def simpleMultivariateNormalPdf(z, detFactorSigma):
 dim = len(z)
 return (exp(((-0.5) * dot(z, z))) / (power((2.0 * pi), (dim / 2.0)) * detFactorSigma))

def simpleMultivariateNormalPdf ( z , detFactorSigma ) : dim = len ( z ) return ( exp ( ( ( - 0.5 ) * dot ( z , z ) ) ) / ( power ( ( 2.0 * pi ) , ( dim / 2.0 ) ) * detFactorSigma ) )
assuming z has been transformed to a mean of zero and an identity matrix of covariances .