FIX Add check array for empirical_covariance #26108
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jeremiedbb
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Apr 5, 2023
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Thanks for the PR @qbarthelemy. We don't need it for _oas because it's a private function only called by OAS which already validates X.
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>
jeremiedbb
reviewed
Apr 7, 2023
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>
thomasjpfan
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Apr 28, 2023
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Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
thomasjpfan
approved these changes
May 4, 2023
| @@ -84,7 +84,7 @@ def empirical_covariance(X, *, assume_centered=False): | |||
| [0.25, 0.25, 0.25], | |||
| [0.25, 0.25, 0.25]]) | |||
| """ | |||
| X = np.asarray(X) | |||
| X = check_array(X, ensure_2d=False, force_all_finite=False) | |||
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For reviewers, I think it's okay to set force_all_finite=False here, which is consistent with the behavior on main. If we set force_all_finite=True, then there can be a performance regression when empirical_covariance is called. The alternative is to set config_context(assume_finite=True) everywhere, but it adds the context manager to many places.
jeremiedbb
approved these changes
May 23, 2023
REDVM
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Nov 16, 2023
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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Reference Issues/PRs
Fixes #25519
What does this implement/fix? Explain your changes.
It adds
check_arraytoempirical_covariance.