diff options
Diffstat (limited to 'numpy/core/fromnumeric.py')
| -rw-r--r-- | numpy/core/fromnumeric.py | 111 |
1 files changed, 91 insertions, 20 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 6a7690c94..d65e26827 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -2248,12 +2248,13 @@ def sum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, initial=initial, where=where) -def _any_dispatcher(a, axis=None, out=None, keepdims=None): - return (a, out) +def _any_dispatcher(a, axis=None, out=None, keepdims=None, *, + where=np._NoValue): + return (a, where, out) @array_function_dispatch(_any_dispatcher) -def any(a, axis=None, out=None, keepdims=np._NoValue): +def any(a, axis=None, out=None, keepdims=np._NoValue, *, where=np._NoValue): """ Test whether any array element along a given axis evaluates to True. @@ -2291,6 +2292,12 @@ def any(a, axis=None, out=None, keepdims=np._NoValue): sub-class' method does not implement `keepdims` any exceptions will be raised. + where : array_like of bool, optional + Elements to include in checking for any `True` values. + See `~numpy.ufunc.reduce` for details. + + .. versionadded:: 1.20.0 + Returns ------- any : bool or ndarray @@ -2322,6 +2329,9 @@ def any(a, axis=None, out=None, keepdims=np._NoValue): >>> np.any(np.nan) True + >>> np.any([[True, False], [False, False]], where=[[False], [True]]) + False + >>> o=np.array(False) >>> z=np.any([-1, 4, 5], out=o) >>> z, o @@ -2333,15 +2343,17 @@ def any(a, axis=None, out=None, keepdims=np._NoValue): (191614240, 191614240) """ - return _wrapreduction(a, np.logical_or, 'any', axis, None, out, keepdims=keepdims) + return _wrapreduction(a, np.logical_or, 'any', axis, None, out, + keepdims=keepdims, where=where) -def _all_dispatcher(a, axis=None, out=None, keepdims=None): - return (a, out) +def _all_dispatcher(a, axis=None, out=None, keepdims=None, *, + where=None): + return (a, where, out) @array_function_dispatch(_all_dispatcher) -def all(a, axis=None, out=None, keepdims=np._NoValue): +def all(a, axis=None, out=None, keepdims=np._NoValue, *, where=np._NoValue): """ Test whether all array elements along a given axis evaluate to True. @@ -2377,6 +2389,12 @@ def all(a, axis=None, out=None, keepdims=np._NoValue): sub-class' method does not implement `keepdims` any exceptions will be raised. + where : array_like of bool, optional + Elements to include in checking for all `True` values. + See `~numpy.ufunc.reduce` for details. + + .. versionadded:: 1.20.0 + Returns ------- all : ndarray, bool @@ -2408,13 +2426,17 @@ def all(a, axis=None, out=None, keepdims=np._NoValue): >>> np.all([1.0, np.nan]) True + >>> np.all([[True, True], [False, True]], where=[[True], [False]]) + True + >>> o=np.array(False) >>> z=np.all([-1, 4, 5], out=o) >>> id(z), id(o), z (28293632, 28293632, array(True)) # may vary """ - return _wrapreduction(a, np.logical_and, 'all', axis, None, out, keepdims=keepdims) + return _wrapreduction(a, np.logical_and, 'all', axis, None, out, + keepdims=keepdims, where=where) def _cumsum_dispatcher(a, axis=None, dtype=None, out=None): @@ -3271,12 +3293,14 @@ def around(a, decimals=0, out=None): return _wrapfunc(a, 'round', decimals=decimals, out=out) -def _mean_dispatcher(a, axis=None, dtype=None, out=None, keepdims=None): - return (a, out) +def _mean_dispatcher(a, axis=None, dtype=None, out=None, keepdims=None, *, + where=None): + return (a, where, out) @array_function_dispatch(_mean_dispatcher) -def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): +def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, + where=np._NoValue): """ Compute the arithmetic mean along the specified axis. @@ -3318,6 +3342,11 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): sub-class' method does not implement `keepdims` any exceptions will be raised. + where : array_like of bool, optional + Elements to include in the mean. See `~numpy.ufunc.reduce` for details. + + .. versionadded:: 1.20.0 + Returns ------- m : ndarray, see dtype parameter above @@ -3366,10 +3395,19 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): >>> np.mean(a, dtype=np.float64) 0.55000000074505806 # may vary + Specifying a where argument: + >>> a = np.array([[5, 9, 13], [14, 10, 12], [11, 15, 19]]) + >>> np.mean(a) + 12.0 + >>> np.mean(a, where=[[True], [False], [False]]) + 9.0 + """ kwargs = {} if keepdims is not np._NoValue: kwargs['keepdims'] = keepdims + if where is not np._NoValue: + kwargs['where'] = where if type(a) is not mu.ndarray: try: mean = a.mean @@ -3382,13 +3420,14 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): out=out, **kwargs) -def _std_dispatcher( - a, axis=None, dtype=None, out=None, ddof=None, keepdims=None): - return (a, out) +def _std_dispatcher(a, axis=None, dtype=None, out=None, ddof=None, + keepdims=None, *, where=None): + return (a, where, out) @array_function_dispatch(_std_dispatcher) -def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): +def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue, *, + where=np._NoValue): """ Compute the standard deviation along the specified axis. @@ -3431,6 +3470,12 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): sub-class' method does not implement `keepdims` any exceptions will be raised. + where : array_like of bool, optional + Elements to include in the standard deviation. + See `~numpy.ufunc.reduce` for details. + + .. versionadded:: 1.20.0 + Returns ------- standard_deviation : ndarray, see dtype parameter above. @@ -3490,11 +3535,20 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): >>> np.std(a, dtype=np.float64) 0.44999999925494177 # may vary + Specifying a where argument: + + >>> a = np.array([[14, 8, 11, 10], [7, 9, 10, 11], [10, 15, 5, 10]]) + >>> np.std(a) + 2.614064523559687 # may vary + >>> np.std(a, where=[[True], [True], [False]]) + 2.0 + """ kwargs = {} if keepdims is not np._NoValue: kwargs['keepdims'] = keepdims - + if where is not np._NoValue: + kwargs['where'] = where if type(a) is not mu.ndarray: try: std = a.std @@ -3507,13 +3561,14 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): **kwargs) -def _var_dispatcher( - a, axis=None, dtype=None, out=None, ddof=None, keepdims=None): - return (a, out) +def _var_dispatcher(a, axis=None, dtype=None, out=None, ddof=None, + keepdims=None, *, where=None): + return (a, where, out) @array_function_dispatch(_var_dispatcher) -def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): +def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue, *, + where=np._NoValue): """ Compute the variance along the specified axis. @@ -3557,6 +3612,12 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): sub-class' method does not implement `keepdims` any exceptions will be raised. + where : array_like of bool, optional + Elements to include in the variance. See `~numpy.ufunc.reduce` for + details. + + .. versionadded:: 1.20.0 + Returns ------- variance : ndarray, see dtype parameter above @@ -3614,10 +3675,20 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): >>> ((1-0.55)**2 + (0.1-0.55)**2)/2 0.2025 + Specifying a where argument: + + >>> a = np.array([[14, 8, 11, 10], [7, 9, 10, 11], [10, 15, 5, 10]]) + >>> np.var(a) + 6.833333333333333 # may vary + >>> np.var(a, where=[[True], [True], [False]]) + 4.0 + """ kwargs = {} if keepdims is not np._NoValue: kwargs['keepdims'] = keepdims + if where is not np._NoValue: + kwargs['where'] = where if type(a) is not mu.ndarray: try: |