gul916 / NMR_post_proc

Post Processing of NMR data

NMR_post_proc

Post Processing of NMR Bruker data using Topspin software

Written by Guillaume LAURENT and Pierre-Aymeric GILLES in 2017-2019

Introduction

Two kinds of files are present in this repository :

• Jython files based on Java language. They are in NMR_post_proc directory and provide an interface from Topspin to standard Python files.
• Standard Python files based on C language (CPython). They are in CPython subdirectory and can be started directly with a Python 3 program.

Prerequisites

• Install Bruker Topspin
• Install Anaconda Python. It uses Intel MKL library which is especially fast.
• Install nmrglue: pip install nmrglue-0.7-py2.py3-none-any.whl

Installation

• Download NMR_post_proc.zip.
• Extract NMR_post_proc.zip into the desired directory.
• Modify CPython_init.py according to Anaconda and NMR_post_proc directories.
• Under Windows, copy CPython_init.py into 'C:\Bruker\TopSpin3.6.1\exp\stan\nmr\py\user'.
• Under Linux, copy CPython_init.py into '/opt/Bruker/TopSpin3.6.1/exp/stan/nmr/py/user'.
• In Topspin, click on Manage tab and preferences button, locate Directories section, "Manage source directories for edpul, edau, etc." and click on "Change". Select "Python Programs", and add NMR_post_proc directory.
• Restart Topspin.

Tests

• Enter hello_numpy in Topspin command line. In Topspin, you should see a message window with various libraries refering to anaconda and MKL.
• Open a processed 1D or 2D dataset. Enter hello_nmrglue in Topspin command line. You should see a figure of the corresponding spectrum.

Further CPython_init.py modifications

If you further modify CPython_init.py, you will need to remove CPython_init$py.class file in $TOPSPIN/exp/stan/nmr/py/user and to restart Topspin.

Citing this work

• Concerning Signal-to-Noise Ratio (SNR) and Singular Value Decomposition (SVD) generalities

G. Laurent, W. Woelffel, V. Barret-Vivin, E. Gouillart, and C. Bonhomme ‘Denoising applied to spectroscopies – part I: concept and limits’ Appl. Spectrosc. Rev., vol. 54, no. 7, pp. 602–630, 2019. Available at https://hal.archives-ouvertes.fr/hal-01879736

• Concerning SVD computation time and denoising program

G. Laurent, P.-A. Gilles, W. Woelffel, V. Barret-Vivin, E. Gouillart, and C. Bonhomme ‘Denoising applied to spectroscopies – Part II: Decreasing computation time’ Appl. Spectrosc. Rev., in press, 2019, doi: 10.1080/05704928.2018.1559851 Available at https://hal.archives-ouvertes.fr/hal-02063604

Acknowledgments

Julien TREBOSC is thanked for providing sample code in https://github.com/jtrebosc/JTutils, especially for the subprocess call.