0.1.1 • Public • Published

MAIA Markov

Markov-based analysis and generation functions supporting various applications by Music Artificial Intelligence Algorithms, Inc.

Local Installation

Set yourself up with an installation of Node.js. Then open up a terminal window and navigate to a directory where you want to experiment with MAIA Markov.


In the terminal window, execute

npm install maia-markov --save

which should make a node_modules folder that contains MAIA Markov and its dependencies.

Make yourself a new JavaScript (plain-text) file – Atom is a good editor for such purposes – and copy/paste the first three lines of code from the hello-world example below. Save the file as something like hello_world.js at the same level as node_modules (not inside it).

Return to the terminal and execute

node hello_world.js

which should run the hello_world.js script you just wrote, giving the output

ans: [0, 0, 0, 2], [0, 7, 4, 1], [1, 9, 5, 0.5], [1.5, 7, 4, 0.5]

You have started to use MAIA Markov!


With Node.js set up, clone the MAIA Markov repository from here and run npm install to acquire the dependencies. Some packages, such as Rollup, might need a general install.

Please follow these steps when making additions or changes:

  1. Additions or changes to the code should be made in the es6 folder;
  2. When documenting, follow the JSDoc format used therein;
  3. Write unit tests below each method/function;
  4. Execute npm run compile to convert the various components in the es6 into the corresponding components in the dist folder, and to combine them into an IIFE (called maia-markov.js, in the root of the repository);
  5. Execute jsdoc --configure .jsdoc.config.js es6 to update the documentation, which gets written to the docs folder, and check it looks good and reads well;
  6. Say in step 1 you added a new file to the es6 folder called hello_world.js, then now it's time to check on your unit tests by executing node hello_world.js and seeing whether the console.log()s match your expected output;
  7. Once you are satisfied with your unit tests, comment them out and paste them to test/index.js, following the chai format used therein. Execute npm test to verify that there are ticks everywhere and in particular that your new tests are being invoked;
  8. Do the usual git add ., git commit -m "Short meaningful message", and git push, and we'll see it on the other side as a pull request;
  9. There should not be any need for you to edit the version in package.json;
  10. Please keep any data files out of the repository by editing the .gitignore file.

Hello-world example

const mm = require('maia-markov')
const ps = [
  [0, 60, 60, 2], [0, 67, 64, 1],
  [1, 69, 65, 0.5], [1.5, 67, 64, 0.5]
let an = new mm.Analyzer()
const ans = an.centre_point_set([0, 0], ps)
console.log('ans:', ans)





Release History

  • 0.1.1 Working on scenic_path().
  • 0.0.72-73 Fixed ontime correction bug.
  • 0.0.70-71 Switched unique_rows(ps, true) in for sort_rows(ps) in MidiImport, in order to address issue of MIDI files containing duplicate points.
  • 0.0.64-69 Use of timelapse objects in new version of MAIA Util, and some debugging of MidiImport's get_points().
  • 0.0.63 Better MIDI import/export/import management.
  • 0.0.60-62 Added some track-extract methods to the MidiImport class.
  • 0.0.57-59 Multitrack MIDI export including control changes.
  • 0.0.51-56 Added musicXml property alongside midi property under miscImport, and deprecated miscXml, to conform with the Composition object spec.
  • 0.0.50 More imported MIDI properties included in MidiImport, including control changes.
  • 0.0.45-49 Corrected an error involving undefined time signatures.
  • 0.0.32-44 Working on a new version of XmlImport whose XML converter respects the order of entries.
  • 0.0.31 Edited note_point_set2comp_obj() so that quantisation will not be applied if the set of fractions is null.
  • 0.0.30 Added a MidiExport class.
  • 0.0.29 Fixed bug in comp_obj2beat_mnn_states().
  • 0.0.7-28 Working on import capabilities.
  • 0.0.6 Tagged for the submission to the AI Music Generation Challenge 2020. Some bug fixes as well, e.g. to get_phrase_boundary_ontimes() in the MidiImport class (this didn't affect the excerpts generated for the listening study).
  • 0.0.5 Tagged for Alex's listening study and (separately).
  • 0.0.4 Continuing to refactor code from the examples folder into the package itself.
  • 0.0.3 Fixed bug in analysis code and refactored analyze.js and generate.js into classes.
  • 0.0.2 Many code components still in the wrong places, but wanted to tag a version for generating the material for AI Eurovision 2020.
  • 0.0.0 Initial release

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  • tomthecollins