numpy.ma.masked_array.mini¶
-
masked_array.
mini
(axis=None)[source]¶ Return the array minimum along the specified axis.
Deprecated since version 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) >>> print(x) [[0 --] [2 3] [4 --]] >>> x.mini() 0 >>> x.mini(axis=0) masked_array(data = [0 3], mask = [False False], fill_value = 999999) >>> print(x.mini(axis=1)) [0 2 4]
There is a small difference between
mini
andmin
:>>> x[:,1].mini(axis=0) masked_array(data = --, mask = True, fill_value = 999999) >>> x[:,1].min(axis=0) masked