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ENH: Modify `np.logspace` so that the `base` argument broadcasts against `start` and `stop`
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correctly against `start` and `stop`.
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DEP: deprecate np.math and np.lib.math
[skip ci]
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Allows clang-cl and other MSVC-compatible compilers to build
correctly.
Closes gh-23506
[skip cirrus] [skip circle] [skip azp]
Co-authored-by: Alexander Neumann <Alexander.Neumann@hamburg.de>
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DOC: Fix a reference to built-in `len` in `char.str_len` docstring
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Built-in function `len()` should not have prefix `builtins.`,
so removed it to fix the reference.
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BUG: fix loading and storing big arrays on s390x
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ENH: Raise C++ standard to C++17
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MAINT: improve error when a dtype doesn't support the buffer interface
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DOC: Remove doc for non-existing `PyArray_XDECREF_ERR`
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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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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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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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ENH: allow using dtype classes in array creation functions
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Also make internal versions accept a dtype and a descriptor.
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This enables writing np.array(some_object, dtype=type(np.dtype('i'))). This
is a follow-on from https://github.com/numpy/numpy/pull/23154, see that PR
for more details.
I had to add a new include to `ctors.h` to bring in the definition of the
`npy_dtype_info` struct. Since `ctors.h` is included in many other files inside
numpy, I found that I needed to modify fewer includes across numpy if I moved
the definition of `npy_dtype_info` to `common.h` from `descriptor.h`. The new
includes of `common.h` are needed to support later includes of `ctors.h` in
those files. If anyone has an alternate place to put `npy_dtype_info` that would
cause less churn of includes I'd love to hear about it.
I spent a bunch of time tweaking the reference counts. I'm reasonably confident
this is correct but not 100%, an additional careful pass over the reference
count logic from a reviewer would be very appreciated.
I could have made `_PyArray_FromAny` and `_PyArray_CheckFromAny` take just a
`npy_dtype_info` struct, but I found it made the reference count logic more
complicated, since `PyArray_FromAny` and `PyArray_CheckFromAny` steal the
reference to the descriptor they are passed and I needed to conserve that
behavior. Also both functions support passing in a `NULL` pointer for the
descriptor and I needed to maintain that behavior as well.
The change to `ucsnarrow.h` fixes a preexisting conflict with the prototype
in `ucsnarrow.c` that triggered a compiler error while I was working on this.
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ENH: Allow ``where`` argument to override ``__array_ufunc__``
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override `__array_ufunc__`.
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Fixes #23197
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