sound_field_analysis-py

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.

Requirements

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:

NumPy
SciPy
Pysofaconventions
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 / pip:

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 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

Examples

The following examples are available as Jupyter Notebooks, either statically on GitHub or interactively on nbviewer. You can of course also simply download the examples and run them locally!