KStarbound/src/main/kotlin/ru/dbotthepony/kstarbound/util/random/RidgedNoise.kt

85 lines
2.0 KiB
Kotlin

package ru.dbotthepony.kstarbound.util.random
import ru.dbotthepony.kstarbound.defs.PerlinNoiseParameters
import kotlin.math.absoluteValue
class RidgedNoise(parameters: PerlinNoiseParameters) : AbstractPerlinNoise(parameters) {
init {
require(parameters.type == PerlinNoiseParameters.Type.RIDGED_MULTI)
}
override fun get(x: Double): Double {
checkInit()
var sum = 0.0
var p = x * parameters.frequency
var scale = 1.0
var weight = 1.0
for (i in 0 until parameters.octaves) {
var value = noise1(p)
value = parameters.offset - value.absoluteValue
value *= value
value *= weight
weight = (value * parameters.gain).coerceIn(0.0, 1.0)
sum += value / scale
scale *= parameters.alpha
p *= parameters.beta
}
return ((sum * 1.25) - 1.0) * parameters.amplitude + parameters.bias
}
override fun get(x: Double, y: Double): Double {
checkInit()
var sum = 0.0
var px = x * parameters.frequency
var py = y * parameters.frequency
var scale = 1.0
var weight = 1.0
for (i in 0 until parameters.octaves) {
var value = noise2(px, py)
value = parameters.offset - value.absoluteValue
value *= value
value *= weight
weight = (value * parameters.gain).coerceIn(0.0, 1.0)
sum += value / scale
scale *= parameters.alpha
px *= parameters.beta
py *= parameters.beta
}
return ((sum * 1.25) - 1.0) * parameters.amplitude + parameters.bias
}
override fun get(x: Double, y: Double, z: Double): Double {
checkInit()
var sum = 0.0
var px = x * parameters.frequency
var py = y * parameters.frequency
var pz = z * parameters.frequency
var scale = 1.0
var weight = 1.0
for (i in 0 until parameters.octaves) {
var value = noise3(px, py, pz)
value = parameters.offset - value.absoluteValue
value *= value
value *= weight
weight = (value * parameters.gain).coerceIn(0.0, 1.0)
sum += value / scale
scale *= parameters.alpha
px *= parameters.beta
py *= parameters.beta
pz *= parameters.beta
}
return ((sum * 1.25) - 1.0) * parameters.amplitude + parameters.bias
}
}