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TST: Show that histogramdd's normed argument is histogram's density
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Relevant to gh-4371
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DOC: Clarify requirement that histogram bins are monotonic.
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Close gh-631
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DEP: Actually deprecate the normed argument to histogram
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Documenting this argument at such length gives it authenticity it does not deserve.
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* update docstring of interp()
* change "calculate" to "evaluate" to be consistent
* remove "values"
* make "data points" consistent
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BUG,MAINT: Ensure masked elements can be tested against nan and inf.
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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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DOC: Fix doctest formatting in `rot90()` examples
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Fixes #11028
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np.ogrid was not tested anyway, so this was not caught.
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ENH: Add (put|take)_along_axis
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This is the reduced version that does not allow any insertion of extra dimensions
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* added function commonpts1d
* Update arraysetops.py
* Update arraysetops.py
* modified intersect1d to return common indices
Proposed this idea in previous pull request (https://github.com/numpy/numpy/pull/10683) and made suggested changes for implementing this idea to have relevant common indices that correspond to the values in the intersection of the two arrays.
* update intersect1d with suggested changes
* implemented return_indices options for intersect1d
I've tested out the above code and for the ~10 different test sets I've tried it's worked thus far. It's probably not the cleanest implementation but it works and is vectorized.
* cleaned up structure for intersect1d
* fixed copy-paste error, added second test, changed a conditional
* Testing return_indices in intersect1d
* formatting
* created separate test function for intersect1d indices, added spaces after commas
* fixed up example and some style
* fixed style
* style change
* removed one example
* removed extra space
* added version number for return_indices
* added 'return_indices' keyword for np.intersect1d
* fixed formatting
* updated return_indices entry
* fixed some typos and style
* added bit about first instance of a value being used
* STY: Fix comment formats
* DOC: missing space
* DOC: correct parameter names in docstring
* made suggested changes
* fixed a mistake from previous update
also added documentation for comm1, comm2 to match doc from np.unique
* added in tests for 2d inputs
* STY: Add missing spaces around commas
* TST: Correct array to actually be unique
* STY: Spaces at beginning of comments
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This makes it a little easier to tell the difference between the prepend and append functions
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This makes `_slice_first` almost a factor of two faster
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Move remaining Matrix tests to matrixlib
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DOC: add numpy.lib.format to docs and link to it
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BUG: np.histogramdd loses precision on its inputs, leading to incorrect results
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This is due to gh-11022.
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Previously a fuzzy rounded comparison was used for the rightmost bin of histogramdd.
It's not clear why this was done, and it resulted in surprising behavior.
This also removes the restriction that bin edges must be floats, and allows integer arrays to be passed (and returned)
Fixes gh-10864
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DOC: create label and ref, fixes broken link
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MAINT: Simplify dimension-juggling in np.pad
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This is safe, because the arguments are always base-class ndarrays, so `keepdims` is guaranteed to be supported
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the dimension in the first place.
`arr[:,:,0,:,:].reshape(arr.shape[:2] + (1,) + arr.shape[3:])` is much more readable as `arr[:,:,0:1,:,:]` (and easier for subclasses to handle)
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The old way of creating the padded array padded with wrong values for
large integers because the new prepended / appended array was implicitly
created with dtype float64:
>>> (np.zeros(1) + (2 ** 64 - 1)).astype(np.uint64)
array([0], np.uint64)
>>> (np.zeros(1) + (2 ** 63 - 1)).astype(np.int64)
array([-9223372036854775808])
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User- and non-user-facing typos.
Some source typos fixes as well.
Found via `codespell`.
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MAINT: Remove unnecessary special case in np.histogramdd for N == 0
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ENH: Quantile
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* fixed doc typo
* fixed lib typos
* fixed lapack_lite typos
* Revert "fixed lapack_lite typos"
This reverts commit e7dada860cb73af190234402508ab79965ecd079.
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TST: Extract a helper function to test for reference cycles
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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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