Can someone help me replace a slow expression with a faster one based on tensordot? I've read the documentation and I'm still confused.
I have two matrices b and d. b is n x m and d is m x m. I want to replace the expression >>> bdb = zeros(n,'d') >>> for i in xrange(n): >>> bdb[i,:] = dot(b[i,:],dot(d,b[i,:]) with something that doesn't have the for loop and thus is a bit faster. The first step is >>> bd = dot(b,d) However, following this with >>> bdb = dot(bd,b.T) doesn't work, since it yields a n x n matrix instead of an n x 1 vector. Reading the notes on tensordot makes me think it's the function to use, but I'm having trouble grokking the axes argument. Can anyone help? Thanks in advance! -- Rick Muller rpmul...@gmail.com
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