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| author | Pauli Virtanen <pav@iki.fi> | 2013-10-12 22:57:22 +0300 |
|---|---|---|
| committer | Pauli Virtanen <pav@iki.fi> | 2013-10-12 23:07:01 +0300 |
| commit | 984854aa605b5b4d5afe630e1879aa83845b11fb (patch) | |
| tree | 324e8b43ae7968caf9a636dc7d88b99f232cc455 /numpy/linalg/tests | |
| parent | c9ed04a5a72fa488a203a7c82cc73f390c3afe8b (diff) | |
| download | numpy-984854aa605b5b4d5afe630e1879aa83845b11fb.tar.gz | |
BUG: linalg: don't tell BLAS to use zero strides
At least OSX Accelerate fails for this case.
Diffstat (limited to 'numpy/linalg/tests')
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 32 |
1 files changed, 31 insertions, 1 deletions
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index aefb61b14..d40157904 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -105,6 +105,9 @@ SQUARE_CASES = [ LinalgCase("8x8", np.random.rand(8, 8), np.random.rand(8)), + LinalgCase("1x1", + np.random.rand(1, 1), + np.random.rand(1)), LinalgCase("nonarray", [[1, 2], [3, 4]], [2, 1]), @@ -150,6 +153,12 @@ NONSQUARE_CASES = [ LinalgCase("8x11", np.random.rand(8, 11), np.random.rand(11)), + LinalgCase("1x5", + np.random.rand(1, 5), + np.random.rand(5)), + LinalgCase("5x1", + np.random.rand(5, 1), + np.random.rand(1)), ] HERMITIAN_CASES = [ @@ -177,7 +186,10 @@ HERMITIAN_CASES = [ None), LinalgCase("hmatrix_a_and_b", matrix([[1., 2.], [2., 1.]]), - None) + None), + LinalgCase("hmatrix_1x1", + np.random.rand(1, 1), + None), ] @@ -247,6 +259,24 @@ def _stride_comb_iter(x): assert np.all(xi == x) yield xi, "stride_" + "_".join(["%+d" % j for j in repeats]) + # generate also zero strides if possible + if x.ndim >= 1 and x.shape[-1] == 1: + s = list(x.strides) + s[-1] = 0 + xi = np.lib.stride_tricks.as_strided(x, strides=s) + yield xi, "stride_xxx_0" + if x.ndim >= 2 and x.shape[-2] == 1: + s = list(x.strides) + s[-2] = 0 + xi = np.lib.stride_tricks.as_strided(x, strides=s) + yield xi, "stride_xxx_0_x" + if x.ndim >= 2 and x.shape[:-2] == (1, 1): + s = list(x.strides) + s[-1] = 0 + s[-2] = 0 + xi = np.lib.stride_tricks.as_strided(x, strides=s) + yield xi, "stride_xxx_0_0" + for src in (SQUARE_CASES, NONSQUARE_CASES, HERMITIAN_CASES, |