Skip to main content

Networked Music Performance software

Project description

======
Matriz
======

.. image:: https://badge.fury.io/py/matriz.png
:target: http://badge.fury.io/py/matriz

.. image:: https://travis-ci.org/stressfm/matriz.png?branch=master
:target: https://travis-ci.org/stressfm/matriz

.. image:: https://badge.fury.io/py/matriz.svg
:target: https://badge.fury.io/py/matriz


Matriz is a `Networked Music Performance <https://en.wikipedia.org/wiki/Networked_music_performance>`_ software.
The intended use is allowing real time musical performance of artists in different locations through computer networks.
The name "matriz" is portuguese for "matrix" and is inspired on the light and sound matrixes used in music and theater settings.


Why?
----

* Tools like `jacktrip <https://ccrma.stanford.edu/groups/soundwire/software/jacktrip/>`_
are built to work in high bandwidth academic networks like the internet2 or GEANT networks.
Matriz is built to offer the lowest latencies possible, while using the lest bandwidth possible.
This allows musician to have low latency high quality music streaming using regular network connections.
* For fun.

Features
--------

* Low latency (using OPUS codec)
* Easy to use and extend
* Tested in live performances
* Documentation: https://matriz.readthedocs.org.


What?
-----

The software is composed of two components, the client and the configuration server.
The client connects to the server over websockets and receives a list of all connected clients.
After starting it's own RTSP stream with audio from the sound card, it spawns an RTSP client for all connected clients, forming a P2P streaming network.
For all connection or disconnection events, the client list is broadcasted to all connected clients, which open or close new RTSP clients as necessary.
Audio is encoded with the OPUS codec, which allows for low bandwidth use and high quality sound, while keeping the latency to a minimum.

The system was used several times in live peformances, with three three groups of musicians.
Distances between groups ranged from tens of meters (same building) to 150 to 400 km in the final performance.
The hardware used was a Raspberry pi 2 with a Focusrite Scarlet 2i2 USB sound card.
The resulting streams where broadcasted live at http://stress.fm.
More information, including recordings of the performances, can be obtained at the project website: http://matriz.stress.fm.
For any inquiries concerning the software or the project, contact us at info@stress.fm.

Installation
------------

Prerequisites
.............

In both cases external dependencies must be installed for the program to work. For the client:

* Jack
* GStreamer, including the gst-rtsp-server package and Pyhton bindings
* Python bindings for gobject-introspection libraries

These can be installed in Debian or Rapsbian whith the following command::

$ apt-get install -y jackd2 \
python-gst-1.0 \
libgstrtspserver-1.0 \
gstreamer1.0-plugins-bad\
libgstreamer-plugins-bad1.0


For the server, if you want to stream the performance, you might want to install and configure:

* liquidsoap (to receive and combine client streams)
* icecast2 (to stream the combined audio from all clients)
* GStreamer (to decode client streams)

Using PyPi
..........
To install the program just to use the client::

$ pip install matriz

In the machine where the server will run, server dependencies must be explicitly installed::

$ pip install matriz[server]

Using ansible
.............
A set of ansible playbooks is supplied in the ansible directory. These where used to install the clients in Raspberry Pi 2 machines
and the server in a Linode instance, all running Debian Jessie (Raspbian for the pis). All dependencies are installed and supervisord
is used to run the programs. Be aware that these might need heavy modifications to work in another setup.


Usage
-----


Client
......

To use the client open a shell and just type::

$ matriz

without arguments, to start the client. The program will try to read configuration options from a file
called client.json in the same directory where the program was invoked.
If you want to use another filename, just give that as an argumento to the program::

$ matriz <filename>

An example configuration file is in config/client.json:

.. code-block:: json
{
"key": "key1",
"name": "porto",
"url": "ws://localhost:5000/config",
"interface": "eth0",
"port": 8554,
"client_pem": "fake_client.pem",
"client_crt": "fake_client.crt",
"ca_crt": "fake_ca.crt"
}

`key:` supposed to be unique id for client
`name:` some label identifying the client
`url:` the configuration server url
`interface:` network card to start de emitter on
`port:` port for emitter to listen on
`client_pem:` openssl key for secure websockets
`client_crt:` openssl client certificate
`ca_crt:` openssl server certificate

To get a list of command line arguments type::

$ matriz -h

Server
......
The configuration server is just a single file Flask app (matriz/config_server.py). For deployment instructions consult the Flask documentation at http://flask.pocoo.org. The server will try to read configuration options from the file given in the
MATRIZ_CONFIG_FILE environment variable or, if not set, from a file called clients.json in the same directory
where the program was invoked. An example configuration file can be found in config/clients.json:

.. code-block:: json
{
"client_keys": [
{"name": "porto", "key": "key1"},
{"name": "montemor", "key": "key2"},
{"name": "lisboa", "key": "key3"},
{"name": "marte", "key": "key666"}
],
"monitor_key": {"name": "monitor", "key": "monitorkey"}
}

Misc
....

For the software to work ports 8554 (TCP) and 8600-8700 (UDP) must be able accept incoming connections. This means you have to configure the gateways if you intend to use the software across the internet.

Partners
--------
* Oficinas do Convento
* Sonoscopia
* Osso
* Trienal de Arquitectura de Lisboa
* Digitópia - Casa da Música
* Câmara Municipal de Montemor-o-Novo.

Funding
-------
* Direção Geral das Artes.




History
-------

0.1.0 (2016-05-19)
---------------------

* First release.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

matriz-0.1.0.tar.gz (12.7 kB view details)

Uploaded Source

Built Distribution

matriz-0.1.0-py2.py3-none-any.whl (18.8 kB view details)

Uploaded Python 2Python 3

File details

Details for the file matriz-0.1.0.tar.gz.

File metadata

  • Download URL: matriz-0.1.0.tar.gz
  • Upload date:
  • Size: 12.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for matriz-0.1.0.tar.gz
Algorithm Hash digest
SHA256 ce4ad3183719fb72037a5173b90f921a49989ec6527d98776247c9435f466c43
MD5 0a0430307a21a8e04f85ac929d592529
BLAKE2b-256 c8c230a21708dd1f9b9f01312fc46ba9045db8d1c11dacc46f56260f1911b5ba

See more details on using hashes here.

File details

Details for the file matriz-0.1.0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for matriz-0.1.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 6c3c54fbf7bf488b78d1baf91b7faa063bca54726ad9ec2b969b79a0d39a811f
MD5 64248b34b26830eab22c1977beae45d2
BLAKE2b-256 76ba6e6b3537331e3416b85555b7b521a452812358541fcadf1f6070bcc1c86a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page