 794, 597, 442, 737, 375, 384, 228, 320, 270, 145, 81, 0), # 92
(898, 843, 795, 806, 727, 307, 351, 283, 363, 167, 116, 77, 0, 996, 803, 605, 444, 749, 380, 387, 230, 323, 273, 150, 81, 0), # 93
(902, 847, 804, 813, 736, 310, 352, 286, 364, 168, 118, 77, 0, 1008, 812, 608, 449, 759, 384, 390, 233, 325, 275, 152, 81, 0), # 94
(907, 856, 816, 823, 751, 314, 356, 292, 366, 170, 120, 77, 0, 1021, 823, 608, 456, 766, 387, 391, 238, 328, 277, 152, 82, 0), # 95
(909, 862, 829, 832, 756, 316, 360, 297, 368, 170, 123, 77, 0, 1033, 831, 611, 462, 773, 389, 394, 242, 331, 282, 155, 82, 0), # 96
(917, 868, 834, 838, 764, 320, 361, 299, 370, 170, 124, 78, 0, 1042, 838, 615, 466, 780, 390, 398, 243, 333, 285, 156, 82, 0), # 97
(929, 880, 842, 845, 769, 322, 365, 304, 378, 170, 126, 79, 0, 1052, 847, 620, 471, 789, 390, 402, 245, 339, 288, 157, 83, 0), # 98
(937, 889, 852, 851, 782, 329, 370, 308, 383, 172, 127, 82, 0, 1064, 854, 627, 477, 795, 392, 405, 247, 347, 291, 161, 83, 0), # 99
(947, 901, 863, 855, 794, 332, 373, 312, 386, 174, 128, 82, 0, 1072, 862, 631, 480, 800, 399, 407, 252, 352, 292, 162, 83, 0), # 100
(956, 909, 869, 859, 800, 333, 377, 315, 389, 177, 129, 83, 0, 1083, 871, 635, 490, 811, 401, 408, 254, 355, 296, 164, 83, 0), # 101
(967, 917, 879, 869, 804, 338, 380, 315, 394, 179, 129, 83, 0, 1096, 879, 638, 497, 821, 404, 409, 256, 361, 299, 166, 84, 0), # 102
(973, 926, 888, 876, 809, 343, 382, 317, 399, 179, 131, 85, 0, 1110, 890, 643, 500, 829, 404, 411, 259, 366, 300, 166, 86, 0), # 103
(985, 934, 895, 881, 817, 347, 384, 319, 402, 182, 131, 85, 0, 1119, 896, 648, 503, 836, 408, 411, 262, 369, 303, 168, 87, 0), # 104
(994, 940, 903, 895, 823, 351, 386, 321, 403, 183, 131, 86, 0, 1125, 899, 654, 505, 841, 412, 417, 264, 370, 307, 170, 90, 0), # 105
(1002, 953, 912, 902, 835, 357, 391, 325, 408, 184, 134, 86, 0, 1138, 908, 661, 510, 847, 415, 418, 267, 373, 308, 171, 90, 0), # 106
(1010, 961, 925, 910, 846, 357, 392, 329, 414, 185, 134, 86, 0, 1147, 918, 665, 516, 852, 417, 421, 268, 374, 309, 171, 90, 0), # 107
(1020, 969, 935, 923, 855, 362, 396, 330, 419, 186, 135, 86, 0, 1156, 926, 669, 523, 862, 421, 421, 270, 377, 313, 171, 91, 0), # 108
(1027, 977, 940, 930, 866, 369, 401, 334, 426, 187, 135, 87, 0, 1170, 934, 677, 529, 872, 424, 422, 271, 380, 317, 172, 92, 0), # 109
(1041, 985, 948, 937, 874, 371, 405, 335, 430, 189, 135, 87, 0, 1180, 941, 679, 531, 876, 430, 424, 273, 382, 319, 175, 92, 0), # 110
(1048, 998, 959, 941, 884, 373, 405, 335, 432, 190, 135, 87, 0, 1193, 946, 685, 534, 879, 430, 428, 274, 382, 323, 177, 93, 0), # 111
(1061, 1003, 970, 949, 889, 377, 406, 337, 434, 192, 137, 87, 0, 1200, 952, 695, 539, 886, 432, 431, 276, 384, 325, 177, 94, 0), # 112
(1072, 1011, 976, 955, 893, 383, 409, 339, 440, 192, 138, 88, 0, 1202, 965, 700, 540, 899, 436, 436, 278, 386, 326, 178, 95, 0), # 113
(1081, 1020, 985, 963, 901, 389, 411, 342, 444, 194, 139, 90, 0, 1209, 969, 709, 548, 906, 438, 438, 279, 389, 326, 181, 95, 0), # 114
(1093, 1030, 994, 971, 910, 393, 411, 342, 448, 194, 139, 90, 0, 1215, 977, 710, 551, 913, 442, 439, 281, 392, 328, 183, 96, 0), # 115
(1101, 1040, 1001, 981, 915, 400, 411, 345, 449, 195, 141, 91, 0, 1229, 984, 712, 556, 916, 446, 445, 282, 395, 331, 184, 97, 0), # 116
(1109, 1053, 1006, 991, 924, 400, 414, 345, 454, 196, 141, 92, 0, 1239, 989, 718, 559, 921, 447, 445, 283, 399, 334, 186, 97, 0), # 117
(1118, 1059, 1012, 1004, 939, 403, 414, 352, 457, 197, 143, 92, 0, 1246, 999, 723, 564, 927, 447, 447, 283, 401, 336, 187, 99, 0), # 118
(1130, 1067, 1021, 1013, 948, 408, 417, 355, 459, 198, 143, 95, 0, 1256, 1005, 726, 565, 935, 448, 451, 289, 403, 336, 188, 99, 0), # 119
(1138, 1074, 1030, 1020, 959, 411, 423, 356, 465, 200, 143, 96, 0, 1262, 1009, 730, 573, 938, 449, 454, 290, 404, 338, 188, 100, 0), # 120
(1146, 1080, 1041, 1026, 969, 417, 427, 357, 469, 203, 143, 98, 0, 1267, 1018, 736, 580, 946, 451, 457, 293, 409, 342, 188, 101, 0), # 121
(1156, 1084, 1049, 1037, 977, 422, 433, 364, 471, 203, 144, 98, 0, 1272, 1025, 743, 583, 954, 456, 460, 298, 411, 345, 189, 101, 0), # 122
(1160, 1095, 1057, 1039, 987, 424, 435, 366, 477, 204, 146, 98, 0, 1279, 1035, 751, 587, 960, 462, 464, 301, 414, 351, 190, 101, 0), # 123
(1169, 1099, 1067, 1050, 993, 428, 437, 366, 479, 206, 146, 98, 0, 1289, 1045, 757, 589, 970, 469, 466, 302, 417, 353, 191, 101, 0), # 124
(1181, 1109, 1077, 1053, 1001, 433, 440, 368, 482, 208, 146, 101, 0, 1297, 1053, 760, 591, 979, 472, 469, 303, 421, 358, 191, 101, 0), # 125
(1186, 1113, 1093, 1059, 1012, 436, 441, 370, 486, 209, 146, 102, 0, 1308, 1061, 767, 594, 989, 474, 478, 304, 424, 359, 191, 101, 0), # 126
(1201, 1121, 1098, 1067, 1019, 438, 442, 374, 489, 210, 148, 102, 0, 1317, 1068, 769, 601, 996, 477, 480, 306, 427, 360, 192, 102, 0), # 127
(1207, 1130, 1109, 1074, 1028, 446, 443, 376, 494, 212, 149, 102, 0, 1330, 1074, 777, 607, 1001, 478, 481, 309, 432, 364, 193, 102, 0), # 128
(1213, 1136, 1113, 1084, 1036, 453, 443, 378, 497, 212, 151, 102, 0, 1339, 1084, 780, 610, 1005, 480, 484, 310, 434, 367, 196, 104, 0), # 129
(1231, 1141, 1121, 1094, 1043, 456, 446, 383, 498, 214, 152, 102, 0, 1351, 1091, 786, 615, 1009, 482, 488, 312, 438, 369, 197, 104, 0), # 130
(1237, 1151, 1129, 1106, 1052, 459, 448, 385, 502, 216, 155, 103, 0, 1360, 1101, 791, 616, 1013, 484, 492, 315, 443, 370, 201, 106, 0), # 131
(1247, 1157, 1135, 1111, 1060, 462, 454, 386, 507, 219, 156, 103, 0, 1372, 1111, 794, 618, 1024, 485, 496, 316, 448, 373, 201, 106, 0), # 132
(1258, 1164, 1143, 1114, 1070, 466, 456, 388, 511, 220, 157, 104, 0, 1383, 1120, 798, 619, 1029, 489, 499, 318, 451, 377, 203, 108, 0), # 133
(1264, 1174, 1148, 1121, 1078, 468, 458, 391, 512, 223, 159, 105, 0, 1392, 1129, 801, 624, 1035, 494, 502, 320, 455, 378, 205, 108, 0), # 134
(1272, 1180, 1155, 1128, 1087, 470, 460, 395, 516, 223, 159, 105, 0, 1404, 1133, 809, 631, 1043, 497, 505, 323, 459, 379, 207, 108, 0), # 135
(1279, 1188, 1157, 1139, 1092, 471, 465, 397, 524, 223, 160, 107, 0, 1409, 1138, 818, 633, 1048, 497, 509, 327, 466, 381, 209, 111, 0), # 136
(1289, 1197, 1163, 1145, 1099, 476, 467, 402, 525, 225, 161, 108, 0, 1416, 1143, 821, 636, 1063, 497, 512, 327, 469, 384, 210, 112, 0), # 137
(1296, 1204, 1170, 1150, 1108, 480, 471, 403, 527, 225, 163, 108, 0, 1420, 1147, 829, 639, 1069, 502, 520, 330, 473, 388, 213, 113, 0), # 138
(1307, 1209, 1176, 1156, 1113, 483, 475, 406, 528, 225, 164, 108, 0, 1431, 1154, 834, 643, 1073, 503, 523, 331, 477, 390, 214, 116, 0), # 139
(1324, 1218, 1186, 1164, 1116, 486, 478, 407, 531, 226, 165, 108, 0, 1441, 1158, 837, 647, 1081, 510, 527, 332, 481, 391, 215, 118, 0), # 140
(1333, 1224, 1194, 1165, 1122, 487, 479, 407, 534, 228, 168, 108, 0, 1448, 1164, 841, 651, 1087, 512, 529, 332, 481, 393, 218, 118, 0), # 141
(1340, 1230, 1203, 1173, 1135, 491, 481, 413, 539, 230, 169, 108, 0, 1455, 1173, 847, 654, 1098, 517, 534, 334, 487, 395, 218, 118, 0), # 142
(1344, 1236, 1212, 1183, 1142, 494, 483, 413, 540, 230, 171, 108, 0, 1461, 1177, 853, 657, 1101, 519, 536, 338, 488, 397, 218, 120, 0), # 143
(1348, 1242, 1227, 1191, 1150, 499, 486, 415, 544, 230, 173, 110, 0, 1467, 1187, 856, 659, 1108, 521, 537, 339, 490, 400, 221, 120, 0), # 144
(1354, 1247, 1233, 1197, 1161, 502, 489, 415, 546, 231, 174, 111, 0, 1476, 1191, 859, 662, 1114, 523, 538, 340, 490, 403, 222, 120, 0), # 145
(1364, 1252, 1238, 1207, 1167, 504, 490, 416, 548, 232, 175, 111, 0, 1487, 1195, 866, 666, 1123, 525, 539, 340, 498, 406, 225, 120, 0), # 146
(1370, 1257, 1244, 1212, 1173, 506, 493, 418, 550, 233, 177, 112, 0, 1497, 1202, 875, 669, 1131, 527, 541, 343, 501, 408, 226, 120, 0), # 147
(1377, 1261, 1255, 1222, 1178, 507, 495, 420, 552, 233, 177, 112, 0, 1508, 1212, 877, 675, 1137, 529, 542, 346, 507, 410, 226, 120, 0), # 148
(1380, 1267, 1261, 1230, 1184, 510, 498, 425, 553, 233, 178, 112, 0, 1516, 1221, 885, 683, 1143, 536, 544, 347, 509, 410, 229, 122, 0), # 149
(1390, 1275, 1274, 1240, 1186, 513, 501, 427, 558, 234, 181, 112, 0, 1521, 1224, 890, 688, 1149, 537, 545, 350, 513, 410, 231, 122, 0), # 150
(1397, 1277, 1282, 1252, 1193, 518, 506, 431, 560, 238, 182, 113, 0, 1529, 1230, 897, 689, 1157, 541, 545, 353, 515, 410, 231, 122, 0), # 151
(1407, 1284, 1288, 1258, 1200, 519, 506, 436, 561, 240, 182, 115, 0, 1539, 1234, 902, 692, 1165, 545, 547, 357, 516, 412, 234, 122, 0), # 152
(1411, 1293, 1295, 1259, 1210, 523, 508, 439, 565, 241, 182, 116, 0, 1551, 1237, 908, 694, 1170, 548, 552, 358, 519, 419, 234, 122, 0), # 153
(1418, 1301, 1305, 1265, 1214, 524, 511, 441, 571, 244, 183, 117, 0, 1558, 1244, 909, 697, 1180, 553, 553, 360, 522, 423, 237, 122, 0), # 154
(1425, 1307, 1311, 1272, 1217, 530, 514, 444, 574, 246, 184, 118, 0, 1565, 1252, 914, 701, 1185, 556, 553, 361, 525, 424, 238, 122, 0), # 155
(1431, 1312, 1318, 1275, 1222, 534, 515, 449, 578, 249, 184, 118, 0, 1574, 1263, 915, 707, 1196, 561, 557, 364, 528, 426, 241, 123, 0), # 156
(1442, 1317, 1324, 1290, 1231, 538, 516, 450, 581, 249, 185, 118, 0, 1580, 1267, 922, 711, 1210, 568, 561, 365, 531, 428, 243, 123, 0), # 157
(1453, 1321, 1329, 1294, 1233, 543, 518, 451, 587, 249, 185, 118, 0, 1591, 1272, 928, 717, 1214, 570, 563, 369, 533, 430, 244, 123, 0), # 158
(1462, 1323, 1340, 1301, 1236, 543, 521, 452, 587, 249, 186, 118, 0, 1595, 1276, 934, 718, 1220, 571, 567, 371, 534, 434, 244, 123, 0), # 159
(1472, 1332, 1347, 1306, 1243, 547, 525, 452, 591, 252, 186, 118, 0, 1599, 1280, 940, 718, 1225, 576, 569, 372, 539, 438, 244, 125, 0), # 160
(1480, 1344, 1358, 1318, 1247, 550, 527, 457, 592, 254, 186, 118, 0, 1606, 1281, 943, 723, 1234, 579, 570, 374, 542, 439, 246, 125, 0), # 161
(1483, 1348, 1364, 1325, 1250, 553, 529, 457, 593, 255, 186, 118, 0, 1615, 1286, 945, 725, 1238, 580, 572, 376, 544, 441, 246, 125, 0), # 162
(1496, 1355, 1371, 1335, 1258, 556, 530, 463, 597, 255, 186, 118, 0, 1624, 1289, 949, 726, 1244, 581, 574, 377, 551, 442, 248, 125, 0), # 163
(1508, 1360, 1373, 1340, 1265, 560, 531, 464, 600, 256, 188, 119, 0, 1632, 1292, 956, 729, 1252, 582, 576, 379, 553, 446, 248, 125, 0), # 164
(1512, 1366, 1379, 1348, 1269, 561, 535, 467, 602, 257, 189, 120, 0, 1641, 1295, 958, 731, 1261, 586, 577, 379, 557, 450, 249, 126, 0), # 165
(1521, 1370, 1382, 1353, 1275, 562, 537, 471, 603, 258, 189, 120, 0, 1651, 1298, 962, 734, 1269, 586, 577, 380, 561, 453, 251, 128, 0), # 166
(1525, 1373, 1390, 1355, 1284, 563, 539, 472, 606, 258, 190, 120, 0, 1656, 1301, 966, 737, 1276, 589, 580, 381, 563, 454, 255, 128, 0), # 167
(1532, 1376, 1399, 1364, 1286, 568, 544, 473, 608, 259, 190, 120, 0, 1662, 1307, 968, 739, 1282, 592, 581, 383, 565, 455, 256, 128, 0), # 168
(1535, 1380, 1405, 1368, 1290, 573, 545, 475, 612, 259, 191, 120, 0, 1670, 1315, 971, 743, 1287, 594, 583, 384, 569, 456, 258, 128, 0), # 169
(1540, 1385, 1408, 1373, 1292, 578, 547, 475, 613, 261, 192, 121, 0, 1674, 1318, 976, 745, 1288, 594, 585, 387, 571, 457, 258, 129, 0), # 170
(1548, 1389, 1410, 1381, 1296, 581, 550, 477, 617, 262, 193, 121, 0, 1681, 1324, 979, 748, 1294, 594, 585, 389, 574, 458, 258, 129, 0), # 171
(1553, 1393, 1418, 1385, 1301, 581, 553, 477, 623, 262, 193, 122, 0, 1685, 1332, 981, 750, 1296, 595, 586, 390, 577, 459, 259, 130, 0), # 172
(1559, 1395, 1420, 1390, 1304, 581, 554, 478, 626, 263, 193, 122, 0, 1692, 1338, 983, 756, 1299, 599, 587, 392, 578, 459, 259, 130, 0), # 173
(1561, 1404, 1422, 1395, 1307, 583, 555, 479, 628, 265, 193, 122, 0, 1697, 1342, 985, 756, 1302, 601, 588, 392, 581, 460, 260, 130, 0), # 174
(1568, 1410, 1425, 1397, 1312, 586, 555, 482, 629, 266, 193, 122, 0, 1699, 1345, 988, 760, 1307, 604, 591, 392, 585, 463, 260, 130, 0), # 175
(1574, 1414, 1432, 1398, 1316, 589, 556, 483, 629, 266, 194, 122, 0, 1704, 1349, 991, 762, 1311, 605, 592, 392, 585, 466, 260, 130, 0), # 176
(1578, 1415, 1436, 1404, 1318, 590, 556, 483, 632, 267, 194, 123, 0, 1709, 1351, 994, 764, 1319, 606, 593, 393, 588, 467, 261, 132, 0), # 177
(1584, 1417, 1441, 1405, 1319, 591, 557, 483, 634, 268, 195, 123, 0, 1713, 1351, 998, 765, 1323, 606, 594, 394, 592, 470, 261, 132, 0), # 178
(1584, 1417, 1441, 1405, 1319, 591, 557, 483, 634, 268, 195, 123, 0, 1713, 1351, 998, 765, 1323, 606, 594, 394, 592, 470, 261, 132, 0), # 179
)
passenger_arriving_rate = (
(5.020865578371768, 5.064847846385402, 4.342736024677089, 4.661000830397574, 3.7031237384064077, 1.8308820436884476, 2.0730178076869574, 1.938823405408093, 2.030033020722669, 0.9895037538805926, 0.7008775273142672, 0.4081595898588478, 0.0, 5.083880212578363, 4.489755488447325, 3.5043876365713356, 2.968511261641777, 4.060066041445338, 2.7143527675713304, 2.0730178076869574, 1.3077728883488913, 1.8515618692032039, 1.5536669434658585, 0.8685472049354179, 0.4604407133077639, 0.0), # 0
(5.354327152019974, 5.399222302966028, 4.629455492775127, 4.968858189957462, 3.948326891649491, 1.9518237573581576, 2.209734470631847, 2.066464051210712, 2.164081775444303, 1.0547451730692876, 0.7471826893260219, 0.4351013884011963, 0.0, 5.419791647439855, 4.786115272413158, 3.73591344663011, 3.164235519207862, 4.328163550888606, 2.8930496716949965, 2.209734470631847, 1.3941598266843982, 1.9741634458247455, 1.6562860633191545, 0.9258910985550255, 0.49083839117872996, 0.0), # 1
(5.686723008979731, 5.732269739983398, 4.915035237956178, 5.275490778498595, 4.192641982499829, 2.072282983465593, 2.345909253980352, 2.193593853293508, 2.297595602292516, 1.1197284437551367, 0.7933038581293855, 0.46193605433775464, 0.0, 5.75436482820969, 5.0812965977153, 3.9665192906469278, 3.3591853312654094, 4.595191204585032, 3.0710313946109116, 2.345909253980352, 1.480202131046852, 2.0963209912499146, 1.758496926166199, 0.9830070475912357, 0.5211154309075817, 0.0), # 2
(6.016757793146562, 6.062668793441743, 5.198342391099879, 5.579682305649055, 4.435107784001268, 2.191782029841316, 2.4810018208239777, 2.3197088156227115, 2.430045053640364, 1.1841956746065454, 0.8390580686378972, 0.4885571404108718, 0.0, 6.086272806254225, 5.374128544519589, 4.195290343189486, 3.5525870238196355, 4.860090107280728, 3.247592341871796, 2.4810018208239777, 1.5655585927437972, 2.217553892000634, 1.8598941018830188, 1.0396684782199759, 0.551151708494704, 0.0), # 3
(6.343136148415981, 6.389098099345293, 5.478244083085864, 5.880216481036927, 4.674763069197661, 2.3098432043158894, 2.6144718342542292, 2.444304942164548, 2.560900681860902, 1.24788897429192, 0.8842623557650959, 0.514858199362897, 0.0, 6.414188632939817, 5.6634401929918665, 4.42131177882548, 3.743666922875759, 5.121801363721804, 3.422026919030367, 2.6144718342542292, 1.6498880030827783, 2.3373815345988307, 1.9600721603456428, 1.095648816617173, 0.5808270999404813, 0.0), # 4
(6.66456271868351, 6.710236293698289, 5.753607444793765, 6.175877014290295, 4.910646611132853, 2.4259888147198754, 2.745778957362612, 2.566878236885247, 2.689633039327186, 1.310550451479666, 0.9287337544245222, 0.5407327839361791, 0.0, 6.736785359632827, 5.948060623297969, 4.64366877212261, 3.9316513544389973, 5.379266078654372, 3.593629531639346, 2.745778957362612, 1.7328491533713395, 2.4553233055664263, 2.058625671430099, 1.1507214889587531, 0.6100214812452991, 0.0), # 5
(6.979742147844666, 7.024762012504959, 6.023299607103222, 6.465447615037239, 5.141797182850695, 2.5397411688838374, 2.8743828532406313, 2.686924703751037, 2.8157126784122717, 1.3719222148381898, 0.9722892995297139, 0.5660744468730674, 0.0, 7.052736037699606, 6.22681891560374, 4.8614464976485685, 4.115766644514569, 5.631425356824543, 3.761694585251452, 2.8743828532406313, 1.8141008349170267, 2.5708985914253475, 2.1551492050124135, 1.2046599214206444, 0.6386147284095418, 0.0), # 6
(7.2873790797949685, 7.331353891769537, 6.286187700893863, 6.747711992905847, 5.367253557395036, 2.650622574638337, 2.9997431849797924, 2.8039403467281465, 2.9386101514892147, 1.4317463730358968, 1.0147460259942116, 0.5907767409159108, 0.0, 7.360713718506519, 6.498544150075018, 5.073730129971057, 4.2952391191076895, 5.877220302978429, 3.9255164854194056, 2.9997431849797924, 1.8933018390273837, 2.683626778697518, 2.249237330968616, 1.2572375401787725, 0.6664867174335943, 0.0), # 7
(7.586178158429934, 7.628690567496257, 6.54113885704533, 7.021453857524196, 5.586054507809724, 2.7581553398139356, 3.1213196156715988, 2.917421169782802, 3.0577960109310682, 1.4897650347411937, 1.0559209687315536, 0.6147332188070586, 0.0, 7.659391453419917, 6.762065406877643, 5.279604843657768, 4.469295104223581, 6.1155920218621365, 4.084389637695923, 3.1213196156715988, 1.970110957009954, 2.793027253904862, 2.3404846191747324, 1.3082277714090662, 0.6935173243178416, 0.0), # 8
(7.874844027645085, 7.915450675689353, 6.787020206437253, 7.285456918520376, 5.797238807138606, 2.861861772241199, 3.23857180840756, 3.0268631768812346, 3.1727408091108913, 1.5457203086224858, 1.0956311626552797, 0.6378374332888596, 0.0, 7.947442293806162, 7.016211766177453, 5.478155813276398, 4.637160925867456, 6.345481618221783, 4.237608447633728, 3.23857180840756, 2.044186980172285, 2.898619403569303, 2.4284856395067926, 1.3574040412874508, 0.7195864250626686, 0.0), # 9
(8.152081331335932, 8.190312852353056, 7.022698879949271, 7.538504885522466, 5.999845228425533, 2.961264179750688, 3.3509594262791773, 3.1317623719896712, 3.282915098401738, 1.599354303348179, 1.133693642678929, 0.6599829371036627, 0.0, 8.22353929103161, 7.259812308140289, 5.668468213394645, 4.798062910044536, 6.565830196803476, 4.384467320785539, 3.3509594262791773, 2.11518869982192, 2.9999226142127666, 2.5128349618408223, 1.4045397759898541, 0.7445738956684597, 0.0), # 10
(8.416594713398005, 8.451955733491605, 7.247042008461013, 7.779381468158547, 6.192912544714355, 3.055884870172965, 3.457942132377958, 3.2316147590743394, 3.3877894311766643, 1.6504091275866801, 1.1699254437160416, 0.6810632829938176, 0.0, 8.486355496462611, 7.491696112931993, 5.849627218580208, 4.951227382760039, 6.775578862353329, 4.524260662704076, 3.457942132377958, 2.1827749072664036, 3.0964562723571776, 2.5931271560528497, 1.4494084016922026, 0.7683596121356006, 0.0), # 11
(8.667088817726812, 8.699057955109222, 7.458916722852117, 8.006870376056709, 6.375479529048918, 3.1452461513385908, 3.5589795897954057, 3.325916342101467, 3.486834359808726, 1.6986268900063934, 1.2041436006801558, 0.7009720237016724, 0.0, 8.734563961465534, 7.710692260718395, 6.020718003400779, 5.095880670019179, 6.973668719617452, 4.656282878942054, 3.5589795897954057, 2.246604393813279, 3.187739764524459, 2.6689567920189035, 1.4917833445704234, 0.7908234504644749, 0.0), # 12
(8.902268288217876, 8.93029815321015, 7.657190154002218, 8.219755318845033, 6.546584954473067, 3.2288703310781304, 3.653531461623028, 3.414163125037284, 3.579520436670977, 1.7437496992757264, 1.2361651484848115, 0.7196027119695768, 0.0, 8.966837737406735, 7.915629831665344, 6.180825742424058, 5.2312490978271775, 7.159040873341954, 4.7798283750521975, 3.653531461623028, 2.306335950770093, 3.2732924772365335, 2.7399184396150114, 1.5314380308004438, 0.8118452866554684, 0.0), # 13
(9.120837768766716, 9.144354963798623, 7.840729432790956, 8.416820006151594, 6.705267594030659, 3.306279717222145, 3.7410574109523305, 3.4958511118480193, 3.6653182141364735, 1.785519664063084, 1.2658071220435476, 0.7368489005398801, 0.0, 9.181849875652563, 8.10533790593868, 6.329035610217737, 5.3565589921892505, 7.330636428272947, 4.894191556587227, 3.7410574109523305, 2.3616283694443894, 3.3526337970153297, 2.8056066687171985, 1.5681458865581912, 0.8313049967089657, 0.0), # 14
(9.321501903268855, 9.339907022878865, 8.008401690097953, 8.59684814760449, 6.850566220765538, 3.376996617601199, 3.821017100874813, 3.5704763064998986, 3.743698244578273, 1.823678893036873, 1.2928865562699035, 0.752604142154931, 0.0, 9.37827342756938, 8.27864556370424, 6.464432781349516, 5.471036679110618, 7.487396489156546, 4.998666829099858, 3.821017100874813, 2.4121404411437135, 3.425283110382769, 2.865616049201497, 1.6016803380195905, 0.8490824566253515, 0.0), # 15
(9.5029653356198, 9.51563296645512, 8.159074056802854, 8.758623452831788, 6.981519607721555, 3.4405433400458514, 3.892870194481988, 3.6375347129591504, 3.8141310803694286, 1.8579694948654994, 1.3172204860774188, 0.7667619895570784, 0.0, 9.554781444523545, 8.434381885127861, 6.586102430387094, 5.5739084845964975, 7.628262160738857, 5.092548598142811, 3.892870194481988, 2.4575309571756083, 3.4907598038607777, 2.9195411509439295, 1.6318148113605708, 0.8650575424050111, 0.0), # 16
(9.663932709715075, 9.670211430531618, 8.291613663785293, 8.900929631461583, 7.097166527942559, 3.4964421923866666, 3.9560763548653552, 3.6965223351920073, 3.8760872738829946, 1.8881335782173672, 1.3386259463796333, 0.7792159954886714, 0.0, 9.710046977881415, 8.571375950375383, 6.693129731898166, 5.6644007346521, 7.752174547765989, 5.17513126926881, 3.9560763548653552, 2.4974587088476192, 3.5485832639712793, 2.9669765438205284, 1.6583227327570589, 0.8791101300483289, 0.0), # 17
(9.803108669450204, 9.802321051112584, 8.404887641924901, 9.022550393121959, 7.1965457544723925, 3.5442154824542103, 4.010095245116426, 3.746935177164692, 3.929037377492032, 1.9139132517608846, 1.3569199720900849, 0.7898597126920597, 0.0, 9.842743079009345, 8.688456839612655, 6.784599860450424, 5.741739755282652, 7.858074754984064, 5.245709248030569, 4.010095245116426, 2.531582487467293, 3.5982728772361963, 3.0075167977073205, 1.6809775283849802, 0.8911200955556896, 0.0), # 18
(9.919197858720699, 9.910640464202265, 8.497763122101317, 9.122269447440985, 7.2786960603549105, 3.5833855180790386, 4.054386528326697, 3.7882692428434357, 3.9724519435695926, 1.9350506241644574, 1.3719195981223131, 0.7985866939095915, 0.0, 9.951542799273696, 8.784453633005505, 6.859597990611565, 5.80515187249337, 7.944903887139185, 5.30357693998081, 4.054386528326697, 2.55956108434217, 3.6393480301774552, 3.0407564824803295, 1.6995526244202632, 0.9009673149274788, 0.0), # 19
(10.010904921422082, 9.993848305804882, 8.569107235194169, 9.198870504046766, 7.342656218633962, 3.613474607091719, 4.088409867587681, 3.8200205361944657, 4.005801524488732, 1.95128780409649, 1.3834418593898585, 0.805290491883616, 0.0, 10.035119190040824, 8.858195410719775, 6.9172092969492915, 5.853863412289469, 8.011603048977465, 5.348028750672252, 4.088409867587681, 2.5810532907797996, 3.671328109316981, 3.0662901680155894, 1.713821447038834, 0.9085316641640803, 0.0), # 20
(10.076934501449866, 10.050623211924679, 8.6177871120831, 9.251137272567364, 7.387465002353392, 3.6340050573228124, 4.1116249259908795, 3.84168506118401, 4.028556672622507, 1.9623669002253892, 1.39130379080626, 0.8098646593564828, 0.0, 10.092145302677078, 8.90851125292131, 6.9565189540313, 5.887100700676166, 8.057113345245014, 5.378359085657614, 4.1116249259908795, 2.5957178980877234, 3.693732501176696, 3.0837124241891223, 1.72355742241662, 0.91369301926588, 0.0), # 21
(10.115991242699579, 10.079643818565883, 8.642669883647738, 9.277853462630876, 7.41216118455705, 3.644499176602881, 4.1234913666278, 3.852758821778298, 4.040187940343971, 1.968030021219561, 1.3953224272850568, 0.8122027490705409, 0.0, 10.121294188548827, 8.934230239775948, 6.976612136425284, 5.904090063658682, 8.080375880687942, 5.393862350489617, 4.1234913666278, 2.6032136975734863, 3.706080592278525, 3.09261782087696, 1.7285339767295478, 0.9163312562332622, 0.0), # 22
(10.13039336334264, 10.083079961133974, 8.645769318701419, 9.281198109567903, 7.418488037355065, 3.6458333333333335, 4.124902001129669, 3.8539557613168727, 4.0416420781893, 1.9686980681298587, 1.3958263395269568, 0.8124914647157445, 0.0, 10.125, 8.93740611187319, 6.9791316976347835, 5.906094204389575, 8.0832841563786, 5.395538065843622, 4.124902001129669, 2.604166666666667, 3.7092440186775324, 3.0937327031893016, 1.729153863740284, 0.9166436328303613, 0.0), # 23
(10.141012413034153, 10.08107561728395, 8.645262345679013, 9.280786458333335, 7.422071742409901, 3.6458333333333335, 4.124126906318083, 3.852291666666667, 4.041447222222222, 1.968287654320988, 1.39577076318743, 0.8124238683127573, 0.0, 10.125, 8.936662551440328, 6.978853815937151, 5.904862962962962, 8.082894444444443, 5.393208333333334, 4.124126906318083, 2.604166666666667, 3.7110358712049507, 3.0935954861111123, 1.7290524691358027, 0.9164614197530866, 0.0), # 24
(10.15140723021158, 10.077124771376313, 8.644261545496114, 9.279972029320987, 7.4255766303963355, 3.6458333333333335, 4.122599451303155, 3.8490226337448563, 4.041062242798354, 1.96747970964792, 1.3956605665710604, 0.8122904282883707, 0.0, 10.125, 8.935194711172077, 6.978302832855302, 5.902439128943758, 8.082124485596708, 5.388631687242799, 4.122599451303155, 2.604166666666667, 3.7127883151981678, 3.0933240097736636, 1.728852309099223, 0.9161022519433014, 0.0), # 25
(10.161577019048034, 10.071287780064015, 8.642780635573846, 9.278764081790122, 7.429002578947403, 3.6458333333333335, 4.120343359154361, 3.8442103909465026, 4.0404920781893, 1.9662876771833566, 1.3954967473084758, 0.8120929736320684, 0.0, 10.125, 8.933022709952752, 6.977483736542379, 5.898863031550069, 8.0809841563786, 5.381894547325103, 4.120343359154361, 2.604166666666667, 3.7145012894737013, 3.0929213605967085, 1.7285561271147696, 0.915571616369456, 0.0), # 26
(10.171520983716636, 10.063624999999998, 8.640833333333333, 9.277171874999999, 7.432349465696142, 3.6458333333333335, 4.117382352941177, 3.837916666666667, 4.039741666666666, 1.9647250000000003, 1.3952803030303031, 0.8118333333333335, 0.0, 10.125, 8.930166666666667, 6.976401515151515, 5.894175, 8.079483333333332, 5.373083333333334, 4.117382352941177, 2.604166666666667, 3.716174732848071, 3.0923906250000006, 1.7281666666666669, 0.914875, 0.0), # 27
(10.181238328390501, 10.054196787837219, 8.638433356195703, 9.275204668209877, 7.4356171682756, 3.6458333333333335, 4.113740155733075, 3.830203189300412, 4.038815946502057, 1.9628051211705537, 1.3950122313671698, 0.8115133363816492, 0.0, 10.125, 8.926646700198141, 6.9750611568358485, 5.88841536351166, 8.077631893004114, 5.3622844650205765, 4.113740155733075, 2.604166666666667, 3.7178085841378, 3.091734889403293, 1.7276866712391405, 0.9140178898033837, 0.0), # 28
(10.19072825724275, 10.043063500228623, 8.635594421582077, 9.272871720679012, 7.438805564318813, 3.6458333333333335, 4.109440490599533, 3.821131687242798, 4.037719855967078, 1.9605414837677189, 1.3946935299497027, 0.811134811766499, 0.0, 10.125, 8.922482929431489, 6.973467649748514, 5.881624451303155, 8.075439711934155, 5.349584362139917, 4.109440490599533, 2.604166666666667, 3.7194027821594067, 3.0909572402263383, 1.7271188843164156, 0.9130057727480568, 0.0), # 29
(10.199989974446497, 10.03028549382716, 8.63233024691358, 9.270182291666666, 7.441914531458824, 3.6458333333333335, 4.104507080610022, 3.8107638888888884, 4.036458333333333, 1.957947530864198, 1.39432519640853, 0.8106995884773662, 0.0, 10.125, 8.917695473251028, 6.9716259820426485, 5.873842592592593, 8.072916666666666, 5.335069444444444, 4.104507080610022, 2.604166666666667, 3.720957265729412, 3.0900607638888897, 1.7264660493827162, 0.9118441358024693, 0.0), # 30
(10.209022684174858, 10.01592312528578, 8.62865454961134, 9.267145640432098, 7.444943947328672, 3.6458333333333335, 4.09896364883402, 3.799161522633745, 4.035036316872428, 1.9550367055326936, 1.3939082283742779, 0.8102094955037343, 0.0, 10.125, 8.912304450541077, 6.969541141871389, 5.865110116598079, 8.070072633744855, 5.318826131687243, 4.09896364883402, 2.604166666666667, 3.722471973664336, 3.0890485468107003, 1.7257309099222682, 0.910538465935071, 0.0), # 31
(10.217825590600954, 10.00003675125743, 8.624581047096479, 9.263771026234568, 7.447893689561397, 3.6458333333333335, 4.092833918340999, 3.7863863168724285, 4.033458744855967, 1.951822450845908, 1.3934436234775742, 0.8096663618350862, 0.0, 10.125, 8.906329980185948, 6.96721811738787, 5.8554673525377225, 8.066917489711933, 5.3009408436214, 4.092833918340999, 2.604166666666667, 3.7239468447806985, 3.0879236754115236, 1.7249162094192958, 0.909094250114312, 0.0), # 32
(10.226397897897897, 9.98268672839506, 8.620123456790123, 9.260067708333333, 7.450763635790041, 3.6458333333333335, 4.086141612200436, 3.7725000000000004, 4.031730555555555, 1.9483182098765437, 1.392932379349046, 0.8090720164609053, 0.0, 10.125, 8.899792181069957, 6.96466189674523, 5.84495462962963, 8.06346111111111, 5.2815, 4.086141612200436, 2.604166666666667, 3.7253818178950207, 3.086689236111112, 1.724024691358025, 0.9075169753086421, 0.0), # 33
(10.23473881023881, 9.963933413351622, 8.615295496113397, 9.256044945987654, 7.453553663647644, 3.6458333333333335, 4.078910453481805, 3.7575643004115222, 4.029856687242798, 1.9445374256973027, 1.3923754936193207, 0.8084282883706753, 0.0, 10.125, 8.892711172077426, 6.961877468096604, 5.833612277091907, 8.059713374485597, 5.260590020576132, 4.078910453481805, 2.604166666666667, 3.726776831823822, 3.085348315329219, 1.7230590992226795, 0.9058121284865113, 0.0), # 34
(10.242847531796807, 9.943837162780063, 8.610110882487428, 9.25171199845679, 7.456263650767246, 3.6458333333333335, 4.071164165254579, 3.741640946502058, 4.0278420781893, 1.9404935413808875, 1.3917739639190256, 0.807737006553879, 0.0, 10.125, 8.88510707209267, 6.958869819595128, 5.821480624142661, 8.0556841563786, 5.238297325102881, 4.071164165254579, 2.604166666666667, 3.728131825383623, 3.0839039994855972, 1.7220221764974855, 0.9039851966163696, 0.0), # 35
(10.250723266745005, 9.922458333333331, 8.604583333333334, 9.247078125, 7.45889347478189, 3.6458333333333335, 4.062926470588235, 3.724791666666667, 4.025691666666666, 1.9362000000000004, 1.391128787878788, 0.8070000000000002, 0.0, 10.125, 8.877, 6.95564393939394, 5.8086, 8.051383333333332, 5.214708333333334, 4.062926470588235, 2.604166666666667, 3.729446737390945, 3.0823593750000007, 1.7209166666666669, 0.9020416666666666, 0.0), # 36
(10.258365219256524, 9.89985728166438, 8.598726566072246, 9.242152584876543, 7.4614430133246135, 3.6458333333333335, 4.054221092552247, 3.707078189300412, 4.023410390946502, 1.931670244627344, 1.3904409631292352, 0.8062190976985216, 0.0, 10.125, 8.868410074683737, 6.952204815646175, 5.79501073388203, 8.046820781893004, 5.189909465020577, 4.054221092552247, 2.604166666666667, 3.7307215066623067, 3.080717528292182, 1.7197453132144491, 0.8999870256058529, 0.0), # 37
(10.265772593504476, 9.876094364426155, 8.592554298125286, 9.23694463734568, 7.46391214402846, 3.6458333333333335, 4.04507175421609, 3.6885622427983544, 4.021003189300411, 1.92691771833562, 1.3897114873009937, 0.8053961286389272, 0.0, 10.125, 8.859357415028198, 6.948557436504967, 5.780753155006859, 8.042006378600822, 5.163987139917697, 4.04507175421609, 2.604166666666667, 3.73195607201423, 3.078981545781894, 1.7185108596250571, 0.8978267604023779, 0.0), # 38
(10.272944593661986, 9.851229938271604, 8.586080246913582, 9.231463541666667, 7.466300744526468, 3.6458333333333335, 4.035502178649238, 3.6693055555555554, 4.0184750000000005, 1.9219558641975314, 1.3889413580246914, 0.8045329218106996, 0.0, 10.125, 8.849862139917693, 6.944706790123457, 5.765867592592593, 8.036950000000001, 5.137027777777778, 4.035502178649238, 2.604166666666667, 3.733150372263234, 3.07715451388889, 1.7172160493827164, 0.8955663580246914, 0.0), # 39
(10.279880423902163, 9.82532435985368, 8.579318129858253, 9.225718557098766, 7.468608692451679, 3.6458333333333335, 4.025536088921165, 3.649369855967079, 4.015830761316872, 1.9167981252857802, 1.3881315729309558, 0.8036313062033228, 0.0, 10.125, 8.83994436823655, 6.940657864654778, 5.750394375857339, 8.031661522633744, 5.1091177983539104, 4.025536088921165, 2.604166666666667, 3.7343043462258394, 3.0752395190329227, 1.7158636259716507, 0.8932113054412438, 0.0), # 40
(10.286579288398128, 9.79843798582533, 8.57228166438043, 9.219718942901235, 7.4708358654371345, 3.6458333333333335, 4.015197208101347, 3.628816872427984, 4.0130754115226335, 1.9114579446730684, 1.3872831296504138, 0.8026931108062796, 0.0, 10.125, 8.829624218869075, 6.936415648252069, 5.734373834019204, 8.026150823045267, 5.0803436213991775, 4.015197208101347, 2.604166666666667, 3.7354179327185673, 3.073239647633746, 1.7144563328760862, 0.8907670896204848, 0.0), # 41
(10.293040391323, 9.770631172839506, 8.564984567901236, 9.213473958333335, 7.472982141115872, 3.6458333333333335, 4.004509259259259, 3.6077083333333335, 4.010213888888889, 1.9059487654320992, 1.3863970258136926, 0.8017201646090536, 0.0, 10.125, 8.818921810699589, 6.931985129068463, 5.717846296296297, 8.020427777777778, 5.050791666666667, 4.004509259259259, 2.604166666666667, 3.736491070557936, 3.0711579861111122, 1.7129969135802474, 0.8882391975308643, 0.0), # 42
(10.299262936849892, 9.741964277549155, 8.557440557841794, 9.206992862654321, 7.475047397120935, 3.6458333333333335, 3.993495965464375, 3.58610596707819, 4.007251131687243, 1.9002840306355744, 1.3854742590514195, 0.800714296601128, 0.0, 10.125, 8.807857262612407, 6.927371295257098, 5.700852091906722, 8.014502263374485, 5.020548353909466, 3.993495965464375, 2.604166666666667, 3.7375236985604676, 3.0689976208847747, 1.7114881115683587, 0.8856331161408324, 0.0), # 43
(10.305246129151927, 9.712497656607225, 8.549663351623229, 9.200284915123458, 7.477031511085363, 3.6458333333333335, 3.9821810497861696, 3.564071502057614, 4.0041920781893, 1.8944771833561962, 1.3845158269942222, 0.7996773357719861, 0.0, 10.125, 8.796450693491845, 6.92257913497111, 5.683431550068587, 8.0083841563786, 4.98970010288066, 3.9821810497861696, 2.604166666666667, 3.7385157555426813, 3.0667616383744867, 1.709932670324646, 0.8829543324188387, 0.0), # 44
(10.310989172402216, 9.682291666666666, 8.541666666666668, 9.193359375, 7.478934360642197, 3.6458333333333335, 3.9705882352941178, 3.541666666666667, 4.001041666666666, 1.8885416666666672, 1.3835227272727273, 0.798611111111111, 0.0, 10.125, 8.784722222222221, 6.917613636363637, 5.665625, 8.002083333333331, 4.958333333333334, 3.9705882352941178, 2.604166666666667, 3.7394671803210984, 3.064453125000001, 1.7083333333333335, 0.8802083333333335, 0.0), # 45
(10.31649127077388, 9.65140666438043, 8.533464220393233, 9.186225501543209, 7.480755823424477, 3.6458333333333335, 3.958741245057694, 3.518953189300412, 3.997804835390946, 1.8824909236396894, 1.3824959575175624, 0.7975174516079867, 0.0, 10.125, 8.772691967687852, 6.912479787587812, 5.647472770919067, 7.995609670781892, 4.926534465020577, 3.958741245057694, 2.604166666666667, 3.7403779117122387, 3.062075167181071, 1.7066928440786466, 0.8774006058527665, 0.0), # 46
(10.321751628440035, 9.619903006401461, 8.525069730224052, 9.178892554012345, 7.482495777065244, 3.6458333333333335, 3.9466638021463734, 3.4959927983539094, 3.994486522633745, 1.8763383973479657, 1.3814365153593549, 0.7963981862520958, 0.0, 10.125, 8.760380048773053, 6.9071825767967745, 5.629015192043896, 7.98897304526749, 4.894389917695474, 3.9466638021463734, 2.604166666666667, 3.741247888532622, 3.0596308513374493, 1.7050139460448106, 0.8745366369455876, 0.0), # 47
(10.326769449573796, 9.587841049382716, 8.516496913580248, 9.171369791666667, 7.48415409919754, 3.6458333333333335, 3.9343796296296296, 3.4728472222222226, 3.9910916666666667, 1.8700975308641978, 1.3803453984287317, 0.7952551440329219, 0.0, 10.125, 8.74780658436214, 6.901726992143659, 5.610292592592592, 7.982183333333333, 4.861986111111112, 3.9343796296296296, 2.604166666666667, 3.74207704959877, 3.05712326388889, 1.7032993827160496, 0.871621913580247, 0.0), # 48
(10.331543938348286, 9.555281149977136, 8.507759487882945, 9.163666473765433, 7.485730667454405, 3.6458333333333335, 3.9219124505769383, 3.4495781893004116, 3.987625205761317, 1.8637817672610888, 1.3792236043563206, 0.7940901539399483, 0.0, 10.125, 8.73499169333943, 6.896118021781603, 5.5913453017832655, 7.975250411522634, 4.829409465020577, 3.9219124505769383, 2.604166666666667, 3.7428653337272024, 3.054555491255145, 1.7015518975765893, 0.8686619227251944, 0.0), # 49
(10.336074298936616, 9.522283664837678, 8.49887117055327, 9.155791859567902, 7.4872253594688765, 3.6458333333333335, 3.909285988057775, 3.4262474279835393, 3.9840920781893, 1.85740454961134, 1.3780721307727481, 0.7929050449626583, 0.0, 10.125, 8.72195549458924, 6.89036065386374, 5.572213648834019, 7.9681841563786, 4.796746399176955, 3.909285988057775, 2.604166666666667, 3.7436126797344382, 3.051930619855968, 1.6997742341106543, 0.86566215134888, 0.0), # 50
(10.34035973551191, 9.488908950617283, 8.489845679012346, 9.147755208333333, 7.488638052873998, 3.6458333333333335, 3.896523965141612, 3.4029166666666666, 3.9804972222222226, 1.8509793209876546, 1.3768919753086422, 0.7917016460905352, 0.0, 10.125, 8.708718106995885, 6.884459876543211, 5.552937962962963, 7.960994444444445, 4.764083333333334, 3.896523965141612, 2.604166666666667, 3.744319026436999, 3.049251736111112, 1.6979691358024693, 0.8626280864197532, 0.0), # 51
(10.344399452247279, 9.455217363968908, 8.480696730681299, 9.139565779320987, 7.489968625302809, 3.6458333333333335, 3.883650104897926, 3.3796476337448556, 3.976845576131687, 1.8445195244627348, 1.3756841355946297, 0.7904817863130622, 0.0, 10.125, 8.695299649443683, 6.878420677973147, 5.533558573388203, 7.953691152263374, 4.731506687242798, 3.883650104897926, 2.604166666666667, 3.7449843126514044, 3.04652192644033, 1.69613934613626, 0.8595652149062645, 0.0), # 52
(10.348192653315843, 9.421269261545497, 8.471438042981255, 9.131232831790122, 7.491216954388353, 3.6458333333333335, 3.8706881303961915, 3.3565020576131688, 3.9731420781893005, 1.8380386031092826, 1.3744496092613379, 0.7892472946197227, 0.0, 10.125, 8.681720240816947, 6.872248046306688, 5.514115809327846, 7.946284156378601, 4.699102880658437, 3.8706881303961915, 2.604166666666667, 3.7456084771941764, 3.043744277263375, 1.694287608596251, 0.8564790237768635, 0.0), # 53
(10.351738542890716, 9.387125000000001, 8.462083333333332, 9.122765625, 7.492382917763668, 3.6458333333333335, 3.8576617647058824, 3.333541666666666, 3.9693916666666667, 1.8315500000000005, 1.3731893939393938, 0.788, 0.0, 10.125, 8.668, 6.865946969696969, 5.49465, 7.938783333333333, 4.666958333333333, 3.8576617647058824, 2.604166666666667, 3.746191458881834, 3.040921875000001, 1.6924166666666667, 0.8533750000000002, 0.0), # 54
(10.355036325145022, 9.352844935985367, 8.452646319158665, 9.114173418209877, 7.493466393061793, 3.6458333333333335, 3.844594730896474, 3.3108281893004117, 3.9655992798353905, 1.8250671582075908, 1.3719044872594257, 0.7867417314433777, 0.0, 10.125, 8.654159045877153, 6.859522436297127, 5.4752014746227715, 7.931198559670781, 4.6351594650205765, 3.844594730896474, 2.604166666666667, 3.7467331965308963, 3.0380578060699595, 1.6905292638317333, 0.8502586305441244, 0.0), # 55
(10.358085204251871, 9.31848942615455, 8.443140717878373, 9.105465470679011, 7.4944672579157725, 3.6458333333333335, 3.8315107520374405, 3.288423353909465, 3.961769855967078, 1.818603520804756, 1.3705958868520598, 0.7854743179393385, 0.0, 10.125, 8.640217497332722, 6.852979434260299, 5.455810562414267, 7.923539711934156, 4.603792695473251, 3.8315107520374405, 2.604166666666667, 3.7472336289578863, 3.035155156893005, 1.6886281435756747, 0.8471354023776865, 0.0), # 56
(10.360884384384383, 9.284118827160494, 8.433580246913582, 9.096651041666666, 7.495385389958644, 3.6458333333333335, 3.818433551198257, 3.2663888888888892, 3.957908333333333, 1.812172530864198, 1.369264590347924, 0.7841995884773663, 0.0, 10.125, 8.626195473251027, 6.8463229517396185, 5.436517592592593, 7.915816666666666, 4.572944444444445, 3.818433551198257, 2.604166666666667, 3.747692694979322, 3.0322170138888898, 1.6867160493827165, 0.844010802469136, 0.0), # 57
(10.36343306971568, 9.24979349565615, 8.423978623685414, 9.087739390432098, 7.496220666823449, 3.6458333333333335, 3.8053868514483984, 3.2447865226337447, 3.954019650205761, 1.8057876314586196, 1.367911595377645, 0.7829193720469442, 0.0, 10.125, 8.612113092516385, 6.8395579768882255, 5.417362894375858, 7.908039300411522, 4.5427011316872425, 3.8053868514483984, 2.604166666666667, 3.7481103334117245, 3.029246463477367, 1.684795724737083, 0.8408903177869229, 0.0), # 58
(10.36573046441887, 9.215573788294467, 8.414349565614998, 9.078739776234567, 7.49697296614323, 3.6458333333333335, 3.792394375857339, 3.2236779835390945, 3.9501087448559673, 1.799462265660723, 1.3665378995718502, 0.7816354976375554, 0.0, 10.125, 8.597990474013107, 6.83268949785925, 5.398386796982168, 7.900217489711935, 4.513149176954733, 3.792394375857339, 2.604166666666667, 3.748486483071615, 3.02624659207819, 1.6828699131229998, 0.8377794352994972, 0.0), # 59
(10.367775772667077, 9.181520061728396, 8.404706790123456, 9.069661458333334, 7.497642165551024, 3.6458333333333335, 3.779479847494553, 3.203125, 3.946180555555556, 1.7932098765432103, 1.3651445005611673, 0.7803497942386832, 0.0, 10.125, 8.583847736625515, 6.825722502805837, 5.37962962962963, 7.892361111111112, 4.484375, 3.779479847494553, 2.604166666666667, 3.748821082775512, 3.023220486111112, 1.6809413580246915, 0.8346836419753088, 0.0), # 60
(10.369568198633415, 9.147692672610884, 8.395064014631917, 9.060513695987654, 7.498228142679874, 3.6458333333333335, 3.7666669894295164, 3.183189300411523, 3.9422400205761314, 1.7870439071787843, 1.3637323959762233, 0.7790640908398111, 0.0, 10.125, 8.56970499923792, 6.818661979881115, 5.361131721536351, 7.884480041152263, 4.456465020576132, 3.7666669894295164, 2.604166666666667, 3.749114071339937, 3.0201712319958856, 1.6790128029263836, 0.8316084247828076, 0.0), # 61
(10.371106946491004, 9.114151977594878, 8.385434956561502, 9.051305748456791, 7.498730775162823, 3.6458333333333335, 3.753979524731703, 3.1639326131687247, 3.9382920781893, 1.7809778006401469, 1.3623025834476452, 0.7777802164304223, 0.0, 10.125, 8.555582380734645, 6.811512917238226, 5.3429334019204395, 7.8765841563786, 4.429505658436215, 3.753979524731703, 2.604166666666667, 3.7493653875814115, 3.0171019161522645, 1.6770869913123003, 0.8285592706904436, 0.0), # 62
(10.37239122041296, 9.080958333333333, 8.375833333333334, 9.042046875, 7.499149940632904, 3.6458333333333335, 3.741441176470588, 3.1454166666666667, 3.9343416666666666, 1.7750250000000003, 1.360856060606061, 0.7765000000000001, 0.0, 10.125, 8.5415, 6.804280303030303, 5.325075, 7.868683333333333, 4.403583333333334, 3.741441176470588, 2.604166666666667, 3.749574970316452, 3.014015625000001, 1.675166666666667, 0.8255416666666667, 0.0), # 63
(10.373420224572397, 9.048172096479195, 8.366272862368541, 9.032746334876544, 7.4994855167231655, 3.6458333333333335, 3.729075667715646, 3.127703189300412, 3.9303937242798352, 1.7691989483310475, 1.3593938250820965, 0.7752252705380279, 0.0, 10.125, 8.527477975918305, 6.796969125410483, 5.307596844993141, 7.8607874485596705, 4.378784465020577, 3.729075667715646, 2.604166666666667, 3.7497427583615828, 3.0109154449588487, 1.6732545724737085, 0.822561099679927, 0.0), # 64
(10.374193163142438, 9.015853623685413, 8.35676726108825, 9.023413387345679, 7.499737381066645, 3.6458333333333335, 3.7169067215363514, 3.1108539094650207, 3.9264531893004113, 1.7635130887059902, 1.357916874506381, 0.7739578570339887, 0.0, 10.125, 8.513536427373873, 6.7895843725319045, 5.290539266117969, 7.852906378600823, 4.355195473251029, 3.7169067215363514, 2.604166666666667, 3.7498686905333223, 3.0078044624485605, 1.67135345221765, 0.819623056698674, 0.0), # 65
(10.374709240296196, 8.984063271604938, 8.34733024691358, 9.014057291666667, 7.499905411296382, 3.6458333333333335, 3.7049580610021784, 3.094930555555556, 3.9225250000000003, 1.7579808641975312, 1.3564262065095398, 0.7726995884773664, 0.0, 10.125, 8.499695473251029, 6.782131032547699, 5.273942592592592, 7.8450500000000005, 4.332902777777778, 3.7049580610021784, 2.604166666666667, 3.749952705648191, 3.0046857638888897, 1.6694660493827165, 0.8167330246913582, 0.0), # 66
(10.374967660206792, 8.952861396890716, 8.337975537265661, 9.004687307098765, 7.499989485045419, 3.6458333333333335, 3.693253409182603, 3.0799948559670787, 3.9186140946502057, 1.7526157178783728, 1.3549228187222018, 0.7714522938576437, 0.0, 10.125, 8.485975232434079, 6.774614093611008, 5.257847153635117, 7.837228189300411, 4.31199279835391, 3.693253409182603, 2.604166666666667, 3.7499947425227096, 3.001562435699589, 1.6675951074531323, 0.8138964906264289, 0.0), # 67
(10.374791614480825, 8.922144586043629, 8.328671624942844, 8.995231305354269, 7.499918636864896, 3.645765673423767, 3.681757597414823, 3.0659766041761927, 3.9146959495503735, 1.747405110411792, 1.3533809980900628, 0.770210835158312, 0.0, 10.124875150034294, 8.47231918674143, 6.766904990450313, 5.242215331235375, 7.829391899100747, 4.29236724584667, 3.681757597414823, 2.604118338159833, 3.749959318432448, 2.99841043511809, 1.6657343249885688, 0.8111040532766937, 0.0), # 68
(10.373141706924315, 8.890975059737157, 8.319157021604937, 8.985212635869564, 7.499273783587508, 3.6452307956104257, 3.6701340906733066, 3.052124485596708, 3.910599279835391, 1.7422015976761076, 1.3516438064859118, 0.7689349144466104, 0.0, 10.12388599537037, 8.458284058912714, 6.758219032429559, 5.226604793028321, 7.821198559670782, 4.272974279835391, 3.6701340906733066, 2.6037362825788755, 3.749636891793754, 2.9950708786231885, 1.6638314043209876, 0.8082704599761052, 0.0), # 69
(10.369885787558895, 8.859209754856408, 8.309390360653863, 8.974565343196456, 7.497999542752628, 3.6441773992785653, 3.658330067280685, 3.0383135192805977, 3.9063009640298736, 1.736979881115684, 1.3496914810876801, 0.7676185634410675, 0.0, 10.121932334533609, 8.44380419785174, 6.7484574054383994, 5.210939643347051, 7.812601928059747, 4.253638926992837, 3.658330067280685, 2.6029838566275467, 3.748999771376314, 2.991521781065486, 1.6618780721307727, 0.8053827049869463, 0.0), # 70
(10.365069660642929, 8.826867654542236, 8.299375071444901, 8.963305127818035, 7.496112052502757, 3.6426225549966977, 3.646350829769494, 3.0245482777015704, 3.9018074035970125, 1.7317400898356603, 1.347531228463977, 0.7662627447677263, 0.0, 10.119039887688615, 8.428890192444989, 6.737656142319885, 5.195220269506979, 7.803614807194025, 4.234367588782199, 3.646350829769494, 2.6018732535690696, 3.7480560262513785, 2.987768375939346, 1.6598750142889804, 0.8024425140492942, 0.0), # 71
(10.358739130434783, 8.793967741935482, 8.289114583333333, 8.95144769021739, 7.493627450980392, 3.6405833333333337, 3.634201680672269, 3.0108333333333333, 3.897125, 1.7264823529411768, 1.3451702551834133, 0.7648684210526316, 0.0, 10.115234375, 8.413552631578947, 6.7258512759170666, 5.179447058823529, 7.79425, 4.215166666666667, 3.634201680672269, 2.600416666666667, 3.746813725490196, 2.983815896739131, 1.6578229166666667, 0.7994516129032258, 0.0), # 72
(10.35094000119282, 8.760529000176998, 8.27861232567444, 8.939008730877617, 7.490561876328034, 3.638076804856983, 3.621887922521546, 2.9971732586495965, 3.8922601547020275, 1.7212067995373737, 1.3426157678145982, 0.7634365549218266, 0.0, 10.110541516632374, 8.397802104140093, 6.71307883907299, 5.163620398612119, 7.784520309404055, 4.196042562109435, 3.621887922521546, 2.598626289183559, 3.745280938164017, 2.979669576959206, 1.655722465134888, 0.7964117272888181, 0.0), # 73
(10.341718077175404, 8.726570412407629, 8.267871727823502, 8.926003950281803, 7.486931466688183, 3.6351200401361585, 3.609414857849861, 2.9835726261240665, 3.8872192691662857, 1.7159135587293908, 1.3398749729261428, 0.7619681090013557, 0.0, 10.104987032750344, 8.38164919901491, 6.699374864630713, 5.147740676188171, 7.774438538332571, 4.177001676573693, 3.609414857849861, 2.5965143143829703, 3.7434657333440917, 2.975334650093935, 1.6535743455647005, 0.7933245829461482, 0.0), # 74
(10.331119162640901, 8.692110961768218, 8.256896219135802, 8.912449048913043, 7.482752360203341, 3.6317301097393697, 3.59678778918975, 2.9700360082304527, 3.8820087448559666, 1.7106027596223679, 1.336955077086656, 0.7604640459172624, 0.0, 10.098596643518519, 8.365104505089885, 6.684775385433279, 5.131808278867102, 7.764017489711933, 4.158050411522634, 3.59678778918975, 2.594092935528121, 3.7413761801016703, 2.9708163496376816, 1.6513792438271604, 0.7901919056152927, 0.0), # 75
(10.319189061847677, 8.65716963139962, 8.245689228966622, 8.898359727254428, 7.478040695016003, 3.6279240842351275, 3.5840120190737474, 2.956567977442463, 3.876634983234263, 1.7052745313214452, 1.3338632868647486, 0.7589253282955902, 0.0, 10.091396069101508, 8.348178611251491, 6.669316434323743, 5.115823593964334, 7.753269966468526, 4.139195168419449, 3.5840120190737474, 2.5913743458822336, 3.7390203475080015, 2.96611990908481, 1.6491378457933243, 0.7870154210363293, 0.0), # 76
(10.305973579054093, 8.621765404442675, 8.234254186671238, 8.883751685789049, 7.472812609268672, 3.6237190341919425, 3.5710928500343897, 2.9431731062338065, 3.871104385764365, 1.699929002931763, 1.3306068088290313, 0.7573529187623839, 0.0, 10.083411029663925, 8.330882106386222, 6.653034044145156, 5.099787008795288, 7.74220877152873, 4.120442348727329, 3.5710928500343897, 2.58837073870853, 3.736406304634336, 2.9612505619296834, 1.6468508373342476, 0.7837968549493343, 0.0), # 77
(10.291518518518519, 8.585917264038233, 8.222594521604938, 8.868640625, 7.467084241103849, 3.6191320301783265, 3.5580355846042124, 2.9298559670781894, 3.8654233539094642, 1.6945663035584608, 1.327192849548113, 0.7557477799436866, 0.0, 10.074667245370371, 8.313225579380552, 6.635964247740564, 5.083698910675381, 7.7308467078189285, 4.101798353909466, 3.5580355846042124, 2.585094307270233, 3.7335421205519244, 2.956213541666667, 1.6445189043209878, 0.7805379330943849, 0.0), # 78
(10.275869684499314, 8.549644193327138, 8.210713663123, 8.85304224537037, 7.460871728664031, 3.61418014276279, 3.5448455253157505, 2.916621132449322, 3.859598289132754, 1.6891865623066789, 1.3236286155906039, 0.7541108744655421, 0.0, 10.065190436385459, 8.295219619120962, 6.618143077953018, 5.067559686920035, 7.719196578265508, 4.083269585429051, 3.5448455253157505, 2.5815572448305644, 3.7304358643320157, 2.951014081790124, 1.6421427326246, 0.7772403812115581, 0.0), # 79
(10.259072881254847, 8.51296517545024, 8.198615040580703, 8.836972247383253, 7.454191210091719, 3.6088804425138448, 3.5315279747015405, 2.9034731748209115, 3.853635592897424, 1.683789908281557, 1.3199213135251149, 0.7524431649539947, 0.0, 10.0550063228738, 8.27687481449394, 6.599606567625574, 5.05136972484467, 7.707271185794848, 4.064862444749276, 3.5315279747015405, 2.577771744652746, 3.7270956050458595, 2.945657415794418, 1.639723008116141, 0.7739059250409311, 0.0), # 80
(10.241173913043479, 8.475899193548386, 8.186302083333333, 8.82044633152174, 7.447058823529411, 3.60325, 3.5180882352941176, 2.890416666666667, 3.8475416666666664, 1.6783764705882358, 1.3160781499202554, 0.7507456140350878, 0.0, 10.044140624999999, 8.258201754385965, 6.580390749601277, 5.035129411764706, 7.695083333333333, 4.046583333333333, 3.5180882352941176, 2.57375, 3.7235294117647055, 2.940148777173914, 1.6372604166666667, 0.7705362903225808, 0.0), # 81
(10.222218584123576, 8.438465230762423, 8.17377822073617, 8.803480198268922, 7.43949070711961, 3.5973058857897686, 3.504531609626018, 2.8774561804602956, 3.841322911903673, 1.6729463783318543, 1.3121063313446355, 0.7490191843348656, 0.0, 10.03261906292867, 8.23921102768352, 6.560531656723177, 5.018839134995561, 7.682645823807346, 4.0284386526444145, 3.504531609626018, 2.5695042041355487, 3.719745353559805, 2.934493399422974, 1.634755644147234, 0.767133202796584, 0.0), # 82
(10.202252698753504, 8.400682270233196, 8.16104688214449, 8.78608954810789, 7.431502999004814, 3.591065170451659, 3.4908634002297765, 2.8645962886755068, 3.8349857300716352, 1.6674997606175532, 1.3080130643668657, 0.7472648384793719, 0.0, 10.020467356824417, 8.219913223273089, 6.540065321834328, 5.002499281852659, 7.6699714601432705, 4.01043480414571, 3.4908634002297765, 2.5650465503226134, 3.715751499502407, 2.9286965160359637, 1.632209376428898, 0.7636983882030178, 0.0), # 83
(10.181322061191626, 8.362569295101553, 8.14811149691358, 8.768290081521739, 7.423111837327523, 3.584544924554184, 3.477088909637929, 2.851841563786008, 3.8285365226337444, 1.6620367465504726, 1.3038055555555557, 0.7454835390946503, 0.0, 10.007711226851852, 8.200318930041153, 6.519027777777778, 4.986110239651417, 7.657073045267489, 3.9925781893004113, 3.477088909637929, 2.5603892318244172, 3.7115559186637617, 2.922763360507247, 1.629622299382716, 0.7602335722819594, 0.0), # 84
(10.159472475696308, 8.32414528850834, 8.13497549439872, 8.75009749899356, 7.414333360230238, 3.577762218665854, 3.463213440383012, 2.8391965782655086, 3.8219816910531925, 1.6565574652357518, 1.2994910114793157, 0.7436762488067449, 0.0, 9.994376393175584, 8.180438736874192, 6.497455057396579, 4.969672395707254, 7.643963382106385, 3.9748752095717124, 3.463213440383012, 2.5555444419041815, 3.707166680115119, 2.916699166331187, 1.626995098879744, 0.7567404807734855, 0.0), # 85
(10.136749746525913, 8.285429233594407, 8.121642303955191, 8.731527501006443, 7.405183705855455, 3.57073412335518, 3.44924229499756, 2.826665904587715, 3.815327636793172, 1.6510620457785314, 1.2950766387067558, 0.7418439302416996, 0.0, 9.98048857596022, 8.160283232658694, 6.475383193533778, 4.953186137335593, 7.630655273586344, 3.9573322664228017, 3.44924229499756, 2.550524373825129, 3.7025918529277275, 2.910509167002148, 1.6243284607910382, 0.7532208394176735, 0.0), # 86
(10.113199677938807, 8.246440113500597, 8.10811535493827, 8.712595788043478, 7.3956790123456795, 3.563477709190672, 3.4351807760141093, 2.8142541152263374, 3.8085807613168727, 1.645550617283951, 1.290569643806486, 0.7399875460255577, 0.0, 9.96607349537037, 8.139863006281134, 6.452848219032429, 4.936651851851852, 7.6171615226337455, 3.9399557613168725, 3.4351807760141093, 2.54534122085048, 3.6978395061728397, 2.904198596014493, 1.6216230709876542, 0.7496763739545999, 0.0), # 87
(10.088868074193357, 8.207196911367758, 8.094398076703246, 8.693318060587762, 7.385835417843406, 3.5560100467408424, 3.4210341859651954, 2.801965782655083, 3.8017474660874866, 1.6400233088571508, 1.2859772333471164, 0.7381080587843638, 0.0, 9.951156871570646, 8.119188646628, 6.429886166735582, 4.9200699265714505, 7.603494932174973, 3.9227520957171165, 3.4210341859651954, 2.540007176243459, 3.692917708921703, 2.897772686862588, 1.6188796153406495, 0.7461088101243417, 0.0), # 88
(10.063800739547922, 8.16771861033674, 8.080493898605397, 8.673710019122383, 7.375669060491138, 3.5483482065742016, 3.406807827383354, 2.7898054793476605, 3.794834152568206, 1.634480249603271, 1.2813066138972575, 0.7362064311441613, 0.0, 9.935764424725651, 8.098270742585774, 6.4065330694862865, 4.903440748809812, 7.589668305136412, 3.905727671086725, 3.406807827383354, 2.534534433267287, 3.687834530245569, 2.891236673040795, 1.6160987797210793, 0.7425198736669765, 0.0), # 89
(10.03804347826087, 8.128024193548386, 8.06640625, 8.653787364130435, 7.365196078431373, 3.5405092592592595, 3.3925070028011204, 2.7777777777777777, 3.7878472222222226, 1.6289215686274514, 1.2765649920255184, 0.7342836257309943, 0.0, 9.919921875, 8.077119883040936, 6.382824960127592, 4.886764705882353, 7.575694444444445, 3.888888888888889, 3.3925070028011204, 2.5289351851851856, 3.6825980392156863, 2.884595788043479, 1.6132812500000002, 0.7389112903225807, 0.0), # 90
(10.011642094590563, 8.088132644143545, 8.05213856024234, 8.63356579609501, 7.35443260980661, 3.532510275364528, 3.378137014751031, 2.7658872504191434, 3.780793076512727, 1.6233473950348318, 1.2717595743005101, 0.7323406051709063, 0.0, 9.903654942558298, 8.055746656879968, 6.35879787150255, 4.870042185104494, 7.561586153025454, 3.872242150586801, 3.378137014751031, 2.5232216252603767, 3.677216304903305, 2.8778552653650036, 1.6104277120484682, 0.7352847858312315, 0.0), # 91
(9.984642392795372, 8.048062945263066, 8.0376942586877, 8.613061015499195, 7.343394792759352, 3.524368325458518, 3.363703165765621, 2.754138469745466, 3.773678116902911, 1.6177578579305527, 1.2668975672908422, 0.7303783320899415, 0.0, 9.886989347565157, 8.034161652989356, 6.334487836454211, 4.853273573791657, 7.547356233805822, 3.8557938576436523, 3.363703165765621, 2.517405946756084, 3.671697396379676, 2.871020338499732, 1.6075388517375402, 0.7316420859330061, 0.0), # 92
(9.957090177133654, 8.00783408004779, 8.023076774691358, 8.592288722826089, 7.332098765432098, 3.5161004801097393, 3.349210758377425, 2.742536008230453, 3.766508744855967, 1.6121530864197533, 1.261986177565125, 0.7283977691141434, 0.0, 9.869950810185184, 8.012375460255576, 6.309930887825625, 4.836459259259259, 7.533017489711934, 3.839550411522634, 3.349210758377425, 2.5115003429355283, 3.666049382716049, 2.86409624094203, 1.6046153549382718, 0.727984916367981, 0.0), # 93
(9.92903125186378, 7.967465031638567, 8.008289537608597, 8.571264618558777, 7.320560665967347, 3.5077238098867043, 3.3346650951189805, 2.7310844383478132, 3.759291361835086, 1.6065332096075746, 1.2570326116919686, 0.7263998788695563, 0.0, 9.85256505058299, 7.990398667565118, 6.285163058459842, 4.819599628822722, 7.518582723670172, 3.823518213686939, 3.3346650951189805, 2.5055170070619317, 3.6602803329836733, 2.8570882061862592, 1.6016579075217197, 0.7243150028762335, 0.0), # 94
(9.90051142124411, 7.926974783176247, 7.993335976794697, 8.550004403180354, 7.308796632507598, 3.499255385357923, 3.320071478522822, 2.719788332571255, 3.7520323693034596, 1.6008983565991557, 1.2520440762399827, 0.7243856239822234, 0.0, 9.834857788923182, 7.968241863804456, 6.260220381199914, 4.8026950697974655, 7.504064738606919, 3.8077036655997567, 3.320071478522822, 2.4994681323985164, 3.654398316253799, 2.850001467726785, 1.5986671953589393, 0.7206340711978407, 0.0), # 95
(9.871576489533012, 7.886382317801674, 7.978219521604939, 8.528523777173913, 7.296822803195352, 3.4907122770919066, 3.3054352111214853, 2.708652263374486, 3.7447381687242793, 1.5952486564996373, 1.247027777777778, 0.7223559670781895, 0.0, 9.816854745370371, 7.945915637860083, 6.23513888888889, 4.785745969498911, 7.489476337448559, 3.7921131687242804, 3.3054352111214853, 2.4933659122085046, 3.648411401597676, 2.8428412590579715, 1.595643904320988, 0.7169438470728796, 0.0), # 96
(9.842272260988848, 7.845706618655694, 7.962943601394604, 8.506838441022543, 7.284655316173109, 3.482111555657166, 3.2907615954475067, 2.697680803231215, 3.7374151615607376, 1.589584238414159, 1.2419909228739638, 0.7203118707834976, 0.0, 9.798581640089164, 7.923430578618472, 6.209954614369819, 4.768752715242476, 7.474830323121475, 3.7767531245237014, 3.2907615954475067, 2.4872225397551184, 3.6423276580865545, 2.8356128136741816, 1.5925887202789208, 0.7132460562414268, 0.0), # 97
(9.812644539869984, 7.804966668879153, 7.947511645518976, 8.48496409520934, 7.272310309583368, 3.4734702916222124, 3.276055934033421, 2.68687852461515, 3.7300697492760246, 1.5839052314478608, 1.236940718097151, 0.7182542977241916, 0.0, 9.78006419324417, 7.900797274966106, 6.184703590485755, 4.751715694343581, 7.460139498552049, 3.7616299344612103, 3.276055934033421, 2.48105020830158, 3.636155154791684, 2.8283213650697805, 1.589502329103795, 0.7095424244435595, 0.0), # 98
(9.782739130434782, 7.764181451612902, 7.931927083333334, 8.462916440217391, 7.259803921568627, 3.464805555555556, 3.261323529411765, 2.67625, 3.7227083333333333, 1.5782117647058826, 1.2318843700159492, 0.7161842105263159, 0.0, 9.761328125, 7.878026315789473, 6.159421850079745, 4.734635294117647, 7.445416666666667, 3.7467500000000005, 3.261323529411765, 2.474861111111111, 3.6299019607843137, 2.820972146739131, 1.5863854166666669, 0.7058346774193549, 0.0), # 99
(9.752601836941611, 7.723369949997786, 7.916193344192958, 8.44071117652979, 7.247152290271389, 3.4561344180257074, 3.2465696841150726, 2.665799801859473, 3.715337315195854, 1.572503967293365, 1.2268290851989685, 0.714102571815914, 0.0, 9.742399155521262, 7.8551282899750525, 6.134145425994841, 4.717511901880093, 7.430674630391708, 3.732119722603262, 3.2465696841150726, 2.468667441446934, 3.6235761451356945, 2.8135703921765973, 1.5832386688385918, 0.7021245409088898, 0.0), # 100
(9.722278463648834, 7.682551147174654, 7.900313857453133, 8.41836400462963, 7.234371553834153, 3.4474739496011786, 3.231799700675881, 2.6555325026672763, 3.7079630963267793, 1.5667819683154474, 1.2217820702148188, 0.7120103442190294, 0.0, 9.723303004972564, 7.832113786409323, 6.108910351074094, 4.7003459049463405, 7.415926192653559, 3.7177455037341867, 3.231799700675881, 2.4624813925722706, 3.6171857769170765, 2.806121334876544, 1.5800627714906266, 0.6984137406522414, 0.0), # 101
(9.691814814814816, 7.641744026284349, 7.884292052469135, 8.395890625, 7.221477850399419, 3.4388412208504806, 3.217018881626725, 2.645452674897119, 3.7005920781893, 1.56104589687727, 1.2167505316321108, 0.7099084903617069, 0.0, 9.704065393518519, 7.808993393978774, 6.083752658160553, 4.683137690631809, 7.4011841563786, 3.703633744855967, 3.217018881626725, 2.4563151577503435, 3.6107389251997093, 2.798630208333334, 1.5768584104938272, 0.6947040023894864, 0.0), # 102
(9.661256694697919, 7.60096757046772, 7.8681313585962505, 8.373306738123993, 7.208487318109686, 3.430253302342123, 3.20223252950014, 2.63556489102271, 3.6932306622466085, 1.5552958820839726, 1.211741676019454, 0.7077979728699895, 0.0, 9.68471204132373, 7.785777701569883, 6.058708380097269, 4.6658876462519165, 7.386461324493217, 3.689790847431794, 3.20223252950014, 2.4501809302443736, 3.604243659054843, 2.7911022460413317, 1.5736262717192502, 0.6909970518607019, 0.0), # 103
(9.63064990755651, 7.560240762865614, 7.851835205189758, 8.350628044484703, 7.195416095107452, 3.421727264644617, 3.187445946828663, 2.6258737235177567, 3.685885249961896, 1.5495320530406955, 1.2067627099454585, 0.7056797543699213, 0.0, 9.665268668552812, 7.762477298069133, 6.033813549727292, 4.648596159122086, 7.371770499923792, 3.6762232129248593, 3.187445946828663, 2.4440909033175835, 3.597708047553726, 2.783542681494901, 1.5703670410379515, 0.687294614805965, 0.0), # 104
(9.600040257648953, 7.519582586618876, 7.835407021604938, 8.327870244565217, 7.182280319535221, 3.4132801783264752, 3.172664436144829, 2.6163837448559675, 3.6785622427983538, 1.5437545388525786, 1.201820839978735, 0.7035547974875461, 0.0, 9.64576099537037, 7.739102772363006, 6.009104199893674, 4.631263616557734, 7.3571244855967075, 3.662937242798354, 3.172664436144829, 2.4380572702331964, 3.5911401597676105, 2.775956748188406, 1.5670814043209877, 0.6835984169653525, 0.0), # 105
(9.569473549233614, 7.479012024868357, 7.818850237197074, 8.305049038848631, 7.1690961295354905, 3.404929113956206, 3.1578932999811724, 2.6070995275110502, 3.6712680422191735, 1.5379634686247616, 1.1969232726878927, 0.701424064848908, 0.0, 9.626214741941014, 7.715664713337986, 5.9846163634394625, 4.613890405874283, 7.342536084438347, 3.6499393385154706, 3.1578932999811724, 2.4320922242544327, 3.5845480647677452, 2.768349679616211, 1.5637700474394147, 0.6799101840789417, 0.0), # 106
(9.538995586568856, 7.438548060754901, 7.802168281321446, 8.282180127818036, 7.155879663250759, 3.3966911421023225, 3.1431378408702306, 2.5980256439567144, 3.6640090496875475, 1.532158971462385, 1.1920772146415421, 0.6992885190800504, 0.0, 9.606655628429355, 7.692173709880553, 5.96038607320771, 4.596476914387154, 7.328018099375095, 3.6372359015394005, 3.1431378408702306, 2.426207958644516, 3.5779398316253794, 2.760726709272679, 1.5604336562642893, 0.6762316418868093, 0.0), # 107
(9.508652173913044, 7.398209677419356, 7.785364583333334, 8.259279211956523, 7.1426470588235285, 3.3885833333333335, 3.1284033613445374, 2.589166666666667, 3.656791666666667, 1.5263411764705888, 1.1872898724082936, 0.6971491228070177, 0.0, 9.587109375, 7.668640350877193, 5.936449362041468, 4.579023529411765, 7.313583333333334, 3.624833333333334, 3.1284033613445374, 2.4204166666666667, 3.5713235294117642, 2.7530930706521746, 1.557072916666667, 0.6725645161290325, 0.0), # 108
(9.478489115524543, 7.358015858002567, 7.768442572588021, 8.23636199174718, 7.129414454396299, 3.3806227582177515, 3.113695163936631, 2.580527168114617, 3.6496222946197223, 1.5205102127545123, 1.1825684525567568, 0.6950068386558532, 0.0, 9.567601701817559, 7.645075225214384, 5.9128422627837836, 4.561530638263536, 7.299244589239445, 3.612738035360464, 3.113695163936631, 2.4147305415841083, 3.5647072271981495, 2.7454539972490606, 1.5536885145176043, 0.668910532545688, 0.0), # 109
(9.448552215661715, 7.317985585645383, 7.751405678440788, 8.213444167673108, 7.116197988111569, 3.3728264873240867, 3.0990185511790447, 2.5721117207742723, 3.6425073350099066, 1.5146662094192962, 1.177920161655542, 0.6928626292526012, 0.0, 9.54815832904664, 7.621488921778612, 5.8896008082777085, 4.543998628257887, 7.285014670019813, 3.600956409083981, 3.0990185511790447, 2.409161776660062, 3.5580989940557846, 2.737814722557703, 1.5502811356881578, 0.6652714168768531, 0.0), # 110
(9.41888727858293, 7.278137843488651, 7.7342573302469155, 8.190541440217391, 7.103013798111837, 3.365211591220851, 3.0843788256043156, 2.5639248971193416, 3.635453189300412, 1.5088092955700803, 1.173352206273259, 0.6907174572233054, 0.0, 9.528804976851852, 7.597892029456357, 5.866761031366295, 4.526427886710239, 7.270906378600824, 3.5894948559670783, 3.0843788256043156, 2.4037225651577505, 3.5515068990559184, 2.7301804800724643, 1.546851466049383, 0.6616488948626047, 0.0), # 111
(9.38954010854655, 7.238491614673214, 7.717000957361684, 8.167669509863124, 7.089878022539605, 3.357795140476554, 3.069781289744979, 2.5559712696235333, 3.628466258954427, 1.5029396003120044, 1.1688717929785184, 0.6885722851940093, 0.0, 9.509567365397805, 7.574295137134101, 5.844358964892591, 4.5088188009360115, 7.256932517908854, 3.5783597774729463, 3.069781289744979, 2.3984251003403956, 3.5449390112698027, 2.7225565032877084, 1.543400191472337, 0.6580446922430195, 0.0), # 112
(9.360504223703044, 7.1991320672204555, 7.699681523543391, 8.14487541186903, 7.076783786782469, 3.3505906987084666, 3.0552629818283847, 2.548271903658586, 3.6215709370862066, 1.4970761841531826, 1.1644873176921446, 0.6864327447087024, 0.0, 9.490443900843221, 7.550760191795725, 5.8224365884607225, 4.491228552459547, 7.243141874172413, 3.5675806651220205, 3.0552629818283847, 2.3932790705060474, 3.5383918933912346, 2.7149584706230105, 1.5399363047086783, 0.654466551565496, 0.0), # 113
(9.331480897900065, 7.16044741823174, 7.682538062518016, 8.122342065958001, 7.063595569710884, 3.343581854975776, 3.0410091042052896, 2.5409213581271333, 3.6148730119043533, 1.491328791978196, 1.1602073895188663, 0.684326014342748, 0.0, 9.471275414160035, 7.5275861577702265, 5.801036947594331, 4.473986375934587, 7.229746023808707, 3.557289901377987, 3.0410091042052896, 2.3882727535541255, 3.531797784855442, 2.7074473553193346, 1.5365076125036032, 0.6509497652937947, 0.0), # 114
(9.302384903003995, 7.122451598792792, 7.665580777256098, 8.100063378886334, 7.050271785259067, 3.3367503822909463, 3.027029825095781, 2.533917772616129, 3.6083749928895963, 1.4857063319970194, 1.1560257519045158, 0.6822531318799043, 0.0, 9.452006631660376, 7.5047844506789465, 5.7801287595225785, 4.457118995991058, 7.216749985779193, 3.5474848816625806, 3.027029825095781, 2.3833931302078186, 3.5251358926295335, 2.700021126295445, 1.5331161554512198, 0.647495599890254, 0.0), # 115
(9.273179873237634, 7.0850892578507265, 7.648776824986561, 8.077999612699802, 7.036792350922519, 3.330080178417474, 3.0133024087639466, 2.5272417970412473, 3.6020604464092765, 1.480198339612387, 1.1519343218785802, 0.6802102664572789, 0.0, 9.43260725975589, 7.482312931030067, 5.7596716093929015, 4.44059501883716, 7.204120892818553, 3.5381385158577463, 3.0133024087639466, 2.3786286988696244, 3.5183961754612594, 2.6926665375666015, 1.5297553649973124, 0.6440990234409752, 0.0), # 116
(9.243829442823772, 7.04830504435266, 7.632093362938321, 8.056111029444182, 7.02313718419674, 3.323555141118853, 2.9998041194738763, 2.5208740813181603, 3.5959129388307343, 1.4747943502270324, 1.1479250164705472, 0.6781935872119792, 0.0, 9.413047004858225, 7.46012945933177, 5.739625082352736, 4.424383050681096, 7.1918258776614685, 3.5292237138454245, 2.9998041194738763, 2.3739679579420376, 3.51156859209837, 2.6853703431480613, 1.5264186725876645, 0.6407550040320601, 0.0), # 117
(9.214297245985211, 7.0120436072457135, 7.615497548340306, 8.03435789116525, 7.009286202577227, 3.317159168158581, 2.9865122214896576, 2.51479527536254, 3.5899160365213114, 1.46948389924369, 1.143989752709904, 0.6761992632811126, 0.0, 9.393295573379024, 7.438191896092237, 5.71994876354952, 4.40845169773107, 7.179832073042623, 3.5207133855075567, 2.9865122214896576, 2.369399405827558, 3.5046431012886137, 2.678119297055084, 1.5230995096680613, 0.6374585097496104, 0.0), # 118
(9.184546916944742, 6.976249595477001, 7.598956538421437, 8.012700459908778, 6.99521932355948, 3.3108761573001524, 2.973403979075378, 2.5089860290900607, 3.5840533058483475, 1.4642565220650932, 1.1401204476261382, 0.6742234638017862, 0.0, 9.373322671729932, 7.416458101819647, 5.70060223813069, 4.392769566195279, 7.168106611696695, 3.5125804407260848, 2.973403979075378, 2.3649115409286803, 3.49760966177974, 2.670900153302927, 1.5197913076842873, 0.6342045086797276, 0.0), # 119
(9.154542089925162, 6.940867657993644, 7.582437490410635, 7.991098997720545, 6.980916464638998, 3.304690006307063, 2.9604566564951265, 2.5034269924163928, 3.578308313179186, 1.4591017540939766, 1.136309018248736, 0.6722623579111081, 0.0, 9.353098006322597, 7.394885937022188, 5.68154509124368, 4.377305262281929, 7.156616626358372, 3.50479778938295, 2.9604566564951265, 2.360492861647902, 3.490458232319499, 2.663699665906849, 1.516487498082127, 0.6309879689085133, 0.0), # 120
(9.124246399149268, 6.90584244374276, 7.565907561536823, 7.969513766646325, 6.966357543311279, 3.29858461294281, 2.94764751801299, 2.4980988152572112, 3.572664624881166, 1.4540091307330743, 1.1325473816071863, 0.6703121147461852, 0.0, 9.33259128356866, 7.373433262208036, 5.662736908035931, 4.362027392199222, 7.145329249762332, 3.497338341360096, 2.94764751801299, 2.356131866387721, 3.4831787716556395, 2.656504588882109, 1.5131815123073646, 0.6278038585220692, 0.0), # 121
(9.093623478839854, 6.871118601671464, 7.549333909028926, 7.947905028731892, 6.951522477071823, 3.292543874970886, 2.9349538278930587, 2.492982147528187, 3.5671058073216297, 1.4489681873851195, 1.1288274547309753, 0.6683689034441251, 0.0, 9.31177220987977, 7.352057937885375, 5.644137273654876, 4.346904562155357, 7.1342116146432595, 3.490175006539462, 2.9349538278930587, 2.351817053550633, 3.4757612385359113, 2.6493016762439643, 1.5098667818057854, 0.6246471456064968, 0.0), # 122
(9.062636963219719, 6.836640780726876, 7.532683690115864, 7.92623304602302, 6.936391183416127, 3.28655169015479, 2.9223528503994194, 2.4880576391449933, 3.5616154268679177, 1.443968459452847, 1.1251411546495909, 0.6664288931420351, 0.0, 9.290610491667572, 7.330717824562385, 5.625705773247954, 4.33190537835854, 7.123230853735835, 3.4832806948029904, 2.9223528503994194, 2.3475369215391355, 3.4681955917080636, 2.642077682007674, 1.5065367380231727, 0.621512798247898, 0.0), # 123
(9.031250486511654, 6.802353629856113, 7.515924062026559, 7.90445808056549, 6.920943579839691, 3.2805919562580144, 2.9098218497961597, 2.483305940023303, 3.5561770498873715, 1.4389994823389904, 1.1214803983925201, 0.664488252977023, 0.0, 9.269075835343711, 7.309370782747252, 5.6074019919625995, 4.316998447016971, 7.112354099774743, 3.476628316032624, 2.9098218497961597, 2.3432799687557244, 3.4604717899198456, 2.634819360188497, 1.5031848124053118, 0.618395784532374, 0.0), # 124
(8.999427682938459, 6.768201798006293, 7.499022181989936, 7.88254039440507, 6.905159583838015, 3.274648571044058, 2.8973380903473696, 2.478707700078788, 3.5507742427473308, 1.4340507914462837, 1.1178371029892504, 0.6625431520861957, 0.0, 9.247137947319828, 7.2879746729481525, 5.5891855149462515, 4.30215237433885, 7.1015484854946616, 3.470190780110303, 2.8973380903473696, 2.3390346936028985, 3.4525797919190073, 2.6275134648016905, 1.4998044363979874, 0.6152910725460268, 0.0), # 125
(8.967132186722928, 6.734129934124536, 7.481945207234916, 7.8604402495875405, 6.889019112906595, 3.2687054322764144, 2.884878836317135, 2.474243569227122, 3.545390571815139, 1.4291119221774609, 1.1142031854692689, 0.6605897596066612, 0.0, 9.224766534007578, 7.266487355673273, 5.571015927346345, 4.287335766532382, 7.090781143630278, 3.463940996917971, 2.884878836317135, 2.334789594483153, 3.4445095564532977, 2.620146749862514, 1.4963890414469831, 0.6121936303749579, 0.0), # 126
(8.93432763208786, 6.7000826871579555, 7.464660294990421, 7.838117908158674, 6.8725020845409315, 3.26274643771858, 2.872421351969547, 2.469894197383977, 3.5400096034581354, 1.4241724099352562, 1.1105705628620632, 0.6586242446755264, 0.0, 9.201931301818599, 7.244866691430789, 5.552852814310316, 4.272517229805768, 7.080019206916271, 3.457851876337568, 2.872421351969547, 2.3305331697989855, 3.4362510422704657, 2.612705969386225, 1.4929320589980841, 0.6090984261052688, 0.0), # 127
(8.900977653256046, 6.666004706053673, 7.447134602485375, 7.815533632164248, 6.855588416236526, 3.2567554851340508, 2.859942901568691, 2.465640234465026, 3.534614904043661, 1.4192217901224033, 1.1069311521971208, 0.6566427764298991, 0.0, 9.178601957164537, 7.223070540728888, 5.534655760985604, 4.257665370367209, 7.069229808087322, 3.4518963282510366, 2.859942901568691, 2.3262539179528936, 3.427794208118263, 2.6051778773880834, 1.4894269204970751, 0.6060004278230613, 0.0), # 128
(8.867045884450281, 6.631840639758805, 7.4293352869486995, 7.792647683650037, 6.838258025488874, 3.250716472286322, 2.8474207493786565, 2.4614623303859418, 3.529190039939058, 1.4142495981416365, 1.1032768705039286, 0.6546415240068865, 0.0, 9.154748206457038, 7.20105676407575, 5.516384352519642, 4.242748794424909, 7.058380079878116, 3.4460472625403185, 2.8474207493786565, 2.321940337347373, 3.419129012744437, 2.597549227883346, 1.4858670573897401, 0.6028946036144368, 0.0), # 129
(8.832495959893366, 6.5975351372204685, 7.411229505609316, 7.769420324661814, 6.820490829793475, 3.2446132969388883, 2.8348321596635313, 2.457341135062396, 3.5237185775116666, 1.4092453693956895, 1.0995996348119743, 0.6526166565435961, 0.0, 9.130339756107748, 7.178783221979556, 5.4979981740598705, 4.2277361081870675, 7.047437155023333, 3.4402775890873545, 2.8348321596635313, 2.3175809263849203, 3.4102454148967376, 2.589806774887272, 1.4822459011218634, 0.5997759215654973, 0.0), # 130
(8.797291513808094, 6.563032847385783, 7.392784415696151, 7.7458118172453565, 6.802266746645829, 3.238429856855247, 2.8221543966874045, 2.4532572984100627, 3.5181840831288285, 1.4041986392872965, 1.0958913621507447, 0.6505643431771354, 0.0, 9.105346312528312, 7.156207774948489, 5.479456810753724, 4.212595917861889, 7.036368166257657, 3.4345602177740875, 2.8221543966874045, 2.3131641834680337, 3.4011333733229145, 2.5819372724151193, 1.4785568831392302, 0.596639349762344, 0.0), # 131
(8.76139618041726, 6.528278419201865, 7.373967174438122, 7.72178242344644, 6.783565693541435, 3.2321500497988933, 2.8093647247143627, 2.449191470344614, 3.5125701231578845, 1.3990989432191914, 1.0921439695497275, 0.6484807530446118, 0.0, 9.079737582130376, 7.13328828349073, 5.460719847748638, 4.1972968296575734, 7.025140246315769, 3.4288680584824593, 2.8093647247143627, 2.3086786069992096, 3.3917828467707176, 2.573927474482147, 1.4747934348876244, 0.5934798562910787, 0.0), # 132
(8.724773593943663, 6.493216501615832, 7.354744939064153, 7.697292405310838, 6.764367587975791, 3.225757773533322, 2.7964404080084946, 2.445124300781722, 3.5068602639661752, 1.3939358165941083, 1.0883493740384103, 0.6463620552831327, 0.0, 9.053483271325586, 7.10998260811446, 5.44174687019205, 4.181807449782324, 7.0137205279323505, 3.4231740210944106, 2.7964404080084946, 2.3041126953809443, 3.3821837939878954, 2.5657641351036133, 1.4709489878128308, 0.590292409237803, 0.0), # 133
(8.687387388610095, 6.457791743574804, 7.33508486680317, 7.672302024884328, 6.7446523474443945, 3.2192369258220297, 2.7833587108338893, 2.44103643963706, 3.5010380719210428, 1.388698794814781, 1.0844994926462799, 0.6442044190298056, 0.0, 9.026553086525583, 7.0862486093278605, 5.422497463231399, 4.166096384444343, 7.0020761438420855, 3.417451015491884, 2.7833587108338893, 2.2994549470157355, 3.3723261737221972, 2.557434008294776, 1.4670169733606342, 0.5870719766886187, 0.0), # 134
(8.649201198639354, 6.421948794025897, 7.314954114884091, 7.646771544212684, 6.724399889442747, 3.212571404428512, 2.770096897454634, 2.4369085368263, 3.4950871133898262, 1.3833774132839443, 1.0805862424028239, 0.6420040134217377, 0.0, 8.99891673414202, 7.0620441476391145, 5.402931212014119, 4.150132239851832, 6.9901742267796525, 3.41167195155682, 2.770096897454634, 2.2946938603060802, 3.3621999447213735, 2.548923848070895, 1.4629908229768183, 0.583813526729627, 0.0), # 135
(8.610178658254235, 6.385632301916229, 7.294319840535841, 7.62066122534168, 6.703590131466344, 3.205745107116265, 2.7566322321348173, 2.4327212422651154, 3.4889909547398688, 1.3779612074043308, 1.0766015403375297, 0.6397570075960368, 0.0, 8.970543920586536, 7.037327083556404, 5.383007701687648, 4.133883622212991, 6.9779819094797375, 3.4058097391711617, 2.7566322321348173, 2.289817933654475, 3.351795065733172, 2.540220408447227, 1.4588639681071682, 0.58051202744693, 0.0), # 136
(8.570283401677534, 6.348786916192918, 7.273149200987342, 7.593931330317094, 6.682202991010689, 3.1987419316487826, 2.7429419791385277, 2.428455205869179, 3.4827331623385107, 1.3724397125786756, 1.0725373034798844, 0.63745957068981, 0.0, 8.941404352270776, 7.012055277587909, 5.362686517399421, 4.117319137736026, 6.965466324677021, 3.3998372882168506, 2.7429419791385277, 2.284815665463416, 3.3411014955053444, 2.5313104434390317, 1.4546298401974684, 0.577162446926629, 0.0), # 137
(8.529479063132047, 6.311357285803083, 7.251409353467515, 7.566542121184698, 6.660218385571278, 3.1915457757895624, 2.729003402729852, 2.4240910775541624, 3.4762973025530934, 1.3668024642097119, 1.0683854488593754, 0.6351078718401649, 0.0, 8.91146773560639, 6.986186590241813, 5.341927244296877, 4.100407392629135, 6.952594605106187, 3.3937275085758274, 2.729003402729852, 2.2796755541354017, 3.330109192785639, 2.5221807070615663, 1.450281870693503, 0.5737597532548258, 0.0), # 138
(8.487729276840568, 6.273288059693839, 7.229067455205284, 7.538453859990269, 6.63761623264361, 3.184140537302099, 2.7147937671728797, 2.4196095072357395, 3.469666941750957, 1.3610389977001744, 1.0641378935054902, 0.6326980801842089, 0.0, 8.880703777005019, 6.959678882026297, 5.32068946752745, 4.083116993100523, 6.939333883501914, 3.3874533101300353, 2.7147937671728797, 2.274386098072928, 3.318808116321805, 2.51281795333009, 1.4458134910410567, 0.5702989145176218, 0.0), # 139
(8.444997677025897, 6.234523886812306, 7.206090663429573, 7.509626808779583, 6.614376449723186, 3.176510113949888, 2.7002903367316984, 2.4149911448295818, 3.462825646299444, 1.3551388484527966, 1.0597865544477159, 0.6302263648590494, 0.0, 8.849082182878314, 6.932490013449542, 5.298932772238579, 4.0654165453583895, 6.925651292598888, 3.3809876027614147, 2.7002903367316984, 2.2689357956784915, 3.307188224861593, 2.5032089362598615, 1.4412181326859146, 0.5667748988011189, 0.0), # 140
(8.40124789791083, 6.195009416105602, 7.1824461353693, 7.480021229598415, 6.590478954305501, 3.1686384034964257, 2.6854703756703975, 2.4102166402513627, 3.455756982565893, 1.349091551870313, 1.0553233487155398, 0.6276888950017938, 0.0, 8.816572659637913, 6.904577845019731, 5.276616743577699, 4.047274655610939, 6.911513965131786, 3.3743032963519077, 2.6854703756703975, 2.26331314535459, 3.2952394771527507, 2.4933404098661387, 1.4364892270738603, 0.5631826741914184, 0.0), # 141
(8.356443573718156, 6.154689296520844, 7.158101028253392, 7.44959738449254, 6.565903663886058, 3.1605093037052074, 2.670311148253063, 2.4052666434167547, 3.448444516917647, 1.3428866433554572, 1.0507401933384497, 0.6250818397495496, 0.0, 8.783144913695466, 6.875900237245045, 5.253700966692247, 4.028659930066371, 6.896889033835294, 3.3673733007834565, 2.670311148253063, 2.2575066455037196, 3.282951831943029, 2.4831991281641805, 1.4316202056506786, 0.5595172087746222, 0.0), # 142
(8.310548338670674, 6.113508177005149, 7.133022499310772, 7.418315535507731, 6.540630495960352, 3.152106712339729, 2.6547899187437842, 2.4001218042414303, 3.4408718157220486, 1.3365136583109634, 1.0460290053459322, 0.6224013682394242, 0.0, 8.748768651462617, 6.846415050633665, 5.230145026729661, 4.009540974932889, 6.881743631444097, 3.360170525938002, 2.6547899187437842, 2.251504794528378, 3.270315247980176, 2.472771845169244, 1.4266044998621543, 0.5557734706368318, 0.0), # 143
(8.263525826991184, 6.071410706505636, 7.107177705770357, 7.386135944689768, 6.514639368023886, 3.1434145271634857, 2.6388839514066493, 2.3947627726410623, 3.4330224453464364, 1.3299621321395652, 1.0411817017674754, 0.619643649608525, 0.0, 8.713413579351014, 6.816080145693774, 5.205908508837376, 3.9898863964186946, 6.866044890692873, 3.3526678816974873, 2.6388839514066493, 2.245296090831061, 3.257319684011943, 2.4620453148965895, 1.4214355411540713, 0.5519464278641489, 0.0), # 144
(8.215339672902477, 6.0283415339694235, 7.080533804861075, 7.353018874084421, 6.487910197572155, 3.134416645939974, 2.6225705105057466, 2.3891701985313234, 3.424879972158151, 1.3232216002439972, 1.036190199632566, 0.6168048529939595, 0.0, 8.6770494037723, 6.784853382933553, 5.180950998162829, 3.969664800731991, 6.849759944316302, 3.344838277943853, 2.6225705105057466, 2.238869032814267, 3.2439550987860777, 2.451006291361474, 1.4161067609722149, 0.548031048542675, 0.0), # 145
(8.16595351062735, 5.984245308343629, 7.053057953811847, 7.318924585737469, 6.460422902100661, 3.1250969664326886, 2.605826860305165, 2.3833247318278863, 3.4164279625245353, 1.3162815980269928, 1.0310464159706916, 0.6138811475328351, 0.0, 8.639645831138118, 6.7526926228611845, 5.155232079853457, 3.948844794080978, 6.832855925049071, 3.3366546245590407, 2.605826860305165, 2.2322121188804918, 3.2302114510503306, 2.439641528579157, 1.4106115907623695, 0.5440223007585119, 0.0), # 146
(8.1153309743886, 5.93906667857537, 7.024717309851591, 7.283813341694685, 6.4321573991049, 3.1154393864051255, 2.5886302650689905, 2.3772070224464232, 3.40764998281293, 1.3091316608912866, 1.0257422678113395, 0.6108687023622593, 0.0, 8.601172567860118, 6.719555725984851, 5.1287113390566965, 3.9273949826738592, 6.81529996562586, 3.3280898314249923, 2.5886302650689905, 2.2253138474322327, 3.21607869955245, 2.4279377805648954, 1.4049434619703185, 0.5399151525977609, 0.0), # 147
(8.063435698409021, 5.892750293611764, 6.9954790302092364, 7.247645404001847, 6.403093606080374, 3.105427803620781, 2.5709579890613132, 2.3707977203026074, 3.398529599390676, 1.301761324239612, 1.0202696721839972, 0.6077636866193392, 0.0, 8.561599320349941, 6.68540055281273, 5.101348360919985, 3.905283972718835, 6.797059198781352, 3.3191168084236504, 2.5709579890613132, 2.2181627168719866, 3.201546803040187, 2.4158818013339496, 1.3990958060418472, 0.535704572146524, 0.0), # 148
(8.010231316911412, 5.845240802399927, 6.965310272113703, 7.210381034704727, 6.37321144052258, 3.0950461158431497, 2.5527872965462204, 2.3640774753121114, 3.3890503786251127, 1.2941601234747035, 1.0146205461181517, 0.6045622694411826, 0.0, 8.520895795019237, 6.650184963853008, 5.073102730590758, 3.88248037042411, 6.778100757250225, 3.3097084654369557, 2.5527872965462204, 2.21074722560225, 3.18660572026129, 2.403460344901576, 1.3930620544227408, 0.5313855274909026, 0.0), # 149
(7.955681464118564, 5.796482853886981, 6.934178192793912, 7.171980495849104, 6.342490819927017, 3.0842782208357287, 2.5340954517878003, 2.3570269373906068, 3.3791958868835836, 1.2863175939992944, 1.0087868066432906, 0.601260619964897, 0.0, 8.479031698279647, 6.6138668196138655, 5.043934033216452, 3.8589527819978824, 6.758391773767167, 3.2998377123468496, 2.5340954517878003, 2.2030558720255207, 3.1712454099635083, 2.390660165283035, 1.3868356385587826, 0.5269529867169983, 0.0), # 150
(7.899749774253275, 5.746421097020041, 6.902049949478785, 7.132404049480748, 6.310911661789184, 3.0731080163620113, 2.5148597190501416, 2.3496267564537683, 3.3689496905334293, 1.2782232712161197, 1.002760370788901, 0.5978549073275894, 0.0, 8.435976736542818, 6.576403980603482, 5.013801853944504, 3.8346698136483583, 6.737899381066859, 3.2894774590352753, 2.5148597190501416, 2.1950771545442938, 3.155455830894592, 2.377468016493583, 1.3804099898957571, 0.5224019179109128, 0.0), # 151
(7.842399881538343, 5.6950001807462245, 6.868892699397251, 7.091611957645439, 6.278453883604579, 3.0615194001854955, 2.4950573625973322, 2.3418575824172674, 3.3582953559419897, 1.2698666905279126, 0.9965331555844703, 0.5943413006663675, 0.0, 8.391700616220398, 6.537754307330042, 4.982665777922351, 3.809600071583737, 6.716590711883979, 3.2786006153841742, 2.4950573625973322, 2.1867995715610684, 3.1392269418022893, 2.36387065254848, 1.3737785398794504, 0.5177272891587478, 0.0), # 152
(7.78359542019656, 5.642164754012652, 6.834673599778224, 7.049564482388949, 6.245097402868703, 3.049496270069676, 2.4746656466934596, 2.333700065196776, 3.3472164494766075, 1.2612373873374074, 0.9900970780594861, 0.5907159691183387, 0.0, 8.346173043724027, 6.497875660301725, 4.95048539029743, 3.783712162012222, 6.694432898953215, 3.2671800912754865, 2.4746656466934596, 2.17821162147834, 3.1225487014343516, 2.3498548274629836, 1.3669347199556448, 0.5129240685466048, 0.0), # 153
(7.723300024450729, 5.587859465766439, 6.7993598078506325, 7.006221885757057, 6.210822137077053, 3.0370225237780484, 2.453661835602614, 2.325134854707968, 3.3356965375046217, 1.2523248970473384, 0.9834440552434354, 0.5869750818206104, 0.0, 8.299363725465357, 6.456725900026714, 4.917220276217177, 3.7569746911420143, 6.671393075009243, 3.2551887965911552, 2.453661835602614, 2.169301802698606, 3.1054110685385266, 2.335407295252353, 1.3598719615701265, 0.5079872241605854, 0.0), # 154
(7.6614773285236355, 5.532028964954703, 6.762918480843396, 6.961544429795533, 6.175608003725131, 3.0240820590741087, 2.4320231935888805, 2.316142600866515, 3.323719186393376, 1.2431187550604388, 0.9765660041658056, 0.5831148079102902, 0.0, 8.251242367856026, 6.414262887013191, 4.882830020829028, 3.7293562651813157, 6.647438372786752, 3.242599641213121, 2.4320231935888805, 2.160058613624363, 3.0878040018625654, 2.320514809931845, 1.3525836961686795, 0.5029117240867913, 0.0), # 155
(7.598090966638081, 5.474617900524564, 6.725316775985439, 6.915492376550157, 6.139434920308432, 3.0106587737213526, 2.40972698491635, 2.3067039535880913, 3.3112679625102084, 1.2336084967794434, 0.9694548418560842, 0.5791313165244852, 0.0, 8.201778677307685, 6.370444481769337, 4.84727420928042, 3.7008254903383295, 6.622535925020417, 3.2293855350233276, 2.40972698491635, 2.150470552658109, 3.069717460154216, 2.3051641255167192, 1.3450633551970879, 0.49769253641132405, 0.0), # 156
(7.533104573016862, 5.415570921423138, 6.686521850505682, 6.868025988066703, 6.102282804322456, 2.9967365654832747, 2.3867504738491094, 2.2967995627883675, 3.2983264322224626, 1.2237836576070855, 0.9621024853437583, 0.5750207768003032, 0.0, 8.150942360231976, 6.325228544803333, 4.810512426718791, 3.671350972821256, 6.596652864444925, 3.2155193879037145, 2.3867504738491094, 2.140526118202339, 3.051141402161228, 2.2893419960222348, 1.3373043701011365, 0.4923246292202853, 0.0), # 157
(7.464680946405239, 5.353748694041236, 6.644659961585297, 6.817327186238432, 6.062454070580665, 2.9814309445183143, 2.3625533604639286, 2.285748730145572, 3.2838873638663655, 1.213341479072786, 0.9542659587564906, 0.570633297016195, 0.0, 8.096485859415345, 6.276966267178143, 4.771329793782452, 3.640024437218358, 6.567774727732731, 3.200048222203801, 2.3625533604639286, 2.129593531798796, 3.0312270352903323, 2.2724423954128112, 1.3289319923170593, 0.48670442673102154, 0.0), # 158
(7.382286766978402, 5.282809876299521, 6.58894818200249, 6.7529828690913405, 6.010127539854418, 2.95965229467081, 2.334106381692858, 2.2696723053184926, 3.2621424204073812, 1.2005702485246865, 0.9445694892698324, 0.5651135436402591, 0.0, 8.025427646920194, 6.216248980042849, 4.722847446349162, 3.601710745574059, 6.5242848408147625, 3.17754122744589, 2.334106381692858, 2.114037353336293, 3.005063769927209, 2.250994289697114, 1.3177896364004982, 0.4802554432999565, 0.0), # 159
(7.284872094904309, 5.202172001162321, 6.51826746496324, 6.673933132806645, 5.94428008756453, 2.9308657560278157, 2.301121874191892, 2.248166328969728, 3.2324750757428835, 1.1853014129657236, 0.9328765847682567, 0.5583751624073207, 0.0, 7.93642060889358, 6.142126786480525, 4.664382923841283, 3.55590423889717, 6.464950151485767, 3.147432860557619, 2.301121874191892, 2.0934755400198686, 2.972140043782265, 2.2246443776022153, 1.3036534929926482, 0.47292472737839286, 0.0), # 160
(7.17322205458596, 5.11236079574043, 6.4333724765919245, 6.5809293778175455, 5.865595416188075, 2.895420057582683, 2.263840723003438, 2.2215002221290754, 3.1952765889996724, 1.1676645482927346, 0.9192902757666179, 0.5504806224089643, 0.0, 7.830374044819097, 6.055286846498606, 4.596451378833089, 3.5029936448782033, 6.390553177999345, 3.1101003109807053, 2.263840723003438, 2.0681571839876307, 2.9327977080940375, 2.1936431259391824, 1.2866744953183848, 0.46476007234003913, 0.0), # 161
(7.048121770426357, 5.013901987144635, 6.335017883012913, 6.474723004557244, 5.7747572282021356, 2.853663928328766, 2.2225038131699044, 2.1899434058263343, 3.150938219304545, 1.147789230402558, 0.9039135927797701, 0.5414923927367745, 0.0, 7.708197254180333, 5.956416320104519, 4.519567963898851, 3.4433676912076736, 6.30187643860909, 3.065920768156868, 2.2225038131699044, 2.03833137737769, 2.8873786141010678, 2.158241001519082, 1.2670035766025827, 0.4558092715586033, 0.0), # 162
(6.9103563668284975, 4.90732130248573, 6.223958350350585, 6.35606541345895, 5.672449226083792, 2.8059460972594175, 2.1773520297337003, 2.153765301091302, 3.0998512257843016, 1.1258050351920315, 0.8868495663225682, 0.5314729424823361, 0.0, 7.570799536460879, 5.846202367305696, 4.43424783161284, 3.3774151055760937, 6.199702451568603, 3.015271421527823, 2.1773520297337003, 2.0042472123281554, 2.836224613041896, 2.118688471152984, 1.2447916700701172, 0.4461201184077937, 0.0), # 163
(6.760710968195384, 4.793144468874502, 6.100948544729314, 6.225708004955863, 5.559355112310126, 2.752615293367992, 2.128626257737233, 2.113235328953779, 3.0424068675657407, 1.1018415385579923, 0.8682012269098661, 0.5204847407372336, 0.0, 7.419090191144328, 5.725332148109569, 4.34100613454933, 3.305524615673976, 6.0848137351314815, 2.9585294605352903, 2.128626257737233, 1.9661537809771372, 2.779677556155063, 2.075236001651955, 1.2201897089458629, 0.43574040626131844, 0.0), # 164
(6.599970698930017, 4.671897213421746, 5.966743132273474, 6.084402179481189, 5.436158589358215, 2.694020245647842, 2.076567382222911, 2.068622910443561, 2.9789964037756596, 1.0760283163972786, 0.8480716050565187, 0.5085902565930517, 0.0, 7.25397851771427, 5.594492822523568, 4.2403580252825925, 3.2280849491918353, 5.957992807551319, 2.8960720746209856, 2.076567382222911, 1.9243001754627442, 2.7180792946791077, 2.0281340598270634, 1.1933486264546949, 0.42471792849288603, 0.0), # 165
(6.428920683435397, 4.54410526323825, 5.82209677910744, 5.932899337468126, 5.3035433597051425, 2.630509683092322, 2.021416288233143, 2.020197466590449, 2.9100110935408576, 1.0484949446067282, 0.8265637312773799, 0.49585195914137514, 0.0, 7.0763738156542955, 5.454371550555126, 4.1328186563869, 3.145484833820184, 5.820022187081715, 2.8282764532266285, 2.021416288233143, 1.8789354879230868, 2.6517716798525712, 1.9776331124893758, 1.1644193558214881, 0.41310047847620457, 0.0), # 166
(6.248346046114523, 4.410294345434805, 5.667764151355587, 5.771950879349882, 5.1621931258279865, 2.562432334694784, 1.9634138608103373, 1.9682284184242402, 2.835842195988133, 1.0193709990831787, 0.8037806360873045, 0.48233231747378824, 0.0, 6.887185384447996, 5.30565549221167, 4.0189031804365225, 3.058112997249536, 5.671684391976266, 2.755519785793936, 1.9634138608103373, 1.8303088104962744, 2.5810965629139933, 1.9239836264499612, 1.1335528302711175, 0.4009358495849823, 0.0), # 167
(6.059031911370395, 4.270990187122201, 5.50449991514229, 5.60230820555966, 5.012791590203827, 2.490136929448583, 1.902800984996902, 1.9129851869747332, 2.7568809702442847, 0.9887860557234682, 0.7798253500011468, 0.468093800681876, 0.0, 6.6873225235789615, 5.149031807500635, 3.8991267500057343, 2.9663581671704042, 5.513761940488569, 2.6781792617646265, 1.902800984996902, 1.7786692353204163, 2.5063957951019136, 1.867436068519887, 1.100899983028458, 0.3882718351929274, 0.0), # 168
(5.861763403606015, 4.1267185154112305, 5.333058736591924, 5.4247227165306615, 4.856022455309747, 2.413972196347072, 1.8398185458352458, 1.8547371932717271, 2.6735186754361124, 0.9568696904244344, 0.7548009035337614, 0.45319887785722274, 0.0, 6.477694532530785, 4.985187656429449, 3.774004517668807, 2.8706090712733023, 5.347037350872225, 2.596632070580418, 1.8398185458352458, 1.724265854533623, 2.4280112276548733, 1.808240905510221, 1.066611747318385, 0.3751562286737483, 0.0), # 169
(5.657325647224384, 3.978005057412684, 5.154195281828863, 5.23994581269609, 4.692569423622822, 2.334286864383604, 1.7747074283677764, 1.7937538583450197, 2.5861465706904125, 0.9237514790829147, 0.7288103272000027, 0.4377100180914133, 0.0, 6.259210710787055, 4.814810199005545, 3.6440516360000137, 2.7712544372487433, 5.172293141380825, 2.5112554016830275, 1.7747074283677764, 1.6673477602740028, 2.346284711811411, 1.7466486042320304, 1.0308390563657726, 0.36163682340115316, 0.0), # 170
(5.4465037666285, 3.82537554023735, 4.968664216977482, 5.048728894489152, 4.523116197620137, 2.2514296625515327, 1.7077085176369027, 1.7303046032244096, 2.495155915133985, 0.8895609975957474, 0.7019566515147247, 0.4216896904760322, 0.0, 6.032780357831365, 4.638586595236354, 3.509783257573624, 2.6686829927872413, 4.99031183026797, 2.4224264445141737, 1.7077085176369027, 1.6081640446796661, 2.2615580988100685, 1.6829096314963843, 0.9937328433954964, 0.3477614127488501, 0.0), # 171
(5.230082886221365, 3.6693556909960217, 4.777220208162156, 4.851823362343048, 4.348346479778769, 2.1657493198442115, 1.6390626986850327, 1.664658848939696, 2.4009379678936282, 0.8544278218597702, 0.6743429069927823, 0.4052003641026643, 0.0, 5.799312773147303, 4.457204005129307, 3.3717145349639117, 2.56328346557931, 4.8018759357872565, 2.3305223885155746, 1.6390626986850327, 1.5469637998887225, 2.1741732398893845, 1.6172744541143496, 0.9554440416324312, 0.3335777900905475, 0.0), # 172
(5.00884813040598, 3.510471236799489, 4.58061792150726, 4.649980616690982, 4.168943972575801, 2.077594565254994, 1.5690108565545748, 1.5970860165206766, 2.303883988096141, 0.8184815277718206, 0.6460721241490297, 0.3883045080628938, 0.0, 5.5597172562184625, 4.271349588691831, 3.2303606207451483, 2.4554445833154612, 4.607767976192282, 2.235920423128947, 1.5690108565545748, 1.483996118039281, 2.0844719862879004, 1.5499935388969943, 0.916123584301452, 0.31913374879995354, 0.0), # 173
(4.783584623585344, 3.349247904758541, 4.3796120231371685, 4.443952057966156, 3.9855923784883105, 1.987314127777233, 1.4977938762879377, 1.5278555269971503, 2.204385234868321, 0.7818516912287369, 0.6172473334983214, 0.37106459144830567, 0.0, 5.314903106528433, 4.081710505931362, 3.0862366674916064, 2.34555507368621, 4.408770469736642, 2.1389977377960103, 1.4977938762879377, 1.4195100912694523, 1.9927961892441552, 1.4813173526553853, 0.8759224046274336, 0.3044770822507765, 0.0), # 174
(4.555077490162455, 3.18621142198397, 4.174957179176257, 4.2344890866017755, 3.7989753999933793, 1.8952567364042834, 1.425652642927529, 1.457236801398915, 2.102832967336968, 0.7446678881273562, 0.5879715655555117, 0.35354308335048457, 0.0, 5.0657796235608075, 3.8889739168553294, 2.939857827777558, 2.234003664382068, 4.205665934673936, 2.040131521958481, 1.425652642927529, 1.3537548117173452, 1.8994876999966896, 1.411496362200592, 0.8349914358352515, 0.28965558381672457, 0.0), # 175
(4.324111854540319, 3.0218875155865668, 3.9674080557488987, 4.0223431030310435, 3.609776739568087, 1.8017711201294973, 1.3528280415157574, 1.3854992607557703, 1.9996184446288805, 0.7070596943645169, 0.558347850835455, 0.33580245286101496, 0.0, 4.813256106799174, 3.693826981471164, 2.791739254177275, 2.1211790830935504, 3.999236889257761, 1.9396989650580787, 1.3528280415157574, 1.2869793715210696, 1.8048883697840434, 1.3407810343436815, 0.7934816111497798, 0.2747170468715061, 0.0), # 176
(4.0914728411219325, 2.856801912677122, 3.7577193189794698, 3.808265507687162, 3.4186800996895155, 1.7072060079462288, 1.2795609570950313, 1.3129123260975137, 1.8951329258708567, 0.6691566858370562, 0.528479219853006, 0.3179051690714816, 0.0, 4.5582418557271245, 3.496956859786297, 2.6423960992650297, 2.0074700575111684, 3.7902658517417134, 1.838077256536519, 1.2795609570950313, 1.2194328628187348, 1.7093400498447577, 1.269421835895721, 0.751543863795894, 0.25970926478882933, 0.0), # 177
(3.8579455743102966, 2.6914803403664256, 3.5466456349923448, 3.593007701003337, 3.226369182834742, 1.6119101288478317, 1.2060922747077587, 1.239745418453944, 1.7897676701896952, 0.6310884384418126, 0.49846870312301883, 0.299913701073469, 0.0, 4.301646169828252, 3.299050711808158, 2.4923435156150937, 1.8932653153254375, 3.5795353403793904, 1.7356435858355217, 1.2060922747077587, 1.1513643777484512, 1.613184591417371, 1.1976692336677792, 0.7093291269984691, 0.24468003094240237, 0.0), # 178
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179
)
passenger_allighting_rate = (
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 0
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 1
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 2
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 3
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 4
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 5
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 6
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 7
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 8
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 9
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 10
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 11
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 12
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 13
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 14
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 15
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 16
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 24
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 25
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 26
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 27
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 28
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 29
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 30
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 31
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 32
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 33
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 34
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 35
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 36
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 37
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 38
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 39
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 40
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 41
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 42
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 43
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 44
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 45
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 46
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 47
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 48
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 49
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 50
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 51
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 52
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 53
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 54
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 55
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 56
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 57
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 58
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 59
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 60
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 61
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 62
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 63
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 64
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 65
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 66
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 67
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 68
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 69
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 70
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 71
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 72
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 73
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 74
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 75
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 76
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 77
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 78
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 79
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 80
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 81
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 82
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 83
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 84
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 85
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 86
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 87
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 88
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 89
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 90
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 91
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 92
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 93
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 94
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 95
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 96
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 97
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 98
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 99
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 100
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 101
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 102
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 103
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 104
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 105
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 106
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 107
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 108
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 109
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 110
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 111
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 112
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 113
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 114
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 115
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 116
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 117
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 118
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 119
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 120
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 121
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 122
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(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 153
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 154
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 155
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 156
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 157
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 158
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 159
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 160
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 161
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 162
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 163
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 164
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 165
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 166
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 167
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 168
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 169
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 170
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 171
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 172
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 173
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 174
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 175
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 176
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 177
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 178
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179
)
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 8991598675325360468762009371570610170
#index for seed sequence child
child_seed_index = (
1, # 0
68, # 1
)
|
"""
PASSENGERS
"""
num_passengers = 19216
passenger_arriving = ((7, 4, 4, 3, 2, 1, 4, 2, 4, 2, 0, 0, 0, 7, 5, 8, 3, 7, 1, 3, 0, 1, 2, 1, 1, 0), (4, 7, 2, 3, 3, 1, 2, 5, 2, 1, 1, 0, 0, 6, 4, 4, 3, 2, 1, 5, 1, 1, 1, 0, 1, 0), (6, 4, 5, 6, 2, 1, 2, 4, 1, 1, 0, 0, 0, 11, 3, 6, 7, 7, 0, 3, 2, 1, 2, 0, 0, 0), (6, 3, 6, 7, 6, 1, 3, 3, 1, 2, 1, 0, 0, 7, 11, 8, 2, 4, 3, 0, 0, 2, 2, 0, 0, 0), (11, 5, 8, 3, 6, 1, 2, 2, 2, 0, 0, 0, 0, 6, 9, 5, 1, 5, 1, 2, 1, 1, 1, 0, 0, 0), (3, 5, 7, 7, 5, 2, 5, 3, 3, 2, 3, 0, 0, 9, 10, 3, 2, 7, 2, 1, 0, 3, 1, 1, 2, 0), (6, 4, 5, 5, 6, 2, 1, 3, 4, 1, 0, 2, 0, 7, 6, 2, 4, 4, 1, 3, 1, 3, 5, 0, 2, 0), (5, 8, 6, 4, 6, 0, 6, 4, 2, 1, 2, 0, 0, 9, 6, 2, 5, 3, 0, 1, 1, 3, 2, 2, 0, 0), (6, 3, 2, 11, 4, 2, 7, 4, 2, 1, 1, 0, 0, 4, 4, 4, 1, 4, 5, 1, 2, 2, 2, 4, 0, 0), (7, 5, 8, 5, 10, 0, 7, 2, 4, 2, 1, 1, 0, 8, 3, 4, 3, 8, 4, 1, 4, 4, 3, 2, 1, 0), (3, 4, 12, 6, 6, 4, 4, 0, 2, 1, 0, 0, 0, 15, 3, 9, 3, 0, 4, 2, 2, 4, 3, 2, 1, 0), (9, 11, 8, 8, 4, 3, 2, 0, 3, 2, 0, 1, 0, 6, 12, 7, 4, 7, 2, 5, 4, 3, 3, 2, 1, 0), (8, 3, 6, 9, 10, 2, 9, 2, 4, 1, 1, 1, 0, 6, 5, 7, 1, 5, 4, 3, 2, 4, 1, 0, 2, 0), (5, 11, 12, 7, 6, 3, 5, 4, 3, 2, 1, 3, 0, 16, 6, 8, 8, 8, 1, 2, 4, 2, 2, 2, 1, 0), (17, 12, 8, 14, 4, 2, 2, 5, 4, 0, 2, 1, 0, 11, 4, 9, 6, 10, 1, 2, 2, 4, 1, 1, 0, 0), (12, 11, 13, 8, 13, 2, 5, 3, 4, 0, 0, 0, 0, 16, 7, 2, 8, 6, 4, 4, 4, 3, 2, 1, 1, 0), (7, 5, 4, 7, 9, 1, 5, 4, 4, 4, 1, 1, 0, 11, 10, 4, 7, 8, 7, 5, 1, 3, 4, 0, 0, 0), (11, 7, 5, 6, 6, 6, 4, 1, 6, 0, 1, 1, 0, 9, 9, 6, 6, 7, 5, 2, 1, 1, 3, 0, 0, 0), (9, 12, 9, 3, 7, 4, 3, 2, 3, 2, 1, 2, 0, 12, 9, 6, 3, 7, 8, 4, 4, 5, 2, 2, 2, 0), (11, 15, 6, 8, 7, 6, 5, 6, 2, 1, 0, 1, 0, 11, 11, 3, 4, 9, 4, 6, 4, 4, 2, 3, 1, 0), (7, 11, 6, 10, 5, 4, 3, 2, 3, 2, 1, 0, 0, 7, 8, 8, 1, 11, 8, 6, 3, 4, 4, 3, 0, 0), (10, 9, 10, 11, 7, 3, 4, 3, 3, 1, 3, 2, 0, 10, 17, 12, 11, 6, 3, 2, 2, 5, 4, 2, 1, 0), (14, 8, 8, 11, 4, 6, 3, 3, 4, 1, 1, 0, 0, 11, 5, 6, 6, 15, 3, 1, 4, 5, 2, 1, 0, 0), (12, 17, 8, 14, 10, 2, 4, 2, 4, 3, 0, 1, 0, 11, 12, 7, 5, 9, 5, 2, 2, 1, 5, 2, 3, 0), (7, 12, 17, 16, 5, 3, 6, 4, 6, 1, 2, 0, 0, 13, 4, 5, 4, 14, 2, 3, 6, 5, 1, 1, 0, 0), (10, 11, 9, 7, 4, 6, 2, 1, 5, 3, 0, 3, 0, 5, 9, 8, 6, 8, 3, 4, 4, 3, 1, 4, 1, 0), (11, 7, 8, 8, 9, 5, 2, 5, 7, 3, 1, 1, 0, 10, 5, 11, 3, 11, 3, 7, 2, 3, 3, 3, 2, 0), (11, 8, 6, 7, 6, 5, 8, 0, 7, 0, 0, 0, 0, 11, 15, 8, 3, 9, 8, 5, 1, 4, 1, 1, 2, 0), (6, 15, 10, 15, 9, 2, 4, 5, 4, 4, 0, 0, 0, 16, 9, 7, 6, 7, 1, 6, 0, 7, 3, 0, 4, 0), (15, 3, 13, 9, 9, 6, 3, 3, 3, 1, 1, 0, 0, 6, 6, 8, 7, 13, 6, 5, 5, 5, 4, 0, 1, 0), (17, 12, 13, 7, 8, 3, 4, 3, 3, 1, 2, 1, 0, 14, 13, 3, 7, 11, 6, 6, 3, 6, 1, 2, 2, 0), (17, 10, 3, 9, 4, 3, 5, 2, 5, 3, 1, 1, 0, 12, 10, 4, 7, 12, 7, 5, 1, 3, 4, 1, 2, 0), (8, 10, 7, 8, 12, 1, 5, 4, 3, 0, 0, 3, 0, 8, 18, 7, 1, 13, 7, 6, 1, 3, 1, 1, 1, 0), (7, 5, 10, 8, 7, 4, 4, 8, 8, 5, 1, 0, 0, 8, 8, 5, 2, 4, 3, 6, 2, 4, 1, 3, 1, 0), (5, 10, 12, 11, 9, 7, 4, 4, 2, 1, 0, 1, 0, 9, 11, 6, 6, 11, 6, 5, 0, 1, 2, 2, 2, 0), (13, 11, 5, 8, 7, 4, 4, 4, 7, 2, 1, 0, 0, 13, 10, 5, 5, 11, 7, 3, 0, 1, 3, 0, 0, 0), (10, 12, 5, 7, 5, 5, 2, 6, 4, 2, 1, 3, 0, 10, 12, 15, 7, 11, 5, 6, 2, 2, 2, 0, 0, 0), (11, 11, 13, 9, 9, 4, 1, 1, 4, 2, 1, 1, 0, 13, 12, 6, 3, 7, 6, 5, 1, 4, 2, 2, 0, 0), (4, 7, 9, 5, 6, 3, 6, 1, 3, 2, 1, 1, 0, 13, 7, 4, 5, 14, 1, 4, 2, 1, 1, 1, 0, 0), (12, 8, 9, 11, 11, 4, 6, 8, 5, 5, 2, 1, 0, 6, 10, 6, 4, 11, 8, 6, 0, 8, 4, 4, 2, 0), (12, 14, 10, 9, 6, 2, 5, 0, 4, 2, 0, 2, 0, 10, 8, 5, 4, 7, 6, 3, 1, 3, 6, 1, 2, 0), (10, 13, 11, 10, 9, 5, 1, 5, 6, 4, 1, 0, 0, 11, 5, 7, 6, 8, 4, 4, 1, 4, 1, 1, 1, 0), (12, 9, 17, 9, 6, 6, 1, 3, 3, 3, 2, 0, 0, 13, 4, 7, 4, 4, 6, 3, 4, 2, 1, 2, 2, 0), (3, 14, 13, 6, 11, 5, 4, 3, 3, 2, 0, 3, 0, 13, 6, 8, 4, 6, 7, 9, 3, 2, 2, 3, 0, 0), (10, 12, 12, 8, 10, 3, 3, 10, 4, 2, 1, 1, 0, 8, 12, 10, 5, 9, 5, 6, 2, 5, 4, 2, 1, 0), (11, 11, 16, 8, 8, 2, 11, 5, 6, 1, 2, 2, 0, 10, 12, 7, 10, 8, 1, 6, 4, 4, 2, 2, 1, 0), (9, 10, 12, 14, 12, 5, 3, 2, 2, 1, 4, 0, 0, 12, 9, 8, 6, 13, 6, 3, 1, 4, 3, 3, 0, 0), (7, 8, 8, 4, 5, 2, 2, 2, 4, 4, 2, 0, 0, 17, 10, 9, 7, 9, 6, 3, 5, 4, 7, 5, 0, 0), (12, 8, 6, 14, 6, 1, 4, 2, 3, 0, 2, 0, 0, 19, 9, 7, 3, 7, 3, 4, 3, 3, 4, 1, 0, 0), (11, 8, 7, 8, 12, 5, 3, 2, 9, 1, 2, 0, 0, 14, 11, 8, 2, 4, 7, 3, 3, 7, 2, 1, 0, 0), (10, 10, 4, 7, 5, 3, 2, 1, 4, 2, 1, 0, 0, 14, 11, 3, 8, 5, 3, 7, 5, 3, 1, 1, 1, 0), (14, 11, 8, 14, 10, 3, 1, 2, 6, 1, 2, 0, 0, 12, 6, 2, 4, 7, 1, 5, 3, 5, 3, 1, 2, 0), (5, 16, 8, 10, 9, 6, 5, 7, 1, 3, 1, 2, 0, 14, 12, 4, 6, 8, 3, 3, 3, 5, 8, 2, 0, 0), (6, 9, 4, 13, 8, 2, 6, 4, 2, 1, 3, 2, 0, 13, 6, 6, 5, 15, 6, 4, 2, 5, 4, 0, 3, 0), (15, 15, 15, 12, 12, 2, 0, 3, 6, 0, 4, 1, 0, 10, 12, 8, 6, 5, 5, 4, 2, 6, 2, 2, 0, 0), (11, 8, 8, 6, 9, 4, 4, 1, 2, 4, 1, 1, 0, 3, 14, 5, 3, 7, 4, 4, 1, 1, 3, 3, 1, 0), (5, 10, 5, 12, 10, 3, 5, 5, 2, 1, 0, 0, 0, 10, 7, 11, 6, 8, 2, 6, 3, 1, 4, 6, 0, 0), (9, 11, 10, 13, 7, 4, 4, 2, 6, 3, 0, 1, 0, 11, 7, 9, 5, 7, 1, 6, 3, 1, 8, 1, 0, 0), (13, 12, 11, 6, 9, 1, 1, 5, 3, 4, 4, 0, 0, 14, 10, 9, 10, 10, 2, 6, 3, 3, 3, 1, 1, 0), (11, 11, 15, 9, 9, 5, 1, 3, 7, 3, 0, 2, 0, 11, 5, 7, 3, 6, 4, 3, 3, 2, 1, 1, 2, 0), (7, 12, 10, 11, 11, 4, 2, 5, 5, 0, 2, 0, 0, 5, 13, 13, 3, 11, 7, 6, 3, 2, 3, 2, 0, 0), (11, 5, 10, 12, 8, 1, 2, 0, 2, 1, 1, 0, 0, 4, 7, 4, 5, 13, 5, 3, 7, 3, 4, 2, 2, 0), (6, 4, 5, 10, 13, 1, 6, 3, 7, 1, 2, 2, 0, 9, 10, 3, 3, 8, 3, 6, 4, 8, 0, 0, 0, 0), (11, 11, 9, 5, 8, 3, 4, 2, 8, 4, 0, 1, 0, 12, 12, 11, 5, 8, 1, 5, 6, 7, 4, 1, 0, 0), (8, 11, 12, 7, 16, 3, 6, 4, 3, 1, 1, 2, 0, 14, 4, 6, 6, 7, 3, 4, 3, 2, 4, 1, 1, 0), (7, 11, 10, 10, 6, 5, 8, 1, 3, 2, 1, 2, 0, 12, 7, 8, 3, 11, 6, 4, 1, 5, 2, 1, 0, 0), (15, 6, 5, 11, 10, 2, 4, 7, 2, 1, 2, 1, 0, 14, 11, 7, 4, 9, 6, 4, 2, 2, 5, 4, 0, 0), (4, 7, 4, 10, 5, 4, 0, 4, 4, 3, 2, 0, 0, 14, 5, 11, 4, 6, 4, 5, 4, 3, 3, 2, 2, 0), (12, 10, 5, 8, 4, 1, 1, 5, 9, 2, 1, 1, 0, 13, 12, 4, 7, 8, 4, 4, 2, 3, 3, 2, 1, 0), (8, 9, 11, 8, 10, 4, 3, 5, 3, 1, 3, 1, 0, 11, 8, 8, 7, 8, 3, 1, 1, 1, 3, 3, 0, 0), (9, 6, 3, 11, 9, 3, 5, 2, 2, 3, 4, 1, 0, 11, 5, 7, 5, 9, 5, 4, 4, 5, 2, 0, 0, 0), (4, 7, 5, 5, 6, 5, 1, 3, 0, 4, 1, 0, 0, 9, 9, 9, 3, 10, 5, 5, 2, 5, 1, 3, 1, 0), (11, 6, 8, 11, 12, 3, 5, 1, 6, 4, 1, 2, 0, 16, 9, 4, 7, 8, 4, 9, 2, 5, 1, 2, 2, 0), (10, 10, 10, 5, 11, 5, 3, 3, 4, 0, 2, 1, 0, 15, 3, 8, 6, 8, 2, 6, 1, 4, 1, 0, 2, 0), (14, 8, 9, 8, 7, 6, 1, 1, 2, 1, 2, 0, 0, 13, 4, 4, 7, 5, 3, 9, 8, 5, 4, 1, 0, 0), (10, 11, 11, 9, 10, 1, 3, 2, 5, 1, 1, 0, 0, 14, 13, 7, 4, 8, 4, 4, 2, 7, 2, 3, 0, 0), (13, 10, 10, 12, 7, 6, 3, 3, 4, 3, 0, 1, 0, 12, 12, 9, 8, 4, 3, 3, 6, 2, 3, 2, 1, 0), (9, 7, 10, 7, 10, 5, 2, 4, 5, 2, 0, 2, 0, 11, 5, 6, 8, 12, 5, 6, 1, 3, 4, 1, 1, 0), (5, 7, 8, 5, 12, 2, 5, 1, 4, 1, 0, 1, 0, 8, 13, 6, 3, 6, 2, 4, 3, 3, 10, 3, 0, 0), (13, 11, 10, 3, 9, 4, 5, 3, 3, 0, 0, 0, 0, 10, 12, 8, 7, 5, 1, 4, 7, 5, 4, 0, 3, 0), (9, 9, 11, 11, 8, 1, 2, 1, 4, 4, 2, 1, 0, 10, 7, 2, 7, 8, 4, 3, 1, 3, 2, 2, 0, 0), (13, 4, 5, 11, 3, 3, 6, 4, 5, 0, 3, 0, 0, 8, 10, 3, 9, 4, 7, 3, 3, 4, 5, 0, 1, 0), (13, 9, 8, 4, 5, 3, 5, 3, 4, 1, 2, 1, 0, 12, 5, 7, 2, 7, 5, 0, 0, 2, 0, 2, 1, 0), (7, 9, 4, 5, 5, 2, 1, 2, 3, 1, 1, 0, 0, 10, 7, 5, 2, 9, 3, 1, 2, 3, 5, 1, 1, 0), (12, 6, 9, 7, 7, 6, 4, 2, 4, 1, 1, 0, 0, 10, 8, 3, 3, 6, 5, 4, 3, 1, 4, 2, 0, 0), (10, 10, 3, 7, 10, 4, 5, 3, 1, 1, 1, 2, 0, 9, 13, 3, 5, 5, 5, 3, 4, 5, 3, 1, 0, 0), (7, 10, 13, 11, 8, 3, 2, 2, 1, 3, 1, 0, 0, 5, 11, 7, 2, 6, 4, 5, 1, 3, 3, 1, 1, 0), (13, 10, 13, 12, 15, 4, 8, 2, 6, 0, 0, 1, 0, 9, 7, 6, 2, 9, 7, 8, 1, 6, 6, 2, 1, 0), (6, 10, 7, 12, 4, 4, 2, 2, 3, 4, 3, 1, 0, 11, 7, 9, 0, 2, 7, 4, 2, 4, 3, 0, 1, 0), (14, 10, 7, 11, 7, 2, 1, 1, 2, 1, 2, 1, 0, 6, 8, 5, 3, 9, 4, 5, 0, 4, 1, 3, 2, 0), (10, 6, 6, 13, 7, 2, 3, 2, 5, 1, 2, 1, 0, 11, 12, 7, 6, 9, 4, 5, 2, 1, 4, 0, 0, 0), (14, 8, 8, 7, 5, 3, 6, 1, 4, 3, 1, 0, 0, 12, 5, 4, 4, 9, 1, 5, 4, 0, 5, 3, 0, 0), (14, 7, 7, 7, 10, 6, 5, 1, 2, 1, 4, 0, 0, 10, 6, 5, 5, 11, 5, 2, 0, 5, 4, 0, 0, 0), (13, 10, 12, 7, 8, 3, 3, 3, 5, 1, 0, 1, 0, 14, 9, 8, 2, 12, 5, 3, 2, 3, 3, 5, 0, 0), (4, 4, 9, 7, 9, 3, 1, 3, 1, 1, 2, 0, 0, 12, 9, 3, 5, 10, 4, 3, 3, 2, 2, 2, 0, 0), (5, 9, 12, 10, 15, 4, 4, 6, 2, 2, 2, 0, 0, 13, 11, 0, 7, 7, 3, 1, 5, 3, 2, 0, 1, 0), (2, 6, 13, 9, 5, 2, 4, 5, 2, 0, 3, 0, 0, 12, 8, 3, 6, 7, 2, 3, 4, 3, 5, 3, 0, 0), (8, 6, 5, 6, 8, 4, 1, 2, 2, 0, 1, 1, 0, 9, 7, 4, 4, 7, 1, 4, 1, 2, 3, 1, 0, 0), (12, 12, 8, 7, 5, 2, 4, 5, 8, 0, 2, 1, 0, 10, 9, 5, 5, 9, 0, 4, 2, 6, 3, 1, 1, 0), (8, 9, 10, 6, 13, 7, 5, 4, 5, 2, 1, 3, 0, 12, 7, 7, 6, 6, 2, 3, 2, 8, 3, 4, 0, 0), (10, 12, 11, 4, 12, 3, 3, 4, 3, 2, 1, 0, 0, 8, 8, 4, 3, 5, 7, 2, 5, 5, 1, 1, 0, 0), (9, 8, 6, 4, 6, 1, 4, 3, 3, 3, 1, 1, 0, 11, 9, 4, 10, 11, 2, 1, 2, 3, 4, 2, 0, 0), (11, 8, 10, 10, 4, 5, 3, 0, 5, 2, 0, 0, 0, 13, 8, 3, 7, 10, 3, 1, 2, 6, 3, 2, 1, 0), (6, 9, 9, 7, 5, 5, 2, 2, 5, 0, 2, 2, 0, 14, 11, 5, 3, 8, 0, 2, 3, 5, 1, 0, 2, 0), (12, 8, 7, 5, 8, 4, 2, 2, 3, 3, 0, 0, 0, 9, 6, 5, 3, 7, 4, 0, 3, 3, 3, 2, 1, 0), (9, 6, 8, 14, 6, 4, 2, 2, 1, 1, 0, 1, 0, 6, 3, 6, 2, 5, 4, 6, 2, 1, 4, 2, 3, 0), (8, 13, 9, 7, 12, 6, 5, 4, 5, 1, 3, 0, 0, 13, 9, 7, 5, 6, 3, 1, 3, 3, 1, 1, 0, 0), (8, 8, 13, 8, 11, 0, 1, 4, 6, 1, 0, 0, 0, 9, 10, 4, 6, 5, 2, 3, 1, 1, 1, 0, 0, 0), (10, 8, 10, 13, 9, 5, 4, 1, 5, 1, 1, 0, 0, 9, 8, 4, 7, 10, 4, 0, 2, 3, 4, 0, 1, 0), (7, 8, 5, 7, 11, 7, 5, 4, 7, 1, 0, 1, 0, 14, 8, 8, 6, 10, 3, 1, 1, 3, 4, 1, 1, 0), (14, 8, 8, 7, 8, 2, 4, 1, 4, 2, 0, 0, 0, 10, 7, 2, 2, 4, 6, 2, 2, 2, 2, 3, 0, 0), (7, 13, 11, 4, 10, 2, 0, 0, 2, 1, 0, 0, 0, 13, 5, 6, 3, 3, 0, 4, 1, 0, 4, 2, 1, 0), (13, 5, 11, 8, 5, 4, 1, 2, 2, 2, 2, 0, 0, 7, 6, 10, 5, 7, 2, 3, 2, 2, 2, 0, 1, 0), (11, 8, 6, 6, 4, 6, 3, 2, 6, 0, 1, 1, 0, 2, 13, 5, 1, 13, 4, 5, 2, 2, 1, 1, 1, 0), (9, 9, 9, 8, 8, 6, 2, 3, 4, 2, 1, 2, 0, 7, 4, 9, 8, 7, 2, 2, 1, 3, 0, 3, 0, 0), (12, 10, 9, 8, 9, 4, 0, 0, 4, 0, 0, 0, 0, 6, 8, 1, 3, 7, 4, 1, 2, 3, 2, 2, 1, 0), (8, 10, 7, 10, 5, 7, 0, 3, 1, 1, 2, 1, 0, 14, 7, 2, 5, 3, 4, 6, 1, 3, 3, 1, 1, 0), (8, 13, 5, 10, 9, 0, 3, 0, 5, 1, 0, 1, 0, 10, 5, 6, 3, 5, 1, 0, 1, 4, 3, 2, 0, 0), (9, 6, 6, 13, 15, 3, 0, 7, 3, 1, 2, 0, 0, 7, 10, 5, 5, 6, 0, 2, 0, 2, 2, 1, 2, 0), (12, 8, 9, 9, 9, 5, 3, 3, 2, 1, 0, 3, 0, 10, 6, 3, 1, 8, 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0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1))
'\nparameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html\n'
entropy = 8991598675325360468762009371570610170
child_seed_index = (1, 68)
|
class ATMOS(object):
'''
class ATMOS
- attributes:
- self defined
- methods:
- None
'''
def __init__(self,info):
self.info = info
for key in info.keys():
setattr(self, key, info[key])
def __repr__(self):
return 'Instance of class ATMOS'
|
class Atmos(object):
"""
class ATMOS
- attributes:
- self defined
- methods:
- None
"""
def __init__(self, info):
self.info = info
for key in info.keys():
setattr(self, key, info[key])
def __repr__(self):
return 'Instance of class ATMOS'
|
t=int(input())
if not (1 <= t <= 100000): exit(-1)
dp=[0]*100001
dp[3]=3
for i in range(4,100001):
if i%3==0 or i%7==0: dp[i]=i
dp[i]+=dp[i-1]
query=[*map(int,input().split())]
if len(query)!=t: exit(-1)
for i in query:
if not (10 <= int(i) <= 80000): exit(-1)
print(dp[int(i)])
succ=False
try: input()
except: succ=True
if not succ: exit(-1)
|
t = int(input())
if not 1 <= t <= 100000:
exit(-1)
dp = [0] * 100001
dp[3] = 3
for i in range(4, 100001):
if i % 3 == 0 or i % 7 == 0:
dp[i] = i
dp[i] += dp[i - 1]
query = [*map(int, input().split())]
if len(query) != t:
exit(-1)
for i in query:
if not 10 <= int(i) <= 80000:
exit(-1)
print(dp[int(i)])
succ = False
try:
input()
except:
succ = True
if not succ:
exit(-1)
|
"""
Define the environment paths
"""
#Path variables
TEMPLATE_PATH = "/home/scom/documents/opu_surveillance_system/monitoring/master/"
STATIC_PATH = "/home/scom/documents/opu_surveillance_system/monitoring/static/"
|
"""
Define the environment paths
"""
template_path = '/home/scom/documents/opu_surveillance_system/monitoring/master/'
static_path = '/home/scom/documents/opu_surveillance_system/monitoring/static/'
|
N = int(input())
A = list(map(int, input().split()))
ans = 0
for a in A:
if a > 10:
ans += a - 10
print(ans)
|
n = int(input())
a = list(map(int, input().split()))
ans = 0
for a in A:
if a > 10:
ans += a - 10
print(ans)
|
#!/usr/bin/env python
# encoding: utf-8
def run(whatweb, pluginname):
whatweb.recog_from_content(pluginname, "espcms")
whatweb.recog_from_file(pluginname, "templates/wap/cn/public/footer.html", "espcms")
|
def run(whatweb, pluginname):
whatweb.recog_from_content(pluginname, 'espcms')
whatweb.recog_from_file(pluginname, 'templates/wap/cn/public/footer.html', 'espcms')
|
vetor = []
entradaUsuario = int(input())
repetir = 1000
indice = 0
adicionar = 0
while(repetir > 0):
vetor.append(adicionar)
adicionar += 1
if(adicionar == entradaUsuario):
adicionar = 0
repetir -= 1
repetir = 1000
while(repetir>0):
repetir -= 1
print("N[{}] = {}".format(indice, vetor[indice]))
indice += 1
|
vetor = []
entrada_usuario = int(input())
repetir = 1000
indice = 0
adicionar = 0
while repetir > 0:
vetor.append(adicionar)
adicionar += 1
if adicionar == entradaUsuario:
adicionar = 0
repetir -= 1
repetir = 1000
while repetir > 0:
repetir -= 1
print('N[{}] = {}'.format(indice, vetor[indice]))
indice += 1
|
# -*- coding: utf-8 -*-
"""
eve-app settings
"""
# Use the MongoHQ sandbox as our backend.
MONGO_HOST = 'localhost'
MONGO_PORT = 27017
MONGO_USERNAME = ''
MONGO_PASSWORD = ''
MONGO_DBNAME = 'notifications'
# also, correctly set the API entry point
# SERVER_NAME = 'localhost'
# Enable reads (GET), inserts (POST) and DELETE for resources/collections
# (if you omit this line, the API will default to ['GET'] and provide
# read-only access to the endpoint).
RESOURCE_METHODS = ['GET', 'POST', 'DELETE']
# Enable reads (GET), edits (PATCH) and deletes of individual items
# (defaults to read-only item access).
ITEM_METHODS = ['GET', 'PATCH', 'DELETE']
# We enable standard client cache directives for all resources exposed by the
# API. We can always override these global settings later.
CACHE_CONTROL = 'max-age=20'
CACHE_EXPIRES = 20
X_DOMAINS = '*'
X_HEADERS = ['Authorization','If-Match','Access-Control-Expose-Headers','Content-Type','Pragma','Cache-Control']
X_EXPOSE_HEADERS = ['Origin', 'X-Requested-With', 'Content-Type', 'Accept']
units = ['ATG', 'ATC Mobile', 'Dealer Site', 'ATC', 'RealDeal', 'KBB', 'Tradein', 'vAuto', 'Fastlane', 'ATC SYC', 'VinSolution', 'HomeNet', 'ATX', 'CRM']
incident = {
# if 'item_title' is not provided API will just strip the final
# 's' from resource name, and use it as the item_title.
# 'item_title': 'incident',
'schema': {
'title': {
'type': 'string',
'minlength': 1,
'maxlength': 128,
},
'status': {
'type': 'string',
'allowed': ['red', 'yellow', 'green'],
'required': True,
},
'unit': {
'type': 'string',
'allowed': units,
'required': True,
},
'summary': {
'type': 'string',
'minlength': 1,
'maxlength': 512,
},
'created_by': {
'type': 'string',
'maxlength': 32,
},
}
}
update = {
# We choose to override global cache-control directives for this resource.
'cache_control': 'max-age=10,must-revalidate',
'cache_expires': 10,
'schema': {
'created_by': {
'type': 'string',
'maxlength': 32,
},
'description': {
'type': 'string',
'minlength': 1,
'maxlength': 512,
'required': True,
},
'incident': {
'type': 'objectid',
'required': True,
# referential integrity constraint: value must exist in the
# 'incidents' collection. Since we aren't declaring a 'field' key,
# will default to `incidents._id` (or, more precisely, to whatever
# ID_FIELD value is).
'data_relation': {
'resource': 'incidents',
# make the owner embeddable with ?embedded={"incident":1}
'embeddable': True
},
},
}
}
# The DOMAIN dict explains which resources will be available and how they will
# be accessible to the API consumer.
DOMAIN = {
'incidents': incident,
'updates': update,
}
|
"""
eve-app settings
"""
mongo_host = 'localhost'
mongo_port = 27017
mongo_username = ''
mongo_password = ''
mongo_dbname = 'notifications'
resource_methods = ['GET', 'POST', 'DELETE']
item_methods = ['GET', 'PATCH', 'DELETE']
cache_control = 'max-age=20'
cache_expires = 20
x_domains = '*'
x_headers = ['Authorization', 'If-Match', 'Access-Control-Expose-Headers', 'Content-Type', 'Pragma', 'Cache-Control']
x_expose_headers = ['Origin', 'X-Requested-With', 'Content-Type', 'Accept']
units = ['ATG', 'ATC Mobile', 'Dealer Site', 'ATC', 'RealDeal', 'KBB', 'Tradein', 'vAuto', 'Fastlane', 'ATC SYC', 'VinSolution', 'HomeNet', 'ATX', 'CRM']
incident = {'schema': {'title': {'type': 'string', 'minlength': 1, 'maxlength': 128}, 'status': {'type': 'string', 'allowed': ['red', 'yellow', 'green'], 'required': True}, 'unit': {'type': 'string', 'allowed': units, 'required': True}, 'summary': {'type': 'string', 'minlength': 1, 'maxlength': 512}, 'created_by': {'type': 'string', 'maxlength': 32}}}
update = {'cache_control': 'max-age=10,must-revalidate', 'cache_expires': 10, 'schema': {'created_by': {'type': 'string', 'maxlength': 32}, 'description': {'type': 'string', 'minlength': 1, 'maxlength': 512, 'required': True}, 'incident': {'type': 'objectid', 'required': True, 'data_relation': {'resource': 'incidents', 'embeddable': True}}}}
domain = {'incidents': incident, 'updates': update}
|
# AUTHOR = PAUL KEARNEY
# DATE = 2018-02-05
# STUDENT ID = G00364787
# EXERCISE 03
#
# filename= gmit--exercise03--collatz--20180205d.py
#
# the Collatz conjecture
print("The COLLATZ CONJECTURE")
# define the variables
num = ""
x = 0
# obtain user input
num = input("A start nummber: ")
x = int(num)
print("--Start of sequence.")
print (x)
# calculate the sequence/conjecture
while x != 1:
if x % 2 == 0:
x = x / 2
else:
x = (x * 3) + 1
print(int(x))
print("--End of sequence")
#
#
#
#
#
#
#
# WEEK 03
#
# filename= gmit--week03--collatz--20180205d.py
#
# STUDENT ID= g00364787
#
# the Collatz conjecture
#
#
#
#The COLLATZ CONJECTURE
#
#A start nummber: 12
#--Start of sequence.
#12
#6
#3
#10
#5
#16
#8
#4
#2
#1
#--End of sequence
#
## end ##
|
print('The COLLATZ CONJECTURE')
num = ''
x = 0
num = input('A start nummber: ')
x = int(num)
print('--Start of sequence.')
print(x)
while x != 1:
if x % 2 == 0:
x = x / 2
else:
x = x * 3 + 1
print(int(x))
print('--End of sequence')
|
"""django-livereload"""
__version__ = '1.7'
__license__ = 'BSD License'
__author__ = 'Fantomas42'
__email__ = 'fantomas42@gmail.com'
__url__ = 'https://github.com/Fantomas42/django-livereload'
|
"""django-livereload"""
__version__ = '1.7'
__license__ = 'BSD License'
__author__ = 'Fantomas42'
__email__ = 'fantomas42@gmail.com'
__url__ = 'https://github.com/Fantomas42/django-livereload'
|
DEFAULT_TEXT_TYPE = "mrkdwn"
class BaseBlock:
def generate(self):
raise NotImplemented("Subclass missing generate implementation")
class TextBlock(BaseBlock):
def __init__(self, text, _type=DEFAULT_TEXT_TYPE):
self._text = text
self._type = _type
def __repr__(self):
return f"TextBlock({self._text}, _type={self._type})"
def generate(self):
return {"type": "section", "text": {"type": self._type, "text": self._text}}
|
default_text_type = 'mrkdwn'
class Baseblock:
def generate(self):
raise not_implemented('Subclass missing generate implementation')
class Textblock(BaseBlock):
def __init__(self, text, _type=DEFAULT_TEXT_TYPE):
self._text = text
self._type = _type
def __repr__(self):
return f'TextBlock({self._text}, _type={self._type})'
def generate(self):
return {'type': 'section', 'text': {'type': self._type, 'text': self._text}}
|
#Script to calc. area of circle.
print("enter the radius")
r= float(input())
area= 3.14*r**2
print("area of circle is",area)
|
print('enter the radius')
r = float(input())
area = 3.14 * r ** 2
print('area of circle is', area)
|
#doc4
#1.
print([1, 'Hello', 1.0])
#2
print([1, 1, [1,2]][2][1])
#3. out: 'b', 'c'
print(['a','b', 'c'][1:])
#4.
weekDict= {'Sunday':0,'Monday':1,'Tuesday':2,'Wednesday':3,'Thursday':4,'Friday':5,'Saturday':6, }
#5. out: 2 if you replace D[k1][1] with D['k1][1]
D={'k1':[1,2,3]}
print(D['k1'][1])
#6.
tup = ( 'a', [1,[2,3]] )
print(tup)
#7.
x= set('Missipi')
print(x)
#8
x.add('X')
print(x)
#9 out: [1, 2, ,3]
print(set([1,1,2,3]))
#10
for i in range(2000,3001):
if (i%7==0) and (i%5!=0):
print(i)
|
print([1, 'Hello', 1.0])
print([1, 1, [1, 2]][2][1])
print(['a', 'b', 'c'][1:])
week_dict = {'Sunday': 0, 'Monday': 1, 'Tuesday': 2, 'Wednesday': 3, 'Thursday': 4, 'Friday': 5, 'Saturday': 6}
d = {'k1': [1, 2, 3]}
print(D['k1'][1])
tup = ('a', [1, [2, 3]])
print(tup)
x = set('Missipi')
print(x)
x.add('X')
print(x)
print(set([1, 1, 2, 3]))
for i in range(2000, 3001):
if i % 7 == 0 and i % 5 != 0:
print(i)
|
description = 'Resi instrument setup'
group = 'basic'
includes = ['base']
|
description = 'Resi instrument setup'
group = 'basic'
includes = ['base']
|
def quick_sort(array):
'''
Prototypical quick sort algorithm using Python
Time and Space Complexity:
* Best: O(n * log(n)) time | O(log(n)) space
* Avg: O(n * log(n)) time | O(log(n)) space
* Worst: O(n^2) time | O(log(n)) space
'''
return _quick_sort(array, 0, len(array)-1)
def _quick_sort(array, start, end):
# We don't need to sort an array of size 1 (already sorted), or less
if start >= end:
return
pivot = partition(array, start, end)
_quick_sort(array, start, pivot-1)
_quick_sort(array, pivot+1, end)
def partition(array, start, end):
pivot, pivotVal = start, array[start]
left, right = start+1, end
while left <= right:
if array[left] > pivotVal and array[right] < pivotVal:
swap(array, left, right)
if array[left] <= pivotVal:
left += 1
if pivotVal <= array[right]:
right -= 1
swap(array, pivot, right)
return right
def swap(array, i, j):
'''
Swaps the value at the i-th index with the value at the j-th index in place.
'''
if i < 0 or i > len(array)-1:
raise IndexError(f'Index <i> of {i} is not a valid index of <array>')
elif j < 0 or j > len(array)-1:
raise IndexError(f'Index <j> of {j} is not a valid index of <array>')
elif i == j:
return
array[i], array[j] = array[j], array[i]
test_cases = [
[],
[3,2],
[2,3,1],
[1,2,3],
[33, 33, 33, 33, 33],
[33, 33, 33, 33, 44],
[16, 1, 53, 99, 16, 9, 100, 300, 12],
]
for test_case in test_cases:
result = test_case.copy()
quick_sort(result)
assert result == sorted(test_case)
|
def quick_sort(array):
"""
Prototypical quick sort algorithm using Python
Time and Space Complexity:
* Best: O(n * log(n)) time | O(log(n)) space
* Avg: O(n * log(n)) time | O(log(n)) space
* Worst: O(n^2) time | O(log(n)) space
"""
return _quick_sort(array, 0, len(array) - 1)
def _quick_sort(array, start, end):
if start >= end:
return
pivot = partition(array, start, end)
_quick_sort(array, start, pivot - 1)
_quick_sort(array, pivot + 1, end)
def partition(array, start, end):
(pivot, pivot_val) = (start, array[start])
(left, right) = (start + 1, end)
while left <= right:
if array[left] > pivotVal and array[right] < pivotVal:
swap(array, left, right)
if array[left] <= pivotVal:
left += 1
if pivotVal <= array[right]:
right -= 1
swap(array, pivot, right)
return right
def swap(array, i, j):
"""
Swaps the value at the i-th index with the value at the j-th index in place.
"""
if i < 0 or i > len(array) - 1:
raise index_error(f'Index <i> of {i} is not a valid index of <array>')
elif j < 0 or j > len(array) - 1:
raise index_error(f'Index <j> of {j} is not a valid index of <array>')
elif i == j:
return
(array[i], array[j]) = (array[j], array[i])
test_cases = [[], [3, 2], [2, 3, 1], [1, 2, 3], [33, 33, 33, 33, 33], [33, 33, 33, 33, 44], [16, 1, 53, 99, 16, 9, 100, 300, 12]]
for test_case in test_cases:
result = test_case.copy()
quick_sort(result)
assert result == sorted(test_case)
|
def loops():
# String Array
names = ["Apple", "Orange", "Pear"]
# \n is a newline in a string
print('\n---------------')
print(' For Each Loop')
print('---------------\n')
# For Each Loop
for i in names:
print(i)
print('\n---------------')
print(' For Loop')
print('---------------\n')
# For Loop
# the range() function can take a min, max, and interval
# value, max is non-inclusive i.e. 101 stops at 100
# example: range(0, 101, 2)
for i in range(5):
if i == 1:
print('1, continue')
# continue will move to the next iteration in the loop
continue
elif i == 3:
print('3, break')
# the break statement will end the loop
break
# if the number doesn't fit the conditions above
# it will be printed to the console
print(i)
print('\n---------------')
print(' While Loop')
print('---------------\n')
# Boolean variables hold True or False, 0 or 1
loop = True
# Integer variables hold whole numbers
iterations = 0
max_iterations = 10
print('0 -', max_iterations, '\n')
# The while loop will run as long as the given
# condition or variable is true
# Parentheses are optional
while loop:
# the += operator adds the given value to
# the current value of a variable
iterations += 1
print(iterations)
if iterations == max_iterations:
# break will end a loops execution
break
if __name__ == '__main__':
loops()
|
def loops():
names = ['Apple', 'Orange', 'Pear']
print('\n---------------')
print(' For Each Loop')
print('---------------\n')
for i in names:
print(i)
print('\n---------------')
print(' For Loop')
print('---------------\n')
for i in range(5):
if i == 1:
print('1, continue')
continue
elif i == 3:
print('3, break')
break
print(i)
print('\n---------------')
print(' While Loop')
print('---------------\n')
loop = True
iterations = 0
max_iterations = 10
print('0 -', max_iterations, '\n')
while loop:
iterations += 1
print(iterations)
if iterations == max_iterations:
break
if __name__ == '__main__':
loops()
|
class Node:
def __init__(self, value, next_p=None):
self.next = next_p
self.value = value
def __str__(self):
return f'{self.value}'
class InvalidOperationError(Exception):
pass
class Stack:
def __init__(self):
self.top = None
def push(self, value):
current = self.top
if self.top == None:
self.top = Node(value)
else:
node_n = Node(value)
node_n.next = self.top
self.top = node_n
def pop(self):
if not self.top:
raise InvalidOperationError('Method not allowed on empty collection')
if self.top:
top_value = self.top
self.top = self.top.next
return top_value.value
def peek(self):
if not self.top:
raise InvalidOperationError("Method not allowed on empty collection")
return self.top.value
def is_empty(self):
return not self.top
class Queue:
def __init__(self):
self.f = None
self.r = None
def enqueue(self, value):
node = Node(value)
if self.r:
node = self.r.next
node = self.r
def dequeue(self):
if not self.f:
raise InvalidOperationError('Method not allowed on empty collection')
leave = self.f
if self.f == self.r:
self.r = None
self.f = self.f.next
return leave.value
def peek(self):
if not self.f:
raise InvalidOperationError('Method not allowed on empty collection')
return self.f.value
def is_empty(self):
return not self.f and not self.r
|
class Node:
def __init__(self, value, next_p=None):
self.next = next_p
self.value = value
def __str__(self):
return f'{self.value}'
class Invalidoperationerror(Exception):
pass
class Stack:
def __init__(self):
self.top = None
def push(self, value):
current = self.top
if self.top == None:
self.top = node(value)
else:
node_n = node(value)
node_n.next = self.top
self.top = node_n
def pop(self):
if not self.top:
raise invalid_operation_error('Method not allowed on empty collection')
if self.top:
top_value = self.top
self.top = self.top.next
return top_value.value
def peek(self):
if not self.top:
raise invalid_operation_error('Method not allowed on empty collection')
return self.top.value
def is_empty(self):
return not self.top
class Queue:
def __init__(self):
self.f = None
self.r = None
def enqueue(self, value):
node = node(value)
if self.r:
node = self.r.next
node = self.r
def dequeue(self):
if not self.f:
raise invalid_operation_error('Method not allowed on empty collection')
leave = self.f
if self.f == self.r:
self.r = None
self.f = self.f.next
return leave.value
def peek(self):
if not self.f:
raise invalid_operation_error('Method not allowed on empty collection')
return self.f.value
def is_empty(self):
return not self.f and (not self.r)
|
def main():
number = int(input("Enter number (Only positive integer is allowed)"))
print(f'{number} square is {number ** 2}')
# Press the green button in the gutter to run the script.
if __name__ == '__main__':
main()
|
def main():
number = int(input('Enter number (Only positive integer is allowed)'))
print(f'{number} square is {number ** 2}')
if __name__ == '__main__':
main()
|
number_of_computers = int(input())
number_of_sales = 0
real_sales = 0
made_sales = 0
counter_sales = 0
total_ratings = 0
for i in range (number_of_computers):
rating = int(input())
rating_scale = rating % 10
possible_sales = rating // 10
total_ratings += rating_scale
if rating_scale == 2:
real_sales = possible_sales * 0 / 100
counter_sales += real_sales
elif rating_scale == 3:
real_sales = possible_sales * 50 / 100
counter_sales += real_sales
elif rating_scale == 4:
real_sales = possible_sales * 70 / 100
counter_sales += real_sales
elif rating_scale == 5:
real_sales = possible_sales * 85 / 100
counter_sales += real_sales
elif rating_scale == 6:
real_sales = possible_sales * 100 / 100
counter_sales += real_sales
average_rating = total_ratings / number_of_computers
print (f'{counter_sales:.2f}')
print (f'{average_rating:.2f}')
|
number_of_computers = int(input())
number_of_sales = 0
real_sales = 0
made_sales = 0
counter_sales = 0
total_ratings = 0
for i in range(number_of_computers):
rating = int(input())
rating_scale = rating % 10
possible_sales = rating // 10
total_ratings += rating_scale
if rating_scale == 2:
real_sales = possible_sales * 0 / 100
counter_sales += real_sales
elif rating_scale == 3:
real_sales = possible_sales * 50 / 100
counter_sales += real_sales
elif rating_scale == 4:
real_sales = possible_sales * 70 / 100
counter_sales += real_sales
elif rating_scale == 5:
real_sales = possible_sales * 85 / 100
counter_sales += real_sales
elif rating_scale == 6:
real_sales = possible_sales * 100 / 100
counter_sales += real_sales
average_rating = total_ratings / number_of_computers
print(f'{counter_sales:.2f}')
print(f'{average_rating:.2f}')
|
"""
Created: 2001/08/05
Purpose: Turn PythonCard into a package
__version__ = "$Revision: 1.1.1.1 $"
__date__ = "$Date: 2001/08/06 19:53:11 $"
"""
|
"""
Created: 2001/08/05
Purpose: Turn PythonCard into a package
__version__ = "$Revision: 1.1.1.1 $"
__date__ = "$Date: 2001/08/06 19:53:11 $"
"""
|
def main():
valid_passwords_by_range_policy = 0
valid_passwords_by_position_policy = 0
with open('input') as f:
for line in f:
policy_string, password = parse_line(line.strip())
policy = Policy.parse(policy_string)
if policy.is_valid_by_range_policy(password):
valid_passwords_by_range_policy += 1
if policy.is_valid_by_position_policy(password):
valid_passwords_by_position_policy += 1
print(f'There are {valid_passwords_by_range_policy} valid passwords by "range" policy.')
print(f'There are {valid_passwords_by_position_policy} valid passwords by "position" policy.')
def parse_line(line):
tokens = line.split(':', 1)
policy_string = tokens[0]
password = tokens[1].strip()
return policy_string, password
class Policy:
def __init__(self, first_number, second_number, letter):
self._first_number = first_number
self._second_number = second_number
self._letter = letter
def is_valid_by_range_policy(self, password):
count = password.count(self._letter)
return count >= self._first_number and count <= self._second_number
def is_valid_by_position_policy(self, password):
index1 = self._first_number - 1
index2 = self._second_number - 1
return (password[index1] == self._letter) != (password[index2] == self._letter)
@classmethod
def parse (cls, string):
tokens = string.split(' ')
first_number_string, second_number_string = tokens[0].split('-')
letter = tokens[1]
return cls(int(first_number_string), int(second_number_string), letter)
if __name__ == '__main__':
main()
|
def main():
valid_passwords_by_range_policy = 0
valid_passwords_by_position_policy = 0
with open('input') as f:
for line in f:
(policy_string, password) = parse_line(line.strip())
policy = Policy.parse(policy_string)
if policy.is_valid_by_range_policy(password):
valid_passwords_by_range_policy += 1
if policy.is_valid_by_position_policy(password):
valid_passwords_by_position_policy += 1
print(f'There are {valid_passwords_by_range_policy} valid passwords by "range" policy.')
print(f'There are {valid_passwords_by_position_policy} valid passwords by "position" policy.')
def parse_line(line):
tokens = line.split(':', 1)
policy_string = tokens[0]
password = tokens[1].strip()
return (policy_string, password)
class Policy:
def __init__(self, first_number, second_number, letter):
self._first_number = first_number
self._second_number = second_number
self._letter = letter
def is_valid_by_range_policy(self, password):
count = password.count(self._letter)
return count >= self._first_number and count <= self._second_number
def is_valid_by_position_policy(self, password):
index1 = self._first_number - 1
index2 = self._second_number - 1
return (password[index1] == self._letter) != (password[index2] == self._letter)
@classmethod
def parse(cls, string):
tokens = string.split(' ')
(first_number_string, second_number_string) = tokens[0].split('-')
letter = tokens[1]
return cls(int(first_number_string), int(second_number_string), letter)
if __name__ == '__main__':
main()
|
# LTE using two pointers O(n**3)
class Solution(object):
def fourSumCount(self, A, B, C, D):
# corner case:
if len(A) == 0:
return 0
A.sort()
B.sort()
C.sort()
D.sort()
count = 0
for i in range(len(A)):
for j in range(len(B)):
k = 0
t = len(D) - 1
while 0 <= k < len(C) and 0 <= t < len(D):
if A[i] + B[j] + C[k] + D[t] > 0:
t -= 1
elif A[i] + B[j] + C[k] + D[t] < 0:
k += 1
else:
tmp1 = 1
tmp2 = 1
while 0 <= k < len(C) - 1 and C[k + 1] == C[k]:
k += 1
tmp1 += 1
while 1 <= t < len(D) and D[t - 1] == D[t]:
t -= 1
tmp2 += 1
count += tmp1 * tmp2
k += 1
t -= 1
return count
# hashmap Solution AC O(n**2)
class Solution(object):
def fourSumCount(self, A, B, C, D):
"""
:type A: List[int]
:type B: List[int]
:type C: List[int]
:type D: List[int]
:rtype: int
"""
hashtable = {}
count = 0
for a in A:
for b in B:
if a+b in hashtable:
hashtable[a+b] += 1
else:
hashtable[a+b] = 1
for c in C:
for d in D:
if -c-d in hashtable:
count += hashtable[-c-d]
return count
|
class Solution(object):
def four_sum_count(self, A, B, C, D):
if len(A) == 0:
return 0
A.sort()
B.sort()
C.sort()
D.sort()
count = 0
for i in range(len(A)):
for j in range(len(B)):
k = 0
t = len(D) - 1
while 0 <= k < len(C) and 0 <= t < len(D):
if A[i] + B[j] + C[k] + D[t] > 0:
t -= 1
elif A[i] + B[j] + C[k] + D[t] < 0:
k += 1
else:
tmp1 = 1
tmp2 = 1
while 0 <= k < len(C) - 1 and C[k + 1] == C[k]:
k += 1
tmp1 += 1
while 1 <= t < len(D) and D[t - 1] == D[t]:
t -= 1
tmp2 += 1
count += tmp1 * tmp2
k += 1
t -= 1
return count
class Solution(object):
def four_sum_count(self, A, B, C, D):
"""
:type A: List[int]
:type B: List[int]
:type C: List[int]
:type D: List[int]
:rtype: int
"""
hashtable = {}
count = 0
for a in A:
for b in B:
if a + b in hashtable:
hashtable[a + b] += 1
else:
hashtable[a + b] = 1
for c in C:
for d in D:
if -c - d in hashtable:
count += hashtable[-c - d]
return count
|
def tree_16b(features):
if features[12] <= 0.0026689696301218646:
if features[2] <= 0.00825153129312639:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.0029812112336458085:
if features[17] <= 0.001915214421615019:
return 0
else: # if features[17] > 0.001915214421615019
return 0
else: # if features[19] > 0.0029812112336458085
if features[2] <= 0.0018615168210089905:
return 0
else: # if features[2] > 0.0018615168210089905
return 0
else: # if features[19] > 0.005966400067336508
if features[19] <= 0.00793332328953511:
if features[18] <= 0.005491076861972033:
return 1
else: # if features[18] > 0.005491076861972033
return 0
else: # if features[19] > 0.00793332328953511
if features[6] <= 0.001075940812143017:
return 1
else: # if features[6] > 0.001075940812143017
return 1
else: # if features[2] > 0.00825153129312639
if features[2] <= 0.011165123326009052:
if features[19] <= 0.0012947088146120223:
if features[9] <= 0.002559585628887362:
return 1
else: # if features[9] > 0.002559585628887362
return 0
else: # if features[19] > 0.0012947088146120223
if features[10] <= 0.0028857488325684244:
return 1
else: # if features[10] > 0.0028857488325684244
return 0
else: # if features[2] > 0.011165123326009052
if features[1] <= 0.012951065746165114:
if features[6] <= 0.009407024106167228:
return 1
else: # if features[6] > 0.009407024106167228
return 0
else: # if features[1] > 0.012951065746165114
return 1
else: # if features[12] > 0.0026689696301218646
if features[19] <= 0.017378134596128803:
if features[2] <= 0.01920186421671133:
if features[0] <= 0.0018734496211436635:
if features[10] <= 0.0055686400628474075:
return 0
else: # if features[10] > 0.0055686400628474075
return 1
else: # if features[0] > 0.0018734496211436635
if features[3] <= 0.02158046904355615:
return 0
else: # if features[3] > 0.02158046904355615
return 1
else: # if features[2] > 0.01920186421671133
if features[3] <= 0.06516701033547179:
if features[15] <= 0.00476715365380187:
return 1
else: # if features[15] > 0.00476715365380187
return 1
else: # if features[3] > 0.06516701033547179
if features[0] <= 0.034261057986668675:
return 1
else: # if features[0] > 0.034261057986668675
return 0
else: # if features[19] > 0.017378134596128803
if features[0] <= 0.0035281312398183218:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008929712100780307:
return 1
else: # if features[14] > 0.008929712100780307
return 0
else: # if features[2] > 0.0026570368299871916
if features[19] <= 0.03522761479757719:
return 1
else: # if features[19] > 0.03522761479757719
return 0
else: # if features[0] > 0.0035281312398183218
if features[8] <= 0.0518500053851767:
if features[13] <= 0.010222432115369884:
return 1
else: # if features[13] > 0.010222432115369884
return 0
else: # if features[8] > 0.0518500053851767
if features[0] <= 0.03477615719248206:
return 1
else: # if features[0] > 0.03477615719248206
return 0
##################################################
def tree_15b(features):
if features[12] <= 0.0026689696301218646:
if features[2] <= 0.008249542493103945:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002979222433623363:
if features[17] <= 0.0019132256215925736:
return 0
else: # if features[17] > 0.0019132256215925736
return 0
else: # if features[19] > 0.002979222433623363
if features[2] <= 0.0018615168210089905:
return 0
else: # if features[2] > 0.0018615168210089905
return 0
else: # if features[19] > 0.005966400067336508
if features[19] <= 0.007935312089557556:
if features[18] <= 0.005493065661994478:
return 1
else: # if features[18] > 0.005493065661994478
return 0
else: # if features[19] > 0.007935312089557556
if features[6] <= 0.0010739520121205715:
return 1
else: # if features[6] > 0.0010739520121205715
return 1
else: # if features[2] > 0.008249542493103945
if features[2] <= 0.011165123326009052:
if features[19] <= 0.0012927200145895767:
if features[9] <= 0.0025575968288649165:
return 1
else: # if features[9] > 0.0025575968288649165
return 0
else: # if features[19] > 0.0012927200145895767
if features[10] <= 0.00288773763259087:
return 1
else: # if features[10] > 0.00288773763259087
return 0
else: # if features[2] > 0.011165123326009052
if features[1] <= 0.012951065746165114:
if features[6] <= 0.009407024106167228:
return 1
else: # if features[6] > 0.009407024106167228
return 0
else: # if features[1] > 0.012951065746165114
return 1
else: # if features[12] > 0.0026689696301218646
if features[19] <= 0.017378134596128803:
if features[2] <= 0.019199875416688883:
if features[0] <= 0.0018734496211436635:
if features[10] <= 0.0055686400628474075:
return 0
else: # if features[10] > 0.0055686400628474075
return 1
else: # if features[0] > 0.0018734496211436635
if features[3] <= 0.021582457843578595:
return 0
else: # if features[3] > 0.021582457843578595
return 1
else: # if features[2] > 0.019199875416688883
if features[3] <= 0.06516502153544934:
if features[15] <= 0.0047651648537794244:
return 1
else: # if features[15] > 0.0047651648537794244
return 1
else: # if features[3] > 0.06516502153544934
if features[0] <= 0.03426304678669112:
return 1
else: # if features[0] > 0.03426304678669112
return 0
else: # if features[19] > 0.017378134596128803
if features[0] <= 0.0035281312398183218:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008929712100780307:
return 1
else: # if features[14] > 0.008929712100780307
return 0
else: # if features[2] > 0.0026570368299871916
if features[19] <= 0.035225625997554744:
return 1
else: # if features[19] > 0.035225625997554744
return 0
else: # if features[0] > 0.0035281312398183218
if features[8] <= 0.051848016585154255:
if features[13] <= 0.010222432115369884:
return 1
else: # if features[13] > 0.010222432115369884
return 0
else: # if features[8] > 0.051848016585154255
if features[0] <= 0.03477615719248206:
return 1
else: # if features[0] > 0.03477615719248206
return 0
##################################################
def tree_14b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008249542493103945:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002983200033668254:
if features[17] <= 0.0019172032216374646:
return 0
else: # if features[17] > 0.0019172032216374646
return 0
else: # if features[19] > 0.002983200033668254
if features[2] <= 0.0018615168210089905:
return 0
else: # if features[2] > 0.0018615168210089905
return 0
else: # if features[19] > 0.005966400067336508
if features[19] <= 0.007931334489512665:
if features[18] <= 0.005489088061949587:
return 1
else: # if features[18] > 0.005489088061949587
return 0
else: # if features[19] > 0.007931334489512665
if features[6] <= 0.0010739520121205715:
return 1
else: # if features[6] > 0.0010739520121205715
return 1
else: # if features[2] > 0.008249542493103945
if features[2] <= 0.011161145725964161:
if features[19] <= 0.0012966976146344678:
if features[9] <= 0.0025615744289098075:
return 1
else: # if features[9] > 0.0025615744289098075
return 0
else: # if features[19] > 0.0012966976146344678
if features[10] <= 0.00288773763259087:
return 1
else: # if features[10] > 0.00288773763259087
return 0
else: # if features[2] > 0.011161145725964161
if features[1] <= 0.012951065746165114:
if features[6] <= 0.009411001706212119:
return 1
else: # if features[6] > 0.009411001706212119
return 0
else: # if features[1] > 0.012951065746165114
return 1
else: # if features[12] > 0.0026729472301667556
if features[19] <= 0.01737415699608391:
if features[2] <= 0.019203853016733774:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else: # if features[10] > 0.0055686400628474075
return 1
else: # if features[0] > 0.0018774272211885545
if features[3] <= 0.021582457843578595:
return 0
else: # if features[3] > 0.021582457843578595
return 1
else: # if features[2] > 0.019203853016733774
if features[3] <= 0.06516104393540445:
if features[15] <= 0.0047651648537794244:
return 1
else: # if features[15] > 0.0047651648537794244
return 1
else: # if features[3] > 0.06516104393540445
if features[0] <= 0.03426304678669112:
return 1
else: # if features[0] > 0.03426304678669112
return 0
else: # if features[19] > 0.01737415699608391
if features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008925734500735416:
return 1
else: # if features[14] > 0.008925734500735416
return 0
else: # if features[2] > 0.0026570368299871916
if features[19] <= 0.035225625997554744:
return 1
else: # if features[19] > 0.035225625997554744
return 0
else: # if features[0] > 0.0035321088398632128
if features[8] <= 0.051851994185199146:
if features[13] <= 0.010222432115369884:
return 1
else: # if features[13] > 0.010222432115369884
return 0
else: # if features[8] > 0.051851994185199146
if features[0] <= 0.03477217959243717:
return 1
else: # if features[0] > 0.03477217959243717
return 0
##################################################
def tree_13b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008257497693193727:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002975244833578472:
if features[17] <= 0.0019092480215476826:
return 0
else: # if features[17] > 0.0019092480215476826
return 0
else: # if features[19] > 0.002975244833578472
if features[2] <= 0.0018615168210089905:
return 0
else: # if features[2] > 0.0018615168210089905
return 0
else: # if features[19] > 0.005966400067336508
if features[19] <= 0.007939289689602447:
if features[18] <= 0.005489088061949587:
return 1
else: # if features[18] > 0.005489088061949587
return 0
else: # if features[19] > 0.007939289689602447
if features[6] <= 0.0010819072122103535:
return 1
else: # if features[6] > 0.0010819072122103535
return 1
else: # if features[2] > 0.008257497693193727
if features[2] <= 0.011169100926053943:
if features[19] <= 0.0012887424145446857:
if features[9] <= 0.0025615744289098075:
return 1
else: # if features[9] > 0.0025615744289098075
return 0
else: # if features[19] > 0.0012887424145446857
if features[10] <= 0.002879782432501088:
return 1
else: # if features[10] > 0.002879782432501088
return 0
else: # if features[2] > 0.011169100926053943
if features[1] <= 0.012951065746165114:
if features[6] <= 0.009403046506122337:
return 1
else: # if features[6] > 0.009403046506122337
return 0
else: # if features[1] > 0.012951065746165114
return 1
else: # if features[12] > 0.0026729472301667556
if features[19] <= 0.01737415699608391:
if features[2] <= 0.019203853016733774:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else: # if features[10] > 0.0055686400628474075
return 1
else: # if features[0] > 0.0018774272211885545
if features[3] <= 0.021574502643488813:
return 0
else: # if features[3] > 0.021574502643488813
return 1
else: # if features[2] > 0.019203853016733774
if features[3] <= 0.06515308873531467:
if features[15] <= 0.0047731200538692065:
return 1
else: # if features[15] > 0.0047731200538692065
return 1
else: # if features[3] > 0.06515308873531467
if features[0] <= 0.03425509158660134:
return 1
else: # if features[0] > 0.03425509158660134
return 0
else: # if features[19] > 0.01737415699608391
if features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008925734500735416:
return 1
else: # if features[14] > 0.008925734500735416
return 0
else: # if features[2] > 0.0026570368299871916
if features[19] <= 0.035225625997554744:
return 1
else: # if features[19] > 0.035225625997554744
return 0
else: # if features[0] > 0.0035321088398632128
if features[8] <= 0.051851994185199146:
if features[13] <= 0.010214476915280102:
return 1
else: # if features[13] > 0.010214476915280102
return 0
else: # if features[8] > 0.051851994185199146
if features[0] <= 0.03478013479252695:
return 1
else: # if features[0] > 0.03478013479252695
return 0
##################################################
def tree_12b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008241587293014163:
if features[19] <= 0.005950489667156944:
if features[19] <= 0.002991155233758036:
if features[17] <= 0.0019092480215476826:
return 0
else: # if features[17] > 0.0019092480215476826
return 0
else: # if features[19] > 0.002991155233758036
if features[2] <= 0.0018456064208294265:
return 0
else: # if features[2] > 0.0018456064208294265
return 0
else: # if features[19] > 0.005950489667156944
if features[19] <= 0.007923379289422883:
if features[18] <= 0.0055049984621291514:
return 1
else: # if features[18] > 0.0055049984621291514
return 0
else: # if features[19] > 0.007923379289422883
if features[6] <= 0.0010819072122103535:
return 1
else: # if features[6] > 0.0010819072122103535
return 1
else: # if features[2] > 0.008241587293014163
if features[2] <= 0.011169100926053943:
if features[19] <= 0.0013046528147242498:
if features[9] <= 0.0025456640287302434:
return 1
else: # if features[9] > 0.0025456640287302434
return 0
else: # if features[19] > 0.0013046528147242498
if features[10] <= 0.002895692832680652:
return 1
else: # if features[10] > 0.002895692832680652
return 0
else: # if features[2] > 0.011169100926053943
if features[1] <= 0.012951065746165114:
if features[6] <= 0.0094189569063019:
return 1
else: # if features[6] > 0.0094189569063019
return 0
else: # if features[1] > 0.012951065746165114
return 1
else: # if features[12] > 0.0026729472301667556
if features[19] <= 0.01737415699608391:
if features[2] <= 0.01918794261655421:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else: # if features[10] > 0.0055686400628474075
return 1
else: # if features[0] > 0.0018774272211885545
if features[3] <= 0.021574502643488813:
return 0
else: # if features[3] > 0.021574502643488813
return 1
else: # if features[2] > 0.01918794261655421
if features[3] <= 0.0651371783351351:
if features[15] <= 0.0047731200538692065:
return 1
else: # if features[15] > 0.0047731200538692065
return 1
else: # if features[3] > 0.0651371783351351
if features[0] <= 0.0342710019867809:
return 1
else: # if features[0] > 0.0342710019867809
return 0
else: # if features[19] > 0.01737415699608391
if features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026411264298076276:
if features[14] <= 0.00894164490091498:
return 1
else: # if features[14] > 0.00894164490091498
return 0
else: # if features[2] > 0.0026411264298076276
if features[19] <= 0.035225625997554744:
return 1
else: # if features[19] > 0.035225625997554744
return 0
else: # if features[0] > 0.0035321088398632128
if features[8] <= 0.05183608378501958:
if features[13] <= 0.010214476915280102:
return 1
else: # if features[13] > 0.010214476915280102
return 0
else: # if features[8] > 0.05183608378501958
if features[0] <= 0.03478013479252695:
return 1
else: # if features[0] > 0.03478013479252695
return 0
##################################################
def tree_11b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008273408093373291:
if features[19] <= 0.005982310467516072:
if features[19] <= 0.002991155233758036:
if features[17] <= 0.0019092480215476826:
return 0
else: # if features[17] > 0.0019092480215476826
return 0
else: # if features[19] > 0.002991155233758036
if features[2] <= 0.0018456064208294265:
return 0
else: # if features[2] > 0.0018456064208294265
return 0
else: # if features[19] > 0.005982310467516072
if features[19] <= 0.00795520008978201:
if features[18] <= 0.005473177661770023:
return 1
else: # if features[18] > 0.005473177661770023
return 0
else: # if features[19] > 0.00795520008978201
if features[6] <= 0.0010819072122103535:
return 1
else: # if features[6] > 0.0010819072122103535
return 1
else: # if features[2] > 0.008273408093373291
if features[2] <= 0.011137280125694815:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else: # if features[9] > 0.0025456640287302434
return 0
else: # if features[19] > 0.0012728320143651217
if features[10] <= 0.002863872032321524:
return 1
else: # if features[10] > 0.002863872032321524
return 0
else: # if features[2] > 0.011137280125694815
if features[1] <= 0.012919244945805985:
if features[6] <= 0.0094189569063019:
return 1
else: # if features[6] > 0.0094189569063019
return 0
else: # if features[1] > 0.012919244945805985
return 1
else: # if features[12] > 0.0026729472301667556
if features[19] <= 0.01737415699608391:
if features[2] <= 0.019219763416913338:
if features[0] <= 0.0018456064208294265:
if features[10] <= 0.0055368192624882795:
return 0
else: # if features[10] > 0.0055368192624882795
return 1
else: # if features[0] > 0.0018456064208294265
if features[3] <= 0.021574502643488813:
return 0
else: # if features[3] > 0.021574502643488813
return 1
else: # if features[2] > 0.019219763416913338
if features[3] <= 0.06510535753477598:
if features[15] <= 0.0047731200538692065:
return 1
else: # if features[15] > 0.0047731200538692065
return 1
else: # if features[3] > 0.06510535753477598
if features[0] <= 0.034239181186421774:
return 1
else: # if features[0] > 0.034239181186421774
return 0
else: # if features[19] > 0.01737415699608391
if features[0] <= 0.0035002880395040847:
if features[2] <= 0.0026729472301667556:
if features[14] <= 0.008909824100555852:
return 1
else: # if features[14] > 0.008909824100555852
return 0
else: # if features[2] > 0.0026729472301667556
if features[19] <= 0.03525744679791387:
return 1
else: # if features[19] > 0.03525744679791387
return 0
else: # if features[0] > 0.0035002880395040847
if features[8] <= 0.05186790458537871:
if features[13] <= 0.01024629771563923:
return 1
else: # if features[13] > 0.01024629771563923
return 0
else: # if features[8] > 0.05186790458537871
if features[0] <= 0.03474831399216782:
return 1
else: # if features[0] > 0.03474831399216782
return 0
##################################################
def tree_10b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008273408093373291:
if features[19] <= 0.005982310467516072:
if features[19] <= 0.00292751363303978:
if features[17] <= 0.0019092480215476826:
return 0
else: # if features[17] > 0.0019092480215476826
return 0
else: # if features[19] > 0.00292751363303978
if features[2] <= 0.0019092480215476826:
return 0
else: # if features[2] > 0.0019092480215476826
return 0
else: # if features[19] > 0.005982310467516072
if features[19] <= 0.007891558489063755:
if features[18] <= 0.005473177661770023:
return 1
else: # if features[18] > 0.005473177661770023
return 0
else: # if features[19] > 0.007891558489063755
if features[6] <= 0.0010182656114920974:
return 1
else: # if features[6] > 0.0010182656114920974
return 1
else: # if features[2] > 0.008273408093373291
if features[2] <= 0.011200921726413071:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else: # if features[9] > 0.0025456640287302434
return 0
else: # if features[19] > 0.0012728320143651217
if features[10] <= 0.00292751363303978:
return 1
else: # if features[10] > 0.00292751363303978
return 0
else: # if features[2] > 0.011200921726413071
if features[1] <= 0.012982886546524242:
if features[6] <= 0.0094189569063019:
return 1
else: # if features[6] > 0.0094189569063019
return 0
else: # if features[1] > 0.012982886546524242
return 1
else: # if features[12] > 0.0026729472301667556
if features[19] <= 0.017437798596802168:
if features[2] <= 0.019219763416913338:
if features[0] <= 0.0019092480215476826:
if features[10] <= 0.005600460863206536:
return 0
else: # if features[10] > 0.005600460863206536
return 1
else: # if features[0] > 0.0019092480215476826
if features[3] <= 0.02163814424420707:
return 0
else: # if features[3] > 0.02163814424420707
return 1
else: # if features[2] > 0.019219763416913338
if features[3] <= 0.06504171593405772:
if features[15] <= 0.00470947845315095:
return 1
else: # if features[15] > 0.00470947845315095
return 1
else: # if features[3] > 0.06504171593405772
if features[0] <= 0.034239181186421774:
return 1
else: # if features[0] > 0.034239181186421774
return 0
else: # if features[19] > 0.017437798596802168
if features[0] <= 0.003563929640222341:
if features[2] <= 0.0026729472301667556:
if features[14] <= 0.008909824100555852:
return 1
else: # if features[14] > 0.008909824100555852
return 0
else: # if features[2] > 0.0026729472301667556
if features[19] <= 0.03525744679791387:
return 1
else: # if features[19] > 0.03525744679791387
return 0
else: # if features[0] > 0.003563929640222341
if features[8] <= 0.051804262984660454:
if features[13] <= 0.010182656114920974:
return 1
else: # if features[13] > 0.010182656114920974
return 0
else: # if features[8] > 0.051804262984660454
if features[0] <= 0.03474831399216782:
return 1
else: # if features[0] > 0.03474831399216782
return 0
##################################################
def tree_9b(features):
if features[12] <= 0.0025456640287302434:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.00585502726607956:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else: # if features[17] > 0.0020365312229841948
return 0
else: # if features[19] > 0.003054796834476292
if features[2] <= 0.0017819648201111704:
return 0
else: # if features[2] > 0.0017819648201111704
return 0
else: # if features[19] > 0.00585502726607956
if features[19] <= 0.007891558489063755:
if features[18] <= 0.005600460863206536:
return 1
else: # if features[18] > 0.005600460863206536
return 0
else: # if features[19] > 0.007891558489063755
if features[6] <= 0.0010182656114920974:
return 1
else: # if features[6] > 0.0010182656114920974
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.011200921726413071:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else: # if features[9] > 0.0025456640287302434
return 0
else: # if features[19] > 0.0012728320143651217
if features[10] <= 0.002800230431603268:
return 1
else: # if features[10] > 0.002800230431603268
return 0
else: # if features[2] > 0.011200921726413071
if features[1] <= 0.012982886546524242:
if features[6] <= 0.0094189569063019:
return 1
else: # if features[6] > 0.0094189569063019
return 0
else: # if features[1] > 0.012982886546524242
return 1
else: # if features[12] > 0.0025456640287302434
if features[19] <= 0.017310515395365655:
if features[2] <= 0.019092480215476826:
if features[0] <= 0.0017819648201111704:
if features[10] <= 0.005600460863206536:
return 0
else: # if features[10] > 0.005600460863206536
return 1
else: # if features[0] > 0.0017819648201111704
if features[3] <= 0.02163814424420707:
return 0
else: # if features[3] > 0.02163814424420707
return 1
else: # if features[2] > 0.019092480215476826
if features[3] <= 0.06491443273262121:
if features[15] <= 0.0048367616545874625:
return 1
else: # if features[15] > 0.0048367616545874625
return 1
else: # if features[3] > 0.06491443273262121
if features[0] <= 0.034366464387858286:
return 1
else: # if features[0] > 0.034366464387858286
return 0
else: # if features[19] > 0.017310515395365655
if features[0] <= 0.003563929640222341:
if features[2] <= 0.0025456640287302434:
if features[14] <= 0.008909824100555852:
return 1
else: # if features[14] > 0.008909824100555852
return 0
else: # if features[2] > 0.0025456640287302434
if features[19] <= 0.03513016359647736:
return 1
else: # if features[19] > 0.03513016359647736
return 0
else: # if features[0] > 0.003563929640222341
if features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else: # if features[13] > 0.010182656114920974
return 0
else: # if features[8] > 0.051931546186096966
if features[0] <= 0.034875597193604335:
return 1
else: # if features[0] > 0.034875597193604335
return 0
##################################################
def tree_8b(features):
if features[12] <= 0.0025456640287302434:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else: # if features[17] > 0.0020365312229841948
return 0
else: # if features[19] > 0.003054796834476292
if features[2] <= 0.0020365312229841948:
return 0
else: # if features[2] > 0.0020365312229841948
return 0
else: # if features[19] > 0.006109593668952584
if features[19] <= 0.008146124891936779:
if features[18] <= 0.005600460863206536:
return 1
else: # if features[18] > 0.005600460863206536
return 0
else: # if features[19] > 0.008146124891936779
if features[6] <= 0.0010182656114920974:
return 1
else: # if features[6] > 0.0010182656114920974
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.011200921726413071:
if features[19] <= 0.001527398417238146:
if features[9] <= 0.0025456640287302434:
return 1
else: # if features[9] > 0.0025456640287302434
return 0
else: # if features[19] > 0.001527398417238146
if features[10] <= 0.003054796834476292:
return 1
else: # if features[10] > 0.003054796834476292
return 0
else: # if features[2] > 0.011200921726413071
if features[1] <= 0.012728320143651217:
if features[6] <= 0.009164390503428876:
return 1
else: # if features[6] > 0.009164390503428876
return 0
else: # if features[1] > 0.012728320143651217
return 1
else: # if features[12] > 0.0025456640287302434
if features[19] <= 0.017310515395365655:
if features[2] <= 0.01934704661834985:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.005600460863206536:
return 0
else: # if features[10] > 0.005600460863206536
return 1
else: # if features[0] > 0.0020365312229841948
if features[3] <= 0.021383577841334045:
return 0
else: # if features[3] > 0.021383577841334045
return 1
else: # if features[2] > 0.01934704661834985
if features[3] <= 0.06465986632974818:
if features[15] <= 0.004582195251714438:
return 1
else: # if features[15] > 0.004582195251714438
return 1
else: # if features[3] > 0.06465986632974818
if features[0] <= 0.03411189798498526:
return 1
else: # if features[0] > 0.03411189798498526
return 0
else: # if features[19] > 0.017310515395365655
if features[0] <= 0.003563929640222341:
if features[2] <= 0.0025456640287302434:
if features[14] <= 0.009164390503428876:
return 1
else: # if features[14] > 0.009164390503428876
return 0
else: # if features[2] > 0.0025456640287302434
if features[19] <= 0.03513016359647736:
return 1
else: # if features[19] > 0.03513016359647736
return 0
else: # if features[0] > 0.003563929640222341
if features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else: # if features[13] > 0.010182656114920974
return 0
else: # if features[8] > 0.051931546186096966
if features[0] <= 0.03462103079073131:
return 1
else: # if features[0] > 0.03462103079073131
return 0
##################################################
def tree_7b(features):
if features[12] <= 0.003054796834476292:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else: # if features[17] > 0.0020365312229841948
return 0
else: # if features[19] > 0.003054796834476292
if features[2] <= 0.0020365312229841948:
return 0
else: # if features[2] > 0.0020365312229841948
return 0
else: # if features[19] > 0.006109593668952584
if features[19] <= 0.008146124891936779:
if features[18] <= 0.005091328057460487:
return 1
else: # if features[18] > 0.005091328057460487
return 0
else: # if features[19] > 0.008146124891936779
if features[6] <= 0.0010182656114920974:
return 1
else: # if features[6] > 0.0010182656114920974
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.011200921726413071:
if features[19] <= 0.0010182656114920974:
if features[9] <= 0.003054796834476292:
return 1
else: # if features[9] > 0.003054796834476292
return 0
else: # if features[19] > 0.0010182656114920974
if features[10] <= 0.003054796834476292:
return 1
else: # if features[10] > 0.003054796834476292
return 0
else: # if features[2] > 0.011200921726413071
if features[1] <= 0.013237452949397266:
if features[6] <= 0.009164390503428876:
return 1
else: # if features[6] > 0.009164390503428876
return 0
else: # if features[1] > 0.013237452949397266
return 1
else: # if features[12] > 0.003054796834476292
if features[19] <= 0.017310515395365655:
if features[2] <= 0.01934704661834985:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.005091328057460487:
return 0
else: # if features[10] > 0.005091328057460487
return 1
else: # if features[0] > 0.0020365312229841948
if features[3] <= 0.021383577841334045:
return 0
else: # if features[3] > 0.021383577841334045
return 1
else: # if features[2] > 0.01934704661834985
if features[3] <= 0.06415073352400213:
if features[15] <= 0.005091328057460487:
return 1
else: # if features[15] > 0.005091328057460487
return 1
else: # if features[3] > 0.06415073352400213
if features[0] <= 0.03462103079073131:
return 1
else: # if features[0] > 0.03462103079073131
return 0
else: # if features[19] > 0.017310515395365655
if features[0] <= 0.003054796834476292:
if features[2] <= 0.003054796834476292:
if features[14] <= 0.009164390503428876:
return 1
else: # if features[14] > 0.009164390503428876
return 0
else: # if features[2] > 0.003054796834476292
if features[19] <= 0.03563929640222341:
return 1
else: # if features[19] > 0.03563929640222341
return 0
else: # if features[0] > 0.003054796834476292
if features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else: # if features[13] > 0.010182656114920974
return 0
else: # if features[8] > 0.051931546186096966
if features[0] <= 0.03462103079073131:
return 1
else: # if features[0] > 0.03462103079073131
return 0
##################################################
def tree_6b(features):
if features[12] <= 0.0020365312229841948:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.0020365312229841948:
if features[17] <= 0.0020365312229841948:
return 0
else: # if features[17] > 0.0020365312229841948
return 0
else: # if features[19] > 0.0020365312229841948
if features[2] <= 0.0020365312229841948:
return 0
else: # if features[2] > 0.0020365312229841948
return 0
else: # if features[19] > 0.006109593668952584
if features[19] <= 0.008146124891936779:
if features[18] <= 0.006109593668952584:
return 1
else: # if features[18] > 0.006109593668952584
return 0
else: # if features[19] > 0.008146124891936779
if features[6] <= 0.0020365312229841948:
return 1
else: # if features[6] > 0.0020365312229841948
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.010182656114920974:
if features[19] <= 0.0020365312229841948:
if features[9] <= 0.0020365312229841948:
return 1
else: # if features[9] > 0.0020365312229841948
return 0
else: # if features[19] > 0.0020365312229841948
if features[10] <= 0.0020365312229841948:
return 1
else: # if features[10] > 0.0020365312229841948
return 0
else: # if features[2] > 0.010182656114920974
if features[1] <= 0.012219187337905169:
if features[6] <= 0.010182656114920974:
return 1
else: # if features[6] > 0.010182656114920974
return 0
else: # if features[1] > 0.012219187337905169
return 1
else: # if features[12] > 0.0020365312229841948
if features[19] <= 0.018328781006857753:
if features[2] <= 0.018328781006857753:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.006109593668952584:
return 0
else: # if features[10] > 0.006109593668952584
return 1
else: # if features[0] > 0.0020365312229841948
if features[3] <= 0.022401843452826142:
return 0
else: # if features[3] > 0.022401843452826142
return 1
else: # if features[2] > 0.018328781006857753
if features[3] <= 0.06313246791251004:
if features[15] <= 0.0040730624459683895:
return 1
else: # if features[15] > 0.0040730624459683895
return 1
else: # if features[3] > 0.06313246791251004
if features[0] <= 0.03462103079073131:
return 1
else: # if features[0] > 0.03462103079073131
return 0
else: # if features[19] > 0.018328781006857753
if features[0] <= 0.0040730624459683895:
if features[2] <= 0.0020365312229841948:
if features[14] <= 0.008146124891936779:
return 1
else: # if features[14] > 0.008146124891936779
return 0
else: # if features[2] > 0.0020365312229841948
if features[19] <= 0.03462103079073131:
return 1
else: # if features[19] > 0.03462103079073131
return 0
else: # if features[0] > 0.0040730624459683895
if features[8] <= 0.05091328057460487:
if features[13] <= 0.010182656114920974:
return 1
else: # if features[13] > 0.010182656114920974
return 0
else: # if features[8] > 0.05091328057460487
if features[0] <= 0.03462103079073131:
return 1
else: # if features[0] > 0.03462103079073131
return 0
##################################################
def tree_5b(features):
if features[12] <= 0.0040730624459683895:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.0040730624459683895:
if features[19] <= 0.0040730624459683895:
if features[17] <= 0.0:
return 0
else: # if features[17] > 0.0
return 0
else: # if features[19] > 0.0040730624459683895
if features[2] <= 0.0:
return 0
else: # if features[2] > 0.0
return 0
else: # if features[19] > 0.0040730624459683895
if features[19] <= 0.008146124891936779:
if features[18] <= 0.0040730624459683895:
return 1
else: # if features[18] > 0.0040730624459683895
return 0
else: # if features[19] > 0.008146124891936779
if features[6] <= 0.0:
return 1
else: # if features[6] > 0.0
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.012219187337905169:
if features[19] <= 0.0:
if features[9] <= 0.0040730624459683895:
return 1
else: # if features[9] > 0.0040730624459683895
return 0
else: # if features[19] > 0.0
if features[10] <= 0.0040730624459683895:
return 1
else: # if features[10] > 0.0040730624459683895
return 0
else: # if features[2] > 0.012219187337905169
if features[1] <= 0.012219187337905169:
if features[6] <= 0.008146124891936779:
return 1
else: # if features[6] > 0.008146124891936779
return 0
else: # if features[1] > 0.012219187337905169
return 1
else: # if features[12] > 0.0040730624459683895
if features[19] <= 0.016292249783873558:
if features[2] <= 0.020365312229841948:
if features[0] <= 0.0:
if features[10] <= 0.0040730624459683895:
return 0
else: # if features[10] > 0.0040730624459683895
return 1
else: # if features[0] > 0.0
if features[3] <= 0.020365312229841948:
return 0
else: # if features[3] > 0.020365312229841948
return 1
else: # if features[2] > 0.020365312229841948
if features[3] <= 0.06109593668952584:
if features[15] <= 0.0040730624459683895:
return 1
else: # if features[15] > 0.0040730624459683895
return 1
else: # if features[3] > 0.06109593668952584
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
else: # if features[19] > 0.016292249783873558
if features[0] <= 0.0040730624459683895:
if features[2] <= 0.0040730624459683895:
if features[14] <= 0.008146124891936779:
return 1
else: # if features[14] > 0.008146124891936779
return 0
else: # if features[2] > 0.0040730624459683895
if features[19] <= 0.036657562013715506:
return 1
else: # if features[19] > 0.036657562013715506
return 0
else: # if features[0] > 0.0040730624459683895
if features[8] <= 0.052949811797589064:
if features[13] <= 0.012219187337905169:
return 1
else: # if features[13] > 0.012219187337905169
return 0
else: # if features[8] > 0.052949811797589064
if features[0] <= 0.036657562013715506:
return 1
else: # if features[0] > 0.036657562013715506
return 0
##################################################
def tree_4b(features):
if features[12] <= 0.0:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.008146124891936779:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else: # if features[17] > 0.0
return 0
else: # if features[19] > 0.0
if features[2] <= 0.0:
return 0
else: # if features[2] > 0.0
return 0
else: # if features[19] > 0.008146124891936779
if features[19] <= 0.008146124891936779:
if features[18] <= 0.008146124891936779:
return 1
else: # if features[18] > 0.008146124891936779
return 0
else: # if features[19] > 0.008146124891936779
if features[6] <= 0.0:
return 1
else: # if features[6] > 0.0
return 1
else: # if features[2] > 0.008146124891936779
if features[2] <= 0.008146124891936779:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else: # if features[9] > 0.0
return 0
else: # if features[19] > 0.0
if features[10] <= 0.0:
return 1
else: # if features[10] > 0.0
return 0
else: # if features[2] > 0.008146124891936779
if features[1] <= 0.016292249783873558:
if features[6] <= 0.008146124891936779:
return 1
else: # if features[6] > 0.008146124891936779
return 0
else: # if features[1] > 0.016292249783873558
return 1
else: # if features[12] > 0.0
if features[19] <= 0.016292249783873558:
if features[2] <= 0.016292249783873558:
if features[0] <= 0.0:
if features[10] <= 0.008146124891936779:
return 0
else: # if features[10] > 0.008146124891936779
return 1
else: # if features[0] > 0.0
if features[3] <= 0.024438374675810337:
return 0
else: # if features[3] > 0.024438374675810337
return 1
else: # if features[2] > 0.016292249783873558
if features[3] <= 0.05702287424355745:
if features[15] <= 0.008146124891936779:
return 1
else: # if features[15] > 0.008146124891936779
return 1
else: # if features[3] > 0.05702287424355745
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
else: # if features[19] > 0.016292249783873558
if features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.008146124891936779:
return 1
else: # if features[14] > 0.008146124891936779
return 0
else: # if features[2] > 0.0
if features[19] <= 0.032584499567747116:
return 1
else: # if features[19] > 0.032584499567747116
return 0
else: # if features[0] > 0.0
if features[8] <= 0.048876749351620674:
if features[13] <= 0.008146124891936779:
return 1
else: # if features[13] > 0.008146124891936779
return 0
else: # if features[8] > 0.048876749351620674
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
##################################################
def tree_3b(features):
if features[12] <= 0.0:
if features[2] <= 0.016292249783873558:
if features[19] <= 0.0:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else: # if features[17] > 0.0
return 0
else: # if features[19] > 0.0
if features[2] <= 0.0:
return 0
else: # if features[2] > 0.0
return 0
else: # if features[19] > 0.0
if features[19] <= 0.0:
if features[18] <= 0.0:
return 1
else: # if features[18] > 0.0
return 0
else: # if features[19] > 0.0
if features[6] <= 0.0:
return 1
else: # if features[6] > 0.0
return 1
else: # if features[2] > 0.016292249783873558
if features[2] <= 0.016292249783873558:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else: # if features[9] > 0.0
return 0
else: # if features[19] > 0.0
if features[10] <= 0.0:
return 1
else: # if features[10] > 0.0
return 0
else: # if features[2] > 0.016292249783873558
if features[1] <= 0.016292249783873558:
if features[6] <= 0.016292249783873558:
return 1
else: # if features[6] > 0.016292249783873558
return 0
else: # if features[1] > 0.016292249783873558
return 1
else: # if features[12] > 0.0
if features[19] <= 0.016292249783873558:
if features[2] <= 0.016292249783873558:
if features[0] <= 0.0:
if features[10] <= 0.0:
return 0
else: # if features[10] > 0.0
return 1
else: # if features[0] > 0.0
if features[3] <= 0.016292249783873558:
return 0
else: # if features[3] > 0.016292249783873558
return 1
else: # if features[2] > 0.016292249783873558
if features[3] <= 0.048876749351620674:
if features[15] <= 0.0:
return 1
else: # if features[15] > 0.0
return 1
else: # if features[3] > 0.048876749351620674
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
else: # if features[19] > 0.016292249783873558
if features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.016292249783873558:
return 1
else: # if features[14] > 0.016292249783873558
return 0
else: # if features[2] > 0.0
if features[19] <= 0.032584499567747116:
return 1
else: # if features[19] > 0.032584499567747116
return 0
else: # if features[0] > 0.0
if features[8] <= 0.048876749351620674:
if features[13] <= 0.016292249783873558:
return 1
else: # if features[13] > 0.016292249783873558
return 0
else: # if features[8] > 0.048876749351620674
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
##################################################
def tree_2b(features):
if features[12] <= 0.0:
if features[2] <= 0.0:
if features[19] <= 0.0:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else: # if features[17] > 0.0
return 0
else: # if features[19] > 0.0
if features[2] <= 0.0:
return 0
else: # if features[2] > 0.0
return 0
else: # if features[19] > 0.0
if features[19] <= 0.0:
if features[18] <= 0.0:
return 1
else: # if features[18] > 0.0
return 0
else: # if features[19] > 0.0
if features[6] <= 0.0:
return 1
else: # if features[6] > 0.0
return 1
else: # if features[2] > 0.0
if features[2] <= 0.0:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else: # if features[9] > 0.0
return 0
else: # if features[19] > 0.0
if features[10] <= 0.0:
return 1
else: # if features[10] > 0.0
return 0
else: # if features[2] > 0.0
if features[1] <= 0.0:
if features[6] <= 0.0:
return 1
else: # if features[6] > 0.0
return 0
else: # if features[1] > 0.0
return 1
else: # if features[12] > 0.0
if features[19] <= 0.032584499567747116:
if features[2] <= 0.032584499567747116:
if features[0] <= 0.0:
if features[10] <= 0.0:
return 0
else: # if features[10] > 0.0
return 1
else: # if features[0] > 0.0
if features[3] <= 0.032584499567747116:
return 0
else: # if features[3] > 0.032584499567747116
return 1
else: # if features[2] > 0.032584499567747116
if features[3] <= 0.032584499567747116:
if features[15] <= 0.0:
return 1
else: # if features[15] > 0.0
return 1
else: # if features[3] > 0.032584499567747116
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
else: # if features[19] > 0.032584499567747116
if features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.0:
return 1
else: # if features[14] > 0.0
return 0
else: # if features[2] > 0.0
if features[19] <= 0.032584499567747116:
return 1
else: # if features[19] > 0.032584499567747116
return 0
else: # if features[0] > 0.0
if features[8] <= 0.032584499567747116:
if features[13] <= 0.0:
return 1
else: # if features[13] > 0.0
return 0
else: # if features[8] > 0.032584499567747116
if features[0] <= 0.032584499567747116:
return 1
else: # if features[0] > 0.032584499567747116
return 0
##################################################
|
def tree_16b(features):
if features[12] <= 0.0026689696301218646:
if features[2] <= 0.00825153129312639:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.0029812112336458085:
if features[17] <= 0.001915214421615019:
return 0
else:
return 0
elif features[2] <= 0.0018615168210089905:
return 0
else:
return 0
elif features[19] <= 0.00793332328953511:
if features[18] <= 0.005491076861972033:
return 1
else:
return 0
elif features[6] <= 0.001075940812143017:
return 1
else:
return 1
elif features[2] <= 0.011165123326009052:
if features[19] <= 0.0012947088146120223:
if features[9] <= 0.002559585628887362:
return 1
else:
return 0
elif features[10] <= 0.0028857488325684244:
return 1
else:
return 0
elif features[1] <= 0.012951065746165114:
if features[6] <= 0.009407024106167228:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017378134596128803:
if features[2] <= 0.01920186421671133:
if features[0] <= 0.0018734496211436635:
if features[10] <= 0.0055686400628474075:
return 0
else:
return 1
elif features[3] <= 0.02158046904355615:
return 0
else:
return 1
elif features[3] <= 0.06516701033547179:
if features[15] <= 0.00476715365380187:
return 1
else:
return 1
elif features[0] <= 0.034261057986668675:
return 1
else:
return 0
elif features[0] <= 0.0035281312398183218:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008929712100780307:
return 1
else:
return 0
elif features[19] <= 0.03522761479757719:
return 1
else:
return 0
elif features[8] <= 0.0518500053851767:
if features[13] <= 0.010222432115369884:
return 1
else:
return 0
elif features[0] <= 0.03477615719248206:
return 1
else:
return 0
def tree_15b(features):
if features[12] <= 0.0026689696301218646:
if features[2] <= 0.008249542493103945:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002979222433623363:
if features[17] <= 0.0019132256215925736:
return 0
else:
return 0
elif features[2] <= 0.0018615168210089905:
return 0
else:
return 0
elif features[19] <= 0.007935312089557556:
if features[18] <= 0.005493065661994478:
return 1
else:
return 0
elif features[6] <= 0.0010739520121205715:
return 1
else:
return 1
elif features[2] <= 0.011165123326009052:
if features[19] <= 0.0012927200145895767:
if features[9] <= 0.0025575968288649165:
return 1
else:
return 0
elif features[10] <= 0.00288773763259087:
return 1
else:
return 0
elif features[1] <= 0.012951065746165114:
if features[6] <= 0.009407024106167228:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017378134596128803:
if features[2] <= 0.019199875416688883:
if features[0] <= 0.0018734496211436635:
if features[10] <= 0.0055686400628474075:
return 0
else:
return 1
elif features[3] <= 0.021582457843578595:
return 0
else:
return 1
elif features[3] <= 0.06516502153544934:
if features[15] <= 0.0047651648537794244:
return 1
else:
return 1
elif features[0] <= 0.03426304678669112:
return 1
else:
return 0
elif features[0] <= 0.0035281312398183218:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008929712100780307:
return 1
else:
return 0
elif features[19] <= 0.035225625997554744:
return 1
else:
return 0
elif features[8] <= 0.051848016585154255:
if features[13] <= 0.010222432115369884:
return 1
else:
return 0
elif features[0] <= 0.03477615719248206:
return 1
else:
return 0
def tree_14b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008249542493103945:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002983200033668254:
if features[17] <= 0.0019172032216374646:
return 0
else:
return 0
elif features[2] <= 0.0018615168210089905:
return 0
else:
return 0
elif features[19] <= 0.007931334489512665:
if features[18] <= 0.005489088061949587:
return 1
else:
return 0
elif features[6] <= 0.0010739520121205715:
return 1
else:
return 1
elif features[2] <= 0.011161145725964161:
if features[19] <= 0.0012966976146344678:
if features[9] <= 0.0025615744289098075:
return 1
else:
return 0
elif features[10] <= 0.00288773763259087:
return 1
else:
return 0
elif features[1] <= 0.012951065746165114:
if features[6] <= 0.009411001706212119:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.01737415699608391:
if features[2] <= 0.019203853016733774:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else:
return 1
elif features[3] <= 0.021582457843578595:
return 0
else:
return 1
elif features[3] <= 0.06516104393540445:
if features[15] <= 0.0047651648537794244:
return 1
else:
return 1
elif features[0] <= 0.03426304678669112:
return 1
else:
return 0
elif features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008925734500735416:
return 1
else:
return 0
elif features[19] <= 0.035225625997554744:
return 1
else:
return 0
elif features[8] <= 0.051851994185199146:
if features[13] <= 0.010222432115369884:
return 1
else:
return 0
elif features[0] <= 0.03477217959243717:
return 1
else:
return 0
def tree_13b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008257497693193727:
if features[19] <= 0.005966400067336508:
if features[19] <= 0.002975244833578472:
if features[17] <= 0.0019092480215476826:
return 0
else:
return 0
elif features[2] <= 0.0018615168210089905:
return 0
else:
return 0
elif features[19] <= 0.007939289689602447:
if features[18] <= 0.005489088061949587:
return 1
else:
return 0
elif features[6] <= 0.0010819072122103535:
return 1
else:
return 1
elif features[2] <= 0.011169100926053943:
if features[19] <= 0.0012887424145446857:
if features[9] <= 0.0025615744289098075:
return 1
else:
return 0
elif features[10] <= 0.002879782432501088:
return 1
else:
return 0
elif features[1] <= 0.012951065746165114:
if features[6] <= 0.009403046506122337:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.01737415699608391:
if features[2] <= 0.019203853016733774:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else:
return 1
elif features[3] <= 0.021574502643488813:
return 0
else:
return 1
elif features[3] <= 0.06515308873531467:
if features[15] <= 0.0047731200538692065:
return 1
else:
return 1
elif features[0] <= 0.03425509158660134:
return 1
else:
return 0
elif features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026570368299871916:
if features[14] <= 0.008925734500735416:
return 1
else:
return 0
elif features[19] <= 0.035225625997554744:
return 1
else:
return 0
elif features[8] <= 0.051851994185199146:
if features[13] <= 0.010214476915280102:
return 1
else:
return 0
elif features[0] <= 0.03478013479252695:
return 1
else:
return 0
def tree_12b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008241587293014163:
if features[19] <= 0.005950489667156944:
if features[19] <= 0.002991155233758036:
if features[17] <= 0.0019092480215476826:
return 0
else:
return 0
elif features[2] <= 0.0018456064208294265:
return 0
else:
return 0
elif features[19] <= 0.007923379289422883:
if features[18] <= 0.0055049984621291514:
return 1
else:
return 0
elif features[6] <= 0.0010819072122103535:
return 1
else:
return 1
elif features[2] <= 0.011169100926053943:
if features[19] <= 0.0013046528147242498:
if features[9] <= 0.0025456640287302434:
return 1
else:
return 0
elif features[10] <= 0.002895692832680652:
return 1
else:
return 0
elif features[1] <= 0.012951065746165114:
if features[6] <= 0.0094189569063019:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.01737415699608391:
if features[2] <= 0.01918794261655421:
if features[0] <= 0.0018774272211885545:
if features[10] <= 0.0055686400628474075:
return 0
else:
return 1
elif features[3] <= 0.021574502643488813:
return 0
else:
return 1
elif features[3] <= 0.0651371783351351:
if features[15] <= 0.0047731200538692065:
return 1
else:
return 1
elif features[0] <= 0.0342710019867809:
return 1
else:
return 0
elif features[0] <= 0.0035321088398632128:
if features[2] <= 0.0026411264298076276:
if features[14] <= 0.00894164490091498:
return 1
else:
return 0
elif features[19] <= 0.035225625997554744:
return 1
else:
return 0
elif features[8] <= 0.05183608378501958:
if features[13] <= 0.010214476915280102:
return 1
else:
return 0
elif features[0] <= 0.03478013479252695:
return 1
else:
return 0
def tree_11b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008273408093373291:
if features[19] <= 0.005982310467516072:
if features[19] <= 0.002991155233758036:
if features[17] <= 0.0019092480215476826:
return 0
else:
return 0
elif features[2] <= 0.0018456064208294265:
return 0
else:
return 0
elif features[19] <= 0.00795520008978201:
if features[18] <= 0.005473177661770023:
return 1
else:
return 0
elif features[6] <= 0.0010819072122103535:
return 1
else:
return 1
elif features[2] <= 0.011137280125694815:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else:
return 0
elif features[10] <= 0.002863872032321524:
return 1
else:
return 0
elif features[1] <= 0.012919244945805985:
if features[6] <= 0.0094189569063019:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.01737415699608391:
if features[2] <= 0.019219763416913338:
if features[0] <= 0.0018456064208294265:
if features[10] <= 0.0055368192624882795:
return 0
else:
return 1
elif features[3] <= 0.021574502643488813:
return 0
else:
return 1
elif features[3] <= 0.06510535753477598:
if features[15] <= 0.0047731200538692065:
return 1
else:
return 1
elif features[0] <= 0.034239181186421774:
return 1
else:
return 0
elif features[0] <= 0.0035002880395040847:
if features[2] <= 0.0026729472301667556:
if features[14] <= 0.008909824100555852:
return 1
else:
return 0
elif features[19] <= 0.03525744679791387:
return 1
else:
return 0
elif features[8] <= 0.05186790458537871:
if features[13] <= 0.01024629771563923:
return 1
else:
return 0
elif features[0] <= 0.03474831399216782:
return 1
else:
return 0
def tree_10b(features):
if features[12] <= 0.0026729472301667556:
if features[2] <= 0.008273408093373291:
if features[19] <= 0.005982310467516072:
if features[19] <= 0.00292751363303978:
if features[17] <= 0.0019092480215476826:
return 0
else:
return 0
elif features[2] <= 0.0019092480215476826:
return 0
else:
return 0
elif features[19] <= 0.007891558489063755:
if features[18] <= 0.005473177661770023:
return 1
else:
return 0
elif features[6] <= 0.0010182656114920974:
return 1
else:
return 1
elif features[2] <= 0.011200921726413071:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else:
return 0
elif features[10] <= 0.00292751363303978:
return 1
else:
return 0
elif features[1] <= 0.012982886546524242:
if features[6] <= 0.0094189569063019:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017437798596802168:
if features[2] <= 0.019219763416913338:
if features[0] <= 0.0019092480215476826:
if features[10] <= 0.005600460863206536:
return 0
else:
return 1
elif features[3] <= 0.02163814424420707:
return 0
else:
return 1
elif features[3] <= 0.06504171593405772:
if features[15] <= 0.00470947845315095:
return 1
else:
return 1
elif features[0] <= 0.034239181186421774:
return 1
else:
return 0
elif features[0] <= 0.003563929640222341:
if features[2] <= 0.0026729472301667556:
if features[14] <= 0.008909824100555852:
return 1
else:
return 0
elif features[19] <= 0.03525744679791387:
return 1
else:
return 0
elif features[8] <= 0.051804262984660454:
if features[13] <= 0.010182656114920974:
return 1
else:
return 0
elif features[0] <= 0.03474831399216782:
return 1
else:
return 0
def tree_9b(features):
if features[12] <= 0.0025456640287302434:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.00585502726607956:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[2] <= 0.0017819648201111704:
return 0
else:
return 0
elif features[19] <= 0.007891558489063755:
if features[18] <= 0.005600460863206536:
return 1
else:
return 0
elif features[6] <= 0.0010182656114920974:
return 1
else:
return 1
elif features[2] <= 0.011200921726413071:
if features[19] <= 0.0012728320143651217:
if features[9] <= 0.0025456640287302434:
return 1
else:
return 0
elif features[10] <= 0.002800230431603268:
return 1
else:
return 0
elif features[1] <= 0.012982886546524242:
if features[6] <= 0.0094189569063019:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017310515395365655:
if features[2] <= 0.019092480215476826:
if features[0] <= 0.0017819648201111704:
if features[10] <= 0.005600460863206536:
return 0
else:
return 1
elif features[3] <= 0.02163814424420707:
return 0
else:
return 1
elif features[3] <= 0.06491443273262121:
if features[15] <= 0.0048367616545874625:
return 1
else:
return 1
elif features[0] <= 0.034366464387858286:
return 1
else:
return 0
elif features[0] <= 0.003563929640222341:
if features[2] <= 0.0025456640287302434:
if features[14] <= 0.008909824100555852:
return 1
else:
return 0
elif features[19] <= 0.03513016359647736:
return 1
else:
return 0
elif features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else:
return 0
elif features[0] <= 0.034875597193604335:
return 1
else:
return 0
def tree_8b(features):
if features[12] <= 0.0025456640287302434:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[2] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[19] <= 0.008146124891936779:
if features[18] <= 0.005600460863206536:
return 1
else:
return 0
elif features[6] <= 0.0010182656114920974:
return 1
else:
return 1
elif features[2] <= 0.011200921726413071:
if features[19] <= 0.001527398417238146:
if features[9] <= 0.0025456640287302434:
return 1
else:
return 0
elif features[10] <= 0.003054796834476292:
return 1
else:
return 0
elif features[1] <= 0.012728320143651217:
if features[6] <= 0.009164390503428876:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017310515395365655:
if features[2] <= 0.01934704661834985:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.005600460863206536:
return 0
else:
return 1
elif features[3] <= 0.021383577841334045:
return 0
else:
return 1
elif features[3] <= 0.06465986632974818:
if features[15] <= 0.004582195251714438:
return 1
else:
return 1
elif features[0] <= 0.03411189798498526:
return 1
else:
return 0
elif features[0] <= 0.003563929640222341:
if features[2] <= 0.0025456640287302434:
if features[14] <= 0.009164390503428876:
return 1
else:
return 0
elif features[19] <= 0.03513016359647736:
return 1
else:
return 0
elif features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else:
return 0
elif features[0] <= 0.03462103079073131:
return 1
else:
return 0
def tree_7b(features):
if features[12] <= 0.003054796834476292:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.003054796834476292:
if features[17] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[2] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[19] <= 0.008146124891936779:
if features[18] <= 0.005091328057460487:
return 1
else:
return 0
elif features[6] <= 0.0010182656114920974:
return 1
else:
return 1
elif features[2] <= 0.011200921726413071:
if features[19] <= 0.0010182656114920974:
if features[9] <= 0.003054796834476292:
return 1
else:
return 0
elif features[10] <= 0.003054796834476292:
return 1
else:
return 0
elif features[1] <= 0.013237452949397266:
if features[6] <= 0.009164390503428876:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.017310515395365655:
if features[2] <= 0.01934704661834985:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.005091328057460487:
return 0
else:
return 1
elif features[3] <= 0.021383577841334045:
return 0
else:
return 1
elif features[3] <= 0.06415073352400213:
if features[15] <= 0.005091328057460487:
return 1
else:
return 1
elif features[0] <= 0.03462103079073131:
return 1
else:
return 0
elif features[0] <= 0.003054796834476292:
if features[2] <= 0.003054796834476292:
if features[14] <= 0.009164390503428876:
return 1
else:
return 0
elif features[19] <= 0.03563929640222341:
return 1
else:
return 0
elif features[8] <= 0.051931546186096966:
if features[13] <= 0.010182656114920974:
return 1
else:
return 0
elif features[0] <= 0.03462103079073131:
return 1
else:
return 0
def tree_6b(features):
if features[12] <= 0.0020365312229841948:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.006109593668952584:
if features[19] <= 0.0020365312229841948:
if features[17] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[2] <= 0.0020365312229841948:
return 0
else:
return 0
elif features[19] <= 0.008146124891936779:
if features[18] <= 0.006109593668952584:
return 1
else:
return 0
elif features[6] <= 0.0020365312229841948:
return 1
else:
return 1
elif features[2] <= 0.010182656114920974:
if features[19] <= 0.0020365312229841948:
if features[9] <= 0.0020365312229841948:
return 1
else:
return 0
elif features[10] <= 0.0020365312229841948:
return 1
else:
return 0
elif features[1] <= 0.012219187337905169:
if features[6] <= 0.010182656114920974:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.018328781006857753:
if features[2] <= 0.018328781006857753:
if features[0] <= 0.0020365312229841948:
if features[10] <= 0.006109593668952584:
return 0
else:
return 1
elif features[3] <= 0.022401843452826142:
return 0
else:
return 1
elif features[3] <= 0.06313246791251004:
if features[15] <= 0.0040730624459683895:
return 1
else:
return 1
elif features[0] <= 0.03462103079073131:
return 1
else:
return 0
elif features[0] <= 0.0040730624459683895:
if features[2] <= 0.0020365312229841948:
if features[14] <= 0.008146124891936779:
return 1
else:
return 0
elif features[19] <= 0.03462103079073131:
return 1
else:
return 0
elif features[8] <= 0.05091328057460487:
if features[13] <= 0.010182656114920974:
return 1
else:
return 0
elif features[0] <= 0.03462103079073131:
return 1
else:
return 0
def tree_5b(features):
if features[12] <= 0.0040730624459683895:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.0040730624459683895:
if features[19] <= 0.0040730624459683895:
if features[17] <= 0.0:
return 0
else:
return 0
elif features[2] <= 0.0:
return 0
else:
return 0
elif features[19] <= 0.008146124891936779:
if features[18] <= 0.0040730624459683895:
return 1
else:
return 0
elif features[6] <= 0.0:
return 1
else:
return 1
elif features[2] <= 0.012219187337905169:
if features[19] <= 0.0:
if features[9] <= 0.0040730624459683895:
return 1
else:
return 0
elif features[10] <= 0.0040730624459683895:
return 1
else:
return 0
elif features[1] <= 0.012219187337905169:
if features[6] <= 0.008146124891936779:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.016292249783873558:
if features[2] <= 0.020365312229841948:
if features[0] <= 0.0:
if features[10] <= 0.0040730624459683895:
return 0
else:
return 1
elif features[3] <= 0.020365312229841948:
return 0
else:
return 1
elif features[3] <= 0.06109593668952584:
if features[15] <= 0.0040730624459683895:
return 1
else:
return 1
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
elif features[0] <= 0.0040730624459683895:
if features[2] <= 0.0040730624459683895:
if features[14] <= 0.008146124891936779:
return 1
else:
return 0
elif features[19] <= 0.036657562013715506:
return 1
else:
return 0
elif features[8] <= 0.052949811797589064:
if features[13] <= 0.012219187337905169:
return 1
else:
return 0
elif features[0] <= 0.036657562013715506:
return 1
else:
return 0
def tree_4b(features):
if features[12] <= 0.0:
if features[2] <= 0.008146124891936779:
if features[19] <= 0.008146124891936779:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else:
return 0
elif features[2] <= 0.0:
return 0
else:
return 0
elif features[19] <= 0.008146124891936779:
if features[18] <= 0.008146124891936779:
return 1
else:
return 0
elif features[6] <= 0.0:
return 1
else:
return 1
elif features[2] <= 0.008146124891936779:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else:
return 0
elif features[10] <= 0.0:
return 1
else:
return 0
elif features[1] <= 0.016292249783873558:
if features[6] <= 0.008146124891936779:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.016292249783873558:
if features[2] <= 0.016292249783873558:
if features[0] <= 0.0:
if features[10] <= 0.008146124891936779:
return 0
else:
return 1
elif features[3] <= 0.024438374675810337:
return 0
else:
return 1
elif features[3] <= 0.05702287424355745:
if features[15] <= 0.008146124891936779:
return 1
else:
return 1
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
elif features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.008146124891936779:
return 1
else:
return 0
elif features[19] <= 0.032584499567747116:
return 1
else:
return 0
elif features[8] <= 0.048876749351620674:
if features[13] <= 0.008146124891936779:
return 1
else:
return 0
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
def tree_3b(features):
if features[12] <= 0.0:
if features[2] <= 0.016292249783873558:
if features[19] <= 0.0:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else:
return 0
elif features[2] <= 0.0:
return 0
else:
return 0
elif features[19] <= 0.0:
if features[18] <= 0.0:
return 1
else:
return 0
elif features[6] <= 0.0:
return 1
else:
return 1
elif features[2] <= 0.016292249783873558:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else:
return 0
elif features[10] <= 0.0:
return 1
else:
return 0
elif features[1] <= 0.016292249783873558:
if features[6] <= 0.016292249783873558:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.016292249783873558:
if features[2] <= 0.016292249783873558:
if features[0] <= 0.0:
if features[10] <= 0.0:
return 0
else:
return 1
elif features[3] <= 0.016292249783873558:
return 0
else:
return 1
elif features[3] <= 0.048876749351620674:
if features[15] <= 0.0:
return 1
else:
return 1
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
elif features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.016292249783873558:
return 1
else:
return 0
elif features[19] <= 0.032584499567747116:
return 1
else:
return 0
elif features[8] <= 0.048876749351620674:
if features[13] <= 0.016292249783873558:
return 1
else:
return 0
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
def tree_2b(features):
if features[12] <= 0.0:
if features[2] <= 0.0:
if features[19] <= 0.0:
if features[19] <= 0.0:
if features[17] <= 0.0:
return 0
else:
return 0
elif features[2] <= 0.0:
return 0
else:
return 0
elif features[19] <= 0.0:
if features[18] <= 0.0:
return 1
else:
return 0
elif features[6] <= 0.0:
return 1
else:
return 1
elif features[2] <= 0.0:
if features[19] <= 0.0:
if features[9] <= 0.0:
return 1
else:
return 0
elif features[10] <= 0.0:
return 1
else:
return 0
elif features[1] <= 0.0:
if features[6] <= 0.0:
return 1
else:
return 0
else:
return 1
elif features[19] <= 0.032584499567747116:
if features[2] <= 0.032584499567747116:
if features[0] <= 0.0:
if features[10] <= 0.0:
return 0
else:
return 1
elif features[3] <= 0.032584499567747116:
return 0
else:
return 1
elif features[3] <= 0.032584499567747116:
if features[15] <= 0.0:
return 1
else:
return 1
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
elif features[0] <= 0.0:
if features[2] <= 0.0:
if features[14] <= 0.0:
return 1
else:
return 0
elif features[19] <= 0.032584499567747116:
return 1
else:
return 0
elif features[8] <= 0.032584499567747116:
if features[13] <= 0.0:
return 1
else:
return 0
elif features[0] <= 0.032584499567747116:
return 1
else:
return 0
|
class Employee:
def __init__(self, name, emp_id, email_id):
self.__name=name
self.__emp_id=emp_id
self.__email_id=email_id
def get_name(self):
return self.__name
def get_emp_id(self):
return self.__emp_id
def get_email_id(self):
return self.__email_id
class OrganizationDirectory:
def __init__(self,emp_list):
self.__emp_list=emp_list
def lookup(self,key_name):
result_list=[]
for emp in self.__emp_list:
if(key_name in emp.get_name()):
result_list.append(emp)
self.display(result_list)
return result_list
def display(self,result_list):
print("Search results:")
for emp in result_list:
print(emp.get_name()," ", emp.get_emp_id()," ",emp.get_email_id())
emp1=Employee("Kevin",24089, "Kevin_xyz@organization.com")
emp2=Employee("Jack",56789,"Jack_xyz@organization.com")
emp3=Employee("Jackson",67895,"Jackson_xyz@organization.com")
emp4=Employee("Henry Jack",23456,"Jacky_xyz@organization.com")
emp_list=[emp1,emp2,emp3,emp4]
org_dir=OrganizationDirectory(emp_list)
#Search for an employee
org_dir.lookup("KEVIN")
|
class Employee:
def __init__(self, name, emp_id, email_id):
self.__name = name
self.__emp_id = emp_id
self.__email_id = email_id
def get_name(self):
return self.__name
def get_emp_id(self):
return self.__emp_id
def get_email_id(self):
return self.__email_id
class Organizationdirectory:
def __init__(self, emp_list):
self.__emp_list = emp_list
def lookup(self, key_name):
result_list = []
for emp in self.__emp_list:
if key_name in emp.get_name():
result_list.append(emp)
self.display(result_list)
return result_list
def display(self, result_list):
print('Search results:')
for emp in result_list:
print(emp.get_name(), ' ', emp.get_emp_id(), ' ', emp.get_email_id())
emp1 = employee('Kevin', 24089, 'Kevin_xyz@organization.com')
emp2 = employee('Jack', 56789, 'Jack_xyz@organization.com')
emp3 = employee('Jackson', 67895, 'Jackson_xyz@organization.com')
emp4 = employee('Henry Jack', 23456, 'Jacky_xyz@organization.com')
emp_list = [emp1, emp2, emp3, emp4]
org_dir = organization_directory(emp_list)
org_dir.lookup('KEVIN')
|
class tablecloumninfo:
col_name=""
data_type=""
comment=""
def __init__(self,col_name,data_type,comment):
self.col_name=col_name
self.data_type=data_type
self.comment=comment
|
class Tablecloumninfo:
col_name = ''
data_type = ''
comment = ''
def __init__(self, col_name, data_type, comment):
self.col_name = col_name
self.data_type = data_type
self.comment = comment
|
class GraphLearner:
"""Base class for causal discovery methods.
Subclasses implement different discovery methods. All discovery methods are in the package "dowhy.causal_discoverers"
"""
def __init__(self, data, library_class, *args, **kwargs):
self._data = data
self._labels = list(self._data.columns)
self._adjacency_matrix = None
self._graph_dot = None
def learn_graph(self):
'''
Discover causal graph and the graph in DOT format.
'''
raise NotImplementedError
|
class Graphlearner:
"""Base class for causal discovery methods.
Subclasses implement different discovery methods. All discovery methods are in the package "dowhy.causal_discoverers"
"""
def __init__(self, data, library_class, *args, **kwargs):
self._data = data
self._labels = list(self._data.columns)
self._adjacency_matrix = None
self._graph_dot = None
def learn_graph(self):
"""
Discover causal graph and the graph in DOT format.
"""
raise NotImplementedError
|
"""
aiida_crystal_dft
AiiDA plugin for running the CRYSTAL code
"""
__version__ = "0.8"
|
"""
aiida_crystal_dft
AiiDA plugin for running the CRYSTAL code
"""
__version__ = '0.8'
|
class attributes_de:
def __init__(self,threshold_list,range_for_r):
self.country_name = 'Germany'
self.population = 83190556
self.url = 'https://opendata.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0.geojson'
self.contains_tests=False
self.csv=False # if the resources have csv format
self.CasesPer100k_thresholds=threshold_list
self.Range_for_R=range_for_r
self.color_sizes = dict(
colorEvenRows = '#FFE6D9',
colorOddRows = 'white',
colorHeaderBG= '#FFCE00',
sizeHeaderFont = 14,
colorHeaderFont='black',
colorCellFont = 'black',
sizeCellFont = 12,
colorTitle = 'black',
sizeTitleFont = 27,
colorPivotColumnText='#DD0000'
)
# https://www.data.gouv.fr/fr/datasets/synthese-des-indicateurs-de-suivi-de-lepidemie-covid-19/
class attributes_fr:
def __init__(self,threshold_list,range_for_r):
self.country_name = 'France'
self.population = 67406000
self.url = "https://www.data.gouv.fr/fr/datasets/r/f335f9ea-86e3-4ffa-9684-93c009d5e617"
self.contains_tests=True
self.csv_encoding='latin'
self.csv_separator=','
self.csv=True # if the resources have csv format
self.CasesPer100k_thresholds=threshold_list
self.Range_for_R=range_for_r
self.color_sizes=dict(
colorEvenRows = '#FFE6D9', #'#FFE3F1'#'#FFAFAE'
colorOddRows = 'white',
colorHeaderBG='#001489',
sizeHeaderFont = 14,
colorHeaderFont='white',
colorCellFont = 'black',
sizeCellFont = 12,
colorTitle = '#001489',
sizeTitleFont = 27,
colorPivotColumnText='#001489'
)
class attributes_at:
def __init__(self,threshold_list,range_for_r):
self.country_name = 'Austria'
self.population = 8901064
self.url="https://covid19-dashboard.ages.at/data/CovidFaelle_Timeline.csv"
self.contains_tests=False
self.csv_encoding='utf-8'
self.csv_separator=';'
self.csv=True # if the resources have csv format
self.CasesPer100k_thresholds=threshold_list
self.Range_for_R=range_for_r
self.color_sizes=dict(
colorEvenRows = '#F3EED9', #'#FFE3F1'#'#FFAFAE'
colorOddRows = 'white',
colorHeaderBG='#ED2939',
sizeHeaderFont = 14,
colorHeaderFont='white',
colorCellFont = 'black',
sizeCellFont = 12,
colorTitle = '#ED2939',
sizeTitleFont = 27,
colorPivotColumnText='#ED2939'
)
# Austria: What the fuck?! The way data is published I would guess this country is a banana republic
class attributes_be:
def __init__(self,threshold_list,range_for_r):
self.country_name = 'Belgium'
self.population = 11492641
self.url = 'https://epistat.sciensano.be/Data/COVID19BE_tests.json'
self.contains_tests=True
self.csv=False # if the resources have csv format
self.CasesPer100k_thresholds=threshold_list
self.Range_for_R=range_for_r
self.color_sizes = dict(
colorEvenRows = '#FFE6D9',
colorOddRows = 'white',
colorHeaderBG= '#FDDA24',
sizeHeaderFont = 14,
colorHeaderFont='black',
colorCellFont = 'black',
sizeCellFont = 12,
colorTitle = 'black',
sizeTitleFont = 27,
colorPivotColumnText='#EF3340'
)
class attributes_lv:
def __init__(self,threshold_list,range_for_r):
self.country_name = 'Latvia'
self.population = 1907675
self.url = 'https://data.gov.lv/dati/eng/api/3/action/datastore_search_sql?sql=SELECT%20*%20from%20%22d499d2f0-b1ea-4ba2-9600-2c701b03bd4a%22'
self.contains_tests=True
self.csv=False # if the resources have csv format
self.CasesPer100k_thresholds=threshold_list
self.Range_for_R=range_for_r
self.color_sizes=dict(
colorEvenRows = '#F3EED9', #'#FFE3F1'#'#FFAFAE'
colorOddRows = 'white',
colorHeaderBG='#9E3039',
sizeHeaderFont = 14,
colorHeaderFont='white',
colorCellFont = 'black',
sizeCellFont = 12,
colorTitle = '#9E3039',
sizeTitleFont = 27,
colorPivotColumnText='#9E3039'
)
def get_attributes(country,threshold_list=[10,20,50,100,200,400,600,800,1000],range_for_r=[0.8,0.85,0.9,0.95,1.05,1.1,1.15,1.2]):
"""
Gets the country specific attributes like Name, population, url etc.
Parameters
----------
country : str
A two letter color code for a country e.g. 'de' for Germany
thresholds_list : list
optional: A list of integers representing the threshold which R has to go above or below
range_for_r : list
optional: A list of floats representing the range of R
Returns
-------
class
Class with the country specific attributes. Also contains a color scheme class for this country
"""
try:
if country=='de':
attributes=attributes_de(threshold_list,range_for_r)
elif country=='fr':
attributes=attributes_fr(threshold_list,range_for_r)
elif country=='at':
attributes=attributes_at(threshold_list,range_for_r)
elif country=='be':
attributes=attributes_be(threshold_list,range_for_r)
elif country=='lv':
attributes=attributes_lv(threshold_list,range_for_r)
else:
print("Error no such country attribute defined")
return attributes
except Exception as e:
print(e)
# de -> Germany attributes
# lv -> Latvia attributes
# de
|
class Attributes_De:
def __init__(self, threshold_list, range_for_r):
self.country_name = 'Germany'
self.population = 83190556
self.url = 'https://opendata.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0.geojson'
self.contains_tests = False
self.csv = False
self.CasesPer100k_thresholds = threshold_list
self.Range_for_R = range_for_r
self.color_sizes = dict(colorEvenRows='#FFE6D9', colorOddRows='white', colorHeaderBG='#FFCE00', sizeHeaderFont=14, colorHeaderFont='black', colorCellFont='black', sizeCellFont=12, colorTitle='black', sizeTitleFont=27, colorPivotColumnText='#DD0000')
class Attributes_Fr:
def __init__(self, threshold_list, range_for_r):
self.country_name = 'France'
self.population = 67406000
self.url = 'https://www.data.gouv.fr/fr/datasets/r/f335f9ea-86e3-4ffa-9684-93c009d5e617'
self.contains_tests = True
self.csv_encoding = 'latin'
self.csv_separator = ','
self.csv = True
self.CasesPer100k_thresholds = threshold_list
self.Range_for_R = range_for_r
self.color_sizes = dict(colorEvenRows='#FFE6D9', colorOddRows='white', colorHeaderBG='#001489', sizeHeaderFont=14, colorHeaderFont='white', colorCellFont='black', sizeCellFont=12, colorTitle='#001489', sizeTitleFont=27, colorPivotColumnText='#001489')
class Attributes_At:
def __init__(self, threshold_list, range_for_r):
self.country_name = 'Austria'
self.population = 8901064
self.url = 'https://covid19-dashboard.ages.at/data/CovidFaelle_Timeline.csv'
self.contains_tests = False
self.csv_encoding = 'utf-8'
self.csv_separator = ';'
self.csv = True
self.CasesPer100k_thresholds = threshold_list
self.Range_for_R = range_for_r
self.color_sizes = dict(colorEvenRows='#F3EED9', colorOddRows='white', colorHeaderBG='#ED2939', sizeHeaderFont=14, colorHeaderFont='white', colorCellFont='black', sizeCellFont=12, colorTitle='#ED2939', sizeTitleFont=27, colorPivotColumnText='#ED2939')
class Attributes_Be:
def __init__(self, threshold_list, range_for_r):
self.country_name = 'Belgium'
self.population = 11492641
self.url = 'https://epistat.sciensano.be/Data/COVID19BE_tests.json'
self.contains_tests = True
self.csv = False
self.CasesPer100k_thresholds = threshold_list
self.Range_for_R = range_for_r
self.color_sizes = dict(colorEvenRows='#FFE6D9', colorOddRows='white', colorHeaderBG='#FDDA24', sizeHeaderFont=14, colorHeaderFont='black', colorCellFont='black', sizeCellFont=12, colorTitle='black', sizeTitleFont=27, colorPivotColumnText='#EF3340')
class Attributes_Lv:
def __init__(self, threshold_list, range_for_r):
self.country_name = 'Latvia'
self.population = 1907675
self.url = 'https://data.gov.lv/dati/eng/api/3/action/datastore_search_sql?sql=SELECT%20*%20from%20%22d499d2f0-b1ea-4ba2-9600-2c701b03bd4a%22'
self.contains_tests = True
self.csv = False
self.CasesPer100k_thresholds = threshold_list
self.Range_for_R = range_for_r
self.color_sizes = dict(colorEvenRows='#F3EED9', colorOddRows='white', colorHeaderBG='#9E3039', sizeHeaderFont=14, colorHeaderFont='white', colorCellFont='black', sizeCellFont=12, colorTitle='#9E3039', sizeTitleFont=27, colorPivotColumnText='#9E3039')
def get_attributes(country, threshold_list=[10, 20, 50, 100, 200, 400, 600, 800, 1000], range_for_r=[0.8, 0.85, 0.9, 0.95, 1.05, 1.1, 1.15, 1.2]):
"""
Gets the country specific attributes like Name, population, url etc.
Parameters
----------
country : str
A two letter color code for a country e.g. 'de' for Germany
thresholds_list : list
optional: A list of integers representing the threshold which R has to go above or below
range_for_r : list
optional: A list of floats representing the range of R
Returns
-------
class
Class with the country specific attributes. Also contains a color scheme class for this country
"""
try:
if country == 'de':
attributes = attributes_de(threshold_list, range_for_r)
elif country == 'fr':
attributes = attributes_fr(threshold_list, range_for_r)
elif country == 'at':
attributes = attributes_at(threshold_list, range_for_r)
elif country == 'be':
attributes = attributes_be(threshold_list, range_for_r)
elif country == 'lv':
attributes = attributes_lv(threshold_list, range_for_r)
else:
print('Error no such country attribute defined')
return attributes
except Exception as e:
print(e)
|
"""
Common bazel version requirements for tests
"""
CURRENT_BAZEL_VERSION = "5.0.0"
OTHER_BAZEL_VERSIONS = [
"4.2.2",
]
SUPPORTED_BAZEL_VERSIONS = [
CURRENT_BAZEL_VERSION,
] + OTHER_BAZEL_VERSIONS
|
"""
Common bazel version requirements for tests
"""
current_bazel_version = '5.0.0'
other_bazel_versions = ['4.2.2']
supported_bazel_versions = [CURRENT_BAZEL_VERSION] + OTHER_BAZEL_VERSIONS
|
# See also examples/example_track/track_meta.py for a longer, commented example
track = dict(
author_username='dansbecker',
course_name='Machine Learning',
course_url='https://www.kaggle.com/learn/intro-to-machine-learning'
)
lessons = [
dict(
topic='Your First BiqQuery ML Model',
),
]
notebooks = [
dict(
filename='tut1.ipynb',
lesson_idx=0,
type='tutorial',
scriptid=4076893,
),
dict(
filename='ex1.ipynb',
lesson_idx=0,
type='exercise',
scriptid=4077160,
),
]
|
track = dict(author_username='dansbecker', course_name='Machine Learning', course_url='https://www.kaggle.com/learn/intro-to-machine-learning')
lessons = [dict(topic='Your First BiqQuery ML Model')]
notebooks = [dict(filename='tut1.ipynb', lesson_idx=0, type='tutorial', scriptid=4076893), dict(filename='ex1.ipynb', lesson_idx=0, type='exercise', scriptid=4077160)]
|
class Solution:
def canThreePartsEqualSum(self, A: List[int]) -> bool:
# Since all the three parts are equal, if we sum all element of arrary it should be a multiplication of 3
# so the sum of each part must be equal to sum of all element divided by 3
quotient, remainder = divmod(sum(A), 3)
if remainder != 0:
return False
subarray = 0
partitions = 0
for num in A:
subarray += num
if subarray == quotient:
partitions += 1
subarray = 0
# Check if it consist at least 3 partitions
return partitions >= 3
|
class Solution:
def can_three_parts_equal_sum(self, A: List[int]) -> bool:
(quotient, remainder) = divmod(sum(A), 3)
if remainder != 0:
return False
subarray = 0
partitions = 0
for num in A:
subarray += num
if subarray == quotient:
partitions += 1
subarray = 0
return partitions >= 3
|
STATE_CITY = "fluids_state_city"
OBS_QLIDAR = "fluids_obs_qlidar"
OBS_GRID = "fluids_obs_grid"
OBS_BIRDSEYE = "fluids_obs_birdseye"
OBS_NONE = "fluids_obs_none"
BACKGROUND_CSP = "fluids_background_csp"
BACKGROUND_NULL = "fluids_background_null"
REWARD_PATH = "fluids_reward_path"
REWARD_NONE = "fluids_reward_none"
RIGHT = "RIGHT"
LEFT = "LEFT"
STRAIGHT = "STRAIGHT"
RED = (0xf6, 0x11, 0x46)
YELLOW = (0xfc, 0xef, 0x5e),
GREEN = (0, 0xc6, 0x44)
|
state_city = 'fluids_state_city'
obs_qlidar = 'fluids_obs_qlidar'
obs_grid = 'fluids_obs_grid'
obs_birdseye = 'fluids_obs_birdseye'
obs_none = 'fluids_obs_none'
background_csp = 'fluids_background_csp'
background_null = 'fluids_background_null'
reward_path = 'fluids_reward_path'
reward_none = 'fluids_reward_none'
right = 'RIGHT'
left = 'LEFT'
straight = 'STRAIGHT'
red = (246, 17, 70)
yellow = ((252, 239, 94),)
green = (0, 198, 68)
|
class Solution:
def generate(self, num_rows):
if num_rows == 0:
return []
ans = [1]
result = [ans]
for _ in range(num_rows - 1):
ans = [1] + [ans[i] + ans[i + 1] for i in range(len(ans[:-1]))] + [1]
result.append(ans)
return result
|
class Solution:
def generate(self, num_rows):
if num_rows == 0:
return []
ans = [1]
result = [ans]
for _ in range(num_rows - 1):
ans = [1] + [ans[i] + ans[i + 1] for i in range(len(ans[:-1]))] + [1]
result.append(ans)
return result
|
for testcase in range(int(input())):
n = int(input())
dict = {}
comb = 1
m = (10**9)+7
for x in input().split():
no = int(x)
try:
dict[no] = dict[no] + 1
except:
dict[no] = 1
dict = list(dict.items())
dict.sort(key=lambda x: x[0], reverse=True)
dict = [x[1] for x in dict]
for ind in range(len(dict)):
if dict[ind]==0:
continue
if (dict[ind]%2==0):
for j in range(dict[ind]-1,2,-2):
comb = (comb*j) % m
else:
for j in range(dict[ind],2,-2):
comb = (comb*j) % m
comb = (comb*dict[ind+1]) % m
dict[ind+1] -= 1
print(comb)
|
for testcase in range(int(input())):
n = int(input())
dict = {}
comb = 1
m = 10 ** 9 + 7
for x in input().split():
no = int(x)
try:
dict[no] = dict[no] + 1
except:
dict[no] = 1
dict = list(dict.items())
dict.sort(key=lambda x: x[0], reverse=True)
dict = [x[1] for x in dict]
for ind in range(len(dict)):
if dict[ind] == 0:
continue
if dict[ind] % 2 == 0:
for j in range(dict[ind] - 1, 2, -2):
comb = comb * j % m
else:
for j in range(dict[ind], 2, -2):
comb = comb * j % m
comb = comb * dict[ind + 1] % m
dict[ind + 1] -= 1
print(comb)
|
class Timer:
def __init__(self, duration, ticks):
self.duration = duration
self.ticks = ticks
self.thread = None
def start(self):
pass
# start Thread here
|
class Timer:
def __init__(self, duration, ticks):
self.duration = duration
self.ticks = ticks
self.thread = None
def start(self):
pass
|
#MAIN PROGRAM STARTS HERE:
num = int(input('Enter the number of rows and columns for the square: '))
for x in range(1, num + 1):
for y in range(1, num - 2 + 1):
print ('{} {} '.format(x, y), end='')
print()
|
num = int(input('Enter the number of rows and columns for the square: '))
for x in range(1, num + 1):
for y in range(1, num - 2 + 1):
print('{} {} '.format(x, y), end='')
print()
|
class PrivilegeNotHeldException(UnauthorizedAccessException):
"""
The exception that is thrown when a method in the System.Security.AccessControl namespace attempts to enable a privilege that it does not have.
PrivilegeNotHeldException()
PrivilegeNotHeldException(privilege: str)
PrivilegeNotHeldException(privilege: str,inner: Exception)
"""
def ZZZ(self):
"""hardcoded/mock instance of the class"""
return PrivilegeNotHeldException()
instance=ZZZ()
"""hardcoded/returns an instance of the class"""
def GetObjectData(self,info,context):
"""
GetObjectData(self: PrivilegeNotHeldException,info: SerializationInfo,context: StreamingContext)
Sets the info parameter with information about the exception.
info: The System.Runtime.Serialization.SerializationInfo that holds the serialized object data about the exception being thrown.
context: The System.Runtime.Serialization.StreamingContext that contains contextual information about the source or destination.
"""
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self,privilege=None,inner=None):
"""
__new__(cls: type)
__new__(cls: type,privilege: str)
__new__(cls: type,privilege: str,inner: Exception)
"""
pass
def __reduce_ex__(self,*args):
pass
def __str__(self,*args):
pass
PrivilegeName=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Gets the name of the privilege that is not enabled.
Get: PrivilegeName(self: PrivilegeNotHeldException) -> str
"""
SerializeObjectState=None
|
class Privilegenotheldexception(UnauthorizedAccessException):
"""
The exception that is thrown when a method in the System.Security.AccessControl namespace attempts to enable a privilege that it does not have.
PrivilegeNotHeldException()
PrivilegeNotHeldException(privilege: str)
PrivilegeNotHeldException(privilege: str,inner: Exception)
"""
def zzz(self):
"""hardcoded/mock instance of the class"""
return privilege_not_held_exception()
instance = zzz()
'hardcoded/returns an instance of the class'
def get_object_data(self, info, context):
"""
GetObjectData(self: PrivilegeNotHeldException,info: SerializationInfo,context: StreamingContext)
Sets the info parameter with information about the exception.
info: The System.Runtime.Serialization.SerializationInfo that holds the serialized object data about the exception being thrown.
context: The System.Runtime.Serialization.StreamingContext that contains contextual information about the source or destination.
"""
pass
def __init__(self, *args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self, privilege=None, inner=None):
"""
__new__(cls: type)
__new__(cls: type,privilege: str)
__new__(cls: type,privilege: str,inner: Exception)
"""
pass
def __reduce_ex__(self, *args):
pass
def __str__(self, *args):
pass
privilege_name = property(lambda self: object(), lambda self, v: None, lambda self: None)
'Gets the name of the privilege that is not enabled.\n\n\n\nGet: PrivilegeName(self: PrivilegeNotHeldException) -> str\n\n\n\n'
serialize_object_state = None
|
def segmented_sieve(n):
# Create an boolean array with all values True
primes = [True]*n
for p in range(2,n):
#If prime[p] is True,it is a prime and its multiples are not prime
if primes[p]:
for i in range(2*p,n,p):
# Mark every multiple of a prime as not prime
primes[i]=False
#If value is true it is prime and print value
for l in range(2,n):
if primes[l]:
print(f"{l} ")
#Test
while True:
try:
input_value = int(input("Please a number: "))
segmented_sieve(input_value)
break
except ValueError:
print("No valid integer! Please try again ...")
|
def segmented_sieve(n):
primes = [True] * n
for p in range(2, n):
if primes[p]:
for i in range(2 * p, n, p):
primes[i] = False
for l in range(2, n):
if primes[l]:
print(f'{l} ')
while True:
try:
input_value = int(input('Please a number: '))
segmented_sieve(input_value)
break
except ValueError:
print('No valid integer! Please try again ...')
|
def test_test():
"""A generic test
:return:
"""
assert True
|
def test_test():
"""A generic test
:return:
"""
assert True
|
class AuxPowMixin(object):
AUXPOW_START_HEIGHT = 0
AUXPOW_CHAIN_ID = 0x0001
BLOCK_VERSION_AUXPOW_BIT = 0
@classmethod
def is_auxpow_active(cls, header) -> bool:
height_allows_auxpow = header['block_height'] >= cls.AUXPOW_START_HEIGHT
version_allows_auxpow = header['version'] & cls.BLOCK_VERSION_AUXPOW_BIT
return height_allows_auxpow and version_allows_auxpow
|
class Auxpowmixin(object):
auxpow_start_height = 0
auxpow_chain_id = 1
block_version_auxpow_bit = 0
@classmethod
def is_auxpow_active(cls, header) -> bool:
height_allows_auxpow = header['block_height'] >= cls.AUXPOW_START_HEIGHT
version_allows_auxpow = header['version'] & cls.BLOCK_VERSION_AUXPOW_BIT
return height_allows_auxpow and version_allows_auxpow
|
#!/usr/bin/env python3
#filter sensitive words in user's input
def replace_sensitive_words(input_word):
s_words = []
with open('filtered_words','r') as f:
line = f.readline()
while line != '':
s_words.append(line.strip())
line = f.readline()
for word in s_words:
if word in input_word:
input_word = input_word.replace(word, "**")
print(input_word)
if __name__ == '__main__':
while True:
input_word = input('--> ')
replace_sensitive_words(input_word)
|
def replace_sensitive_words(input_word):
s_words = []
with open('filtered_words', 'r') as f:
line = f.readline()
while line != '':
s_words.append(line.strip())
line = f.readline()
for word in s_words:
if word in input_word:
input_word = input_word.replace(word, '**')
print(input_word)
if __name__ == '__main__':
while True:
input_word = input('--> ')
replace_sensitive_words(input_word)
|
#Calcular el salario neto de un tnrabajador en fucion del numero de horas trabajadas, el precio de la hora
#y el descuento fijo al sueldo base por concepto de impuestos del 20%
horas = float(input("Ingrese el numero de horas trabajadas: "))
precio_hora = float(input("Ingrese el precio por hora trabajada: "))
sueldo_base = float(input("Ingrese el valor del sueldo base: "))
pago_hora = horas * precio_hora
impuesto = 0.2
salario_neto = pago_hora + (sueldo_base * 0.8)
print(f"Si el trabajador tiene un sueldo base de {sueldo_base}$ (al cual se le descuenta un 20% por impuestos), trabaja {horas} horas, y la hora se le paga a {precio_hora}$.")
print(f"El salario neto del trabajador es de {salario_neto}$")
|
horas = float(input('Ingrese el numero de horas trabajadas: '))
precio_hora = float(input('Ingrese el precio por hora trabajada: '))
sueldo_base = float(input('Ingrese el valor del sueldo base: '))
pago_hora = horas * precio_hora
impuesto = 0.2
salario_neto = pago_hora + sueldo_base * 0.8
print(f'Si el trabajador tiene un sueldo base de {sueldo_base}$ (al cual se le descuenta un 20% por impuestos), trabaja {horas} horas, y la hora se le paga a {precio_hora}$.')
print(f'El salario neto del trabajador es de {salario_neto}$')
|
# Copyright 2017 The Bazel Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Actions to manipulate debug symbol outputs."""
load("@build_bazel_rules_apple//apple/bundling:file_actions.bzl", "file_actions")
def _collect_linkmaps(ctx, debug_outputs, bundle_name):
"""Collects the available linkmaps from the binary.
Args:
ctx: The current context.
debug_outputs: dSYM bundle binary provider.
bundle_name: Anticipated name of the dSYM bundle.
Returns:
A list of linkmap files, one per linked architecture.
"""
outputs = []
actions = ctx.actions
# TODO(b/36174487): Iterate over .items() once the Map/dict problem is fixed.
for arch in debug_outputs.outputs_map:
arch_outputs = debug_outputs.outputs_map[arch]
linkmap = arch_outputs["linkmap"]
out_linkmap = actions.declare_file("%s_%s.linkmap" % (bundle_name, arch))
outputs.append(out_linkmap)
file_actions.symlink(ctx, linkmap, out_linkmap)
return outputs
def _create_symbol_bundle(ctx, debug_outputs, bundle_name, bundle_extension = ""):
"""Creates the .dSYM bundle next to the output archive.
The generated bundle will have the same name as the bundle being built
(including its extension), but with the ".dSYM" extension appended to it.
If the target being built does not have a binary or if the build it not
generating debug symbols (`--apple_generate_dsym` is not provided), then this
function is a no-op that returns an empty list.
This function assumes that the target has a user-provided binary in the
`binary` attribute. It is the responsibility of the caller to check this.
Args:
ctx: The Skylark context.
debug_outputs: dSYM bundle binary provider.
bundle_name: Anticipated name of the dSYM bundle.
bundle_extension: Anticipated extension of the dSYM bundle, empty string if
it does not have one.
Returns:
A list of files that comprise the .dSYM bundle, which should be returned as
additional outputs from the rule.
"""
dsym_bundle_name = bundle_name + bundle_extension + ".dSYM"
outputs = []
actions = ctx.actions
# TODO(b/36174487): Iterate over .items() once the Map/dict problem is fixed.
for arch in debug_outputs.outputs_map:
arch_outputs = debug_outputs.outputs_map[arch]
dsym_binary = arch_outputs["dsym_binary"]
out_symbols = actions.declare_file("%s/Contents/Resources/DWARF/%s_%s" % (
dsym_bundle_name,
bundle_name,
arch,
))
outputs.append(out_symbols)
file_actions.symlink(ctx, dsym_binary, out_symbols)
# If we found any outputs, create the Info.plist for the bundle as well;
# otherwise, we just return the empty list. The plist generated by dsymutil
# only varies based on the bundle name, so we regenerate it here rather than
# propagate the other one from the apple_binary. (See
# https://github.com/llvm-mirror/llvm/blob/master/tools/dsymutil/dsymutil.cpp)
if outputs:
out_plist = actions.declare_file("%s/Contents/Info.plist" %
dsym_bundle_name)
outputs.append(out_plist)
actions.expand_template(
template = ctx.file._dsym_info_plist_template,
output = out_plist,
substitutions = {
"%bundle_name_with_extension%": bundle_name + bundle_extension,
},
)
return outputs
# Define the loadable module that lists the exported symbols in this file.
debug_symbol_actions = struct(
collect_linkmaps = _collect_linkmaps,
create_symbol_bundle = _create_symbol_bundle,
)
|
"""Actions to manipulate debug symbol outputs."""
load('@build_bazel_rules_apple//apple/bundling:file_actions.bzl', 'file_actions')
def _collect_linkmaps(ctx, debug_outputs, bundle_name):
"""Collects the available linkmaps from the binary.
Args:
ctx: The current context.
debug_outputs: dSYM bundle binary provider.
bundle_name: Anticipated name of the dSYM bundle.
Returns:
A list of linkmap files, one per linked architecture.
"""
outputs = []
actions = ctx.actions
for arch in debug_outputs.outputs_map:
arch_outputs = debug_outputs.outputs_map[arch]
linkmap = arch_outputs['linkmap']
out_linkmap = actions.declare_file('%s_%s.linkmap' % (bundle_name, arch))
outputs.append(out_linkmap)
file_actions.symlink(ctx, linkmap, out_linkmap)
return outputs
def _create_symbol_bundle(ctx, debug_outputs, bundle_name, bundle_extension=''):
"""Creates the .dSYM bundle next to the output archive.
The generated bundle will have the same name as the bundle being built
(including its extension), but with the ".dSYM" extension appended to it.
If the target being built does not have a binary or if the build it not
generating debug symbols (`--apple_generate_dsym` is not provided), then this
function is a no-op that returns an empty list.
This function assumes that the target has a user-provided binary in the
`binary` attribute. It is the responsibility of the caller to check this.
Args:
ctx: The Skylark context.
debug_outputs: dSYM bundle binary provider.
bundle_name: Anticipated name of the dSYM bundle.
bundle_extension: Anticipated extension of the dSYM bundle, empty string if
it does not have one.
Returns:
A list of files that comprise the .dSYM bundle, which should be returned as
additional outputs from the rule.
"""
dsym_bundle_name = bundle_name + bundle_extension + '.dSYM'
outputs = []
actions = ctx.actions
for arch in debug_outputs.outputs_map:
arch_outputs = debug_outputs.outputs_map[arch]
dsym_binary = arch_outputs['dsym_binary']
out_symbols = actions.declare_file('%s/Contents/Resources/DWARF/%s_%s' % (dsym_bundle_name, bundle_name, arch))
outputs.append(out_symbols)
file_actions.symlink(ctx, dsym_binary, out_symbols)
if outputs:
out_plist = actions.declare_file('%s/Contents/Info.plist' % dsym_bundle_name)
outputs.append(out_plist)
actions.expand_template(template=ctx.file._dsym_info_plist_template, output=out_plist, substitutions={'%bundle_name_with_extension%': bundle_name + bundle_extension})
return outputs
debug_symbol_actions = struct(collect_linkmaps=_collect_linkmaps, create_symbol_bundle=_create_symbol_bundle)
|
class Runtime:
@staticmethod
def v3(major: str, feature: str, ml_type: str = None, scala_version: str = "2.12"):
if ml_type and ml_type.lower() not in ["cpu", "gpu"]:
raise ValueError('"ml_type" can only be "cpu" or "gpu"!')
return "".join(
[
f"{major}.",
f"{feature}.x",
"" if not ml_type else f"-{ml_type}-ml",
f"-scala{scala_version}",
]
)
@staticmethod
def v2(
major: str,
feature: str,
maintenance: str,
runtime_version: str,
scala_version: str = "2.11",
):
raise ValueError("This version of runtime is no longer supported!")
@staticmethod
def light(major: str, feature: str, scala_version: str = "2.11"):
return f"apache-spark.{major}.{feature}.x-scala{scala_version}"
|
class Runtime:
@staticmethod
def v3(major: str, feature: str, ml_type: str=None, scala_version: str='2.12'):
if ml_type and ml_type.lower() not in ['cpu', 'gpu']:
raise value_error('"ml_type" can only be "cpu" or "gpu"!')
return ''.join([f'{major}.', f'{feature}.x', '' if not ml_type else f'-{ml_type}-ml', f'-scala{scala_version}'])
@staticmethod
def v2(major: str, feature: str, maintenance: str, runtime_version: str, scala_version: str='2.11'):
raise value_error('This version of runtime is no longer supported!')
@staticmethod
def light(major: str, feature: str, scala_version: str='2.11'):
return f'apache-spark.{major}.{feature}.x-scala{scala_version}'
|
s = 'abc'; print(s.isupper(), s)
s = 'Abc'; print(s.isupper(), s)
s = 'aBc'; print(s.isupper(), s)
s = 'abC'; print(s.isupper(), s)
s = 'abc'; print(s.isupper(), s)
s = 'ABC'; print(s.isupper(), s)
s = 'abc'; print(s.capitalize().isupper(), s.capitalize())
|
s = 'abc'
print(s.isupper(), s)
s = 'Abc'
print(s.isupper(), s)
s = 'aBc'
print(s.isupper(), s)
s = 'abC'
print(s.isupper(), s)
s = 'abc'
print(s.isupper(), s)
s = 'ABC'
print(s.isupper(), s)
s = 'abc'
print(s.capitalize().isupper(), s.capitalize())
|
#!/usr/bin/env python
'''
Global Variables convention:
* start with UpperCase
* have no _ character
* may have mid UpperCase words
'''
Debug = True
Silent = True
Verbose = False
CustomerName = 'customer_name'
AuthHeader = {'Content-Type': 'application/json'}
BaseURL = "https://firewall-api.d-zone.ca"
AuthURL = 'https://firewall-auth.d-zone.ca/auth/realms/D-ZoneFireWall/protocol/openid-connect/token'
|
"""
Global Variables convention:
* start with UpperCase
* have no _ character
* may have mid UpperCase words
"""
debug = True
silent = True
verbose = False
customer_name = 'customer_name'
auth_header = {'Content-Type': 'application/json'}
base_url = 'https://firewall-api.d-zone.ca'
auth_url = 'https://firewall-auth.d-zone.ca/auth/realms/D-ZoneFireWall/protocol/openid-connect/token'
|
"""Base observer class for weighmail operations.
"""
class BaseObserver(object):
"""Base observer class; does nothing."""
def searching(self, label):
"""Called when the search process has started for a label"""
pass
def labeling(self, label, count):
"""Called when the labelling process has started for a given label
label - the label we are working on
count - number of messages to label
"""
pass
def done_labeling(self, label, count):
"""Called when finished labelling for a given label
label - the label we were working on
count - number of messages that were labelled
"""
pass
def done(self):
"""Called when completely finished"""
pass
|
"""Base observer class for weighmail operations.
"""
class Baseobserver(object):
"""Base observer class; does nothing."""
def searching(self, label):
"""Called when the search process has started for a label"""
pass
def labeling(self, label, count):
"""Called when the labelling process has started for a given label
label - the label we are working on
count - number of messages to label
"""
pass
def done_labeling(self, label, count):
"""Called when finished labelling for a given label
label - the label we were working on
count - number of messages that were labelled
"""
pass
def done(self):
"""Called when completely finished"""
pass
|
#
# PySNMP MIB module FUNI-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/FUNI-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 19:03:03 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsUnion, SingleValueConstraint, ValueRangeConstraint, ConstraintsIntersection, ValueSizeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "SingleValueConstraint", "ValueRangeConstraint", "ConstraintsIntersection", "ValueSizeConstraint")
ifIndex, = mibBuilder.importSymbols("IF-MIB", "ifIndex")
NotificationGroup, ModuleCompliance, ObjectGroup = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance", "ObjectGroup")
TimeTicks, enterprises, MibIdentifier, Counter32, MibScalar, MibTable, MibTableRow, MibTableColumn, iso, Gauge32, ObjectIdentity, NotificationType, ModuleIdentity, Bits, Integer32, Unsigned32, Counter64, IpAddress = mibBuilder.importSymbols("SNMPv2-SMI", "TimeTicks", "enterprises", "MibIdentifier", "Counter32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "iso", "Gauge32", "ObjectIdentity", "NotificationType", "ModuleIdentity", "Bits", "Integer32", "Unsigned32", "Counter64", "IpAddress")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString")
atmfFuniMIB = ModuleIdentity((1, 3, 6, 1, 4, 1, 353, 5, 6, 1))
if mibBuilder.loadTexts: atmfFuniMIB.setLastUpdated('9705080000Z')
if mibBuilder.loadTexts: atmfFuniMIB.setOrganization('The ATM Forum')
atmForum = MibIdentifier((1, 3, 6, 1, 4, 1, 353))
atmForumNetworkManagement = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5))
atmfFuni = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5, 6))
funiMIBObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1))
class FuniValidVpi(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ValueRangeConstraint(0, 255)
class FuniValidVci(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ValueRangeConstraint(0, 65535)
funiIfConfTable = MibTable((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1), )
if mibBuilder.loadTexts: funiIfConfTable.setStatus('current')
funiIfConfEntry = MibTableRow((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"))
if mibBuilder.loadTexts: funiIfConfEntry.setStatus('current')
funiIfConfMode = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("mode1a", 1), ("mode1b", 2), ("mode3", 3), ("mode4", 4))).clone('mode1a')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfMode.setStatus('current')
funiIfConfFcsBits = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("fcsBits16", 1), ("fcsBits32", 2))).clone('fcsBits16')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfFcsBits.setStatus('current')
funiIfConfSigSupport = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enabled", 1), ("disabled", 2))).clone('disabled')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfSigSupport.setStatus('current')
funiIfConfSigVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 4), FuniValidVpi()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfSigVpi.setStatus('current')
funiIfConfSigVci = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 5), FuniValidVci().clone(5)).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfSigVci.setStatus('current')
funiIfConfIlmiSupport = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 6), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enabled", 1), ("disabled", 2))).clone('disabled')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfIlmiSupport.setStatus('current')
funiIfConfIlmiVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 7), FuniValidVpi()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfIlmiVpi.setStatus('current')
funiIfConfIlmiVci = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 8), FuniValidVci().clone(16)).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfIlmiVci.setStatus('current')
funiIfConfOamSupport = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 9), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enabled", 1), ("disabled", 2))).clone('disabled')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfConfOamSupport.setStatus('current')
funiIfStatsTable = MibTable((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2), )
if mibBuilder.loadTexts: funiIfStatsTable.setStatus('current')
funiIfStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"))
if mibBuilder.loadTexts: funiIfStatsEntry.setStatus('current')
funiIfEstablishedPvccs = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 1), Gauge32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfEstablishedPvccs.setStatus('current')
funiIfEstablishedSvccs = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 2), Gauge32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfEstablishedSvccs.setStatus('current')
funiIfRxAbortedFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfRxAbortedFrames.setStatus('current')
funiIfRxTooShortFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfRxTooShortFrames.setStatus('current')
funiIfRxTooLongFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfRxTooLongFrames.setStatus('current')
funiIfRxFcsErrFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 6), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfRxFcsErrFrames.setStatus('current')
funiIfRxUnknownFaFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 7), Counter32()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: funiIfRxUnknownFaFrames.setStatus('current')
funiIfRxDiscardedFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfRxDiscardedFrames.setStatus('current')
funiIfTxTooLongFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxTooLongFrames.setStatus('current')
funiIfTxLenErrFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxLenErrFrames.setStatus('current')
funiIfTxCrcErrFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxCrcErrFrames.setStatus('current')
funiIfTxPartialFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxPartialFrames.setStatus('current')
funiIfTxTimeOutFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 13), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxTimeOutFrames.setStatus('current')
funiIfTxDiscardedFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiIfTxDiscardedFrames.setStatus('current')
funiVclStatsTable = MibTable((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3), )
if mibBuilder.loadTexts: funiVclStatsTable.setStatus('current')
funiVclStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"), (0, "FUNI-MIB", "funiVclFaVpi"), (0, "FUNI-MIB", "funiVclFaVci"))
if mibBuilder.loadTexts: funiVclStatsEntry.setStatus('current')
funiVclFaVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 1), FuniValidVpi())
if mibBuilder.loadTexts: funiVclFaVpi.setStatus('current')
funiVclFaVci = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 2), FuniValidVci())
if mibBuilder.loadTexts: funiVclFaVci.setStatus('current')
funiVclRxClp0Frames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxClp0Frames.setStatus('current')
funiVclRxTotalFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxTotalFrames.setStatus('current')
funiVclTxClp0Frames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxClp0Frames.setStatus('current')
funiVclTxTotalFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 6), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxTotalFrames.setStatus('current')
funiVclRxClp0Octets = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxClp0Octets.setStatus('current')
funiVclRxTotalOctets = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxTotalOctets.setStatus('current')
funiVclTxClp0Octets = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxClp0Octets.setStatus('current')
funiVclTxTotalOctets = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxTotalOctets.setStatus('current')
funiVclRxErrors = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxErrors.setStatus('current')
funiVclTxErrors = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxErrors.setStatus('current')
funiVclRxOamFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 13), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclRxOamFrames.setStatus('current')
funiVclTxOamFrames = MibTableColumn((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: funiVclTxOamFrames.setStatus('current')
funiMIBConformance = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2))
funiMIBCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 1))
funiMIBGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2))
funiMIBCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 1, 1)).setObjects(("FUNI-MIB", "funiIfConfMinGroup"), ("FUNI-MIB", "funiIfStatsMinGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funiMIBCompliance = funiMIBCompliance.setStatus('current')
funiIfConfMinGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 1)).setObjects(("FUNI-MIB", "funiIfConfMode"), ("FUNI-MIB", "funiIfConfFcsBits"), ("FUNI-MIB", "funiIfConfSigSupport"), ("FUNI-MIB", "funiIfConfSigVpi"), ("FUNI-MIB", "funiIfConfSigVci"), ("FUNI-MIB", "funiIfConfIlmiSupport"), ("FUNI-MIB", "funiIfConfIlmiVpi"), ("FUNI-MIB", "funiIfConfIlmiVci"), ("FUNI-MIB", "funiIfConfOamSupport"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funiIfConfMinGroup = funiIfConfMinGroup.setStatus('current')
funiIfStatsMinGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 2)).setObjects(("FUNI-MIB", "funiIfEstablishedPvccs"), ("FUNI-MIB", "funiIfEstablishedSvccs"), ("FUNI-MIB", "funiIfRxAbortedFrames"), ("FUNI-MIB", "funiIfRxTooShortFrames"), ("FUNI-MIB", "funiIfRxTooLongFrames"), ("FUNI-MIB", "funiIfRxFcsErrFrames"), ("FUNI-MIB", "funiIfRxUnknownFaFrames"), ("FUNI-MIB", "funiIfRxDiscardedFrames"), ("FUNI-MIB", "funiIfTxTooLongFrames"), ("FUNI-MIB", "funiIfTxLenErrFrames"), ("FUNI-MIB", "funiIfTxCrcErrFrames"), ("FUNI-MIB", "funiIfTxPartialFrames"), ("FUNI-MIB", "funiIfTxTimeOutFrames"), ("FUNI-MIB", "funiIfTxDiscardedFrames"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funiIfStatsMinGroup = funiIfStatsMinGroup.setStatus('current')
funiVclStatsOptionalGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 3)).setObjects(("FUNI-MIB", "funiVclRxClp0Frames"), ("FUNI-MIB", "funiVclRxTotalFrames"), ("FUNI-MIB", "funiVclTxClp0Frames"), ("FUNI-MIB", "funiVclTxTotalFrames"), ("FUNI-MIB", "funiVclRxClp0Octets"), ("FUNI-MIB", "funiVclRxTotalOctets"), ("FUNI-MIB", "funiVclTxClp0Octets"), ("FUNI-MIB", "funiVclTxTotalOctets"), ("FUNI-MIB", "funiVclRxErrors"), ("FUNI-MIB", "funiVclTxErrors"), ("FUNI-MIB", "funiVclRxOamFrames"), ("FUNI-MIB", "funiVclTxOamFrames"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funiVclStatsOptionalGroup = funiVclStatsOptionalGroup.setStatus('current')
mibBuilder.exportSymbols("FUNI-MIB", funiVclRxErrors=funiVclRxErrors, funiVclTxClp0Octets=funiVclTxClp0Octets, funiVclTxClp0Frames=funiVclTxClp0Frames, funiIfConfIlmiSupport=funiIfConfIlmiSupport, funiIfConfMode=funiIfConfMode, FuniValidVpi=FuniValidVpi, funiIfEstablishedPvccs=funiIfEstablishedPvccs, funiIfTxCrcErrFrames=funiIfTxCrcErrFrames, funiIfTxTimeOutFrames=funiIfTxTimeOutFrames, funiIfTxTooLongFrames=funiIfTxTooLongFrames, funiVclRxTotalOctets=funiVclRxTotalOctets, funiIfStatsMinGroup=funiIfStatsMinGroup, funiIfConfTable=funiIfConfTable, funiIfStatsEntry=funiIfStatsEntry, funiVclFaVpi=funiVclFaVpi, funiIfConfSigVpi=funiIfConfSigVpi, funiIfConfFcsBits=funiIfConfFcsBits, funiIfRxTooLongFrames=funiIfRxTooLongFrames, funiIfRxDiscardedFrames=funiIfRxDiscardedFrames, atmfFuniMIB=atmfFuniMIB, funiVclTxErrors=funiVclTxErrors, atmfFuni=atmfFuni, funiIfRxUnknownFaFrames=funiIfRxUnknownFaFrames, funiIfTxPartialFrames=funiIfTxPartialFrames, funiIfConfIlmiVci=funiIfConfIlmiVci, funiIfTxLenErrFrames=funiIfTxLenErrFrames, funiVclRxTotalFrames=funiVclRxTotalFrames, funiIfConfMinGroup=funiIfConfMinGroup, funiVclStatsTable=funiVclStatsTable, FuniValidVci=FuniValidVci, funiVclRxOamFrames=funiVclRxOamFrames, funiIfConfIlmiVpi=funiIfConfIlmiVpi, funiVclStatsEntry=funiVclStatsEntry, funiIfConfSigSupport=funiIfConfSigSupport, funiIfRxFcsErrFrames=funiIfRxFcsErrFrames, funiVclTxTotalOctets=funiVclTxTotalOctets, funiIfStatsTable=funiIfStatsTable, funiVclStatsOptionalGroup=funiVclStatsOptionalGroup, funiVclRxClp0Frames=funiVclRxClp0Frames, funiVclTxOamFrames=funiVclTxOamFrames, funiMIBGroups=funiMIBGroups, atmForum=atmForum, funiMIBCompliance=funiMIBCompliance, funiIfConfSigVci=funiIfConfSigVci, PYSNMP_MODULE_ID=atmfFuniMIB, funiIfConfEntry=funiIfConfEntry, funiIfRxTooShortFrames=funiIfRxTooShortFrames, funiIfEstablishedSvccs=funiIfEstablishedSvccs, funiMIBCompliances=funiMIBCompliances, atmForumNetworkManagement=atmForumNetworkManagement, funiVclTxTotalFrames=funiVclTxTotalFrames, funiIfTxDiscardedFrames=funiIfTxDiscardedFrames, funiVclFaVci=funiVclFaVci, funiMIBConformance=funiMIBConformance, funiIfConfOamSupport=funiIfConfOamSupport, funiVclRxClp0Octets=funiVclRxClp0Octets, funiIfRxAbortedFrames=funiIfRxAbortedFrames, funiMIBObjects=funiMIBObjects)
|
(object_identifier, octet_string, integer) = mibBuilder.importSymbols('ASN1', 'ObjectIdentifier', 'OctetString', 'Integer')
(named_values,) = mibBuilder.importSymbols('ASN1-ENUMERATION', 'NamedValues')
(constraints_union, single_value_constraint, value_range_constraint, constraints_intersection, value_size_constraint) = mibBuilder.importSymbols('ASN1-REFINEMENT', 'ConstraintsUnion', 'SingleValueConstraint', 'ValueRangeConstraint', 'ConstraintsIntersection', 'ValueSizeConstraint')
(if_index,) = mibBuilder.importSymbols('IF-MIB', 'ifIndex')
(notification_group, module_compliance, object_group) = mibBuilder.importSymbols('SNMPv2-CONF', 'NotificationGroup', 'ModuleCompliance', 'ObjectGroup')
(time_ticks, enterprises, mib_identifier, counter32, mib_scalar, mib_table, mib_table_row, mib_table_column, iso, gauge32, object_identity, notification_type, module_identity, bits, integer32, unsigned32, counter64, ip_address) = mibBuilder.importSymbols('SNMPv2-SMI', 'TimeTicks', 'enterprises', 'MibIdentifier', 'Counter32', 'MibScalar', 'MibTable', 'MibTableRow', 'MibTableColumn', 'iso', 'Gauge32', 'ObjectIdentity', 'NotificationType', 'ModuleIdentity', 'Bits', 'Integer32', 'Unsigned32', 'Counter64', 'IpAddress')
(textual_convention, display_string) = mibBuilder.importSymbols('SNMPv2-TC', 'TextualConvention', 'DisplayString')
atmf_funi_mib = module_identity((1, 3, 6, 1, 4, 1, 353, 5, 6, 1))
if mibBuilder.loadTexts:
atmfFuniMIB.setLastUpdated('9705080000Z')
if mibBuilder.loadTexts:
atmfFuniMIB.setOrganization('The ATM Forum')
atm_forum = mib_identifier((1, 3, 6, 1, 4, 1, 353))
atm_forum_network_management = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5))
atmf_funi = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5, 6))
funi_mib_objects = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1))
class Funivalidvpi(TextualConvention, Integer32):
status = 'current'
subtype_spec = Integer32.subtypeSpec + value_range_constraint(0, 255)
class Funivalidvci(TextualConvention, Integer32):
status = 'current'
subtype_spec = Integer32.subtypeSpec + value_range_constraint(0, 65535)
funi_if_conf_table = mib_table((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1))
if mibBuilder.loadTexts:
funiIfConfTable.setStatus('current')
funi_if_conf_entry = mib_table_row((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1)).setIndexNames((0, 'IF-MIB', 'ifIndex'))
if mibBuilder.loadTexts:
funiIfConfEntry.setStatus('current')
funi_if_conf_mode = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 1), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2, 3, 4))).clone(namedValues=named_values(('mode1a', 1), ('mode1b', 2), ('mode3', 3), ('mode4', 4))).clone('mode1a')).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfMode.setStatus('current')
funi_if_conf_fcs_bits = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 2), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2))).clone(namedValues=named_values(('fcsBits16', 1), ('fcsBits32', 2))).clone('fcsBits16')).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfFcsBits.setStatus('current')
funi_if_conf_sig_support = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 3), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2))).clone(namedValues=named_values(('enabled', 1), ('disabled', 2))).clone('disabled')).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfSigSupport.setStatus('current')
funi_if_conf_sig_vpi = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 4), funi_valid_vpi()).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfSigVpi.setStatus('current')
funi_if_conf_sig_vci = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 5), funi_valid_vci().clone(5)).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfSigVci.setStatus('current')
funi_if_conf_ilmi_support = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 6), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2))).clone(namedValues=named_values(('enabled', 1), ('disabled', 2))).clone('disabled')).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfIlmiSupport.setStatus('current')
funi_if_conf_ilmi_vpi = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 7), funi_valid_vpi()).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfIlmiVpi.setStatus('current')
funi_if_conf_ilmi_vci = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 8), funi_valid_vci().clone(16)).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfIlmiVci.setStatus('current')
funi_if_conf_oam_support = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 1, 1, 9), integer32().subtype(subtypeSpec=constraints_union(single_value_constraint(1, 2))).clone(namedValues=named_values(('enabled', 1), ('disabled', 2))).clone('disabled')).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfConfOamSupport.setStatus('current')
funi_if_stats_table = mib_table((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2))
if mibBuilder.loadTexts:
funiIfStatsTable.setStatus('current')
funi_if_stats_entry = mib_table_row((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1)).setIndexNames((0, 'IF-MIB', 'ifIndex'))
if mibBuilder.loadTexts:
funiIfStatsEntry.setStatus('current')
funi_if_established_pvccs = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 1), gauge32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfEstablishedPvccs.setStatus('current')
funi_if_established_svccs = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 2), gauge32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfEstablishedSvccs.setStatus('current')
funi_if_rx_aborted_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 3), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfRxAbortedFrames.setStatus('current')
funi_if_rx_too_short_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 4), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfRxTooShortFrames.setStatus('current')
funi_if_rx_too_long_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 5), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfRxTooLongFrames.setStatus('current')
funi_if_rx_fcs_err_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 6), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfRxFcsErrFrames.setStatus('current')
funi_if_rx_unknown_fa_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 7), counter32()).setMaxAccess('readwrite')
if mibBuilder.loadTexts:
funiIfRxUnknownFaFrames.setStatus('current')
funi_if_rx_discarded_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 8), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfRxDiscardedFrames.setStatus('current')
funi_if_tx_too_long_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 9), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxTooLongFrames.setStatus('current')
funi_if_tx_len_err_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 10), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxLenErrFrames.setStatus('current')
funi_if_tx_crc_err_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 11), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxCrcErrFrames.setStatus('current')
funi_if_tx_partial_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 12), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxPartialFrames.setStatus('current')
funi_if_tx_time_out_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 13), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxTimeOutFrames.setStatus('current')
funi_if_tx_discarded_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 2, 1, 14), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiIfTxDiscardedFrames.setStatus('current')
funi_vcl_stats_table = mib_table((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3))
if mibBuilder.loadTexts:
funiVclStatsTable.setStatus('current')
funi_vcl_stats_entry = mib_table_row((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1)).setIndexNames((0, 'IF-MIB', 'ifIndex'), (0, 'FUNI-MIB', 'funiVclFaVpi'), (0, 'FUNI-MIB', 'funiVclFaVci'))
if mibBuilder.loadTexts:
funiVclStatsEntry.setStatus('current')
funi_vcl_fa_vpi = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 1), funi_valid_vpi())
if mibBuilder.loadTexts:
funiVclFaVpi.setStatus('current')
funi_vcl_fa_vci = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 2), funi_valid_vci())
if mibBuilder.loadTexts:
funiVclFaVci.setStatus('current')
funi_vcl_rx_clp0_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 3), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxClp0Frames.setStatus('current')
funi_vcl_rx_total_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 4), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxTotalFrames.setStatus('current')
funi_vcl_tx_clp0_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 5), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxClp0Frames.setStatus('current')
funi_vcl_tx_total_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 6), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxTotalFrames.setStatus('current')
funi_vcl_rx_clp0_octets = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 7), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxClp0Octets.setStatus('current')
funi_vcl_rx_total_octets = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 8), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxTotalOctets.setStatus('current')
funi_vcl_tx_clp0_octets = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 9), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxClp0Octets.setStatus('current')
funi_vcl_tx_total_octets = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 10), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxTotalOctets.setStatus('current')
funi_vcl_rx_errors = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 11), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxErrors.setStatus('current')
funi_vcl_tx_errors = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 12), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxErrors.setStatus('current')
funi_vcl_rx_oam_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 13), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclRxOamFrames.setStatus('current')
funi_vcl_tx_oam_frames = mib_table_column((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 1, 3, 1, 14), counter32()).setMaxAccess('readonly')
if mibBuilder.loadTexts:
funiVclTxOamFrames.setStatus('current')
funi_mib_conformance = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2))
funi_mib_compliances = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 1))
funi_mib_groups = mib_identifier((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2))
funi_mib_compliance = module_compliance((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 1, 1)).setObjects(('FUNI-MIB', 'funiIfConfMinGroup'), ('FUNI-MIB', 'funiIfStatsMinGroup'))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funi_mib_compliance = funiMIBCompliance.setStatus('current')
funi_if_conf_min_group = object_group((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 1)).setObjects(('FUNI-MIB', 'funiIfConfMode'), ('FUNI-MIB', 'funiIfConfFcsBits'), ('FUNI-MIB', 'funiIfConfSigSupport'), ('FUNI-MIB', 'funiIfConfSigVpi'), ('FUNI-MIB', 'funiIfConfSigVci'), ('FUNI-MIB', 'funiIfConfIlmiSupport'), ('FUNI-MIB', 'funiIfConfIlmiVpi'), ('FUNI-MIB', 'funiIfConfIlmiVci'), ('FUNI-MIB', 'funiIfConfOamSupport'))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funi_if_conf_min_group = funiIfConfMinGroup.setStatus('current')
funi_if_stats_min_group = object_group((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 2)).setObjects(('FUNI-MIB', 'funiIfEstablishedPvccs'), ('FUNI-MIB', 'funiIfEstablishedSvccs'), ('FUNI-MIB', 'funiIfRxAbortedFrames'), ('FUNI-MIB', 'funiIfRxTooShortFrames'), ('FUNI-MIB', 'funiIfRxTooLongFrames'), ('FUNI-MIB', 'funiIfRxFcsErrFrames'), ('FUNI-MIB', 'funiIfRxUnknownFaFrames'), ('FUNI-MIB', 'funiIfRxDiscardedFrames'), ('FUNI-MIB', 'funiIfTxTooLongFrames'), ('FUNI-MIB', 'funiIfTxLenErrFrames'), ('FUNI-MIB', 'funiIfTxCrcErrFrames'), ('FUNI-MIB', 'funiIfTxPartialFrames'), ('FUNI-MIB', 'funiIfTxTimeOutFrames'), ('FUNI-MIB', 'funiIfTxDiscardedFrames'))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funi_if_stats_min_group = funiIfStatsMinGroup.setStatus('current')
funi_vcl_stats_optional_group = object_group((1, 3, 6, 1, 4, 1, 353, 5, 6, 1, 2, 2, 3)).setObjects(('FUNI-MIB', 'funiVclRxClp0Frames'), ('FUNI-MIB', 'funiVclRxTotalFrames'), ('FUNI-MIB', 'funiVclTxClp0Frames'), ('FUNI-MIB', 'funiVclTxTotalFrames'), ('FUNI-MIB', 'funiVclRxClp0Octets'), ('FUNI-MIB', 'funiVclRxTotalOctets'), ('FUNI-MIB', 'funiVclTxClp0Octets'), ('FUNI-MIB', 'funiVclTxTotalOctets'), ('FUNI-MIB', 'funiVclRxErrors'), ('FUNI-MIB', 'funiVclTxErrors'), ('FUNI-MIB', 'funiVclRxOamFrames'), ('FUNI-MIB', 'funiVclTxOamFrames'))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
funi_vcl_stats_optional_group = funiVclStatsOptionalGroup.setStatus('current')
mibBuilder.exportSymbols('FUNI-MIB', funiVclRxErrors=funiVclRxErrors, funiVclTxClp0Octets=funiVclTxClp0Octets, funiVclTxClp0Frames=funiVclTxClp0Frames, funiIfConfIlmiSupport=funiIfConfIlmiSupport, funiIfConfMode=funiIfConfMode, FuniValidVpi=FuniValidVpi, funiIfEstablishedPvccs=funiIfEstablishedPvccs, funiIfTxCrcErrFrames=funiIfTxCrcErrFrames, funiIfTxTimeOutFrames=funiIfTxTimeOutFrames, funiIfTxTooLongFrames=funiIfTxTooLongFrames, funiVclRxTotalOctets=funiVclRxTotalOctets, funiIfStatsMinGroup=funiIfStatsMinGroup, funiIfConfTable=funiIfConfTable, funiIfStatsEntry=funiIfStatsEntry, funiVclFaVpi=funiVclFaVpi, funiIfConfSigVpi=funiIfConfSigVpi, funiIfConfFcsBits=funiIfConfFcsBits, funiIfRxTooLongFrames=funiIfRxTooLongFrames, funiIfRxDiscardedFrames=funiIfRxDiscardedFrames, atmfFuniMIB=atmfFuniMIB, funiVclTxErrors=funiVclTxErrors, atmfFuni=atmfFuni, funiIfRxUnknownFaFrames=funiIfRxUnknownFaFrames, funiIfTxPartialFrames=funiIfTxPartialFrames, funiIfConfIlmiVci=funiIfConfIlmiVci, funiIfTxLenErrFrames=funiIfTxLenErrFrames, funiVclRxTotalFrames=funiVclRxTotalFrames, funiIfConfMinGroup=funiIfConfMinGroup, funiVclStatsTable=funiVclStatsTable, FuniValidVci=FuniValidVci, funiVclRxOamFrames=funiVclRxOamFrames, funiIfConfIlmiVpi=funiIfConfIlmiVpi, funiVclStatsEntry=funiVclStatsEntry, funiIfConfSigSupport=funiIfConfSigSupport, funiIfRxFcsErrFrames=funiIfRxFcsErrFrames, funiVclTxTotalOctets=funiVclTxTotalOctets, funiIfStatsTable=funiIfStatsTable, funiVclStatsOptionalGroup=funiVclStatsOptionalGroup, funiVclRxClp0Frames=funiVclRxClp0Frames, funiVclTxOamFrames=funiVclTxOamFrames, funiMIBGroups=funiMIBGroups, atmForum=atmForum, funiMIBCompliance=funiMIBCompliance, funiIfConfSigVci=funiIfConfSigVci, PYSNMP_MODULE_ID=atmfFuniMIB, funiIfConfEntry=funiIfConfEntry, funiIfRxTooShortFrames=funiIfRxTooShortFrames, funiIfEstablishedSvccs=funiIfEstablishedSvccs, funiMIBCompliances=funiMIBCompliances, atmForumNetworkManagement=atmForumNetworkManagement, funiVclTxTotalFrames=funiVclTxTotalFrames, funiIfTxDiscardedFrames=funiIfTxDiscardedFrames, funiVclFaVci=funiVclFaVci, funiMIBConformance=funiMIBConformance, funiIfConfOamSupport=funiIfConfOamSupport, funiVclRxClp0Octets=funiVclRxClp0Octets, funiIfRxAbortedFrames=funiIfRxAbortedFrames, funiMIBObjects=funiMIBObjects)
|
x = 5
x |= 3
print(x)
|
x = 5
x |= 3
print(x)
|
## CUDA blocks are initialized here!
## Created by: Aditya Atluri
## Date: Mar 03 2014
def bx(blocks_dec, kernel):
if blocks_dec == False:
string = "int bx = blockIdx.x;\n"
kernel = kernel + string
blocks_dec = True
return kernel, blocks_dec
def by(blocks_dec, kernel):
if blocks_dec == False:
string = "int by = blockIdx.y;\n"
kernel = kernel + string
blocks_dec = True
return kernel, blocks_dec
def bz(blocks_dec, kernel):
if blocks_dec == False:
string = "int bz = blockIdx.z;\n"
kernel = kernel + string
blocks_dec = True
return kernel, blocks_dec
def blocks_decl(stmt, var_nam, var_val, blocks, type_vars):
equ = stmt.index('=')
kernel = ""
if var_nam.count('Bx') < 1 and stmt.count('Bx') > 0:
pos = stmt.index('Bx')
var_nam.append(stmt[pos])
kernel += "int Bx = gridDim.x;\n"
type_vars.append("int")
if var_nam.count('By') < 1 and stmt.count('By') > 0:
pos = stmt.index('By')
var_nam.append(stmt[pos])
kernel += "int By = gridDim.y;\n"
type_vars.append("int")
if var_nam.count('Bz') < 1 and stmt.count('Bz') > 0:
pos = stmt.index('Bz')
var_nam.append(stmt[pos])
kernel += "int Bz = gridDim.z;\n"
type_vars.append("int")
return var_nam, var_val, blocks, kernel, type_vars
|
def bx(blocks_dec, kernel):
if blocks_dec == False:
string = 'int bx = blockIdx.x;\n'
kernel = kernel + string
blocks_dec = True
return (kernel, blocks_dec)
def by(blocks_dec, kernel):
if blocks_dec == False:
string = 'int by = blockIdx.y;\n'
kernel = kernel + string
blocks_dec = True
return (kernel, blocks_dec)
def bz(blocks_dec, kernel):
if blocks_dec == False:
string = 'int bz = blockIdx.z;\n'
kernel = kernel + string
blocks_dec = True
return (kernel, blocks_dec)
def blocks_decl(stmt, var_nam, var_val, blocks, type_vars):
equ = stmt.index('=')
kernel = ''
if var_nam.count('Bx') < 1 and stmt.count('Bx') > 0:
pos = stmt.index('Bx')
var_nam.append(stmt[pos])
kernel += 'int Bx = gridDim.x;\n'
type_vars.append('int')
if var_nam.count('By') < 1 and stmt.count('By') > 0:
pos = stmt.index('By')
var_nam.append(stmt[pos])
kernel += 'int By = gridDim.y;\n'
type_vars.append('int')
if var_nam.count('Bz') < 1 and stmt.count('Bz') > 0:
pos = stmt.index('Bz')
var_nam.append(stmt[pos])
kernel += 'int Bz = gridDim.z;\n'
type_vars.append('int')
return (var_nam, var_val, blocks, kernel, type_vars)
|
def sample(name, custom_package):
native.android_binary(
name = name,
deps = [":sdk"],
srcs = native.glob(["samples/" + name + "/src/**/*.java"]),
custom_package = custom_package,
manifest = "samples/" + name + "/AndroidManifest.xml",
resource_files = native.glob(["samples/" + name + "/res/**/*"]),
)
|
def sample(name, custom_package):
native.android_binary(name=name, deps=[':sdk'], srcs=native.glob(['samples/' + name + '/src/**/*.java']), custom_package=custom_package, manifest='samples/' + name + '/AndroidManifest.xml', resource_files=native.glob(['samples/' + name + '/res/**/*']))
|
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