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Implementation of the Bhattacharyya distance in Python
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# bhattacharyya test | |
import numpy | |
import math | |
h1 = [ 1, 2, 3, 4, 5, 6, 7, 8 ]; | |
h2 = [ 6, 5, 4, 3, 2, 1, 0, 0 ]; | |
h3 = [ 8, 7, 6, 5, 4, 3, 2, 1 ]; | |
h4 = [ 1, 2, 3, 4, 4, 3, 2, 1 ]; | |
h5 = [ 8, 8, 8, 8, 8, 8, 8, 8 ]; | |
h = [ h1, h2, h3, h4, h5 ]; | |
def mean( hist ): | |
mean = 0.0; | |
for i in hist: | |
mean += i; | |
mean/= len(hist); | |
return mean; | |
def bhatta ( hist1, hist2): | |
# calculate mean of hist1 | |
h1_ = mean(hist1); | |
# calculate mean of hist2 | |
h2_ = mean(hist2); | |
# calculate score | |
score = 0; | |
for i in range(8): | |
score += math.sqrt( hist1[i] * hist2[i] ); | |
# print h1_,h2_,score; | |
score = math.sqrt( 1 - ( 1 / math.sqrt(h1_*h2_*8*8) ) * score ); | |
return score; | |
# generate and output scores | |
scores = []; | |
for i in range(len(h)): | |
score = []; | |
for j in range(len(h)): | |
score.append( bhatta(h[i],h[j]) ); | |
scores.append(score); | |
for i in scores: | |
print i |
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