diff --git a/orx-noise/build.gradle.kts b/orx-noise/build.gradle.kts index 97398c1d..f7a78015 100644 --- a/orx-noise/build.gradle.kts +++ b/orx-noise/build.gradle.kts @@ -37,6 +37,8 @@ kotlin { implementation(project(":orx-hash-grid")) implementation(project(":orx-noise")) implementation(project(":orx-jvm:orx-gui")) + implementation(project(":orx-mesh-generators")) + implementation(project(":orx-camera")) } } } diff --git a/orx-noise/src/commonMain/kotlin/hammersley/Hammersley.kt b/orx-noise/src/commonMain/kotlin/hammersley/Hammersley.kt new file mode 100644 index 00000000..b87a574a --- /dev/null +++ b/orx-noise/src/commonMain/kotlin/hammersley/Hammersley.kt @@ -0,0 +1,75 @@ +package org.openrndr.extra.noise.hammersley + +import org.openrndr.math.Vector2 +import org.openrndr.math.Vector3 +import org.openrndr.math.Vector4 + +/** + * Computes a 2D Hammersley point based on the given index and total number of samples. + * + * @param i The index of the sample, typically in the range [0, n). + * @param n The total number of samples. + * @return A 2D point as a `Vector2` within the unit square [0, 1] x [0, 1]. + */ +fun hammersley2D(i: Int, n: Int): Vector2 { + return Vector2(i.toDouble() / n, radicalInverseBase2(i.toUInt())) +} + +/** + * Computes a 3D point in the Hammersley sequence based on the given index and total number of samples. + * + * @param i The index of the sample, typically in the range [0, n). + * @param n The total number of samples. + * @return A 3D point as a `Vector3` within the unit cube [0, 1] x [0, 1] x [0, 1]. + */ +fun hammersley3D(i: Int, n: Int): Vector3 { + return Vector3(i.toDouble() / n, radicalInverseBase2(i.toUInt()), radicalInverse(3, i)) +} + +/** + * Computes a 4D Hammersley point based on the given index and total number of samples. + * + * @param i The index of the sample, typically in the range [0, n). + * @param n The total number of samples. + * @return A 4D point as a `Vector4` where each component lies within the range [0, 1]. + */ +fun hammersley4D(i: Int, n: Int): Vector4 { + return Vector4(i.toDouble() / n, radicalInverseBase2(i.toUInt()), radicalInverse(3, i), radicalInverse(5, i)) +} + +/** + * Computes the radical inverse of a given unsigned integer `i` in base 2. + * + * @param i The input unsigned integer for which the radical inverse in base 2 is computed. + * @return The radical inverse value of the input as a `Double`, mapped to the range [0, 1). + */ +fun radicalInverseBase2(i: UInt): Double { + var bits = i + bits = ((bits shl 16) or (bits shr 16)) + bits = ((bits and 0x55555555u) shl 1) or ((bits and 0xAAAAAAAAu) shr 1) + bits = ((bits and 0x33333333u) shl 2) or ((bits and 0xCCCCCCCCu) shr 2) + bits = ((bits and 0x0F0F0F0Fu) shl 4) or ((bits and 0xF0F0F0F0u) shr 4) + bits = ((bits and 0x00FF00FFu) shl 8) or ((bits and 0xFF00FF00u) shr 8) + return bits.toDouble() * 2.3283064365386963e-10 +} + +/** + * Computes the radical inverse of an integer `i` in a given base. + * This method is often used in quasi-random sequence generation for sampling. + * + * @param base The base in which to compute the radical inverse. Must be greater than 1. + * @param i The integer for which the radical inverse is calculated. Must be non-negative. + * @return The radical inverse value as a `Double`, within the range [0, 1). + */ +fun radicalInverse(base: Int, i: Int): Double { + var v = 0.0 + var denom = 1.0 + var n = i + while (n > 0) { + denom *= base + val remainder = n.mod(base) + n /= base + v += remainder / denom + } + return v +} diff --git a/orx-noise/src/commonMain/kotlin/rseq/Rseq.kt b/orx-noise/src/commonMain/kotlin/rseq/Rseq.kt new file mode 100644 index 00000000..808c1a12 --- /dev/null +++ b/orx-noise/src/commonMain/kotlin/rseq/Rseq.kt @@ -0,0 +1,67 @@ +package org.openrndr.extra.noise.rsequence + +import org.openrndr.math.Vector2 +import org.openrndr.math.Vector3 +import org.openrndr.math.Vector4 + +private const val g1 = 1.618033988749895 +private const val a11 = 1.0 / g1 + +private const val g2 = 1.324717957244746 +private const val a21 = 1.0 / g2 +private const val a22 = 1.0 / (g2 * g2) + +private const val g3 = 1.2207440846057596 +private const val a31 = 1.0 / g3 +private const val a32 = 1.0 / (g3 * g3) +private const val a33 = 1.0 / (g3 * g3 * g3) + +private const val g4 = 1.1673039782614187 +private const val a41 = 1.0 / g4 +private const val a42 = 1.0 / (g4 * g4) +private const val a43 = 1.0 / (g4 * g4 * g4) +private const val a44 = 1.0 / (g4 * g4 * g4 * g4) + +/** + * Computes the R1 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts. + * + * @param n The index for which the R1 sequence value is to be calculated. + * @return The R1 sequence value as a Double, providing a low-discrepancy quasirandom number. + */ +fun rSeq1D(n: Int): Double = (0.5 + a11 * n).mod(1.0) + +/** + * Computes the R2 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts. + * + * @param n The index for which the R2 sequence value is to be calculated. + * @return The R2 sequence value as a [Vector2], providing a low-discrepancy quasirandom number. + */ +fun rSeq2D(n: Int): Vector2 = Vector2( + (0.5 + a21 * n).mod(1.0), + (0.5 + a22 * n).mod(1.0) +) + +/** + * Computes the R3 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts. + * + * @param n The index for which the R3 sequence value is to be calculated. + * @return The R3 sequence value as a [Vector3], providing a low-discrepancy quasirandom number. + */ +fun rSeq3D(n: Int): Vector3 = Vector3( + (0.5 + a31 * n).mod(1.0), + (0.5 + a32 * n).mod(1.0), + (0.5 + a33 * n).mod(1.0) +) + +/** + * Computes the R4 low-discrepancy quasirandom sequence value for a given index as described by Martin Roberts. + * + * @param n The index for which the R4 sequence value is to be calculated. + * @return The R4 sequence value as a [Vector4], providing a low-discrepancy quasirandom number. + */ +fun rSeq4D(n: Int): Vector4 = Vector4( + (0.5 + a41 * n).mod(1.0), + (0.5 + a42 * n).mod(1.0), + (0.5 + a43 * n).mod(1.0), + (0.5 + a44 * n).mod(1.0) +) diff --git a/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley2D01.kt b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley2D01.kt new file mode 100644 index 00000000..addee41f --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley2D01.kt @@ -0,0 +1,29 @@ +package hammersley + +import org.openrndr.application +import org.openrndr.extra.noise.hammersley.hammersley2D + +/** + * Demo that visualizes a 2D Hammersley point set. + * + * The application is configured to run at 720x720 resolution. The program computes + * 400 2D Hammersley points mapped within the bounds of the application's resolution. + * These points are visualized by rendering circles at their respective positions. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + extend { + val points = (0 until 400).map { + hammersley2D(it, 400) * 720.0 + } + drawer.circles(points, 5.0) + } + } + } +} \ No newline at end of file diff --git a/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley3D01.kt b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley3D01.kt new file mode 100644 index 00000000..33df6acd --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley3D01.kt @@ -0,0 +1,46 @@ +package hammersley + +import org.openrndr.application +import org.openrndr.draw.DrawPrimitive +import org.openrndr.draw.isolated +import org.openrndr.extra.camera.Orbital +import org.openrndr.extra.meshgenerators.sphereMesh +import org.openrndr.extra.noise.hammersley.hammersley3D +import org.openrndr.math.Vector3 + +/** + * Demo program rendering a 3D visualization of points distributed using the Hammersley sequence in 3D space. + * + * The application is set up at a resolution of 720x720 pixels. Within the visual + * program, a sphere mesh is created and a set of 1400 points is generated using + * the Hammersley sequence. Each point is translated and rendered as a small sphere + * in 3D space. This is achieved by mapping the generated points into a scaled domain. + * + * The rendering utilizes the Orbital extension, enabling an interactive 3D camera + * to navigate the scene. The visualization relies on the draw loop for continuous + * rendering of the points. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + val sphere = sphereMesh(radius = 0.1) + extend(Orbital()) + extend { + val points = (0 until 1400).map { + (hammersley3D(it, 1400) - Vector3(0.5)) * 10.0 + } + for (point in points) { + drawer.isolated { + drawer.translate(point) + drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES) + } + } + } + } + } +} \ No newline at end of file diff --git a/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley4D01.kt b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley4D01.kt new file mode 100644 index 00000000..1c4b872a --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/hammersley/DemoHammersley4D01.kt @@ -0,0 +1,52 @@ +package hammersley + +import org.openrndr.application +import org.openrndr.color.ColorRGBa +import org.openrndr.draw.DrawPrimitive +import org.openrndr.draw.isolated +import org.openrndr.extra.camera.Orbital +import org.openrndr.extra.meshgenerators.sphereMesh +import org.openrndr.extra.noise.hammersley.hammersley4D +import org.openrndr.extra.noise.rsequence.rSeq4D +import org.openrndr.math.Vector4 +import kotlin.math.abs +import kotlin.math.min + +/** + * Demo that visualizes a 4D Hammersley point set in a 3D space, with colors determined by the 4th dimension. + * + * The application is configured at a resolution of 720x720 pixels. A sphere mesh is created + * using the `sphereMesh` utility, and a total of 10,000 4D points are generated with the + * `hammersley4D` sequence. These points are scaled, translated, and rendered as small spheres. + * The color of each sphere is modified based on the 4th dimension of its corresponding point by + * shifting the hue in HSV color space. + * + * This program employs the `Orbital` extension, enabling camera interaction for 3D navigation + * of the scene. Rendering occurs within the draw loop, providing continuous visualization + * of the point distribution. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + val sphere = sphereMesh(radius = 0.1) + extend(Orbital()) + extend { + val points = (0 until 10000).map { + (hammersley4D(it, 10000) - Vector4(0.5, 0.5, 0.5, 0.0)) * Vector4(10.0, 10.0, 10.0, 1.0) + } + for (point in points) { + drawer.isolated { + drawer.translate(point.xyz) + drawer.fill = ColorRGBa.RED.toHSVa().shiftHue(point.w * 360.0).toRGBa() + drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES) + } + } + } + } + } +} \ No newline at end of file diff --git a/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq2D01.kt b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq2D01.kt new file mode 100644 index 00000000..a0272016 --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq2D01.kt @@ -0,0 +1,27 @@ +package rseq + +import org.openrndr.application +import org.openrndr.extra.noise.rsequence.rSeq2D + +/** + * This demo sets up a window with dimensions 720x720 and renders frames + * demonstrating 2D quasirandomly distributed points. The points are generated + * using the R2 sequence and drawn as circles with a radius of 5.0. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + extend { + val points = (0 until 4000).map { + rSeq2D(it) * 720.0 + } + drawer.circles(points, 5.0) + } + } + } +} \ No newline at end of file diff --git a/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq3D01.kt b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq3D01.kt new file mode 100644 index 00000000..94b50757 --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq3D01.kt @@ -0,0 +1,45 @@ +package rseq + +import org.openrndr.application +import org.openrndr.draw.DrawPrimitive +import org.openrndr.draw.isolated +import org.openrndr.extra.camera.Orbital +import org.openrndr.extra.meshgenerators.sphereMesh +import org.openrndr.extra.noise.rsequence.rSeq3D +import org.openrndr.math.Vector3 + +/** + * This demo renders a 3D visualizationof points distributed using the R3 quasirandom sequence. Each point is + * represented as a sphere and positioned in 3D space based on the quasirandom sequence values. + * + * The visualization setup includes: + * - Configuration of application window size to 720x720. + * - Usage of an orbital camera for interactive 3D navigation. + * - Creation of a reusable sphere mesh with a specified radius. + * - Generation of quasirandom points in 3D space using the `rSeq3D` function. + * - Transformation and rendering of each point as a sphere using vertex buffers. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + val sphere = sphereMesh(radius = 0.1) + extend(Orbital()) + extend { + val points = (0 until 1400).map { + (rSeq3D(it) - Vector3(0.5)) * 10.0 + } + for (point in points) { + drawer.isolated { + drawer.translate(point) + drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES) + } + } + } + } + } +} \ No newline at end of file diff --git a/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq4D01.kt b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq4D01.kt new file mode 100644 index 00000000..589a4285 --- /dev/null +++ b/orx-noise/src/jvmDemo/kotlin/rseq/DemoRseq4D01.kt @@ -0,0 +1,54 @@ +package rseq + +import org.openrndr.application +import org.openrndr.color.ColorRGBa +import org.openrndr.draw.DrawPrimitive +import org.openrndr.draw.isolated +import org.openrndr.extra.camera.Orbital +import org.openrndr.extra.meshgenerators.sphereMesh +import org.openrndr.extra.noise.rsequence.rSeq3D +import org.openrndr.extra.noise.rsequence.rSeq4D +import org.openrndr.math.Vector3 +import org.openrndr.math.Vector4 +import kotlin.math.abs +import kotlin.math.min + +/** + * Demo that presents a 3D visualization of points distributed using a 4D quasirandom sequence (R4). + * Each point is represented as a sphere with it position and color derived from the sequence values. + * + * This function performs the following tasks: + * - Configures the application window dimensions to 720x720 pixels. + * - Initializes a 3D camera for orbital navigation of the scene. + * - Generates 10,000 points in 4D space using the `rSeq4D` function. The points are scaled + * and transformed into 3D positions with an additional w-coordinate for color variation. + * - Creates a reusable sphere mesh for rendering. + * - Renders each point as a sphere with its position determined by the 3D coordinates + * of the point and its color calculated by shifting the hue of a base color using + * the w-coordinate value. + */ +fun main() { + application { + configure { + width = 720 + height = 720 + } + + program { + val sphere = sphereMesh(radius = 0.1) + val points = (0 until 10000).map { + (rSeq4D(it) - Vector4(0.5, 0.5, 0.5, 0.0)) * Vector4(10.0, 10.0, 10.0, 1.0) + } + extend(Orbital()) + extend { + for (point in points) { + drawer.isolated { + drawer.translate(point.xyz) + drawer.fill = ColorRGBa.RED.toHSVa().shiftHue(point.w * 360.0).toRGBa() + drawer.vertexBuffer(sphere, DrawPrimitive.TRIANGLES) + } + } + } + } + } +} \ No newline at end of file