Examples of java.util.Random.nextGaussian()

java.util.Random.nextGaussian()
een -1.0 and 1.0 v2=2 * nextDouble() - 1; // between -1.0 and 1.0 s=v1 * v1 + v2 * v2; } while (s >= 1 || s == 0); double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); nextNextGaussian = v2 * multiplier; haveNextNextGaussian = true; return v1 * multiplier; } }} This uses the polar method of G. E. P. Box, M. E. Muller, and G. Marsaglia, as described by Donald E. Knuth in The Art of Computer Programming, Volume 3: Seminumerical Algorithms, section 3.4.1, subsection C, algorithm P. Note that it generates two independent values at the cost of only one call to {@code StrictMath.log}and one call to {@code StrictMath.sqrt}. @return the next pseudorandom, Gaussian ("normally") distributed{@code double} value with mean {@code 0.0} andstandard deviation {@code 1.0} from this random numbergenerator's sequence

            long startTime = System.currentTimeMillis();
            int totalEntriesReturned = 0;
            
            for (int id = 0; id < queryCount; id++) {
              float x = (float) random.nextGaussian() * canvasSize;
              float y = (float) random.nextGaussian() * canvasSize;
              
              List<Integer> l = ld.nearestN(new Point(x, y), n, Float.POSITIVE_INFINITY);
              
              totalEntriesReturned += l.size();

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  }


  public List<GameChange> receive(Damage damage) {
     List<GameChange> retList = new ArrayList<GameChange>();
    Random random = new Random();
    double healthDecrease = Math.abs(random.nextGaussian() * 0.25);
    SetMapObjectHealth change = new SetMapObjectHealth(this.getID(), 
                               this.getHealth() - healthDecrease);
    retList.add(change);
     return retList;
  }

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    final MetricsHistogram h = new MetricsHistogram("testHistogram", null);


    final long[] data = new long[1000];


    for (int i = 0; i < data.length; i++) {
      data[i] = (long) (r.nextGaussian() * 10000.0);
      h.update(data[i]);
    }


    final Snapshot s = h.getSnapshot();
    Arrays.sort(data);

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      Random random = new Random();
        int n = A.numRows(), m = A.numColumns();
        double[][] values = new double[n][m];
        for (int i = 0; i < n; ++i)
            for (int j = 0; j < m; ++j) {
              double value = random.nextGaussian();
                values[i][j] = value;
                A.set(i, j, value);
            }
        return values;
    }

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  public static void upperPopulateGauss(Matrix A) {
    Random random = new Random();
    for (int i = 0; i < A.numRows(); i++)
      for (int j = 0; j <= i; j++)
        A.set(i, j, random.nextGaussian());
  }


    /**
     * Populates the strictly lower triangular part of the matrix
     *

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                public String toString() {
                    return random+".nextGaussian()";
                }
                @Override
                public double nextGaussian() {
                    return random.nextGaussian();
                }
            });
        }
    }

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        tmp += y * 0x0123456789ABCDEFL;
        Random rng = new Random(tmp);
        int starX = x * STAR_GRID + rng.nextInt(STAR_GRID);
        int starY = y * STAR_GRID + rng.nextInt(STAR_GRID);
        g2d.setColor(new Color(rng.nextInt()));
        int size = (int) (1.5 + 3 * Math.abs(rng.nextGaussian()));
        g2d.fillOval(starX - size/2, starY - size/2, size, size);
      }
      
    }
  }

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{
  public static void main(String[] argv)
  {
    Random r = new Random();
    IHistogram1D h1 = new Histogram1D("AIDA 1D Histogram",40,-3,3);
    for (int i=0; i<10000; i++) h1.fill(r.nextGaussian());
    
    IHistogram2D h2 = new Histogram2D("AIDA 2D Histogram",40,-3,3,40,-3,3);
    for (int i=0; i<10000; i++) h2.fill(r.nextGaussian(),r.nextGaussian());
    
    // Write the results as a PlotML files!

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    Random r = new Random();
    IHistogram1D h1 = new Histogram1D("AIDA 1D Histogram",40,-3,3);
    for (int i=0; i<10000; i++) h1.fill(r.nextGaussian());
    
    IHistogram2D h2 = new Histogram2D("AIDA 2D Histogram",40,-3,3,40,-3,3);
    for (int i=0; i<10000; i++) h2.fill(r.nextGaussian(),r.nextGaussian());
    
    // Write the results as a PlotML files!
    writeAsXML(h1,"aida1.xml");
    writeAsXML(h2,"aida2.xml");

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    Random r = new Random();
    IHistogram1D h1 = new Histogram1D("AIDA 1D Histogram",40,-3,3);
    for (int i=0; i<10000; i++) h1.fill(r.nextGaussian());
    
    IHistogram2D h2 = new Histogram2D("AIDA 2D Histogram",40,-3,3,40,-3,3);
    for (int i=0; i<10000; i++) h2.fill(r.nextGaussian(),r.nextGaussian());
    
    // Write the results as a PlotML files!
    writeAsXML(h1,"aida1.xml");
    writeAsXML(h2,"aida2.xml");

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