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"""Tests for ot.smooth model """
# Author: Remi Flamary <remi.flamary@unice.fr>
#
# License: MIT License
import numpy as np
import ot
def test_smooth_ot_dual():
# get data
n = 100
rng = np.random.RandomState(0)
x = rng.randn(n, 2)
u = ot.utils.unif(n)
M = ot.dist(x, x)
Gl2 = ot.smooth.smooth_ot_dual(u, u, M, 1, reg_type='l2', stopThr=1e-10)
# check constratints
np.testing.assert_allclose(
u, Gl2.sum(1), atol=1e-05) # cf convergence sinkhorn
np.testing.assert_allclose(
u, Gl2.sum(0), atol=1e-05) # cf convergence sinkhorn
# kl regyularisation
G = ot.smooth.smooth_ot_dual(u, u, M, 1, reg_type='kl', 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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