numpy.broadcast_arrays

numpy.broadcast_arrays(*args, **kwargs) [source]

Broadcast any number of arrays against each other.

Parameters:	`*args` : array_likes The arrays to broadcast. subok : bool, optional If True, then sub-classes will be passed-through, otherwise the returned arrays will be forced to be a base-class array (default).
Returns:	broadcasted : list of arrays These arrays are views on the original arrays. They are typically not contiguous. Furthermore, more than one element of a broadcasted array may refer to a single memory location. If you need to write to the arrays, make copies first.

Examples

>>> x = np.array([[1,2,3]])
>>> y = np.array([[4],[5]])
>>> np.broadcast_arrays(x, y)
[array([[1, 2, 3],
       [1, 2, 3]]), array([[4, 4, 4],
       [5, 5, 5]])]

Here is a useful idiom for getting contiguous copies instead of non-contiguous views.

>>> [np.array(a) for a in np.broadcast_arrays(x, y)]
[array([[1, 2, 3],
       [1, 2, 3]]), array([[4, 4, 4],
       [5, 5, 5]])]