gamut 0.1

Granular Audio Musaicing Toolkit for Python

GAMuT: Granular Audio Musaicing Toolkit

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Description

GAMuT is a high-level, user-friendly granular audio musaicing toolkit implemented in Python.

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Installation

To install gamut, run the pip install gamut command in the terminal.

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Main functions

• build_corpus(): Takes a folder directory, or an audio file directory, or a list of directories to audio files, and returns a dict object (i.e. the corpus). The output can be saved as a .gamut file with the write_gamut() function, for later use in get_audio_recipe().

• get_audio_recipe(): Takes an audio sample directory/path (i.e. the target) and a dict object (i.e. the corpus), and returns another dict object containing the instructions to rebuild the target using grains from the corpus. The output can be saved as a .gamut file with the write_gamut() function, for later use in cook_recipe().

• cook_recipe(): Takes a dict object (i.e. the recipe), and returns an array of audio samples, intended to be written as an audio file.

Additionally, the following functions are included to read and write audio and .gamut[1] files:

• dict_to_gamut(): writes dict object into a .gamut file. This function is a simple wrapper of np.save().
• dict_from_gamut(): reads a .gamut file as a dict object. This function is a simple wrapper of np.load().
• write_audio(): writes a ndarray as audio. This function is a simple wrapper of sf.write().

[1]: .gamut is a custom binary data format used for storing GAMuT corpora and recipe data. This file is simply a renaming of Numpy's .npy file extension.

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Examples

• Basic: generates corpus, recipe, and audio in a single script — not recommended.

# imports
from gamut import gamut

# set target sound
target = './soundfile.wav'

# set corpus folder containing audio samples
audio_files = './audio_folder'

 # build corpus
corpus = gamut.build_corpus(audio_files)

 # make target recipe
recipe = gamut.get_audio_recipe(target, corpus)

# cook target recipe
output = gamut.cook_recipe(recipe)

# write output into audio file
gamut.write_audio('./output.wav',output)

• Build corpus: Builds and writes .gamut corpus into file for future reuse.

# imports
from gamut import gamut

# set path to audio folder
audio_folder = '/Users/felipe-tovar-henao/Documents/Sample collections/Violin_notes'

# build corpus from folder
my_corpus = gamut.build_corpus(folder_dir=audio_folder)

# set corpus output path
outfile_path = '/Users/felipe-tovar-henao/Desktop/Violin_notes_corpus'

# write corpus into disk
gamut.dict_to_gamut(dict=my_corpus, outpath=outfile_path)

• Make recipe: Makes and writes .gamut recipe into file for future reuse.

# imports
from gamut import gamut

# path of audio target
target_path = '/Users/felipe-tovar-henao/Documents/target_samples/dialogo_44.1Hz.wav'

# gamut corpus path
corpus_path = '/Users/felipe-tovar-henao/Desktop/Violin_notes_corpus'

# load corpus
corpus = gamut.dict_from_gamut(corpus_path)

# build audio recipe
target_recipe = gamut.get_audio_recipe(target_path=target_path, corpus_dict=corpus)

# set recipe output path
outfile_path = '/Users/felipe-tovar-henao/Desktop/MyRecipe.gamut'

# write recipe into disk
gamut.dict_to_gamut(dict=target_recipe, outpath=outfile_path)

• Cook recipe: Generates and writes audio file (.wav, .aif. or .aif) gamut from recipe.

# imports
from gamut import gamut

# audio recipe path
recipe_path = '/Users/felipe-tovar-henao/Desktop/MyRecipe.gamut'

# load corpus
recipe = gamut.dict_from_gamut(recipe_path)

# cooking settings
envelope = [0, 1, 0.5, 0.1, 0] # grain amplitude envelope (type: str, int, float or list -- if str, use scipy.signal.windows types)
grain_dur = [0.05, 0.25] # grain duration (type: int, float, or list)
sr = 44100 # output sampling rate (type: int)
pan_width = [0.1, 0.9] # spread of panning across channels (0.0-1.0) (type: int, float or list)
target_mix = [0, 0.5] # dry/wet mix of input target (0.0-1.0) (type: int, float, or list)

# cook audio recipe
audio_array = gamut.cook_recipe(recipe_dict=recipe,
                        envelope=envelope,
                        grain_dur=grain_dur,
                        sr=sr,
                        pan_width=pan_width,
                        target_mix=target_mix)

# set audio output path
outfile_path = '/Users/felipe-tovar-henao/Desktop/MyAudioMosaicing.wav'

# write audio into disk
gamut.write_audio(path=outfile_path,
            ndarray=audio_array,
            sr=sr,
            bit_depth=24)