8000 ENH: add signature argument to vectorize for vectorizing like generalized ufuncs by shoyer · Pull Request #8054 · numpy/numpy · GitHub
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ENH: add signature argument to vectorize for vectorizing like generalized ufuncs #8054

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Merged
merged 6 commits into from
Oct 18, 2016
Merged

ENH: add signature argument to vectorize for vectorizing like generalized ufuncs #8054

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77e7ff8
ENH: add signature argument to vectorize for generalized ufuncs
shoyer Sep 15, 2016
1678a72
Use str.format rather than %
shoyer Oct 3, 2016
7d14629
Fix spelling typo
shoyer Oct 11, 2016
0498f28
BUG: fix np.vectorize for size 0 inputs
shoyer Oct 11, 2016
6d2a998
DOC: add vectorize to 1.12.0 release notes
shoyer Oct 14, 2016
138cbd3
[ci-skip] Remove outdated comment
shoyer Oct 17, 2016
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11 changes: 11 additions & 0 deletions doc/release/1.12.0-notes.rst
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Expand Up @@ -7,6 +7,7 @@ Highlights
==========

* Order of operations in ``np.einsum`` now can be optimized for large speed improvements.
* New ``signature`` argument to ``np.vectorize`` for vectorizing with core dimensions.

Dropped Support
===============
Expand Down Expand Up @@ -328,6 +329,16 @@ an intermediate array to reduce this scaling to ``N^3`` or effectively
been applied to the general einsum summation notation. See ``np.einsum_path``
for more details.

New ``signature`` argument to ``np.vectorize``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This argument allows for vectorizing user defined functions with core
dimensions, in the style of NumPy's
:ref:`generalized universal functions<c-api.generalized-ufuncs>`. This allows
for vectorizing a much broader class of functions. For example, an arbitrary
distance metric that combines two vectors to produce a scalar could be
vectorized with ``signature='(n),(n)->()'``. See ``np.vectorize`` for full
details.

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=======

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2 changes: 2 additions & 0 deletions doc/source/reference/c-api.generalized-ufuncs.rst
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8000
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@@ -1,3 +1,5 @@
.. _c-api.generalized-ufuncs:
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I'd like to add a reference to this doc page from the docstring for guvectorize. Do we have a standard way to do that? I guess a URL under "References" is probably most robust, though I was thinking a sphinx reference might work...


==================================
Generalized Universal Function API
==================================
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