diff options
Diffstat (limited to 'test/test_dr.py')
| -rw-r--r-- | test/test_dr.py | 25 |
1 files changed, 10 insertions, 15 deletions
diff --git a/test/test_dr.py b/test/test_dr.py index 3faba48..e3d1e6b 100644 --- a/test/test_dr.py +++ b/test/test_dr.py @@ -13,15 +13,15 @@ except ImportError: @pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)") def test_fda(): - n = 90 # nb samples in source and target datasets + n_samples = 90 # nb samples in source and target datasets np.random.seed(0) - # generate circle dataset - xs, ys = ot.datasets.get_data_classif('gaussrot', n) + # generate gaussian dataset + xs, ys = ot.datasets.get_data_classif('gaussrot', n_samples) - nbnoise = 8 + n_features_noise = 8 - xs = np.hstack((xs, np.random.randn(n, nbnoise))) + xs = np.hstack((xs, np.random.randn(n_samples, n_features_noise))) p = 1 @@ -35,20 +35,15 @@ def test_fda(): @pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)") def test_wda(): - n = 100 # nb samples in source and target datasets - nz = 0.2 + n_samples = 100 # nb samples in source and target datasets np.random.seed(0) - # generate circle dataset - t = np.random.rand(n) * 2 * np.pi - ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1 - xs = np.concatenate( - (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1) - xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2) + # generate gaussian dataset + xs, ys = ot.datasets.get_data_classif('gaussrot', n_samples) - nbnoise = 8 + n_features_noise = 8 - xs = np.hstack((xs, np.random.randn(n, nbnoise))) + xs = np.hstack((xs, np.random.randn(n_samples, n_features_noise))) p = 2 |