Research

Reproducible Data Analysis

Reproducible Research

Concepts

Ideas and tools for reproducibility

ASpecD

Python framework for reproducible data analysis

LabInform

Infrastructure for reproducible research

Python Packages

Python is an excellent choice if it comes to writing software for scientific data analysis. With its comparably simple syntax it is easy to learn yet powerful. The scientific software stack (SciPy) is well developed, and perhaps the best: Python is free software.

trepr

Python package for trEPR data (ASpecD based)

cwepr

Python package for cwEPR data (ASpecD based)

UVVisPy

Python package for UVVis data (ASpecD based)

SpinPy

Python package for simulating EPR spectra

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FitPy

Python package for fitting spectroscopic data

MATLAB® Toolboxes

MATLAB® has long been a prime choice for writing software for scientific data analysis. It features a very simple to use GUI, simple syntax, and excellent support for all kinds of data processing. However, it is not a general-purpose language and quite expensive.

trepr

Toolbox for analysing trEPR data (with GUI)

TSim

Toolbox for simulating and fitting triplet spectra

TA

Toolbox for analysing TA data (with GUI)

common

Base toolbox for data analysis

epr

Toolbox for analysing EPR data

cwepr

Toolbox for analysing cwEPR data

eprfit

Toolbox for fitting EPR spectra

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eprcontrol

Toolbox for controlling EPR spectrometers

A note on the logos: The copyright of the Python logo belongs to the Python Software Foundation (PSF), that of the MATLAB® logo to The Mathworks, Inc. Both logos appear here only to highlight the programming languages used. The copyright of the logos for the Python ASpecD, LabInform, cwepr, trepr, UVVisPy, FitPy, and SpinPy packages as well as for “Reproducible Research” belongs to Jara Popp.