# numpy.ma.masked_array.nonzero

`masked_array.``nonzero`()

  Return the indices of unmasked elements that are not zero.

  Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values can be obtained with:

      a[a.nonzero()]

  To group the indices by element, rather than dimension, use instead:

      np.transpose(a.nonzero())

  The result of this is always a 2d array, with a row for each non-zero element.

  Parameters: | None :
  Returns: | tuple_of_arrays : tuple Indices of elements that are non-zero.

  See also

  `numpy.nonzero`
    Function operating on ndarrays.
  `flatnonzero`
    Return indices that are non-zero in the flattened version of the input array.
  `ndarray.nonzero`
    Equivalent ndarray method.
  `count_nonzero`
    Counts the number of non-zero elements in the input array.

  Examples

      >>> import numpy.ma as ma
      >>> x = ma.array(np.eye(3))
      >>> x
      masked_array(data =
       [[ 1.  0.  0.]
       [ 0.  1.  0.]
       [ 0.  0.  1.]],
            mask =
       False,
            fill_value=1e+20)
      >>> x.nonzero()
      (array([0, 1, 2]), array([0, 1, 2]))

  Masked elements are ignored.

      >>> x[1, 1] = ma.masked
      >>> x
      masked_array(data =
       [[1.0 0.0 0.0]
       [0.0 -- 0.0]
       [0.0 0.0 1.0]],
            mask =
       [[False False False]
       [False  True False]
       [False False False]],
            fill_value=1e+20)
      >>> x.nonzero()
      (array([0, 2]), array([0, 2]))

  Indices can also be grouped by element.

      >>> np.transpose(x.nonzero())
      array([[0, 0],
             [2, 2]])

  A common use for `nonzero` is to find the indices of an array, where a condition is True. Given an array a, the condition a > 3 is a boolean array and since False is interpreted as 0, ma.nonzero(a > 3) yields the indices of the a where the condition is true.

      >>> a = ma.array([[1,2,3],[4,5,6],[7,8,9]])
      >>> a > 3
      masked_array(data =
       [[False False False]
       [ True  True  True]
       [ True  True  True]],
            mask =
       False,
            fill_value=999999)
      >>> ma.nonzero(a > 3)
      (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))

  The `nonzero` method of the condition array can also be called.

      >>> (a > 3).nonzero()
      (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))