argmin(self, axis=None, fill_value=None, out=None)
If None, the index is into the flattened array, otherwise along the specified axis
Value used to fill in the masked values. If None, the output of minimum_fill_value(self._data) is used instead.
Array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.
If multi-dimension input, returns a new ndarray of indices to the minimum values along the given axis. Otherwise, returns a scalar of index to the minimum values along the given axis.
Return array of indices to the minimum values along the given axis.
>>> x = np.ma.array(np.arange(4), mask=[1,1,0,0])This example is valid syntax, but we were not able to check execution
... x.shape = (2,2)
... x masked_array( data=[[--, --], [2, 3]], mask=[[ True, True], [False, False]], fill_value=999999)
>>> x.argmin(axis=0, fill_value=-1) array([0, 0])This example is valid syntax, but we were not able to check execution
>>> x.argmin(axis=0, fill_value=9) array([1, 1])See :
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