Welcome to moseq2, the latest version of a software package for mouse tracking in depth videos first developed by Alex Wiltschko in the Datta Lab at Harvard Medical School.
Latest version is 0.5.0
Below are the commands/functionality that moseq2-model currently affords. They are accessible via CLI or Jupyter Notebook in moseq2-app.
Usage: moseq2-model [OPTIONS] COMMAND [ARGS]...
Options:
--version Show the version and exit. [default: False]
--help Show this message and exit. [default: False]
Commands:
count-frames Counts number of frames in given h5 file (pca_scores)
kappa-scan Batch fit multiple models scanning over different syllable...
learn-model Trains ARHMM on PCA Scores with given training parameters count-frames Counts number of frames in given h5 file (pca_scores)
kappa-scan Batch fit multiple models scanning over different syllable...The kappa-scan functionality is merged into the learn_model() function.
To use it, simple set kappa='scan', and for additional control, adjust the scan_scale,
min_kappa, max_kappa, and out_script input parameters.
Options can be found in the documentation or the jupyter notebook
Run any command with the --help flag to display all available options and their descriptions.
MoSeq2 uses sphinx to generate the documentation in HTML and PDF forms. To install sphinx, follow the commands below:
pip install sphinx==3.0.3 sphinx_click==2.5.0
pip install sphinx-rtd-theme
pip install rst2pdfAll documentation regarding moseq2-extract can be found in the Documentation.pdf file in the root directory,
an HTML ReadTheDocs page can be generated via running the make html in the docs/ directory.
To generate a PDF version of the documentation, simply run make pdf in the docs/ directory.
To use this package, you must have already generated a pca_scores.h5 file and an index file moseq2-index.yaml containing all of your
session metadata (specifically data groupings).
- The index file is generated when aggregating the results in moseq2-extract
- The pca_scores are generated via moseq2-pca.
If you would like to contribute, fork the repository and issue a pull request.