def test_sdml_converges_if_psd(self):
"""Tests that sdml converges on a simple problem where we know the
pseudo-covariance matrix is PSD"""
pairs = np.array([[[-10., 0.], [10., 0.]], [[0., -55.], [0., -60]]])
y = [1, -1]
sdml = SDML(use_cov=True, sparsity_param=0.01, balance_param=0.5)
sdml.fit(pairs, y)
assert np.isfinite(sdml.get_mahalanobis_matrix()).all()
def test_sdml_converges_if_psd(self): """Tests that sdml converges on a simple problem where we know the pseudo-covariance matrix is PSD""" pairs = np.array([[[-10., 0.], [10., 0.]], [[0., -55.], [0., -60]]]) y = [1, -1] sdml = SDML(use_cov=True, sparsity_param=0.01, balance_param=0.5) sdml.fit(pairs, y) assert np.isfinite(sdml.get_mahalanobis_matrix()).all()
