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Ture - [Demo](http://dannycalleri.github.io/ture)\n\n[![npm version](https://badge.fury.io/js/ture.svg)](https://badge.fury.io/js/ture)\n![Node.js CI](https://github.com/dannycalleri/ture/workflows/Node.js%20CI/badge.svg)\n\nTure is a collection of algorithms and data structures written in TypeScript for fun and profit.\n\n**WTF does Ture mean?** Essentially, it's a famous **sicilian** personal name, but it's contained in the word strucTUREs and remembers Alan Turing as well, so why not.\n\nBeware that some algorithms and data structure aren't really optimized for production use, so please take this into account before depending on this package. At the moment I'm using it on personal small projects, especially small video game demos.\n\nFor instance the KdTree (a 2d tree implementation actually) and its operation are ready for production use and guaranteed to run on logarithmic time in the typical case (nearest), while some other algorithms on graphs are in the works and may need some testing.\n\n## Features\n\n* KdTree (2d tree implementation)\n  * `range` and `nearest` operations\n  * nearest operation runs in logarithimic time in the typical case, worst case O(n)\n  * range worst case R + sqrt(n), where R is the number of points returned that are in range\n* Test cases and examples (found in the `/examples` folder) to get started\n\n\n## Install\n\nSimply `npm install ture --save`.\n\nThen use it like in the following example:\n\n```typescript\nimport {\n  KdTree,\n  Point2D\n} from \"ture\";\n\n// contains\n\nconst tree: KdTree = new KdTree();\ntree.insert(new Point2D(0.7, 0.2));\ntree.insert(new Point2D(0.5, 0.4));\ntree.insert(new Point2D(0.2, 0.3));\ntree.insert(new Point2D(0.4, 0.7));\ntree.insert(new Point2D(0.9, 0.6));\n\ntree.contains(new Point2D(0.4, 0.7)); // true\ntree.contains(new Point2D(0.3, 0.7)); // false\n\n// range\n\nconst tree: KdTree = new KdTree();\ntree.insert(new Point2D(0.1, 0.4));\ntree.insert(new Point2D(0.6, 0.5));\nconst points = tree.range(new Rect(0.4, 0.3, 0.8, 0.6));\nconsole.log(points.length); // 1\nconsole.log(points[0]); // (0.6, 0.5)\n\n// nearest\n\nconst tree: KdTree = new KdTree();\ntree.insert(new Point2D(0.206107, 0.095492)); // A\ntree.insert(new Point2D(0.975528, 0.654508)); // B\ntree.insert(new Point2D(0.024472, 0.345492)); // C\ntree.insert(new Point2D(0.793893, 0.095492)); // D\ntree.insert(new Point2D(0.793893, 0.904508)); // E\ntree.insert(new Point2D(0.975528, 0.345492)); // F\ntree.insert(new Point2D(0.206107, 0.904508)); // G\ntree.insert(new Point2D(0.500000, 0.000000)); // H\ntree.insert(new Point2D(0.024472, 0.654508)); // I\ntree.insert(new Point2D(0.500000, 1.000000)); // L\nconst nearestPoint = tree.nearest(new Point2D(0.81, 0.30));\nconsole.log(nearestPoint); // (0.975528, 0.345492)\n```\n\nor\n\n```typescript\nimport {\n  Graph,\n} from \"ture\";\nconst graph: Graph = createGraph([\n  '1337',\n  '1338',\n  '1339',\n]);\ngraph.addEdge('1337', '1338');\n```\n\n## Credits\n\nSome of the data structures are ported from Java from the wonderful book \"Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne\".\n\n\n## License\n\nThis project is licensed under the terms of the MIT license.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdannycalleri%2Fture","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdannycalleri%2Fture","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdannycalleri%2Fture/lists"}