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HighLevel.py
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HighLevel.py
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import Networks as ntk
import numpy as np
import os
import Transfer as tp
from Node import *
from DNA import *
from Socialiser import *
from PetriDish import *
from Networks import *
import numpy as np
def simulateNetworksEasy(folderPath):
explorationProbabilityV = np.linspace(0.1,0.5,3)
connectionPercentageWithMatchedNodesV = np.arange(5,30,3)
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in range(1, 5):
os.mkdir(folderPath + '\\' +'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PPV'+ str(popularityPreferenceIntensity))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=True, additionalFeatureLen=2,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=[3, 2, 1])
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.3)
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.5)
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.7)
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\' +'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PPV'+ str(popularityPreferenceIntensity)+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasy2(folderPath):
explorationProbabilityV = np.linspace(0.01,0.1,2)
popularityPreferenceIntensityV = np.linspace(0.5,1.5,2)
connectionPercentageWithMatchedNodesV = np.linspace(0.5,2,2)
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=2)
len3 = np.random.uniform(low=0.3, high=0.7, size=2)
len4 = np.random.uniform(low=0.0, high=0.3, size=2)
for i in range(0, 2):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PP'+ str(popularityPreferenceIntensity)+'mpi'+str(mutualPreferenceIntensity[0])+str(mutualPreferenceIntensity[1])+str(mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.3)
graphTemp1.socialise()
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.7)
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PP'+ str(popularityPreferenceIntensity)+'mpi'+str(mutualPreferenceIntensity[0])+str(mutualPreferenceIntensity[1])+str(mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasy3(folderPath):
explorationProbabilityV = np.linspace(0.1,1,10)
popularityPreferenceIntensityV = np.linspace(1,10,10)
connectionPercentageWithMatchedNodesV = np.linspace(1,20,10)
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=3, high=5, size=10)
len3 = np.random.uniform(low=1, high=3, size=10)
len4 = np.random.uniform(low=0.01, high=1, size=10)
for i in range(0, 10):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PP'+ str(popularityPreferenceIntensity)+'mpi'+str(mutualPreferenceIntensity[0])+str(mutualPreferenceIntensity[1])+str(mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.3)
graphTemp1.socialise()
graphTemp1.mutateDNAandSocialise(mutationIntensity=0.7)
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str(explorationProbability)+ 'CPN'+str(connectionPercentageWithMatchedNodes)+'PP'+ str(popularityPreferenceIntensity)+'mpi'+str(mutualPreferenceIntensity[0])+str(mutualPreferenceIntensity[1])+str(mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasyExplorationProbabilityTest(folderPath):
explorationProbabilityV = np.linspace(0.01,1,300)
popularityPreferenceIntensityV = np.linspace(0.5,1.5,1)
connectionPercentageWithMatchedNodesV = np.linspace(0.5,2,1)
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=1)
len3 = np.random.uniform(low=0.3, high=0.7, size=1)
len4 = np.random.uniform(low=0.0, high=0.3, size=1)
for i in range(0, 1):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasyConnectionPercentageWithMatchedNodesTest(folderPath):
explorationProbabilityV = [0.5]
popularityPreferenceIntensityV = np.linspace(0.5,1.5,1)
connectionPercentageWithMatchedNodesV = np.linspace(1,30,300)
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=1)
len3 = np.random.uniform(low=0.3, high=0.7, size=1)
len4 = np.random.uniform(low=0.0, high=0.3, size=1)
for i in range(0, 1):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f"%connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f"%popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f"%mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f"%explorationProbability)+ 'CPN'+str("%6.3f"%connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f"%mutualPreferenceIntensity[1])+str("%6.3f"%mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasypopularityPreferenceIntensityTest1(folderPath):
explorationProbabilityV = [0.5]
popularityPreferenceIntensityV = np.linspace(0.1,1,300)
connectionPercentageWithMatchedNodesV = [10.00]
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=1)
len3 = np.random.uniform(low=0.3, high=0.7, size=1)
len4 = np.random.uniform(low=0.0, high=0.3, size=1)
for i in range(0, 1):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasypopularityPreferenceIntensityTest2(folderPath):
explorationProbabilityV = [0.5]
popularityPreferenceIntensityV = np.linspace(1,30,300)
connectionPercentageWithMatchedNodesV = [10.00]
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=1)
len3 = np.random.uniform(low=0.3, high=0.7, size=1)
len4 = np.random.uniform(low=0.0, high=0.3, size=1)
for i in range(0, 1):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])
def simulateNetworksEasymutualPreferenceIntensityTest1(folderPath):
explorationProbabilityV = [0.5]
popularityPreferenceIntensityV = [1]
connectionPercentageWithMatchedNodesV = [10.00]
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=0.7, high=1.0, size=300)
len3 = np.random.uniform(low=0.3, high=0.7, size=300)
len4 = np.random.uniform(low=0.0, high=0.3, size=300)
for i in range(0, 300):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2])+'\\')
def simulateNetworksEasymutualPreferenceIntensityTest2(folderPath):
explorationProbabilityV = [0.5]
popularityPreferenceIntensityV = [1]
connectionPercentageWithMatchedNodesV = [10.00]
mutualPreferenceIntensityV = []
len2 = np.random.uniform(low=20, high=30, size=300)
len3 = np.random.uniform(low=10, high=20, size=300)
len4 = np.random.uniform(low=1, high=10, size=300)
for i in range(0, 300):
mutualPreferenceIntensityV.append([len2[i], len3[i], len4[i]])
# popularityPreferenceIntensityV = np.arange(1,10,1)
# popularityPreferenceIntensityV = popularityPreferenceIntensityV.tolist()
for explorationProbability in explorationProbabilityV:
for connectionPercentageWithMatchedNodes in connectionPercentageWithMatchedNodesV:
for popularityPreferenceIntensity in popularityPreferenceIntensityV:
for mutualPreferenceIntensity in mutualPreferenceIntensityV:
os.mkdir(folderPath + '\\' +'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+ str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2]))
graphTemp1 = RandomSocialGraphAdvanced(labelSplit=[100, 200, 300], connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
explorationProbability=explorationProbability, addTraidtionalFeatures=False, additionalFeatureLen=3,
npDistFunc=['np.random.randint(18, high=80)', 'np.random.binomial(2, 0.5)'],
popularityPreferenceIntensity=popularityPreferenceIntensity, mutualPreferenceIntensity=mutualPreferenceIntensity)
graphTemp1.socialise()
graphTemp1.socialise()
tp.WriteToFile(graphTemp1).easySaveEverything(folderPath + '\\'+'EP'+ str("%6.5f" % explorationProbability)+ 'CPN'+str("%6.3f" % connectionPercentageWithMatchedNodes)+'PP'+ str("%6.3f" % popularityPreferenceIntensity)+'mpi'+str("%6.3f" % mutualPreferenceIntensity[0])+str("%6.3f" % mutualPreferenceIntensity[1])+str("%6.3f" % mutualPreferenceIntensity[2])+'\\')
# graphTemp2 = ntk.RandomSocialGraphAdvanced(labelSplit=[500, 1000, 1500],
# connectionPercentageWithMatchedNodes=connectionPercentageWithMatchedNodes,
# explorationProbability=0.3, addTraidtionalFeatures=False,
# additionalFeatureLen=5,
# npDistFunc=['np.random.randint(18, high=80)',
# 'np.random.binomial(2, 0.5)'],
# popularityPreferenceIntensity=1,
# mutualPreferenceIntensity=[0.9, 0.6, 0.3])