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3D spatial index for cuboids (based on R*-tree with bulk loading and bulk insertion algorithms)","maintainers":[{"name":"mikolalysenko","email":"mikolalysenko@gmail.com"},{"name":"erona","email":"erona@loli.bz"}],"readme":"RBush-3D\n=====\n\nRBush-3D is 3D version of [RBush](https://github.com/mourner/rbush).\n\n[![.github/workflows/ci.yml](https://github.com/Eronana/rbush-3d/actions/workflows/ci.yml/badge.svg?branch=master)](https://github.com/Eronana/rbush-3d/actions/workflows/ci.yml)\n[![Coverage Status](https://coveralls.io/repos/github/Eronana/rbush-3d/badge.svg?branch=master)](https://coveralls.io/github/Eronana/rbush-3d?branch=master)\n\n![](https://raw.githubusercontent.com/Eronana/rbush-3d/master/viz.png)\n\n## Install\n\nInstall with NPM: `npm install rbush-3d`\n\nOr use CDN links for browsers: https://app.unpkg.com/rbush-3d/files/dist/index.js\n\n## Usage\n\n### Creating a Tree\n\n```typescript\nimport { RBush3D } from 'rbush-3d';\nconst tree = new RBush3D();\n```\n\nAn optional argument to `RBush3D` defines the maximum number of entries in a tree node.\n`16` (used by default) is a reasonable choice for most applications.\nHigher value means faster insertion and slower search, and vice versa.\n\n```typescript\nconst tree = new RBush3D(16);\n```\n\n### Adding Data\n\nInsert an item:\n\n```typescript\nconst item = {\n    minX: 20,\n    minY: 40,\n    minZ: 60,\n    maxX: 30,\n    maxY: 50,\n    maxZ: 70,\n    foo: 'bar'\n};\ntree.insert(item);\n```\n\n### Removing Data\n\nRemove a previously inserted item:\n\n```typescript\ntree.remove(item);\n```\n\nBy default, RBush-3D removes objects by reference.\nHowever, you can pass a custom `equals` function to compare by value for removal,\nwhich is useful when you only have a copy of the object you need removed (e.g. loaded from server):\n\n```typescript\ntree.remove(itemCopy, function (a, b) {\n    return a.id === b.id;\n});\n```\n\nRemove all items:\n\n```typescript\ntree.clear();\n```\n\n### Data Format\n\nBy default, RBush-3D assumes the format of data points to be an object\nwith `minX`, `minY`, `minZ`, `maxX`, `maxY` and `maxZ` properties.\nYou can customize this by providing an array with corresponding accessor strings\nas a second argument to `rbush3d` like this:\n\n```typescript\nconst tree = rbush3d(16, ['[0]', '[1]', '[2]', '[0]', '[1]', '[2]']); // accept [x, y, z] points\ntree.insert([20, 50, 80]);\n```\n\n### Bulk-Inserting Data\n\nBulk-insert the given data into the tree:\n\n```typescript\ntree.load([item1, item2, ...]);\n```\n\nBulk insertion is usually ~2-3 times faster than inserting items one by one.\nAfter bulk loading (bulk insertion into an empty tree),\nsubsequent query performance is also ~20-30% better.\n\nNote that when you do bulk insertion into an existing tree,\nit bulk-loads the given data into a separate tree\nand inserts the smaller tree into the larger tree.\nThis means that bulk insertion works very well for clustered data\n(where items in one update are close to each other),\nbut makes query performance worse if the data is scattered.\n\n### Search\n\n```typescript\nconst result = tree.search({\n    minX: 40,\n    minY: 20,\n    minZ: 50,\n    maxX: 80,\n    maxY: 70,\n    maxZ: 90\n});\n```\n\nReturns an array of data items (points or rectangles) that the given bounding box intersects.\n\nNote that the `search` method accepts a bounding box in `{minX, minY, minZ, maxX, maxY, maxZ}` format\nregardless of the format specified in the constructor (which only affects inserted objects).\n\n```typescript\nconst allItems = tree.all();\n```\n\nReturns all items of the tree.\n\n### Collisions\n\n```typescript\nconst result = tree.collides({minX: 40, minY: 20, minZ: 50, maxX: 80, maxY: 70, maxZ: 90});\n```\n\nReturns `true` if there are any items intersecting the given bounding box, otherwise `false`.\n\n\n### Export and Import\n\n```typescript\n// export data as JSON object\nconst treeData = tree.toJSON();\n\n// import previously exported data\nconst tree = rbush3d(16).fromJSON(treeData);\n```\n\nImporting and exporting as JSON allows you to use RBush-3D on both the server (using Node.js) and the browser combined,\ne.g. first indexing the data on the server and and then importing the resulting tree data on the client for searching.\n\nNote that the `nodeSize` option passed to the constructor must be the same in both trees for export/import to work properly.\n\n## Performance\n\nThe following sample performance test was done by generating\nrandom uniformly distributed rectangles of ~0.01% area and setting `maxEntries` to `16`\n(see `debug/perf.ts` script).\nPerformed with Node.js v24.6.0 on a MacBook Pro (Apple M2 Max).\n\nTest                         | RBush-3D | [RBush](https://github.com/mourner/rbush) (2D version)\n---------------------------- | -------- | ------\ninsert 1M items one by one   | 1265ms   | 904ms\n1000 searches of 0.01% area  | 12ms     | 20ms\n1000 searches of 1% area     | 67ms     | 171ms\n1000 searches of 10% area    | 487ms    | 774ms\nremove 1000 items one by one | 8ms      | 5ms\nbulk-insert 1M items         | 805ms    | 703ms\n\n\n## Algorithms Used\n\n* single insertion: non-recursive R-tree insertion with overlap minimizing split routine from R\\*-tree (split is very effective in JS, while other R\\*-tree modifications like reinsertion on overflow and overlap minimizing subtree search are too slow and not worth it)\n* single deletion: non-recursive R-tree deletion using depth-first tree traversal with free-at-empty strategy (entries in underflowed nodes are not reinserted, instead underflowed nodes are kept in the tree and deleted only when empty, which is a good compromise of query vs removal performance)\n* bulk loading: OMT algorithm (Overlap Minimizing Top-down Bulk Loading) combined with Floyd–Rivest selection algorithm\n* bulk insertion: STLT algorithm (Small-Tree-Large-Tree)\n* search: standard non-recursive R-tree search\n\n## Papers\n\n* [R-trees: a Dynamic Index Structure For Spatial Searching](http://www-db.deis.unibo.it/courses/SI-LS/papers/Gut84.pdf)\n* [The R*-tree: An Efficient and Robust Access Method for Points and Rectangles+](http://dbs.mathematik.uni-marburg.de/publications/myPapers/1990/BKSS90.pdf)\n* [OMT: Overlap Minimizing Top-down Bulk Loading Algorithm for R-tree](http://ftp.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-74/files/FORUM_18.pdf)\n* [Bulk Insertions into R-Trees Using the Small-Tree-Large-Tree Approach](http://www.cs.arizona.edu/~bkmoon/papers/dke06-bulk.pdf)\n* [R-Trees: Theory and Applications (book)](http://www.apress.com/9781852339777)\n\n## Development\n\n```bash\nnpm install   # install dependencies\n\nnpm test      # check the code with JSHint and run tests\nnpm run perf  # run performance benchmarks\nnpm run cover # report test coverage (with more detailed report in coverage/lcov-report/index.html)\nnpm run viz   # show 3d visualization in browser\n```\n","readmeFilename":"README.md"}