| Commit message (Collapse) | Author | Age | Files | Lines |
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stanza
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DOC: testing: Fix typo: nulps -> nulp
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[skip actions] [skip travis] [skip azp]
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* BUG: Histogramdd breaks on big arrays in Windows
Resolved the issue with line change from int to np.intp in numpy/numpy/lib/histograms.py
* BUG: Histogramdd breaks on big arrays in Windows
Resolved the issue with line change from int to np.intp in numpy/numpy/lib/histograms.py
* Removed the binary files
* Update test_histograms.py
* Update test_histograms.py
* Update test_histograms.py
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DOC: Rm round_ from the autosummary for rounding
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MAINT: remove macOS specific long double handling in numpyconfig.h
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This was put in place for universal builds (the old kind, PPC/Intel),
and then extended for arm64 support. It was only needed when building
for two architectures in a single build.
We no longer support i386/PPC/universal, and for producing universal2
wheels for those users that want that, the way to do it is to
take a x86-64 wheel and an arm64 wheel and fuse those with the
`delocate-fuse` utility from `delocate`.
Hence this code is no longer needed.
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* BUILD: update OpenBLAS to 0.3.21 and clean up openblas download test
* set LDFLAGS on windows64 like the openblaslib build does
* use rtools compilers on windows when building wheels
* fix typos
* add rtools gfortran to PATH
* use the openblas dll from the zip archive without rewrapping
* typos
* copy dll import library for 64-bit interfaces
* revert many of the changes to azure-steps-windows.yaml, copy openblas better in wheels
* fix wildcard copy
* test OpenBLAS build worked with threadpoolctl
* typos
* install threadpoolctl where needed, use for loop to recursively copy
* update macos OpenBLAS suffixes for newer gfortran hashes
* use libgfortran5.dylib on macos
* fix scripts
* re-use gfortran install from MacPython/gfortran-install on macos
* use pre-release version of delocate
* fixes for wheel builds/tests
* add debugging cruft for pypy+win, macos wheels
* add DYLD_LIBRARY_PATH on macosx-x86_64
* use 32-bit openblas interfaces for ppc64le tests
* skip large_archive test that sometimes segfaults on PyPy+windows
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MAINT, CI: Enable coverage checking.
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Coverage checking was disabled for the "full" test because of internal
compiler errors with the gcc supplied by Ubuntu-20.04. That problem is
fixed in Ubuntu-22.04, but there were unrelated warnings. Those warnings
are now fixed, so re-enable coverage checking.
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MAINT: (array-coercion) Silence invalid read warning in some gcc versions
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The warnings are harmless and seem to be caused by the "hint" that the
shape cannot be larger than that area. But some compiler versions seem
to check that the function call is always correct based on the signature.
That probably makes sense, so just remove that "size hint" which is maybe
even technically incorrect (the compiler is not allowed to read more as
an optimization).
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MAINT, CI: Update Ubuntu 18.04 to Ubuntu 20.04
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We have dropped GCC-6 build testing.
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Github actions will drop support for 18.04 April 1, 2023. There
are now sporadic test cancelations due to warning brownouts, and
the NumPy 1.24.x release will overlap that date, so increase the Ubuntu
version.
The main change here is that there is no support for gcc-6 in Ubuntu
20.04, so testing with that version is also dropped.
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MAINT: Use C99 flexible struct construct for `NpyIter_InternalOnly`
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This reduces the allocation size by 1 byte, but that doesn't matter
(everything we store later is larger anyway and the 1 doesn't seem to
be accounted for in `NIT_SIZEOF_ITERATOR`).
This should fix certain compiler warnings and because of that:
Closes gh-22599
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ENH: Expose `ufunc.resolve_dtypes` and strided loop access
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Co-authored-by: stuartarchibald <stuartarchibald@users.noreply.github.com>
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Reusing `result` doesn't work with a single "finish" goto, since
result must be NULL on error then.
This copies the result over for continuation, which is maybe also a bit
awkward, but at least not buggy...
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Also add tests (including for a bad capsule)
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Co-authored-by: stuartarchibald <stuartarchibald@users.noreply.github.com>
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The API here designed is "future" in the sense that it implementes
NEP 50 and exposes loop specializations as per NEP 43 which is barely
used by NumPy itself at this point.
Due to the fact that NEP 50 is not implemented (or rather finalized)
this API is not ideal and creates dummy-arrays internally so that
it is not much faster than if the user created dummy arrays to
probe the correct result.
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BUG: fix misleading error message
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Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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closes gh-22570
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DOC: Clarify relationship between row_stack and vstack.
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