# Supplementary Material README

## Overview

The contents of this archive include the original and specialized models parameters, and minimal code to load and interact with the models.

## Contents

### 1. Models (`models/`)

This directory contains parameters for all mixture models reported in the paper in `.csv` format. 
These files can be loaded using the provided Python implementation (see below).


### 3. Minimal Code (`CBMD.py`)

A single Python file provides a lightweight, proof-of-concept implementation for:

* Loading the model parameter files
* Sampling the models
* Evaluating the model's density functions

This implementation is intentionally minimal and is not optimized for performance or production use. 

### 4. Example Notebook (`example_usage.ipynb`)

This Jupyter notebook demonstrates how to:

* Loads the baseline ALA model, and the ALA model conditioned on the 'P' dssp label, using the provided code
* Sample and plots datapoints from both models

## Requirements

To run the provided code and notebook, you will need:

* Python 3.8+
* Common scientific Python libraries (`numpy`, `scipy`, `matplotlib`)
* Jupyter Notebook or JupyterLab (for running the example notebook)