def simpleMultivariateNormalPdf(z, detFactorSigma):
    dim = len(z)
    return exp(-0.5 * dot(z, z)) / (power(2.0 * pi, dim / 2.) * detFactorSigma)
Assuming z has been transformed to a mean of zero and an identity matrix of covariances.
dataset/ETHPy150Open pybrain/pybrain/pybrain/tools/functions.py/simpleMultivariateNormalPdf