Tom Kaz wrote:

[I wrote:] (please attribute quotes)

Do each function separately. The routine that scipy.integrate.quad uses

adapts to the local conditions of the function (when the function is

flat, it uses fewer samples; when steep, more).

It's not so easy to do it separately. I want to integrate function that

includes linalg.expm - as you see calculation the function is quite

expensive.

I understand, but the good integration algorithms really do need to

evaluate each dimension separately.

If you can bear algorithms that only use samples from fixed intervals,

then you can use the functions romb(), simps(), or trapz() in

scipy.integrate.

BTW, a better place to ask scipy questions would be the scipy mailing list.

http://scipy.net/mailman/listinfo/scipy-user
--

Robert Kern

rk***@ucsd.edu
"In the fields of hell where the grass grows high

Are the graves of dreams allowed to die."

-- Richard Harter