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-rwxr-xr-xtest/test_partial.py10
1 files changed, 5 insertions, 5 deletions
diff --git a/test/test_partial.py b/test/test_partial.py
index e07377b..33fc259 100755
--- a/test/test_partial.py
+++ b/test/test_partial.py
@@ -137,7 +137,7 @@ def test_partial_wasserstein():
def test_partial_gromov_wasserstein():
- np.random.seed(42)
+ rng = np.random.RandomState(seed=42)
n_samples = 20 # nb samples
n_noise = 10 # nb of samples (noise)
@@ -150,11 +150,11 @@ def test_partial_gromov_wasserstein():
mu_t = np.array([0, 0, 0])
cov_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
- xs = ot.datasets.make_2D_samples_gauss(n_samples, mu_s, cov_s)
- xs = np.concatenate((xs, ((np.random.rand(n_noise, 2) + 1) * 4)), axis=0)
+ xs = ot.datasets.make_2D_samples_gauss(n_samples, mu_s, cov_s, rng)
+ xs = np.concatenate((xs, ((rng.rand(n_noise, 2) + 1) * 4)), axis=0)
P = sp.linalg.sqrtm(cov_t)
- xt = np.random.randn(n_samples, 3).dot(P) + mu_t
- xt = np.concatenate((xt, ((np.random.rand(n_noise, 3) + 1) * 10)), axis=0)
+ xt = rng.randn(n_samples, 3).dot(P) + mu_t
+ xt = np.concatenate((xt, ((rng.rand(n_noise, 3) + 1) * 10)), axis=0)
xt2 = xs[::-1].copy()
C1 = ot.dist(xs, xs)