Hi, I'm doing some computations with complex numbers and speed is critical. I'm puzzled by the following.
sage: A= MatrixSpace(CDF, 2).random_element() sage: B= MatrixSpace(CDF, 2).random_element() sage: %timeit A*B 625 loops, best of 3: 20 µs per loop sage: AA= numpy.array(A); BB= numpy.array(B) sage: %timeit AA.dot(BB) 625 loops, best of 3: 2.24 µs per loop So numpy seems much faster for this. But on the other hand sage: z= A[0,0] sage: %timeit z*z 625 loops, best of 3: 241 ns per loop sage: zz= AA[0,0] sage: %timeit zz*zz 625 loops, best of 3: 521 ns per loop so now numpy is much slower!! what is going on? is there a way to get the best of both worlds simply, both for matrix operations and simple arithmetic? i think zz above might still be considered as a 1 x 1 matrix instead of a complex number, somehow, and this may be slowing things down. any help appreciated! thanks pierre -- To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to sage-support+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
