Metadata-Version: 2.1
Name: audio-plot
Version: 0.0.1
Summary: Plot tools based on audio
Home-page: https://github.com/hassaku/audio-plot
Author: hassaku
Author-email: hassaku.apps@gmail.com
License: MIT
Description: [![Build Status](https://travis-ci.org/hassaku/audio-plot.png)](https://travis-ci.org/hassaku/audio-plot)
        
        Converts a line graph to sound and returns an object that can be played
        in Jupyter notebook or Google Colab.
        It was created to make data science fun for the visually impaired.
        
        # Install
        
        ```
        $ pip install audio-plot
        ```
        
        # Usage
        
        ```
        y = np.sin(np.arange(0, np.pi*2, 0.1))
        yy = np.array([y, -y]).T
        plot(yy)  # audio control will be appeared on notebook.
        ```
        
        [The audio is as follows for this example]
        ```
        tts > minimum value is -1.0
        (Low sinusoidal sound)
        tts > maximum value is 1.0
        (High sinusoidal sound)
        tts > line 1
        (Sound in response to changes in the line 1 graph)
        tts > line 2
        (Sound in response to changes in the line 2 graph)
        ```
        
        # Update PyPI
        
        ```
        $ nosetests -vs
        $ pip install twine # if necessary
        $ cat ~/.pypirc  # if necessary
        [distutils]
        index-servers = pypi
        
        [pypi]
        repository: https://pypi.python.org/pypi
        username: YOUR_USERNAME
        password: YOUR_PASSWORD
        $ python setup.py sdist
        $ twine upload --repository pypi dist/*
        $ pip --no-cache-dir install --upgrade audio-plot
        ```
        
        # 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
        
Keywords: audio plot visually-impaired
Platform: UNKNOWN
Description-Content-Type: text/markdown
