spectrographic - Man Page

Name

spectrographic ā€” spectrographic unknown

This is the documentation of spectrographic.

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Contents

License

The MIT License (MIT)

Copyright (c) 2019 Levi Borodenko

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR Copyright HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contributors

  • Levi Borodenko <Levi.borodenko@gmail.com>

Changelog

Version 0.8.0

  • The core implementation is done
    • base.py contains a working implementation

    of the spetrographic idea.

  • Created some examples.
  • Adding requirements

Version 0.8.1

  • Wrote README.md
  • test upload to testpypi
  • create demonstrational video

Version 0.8.5

  • quick fix of centering in README.md

Version 0.8.6

  • added gitpython as dependency

Version 0.8.7

  • removed dependencies from config file and moved to requirements

Version 0.9.0

  • Release
  • upload to the official pypi and making github repo public.

Version 0.9.3

  • Put dependencies into setup.cfg so pip can pull them while installing

spectrographic

spectrographic package

Submodules

spectrographic.base module

class spectrographic.base.ColumnToSound(duration: int, sample_rate: int = 44100, min_freq: int = 10000, max_freq: int = 17000, y_resolution: int = 1000, num_tones: int = 3, contrast: float = 5)

Bases: object

Class to turn grey-scale image columns into a sound.

It takes a numpy array of grey intensities (in the range 0 to 1) of length Y_RESOLUTION and turns them into a DURATION seconds long sound in the frequency range between MIN_FREQ and MAX_FREQ.

Parameters

{int} -- Duration of sound in seconds (duration) --

Keyword Arguments
  • {int} -- Sample rate of sound (default (sample_rate) -- {44100})
  • {int} -- Minimal frequency in the spectrograph (min_freq) --
  • (default -- {10000})
  • {int} -- Maximal frequency in the spectrograph (max_freq) --
  • (default -- {17000})
  • {int} -- Number of pixels to plot (default (y_resolution) -- {1000})
  • {int} -- Number of tones to use to fill out each pixel (num_tones) --
  • (default -- {3})
  • {float} -- Contrast between loud and quiet pixels (contrast) --
  • (default -- {5})
gen_soundwall(column: numpy.ndarray)

Takes a column of pixels and generates the sound wall.

[description]

Parameters
  • {np.ndarray} -- Y_RESOLUTION long column of (column) --
  • pixels (values between 0 and 1) --
Returns

np.ndarray -- soundwall

pixel_to_sound(y: int, intensity: float = 1)

Takes a pixel in a imagae column at the y'th position from the top and turns it into a sound at a corresponding position in the spectrum.

[description]

Parameters

{int} -- position of pixel in column from the top. (y) --

Keyword Arguments

{float} -- [description] (default (intensity) -- {1})

Returns

np.ndarray -- sound array

Raises

ValueError --

class spectrographic.base.SpectroGraphic(path: pathlib.Path, height: int = 100, duration: int = 20, min_freq: int = 1000, max_freq: int = 8000, sample_rate: int = 44100, num_tones: int = 3, contrast: float = 5, use_black_and_white: bool = False)

Bases: object

Takes an image file and creates a sound that draws that image on a spectrogram.

[description] :param path {Path} -- Path to file (e.g.: {"./data/python.png"})

Keyword Arguments
  • {int} -- y-resolution in spectrogram (default (height) -- {100})
  • {int} -- duration of sound in seconds (default (duration) -- {20})
  • {int} -- minimal freq. for image (default (min_freq) -- {1000})
  • {int} -- maximal freq. for image (default (max_freq) -- {8000})
  • {int} -- Sample rate (default (sample_rate) -- {44100})
  • {int} -- Number of tones to used to fill in each pixel (num_tones) --
  • (default -- {3})
  • {float} -- Contrast between loud and quiet pixels (contrast) --
  • (default -- {5})
play()

Plays the SpectroGraphic sound.

save(wav_file: pathlib.Path = 'SpectroGraphic.wav')

saves the spectrographic to a .wav file

We use the wavio module

property sound_array

spectrographic.cli module

This is a skeleton file that can serve as a starting point for a Python console script. To run this script uncomment the following lines in the [options.entry_points] section in setup.cfg:

console_scripts =

spectrographic = spectrographic.cli:run

Then run python setup.py install which will install the command spectrographic inside your current environment.

spectrographic.cli.main(args)

Main entry point allowing external calls

Parameters

args ([str]) -- command line parameter list

spectrographic.cli.parse_args(args)

Parse command line parameters

Parameters

args ([str]) -- command line parameters as list of strings

Returns

command line parameters namespace

Return type

argparse.Namespace

spectrographic.cli.run()

Entry point for console_scripts

Module contents

Indices and Tables

Author

unknown

Info

Jan 27, 2021 unknown