DidgeLab

1. Introduction
2. Related works
3. Getting Started
- 3.1 Installation
- 3.2 Documentation
4. Developer Instructions
5. Source code overview
6. Licensing

1. Introduction

DidgeLab is a free open-source toolkit to compute didgeridoo geometries. Traditionally, building a didgeridoo is a random process: builders know how geometry influences the sound, but the exact sonic properties can only be determined after the instrument is built. DidgeLab helps by first defining the desired sound and then computing a geometry that (in simulation) achieves it.

It provides:

Acoustical simulation — Compute resonant frequencies and impedance spectra for a given didgeridoo geometry. This is similar in spirit to Didgmo and DidjiImp.
Computational evolution — Search for bore shapes that meet target sonic properties (e.g. drone in D, toots in F, G, B). This is inspired by the work of Frank Geipel (Computer-Aided Didgeridoo Sound Design, CADSD).

So the first part takes a geometry and predicts its sound; the second takes a target sound and searches for a matching geometry. To the best of our knowledge, DidgeLab is the first open toolkit that implements this inverse design.

The software is a Python toolkit rather than a point-and-click app: you use it from scripts or Jupyter notebooks. There is no graphical user interface. You need Python skills to use it.

If you are not into Python programming, I suggest you use the web-based software didgelab.com.

2. Related works

Frank Geipel — Computer-Aided Didgeridoo Sound Design (CADSD). DidgeLab’s approach is based on our reading of his ideas and descriptions.
Dan Mapes-Riordan (1991) — Horn Modeling with Conical and Cylindrical Transmission Line Elements. Foundation for the transmission-line acoustical model.
Andrea Ferroni (YouTube) — Didgeridoo acoustics and playing; e.g. DIDGMO explanation, backpressure, cylindrical vs conical bore.
Didgmo / Didjimp — Existing tools for didgeridoo sound design; used here as a reference (DidgeLab’s impedance spectra match when given the same geometry).

3. Getting Started

3.1 Installation

Prerequisites

Python 3.8+ (Conda or venv recommended)
Optional: Cython and a C compiler for the fast simulation backend

Use Pip Package

pip install didgelab

3.2 Documentation

Here is an overview of the available documentation. The best place to get started are the tutorials:

4. Developer Instructions

4.1 Compile from source

If you use the pip package, you do not need to compile it from source.

Clone the repository and go to the project directory:
```
git clone https://github.com/jnehring/didge-lab/
cd didge-lab
```
(Or download and unzip the source.)

Create and activate a Conda environment:

conda create -n didgelab python=3.8
conda activate didgelab

Install the package (from the repository root; this builds the Cython extension and installs didgelab):
```
pip install -e .
```
Dependencies (NumPy, Cython, etc.) are installed as build/install dependencies. For a non-editable install: pip install .
Run a quick check (e.g. a script or notebook that runs a simulation and prints a small impedance table). If you see a frequency/impedance/note table, the installation is working.

4.2 Unit Tests (pytest)

From the repository root:

pytest

Tests live in src/tests/. To run a subset:

pytest src/tests/test_geo.py
pytest src/tests/test_KigaliShape.py -v

Some tests mock the Cython simulation backend so they run without building it; others require the full install (including the compiled _cadsd extension). Use the same Python environment in which you installed didgelab.

4.3 Building the Python package

Editable install (recommended for development)
From the repo root:
```
pip install -e .
```
Changes in src/didgelab are picked up without reinstalling.
Regular install
```
pip install .
```
Rebuild after changing Cython code
Reinstall so the extension is recompiled:
```
pip install -e . --no-build-isolation
```
Or pip install -e . --force-reinstall if needed. A C compiler and Cython are required; see Cython docs for your OS.
Source distribution and wheel
```
pip install build
python -m build
```
Outputs go to dist/ (e.g. pip install dist/didgelab-*.whl).
Tutorials in examples/tutorials/ walk through acoustical simulation, shape parameters, and evolution.
The didgelab package is documented with module and function/class docstrings; use help() in Python or read the source.

4.4 Build Documentation

API documentation (pdoc)
Use pdoc to generate API docs from docstrings. From the repo root, ensure the local package is used (e.g. after pip install -e . or with PYTHONPATH=src).

Development — live preview
Serve docs locally and reload as you edit:
```
pip install pdoc
PYTHONPATH=src pdoc src/didgelab --http 8080
```
Open http://localhost:8080. Stop with Ctrl+C.
Render static HTML
Write the API docs into a folder (e.g. for deployment or offline use):
```
pip install pdoc
PYTHONPATH=src pdoc src/didgelab -o docs/html
```
Then open docs/html/index.html in a browser or serve the docs/html directory with any static file server.

5. Source code overview

didgelab — Main package:
- acoustical_simulation — Entry point for running simulation (Python or Cython backend).
- geo — Geometry class (segment list, load/save, scale, cones, volume, etc.).
- conv — Note/frequency conversion (note names, cents, wavelengths).
- fft — FFT and spectrum helpers (WAV, harmonics, fundamental, peaks).
- visualize — Plot bore profiles (2D cross-section).
- app — Global app, config, logging, publish/subscribe, services.
- sim — Simulation: sim_interface, tlm_python, tlm_cython (TLM = transmission line model).
- evo — Evolution: shapes, loss functions, mutators, evolution loop, checkpoint/loss logging.
Build — From repo root: pip install -e . (see §4.1 and §4.3).

6. Licensing

DidgeLab is published under Creative Commons BY-NC-SA 4.0:

Share — copy and redistribute in any medium or format
Adapt — remix, transform, and build upon the material

Under these terms:

Attribution — Give appropriate credit, link to the license, and indicate if changes were made.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix or build upon the material, you must distribute your contributions under the same license.
No additional restrictions — Do not apply legal or technical measures that restrict others from doing what the license permits.

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didgelab 3.0.21

DidgeLab

1. Introduction

2. Related works

3. Getting Started

3.1 Installation

3.2 Documentation

4. Developer Instructions

4.1 Compile from source

4.2 Unit Tests (pytest)

4.3 Building the Python package

4.4 Build Documentation

5. Source code overview

6. Licensing

Project links

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1 maintainer

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BLAKE2b-256	`457c362ef11f6ab0b9cef2b457a9b1b320cacca6d9228a726fa56c4f96bf6b47`

Algorithm	Hash digest
SHA256	`495e3a69c058d6a5a6177b8b80313429f4b7bd409a765bca48e0f1ecfd518f7d`
MD5	`081f049b3093a708054c91e3905757df`
BLAKE2b-256	`c508417b641bc2e5fd73e01f32149d29d6ccfc97b8fb8db0725fccd05e7b330a`

Algorithm	Hash digest
SHA256	`1dea6c967e974c42813353cb8948ed390728a870ce708045c744ab8451ccafec`
MD5	`c5d6f7633b0a15b77c503a6915f9bf61`
BLAKE2b-256	`b776df0fc9a37a6829337e4c54f67dbb7e9f722f24120fbb921c13237f956d0a`

Algorithm	Hash digest
SHA256	`609924b45b1394d4a5c48bb3d755a80b7fe5e73f6ae2eb5ff97fc1c0f542f39d`
MD5	`50e0c9699604272be87d308e734ba6e5`
BLAKE2b-256	`74f5e68c97fc17227b47b8aed7b9ae16bf7e192b832845375a302fbf4ea7a372`

Algorithm	Hash digest
SHA256	`d54ca50d1096950b9cee3857d27b7f953a450e70e7f31a4ec832825343b48142`
MD5	`c3c4f553bd8a0f421ab9c3383850a05a`
BLAKE2b-256	`3118a99c518b89de4b5862abc53eacabdd8a3afa3566ff3cb191b39af9db078a`

Algorithm	Hash digest
SHA256	`0b40841ebeb9a607e55d2fe8c92458273a44daaaad8a4f1e3b8396a05bd8a545`
MD5	`a146fb2ac74712ed985bda9ef34859c9`
BLAKE2b-256	`dcda8ec9423ce8f5139cce2ce8566136d2bd5229f9fb727560abdb7fae999dad`

Algorithm	Hash digest
SHA256	`7e5aa21a57e1141ca9d2d8fc960336a1a97eb791eed4e0c80aa66ae64c1d5cbb`
MD5	`eb6c4aa77797cb620f7ed5253680df96`
BLAKE2b-256	`5a73f0eb72067a7cdd18fab3aa42a6052632a45ca0877a3303e22de19b7b5a12`

Algorithm	Hash digest
SHA256	`cd47304ce03ab82e97cc6791df40a73c0b32ab7b03111d4dba24108b1667a8f7`
MD5	`8052ce8ad5274d6907d83cf71d854b48`
BLAKE2b-256	`1b63bc31d37d33c6ef404ec1c5595bdf6afc123a9a21ed92016ccd8c89b12866`

Algorithm	Hash digest
SHA256	`abf91c1c1f66cc0973cbc470614ddd17bb32697568ac028bdd0eef9cba5eed40`
MD5	`7877ebbfda8513d8453af0f39eb8557e`
BLAKE2b-256	`ce8fa8163253e6b6438481adacbe3e339b88fb302fc5efac4db72d5858c04687`

Algorithm	Hash digest
SHA256	`039c1f7a9c7e2d04e35c05aff7db32ff7b3a10113d68ad13707c26d9b0151d18`
MD5	`79182832e61feeb0dec97d8bb9eea75a`
BLAKE2b-256	`ba364502bec21dcf0c12ef3f67d2605a594afa3991a24a37534f29d88985e373`