README - Setup Guide for Virtual Environment

Purpose of the Repository

This repository is dedicated to replicating the results displayed in our study currently under revision for publication in a peer-reviewed journal. It includes all necessary Python scripts, data processing tools, and documentation needed to reproduce the findings as presented in our submission. Our goal is to facilitate transparency, validation, and further research by providing a comprehensive and accessible resource for replicating our study's results.

Introduction

This guide provides step-by-step instructions to set up the virtual environment required for running the Python analysis code. The code utilizes several libraries including matplotlib, numpy, pandas, mpl_toolkits.axes_grid1, seaborn, and scipy.

Prerequisites

• Python (latest stable release recommended)
• Git (for version control, optional)
• Command Line Interface (CLI) such as Terminal on MacOS/Linux or Command Prompt/Powershell on Windows.

Setting Up the Virtual Environment

1. Clone the Repository (Optional)

If the code is hosted on a version control platform like GitHub:

git clone [URL of the Repository]
cd [Repository Name]

2. Creating a Virtual Environment

Navigate to the project directory and create a virtual environment.

# On MacOS/Linux
python3 -m venv venv

# On Windows
python -m venv venv

3. Activating the Virtual Environment

Activate the created virtual environment.

# On MacOS/Linux
source venv/bin/activate

# On Windows
venv\Scripts\activate

4. Installing Dependencies

Install the required libraries using the provided requirements.txt or environment.yml.

pip install -r requirements.txt

5. Deactivating the Virtual Environment

After running the code, you can deactivate the virtual environment.

deactivate

Troubleshooting

If you encounter any issues with library versions or compatibility, ensure you're using the Python version recommended and the correct versions of the libraries as specified in requirements.txt.

Additional Notes

• Ensure that your data files, if any, are placed in the designated directories as per the project's file structure.
• For any specific configurations or environment variables, refer to the project's documentation.