8000 Make AdvancedNew iter more 0-d aware by seberg · Pull Request #3104 · numpy/numpy · GitHub
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Make AdvancedNew iter more 0-d aware #3104

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Merged
merged 8 commits into from
Apr 1, 2013
Merged

Make AdvancedNew iter more 0-d aware #3104

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2e8fcc0
API: Make nditer support ndim == 0 for 0-d iterations.
seberg Feb 23, 2013
acce195
ENH: Allow np.nditer to support scalar op_axes
seberg Feb 26, 2013
c11fa49
TST: Add basic tests for 0-d np.nditer/np.nested_iter support
seberg Mar 1, 2013
610faef
TST: Add test that einsum multiplies scalars fine
seberg Mar 1, 2013
22e1fe4
MAINT: Remove np.ndindex 0-d hack.
seberg Feb 23, 2013
b66a15e
DOC: Add documentation clarifying the use of oa_ndim
seberg Mar 1, 2013
20f44ef
DOC: mention AdvancedNew iterator change in the release notes.
seberg Mar 1, 2013
aa4d003
MAINT: Remove 0-d iterator special case from ufunc_object.c
seberg Mar 2, 2013
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DOC: Add documentation clarifying the use of oa_ndim
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@seberg
seberg committed Mar 3, 2013
commit b66a15e0985eb809f735fb47e3d0ea6317f86406
11 changes: 8 additions & 3 deletions doc/source/reference/c-api.iterator.rst
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Expand Up @@ -634,12 +634,12 @@ Construction and Destruction
Extends :cfunc:`NpyIter_MultiNew` with several advanced options providing
more control over broadcasting and buffering.

If 0/NULL values are passed to ``oa_ndim``, ``op_axes``, ``itershape``,
If -1/NULL values are passed to ``oa_ndim``, ``op_axes``, ``itershape``,
and ``buffersize``, it is equivalent to :cfunc:`NpyIter_MultiNew`.

The parameter ``oa_ndim``, when non-zero, specifies the number of
The parameter ``oa_ndim``, when not zero or -1, specifies the number of
dimensions that will be iterated with customized broadcasting.
If it is provided, ``op_axes`` and/or ``itershape`` must also be provided.
If it is provided, ``op_axes`` must and ``itershape`` can also be provided.
The ``op_axes`` parameter let you control in detail how the
axes of the operand arrays get matched together and iterated.
In ``op_axes``, you must provide an array of ``nop`` pointers
Expand All @@ -649,6 +649,11 @@ Construction and Destruction
-1 which means ``newaxis``. Within each ``op_axes[j]`` array, axes
may not be repeated. The following example is how normal broadcasting
applies to a 3-D array, a 2-D array, a 1-D array and a scalar.

**Note**: Before NumPy 1.8 ``oa_ndim == 0` was used for signalling that
that ``op_axes`` and ``itershape`` are unused. This is deprecated and
should be replaced with -1. Better backward compatibility may be
achieved by using :cfunc:`NpyIter_MultiNew` for this case.

.. code-block:: c

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