Getting started

Prerequisites

You need Python version 3.8 or later. Versions up to and including 3.11 are tested, version 3.12 is not tested on deployment with Github Actions but successfully tested locally.

You can install Python from https://www.python.org or https://www.anaconda.com.

Installation

QATS is installed from PyPI by using pip:

$ python -m pip install qats

Now you should be able to import the package in the Python console

>>> import qats
>>> help(qats)

Help on package qats:

NAME
    qats - Library for efficient processing and visualization of time series.

PACKAGE CONTENTS
    app (package)
    cli
    fatigue
    gumbel
    gumbelmin
    rainflow
    readers (package)
    signal
    stats
    ts
    tsdb
    weibull
...
...
>>>

and run the command line interface (CLI).

$ qats -h

usage: qats [-h] [--version] {app,config} ...

QATS is a library and desktop application for time series analysis

optional arguments:
  -h, --help    show this help message and exit
  --version     Package version

Commands:
  {app,config}
    app         Launch the desktop application
    config      Configure the package

Note

As of version 5.0.0, qats installs the Qt binding PySide6. Although not recommended, you can choose a different qt binding yourself by installing the package and setting the environmental variable QT_API. Accepted values include pyqt6 (to use PyQt6) and pyside6 (PySide6). For more details, see README file for qtpy.

Note

As of version 4.11.0, the CLI is also available through the python -m switch, for example:

$ python -m qats -h
$ python -m qats app

Launching the GUI

The GUI is launched via the CLI:

$ qats app

If using qats on Windows, you may add a shortcut for launching the qats GUI to your Windows Start menu and on the Desktop by running the command:

C:\> qats config --link-app

Your first script

Import the time series database, load data to it from file and plot it all.

"""
Example of using the time series database class
"""
import os

from qats import TsDB

db = TsDB()

# locate time series file
file_name = os.path.join("..", "..", "..", "data", "mooring.ts")

# load time series from file
db.load([file_name])

# plot everything on the file
db.plot()

Take a look at Code examples and the API Reference to learn how to use qats and build it into your code.