numpy.broadcast

class numpy.broadcast[源代码]

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 and nd properties, and may be used as an iterator.

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:
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.

1.12.0 新版功能.

>>> 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

next
reset() Reset the broadcasted result’s iterator(s).