diff options
Diffstat (limited to 'numpy/_array_api/_statistical_functions.py')
| -rw-r--r-- | numpy/_array_api/_statistical_functions.py | 18 |
1 files changed, 11 insertions, 7 deletions
diff --git a/numpy/_array_api/_statistical_functions.py b/numpy/_array_api/_statistical_functions.py index 833c47f66..020053896 100644 --- a/numpy/_array_api/_statistical_functions.py +++ b/numpy/_array_api/_statistical_functions.py @@ -1,24 +1,28 @@ +from __future__ import annotations + +from ._types import Optional, Tuple, Union, array + import numpy as np -def max(x, /, *, axis=None, keepdims=False): +def max(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: return np.max(x, axis=axis, keepdims=keepdims) -def mean(x, /, *, axis=None, keepdims=False): +def mean(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: return np.mean(x, axis=axis, keepdims=keepdims) -def min(x, /, *, axis=None, keepdims=False): +def min(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: return np.min(x, axis=axis, keepdims=keepdims) -def prod(x, /, *, axis=None, keepdims=False): +def prod(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: return np.prod(x, axis=axis, keepdims=keepdims) -def std(x, /, *, axis=None, correction=0.0, keepdims=False): +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.std(x, axis=axis, ddof=correction, keepdims=keepdims) -def sum(x, /, *, axis=None, keepdims=False): +def sum(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keepdims: bool = False) -> array: return np.sum(x, axis=axis, keepdims=keepdims) -def var(x, /, *, axis=None, correction=0.0, keepdims=False): +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.var(x, axis=axis, ddof=correction, keepdims=keepdims) |