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This PR adds an implementation of `nancumsum` and `nancumprod`.
The actual function is a two-liner adapted from `nansum`.
Its structure is adapted from PR: https://github.com/numpy/numpy/pull/5418/
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TST: Add test for #6469
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Removed superfluous `ceil` call in automated bin width estimator.
Updated tests to reflect modified estimator.
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Described ad nauseum the relationship between `range` parameter and bin estimation.
Updated formulas for estimators now that they are returning bin widths.
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Fixes #7411. Tests and documentation updated.
Fixes other small issues with range and bin count computations.
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Fixes bug in string copying in np.place
in which replacements strings that were
smaller than their replaced elements
would only partially replace the element
instead of the entire element.
Closes gh-6974.
Addendum: this commit also appears to have
fixed issue with overflow for very large
input arrays.
Closes gh-7207.
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Tweak corrcoef
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This doesn't actually test much, as we don't have any inputs where that
was not already the case. But at least it is there and perhaps a fuzz
test can be added at a later date.
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The non-nan elements of the result of corrcoef should satisfy the
inequality abs(x) <= 1 and the non-nan elements of the diagonal should
be exactly one. We can't guarantee those results due to roundoff, but
clipping the real and imaginary parts to the interval [-1, 1] improves
things to a small degree.
Closes #7392.
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The input arrays are documented to have ndim <=2, so check for that
and raise a ValueError on failure.
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Generalized flip
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Found this while reading a docstring.
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TST: fix #6542, add tests to check non-iterable argument raises in hstack and related functions.
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...to hstack, vstack, stack,
hsplit, vsplit, dsplit, dstack
that check that they raise exceptions.
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Constant padding on 4 sides of a 2d array expected a numpy ndarray, and not a ndarray like (tuple, list, ...)
Detailed description is in the issue #7353
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This test exposes padding bug described in the issue #7353
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This is just me being OCD. I am not sure this even merits a full commit, much less a PR, but here goes anyway.
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MAINT: Cleanup for histogram bin estimator selection
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Private function with superfluous checks was removed. Estimator
Estimator functions are now semi-public and selection is simplified
within histogram itself.
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Since shuffle only works along the first dimension, it must be done before
reshape to get reasonable looking data. Did not affect the current tests. I
noticed while working on some scipy code.
Also, made a couple of doc changes to np.random.shuffle.
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Closes gh-7113.
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Closes gh-7269.
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The missing whitespace lead to inconsistent rendering in the
online documentation. [ci skip]
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number of bins and associated tests
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DEP: Deprecate as_strided returning a writable array as default
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savez: temporary file alongside with target file and improve exception message upon IOError
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Closes: gh-5336
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change test from `type(a) is not mu.ndarray` to
`not isinstance(a, mu.ndarray)`
Because every sub-class of ndarray is not guaranteed to implement
`keepdims` as a kwarg, when wrapping these methods care must be taken.
The previous behavior was to silently eat the kwarg when dealing with
a sub-class of ndarray.
Now, if `keepdims=np._NoValue` (the new default) it is not passed
through to the underlying function call (so the default value of
`keepdims` is now controlled by the sub-class). If `keepdims` is not
`np._NoValue` then it is passed through and will raise an exception if
the sub-class does not support the kwarg.
A special case in nanvar was required to deal with `matrix` that previously
relied on `fromnumeric` silently dropping `keepdims`.
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DOC: Updated minor typos in function_base.py and test_function_base.py
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BUG: Fixed previous attempt to fix dimension mismatch in nanpercentile
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nanpercentile was conforming to dimension convention of percentile incorrectly.
percentile outputs results for the different percentiles along the first
dimension of the output. nanpercentile was moving the reduction axis to the
front using swapaxes, which would move the first axis out of place if there
were more than two in the array. Added a test with more than two axes to
demonstrate and used rollaxis instead of swapaxes to do the interhange.
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