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# numpy.ma.where

`numpy.ma.``where`(condition, x=<class numpy._globals._NoValue>, y=<class numpy._globals._NoValue>)

  Return a masked array with elements from x or y, depending on condition.

  Returns a masked array, shaped like condition, where the elements are from x when condition is True, and from y otherwise. If neither x nor y are given, the function returns a tuple of indices where condition is True (the result of `condition.nonzero()`).

  Parameters: | condition : array_like, bool The condition to meet. For each True element, yield the corresponding element from x, otherwise from y. x, y : array_like, optional Values from which to choose. x, y and condition need to be broadcastable to some shape.
  Returns: | out : MaskedArray or tuple of ndarrays The resulting masked array if x and y were given, otherwise the result of `condition.nonzero()`.

  See also

  `numpy.where`
    Equivalent function in the top-level NumPy module.

  Examples

      >>> x = np.ma.array(np.arange(9.).reshape(3, 3), mask=[[0, 1, 0],
      ...                                                    [1, 0, 1],
      ...                                                    [0, 1, 0]])
      >>> print(x)
      [[0.0 -- 2.0]
       [-- 4.0 --]
       [6.0 -- 8.0]]
      >>> np.ma.where(x > 5)    # return the indices where x > 5
      (array([2, 2]), array([0, 2]))

      >>> print(np.ma.where(x > 5, x, -3.1416))
      [[-3.1416 -- -3.1416]
       [-- -3.1416 --]
       [6.0 -- 8.0]]