Feb. 27, 2013
11:44 p.m.
On 27 Feb 2013 12:57, "Jorge Scandaliaris" <jorgesmbox-ml@yahoo.es> wrote:
Hi, First of all excuse me if this is a trivial question. I have the feeling
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
it is, 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