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Analyze, visualize and process sound field data recorded by spherical microphone arrays.
Project description
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The sound_field_analysis toolbox (short: sfa) is a Python port of the Sound Field AnalysisToolbox (SOFiA) toolbox, originally by Benjamin Bernschütz [1]. The main goal of the sfatoolbox is to analyze, visualize and process sound field data recorded by spherical microphonearrays. Furthermore, various types of test-data may be generated to evaluate the implementedfunctions. It is an essential building block of ReTiSAR, an implementation of real timebinaural rendering of spherical microphone array data.
Requirements
We use Python 3.7 for development. Chances are that earlier version will work too but this is currently untested.
The following external libraries are required:
- Jupyter (for running Notebooks locally)
- Plotly (for plotting)
Installation
For performance and convenience reasons we highly recommend to use Conda (miniconda for simplicity) to manage your Python installation. Once installed, you can use the following steps to receive and use sfa, depending on your use case:
From PyPI:
Install into an existing environment (without example Jupyter Notebooks):pip install sound_field_analysis
By cloning (or downloading) the repository and setting up a new environment:
git clone https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py.git
cd sound_field_analysis-py/
Create a new Conda environment from the specified requirements:conda env create --file environment.yml
Activate the environment:source activate sfa
Optional: Install additional requirements in case you want to locally run the Jupyter Notebooks with examples:conda env update --file environment_jupyter.yml
Documentation
Find the full documentation at https://appliedacousticschalmers.github.io/sound_field_analysis-py/.
Examples
The following examples are available as Jupyter notebooks, either statically on GitHub or interactively onnbviewer. You can of course also simply download the examples and run them locally!
Exp1: Ideal plane wave
Ideal unity plane wave simulation and 3D plot.
Exp2: Measured plane wave
A measured plane wave from AZ=180°, EL=90° in the anechoic chamber using a cardioid mic.
Exp4: Binaural rendering
Render a spherical microphone array impulse response measurement binaurally. The example shows examples for loadingmiro or SOFA files.
Version history
- Update of README and PyPI package
- Update of internal documentation and string formatting
- Change of version number scheme to CalVer
- Improvement of Exp4
- Update of read_SOFA_file
- Update of 2D plotting functions
- Improvement of write_SSR_IRs
- Improved environment setup for jupyter notebook
- Update of miro_to_struct
- Implement SOFA import
- Update Exp4 to contain SOFA import
- Delete obsolete Exp3
- Add named tuple HRIRSignal
- Implement cart2sph and sph2cart utility functions
- Add conda environment file for convenient installation of required packages
- Implement Spherical Harmonics coefficients tapering
- Adaption of associated Spherical Head Filter
- Implement Bandwidth Extension for Microphone Arrays (BEMA)
- Edit read_miro_struct, named tuple ArraySignal and miro_to_struct.m to load center measurements
Sofa Downloadsofashallow Foundation Analysis Software For Beginners
- Port of Radial Filter Improvement from SOFiA
- Implement Spherical Head Filter
- Implement Spherical Fourier Transform using pseudo-inverse
- Extract real time capable Spatial Fourier Transform
- Outsource reversed m index function (Exp4)
References
The sound_field_analysis toolbox is based on the Matlab/C++ Sound Field Analysis Toolbox (SOFiA) toolbox byBenjamin Bernschütz. For more information you may refer to the original publication:
[1] Bernschütz, B., Pörschmann, C., Spors, S., and Weinzierl, S. (2011). SOFiA Sound Field Analysis Toolbox.Proceedings of the ICSA International Conference on Spatial Audio
The Lebedev grid generation was adapted from an implementation by Richard P. Muller.
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- Change of version number scheme to CalVer
- Improvement of Exp4
- Update of read_SOFA_file
- Update of 2D plotting functions
- Improvement of write_SSR_IRs
- Improved environment setup for jupyter notebook
- Update of miro_to_struct
- Implement SOFA import
- Update Exp4 to contain SOFA import
- Delete obsolete Exp3
- Add named tuple HRIRSignal
- Implement cart2sph and sph2cart utility functions
- Add conda environment file for convenient installation of required packages
- Implement Spherical Harmonics coefficients tapering
- Adaption of associated Spherical Head Filter
- Implement Bandwidth Extension for Microphone Arrays (BEMA)
- Edit read_miro_struct, named tuple ArraySignal and miro_to_struct.m to load center measurements
Sofa Downloadsofashallow Foundation Analysis Software For Beginners
- Port of Radial Filter Improvement from SOFiA
- Implement Spherical Head Filter
- Implement Spherical Fourier Transform using pseudo-inverse
- Extract real time capable Spatial Fourier Transform
- Outsource reversed m index function (Exp4)
References
The sound_field_analysis toolbox is based on the Matlab/C++ Sound Field Analysis Toolbox (SOFiA) toolbox byBenjamin Bernschütz. For more information you may refer to the original publication:
[1] Bernschütz, B., Pörschmann, C., Spors, S., and Weinzierl, S. (2011). SOFiA Sound Field Analysis Toolbox.Proceedings of the ICSA International Conference on Spatial Audio
The Lebedev grid generation was adapted from an implementation by Richard P. Muller.
Release historyRelease notifications | RSS feed
Sofa Download Sofa Shallow Foundation Analysis Software Windows 10
2020.1.30
0.3
0.2
0.1.dev0 pre-release
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Filename, size | File type | Python version | Upload date | Hashes |
---|---|---|---|---|
Filename, size sound_field_analysis-2020.1.30-py3-none-any.whl (37.7 kB) | File type Wheel | Python version py3 | Upload date | Hashes |
Filename, size sound_field_analysis-2020.1.30.tar.gz (43.5 kB) | File type Source | Python version None | Upload date | Hashes |
Hashes for sound_field_analysis-2020.1.30-py3-none-any.whl
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SHA256 | e0bf15abb5e86fb67b2b52442d12f62830dbcac64ee8bceb1ab549e142a8a9d8 |
MD5 | 34f03bd880e2aa24e8cb69a5fabc7087 |
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Sofa Downloadsofashallow Foundation Analysis Software Free
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Sofa Downloadsofashallow Foundation Analysis Software Developer
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