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BUG: np.piecewise not working for scalars
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Fixed meshgrid to return arrays with same dtype as arguments.
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BUG: Let linspace accept input that has an array_interface but is not othe…
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numpy or python type.
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Addresses part of issue reported in gh-8224.
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I forgot to keep the test fixes when the scalar `**` operator
was refactored the second time.
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REL: Prepare for 1.12.x branch
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No changes in the interfaces but some housekeeping is needed.
- Add comments to cversions.txt and setup_common.py
- Add NPY_1_12_API_VERSION to numpyconfig.h
[ci skip]
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BUG: Better check for invalid bounds in np.random.uniform.
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Also check for invalid bounds when low= and high= are arraylike rather than scalar (closes #8226)
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ENH: Refactor numpy ** operators for numpy scalar integer powers
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This change is the upshot of discussion on the numpy mailing list where
it was decided that a numpy scalar integer raised to a negative integer
power should raise a ValueError, as do Numpy arrays. In particular, we
want numpy scalars and numpy 0-d arrays to have similar behavior.
Previously zero was returned for this case.
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ENH: Add a float_power function with at least float64 precision.
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The new float_power function converts integers and inexact type to
inexact types of minimum precision float64 before computing the power.
The intent is one should not need to worry about overflow or negative
powers when computing a power when type preservation is not a factor. It
also implements the popular proposal on the numpy mailing list that the
`**` operator should always return at least double precision.
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DOC: Fix documentation pull requests.
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Corrections to #7492.
Correct the examples in the notes specifying the output length for the
hfft. Also clean up the documentation a bit.
[ci skip]
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DOC: Enhance description/usage for np.linalg.eig*h
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The UPLO parameter of eigvalsh was marked as deprecated, apparently in anticipation
of convergence with the scipy version which uses a `lower` boolean parameter. There is
no deprecation in the code, nor a lower parameter, so remove the deprecation.
[ci skip]
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Proposed documentation enhancement to the `np.linalg.eig*h`
routines.
The current documentation does not reflect the nature of the
underlying LAPACK routines and the way in which they interpet
the input. This documentation and examples are with view of
adding clarity to what is actually performed.
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ENH: Make numpy.mean() do more precise computation
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output dtype that stay in float16.
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asarray does copy the input if the specified dtype and/or order differ
from the input even if it is an ndarray.
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BUG: Fix structured array format functions
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Related to PR #8200
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PR #8160 added format function for structured arrays.
But it is not applied for structured array scalars.
Closes #8172
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Preserving structured array element format,
this commit fixes subarray format changed in PR #8160.
This commit also changes iterator for field name from dtype_.descr to
dtype_.names (Related to #8174).
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When python is invoked with switch -3, it emits waring "classic int division"
for strict integer divisions. The same behavior is now implemented to numpy
with this fix
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DOC: See also np.load and np.memmap in np.lib.format.open_memmap
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np.load supports memmap_mode to open existing .npy files as
memory-mapped files. np.memmap supports creating or loading raw
binary files as memory-mapped files. This adds a link to a
function for creating memory-mapped files in .npy format.
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BUG: ediff1d should return subclasses
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Special case to_begin and to_end both equal to None, avoiding
subsequent steps. Particulary faster for small arrays where
overhead plays a big role.
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Closes #5813.
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Closes gh-8214.
Closes gh-8215.
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Ediff1d performance
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Eliminate a copy operation when to_begin or to_end is given. Also
use ravel instead of flatiter which is much faster.
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DEP: Deprecate the keepdims argument to accumulate
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