def test_apply_dimensionality_reduction(self):
test_cases =[(self.x, self.us)]
red = Svd(2)
for in_mat, expected_us_mat in test_cases:
op = DimensionalityReductionOperation(red)
tmp_mat = in_mat.copy()
out_us_mat = op.apply(DenseMatrix(in_mat)).mat
np.testing.assert_array_almost_equal(expected_us_mat, out_us_mat, 2)
np.testing.assert_array_equal(in_mat, tmp_mat)
self.assertRaises(IllegalStateError, op.apply, DenseMatrix(in_mat))
self.assertRaises(IllegalStateError, op.apply, SparseMatrix(in_mat))
def test_project_dimensionality_reduction_nmf(self):
test_cases = [self.xnmf]
red = Nmf(2)
for in_mat in test_cases:
d_in_mat = DenseMatrix(in_mat)
op = DimensionalityReductionOperation(red)
tmp_mat = in_mat.copy()
self.assertRaises(IllegalStateError, op.project, d_in_mat)
out_core_mat = op.apply(d_in_mat).mat
out_proj_mat = op.project(d_in_mat).mat
np.testing.assert_array_almost_equal(out_proj_mat, out_core_mat, 5)
np.testing.assert_array_equal(in_mat, tmp_mat)
self.assertRaises(IllegalStateError, op.apply, d_in_mat)
out_proj_mat2 = op.project(d_in_mat).mat
np.testing.assert_array_almost_equal(out_proj_mat2, out_core_mat, 5)
def create_operation(self):
return DimensionalityReductionOperation(self)
