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Python audio coding classes - for dsp and sonification

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pya

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What is pya?

pya is a package to support creation and manipulation of audio signals with Python. It uses numpy arrays to store and compute audio signals.

It provides:

  • Asig - a versatile audio signal class
    • Ugen - a subclass of Asig, which offers unit generators such as sine, square, swatooth, noise
  • Aserver - an audio server class for queuing and playing Asigs
  • Arecorder - an audio recorder class
  • Aspec - an audio spectrum class, using rfft as real-valued signals are always implied
  • Astft - an audio STFT (short-term Fourier transform) class
  • A number of helper functions, e.g. device_info()

pya can be used for

  • multi-channel audio processing
  • auditory display and sonification
  • sound synthesis experiment
  • audio applications in general such as games or GUI-enhancements
  • signal analysis and plotting

At this time pya is more suitable for offline rendering than realtime.

Authors and Contributors

  • Thomas Hermann, Ambient Intelligence Group, Faculty of Technology, Bielefeld University (author and maintainer)
  • Jiajun Yang, Ambient Intelligence Group, Faculty of Technology, Bielefeld University (co-author)
  • Alexander Neumann, Neurocognitions and Action - Biomechanics, Bielefeld University
  • Contributors will be acknowledged here, contributions are welcome.

Installation

Note: pya can be installed using pip. But pya uses PyAudio for audio playback and record, and PyAudio 0.2.11 has yet to fully support Python 3.7. So using pip install with Python 3.7 may encounter issues such as portaudio. Solutions are:

  1. Anaconda can install non-python packages, so that the easiest way (if applicable) would be to

    conda install pyaudio

  2. For Mac users, you can brew install portaudio beforehand.

  3. For Linux users, try sudo apt-get install portaudio19-dev or equivalent to your distro.

  4. For Windows users, you can install PyAudio wheel at: https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyaudio

Then pya can be installed using pip:

pip install pya

See pyaudio installation http://people.csail.mit.edu/hubert/pyaudio/#downloads

A simple example

Startup:

from pya import *
s = Aserver(bs=1024)
Aserver.default = s  # to set as default server
s.boot()   

Create an Asig signal:

A 1s / 440 Hz sine tone at sampling rate 44100 as channel name 'left':

import numpy as np
signal_array = np.sin(2 * np.pi * 440 * np.linspace(0, 1, 44100))
atone = Asig(signal_array, sr=44100, label='1s sine tone', cn=['left'])

Other ways of creating an Asig object:

asig_int = Asig(44100, sr=44100)  # zero array with 44100 samples
asig_float = Asig(2., sr=44100)  # float argument, 2 seconds of zero array
asig_str = Asig('./song.wav')  # load audio file
asig_ugen = Ugen().square(freq=440, sr=44100, dur=2., amp=0.5)  # using Ugen class to create common waveforms

Audio files are also possible using the file path. WAV should work without issues. MP3 is supported but may raise error if FFmpeg.

If you use Anacodna, installation is quite easy:

conda install -c conda-forge ffmpeg

Otherwise:

Key attributes

  • atone.sig --> The numpy array containing the signal is
  • atone.sr --> the sampling rate
  • atone.cn --> the list of custom defined channel names
  • atone.label --> a custom set identifier string

Play signals

atone.play(server=s)  

play() uses Aserver.default if server is not specified

Plotting signals

to plot the first 1000 samples:

atone[:1000].plot()

to plot the magnitude and phase spectrum:

atone.plot_spectrum()

to plot the spectrum via the Aspec class

atone.to_spec().plot()

to plot the spectrogram via the Astft class

atone.to_stft().plot(ampdb)

Selection of subsets

  • Asigs support multi-channel audio (as columns of the signal array)
    • a1[:100, :3] would select the first 100 samples and the first 3 channels,
    • a1[{1.2:2}, ['left']] would select the channel named 'left' using a time slice from 1

Method chaining

Asig methods usually return an Asig, so methods can be chained, e.g

atone[{0:1.5}].fade_in(0.1).fade_out(0.8).gain(db=-6).plot(lw=0.1).play(rate=0.4, onset=1)

Learning more

  • Please check the examples/pya-examples.ipynb for more examples and details.

Contributing

  • Please get in touch with us if you wish to contribute. We are happy to be involved in the discussion of new features and to receive pull requests.

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