d69d5bd992730a7a8f19530078e1e185f9e4772d,pyemma/coordinates/clustering/kmeans.py,MiniBatchKmeansClustering,_estimate,#MiniBatchKmeansClustering#Any#,400

Before Change

                i_pass += 1

        self._finish_estimate()

        if not self._converged:
            self.logger.info("Algorithm did not reach convergence criterion"
                              " of %g in %i iterations. Consider increasing max_iter.", self.tolerance, self.max_iter)

After Change

        ra_stride = self._draw_mini_batch_sample()
        with iterable.iterator(return_trajindex=False, stride=ra_stride, skip=self.skip) as iterator, \
            self._progress_context(), self._finish_estimate():
            while not (self._converged or i_pass + 1 > self.max_iter):
                first_chunk = True
                // draw new sample and re-use existing iterator instance.

Instances