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<!DOCTYPE html>

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<title>ot.bregman._utils — POT Python Optimal Transport 0.9.7 documentation</title>

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<h1>Source code for ot.bregman._utils</h1><div class="highlight"><pre>

# -*- coding: utf-8 -*-

"""

Common tools of Bregman projections solvers for entropic regularized OT

"""

# Author: Remi Flamary <remi.flamary@unice.fr>

# Nicolas Courty <ncourty@irisa.fr>

#

# License: MIT License

from ..utils import list_to_array

from ..backend import get_backend

def geometricBar(weights, alldistribT):

"""return the weighted geometric mean of distributions"""

weights, alldistribT = list_to_array(weights, alldistribT)

nx = get_backend(weights, alldistribT)

assert len(weights) == alldistribT.shape[1]

return nx.exp(nx.dot(nx.log(alldistribT), weights.T))</div>

def geometricMean(alldistribT):

"""return the geometric mean of distributions"""

alldistribT = list_to_array(alldistribT)

nx = get_backend(alldistribT)

return nx.exp(nx.mean(nx.log(alldistribT), axis=1))</div>

def projR(gamma, p):

"""return the KL projection on the row constraints"""

gamma, p = list_to_array(gamma, p)

nx = get_backend(gamma, p)

return (gamma.T * p / nx.maximum(nx.sum(gamma, axis=1), 1e-10)).T</div>

def projC(gamma, q):

"""return the KL projection on the column constraints"""

gamma, q = list_to_array(gamma, q)

return gamma * q / nx.maximum(nx.sum(gamma, axis=0), 1e-10)</div>

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