def test_basic_spsolve_matrix():
ps.remove_stored_factorization()
ps.free_memory()
A, b = create_test_A_b_rand(matrix=True)
xpp = spsolve(A, b)
xscipy = scipyspsolve(A, b)
np.testing.assert_array_almost_equal(xpp, xscipy)
def test_input_b_shape():
A, b = create_test_A_b_rand()
x_array = ps.solve(A,b)
assert x_array.shape == b.shape
x_vector = ps.solve(A, b.squeeze())
assert x_vector.shape == b.squeeze().shape
np.testing.assert_array_equal(x_array.squeeze(), x_vector)
def test_input_A_empty_row():
A, b = create_test_A_b_rand(25, 0.7)
A = np.array(A.todense())
A[0,:] = 0
A[1, 0] = 1
Asp = sp.csr_matrix(A)
with pytest.raises(ValueError):
basic_solve(Asp,b)
def test_spsolve_csc_matrix():
ps.remove_stored_factorization()
ps.free_memory()
A, b = create_test_A_b_rand()
x_csc = spsolve(A.tocsc(), b)
assert sp.isspmatrix_csr(ps.factorized_A)
x_csr = spsolve(A, b)
np.testing.assert_array_equal(x_csr, x_csc)
def test_basic_factorized():
ps.remove_stored_factorization()
ps.free_memory()
A, b = create_test_A_b_rand()
ppfact = factorized(A)
xpp = ppfact(b)
scipyfact = scipyfactorized(A)
xscipy = scipyfact(b)
np.testing.assert_array_almost_equal(xpp, xscipy)
def test_factorized_csc_matrix():
ps.remove_stored_factorization()
ps.free_memory()
A, b = create_test_A_b_rand()
Afact_csr = factorized(A)
Afact_csc = factorized(A.tocsc())
assert sp.isspmatrix_csr(Afact_csc.args[0])
x1 = Afact_csr(b)
x2 = Afact_csc(b)
np.testing.assert_array_equal(x1, x2)
def test_input_b_dtypes():
A, b = create_test_A_b_rand()
for dt in [np.float16, np.float32, np.int16, np.int32, np.int64]:
bdt = b.astype(dt)
with pytest.warns(PyPardisoWarning):
basic_solve(A, bdt)
for dt in [np.complex64, np.complex128, np.complex128, np.uint16, np.uint32, np.uint64]:
bdt = b.astype(dt)
with pytest.raises(TypeError):
basic_solve(A, bdt)
def test_input_A_non_sparse():
A, b = create_test_A_b_rand(10,0.9)
A = A.todense()
assert not sp.issparse(A)
with pytest.raises(TypeError):
ps.solve(A,b)
def test_input_A_dtypes():
A, b = create_test_A_b_rand(10,0.5)
for d in [np.float16, np.float32, np.int16, np.int32, np.int64, np.complex64,
np.complex128, np.complex128, np.uint16, np.uint32, np.uint64]:
with pytest.raises(TypeError):
ps.solve(A.astype(d), b)
def test_input_A_other_sparse():
A, b = create_test_A_b_rand(50)
for f in ['coo', 'lil', 'dia']:
Aother = A.asformat(f)
with pytest.raises(TypeError):
ps.solve(Aother,b)
def test_bvector_smoketest():
A, b = create_test_A_b_rand()
basic_solve(A, b)
def test_input_A_nonsquare():
A, b = create_test_A_b_rand()
A = sp.csr_matrix(np.concatenate([A.todense(), np.ones((A.shape[0], 1))], axis=1))
with pytest.raises(ValueError):
basic_solve(A,b)
def test_bmatrix_smoketest():
A, b = create_test_A_b_rand(matrix=True)
basic_solve(A, b)
def test_input_b_wrong_shape():
A, b = create_test_A_b_rand()
b = np.append(b, 1)
with pytest.raises(ValueError):
basic_solve(A,b)
def test_input_b_fortran_order():
A, b = create_test_A_b_rand(matrix=True)
x = ps.solve(A,b)
xfort = ps.solve(A, np.asfortranarray(b))
np.testing.assert_array_equal(x, xfort)
def test_input_A_csc():
A, b = create_test_A_b_rand()
x_csr = ps.solve(A,b)
Acsc = A.copy().asformat('csc')
x_csc = ps.solve(Acsc, b)
np.testing.assert_array_almost_equal(x_csr, x_csc)
def test_input_b_sparse():
A, b = create_test_A_b_rand()
bsparse = sp.csr_matrix(b)
with pytest.warns(SparseEfficiencyWarning):
x = ps.solve(A, bsparse)
np.testing.assert_array_almost_equal(A*x, b)
