Supplementary Data for: Embodied mechanical sensing through self-generated motion in climbing plants

This repository contains the complete dataset, analysis pipeline, and figure-generation code associated with the scientific article: “Embodied mechanical sensing through self-generated motion in climbing plants” Summary This project investigates the mechanics and dynamics of plant stem twining, contact initiation, and force generation through a combination of controlled experiments, motorized perturbations, and numerical simulations. The dataset includes tracking logs (side and top views), two-point contact tracking, material property measurements (Young’s modulus and radius profiles), motor-stage experiments, and simulation outputs. Custom-built experimental setups - including motorized rotation stages and 3D-printed mechanical components - were used to for specific experiments. The analysis framework extracts geometric variables (angles, curvature, support length), computes effective forces and resistances, performs sine fitting of oscillatory trajectories, and evaluates material-property-dependent behavior. The repository is structured to ensure reproducibility: Analysis of raw experimental tracking data Material property analysis Motor modified circumnutation twining analysis High/low support resistance twining analysis Fits and comparison to simulation data Reproducibility and Code Availability All figures in the manuscript can be regenerated directly from the raw data using the provided Python analysis pipeline. The accompanying GitHub repository contains the full modular codebase required to: Import raw tracking data Construct plant and event objects Perform geometric and mechanical analysis Fit trajectories and extract parameters Reproduce all manuscript and supplementary figures