Produce an object that mimics broadcasting.
in1, in2, … : array_like
b : broadcast object
Broadcast the input parameters against one another, and return an object that encapsulates the result. Amongst others, it has
ndproperties, and may be used as an iterator.
Manually adding two vectors, using broadcasting:
>>> x = np.array([, , ]) >>> y = np.array([4, 5, 6]) >>> b = np.broadcast(x, y)
>>> out = np.empty(b.shape) >>> out.flat = [u+v for (u,v) in b] >>> out array([[ 5., 6., 7.], [ 6., 7., 8.], [ 7., 8., 9.]])
Compare against built-in broadcasting:
>>> x + y array([[5, 6, 7], [6, 7, 8], [7, 8, 9]])
current index in broadcasted result
tuple of iterators along
Shape of broadcasted result.
Total size of broadcasted result.
Reset the broadcasted result’s iterator(s).