| BaseFlatClusterer(metric[, trajectories, ...]) | (Abstract) base class / mixin that Clusterers can extend. Provides convenience |
| Clarans(metric[, trajectories, ...]) | |
| Hierarchical(metric, trajectories[, method, ...]) | |
| HybridKMedoids(metric[, trajectories, ...]) | |
| KCenters(metric[, trajectories, ...]) | |
| concatenate_prep_trajectories(...) | Concatenate a list of prepared trajectories and create a single prepared_trajectory. |
| unconcatenate_trajectory(trajectory, lengths) | Take a single trajectory that was created by concatenating seperate trajectories and unconcenatenate it, returning the original trajectories. |
| concatenate_trajectories(trajectories) | Concatenate a list of trajectories into a single long trajectory |
| deterministic_subsample(trajectories, stride) | Given a list of trajectories, return a single trajectory |
| stochastic_subsample(trajectories, ...) | Randomly subsample from a trajectory |
| p_norm(data[, p]) | p_norm of an ndarray with XYZ coordinates |