scikit-maad
Open-source and modular toolbox for quantitative soundscape analysis in Python
Science Score: 77.0%
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 5 DOI reference(s) in README -
✓Academic publication links
Links to: researchgate.net, zenodo.org -
✓Committers with academic emails
2 of 11 committers (18.2%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (17.0%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Open-source and modular toolbox for quantitative soundscape analysis in Python
Basic Info
- Host: GitHub
- Owner: scikit-maad
- License: bsd-3-clause
- Language: Python
- Default Branch: production
- Homepage: https://scikit-maad.github.io/
- Size: 180 MB
Statistics
- Stars: 121
- Watchers: 9
- Forks: 23
- Open Issues: 10
- Releases: 0
Topics
Metadata Files
README.md
scikit-maad
scikit-maad is an open source Python package dedicated to the quantitative analysis of environmental audio recordings. This package was designed to 1. load and process digital audio, 2. segment and find regions of interest, 3. compute acoustic features, and 4. estimate sound pressure level.
This workflow opens the possibility to scan large audio datasets and use powerful machine learning techniques, allowing to measure acoustic properties and identify key patterns in all kinds of soundscapes.
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Operating Systems
scikit-maad seamlessly supports Linux, macOS, and Windows operating systems.
Interpreter
The latest version of scikit-maad requires one of these interpreters:
- Python 3.9, 3.10, 3.11 or 3.12
Packages dependency
scikit-maad requires these Python packages to run:
- matplotlib >=3.6
- numpy >= 1.21
- pandas >= 1.5
- scikit-image >= 0.23.1
- scipy >= 1.8
Installing from PyPI
scikit-maad is hosted on PyPI. The easiest way to install the package is using pip the standard package installer for Python:
bash
$ pip install scikit-maad
Quick start
The package is imported as maad. To use scikit-maad tools, audio must be loaded as a numpy array. The function maad.sound.load is a simple and effective way to load audio from disk. For example, download the spinetail audio example to your working directory. You can load it and then apply any analysis to find regions of interest or characterize your audio signals:
python
from maad import sound, rois
s, fs = sound.load('spinetail.wav')
rois.find_rois_cwt(s, fs, flims=(4500,8000), tlen=2, th=0, display=True)
For advance users
Installing from source
If you are interested in developing new features for scikit-maad or working with the latest version, clone and install it:
bash
$ git clone https://github.com/scikit-maad/scikit-maad.git
$ cd scikit-maad
$ pip install --editable .
Running tests
Install the test requirements:
bash
$ pip install pytest
And run the tests:
bash
$ cd scikit-maad
$ pytest
Examples and documentation
- See https://scikit-maad.github.io for a complete reference manual and example gallery.
Runnin all examples requires to install the following packages :
- scikit-learn, a popular Python package for machine learning: link
- librosa, a popular package for audio and music analysis: link
- tqdm, a package that provides a fast, extensible progress bar for loops and other iterable tasks: link
- In depth information related to the Multiresolution Analysis of Acoustic Diversity implemented in scikit-maad was published in: Ulloa, J. S., Aubin, T., Llusia, D., Bouveyron, C., & Sueur, J. (2018). Estimating animal acoustic diversity in tropical environments using unsupervised multiresolution analysis. Ecological Indicators, 90, 346–355
Citing this work
If you find scikit-maad usefull for your research, please consider citing it as:
- Ulloa, J. S., Haupert, S., Latorre, J. F., Aubin, T., & Sueur, J. (2021). scikit‐maad: An open‐source and modular toolbox for quantitative soundscape analysis in Python. Methods in Ecology and Evolution, 2041-210X.13711. https://doi.org/10.1111/2041-210X.13711
or use our citing file for custom citation formats.
Feedback and contributions
Improvements and new features are greatly appreciated. If you would like to contribute submitting issues, developing new features or making improvements to scikit-maad, please refer to our contributors guide.
To create a positive social atmosphere for our community, we ask contributors to adopt and enforce our code of conduct.
About the project
In 2018, we began to translate a set of audio processing functions from Matlab to an open-source programming language, namely, Python. These functions provided the necessary tools to replicate the Multiresolution Analysis of Acoustic Diversity (MAAD), a method to estimate animal acoustic diversity using unsupervised learning (Ulloa et al., 2018). We soon realized that Python provided a suitable environment to extend these core functions and to develop a flexible toolbox for our research. During the past few years, we added over 50 acoustic indices, plus a module to estimate the sound pressure level of audio events. Furthermore, we updated, organized, and fully documented the code to make this development accessible to a much wider audience. This work was initiated by Juan Sebastian Ulloa, supervised by Jérôme Sueur and Thierry Aubin at the Muséum National d'Histoire Naturelle and the Université Paris Saclay respectively. Python functions have been added by Sylvain Haupert, Juan Felipe Latorre (Universidad Nacional de Colombia) and Juan Sebastián Ulloa (Instituto de Investigación de Recursos Biológicos Alexander von Humboldt). For an updated list of collaborators, check the contributors list.
License
To support reproducible research, the package is released under the BSD open-source licence, which allows unrestricted redistribution for commercial and private use.
Owner
- Name: scikit-maad
- Login: scikit-maad
- Kind: user
- Website: https://scikit-maad.github.io
- Repositories: 1
- Profile: https://github.com/scikit-maad
An open-source and modular toolbox for quantitative soundscape analysis in Python
Citation (CITATION.bib)
@article{ulloa_etal_scikitmaad_2021,
title = {scikit‐maad: {An} open‐source and modular toolbox for quantitative soundscape analysis in {Python}},
issn = {2041-210X, 2041-210X},
shorttitle = {scikit‐maad},
url = {https://onlinelibrary.wiley.com/doi/10.1111/2041-210X.13711},
doi = {10.1111/2041-210X.13711},
language = {en},
urldate = {2021-10-04},
journal = {Methods in Ecology and Evolution},
author = {Ulloa, Juan Sebastián and Haupert, Sylvain and Latorre, Juan Felipe and Aubin, Thierry and Sueur, Jérôme},
month = sep,
year = {2021},
pages = {2041--210X.13711},
}
GitHub Events
Total
- Create event: 6
- Release event: 2
- Issues event: 5
- Watch event: 18
- Delete event: 4
- Issue comment event: 11
- Push event: 26
- Gollum event: 1
- Pull request review comment event: 4
- Pull request review event: 8
- Pull request event: 11
- Fork event: 1
Last Year
- Create event: 6
- Release event: 2
- Issues event: 5
- Watch event: 18
- Delete event: 4
- Issue comment event: 11
- Push event: 26
- Gollum event: 1
- Pull request review comment event: 4
- Pull request review event: 8
- Pull request event: 11
- Fork event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Sylvain Haupert | s****t@m****r | 341 |
| Juan Sebastian Ulloa | j****a@g****m | 260 |
| saguileran | s****n@u****o | 42 |
| scikit-maad | 4****d | 41 |
| jflatorreg | j****g@u****o | 40 |
| Juan Sebastian Ulloa | j****a@J****l | 7 |
| dependabot[bot] | 4****] | 3 |
| Pierre Aumond | p****d@i****r | 1 |
| GabrielPerilla | g****a@h****o | 1 |
| Juan Sebastian Ulloa | l****a@g****m | 1 |
| Juan Cañas | j****s@J****l | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 44
- Total pull requests: 68
- Average time to close issues: 3 months
- Average time to close pull requests: 17 days
- Total issue authors: 27
- Total pull request authors: 10
- Average comments per issue: 1.77
- Average comments per pull request: 0.28
- Merged pull requests: 51
- Bot issues: 0
- Bot pull requests: 7
Past Year
- Issues: 6
- Pull requests: 10
- Average time to close issues: 2 days
- Average time to close pull requests: 3 days
- Issue authors: 6
- Pull request authors: 4
- Average comments per issue: 1.67
- Average comments per pull request: 0.7
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Bengt (9)
- dariodematties (3)
- saguileran (3)
- shaupert (3)
- jokot025 (2)
- charleygros (2)
- kroegern1 (2)
- gg4u (1)
- lizferguson5 (1)
- charlie-garcia (1)
- ss3443 (1)
- apotenza (1)
- Mari2061 (1)
- YizharLavner (1)
- sammlapp (1)
Pull Request Authors
- shaupert (26)
- juansulloa (22)
- dependabot[bot] (7)
- scikit-maad (5)
- Bengt (4)
- Ryanff72 (2)
- arpit-omprakash (2)
- ghost (2)
- jscanass (2)
- pierromond (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 5,875 last-month
- Total docker downloads: 107
- Total dependent packages: 7
- Total dependent repositories: 68
- Total versions: 13
- Total maintainers: 2
pypi.org: scikit-maad
Open-source and modular toolbox for quantitative soundscape analysis in Python
- Homepage: https://github.com/scikit-maad/scikit-maad
- Documentation: https://scikit-maad.github.io/
- License: BSD License
-
Latest release: 1.5.1
published 11 months ago
Rankings
Maintainers (2)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- matplotlib >=3.6
- numpy >=1.21
- pandas >=1.5
- resampy >=0.4
- scikit-image >=0.19
- scipy >=1.8
- matplotlib >=3.6
- numpy >=1.21
- pandas >=1.5
- resampy >=0.4
- scikit-image >=0.19
- scipy >=1.8.0