This series of notebooks are meant to illustrate the different features of the
*pyActigraphy* package:

* `a gentle introduction to the basic functionalities`_
* how to discard invalid sequences in actigraphy recordings before analysis:

  * `Invalid sequences during the recordings`_
  * `Invalid sequences at the beginning and/or the end of the recordings`_

* `how to calculate the usual rest-activity rhythm variables`_
* `how to visualise sleep diaries and compute summary statistics`_
* `how to detect rest periods automatically`_
* `how to quantify sleep fragmentation using state transition probabilities`_

.. _a gentle introduction to the basic functionalities: pyActigraphy-Intro.ipynb
.. _Invalid sequences during the recordings: pyActigraphy-Masking.ipynb
.. _Invalid sequences at the beginning and/or the end of the recordings: pyActigraphy-SSt-log.ipynb
.. _how to calculate the usual rest-activity rhythm variables: pyActigraphy-Non-parametric-variables.ipynb
.. _how to visualise sleep diaries and compute summary statistics: pyActigraphy-Sleep-Diary.ipynb
.. _how to detect rest periods automatically: pyActigraphy-Sleep-Algorithms.ipynb
.. _how to quantify sleep fragmentation using state transition probabilities: pyActigraphy-StateTransitionProb.ipynb

If a feature of the *pyActigraphy* package is not illustrated here, do not
hesitate to suggest it by fill an issue.

Or, even better, contribute to this section by providing us with your favourite
notebook where you illustrate how this feature is relevant for your analysis.