mirrors/Terra
1
0
Fork 0
mirror of https://github.com/PolyhedralDev/Terra.git synced 2026-02-16 02:20:57 +00:00
Code Issues Packages Projects Releases Wiki Activity

Implement distance sampler

Browse Source
This commit is contained in:
Astrash
2023-07-18 14:29:28 +10:00
parent 00aeb98419
commit 02198e1b88
3 changed files with 112 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
common/addons/config-noise-function/src/main/java/com/dfsek/terra/addons/noise/NoiseAddon.java
View File

@@ -24,6 +24,7 @@ import com.dfsek.terra.addons.noise.config.templates.LinearHeightmapSamplerTempl
import com.dfsek.terra.addons.noise.config.templates.TranslateSamplerTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.CellularNoiseTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.ConstantNoiseTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.DistanceSamplerTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.ExpressionFunctionTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.GaborNoiseTemplate;
import com.dfsek.terra.addons.noise.config.templates.noise.SimpleNoiseTemplate;
@@ -44,6 +45,7 @@ import com.dfsek.terra.addons.noise.samplers.arithmetic.MinSampler;
import com.dfsek.terra.addons.noise.samplers.arithmetic.MultiplicationSampler;
import com.dfsek.terra.addons.noise.samplers.arithmetic.SubtractionSampler;
import com.dfsek.terra.addons.noise.samplers.noise.CellularSampler;
import com.dfsek.terra.addons.noise.samplers.noise.DistanceSampler;
import com.dfsek.terra.addons.noise.samplers.noise.random.GaussianNoiseSampler;
import com.dfsek.terra.addons.noise.samplers.noise.random.PositiveWhiteNoiseSampler;
import com.dfsek.terra.addons.noise.samplers.noise.random.WhiteNoiseSampler;
@@ -85,6 +87,8 @@ public class NoiseAddon implements AddonInitializer {
(type, o, loader, depthTracker) -> CellularSampler.DistanceFunction.valueOf((String) o))
.applyLoader(CellularSampler.ReturnType.class,
(type, o, loader, depthTracker) -> CellularSampler.ReturnType.valueOf((String) o))
.applyLoader(DistanceSampler.DistanceFunction.class,
(type, o, loader, depthTracker) -> DistanceSampler.DistanceFunction.valueOf((String) o))
.applyLoader(DimensionApplicableNoiseSampler.class, DimensionApplicableNoiseSampler::new)
.applyLoader(FunctionTemplate.class, FunctionTemplate::new);

42
common/addons/config-noise-function/src/main/java/com/dfsek/terra/addons/noise/config/templates/noise/DistanceSamplerTemplate.java Normal file
View File

@@ -0,0 +1,42 @@
package com.dfsek.terra.addons.noise.config.templates.noise;
import com.dfsek.tectonic.api.config.template.annotations.Default;
import com.dfsek.tectonic.api.config.template.annotations.Value;
import com.dfsek.terra.addons.noise.config.templates.SamplerTemplate;
import com.dfsek.terra.addons.noise.samplers.noise.DistanceSampler;
import com.dfsek.terra.addons.noise.samplers.noise.DistanceSampler.DistanceFunction;
import com.dfsek.terra.api.config.meta.Meta;
public class DistanceSamplerTemplate extends SamplerTemplate<DistanceSampler> {
@Value("distance-function")
@Default
private DistanceSampler.@Meta DistanceFunction distanceFunction = DistanceFunction.Euclidean;
@Value("point.x")
@Default
private @Meta double x = 0;
@Value("point.y")
@Default
private @Meta double y = 0;
@Value("point.z")
@Default
private @Meta double z = 0;
@Value("normalize")
@Default
private @Meta boolean normalize = false;
@Value("radius")
@Default
private @Meta double normalizeRadius = 100;
@Override
public DistanceSampler get() {
return new DistanceSampler(distanceFunction, x, y, z, normalize, normalizeRadius);
}
}

66
common/addons/config-noise-function/src/main/java/com/dfsek/terra/addons/noise/samplers/noise/DistanceSampler.java Normal file
View File

@@ -0,0 +1,66 @@
package com.dfsek.terra.addons.noise.samplers.noise;
public class DistanceSampler extends NoiseFunction {
private final DistanceFunction distanceFunction;
private final double ox, oy, oz;
private final boolean normalize;
private final double radius;
private final double distanceAtRadius;
public DistanceSampler(DistanceFunction distanceFunction, double ox, double oy, double oz, boolean normalize, double radius) {
frequency = 1;
this.distanceFunction = distanceFunction;
this.ox = ox;
this.oy = oy;
this.oz = oz;
this.normalize = normalize;
this.radius = radius;
this.distanceAtRadius = distance2d(distanceFunction, radius, 0); // distance2d and distance3d should return the same value
}
@Override
public double getNoiseRaw(long seed, double x, double y) {
double dx = x - ox;
double dy = y - oz;
if (normalize && (fastAbs(dx) > radius || fastAbs(dy) > radius)) return 1;
double dist = distance2d(distanceFunction, dx, dy);
if (normalize) return fastMin(((2*dist)/distanceAtRadius)-1, 1);
return dist;
}
@Override
public double getNoiseRaw(long seed, double x, double y, double z) {
double dx = x - ox;
double dy = y - oy;
double dz = z - oz;
if(normalize && (fastAbs(dx) > radius || fastAbs(dy) > radius || fastAbs(dz) > radius)) return 1;
double dist = distance3d(distanceFunction, dx, dy, dz);
if (normalize) return fastMin(((2*dist)/distanceAtRadius)-1, 1);
return dist;
}
private static double distance2d(DistanceFunction distanceFunction, double x, double z) {
return switch(distanceFunction) {
case Euclidean -> fastSqrt(x*x + z*z);
case EuclideanSq -> x*x + z*z;
case Manhattan -> fastAbs(x) + fastAbs(z);
};
}
private static double distance3d(DistanceFunction distanceFunction, double x, double y, double z) {
return switch(distanceFunction) {
case Euclidean -> fastSqrt(x*x + y*y + z*z);
case EuclideanSq -> x*x + y*y + z*z;
case Manhattan -> fastAbs(x) + fastAbs(y) + fastAbs(z);
};
}
public enum DistanceFunction {
Euclidean,
EuclideanSq,
Manhattan
}
}