numpy.broadcast¶

class
numpy.
broadcast
[source]¶ Produce an object that mimics broadcasting.
Parameters:  in1, in2, … : array_like
Input parameters.
Returns:  b : broadcast object
Broadcast the input parameters against one another, and return an object that encapsulates the result. Amongst others, it has
shape
andnd
properties, and may be used as an iterator.
See also
Examples
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 builtin broadcasting:
>>> x + y array([[5, 6, 7], [6, 7, 8], [7, 8, 9]])
Attributes: index
current index in broadcasted result
iters
tuple of iterators along
self
’s “components.” nd
Number of dimensions of broadcasted result. For code intended for NumPy 1.12.0 and later the more consistent
ndim
is preferred.>>> x = np.array([1, 2, 3]) >>> y = np.array([[4], [5], [6]]) >>> b = np.broadcast(x, y) >>> b.nd 2
 ndim
Number of dimensions of broadcasted result. Alias for
nd
.New in version 1.12.0.
>>> x = np.array([1, 2, 3]) >>> y = np.array([[4], [5], [6]]) >>> b = np.broadcast(x, y) >>> b.ndim 2
 numiter
Number of iterators possessed by the broadcasted result.
>>> x = np.array([1, 2, 3]) >>> y = np.array([[4], [5], [6]]) >>> b = np.broadcast(x, y) >>> b.numiter 2
shape
Shape of broadcasted result.
size
Total size of broadcasted result.
Methods
reset
()Reset the broadcasted result’s iterator(s).