Package index • cplass

Main algorithm

Run CPLASS and manage the Metropolis-Hastings search.

CPLASS(): Run CPLASS on a single 2D trajectory
CPLASS_multistart(): Run CPLASS from multiple independent random starts and keep the best
MHsearch(): Metropolis-Hastings search over the changepoint space
FinalMH(): Collect a Metropolis-Hastings trace into flat vectors/lists

Check whether the stochastic search has stabilized.

check_convergence(): Check whether a single CPLASS chain has stopped improving
plot_convergence(): Plot a CPLASS chain's convergence trace

Continuous piecewise-linear MLE given a set of changepoints (Section 2.2 of the paper).

piecewise_linear_con(): Continuous piecewise-linear fit given a set of changepoints
build_j_inferred(): Broadcast per-segment states back onto the original observation grid

The penalized-likelihood criterion Phi(r) (Section 2.3).

CS(): Criterion function for a changepoint configuration
loglikelihood(): Gaussian log-likelihood from residual sum of squares
sSIC(): Strengthened Schwarz Information Criterion penalty
AICc(): Corrected AIC penalty
cp_to_r(): Convert a changepoint index vector to a 0/1 indicator vector
r_to_cp(): Convert a 0/1 changepoint indicator vector to changepoint indices

The four changepoint-proposal types described in Section 2.4.

log_q_new_pmf() q_new() log_q_bd_pmf() q_bd() q_shift() q_as_pmf() q_as() q_ds_pmf() q_ds() q_bd2() log_q_bd2_pmf() proposal_function() pproposal(): Proposal functions for the CPLASS Metropolis-Hastings sampler

Duration-weighted speed summaries (Cook et al. 2025).

compute_csa(): Cumulative Speed Allocation (CSA)
csa_theoretical(): Theoretical CSA under a two-state (stationary/motile) kinetic model
plot_csa(): Plot Cumulative Speed Allocation curves
summarize_segments(): Stack segment summaries from a list of true (ground-truth) paths
summarize_segments_inferred(): Stack segment summaries from a list of CPLASS-inferred paths
summarize_segments_cutoff(): Stack segment summaries from inferred paths (cutoff-labeled states)
summarize_segments_test(): Stack segment summaries using a threshold-based test-state column

plot_path_inferred(): Four-panel dashboard for a single CPLASS-segmented trajectory
plot_path_inferred_second_version(): Alternate 3-row layout for a single segmented trajectory
plot_path_inferred_xy(): Just the x-y panel of a segmented trajectory
plot_path_actual_and_inferred(): Side-by-side comparison of true vs. inferred segmentation
plot_msd(): Plot pathwise and ensemble MSD curves for a group, split by activity
get_plot_size(): Compute shared plot bounds across a list of ground-truth paths
get_plot_size_inferred(): Compute shared plot bounds across a list of inferred paths
get_one_plot_size(): Compute plot bounds for a single inferred path

fill_missing_data(): Fill gaps in an unevenly-sampled 2D trajectory
duration_of_difference(): Total duration over which true and inferred segmentations disagree on state
infer_states_speed_cutoff(): Classify inferred segments as motile/stationary by a speed cutoff
cplass cplass-package: cplass: Continuous Piecewise-Linear Approximation via Stochastic Search