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Plot tools based on audio

Project description

audio-plot-lib

Python package

This library provides graph sonification functions and has been developed for a project named "Data science and machine learning resources for screen reader users". Please refer to the project page for more details.

https://hassaku.github.io/DS-and-ML-with-screen-reader/

Use in Google Colab (recommended)

Try the following example.

Open In Colab

Use in script (option)

Interactive

Generate html with graphs that can be displayed interactively in a browser.

Dependency

$ pip install audio-plot-lib
$ pip install beautifulsoup4

Example

import audio_plot_lib as apl
# apl.interactive.set_language("ja")  # Option to change language. Default is "en"
apl.interactive.plot([0, 1, 2, 3, 2, 1, 0], script_name=__file__)

Open the html file with the same name as the script name in your browser, and if you find a button that reads 'push here to unmute graph', try moving the mouse cursor appropriately after pressing the button. If not, try reloading the page.

Playable

Generate an audio file with sonified graphs.

Dependency

$ sudo apt-get install libavformat-dev libavfilter-dev libavdevice-dev ffmpeg
$ pip install audio-plot-lib

Example

import audio_plot_lib as apl
from pydub.playback import play

# generate graph sound
audio = apl.playable.plot([0, 1, 2, 3, 2, 1, 0], duration=300, autoplay=False)

# play
play(audio)

# save to audio file
audio.export("graph.wav", format="wav")

For contributer

Update PyPI

$ python -m unittest discover tests
$ pip install twine # if necessary
$ cat ~/.pypirc  # if necessary
[distutils]
index-servers = pypi

[pypi]
repository: https://upload.pypi.org/legacy/
username: YOUR_USERNAME
password: YOUR_PASSWORD
$ rm -rf audio-plot-lib.egg-info dist # if necessary
$ python setup.py sdist
$ twine upload --repository pypi dist/*
$ pip --no-cache-dir install --upgrade audio-plot-lib

https://pypi.org/project/audio-plot-lib/

Contributing

  • Fork the repository on Github
  • Create a named feature branch (like add_component_x)
  • Write your change
  • Write tests for your change (if applicable)
  • Run the tests, ensuring they all pass
  • Submit a Pull Request using Github

License

MIT

Project details


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