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Toolkit for data reduction, normalization, combination, visualization and analyis of triple-axis spectrometers, especially for Tapain and Sika

Project description

TasVisAn

TasVisAn is a Python library for data reduction, visualization, and analysis of neutron triple-axis spectrometers (TASs), particularly for the thermal-neutron triple-axis spectrometer Taipan and cold-neutron triple-axis spectrometer Sika at Australian Centre for Neutron Scattering, ANSTO. It can also be used for other triple-axis spectrometers in other facilities, for example, the thermal-neutron triple-axis spectrometer BT7 and the cold-neutron triple-axis spectrometer BT4 at NIST. More triple-axis spectrometers will be supported soon.

Install name: tasvisan
Import name: tasvisan


🚀 Installation

pip install tasvisan

📦 Usage

import tasvisan

# Example usage
# (replace with real functionality)
result = tasvisan.do_something()
print(result)

🎯 Features

Modular design for scientific workflows Lightweight and easy to integrate into existing pipelines Designed for extensibility in research environments Compatible with NumPy-based data processing Friendly GUI for Data Browsing

📁 Project Structure

tasvisan/
├── src/tasvisan/     # Main package (import tasvisan)
├── pyproject.toml    # Build configuration
├── README.md
└── LICENSE

🔬 Scope

This package is intended for:

Triple-axis Spectrometer Data Reduction, Normalization, Visualization, and Analysis

Quick Data Combination and Contour Mapping

Resolution Convolution Fitting to Inelastic Neutron Scattering Data

Experimental Planning and Command Validation and Simulation

Data Reduction and 3D Visualization of Multiplexing and Multi-analyzer Triple-axis Spectrometers

🛠️ Development

Repository:

https://github.com/gcdengansto/TasVisAn

Install in editable mode:

pip install -e .

📖 Documentation

Documentation is under development. Usage examples and tutorials can be found at https://github.com/gcdengansto/TasVisAn.

🤝 Contributing

Please contact the author for fixing bugs and adding additional functions

📜 License

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

👤 Author

Guochu Deng

Email: gc.deng.ansto@gmail.com

⚠️ Disclaimer

This software is provided for scientific research purposes. No guarantees are made regarding correctness or fitness for a particular application.

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