Beamshapes: directivity patterns for various sound sources

Introduction

The beamshapes package implements directivity functions (\(\frac{D_{\theta}}{D_{0}}\)) of various published sound radiation models.

What is a directivity function? It’s a function that quantifies how sound level changes as you change the frequency of the emitted sound, and location of the receiver.

Check out a general introduction to the concepts of the package here.

Why beamshapes?

While there are many sound radiation models described in the literature, there aren’t that many (also see levitate ) openly available computational implementations of their beamshapes. Existing packages focus on implementing directivities with analytical solutions - which can be calculated directly and quickly. beamshapes aims to increase the breadth of implemented directivities beyond those with analytical solutions.

Who is this useful for?

Acousticians and bio-acousticians looking to assess model-fits or perform parameter estimation on their sound sources. Check out more on the how to use this package in the examples.

Package installation

pip installation : Install the latest stable version with pip install beamshapes

Local installation : Install from the GitHub repo directly by cloning and following the instructions in the README.

Source models implemented

  • Point source on a sphere

  • Piston in an infinite baffle

  • Oscillating cap of a sphere

  • Piston in a sphere

Concepts

Use Cases

Wishlist for future releases

  • Piston in a finite closed baffle

  • One-sided piston radiator (baffle=cylinder width)

  • Rectangular cap of a sphere

  • Piston on a prolate spheroid

Interested?? Contribute, check out the general workflow tips here. All of the sound-source models and directivity calculations are from Leo Beranek & Tim Mellow’s Acoustics: sound fields and transducers. (Academic Press) - check it out for models that may be of interest or to get an idea of how the wishlist models look like!

Contributors

Thejasvi Beleyur (maintainer, thejasvib@gmail.com)

Gaurav Dhariwal

Acknowledgements

Many thanks to Tim Mellow for sharing Mathematica code to help with porting to Python. Also thanks to Holger R. Goerlitz for layout feedback (still in progress!) and Neetash MR for inspiring the package logo!

API reference:

dev notes