[orx-noise] Add Rseq and Hammersley sequences
This commit is contained in:
@@ -37,6 +37,8 @@ kotlin {
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implementation(project(":orx-hash-grid"))
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implementation(project(":orx-noise"))
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implementation(project(":orx-jvm:orx-gui"))
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implementation(project(":orx-mesh-generators"))
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implementation(project(":orx-camera"))
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}
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}
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}
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75
orx-noise/src/commonMain/kotlin/hammersley/Hammersley.kt
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75
orx-noise/src/commonMain/kotlin/hammersley/Hammersley.kt
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@@ -0,0 +1,75 @@
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package org.openrndr.extra.noise.hammersley
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import org.openrndr.math.Vector2
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import org.openrndr.math.Vector3
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import org.openrndr.math.Vector4
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/**
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* Computes a 2D Hammersley point based on the given index and total number of samples.
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*
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* @param i The index of the sample, typically in the range [0, n).
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* @param n The total number of samples.
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* @return A 2D point as a `Vector2` within the unit square [0, 1] x [0, 1].
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*/
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fun hammersley2D(i: Int, n: Int): Vector2 {
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return Vector2(i.toDouble() / n, radicalInverseBase2(i.toUInt()))
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}
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/**
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* Computes a 3D point in the Hammersley sequence based on the given index and total number of samples.
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*
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* @param i The index of the sample, typically in the range [0, n).
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* @param n The total number of samples.
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* @return A 3D point as a `Vector3` within the unit cube [0, 1] x [0, 1] x [0, 1].
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*/
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fun hammersley3D(i: Int, n: Int): Vector3 {
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return Vector3(i.toDouble() / n, radicalInverseBase2(i.toUInt()), radicalInverse(3, i))
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}
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/**
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* Computes a 4D Hammersley point based on the given index and total number of samples.
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*
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* @param i The index of the sample, typically in the range [0, n).
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* @param n The total number of samples.
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* @return A 4D point as a `Vector4` where each component lies within the range [0, 1].
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*/
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fun hammersley4D(i: Int, n: Int): Vector4 {
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return Vector4(i.toDouble() / n, radicalInverseBase2(i.toUInt()), radicalInverse(3, i), radicalInverse(5, i))
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}
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/**
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* Computes the radical inverse of a given unsigned integer `i` in base 2.
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*
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* @param i The input unsigned integer for which the radical inverse in base 2 is computed.
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* @return The radical inverse value of the input as a `Double`, mapped to the range [0, 1).
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*/
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fun radicalInverseBase2(i: UInt): Double {
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var bits = i
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bits = ((bits shl 16) or (bits shr 16))
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bits = ((bits and 0x55555555u) shl 1) or ((bits and 0xAAAAAAAAu) shr 1)
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bits = ((bits and 0x33333333u) shl 2) or ((bits and 0xCCCCCCCCu) shr 2)
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bits = ((bits and 0x0F0F0F0Fu) shl 4) or ((bits and 0xF0F0F0F0u) shr 4)
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bits = ((bits and 0x00FF00FFu) shl 8) or ((bits and 0xFF00FF00u) shr 8)
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return bits.toDouble() * 2.3283064365386963e-10
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}
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/**
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* Computes the radical inverse of an integer `i` in a given base.
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* This method is often used in quasi-random sequence generation for sampling.
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*
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* @param base The base in which to compute the radical inverse. Must be greater than 1.
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* @param i The integer for which the radical inverse is calculated. Must be non-negative.
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* @return The radical inverse value as a `Double`, within the range [0, 1).
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*/
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fun radicalInverse(base: Int, i: Int): Double {
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var v = 0.0
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var denom = 1.0
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var n = i
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while (n > 0) {
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denom *= base
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val remainder = n.mod(base)
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n /= base
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v += remainder / denom
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}
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return v
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}
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67
orx-noise/src/commonMain/kotlin/rseq/Rseq.kt
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67
orx-noise/src/commonMain/kotlin/rseq/Rseq.kt
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@@ -0,0 +1,67 @@
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package org.openrndr.extra.noise.rsequence
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import org.openrndr.math.Vector2
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import org.openrndr.math.Vector3
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import org.openrndr.math.Vector4
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private const val g1 = 1.618033988749895
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private const val a11 = 1.0 / g1
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private const val g2 = 1.324717957244746
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private const val a21 = 1.0 / g2
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private const val a22 = 1.0 / (g2 * g2)
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private const val g3 = 1.2207440846057596
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private const val a31 = 1.0 / g3
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private const val a32 = 1.0 / (g3 * g3)
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private const val a33 = 1.0 / (g3 * g3 * g3)
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private const val g4 = 1.1673039782614187
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private const val a41 = 1.0 / g4
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private const val a42 = 1.0 / (g4 * g4)
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private const val a43 = 1.0 / (g4 * g4 * g4)
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private const val a44 = 1.0 / (g4 * g4 * g4 * g4)
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/**
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* Computes the R1 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts.
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*
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* @param n The index for which the R1 sequence value is to be calculated.
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* @return The R1 sequence value as a Double, providing a low-discrepancy quasirandom number.
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*/
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fun rSeq1D(n: Int): Double = (0.5 + a11 * n).mod(1.0)
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/**
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* Computes the R2 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts.
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*
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* @param n The index for which the R2 sequence value is to be calculated.
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* @return The R2 sequence value as a [Vector2], providing a low-discrepancy quasirandom number.
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*/
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fun rSeq2D(n: Int): Vector2 = Vector2(
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(0.5 + a21 * n).mod(1.0),
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(0.5 + a22 * n).mod(1.0)
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)
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/**
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* Computes the R3 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts.
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*
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* @param n The index for which the R3 sequence value is to be calculated.
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* @return The R3 sequence value as a [Vector3], providing a low-discrepancy quasirandom number.
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*/
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fun rSeq3D(n: Int): Vector3 = Vector3(
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(0.5 + a31 * n).mod(1.0),
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(0.5 + a32 * n).mod(1.0),
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(0.5 + a33 * n).mod(1.0)
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)
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/**
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* Computes the R4 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts.
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*
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* @param n The index for which the R4 sequence value is to be calculated.
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* @return The R4 sequence value as a [Vector4], providing a low-discrepancy quasirandom number.
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*/
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fun rSeq4D(n: Int): Vector4 = Vector4(
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(0.5 + a41 * n).mod(1.0),
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(0.5 + a42 * n).mod(1.0),
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(0.5 + a43 * n).mod(1.0),
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(0.5 + a44 * n).mod(1.0)
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)
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@@ -0,0 +1,29 @@
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package hammersley
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import org.openrndr.application
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import org.openrndr.extra.noise.hammersley.hammersley2D
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/**
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* Demo that visualizes a 2D Hammersley point set.
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*
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* The application is configured to run at 720x720 resolution. The program computes
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* 400 2D Hammersley points mapped within the bounds of the application's resolution.
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* These points are visualized by rendering circles at their respective positions.
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*/
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fun main() {
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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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extend {
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val points = (0 until 400).map {
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hammersley2D(it, 400) * 720.0
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}
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drawer.circles(points, 5.0)
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}
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}
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}
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}
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@@ -0,0 +1,46 @@
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package hammersley
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import org.openrndr.application
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import org.openrndr.draw.DrawPrimitive
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import org.openrndr.draw.isolated
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import org.openrndr.extra.camera.Orbital
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import org.openrndr.extra.meshgenerators.sphereMesh
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import org.openrndr.extra.noise.hammersley.hammersley3D
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import org.openrndr.math.Vector3
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/**
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* Demo program rendering a 3D visualization of points distributed using the Hammersley sequence in 3D space.
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*
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* The application is set up at a resolution of 720x720 pixels. Within the visual
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* program, a sphere mesh is created and a set of 1400 points is generated using
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* the Hammersley sequence. Each point is translated and rendered as a small sphere
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* in 3D space. This is achieved by mapping the generated points into a scaled domain.
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*
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* The rendering utilizes the Orbital extension, enabling an interactive 3D camera
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* to navigate the scene. The visualization relies on the draw loop for continuous
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* rendering of the points.
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*/
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fun main() {
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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 sphere = sphereMesh(radius = 0.1)
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extend(Orbital())
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extend {
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val points = (0 until 1400).map {
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(hammersley3D(it, 1400) - Vector3(0.5)) * 10.0
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}
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for (point in points) {
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drawer.isolated {
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drawer.translate(point)
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drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES)
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}
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}
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}
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}
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}
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}
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@@ -0,0 +1,52 @@
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package hammersley
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.DrawPrimitive
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import org.openrndr.draw.isolated
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import org.openrndr.extra.camera.Orbital
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import org.openrndr.extra.meshgenerators.sphereMesh
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import org.openrndr.extra.noise.hammersley.hammersley4D
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import org.openrndr.extra.noise.rsequence.rSeq4D
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import org.openrndr.math.Vector4
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import kotlin.math.abs
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import kotlin.math.min
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/**
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* Demo that visualizes a 4D Hammersley point set in a 3D space, with colors determined by the 4th dimension.
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*
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* The application is configured at a resolution of 720x720 pixels. A sphere mesh is created
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* using the `sphereMesh` utility, and a total of 10,000 4D points are generated with the
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* `hammersley4D` sequence. These points are scaled, translated, and rendered as small spheres.
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* The color of each sphere is modified based on the 4th dimension of its corresponding point by
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* shifting the hue in HSV color space.
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*
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* This program employs the `Orbital` extension, enabling camera interaction for 3D navigation
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* of the scene. Rendering occurs within the draw loop, providing continuous visualization
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* of the point distribution.
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*/
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fun main() {
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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 sphere = sphereMesh(radius = 0.1)
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extend(Orbital())
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extend {
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val points = (0 until 10000).map {
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(hammersley4D(it, 10000) - Vector4(0.5, 0.5, 0.5, 0.0)) * Vector4(10.0, 10.0, 10.0, 1.0)
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}
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for (point in points) {
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drawer.isolated {
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drawer.translate(point.xyz)
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drawer.fill = ColorRGBa.RED.toHSVa().shiftHue(point.w * 360.0).toRGBa()
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drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES)
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}
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}
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}
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}
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}
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}
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27
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq2D01.kt
Normal file
27
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq2D01.kt
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@@ -0,0 +1,27 @@
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package rseq
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import org.openrndr.application
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import org.openrndr.extra.noise.rsequence.rSeq2D
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/**
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* This demo sets up a window with dimensions 720x720 and renders frames
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* demonstrating 2D quasirandomly distributed points. The points are generated
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* using the R2 sequence and drawn as circles with a radius of 5.0.
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*/
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fun main() {
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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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extend {
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val points = (0 until 4000).map {
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rSeq2D(it) * 720.0
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}
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drawer.circles(points, 5.0)
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}
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}
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}
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}
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45
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq3D01.kt
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45
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq3D01.kt
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@@ -0,0 +1,45 @@
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package rseq
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import org.openrndr.application
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import org.openrndr.draw.DrawPrimitive
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import org.openrndr.draw.isolated
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import org.openrndr.extra.camera.Orbital
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import org.openrndr.extra.meshgenerators.sphereMesh
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import org.openrndr.extra.noise.rsequence.rSeq3D
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import org.openrndr.math.Vector3
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/**
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* This demo renders a 3D visualizationof points distributed using the R3 quasirandom sequence. Each point is
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* represented as a sphere and positioned in 3D space based on the quasirandom sequence values.
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*
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* The visualization setup includes:
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* - Configuration of application window size to 720x720.
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* - Usage of an orbital camera for interactive 3D navigation.
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* - Creation of a reusable sphere mesh with a specified radius.
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* - Generation of quasirandom points in 3D space using the `rSeq3D` function.
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* - Transformation and rendering of each point as a sphere using vertex buffers.
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*/
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fun main() {
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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 sphere = sphereMesh(radius = 0.1)
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extend(Orbital())
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extend {
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val points = (0 until 1400).map {
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(rSeq3D(it) - Vector3(0.5)) * 10.0
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}
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for (point in points) {
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drawer.isolated {
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drawer.translate(point)
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drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES)
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}
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}
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}
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}
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}
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}
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54
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq4D01.kt
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54
orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq4D01.kt
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@@ -0,0 +1,54 @@
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package rseq
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.DrawPrimitive
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import org.openrndr.draw.isolated
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import org.openrndr.extra.camera.Orbital
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import org.openrndr.extra.meshgenerators.sphereMesh
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import org.openrndr.extra.noise.rsequence.rSeq3D
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import org.openrndr.extra.noise.rsequence.rSeq4D
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import org.openrndr.math.Vector3
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import org.openrndr.math.Vector4
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import kotlin.math.abs
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import kotlin.math.min
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/**
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* Demo that presents a 3D visualization of points distributed using a 4D quasirandom sequence (R4).
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* Each point is represented as a sphere with it position and color derived from the sequence values.
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*
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* This function performs the following tasks:
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* - Configures the application window dimensions to 720x720 pixels.
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* - Initializes a 3D camera for orbital navigation of the scene.
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* - Generates 10,000 points in 4D space using the `rSeq4D` function. The points are scaled
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* and transformed into 3D positions with an additional w-coordinate for color variation.
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* - Creates a reusable sphere mesh for rendering.
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* - Renders each point as a sphere with its position determined by the 3D coordinates
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* of the point and its color calculated by shifting the hue of a base color using
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* the w-coordinate value.
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*/
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fun main() {
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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 sphere = sphereMesh(radius = 0.1)
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val points = (0 until 10000).map {
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(rSeq4D(it) - Vector4(0.5, 0.5, 0.5, 0.0)) * Vector4(10.0, 10.0, 10.0, 1.0)
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}
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extend(Orbital())
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extend {
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for (point in points) {
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drawer.isolated {
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drawer.translate(point.xyz)
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drawer.fill = ColorRGBa.RED.toHSVa().shiftHue(point.w * 360.0).toRGBa()
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drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES)
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}
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}
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}
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}
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}
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}
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Reference in New Issue
Block a user