Fast Chladni figure simulation in Python with NumPy vectorization
Beautiful physics visualization, but Chladni simulations exist in MATLAB, Mathematica, and other interactive platforms.

No-buffering spectral analysis that updates per sample, but audio DSP is a tiny audience.
Audio developers, DSP researchers, music technologists
librosa · Essentia · phase vocoder implementations
A lot has happened since: the work I presented in much more detail at last June's International Computer Music Conference (ICMC) got best paper award. I also gave a talk at the Audio Developer Conference in Bristol last November, the video is on YouTube).
This year's work, which I recently presented at this year's ICMC, starts with known techniques from the phase vocoder literature to build self-tuning filter banks that extract very efficiently the frequency components that are actually present in the input signal. Overview on the project website, more details in the papers, including applications to super-resolution spectrograms and re-synthesis experiments.
As many people have pointed out, none of the techniques I have used are new (some of them even have different names across different fields), but I haven't seen them applied together in this way, and to me the results are incredibly satisfying and sometimes look magical. See for example this demo: https://youtu.be/LasdoIJJkw8
Of course the best way to experience in person is through the free demo app: https://alexandrefrancois.org/Oscillators
Looking forward to feedback from the community!
Beautiful physics visualization, but Chladni simulations exist in MATLAB, Mathematica, and other interactive platforms.
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