The SyncPy Python Library is an ongoing open-source project conceived and developed at the Institut des Systèmes Intelligentes et Robotique (ISIR) at the Université Pierre et Marie Curie (UPMC), Paris 6, France.

SyncPy library is currently under development in the framework of the SMART Labex Project (http://www.smart-labex.fr)

SyncPy is a novel open-source analytic library for investigating synchrony in a fast and exhaustive way. It stems from work and discussions among researchers on synchrony in different domains as engineering, computer science and psychology.

SyncPy is mainly aimed at helping researchers to explore, try and compare in an easy way and with a single tool synchrony methods starting from signals. Signals are synthetic or experimental time series organized as Python pandas DataFrames.

The library has been conceived to investigate synchrony in human-human/ human machine interaction, however, although it focuses on interpersonal synchrony, all the methods are exploitable in other contexts.

SyncPy includes three main components:

• Utils package
• Graphical interface
• Synchrony methods package

The utils package contains functionals of general utility directly used by the synchrony methods or to preprocess the input signals.

The graphical interface is a pyQT application conceived to assist users to choose and try several methods. More specifically, it allows users to:

1. load time series from files
2. visualize these time series
3. choose a consistent method according to the data set
4. compute the selected method and
5. visualize and/or save the result in a file (.csv format, .png format).

The synchrony methods package contains the methods to compute synchrony. The methods are organized following the structure described in the paper: "SyncPy - A unified analytic library for synchrony" (see References).

Version number : 2.0 Last update : 14/09/2016

News :

• New GUI

• Python 2.7
• Mathplotlib 1.4.3

• Matplotlib: http://matplotlib.org/downloads.html
• If you are Working with Matplotlib in a virtual environment see 'Working with Matplotlib in Virtual environments' in the Matplotlib FAQ
• NetworkX: https://networkx.github.io/download.html
• Numpy and Scipy: http://www.scipy.org/scipylib/download.html
• Pandas: http://pandas.pydata.org/pandas-docs/stable/install.html
• Statsmodels and Patsy: http://statsmodels.sourceforge.net/install.html

For the interface:

• PyQt : http://pyqt.sourceforge.net/Docs/PyQt4/installation.html

• installers\ : it contains the installers for the following operating systems: Windows, Mac OSX and Linux.
• src\ : it contains the source files of syncpy methods and UI;
• doc\ : it contains the SyncPy documentation, in html and pdf format;
• examples\ : it contains fully functional examples of use of SyncPy modules;

Any uncritical application of the utils and methods of this library can produce pitfalls.

• Giovanna Varni
• Mohamed Chetouani
• Technical help from Marie Avril, Philippe Gauthier and David Reversat

For any questions, bugs reporting and comments don't hesitate to contact us: syncpy(AT)isir.upmc.fr

This software is governed by the CeCILL-B license under French law and abiding by the rules of distribution of free software. You can use, modify and/ or redistribute the software under the terms of the CeCILL-B license as circulated by CEA, CNRS and INRIA at the following URL "http://www.cecill.info".

Please cite this paper if you are using SyncPy for your own research :

Giovanna Varni, Marie Avril, Adem Usta, Mohamed Chetouani.
*SyncPy - A unified analytic library for synchrony.*
Accepted at First International Workshop on Modeling INTEPERsonal SynchrONy @ICMI 2015 Conference.