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
shapeandndproperties, 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 built-in broadcasting:
>>> x + y array([[5, 6, 7], [6, 7, 8], [7, 8, 9]])
Attributes: indexcurrent index in broadcasted result
iterstuple 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
ndimis 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
shapeShape of broadcasted result.
sizeTotal size of broadcasted result.
Methods
reset()Reset the broadcasted result’s iterator(s).