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"""Tests for module plot for visualization """
# Author: Remi Flamary <remi.flamary@unice.fr>
#
# License: MIT License
import numpy as np
import pytest
try: # test if matplotlib is installed
import matplotlib
matplotlib.use('Agg')
nogo = False
except ImportError:
nogo = True
@pytest.mark.skipif(nogo, reason="Matplotlib not installed")
def test_plot1D_mat():
import ot
import ot.plot
n_bins = 100 # nb bins
# bin positions
x = np.arange(n_bins, dtype=np.float64)
# Gaussian distributions
a = ot.datasets.make_1D_gauss(n_bins, m=20, s=5) # m= mean, s= std
b = ot.datasets.make_1D_gauss(n_bins, m=60, s=10)
# loss matrix
M = ot.dist(x.reshape((n_bins, 1)), x.reshape((n_bins, 1)))
M /= M.max()
ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
@pytest.mark.skipif(nogo, reason="Matplotlib not installed")
def test_plot2D_samples_mat():
import ot
import ot.plot
n_bins = 50 # nb samples
mu_s = np.array([0, 0])
cov_s = np.array([[1, 0], [0, 1]])
mu_t = np.array([4, 4])
cov_t = np.array([[1, -.8], [-.8, 1]])
xs = ot.datasets.make_2D_samples_gauss(n_bins, mu_s, cov_s)
xt = ot.datasets.make_2D_samples_gauss(n_bins, mu_t, cov_t)
G = 1.0 * (np.random.rand(n_bins, n_bins) < 0.01)
ot.plot.plot2D_samples_mat(xs, xt, G, thr=1e-5)
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