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RBush is a high-performance Web coding library for 2D spatial indexing of elements and rectangles. It's based on an optimized R-tree data model with bulk insertion support. Spatial classification is a singular facts structure for points additionally rectangles that allows you to perform queries equal to "all items within this bounding box" very successfully (e.g. hundreds of times faster against looping over all items). It's most commonly used in maps and details visualizations. Any demos contain visualization featuring trees generated from 50k bulk-loaded haphazard points. Open web console to peek benchmarks; click throughout buttons to transpose or sever possessions; click to perform search under the cursor. Individual optional argument to RBush defines the top number of entries in a cedar node. 9 (used through default) is a reasonable choice for most applications. Higher value means faster insertion and slower search, and evil versa.

Features

• RBush removes objects by reference
• RBush assumes all composition of data points to be a object with minX, minY, maxX and maxY properties
• Bulk-Inserting Data
• Bulk insertion is usually ~2-3 times faster than inserting items someone by one
• Importing and exporting as JSON allows you in order to use RBush on both certain server (using Node.js) and its browser combined
• Non-recursive R-tree insertion including overlap minimizing split routine from R*-tree

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