PyMICE 1.2.0

PyMICE - a Python® library for mice behavioural data analysis

PyMICE is a Python® library for mice behavioural data analysis.

The library can be used for loading and analysing of data obtained from IntelliCage™ system in an intuitive way in Python programming language.

The library provides user with an object oriented application programming interface (API) and a data abstraction layer. It also comes with auxiliary tools supporting development of analysis workflows, like data validators and a tool for workflow configuration.

Terms of use

The library is available under GPL3 license.

We ask that that reference to our paper as well as to the library itself is provided in any published research making use of PyMICE.

The recommended in-text citation format is: PyMICE (Dzik, Puścian, et al. 2017) v. 1.2.0 (Dzik, Łęski, & Puścian 2017)

and the recommended bibliography entry format:

Dzik J. M., Łęski S., Puścian A. (July 21, 2017) “PyMICE” computer software (v. 1.2.0; RRID:nlx_158570) doi: 10.5281/zenodo.832982

Dzik J. M., Puścian A., Mijakowska Z., Radwanska K., Łęski S. (June 22, 2017) “PyMICE: A Python library for analysis of IntelliCage data” Behavior Research Methods doi: 10.3758/s13428-017-0907-5

If the journal does not allow for inclusion of the resource identifier (RRID:nlx_158570) in the bibliography, we ask to provide it in-text: PyMICE (RRID:nlx_158570) [1] v. 1.2.0 [2]

1. Dzik JM, Puścian A, Mijakowska Z, Radwanska K, Łęski S. PyMICE: A Python library for analysis of IntelliCage data. Behav Res Methods. 2017. DOI: 10.3758/s13428-017-0907-5

2. Dzik JM, Łęski S, Puścian A. PyMICE [computer software]. Version 1.2.0. Warsaw: Nencki Institute - PAS; 2017. DOI: 10.5281/zenodo.832982

We have provided a solution to facilitate referencing to the library. Please run:

>>> help(pm.Citation)

for more information (given that the library is imported as pm).

More details

For more details please see The project website.

Authors

• The library

  • Jakub M. Dzik a.k.a. Kowalski

  • Szymon Łęski

• Tutorial data

  • Alicja Puścian

Acknowledgement

JD and SŁ supported by Symfonia NCN grant: UMO-2013/08/W/NZ4/00691.

AP supported by a grant from Switzerland through the Swiss Contribution to the enlarged European Union (PSPB-210/2010 to Ewelina Knapska and Hans-Peter Lipp).