jackgoffinet -> pearsonlab transfer

LICENSE.md

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+Copyright 2021 Jack Goffinet
+
+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.

README.md

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-# autoencoded-vocal-analysis
-Modeling animal vocalizations with variational autoencoders
+## Autoencoded Vocal Analysis v0.3.1
+#### Modeling animal vocalizations with VAEs
 
-* Future home of autoencoded-vocal-analysis (AVA).
-* Current home: https://github.com/jackgoffinet/autoencoded-vocal-analysis
+<img src="docs/source/logo.png" width="300" align="middle" alt="logo">
+
+See our article for details:
+
+> Goffinet, J., Brudner, S., Mooney, R., & Pearson, J. (2021). Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires. *eLife*, 10:e67855. [https://doi.org/10.7554/eLife.67855](https://doi.org/10.7554/eLife.67855)
+
+See `examples/` for usage.
+
+See [readthedocs](https://autoencoded-vocal-analysis.readthedocs.io/en/latest/index.html)
+for documentation and a tutorial.
+
+#### To build:
+```
+$ git clone https://github.com/jackgoffinet/autoencoded-vocal-analysis.git
+$ cd autoencoded-vocal-analysis
+$ pip install .
+```
+
+#### Dependencies:
+* [Python3](https://www.python.org/) (3.5+)
+* [PyTorch](https://pytorch.org)
+* [UMAP](https://umap-learn.readthedocs.io/)
+* [affinewarp](https://github.com/ahwillia/affinewarp)
+
+Issues and pull requests are appreciated!
+
+#### See also:
+* [Animal Vocalization Generative Network](https://github.com/timsainb/AVGN), a
+	nice repo by Tim Sainburg for clustering birdsong syllables and generating
+	syllable interpolations.
+* [DeepSqueak](https://github.com/DrCoffey/DeepSqueak) and
+	[MUPET](https://github.com/mvansegbroeck/mupet), MATLAB packages for
+	detecting and classifying rodent ultrasonic vocalizations.
+* [Sound Analysis Pro](http://www.soundanalysispro.com/), software for analyzing
+	birdsong.

ava/__init__.py

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+"""
+AVA: Autoencoded Vocal Analysis
+
+Contents
+--------
+
+::
+
+	ava
+	│
+	├── data
+	│	└── data_container
+	├── models
+	│	├── vae_dataset
+	│	├── vae
+	│	└── window_vae_dataset
+	├── plotting
+	│	├── grid_plot
+	│	├── latent_projection
+	│	├── mmd_plots
+	│	├── shotgun_movie
+	│	└── tooltip_plot
+	├── preprocessing
+	│	├── preprocess
+	│	└── utils
+	└── segmenting
+		├── amplitude_segmenting
+		├── refine_segments
+		├── segment
+		├── template_segmentation
+		└── utils
+"""
+__version__ = "0.3.1"

ava/data/__init__.py

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+"""
+AVA package for organizing different kinds of data
+
+Contains
+--------
+`ava.data.data_container`
+	DataContainer class for linking directories containing different sorts of
+	data.
+"""