Overview | Import Pipeline | Full Millipede Dataset | Plotting Trajectories | Colour tracks by position | Representing time | Heading Overlays | Circular Interval Arc | Building Up a Panel | Circular Boxplot | Colour Options | Per-Condition Panels | Circular Density Overlays | Bootstrap Confidence Band | Circular Summary Statistics | Alternative Heading Rules | distal | net | Simulating Demo Data

Overview | A heading data frame | Dispersion summaries | Parametric fits | Hypothesis tests | Uniformity | Equal mean directions | Equal concentrations | Circular correlation | Circular regression | Distribution overlays | Per-group overlays | Significance geometry | Where next

Rich objects, only where structure is irreducible | Everything else is a plain tibble, in and out | headings_frame: a dplyr-durable tibble subclass

Overview | Quick Start | Output Formats | Plotting the Default Simulation | The Conditions Table | Concentration (κ) | Tortuosity and Path Smoothness | Directional Bias (ref_mean) | Multi-Condition Gradient | Continuous Predictor | Connecting to Circular Analysis | Known Modality and Shape | Reproducibility and Saving

Overview | Loading a Real Experiment | Step 1 — discover files | Step 2 — read the manifest | Step 3 — join metadata | Step 4 — extract and normalise trajectories | dtrack format | Tracking-tool format support | Bundled single-file examples | Reading Tabular Trajectories | Manifest Helpers (Synthetic Example) | Registering a Custom Dialect