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In some cases, the replacement is clearly not what is intended,
in those (where setup was called explicitly), I mostly renamed
`setup` to `_setup`.
The `test_ccompile_opt` is a bit confusing, so left it right now
(this will probably fail)
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Previously we converted matrices to arrays for the user, since
`np.outer` does not make sense for matrix. This deprecates that
usage (which in almost all cases will result in an error).
The main reason for this deprecation is to remove all direct
references of matrix from the NumPy codebase, so that it is
easier to move it out of NumPy eventually.
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MAINT: Python2 Cleanups
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Inheriting from object was necessary for Python 2 compatibility to use
new-style classes. In Python 3, this is unnecessary as there are no
old-style classes.
Dropping the object is more idiomatic Python.
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As numpy is Python 3 only, these import statements are now unnecessary
and don't alter runtime behavior.
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The pickle module was being imported from numpy.core.numeric. It was
defined there in order to use pickle5 when available in Python3 and
cpickle in Python2. The numpy.compat module seems a better place for
that.
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(#12448)
* Review F401,F841,F842 flake8 errors (unused variables, imports)
* Review comments
* More tests in test_installed_npymath_ini
* Review comments
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All imports of pickle from numpy modules are now done this way:
>>> from numpy.core.numeric import pickle
Also, some loops on protocol numbers are added over pickle tests that
were not caught from #12090
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After the pytest migration, test classes no longer inherit
from unittest.TestCase and and the fail method does not
exist anymore.
In all these cases, we can use assert_raises and assert_raises_regex instead
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Pytest < 3.8 ignored warnings issued during test collection, but that
changed in pytest 3.8 and the method NumPy used to suppress the
PendingDeprecationWarning for matrices no longer worked, or rather, was
exposed as not working. The fix here is to suppress the warning in
pytest.ini and pytesttester.py , which should work as long as the tests
are the only places left where NumPy uses matrices.
An alternate fix is to delay the construction of matrices in the tests
until they are actually run, which has the virtue of test localization
but is a bit more complicated.
See https://github.com/pytest-dev/pytest/issues/3945 for discussion.
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Move remaining Matrix tests to matrixlib
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MAINT: move linalg tests using matrix to matrixlib
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This is in preparation for deprecation and eventual removal
of the matrix class.
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The docstring already assumed it was in linalg, and this ensures
linalg becomes completely independent of matrixlib.
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Further progress in isolating matrix in preparation of its
deprecation. There is one place left with an explicit reference
to matrix (in MaskedArray.count), which is to be solved later.
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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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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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Fixes #8459
* DOC: add release note [ci skip]
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Fixes #5837
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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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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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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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