ReaFS Analysis

This repository contains the analysis code to reproduce the results and plots from the main manuscript and supplementary information.

Setup

Prerequisites

• Python 3.12 or higher
• uv (recommended) or pip
• reafs
• ipykernel
• ipywidgets

See pyproject.toml for complete dependency specifications. Most of the dependencies are installed with reafs.

Installation

Using uv (recommended)

uv sync

Notes

The reafs package is expected to be located in the parent directory. Modify pyproject.toml accordingly.

Main Scripts

Results & Plots

• plot_cc_model_cards_1.py - Generate parts of the model "cards" for the featurization comparison as in the main manuscript.
• plot_cc_model_cards_SI_1.py - Supplementary information version of model cards for the featurization comparison
• plot_data_diagno_1.py - Diagnostic plots for data analysis
• plot_data_g23_outliers_1.py - Outlier analysis and visualization
• plot_fs_common_1.py - Visualize common feature selections across analyses
• plot_fs_sequential_extension_1.py - Sequential feature selection extension plots
• plot_oa_prospect_1.py - Prospective analysis "cards" parts.
• plot_oa_prospect_SI_1.py - Supplementary information for the prospective analysis

Utilities

• svg_composer_feat.py - Compose the final plot from the featurization comparison from all the parts
• svg_composer_prosp.py - Compose the final plot from the prospective analysis from all the parts

Running the Analysis

To run a specific analysis script:

uv run python script_name.py

Or,

python script_name.py

Output

Results and generated figures are saved to the results/ directory.

Acknowledgments

This project was created as part of NCCR Catalysis (grant number 225147), a National Centre of Competence in Research funded by the Swiss National Science Foundation.