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Previously, we would check if the attribute existed on the class, yet use it from the instance.
This also cuts 3 lookups of `__array_ufunc__` down to one.
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This also corrects a broken short-circuit when looking up __array_ufunc__
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BUG: distutils, add compatiblity python parallelization
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Python 3.5 also added build parallelization at the extension level
instead of the file leve numpy uses.
This causes two problems:
- numpy.distutils is not threadsafe with duplicated source files
When source files are duplicated in multiple extensions the output
objects are overwritten which can truncate in a parallel context.
This is fixed by keeping track of the files being worked on and wait
for completion if another thread is already using the object name.
- The parallelization on two nested levels causes oversubscription.
When building multiple extensions with multiple source files the number
of jobs running is multiplied.
This is fixed by adding a semaphore that limits the number of jobs numpy
starts to the defined amount.
closes gh-7139
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Placing them all under the same name in the top level folder breaks when
using the parallel extension compilation option of python 3.5.
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BUG: Preserve field order in join_by, avoids FutureWarning
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Fixes #8940
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BUG: Prevent stackoverflow on self-containing arrays
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Fixes #9078
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Approaches #8306. This still errors, but it does so at a python level, without
a segfault.
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BUG: Various fixes to _dtype_from_pep3118
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Fixes gh-9053
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Adding padding fields means that dtypes with the same fields cannot necessarily
be cast to one another. Padding shouldn't prevent casting.
Partially fixes #9053
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BUG: Buttress handling of extreme values in randint
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ENH: Show full PEP 457 argument lists for ufuncs
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The distinction between unary and binary is not too helpful, and ignores the fact that trinary ufuncs can exist.
Also add a link to the ufunc docs
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This was covered by very few ufuncs, and is probably better to leave out.
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This will hopefully make it easier to debug problems like those seen
in gh-8653.
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ENH: add np.divmod ufunc
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This fixes a regression in 3c1a13dea6a7e189675977ad65ea230ce4816061, restoring the
behaviour intended by eee00f8f7e15592a048c8b841aef9ea81faa0fda.
This also extends the support on ctype-less systems for `arr.ctypes.shape` and `arr.ctypes.strides`.
The dummy_ctype object is a naive fake used when ctypes is not importable. It does not intend to fake any ctypes behavior, but provides a duck-typed interface so that method calls do not fail.
The get_shape and get_strides refactors take advantage of other instance methods and reduce code duplication.
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MAINT: Update FutureWarning message.
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The future structured array assignment change warned about in
dtype_transfer.c will take place in NumPy 1.14, not 1.13.
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types
This behavior is contrary to np.conjugate (which will error on
non-numeric types), even though documentation claims they are identical.
This deprecation favors failing fast.
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ENH: Add isnat function and make comparison tests NAT specific
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This may show warnings in downstream projects, which should likely
not be there. We could also drop in the normal assert_equal there,
which would support NaT, and NaN, but checks for scalarness, which
this currently does not (which also could create problems).
Works around the only test with this problem, by using the normal
assert_equal there.
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These warning filters are not threadsafe, while it is nicer if the
comparison functions can be called in a threaded environment since
they do no explicite warning checking.
Less filters are also cleaner in general, though may also mean that
downstream projects see warnings that were previously hidden.
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BUG: don't create array with invalid memory in where
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When creating the tuple view of np.where, make sure the arrays point to
valid memory when they are empty.
Numpy assumes that even empty arrays have valid memory, e.g. in the
source stride == 0 assignments.
Closes gh-8922.
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DEP: Deprecate `np.ma.MaskedArray.mini
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Also, remove unecessary subclasses
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Introduced by me in #8918
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This does not match np.maximum, which is confusing because the masked
version has no documentation at all. This uses a similar deprecation approach
to gh-8918, noting that the warning is only needed for arrays of more than one
dimension.
The same remarks apply to `np.ma.minimum`
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