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Added a See also section to mention np.random.Generator.uniform.
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BLD: Allow GCC compile on mingw-w64-based systems
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Macro `__MINGW32__` always defined for Mingw-w64 compilers (32- or
64-bit):
https://sourceforge.net/p/predef/wiki/Compilers/
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TYP,ENH: Mark all unhashable classes as such
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ENH: Adding __array_ufunc__ capability to MaskedArrays
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This test makes sure that a MaskedArray defers properly to another
class if it doesn't know how to handle it. See #15200.
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This enables any ufunc numpy operations that are called on a
MaskedArray to use the masked version of that function automatically
without needing to resort to np.ma.func() calls.
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BUG: Fix KeyError in crackfortran operator support
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Some of the values in the documentation of lagfit are in single-backticks,
though single backticks usually means that this is a reference to
something else that sphinx tries to resolve. Here I update values that
reference nothing to use double backticks (verbatim), or emphasis.
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PERF: Micro optimize np.linspace
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Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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Right now, example for ascontiguousarray() only demonstrates that the function is capable to change the dtype, but it doesn't really change the memory layout since x is already C_CONTIGUOUS. In this PR we make this example more relevant and be consistent with the example for asfortranarray().
* DOC: make examples for `ascontiguousarray()` and `asfortranarray()` to be consistent
* Add more examples
* Get rid of .reshape()
* Reduce line length to 79 chars
* Change order of examples, remove trailing comments
* Use two-space indent
* Change `::` to `:`, remove code indentation
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That way incompatible included headers are not affected.
Fix #21802
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ENH: Ensure that assertion of unsigned dtypes does not return results
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that wrapped around.
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DOC: Fix the interpolation formulae for quantile and percentile
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and percentile().
Fix the interpolation formulae in the docs which led to absurd results. For quantile() and percentile().
Example, for median of a = [1,2,10,11], you expect to obtain i+g=2.5 for method = linear (or weibull, or hazen, or median_unbiased or normal_unbiased).
Instead, you obtain a /negative/ index.
The correted formula is:
i + g = q * (n - alpha - beta + 1 ) + alpha
Notice among other things that n belongs in the numerator, not the denominator!
As a check, the corrected formula does lead to the correct index 2.5 for each of the cases above.
MYSTERY: Surely the original formula was the result of a small typo/thinko? Then, why does the correction look so completely different?
RESOLUTION OF MYSTERY:
Take our formula, massage it, and swap q with (i+g), and you end up with the original formula.
In other words, the original author of the doc. simply confused their percentile with their index halfway through the creation of the doc. Then, they massaged it to isolate (i+g) on the left.
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Closes gh-21910
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Closes #19138
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[ci skip]
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numpy/core/setup.py (`can_link_svml`): False for 32bit builds on `x86_64`
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DOC: Add usage example to np.char.center docstring
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Also add an example to illustrate how usecols can be used
to read a file with varying number of fields.
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DOC: Link to PEP-484 in the typing docs
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Co-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>
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Fix lib flags for librandom
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Add the voltbl fix to librandom. Remove SSE flag for GCC on 32-bit
Windows, it's the default.
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* Disable checks for Win workaround for GCC
Python compiled with GCC on Windows does not suffer the same
deficiencies as MSVC; disable check for that platform.
Here are a couple of `sys.version` strings from Windows / Mingw-w64
Python binaries:
* '3.10.5 (main, Jun 18 2022, 01:33:07) [GCC 12.1.0 32 bit]'
* '3.10.5 (main, Jun 18 2022, 01:32:32) [GCC UCRT 12.1.0 64 bit (AMD64)]'
For MSVC Python binaries:
* '3.9.13 (tags/v3.9.13:6de2ca5, May 17 2022, 16:24:45) [MSC v.1929 32 bit (Intel)]'
* '3.10.5 (tags/v3.10.5:f377153, Jun 6 2022, 16:14:13) [MSC v.1929 64 bit (AMD64)]'
* Update numpy/core/tests/test_multiarray.py
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This PR fixes the issue discussed on #12065 and #21843 where 'timedelta64' was noted to be a subtype of numpy.integer. This in principle should detect any cases where int(np.min(ar2)) fails. This PR also adds unittests for these.
* TST: Create in1d test for timedelta input
* MAINT: fix in1d for timedelta input
* TST: in1d raise ValueError for timedelta input
* MAINT: Clean up type checking for isin kind="table"
* TST: Add test for mixed boolean/integer in1d
* MAINT: Increase readability of in1d type checking
* STY: Apply small code style tweaks
This is probably really mainly my personal opinion...
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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MAINT: Fix non-void function does not return a value warning
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Co-authored-by: Bram <b.t.ton@saxion.nl>
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ENH,MAINT: Improve and simplify scalar floating point warnings
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This makes the scalar operations warnings read e.g.:
overflow encountered in scalar multiply
rather than:
overflow encountered in float_scalars
It also fixes one case where "assignment" rather than "cast" was
used when I added the FPEs for casts.
Otherwise, uses the helper that I intrudced for for the floating
point casts in all places to simplify the code, the only
"complicated" thing is that I try to give "scalar divide" rather
than "scalar true_divide" as warnings, since "true_divide" should
not really be something that end-users need be aware of.
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Non integer array-likes were not correctly rejected when a new
fast-path was added to `np.delete` in gh-16895.
This includes the _explicitly_ added `dtype=object` which should
not be allowed since it is not allowed in normal indexing either.
Closes gh-21840
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