Welcome to the documentation of dtaianomaly!
============================================

``dtaianomaly`` is an easy-to-use Python package for time series anomaly detection. Its main
goal is to offer a simple interface to detect anomalies in time series data using
state-of-the-art methods. Additionally, ``dtaianomaly`` provides a benchmark framework to
quantitatively evaluate time series anomaly detection methods on a large repository of
time series.

The source is available on `GitHub <https://github.com/ML-KULeuven/dtaianomaly>`_.

.. toctree::
   :maxdepth: 1
   :caption: Getting started

   getting_started/installation
   getting_started/anomaly_detection
   getting_started/custom_models
   getting_started/quantitative_evaluation
   getting_started/data

.. toctree::
   :maxdepth: 1
   :caption: Documentation

   api/anomaly_detection
   api/data
   api/preprocessing
   api/thresholding
   api/evaluation
   api/pipeline
   api/workflow
   api/visualization