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* DOC: Changed the example for modifying the shape without modifying the initial object
* DOC: Removed the example for directly assigning a tuple to the shape attribute of a numpy array
* DOC: Re-added note about copying data when reshaping an array to numpy.reshape docs
* DOC: reformat for linting
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Co-authored-by: Jory Klaverstijn <j.klaverstijn@student.rug.nl>
Co-authored-by: Matti Picus <matti.picus@gmail.com>
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It has been deprecated since numpy 1.20, and code search engines
don't turn up a reason to keep this around.
[skip actions] [skip cirrus]
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Updated the dot function C-API so that it now calls `np.multiply` with `out=` and returns it on branch of the function where the correct behaviour was not in place. Added two tests regarding this issue.
Closes #21081.
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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MAINT: Fix ReDOS vulnerability in crackfortran.py
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My first replacement regex would have failed to match
cases like '@)@bind foo bar baz@(@@)@' which should
apparently be matched.
Added a test to make sure the regex does this.
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Revert "ENH: Enabled the use of numpy.vectorize as a decorator"
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ENH: Add support for inplace matrix multiplication
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It appears that assertion is not true for bad __array_ufunc__
or similar implementations. And we have at least one test that runs
into it.
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In theory, an object matmul could be caught here, but lets assume
that doesn't happen...
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This uses the `axes` argument. Arguably the most correct version since
we use the full ufunc machinery, so we can't mess up with random conversions
(which the test suite actually did notice, at least for an array subclass).
OTOH, for now the errors are ridiculously unhelpful, some of which could
be fixed in the gufunc code (at least made _better_).
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In principle, this is probably still not 100% correct always since
we convert the the other object to an array upfront (to get the
error). But the alternative solution using `axes=` seems tricky
as well...
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Add special casing for `1d @ 1d` and `2d @ 1d` ops.
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array-api
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ENH: Enabled the use of numpy.vectorize as a decorator
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This reverses commit 7a2ded1522305
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This test makes sure a function's docstring is properly preserved
after calling the vectorize decorator.
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Previous definition implies that vectorize returns generalized functions,
which is not true.
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Most of this code comes from PR-9593, but with the default value for pyfunc
being numpy._NoValue instead of None, no override of __new__, and no effort
to make subclassing possible.
Co-Authored-By: Michael Lamparski <diagonaldevice@gmail.com>
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ENH: Add support to `ma.dot()` for non-2d arrays with `strict=True`
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ENH: allow using dtype classes in array creation functions
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