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# numpy.ma.getmask

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 as np
      >>> 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=2)
      >>> ma.getmask(a)
      array([[False,  True],
             [False, False]])

  Equivalently use the `MaskedArray` mask attribute.

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

  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