On 27 Feb 2013 12:57, "Jorge Scandaliaris" <jorgesmbox...@yahoo.es> wrote: > > Hi, > First of all excuse me if this is a trivial question. I have the feeling it is, > but searching and looking through the docs has proven unsuccesful so far. > > I have an ndarray A of shape (M,2,2) representing M 2 x 2 matrices. Now I want > to apply a transform T of shape (2,2) to each of matrix. The way I do this now > is by iterating over all rows of A multiplying the matrices using numpy.dot(): > > for row in np.arange(A.shape[0]): > A[row] = np.dot(A[row],T) > > but this seems to be slow when M is large and I have the feeling there must be a > way of doing it better.
Pretty sure the code you wrote above is equivalent to np.dot(A, T, out=A) -n
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