numpy.ma.MaskedArray.argmin#

method

ma.MaskedArray.argmin(axis=None, fill_value=None, out=None, *, keepdims=<no value>)[source]#

Return array of indices to the minimum values along the given axis.

Parameters:

axis{None, integer}: If None, the index is into the flattened array, otherwise along the specified axis
fill_valuescalar or None, optional: Value used to fill in the masked values. If None, the output of minimum_fill_value(self._data) is used instead.
out{None, array}, optional: Array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.

Returns:

ndarray or scalar: 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.

Examples

>>> import numpy as np
>>> x = np.ma.array(np.arange(4), mask=[1,1,0,0])
>>> 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])
>>> x.argmin(axis=0, fill_value=9)
array([1, 1])