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# numpy.ma.getmask

`numpy.ma.``getmask`(a)

  Return the mask of a masked array, or nomask.

  Return the mask of a as an ndarray if a is a `MaskedArray` and the mask is not `nomask`, else return `nomask`. To guarantee a full array of booleans of the same shape as a, use `getmaskarray`.

  Parameters: | a : array_like Input `MaskedArray` for which the mask is required.

  See also

  `getdata`
    Return the data of a masked array as an ndarray.
  `getmaskarray`
    Return the mask of a masked array, or full array of False.

  Examples

      >>> import numpy.ma as ma
      >>> a = ma.masked_equal([[1,2],[3,4]], 2)
      >>> a
      masked_array(data =
       [[1 --]
       [3 4]],
            mask =
       [[False  True]
       [False False]],
            fill_value=999999)
      >>> ma.getmask(a)
      array([[False,  True],
             [False, False]], dtype=bool)

  Equivalently use the `MaskedArray` mask attribute.

      >>> a.mask
      array([[False,  True],
             [False, False]], dtype=bool)

  Result when mask == `nomask`

      >>> b = ma.masked_array([[1,2],[3,4]])
      >>> b
      masked_array(data =
       [[1 2]
       [3 4]],
            mask =
       False,
            fill_value=999999)
      >>> ma.nomask
      False
      >>> ma.getmask(b) == ma.nomask
      True
      >>> b.mask == ma.nomask
      True