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trEPR documentation

Welcome! This is the documentation for trEPR, a Python package for processing and analysis of time-resolved electron paramagnetic resonance (tr-EPR) spectra based on the ASpecD framework. For general information see its Homepage. Due to the inheritance from the ASpecD framework, all data generated with the trepr package are completely reproducible and have a complete history.

What is even better: Actual data processing and analysis no longer requires programming skills, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Have a look at the following example:

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default_package: trepr

datasets:
  - /path/to/first/dataset
  - /path/to/second/dataset

tasks:
  - kind: processing
    type: PretriggerOffsetCompensation
  - kind: processing
    type: BackgroundCorrection
    properties:
      parameters:
        num_profiles: [10, 10]
  - kind: singleplot
    type: SinglePlotter2D
    properties:
      filename:
        - first-dataset.pdf
        - second-dataset.pdf

Interested in more real-live examples? Check out the use cases section.

Features

A list of features:

  • Fully reproducible processing of tr-EPR data

  • Import and export of data from and to different formats

  • Customisable plots

  • Automatically generated reports

  • Recipe-driven data analysis, allowing tasks to be performed fully unattended in the background and without programming skills

And to make it even more convenient for users and future-proof:

  • Open source project written in Python (>= 3.5)

  • Extensive user and API documentation

Warning

The trepr package is currently under active development and still considered in Beta development state. Therefore, expect frequent changes in features and public APIs that may break your own code. Nevertheless, feedback as well as feature requests are highly welcome.

Where to start

Users new to the trepr package should probably start at the beginning, those familiar with its underlying concepts may jump straight to the section explaining frequent use cases.

The API documentation is the definite source of information for developers, besides having a look at the source code.

Installation

To install the trepr package on your computer (sensibly within a Python virtual environment), open a terminal (activate your virtual environment), and type in the following:

pip install trepr

Have a look at the more detailed installation instructions as well.

License

This program is free software: you can redistribute it and/or modify it under the terms of the BSD License.