d15d9ad19021a8a3f26a86fbc6b71838ac37e7d1,pymc3/distributions/multivariate.py,MvNormal,logp,#MvNormal#Any#,121

Before Change

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

        result = k * tt.log(2 * np.pi)
        if self.gpu_compat:
            result -= tt.log(det(tau))
        else:
            result -= logdet(tau)
        result += (tt.dot(delta, tau) * delta).sum(axis=delta.ndim - 1)
        return -1 / 2. * result


class MvStudentT(Continuous):
    R

After Change

    def logp(self, value):
        if self.has_tau:
            return self._logp_tau(value)
        return self._logp_chol(value)

    def _logp_chol(self, value):
        chol_cov = self.chol_cov

Instances