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authorAaron Meurer <asmeurer@gmail.com>2021-03-02 16:29:07 -0700
committerAaron Meurer <asmeurer@gmail.com>2021-03-02 16:29:07 -0700
commit7132764661b01e2f15a66d7c39d74ad4b2d434a9 (patch)
tree90a3dcbb52452f84ca67de8a7c1eb9eb44e8b6d9 /numpy/_array_api/_statistical_functions.py
parent63be085194ddf9d2d8fc32a0ccbe30936c78d870 (diff)
downloadnumpy-7132764661b01e2f15a66d7c39d74ad4b2d434a9.tar.gz
Remove _implementation from the array API functions
As discussed at https://mail.python.org/pipermail/numpy-discussion/2021-February/081541.html, _implementation is not as useful for the array API module as previously thought.
Diffstat (limited to 'numpy/_array_api/_statistical_functions.py')
-rw-r--r--numpy/_array_api/_statistical_functions.py14
1 files changed, 7 insertions, 7 deletions
diff --git a/numpy/_array_api/_statistical_functions.py b/numpy/_array_api/_statistical_functions.py
index 79bc125dc..e62410d01 100644
--- a/numpy/_array_api/_statistical_functions.py
+++ b/numpy/_array_api/_statistical_functions.py
@@ -5,24 +5,24 @@ from ._types import Optional, Tuple, Union, array
import numpy as np
def max(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array:
- return np.max._implementation(x, axis=axis, keepdims=keepdims)
+ return np.max(x, axis=axis, keepdims=keepdims)
def mean(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array:
- return np.asarray(np.mean._implementation(x, axis=axis, keepdims=keepdims))
+ return np.asarray(np.mean(x, axis=axis, keepdims=keepdims))
def min(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array:
- return np.min._implementation(x, axis=axis, keepdims=keepdims)
+ return np.min(x, axis=axis, keepdims=keepdims)
def prod(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array:
- return np.asarray(np.prod._implementation(x, axis=axis, keepdims=keepdims))
+ return np.asarray(np.prod(x, axis=axis, keepdims=keepdims))
def std(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, correction: Union[int, float] = 0.0, keepdims: bool = False) -> array:
# Note: the keyword argument correction is different here
- return np.asarray(np.std._implementation(x, axis=axis, ddof=correction, keepdims=keepdims))
+ return np.asarray(np.std(x, axis=axis, ddof=correction, keepdims=keepdims))
def sum(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array:
- return np.asarray(np.sum._implementation(x, axis=axis, keepdims=keepdims))
+ return np.asarray(np.sum(x, axis=axis, keepdims=keepdims))
def var(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, correction: Union[int, float] = 0.0, keepdims: bool = False) -> array:
# Note: the keyword argument correction is different here
- return np.asarray(np.var._implementation(x, axis=axis, ddof=correction, keepdims=keepdims))
+ return np.asarray(np.var(x, axis=axis, ddof=correction, keepdims=keepdims))