Welcome to QATS’s 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.

Source code

The source code, issue tracker and changelog is on GitHub.

Downloads

You can download and install QATS from PyPI.

Table of contents

• Getting started
  • Prerequisites
  • Installation
  • Your first script
• Code examples
  • Plot time series and power spectral density
  • Count cycles using the Rainflow algorithm
  • Calculate fatigue damage in mooring lines
  • Apply low-pass and high-pass filters to time series
  • Merge files and export to different format
• Graphical User Interface
  • Create link to GUI in start menu and desktop
  • Import time series from file
• API Reference
  • Top-level classes
  • Submodules
  • Subpackages

Indices and tables

• Index

• Module Index

• Search Page