DNMR 1.6.4

A package to analyse the data generated by the frappy/NICOS interface, with the TNMR setup at Paul Scherrer Institut, Villigen, Switzerland

DNMR

The Data Analysis, Visualisation, and Interpretation Software for Nuclear Magnetic Resonance (DAVISNMR, or more simply DNMR) is a piece of software including a GUI to read and analyse files generated by the frappy-Tecmag NMR interface described here.

Features

• Quick comparison of completely separate datasets (parallel viewing and handling)
• Equally quick loading and combination of separate-but-related datasets for analysis (live concatenation of datasets)
• Auto or manual data re-phasing, both for individual data points or in bulk
• View time-domain and frequency-domain data
• Apply easily-customisable filters to time-domain data
• Common NMR analysis workflows including T₁ fitting, field scans, and inverse Laplace transforms (ILTs)
• Export processed data into an easy-to-handle CSV format
• Easily extensible framework for custom analyses
• Limited support for .TNT files natively generated by Tecmag's TNMR program

Installation

This software is available on Pip:

python -m pip install DNMR

Running

Simply load the software as a module. For example:

python -m DNMR

Any additional arguments will be loaded as datafiles into the zero-th channel. I.e., if you wanted to load "test_file_0p25K.hdf" and "test_file_1K.hdf" together, you'd run:

python -m DNMR test_file_0p25K.hdf test_file_1K.hdf

(one could also just use the buttons and dialogs in the GUI)

Modification

To add new tabs, there are a few different steps:

1. Read through tab.py. This is the class that your new tab will be inheriting from. a. Take specific note of the functions generate_layout, plot_logic, and get_exported_data. These are the functions you'll override. b. Notice that every tab is given a matplotlib axis, self.ax, a reference to data_widgets['fileselector'] (self.fileselector), and a shared pool of other tabs, self.data_widgets, which it adds itself to upon construction.
2. Create a new file, example_tab.py for example. a. "Fill in" the functions listed above. Don't forget to supercall the Tab constructor b. Feel free to take functionality from miniwidgets.py, pull data from other widgets (from data_widgets[X].data, for example; these tabs are all designed under a "friendly" architecture, in C++ terms), and separate plot_logic and update calls intelligently.
3. Once you're happy with some basic functionality, edit the __main__.py file. a. In the MainWindow __init__ function, you'll need to create your tab with the rest of them. b. After creation, you must add your tab to the tabwidget_tabs object so that it will be loaded as a functional tab.

Once you've completed the above, you should see your tab in the main window.

Notes

If you're editing the code, it may be most useful to git clone the repository, then pip install -e . inside, to create a suitable development environment. I learned about this functionality through this project, so you might too :)