# numpy.ma.argsort

ma.argsort(a, axis=<no value>, kind=None, order=None, endwith=True, fill_value=None)

  Return an ndarray of indices that sort the array along the specified axis. Masked values are filled beforehand to fill_value.

  Parameters
    axis int, optional

      Axis along which to sort. If None, the default, the flattened array is used.

      Changed in version 1.13.0: Previously, the default was documented to be -1, but that was in error. At some future date, the default will change to -1, as originally intended. Until then, the axis should be given explicitly when `arr.ndim > 1`, to avoid a FutureWarning.

    kind{‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional

      The sorting algorithm used.

    order list, optional

      When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. Not all fields need be specified.

    endwith{True, False}, optional

      Whether missing values (if any) should be treated as the largest values (True) or the smallest values (False) When the array contains unmasked values at the same extremes of the datatype, the ordering of these values and the masked values is undefined.

    fill_value scalar or None, optional

      Value used internally for the masked values. If `fill_value` is not None, it supersedes `endwith`.

  Returns
    index_array ndarray, int

      Array of indices that sort a along the specified axis. In other words, `a[index_array]` yields a sorted a.

  See also

  `ma.MaskedArray.sort`

    Describes sorting algorithms used.

  `lexsort`

    Indirect stable sort with multiple keys.

  `numpy.ndarray.sort`

    Inplace sort.

  Notes

  See `sort` for notes on the different sorting algorithms.

  Examples

      >>> a = np.ma.array([3,2,1], mask=[False, False, True])
      >>> a
      masked_array(data=[3, 2, --],
                   mask=[False, False,  True],
             fill_value=999999)
      >>> a.argsort()
      array([1, 0, 2])

previous

numpy.ma.diff

next

numpy.ma.sort