relaxometrynmr: NMR relaxometry made easy !

relaxometrynmr an open-source Python package for solid-state NMR relaxation data analysis: T1, T1_rho and T2.

This package is only compatible with Bruker's NMR data (see User's guide).

Why relaxometrynmr?

This package is built for NMR relaxometry data analysis and offers a user-friendly data processing. It streamlines the analysis of relaxation time constant (T1, T1_rho or T2) and reduces analysis time by more than 50%. It comprises several built-in modeling functions such as mono-, di-, tri-, and stretch-exponential. These functions offer the flexibility to model a wide range of relaxation behaviors -- from simple to complex systems.

Key Features

Comprehensive NMR Data Handling

• Supports mainly Bruker's data
• Handles data reading, conversion, and processing seamlessly
• Automatically detects and loads delay list (vdlist, vplist, or vclist) for relaxometry experiments

Advanced Data Processing

• Zero-filling for improved spectral resolution
• Phase correction (0th and 1st order) for signal representation in pure-absorption mode
• Gaussian apodisation for line broadening and improvement of signal-noise ratio

Spectral Integration

• Numerical integration methods (trapezoid and Simpson's rule) for robust quantification of peak area

Visualisation

• Full spectrum view for context
• Zoomed-in region for detailed analysis

Modelling and Data Fitting

• multiple-component models: mono-, bi-, and tri-exponential functions for simple to complex relaxation
• stretched exponential models: for systems with non-standard relaxation dynamics (e.g., disordered materials)
• decay analysis: tools for analysing exponential decay curves with multiple components

Install

pip install relaxometrynmr

Dependencies

The following packages are required:

nmrglue 
numpy
matplotlib >= 3.9.0
mrsimulator = 1.0

You can install these dependencies using pip:

pip install nmrglue numpy scipy mrsimulator = 1.0

Examples can be found in User Guide

Contact

For questions and support, please open an issue in the GitHub repository.