music as data, data as music

unleashing data tools for music theory, analysis and composition

A python library for pitch class set and rhythmic sequences classification and manipulation, the generation of networks in generalized music and sound spaces, deep learning algorithms for timbre recognition, and the sonification of arbitrary data:

The software tools for the CADDC environment are based on Python, MAX and Ableton Live:


  • A suite of Python scripts for the reading, mapping and formatting of the data:

    • ​data from the AFLOWLIB database are read and entries are mapped to MIDI events according to predefined algorithms

    • the choice of mapping can be made arbitrarily by the user. So far data can be mapped to MIDI notes from 21 to 108 on the full chromatic, diatonic, harmonic minor, diminished, whole tone and pentatonic scales or any 12 tone row of choice.


  • A suite of standalone MAX or MAX for Live patches (and VST plugins) for MIDI elaboration, music encoding and sound synthesys: the DataPlayer


  • Further manipulation of the data can involve any operation one can do on a list of numbers (transpose, invert, retrograde, multiply, loop sections, randomize order, etc) and can be done in a precomposed way or directly on the live data stream during the performance.

© 2020 Marco Buongiorno Nardelli.