43 lines
1.6 KiB
Kotlin
43 lines
1.6 KiB
Kotlin
import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.extra.kdtree.kdTree
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import org.openrndr.math.Vector2
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import org.openrndr.shape.LineSegment
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/**
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* This demo initializes an interactive graphical application where 1000 randomly distributed points
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* are displayed on a 2D canvas. A KD-tree structure is used for spatial querying of the points, enabling
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* efficient nearest-neighbor searches based on the user's cursor position. The closest 7 points to the
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* cursor are highlighted with circles and lines connecting them to the cursor.
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*
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* Key features:
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* - Generates 1000 random 2D points within the canvas.
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* - Builds a KD-tree from the list of points for optimized spatial querying.
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* - Visualizes the points and highlights the 7 nearest neighbors to the user's cursor position dynamically.
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* - Highlights include red-colored circles around the nearest points and red lines connecting them to the cursor.
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*/
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fun main() = application {
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configure {
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width = 720
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height = 720
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}
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program {
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val points = MutableList(1000) {
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Vector2(Math.random() * width, Math.random() * height)
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}
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val tree = points.kdTree()
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extend {
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drawer.circles(points, 5.0)
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val kNearest = tree.findKNearest(mouse.position, k = 7)
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drawer.fill = ColorRGBa.RED
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drawer.stroke = ColorRGBa.RED
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drawer.strokeWeight = 2.0
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drawer.circles(kNearest, 7.0)
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drawer.lineSegments(kNearest.map { LineSegment(mouse.position, it) })
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}
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}
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}
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