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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithm","interpolation","sparse-data"],"created_at":"2025-02-12T21:51:00.305Z","updated_at":"2026-03-06T20:31:34.484Z","avatar_url":"https://github.com/jonathanlurie.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 2D natural neighbor interpolation (nni)\nFor Node and browsers.  \n\nSome info [about nni](http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-natural-neighbor-works.htm).  \nThe *nii* method is used to interpolate sparse data point along a regular 2D grid surface. This methods work with Voronoi cells and area stilling and is said to give results that are close to the \"real solution\". The only issue with this method is that it's very computational, and thus, quite slow.\n\nOn the left: nni, on the right: same but with using some threshold at rendering.  \n![](nni.png)\n\n## Concept\nSparse point interpolations need:  \n- a set of sparse points. Here, we will call them *seeds*\n- an output size (width and height)\n\nThis implementation performs the interpolation in two steps:\n- build the interpolation map for each output pixel, aka the weight of each seeds involved in each output pixel\n- use the interpolation map to create the output image\n\nThe purpose of creating the map at an intermediary step is to be able to reuse it for the same configuration but with different seed values, because what takes a while to generate is this interpolation map.\n\n## Install\n`npm install --save natninter`\n\nUse it in a HTML file:  \n```html\n\u003cscript src=\"natinter/dist/natninter.js\"\u003e\u003c/script\u003e\n```\n\nUse it in ES6:  \n```js\nimport * as natninter from 'natninter';\n```\n\nUse it in Node:  \n```js\nconst natninter = require(\"natninter\");\n```\n\n## Basic usage\n```js\n// a list of seeds\nvar seeds = [\n  {x: 100, y: 100,  value: Math.random()*255 },\n  {x: 300, y: 100,  value: Math.random()*255  },\n  {x: 300, y: 300, value: Math.random()*255 },\n  {x: 100, y: 300, value: Math.random()*255  },\n  {x: 200 , y: 200 , value: Math.random()*255 }\n]\n\n// creating the nni interpolator instance\nvar nnInter = new natninter.Interpolator();\n\n// setting the output size\nnnInter.setOutputSize(256, 256);\n\n// add a list of seeds\nnnInter.addSeeds( seeds );\n\n// Create the interpolation map\n// (this may take some seconds, start with a small image to benchmark it)\nnnInter.generateMap();\n\n// generate the output image witha  nice interpolation\nvar output = nnInter.generateImage();\n```\n\nThe `output` is actually an object of the form:\n```js\n{\n  _data: Float32Array,\n  _metadata: {\n    width: Number,\n    heigth: Number\n  }\n}\n```\nWhere `_data` is a 1D array of length `height`x`width` arrange in a row major way.\n\n## Examples\n[A regular example](http://me.jonathanlurie.fr/natninter/examples/browser.html) and [A wavy example](http://me.jonathanlurie.fr/natninter/examples/browserwaves.html)  \nSee the folder `examples` for a Node and a browser example.\n\n## Generate a map and save it locally\n`natninter` comes with a *node* executable to generate a samplig-map file in JSON format. In a terminal, find the executable `generatemap.js`, located in the `bin` folder. Then:\n\n```bash\n./generatemap.js --seeds=your/own/seedsfile.json -width=400 --height=400 --output=somehwere/map.json\n```\nYou can use the seed file in `bin/samples/seeds1.json` and use it as a a model to write your own seed file.\n\n\n# Special thanks\nSince I didn't want to reinvent the wheel and that I trust some good developers out there, here are the dependencies *natninter* uses:\n- [Compute Voronoi diagram](https://github.com/gorhill/Javascript-Voronoi) - damn fast!\n- [Polygon area computation](https://github.com/math-utils/area-polygon) - super simple a pretty fast too!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanlurie%2Fnatninter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonathanlurie%2Fnatninter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanlurie%2Fnatninter/lists"}