| Commit message (Collapse) | Author | Age | Files | Lines |
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That function is nose specific and has not worked since `__init__` files
were added to the tests directories.
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Numpy can now be tested using the standard
`python -c"import numpy; numpy.test()"`
construct.
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The "bench" testing with the old bench files is no longer supported.
These days we use `runtests.py` and `asv`.
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Found via `codespell -q 3 -I ../numpy-whitelist.txt`
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Abstract collection classes accessed from the collections module
have been deprecated since Python 3.3. They should be
accessed through collections.abc. When run with Python
3.7, the deprecation warning cause multiple tests to
fail.
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This allows pytest to run with duplicate test file names. Note that
`python <path-to-test-file>` no longer works with this change, nor will
a simple `pytest numpy`, because numpy is imported from the numpy
repository. However, `python runtests.py` and `>>> numpy.test()` are
still available.
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BUG: issubdtype is inconsistent on types and dtypes
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Fixes gh-9506, unsigned exponentiation
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I don't know what that argument was used for, but it showis up in old
tests and is not explicitly used within the tests. I assume it was part
of an old testing framework and is now longer needed.
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The aim here is to separate out the nose dependent files prior to adding
pytest support. This could be done by adding new files to the general
numpy/testing directory, but I felt that it was to have the relevant
files separated out as it makes it easier to completely remove nose
dependencies when needed.
Many places were accessing submodules in numpy/testing directly, and in
some cases incorrectly. That presented a backwards compatibility
problem. The solution adapted here is to have "dummy" files whose
contents will depend on whether of not pytest is active. That way the
module looks the same as before from the outside.
In the case of numpy itself, direct accesses have been fixed. Having
proper `__all__` lists in the submodules helped in that.
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Bare except is very rarely the right thing
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Based on feedback in #7768
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Fixes #8459
* DOC: add release note [ci skip]
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[ci skip]
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[ci skip]
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Closes gh-6863.
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The bug traces to the PyArray_OrderConverter
method in conversion_utils.c, where no errors
are thrown if the ORDER parameter passed in
is not of the string data-type or has a string
value of length greater than one. This commit
causes a DeprecationWarning to be raised, which
will later be turned into a TypeError or another
type of error in a future release.
Closes gh-6598.
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Fixes #5837
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Fixed typos in docstrings were updated for functions where the parameter
names in the docstring didn't match the function signature.
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This is a backward compatibility hack to avoid breaking scipy.sparse
after fixing ravel to respect subtypes. Subtypes are still respected
except in the case of matrices and subclasses of matrices.
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This is an ugly hack to preserve backwards compatibility for code
that uses matrices. It is needed since both diag and diagonal have
been changed to preserve subtypes otherwise.
Note that a.diagonal() still returns matrices when a is a matrix.
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In PR #5358, np.diagonal was modified to return whatever array type it took in.
Also, np.cumsum and np.clip return the same array type. So, np.ravel's behavior is surprising.
Two tests which were expecting np.ravel to return an array have been changed.
Also, the optional `order` parameter was added to MaskedArray.ravel to make it compatible
(matrix.ravel already had this parameter).
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If x is a matrix, np.diag(x) and np.diagonal(x) now return matrices
instead of arrays. Both of these cause x.diagonal() to be called.
That means they return row vectors (just like x.flatten(), x.ravel(),
x.cumprod(), etc.)
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allows passing flags like --pdb to test files
also add call to files where its missing
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DOC: clarify matrix.ravel docstring and add tests
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tostring returns bytes which are not equal to string, so provide a
tobytes function alias.
tostring does not emit a deprecation warning yet so rdepends do not need
to check two names to support older versions of numpy without warnings.
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Closes gh-1939.
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Run the 2to3 ws_comma fixer on *.py files. Some lines are now too long
and will need to be broken at some point. OTOH, some lines were already
too long and need to be broken at some point. Now seems as good a time
as any to do this with open PRs at a minimum.
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Now is as good a time as any with open PR's at a low.
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A partition sorts the kth element into its sorted order and moves all
smaller elements before the kth element and all equal or greater
elements behind it.
The ordering of all elements in the partitions is undefined.
It is implemented via the introselection algorithm which has worst case
linear complexity compared to a full sort that has linearithmic
complexity.
The introselect algorithm uses a quickselect with median of three pivot
and falls back to a quickselect with median of median of five pivot if
no sufficient progress is made.
The pivots used during the search for the wanted kth element can
optionally be stored and reused for further partitionings of the array.
This is used by the python interface if an array of kth is provided to
the partitions function. This improves the performance of median and
which need to select two elements if the size of the array is even. A
percentile function interpolating between values also profits from this.
String selection is implemented in terms of quicksort which has the same
properties as a selection for now.
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The numpy.matrix constructor uses eval(str.translate(table)) to convert
input strings to numeric matrix contents. str.translate(table) will
return empty string if str consists only of invalid characters, causing
SyntaxError in eval(). This is confusing, as one would expect an
exception like TypeError when trying to construct a matrix from invalid
input.
This fix makes sure eval() is only called if str is not empty and
TypeError is raised otherwise.
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