def test_project_weighting_operation(self):
test_cases = [(self.m1, self.m3,
np.array([[0.69314718,0,0]])),
(self.m2, self.m4, np.array([[0]]))]
w = PpmiWeighting()
for (core_mat, per_mat, expected_mat) in test_cases:
op = ScalingOperation(w)
tmp_mat = per_mat.copy()
self.assertRaises(IllegalStateError, op.project,
DenseMatrix(per_mat))
op.apply(DenseMatrix(core_mat))
out_mat = op.project(DenseMatrix(per_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
np.testing.assert_array_equal(per_mat, tmp_mat)
out_mat = op.project(DenseMatrix(per_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
def test_apply_weighting_operation(self):
test_cases = [(self.m1, np.array([[0,0,0]])),
(self.m2, np.array([[0]]))]
w = PpmiWeighting()
for in_mat, expected_mat in test_cases:
op = ScalingOperation(w)
tmp_mat = in_mat.copy()
out_mat = op.apply(DenseMatrix(in_mat)).mat
np.testing.assert_array_almost_equal(expected_mat, out_mat, 7)
np.testing.assert_array_equal(in_mat, tmp_mat)
self.assertRaises(IllegalStateError, op.apply, DenseMatrix(in_mat))