https://github.com/ntoll/cityrhythm

A musical representation of footfall data provided by Leeds City Council through the medium of Brass Band
https://github.com/ntoll/cityrhythm

Last synced: 8 days ago
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A musical representation of footfall data provided by Leeds City Council through the medium of Brass Band

• Host: GitHub
• URL: https://github.com/ntoll/cityrhythm
• Owner: ntoll
• License: mit
• Created: 2014-03-08T16:06:13.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2014-09-21T09:47:14.000Z (about 10 years ago)
• Last Synced: 2024-10-11T22:45:24.125Z (about 1 month ago)
• Language: JavaScript
• Size: 29.5 MB
• Stars: 3
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

README

        
Oompah.py

=========

See: http://www.leedsdatamill.org/blog/oompah-py-big-brass-meets-big-data

Code and data needed to generate the score and parts for an approximately

10 minute composition for brass band representing foot-fall data collected in

the city of Leeds.

Programme Notes

---------------

The piece is called "The Rhythm of the City" and is scored for a traditional

British brass band with one percussionist on tubular bells. The code used to

generate it is called ``oompah.py`` and is a Python script initially hacked

together over the course of a LeedsDataMill sponsored hackathon weekend (and

subsequently finished as an exercise in musical exploration).

Each section of the brass band represents a location in the city of Leeds.

The piece is split into 24 8 bar phrases (encompassing each hour of the day).

As each location's footfall data changes - becoming quiter or busier - so the

music played by the associated section within the band reflects this change.

The piece begins at midnight in a quiet mood but as the music progresses

(punctuated by bells sounding the hours) the different parts of the city

wake up to a climax during the working day before returning to a placid

state of affairs as the evening closes the musical proceedings.

The software reads the raw footfall data and turns it into the musical score

for the piece.

Requirements

------------

* Python 2.7+

* Lilypond 2.14.2+

Usage

-----

The ``make`` command is your best bet::

    make

Will generate a lilypond and PDF for the score and each part along with a

``score.midi`` file so you get a sense of what it'll sound like::

    make clean

Cleans up all the parts and Lilypond related junk.

Presentation

------------

Check out the instructions in the ``presentation`` directory for displaying

the presentation both authors gave on this project at PyconUK 2014.

All feedback is most welcome!