| Commit message (Collapse) | Author | Age | Files | Lines |
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Swaps the order to the correct thing and thus
closes gh-23651
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Giving a warning for invalid/overflow in settitem/casts is right
(IMO), however for masked arrays it can be surprising since the
warning is not useful if the value is invalid but also masked.
So, simply blanket ignore the relevant warnings in setitem via errstate.
(There may be some other cases like `.astype()` where it might be
helpful to MA users to just blanket opt-out of these new warnings.)
Closes gh-23000
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Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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Co-authored-by: Charles Harris <charlesr.harris@gmail.com>
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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* DOC: Add example to np.ma.compressed().
* Update example.
* Update core.py
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Fixes #22041
* add regression test and fix for creating a masked array with a
structured dtype; the test is simply for lack of error in the repoducer
* the concern expressed by core team in matching issue was that
`astropy` might be negatively affected; I ran full `astropy` (hash: `c9ad7c56`)
test suite locally with this feature branch and it seemed "ok,"
just 1 unrelated network failure in the network-requiring tests
(`test_ftp_tls_auto`):
```1 failed, 21430 passed, 3490 skipped, 176 xfailed, 23275 warnings in
430.18s (0:07:10)```
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* handle 0-D masked object array deepcopies, with
regression test, based on reviewer feedback
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* the deepcopy of masked array object type now also includes
the components beyond just `_data`; add a related test case
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* guard masked array `__deepcopy__` special object
handling behind `dtype.hasobject`, based on reviewer
feedback
* masked array `__deepcopy__` for object type handling
now deepcopies from `self._data` directly, based on
reviewer feedback
* add a test case for 2D masked array object
deepcopies, since reviewer was not convinced this was
working
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Fixes #22556
Fixes #21022
* add regression test and fix for gh-22556, where
we were relying on the array `copy` arg to deepcopy
a compound object type; I thought about performance issues
here, but if you are already in the land of `object` and
you are explicitly opting in to `deepcopy`, it seems like
performance might be wishful thinking anyway
* add regression test and fix for gh-21022--this one was
weirder but seems possible to sidestep by not trying
to assign a shape of `()` to something that already has
shape `()` and a non-writeable `shape` attribute
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Port CORE diff relevant code to MA and adapt docstrings examples and add tsts.
Closes gh-22465
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* DOC: Add example for np.ma.diag as part of numpy#22269
* Add descriptions to example.
* Fix typo.
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Matplotlib relies on this, so we don't seem to have much of a choice.
I am surprised that we were not notified of the issue before release
time.
Closes gh-22720, gh-22720
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This is the minimal solution to fix gh-22826 with as little change
as possible.
We should fix `getdata()` but I don't want to do that in a bug-fix
release really.
IMO the alternative is to revert gh-22046 which would also revert
the behavior noticed in gh-22720 (which seems less harmful though).
Closes gh-22826
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This PR Closes gh-17046.
The problem was that when calling mask=None, the array creation took seconds compared to the microseconds needed when calling mask=False.
Using `mask=None` is a bit dubious, since it has a different meaning from the default `mask=nomask`, but the speed trap is so hard to find, that it seems pragmatic to support it. OTOH, it also would seem fine to deprecate the whole path (or maybe see if the path can be sped up so that the speed difference isn't forbidding eough to bother).
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DOC: Clarify docstring of `masked_equal` and `masked_values`
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DEP: Deprecate conversion of out-of-bound Python integers
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This wraps the fill value into an array, the default fill value for all
ointegers is 99999 which doesn't work for many integer dtypes.
Note that this might still subtle change the behavior in other
code paths where we cannot avoid this. Plus, the deprecationwarning
may show up (and in fact be a "in the future will use the default
fill value" warning).
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This PR is partially addressing #22269
Added examples for ma.round and ma.round_
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BUG: Make `mask_invalid` consistent with `mask_where` if `copy` is set to `False`
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test for type erroring.
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* Add examples to ma.max function
* indent fix
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
* Indententation fixes
* Indent fixes
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
* Indent fixes
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
* Added example that gives masked array
* fix output indent
* Update numpy/ma/core.py
* Update numpy/ma/core.py
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
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This reverts commit 8cd6f4ca00b6e0da3833fc267d50067b2ddbc069.
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This reverts commit db1a98bf194771a677dbc0c2e06bc47f4a9947a8.
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This reverts commit b8c6d09208ecb7f0d83a8b06ab9e15e720f03730.
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Fixes the problem reported at
https://github.com/numpy/numpy/pull/21977#issuecomment-1186082534
The reduce method here effectively calls itself with an unmasked
MaskedArray (mask=nomask) and then expects either a MaskedArray or
a scalar. This change ensures that an ordinary ndarray is
converted to a MaskedArray, following the pattern already used in
mean and var in this module.
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This enables any ufunc numpy operations that are called on a
MaskedArray to use the masked version of that function automatically
without needing to resort to np.ma.func() calls.
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This enables any ufunc numpy operations that are called on a
MaskedArray to use the masked version of that function automatically
without needing to resort to np.ma.func() calls.
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This defines the comparison operators (other than `==` and `!=`)
explicitly for masked arrays.
The mask is ignored for the resuling `res._data` (unlike `==` and
`!=` which take the mask into account.
Closes gh-21770, although the way that masked arrays propagate the
fill-value seems generally broken and error prone.
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BUG: change `ma.mean` dtype to be consistent with `np.mean`
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These warnings are probably optional in the future. They should
not matter much (since the following is an in-place op), but
the `np.where` could upcast currently!
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* DEP: remove NPY_ARRAY_UPDATEIFCOPY, deprecated in 1.14
* remove more UPDATEIFCOPY
* typo: add missing comma
* remove a few more UPDATEIFCOPY
* Add release note
* remove UPDATEIFCOPY from comment (from review)
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