8000 MAINT: let average preserve subclass information. by mhvk · Pull Request #8290 · numpy/numpy · GitHub
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MAINT: let average preserve subclass information. #8290

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merged 1 commit into from
Nov 19, 2016
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MAINT: let average preserve subclass information. #8290

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12 changes: 12 additions & 0 deletions doc/release/1.13.0-notes.rst
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Expand Up @@ -33,6 +33,11 @@ DeprecationWarning to error
FutureWarning to changed behavior
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

* ``numpy.average`` now preserves subclasses, matching the behavior of most
other numpy functions such as ``mean``. As a consequence, also calls that
returned a scalar may now return a subclass array scalar.


C API
~~~~~

Expand All @@ -53,3 +58,10 @@ Improvements

Changes
=======

``average`` now preserves subclasses
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
8000 For ndarray subclasses, ``numpy.average`` will now return an instance of the
subclass, matching the behavior of most other numpy functions such as ``mean``.
As a consequence, also calls that returned a scalar may now return a subclass
array scalar.
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Could you also add something under Compatibility notes? If you look In the 1.12 notes there is a subsection FutureWarning to changed behavior that has a list of changes.

14 changes: 1 addition & 13 deletions numpy/lib/function_base.py
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Expand Up @@ -1092,19 +1092,7 @@ def average(a, axis=None, weights=None, returned=False):
TypeError: Axis must be specified when shapes of a and weights differ.

"""
# 3/19/2016 1.12.0:
# replace the next few lines with "a = np.asanyarray(a)"
if (type(a) not in (np.ndarray, np.matrix) and
issubclass(type(a), np.ndarray)):
warnings.warn("np.average currently does not preserve subclasses, but "
"will do so in the future to match the behavior of most "
"other numpy functions such as np.mean. In particular, "
"this means calls which returned a scalar may return a "
"0-d subclass object instead.",
FutureWarning, stacklevel=2)

if not isinstance(a, np.matrix):
a = np.asarray(a)
a = np.asanyarray(a)

if weights is None:
avg = a.mean(axis)
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7 changes: 2 additions & 5 deletions numpy/lib/tests/test_function_base.py
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Expand Up @@ -321,11 +321,8 @@ class subclass(np.ndarray):
a = np.array([[1,2],[3,4]]).view(subclass)
w = np.array([[1,2],[3,4]]).view(subclass)

with suppress_warnings() as sup:
# Note that the warning is spurious, because the test checks
# for weights while a is ignored.
sup.filter(FutureWarning, "np.average currently does not preserve")
assert_equal(type(np.average(a, weights=w)), subclass)
assert_equal(type(np.average(a)), subclass)
assert_equal(type(np.average(a, weights=w)), subclass)

# also test matrices
a = np.matrix([[1,2],[3,4]])
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0