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A comprehensive toolkit for processing, simulating, and analyzing scientific data, integrating Python, Fortran, and Jupyter notebooks for seamless workflows.

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Scientific Data Processing and Analysis Project

Table of Contents

  1. Overview
  2. Project Structure
  3. Installation
  4. Usage
  5. Contributing
  6. License

Overview

This project processes and analyzes scientific data from various datasets. It includes data processing scripts, simulation code, and analysis notebooks. The primary goal is to provide a robust framework for handling scientific data, running simulations, and visualizing results. The project is designed to be modular and easily extensible for future developments.

For a detailed overview, see PROJECT_OVERVIEW.md.

Project Structure

├── data
│   ├── base.dat
│   └── data.dat
├── docs
│   ├── documents.doc
│   └── newdocs.doc
├── notebooks
│   ├── code.ipynb
│   └── new.ipynb
├── src
│   ├── csrc.b
│   ├── hello.f
│   └── sourcecode.b
├── test
│   ├── testing.s
│   └── tests.s
├── .gitignore
├── LICENSE
├── README.md
├── requirements.txt
├── setup.py
  • assets: Contains image assets for the project.
    • readme_image.png: An example image used in the README.
  • data: Contains data files required for the project.
    • base.dat: An additional data file for base values.
    • data.dat: The main data file.
  • docs: Contains documentation files.
    • documents.doc: Detailed project documentation.
    • newdocs.doc: Additional documentation.
  • notebooks: Contains Jupyter notebooks for exploration and analysis.
    • code.ipynb: Main notebook for running the code.
    • new.ipynb: Additional notebook for further analysis.
  • src: Contains the source code of the project.
    • csrc.b: Bash script to compile and run Fortran code.
    • hello.f: Fortran source code for simulations.
    • sourcecode.b: Main script for data processing.
  • test: Contains tests for the project.
    • testing.s: Test script for data processing.
    • tests.s: Additional test script.
  • .gitignore: Specifies files and directories to be ignored by git.
  • LICENSE: License for the project.
  • README.md: This file, providing an overview of the project.
  • requirements.txt: List of dependencies required for the project.
  • setup.py: Script for installing the project.

Installation

Follow these instructions to set up the project on your local machine:

  1. Clone the repository:
    git clone https://github.com/yourusername/yourproject.git
  2. Navigate to the project directory:
    cd yourproject
  3. Create a virtual environment (optional but recommended):
    python3 -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
  4. Install the required dependencies:
    pip install -r requirements.txt

Usage

Here are some examples and instructions on how to use the project.

Processing Data

Run the main script to process the data:

bash src/sourcecode.b

Running Fortran Simulation

Compile and run the Fortran simulation:

bash src/csrc.b

Running Jupyter Notebooks

To analyze the data using Jupyter Notebooks, run:

jupyter notebook notebooks/code.ipynb

Contributing

We welcome contributions! Please follow these steps:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature-branch).
  3. Make your changes.
  4. Commit your changes (git commit -am 'Add new feature').
  5. Push to the branch (git push origin feature-branch).
  6. Create a new Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.


Feel free to further customize this README file to better suit your project's specific details and requirements.


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A comprehensive toolkit for processing, simulating, and analyzing scientific data, integrating Python, Fortran, and Jupyter notebooks for seamless workflows.

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