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BUG: copy inherited masks in MaskedArray.__array_finalize__
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Previously, operations which created a new masked array from an old
masked array -- e.g., np.empty_like -- would tend to result in the new
and old arrays sharing the same .mask attribute. This leads to
horrible brokenness in which writes to one array affect the other. In
particular this was responsible for part of the brokenness that
@jenshnielsen reported in gh-5184 in which np.gradient on masked
arrays would modify the original array's mask.
This fixes the worst part of the issues addressed in gh-3404, though
there's still an argument that we ought to deprecate the mask-copying
behaviour entirely so that empty_like returns an array with an empty
mask. That can wait until we find someone who cares though.
I also applied a small speedup to np.gradient (avoiding one copy);
previously this inefficiency was masking (heh) some of the problems
with masked arrays, so removing it is both an optimization and makes
it easier to test that things are working now.
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BUG: fix nanmedian on arrays containing inf
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There are two issues:
A masked divide of an infinite value is a masked value which means one
can't use np.ma.mean to compute the median as infinity division is well
defined.
This behaviour seems wrong to me but it also looks intentional so
changing it is not appropriate for a bugfix release.
The second issue is that the ordering of the sorted masked array is
undefined for equal values, the sorting considers infinity the largest
floating point value which is not correct in respect to sorting where
nan is considered larger. This is fixed by changing the
minimum_fill_value to nan for float data in the masked sorts.
Closes gh-5138
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* Previous expected behavior was that the gradient is computed using central
differences in the interior and first differences at the boundaries.
* gradient was updated in v1.9.0 so that second-order accurate calculations are
done at the boundaries, but this breaks expected behavior with old code, so
`edge_order` keyword (Default: 1) is added to specify whether first or second
order calculations at the boundaries should be used.
* Since the second argument is *varargs, in order to maintain compatibility
with old code and compatibility with python 2.6 & 2.7, **kwargs is used, and
all kwargs that are not `edge_order` raise an error, listing the offending
kwargs.
* Tests and documentation updated to reflect this change.
* Added `.. versionadded:: 1.9.1` to the new optional kwarg `edge_order`
documentation, and specified supported `edge_order` kwarg values.
* Clarified documentation for `varargs`.
* Made indentation in docstring consistent with other docstring styles.
* Examples corrected
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The class is no longer used in numpy and was never exported.
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This does what is needed now that the compiler module is no longer
used.
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MAINT: Remove use of compiler module.
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The ast module was added in Python 2.6 as a replacement for the compiler
module. As we no longer support Python versions < 2.6, all uses of the
compiler module can be removed.
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BUG: Fix writing of intrinsic long integers in python2 npy files.
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This only happens when C long is smaller than npy_intp, in particular,
on 64 bit windows. The 'L' suffix is not needed as long as safe_eval
is used to recover the values, and the long intrinsic causes problems
for python3.
The python3 read side has been fixed, but we might as well fix the
problem at the root as well.
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The approach was suggested by Jaime Frio in issue #5179.
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Fix npz header incompatibility
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The Python2 generated file had long integer literals like '1L' that
broke in Python3. The fix here is to filter out the 'L' and let
safe_eval take care of the integer type in converting the string.
The fix here comes from Nathaniel Smith with a few added fixups.
Closes #5170.
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BUG: Make numpy import when run with Python flag '-OO
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This consists of checking for a docstring equal to None and skipping two
tests that require docstrings.
Closes #5148.
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ENH: implement `digitize` with `PyArray_SearchSorted`
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ENH: add subok flag to stride_tricks (and thus broadcast_arrays)
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Closes #5096. Casts integer arrays to np.double, to prevent
integer overflow. Object arrays are left unchanged, to allow
use of arbitrary precision objects.
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The call to `empty_like` was trying to use the `chararray` subclass,
which doesn't support the `np.intp` dtype.
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DOC: warn about using a set with 'in1d'.
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Multiplying a numpy_scalar times a numpy_array is much faster than
the other way around. This PR switches the order of multiplication
in the polyval function resulting in a speedup of about 5x for scalar
values of x.
Closes #4610.
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BUG: Fix np.insert for inserting a single item into a structured array
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Note that there are some object array special cases because of allowing
multiple inserts. `np.array(..., dtype=object)` is not always clear.
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MAINT: Remove references to missing files from install.
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The following directories and files have been moved or deleted
numpy/lib/benchmarks
numpy/f2py/docs
numpy/f2py/f2py.1
This PR removes references to them from the relevant setup.py files.
Closes #5010.
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This replaces a sort with fancy indexing.
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BUG: fix genfromtxt check of converters when using usecols
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fixes an issue reported by Adrian Altenhoff where user-supplied
converters in genfromtxt were not tested with the right first_values
when also specifying usecols.
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Use tempdir for large file
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nobody knows if it supports sparse filesystems, so just skip it.
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NamedTemporaryFile files can't be reopened on Windows.
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BUG: don't overwrite input percentile arrays
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DOC: Fix typo in _iotools.py docstring.
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The error is in the StringConverter.upgrade docstring.
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Charris pep8 numpy lib
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The rules enforced are the same as those used for scipy.
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