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/*
* Copyright (C) 2013 Jason Taylor.
* Released as open-source under the Apache License, Version 2.0.
*
* ============================================================================
* | Joise
* ============================================================================
*
* Copyright (C) 2013 Jason Taylor
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* ============================================================================
* | Accidental Noise Library
* | --------------------------------------------------------------------------
* | Joise is a derivative work based on Josua Tippetts' C++ library:
* | http://accidentalnoise.sourceforge.net/index.html
* ============================================================================
*
* Copyright (C) 2011 Joshua Tippetts
*
* This software is provided 'as-is', without any express or implied
* warranty. In no event will the authors be held liable for any damages
* arising from the use of this software.
*
* Permission is granted to anyone to use this software for any purpose,
* including commercial applications, and to alter it and redistribute it
* freely, subject to the following restrictions:
*
* 1. The origin of this software must not be misrepresented; you must not
* claim that you wrote the original software. If you use this software
* in a product, an acknowledgment in the product documentation would be
* appreciated but is not required.
* 2. Altered source versions must be plainly marked as such, and must not be
* misrepresented as being the original software.
* 3. This notice may not be removed or altered from any source distribution.
*/
package com.sudoplay.joise.module
import com.sudoplay.joise.noise.Util.lerp
import com.sudoplay.joise.noise.Util.quinticBlend
class ModuleSelect : Module() {
var low: ScalarParameter = ScalarParameter(0.0)
var high: ScalarParameter = ScalarParameter(0.0)
var control: ScalarParameter = ScalarParameter(0.0)
var threshold: ScalarParameter = ScalarParameter(0.0)
var falloff: ScalarParameter = ScalarParameter(0.0)
fun setLowSource(source: Double) {
low.value = source
}
fun setHighSource(source: Double) {
high.value = source
}
fun setControlSource(source: Double) {
control.value = source
}
fun setThreshold(source: Double) {
threshold.value = source
}
fun setFalloff(source: Double) {
falloff.value = source
}
fun setLowSource(source: Module?) {
low.module = source
}
fun setHighSource(source: Module?) {
high.module = source
}
fun setControlSource(source: Module?) {
control.module = source
}
fun setThreshold(source: Module?) {
threshold.module = source
}
fun setFalloff(source: Module?) {
falloff.module = source
}
override fun get(x: Double, y: Double): Double {
val c = control[x, y]
val f = falloff[x, y]
val t = threshold[x, y]
return if (f > 0.0) {
if (c < t - f) {
low[x, y]
} else if (c > t + f) {
high[x, y]
} else {
val lower = t - f
val upper = t + f
val blend = quinticBlend((c - lower) / (upper - lower))
lerp(blend, low[x, y], high[x, y])
}
} else {
if (c < t) {
low[x, y]
} else {
high[x, y]
}
}
}
override fun get(x: Double, y: Double, z: Double): Double {
val c = control[x, y, z]
val f = falloff[x, y, z]
val t = threshold[x, y, z]
return if (f > 0.0) {
if (c < t - f) {
low[x, y, z]
} else if (c > t + f) {
high[x, y, z]
} else {
val lower = t - f
val upper = t + f
val blend = quinticBlend((c - lower) / (upper - lower))
lerp(blend, low[x, y, z], high[x, y, z])
}
} else {
if (c < t) {
low[x, y, z]
} else {
high[x, y, z]
}
}
}
override fun get(x: Double, y: Double, z: Double, w: Double): Double {
val c = control[x, y, z, w]
val f = falloff[x, y, z, w]
val t = threshold[x, y, z, w]
return if (f > 0.0) {
if (c < t - f) {
low[x, y, z, w]
} else if (c > t + f) {
high[x, y, z, w]
} else {
val lower = t - f
val upper = t + f
val blend = quinticBlend((c - lower) / (upper - lower))
lerp(blend, low[x, y, z, w], high[x, y, z, w])
}
} else {
if (c < t) {
low[x, y, z, w]
} else {
high[x, y, z, w]
}
}
}
override fun get(
x: Double,
y: Double,
z: Double,
w: Double,
u: Double,
v: Double
): Double {
val c = control[x, y, z, w, u, v]
val f = falloff[x, y, z, w, u, v]
val t = threshold[x, y, z, w, u, v]
return if (f > 0.0) {
when {
c < t - f -> {
low[x, y, z, w, u, v]
}
c > t + f -> {
high[x, y, z, w, u, v]
}
else -> {
val lower = t - f
val upper = t + f
val blend = quinticBlend((c - lower) / (upper - lower))
lerp(
blend, low[x, y, z, w, u, v],
high[x, y, z, w, u, v]
)
}
}
} else {
if (c < t) {
low[x, y, z, w, u, v]
} else {
high[x, y, z, w, u, v]
}
}
}
}