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CalculateNMI.py
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CalculateNMI.py
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# coding: utf-8
# In[1]:
import numpy as np
import math
# In[11]:
def NMI(A,B):
# len(A) should be equal to len(B)
total = len(A)
A_ids = set(A)
B_ids = set(B)
# Mutual information
MI = 0
eps = 1.4e-45
for idA in A_ids:
for idB in B_ids:
idAOccur = np.where(A==idA)
idBOccur = np.where(B==idB)
idABOccur = np.intersect1d(idAOccur,idBOccur)
px = 1.0*len(idAOccur[0])/total
py = 1.0*len(idBOccur[0])/total
pxy = 1.0*len(idABOccur)/total
MI = MI + pxy*math.log(pxy/(px*py)+eps,2)
# Normalized Mutual information
Hx = 0
for idA in A_ids:
idAOccurCount = 1.0*len(np.where(A==idA)[0])
Hx = Hx - (idAOccurCount/total)*math.log(idAOccurCount/total+eps,2)
Hy = 0
for idB in B_ids:
idBOccurCount = 1.0*len(np.where(B==idB)[0])
Hy = Hy - (idBOccurCount/total)*math.log(idBOccurCount/total+eps,2)
MIhat = 2.0*MI/(Hx+Hy)
return MIhat
# In[18]:
#A = np.array([1,1,1,2,1,1,2,2,3,3])
#B = np.array([1,1,1,0,1,1,0,0,2,2])
A = np.load('ring_story_label.npy')
B = np.load('ap_labels.npy')
#B = np.load('spectral_event_labels.npy')
#B_ = np.load('spectral_story_labels.npy')
#B = np.load('dbscan_labels.npy')
C = np.load('ring_event_label.npy')
# In[19]:
print('Story NMI Calculating Result Is: ', NMI(A, B))
print('Event NMI Calculating Result Is: ', NMI(C, B))
# In[ ]: