Hello, > def rotation(theta, R = np.zeros((3,3))): > cx,cy,cz = np.cos(theta) > sx,sy,sz = np.sin(theta) > R.flat = (cx*cz - sx*cy*sz, cx*sz + sx*cy*cz, sx*sy, > -sx*cz - cx*cy*sz, -sx*sz + cx*cy*cz, > cx*sy, sy*sz, -sy*cz, cy) > return R > > Pretty evil looking ;) but still wouldn't mind somehow getting it faster
I would definitely encourage you to check out cython. I have to write lots of numerically intensive stuff in my python code, and I tend to cythonize it a lot. In cython, the above would be (something like): from numpy cimport ndarray cdef extern from "math.h": double cos(double) double sin(double) def rotation(ndarry[double] theta, ndarray[double, ndim=2] R = np.zeros((3,3))): cdef double cx = cos(theta[0]), cy = cos(theta[1]), cz = cos(theta[2]) cdef double sx = sin(theta[0]), sy = sin(theta[1]), sz = sin(theta[2]) R[0,0] = cx*cz - sx*cy*sz R[0,1] = cx*sz + sx*cy*cz R[0,2] = sx*sy ... R[2,2] = cy return R And that will be probably be orders of magnitude faster than what you currently have, as everything but the function call and the return statement would become C code. Compilers these days are very good at optimizing that kind of thing too. --Hoyt ++++++++++++++++++++++++++++++++++++++++++++++++ + Hoyt Koepke + University of Washington Department of Statistics + http://www.stat.washington.edu/~hoytak/ + hoy...@gmail.com ++++++++++++++++++++++++++++++++++++++++++ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion