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mwm-ml-gen (Morris Water Maze - Machine Learning - Generalized) is the generalised version of mwm-ml (github link, bitbucket link) which is used for rodent trajectory data analysis.
mwm-ml was first created by Tiago V. Gehring as a custom set of software tools capable of reproducing the analysis procedure and findings of the publication Gehring, T. V. et al. Detailed classification of swimming paths in the Morris Water Maze: multiple strategies within one trial. Sci. Rep. 5, 14562; doi: 10.1038/srep14562 (2015).
Due to the publicity of the work of Gehring, T. V. et al., there was the demand of a software that could accept a variety of user data and experimental setups, perform the same analysis procedures and have the same functionalities. To that end the mwm-ml-gen was created.
- Accepts exported custom CSV files from Noldus Ethovision software and custom experimental setups.
- Has an improved and easy to use graphical user interface for trajectory analysis, labelling and classification.
- Much faster in data processing and analysis.
This wiki is focused only on mwm-ml-gen.
Introduction
How to Use
- Getting started
- Data preparation
- Starting a new project
- The Segmentation process
- The Labelling process
- The Classification process
- Results
- Walkthrough
- Extras
Appendix
Version History
How to Use (version 3)
- Getting started
- Data preparation
- Starting a new project
- The Segmentation process
- The Labelling process
- The Classification process
- Results
- Extras
- List of Labels
- Flowcharts
- The Project Folder
How to Use (version 1 and 2)