nmrkit

nmrkit is a Python library for nuclear magnetic resonance (NMR) data processing and analysis.

This is an early-stage project under active development. Contributions are welcome to help expand its capabilities!

Features

• Data Import/Export: Support for common NMR formats including TopSpin and Delta
• Basic Processing: Fourier transform, apodization (exponential multiplication), zero filling, phase correction
• Visualization: Interactive plotting with customizable parameters
• Simple API: Intuitive functions for data processing workflows

Requirements

• Python >= 3.12
• NumPy
• SciPy
• Matplotlib (optional, for visualization)

Installation

From PyPI (Recommended)

pip install nmrkit

With visualization support:

pip install nmrkit[visualization]

Quick Start

Automatic Processing

Use the auto_process function for automated application of common processing steps:

import nmrkit as nk

# Load NMR data
data = nk.read('path/to/data')

# Automatically process the spectrum
data = nk.auto_process(data)

# Save the plot to a PDF file
nk.plot(data, output_path="spectrum.pdf")

Manual Processing

For more control, use individual processing functions:

import nmrkit as nk

# Load data with explicit format specification
data = nk.read('path/to/data.jdf', format='delta')

# Apply exponential multiplication (apodization) with 1.0 Hz line broadening
data = nk.em(data, lb=1.0)

# Zero fill to 2048 points for improved resolution
data = nk.zf(data, size=2048)

# Perform Fourier transform
data = nk.ft(data)

# Apply phase correction
data = nk.phase(data, ph0=10.0, ph1=25.0)

# Plot the manually processed spectrum
nk.plot(data)

License

nmrkit is released under the Apache License 2.0. See the LICENSE file for more information.

Contributing

The nmrkit project welcomes your expertise and enthusiasm!

Reporting Issues

If you encounter a bug or have an idea for a new feature, please open an issue on GitHub. When reporting bugs, please include:

• A clear description of the issue
• Steps to reproduce (if applicable)
• Expected vs actual behavior
• Your Python version and operating system

Contributing Code

To contribute code to nmrkit:

1. Fork and Clone: Fork the repository and clone it locally
2. Set up Development Environment:

   poetry install

3. Create a Branch: Create a new branch for your feature or bug fix

   git checkout -b feature/your-feature-name

4. Make Changes: Implement your changes following the existing code style
5. Run Tests: Ensure all tests pass

   poetry run pytest

6. Commit: Commit your changes with clear, descriptive messages
7. Push and Submit PR: Push to your fork and submit a pull request

Development Guidelines

• Follow PEP 8 style guidelines
• Add type hints for new functions
• Include docstrings following the existing format
• Add tests for new functionality
• Ensure all tests pass before submitting PR

Small improvements or fixes are always appreciated. Even minor contributions can make a significant difference!

Contact

• GitHub Repository: https://github.com/nmrtist/nmrkit