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This wraps `trapz` into a proper python function and then copies all
attributes expected on a Python function over from the "fake" version
to the real one.
This allows SciPy to pretend `trapz` is a Python function to create
their own version.
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pyinstaller should pack it to allow running the tests, but doesn't
pack the tests themselves and thus doesn't find the `import` statements
that use `numpy.core._multiarray_tests`.
This makes sure that pyinstaller will ship `numpy.core._multiarray_tests`
in any case.
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MAINT: Remove all nose testing support.
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NumPy switched to using pytest in 2018 and nose has been unmaintained
for many years. We have kept NumPy's nose support to avoid breaking
downstream projects who might have been using it and not yet switched to
pytest or some other testing framework. With the arrival of Python 3.12,
unpatched nose will raise an error. It it time to move on.
Decorators removed
- raises
- slow
- setastest
- skipif
- knownfailif
- deprecated
- parametrize
- _needs_refcount
These are not to be confused with pytest versions with similar names,
e.g., pytest.mark.slow, pytest.mark.skipif, pytest.mark.parametrize.
Functions removed
- Tester
- import_nose
- run_module_suite
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Deprecate np.finfo(None), it may be that we should more generally deprecate `np.dtype(None)` but this is a start and particularly weird maybe.
Closes gh-14684
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BUG: Implement `ArrayFunctionDispatcher.__get__`
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While functions should not normally need this, Python functions do
provide it (C functions do not, but we are a fatter object anyway).
By implementing `__get__` we also ensure that `inspect.isroutine()`
passes. And by that we ensure that Sphinx considers these a `py:function:`
role.
Closes gh-23032
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Port CORE diff relevant code to MA and adapt docstrings examples and add tsts.
Closes gh-22465
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DEP: Finalize the non-sequence stacking deprecation
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The `__array_function__` API currently will exhaust iterators so we
cannot accept sequences reasonably. Checking for `__getitem__` is presumably
enough to reject that (and was what the deprecation used).
Future changes could allow this again, although it is not a useful API
anyway, since we have to materialize the iterable in any case.
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API: Fix cython exception handling for exported extern C functions
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The incref/decref function shouldn't be able to fail (especially the
decref). But right now they can, this will be fixed when we redo
clearing (see gh-22924)
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This hopefully fixes them for all the functions currently in the `.pyd`
files. A surprising amount of them look like scary thing I wouldn't
mind to just delete :).
Anyway, had looked at some Cython code today and remembered this.
Closes gh-19291
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ENH: Improve array function overhead by using vectorcall
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This makes these functions much faster when used with keyword arguments
now that the array-function dispatching does not rely on `*args, **kwargs`
anymore.
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The refactor to use vectorcall/fastcall is obviously much better
if we don't have to go back and forth, for concatenate we get:
arr = np.random.random(20)
%timeit np.concatenate((arr, arr), axis=0)
Going from ~1.2µs to just below 1µs and all the way down to ~850ns
(fluctuates quite a lot down to 822 even). ~40% speedup in total
which is not too shabby.
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This moves dispatching for `__array_function__` into a C-wrapper. This
helps speed for multiple reasons:
* Avoids one additional dispatching function call to C
* Avoids the use of `*args, **kwargs` which is slower.
* For simple NumPy calls we can stay in the faster "vectorcall" world
This speeds up things generally a little, but can speed things up a lot
when keyword arguments are used on lightweight functions, for example::
np.can_cast(arr, dtype, casting="same_kind")
is more than twice as fast with this.
There is one alternative in principle to get best speed: We could inline
the "relevant argument"/dispatcher extraction. That changes behavior in
an acceptable but larger way (passes default arguments).
Unless the C-entry point seems unwanted, this should be a decent step
in the right direction even if we want to do that eventually, though.
Closes gh-20790
Closes gh-18547 (although not quite sure why)
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WG14 N2350 made very clear that it is an UB having type definitions
within "offsetof" [1]. This patch enhances the implementation of macro
_ALIGN to use builtin "_Alignof" to avoid undefined behavior on
when using std=c11 or newer
clang 16+ has started to flag this [2]
Fixes build when using -std >= gnu11 and using clang16+
Older compilers gcc < 4.9 or clang < 8 has buggy _Alignof even though it
may support C11, exclude those compilers too
[1] https://www.open-std.org/jtc1/sc22/wg14/www/docs/n2350.htm
[2] https://reviews.llvm.org/D133574
Signed-off-by: Khem Raj <raj.khem@gmail.com>
* Apply suggestions from code review
Signed-off-by: Khem Raj <raj.khem@gmail.com>
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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* DOC: #22266 Add examples for tri[lu]_indices_from()
* DOC: see also for tri[lu]_indices_from()
* DOC: Fix triu_indices_from example and minor updates.
* incides -> indices
* Update wording surrounding .
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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BLD: Try building wheels with cibuildwheel 2.12.0
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Also cleanup some uneeded/commented stuff.
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* DOC: Add example for np.ma.diag as part of numpy#22269
* Add descriptions to example.
* Fix typo.
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Updates the free format handling of .f90 and other common extensions (through a minor re-write). Also removes an unused function.
This disallows previously allowed (but highly unlikely to be present) code-paths, namely having fixed form F77 code in a fortran 90 file (with .f90).
Co-authored-by: Sebastian Berg <sebastianb@nvidia.com>
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assert_array_equal (#23015)
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This pull requests speeds up numpy.load. Since _filter_header is quite a bottleneck, we only run it if we must. Users will get a warning if they have a legacy Numpy file so that they can save it again for faster loading.
Main discussion and benchmarks see #22898
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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DEP: Finalize `+arr` returning a copy e.g. for string arrays
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This was deprecated 4-5 years ago in NumPy 1.16. Pandas stumbled
over it cleaning up their warning filters, so I decided to just
expire it.
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The number "changed" is weird if the user fixed it, so give a different
message in that case.
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BUG: Ensure correct loop order in sin, cos, and arctan2
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These were incorrect afer being vectorized. The commit additional
tests these (not arctan2 admittedly) and adds a check to generate_umath
to make it a bit less likely that future additions add this type of thing.
Note that the check allows duplicated loops so long they are correctly
ordered the *first* time. This makes results correct, but duplicated
loops are not nice anyways and it would be nice to remove them.
We could drop them manually in hindsight even? In any case, that should
not be backported, so it is not includedhere.
Closes gh-22984
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This makes it possible for new-style NEP 42 string dtypes like ASCIIDType to work with the functions in np.char, this has leads to some mild modification (stricter behavior in bad paths).
It will only work with dtypes with a scalar that subclasses str or bytes. I also assume that you can create instances of the user dtype from python like dtype_instance = CustomDType(size_in_bytes). This is a pretty big assumption about the API of the dtype, I'm not sure offhand how I can do this more portably or more safely.
I also added a new macro, NPY_DT_is_user_defined, which checks dtype->type_num == -1, which is currently true for all custom dtypes using the experimental dtype API. This new macro is needed because NPY_DT_is_legacy will return false for np.void.
This is only tested via the user dtypes currently.
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MAINT: Fix some noisy clang suggestions.
[ci skip]
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The suggestions looks like:
```
numpy/core/src/npysort/selection.cpp:426:39: warning
suggest braces around initialization of subobject [-Wmissing-braces]
arg_map{Tags::type_value, &introselect_noarg<Tags>,
^~~~~~~~~~~~~~~~~~~~~~~~
{ }
```
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DOC: All integer values must be non-negative
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"All integer values must be non-negative"
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PyArray_FillWithScalar checks if destination is writeable before attempting to fill it. A relevant test is added as a method of TestRegression
Closes gh-22922
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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Make a note on results depending on system due.
Closes gh-22919
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