Spherical Constrained Optimization for Rotational Localization (SCORL)-new 2026

OverviewSCORL is a Monte Carlo‑based method for reconstructing paleo‑positions of tectonic plates using Euler rotations and geometric constraints. It integrates spherical triangle acuteness, angular limits, and rigid‑plate distance consistency to determine the optimal paleolongitude of a target block (Point B) and its robust uncertainty bounds, given observed paleolatitudes and rotation parameters. Model VersionsThis package contains three independent model implementations, each provided in R and Python: Three‑time‑slice model (377 Ma → 353 Ma → 287 Ma) Designed to test the rigid‑plate behaviour of the Indian Plate over 90 Myr and estimate the north‑south width of Greater India (A‑B distance). Outputs robust estimates (median ± half‑IQR of the top 10% solutions) and 95% confidence intervals. Two‑time‑slice model (377 Ma → 353 Ma) Designed to test the rigid‑plate behaviour of the Indian Plate over 20 Myr and estimate the north‑south width of Greater India (A‑B distance). Model test files Contain sample input data (Jin et al., 2026, EPSL), known point coordinates, rotation parameters, and test scripts for quick environment validation. Key Features Fully self‑consistent geometric and kinematic constraints Robust uncertainty quantification (median + half‑IQR) High‑quality publication‑ready plots (longitude distributions, rigidity histograms, scatter plots, spatial maps) Customizable iteration numbers and parameter ranges How to Use Unzip any package and follow the README instructions to set up R or Python. Run the main script (SCORL_*.R or SCORL_*.py). Results (console outputs and six‑panel figures) will be saved to the designated output folder.