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author | Rémi Flamary <remi.flamary@gmail.com> | 2017-07-24 16:39:19 +0200 |
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committer | Rémi Flamary <remi.flamary@gmail.com> | 2017-07-24 16:39:19 +0200 |
commit | a8d7301c132a225b5e4d78cae64683a5e08eae7f (patch) | |
tree | 6782b3b4369bcbe0c652a918ee153e996ebc528e | |
parent | 5aad08aff3e1a171ef9263af4488d175139085a0 (diff) |
add test plot and dataset
-rw-r--r-- | test/test_dr.py | 11 |
1 files changed, 3 insertions, 8 deletions
diff --git a/test/test_dr.py b/test/test_dr.py index 24ccaa1..3da7705 100644 --- a/test/test_dr.py +++ b/test/test_dr.py @@ -12,22 +12,17 @@ except ImportError: @pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)") def test_fda(): - n = 100 # nb samples in source and target datasets - nz = 0.2 + n = 90 # 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) + xs, ys = ot.datasets.get_data_classif('gaussrot', n) nbnoise = 8 xs = np.hstack((xs, np.random.randn(n, nbnoise))) - p = 2 + p = 1 Pfda, projfda = ot.dr.fda(xs, ys, p) |