point-cluster  

Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.

``js
const cluster = require('point-cluster')

let ids = cluster(points)

// get point ids in the indicated range
let selectedIds = ids.range([10, 10, 20, 20])

// get levels of details: list of ids subranges for rendering purposes
let lod = ids.range([10, 10, 20, 20], { lod: true })
`

API

$3

Create index for the set of 2d points based on options.

* points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
* ids is _Uint32Array_ with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
* options

Option | Default | Description
---|---|---
bounds | 'auto' | Data range, if different from points bounds, eg. in case of subdata.
depth | 256 | Max number of levels. Points below the indicated level are grouped into single level.
output | 'array' | Output data array or data format. For available formats see dtype.




---

$3

Get point ids from the indicated range.

* box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
* options

Option | Default | Description
---|---|---
lod | false | Makes result a list of level details instead of ids, useful for obtaining subranges to render.
px | 0 | Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
level | null | Max level to limit search.

`js
let levels = ids.range([0,0, 100, 100], { lod: true, d: dataRange / canvas.width })

levels.forEach([from, to] => {
// offset and count point to range in ids array
render( ids.subarray( from, to ) )
})
``

$3

* snap-points-2d − grouping points by pixels.
* kdgrass − minimal kd-tree implementation.
* regl-scatter2d − highly performant scatter2d plot.

License

© 2017 Dmitry Yv. MIT License

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