diff options
Diffstat (limited to 'numpy/linalg/tests/test_linalg.py')
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 84 |
1 files changed, 67 insertions, 17 deletions
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 173e81e9c..dae4ef61e 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -1,8 +1,6 @@ """ Test functions for linalg module """ -from __future__ import division, absolute_import, print_function - import os import sys import itertools @@ -20,8 +18,9 @@ from numpy.linalg.linalg import _multi_dot_matrix_chain_order from numpy.testing import ( assert_, assert_equal, assert_raises, assert_array_equal, assert_almost_equal, assert_allclose, suppress_warnings, - assert_raises_regex, + assert_raises_regex, HAS_LAPACK64, ) +from numpy.testing._private.utils import requires_memory def consistent_subclass(out, in_): @@ -67,7 +66,7 @@ all_tags = { } -class LinalgCase(object): +class LinalgCase: def __init__(self, name, a, b, tags=set()): """ A bundle of arguments to be passed to a test case, with an identifying @@ -332,7 +331,7 @@ CASES += _make_strided_cases() # # Test different routines against the above cases # -class LinalgTestCase(object): +class LinalgTestCase: TEST_CASES = CASES def check_cases(self, require=set(), exclude=set()): @@ -633,7 +632,7 @@ class TestEig(EigCases): assert_(isinstance(a, np.ndarray)) -class SVDBaseTests(object): +class SVDBaseTests: hermitian = False @pytest.mark.parametrize('dtype', [single, double, csingle, cdouble]) @@ -681,6 +680,14 @@ class SVDHermitianCases(HermitianTestCase, HermitianGeneralizedTestCase): assert_allclose(a, dot_generalized(np.asarray(u) * np.asarray(s)[..., None, :], np.asarray(vt)), rtol=get_rtol(u.dtype)) + def hermitian(mat): + axes = list(range(mat.ndim)) + axes[-1], axes[-2] = axes[-2], axes[-1] + return np.conj(np.transpose(mat, axes=axes)) + + assert_almost_equal(np.matmul(u, hermitian(u)), np.broadcast_to(np.eye(u.shape[-1]), u.shape)) + assert_almost_equal(np.matmul(vt, hermitian(vt)), np.broadcast_to(np.eye(vt.shape[-1]), vt.shape)) + assert_equal(np.sort(s)[..., ::-1], s) assert_(consistent_subclass(u, a)) assert_(consistent_subclass(vt, a)) @@ -975,7 +982,7 @@ class TestLstsq(LstsqCases): @pytest.mark.parametrize('dt', [np.dtype(c) for c in '?bBhHiIqQefdgFDGO']) -class TestMatrixPower(object): +class TestMatrixPower: rshft_0 = np.eye(4) rshft_1 = rshft_0[[3, 0, 1, 2]] @@ -1075,7 +1082,7 @@ class TestEigvalshCases(HermitianTestCase, HermitianGeneralizedTestCase): assert_allclose(ev2, evalues, rtol=get_rtol(ev.dtype)) -class TestEigvalsh(object): +class TestEigvalsh: @pytest.mark.parametrize('dtype', [single, double, csingle, cdouble]) def test_types(self, dtype): x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype) @@ -1151,7 +1158,7 @@ class TestEighCases(HermitianTestCase, HermitianGeneralizedTestCase): rtol=get_rtol(ev.dtype), err_msg=repr(a)) -class TestEigh(object): +class TestEigh: @pytest.mark.parametrize('dtype', [single, double, csingle, cdouble]) def test_types(self, dtype): x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype) @@ -1210,7 +1217,7 @@ class TestEigh(object): assert_(isinstance(a, np.ndarray)) -class _TestNormBase(object): +class _TestNormBase: dt = None dec = None @@ -1473,11 +1480,12 @@ class _TestNorm2D(_TestNormBase): # Using `axis=<integer>` or passing in a 1-D array implies vector # norms are being computed, so also using `ord='fro'` - # or `ord='nuc'` raises a ValueError. + # or `ord='nuc'` or any other string raises a ValueError. assert_raises(ValueError, norm, A, 'fro', 0) assert_raises(ValueError, norm, A, 'nuc', 0) assert_raises(ValueError, norm, [3, 4], 'fro', None) assert_raises(ValueError, norm, [3, 4], 'nuc', None) + assert_raises(ValueError, norm, [3, 4], 'test', None) # Similarly, norm should raise an exception when ord is any finite # number other than 1, 2, -1 or -2 when computing matrix norms. @@ -1496,7 +1504,7 @@ class _TestNorm(_TestNorm2D, _TestNormGeneral): pass -class TestNorm_NonSystematic(object): +class TestNorm_NonSystematic: def test_longdouble_norm(self): # Non-regression test: p-norm of longdouble would previously raise @@ -1551,7 +1559,7 @@ class TestNormInt64(_TestNorm, _TestNormInt64Base): pass -class TestMatrixRank(object): +class TestMatrixRank: def test_matrix_rank(self): # Full rank matrix @@ -1600,7 +1608,7 @@ def test_reduced_rank(): assert_equal(matrix_rank(X), 8) -class TestQR(object): +class TestQR: # Define the array class here, so run this on matrices elsewhere. array = np.array @@ -1700,7 +1708,7 @@ class TestQR(object): self.check_qr(m2.T) -class TestCholesky(object): +class TestCholesky: # TODO: are there no other tests for cholesky? def test_basic_property(self): @@ -1828,6 +1836,7 @@ def test_xerbla_override(): pytest.skip('Numpy xerbla not linked in.') +@pytest.mark.slow def test_sdot_bug_8577(): # Regression test that loading certain other libraries does not # result to wrong results in float32 linear algebra. @@ -1862,7 +1871,7 @@ def test_sdot_bug_8577(): subprocess.check_call([sys.executable, "-c", code]) -class TestMultiDot(object): +class TestMultiDot: def test_basic_function_with_three_arguments(self): # multi_dot with three arguments uses a fast hand coded algorithm to @@ -1956,7 +1965,7 @@ class TestMultiDot(object): assert_raises(ValueError, multi_dot, [np.random.random((3, 3))]) -class TestTensorinv(object): +class TestTensorinv: @pytest.mark.parametrize("arr, ind", [ (np.ones((4, 6, 8, 2)), 2), @@ -2002,3 +2011,44 @@ def test_unsupported_commontype(): arr = np.array([[1, -2], [2, 5]], dtype='float16') with assert_raises_regex(TypeError, "unsupported in linalg"): linalg.cholesky(arr) + + +@pytest.mark.slow +@pytest.mark.xfail(not HAS_LAPACK64, run=False, + reason="Numpy not compiled with 64-bit BLAS/LAPACK") +@requires_memory(free_bytes=16e9) +def test_blas64_dot(): + n = 2**32 + a = np.zeros([1, n], dtype=np.float32) + b = np.ones([1, 1], dtype=np.float32) + a[0,-1] = 1 + c = np.dot(b, a) + assert_equal(c[0,-1], 1) + + +@pytest.mark.xfail(not HAS_LAPACK64, + reason="Numpy not compiled with 64-bit BLAS/LAPACK") +def test_blas64_geqrf_lwork_smoketest(): + # Smoke test LAPACK geqrf lwork call with 64-bit integers + dtype = np.float64 + lapack_routine = np.linalg.lapack_lite.dgeqrf + + m = 2**32 + 1 + n = 2**32 + 1 + lda = m + + # Dummy arrays, not referenced by the lapack routine, so don't + # need to be of the right size + a = np.zeros([1, 1], dtype=dtype) + work = np.zeros([1], dtype=dtype) + tau = np.zeros([1], dtype=dtype) + + # Size query + results = lapack_routine(m, n, a, lda, tau, work, -1, 0) + assert_equal(results['info'], 0) + assert_equal(results['m'], m) + assert_equal(results['n'], m) + + # Should result to an integer of a reasonable size + lwork = int(work.item()) + assert_(2**32 < lwork < 2**42) |