| Commit message (Collapse) | Author | Age | Files | Lines |
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instead of `import numpy.testing as npt`.
- all of NumPy's own tests themselves use the from-import variant
- There's `import numpy.typing as npt` around in some places so
we should not abbreviate another module import with `npt`.
Optional further enhancement: If this is a convention we also want
users to adopt, this should be mentioned in the module docstring of
`numpy.testing`.
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MAINT: OrderedDict is no longer necessary from Python 3.7
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ENH: Use new argument parsing for array creation functions
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The array creation functions have the most to gain:
1. np.asarray is 4 times faster and commonly used.
2. Other functions are wrapped using __array_function__ in Python
making it more difficult
This commit (unfortunatly) has to do a few things:
* Modify __array_function__ C-side dispatching to accomodate
the fastcall argument convention.
* Move asarray, etc. to C after removing all "fast paths" from
np.array (simplifying the code)
* Fixup imports, since asarray was imported directly in a few places
* Replace some places where `np.array` was probably used for speed
instead of np.asarray or similar. (or by accident in 1 or 2 places)
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... or when the input isn't/cannot be a set. I left a few usages, e.g.
in random sampling, where "set" is reasonable as informal description of
an array as the order doesn't matter; however, for e.g. np.gradient the
order of the returned list is clearly important, so "set" is wrong.
Also some other minor doc edits noticed during the grepping: using
`shape` instead of `form` in `cov` is consistent with most other places;
the wording in `Polynomial.trim` now matches other methods on the same
class.
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DEP: deprecate np.testing.dec
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Since the decorators in np.testing.dec are intended for nose test framework
support, deprecate them by updating the docstring and adding a warning when
they are used on functions
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This update a coupe of references (single backticks) that actually are not to
verbatim/code (double backticks); and a couple of verbatim to reference
when they do actually exists and can be resolved in context.
I probably missed other; and stayed simple but spoted a few other
inconsistencies that I did not fix:
- some ``...`` could actually be :math:`...` but not always clear if
it would be better.
- some intervals are [``...``], other are ``[...]``
I guess they could be discussed individually; it was mostly the failing
references that bothered me.
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* ENH: Add traceback-skip to `assert_array_compare`
* TST: Add tests for arraycoercion
These tests have many xfails (some technically maybe not correct),
which describe in detail what will change when merging the
array-coercion changes; since all of those xfails are going
to be removed.
* TST: Add test for empty sequences
* TST: Add tests for bad self-mutating sequence inputs to np.array
These should never happen and rightly should lead to undefined
behaviour (and preferably errors), but they excercise some more
tricky code branches and should probably not crash.
* Simplify the "all scalars" logic (hardcode) and fix complex cases
* MAINT: Some cleanup, and xfail pypy
PyPy seems to have issues with int(numpy_complex), maybe because
it gives a warning during conversion (python does not define it).
So simply mark it as xfail, it should work in my branch.
Also some smaller cleanups.
* TST: Add some further test, re-add missing rational
* MAINT: Make rationals optional, because they fail some tests currently
The failures will go away, since this must again be related to
implemetning int() and float().
* Update numpy/conftest.py
* MAINT: Fix strings and use pytest.param to clean things up
* TST: Add tests for 0-D array-like input to np.array() corner-cases
* TST: Improve parameterization IDs to get better printing at -vv
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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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Add missing closing brackets, script to generate the list in the PR gh-16051.
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* Cleanup unused imports (F401) of mostly standard Python modules,
or some internal but unlikely referenced modules
* Where internal imports are potentially used, mark with noqa
* Avoid redefinition of imports (F811)
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* PEP 8: "Imports should usually be on separate lines"
* Where modified, sort imported modules alphabetically
* Clean-up unused imports from these expanded lines
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This PR uses simple cases of PEP 380 to rewrite:
for v in g:
yield v
into:
yield from <expr>
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This replaces basestring with str except in
- tools/npy_tempita/
- numpy/compat/py3k.py
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MAINT: cleanup sys.version dependant code
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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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MAINT: Implement keyword-only arguments as syntax
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Now that 2.7 is gone, there is no need to pop manually from kwarg dictionaries.
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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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TST: improve assert message of assert_array_max_ulp
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It was not showing the max difference before, which makes it
hard to judge whether something is seriously wrong, or the test
precision simply needs to be bumped by a little.
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