kaze/orx
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

[orx-noise] Improve uni-/bipolar functions, add clamp functions

Browse Source
This commit is contained in:
Edwin Jakobs
2022-08-23 18:46:41 +02:00
parent 01bcdfb47c
commit 6a4e3c3a44
1 changed files with 151 additions and 40 deletions
Download Patch File Download Diff File Expand all files Collapse all files

191
orx-noise/src/commonMain/kotlin/Functions.kt
View File

@@ -2,6 +2,7 @@ package org.openrndr.extra.noise
import org.openrndr.math.*
import kotlin.jvm.JvmName
import kotlin.math.PI
import kotlin.random.Random
@@ -23,70 +24,189 @@ fun ((Int, Double, Double) -> Vector2).gradient(epsilon: Double = 1e-6): (Int, D
dfdx + dfdy
}
fun ((Int, Double) -> Double).unipolar(sampleCount: Int = 1000, random: Random = Random(0)): (Int, Double) -> Double {
val samples = (0 until sampleCount).map {
this(0, random.nextDouble(-1.0, 1.0))
fun ((Int, Double) -> Double).minMax(sampleCount: Int = 1000, random: Random = Random(0)): Pair<Double, Double> {
val nmin: Double
val nmax: Double
when {
this === simplex1D -> {
nmin = -0.7127777710564248
nmax = 0.7127779539425915
}
this === valueLinear1D || this === valueHermite1D || this == valueQuintic1D -> {
nmin = -1.0
nmax = 1.0
}
this === perlin1D -> {
nmin = -0.5
nmax = 0.5
}
else -> {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
}
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val min: Double
val max: Double
if (nmin == Double.POSITIVE_INFINITY) {
val samples = (0 until sampleCount).map {
this(random.nextInt(0, 16384), random.nextDouble(PI * 2.0, PI * 8.0))
}
min = samples.minOrNull()!!
max = samples.maxOrNull()!!
} else {
min = nmin
max = nmax
}
return Pair(min, max)
}
fun ((Int, Double) -> Double).unipolar(sampleCount: Int = 1000, random: Random = Random(0)): (Int, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random)
return { seed, t ->
(this(seed, t) - min) / (max - min)
}
}
fun ((seed: Int, t: Double) -> Double).clamp(min: Double, max: Double): (Int, Double) -> Double = { seed, t ->
this(seed, t).coerceIn(min, max)
}
fun ((Int, Double) -> Double).bipolar(sampleCount: Int = 1000, random: Random = Random(0)): (Int, Double) -> Double {
val samples = (0 until sampleCount).map {
this(0, random.nextDouble(-1.0, 1.0))
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val (min, max) = this.minMax(sampleCount, random)
return { seed, t ->
((this(seed, t) - min) / (max - min)) * 2.0 - 1.0
}
}
fun ((Int, Double, Double) -> Double).minMax(
sampleCount: Int = 1000,
random: Random = Random(0)
): Pair<Double, Double> {
val nmin: Double
val nmax: Double
when {
this === simplex2D -> {
nmin = -0.7127777710564248
nmax = 0.7127779539425915
}
this === valueLinear2D || this === valueHermite2D || this == valueQuintic2D -> {
nmin = -1.0
nmax = 1.0
}
this === perlin2D -> {
nmin = -1.0
nmax = 1.0
}
else -> {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
}
}
val min: Double
val max: Double
if (nmin == Double.POSITIVE_INFINITY) {
val samples = (0 until sampleCount).map {
this(random.nextInt(0, 16384), random.nextDouble(PI * 2.0, PI * 8.0), random.nextDouble(PI * 2.0, PI * 8.0))
}
min = samples.minOrNull()!!
max = samples.maxOrNull()!!
} else {
min = nmin
max = nmax
}
return Pair(min, max)
}
fun ((Int, Double, Double) -> Double).unipolar(
sampleCount: Int = 1000,
random: Random = Random(0)
): (Int, Double, Double) -> Double {
val samples = (0 until sampleCount).map {
this(0, random.nextDouble(-1.0, 1.0), random.nextDouble(-1.0, 1.0))
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val (min, max) = this.minMax(sampleCount, random)
return { seed, x, t ->
(this(seed, x, t) - min) / (max - min)
}
}
fun ((seed: Int, x: Double, t: Double) -> Double).clamp(min: Double, max: Double): (Int, Double, Double) -> Double = { seed, x, t ->
this(seed, x, t).coerceIn(min, max)
}
fun ((Int, Double, Double, Double) -> Double).minMax(
sampleCount: Int = 1000,
random: Random = Random(0)
): Pair<Double, Double> {
val nmin: Double
val nmax: Double
when {
this === simplex3D -> {
nmin = -0.9777
nmax = 0.9777
}
this === valueLinear3D || this === valueHermite3D || this == valueQuintic3D -> {
nmin = -1.0
nmax = 1.0
}
this === perlin3D -> {
nmin = -1.0
nmax = 1.0
}
else -> {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
}
}
val min: Double
val max: Double
if (nmin == Double.POSITIVE_INFINITY) {
val samples = (0 until sampleCount).map {
this(
random.nextInt(0, 16384),
random.nextDouble(PI * 2.0, PI * 8.0),
random.nextDouble(PI * 2.0, PI * 8.0),
random.nextDouble(PI * 2.0, PI * 8.0)
)
}
min = samples.minOrNull()!!
max = samples.maxOrNull()!!
} else {
min = nmin
max = nmax
}
return Pair(min, max)
}
fun ((Int, Double, Double) -> Double).bipolar(
sampleCount: Int = 1000,
random: Random = Random(0)
): (Int, Double, Double) -> Double {
val samples = (0 until sampleCount).map {
this(0, random.nextDouble(-1.0, 1.0), random.nextDouble(-1.0, 1.0))
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val (min, max) = this.minMax(sampleCount, random)
return { seed, x, t ->
((this(seed, x, t) - min) / (max - min)) * 2.0 - 1.0
}
}
fun ((seed: Int, x: Double, y:Double, t: Double) -> Double).clamp(min: Double, max: Double): (Int, Double, Double, Double) -> Double = { seed, x, y, t ->
this(seed, x, y, t).coerceIn(min, max)
}
fun ((Int, Double, Double, Double) -> Double).unipolar(
sampleCount: Int = 1000,
random: Random = Random(0)
): (Int, Double, Double, Double) -> Double {
val samples = (0 until sampleCount).map {
this(
0,
random.nextDouble(-1.0, 1.0),
random.nextDouble(-1.0, 1.0),
random.nextDouble(-1.0, 1.0)
)
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val (min, max) = this.minMax(sampleCount, random)
return { seed, x, y, t ->
(this(seed, x, y, t) - min) / (max - min)
}
@@ -96,16 +216,7 @@ fun ((Int, Double, Double, Double) -> Double).bipolar(
sampleCount: Int = 1000,
random: Random = Random(0)
): (Int, Double, Double, Double) -> Double {
val samples = (0 until sampleCount).map {
this(
0,
random.nextDouble(-1.0, 1.0),
random.nextDouble(-1.0, 1.0),
random.nextDouble(-1.0, 1.0),
)
}
val min = samples.minOrNull()!!
val max = samples.maxOrNull()!!
val (min, max) = this.minMax(sampleCount, random)
return { seed, x, y, t ->
((this(seed, x, y, t) - min) / (max - min)) * 2.0 - 1.0
}