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"""Tests for ot.smooth model """
# Author: Remi Flamary <remi.flamary@unice.fr>
#
# License: MIT License
import warnings
import numpy as np
import ot
from ot.datasets import get_1D_gauss as gauss
import pytest
def test_smooth_ot_dual():
# test sinkhorn
n = 100
rng = np.random.RandomState(0)
x = rng.randn(n, 2)
u = ot.utils.unif(n)
M = ot.dist(x, x)
G = ot.smooth.smooth_ot_dual(u, u, M, 1, stopThr=1e-10)
# check constratints
np.testing.assert_allclose(
u, G.sum(1), atol=1e-05) # cf convergence sinkhorn
np.testing.assert_allclose(
u, G.sum(0), atol=1e-05) # cf convergence sinkhorn
G2 = ot.sinkhorn(u, u, M, 1, stopThr=1e-10)
np.testing.assert_allclose( G, G2 , atol=1e-05)
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