QATS documentation#

General description#

QATS is a python library and GUI for efficient inspection and analysis of time series. It simplifies and improves post-processing, quality assurance and reporting of time-domain simulations.

Library#

The python library provides tools for:

  • Import and export from/to various pre-defined time series file formats

  • Signal processing

  • Inferring statistical distributions

  • Cycle counting using the Rainflow algorithm

It was originally created to handle time series files exported from SIMO and RIFLEX. Now it also handles SIMA hdf5 (.h5) files, Matlab (version < 7.3) .mat files, CSV files and more. If you need handlers for other formats, create a feature request (issue) or make it yourself and create a pull request.

See Code examples for more examples on how to invoke QATS in your own scripts to do more advance operations. API Reference provide information on the content of the QATS library.

GUI#

QATS also features a Graphical User Interface which offers low threshold processing and vizualisation of time series. It is perfect for inspecting, quality assurance and reporting. Use the library for more advanced operations.

_images/demo.gif

Python version support#

QATS currently supports Python version 3.8+.

Note

Python version <=3.11 is recommended, as version 3.12 is not yet formally tested.

Source code, Issue tracker and Changelog#

The source code, issue tracker and changelog are hosted on GitHub.

Downloads#

QATS may be downloaded from PyPI/qats. See the Getting started section for installation instructions.

Table of contents#