Sampling from a multivariate von Mises-Fisher distribution in Python I am looking for a simple way to sample from a multivariate von Mises-Fisher distribution in Python. I have looked in the stats module in scipy and the numpy module but only found the univariate von Mises distribution. Is there any code available? I have not found yet.  

-- edit. Apparently, Wood (1994) has designed an algorithm for sampling from the vMF distribution according to this link, but I can't find the paper.
It looks like you can sample the von Mises-Fisher distribution with that R package. Have you thought about calling R from within Python using the rpy2 package? I haven't tried this for myself, but could you try the following?

from numpy import *
import scipy as sp
from pandas import *
from rpy2.robjects.packages import importr
import rpy2.robjects as ro
import pandas.rpy.common as com
from rpy2.robjects.packages import importr

# import the movMF R package
movMF = importr('movMF')
# call the rmovMF sampling function from the R package
print(movMF.rmovMF(10, 3 * c(1, -1) / sqrt(2)))