Efficient quadtrees library written in CoffeeScript.
Immutable quadtrees in JavaScript
Functions that map the quads in D3 quadtrees to rects and maps the points as well.
Node.js QuadTree Implemention.
Two-dimensional recursive spatial subdivision.
A module to build quadtrees for the barnes-hut algorithm with high performance, implemented using WebAssembly (WIP)
Another quadtree implementation for javascript
geohash (ish) nontree (9-tree) spatial indexing for GeoJSON
Force-directed graph where nodes are calculated as ellipses. Offers better layout than circular nodes when nodes are wide or tall, or vary, e.g. with text labels.
geospatial quadtree encoding and decoding.
Quadkey Bitmask Tiles — cloud-optimized tile index and spatial grid format
Experimental N-dimensional force based graph layout
Super fast point clustering on Google Maps via D3js
Compresses a game map (from tiled editor) using a quadtree
Wrapper for the Met Office's datapoint API
Extends the Cesium3DTileset class to allow temporal segmentation of tiles.
A Quadtree data structure written in Typescript.
Simple, dependency-free ID-based quadtree
A quadtree plugin for bevy
High-performance loose quadtree for 2D collision queries.
Point/region Quadtree with support for overlapping regions.
A generic quadtree implementation
A quadtree-based data structure for placing shapes such as rotated rectangles in bounded 2D space, checking for collision with already placed items.
A simple quadtree implementation
A lightweight Region Quadtree
A quadtree implementation
A fast and flexible generic spatial tree collection (Octree, Quadtree, etc)
A quadtree that maps bounding-boxes to elements
A Quadtree implementation for use within Gaia
Quadtrees in Ruby.
Ruby Quadtree Library
Create a quadtree by decomposing images by color using CIELAB.
This is a data structure to represent and manage k-trees, primarily created for use in RubyNEAT, but may see other possible applications. The goal here is to be roebust in the creation of your k-tree, to allow you to prune during creation, since, especially for higher-dimensional trees, the number of leaf node can become very large. So a parent will have children nodes created down to the desired resolution, and immediately after the creation of the children, will check to see if there's enough variance among the children to keep them. If not, they are pruned immediately.
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