Merge pull request #77 from PolyhedralDev/ver/4.3.0

Noise Changes

build.gradle.kts

@@ -1,6 +1,6 @@
 import com.dfsek.terra.getGitHash
 
-val versionObj = Version("4", "2", "0", true)
+val versionObj = Version("4", "3", "0", true)
 
 allprojects {
     version = versionObj

common/src/main/java/com/dfsek/terra/api/core/TerraPlugin.java

@@ -7,7 +7,6 @@ import com.dfsek.terra.api.platform.handle.WorldHandle;
 import com.dfsek.terra.api.platform.world.World;
 import com.dfsek.terra.config.PluginConfig;
 import com.dfsek.terra.config.lang.Language;
-import com.dfsek.terra.config.pack.ConfigPack;
 import com.dfsek.terra.debug.DebugLogger;
 import com.dfsek.terra.registry.ConfigRegistry;
 import com.dfsek.terra.world.TerraWorld;
@@ -42,13 +41,6 @@ public interface TerraPlugin extends LoaderRegistrar {
 
     String platformName();
 
-    default void packPreLoadCallback(ConfigPack pack) {
-
-    }
-
-    default void packPostLoadCallback(ConfigPack pack) {
-
-    }
 
     DebugLogger getDebugLogger();
 

common/src/main/java/com/dfsek/terra/api/math/noise/normalizer/ExpressionNormalizer.java

@@ -1,33 +0,0 @@
-package com.dfsek.terra.api.math.noise.normalizer;
-
-import com.dfsek.paralithic.Expression;
-import com.dfsek.paralithic.eval.parser.Parser;
-import com.dfsek.paralithic.eval.parser.Scope;
-import com.dfsek.paralithic.eval.tokenizer.ParseException;
-import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction2;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction3;
-
-import java.util.Map;
-
-public class ExpressionNormalizer extends Normalizer {
-    private final Expression expression;
-
-    public ExpressionNormalizer(NoiseSampler sampler, String eq, Map<String, Double> vars) throws ParseException {
-        super(sampler);
-        Parser p = new Parser();
-        Scope scope = new Scope();
-        scope.addInvocationVariable("in");
-
-        vars.forEach(scope::create);
-
-        p.registerFunction("super2", new NoiseFunction2(sampler));
-        p.registerFunction("super3", new NoiseFunction3(sampler));
-        expression = p.parse(eq);
-    }
-
-    @Override
-    public double normalize(double in) {
-        return expression.evaluate(in);
-    }
-}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/ConstantSampler.java

@@ -1,34 +0,0 @@
-package com.dfsek.terra.api.math.noise.samplers;
-
-import com.dfsek.terra.api.math.noise.NoiseSampler;
-
-/**
- * Sampler implementation that returns a constant.
- */
-public class ConstantSampler implements NoiseSampler {
-    private final double constant;
-
-    public ConstantSampler(double constant) {
-        this.constant = constant;
-    }
-
-    @Override
-    public double getNoise(double x, double y) {
-        return constant;
-    }
-
-    @Override
-    public double getNoise(double x, double y, double z) {
-        return constant;
-    }
-
-    @Override
-    public double getNoiseSeeded(int seed, double x, double y) {
-        return constant;
-    }
-
-    @Override
-    public double getNoiseSeeded(int seed, double x, double y, double z) {
-        return constant;
-    }
-}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/ExpressionSampler.java

@@ -5,16 +5,16 @@ import com.dfsek.paralithic.eval.parser.Parser;
 import com.dfsek.paralithic.eval.parser.Scope;
 import com.dfsek.paralithic.eval.tokenizer.ParseException;
 import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.parsii.defined.UserDefinedFunction;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction2;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction3;
+import com.dfsek.terra.api.math.paralithic.defined.UserDefinedFunction;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction2;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction3;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.config.loaders.config.function.FunctionTemplate;
 
 import java.util.Map;
 
 /**
- * Sampler implementation using parsii expression
+ * Sampler implementation using Paralithic expression
  */
 public class ExpressionSampler implements NoiseSampler {
     private final Expression expression;

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/KernelSampler.java

@@ -0,0 +1,59 @@
+package com.dfsek.terra.api.math.noise.samplers;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+
+public class KernelSampler implements NoiseSampler {
+    private final double[][] kernel;
+    private final NoiseSampler in;
+    private double frequency = 1;
+
+    public KernelSampler(double[][] kernel, NoiseSampler in) {
+        this.kernel = kernel;
+        this.in = in;
+    }
+
+    @Override
+    public double getNoise(double x, double y) {
+        return getNoiseSeeded(0, x, y);
+    }
+
+    @Override
+    public double getNoise(double x, double y, double z) {
+        return getNoiseSeeded(0, x, y, z);
+    }
+
+    @Override
+    public double getNoiseSeeded(int seed, double x, double y) {
+        x *= frequency;
+        y *= frequency;
+        double accumulator = 0;
+
+        for(int kx = 0; kx < kernel.length; kx++) {
+            for(int ky = 0; ky < kernel[kx].length; ky++) {
+                accumulator += in.getNoise(x + kx, y + ky) * kernel[kx][ky];
+            }
+        }
+
+        return accumulator;
+    }
+
+    @Override
+    public double getNoiseSeeded(int seed, double x, double y, double z) {
+        x *= frequency;
+        y *= frequency;
+        z *= frequency;
+        double accumulator = 0;
+
+        for(int kx = 0; kx < kernel.length; kx++) {
+            for(int ky = 0; ky < kernel[kx].length; ky++) {
+                accumulator += in.getNoise(x + kx, y, z + ky) * kernel[kx][ky];
+            }
+        }
+
+        return accumulator;
+    }
+
+    public void setFrequency(double frequency) {
+        this.frequency = frequency;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/CellularSampler.java

@@ -0,0 +1,565 @@
+package com.dfsek.terra.api.math.noise.samplers.noise;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2Sampler;
+import com.dfsek.terra.api.math.vector.Vector2;
+import com.dfsek.terra.api.math.vector.Vector3;
+
+/**
+ * NoiseSampler implementation for Cellular (Voronoi/Worley) Noise.
+ */
+public class CellularSampler extends NoiseFunction {
+    private static final double[] RAND_VECS_3D = {
+            -0.7292736885d, -0.6618439697d, 0.1735581948d, 0, 0.790292081d, -0.5480887466d, -0.2739291014d, 0, 0.7217578935d, 0.6226212466d,
+            -0.3023380997d, 0, 0.565683137d, -0.8208298145d, -0.0790000257d, 0, 0.760049034d, -0.5555979497d, -0.3370999617d, 0,
+            0.3713945616d, 0.5011264475d, 0.7816254623d, 0, -0.1277062463d, -0.4254438999d, -0.8959289049d, 0, -0.2881560924d,
+            -0.5815838982d, 0.7607405838d, 0, 0.5849561111d, -0.662820239d, -0.4674352136d, 0, 0.3307171178d, 0.0391653737d, 0.94291689d, 0,
+            0.8712121778d, -0.4113374369d, -0.2679381538d, 0, 0.580981015d, 0.7021915846d, 0.4115677815d, 0, 0.503756873d, 0.6330056931d,
+            -0.5878203852d, 0, 0.4493712205d, 0.601390195d, 0.6606022552d, 0, -0.6878403724d, 0.09018890807d, -0.7202371714d, 0,
+            -0.5958956522d, -0.6469350577d, 0.475797649d, 0, -0.5127052122d, 0.1946921978d, -0.8361987284d, 0, -0.9911507142d,
+            -0.05410276466d, -0.1212153153d, 0, -0.2149721042d, 0.9720882117d, -0.09397607749d, 0, -0.7518650936d, -0.5428057603d,
+            0.3742469607d, 0, 0.5237068895d, 0.8516377189d, -0.02107817834d, 0, 0.6333504779d, 0.1926167129d, -0.7495104896d, 0,
+            -0.06788241606d, 0.3998305789d, 0.9140719259d, 0, -0.5538628599d, -0.4729896695d, -0.6852128902d, 0, -0.7261455366d,
+            -0.5911990757d, 0.3509933228d, 0, -0.9229274737d, -0.1782808786d, 0.3412049336d, 0, -0.6968815002d, 0.6511274338d,
+            0.3006480328d, 0, 0.9608044783d, -0.2098363234d, -0.1811724921d, 0, 0.06817146062d, -0.9743405129d, 0.2145069156d, 0,
+            -0.3577285196d, -0.6697087264d, -0.6507845481d, 0, -0.1868621131d, 0.7648617052d, -0.6164974636d, 0, -0.6541697588d,
+            0.3967914832d, 0.6439087246d, 0, 0.6993340405d, -0.6164538506d, 0.3618239211d, 0, -0.1546665739d, 0.6291283928d, 0.7617583057d,
+            0, -0.6841612949d, -0.2580482182d, -0.6821542638d, 0, 0.5383980957d, 0.4258654885d, 0.7271630328d, 0, -0.5026987823d,
+            -0.7939832935d, -0.3418836993d, 0, 0.3202971715d, 0.2834415347d, 0.9039195862d, 0, 0.8683227101d, -0.0003762656404d,
+            -0.4959995258d, 0, 0.791120031d, -0.08511045745d, 0.6057105799d, 0, -0.04011016052d, -0.4397248749d, 0.8972364289d, 0,
+            0.9145119872d, 0.3579346169d, -0.1885487608d, 0, -0.9612039066d, -0.2756484276d, 0.01024666929d, 0, 0.6510361721d,
+            -0.2877799159d, -0.7023778346d, 0, -0.2041786351d, 0.7365237271d, 0.644859585d, 0, -0.7718263711d, 0.3790626912d, 0.5104855816d,
+            0, -0.3060082741d, -0.7692987727d, 0.5608371729d, 0, 0.454007341d, -0.5024843065d, 0.7357899537d, 0, 0.4816795475d,
+            0.6021208291d, -0.6367380315d, 0, 0.6961980369d, -0.3222197429d, 0.641469197d, 0, -0.6532160499d, -0.6781148932d, 0.3368515753d,
+            0, 0.5089301236d, -0.6154662304d, -0.6018234363d, 0, -0.1635919754d, -0.9133604627d, -0.372840892d, 0, 0.52408019d,
+            -0.8437664109d, 0.1157505864d, 0, 0.5902587356d, 0.4983817807d, -0.6349883666d, 0, 0.5863227872d, 0.494764745d, 0.6414307729d,
+            0, 0.6779335087d, 0.2341345225d, 0.6968408593d, 0, 0.7177054546d, -0.6858979348d, 0.120178631d, 0, -0.5328819713d,
+            -0.5205125012d, 0.6671608058d, 0, -0.8654874251d, -0.0700727088d, -0.4960053754d, 0, -0.2861810166d, 0.7952089234d,
+            0.5345495242d, 0, -0.04849529634d, 0.9810836427d, -0.1874115585d, 0, -0.6358521667d, 0.6058348682d, 0.4781800233d, 0,
+            0.6254794696d, -0.2861619734d, 0.7258696564d, 0, -0.2585259868d, 0.5061949264d, -0.8227581726d, 0, 0.02136306781d,
+            0.5064016808d, -0.8620330371d, 0, 0.200111773d, 0.8599263484d, 0.4695550591d, 0, 0.4743561372d, 0.6014985084d, -0.6427953014d,
+            0, 0.6622993731d, -0.5202474575d, -0.5391679918d, 0, 0.08084972818d, -0.6532720452d, 0.7527940996d, 0, -0.6893687501d,
+            0.0592860349d, 0.7219805347d, 0, -0.1121887082d, -0.9673185067d, 0.2273952515d, 0, 0.7344116094d, 0.5979668656d, -0.3210532909d,
+            0, 0.5789393465d, -0.2488849713d, 0.7764570201d, 0, 0.6988182827d, 0.3557169806d, -0.6205791146d, 0, -0.8636845529d,
+            -0.2748771249d, -0.4224826141d, 0, -0.4247027957d, -0.4640880967d, 0.777335046d, 0, 0.5257722489d, -0.8427017621d,
+            0.1158329937d, 0, 0.9343830603d, 0.316302472d, -0.1639543925d, 0, -0.1016836419d, -0.8057303073d, -0.5834887393d, 0,
+            -0.6529238969d, 0.50602126d, -0.5635892736d, 0, -0.2465286165d, -0.9668205684d, -0.06694497494d, 0, -0.9776897119d,
+            -0.2099250524d, -0.007368825344d, 0, 0.7736893337d, 0.5734244712d, 0.2694238123d, 0, -0.6095087895d, 0.4995678998d,
+            0.6155736747d, 0, 0.5794535482d, 0.7434546771d, 0.3339292269d, 0, -0.8226211154d, 0.08142581855d, 0.5627293636d, 0,
+            -0.510385483d, 0.4703667658d, 0.7199039967d, 0, -0.5764971849d, -0.07231656274d, -0.8138926898d, 0, 0.7250628871d,
+            0.3949971505d, -0.5641463116d, 0, -0.1525424005d, 0.4860840828d, -0.8604958341d, 0, -0.5550976208d, -0.4957820792d,
+            0.667882296d, 0, -0.1883614327d, 0.9145869398d, 0.357841725d, 0, 0.7625556724d, -0.5414408243d, -0.3540489801d, 0,
+            -0.5870231946d, -0.3226498013d, -0.7424963803d, 0, 0.3051124198d, 0.2262544068d, -0.9250488391d, 0, 0.6379576059d, 0.577242424d,
+            -0.5097070502d, 0, -0.5966775796d, 0.1454852398d, -0.7891830656d, 0, -0.658330573d, 0.6555487542d, -0.3699414651d, 0,
+            0.7434892426d, 0.2351084581d, 0.6260573129d, 0, 0.5562114096d, 0.8264360377d, -0.0873632843d, 0, -0.3028940016d, -0.8251527185d,
+            0.4768419182d, 0, 0.1129343818d, -0.985888439d, -0.1235710781d, 0, 0.5937652891d, -0.5896813806d, 0.5474656618d, 0,
+            0.6757964092d, -0.5835758614d, -0.4502648413d, 0, 0.7242302609d, -0.1152719764d, 0.6798550586d, 0, -0.9511914166d,
+            0.0753623979d, -0.2992580792d, 0, 0.2539470961d, -0.1886339355d, 0.9486454084d, 0, 0.571433621d, -0.1679450851d, -0.8032795685d,
+            0, -0.06778234979d, 0.3978269256d, 0.9149531629d, 0, 0.6074972649d, 0.733060024d, -0.3058922593d, 0, -0.5435478392d,
+            0.1675822484d, 0.8224791405d, 0, -0.5876678086d, -0.3380045064d, -0.7351186982d, 0, -0.7967562402d, 0.04097822706d,
+            -0.6029098428d, 0, -0.1996350917d, 0.8706294745d, 0.4496111079d, 0, -0.02787660336d, -0.9106232682d, -0.4122962022d, 0,
+            -0.7797625996d, -0.6257634692d, 0.01975775581d, 0, -0.5211232846d, 0.7401644346d, -0.4249554471d, 0, 0.8575424857d,
+            0.4053272873d, -0.3167501783d, 0, 0.1045223322d, 0.8390195772d, -0.5339674439d, 0, 0.3501822831d, 0.9242524096d, -0.1520850155d,
+            0, 0.1987849858d, 0.07647613266d, 0.9770547224d, 0, 0.7845996363d, 0.6066256811d, -0.1280964233d, 0, 0.09006737436d,
+            -0.9750989929d, -0.2026569073d, 0, -0.8274343547d, -0.542299559d, 0.1458203587d, 0, -0.3485797732d, -0.415802277d, 0.840000362d,
+            0, -0.2471778936d, -0.7304819962d, -0.6366310879d, 0, -0.3700154943d, 0.8577948156d, 0.3567584454d, 0, 0.5913394901d,
+            -0.548311967d, -0.5913303597d, 0, 0.1204873514d, -0.7626472379d, -0.6354935001d, 0, 0.616959265d, 0.03079647928d, 0.7863922953d,
+            0, 0.1258156836d, -0.6640829889d, -0.7369967419d, 0, -0.6477565124d, -0.1740147258d, -0.7417077429d, 0, 0.6217889313d,
+            -0.7804430448d, -0.06547655076d, 0, 0.6589943422d, -0.6096987708d, 0.4404473475d, 0, -0.2689837504d, -0.6732403169d,
+            -0.6887635427d, 0, -0.3849775103d, 0.5676542638d, 0.7277093879d, 0, 0.5754444408d, 0.8110471154d, -0.1051963504d, 0,
+            0.9141593684d, 0.3832947817d, 0.131900567d, 0, -0.107925319d, 0.9245493968d, 0.3654593525d, 0, 0.377977089d, 0.3043148782d,
+            0.8743716458d, 0, -0.2142885215d, -0.8259286236d, 0.5214617324d, 0, 0.5802544474d, 0.4148098596d, -0.7008834116d, 0,
+            -0.1982660881d, 0.8567161266d, -0.4761596756d, 0, -0.03381553704d, 0.3773180787d, -0.9254661404d, 0, -0.6867922841d,
+            -0.6656597827d, 0.2919133642d, 0, 0.7731742607d, -0.2875793547d, -0.5652430251d, 0, -0.09655941928d, 0.9193708367d,
+            -0.3813575004d, 0, 0.2715702457d, -0.9577909544d, -0.09426605581d, 0, 0.2451015704d, -0.6917998565d, -0.6792188003d, 0,
+            0.977700782d, -0.1753855374d, 0.1155036542d, 0, -0.5224739938d, 0.8521606816d, 0.02903615945d, 0, -0.7734880599d,
+            -0.5261292347d, 0.3534179531d, 0, -0.7134492443d, -0.269547243d, 0.6467878011d, 0, 0.1644037271d, 0.5105846203d, -0.8439637196d,
+            0, 0.6494635788d, 0.05585611296d, 0.7583384168d, 0, -0.4711970882d, 0.5017280509d, -0.7254255765d, 0, -0.6335764307d,
+            -0.2381686273d, -0.7361091029d, 0, -0.9021533097d, -0.270947803d, -0.3357181763d, 0, -0.3793711033d, 0.872258117d,
+            0.3086152025d, 0, -0.6855598966d, -0.3250143309d, 0.6514394162d, 0, 0.2900942212d, -0.7799057743d, -0.5546100667d, 0,
+            -0.2098319339d, 0.85037073d, 0.4825351604d, 0, -0.4592603758d, 0.6598504336d, -0.5947077538d, 0, 0.8715945488d, 0.09616365406d,
+            -0.4807031248d, 0, -0.6776666319d, 0.7118504878d, -0.1844907016d, 0, 0.7044377633d, 0.312427597d, 0.637304036d, 0,
+            -0.7052318886d, -0.2401093292d, -0.6670798253d, 0, 0.081921007d, -0.7207336136d, -0.6883545647d, 0, -0.6993680906d,
+            -0.5875763221d, -0.4069869034d, 0, -0.1281454481d, 0.6419895885d, 0.7559286424d, 0, -0.6337388239d, -0.6785471501d,
+            -0.3714146849d, 0, 0.5565051903d, -0.2168887573d, -0.8020356851d, 0, -0.5791554484d, 0.7244372011d, -0.3738578718d, 0,
+            0.1175779076d, -0.7096451073d, 0.6946792478d, 0, -0.6134619607d, 0.1323631078d, 0.7785527795d, 0, 0.6984635305d,
+            -0.02980516237d, -0.715024719d, 0, 0.8318082963d, -0.3930171956d, 0.3919597455d, 0, 0.1469576422d, 0.05541651717d,
+            -0.9875892167d, 0, 0.708868575d, -0.2690503865d, 0.6520101478d, 0, 0.2726053183d, 0.67369766d, -0.68688995d, 0, -0.6591295371d,
+            0.3035458599d, -0.6880466294d, 0, 0.4815131379d, -0.7528270071d, 0.4487723203d, 0, 0.9430009463d, 0.1675647412d, -0.2875261255d,
+            0, 0.434802957d, 0.7695304522d, -0.4677277752d, 0, 0.3931996188d, 0.594473625d, 0.7014236729d, 0, 0.7254336655d, -0.603925654d,
+            0.3301814672d, 0, 0.7590235227d, -0.6506083235d, 0.02433313207d, 0, -0.8552768592d, -0.3430042733d, 0.3883935666d, 0,
+            -0.6139746835d, 0.6981725247d, 0.3682257648d, 0, -0.7465905486d, -0.5752009504d, 0.3342849376d, 0, 0.5730065677d, 0.810555537d,
+            -0.1210916791d, 0, -0.9225877367d, -0.3475211012d, -0.167514036d, 0, -0.7105816789d, -0.4719692027d, -0.5218416899d, 0,
+            -0.08564609717d, 0.3583001386d, 0.929669703d, 0, -0.8279697606d, -0.2043157126d, 0.5222271202d, 0, 0.427944023d, 0.278165994d,
+            0.8599346446d, 0, 0.5399079671d, -0.7857120652d, -0.3019204161d, 0, 0.5678404253d, -0.5495413974d, -0.6128307303d, 0,
+            -0.9896071041d, 0.1365639107d, -0.04503418428d, 0, -0.6154342638d, -0.6440875597d, 0.4543037336d, 0, 0.1074204368d,
+            -0.7946340692d, 0.5975094525d, 0, -0.3595449969d, -0.8885529948d, 0.28495784d, 0, -0.2180405296d, 0.1529888965d, 0.9638738118d,
+            0, -0.7277432317d, -0.6164050508d, -0.3007234646d, 0, 0.7249729114d, -0.00669719484d, 0.6887448187d, 0, -0.5553659455d,
+            -0.5336586252d, 0.6377908264d, 0, 0.5137558015d, 0.7976208196d, -0.3160000073d, 0, -0.3794024848d, 0.9245608561d,
+            -0.03522751494d, 0, 0.8229248658d, 0.2745365933d, -0.4974176556d, 0, -0.5404114394d, 0.6091141441d, 0.5804613989d, 0,
+            0.8036581901d, -0.2703029469d, 0.5301601931d, 0, 0.6044318879d, 0.6832968393d, 0.4095943388d, 0, 0.06389988817d, 0.9658208605d,
+            -0.2512108074d, 0, 0.1087113286d, 0.7402471173d, -0.6634877936d, 0, -0.713427712d, -0.6926784018d, 0.1059128479d, 0,
+            0.6458897819d, -0.5724548511d, -0.5050958653d, 0, -0.6553931414d, 0.7381471625d, 0.159995615d, 0, 0.3910961323d, 0.9188871375d,
+            -0.05186755998d, 0, -0.4879022471d, -0.5904376907d, 0.6429111375d, 0, 0.6014790094d, 0.7707441366d, -0.2101820095d, 0,
+            -0.5677173047d, 0.7511360995d, 0.3368851762d, 0, 0.7858573506d, 0.226674665d, 0.5753666838d, 0, -0.4520345543d, -0.604222686d,
+            -0.6561857263d, 0, 0.002272116345d, 0.4132844051d, -0.9105991643d, 0, -0.5815751419d, -0.5162925989d, 0.6286591339d, 0,
+            -0.03703704785d, 0.8273785755d, 0.5604221175d, 0, -0.5119692504d, 0.7953543429d, -0.3244980058d, 0, -0.2682417366d,
+            -0.9572290247d, -0.1084387619d, 0, -0.2322482736d, -0.9679131102d, -0.09594243324d, 0, 0.3554328906d, -0.8881505545d,
+            0.2913006227d, 0, 0.7346520519d, -0.4371373164d, 0.5188422971d, 0, 0.9985120116d, 0.04659011161d, -0.02833944577d, 0,
+            -0.3727687496d, -0.9082481361d, 0.1900757285d, 0, 0.91737377d, -0.3483642108d, 0.1925298489d, 0, 0.2714911074d, 0.4147529736d,
+            -0.8684886582d, 0, 0.5131763485d, -0.7116334161d, 0.4798207128d, 0, -0.8737353606d, 0.18886992d, -0.4482350644d, 0,
+            0.8460043821d, -0.3725217914d, 0.3814499973d, 0, 0.8978727456d, -0.1780209141d, -0.4026575304d, 0, 0.2178065647d,
+            -0.9698322841d, -0.1094789531d, 0, -0.1518031304d, -0.7788918132d, -0.6085091231d, 0, -0.2600384876d, -0.4755398075d,
+            -0.8403819825d, 0, 0.572313509d, -0.7474340931d, -0.3373418503d, 0, -0.7174141009d, 0.1699017182d, -0.6756111411d, 0,
+            -0.684180784d, 0.02145707593d, -0.7289967412d, 0, -0.2007447902d, 0.06555605789d, -0.9774476623d, 0, -0.1148803697d,
+            -0.8044887315d, 0.5827524187d, 0, -0.7870349638d, 0.03447489231d, 0.6159443543d, 0, -0.2015596421d, 0.6859872284d,
+            0.6991389226d, 0, -0.08581082512d, -0.10920836d, -0.9903080513d, 0, 0.5532693395d, 0.7325250401d, -0.396610771d, 0,
+            -0.1842489331d, -0.9777375055d, -0.1004076743d, 0, 0.0775473789d, -0.9111505856d, 0.4047110257d, 0, 0.1399838409d,
+            0.7601631212d, -0.6344734459d, 0, 0.4484419361d, -0.845289248d, 0.2904925424d, 0
+    };
+
+    private static final double[] RAND_VECS_2D = {
+            -0.2700222198d, -0.9628540911d, 0.3863092627d, -0.9223693152d, 0.04444859006d, -0.999011673d, -0.5992523158d, -0.8005602176d,
+            -0.7819280288d, 0.6233687174d, 0.9464672271d, 0.3227999196d, -0.6514146797d, -0.7587218957d, 0.9378472289d, 0.347048376d,
+            -0.8497875957d, -0.5271252623d, -0.879042592d, 0.4767432447d, -0.892300288d, -0.4514423508d, -0.379844434d, -0.9250503802d,
+            -0.9951650832d, 0.0982163789d, 0.7724397808d, -0.6350880136d, 0.7573283322d, -0.6530343002d, -0.9928004525d, -0.119780055d,
+            -0.0532665713d, 0.9985803285d, 0.9754253726d, -0.2203300762d, -0.7665018163d, 0.6422421394d, 0.991636706d, 0.1290606184d,
+            -0.994696838d, 0.1028503788d, -0.5379205513d, -0.84299554d, 0.5022815471d, -0.8647041387d, 0.4559821461d, -0.8899889226d,
+            -0.8659131224d, -0.5001944266d, 0.0879458407d, -0.9961252577d, -0.5051684983d, 0.8630207346d, 0.7753185226d, -0.6315704146d,
+            -0.6921944612d, 0.7217110418d, -0.5191659449d, -0.8546734591d, 0.8978622882d, -0.4402764035d, -0.1706774107d, 0.9853269617d,
+            -0.9353430106d, -0.3537420705d, -0.9992404798d, 0.03896746794d, -0.2882064021d, -0.9575683108d, -0.9663811329d, 0.2571137995d,
+            -0.8759714238d, -0.4823630009d, -0.8303123018d, -0.5572983775d, 0.05110133755d, -0.9986934731d, -0.8558373281d, -0.5172450752d,
+            0.09887025282d, 0.9951003332d, 0.9189016087d, 0.3944867976d, -0.2439375892d, -0.9697909324d, -0.8121409387d, -0.5834613061d,
+            -0.9910431363d, 0.1335421355d, 0.8492423985d, -0.5280031709d, -0.9717838994d, -0.2358729591d, 0.9949457207d, 0.1004142068d,
+            0.6241065508d, -0.7813392434d, 0.662910307d, 0.7486988212d, -0.7197418176d, 0.6942418282d, -0.8143370775d, -0.5803922158d,
+            0.104521054d, -0.9945226741d, -0.1065926113d, -0.9943027784d, 0.445799684d, -0.8951327509d, 0.105547406d, 0.9944142724d,
+            -0.992790267d, 0.1198644477d, -0.8334366408d, 0.552615025d, 0.9115561563d, -0.4111755999d, 0.8285544909d, -0.5599084351d,
+            0.7217097654d, -0.6921957921d, 0.4940492677d, -0.8694339084d, -0.3652321272d, -0.9309164803d, -0.9696606758d, 0.2444548501d,
+            0.08925509731d, -0.996008799d, 0.5354071276d, -0.8445941083d, -0.1053576186d, 0.9944343981d, -0.9890284586d, 0.1477251101d,
+            0.004856104961d, 0.9999882091d, 0.9885598478d, 0.1508291331d, 0.9286129562d, -0.3710498316d, -0.5832393863d, -0.8123003252d,
+            0.3015207509d, 0.9534596146d, -0.9575110528d, 0.2883965738d, 0.9715802154d, -0.2367105511d, 0.229981792d, 0.9731949318d,
+            0.955763816d, -0.2941352207d, 0.740956116d, 0.6715534485d, -0.9971513787d, -0.07542630764d, 0.6905710663d, -0.7232645452d,
+            -0.290713703d, -0.9568100872d, 0.5912777791d, -0.8064679708d, -0.9454592212d, -0.325740481d, 0.6664455681d, 0.74555369d,
+            0.6236134912d, 0.7817328275d, 0.9126993851d, -0.4086316587d, -0.8191762011d, 0.5735419353d, -0.8812745759d, -0.4726046147d,
+            0.9953313627d, 0.09651672651d, 0.9855650846d, -0.1692969699d, -0.8495980887d, 0.5274306472d, 0.6174853946d, -0.7865823463d,
+            0.8508156371d, 0.52546432d, 0.9985032451d, -0.05469249926d, 0.1971371563d, -0.9803759185d, 0.6607855748d, -0.7505747292d,
+            -0.03097494063d, 0.9995201614d, -0.6731660801d, 0.739491331d, -0.7195018362d, -0.6944905383d, 0.9727511689d, 0.2318515979d,
+            0.9997059088d, -0.0242506907d, 0.4421787429d, -0.8969269532d, 0.9981350961d, -0.061043673d, -0.9173660799d, -0.3980445648d,
+            -0.8150056635d, -0.5794529907d, -0.8789331304d, 0.4769450202d, 0.0158605829d, 0.999874213d, -0.8095464474d, 0.5870558317d,
+            -0.9165898907d, -0.3998286786d, -0.8023542565d, 0.5968480938d, -0.5176737917d, 0.8555780767d, -0.8154407307d, -0.5788405779d,
+            0.4022010347d, -0.9155513791d, -0.9052556868d, -0.4248672045d, 0.7317445619d, 0.6815789728d, -0.5647632201d, -0.8252529947d,
+            -0.8403276335d, -0.5420788397d, -0.9314281527d, 0.363925262d, 0.5238198472d, 0.8518290719d, 0.7432803869d, -0.6689800195d,
+            -0.985371561d, -0.1704197369d, 0.4601468731d, 0.88784281d, 0.825855404d, 0.5638819483d, 0.6182366099d, 0.7859920446d,
+            0.8331502863d, -0.553046653d, 0.1500307506d, 0.9886813308d, -0.662330369d, -0.7492119075d, -0.668598664d, 0.743623444d,
+            0.7025606278d, 0.7116238924d, -0.5419389763d, -0.8404178401d, -0.3388616456d, 0.9408362159d, 0.8331530315d, 0.5530425174d,
+            -0.2989720662d, -0.9542618632d, 0.2638522993d, 0.9645630949d, 0.124108739d, -0.9922686234d, -0.7282649308d, -0.6852956957d,
+            0.6962500149d, 0.7177993569d, -0.9183535368d, 0.3957610156d, -0.6326102274d, -0.7744703352d, -0.9331891859d, -0.359385508d,
+            -0.1153779357d, -0.9933216659d, 0.9514974788d, -0.3076565421d, -0.08987977445d, -0.9959526224d, 0.6678496916d, 0.7442961705d,
+            0.7952400393d, -0.6062947138d, -0.6462007402d, -0.7631674805d, -0.2733598753d, 0.9619118351d, 0.9669590226d, -0.254931851d,
+            -0.9792894595d, 0.2024651934d, -0.5369502995d, -0.8436138784d, -0.270036471d, -0.9628500944d, -0.6400277131d, 0.7683518247d,
+            -0.7854537493d, -0.6189203566d, 0.06005905383d, -0.9981948257d, -0.02455770378d, 0.9996984141d, -0.65983623d, 0.751409442d,
+            -0.6253894466d, -0.7803127835d, -0.6210408851d, -0.7837781695d, 0.8348888491d, 0.5504185768d, -0.1592275245d, 0.9872419133d,
+            0.8367622488d, 0.5475663786d, -0.8675753916d, -0.4973056806d, -0.2022662628d, -0.9793305667d, 0.9399189937d, 0.3413975472d,
+            0.9877404807d, -0.1561049093d, -0.9034455656d, 0.4287028224d, 0.1269804218d, -0.9919052235d, -0.3819600854d, 0.924178821d,
+            0.9754625894d, 0.2201652486d, -0.3204015856d, -0.9472818081d, -0.9874760884d, 0.1577687387d, 0.02535348474d, -0.9996785487d,
+            0.4835130794d, -0.8753371362d, -0.2850799925d, -0.9585037287d, -0.06805516006d, -0.99768156d, -0.7885244045d, -0.6150034663d,
+            0.3185392127d, -0.9479096845d, 0.8880043089d, 0.4598351306d, 0.6476921488d, -0.7619021462d, 0.9820241299d, 0.1887554194d,
+            0.9357275128d, -0.3527237187d, -0.8894895414d, 0.4569555293d, 0.7922791302d, 0.6101588153d, 0.7483818261d, 0.6632681526d,
+            -0.7288929755d, -0.6846276581d, 0.8729032783d, -0.4878932944d, 0.8288345784d, 0.5594937369d, 0.08074567077d, 0.9967347374d,
+            0.9799148216d, -0.1994165048d, -0.580730673d, -0.8140957471d, -0.4700049791d, -0.8826637636d, 0.2409492979d, 0.9705377045d,
+            0.9437816757d, -0.3305694308d, -0.8927998638d, -0.4504535528d, -0.8069622304d, 0.5906030467d, 0.06258973166d, 0.9980393407d,
+            -0.9312597469d, 0.3643559849d, 0.5777449785d, 0.8162173362d, -0.3360095855d, -0.941858566d, 0.697932075d, -0.7161639607d,
+            -0.002008157227d, -0.9999979837d, -0.1827294312d, -0.9831632392d, -0.6523911722d, 0.7578824173d, -0.4302626911d, -0.9027037258d,
+            -0.9985126289d, -0.05452091251d, -0.01028102172d, -0.9999471489d, -0.4946071129d, 0.8691166802d, -0.2999350194d, 0.9539596344d,
+            0.8165471961d, 0.5772786819d, 0.2697460475d, 0.962931498d, -0.7306287391d, -0.6827749597d, -0.7590952064d, -0.6509796216d,
+            -0.907053853d, 0.4210146171d, -0.5104861064d, -0.8598860013d, 0.8613350597d, 0.5080373165d, 0.5007881595d, -0.8655698812d,
+            -0.654158152d, 0.7563577938d, -0.8382755311d, -0.545246856d, 0.6940070834d, 0.7199681717d, 0.06950936031d, 0.9975812994d,
+            0.1702942185d, -0.9853932612d, 0.2695973274d, 0.9629731466d, 0.5519612192d, -0.8338697815d, 0.225657487d, -0.9742067022d,
+            0.4215262855d, -0.9068161835d, 0.4881873305d, -0.8727388672d, -0.3683854996d, -0.9296731273d, -0.9825390578d, 0.1860564427d,
+            0.81256471d, 0.5828709909d, 0.3196460933d, -0.9475370046d, 0.9570913859d, 0.2897862643d, -0.6876655497d, -0.7260276109d,
+            -0.9988770922d, -0.047376731d, -0.1250179027d, 0.992154486d, -0.8280133617d, 0.560708367d, 0.9324863769d, -0.3612051451d,
+            0.6394653183d, 0.7688199442d, -0.01623847064d, -0.9998681473d, -0.9955014666d, -0.09474613458d, -0.81453315d, 0.580117012d,
+            0.4037327978d, -0.9148769469d, 0.9944263371d, 0.1054336766d, -0.1624711654d, 0.9867132919d, -0.9949487814d, -0.100383875d,
+            -0.6995302564d, 0.7146029809d, 0.5263414922d, -0.85027327d, -0.5395221479d, 0.841971408d, 0.6579370318d, 0.7530729462d,
+            0.01426758847d, -0.9998982128d, -0.6734383991d, 0.7392433447d, 0.639412098d, -0.7688642071d, 0.9211571421d, 0.3891908523d,
+            -0.146637214d, -0.9891903394d, -0.782318098d, 0.6228791163d, -0.5039610839d, -0.8637263605d, -0.7743120191d, -0.6328039957d,
+    };
+
+
+    private DistanceFunction distanceFunction = DistanceFunction.EuclideanSq;
+    private ReturnType returnType = ReturnType.Distance;
+    private double jitterModifier = 1.0;
+
+    private NoiseSampler noiseLookup;
+
+    public CellularSampler(int seed) {
+        super(seed);
+        noiseLookup = new OpenSimplex2Sampler(seed);
+    }
+
+    public void setDistanceFunction(DistanceFunction distanceFunction) {
+        this.distanceFunction = distanceFunction;
+    }
+
+    public void setJitterModifier(double jitterModifier) {
+        this.jitterModifier = jitterModifier;
+    }
+
+    public void setNoiseLookup(NoiseSampler noiseLookup) {
+        this.noiseLookup = noiseLookup;
+    }
+
+    public void setReturnType(ReturnType returnType) {
+        this.returnType = returnType;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        int xr = fastRound(x);
+        int yr = fastRound(y);
+
+        double distance0 = Double.MAX_VALUE;
+        double distance1 = Double.MAX_VALUE;
+        double distance2 = Double.MAX_VALUE;
+
+        int closestHash = 0;
+
+        double cellularJitter = 0.43701595 * jitterModifier;
+
+        int xPrimed = (xr - 1) * PRIME_X;
+        int yPrimedBase = (yr - 1) * PRIME_Y;
+
+        Vector2 center = new Vector2(x, y);
+
+        switch(distanceFunction) {
+            default:
+            case Euclidean:
+            case EuclideanSq:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int hash = hash(seed, xPrimed, yPrimed);
+                        int idx = hash & (255 << 1);
+
+                        double vecX = (xi - x) + RAND_VECS_2D[idx] * cellularJitter;
+                        double vecY = (yi - y) + RAND_VECS_2D[idx | 1] * cellularJitter;
+
+                        double newDistance = vecX * vecX + vecY * vecY;
+
+                        distance1 = fastMax(fastMin(distance1, newDistance), distance0);
+                        if(newDistance < distance0) {
+                            distance0 = newDistance;
+                            closestHash = hash;
+                            center.setX((xi + RAND_VECS_2D[idx] * cellularJitter) / frequency);
+                            center.setZ((yi + RAND_VECS_2D[idx | 1] * cellularJitter) / frequency);
+                        } else if(newDistance < distance1) {
+                            distance2 = distance1;
+                            distance1 = newDistance;
+                        } else if(newDistance < distance2) {
+                            distance2 = newDistance;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+            case Manhattan:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int hash = hash(seed, xPrimed, yPrimed);
+                        int idx = hash & (255 << 1);
+
+                        double vecX = (xi - x) + RAND_VECS_2D[idx] * cellularJitter;
+                        double vecY = (yi - y) + RAND_VECS_2D[idx | 1] * cellularJitter;
+
+                        double newDistance = fastAbs(vecX) + fastAbs(vecY);
+
+                        distance1 = fastMax(fastMin(distance1, newDistance), distance0);
+                        if(newDistance < distance0) {
+                            distance0 = newDistance;
+                            closestHash = hash;
+                            center.setX((xi + RAND_VECS_2D[idx] * cellularJitter) / frequency);
+                            center.setZ((yi + RAND_VECS_2D[idx | 1] * cellularJitter) / frequency);
+                        } else if(newDistance < distance1) {
+                            distance2 = distance1;
+                            distance1 = newDistance;
+                        } else if(newDistance < distance2) {
+                            distance2 = newDistance;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+            case Hybrid:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int hash = hash(seed, xPrimed, yPrimed);
+                        int idx = hash & (255 << 1);
+
+                        double vecX = (xi - x) + RAND_VECS_2D[idx] * cellularJitter;
+                        double vecY = (yi - y) + RAND_VECS_2D[idx | 1] * cellularJitter;
+
+                        double newDistance = (fastAbs(vecX) + fastAbs(vecY)) + (vecX * vecX + vecY * vecY);
+
+                        distance1 = fastMax(fastMin(distance1, newDistance), distance0);
+                        if(newDistance < distance0) {
+                            distance0 = newDistance;
+                            closestHash = hash;
+                            center.setX((xi + RAND_VECS_2D[idx] * cellularJitter) / frequency);
+                            center.setZ((yi + RAND_VECS_2D[idx | 1] * cellularJitter) / frequency);
+                        } else if(newDistance < distance1) {
+                            distance2 = distance1;
+                            distance1 = newDistance;
+                        } else if(newDistance < distance2) {
+                            distance2 = newDistance;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+        }
+
+        if(distanceFunction == DistanceFunction.Euclidean && returnType != ReturnType.CellValue) {
+            distance0 = fastSqrt(distance0);
+            if(returnType != ReturnType.CellValue) {
+                distance1 = fastSqrt(distance1);
+            }
+        }
+
+        switch(returnType) {
+            case CellValue:
+                return closestHash * (1 / 2147483648.0);
+            case Distance:
+                return distance0 - 1;
+            case Distance2:
+                return distance1 - 1;
+            case Distance2Add:
+                return (distance1 + distance0) * 0.5 - 1;
+            case Distance2Sub:
+                return distance1 - distance0 - 1;
+            case Distance2Mul:
+                return distance1 * distance0 * 0.5 - 1;
+            case Distance2Div:
+                return distance0 / distance1 - 1;
+            case NoiseLookup:
+                return noiseLookup.getNoise(center.getX(), center.getZ());
+            case Distance3:
+                return distance2 - 1;
+            case Distance3Add:
+                return (distance2 + distance0) * 0.5 - 1;
+            case Distance3Sub:
+                return distance2 - distance0 - 1;
+            case Distance3Mul:
+                return distance2 * distance0 - 1;
+            case Distance3Div:
+                return distance0 / distance2 - 1;
+            default:
+                return 0;
+        }
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        int xr = fastRound(x);
+        int yr = fastRound(y);
+        int zr = fastRound(z);
+
+        double distance0 = Double.MAX_VALUE;
+        double distance1 = Double.MAX_VALUE;
+        double distance2 = Double.MAX_VALUE;
+        int closestHash = 0;
+
+        double cellularJitter = 0.39614353 * jitterModifier;
+
+        int xPrimed = (xr - 1) * PRIME_X;
+        int yPrimedBase = (yr - 1) * PRIME_Y;
+        int zPrimedBase = (zr - 1) * PRIME_Z;
+
+        Vector3 center = new Vector3(x, y, z);
+
+        switch(distanceFunction) {
+            case Euclidean:
+            case EuclideanSq:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int zPrimed = zPrimedBase;
+
+                        for(int zi = zr - 1; zi <= zr + 1; zi++) {
+                            int hash = hash(seed, xPrimed, yPrimed, zPrimed);
+                            int idx = hash & (255 << 2);
+
+                            double vecX = (xi - x) + RAND_VECS_3D[idx] * cellularJitter;
+                            double vecY = (yi - y) + RAND_VECS_3D[idx | 1] * cellularJitter;
+                            double vecZ = (zi - z) + RAND_VECS_3D[idx | 2] * cellularJitter;
+
+                            double newDistance = vecX * vecX + vecY * vecY + vecZ * vecZ;
+
+                            if(newDistance < distance0) {
+                                distance0 = newDistance;
+                                closestHash = hash;
+                                center.setX((xi + RAND_VECS_3D[idx] * cellularJitter) / frequency);
+                                center.setY((yi + RAND_VECS_3D[idx | 1] * cellularJitter) / frequency);
+                                center.setZ((zi + RAND_VECS_3D[idx | 2] * cellularJitter) / frequency);
+                            } else if(newDistance < distance1) {
+                                distance2 = distance1;
+                                distance1 = newDistance;
+                            } else if(newDistance < distance2) {
+                                distance2 = newDistance;
+                            }
+                            zPrimed += PRIME_Z;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+            case Manhattan:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int zPrimed = zPrimedBase;
+
+                        for(int zi = zr - 1; zi <= zr + 1; zi++) {
+                            int hash = hash(seed, xPrimed, yPrimed, zPrimed);
+                            int idx = hash & (255 << 2);
+
+                            double vecX = (xi - x) + RAND_VECS_3D[idx] * cellularJitter;
+                            double vecY = (yi - y) + RAND_VECS_3D[idx | 1] * cellularJitter;
+                            double vecZ = (zi - z) + RAND_VECS_3D[idx | 2] * cellularJitter;
+
+                            double newDistance = fastAbs(vecX) + fastAbs(vecY) + fastAbs(vecZ);
+
+                            if(newDistance < distance0) {
+                                distance0 = newDistance;
+                                closestHash = hash;
+                                center.setX((xi + RAND_VECS_3D[idx] * cellularJitter) / frequency);
+                                center.setY((yi + RAND_VECS_3D[idx | 1] * cellularJitter) / frequency);
+                                center.setZ((zi + RAND_VECS_3D[idx | 2] * cellularJitter) / frequency);
+                            } else if(newDistance < distance1) {
+                                distance2 = distance1;
+                                distance1 = newDistance;
+                            } else if(newDistance < distance2) {
+                                distance2 = newDistance;
+                            }
+                            zPrimed += PRIME_Z;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+            case Hybrid:
+                for(int xi = xr - 1; xi <= xr + 1; xi++) {
+                    int yPrimed = yPrimedBase;
+
+                    for(int yi = yr - 1; yi <= yr + 1; yi++) {
+                        int zPrimed = zPrimedBase;
+
+                        for(int zi = zr - 1; zi <= zr + 1; zi++) {
+                            int hash = hash(seed, xPrimed, yPrimed, zPrimed);
+                            int idx = hash & (255 << 2);
+
+                            double vecX = (xi - x) + RAND_VECS_3D[idx] * cellularJitter;
+                            double vecY = (yi - y) + RAND_VECS_3D[idx | 1] * cellularJitter;
+                            double vecZ = (zi - z) + RAND_VECS_3D[idx | 2] * cellularJitter;
+
+                            double newDistance = (fastAbs(vecX) + fastAbs(vecY) + fastAbs(vecZ)) +
+                                    (vecX * vecX + vecY * vecY + vecZ * vecZ);
+
+                            distance1 = fastMax(fastMin(distance1, newDistance), distance0);
+                            if(newDistance < distance0) {
+                                distance0 = newDistance;
+                                closestHash = hash;
+                                center.setX((xi + RAND_VECS_3D[idx] * cellularJitter) / frequency);
+                                center.setY((yi + RAND_VECS_3D[idx | 1] * cellularJitter) / frequency);
+                                center.setZ((zi + RAND_VECS_3D[idx | 2] * cellularJitter) / frequency);
+                            } else if(newDistance < distance1) {
+                                distance2 = distance1;
+                                distance1 = newDistance;
+                            } else if(newDistance < distance2) {
+                                distance2 = newDistance;
+                            }
+                            zPrimed += PRIME_Z;
+                        }
+                        yPrimed += PRIME_Y;
+                    }
+                    xPrimed += PRIME_X;
+                }
+                break;
+            default:
+                break;
+        }
+
+        if(distanceFunction == DistanceFunction.Euclidean && returnType != ReturnType.CellValue) {
+            distance0 = fastSqrt(distance0);
+            if(returnType != ReturnType.CellValue) {
+                distance1 = fastSqrt(distance1);
+            }
+        }
+
+        switch(returnType) {
+            case CellValue:
+                return closestHash * (1 / 2147483648.0);
+            case Distance:
+                return distance0 - 1;
+            case Distance2:
+                return distance1 - 1;
+            case Distance2Add:
+                return (distance1 + distance0) * 0.5 - 1;
+            case Distance2Sub:
+                return distance1 - distance0 - 1;
+            case Distance2Mul:
+                return distance1 * distance0 * 0.5 - 1;
+            case Distance2Div:
+                return distance0 / distance1 - 1;
+            case NoiseLookup:
+                return noiseLookup.getNoise(center.getX(), center.getY(), center.getZ());
+            case Distance3:
+                return distance2 - 1;
+            case Distance3Add:
+                return (distance2 + distance0) * 0.5 - 1;
+            case Distance3Sub:
+                return distance2 - distance0 - 1;
+            case Distance3Mul:
+                return distance2 * distance0 - 1;
+            case Distance3Div:
+                return distance0 / distance2 - 1;
+            default:
+                return 0;
+        }
+    }
+
+    public enum DistanceFunction {
+        Euclidean,
+        EuclideanSq,
+        Manhattan,
+        Hybrid
+    }
+
+
+    public enum ReturnType {
+        CellValue,
+        Distance,
+        Distance2,
+        Distance2Add,
+        Distance2Sub,
+        Distance2Mul,
+        Distance2Div,
+        NoiseLookup,
+        Distance3,
+        Distance3Add,
+        Distance3Sub,
+        Distance3Mul,
+        Distance3Div
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/ConstantSampler.java

@@ -0,0 +1,23 @@
+package com.dfsek.terra.api.math.noise.samplers.noise;
+
+/**
+ * Sampler implementation that returns a constant.
+ */
+public class ConstantSampler extends NoiseFunction {
+    private final double constant;
+
+    public ConstantSampler(double constant) {
+        super(0);
+        this.constant = constant;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        return constant;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        return constant;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/ExpressionFunction.java

@@ -0,0 +1,43 @@
+package com.dfsek.terra.api.math.noise.samplers.noise;
+
+import com.dfsek.paralithic.Expression;
+import com.dfsek.paralithic.eval.parser.Parser;
+import com.dfsek.paralithic.eval.parser.Scope;
+import com.dfsek.paralithic.eval.tokenizer.ParseException;
+import com.dfsek.paralithic.functions.Function;
+
+import java.util.Map;
+
+/**
+ * NoiseSampler implementation using a Paralithic expression.
+ */
+public class ExpressionFunction extends NoiseFunction {
+    private final Expression expression;
+
+    public ExpressionFunction(Map<String, Function> functions, String eq, Map<String, Double> vars) throws ParseException {
+        super(0);
+        Parser p = new Parser();
+        Scope scope = new Scope();
+
+        scope.addInvocationVariable("x");
+        scope.addInvocationVariable("y");
+        scope.addInvocationVariable("z");
+
+        vars.forEach(scope::create);
+
+        functions.forEach(p::registerFunction);
+
+        expression = p.parse(eq, scope);
+        frequency = 1;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        return expression.evaluate(x, 0, y);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        return expression.evaluate(x, y, z);
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/NoiseFunction.java

@@ -0,0 +1,111 @@
+package com.dfsek.terra.api.math.noise.samplers.noise;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import net.jafama.FastMath;
+
+@SuppressWarnings("ManualMinMaxCalculation")
+public abstract class NoiseFunction implements NoiseSampler {
+    // Hashing
+    protected static final int PRIME_X = 501125321;
+    protected static final int PRIME_Y = 1136930381;
+    protected static final int PRIME_Z = 1720413743;
+
+
+    protected double frequency = 0.02d;
+    protected int seed;
+
+    public NoiseFunction(int seed) {
+        this.seed = seed;
+    }
+
+    protected static int fastFloor(double f) {
+        return f >= 0 ? (int) f : (int) f - 1;
+    }
+
+    protected static int hash(int seed, int xPrimed, int yPrimed, int zPrimed) {
+        int hash = seed ^ xPrimed ^ yPrimed ^ zPrimed;
+
+        hash *= 0x27d4eb2d;
+        return hash;
+    }
+
+    protected static int hash(int seed, int xPrimed, int yPrimed) {
+        int hash = seed ^ xPrimed ^ yPrimed;
+
+        hash *= 0x27d4eb2d;
+        return hash;
+    }
+
+    protected static int fastRound(double f) {
+        return f >= 0 ? (int) (f + 0.5f) : (int) (f - 0.5);
+    }
+
+    protected static double lerp(double a, double b, double t) {
+        return a + t * (b - a);
+    }
+
+    protected static double interpHermite(double t) {
+        return t * t * (3 - 2 * t);
+    }
+
+    protected static double interpQuintic(double t) {
+        return t * t * t * (t * (t * 6 - 15) + 10);
+    }
+
+    protected static double cubicLerp(double a, double b, double c, double d, double t) {
+        double p = (d - c) - (a - b);
+        return t * t * t * p + t * t * ((a - b) - p) + t * (c - a) + b;
+    }
+
+    protected static double fastMin(double a, double b) {
+        return a < b ? a : b;
+    }
+
+    protected static double fastMax(double a, double b) {
+        return a > b ? a : b;
+    }
+
+    protected static double fastAbs(double f) {
+        return f < 0 ? -f : f;
+    }
+
+    protected static double fastSqrt(double f) {
+        return FastMath.sqrt(f);
+    }
+
+    public void setSeed(int seed) {
+        this.seed = seed;
+    }
+
+    public double getFrequency() {
+        return frequency;
+    }
+
+    public void setFrequency(double frequency) {
+        this.frequency = frequency;
+    }
+
+    @Override
+    public double getNoise(double x, double y) {
+        return getNoiseSeeded(seed, x, y);
+    }
+
+    @Override
+    public double getNoise(double x, double y, double z) {
+        return getNoiseSeeded(seed, x, y, z);
+    }
+
+    @Override
+    public double getNoiseSeeded(int seed, double x, double y) {
+        return getNoiseRaw(seed, x * frequency, y * frequency);
+    }
+
+    @Override
+    public double getNoiseSeeded(int seed, double x, double y, double z) {
+        return getNoiseRaw(seed, x * frequency, y * frequency, z * frequency);
+    }
+
+    public abstract double getNoiseRaw(int seed, double x, double y);
+
+    public abstract double getNoiseRaw(int seed, double x, double y, double z);
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/fractal/BrownianMotionSampler.java

@@ -0,0 +1,46 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+
+public class BrownianMotionSampler extends FractalNoiseFunction {
+    public BrownianMotionSampler(int seed, NoiseSampler input) {
+        super(seed, input);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = input.getNoiseSeeded(seed++, x, y);
+            sum += noise * amp;
+            amp *= lerp(1.0, fastMin(noise + 1, 2) * 0.5, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = input.getNoiseSeeded(seed++, x, y, z);
+            sum += noise * amp;
+            amp *= lerp(1.0, (noise + 1) * 0.5, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            z *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/fractal/FractalNoiseFunction.java

@@ -0,0 +1,48 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+public abstract class FractalNoiseFunction extends NoiseFunction {
+    protected final NoiseSampler input;
+    protected double fractalBounding = 1 / 1.75;
+    protected int octaves = 3;
+    protected double gain = 0.5;
+    protected double lacunarity = 2.0d;
+    protected double weightedStrength = 0.0d;
+
+    public FractalNoiseFunction(int seed, NoiseSampler input) {
+        super(seed);
+        this.input = input;
+        frequency = 1;
+    }
+
+    public void setWeightedStrength(double weightedStrength) {
+        this.weightedStrength = weightedStrength;
+    }
+
+    protected void calculateFractalBounding() {
+        double gain = fastAbs(this.gain);
+        double amp = gain;
+        double ampFractal = 1.0;
+        for(int i = 1; i < octaves; i++) {
+            ampFractal += amp;
+            amp *= gain;
+        }
+        fractalBounding = 1 / ampFractal;
+    }
+
+    public void setOctaves(int octaves) {
+        this.octaves = octaves;
+        calculateFractalBounding();
+    }
+
+    public void setGain(double gain) {
+        this.gain = gain;
+        calculateFractalBounding();
+    }
+
+    public void setLacunarity(double lacunarity) {
+        this.lacunarity = lacunarity;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/fractal/PingPongSampler.java

@@ -0,0 +1,58 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+
+public class PingPongSampler extends FractalNoiseFunction {
+    private double pingPongStrength = 2.0;
+
+    public PingPongSampler(int seed, NoiseSampler input) {
+        super(seed, input);
+    }
+
+
+    private static double pingPong(double t) {
+        t -= (int) (t * 0.5f) << 1;
+        return t < 1 ? t : 2 - t;
+    }
+
+    public void setPingPongStrength(double strength) {
+        this.pingPongStrength = strength;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = pingPong((input.getNoiseSeeded(seed++, x, y) + 1) * pingPongStrength);
+            sum += (noise - 0.5) * 2 * amp;
+            amp *= lerp(1.0, noise, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = pingPong((input.getNoiseSeeded(seed++, x, y, z) + 1) * pingPongStrength);
+            sum += (noise - 0.5) * 2 * amp;
+            amp *= lerp(1.0, noise, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            z *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/fractal/RidgedFractalSampler.java

@@ -0,0 +1,47 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+
+public class RidgedFractalSampler extends FractalNoiseFunction {
+
+    public RidgedFractalSampler(int seed, NoiseSampler input) {
+        super(seed, input);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = fastAbs(input.getNoiseSeeded(seed++, x, y));
+            sum += (noise * -2 + 1) * amp;
+            amp *= lerp(1.0, 1 - noise, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        double sum = 0;
+        double amp = fractalBounding;
+
+        for(int i = 0; i < octaves; i++) {
+            double noise = fastAbs(input.getNoiseSeeded(seed++, x, y, z));
+            sum += (noise * -2 + 1) * amp;
+            amp *= lerp(1.0, 1 - noise, weightedStrength);
+
+            x *= lacunarity;
+            y *= lacunarity;
+            z *= lacunarity;
+            amp *= gain;
+        }
+
+        return sum;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/random/GaussianNoiseSampler.java

@@ -0,0 +1,39 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.random;
+
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+/**
+ * NoiseSampler implementation to provide random, normally distributed (Gaussian) noise.
+ */
+public class GaussianNoiseSampler extends NoiseFunction {
+    private final WhiteNoiseSampler whiteNoiseSampler; // Back with a white noise sampler.
+
+    public GaussianNoiseSampler(int seed) {
+        super(seed);
+        whiteNoiseSampler = new WhiteNoiseSampler(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        double v1, v2, s;
+        do {
+            v1 = whiteNoiseSampler.getNoiseSeeded(seed++, x, y);
+            v2 = whiteNoiseSampler.getNoiseSeeded(seed++, x, y);
+            s = v1 * v1 + v2 * v2;
+        } while(s >= 1 || s == 0);
+        double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s) / s);
+        return v1 * multiplier;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        double v1, v2, s;
+        do {
+            v1 = whiteNoiseSampler.getNoiseSeeded(seed++, x, y, z);
+            v2 = whiteNoiseSampler.getNoiseSeeded(seed++, x, y, z);
+            s = v1 * v1 + v2 * v2;
+        } while(s >= 1 || s == 0);
+        double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s) / s);
+        return v1 * multiplier;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/random/WhiteNoiseSampler.java

@@ -0,0 +1,49 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.random;
+
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+/**
+ * NoiseSampler implementation to produce random, uniformly distributed (white) noise.
+ */
+public class WhiteNoiseSampler extends NoiseFunction {
+    private static final long POSITIVE_POW1 = 0b01111111111L << 52; // Bits that when applied to the exponent/sign section of a double, produce a positive number with a power of 1.
+
+    public WhiteNoiseSampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        long hashX = Double.doubleToRawLongBits(x) ^ seed;
+        long hashZ = Double.doubleToRawLongBits(y) ^ seed;
+        long hash = ((hashX ^ (hashX >>> 32)) + ((hashZ ^ (hashZ >>> 32)) << 32)) ^ seed;
+        long base = (murmur64(hash) & 0x000fffffffffffffL)
+                | POSITIVE_POW1; // Sign and exponent
+        return (Double.longBitsToDouble(base) - 1.5) * 2;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        long hashX = Double.doubleToRawLongBits(x) ^ seed;
+        long hashZ = Double.doubleToRawLongBits(y) ^ seed;
+        long hash = (((hashX ^ (hashX >>> 32)) + ((hashZ ^ (hashZ >>> 32)) << 32)) ^ seed) + Double.doubleToRawLongBits(z);
+        long base = ((murmur64(hash)) & 0x000fffffffffffffL)
+                | POSITIVE_POW1; // Sign and exponent
+        return (Double.longBitsToDouble(base) - 1.5) * 2;
+    }
+
+    /**
+     * Murmur64 hashing function
+     *
+     * @param h Input value
+     * @return Hashed value
+     */
+    private static long murmur64(long h) {
+        h ^= h >>> 33;
+        h *= 0xff51afd7ed558ccdL;
+        h ^= h >>> 33;
+        h *= 0xc4ceb9fe1a85ec53L;
+        h ^= h >>> 33;
+        return h;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/simplex/OpenSimplex2SSampler.java

@@ -0,0 +1,266 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.simplex;
+
+/**
+ * NoiseSampler implementation to provide OpenSimplex2 (Smooth Variant) noise.
+ */
+public class OpenSimplex2SSampler extends SimplexStyleSampler {
+    public OpenSimplex2SSampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    @SuppressWarnings("NumericOverflow")
+    public double getNoiseRaw(int seed, double x, double y) {
+        // 2D OpenSimplex2S case is a modified 2D simplex noise.
+
+        final double SQRT3 = 1.7320508075688772935274463415059;
+        final double G2 = (3 - SQRT3) / 6;
+
+        final double F2 = 0.5f * (SQRT3 - 1);
+        double s = (x + y) * F2;
+        x += s;
+        y += s;
+
+
+        int i = fastFloor(x);
+        int j = fastFloor(y);
+        double xi = x - i;
+        double yi = y - j;
+
+        i *= PRIME_X;
+        j *= PRIME_Y;
+        int i1 = i + PRIME_X;
+        int j1 = j + PRIME_Y;
+
+        double t = (xi + yi) * G2;
+        double x0 = xi - t;
+        double y0 = yi - t;
+
+        double a0 = (2.0 / 3.0) - x0 * x0 - y0 * y0;
+        double value = (a0 * a0) * (a0 * a0) * gradCoord(seed, i, j, x0, y0);
+
+        double a1 = 2 * (1 - 2 * G2) * (1 / G2 - 2) * t + ((-2 * (1 - 2 * G2) * (1 - 2 * G2)) + a0);
+        double x1 = x0 - (1 - 2 * G2);
+        double y1 = y0 - (1 - 2 * G2);
+        value += (a1 * a1) * (a1 * a1) * gradCoord(seed, i1, j1, x1, y1);
+
+        // Nested conditionals were faster than compact bit logic/arithmetic.
+        double xmyi = xi - yi;
+        if(t > G2) {
+            if(xi + xmyi > 1) {
+                double x2 = x0 + (3 * G2 - 2);
+                double y2 = y0 + (3 * G2 - 1);
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i + (PRIME_X << 1), j + PRIME_Y, x2, y2);
+                }
+            } else {
+                double x2 = x0 + G2;
+                double y2 = y0 + (G2 - 1);
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i, j + PRIME_Y, x2, y2);
+                }
+            }
+
+            if(yi - xmyi > 1) {
+                double x3 = x0 + (3 * G2 - 1);
+                double y3 = y0 + (3 * G2 - 2);
+                double a3 = (2.0 / 3.0) - x3 * x3 - y3 * y3;
+                if(a3 > 0) {
+                    value += (a3 * a3) * (a3 * a3) * gradCoord(seed, i + PRIME_X, j + (PRIME_Y << 1), x3, y3);
+                }
+            } else {
+                double x3 = x0 + (G2 - 1);
+                double y3 = y0 + G2;
+                double a3 = (2.0 / 3.0) - x3 * x3 - y3 * y3;
+                if(a3 > 0) {
+                    value += (a3 * a3) * (a3 * a3) * gradCoord(seed, i + PRIME_X, j, x3, y3);
+                }
+            }
+        } else {
+            if(xi + xmyi < 0) {
+                double x2 = x0 + (1 - G2);
+                double y2 = y0 - G2;
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i - PRIME_X, j, x2, y2);
+                }
+            } else {
+                double x2 = x0 + (G2 - 1);
+                double y2 = y0 + G2;
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i + PRIME_X, j, x2, y2);
+                }
+            }
+
+            if(yi < xmyi) {
+                double x2 = x0 - G2;
+                double y2 = y0 - (G2 - 1);
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i, j - PRIME_Y, x2, y2);
+                }
+            } else {
+                double x2 = x0 + G2;
+                double y2 = y0 + (G2 - 1);
+                double a2 = (2.0 / 3.0) - x2 * x2 - y2 * y2;
+                if(a2 > 0) {
+                    value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i, j + PRIME_Y, x2, y2);
+                }
+            }
+        }
+
+        return value * 18.24196194486065;
+    }
+
+    @Override
+    @SuppressWarnings("NumericOverflow")
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        // 3D OpenSimplex2S case uses two offset rotated cube grids.
+        final double R3 = (2.0 / 3.0);
+        double r = (x + y + z) * R3; // Rotation, not skew
+        x = r - x;
+        y = r - y;
+        z = r - z;
+
+
+        int i = fastFloor(x);
+        int j = fastFloor(y);
+        int k = fastFloor(z);
+        double xi = x - i;
+        double yi = y - j;
+        double zi = z - k;
+
+        i *= PRIME_X;
+        j *= PRIME_Y;
+        k *= PRIME_Z;
+        int seed2 = seed + 1293373;
+
+        int xNMask = (int) (-0.5 - xi);
+        int yNMask = (int) (-0.5 - yi);
+        int zNMask = (int) (-0.5 - zi);
+
+        double x0 = xi + xNMask;
+        double y0 = yi + yNMask;
+        double z0 = zi + zNMask;
+        double a0 = 0.75 - x0 * x0 - y0 * y0 - z0 * z0;
+        double value = (a0 * a0) * (a0 * a0) * gradCoord(seed, i + (xNMask & PRIME_X), j + (yNMask & PRIME_Y), k + (zNMask & PRIME_Z), x0, y0,
+                z0);
+
+        double x1 = xi - 0.5;
+        double y1 = yi - 0.5;
+        double z1 = zi - 0.5;
+        double a1 = 0.75 - x1 * x1 - y1 * y1 - z1 * z1;
+        value += (a1 * a1) * (a1 * a1) * gradCoord(seed2, i + PRIME_X, j + PRIME_Y, k + PRIME_Z, x1, y1, z1);
+
+        double xAFlipMask0 = ((xNMask | 1) << 1) * x1;
+        double yAFlipMask0 = ((yNMask | 1) << 1) * y1;
+        double zAFlipMask0 = ((zNMask | 1) << 1) * z1;
+        double xAFlipMask1 = (-2 - (xNMask << 2)) * x1 - 1.0;
+        double yAFlipMask1 = (-2 - (yNMask << 2)) * y1 - 1.0;
+        double zAFlipMask1 = (-2 - (zNMask << 2)) * z1 - 1.0;
+
+        boolean skip5 = false;
+        double a2 = xAFlipMask0 + a0;
+        if(a2 > 0) {
+            double x2 = x0 - (xNMask | 1);
+            value += (a2 * a2) * (a2 * a2) * gradCoord(seed, i + (~xNMask & PRIME_X), j + (yNMask & PRIME_Y), k + (zNMask & PRIME_Z), x2, y0,
+                    z0);
+        } else {
+            double a3 = yAFlipMask0 + zAFlipMask0 + a0;
+            if(a3 > 0) {
+                double y3 = y0 - (yNMask | 1);
+                double z3 = z0 - (zNMask | 1);
+                value += (a3 * a3) * (a3 * a3) * gradCoord(seed, i + (xNMask & PRIME_X), j + (~yNMask & PRIME_Y), k + (~zNMask & PRIME_Z), x0,
+                        y3, z3);
+            }
+
+            double a4 = xAFlipMask1 + a1;
+            if(a4 > 0) {
+                double x4 = (xNMask | 1) + x1;
+                value += (a4 * a4) * (a4 * a4) * gradCoord(seed2, i + (xNMask & (PRIME_X << 1)), j + PRIME_Y, k + PRIME_Z, x4, y1, z1);
+                skip5 = true;
+            }
+        }
+
+        boolean skip9 = false;
+        double a6 = yAFlipMask0 + a0;
+        if(a6 > 0) {
+            double y6 = y0 - (yNMask | 1);
+            value += (a6 * a6) * (a6 * a6) * gradCoord(seed, i + (xNMask & PRIME_X), j + (~yNMask & PRIME_Y), k + (zNMask & PRIME_Z), x0, y6,
+                    z0);
+        } else {
+            double a7 = xAFlipMask0 + zAFlipMask0 + a0;
+            if(a7 > 0) {
+                double x7 = x0 - (xNMask | 1);
+                double z7 = z0 - (zNMask | 1);
+                value += (a7 * a7) * (a7 * a7) * gradCoord(seed, i + (~xNMask & PRIME_X), j + (yNMask & PRIME_Y), k + (~zNMask & PRIME_Z), x7,
+                        y0, z7);
+            }
+
+            double a8 = yAFlipMask1 + a1;
+            if(a8 > 0) {
+                double y8 = (yNMask | 1) + y1;
+                value += (a8 * a8) * (a8 * a8) * gradCoord(seed2, i + PRIME_X, j + (yNMask & (PRIME_Y << 1)), k + PRIME_Z, x1, y8, z1);
+                skip9 = true;
+            }
+        }
+
+        boolean skipD = false;
+        double aA = zAFlipMask0 + a0;
+        if(aA > 0) {
+            double zA = z0 - (zNMask | 1);
+            value += (aA * aA) * (aA * aA) * gradCoord(seed, i + (xNMask & PRIME_X), j + (yNMask & PRIME_Y), k + (~zNMask & PRIME_Z), x0, y0,
+                    zA);
+        } else {
+            double aB = xAFlipMask0 + yAFlipMask0 + a0;
+            if(aB > 0) {
+                double xB = x0 - (xNMask | 1);
+                double yB = y0 - (yNMask | 1);
+                value += (aB * aB) * (aB * aB) * gradCoord(seed, i + (~xNMask & PRIME_X), j + (~yNMask & PRIME_Y), k + (zNMask & PRIME_Z), xB,
+                        yB, z0);
+            }
+
+            double aC = zAFlipMask1 + a1;
+            if(aC > 0) {
+                double zC = (zNMask | 1) + z1;
+                value += (aC * aC) * (aC * aC) * gradCoord(seed2, i + PRIME_X, j + PRIME_Y, k + (zNMask & (PRIME_Z << 1)), x1, y1, zC);
+                skipD = true;
+            }
+        }
+
+        if(!skip5) {
+            double a5 = yAFlipMask1 + zAFlipMask1 + a1;
+            if(a5 > 0) {
+                double y5 = (yNMask | 1) + y1;
+                double z5 = (zNMask | 1) + z1;
+                value += (a5 * a5) * (a5 * a5) * gradCoord(seed2, i + PRIME_X, j + (yNMask & (PRIME_Y << 1)), k + (zNMask & (PRIME_Z << 1)),
+                        x1, y5, z5);
+            }
+        }
+
+        if(!skip9) {
+            double a9 = xAFlipMask1 + zAFlipMask1 + a1;
+            if(a9 > 0) {
+                double x9 = (xNMask | 1) + x1;
+                double z9 = (zNMask | 1) + z1;
+                value += (a9 * a9) * (a9 * a9) * gradCoord(seed2, i + (xNMask & (PRIME_X << 1)), j + PRIME_Y, k + (zNMask & (PRIME_Z << 1)), x9,
+                        y1, z9);
+            }
+        }
+
+        if(!skipD) {
+            double aD = xAFlipMask1 + yAFlipMask1 + a1;
+            if(aD > 0) {
+                double xD = (xNMask | 1) + x1;
+                double yD = (yNMask | 1) + y1;
+                value += (aD * aD) * (aD * aD) * gradCoord(seed2, i + (xNMask & (PRIME_X << 1)), j + (yNMask & (PRIME_Y << 1)), k + PRIME_Z,
+                        xD, yD, z1);
+            }
+        }
+
+        return value * 9.046026385208288;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/simplex/OpenSimplex2Sampler.java

@@ -0,0 +1,155 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.simplex;
+
+/**
+ * NoiseSampler implementation to provide OpenSimplex2 noise.
+ */
+public class OpenSimplex2Sampler extends SimplexStyleSampler {
+    private static final double SQRT3 = 1.7320508075688772935274463415059;
+
+    public OpenSimplex2Sampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        // 2D OpenSimplex2 case uses the same algorithm as ordinary Simplex.
+        final double G2 = (3 - SQRT3) / 6;
+
+        final double F2 = 0.5f * (SQRT3 - 1);
+        double s = (x + y) * F2;
+        x += s;
+        y += s;
+
+
+        int i = fastFloor(x);
+        int j = fastFloor(y);
+        double xi = x - i;
+        double yi = y - j;
+
+        double t = (xi + yi) * G2;
+        double x0 = xi - t;
+        double y0 = yi - t;
+
+        i *= PRIME_X;
+        j *= PRIME_Y;
+
+        double n0, n1, n2;
+
+        double a = 0.5 - x0 * x0 - y0 * y0;
+        if(a <= 0) n0 = 0;
+        else {
+            n0 = (a * a) * (a * a) * gradCoord(seed, i, j, x0, y0);
+        }
+
+        double c = 2 * (1 - 2 * G2) * (1 / G2 - 2) * t + ((-2 * (1 - 2 * G2) * (1 - 2 * G2)) + a);
+        if(c <= 0) n2 = 0;
+        else {
+            double x2 = x0 + (2 * G2 - 1);
+            double y2 = y0 + (2 * G2 - 1);
+            n2 = (c * c) * (c * c) * gradCoord(seed, i + PRIME_X, j + PRIME_Y, x2, y2);
+        }
+
+        if(y0 > x0) {
+            double x1 = x0 + G2;
+            double y1 = y0 + (G2 - 1);
+            double b = 0.5 - x1 * x1 - y1 * y1;
+            if(b <= 0) n1 = 0;
+            else {
+                n1 = (b * b) * (b * b) * gradCoord(seed, i, j + PRIME_Y, x1, y1);
+            }
+        } else {
+            double x1 = x0 + (G2 - 1);
+            double y1 = y0 + G2;
+            double b = 0.5 - x1 * x1 - y1 * y1;
+            if(b <= 0) n1 = 0;
+            else {
+                n1 = (b * b) * (b * b) * gradCoord(seed, i + PRIME_X, j, x1, y1);
+            }
+        }
+
+        return (n0 + n1 + n2) * 99.83685446303647f;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        // 3D OpenSimplex2Sampler case uses two offset rotated cube grids.
+        final double R3 = (2.0 / 3.0);
+        double r = (x + y + z) * R3; // Rotation, not skew
+        x = r - x;
+        y = r - y;
+        z = r - z;
+
+
+        int i = fastRound(x);
+        int j = fastRound(y);
+        int k = fastRound(z);
+        double x0 = x - i;
+        double y0 = y - j;
+        double z0 = z - k;
+
+        int xNSign = (int) (-1.0 - x0) | 1;
+        int yNSign = (int) (-1.0 - y0) | 1;
+        int zNSign = (int) (-1.0 - z0) | 1;
+
+        double ax0 = xNSign * -x0;
+        double ay0 = yNSign * -y0;
+        double az0 = zNSign * -z0;
+
+        i *= PRIME_X;
+        j *= PRIME_Y;
+        k *= PRIME_Z;
+
+        double value = 0;
+        double a = (0.6f - x0 * x0) - (y0 * y0 + z0 * z0);
+
+        for(int l = 0; ; l++) {
+            if(a > 0) {
+                value += (a * a) * (a * a) * gradCoord(seed, i, j, k, x0, y0, z0);
+            }
+
+            if(ax0 >= ay0 && ax0 >= az0) {
+                double b = a + ax0 + ax0;
+                if(b > 1) {
+                    b -= 1;
+                    value += (b * b) * (b * b) * gradCoord(seed, i - xNSign * PRIME_X, j, k, x0 + xNSign, y0, z0);
+                }
+            } else if(ay0 > ax0 && ay0 >= az0) {
+                double b = a + ay0 + ay0;
+                if(b > 1) {
+                    b -= 1;
+                    value += (b * b) * (b * b) * gradCoord(seed, i, j - yNSign * PRIME_Y, k, x0, y0 + yNSign, z0);
+                }
+            } else {
+                double b = a + az0 + az0;
+                if(b > 1) {
+                    b -= 1;
+                    value += (b * b) * (b * b) * gradCoord(seed, i, j, k - zNSign * PRIME_Z, x0, y0, z0 + zNSign);
+                }
+            }
+
+            if(l == 1) break;
+
+            ax0 = 0.5 - ax0;
+            ay0 = 0.5 - ay0;
+            az0 = 0.5 - az0;
+
+            x0 = xNSign * ax0;
+            y0 = yNSign * ay0;
+            z0 = zNSign * az0;
+
+            a += (0.75 - ax0) - (ay0 + az0);
+
+            i += (xNSign >> 1) & PRIME_X;
+            j += (yNSign >> 1) & PRIME_Y;
+            k += (zNSign >> 1) & PRIME_Z;
+
+            xNSign = -xNSign;
+            yNSign = -yNSign;
+            zNSign = -zNSign;
+
+            seed = ~seed;
+        }
+
+        return value * 32.69428253173828125;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/simplex/PerlinSampler.java

@@ -0,0 +1,69 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.simplex;
+
+/**
+ * NoiseSampler implementation to provide Perlin Noise.
+ */
+public class PerlinSampler extends SimplexStyleSampler {
+    public PerlinSampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        int x0 = fastFloor(x);
+        int y0 = fastFloor(y);
+
+        double xd0 = x - x0;
+        double yd0 = y - y0;
+        double xd1 = xd0 - 1;
+        double yd1 = yd0 - 1;
+
+        double xs = interpQuintic(xd0);
+        double ys = interpQuintic(yd0);
+
+        x0 *= PRIME_X;
+        y0 *= PRIME_Y;
+        int x1 = x0 + PRIME_X;
+        int y1 = y0 + PRIME_Y;
+
+        double xf0 = lerp(gradCoord(seed, x0, y0, xd0, yd0), gradCoord(seed, x1, y0, xd1, yd0), xs);
+        double xf1 = lerp(gradCoord(seed, x0, y1, xd0, yd1), gradCoord(seed, x1, y1, xd1, yd1), xs);
+
+        return lerp(xf0, xf1, ys) * 1.4247691104677813;
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        int x0 = fastFloor(x);
+        int y0 = fastFloor(y);
+        int z0 = fastFloor(z);
+
+        double xd0 = x - x0;
+        double yd0 = y - y0;
+        double zd0 = z - z0;
+        double xd1 = xd0 - 1;
+        double yd1 = yd0 - 1;
+        double zd1 = zd0 - 1;
+
+        double xs = interpQuintic(xd0);
+        double ys = interpQuintic(yd0);
+        double zs = interpQuintic(zd0);
+
+        x0 *= PRIME_X;
+        y0 *= PRIME_Y;
+        z0 *= PRIME_Z;
+        int x1 = x0 + PRIME_X;
+        int y1 = y0 + PRIME_Y;
+        int z1 = z0 + PRIME_Z;
+
+        double xf00 = lerp(gradCoord(seed, x0, y0, z0, xd0, yd0, zd0), gradCoord(seed, x1, y0, z0, xd1, yd0, zd0), xs);
+        double xf10 = lerp(gradCoord(seed, x0, y1, z0, xd0, yd1, zd0), gradCoord(seed, x1, y1, z0, xd1, yd1, zd0), xs);
+        double xf01 = lerp(gradCoord(seed, x0, y0, z1, xd0, yd0, zd1), gradCoord(seed, x1, y0, z1, xd1, yd0, zd1), xs);
+        double xf11 = lerp(gradCoord(seed, x0, y1, z1, xd0, yd1, zd1), gradCoord(seed, x1, y1, z1, xd1, yd1, zd1), xs);
+
+        double yf0 = lerp(xf00, xf10, ys);
+        double yf1 = lerp(xf01, xf11, ys);
+
+        return lerp(yf0, yf1, zs) * 0.964921414852142333984375;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/simplex/SimplexStyleSampler.java

@@ -0,0 +1,100 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.simplex;
+
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+/**
+ * Abstract NoiseSampler implementation for simplex-style noise functions.
+ */
+public abstract class SimplexStyleSampler extends NoiseFunction {
+    protected static final double[] GRADIENTS_2_D = {
+            0.130526192220052d, 0.99144486137381d, 0.38268343236509d, 0.923879532511287d, 0.608761429008721d, 0.793353340291235d,
+            0.793353340291235d, 0.608761429008721d, 0.923879532511287d, 0.38268343236509d, 0.99144486137381d, 0.130526192220051d,
+            0.99144486137381d, -0.130526192220051d, 0.923879532511287d, -0.38268343236509d, 0.793353340291235d, -0.60876142900872d,
+            0.608761429008721d, -0.793353340291235d, 0.38268343236509d, -0.923879532511287d, 0.130526192220052d, -0.99144486137381d,
+            -0.130526192220052d, -0.99144486137381d, -0.38268343236509d, -0.923879532511287d, -0.608761429008721d, -0.793353340291235d,
+            -0.793353340291235d, -0.608761429008721d, -0.923879532511287d, -0.38268343236509d, -0.99144486137381d, -0.130526192220052d,
+            -0.99144486137381d, 0.130526192220051d, -0.923879532511287d, 0.38268343236509d, -0.793353340291235d, 0.608761429008721d,
+            -0.608761429008721d, 0.793353340291235d, -0.38268343236509d, 0.923879532511287d, -0.130526192220052d, 0.99144486137381d,
+            0.130526192220052d, 0.99144486137381d, 0.38268343236509d, 0.923879532511287d, 0.608761429008721d, 0.793353340291235d,
+            0.793353340291235d, 0.608761429008721d, 0.923879532511287d, 0.38268343236509d, 0.99144486137381d, 0.130526192220051d,
+            0.99144486137381d, -0.130526192220051d, 0.923879532511287d, -0.38268343236509d, 0.793353340291235d, -0.60876142900872d,
+            0.608761429008721d, -0.793353340291235d, 0.38268343236509d, -0.923879532511287d, 0.130526192220052d, -0.99144486137381d,
+            -0.130526192220052d, -0.99144486137381d, -0.38268343236509d, -0.923879532511287d, -0.608761429008721d, -0.793353340291235d,
+            -0.793353340291235d, -0.608761429008721d, -0.923879532511287d, -0.38268343236509d, -0.99144486137381d, -0.130526192220052d,
+            -0.99144486137381d, 0.130526192220051d, -0.923879532511287d, 0.38268343236509d, -0.793353340291235d, 0.608761429008721d,
+            -0.608761429008721d, 0.793353340291235d, -0.38268343236509d, 0.923879532511287d, -0.130526192220052d, 0.99144486137381d,
+            0.130526192220052d, 0.99144486137381d, 0.38268343236509d, 0.923879532511287d, 0.608761429008721d, 0.793353340291235d,
+            0.793353340291235d, 0.608761429008721d, 0.923879532511287d, 0.38268343236509d, 0.99144486137381d, 0.130526192220051d,
+            0.99144486137381d, -0.130526192220051d, 0.923879532511287d, -0.38268343236509d, 0.793353340291235d, -0.60876142900872d,
+            0.608761429008721d, -0.793353340291235d, 0.38268343236509d, -0.923879532511287d, 0.130526192220052d, -0.99144486137381d,
+            -0.130526192220052d, -0.99144486137381d, -0.38268343236509d, -0.923879532511287d, -0.608761429008721d, -0.793353340291235d,
+            -0.793353340291235d, -0.608761429008721d, -0.923879532511287d, -0.38268343236509d, -0.99144486137381d, -0.130526192220052d,
+            -0.99144486137381d, 0.130526192220051d, -0.923879532511287d, 0.38268343236509d, -0.793353340291235d, 0.608761429008721d,
+            -0.608761429008721d, 0.793353340291235d, -0.38268343236509d, 0.923879532511287d, -0.130526192220052d, 0.99144486137381d,
+            0.130526192220052d, 0.99144486137381d, 0.38268343236509d, 0.923879532511287d, 0.608761429008721d, 0.793353340291235d,
+            0.793353340291235d, 0.608761429008721d, 0.923879532511287d, 0.38268343236509d, 0.99144486137381d, 0.130526192220051d,
+            0.99144486137381d, -0.130526192220051d, 0.923879532511287d, -0.38268343236509d, 0.793353340291235d, -0.60876142900872d,
+            0.608761429008721d, -0.793353340291235d, 0.38268343236509d, -0.923879532511287d, 0.130526192220052d, -0.99144486137381d,
+            -0.130526192220052d, -0.99144486137381d, -0.38268343236509d, -0.923879532511287d, -0.608761429008721d, -0.793353340291235d,
+            -0.793353340291235d, -0.608761429008721d, -0.923879532511287d, -0.38268343236509d, -0.99144486137381d, -0.130526192220052d,
+            -0.99144486137381d, 0.130526192220051d, -0.923879532511287d, 0.38268343236509d, -0.793353340291235d, 0.608761429008721d,
+            -0.608761429008721d, 0.793353340291235d, -0.38268343236509d, 0.923879532511287d, -0.130526192220052d, 0.99144486137381d,
+            0.130526192220052d, 0.99144486137381d, 0.38268343236509d, 0.923879532511287d, 0.608761429008721d, 0.793353340291235d,
+            0.793353340291235d, 0.608761429008721d, 0.923879532511287d, 0.38268343236509d, 0.99144486137381d, 0.130526192220051d,
+            0.99144486137381d, -0.130526192220051d, 0.923879532511287d, -0.38268343236509d, 0.793353340291235d, -0.60876142900872d,
+            0.608761429008721d, -0.793353340291235d, 0.38268343236509d, -0.923879532511287d, 0.130526192220052d, -0.99144486137381d,
+            -0.130526192220052d, -0.99144486137381d, -0.38268343236509d, -0.923879532511287d, -0.608761429008721d, -0.793353340291235d,
+            -0.793353340291235d, -0.608761429008721d, -0.923879532511287d, -0.38268343236509d, -0.99144486137381d, -0.130526192220052d,
+            -0.99144486137381d, 0.130526192220051d, -0.923879532511287d, 0.38268343236509d, -0.793353340291235d, 0.608761429008721d,
+            -0.608761429008721d, 0.793353340291235d, -0.38268343236509d, 0.923879532511287d, -0.130526192220052d, 0.99144486137381d,
+            0.38268343236509d, 0.923879532511287d, 0.923879532511287d, 0.38268343236509d, 0.923879532511287d, -0.38268343236509d,
+            0.38268343236509d, -0.923879532511287d, -0.38268343236509d, -0.923879532511287d, -0.923879532511287d, -0.38268343236509d,
+            -0.923879532511287d, 0.38268343236509d, -0.38268343236509d, 0.923879532511287d,
+    };
+
+    protected static final double[] GRADIENTS_3D = {
+            0, 1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0,
+            1, 0, 1, 0, -1, 0, 1, 0, 1, 0, -1, 0, -1, 0, -1, 0,
+            1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0,
+            0, 1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0,
+            1, 0, 1, 0, -1, 0, 1, 0, 1, 0, -1, 0, -1, 0, -1, 0,
+            1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0,
+            0, 1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0,
+            1, 0, 1, 0, -1, 0, 1, 0, 1, 0, -1, 0, -1, 0, -1, 0,
+            1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0,
+            0, 1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0,
+            1, 0, 1, 0, -1, 0, 1, 0, 1, 0, -1, 0, -1, 0, -1, 0,
+            1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0,
+            0, 1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0,
+            1, 0, 1, 0, -1, 0, 1, 0, 1, 0, -1, 0, -1, 0, -1, 0,
+            1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 0, 0, -1, -1, 0, 0,
+            1, 1, 0, 0, 0, -1, 1, 0, -1, 1, 0, 0, 0, -1, -1, 0
+    };
+
+    public SimplexStyleSampler(int seed) {
+        super(seed);
+    }
+
+    protected static double gradCoord(int seed, int xPrimed, int yPrimed, double xd, double yd) {
+        int hash = hash(seed, xPrimed, yPrimed);
+        hash ^= hash >> 15;
+        hash &= 127 << 1;
+
+        double xg = GRADIENTS_2_D[hash];
+        double yg = GRADIENTS_2_D[hash | 1];
+
+        return xd * xg + yd * yg;
+    }
+
+    protected static double gradCoord(int seed, int xPrimed, int yPrimed, int zPrimed, double xd, double yd, double zd) {
+        int hash = hash(seed, xPrimed, yPrimed, zPrimed);
+        hash ^= hash >> 15;
+        hash &= 63 << 2;
+
+        double xg = GRADIENTS_3D[hash];
+        double yg = GRADIENTS_3D[hash | 1];
+        double zg = GRADIENTS_3D[hash | 2];
+
+        return xd * xg + yd * yg + zd * zg;
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/value/ValueCubicSampler.java

@@ -0,0 +1,104 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.value;
+
+public class ValueCubicSampler extends ValueStyleNoise {
+    public ValueCubicSampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        int x1 = fastFloor(x);
+        int y1 = fastFloor(y);
+
+        double xs = x - x1;
+        double ys = y - y1;
+
+        x1 *= PRIME_X;
+        y1 *= PRIME_Y;
+        int x0 = x1 - PRIME_X;
+        int y0 = y1 - PRIME_Y;
+        int x2 = x1 + PRIME_X;
+        int y2 = y1 + PRIME_Y;
+        int x3 = x1 + (PRIME_X << 1);
+        int y3 = y1 + (PRIME_Y << 1);
+
+        return cubicLerp(
+                cubicLerp(valCoord(seed, x0, y0), valCoord(seed, x1, y0), valCoord(seed, x2, y0), valCoord(seed, x3, y0),
+                        xs),
+                cubicLerp(valCoord(seed, x0, y1), valCoord(seed, x1, y1), valCoord(seed, x2, y1), valCoord(seed, x3, y1),
+                        xs),
+                cubicLerp(valCoord(seed, x0, y2), valCoord(seed, x1, y2), valCoord(seed, x2, y2), valCoord(seed, x3, y2),
+                        xs),
+                cubicLerp(valCoord(seed, x0, y3), valCoord(seed, x1, y3), valCoord(seed, x2, y3), valCoord(seed, x3, y3),
+                        xs),
+                ys) * (1 / (1.5 * 1.5));
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        int x1 = fastFloor(x);
+        int y1 = fastFloor(y);
+        int z1 = fastFloor(z);
+
+        double xs = x - x1;
+        double ys = y - y1;
+        double zs = z - z1;
+
+        x1 *= PRIME_X;
+        y1 *= PRIME_Y;
+        z1 *= PRIME_Z;
+
+        int x0 = x1 - PRIME_X;
+        int y0 = y1 - PRIME_Y;
+        int z0 = z1 - PRIME_Z;
+        int x2 = x1 + PRIME_X;
+        int y2 = y1 + PRIME_Y;
+        int z2 = z1 + PRIME_Z;
+        int x3 = x1 + (PRIME_X << 1);
+        int y3 = y1 + (PRIME_Y << 1);
+        int z3 = z1 + (PRIME_Z << 1);
+
+        return cubicLerp(
+                cubicLerp(
+                        cubicLerp(valCoord(seed, x0, y0, z0), valCoord(seed, x1, y0, z0), valCoord(seed, x2, y0, z0),
+                                valCoord(seed, x3, y0, z0), xs),
+                        cubicLerp(valCoord(seed, x0, y1, z0), valCoord(seed, x1, y1, z0), valCoord(seed, x2, y1, z0),
+                                valCoord(seed, x3, y1, z0), xs),
+                        cubicLerp(valCoord(seed, x0, y2, z0), valCoord(seed, x1, y2, z0), valCoord(seed, x2, y2, z0),
+                                valCoord(seed, x3, y2, z0), xs),
+                        cubicLerp(valCoord(seed, x0, y3, z0), valCoord(seed, x1, y3, z0), valCoord(seed, x2, y3, z0),
+                                valCoord(seed, x3, y3, z0), xs),
+                        ys),
+                cubicLerp(
+                        cubicLerp(valCoord(seed, x0, y0, z1), valCoord(seed, x1, y0, z1), valCoord(seed, x2, y0, z1),
+                                valCoord(seed, x3, y0, z1), xs),
+                        cubicLerp(valCoord(seed, x0, y1, z1), valCoord(seed, x1, y1, z1), valCoord(seed, x2, y1, z1),
+                                valCoord(seed, x3, y1, z1), xs),
+                        cubicLerp(valCoord(seed, x0, y2, z1), valCoord(seed, x1, y2, z1), valCoord(seed, x2, y2, z1),
+                                valCoord(seed, x3, y2, z1), xs),
+                        cubicLerp(valCoord(seed, x0, y3, z1), valCoord(seed, x1, y3, z1), valCoord(seed, x2, y3, z1),
+                                valCoord(seed, x3, y3, z1), xs),
+                        ys),
+                cubicLerp(
+                        cubicLerp(valCoord(seed, x0, y0, z2), valCoord(seed, x1, y0, z2), valCoord(seed, x2, y0, z2),
+                                valCoord(seed, x3, y0, z2), xs),
+                        cubicLerp(valCoord(seed, x0, y1, z2), valCoord(seed, x1, y1, z2), valCoord(seed, x2, y1, z2),
+                                valCoord(seed, x3, y1, z2), xs),
+                        cubicLerp(valCoord(seed, x0, y2, z2), valCoord(seed, x1, y2, z2), valCoord(seed, x2, y2, z2),
+                                valCoord(seed, x3, y2, z2), xs),
+                        cubicLerp(valCoord(seed, x0, y3, z2), valCoord(seed, x1, y3, z2), valCoord(seed, x2, y3, z2),
+                                valCoord(seed, x3, y3, z2), xs),
+                        ys),
+                cubicLerp(
+                        cubicLerp(valCoord(seed, x0, y0, z3), valCoord(seed, x1, y0, z3), valCoord(seed, x2, y0, z3),
+                                valCoord(seed, x3, y0, z3), xs),
+                        cubicLerp(valCoord(seed, x0, y1, z3), valCoord(seed, x1, y1, z3), valCoord(seed, x2, y1, z3),
+                                valCoord(seed, x3, y1, z3), xs),
+                        cubicLerp(valCoord(seed, x0, y2, z3), valCoord(seed, x1, y2, z3), valCoord(seed, x2, y2, z3),
+                                valCoord(seed, x3, y2, z3), xs),
+                        cubicLerp(valCoord(seed, x0, y3, z3), valCoord(seed, x1, y3, z3), valCoord(seed, x2, y3, z3),
+                                valCoord(seed, x3, y3, z3), xs),
+                        ys),
+                zs) * (1 / (1.5 * 1.5 * 1.5));
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/value/ValueSampler.java

@@ -0,0 +1,54 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.value;
+
+public class ValueSampler extends ValueStyleNoise {
+    public ValueSampler(int seed) {
+        super(seed);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y) {
+        int x0 = fastFloor(x);
+        int y0 = fastFloor(y);
+
+        double xs = interpHermite(x - x0);
+        double ys = interpHermite(y - y0);
+
+        x0 *= PRIME_X;
+        y0 *= PRIME_Y;
+        int x1 = x0 + PRIME_X;
+        int y1 = y0 + PRIME_Y;
+
+        double xf0 = lerp(valCoord(seed, x0, y0), valCoord(seed, x1, y0), xs);
+        double xf1 = lerp(valCoord(seed, x0, y1), valCoord(seed, x1, y1), xs);
+
+        return lerp(xf0, xf1, ys);
+    }
+
+    @Override
+    public double getNoiseRaw(int seed, double x, double y, double z) {
+        int x0 = fastFloor(x);
+        int y0 = fastFloor(y);
+        int z0 = fastFloor(z);
+
+        double xs = interpHermite(x - x0);
+        double ys = interpHermite(y - y0);
+        double zs = interpHermite(z - z0);
+
+        x0 *= PRIME_X;
+        y0 *= PRIME_Y;
+        z0 *= PRIME_Z;
+        int x1 = x0 + PRIME_X;
+        int y1 = y0 + PRIME_Y;
+        int z1 = z0 + PRIME_Z;
+
+        double xf00 = lerp(valCoord(seed, x0, y0, z0), valCoord(seed, x1, y0, z0), xs);
+        double xf10 = lerp(valCoord(seed, x0, y1, z0), valCoord(seed, x1, y1, z0), xs);
+        double xf01 = lerp(valCoord(seed, x0, y0, z1), valCoord(seed, x1, y0, z1), xs);
+        double xf11 = lerp(valCoord(seed, x0, y1, z1), valCoord(seed, x1, y1, z1), xs);
+
+        double yf0 = lerp(xf00, xf10, ys);
+        double yf1 = lerp(xf01, xf11, ys);
+
+        return lerp(yf0, yf1, zs);
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/noise/samplers/noise/value/ValueStyleNoise.java

@@ -0,0 +1,25 @@
+package com.dfsek.terra.api.math.noise.samplers.noise.value;
+
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+public abstract class ValueStyleNoise extends NoiseFunction {
+    public ValueStyleNoise(int seed) {
+        super(seed);
+    }
+
+    protected static double valCoord(int seed, int xPrimed, int yPrimed) {
+        int hash = hash(seed, xPrimed, yPrimed);
+
+        hash *= hash;
+        hash ^= hash << 19;
+        return hash * (1 / 2147483648.0);
+    }
+
+    protected static double valCoord(int seed, int xPrimed, int yPrimed, int zPrimed) {
+        int hash = hash(seed, xPrimed, yPrimed, zPrimed);
+
+        hash *= hash;
+        hash ^= hash << 19;
+        return hash * (1 / 2147483648.0);
+    }
+}

common/src/main/java/com/dfsek/terra/api/math/paralithic/BlankFunction.java

@@ -1,4 +1,4 @@
-package com.dfsek.terra.api.math.parsii;
+package com.dfsek.terra.api.math.paralithic;
 
 
 import com.dfsek.paralithic.functions.dynamic.DynamicFunction;

common/src/main/java/com/dfsek/terra/api/math/paralithic/defined/UserDefinedFunction.java

@@ -1,4 +1,4 @@
-package com.dfsek.terra.api.math.parsii.defined;
+package com.dfsek.terra.api.math.paralithic.defined;
 
 import com.dfsek.paralithic.Expression;
 import com.dfsek.paralithic.eval.parser.Parser;

common/src/main/java/com/dfsek/terra/api/math/paralithic/noise/NoiseFunction.java

@@ -1,4 +1,4 @@
-package com.dfsek.terra.api.math.parsii.noise;
+package com.dfsek.terra.api.math.paralithic.noise;
 
 
 import com.dfsek.paralithic.functions.dynamic.DynamicFunction;

common/src/main/java/com/dfsek/terra/api/math/paralithic/noise/NoiseFunction2.java

@@ -1,4 +1,4 @@
-package com.dfsek.terra.api.math.parsii.noise;
+package com.dfsek.terra.api.math.paralithic.noise;
 
 import com.dfsek.terra.api.math.noise.NoiseSampler;
 import com.dfsek.terra.util.hash.HashMapDoubleDouble;

common/src/main/java/com/dfsek/terra/api/math/paralithic/noise/NoiseFunction3.java

@@ -1,4 +1,4 @@
-package com.dfsek.terra.api.math.parsii.noise;
+package com.dfsek.terra.api.math.paralithic.noise;
 
 import com.dfsek.terra.api.math.noise.NoiseSampler;
 

common/src/main/java/com/dfsek/terra/api/math/vector/Vector2.java

@@ -6,7 +6,6 @@ import net.jafama.FastMath;
 /**
  * oh yeah
  */
-@SuppressWarnings("unused")
 public class Vector2 implements Cloneable {
     private double x;
     private double z;

common/src/main/java/com/dfsek/terra/api/math/vector/Vector3.java

@@ -5,6 +5,9 @@ import com.dfsek.terra.api.platform.world.World;
 import net.jafama.FastMath;
 import org.jetbrains.annotations.NotNull;
 
+/**
+ * 3D Mutable Vector
+ */
 public class Vector3 implements Cloneable {
 
 

common/src/main/java/com/dfsek/terra/api/structures/parser/exceptions/ParseException.java

@@ -3,6 +3,7 @@ package com.dfsek.terra.api.structures.parser.exceptions;
 import com.dfsek.terra.api.structures.tokenizer.Position;
 
 public class ParseException extends Exception {
+    private static final long serialVersionUID = 6744390543046766386L;
     private final Position position;
 
     public ParseException(String message, Position position) {

common/src/main/java/com/dfsek/terra/api/structures/tokenizer/exceptions/EOFException.java

@@ -4,6 +4,8 @@ import com.dfsek.terra.api.structures.tokenizer.Position;
 
 public class EOFException extends TokenizerException {
 
+    private static final long serialVersionUID = 3980047409902809440L;
+
     public EOFException(String message, Position position) {
         super(message, position);
     }

common/src/main/java/com/dfsek/terra/api/structures/tokenizer/exceptions/FormatException.java

@@ -4,6 +4,8 @@ import com.dfsek.terra.api.structures.tokenizer.Position;
 
 public class FormatException extends TokenizerException {
 
+    private static final long serialVersionUID = -791308012940744455L;
+
     public FormatException(String message, Position position) {
         super(message, position);
     }

common/src/main/java/com/dfsek/terra/api/structures/tokenizer/exceptions/TokenizerException.java

@@ -5,6 +5,8 @@ import com.dfsek.terra.api.structures.tokenizer.Position;
 
 public abstract class TokenizerException extends ParseException {
 
+    private static final long serialVersionUID = 2792384010083575420L;
+
     public TokenizerException(String message, Position position) {
         super(message, position);
     }

common/src/main/java/com/dfsek/terra/api/transform/AttemptsFailedException.java

@@ -5,6 +5,7 @@ import com.dfsek.terra.api.util.GlueList;
 import java.util.List;
 
 public class AttemptsFailedException extends RuntimeException {
+    private static final long serialVersionUID = -1160459550006067137L;
     private final List<Throwable> causes;
 
     public AttemptsFailedException(String message, List<Throwable> causes) {

common/src/main/java/com/dfsek/terra/api/transform/TransformException.java

@@ -1,6 +1,8 @@
 package com.dfsek.terra.api.transform;
 
 public class TransformException extends Exception {
+    private static final long serialVersionUID = -6661338369581162084L;
+
     public TransformException() {
         super();
     }

common/src/main/java/com/dfsek/terra/api/transform/Transformer.java

@@ -58,7 +58,7 @@ public class Transformer<F, T> {
             return this;
         }
 
-        public final Transformer<F, T> build() {
+        public Transformer<F, T> build() {
             return new Transformer<>(transforms);
         }
     }

common/src/main/java/com/dfsek/terra/api/util/FastRandom.java

@@ -8,6 +8,7 @@ import java.util.SplittableRandom;
 
 public class FastRandom extends Random {
 
+    private static final long serialVersionUID = 4571946470190183260L;
     private XoRoShiRo128PlusPlus random;
 
     public FastRandom() {

common/src/main/java/com/dfsek/terra/api/util/GlueList.java

@@ -15,6 +15,8 @@
  */
 package com.dfsek.terra.api.util;
 
+import org.jetbrains.annotations.NotNull;
+
 import java.io.IOException;
 import java.io.ObjectInputStream;
 import java.io.ObjectOutputStream;
@@ -76,14 +78,16 @@ import static net.jafama.FastMath.*;
  * @see ArrayList
  * @param <T> the type of elements held in this collection
  */
+@SuppressWarnings({"ManualMinMaxCalculation", "ConstantConditions", "ManualArrayToCollectionCopy"})
 public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable, Serializable {
 
-    transient Node<T> first;
-    transient Node<T> last;
+    private static final long serialVersionUID = -4339173882660322249L;
+    private transient Node<T> first;
+    private transient Node<T> last;
 
-    int size;
+    private int size;
 
-    int initialCapacity;
+    private int initialCapacity;
 
     private static final int DEFAULT_CAPACITY = 10;
 
@@ -236,7 +240,7 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
 
     @SuppressWarnings("unchecked")
     @Override
-    public boolean addAll(Collection<? extends T> c) {
+    public boolean addAll(@NotNull Collection<? extends T> c) {
 
         Objects.requireNonNull(c);
 
@@ -244,7 +248,7 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
 
         int len = collection.length;
 
-        if (len == 0) {
+        if(len == 0) {
             return false;
         }
 
@@ -426,7 +430,6 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
         return indexOf(o) != -1;
     }
 
-    @SuppressWarnings("unchecked")
     @Override
     public T remove(int index) {
 
@@ -499,12 +502,12 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public boolean removeAll(Collection<?> c) {
+    public boolean removeAll(@NotNull Collection<?> c) {
 
         Objects.requireNonNull(c);
 
         Object[] arr = c.toArray();
-        if (arr.length == 0) {
+        if(arr.length == 0) {
             return false;
         }
 
@@ -518,12 +521,12 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public boolean retainAll(Collection<?> c) {
+    public boolean retainAll(@NotNull Collection<?> c) {
 
         Objects.requireNonNull(c);
 
         Object[] arr = c.toArray();
-        if (arr.length == 0) {
+        if(arr.length == 0) {
             return false;
         }
 
@@ -663,7 +666,7 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public List<T> subList(int fromIndex, int toIndex) {
+    public @NotNull List<T> subList(int fromIndex, int toIndex) {
         return super.subList(fromIndex, toIndex);
     }
 
@@ -689,8 +692,8 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
 
     @SuppressWarnings("unchecked")
     @Override
-    public <T> T[] toArray(T[] a) {
-        return (T[]) Arrays.copyOf(toArray(), size, a.getClass());
+    public <E> E[] toArray(E[] a) {
+        return (E[]) Arrays.copyOf(toArray(), size, a.getClass());
     }
 
     public boolean isEmpty() {
@@ -698,7 +701,7 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public Iterator<T> iterator() {
+    public @NotNull Iterator<T> iterator() {
         return new Itr();
     }
 
@@ -736,7 +739,7 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public ListIterator<T> listIterator(int index) {
+    public @NotNull ListIterator<T> listIterator(int index) {
 
         checkPositionIndex(index);
 
@@ -751,89 +754,65 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
     }
 
     @Override
-    public ListIterator<T> listIterator() {
+    public @NotNull ListIterator<T> listIterator() {
         return new ListItr(0);
     }
 
-    private class Itr implements Iterator<T> {
+    protected static class Node<T> {
 
-        Node<T> node = first;
+        protected Node<T> pre;
+        protected Node<T> next;
 
-        int i = 0;//inner-array index
-        int j = 0;//total index -> cursor
+        protected int listSize;
 
-        int lastReturn = -1;
+        protected int startingIndex;
+        protected int endingIndex;
 
-        int expectedModCount = modCount;
-        int elementDataPointer = node.elementDataPointer;
+        protected T[] elementData;
+        protected int elementDataPointer;
 
-        @Override
-        public boolean hasNext() {
-            return j != size;
+        @SuppressWarnings("unchecked")
+        Node(Node<T> pre, Node<T> next, int listSize) {
+            this.pre = pre;
+            this.next = next;
+            this.listSize = listSize;
+            this.elementData = (T[]) new Object[listSize >>> 1];
+            this.startingIndex = listSize;
+            this.endingIndex = listSize + elementData.length - 1;
         }
 
-        @Override
-        public T next() {
-
-            checkForComodification();
-
-            if (j >= size) {
-                throw new NoSuchElementException();
-            }
-
-            if (j >= last.endingIndex + 1) {
-                throw new ConcurrentModificationException();
-            }
-
-            if (j == 0) {// it's for listIterator.when node becomes null.
-                node = first;
-                elementDataPointer = node.elementDataPointer;
-                i = 0;
-            }
-
-            T val = node.elementData[i++];
-
-            if (i >= elementDataPointer) {
-                node = node.next;
-                i = 0;
-                elementDataPointer = (node != null) ? node.elementDataPointer : 0;
-            }
-
-            lastReturn = j++;
-
-            return val;
+        Node(Node<T> pre, Node<T> next, int listSize, int initialCapacity) {
+            this.pre = pre;
+            this.next = next;
+            this.listSize = listSize;
+            this.elementData = createElementData(initialCapacity);
+            this.startingIndex = listSize;
+            this.endingIndex = listSize + elementData.length - 1;
         }
 
-        @Override
-        public void remove() {
+        @SuppressWarnings("unchecked")
+        T[] createElementData(int capacity) {
 
-            if (lastReturn < 0) {
-                throw new IllegalStateException();
-            }
-
-            checkForComodification();
-
-            try {
-                com.dfsek.terra.api.util.GlueList.this.remove(lastReturn);
-
-                j = lastReturn;
-
-                lastReturn = -1;
-
-                i = (--i < 0) ? 0 : i;
-
-                elementDataPointer = (node != null) ? node.elementDataPointer : 0;
-
-                expectedModCount = modCount;
-            } catch (IndexOutOfBoundsException e) {
-                throw new ConcurrentModificationException();
+            if(capacity == 0 || capacity == 1) {
+                return (T[]) new Object[DEFAULT_CAPACITY];
+            } else if(capacity > 1) {
+                return (T[]) new Object[capacity];
+            } else {
+                throw new IllegalArgumentException("Illegal Capacity: " + capacity);
             }
         }
 
-        void checkForComodification() {
-            if (modCount != expectedModCount) {
-                throw new ConcurrentModificationException();
-            }
+        boolean isAddable() {
+            return elementDataPointer < elementData.length;
+        }
+
+        void add(T element) {
+            elementData[elementDataPointer++] = element;
+        }
+
+        @Override
+        public String toString() {
+            return String.format("[sIndex: %d - eIndex: %d | elementDataPointer: %d | elementDataLength: %d]", startingIndex, endingIndex, elementDataPointer, elementData.length);
         }
     }
 
@@ -988,61 +967,85 @@ public class GlueList<T> extends AbstractList<T> implements List<T>, Cloneable,
         }
     }
 
-    static class Node<T> {
+    private class Itr implements Iterator<T> {
 
-        Node<T> pre;
-        Node<T> next;
+        protected Node<T> node = first;
 
-        int listSize;
+        protected int i = 0;//inner-array index
+        protected int j = 0;//total index -> cursor
 
-        int startingIndex;
-        int endingIndex;
+        protected int lastReturn = -1;
 
-        T[] elementData;
-        int elementDataPointer;
+        protected int expectedModCount = modCount;
+        protected int elementDataPointer = node.elementDataPointer;
 
-        @SuppressWarnings("unchecked")
-        Node(Node<T> pre, Node<T> next, int listSize) {
-            this.pre = pre;
-            this.next = next;
-            this.listSize = listSize;
-            this.elementData = (T[]) new Object[listSize >>> 1];
-            this.startingIndex = listSize;
-            this.endingIndex = listSize + elementData.length - 1;
-        }
-
-        Node(Node<T> pre, Node<T> next, int listSize, int initialCapacity) {
-            this.pre = pre;
-            this.next = next;
-            this.listSize = listSize;
-            this.elementData = createElementData(initialCapacity);
-            this.startingIndex = listSize;
-            this.endingIndex = listSize + elementData.length - 1;
-        }
-
-        @SuppressWarnings("unchecked")
-        T[] createElementData(int capacity) {
-
-            if (capacity == 0 || capacity == 1) {
-                return (T[]) new Object[DEFAULT_CAPACITY];
-            } else if (capacity > 1) {
-                return (T[]) new Object[capacity];
-            } else {
-                throw new IllegalArgumentException("Illegal Capacity: " + capacity);
-            }
-        }
-
-        boolean isAddable() {
-            return elementDataPointer < elementData.length;
-        }
-
-        void add(T element) {
-            elementData[elementDataPointer++] = element;
+        @Override
+        public boolean hasNext() {
+            return j != size;
         }
 
         @Override
-        public String toString() {
-            return String.format("[sIndex: %d - eIndex: %d | elementDataPointer: %d | elementDataLength: %d]", startingIndex, endingIndex, elementDataPointer, elementData.length);
+        public T next() {
+
+            checkForComodification();
+
+            if(j >= size) {
+                throw new NoSuchElementException();
+            }
+
+            if(j >= last.endingIndex + 1) {
+                throw new ConcurrentModificationException();
+            }
+
+            if(j == 0) {// it's for listIterator.when node becomes null.
+                node = first;
+                elementDataPointer = node.elementDataPointer;
+                i = 0;
+            }
+
+            T val = node.elementData[i++];
+
+            if(i >= elementDataPointer) {
+                node = node.next;
+                i = 0;
+                elementDataPointer = (node != null) ? node.elementDataPointer : 0;
+            }
+
+            lastReturn = j++;
+
+            return val;
+        }
+
+        @Override
+        public void remove() {
+
+            if(lastReturn < 0) {
+                throw new IllegalStateException();
+            }
+
+            checkForComodification();
+
+            try {
+                com.dfsek.terra.api.util.GlueList.this.remove(lastReturn);
+
+                j = lastReturn;
+
+                lastReturn = -1;
+
+                i = (--i < 0) ? 0 : i;
+
+                elementDataPointer = (node != null) ? node.elementDataPointer : 0;
+
+                expectedModCount = modCount;
+            } catch(IndexOutOfBoundsException e) {
+                throw new ConcurrentModificationException();
+            }
+        }
+
+        void checkForComodification() {
+            if(modCount != expectedModCount) {
+                throw new ConcurrentModificationException();
+            }
         }
     }
 }

common/src/main/java/com/dfsek/terra/api/util/mutable/MutableDouble.java

@@ -1,6 +1,8 @@
 package com.dfsek.terra.api.util.mutable;
 
 public class MutableDouble extends MutableNumber<Double> {
+    private static final long serialVersionUID = -2218110876763640053L;
+
     public MutableDouble(Double value) {
         super(value);
     }

common/src/main/java/com/dfsek/terra/api/util/mutable/MutableInteger.java

@@ -1,6 +1,8 @@
 package com.dfsek.terra.api.util.mutable;
 
 public class MutableInteger extends MutableNumber<Integer> {
+    private static final long serialVersionUID = -4427935901819632745L;
+
     public MutableInteger(Integer value) {
         super(value);
     }

common/src/main/java/com/dfsek/terra/api/util/mutable/MutableNumber.java

@@ -1,6 +1,8 @@
 package com.dfsek.terra.api.util.mutable;
 
 public abstract class MutableNumber<T extends Number> extends Number implements MutablePrimitive<T> {
+
+    private static final long serialVersionUID = 8619508342781664393L;
     protected T value;
 
     public MutableNumber(T value) {

common/src/main/java/com/dfsek/terra/carving/UserDefinedCarver.java

@@ -6,9 +6,9 @@ import com.dfsek.paralithic.eval.parser.Scope;
 import com.dfsek.paralithic.eval.tokenizer.ParseException;
 import com.dfsek.terra.api.core.TerraPlugin;
 import com.dfsek.terra.api.math.Range;
-import com.dfsek.terra.api.math.parsii.defined.UserDefinedFunction;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction2;
-import com.dfsek.terra.api.math.parsii.noise.NoiseFunction3;
+import com.dfsek.terra.api.math.paralithic.defined.UserDefinedFunction;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction2;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction3;
 import com.dfsek.terra.api.math.vector.Vector3;
 import com.dfsek.terra.api.platform.world.World;
 import com.dfsek.terra.api.util.FastRandom;

common/src/main/java/com/dfsek/terra/config/GenericLoaders.java

@@ -6,8 +6,8 @@ import com.dfsek.terra.api.core.TerraPlugin;
 import com.dfsek.terra.api.math.GridSpawn;
 import com.dfsek.terra.api.math.ProbabilityCollection;
 import com.dfsek.terra.api.math.Range;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
 import com.dfsek.terra.api.math.noise.samplers.ImageSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.CellularSampler;
 import com.dfsek.terra.api.util.seeded.SourceSeeded;
 import com.dfsek.terra.api.util.seeded.StageSeeded;
 import com.dfsek.terra.api.world.palette.holder.PaletteHolder;
@@ -37,7 +37,6 @@ import com.dfsek.terra.config.loaders.config.biome.templates.stage.mutator.Repla
 import com.dfsek.terra.config.loaders.config.biome.templates.stage.mutator.SmoothMutatorTemplate;
 import com.dfsek.terra.config.loaders.config.function.FunctionTemplate;
 import com.dfsek.terra.config.loaders.config.sampler.templates.DomainWarpTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
 import com.dfsek.terra.config.loaders.config.sampler.templates.ImageSamplerTemplate;
 import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.ClampNormalizerTemplate;
 import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.LinearNormalizerTemplate;
@@ -75,7 +74,6 @@ public class GenericLoaders implements LoaderRegistrar {
                 .registerLoader(TreeLayer.class, new TreeLayerLoader())
                 .registerLoader(MaterialSet.class, new MaterialSetLoader())
                 .registerLoader(OreHolder.class, new OreHolderLoader())
-                .registerLoader(FastNoiseTemplate.class, FastNoiseTemplate::new)
                 .registerLoader(ImageSamplerTemplate.class, ImageSamplerTemplate::new)
                 .registerLoader(DomainWarpTemplate.class, DomainWarpTemplate::new)
                 .registerLoader(LinearNormalizerTemplate.class, LinearNormalizerTemplate::new)
@@ -98,12 +96,8 @@ public class GenericLoaders implements LoaderRegistrar {
                 .registerLoader(ImageBiomeProvider.Align.class, (t, object, cf) -> ImageBiomeProvider.Align.valueOf((String) object))
                 .registerLoader(ExpanderStage.Type.class, (t, object, cf) -> ExpanderStage.Type.valueOf((String) object))
                 .registerLoader(MutatorStage.Type.class, (t, object, cf) -> MutatorStage.Type.valueOf((String) object))
-                .registerLoader(FastNoiseLite.NoiseType.class, (t, object, cf) -> FastNoiseLite.NoiseType.valueOf((String) object))
-                .registerLoader(FastNoiseLite.FractalType.class, (t, object, cf) -> FastNoiseLite.FractalType.valueOf((String) object))
-                .registerLoader(FastNoiseLite.DomainWarpType.class, (t, object, cf) -> FastNoiseLite.DomainWarpType.valueOf((String) object))
-                .registerLoader(FastNoiseLite.RotationType3D.class, (t, object, cf) -> FastNoiseLite.RotationType3D.valueOf((String) object))
-                .registerLoader(FastNoiseLite.CellularReturnType.class, (t, object, cf) -> FastNoiseLite.CellularReturnType.valueOf((String) object))
-                .registerLoader(FastNoiseLite.CellularDistanceFunction.class, (t, object, cf) -> FastNoiseLite.CellularDistanceFunction.valueOf((String) object))
+                .registerLoader(CellularSampler.ReturnType.class, (t, object, cf) -> CellularSampler.ReturnType.valueOf((String) object))
+                .registerLoader(CellularSampler.DistanceFunction.class, (t, object, cf) -> CellularSampler.DistanceFunction.valueOf((String) object))
                 .registerLoader(TerraFlora.Search.class, (t, o, l) -> TerraFlora.Search.valueOf(o.toString()));
     }
 }

common/src/main/java/com/dfsek/terra/config/builder/GeneratorBuilder.java

@@ -3,8 +3,8 @@ package com.dfsek.terra.config.builder;
 import com.dfsek.paralithic.eval.parser.Scope;
 import com.dfsek.paralithic.eval.tokenizer.ParseException;
 import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.noise.samplers.ConstantSampler;
 import com.dfsek.terra.api.math.noise.samplers.ExpressionSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.ConstantSampler;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.api.world.palette.holder.PaletteHolder;
 import com.dfsek.terra.config.loaders.config.function.FunctionTemplate;

common/src/main/java/com/dfsek/terra/config/factories/FloraFactory.java

@@ -1,7 +1,7 @@
 package com.dfsek.terra.config.factories;
 
 import com.dfsek.terra.api.core.TerraPlugin;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.WhiteNoiseSampler;
 import com.dfsek.terra.api.platform.block.BlockData;
 import com.dfsek.terra.api.world.flora.Flora;
 import com.dfsek.terra.api.world.palette.NoisePalette;
@@ -13,9 +13,7 @@ import com.dfsek.terra.world.population.items.flora.TerraFlora;
 public class FloraFactory implements TerraFactory<FloraTemplate, Flora> {
     @Override
     public TerraFlora build(FloraTemplate config, TerraPlugin main) {
-        FastNoiseLite whiteNoise = new FastNoiseLite();
-        whiteNoise.setNoiseType(FastNoiseLite.NoiseType.WhiteNoise);
-        Palette<BlockData> palette = new NoisePalette<>(whiteNoise, false);
+        Palette<BlockData> palette = new NoisePalette<>(new WhiteNoiseSampler(2403), false);
         for(PaletteLayerHolder layer : config.getFloraPalette()) {
             palette.add(layer.getLayer(), layer.getSize(), layer.getSampler());
         }

common/src/main/java/com/dfsek/terra/config/loaders/LinkedHashMapLoader.java

@@ -9,6 +9,7 @@ import java.lang.reflect.Type;
 import java.util.LinkedHashMap;
 import java.util.Map;
 
+@SuppressWarnings("unchecked")
 public class LinkedHashMapLoader implements TypeLoader<LinkedHashMap<Object, Object>> {
     @Override
     public LinkedHashMap<Object, Object> load(Type t, Object c, ConfigLoader loader) throws LoadException {

common/src/main/java/com/dfsek/terra/config/loaders/config/FloraLayerLoader.java

@@ -6,11 +6,10 @@ import com.dfsek.tectonic.loading.ConfigLoader;
 import com.dfsek.tectonic.loading.TypeLoader;
 import com.dfsek.terra.api.math.ProbabilityCollection;
 import com.dfsek.terra.api.math.Range;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.WhiteNoiseSampler;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.api.world.flora.Flora;
 import com.dfsek.terra.config.loaders.Types;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
 import com.dfsek.terra.world.population.items.flora.FloraLayer;
 
 import java.lang.reflect.Type;
@@ -35,10 +34,7 @@ public class FloraLayerLoader implements TypeLoader<FloraLayer> {
             }
             return new FloraLayer(density, range, items, sampler.apply(2403L));
         }
-        FastNoiseTemplate def = new FastNoiseTemplate();
-        def.setType(FastNoiseLite.NoiseType.WhiteNoise);
-        def.setDimensions(3);
 
-        return new FloraLayer(density, range, items, def.apply(2403L));
+        return new FloraLayer(density, range, items, new WhiteNoiseSampler(2403));
     }
 }

common/src/main/java/com/dfsek/terra/config/loaders/config/TreeLayerLoader.java

@@ -1,16 +1,14 @@
 package com.dfsek.terra.config.loaders.config;
 
-import com.dfsek.tectonic.config.Configuration;
-import com.dfsek.tectonic.exception.ConfigException;
 import com.dfsek.tectonic.exception.LoadException;
 import com.dfsek.tectonic.loading.ConfigLoader;
 import com.dfsek.tectonic.loading.TypeLoader;
 import com.dfsek.terra.api.math.ProbabilityCollection;
 import com.dfsek.terra.api.math.Range;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.WhiteNoiseSampler;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.api.world.tree.Tree;
 import com.dfsek.terra.config.loaders.Types;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
 import com.dfsek.terra.world.population.items.tree.TreeLayer;
 
 import java.lang.reflect.Type;
@@ -26,19 +24,11 @@ public class TreeLayerLoader implements TypeLoader<TreeLayer> {
         if(range == null) throw new LoadException("Tree range unspecified");
         ProbabilityCollection<Tree> items = (ProbabilityCollection<Tree>) configLoader.loadType(Types.TREE_PROBABILITY_COLLECTION_TYPE, map.get("items"));
 
-        FastNoiseTemplate sampler = new FastNoiseTemplate();
         if(map.containsKey("distribution")) {
-            try {
-                configLoader.load(sampler, new Configuration((Map<String, Object>) map.get("distribution")));
-            } catch(ConfigException e) {
-                throw new LoadException("Unable to load noise", e);
-            }
-            return new TreeLayer(density, range, items, sampler.apply(2403L));
+            NoiseSeeded noise = configLoader.loadClass(NoiseSeeded.class, map.get("distribution"));
+            return new TreeLayer(density, range, items, noise.apply(2403L));
         }
 
-        sampler.setType(FastNoiseLite.NoiseType.WhiteNoise);
-        sampler.setDimensions(3);
-
-        return new TreeLayer(density, range, items, sampler.apply(2403L));
+        return new TreeLayer(density, range, items, new WhiteNoiseSampler(2403));
     }
 }

common/src/main/java/com/dfsek/terra/config/loaders/config/biome/templates/source/BiomeProviderTemplate.java

@@ -4,7 +4,7 @@ import com.dfsek.tectonic.annotations.Default;
 import com.dfsek.tectonic.annotations.Value;
 import com.dfsek.tectonic.loading.object.ObjectTemplate;
 import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.noise.samplers.ConstantSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.ConstantSampler;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.biome.provider.BiomeProvider;
 import com.dfsek.terra.registry.config.BiomeRegistry;

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/NoiseSamplerBuilderLoader.java

@@ -5,52 +5,31 @@ import com.dfsek.tectonic.exception.ConfigException;
 import com.dfsek.tectonic.exception.LoadException;
 import com.dfsek.tectonic.loading.ConfigLoader;
 import com.dfsek.tectonic.loading.TypeLoader;
+import com.dfsek.tectonic.loading.object.ObjectTemplate;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
-import com.dfsek.terra.config.loaders.config.sampler.templates.DomainWarpTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.ImageSamplerTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.NormalizerTemplate;
-import com.dfsek.terra.registry.config.NormalizerRegistry;
+import com.dfsek.terra.registry.config.NoiseRegistry;
 
 import java.lang.reflect.Type;
+import java.util.Locale;
 import java.util.Map;
 
 @SuppressWarnings("unchecked")
 public class NoiseSamplerBuilderLoader implements TypeLoader<NoiseSeeded> {
-    private final NormalizerRegistry normalizerRegistry;
+    private final NoiseRegistry noiseRegistry;
 
-    public NoiseSamplerBuilderLoader(NormalizerRegistry normalizerRegistry) {
-        this.normalizerRegistry = normalizerRegistry;
+    public NoiseSamplerBuilderLoader(NoiseRegistry noiseRegistry) {
+        this.noiseRegistry = noiseRegistry;
     }
 
     @Override
     public NoiseSeeded load(Type t, Object c, ConfigLoader loader) throws LoadException {
         Map<String, Object> map = (Map<String, Object>) c;
-
-        String samplerType = "NOISE";
-
-        if(map.containsKey("sampler-type")) {
-            samplerType = map.get("sampler-type").toString();
+        try {
+            ObjectTemplate<NoiseSeeded> normalizerTemplate = noiseRegistry.get(((String) map.get("type")).toUpperCase(Locale.ROOT)).get();
+            loader.load(normalizerTemplate, new Configuration(map));
+            return normalizerTemplate.get();
+        } catch(ConfigException e) {
+            throw new LoadException("Unable to load noise function: ", e);
         }
-
-        switch(samplerType) {
-            case "NOISE":
-                return loader.loadClass(FastNoiseTemplate.class, map).get();
-            case "NORMALIZER":
-                try {
-                    NormalizerTemplate<?> normalizerTemplate = normalizerRegistry.get((String) map.get("type")).get();
-                    loader.load(normalizerTemplate, new Configuration(map));
-                    return normalizerTemplate;
-                } catch(ConfigException e) {
-                    throw new LoadException("Unable to load normalizer: ", e);
-                }
-            case "IMAGE": {
-                return loader.loadClass(ImageSamplerTemplate.class, map).get();
-            }
-            case "DOMAIN_WARP":
-                return loader.loadClass(DomainWarpTemplate.class, map).get();
-        }
-
-        throw new LoadException("No such noise sampler type \"" + samplerType + "\"");
     }
 }

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/FastNoiseTemplate.java

@@ -1,227 +0,0 @@
-package com.dfsek.terra.config.loaders.config.sampler.templates;
-
-import com.dfsek.tectonic.annotations.Default;
-import com.dfsek.tectonic.annotations.Value;
-import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
-import com.dfsek.terra.api.util.seeded.NoiseSeeded;
-
-@SuppressWarnings({"unused", "FieldMayBeFinal"})
-public class FastNoiseTemplate extends SamplerTemplate<FastNoiseLite> implements NoiseSeeded {
-    @Value("type")
-    @Default
-    private FastNoiseLite.NoiseType type = FastNoiseLite.NoiseType.OpenSimplex2;
-
-    @Value("fractal.octaves")
-    @Default
-    private int octaves = 1;
-
-    @Value("fractal.type")
-    @Default
-    private FastNoiseLite.FractalType fractalType = FastNoiseLite.FractalType.None;
-
-    @Value("frequency")
-    @Default
-    private double frequency = 0.02D;
-
-    @Value("fractal.gain")
-    @Default
-    private double fractalGain = 0.5D;
-
-    @Value("fractal.lacunarity")
-    @Default
-    private double fractalLacunarity = 2.0D;
-
-    @Value("fractal.ping-pong")
-    @Default
-    private double pingPong = 2.0D;
-
-    @Value("fractal.weighted-strength")
-    @Default
-    private double weightedStrength = 0.0D;
-
-    @Value("salt")
-    @Default
-    private int seedOffset = 0;
-
-    @Value("cellular.distance")
-    @Default
-    private FastNoiseLite.CellularDistanceFunction cellularDistanceFunction = FastNoiseLite.CellularDistanceFunction.EuclideanSq;
-
-    @Value("cellular.return")
-    @Default
-    private FastNoiseLite.CellularReturnType cellularReturnType = FastNoiseLite.CellularReturnType.Distance;
-
-    @Value("cellular.jitter")
-    @Default
-    private double cellularJitter = 1.0D;
-
-    @Value("rotation-type")
-    @Default
-    private FastNoiseLite.RotationType3D rotationType3D = FastNoiseLite.RotationType3D.None;
-
-    @Value("dimensions")
-    @Default
-    private int dimensions = 2;
-
-    @Value("cellular.lookup")
-    @Default
-    private NoiseSeeded lookup;
-
-
-    @Override
-    public NoiseSampler apply(Long seed) {
-        FastNoiseLite noise = new FastNoiseLite((int) (seed + seedOffset));
-        if(!fractalType.equals(FastNoiseLite.FractalType.None)) {
-            noise.setFractalType(fractalType);
-            noise.setFractalOctaves(octaves);
-            noise.setFractalGain(fractalGain);
-            noise.setFractalLacunarity(fractalLacunarity);
-            if(fractalType.equals(FastNoiseLite.FractalType.PingPong)) noise.setFractalPingPongStrength(pingPong);
-            noise.setFractalWeightedStrength(weightedStrength);
-        }
-        if(type.equals(FastNoiseLite.NoiseType.Cellular)) {
-            noise.setCellularDistanceFunction(cellularDistanceFunction);
-            noise.setCellularReturnType(cellularReturnType);
-            noise.setCellularJitter(cellularJitter);
-            if(lookup != null) noise.setCellularNoiseLookup(lookup.apply(seed));
-        }
-
-        noise.setNoiseType(type);
-
-        noise.setRotationType3D(rotationType3D);
-
-        noise.setFrequency(frequency);
-        return noise;
-    }
-
-    public FastNoiseLite.NoiseType getType() {
-        return type;
-    }
-
-    public FastNoiseTemplate setType(FastNoiseLite.NoiseType type) {
-        this.type = type;
-        return this;
-    }
-
-    public int getSeedOffset() {
-        return seedOffset;
-    }
-
-    public void setSeedOffset(int seedOffset) {
-        this.seedOffset = seedOffset;
-    }
-
-    public FastNoiseLite.CellularDistanceFunction getCellularDistanceFunction() {
-        return cellularDistanceFunction;
-    }
-
-    public FastNoiseTemplate setCellularDistanceFunction(FastNoiseLite.CellularDistanceFunction cellularDistanceFunction) {
-        this.cellularDistanceFunction = cellularDistanceFunction;
-        return this;
-    }
-
-    public FastNoiseLite.CellularReturnType getCellularReturnType() {
-        return cellularReturnType;
-    }
-
-    public FastNoiseTemplate setCellularReturnType(FastNoiseLite.CellularReturnType cellularReturnType) {
-        this.cellularReturnType = cellularReturnType;
-        return this;
-    }
-
-    public double getCellularJitter() {
-        return cellularJitter;
-    }
-
-    public FastNoiseTemplate setCellularJitter(double cellularJitter) {
-        this.cellularJitter = cellularJitter;
-        return this;
-    }
-
-    public double getFractalGain() {
-        return fractalGain;
-    }
-
-    public FastNoiseTemplate setFractalGain(double fractalGain) {
-        this.fractalGain = fractalGain;
-        return this;
-    }
-
-    public double getFractalLacunarity() {
-        return fractalLacunarity;
-    }
-
-    public FastNoiseTemplate setFractalLacunarity(double fractalLacunarity) {
-        this.fractalLacunarity = fractalLacunarity;
-        return this;
-    }
-
-    public double getFrequency() {
-        return frequency;
-    }
-
-    public FastNoiseTemplate setFrequency(double frequency) {
-        this.frequency = frequency;
-        return this;
-    }
-
-    public double getPingPong() {
-        return pingPong;
-    }
-
-    public FastNoiseTemplate setPingPong(double pingPong) {
-        this.pingPong = pingPong;
-        return this;
-    }
-
-    public double getWeightedStrength() {
-        return weightedStrength;
-    }
-
-    public FastNoiseTemplate setWeightedStrength(double weightedStrength) {
-        this.weightedStrength = weightedStrength;
-        return this;
-    }
-
-    public int getOctaves() {
-        return octaves;
-    }
-
-    public FastNoiseTemplate setOctaves(int octaves) {
-        this.octaves = octaves;
-        return this;
-    }
-
-    public FastNoiseLite.FractalType getFractalType() {
-        return fractalType;
-    }
-
-    public FastNoiseTemplate setFractalType(FastNoiseLite.FractalType fractalType) {
-        this.fractalType = fractalType;
-        return this;
-    }
-
-    public FastNoiseLite.RotationType3D getRotationType3D() {
-        return rotationType3D;
-    }
-
-    public FastNoiseTemplate setRotationType3D(FastNoiseLite.RotationType3D rotationType3D) {
-        this.rotationType3D = rotationType3D;
-        return this;
-    }
-
-    public int getDimensions() {
-        return dimensions;
-    }
-
-    public void setDimensions(int dimensions) {
-        this.dimensions = dimensions;
-    }
-
-    @Override
-    public NoiseSeeded get() {
-        return this;
-    }
-}
-

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/KernelTemplate.java

@@ -0,0 +1,61 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.tectonic.config.ValidatedConfigTemplate;
+import com.dfsek.tectonic.exception.ValidationException;
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.KernelSampler;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
+
+import java.util.List;
+
+@SuppressWarnings({"unused", "FieldMayBeFinal"})
+public class KernelTemplate extends SamplerTemplate<KernelSampler> implements ValidatedConfigTemplate {
+
+    @Value("kernel")
+    private List<List<Double>> kernel;
+
+    @Value("factor")
+    @Default
+    private double factor = 1;
+
+    @Value("function")
+    private NoiseSeeded function;
+
+    @Value("frequency")
+    @Default
+    private double frequency = 1;
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        double[][] k = new double[kernel.size()][kernel.get(0).size()];
+
+        for(int x = 0; x < kernel.size(); x++) {
+            for(int y = 0; y < kernel.get(x).size(); y++) {
+                k[x][y] = kernel.get(x).get(y) * factor;
+            }
+        }
+
+        KernelSampler sampler = new KernelSampler(k, function.apply(seed));
+        sampler.setFrequency(frequency);
+        return sampler;
+    }
+
+    @Override
+    public boolean validate() throws ValidationException {
+
+        if(kernel.isEmpty()) throw new ValidationException("Kernel must not be empty.");
+
+        int len = kernel.get(0).size();
+
+        if(len == 0) throw new ValidationException("Kernel row must contain data.");
+
+        for(int i = 0; i < kernel.size(); i++) {
+            if(kernel.get(i).size() != len)
+                throw new ValidationException("Kernel row " + i + " size mismatch. Expected " + len + ", found " + kernel.get(i).size());
+        }
+
+        return super.validate();
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/CellularNoiseTemplate.java

@@ -0,0 +1,50 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.CellularSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2Sampler;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
+
+@SuppressWarnings("FieldMayBeFinal")
+public class CellularNoiseTemplate extends NoiseTemplate<CellularSampler> {
+    @Value("distance")
+    @Default
+    private CellularSampler.DistanceFunction cellularDistanceFunction = CellularSampler.DistanceFunction.EuclideanSq;
+
+    @Value("return")
+    @Default
+    private CellularSampler.ReturnType cellularReturnType = CellularSampler.ReturnType.Distance;
+
+    @Value("jitter")
+    @Default
+    private double cellularJitter = 1.0D;
+
+
+    @Value("lookup")
+    @Default
+    private NoiseSeeded lookup = new NoiseSeeded() {
+        @Override
+        public NoiseSampler apply(Long seed) {
+
+            return new OpenSimplex2Sampler((int) (long) seed);
+        }
+
+        @Override
+        public int getDimensions() {
+            return 2;
+        }
+    };
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        CellularSampler sampler = new CellularSampler((int) (long) seed);
+        sampler.setNoiseLookup(lookup.apply(seed));
+        sampler.setFrequency(frequency);
+        sampler.setJitterModifier(cellularJitter);
+        sampler.setReturnType(cellularReturnType);
+        sampler.setDistanceFunction(cellularDistanceFunction);
+        return sampler;
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/ConstantNoiseTemplate.java

@@ -0,0 +1,19 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.ConstantSampler;
+import com.dfsek.terra.config.loaders.config.sampler.templates.SamplerTemplate;
+
+@SuppressWarnings("FieldMayBeFinal")
+public class ConstantNoiseTemplate extends SamplerTemplate<ConstantSampler> {
+    @Value("value")
+    @Default
+    private double value = 0d;
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        return new ConstantSampler(value);
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/ExpressionFunctionTemplate.java

@@ -0,0 +1,67 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise;
+
+import com.dfsek.paralithic.eval.tokenizer.ParseException;
+import com.dfsek.paralithic.functions.Function;
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.tectonic.config.ValidatedConfigTemplate;
+import com.dfsek.tectonic.exception.ValidationException;
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.ExpressionFunction;
+import com.dfsek.terra.api.math.paralithic.BlankFunction;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction2;
+import com.dfsek.terra.api.math.paralithic.noise.NoiseFunction3;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
+import com.dfsek.terra.config.loaders.config.sampler.templates.SamplerTemplate;
+
+import java.util.HashMap;
+import java.util.Map;
+
+
+@SuppressWarnings({"FieldMayBeFinal", "unused"})
+public class ExpressionFunctionTemplate extends SamplerTemplate<ExpressionFunction> implements ValidatedConfigTemplate {
+    @Value("variables")
+    @Default
+    private Map<String, Double> vars = new HashMap<>();
+
+    @Value("equation")
+    private String equation;
+
+    @Value("functions")
+    @Default
+    private Map<String, NoiseSeeded> functions = new HashMap<>();
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        try {
+            Map<String, Function> noiseFunctionMap = new HashMap<>();
+
+            functions.forEach((id, function) -> {
+                if(function.getDimensions() == 2) {
+                    noiseFunctionMap.put(id, new NoiseFunction2(function.apply(seed)));
+                } else noiseFunctionMap.put(id, new NoiseFunction3(function.apply(seed)));
+            });
+
+            return new ExpressionFunction(noiseFunctionMap, equation, vars);
+        } catch(ParseException e) {
+            throw new IllegalStateException(e);
+        }
+    }
+
+    @Override
+    public boolean validate() throws ValidationException {
+        try {
+            Map<String, Function> noiseFunctionMap = new HashMap<>();
+
+            functions.forEach((id, function) -> {
+                if(function.getDimensions() == 2) {
+                    noiseFunctionMap.put(id, new BlankFunction(2));
+                } else noiseFunctionMap.put(id, new BlankFunction(3));
+            });
+            new ExpressionFunction(noiseFunctionMap, equation, vars);
+        } catch(ParseException e) {
+            throw new ValidationException("Errors occurred while parsing noise equation: ", e);
+        }
+        return super.validate();
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/NoiseTemplate.java

@@ -0,0 +1,17 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+import com.dfsek.terra.config.loaders.config.sampler.templates.SamplerTemplate;
+
+@SuppressWarnings({"unused", "FieldMayBeFinal"})
+public abstract class NoiseTemplate<T extends NoiseFunction> extends SamplerTemplate<T> {
+    @Value("frequency")
+    @Default
+    protected double frequency = 0.02d;
+
+    @Value("salt")
+    @Default
+    protected int salt = 0;
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/SimpleNoiseTemplate.java

@@ -0,0 +1,21 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.NoiseFunction;
+
+import java.util.function.Function;
+
+public class SimpleNoiseTemplate extends NoiseTemplate<NoiseFunction> {
+    private final Function<Integer, NoiseFunction> samplerSupplier;
+
+    public SimpleNoiseTemplate(Function<Integer, NoiseFunction> samplerSupplier) {
+        this.samplerSupplier = samplerSupplier;
+    }
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        NoiseFunction sampler = samplerSupplier.apply((int) (long) seed);
+        sampler.setFrequency(frequency);
+        return sampler;
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/fractal/BrownianMotionTemplate.java

@@ -0,0 +1,16 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.fractal.BrownianMotionSampler;
+
+public class BrownianMotionTemplate extends FractalTemplate<BrownianMotionSampler> {
+    @Override
+    public NoiseSampler apply(Long seed) {
+        BrownianMotionSampler sampler = new BrownianMotionSampler((int) (long) seed, function.apply(seed));
+        sampler.setGain(fractalGain);
+        sampler.setLacunarity(fractalLacunarity);
+        sampler.setOctaves(octaves);
+        sampler.setWeightedStrength(weightedStrength);
+        return sampler;
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/fractal/FractalTemplate.java

@@ -0,0 +1,28 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.terra.api.math.noise.samplers.noise.fractal.FractalNoiseFunction;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
+import com.dfsek.terra.config.loaders.config.sampler.templates.SamplerTemplate;
+
+public abstract class FractalTemplate<T extends FractalNoiseFunction> extends SamplerTemplate<T> {
+    @Value("octaves")
+    @Default
+    protected int octaves = 3;
+
+    @Value("gain")
+    @Default
+    protected double fractalGain = 0.5D;
+
+    @Value("lacunarity")
+    @Default
+    protected double fractalLacunarity = 2.0D;
+
+    @Value("weighted-strength")
+    @Default
+    protected double weightedStrength = 0.0D;
+
+    @Value("function")
+    protected NoiseSeeded function;
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/fractal/PingPongTemplate.java

@@ -0,0 +1,23 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal;
+
+import com.dfsek.tectonic.annotations.Default;
+import com.dfsek.tectonic.annotations.Value;
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.fractal.PingPongSampler;
+@SuppressWarnings({"unused", "FieldMayBeFinal"})
+public class PingPongTemplate extends FractalTemplate<PingPongSampler> {
+    @Value("ping-pong")
+    @Default
+    private double pingPong = 2.0D;
+
+    @Override
+    public NoiseSampler apply(Long seed) {
+        PingPongSampler sampler = new PingPongSampler((int) (long) seed, function.apply(seed));
+        sampler.setGain(fractalGain);
+        sampler.setLacunarity(fractalLacunarity);
+        sampler.setOctaves(octaves);
+        sampler.setWeightedStrength(weightedStrength);
+        sampler.setPingPongStrength(pingPong);
+        return sampler;
+    }
+}

common/src/main/java/com/dfsek/terra/config/loaders/config/sampler/templates/noise/fractal/RidgedFractalTemplate.java

@@ -0,0 +1,16 @@
+package com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal;
+
+import com.dfsek.terra.api.math.noise.NoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.fractal.RidgedFractalSampler;
+
+public class RidgedFractalTemplate extends FractalTemplate<RidgedFractalSampler> {
+    @Override
+    public NoiseSampler apply(Long seed) {
+        RidgedFractalSampler sampler = new RidgedFractalSampler((int) (long) seed, function.apply(seed));
+        sampler.setGain(fractalGain);
+        sampler.setLacunarity(fractalLacunarity);
+        sampler.setOctaves(octaves);
+        sampler.setWeightedStrength(weightedStrength);
+        return sampler;
+    }
+}

common/src/main/java/com/dfsek/terra/config/pack/ConfigPack.java

@@ -52,7 +52,7 @@ import com.dfsek.terra.registry.config.BiomeRegistry;
 import com.dfsek.terra.registry.config.CarverRegistry;
 import com.dfsek.terra.registry.config.FloraRegistry;
 import com.dfsek.terra.registry.config.LootRegistry;
-import com.dfsek.terra.registry.config.NormalizerRegistry;
+import com.dfsek.terra.registry.config.NoiseRegistry;
 import com.dfsek.terra.registry.config.OreRegistry;
 import com.dfsek.terra.registry.config.PaletteRegistry;
 import com.dfsek.terra.registry.config.ScriptRegistry;
@@ -97,7 +97,7 @@ public class ConfigPack implements LoaderRegistrar {
 
     private final CarverRegistry carverRegistry = new CarverRegistry();
 
-    private final NormalizerRegistry normalizerRegistry = new NormalizerRegistry();
+    private final NoiseRegistry noiseRegistry = new NoiseRegistry();
     private final FunctionRegistry functionRegistry = new FunctionRegistry();
 
     private final AbstractConfigLoader abstractConfigLoader = new AbstractConfigLoader();
@@ -198,7 +198,7 @@ public class ConfigPack implements LoaderRegistrar {
 
     private void load(long start, TerraPlugin main) throws ConfigException {
         main.getEventManager().callEvent(new ConfigPackPreLoadEvent(this));
-        main.packPreLoadCallback(this);
+
         for(Map.Entry<String, Double> var : template.getVariables().entrySet()) {
             varScope.create(var.getKey(), var.getValue());
         }
@@ -230,7 +230,6 @@ public class ConfigPack implements LoaderRegistrar {
                 .open("structures/structures", ".yml").then(streams -> buildAll(new StructureFactory(), structureRegistry, abstractConfigLoader.load(streams, StructureTemplate::new), main)).close()
                 .open("flora", ".yml").then(streams -> buildAll(new FloraFactory(), floraRegistry, abstractConfigLoader.load(streams, FloraTemplate::new), main)).close()
                 .open("biomes", ".yml").then(streams -> buildAll(new BiomeFactory(this), biomeRegistry, abstractConfigLoader.load(streams, () -> new BiomeTemplate(this, main)), main)).close();
-        main.packPostLoadCallback(this);
 
         main.getEventManager().callEvent(new ConfigPackPostLoadEvent(this));
         LangUtil.log("config-pack.loaded", Level.INFO, template.getID(), String.valueOf((System.nanoTime() - start) / 1000000D), template.getAuthor(), template.getVersion());
@@ -282,7 +281,7 @@ public class ConfigPack implements LoaderRegistrar {
                 .registerLoader(LootTable.class, lootRegistry)
                 .registerLoader(UserDefinedCarver.class, carverRegistry)
                 .registerLoader(BufferedImage.class, new BufferedImageLoader(loader))
-                .registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(normalizerRegistry))
+                .registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(noiseRegistry))
                 .registerLoader(SingleBiomeProviderTemplate.class, () -> new SingleBiomeProviderTemplate(biomeRegistry))
                 .registerLoader(BiomePipelineTemplate.class, () -> new BiomePipelineTemplate(biomeRegistry, main))
                 .registerLoader(ImageSamplerTemplate.class, () -> new ImageProviderTemplate(biomeRegistry));
@@ -312,8 +311,8 @@ public class ConfigPack implements LoaderRegistrar {
         return functionRegistry;
     }
 
-    public NormalizerRegistry getNormalizerRegistry() {
-        return normalizerRegistry;
+    public NoiseRegistry getNormalizerRegistry() {
+        return noiseRegistry;
     }
 
     public CarverRegistry getCarverRegistry() {

common/src/main/java/com/dfsek/terra/config/templates/BiomeTemplate.java

@@ -11,9 +11,9 @@ import com.dfsek.tectonic.exception.ValidationException;
 import com.dfsek.terra.api.core.TerraPlugin;
 import com.dfsek.terra.api.math.ProbabilityCollection;
 import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
-import com.dfsek.terra.api.math.parsii.BlankFunction;
-import com.dfsek.terra.api.math.parsii.defined.UserDefinedFunction;
+import com.dfsek.terra.api.math.noise.samplers.noise.ConstantSampler;
+import com.dfsek.terra.api.math.paralithic.BlankFunction;
+import com.dfsek.terra.api.math.paralithic.defined.UserDefinedFunction;
 import com.dfsek.terra.api.platform.block.BlockData;
 import com.dfsek.terra.api.platform.block.MaterialData;
 import com.dfsek.terra.api.platform.world.Biome;
@@ -24,7 +24,6 @@ import com.dfsek.terra.api.world.palette.SinglePalette;
 import com.dfsek.terra.api.world.palette.holder.PaletteHolder;
 import com.dfsek.terra.carving.UserDefinedCarver;
 import com.dfsek.terra.config.loaders.config.function.FunctionTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
 import com.dfsek.terra.config.pack.ConfigPack;
 import com.dfsek.terra.world.population.items.TerraStructure;
 import com.dfsek.terra.world.population.items.flora.FloraLayer;
@@ -248,12 +247,10 @@ public class BiomeTemplate extends AbstractableTemplate implements ValidatedConf
 
     public BiomeTemplate(ConfigPack pack, TerraPlugin main) {
         this.pack = pack;
-        FastNoiseTemplate builder = new FastNoiseTemplate();
-        builder.setType(FastNoiseLite.NoiseType.Constant);
         biomeNoise = new NoiseSeeded() {
             @Override
             public NoiseSampler apply(Long seed) {
-                return builder.apply(seed);
+                return new ConstantSampler(0);
             }
 
             @Override

common/src/main/java/com/dfsek/terra/config/templates/PaletteTemplate.java

@@ -4,10 +4,9 @@ import com.dfsek.tectonic.annotations.Abstractable;
 import com.dfsek.tectonic.annotations.Default;
 import com.dfsek.tectonic.annotations.Value;
 import com.dfsek.terra.api.math.noise.NoiseSampler;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.WhiteNoiseSampler;
 import com.dfsek.terra.api.util.seeded.NoiseSeeded;
 import com.dfsek.terra.api.world.palette.holder.PaletteLayerHolder;
-import com.dfsek.terra.config.loaders.config.sampler.templates.FastNoiseTemplate;
 
 import java.util.List;
 
@@ -26,13 +25,10 @@ public class PaletteTemplate extends AbstractableTemplate {
     private List<PaletteLayerHolder> palette;
 
     public PaletteTemplate() {
-        FastNoiseTemplate builder = new FastNoiseTemplate();
-        builder.setType(FastNoiseLite.NoiseType.WhiteNoise);
-        builder.setDimensions(3);
         this.noise = new NoiseSeeded() {
             @Override
             public NoiseSampler apply(Long seed) {
-                return builder.apply(seed);
+                return new WhiteNoiseSampler((int) (long) seed);
             }
 
             @Override

common/src/main/java/com/dfsek/terra/registry/config/NoiseRegistry.java

@@ -0,0 +1,61 @@
+package com.dfsek.terra.registry.config;
+
+import com.dfsek.tectonic.loading.object.ObjectTemplate;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.GaussianNoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.random.WhiteNoiseSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2SSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2Sampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.PerlinSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.value.ValueCubicSampler;
+import com.dfsek.terra.api.math.noise.samplers.noise.value.ValueSampler;
+import com.dfsek.terra.api.util.seeded.NoiseSeeded;
+import com.dfsek.terra.config.loaders.config.sampler.templates.DomainWarpTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.ImageSamplerTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.KernelTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.CellularNoiseTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.ConstantNoiseTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.ExpressionFunctionTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.SimpleNoiseTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal.BrownianMotionTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal.PingPongTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.noise.fractal.RidgedFractalTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.ClampNormalizerTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.LinearNormalizerTemplate;
+import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.NormalNormalizerTemplate;
+import com.dfsek.terra.registry.TerraRegistry;
+
+import java.util.function.Supplier;
+
+public class NoiseRegistry extends TerraRegistry<Supplier<ObjectTemplate<NoiseSeeded>>> {
+    public NoiseRegistry() {
+        add("LINEAR", LinearNormalizerTemplate::new);
+        add("NORMAL", NormalNormalizerTemplate::new);
+        add("CLAMP", ClampNormalizerTemplate::new);
+        add("EXPRESSION", ExpressionFunctionTemplate::new);
+
+        add("IMAGE", ImageSamplerTemplate::new);
+
+        add("DOMAINWARP", DomainWarpTemplate::new);
+
+        add("FBM", BrownianMotionTemplate::new);
+        add("PINGPONG", PingPongTemplate::new);
+        add("RIDGED", RidgedFractalTemplate::new);
+
+        add("OPENSIMPLEX2", () -> new SimpleNoiseTemplate(OpenSimplex2Sampler::new));
+        add("OPENSIMPLEX2S", () -> new SimpleNoiseTemplate(OpenSimplex2SSampler::new));
+        add("PERLIN", () -> new SimpleNoiseTemplate(PerlinSampler::new));
+
+
+        add("VALUE", () -> new SimpleNoiseTemplate(ValueSampler::new));
+        add("VALUECUBIC", () -> new SimpleNoiseTemplate(ValueCubicSampler::new));
+
+        add("CELLULAR", CellularNoiseTemplate::new);
+
+        add("WHITENOISE", () -> new SimpleNoiseTemplate(WhiteNoiseSampler::new));
+        add("GAUSSIAN", () -> new SimpleNoiseTemplate(GaussianNoiseSampler::new));
+
+        add("CONSTANT", ConstantNoiseTemplate::new);
+
+        add("KERNEL", KernelTemplate::new);
+    }
+}

common/src/main/java/com/dfsek/terra/registry/config/NormalizerRegistry.java

@@ -1,17 +0,0 @@
-package com.dfsek.terra.registry.config;
-
-import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.ClampNormalizerTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.LinearNormalizerTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.NormalNormalizerTemplate;
-import com.dfsek.terra.config.loaders.config.sampler.templates.normalizer.NormalizerTemplate;
-import com.dfsek.terra.registry.TerraRegistry;
-
-import java.util.function.Supplier;
-
-public class NormalizerRegistry extends TerraRegistry<Supplier<NormalizerTemplate<?>>> {
-    public NormalizerRegistry() {
-        add("LINEAR", LinearNormalizerTemplate::new);
-        add("NORMAL", NormalNormalizerTemplate::new);
-        add("CLAMP", ClampNormalizerTemplate::new);
-    }
-}

common/src/main/java/com/dfsek/terra/world/population/items/ores/DeformedSphereOre.java

@@ -2,7 +2,7 @@ package com.dfsek.terra.world.population.items.ores;
 
 import com.dfsek.terra.api.core.TerraPlugin;
 import com.dfsek.terra.api.math.Range;
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2Sampler;
 import com.dfsek.terra.api.math.vector.Vector3;
 import com.dfsek.terra.api.platform.block.Block;
 import com.dfsek.terra.api.platform.block.BlockData;
@@ -28,8 +28,7 @@ public class DeformedSphereOre extends Ore {
     @Override
     public void generate(Vector3 origin, Chunk c, Random r) {
         WorldHandle handle = main.getWorldHandle();
-        FastNoiseLite ore = new FastNoiseLite(r.nextInt());
-        ore.setNoiseType(FastNoiseLite.NoiseType.OpenSimplex2);
+        OpenSimplex2Sampler ore = new OpenSimplex2Sampler(r.nextInt());
         ore.setFrequency(deformFrequency);
         int rad = size.get(r);
         for(int x = -rad; x <= rad; x++) {

common/src/test/java/biome/DistributionTest.java

@@ -36,7 +36,7 @@ import com.dfsek.terra.config.templates.AbstractableTemplate;
 import com.dfsek.terra.debug.DebugLogger;
 import com.dfsek.terra.registry.ConfigRegistry;
 import com.dfsek.terra.registry.config.BiomeRegistry;
-import com.dfsek.terra.registry.config.NormalizerRegistry;
+import com.dfsek.terra.registry.config.NoiseRegistry;
 import com.dfsek.terra.world.TerraWorld;
 
 import javax.swing.*;
@@ -141,7 +141,7 @@ public class DistributionTest {
 
     private static BiomeProvider getProvider(long seed) throws ConfigException, IOException {
         System.out.println(seed);
-        File pack = new File("/home/dfsek/Documents/Terra/platforms/bukkit/target/server/plugins/Terra/packs/default/");
+        File pack = new File("/home/dfsek/Documents/Terra/platforms/bukkit/target/server/plugins/Terra/packs/betterend/");
         FolderLoader folderLoader = new FolderLoader(pack.toPath());
 
         AbstractConfigLoader loader = new AbstractConfigLoader();
@@ -161,7 +161,7 @@ public class DistributionTest {
                 .registerLoader(ImageProviderTemplate.class, () -> new ImageProviderTemplate(biomeRegistry));
         new GenericLoaders(null).register(pipeLoader);
 
-        pipeLoader.registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(new NormalizerRegistry()));
+        pipeLoader.registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(new NoiseRegistry()));
 
         pipeLoader.load(template, folderLoader.get("pack.yml"));
         return template.getBiomeProviderBuilder().build(seed);

common/src/test/java/noise/NoiseTool.java

@@ -10,7 +10,7 @@ import com.dfsek.terra.config.fileloaders.FolderLoader;
 import com.dfsek.terra.config.loaders.ProbabilityCollectionLoader;
 import com.dfsek.terra.config.loaders.config.BufferedImageLoader;
 import com.dfsek.terra.config.loaders.config.sampler.NoiseSamplerBuilderLoader;
-import com.dfsek.terra.registry.config.NormalizerRegistry;
+import com.dfsek.terra.registry.config.NoiseRegistry;
 import org.apache.commons.io.FileUtils;
 
 import javax.swing.*;
@@ -97,7 +97,7 @@ public class NoiseTool {
         FolderLoader folderLoader = new FolderLoader(Paths.get("./"));
 
         ConfigLoader loader = new ConfigLoader();
-        loader.registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(new NormalizerRegistry()))
+        loader.registerLoader(NoiseSeeded.class, new NoiseSamplerBuilderLoader(new NoiseRegistry()))
                 .registerLoader(BufferedImage.class, new BufferedImageLoader(folderLoader))
                 .registerLoader(ProbabilityCollection.class, new ProbabilityCollectionLoader());
 
@@ -130,6 +130,7 @@ public class NoiseTool {
         System.out.println(template.getBuilder().getDimensions());
         NoiseSampler noise = template.getBuilder().apply((long) seed);
 
+
         int size = 1024;
 
         BufferedImage image = new BufferedImage(size, size, BufferedImage.TYPE_INT_ARGB);

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/TerraBukkitPlugin.java

@@ -18,10 +18,9 @@ import com.dfsek.terra.bukkit.handles.BukkitWorldHandle;
 import com.dfsek.terra.bukkit.listeners.CommonListener;
 import com.dfsek.terra.bukkit.listeners.PaperListener;
 import com.dfsek.terra.bukkit.listeners.SpigotListener;
+import com.dfsek.terra.bukkit.listeners.TerraListener;
 import com.dfsek.terra.bukkit.util.PaperUtil;
-import com.dfsek.terra.bukkit.world.BukkitAdapter;
 import com.dfsek.terra.bukkit.world.BukkitBiome;
-import com.dfsek.terra.bukkit.world.BukkitTree;
 import com.dfsek.terra.config.GenericLoaders;
 import com.dfsek.terra.config.PluginConfig;
 import com.dfsek.terra.config.lang.LangUtil;
@@ -34,7 +33,6 @@ import com.dfsek.terra.world.generation.MasterChunkGenerator;
 import io.papermc.lib.PaperLib;
 import org.bstats.bukkit.Metrics;
 import org.bukkit.Bukkit;
-import org.bukkit.TreeType;
 import org.bukkit.command.PluginCommand;
 import org.bukkit.entity.EntityType;
 import org.bukkit.generator.ChunkGenerator;
@@ -103,13 +101,6 @@ public class TerraBukkitPlugin extends JavaPlugin implements TerraPlugin {
         this.handle = handle;
     }
 
-    @Override
-    public void packPreLoadCallback(ConfigPack pack) {
-        for(TreeType value : TreeType.values()) {
-            pack.getTreeRegistry().add(BukkitAdapter.TREE_TRANSFORMER.translate(value), new BukkitTree(value, this));
-        }
-    }
-
     @Override
     public DebugLogger getDebugLogger() {
         return debugLogger;
@@ -129,6 +120,8 @@ public class TerraBukkitPlugin extends JavaPlugin implements TerraPlugin {
     public void onEnable() {
         debugLogger = new DebugLogger(getLogger());
 
+        eventManager.registerListener(new TerraListener(this)); // Register tree injection event
+
         getLogger().info("Running on version " + BUKKIT_VERSION);
         if(BUKKIT_VERSION.equals(Version.UNKNOWN)) {
             getLogger().warning("Terra is running on an unknown Bukkit version. Proceed with caution.");

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/command/command/biome/BiomeLocateCommand.java

@@ -25,6 +25,7 @@ import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
+@SuppressWarnings("deprecation")
 public class BiomeLocateCommand extends WorldCommand {
     public BiomeLocateCommand(com.dfsek.terra.bukkit.command.Command parent) {
         super(parent);

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/command/command/geometry/DeformedSphereCommand.java

@@ -1,6 +1,6 @@
 package com.dfsek.terra.bukkit.command.command.geometry;
 
-import com.dfsek.terra.api.math.noise.samplers.FastNoiseLite;
+import com.dfsek.terra.api.math.noise.samplers.noise.simplex.OpenSimplex2Sampler;
 import com.dfsek.terra.api.math.vector.Vector3;
 import com.dfsek.terra.api.math.voxel.DeformedSphere;
 import com.dfsek.terra.bukkit.BukkitCommandSender;
@@ -44,8 +44,7 @@ public class DeformedSphereCommand extends PlayerCommand {
             LangUtil.send("command.geometry.deform.invalid-frequency", new BukkitCommandSender(sender), args[2]);
             return true;
         }
-        FastNoiseLite n = new FastNoiseLite((int) sender.getWorld().getSeed());
-        n.setNoiseType(FastNoiseLite.NoiseType.OpenSimplex2);
+        OpenSimplex2Sampler n = new OpenSimplex2Sampler((int) sender.getWorld().getSeed());
         n.setFrequency(freq);
         DeformedSphere sphere = new DeformedSphere(BukkitAdapter.adapt(sender).getLocation().toVector(), radius, deform, n);
         for(Vector3 v : sphere.getGeometry()) {

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/listeners/TerraListener.java

@@ -0,0 +1,22 @@
+package com.dfsek.terra.bukkit.listeners;
+
+import com.dfsek.terra.api.core.TerraPlugin;
+import com.dfsek.terra.api.core.event.EventListener;
+import com.dfsek.terra.api.core.event.events.config.ConfigPackPreLoadEvent;
+import com.dfsek.terra.bukkit.world.BukkitAdapter;
+import com.dfsek.terra.bukkit.world.BukkitTree;
+import org.bukkit.TreeType;
+
+public class TerraListener implements EventListener {
+    private final TerraPlugin main;
+
+    public TerraListener(TerraPlugin main) {
+        this.main = main;
+    }
+
+    public void injectTrees(ConfigPackPreLoadEvent event) {
+        for(TreeType value : TreeType.values()) {
+            event.getPack().getTreeRegistry().add(BukkitAdapter.TREE_TRANSFORMER.translate(value), new BukkitTree(value, main));
+        }
+    }
+}

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/population/SerializationUtil.java

@@ -11,7 +11,7 @@ import java.io.ObjectStreamClass;
 import java.io.Serializable;
 import java.lang.reflect.Field;
 
-public class SerializationUtil {
+public final class SerializationUtil {
     public static Object fromFile(File f) throws IOException, ClassNotFoundException {
         ObjectInputStream ois = new MovedObjectInputStream(new FileInputStream(f), "com.dfsek.terra.api.world.generation.population", "com.dfsek.terra.bukkit.population"); // Backwards compat with old Gaea location
         Object o = ois.readObject();

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/structure/WorldEditNotFoundException.java

@@ -1,6 +1,8 @@
 package com.dfsek.terra.bukkit.structure;
 
 public class WorldEditNotFoundException extends RuntimeException {
+    private static final long serialVersionUID = 3678822468346338227L;
+
     public WorldEditNotFoundException() {
     }
 

platforms/bukkit/src/main/java/com/dfsek/terra/bukkit/world/BukkitBiomeGrid.java

@@ -5,6 +5,7 @@ import com.dfsek.terra.api.platform.world.BiomeGrid;
 import org.bukkit.generator.ChunkGenerator;
 import org.jetbrains.annotations.NotNull;
 
+@SuppressWarnings("deprecation")
 public class BukkitBiomeGrid implements BiomeGrid {
     private final ChunkGenerator.BiomeGrid delegate;