# numpy.ma.masked_array.compress

method

ma.masked_array.compress(condition, axis=None, out=None)

  Return a where condition is `True`.

  If condition is a `MaskedArray`, missing values are considered as `False`.

  Parameters
    condition var

      Boolean 1-d array selecting which entries to return. If len(condition) is less than the size of a along the axis, then output is truncated to length of condition array.

    axis{None, int}, optional

      Axis along which the operation must be performed.

    out{None, ndarray}, optional

      Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary.

  Returns
    result MaskedArray

      A `MaskedArray` object.

  Notes

  Please note the difference with `compressed` ! The output of `compress` has a mask, the output of `compressed` does not.

  Examples

      >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
      >>> x
      masked_array(
        data=[[1, --, 3],
              [--, 5, --],
              [7, --, 9]],
        mask=[[False,  True, False],
              [ True, False,  True],
              [False,  True, False]],
        fill_value=999999)
      >>> x.compress([1, 0, 1])
      masked_array(data=[1, 3],
                   mask=[False, False],
             fill_value=999999)

      >>> x.compress([1, 0, 1], axis=1)
      masked_array(
        data=[[1, 3],
              [--, --],
              [7, 9]],
        mask=[[False, False],
              [ True,  True],
              [False, False]],
        fill_value=999999)