Multivariate normal density in Python?

Question

Is there any python package that allows the efficient computation of the PDF (probability density function) of a multivariate normal distribution?

It doesn\'t seem to be

Answer 1

I use the following code which calculates the logpdf value, which is preferable for larger dimensions. It also works for scipy.sparse matrices.

import numpy as np
import math
import scipy.sparse as sp
import scipy.sparse.linalg as spln

def lognormpdf(x,mu,S):
    """ Calculate gaussian probability density of x, when x ~ N(mu,sigma) """
    nx = len(S)
    norm_coeff = nx*math.log(2*math.pi)+np.linalg.slogdet(S)[1]

    err = x-mu
    if (sp.issparse(S)):
        numerator = spln.spsolve(S, err).T.dot(err)
    else:
        numerator = np.linalg.solve(S, err).T.dot(err)

    return -0.5*(norm_coeff+numerator)

Code is from pyParticleEst, if you want the pdf value instead of the logpdf just take math.exp() on the returned value