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-rw-r--r--numpy/core/fromnumeric.py50
1 files changed, 14 insertions, 36 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 3389e7d66..3314e516e 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -25,7 +25,7 @@ __all__ = [
'argmin', 'argpartition', 'argsort', 'around', 'choose', 'clip',
'compress', 'cumprod', 'cumproduct', 'cumsum', 'diagonal', 'mean',
'ndim', 'nonzero', 'partition', 'prod', 'product', 'ptp', 'put',
- 'rank', 'ravel', 'repeat', 'reshape', 'resize', 'round_',
+ 'ravel', 'repeat', 'reshape', 'resize', 'round_',
'searchsorted', 'shape', 'size', 'sometrue', 'sort', 'squeeze',
'std', 'sum', 'swapaxes', 'take', 'trace', 'transpose', 'var',
]
@@ -380,6 +380,7 @@ def choose(a, choices, out=None, mode='raise'):
See Also
--------
ndarray.choose : equivalent method
+ numpy.take_along_axis : Preferable if `choices` is an array
Notes
-----
@@ -908,17 +909,17 @@ def sort(a, axis=-1, kind=None, order=None):
.. versionadded:: 1.12.0
- quicksort has been changed to `introsort <https://en.wikipedia.org/wiki/Introsort>`_.
+ quicksort has been changed to `introsort <https://en.wikipedia.org/wiki/Introsort>`_.
When sorting does not make enough progress it switches to
- `heapsort <https://en.wikipedia.org/wiki/Heapsort>`_.
+ `heapsort <https://en.wikipedia.org/wiki/Heapsort>`_.
This implementation makes quicksort O(n*log(n)) in the worst case.
'stable' automatically chooses the best stable sorting algorithm
- for the data type being sorted.
- It, along with 'mergesort' is currently mapped to
- `timsort <https://en.wikipedia.org/wiki/Timsort>`_
- or `radix sort <https://en.wikipedia.org/wiki/Radix_sort>`_
- depending on the data type.
+ for the data type being sorted.
+ It, along with 'mergesort' is currently mapped to
+ `timsort <https://en.wikipedia.org/wiki/Timsort>`_
+ or `radix sort <https://en.wikipedia.org/wiki/Radix_sort>`_
+ depending on the data type.
API forward compatibility currently limits the
ability to select the implementation and it is hardwired for the different
data types.
@@ -2782,6 +2783,10 @@ def alen(a):
7
"""
+ # NumPy 1.18.0, 2019-08-02
+ warnings.warn(
+ "`np.alen` is deprecated, use `len` instead",
+ DeprecationWarning, stacklevel=2)
try:
return len(a)
except TypeError:
@@ -3414,7 +3419,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue):
instead of a single axis or all the axes as before.
dtype : data-type, optional
Type to use in computing the variance. For arrays of integer type
- the default is `float32`; for arrays of float types it is the same as
+ the default is `float64`; for arrays of float types it is the same as
the array type.
out : ndarray, optional
Alternate output array in which to place the result. It must have
@@ -3573,30 +3578,3 @@ def alltrue(*args, **kwargs):
numpy.all : Equivalent function; see for details.
"""
return all(*args, **kwargs)
-
-
-@array_function_dispatch(_ndim_dispatcher)
-def rank(a):
- """
- Return the number of dimensions of an array.
-
- .. note::
- This function is deprecated in NumPy 1.9 to avoid confusion with
- `numpy.linalg.matrix_rank`. The ``ndim`` attribute or function
- should be used instead.
-
- See Also
- --------
- ndim : equivalent non-deprecated function
-
- Notes
- -----
- In the old Numeric package, `rank` was the term used for the number of
- dimensions, but in NumPy `ndim` is used instead.
- """
- # 2014-04-12, 1.9
- warnings.warn(
- "`rank` is deprecated; use the `ndim` attribute or function instead. "
- "To find the rank of a matrix see `numpy.linalg.matrix_rank`.",
- VisibleDeprecationWarning, stacklevel=3)
- return ndim(a)