class="kw">package com.hypixel.hytale.procedurallib.property;

class="kw">import com.hypixel.hytale.math.util.MathUtil;

class="kw">public class BlendNoiseProperty class="kw">implements NoiseProperty {
   class="kw">private class="kw">final NoiseProperty alpha;
   class="kw">private class="kw">final NoiseProperty[] noises;
   class="kw">private class="kw">final double[] thresholds;
   class="kw">private class="kw">final class="kw">transient double[] normalize;

   class="kw">public BlendNoiseProperty(NoiseProperty var1, NoiseProperty[] var2, double[] var3) {
      this.alpha = var1;
      this.noises = var2;
      this.thresholds = var3;
      this.normalize = new double[var3.length];

      for (int var4 = 1; var4 < var3.length; var4++) {
         if (var3[var4] <= var3[var4 - 1]) {
            throw new IllegalStateException("Thresholds must be in ascending order");
         }

         this.normalize[var4] = 1.0 / (var3[var4] - var3[var4 - 1]);
      }
   }

   @Override
   class="kw">public double get(int var1, double var2, double var4) {
      if (this.noises.length == 0) {
         class="kw">return 0.0;
      }

      double var6 = this.alpha.get(var1, var2, var4);
      if (var6 <= this.thresholds[0]) {
         class="kw">return this.noises[0].get(var1, var2, var4);
      }

      if (var6 >= this.thresholds[this.thresholds.length - 1]) {
         class="kw">return this.noises[this.noises.length - 1].get(var1, var2, var4);
      }

      for (int var8 = 1; var8 < this.noises.length; var8++) {
         if (var6 <= this.thresholds[var8]) {
            double var9 = (var6 - this.thresholds[var8 - 1]) * this.normalize[var8];
            double var11 = this.noises[var8 - 1].get(var1, var2, var4);
            double var13 = this.noises[var8].get(var1, var2, var4);
            class="kw">return MathUtil.lerp(var11, var13, var9);
         }
      }

      class="kw">return 0.0;
   }

   @Override
   class="kw">public double get(int var1, double var2, double var4, double var6) {
      if (this.noises.length == 0) {
         class="kw">return 0.0;
      }

      double var8 = this.alpha.get(var1, var2, var4, var6);
      if (var8 <= this.thresholds[0]) {
         class="kw">return this.noises[0].get(var1, var2, var4, var6);
      }

      if (var8 >= this.thresholds[this.thresholds.length - 1]) {
         class="kw">return this.noises[this.noises.length - 1].get(var1, var2, var4, var6);
      }

      for (int var10 = 1; var10 < this.noises.length; var10++) {
         if (var8 <= this.thresholds[var10]) {
            double var11 = (var8 - this.thresholds[var10 - 1]) * this.normalize[var10];
            double var13 = this.noises[var10 - 1].get(var1, var2, var4, var6);
            double var15 = this.noises[var10 + 0].get(var1, var2, var4, var6);
            class="kw">return MathUtil.lerp(var13, var15, var11);
         }
      }

      class="kw">return 0.0;
   }
}