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https://github.com/yuweaec/project-scidatapipeline

A comprehensive toolkit for processing, simulating, and analyzing scientific data, integrating Python, Fortran, and Jupyter notebooks for seamless workflows.
https://github.com/yuweaec/project-scidatapipeline

analysis data pipeline processing scientific simulation

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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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README

          

# Scientific Data Processing and Analysis Project

## Table of Contents

1. [Overview](#overview)
2. [Project Structure](#project-structure)
3. [Installation](#installation)
4. [Usage](#usage)
5. [Contributing](#contributing)
6. [License](#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_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**:
```sh
git clone https://github.com/yourusername/yourproject.git
```
2. **Navigate to the project directory**:
```sh
cd yourproject
```
3. **Create a virtual environment** (optional but recommended):
```sh
python3 -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
4. **Install the required dependencies**:
```sh
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:

```sh
bash src/sourcecode.b
```

### Running Fortran Simulation

Compile and run the Fortran simulation:

```sh
bash src/csrc.b
```

### Running Jupyter Notebooks

To analyze the data using Jupyter Notebooks, run:

```sh
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](LICENSE) file for details.

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