Diffusion Equation Software for Room Acoustics Modeling
acousticDE is an open-source software package developed for the simulation of room acoustics based on the diffusion equation method. The package provides two complementary numerical implementations of this method: the Finite Volume Method (FVM) and the Finite Difference Method (FDM). In addition, it includes a tool for auralization enabling users to listen to acoustic renderings generated from the results of the Finite Volume Method. The main strength of acousticDE is in its ability to predict the distribution of acoustic energy over space and time within a given room. With only a minimal set of input parameters, the software delivers accurate and computationally efficient estimates of both the energy propagation and room acoustics properties. This makes it a valuable tool for researchers and practitioners interested in architectural acoustics. The software is being developed as part of an ongoing research within the Building Acoustics Group at the Department of Built Environment, Eindhoven University of Technology. It is currently under active development and implemented in Python by Ilaria Fichera.
Release version
Version 0.1.0
Repository structure
The package acousticDE is formed by three subfolders:
- Auralization generates the auralization wav file for the room in question;
- FiniteDifferenceMethod computes the room acoustics based on the diffusion equation using the finite difference method (Navarro et al., 2012);
- FiniteVolumeMethod computes the room acoustics based on the diffusion equation using the finite volume method (Munoz, 2019);
Installation
Use pip to install acousticDE
pip install acousticDE
Once installed, in cmd window, use the following commands:
python
import acousticDE
To run FVM, continue with:
from acousticDE.FiniteVolumeMethod.FVM import run_fvm_sim
results = run_fvm_sim('C:\....\mesh.msh','C:\....\mesh_input_fvm.json','C:\....\absorption_coefficients.csv')
To run FDM, continue with:
from acousticDE.FiniteDifferenceMethod.FDM import run_fdm_sim
results = run_fdm_sim('C:\....\mesh_input_fdm.json')
To run Auralization, continue with:
from acousticDE.Auralization.Auralization import run_auralization_sim
results = run_auralization_sim('C:\....\anechoic_file.wav','C:\....\resultsFVM.pkl')
To run the codes/functions, check the documentation depending on the method you want to use, create the files needed for the specific function and check the Tutorial sections of the documentation.
Usage & Documentation
The documentation is created to help to use and develop acousticDE effectively. To use acousticDE, please refer to the Tutorial section of the documentation. In addition, the documentation gives an introduction of the package for both FDM and FVM.
Authors
Software is being developed by Ilaria Fichera at Eindhoven University of Technology (TU/e).
Funding
This research is founded by the Dutch Research Council (NWO), Applied and Engineering Sciences (AES) under grant agreement No. 19430, with project title "A new era of room acoustics simulation software: from academic advances to a sustainable open-source project and community".
License
Diffusion is under copyright of Building Acoustics Group at the Eindhoven University of Technology and is licensed under GNU General Public License v2.0. See LICENSE.md for more details.
References
J. M. Navarro, J. Escolano and J. J. Lopez, Implementation and evaluation of a diffusion equation model based on finite difference schemes for sound field prediction in rooms, Applied Acoustics 73 (2012).
R. P. Muñoz, Numerical modeling for urban sound propagation: developments in wave-based and energy based methods, PhD Thesis, Technische Universiteit Eindhoven, 2019.
Metadata
Release files for acousticDE 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| acousticde-0.1.0.tar.gz | 7.6 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| acousticde-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.2 MB
Release files / acousticde-0.1.0.tar.gz
| Download URL | acousticde-0.1.0.tar.gz |
|---|---|
| Size | 7.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4a883246ea3270cc56e8b6fe2abb7fa23e6352e13003cade6433be7337d5f9c8
|
|
BLAKE2b-256 checksum How to use checksums |
bfcbd0c504b63cb698232427b39adc7841efd6ce8aa9e41a59d958da55308e44
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.7
|
Release files / acousticde-0.1.0-py3-none-any.whl
| Download URL | acousticde-0.1.0-py3-none-any.whl |
|---|---|
| Size | 7.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9a7b4fb630b1424e2ab057f50b62ccaef9c5c3a9a10d13a06f5f68169259bcdd
|
|
BLAKE2b-256 checksum How to use checksums |
f8b7ea6a78a698bf278ce97452aea2f33dba68bfcb77a81f08f739a178981c97
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.7
|
Security for acousticDE 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.