File python-ndindex.changes of Package failed_python-ndindex
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Sun Mar 24 09:22:54 UTC 2024 - Dirk Müller <dmueller@suse.com>
- update to 1.8:
* Breaking broadcast_shapes() no longer returns None in the place
of skipped axes. The result is now just the non-skipped axes
broadcasted together.
* The skip_axes flag to iter_indices() and broadcast_shapes() can
now be a list of tuples, of skipped axes, which apply to each
respective shape independently.
* Mixing negative and nonnegative skip_axes in iter_indices() and
broadcast_shapes() is now supported. The only restriction is
that skip axes must refer to unique dimensions for each shape.
* New index method selected_indices(), which iterates indices
corresponding to each element selected by the given index on an
array of a given shape.
* ndindex indices can now be constructed by slicing the ndindex()
constructor function, like ndindex[0:10]. This is generally
preferred for indices with explicit slices, as this allows using
the usual : slice syntax instead of requiring slices to be spelled
out with the slice function.
* Add a negative_int flag to reduce, which makes it normalize
integer indices to negative integers when a shape is provided.
* Slice objects now hash to the same hash value as their
corresponding raw slice in Python 3.12, which now allows native
slice objects to be hashed.
* Fix an incorrect result from ChunkSize.as_subchunks() and
ChunkSize.num_subchunks() when using multiple array indices or a
boolean array index with multiple dimensions.
- drop ndindex-pr159-py312.patch (upstream)
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Wed Feb 7 09:59:37 UTC 2024 - Ben Greiner <code@bnavigator.de>
- Update to 1.7
* Breaking: the skip_axes argument iter_indices() function now
applies the skipped axes before broadcasting, not after. This
behavior is more generally useful and matches how functions
with stacking work (e.g., np.cross or np.matmul). The best way
to get the old behavior is to broadcast the arrays/shapes
together first. The skip_axes in iter_indices must be either
all negative or all nonnegative to avoid ambiguity. A future
version may add support for specifying different skip axes for
each shape.
* iter_indices() no longer requires the skipped axes specified by
skip_axes to be broadcast compatible.
* New method isvalid() to check if an index is valid on a given
shape.
* New function broadcast_shapes() which is the same as
np.broadcast_shapes() except it also allows specifying a set of
skip_axes which will be ignored when broadcasting.
* New exceptions BroadcastError and AxisError which are used by
iter_indices() and broadcast_shapes().
* Fix some test failures with the latest version of NumPy.
* Fix some tests that didn’t work properly when run against the
* sdist.
* The sdist now includes relevant testing files.
- Drop patches fixed upstream
* ndindex-pr133-ragged.patch gh#Quansight-Labs/ndindex#133
* ndindex-pr147-numpy.patch gh#Quansight-Labs/ndindex#147
- Refresh custom-pytest.patch gh#Quansight-Labs/ndindex#150
- Add ndindex-pr159-py312.patch gh#Quansight-Labs/ndindex#159
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Fri Mar 31 09:06:35 UTC 2023 - Ben Greiner <code@bnavigator.de>
- Skip a flaky test in i586
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Thu Mar 30 15:20:45 UTC 2023 - Ben Greiner <code@bnavigator.de>
- Initial specfile for v1.6
- Required by python-blosc2 2.1.1
- Add ndindex-pr133-ragged.patch gh#Quansight-Labs/ndindex#133
- Add ndindex-pr147-numpy.patch gh#Quansight-Labs/ndindex#147
- Add custom-pytest.patch
