Open Source JavaScript Algorithms for Mac

A really fast static spatial index for 2D points and rectangles in JavaScript. An efficient implementation of the packed Hilbert R-tree algorithm. Enables fast spatial queries on a very large number of objects (e.g. millions), which is very useful in maps, data visualizations and computational geometry algorithms.

Free Java Flowchart simulator / interpreter

Delaunator is a fast library for Delaunay triangulation. It takes as input a set of points. The triangulation is represented as compact arrays of integers. It’s less convenient than other representations but is the reason the library is fast. After constructing a delaunay = Delaunator.from(points) object, it will have a triangles array and a halfedges array, both indexed by half-edge id. What’s a half-edge? A triangle edge may be shared with another triangle. Instead of thinking about each edge A↔︎B, we will use two half-edges A→B and B→A. Having two half-edges is the key to everything this library provides. It will also be useful to have some helper functions to go from one half-edge to the next and previous half-edges in the same triangle. We can draw all the triangle edges without constructing the triangles themselves.

Algorithm Visualizer for IPython/Jupyter Notebook. If you use the display(TracerObject) code from where you want to see, you can use it without any special modification.

RBush is a high-performance JavaScript library for 2D spatial indexing of points and rectangles. It's based on an optimized R-tree data structure with bulk insertion support. Spatial index is a special data structure for points and rectangles that allows you to perform queries like "all items within this bounding box" very efficiently (e.g. hundreds of times faster than looping over all items). It's most commonly used in maps and data visualizations. The demos contain visualization of trees generated from 50k bulk-loaded random points. Open web console to see benchmarks; click on buttons to insert or remove items; click to perform search under the cursor. An optional argument to RBush defines the maximum number of entries in a tree node. 9 (used by default) is a reasonable choice for most applications. Higher value means faster insertion and slower search, and vice versa.

This is a review summary project about preparing for front-end interviews that I have summarized, and the project is updated from time to time. This is not only a strategy for job interviews, but also a collection of front-end ers to examine themselves and achieve breakthroughs. I hope that through this guide, everyone can open up their own lines of Ren and Du, and go further on the road to the front. This warehouse uses a large number of diagrams to convey knowledge. The so-called picture is worth a thousand words. I hope that this kind of graphic expression will make it easier for you to remember some abstract and incomprehensible concepts. "Graphic Front End" is my subtitle to it. Interviewing is a very subjective and difficult thing. Just because you don't pass the interview doesn't mean you're unqualified, just like passing the interview doesn't mean you're qualified. As a candidate, you are usually given 45 minutes to demonstrate your skills.

Inspired by Grokking Algorithms and python-execution-trace, this project aims to reveal the mechanics behind algorithms via interactive visualizations of their execution. Visual representations of variables and operations augment the control flow, alongside actual source code. You can fast forward and rewind the execution to closely observe how an algorithm works. The same code that is displayed next to the illustration is also decorated using babel-plugin-trace-execution and executed to record the context at every step. Literally the same source file. Going back and forth between function execution (and call stack when algorithm uses recursion) is effortless. So is pausing and resuming. This project uses styled-jsx, but takes the idea of CSS-in-JS even further. Sizing, positioning and transition offsets are computed by JS, all before elements hit the DOM.

ngraph.path is a JavaScript library that implements efficient pathfinding algorithms for graphs, primarily designed to compute shortest paths in weighted or unweighted networks. It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. Its data structures and algorithm choices are optimized for performance and memory efficiency, so even large meshes or road networks can be navigated interactively. With its standalone design, ngraph.path can be used in browser apps, server-side Node.js services.