def _efficient_traj_join(trajs):
assert trajs
n_frames = sum(t.n_frames for t in trajs)
concat_traj = preallocate_empty_trajectory(trajs[0].top, n_frames)
start = 0
for traj in trajs:
concat_traj = copy_traj_attributes(concat_traj, traj, start)
start += traj.n_frames
return concat_traj
def _allocate_chunk(self, expected_length, ndim):
if (hasattr(self._reader_it._data_source, '_return_traj_obj')
and self._reader_it._data_source._return_traj_obj):
X = preallocate_empty_trajectory(
n_frames=expected_length,
top=self._reader_it._data_source.featurizer.topology)
else:
X = np.empty((expected_length, ndim),
dtype=self._frag_reader.output_type())
return X
def _allocate_chunk(self, expected_length, ndim):
from pyemma.coordinates.data.feature_reader import FeatureReader
if all(
isinstance(r, FeatureReader) and r._return_traj_obj
for r in self._readers):
X = preallocate_empty_trajectory(
n_frames=expected_length,
top=self._readers[0].featurizer.topology)
else:
X = np.empty((expected_length, ndim),
dtype=self._frag_reader.output_type())
return X