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Bumps [hypothesis](https://github.com/HypothesisWorks/hypothesis) from 6.8.1 to 6.8.3.
- [Release notes](https://github.com/HypothesisWorks/hypothesis/releases)
- [Commits](https://github.com/HypothesisWorks/hypothesis/compare/hypothesis-python-6.8.1...hypothesis-python-6.8.3)
Signed-off-by: dependabot-preview[bot] <support@dependabot.com>
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BUG: fix segfault in object/longdouble operations
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The operation None*np.longdouble(3) was causing infinite recursion as it
searched for the appropriate conversion method. This resolves that, both
for general operations and for remainders specifically (they fail in a
subtly different way).
Closes #18548
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REL: Update main after 1.20.2 release.
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BUG: Changed METH_VARARGS to METH_NOARGS
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MAINT: Improve error message when common type not found.
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ENH: Optimize and cleanup ufunc calls and ufunc CheckOverrides
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[skip CI]
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This is based on Marten's review again.
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These functions do not require `NPY_NO_EXPORT`. One of them was
(incorrectly) flagged by code coverage. Maybe this helps...
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This fixes the review comments by Marten, mainly small cleanups.
The largest change is that it is now back to a ValueError if the
out tuple has the wrong length.
Co-Authored-By: Marten van Kerkwijk <mhvk@astro.utoronto.ca>
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The TypeError TODO is also reflected in the tests I think, the
other TODO seems pretty unnecessary (most users will go through
`tp_vectorcall` anyway, so micro-optimizing that is not all that
relevant).
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This is a rather large commit which clean up the ufunc override
code for argument parsing. (I may attempt to split it up)
There are two main things, argument parsing, especially for
reductions is now much faster since `METH_FASTCALL` is used
(when keyword arguments are being used).
By moving the argument parsing and using more generic code this
also simplifies the ufunc override checking especially when
keyword arguments are present.
Both of this decreases the argument parsing overhead quite a lot
for ufunc calls, especially for small reductions. (Without double
checking, I believe the speedup was up to around 30% for small
reductions.)
The downside is some added/annoyance due to the use of marcos to
support both FASTCALL and no FASTCALL semantics.
As a side note: vectorcall is likely not a huge factor for ufuncs
since it is very common not to use any keyword arguments. OTOH,
code that uses ``out=...`` a lot on small arrays should see a nice
difference.
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* ENH: Remove call to `_filter_header` from `_write_array_header`
Improve performance of `np.save` by removing the call
when writing the header, as it is known to be done in Python 3.
* ENH: Only call `_filter_header` from `_read_array_header` for old vers
Improve performance of `np.load` for arrays with version >= (3,0)
by removing the call, as it is known to be done in Python 3.
* ENH: Use a set of keys when checking `read_array`
Improve performance of `np.load`.
* DOC: Improve performance of `np.{save,load}` for small arrays
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BUG: Fix small issues found with pytest-leaks
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None of these are particularly worrying as they either usually only
leak reference (and not memory) or appear in rare or almost impossible
error-paths, or are limited to the tests.
Unfortunately, this PR will not apply to 1.20.x, due to small changes
in the overrides.
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ENH: Use exponentials in place of inversion in Rayleigh and geometric
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Use exponentials rather than generating exponentials via inversion
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MAINT: Bump sphinx from 3.5.2 to 3.5.3
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Bumps [sphinx](https://github.com/sphinx-doc/sphinx) from 3.5.2 to 3.5.3.
- [Release notes](https://github.com/sphinx-doc/sphinx/releases)
- [Changelog](https://github.com/sphinx-doc/sphinx/blob/3.x/CHANGES)
- [Commits](https://github.com/sphinx-doc/sphinx/commits)
Signed-off-by: dependabot-preview[bot] <support@dependabot.com>
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DOC: Update some plotting code to current Matplotlib idioms
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- 3D Axes are created via add_subplot(projection='3d')
- There is now a `stairs()` function that's specifically designed for
showing histogram curves
- Labels should be passed as keyword arguments to the plot functions
instead of to `legend()`, which reduces the risk of mixing them up.
- ensure equal axis scaling in the meshgrid example
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DOC: add release note for removal of /usr/include from include paths
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Follow-up to gh-18658
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BLD: remove /usr/include from default include dirs
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Including this directory is painful for cross-compiling, see
gh-14980 and gh-13280. Removing this directory fixes the following
build failure:
```
gcc: numpy/core/src/common/numpyos.c
In file included from numpy/core/src/common/numpyos.c:23:
/usr/include/xlocale.h:27:16: error: redefinition of ‘struct __locale_struct’
27 | typedef struct __locale_struct
```
This error also shows up in various other build issues outside of the
NumPy issue tracker.
Compilers normally always include this path, so this shouldn't break
anything. The default include paths for the compiler can be checked,
e.g. for gcc with `cpp -v`. That will typically have /usr/include last.
In case this breaks something for a nonstandard compiler, that can be
worked around via a site.cfg file in the root of the repo (or
equivalently, `~/numpy-site.cfg`) containing:
```
[DEFAULT]
include_dirs = /usr/include
```
The same principle should apply to `/usr/lib`. I will make that change
in a separate commit, because the failure mode for that will be
different (and I'm not running into it right now).
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MAINT: OrderedDict is no longer necessary from Python 3.7
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MAINT: Do not claim input to binops is `self` (array object)
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This can currently only be passed positionally, and this is
undocumented.
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Co-authored-by: Matti Picus <matti.picus@gmail.com>
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On the C-side binops only guarantee that one of the operands
is an instance of `PyArrayObject *`, but we do not know which
one. Typing the first as `PyArrayObject *` is just misleading
for almost no actual payoff
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ENH: Use new argument parsing for array creation functions
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I had forgotten that the docs for these functions where updated
when rebasing.
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The argument name for the python side defined function was always
`a` and not `object` so fix it and add a test. Also add a test to
ensure the error paths are taken for all of the function.
The missing NULL returns cannot be tested easily (but thanks to
code coverage its nice to look at the uncovered stuff closer...)
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