numpy.ma.masked_array.mini
method
-
masked_array.mini(self, 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
-
-
axisint, 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
-
-
minscalar or MaskedArray
-
If
axis
is None, the result is a scalar. Otherwise, ifaxis
is given and the array is at least 2-D, the result is a masked array with dimension one smaller than the array on whichmini
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
andmin
:>>> x[:,1].mini(axis=0) masked_array(data=3, mask=False, fill_value=999999) >>> x[:,1].min(axis=0) 3
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.ma.masked_array.mini.html