Just for other peoples reference I eventually went with a cython
version that goes about twice as fast as my old post. Here it is:
import numpy as np
cimport numpy as np
cdef extern from "math.h":
double cos(double)
double sin(double)
def rotation(np.ndarray[double] theta):
cdef np.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[1,0] = -sx*cz - cx*cy*sz
R[1,1] = -sx*sz + cx*cy*cz
R[1,2] = cx*sy
R[2,0] = sy*sz
R[2,1] = -sy*cz
R[2,2] = cy
return R
Best,
Jon.
On Wed, Mar 4, 2009 at 10:28 AM, Lou Pecora <lou_boog2...@yahoo.com> wrote:
>
> Whoops. I see you have profiled your code. Sorry to re-suggest that.
>
> But I agree with those who suggest a C speed up using ctypes or cthyon.
>
> However, thanks for posting your question. It caused a LOT of very useful
> responses that I didn't know about. Thanks to all who replied.
>
> -- Lou Pecora, my views are my own.
>
>
>
>
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> Numpy-discussion@scipy.org
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