The VIS Framework

Currently, vis is only supported in Python3.5 and with an old version of pandas==0.18.1. Eventually, we would like to catch up with current releases, in the meantime, you can run vis-framework using a python virtual environment. See an example in the Running in Virtual Environment section

The VIS Framework for Music Analysis

The VIS Framework is a Python package that uses the music21 and pandas libraries to build a flexible system for writing computational music analysis programs.

Copyright Information:

• All source code is subject to the GNU AGPL 3.0 Licence. A copy of this licence is included as doc/apg-3.0.txt.
• All other content is subject to the CC-BY-SA Unported 3.0 Licence. A copy of this licence is included as doc/CC-BY-SA.txt
• All content in the test_corpus directory is subject to the licence in the file test_corpus/test_corpus_licence.txt

Software Dependencies

The VIS Framework uses many software libraries to help with analysis. These are required dependencies:

• Python 3.5
• music21
• pandas
• multi_key_dict
• requests

These are recommended dependencies:

• numexpr (improved performance for pandas)
• Bottleneck (improved performance for pandas)
• tables (HDF5 output for pandas)
• openpyxl (Excel output for pandas)
• mock (for testing)
• coverage (for testing)
• python-coveralls (to for automated coverage with coveralls.io)
• matplotlib (plotting)
• scipy (plotting)

Documentation

You can find documentation here:

• Major Release Documentation
• Stable Release Documentation
• Latest Release Documentation, a.k.a. "bleeding edge"

Running in Virtual Environment

Using anaconda, create and activate a new Python3.5 environment:

conda create -n vis python=3.5
conda activate vis

Install the required packages:

pip install -r vis/requirements.txt

Install vis:

python setup.py install

You should be ready to go

Citation

If you wish to cite the VIS Framework, please use this ISMIR 2014 article:

Antila, Christopher and Julie Cumming. "The VIS Framework: Analyzing Counterpoint in Large Datasets." In Proceedings of the International Society for Music Information Retrieval, 2014.

A BibTeX entry for LaTeX users is

@inproceedings{,
    title = {The VIS Framework: Analyzing Counterpoint in Large Datasets},
    author = {Antila, Christopher and Cumming, Julie},
    booktitle = {Proceedings of the International Society for Music Information Retrieval},
    location = {Taipei, Taiwan},
    year = {2014},
}

You may also wish to cite the software itself:

Antila, Christopher and Jamie Klassen. The VIS Framework for Music Analysis. Montréal: The ELVIS Project, 2014. URL https://github.com/ELVIS-Project/vis.

A BibTeX entry for LaTeX users is

@Manual{,
    title = {The VIS Framework for Music Analysis},
    author = {Antila, Christopher and Klassen, Jamie},
    organization = {The ELVIS Project},
    location = {Montréal, Québec},
    year = {2014},
    url = {https://github.com/ELVIS-Project/vis},
}