diff options
Diffstat (limited to 'numpy/ma/core.py')
| -rw-r--r-- | numpy/ma/core.py | 84 |
1 files changed, 2 insertions, 82 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 93eb74be3..ba387e585 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -5804,74 +5804,6 @@ class MaskedArray(ndarray): np.copyto(out, np.nan, where=newmask) return out - # unique to masked arrays - def mini(self, axis=None): - """ - Return the array minimum along the specified axis. - - .. deprecated:: 1.13.0 - This function is identical to both: - - * ``self.min(keepdims=True, axis=axis).squeeze(axis=axis)`` - * ``np.ma.minimum.reduce(self, axis=axis)`` - - Typically though, ``self.min(axis=axis)`` is sufficient. - - Parameters - ---------- - axis : int, optional - The axis along which to find the minima. Default is None, in which case - the minimum value in the whole array is returned. - - Returns - ------- - min : scalar or MaskedArray - If `axis` is None, the result is a scalar. Otherwise, if `axis` is - given and the array is at least 2-D, the result is a masked array with - dimension one smaller than the array on which `mini` is called. - - Examples - -------- - >>> x = np.ma.array(np.arange(6), mask=[0 ,1, 0, 0, 0 ,1]).reshape(3, 2) - >>> x - masked_array( - data=[[0, --], - [2, 3], - [4, --]], - mask=[[False, True], - [False, False], - [False, True]], - fill_value=999999) - >>> x.mini() - masked_array(data=0, - mask=False, - fill_value=999999) - >>> x.mini(axis=0) - masked_array(data=[0, 3], - mask=[False, False], - fill_value=999999) - >>> x.mini(axis=1) - masked_array(data=[0, 2, 4], - mask=[False, False, False], - fill_value=999999) - - There is a small difference between `mini` and `min`: - - >>> x[:,1].mini(axis=0) - masked_array(data=3, - mask=False, - fill_value=999999) - >>> x[:,1].min(axis=0) - 3 - """ - - # 2016-04-13, 1.13.0, gh-8764 - warnings.warn( - "`mini` is deprecated; use the `min` method or " - "`np.ma.minimum.reduce instead.", - DeprecationWarning, stacklevel=2) - return minimum.reduce(self, axis) - def max(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue): """ Return the maximum along a given axis. @@ -6719,15 +6651,9 @@ class _extrema_operation(_MaskedUFunc): self.compare = compare self.fill_value_func = fill_value - def __call__(self, a, b=None): + def __call__(self, a, b): "Executes the call behavior." - if b is None: - # 2016-04-13, 1.13.0 - warnings.warn( - f"Single-argument form of np.ma.{self.__name__} is deprecated. Use " - f"np.ma.{self.__name__}.reduce instead.", - DeprecationWarning, stacklevel=2) - return self.reduce(a) + return where(self.compare(a, b), a, b) def reduce(self, target, axis=np._NoValue): @@ -8090,12 +8016,6 @@ def asanyarray(a, dtype=None): # Pickling # ############################################################################## -def _pickle_warn(method): - # NumPy 1.15.0, 2017-12-10 - warnings.warn( - f"np.ma.{method} is deprecated, use pickle.{method} instead", - DeprecationWarning, stacklevel=3) - def fromfile(file, dtype=float, count=-1, sep=''): raise NotImplementedError( |