common Toolbox

A MATLAB(r) toolbox providing basic functionality for data analysis that is used in other toolboxes, such as the cwEPR toolbox. Therefore, this toolbox is a bit of a "meta toolbox". Generally this toolbox will get included into all the other toolboxes eventually.

This toolbox is the spiritual predecessor of the ASpecD framework implemented in Python. Each processing and analysis step gets automatically logged with all parameters to ensure reproducibility. Provides basic functionality for installing and configuring as well as standard processing steps.

Note: While this MATLAB(r) toolbox should still work with current versions of MATLAB(r), you may be interested in the Python framework ASpecD actively being developed and dedicated to fully reproducible data analysis.

Features

The common toolbox provides functions to handle, inter alia:

• configuration files
• toolbox maintenance: installation, info, ...
• datasets and their structures, including IO
• plotting (including axis labels etc.)
• exporting figures
• common processing tasks (polynomial fit, SNR determination, ...)
• handling info files
• IO for binary and text files

Installation

Download the toolbox (usually as compressed archive), uncompress (if necessary), start MATLAB(r), change to the folder you have downloaded/uncompressed the toolbox files to, change to the directory internal and call the function commonInstall from within the MATLAB(r) command line. This should guide you through the installation process (and add, inter alia, the toolbox to the MATLAB(r) search path).

How to cite

The cwEPR toolbox is free software. However, if you use it for your own research, please cite it accordingly:

• Till Biskup, Deborah Meyer. common toolbox (2022). doi:10.5281/zenodo.7396144

  

License

The toolbox is distributed under the GNU Lesser General Public License (LGPL) as published by the Free Software Foundation.

This ensures both, free availability in source-code form and compatibility with the (closed-source and commercial) MATLAB(r) environment.

Authors

• Till Biskup (2014-2022)

  The principal author and main developer of the common toolbox

• Deborah Meyer (2014-15)

  Valuable contributions during her PhD time

Related projects

There is a number of related MATLAB(r) projects you may be interested in, but have a look at the section with related Python projects as well that are actively being developed.

MATLAB(r) projects

• epr toolbox

  Toolbox for analysing EPR data (common Toolbox based). Each processing and analysis step gets automatically logged with all parameters to ensure reproducibility. Provides basic functionality and processing steps for EPR spectroscopy.

• cwepr toolbox

  Toolbox for analysing cwEPR data (common Toolbox based). Spiritual predecessor of the cwepr package implemented in Python. Each processing and analysis step gets automatically logged with all parameters to ensure reproducibility. Focusses particularly on automating the pre-processing and representation of data.

• trepr toolbox

  Toolbox for preprocessing, display, analysis, and postprocessing of transient (i.e., time-resolved) electron spin resonance spectroscopy (in short: trEPR) data. Spiritual predecessor of the trepr package implemented in Python. Each processing and analysis step gets automatically logged with all parameters to ensure reproducibility. Focusses particularly on automating the pre-processing and representation of data.

• TSim (Documentation)

  A toolbox for the simulation and fitting of spin-polarised triplet states, using EasySpin for the simulation part, but guiding the user with an extensive CLI and creating well-formatted reports of the results for enhanced reproducibility. Developed by D. Meyer and maintained by T. Biskup.

• TA toolbox

  Toolbox for preprocessing, display, analysis, and postprocessing of transient absorption (flash photolysis) data. Similarly to the trEPR toolbox, the TA toolbox is fully GUI-based, but all functions are accessible via command line (CLI) as well. Furthermore, the GUI is extensively documented.

Python projects

• ASpecD framework

  A Python framework for the analysis of spectroscopic data focussing on reproducibility and good scientific practice, developed by T. Biskup.

• cwepr package

  Python package for processing and analysing continuous-wave electron paramagnetic resonance (cw-EPR) data, originally implemented by P. Kirchner, developed and maintained by M. Schröder and T. Biskup.

• trEPR package

  Python package for processing and analysing time-resolved electron paramagnetic resonance (trEPR) data, developed by J. Popp, currently developed and maintained by M. Schröder and T. Biskup.

• FitPy

  Python framework for the advanced fitting of models to spectroscopic data focussing on reproducibility, developed by T. Biskup.