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ENH: Refactor numpy ** operators for numpy scalar integer powers
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ENH: Add a float_power function with at least float64 precision.
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Corrections to #8023.
- Fix index types to ssize_t.
- Clean up C code style.
Closes #7701.
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Corrections to #8001.
- Correct markup for code sections.
- Correct link to structured arrays.
Closes #7881.
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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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Closes #5813.
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This is easier to get going, and is the recommended access method
by GitHub itself:
https://help.github.com/articles/which-remote-url-should-i-use/
Also add instructions for pulling from upstream including PRs
by default.
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ENH: Add ma.convolve and ma.correlate for #6458
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BUG: integers to a negative integer powers should error.
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This is a change in behaviour. Previously
* zero to negative integer powers returned least integral value.
* 1, -1 to negative integer powers returned correct values
* all remaining integers returned zero when raised to negative integer
powers.
All of these cases now raise a ``ValueError``. It was felt that a simple
rule was the best way to go rather than have special exceptions for the
units. If you need negative powers, use an inexact type.
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ufuncs (#8054)
* ENH: add signature argument to vectorize for generalized ufuncs
Example usage (from the docstring):
Vectorized convolution:
>>> convolve = np.vectorize(np.convolve, signature='(n),(m)->(k)')
>>> convolve(np.eye(4), [1, 2, 1])
array([[ 1., 2., 1., 0., 0., 0.],
[ 0., 1., 2., 1., 0., 0.],
[ 0., 0., 1., 2., 1., 0.],
[ 0., 0., 0., 1., 2., 1.]])
* Use str.format rather than %
* Fix spelling typo
* BUG: fix np.vectorize for size 0 inputs
* DOC: add vectorize to 1.12.0 release notes
* [ci-skip] Remove outdated comment
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This makes it possible to directly use matplotlib references such as
:func:`matplotlib.pyplot.imshow`.
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ENH: Add ability to runtime select ufunc loops, add AVX2 integer loops
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WIP: MAINT: Add deprecation warning to views of multi-field indexes
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Behavior of multi-field indexes will change in 1.13: Multi-field indexes
will return a view (not a copy) and assignment between structures with
non-identical fieldnames occurs "by position" (not "by fieldname"):
>>> a = zeros(10, dtype=[('x', 'i8'), ('y', 'i8'), ('z', 'i8')])
>>> a[['x', 'z']].view('i4') # Deprecation warning for multifield view
>>> b = ones(10, dtype=[('y', 'i4'), ('x', 'f4')])
>>> a[:] = b # Deprecation warning for multifield assignment
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DOC: Update 1.11.2 release notes.
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Instances remain for NumpyVersion and Numpy.rec.fromarrays that are
references to code.
Release notes were left unchanged.
see issue #7986
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Making the outer context manager a suppress warnings gives good
control to print warnings only once in release mode and suppress
some specific warnings which cannot be easily avoided otherwise.
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This means that warnings of different origin then the one tested for
behave normally. If the normal behaviour is to igonre them this might
decrease specificity in rare cases. In most cases the specificity
will be slightly higher.
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DOC: Create 1.11.2 release notes.
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[skip ci]
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This context has a couple of advantages over the typical one, and can
ensure that warnings are cleanly filtered without side effect for
later tests.
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Closes gh-391.
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BLD: preserve library order
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Before, the list of libraries was resorted to match the order of
library_dirs. Now, the opposite occurs: library_dirs is resorted to
match the library order.
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Document runtests extra argv
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This is useful for things like passing ``--pdb`` to make nose drop into
a pdb post-mortem on exception.
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Introsort is regular quicksort but changing to a heapsort when not
enough progress is made. This retains the good quicksort performance
while changing the worst case runtime from O(N^2) to O(N*log(N))
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