[SciPy-User] speed of logpdf functions in scipy.stats

[Brian Blais]

Hello,

I was playing with some MCMC methods which require logpdf for
different distributions, and thought "hey!  I can use the
scipy.stats.distributions!".  Then, when I tested them, they seemed
slow.  Upon comparison, I noticed a huge speed difference between
these functions and my own not-so-cleverly written python only
functions.  Is there a way to get better performance?  Am I doing
something silly here, and creating unneeded objects somewhere?  The
simplest code which shows the issue is below.

thanks,

bb

-- 
-----------------

             bblais at gmail.com
             http://web.bryant.edu/~bblais

import numpy as np
from scipy.stats import distributions as D

def lognormalpdf(x,mn,sig):
    # 1/sqrt(2*pi*sigma^2)*exp(-x^2/2/sigma^2)
    return -0.5*log(2*np.pi*sig**2)- (x-mn)**2/sig**2/2.0

x=np.random.rand(5)
print lognormalpdf(x,0,1)
print D.norm.logpdf(x,0,1)

x=np.random.rand(15000)

%timeit y=lognormalpdf(x,0,1)
# 10000 loops, best of 3: 66.9 µs per loop

%timeit y=D.norm.logpdf(x,0,1)
# 1000 loops, best of 3: 727 µs per loop