commonMain.HashGrid.kt Maven / Gradle / Ivy
The newest version!
package org.openrndr.extra.hashgrid
import org.openrndr.math.Vector2
import org.openrndr.shape.Rectangle
import kotlin.jvm.JvmRecord
import kotlin.math.abs
import kotlin.math.max
import kotlin.math.min
import kotlin.math.sqrt
import kotlin.random.Random
private fun Double.fastFloor(): Int {
return if (this >= 0) this.toInt() else this.toInt() - 1
}
@JvmRecord
private data class GridCoords(val x: Int, val y: Int) {
fun offset(i: Int, j: Int): GridCoords = copy(x = x + i, y = y + j)
}
class Cell(val x: Int, val y: Int, val cellSize: Double) {
var xMin: Double = Double.POSITIVE_INFINITY
private set
var xMax: Double = Double.NEGATIVE_INFINITY
private set
var yMin: Double = Double.POSITIVE_INFINITY
private set
var yMax: Double = Double.NEGATIVE_INFINITY
private set
val bounds: Rectangle
get() {
return Rectangle(x * cellSize, y * cellSize, cellSize, cellSize)
}
val contentBounds: Rectangle
get() {
if (points.isEmpty()) {
return Rectangle.EMPTY
} else {
return Rectangle(xMin, yMin, xMax - xMin, yMax - yMin)
}
}
internal val points = mutableListOf>()
internal fun insert(point: Vector2, owner: Any?) {
points.add(Pair(point, owner))
xMin = min(xMin, point.x)
xMax = max(xMax, point.x)
yMin = min(yMin, point.y)
yMax = max(yMax, point.y)
}
internal fun squaredDistanceTo(query: Vector2): Double {
val width = xMax - xMin
val height = yMax - yMin
val x = (xMin + xMax) / 2.0
val y = (yMin + yMax) / 2.0
val dx = max(abs(query.x - x) - width / 2, 0.0)
val dy = max(abs(query.y - y) - height / 2, 0.0)
return dx * dx + dy * dy
}
fun points() = sequence {
for (point in points) {
yield(point)
}
}
}
class HashGrid(val radius: Double) {
private val cells = mutableMapOf()
fun cells() = sequence {
for (cell in cells.values) {
yield(cell)
}
}
var size: Int = 0
private set
val cellSize = radius / sqrt(2.0)
private fun coords(v: Vector2): GridCoords {
val x = (v.x / cellSize).fastFloor()
val y = (v.y / cellSize).fastFloor()
return GridCoords(x, y)
}
fun points() = sequence {
for (cell in cells.values) {
for (point in cell.points) {
yield(point)
}
}
}
fun random(random: Random = Random.Default): Vector2 {
return cells.values.random(random).points.random().first
}
fun insert(point: Vector2, owner: Any? = null) {
val gc = coords(point)
val cell = cells.getOrPut(gc) { Cell(gc.x, gc.y, cellSize) }
cell.insert(point, owner)
size += 1
}
fun cell(query: Vector2): Cell? = cells[coords(query)]
fun isFree(query: Vector2, ignoreOwners: Set = emptySet()): Boolean {
val c = coords(query)
if (cells[c] == null) {
for (j in -2..2) {
for (i in -2..2) {
if (i == 0 && j == 0) {
continue
}
val n = c.offset(i, j)
val nc = cells[n]
if (nc != null && nc.squaredDistanceTo(query) <= radius * radius) {
for (p in nc.points) {
if (p.second == null || p.second !in ignoreOwners) {
if (p.first.squaredDistanceTo(query) <= radius * radius) {
return false
}
}
}
}
}
}
return true
} else {
return cells[c]!!.points.all { it.second != null && it.second in ignoreOwners }
}
}
}
/**
* Construct a hash grid containing all points in the list
* @param radius radius of the hash grid
*/
fun List.hashGrid(radius: Double): HashGrid {
val grid = HashGrid(radius)
for (point in this) {
grid.insert(point)
}
return grid
}
/**
* Return a list that only contains points at a minimum distance.
* @param radius the minimum distance between any two points in the returned list
*/
fun List.filter(radius: Double): List {
return if (size <= 1) {
this
} else {
val grid = HashGrid(radius)
for (point in this) {
if (grid.isFree(point)) {
grid.insert(point)
}
}
grid.points().map { it.first }.toList()
}
}