Hi, Suppose I have an array of shape: (n, k, k). In this case, I have n k-by-k matrices. My goal is to compute the product of a (potentially large) user-specified selection (with replacement) of these matrices. For example,
x = [0,1,2,1,3,3,2,1,3,2,1,5,3,2,3,5,2,5,3,2,1,3,5,6] says that I want to take the 0th matrix and dot it with the 1st matrix and dot that product with the 2nd matrix and dot that product with the 1st matrix again and so on... Essentially, I am looking for efficient ways of doing this. It seems like what I *need* is for dot to be a ufunc with a reduce() operator. Then I would construct an array of the matrices, as specified by the input x. For now, I am using a python loop and this is unbearable. >>> prod = np.eye(k) >>> for i in x: ... prod = dot(prod, matrices[i]) ... Is there a better way? _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
