A Gauss-Seidel solver visualization in a single HTML file

Hacker News

Recently I was reading about fluid simulation and stumbled upon the Gauss Seidel method. I got interested in how it works and made a program that visualizes the method in action. I had the idea of making an interactive book-like thing for a while, so took this as a chance to do just that. Note that touch input doesn't work and the layout is targeted towards bigger screens, so it doesn't function properly on mobile. It was fun to make and I wanted to share it. Maybe someone will find it useful. Corrections and feedback are welcome. Technical Stuff - A single 1.7MB HTML file with embedded JavaScript and WebAssembly. You can save this single file and double click it to run. - A math typesetter from scratch in C that compiles/renders the equations in real-time (uses KaTex fonts and STB true type to rasterize the fonts). - Platform code is done using Sokol (tested on windows and web). - The UI is done using Dear ImGui (Most of the code is done in C++ to use ImGui without a wrapper except for the equations compiler).

Visit product View on Hacker NewsAug 6, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, single, using · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: visualize · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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