orx-hash-grid

orx-hash-grid

2D space partitioning for fast point queries.

Usage

orx-hash-grid provides the classes HashGrid and Cell, in most cases only HashGrid is used.

Create a hash grid for a given radius.

val grid = HashGrid(radius)

Check for a given query point if the grid is free, i.e. there is no point in the grid at distance less than radius away from the query point.

grid.isFree(query)

Add a point to the hash grid structure:

grid.insert(point)

Iterate over all points in the hash grid:

for (point in grid.points()) {
    // do something with point
}

Extensions to standard library

orx-hash-grid provides short-hand extension functions to List<Vector2>

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fun List<Vector2>.filter(radius: Double) : List<Vector2>

filters the points in the list such that only points with an inter-distance of radius remain.

val points = (0 until 10_000).map { drawer.bounds.uniform() }
val filtered = points.filter(20.0)

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fun List<Vector2>.hashGrid(radius: Double) : HashGrid

constructs a (mutable) HashGrid containing all points in the list.

val points = (0 until 10_000).map { drawer.bounds.uniform() }
val hashGrid = points.hashGrid(20.0)

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References

• orx-noise uses HashGrid to generate Poisson distributed points. Link

Demos

DemoFilter01

source code

DemoFilter3D01

source code

DemoHashGrid01

source code