66 lines
1.7 KiB
Python
66 lines
1.7 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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The total variation Norm
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"""
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def checkVectors(distrib_1,distrib_2):
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import numpy as np
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mu = np.asarray(distrib_1)
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nu = np.asarray(distrib_2)
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mu_sum = np.sum(mu)
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nu_sum = np.sum(nu)
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mu_chk = (mu >= 0)
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nu_chk = (nu >= 0)
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if mu.size != nu.size:
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print('vectors of diferent length')
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return False
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else:
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if (mu_sum != 1) or (nu_sum != 1):
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#print('one of the vectors is not a probability distribution')
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return False
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else:
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if (mu_chk.all() != True) or (nu_chk.all() != True):
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#print('one of the vectors is not a probability distribution')
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return False
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else:
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if mu.shape != nu.shape:
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return True
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def totalVariation1(distrib_1,distrib_2):
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import numpy as np
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if checkVectors(distrib_1,distrib_2) == False:
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mu = np.asarray(distrib_1)
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nu = np.asarray(distrib_2)
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return np.max(np.abs(mu - nu))
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else:
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print('Not possible to calculate measure of the vectors')
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def totalVariation2(distrib_1,distrib_2):
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import numpy as np
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if checkVectors(distrib_1,distrib_2) == True:
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mu = np.asarray(distrib_1)
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nu = np.asarray(distrib_2)
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temp = []
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for x in range(0,nu.size):
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temp.append(np.abs(mu[x] - nu[x]))
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temp = np.asarray(temp)
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return (0.5)*temp.sum()
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else:
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print('Not possible to calculate measure of the vectors')
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