BUG: numpy.array_api: fix linalg.cholesky upper decomp for complex dtypes#24777
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rgommers merged 1 commit intonumpy:mainfrom Jan 3, 2024
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BUG: numpy.array_api: fix linalg.cholesky upper decomp for complex dtypes#24777rgommers merged 1 commit intonumpy:mainfrom
numpy.array_api: fix linalg.cholesky upper decomp for complex dtypes#24777rgommers merged 1 commit intonumpy:mainfrom
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rgommers
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Thanks @lucascolley, this LGTM. The upstream definition fix got merged, and this seems clearly correct. It's easy to test now too, since np.linalg.cholesky recently gained an upper keyword (we don't want to change this PR though, because it'd be good for this code to work with numpy 1.25/1.26):
>>> A = np.array([[1,-2j], [2j,5]])
>>> np.linalg.cholesky(A)
array([[1.+0.j, 0.+0.j],
[0.+2.j, 1.+0.j]])
>>> np.array_api.linalg.cholesky(np.array_api.asarray(A))
Array([[1.+0.j, 0.+0.j],
[0.+2.j, 1.+0.j]], dtype=complex128)
>>> np.linalg.cholesky(A, upper=True)
array([[ 1.+0.j, -0.-2.j],
[ 0.+0.j, 1.+0.j]])
>>> np.array_api.linalg.cholesky(np.array_api.asarray(A), upper=True)
Array([[1.-0.j, 0.-2.j],
[0.-0.j, 1.-0.j]], dtype=complex128)So that matches, while in main the sign of the off-diagonal element is reversed.
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Adding the backport candidate, because it'd be nice if it were correct in 1.26.x if we do another bugfix release there. |
charris
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numpy.array_api: fix linalg.cholesky upper decomp for complex dtypesnumpy.array_api: fix linalg.cholesky upper decomp for complex dtypes
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Closes gh-24451
cc @asmeurer