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[orx-noise] Add percentile parameter to uni-/bipolar functions

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This commit is contained in:
Edwin Jakobs
2022-08-23 22:57:54 +02:00
parent 6a4e3c3a44
commit b91dc34916
1 changed files with 112 additions and 73 deletions
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185
orx-noise/src/commonMain/kotlin/Functions.kt
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@@ -24,29 +24,48 @@ fun ((Int, Double, Double) -> Vector2).gradient(epsilon: Double = 1e-6): (Int, D
dfdx + dfdy dfdx + dfdy
} }
fun ((Int, Double) -> Double).minMax(sampleCount: Int = 1000, random: Random = Random(0)): Pair<Double, Double> { private fun List<Double>.minMax(percentile: Double) : Pair<Double, Double> {
return if (percentile == 1.0) {
Pair(this.minOrNull()!!, this.maxOrNull()!!)
} else {
val sorted = this.sorted()
@Suppress("NAME_SHADOWING") val percentile = percentile.coerceIn(0.0..1.0)
val minIndex = ((size-1) * (0.5 - percentile/2.0)).toInt()
val maxIndex = ((size-1) * (0.5 + percentile/2.0)).toInt()
Pair(sorted[minIndex], sorted[maxIndex])
}
}
fun ((Int, Double) -> Double).minMax(
sampleCount: Int = 1000,
percentile: Double,
random: Random = Random(0)
): Pair<Double, Double> {
val nmin: Double val nmin: Double
val nmax: Double val nmax: Double
when { if (percentile != 1.0) {
this === simplex1D -> { when {
nmin = -0.7127777710564248 this === simplex1D -> {
nmax = 0.7127779539425915 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
}
} }
} else {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
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: Double val min: Double
@@ -55,8 +74,9 @@ fun ((Int, Double) -> Double).minMax(sampleCount: Int = 1000, random: Random = R
val samples = (0 until sampleCount).map { val samples = (0 until sampleCount).map {
this(random.nextInt(0, 16384), random.nextDouble(PI * 2.0, PI * 8.0)) this(random.nextInt(0, 16384), random.nextDouble(PI * 2.0, PI * 8.0))
} }
min = samples.minOrNull()!! val minMax = samples.minMax(percentile)
max = samples.maxOrNull()!! min = minMax.first
max = minMax.second
} else { } else {
min = nmin min = nmin
max = nmax max = nmax
@@ -65,8 +85,8 @@ fun ((Int, Double) -> Double).minMax(sampleCount: Int = 1000, random: Random = R
} }
fun ((Int, Double) -> Double).unipolar(sampleCount: Int = 1000, random: Random = Random(0)): (Int, Double) -> Double { fun ((Int, Double) -> Double).unipolar(sampleCount: Int = 1000, percentile: Double = 1.0, random: Random = Random(0)): (Int, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random) val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, t -> return { seed, t ->
(this(seed, t) - min) / (max - min) (this(seed, t) - min) / (max - min)
} }
@@ -75,8 +95,8 @@ fun ((seed: Int, t: Double) -> Double).clamp(min: Double, max: Double): (Int, Do
this(seed, t).coerceIn(min, max) this(seed, t).coerceIn(min, max)
} }
fun ((Int, Double) -> Double).bipolar(sampleCount: Int = 1000, random: Random = Random(0)): (Int, Double) -> Double { fun ((Int, Double) -> Double).bipolar(sampleCount: Int = 1000, percentile: Double = 1.0, random: Random = Random(0)): (Int, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random) val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, t -> return { seed, t ->
((this(seed, t) - min) / (max - min)) * 2.0 - 1.0 ((this(seed, t) - min) / (max - min)) * 2.0 - 1.0
} }
@@ -84,30 +104,36 @@ fun ((Int, Double) -> Double).bipolar(sampleCount: Int = 1000, random: Random =
fun ((Int, Double, Double) -> Double).minMax( fun ((Int, Double, Double) -> Double).minMax(
sampleCount: Int = 1000, sampleCount: Int = 1000,
percentile: Double,
random: Random = Random(0) random: Random = Random(0)
): Pair<Double, Double> { ): Pair<Double, Double> {
val nmin: Double val nmin: Double
val nmax: Double val nmax: Double
when { if (percentile != 0.0) {
this === simplex2D -> { when {
nmin = -0.7127777710564248 this === simplex2D -> {
nmax = 0.7127779539425915 nmin = -0.7127777710564248
} nmax = 0.7127779539425915
}
this === valueLinear2D || this === valueHermite2D || this == valueQuintic2D -> { this === valueLinear2D || this === valueHermite2D || this == valueQuintic2D -> {
nmin = -1.0 nmin = -1.0
nmax = 1.0 nmax = 1.0
} }
this === perlin2D -> { this === perlin2D -> {
nmin = -1.0 nmin = -1.0
nmax = 1.0 nmax = 1.0
} }
else -> { else -> {
nmin = Double.POSITIVE_INFINITY nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY nmax = Double.NEGATIVE_INFINITY
}
} }
} else {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
} }
val min: Double val min: Double
val max: Double val max: Double
@@ -116,8 +142,9 @@ fun ((Int, Double, Double) -> Double).minMax(
val samples = (0 until sampleCount).map { 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)) this(random.nextInt(0, 16384), random.nextDouble(PI * 2.0, PI * 8.0), random.nextDouble(PI * 2.0, PI * 8.0))
} }
min = samples.minOrNull()!! val minMax = samples.minMax(percentile)
max = samples.maxOrNull()!! min = minMax.first
max = minMax.second
} else { } else {
min = nmin min = nmin
max = nmax max = nmax
@@ -127,14 +154,26 @@ fun ((Int, Double, Double) -> Double).minMax(
fun ((Int, Double, Double) -> Double).unipolar( fun ((Int, Double, Double) -> Double).unipolar(
sampleCount: Int = 1000, sampleCount: Int = 1000,
percentile: Double = 1.0,
random: Random = Random(0) random: Random = Random(0)
): (Int, Double, Double) -> Double { ): (Int, Double, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random) val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, x, t -> return { seed, x, t ->
(this(seed, x, t) - min) / (max - min) (this(seed, x, t) - min) / (max - min)
} }
} }
fun ((Int, Double, Double) -> Double).bipolar(
sampleCount: Int = 1000,
percentile: Double = 1.0,
random: Random = Random(0)
): (Int, Double, Double) -> Double {
val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, x, t ->
((this(seed, x, t) - min) / (max - min)) * 2.0 - 1.0
}
}
fun ((seed: Int, x: Double, t: Double) -> Double).clamp(min: Double, max: Double): (Int, Double, Double) -> Double = { seed, x, t -> 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) this(seed, x, t).coerceIn(min, max)
@@ -142,30 +181,36 @@ fun ((seed: Int, x: Double, t: Double) -> Double).clamp(min: Double, max: Double
fun ((Int, Double, Double, Double) -> Double).minMax( fun ((Int, Double, Double, Double) -> Double).minMax(
sampleCount: Int = 1000, sampleCount: Int = 1000,
percentile: Double = 1.0,
random: Random = Random(0) random: Random = Random(0)
): Pair<Double, Double> { ): Pair<Double, Double> {
val nmin: Double val nmin: Double
val nmax: Double val nmax: Double
when { if (percentile == 1.0) {
this === simplex3D -> { when {
nmin = -0.9777 this === simplex3D -> {
nmax = 0.9777 nmin = -0.9777
} nmax = 0.9777
}
this === valueLinear3D || this === valueHermite3D || this == valueQuintic3D -> { this === valueLinear3D || this === valueHermite3D || this == valueQuintic3D -> {
nmin = -1.0 nmin = -1.0
nmax = 1.0 nmax = 1.0
} }
this === perlin3D -> { this === perlin3D -> {
nmin = -1.0 nmin = -1.0
nmax = 1.0 nmax = 1.0
} }
else -> { else -> {
nmin = Double.POSITIVE_INFINITY nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY nmax = Double.NEGATIVE_INFINITY
}
} }
} else {
nmin = Double.POSITIVE_INFINITY
nmax = Double.NEGATIVE_INFINITY
} }
val min: Double val min: Double
val max: Double val max: Double
@@ -179,8 +224,9 @@ fun ((Int, Double, Double, Double) -> Double).minMax(
random.nextDouble(PI * 2.0, PI * 8.0) random.nextDouble(PI * 2.0, PI * 8.0)
) )
} }
min = samples.minOrNull()!! val minMax = samples.minMax(percentile)
max = samples.maxOrNull()!! min = minMax.first
max = minMax.second
} else { } else {
min = nmin min = nmin
max = nmax max = nmax
@@ -188,15 +234,6 @@ fun ((Int, Double, Double, Double) -> Double).minMax(
return Pair(min, max) return Pair(min, max)
} }
fun ((Int, Double, Double) -> Double).bipolar(
sampleCount: Int = 1000,
random: Random = Random(0)
): (Int, Double, Double) -> Double {
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 -> 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) this(seed, x, y, t).coerceIn(min, max)
@@ -204,9 +241,10 @@ fun ((seed: Int, x: Double, y:Double, t: Double) -> Double).clamp(min: Double, m
fun ((Int, Double, Double, Double) -> Double).unipolar( fun ((Int, Double, Double, Double) -> Double).unipolar(
sampleCount: Int = 1000, sampleCount: Int = 1000,
percentile: Double = 1.0,
random: Random = Random(0) random: Random = Random(0)
): (Int, Double, Double, Double) -> Double { ): (Int, Double, Double, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random) val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, x, y, t -> return { seed, x, y, t ->
(this(seed, x, y, t) - min) / (max - min) (this(seed, x, y, t) - min) / (max - min)
} }
@@ -214,9 +252,10 @@ fun ((Int, Double, Double, Double) -> Double).unipolar(
fun ((Int, Double, Double, Double) -> Double).bipolar( fun ((Int, Double, Double, Double) -> Double).bipolar(
sampleCount: Int = 1000, sampleCount: Int = 1000,
percentile: Double = 1.0,
random: Random = Random(0) random: Random = Random(0)
): (Int, Double, Double, Double) -> Double { ): (Int, Double, Double, Double) -> Double {
val (min, max) = this.minMax(sampleCount, random) val (min, max) = this.minMax(sampleCount, percentile, random)
return { seed, x, y, t -> return { seed, x, y, t ->
((this(seed, x, y, t) - min) / (max - min)) * 2.0 - 1.0 ((this(seed, x, y, t) - min) / (max - min)) * 2.0 - 1.0
} }