| Commit message (Collapse) | Author | Age | Files | Lines |
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* DOC: Fixes for 18 broken links
This, with PR #16465, should fix nearly all the remaining broken links
on the site. 4 or 5 others should be easy to fix and just
need attention from someone more knowledgeable -- will
open an issue. For release notes with dead links,
I could usually find links on archive.org for roughly contemporary
versions.
* DOC: Update to "Fixes for 18 broken links #16472"
* Obsolete links, previously commented out, now deleted:
https://github.com/numpy/numpy/pull/16472#discussion_r433928958
* Semantic markup for reference to Python class:
https://github.com/numpy/numpy/pull/16472#discussion_r433553928
* Missing :ref: in internal link:
https://github.com/numpy/numpy/pull/16472#discussion_r433554484
Not included: Resolution on using external/internal doc link in .py:
https://github.com/numpy/numpy/pull/16472#discussion_r433554824
* DOC: Add internal link for 'Fixes for 18 broken links' PR #16472
Making reference [1] an internal link in function_base.py => numpy.vectorize.html
* DOC: Redirect 2 link fixes in PR #16472
* governance.rst link reverted
* ununcs.rst `overridden` link goes where it was meant to
per https://github.com/numpy/numpy/pull/16472#pullrequestreview-424666070
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This replaces basestring with str except in
- tools/npy_tempita/
- numpy/compat/py3k.py
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These implemented the __getslice__ and __setslice__ methods in Python 2, which no longer exist in Python 3.
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sys.exc_clear() was removed in Python 3. All internal uses can be
removed.
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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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Example behavior:
>>> x = np.array([1, 2, 3])
>>> y = np.array([1, 2, 3.0001])
>>> np.testing.assert_allclose(x, y)
AssertionError:
Not equal to tolerance rtol=1e-07, atol=0
Mismatch: 33.3%
Max absolute difference: 0.0001
Max relative difference: 3.33322223e-05
x: array([1, 2, 3])
y: array([1. , 2. , 3.0001])
Motivation: when writing numerical algorithms, I frequently find myself
experimenting to pick the right value of `atol` and `rtol` for
`np.testing.assert_allclose()`. If I make the tolerance too generous, I risk
missing regressions in accuracy, so I usually try to pick the smallest values
for which tests pass. This change immediately reveals appropriate values to
use for these parameters, so I don't need to guess and check.
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This is to prepare for the switch to pytest.
* Rename `numpy/testing/nose_tools` to `numpy/testing/_private`.
* Redirect imports as needed.
* Copy `_testutils.py` from scipy to `numpy/testing/_private`.
* Rename `_testutils.py` to `_pytester.py` and remove unneeded bits.
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