numpy.ix_¶

numpy.
ix_
(*args)[source]¶ Construct an open mesh from multiple sequences.
This function takes N 1D 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 nonunit 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 : 1D 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.
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]])