Hi there. I want to do some intensive computations with numpy, and I'm struggling a bit to find myyyyy wayyyyyy. Here is the problem :
m and d are two matrices : > m.shape = (x,y,a,b) > d.shape = (a,b) I want to return > i.shape = (x,y) with > i[x,y] = sum(m[x,y] * d) I already found that > m[:,:] * d will give me a matrix of shape (x,y,a,b) containing the products. Now I want to sum up on axis 2 and 3. If I do : > (m[:,:] * d).sum(axis=3).sum(axis=2) it seems like I get my result. I'm wondering : is this syntax leading to efficient computation, or is there something better ? thanks Thomas -- http://mail.python.org/mailman/listinfo/python-list
