nmrkit 1.0.1

A lightweight Python package for NMR research.

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
• Acquisition Planning: Calculate DOSY diffusion experiment timing and gradient settings
• 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)

DOSY Acquisition Planning

Use acquisition helpers to estimate DOSY experiment settings from a diffusion coefficient and the maximum gradient strength of an instrument:

dosy_params = nk.calculate_dosy_settings(
    diffusion_coefficient_m2_s=5.8e-10,
    max_gradient_t_m=0.535,
    target_attenuation=0.05,
)

print(f"Diffusion time (big delta):   {dosy_params.diffusion_time_ms:.2f} ms")
print(f"Gradient duration (little delta): {dosy_params.gradient_duration_ms:.4f} ms")
print(f"Achieved residual signal:     {dosy_params.achieved_attenuation:.4f}")

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