numpy.broadcast#

classnumpy.broadcast[source]#

Produce an object that mimics broadcasting.

Parameters:

in1, in2, …array_like

Input parameters.

Returns:

bbroadcast object

Broadcast the input parameters against one another, andreturn an object that encapsulates the result.Amongst others, it hasshape andnd properties, andmay be used as an iterator.

See also

broadcast_arrays

broadcast_to

broadcast_shapes

Examples

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Manually adding two vectors, using broadcasting:

>>>importnumpyasnp>>>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+vfor(u,v)inb]>>>outarray([[5.,  6.,  7.],       [6.,  7.,  8.],       [7.,  8.,  9.]])

Compare against built-in broadcasting:

>>>x+yarray([[5, 6, 7],       [6, 7, 8],       [7, 8, 9]])

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Attributes:

index

current index in broadcasted result

iters

tuple of iterators alongself’s “components.”

nd

Number of dimensions of broadcasted result.

ndim

Number of dimensions of broadcasted result.

numiter

Number of iterators possessed by the broadcasted result.

shape

Shape of broadcasted result.

size

Total size of broadcasted result.

Methods

reset()

Reset the broadcasted result's iterator(s).