python - Adding and multiplying columns of a numpy array with another array -

i have 2d numpy array x , and 1d numpy array y:

import numpy np x = np.arange(12).reshape((4, 3)) y = np.array(([1.0,2.0,3.0,4.0])

i want multiply / add column vector y.reshape((4,1)) each column of x. attempted following:

y1 = y.reshape((4,1))     y1 * x

yields

array([[ 0., 1., 2.],         [ 6., 8., 10.],         [ 18., 21., 24.],         [ 36., 40., 44.]])

which wanted. found

array([[ 1., 2., 3.],         [ 5., 6., 7.],         [ 9., 10., 11.],         [ 13., 14., 15.]])

with y1 + x.
know if there better (more efficient) way achieve same thing!

numpy supports via broadcasting. code used broadcasting , it's efficient way things. write as:

>>> x * y[..., np.newaxis] array([[  0.,   1.,   2.],        [  6.,   8.,  10.],        [ 18.,  21.,  24.],        [ 36.,  40.,  44.]])

to see equivalent:

>>> z =  y[..., np.newaxis] >>> z.shape (4, 1)

you can see numpy doesn't copy data, changes iteration on same memory internally

>>> z.base y true

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