A cheat-sheet that translates mathematical notation into JavaScript code examples for developers.
math-as-code is a reference guide that translates mathematical notation into JavaScript code examples. It helps developers understand symbols like summation (Σ), set membership (∈), and vector operations by showing how they correspond to programming constructs. The project addresses the intimidation of academic math papers by providing practical, code-based explanations.
Self-taught game developers, graphics programmers, and developers who encounter mathematical notation in libraries, papers, or APIs but lack formal math training. It's also useful for educators introducing math concepts in coding contexts.
Unlike generic math guides, it focuses specifically on mapping notation to JavaScript, using real code snippets and referencing popular npm packages. It’s concise, open-source, and community-driven, with translations available in multiple languages.
a cheat-sheet for mathematical notation in code form
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Side-by-side comparisons of mathematical symbols like Σ and ∈ with JavaScript code make abstract concepts concrete and accessible, directly addressing the pain point of intimidating academic papers.
References real npm packages such as mathjs and gl-vec3, providing actionable implementation details for complex operations like vector cross products and complex number arithmetic.
Covers a wide range of topics from basic equality to advanced intervals and logical operators, relevant for graphics and game development, as seen in the comprehensive table of contents.
Actively accepts contributions and offers translations in Chinese and Python, ensuring the guide evolves with community input and remains accessible globally.
The README explicitly states 'This guide is not yet finished,' meaning some symbols or concepts may be missing or underdeveloped, requiring users to seek additional resources.
Admits that code examples use floating-point arithmetic without robustness, which could lead to errors in precision-sensitive applications like scientific computing or financial modeling.
Exclusively uses JavaScript examples, which may not translate directly to other programming environments without extra effort, despite the Python version being a separate, less integrated resource.