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# numpy.ma.masked_array.argmin

method

ma.masked_array.argmin(axis=None, fill_value=None, out=None, *, keepdims=<no value>)

  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_value scalar 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])