Input parameters.
Broadcast the input parameters against one another, and return an object that encapsulates the result. Amongst others, it has shape
and nd
properties, and may be used as an iterator.
Produce an object that mimics broadcasting.
Manually adding two vectors, using broadcasting:
>>> x = np.array([[1], [2], [3]])
... 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]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.broadcast_to
numpy.broadcast_shapes
numpy.broadcast_arrays
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