Getting started

Prerequisites

You need Python version 3.6 or later. You can find it at https://www.python.org or https://www.anaconda.com.

Installation

Note

As of version 4.2.0, you must install the desired qt binding yourself (needed for the GUI to work). Supported packages are: PyQt5, Pyside2, PyQt4 and Pyside. See installation instructions below.

QATS is installed from PyPI by using pip:

pip install qats

In order to use the GUI, you must also install a Python package with qt bindings (here, PyQt5 is used as an example):

pip install pyqt5

Supported qt bindings are: PyQt5, Pyside2, PyQt4 and Pyside.

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 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

You can also add shortcuts for the QATS GUI to your start menu and desktop.

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.