Analyze, visualize and process sound field data recorded by spherical microphone arrays.
The sound_field_analysis toolbox (short: sfa) is a Python port of the Sound Field Analysis Toolbox (SOFiA) toolbox, originally by Benjamin Bernschütz. The main goal of the sfa toolbox is to analyze, visualize and process sound field data recorded by spherical microphone arrays. Furthermore, various types of test-data may be generated to evaluate the implemented functions. It is an essential building block of ReTiSAR, an implementation of real time binaural rendering of spherical microphone array data.
We use Python 3.9 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)
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:
Create a new Conda environment from the specified dependencies:
conda env create --file environment.yml --force
Activate the environment:
source activate sfa
Optional: Install additional dependencies for development purposes (locally run Jupyter Notebooks with example, run tests, generate documentation):
conda env update --file environment_dev.yml
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 loading miro or SOFA files.