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Move test_ignore_nan_ulperror to `numpy/testing/tests/test_utils.py
and extend to all floating types.
Closes 16600.
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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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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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* MAINT: only treat 0d case separately in randint, simplify some tests
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Fixed maximum relative error reporting in assert_allclose:
In cases where the two arrays have zeros at the same positions it will
no longer report nan as the max relative error
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The original message included "Mismatch: 33.3%". It's not obvious what this
percentage means. This commit changes the text to
"Mismatched elements: 1 / 3 (33.3%)".
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MAINT: revert __skip_array_function__ from NEP-18
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- Always enable __array_function__ overrides.
- Remove special cases for Python 2 compatibility.
- Document these changes in 1.17.0-notes.rst.
It will be good to see ASV numbers to understand the performance implications
of these changes. If need be, we can speed up NumPy functions internally by
using non-dispatched functions (with ``.__wrapped__``).
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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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(#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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BUG: Fix misleading assert message in assert_almost_equal #12200
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Fixes #12200 by making a copy of the matrix before NaN's are excluded.
Add a test for it.
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* ENH: __array_function__ support for np.lib, part 2
xref GH12028
np.lib.npyio through np.lib.ufunclike
* Fix failures in numpy/core/tests/test_overrides.py
* CLN: handle depreaction in dispatchers for np.lib.ufunclike
* CLN: fewer dispatchers in lib.twodim_base
* CLN: fewer dispatchers in lib.shape_base
* CLN: more dispatcher consolidation
* BUG: fix test failure
* Use all method instead of function in assert_equal
* DOC: indicate n is array_like in scimath.logn
* MAINT: updates per review
* MAINT: more conservative changes in assert_array_equal
* MAINT: add back in comment
* MAINT: casting tweaks in assert_array_equal
* MAINT: fixes and tests for assert_array_equal on subclasses
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* previously, stochastic failures were possible
when running the NumPy test suite in parallel
because of an assumption made by assert_warn_len_equal()
* we now guard against this failure by gracefully
handling the testing contexts of both serial and
parallel execution of the module
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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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This brought to light two bugs in tests, which are fixed here, viz.,
that a sample ndarray subclass that tested propagation of an added
parameter was incomplete, in that in propagating the parameter in
__array_wrap__ it assumed it was there on self, but that assumption
could be broken when a view of self was taken (as is done by
x[~flagged] in the test routine), since there was no
__array_finalize__ defined.
The other subclass bug counted, incorrectly, on only needing to provide
one type of comparison, the __lt__ being explicitly tested. But flags
are compared with __eq__ and those flags will have the same subclass.
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The removal of nan and inf from arrays that are compared using
test routines like assert_array_equal treated the two arrays
separately, which for masked arrays meant that some elements would
not be removed when they should have been. This PR corrects this.
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The underlying problem is that ma.all() evaluates to masked,
which is falsy, and thus triggers test failures.
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It's not always possible to guarantee this, so also adds a test to verify that we don't hang
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This also means we can now test that our test is actually able to detect the type of failure we expect
Trying to give myself some tools to debug the failure at https://github.com/numpy/numpy/pull/10882/files#r180813166
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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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Use standard pytest markers everywhere in the numpy tests. At this point
there should be no nose dependency. However, nose is required to test
the legacy decorators if so desired.
At this point, numpy test cannot be run in the way with runtests, rather
installed numpy can be tested with `pytest --pyargs numpy` as long as
that is not run from the repo. Run it from the tools directory or some
such.
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This removes a few left over uses of unittest. The main changes apart
from removal of Test case are:
* `setUp` replaced by nose and pytest compatible `setup`
* `tearDown` replaced by nose and pytest compatible `teardown`
* `assertRaises` replaced by `assert_raises`
* `assertEqual` replaced by `assert_equal`
The last two are in `numpy/testings/tests/test_utils.py`, so may seem a
but circular, but at least are limited to those two functions.
The use of `setup` and `teardown`, can be fixed up with the pytest
equivalents after we have switched to pytest.
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The contents of the module warnings registries was made more module
specific in Python 3.7 and consequently the tests of the context
managers clear_and_catch_warnings and suppress_warnings need updating.
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Now:
* Has one recursive base case
* Is fewer lines of code
* Does not rstrip the result of format_function (none of the builtin ones have trailing spaces anyway)
* Recurses in the index, instead of the value, which handles `dtype=object` arrays without the need for the rank argument. This fixes #8442.
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This essentially reverts 83accefd143a0e3ee8b3160d0927b3ff616743de, which presumably worked around a bug in an ancient version of python
Similarly, the try/excepts here were to handle `IntegerFormatter` being called on the wrong type of array, which no longer happens
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Also does some cleanup on the float assert_equal to make it look more similar.
Fixes #10081
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ENH: enable OpenBLAS on windows.
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use the correct replace() order
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Allow the error message to contain "large" arrays.
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1. fail tests related to DLL load failure as they were previously untested.
2. fix have_compiler to return false on old compilers
3. xfail some tests that were not working on old Python versions.
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This is the case for x in {int, bool, str, float, complex, object}.
Using the np.{x} version is deceptive as it suggests that there is a
difference. This change doesn't affect any external behaviour. The
`long` type is missing in python 3, so np.long is still useful
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