How to elementwise-multiply a scipy.sparse matrix by a broadcasted dense 1d array?

I replied over at scipy.org as well, but I thought I should add an answer here, in case others find this page when searching.

You can turn the vector into a sparse diagonal matrix and then use matrix multiplication (with *) to do the same thing as broadcasting, but efficiently.

>>> d = ssp.lil_matrix((3,3))
>>> d.setdiag(np.ones(3)*3)
>>> a*d
<5x3 sparse matrix of type '<type 'numpy.float64'>'
 with 2 stored elements in Compressed Sparse Row format>
>>> (a*d).todense()
matrix([[ 0.,  0.,  0.],
        [ 0.,  0., -3.],
        [ 0.,  0.,  0.],
        [ 0.,  0.,  0.],
        [ 0.,  6.,  0.]])

Hope that helps!