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:
.. code-block:: yaml
:linenos:
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 :doc:`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 :doc:`at the beginning `, those familiar with its :doc:`underlying concepts ` may jump straight to the section explaining frequent :doc:`use cases `.
The :doc:`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:
.. code-block:: bash
pip install trepr
Have a look at the more detailed :doc:`installation instructions ` as well.
Related projects
----------------
There is a number of related packages users of the trepr package may well be interested in, as they have a similar scope, focussing on spectroscopy and reproducible research.
* `ASpecD `_
A Python framework for the analysis of spectroscopic data focussing on reproducibility and good scientific practice. The framework the trepr package is based on, developed by T. Biskup.
* `cwepr `_
Package for processing and analysing continuous-wave electron paramagnetic resonance (cw-EPR) data, originally implemented by P. Kirchner, currently developed and maintained by M. Schröder and T. Biskup.
You may as well be interested in the `LabInform project `_ focussing on the necessary more global infrastructure in a laboratory/scientific workgroup interested in more `reproducible research `_. In short, LabInform is "The Open-Source Laboratory Information System".
Finally, don't forget to check out the website on `reproducible research `_ covering in more general terms aspects of reproducible research and good scientific practice.
..
Contribute
----------
- Source Code: https://github.com/tillbiskup/trepr
License
-------
This program is free software: you can redistribute it and/or modify it under the terms of the **BSD License**.
A note on the logo
------------------
The snake (a python) resembles the lines of a tr-EPR spectrum, most probably a light-induced spin-polarised triplet state. The copyright of the logo belongs to J. Popp.
.. toctree::
:maxdepth: 2
:caption: User Manual:
:hidden:
audience
introduction
concepts
usecases
installing
.. toctree::
:maxdepth: 2
:caption: tr-EPR Primer:
:hidden:
trepr/index
trepr/setup
trepr/recording
trepr/processing
trepr/analysis
.. toctree::
:maxdepth: 2
:caption: Developers:
:hidden:
people
developers
changelog
roadmap
dataset-structure
api/index