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VictorSaenger/metric_permutation.py

Created October 15, 2019 11:51
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metric_permutation.py
#Copy pooled distribution:
pS = copy.copy(pV)
#Initialize permutation:
pD = []
#Define p (number of permutations):
p=1000
# Permutation loop:
for i in range(0,p):
# Shuffle the data:
random.shuffle(pS)
# Compute permuted absolute difference of your two sampled distributions and store it in pD:
pD.append(np.abs(np.average(pS[0:int(len(pS)/2)]) - np.average(pS[int(len(pS)/2):])))
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