d1de2f98ec8f851228e28bf28a0f800e90bd9bcf,pyemma/msm/estimators/maximum_likelihood_msm.py,AugmentedMarkovModel,_estimate,#AugmentedMarkovModel#Any#,1712

Before Change

                self._phs.append(self.pihat)
                self._ls.append(self.lagrange.copy())
                self._mhats.append(_np.array(self.mhat))
                self._rmss.append(_np.average(self.E, weights=self.pihat.reshape((self.n_mstates_active,)), axis=0))

            if i>1 and _np.all((_np.abs(self._dmhat)/self.sigmas)<self.eps) and not self._converged:
                self.logger.info("Converged Lagrange multipliers after %i steps..."%i)
                self._converged = True

After Change

                self._estimated = True
            //if Lagrange multipliers are converged, check whether log-likelihood has converged
            if self._converged:
                if _np.abs(self._lls[-2]-self._lls[-1])<1e-8:
                   self.logger.info("Converged pihat after %i steps..."%i)
                   die = True
            if die:

Instances