#### Previous topic

numpy.indices

#### Next topic

numpy.ravel_multi_index

# numpy.ix

`numpy.``ix_`(*args)

  Construct an open mesh from multiple sequences.

  This function takes N 1-D sequences and returns N outputs with N dimensions each, such that the shape is 1 in all but one dimension and the dimension with the non-unit shape value cycles through all N dimensions.

  Using `ix_` one can quickly construct index arrays that will index the cross product. `a[np.ix_([1,3],[2,5])]` returns the array `[[a[1,2] a[1,5]], [a[3,2] a[3,5]]]`.

  Parameters: | args : 1-D sequences Each sequence should be of integer or boolean type. Boolean sequences will be interpreted as boolean masks for the corresponding dimension (equivalent to passing in `np.nonzero(boolean_sequence)`).
  Returns: | out : tuple of ndarrays N arrays with N dimensions each, with N the number of input sequences. Together these arrays form an open mesh.

  See also

  `ogrid`, `mgrid`, `meshgrid`

  Examples

      >>> a = np.arange(10).reshape(2, 5)
      >>> a
      array([[0, 1, 2, 3, 4],
             [5, 6, 7, 8, 9]])
      >>> ixgrid = np.ix_([0, 1], [2, 4])
      >>> ixgrid
      (array([[0],
             [1]]), array([[2, 4]]))
      >>> ixgrid[0].shape, ixgrid[1].shape
      ((2, 1), (1, 2))
      >>> a[ixgrid]
      array([[2, 4],
             [7, 9]])

      >>> ixgrid = np.ix_([True, True], [2, 4])
      >>> a[ixgrid]
      array([[2, 4],
             [7, 9]])
      >>> ixgrid = np.ix_([True, True], [False, False, True, False, True])
      >>> a[ixgrid]
      array([[2, 4],
             [7, 9]])