08ac4fdc7d093e35fde612b050ade7fef8665983,pymc/distributions/multivariate.py,MvNormal,logp,#MvNormal#Any#,28

Before Change

        delta = value - mu
        k = tau.shape[0]

        return 1/2. * (-k * log(2*pi) + log(det(tau)) - dot(delta.T, dot(tau, delta)))


class Dirichlet(Continuous):

After Change

        delta = value - mu
        k = tau.shape[0]

        result = k * log(2*pi) + log(1./det(tau))
        result += (delta.dot(tau) * delta).sum(axis=delta.ndim - 1)
        return -1/2. * result

Instances