Examples of java.util.Random.nextDouble()

java.util.Random.nextDouble()
Returns the next pseudorandom, uniformly distributed {@code double} value between {@code 0.0} and{@code 1.0} from this random number generator's sequence.
The general contract of {@code nextDouble} is that one{@code double} value, chosen (approximately) uniformly from therange {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), ispseudorandomly generated and returned.
The method {@code nextDouble} is implemented by class {@code Random}as if by:
```
  {@code}public double nextDouble()  return (((long)next(26) << 27) + next(27)) / (double)(1L << 53); }}
```
The hedge "approximately" is used in the foregoing description only because the {@code next} method is only approximately an unbiasedsource of independently chosen bits. If it were a perfect source of randomly chosen bits, then the algorithm shown would choose {@code double} values from the stated range with perfect uniformity.
[In early versions of Java, the result was incorrectly calculated as:
```
  {@code return (((long)next(27) << 27) + next(27)) / (double)(1L << 54);}
```
This might seem to be equivalent, if not better, but in fact it introduced a large nonuniformity because of the bias in the rounding of floating-point numbers: it was three times as likely that the low-order bit of the significand would be 0 than that it would be 1! This nonuniformity probably doesn't matter much in practice, but we strive for perfection.] @return the next pseudorandom, uniformly distributed {@code double}value between {@code 0.0} and {@code 1.0} from thisrandom number generator's sequence @see Math#random

            for (int i = 2; i <= 20; i++) {
                ArrayList<Segment> segments = new ArrayList<Segment>();


                for(int j = 0; j < i; j++) {
                    segments.add(new Segment(new Point(rand.nextDouble()*100, rand.nextDouble()*100),
                                             new Point(rand.nextDouble()*100, rand.nextDouble()*100)));
                }


                assertTrue(SegmentsIntersect.any(segments) ==
                            SegmentsIntersect.any_Naive(segments));
            }

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        Random r = new Random();
        int k;
        T temp;
        
        do {
            k = (int)(j*r.nextDouble());
            
            temp = res.get(k);
            res.set(k, res.get(j-1));
            res.set(j-1, temp);

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        if (!Locations.hasDLInitialized) {
            Benchmark.start("DlUtils");
            Logger.logInfo("DownloadUtils.run() starting");
            downloadServers.put("Automatic", Locations.masterRepoNoHTTP);
            Random r = new Random();
            double choice = r.nextDouble();
            try { // Super catch-all to ensure the launcher always renders
                try {
                    // Fetch the percentage json first
                    String json = IOUtils.toString(new URL(Locations.masterRepo + "/FTB2/static/balance.json"));
                    JsonElement element = new JsonParser().parse(json);

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        for (int n = 3; n <= 20; n++) {
            ArrayList<Point> points = new ArrayList<Point>();
            
            for(int i = 0; i < n; i++) {
                points.add(new Point(rand.nextDouble()*100,
                                     rand.nextDouble()*100));
            }
        
            checkConvexHull(points);
        }

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        for (int n = 3; n <= 20; n++) {
            ArrayList<Point> points = new ArrayList<Point>();
            
            for(int i = 0; i < n; i++) {
                points.add(new Point(rand.nextDouble()*100,
                                     rand.nextDouble()*100));
            }
        
            checkConvexHull(points);
        }
    }

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        for (int n = 3; n <= 100; n++) {
            ArrayList<Point> points = new ArrayList<Point>();
            
            for(int i = 0; i < n; i++) {
                points.add(new Point(rand.nextDouble()*100,
                                     rand.nextDouble()*100));
            }
        
            checkClosestPair(points);
        }

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        for (int n = 3; n <= 100; n++) {
            ArrayList<Point> points = new ArrayList<Point>();
            
            for(int i = 0; i < n; i++) {
                points.add(new Point(rand.nextDouble()*100,
                                     rand.nextDouble()*100));
            }
        
            checkClosestPair(points);
        }
    }

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        points.add(new Point(-3, 3));
        points.add(new Point(3, -3));
        points.add(new Point(3, 3));


        for (int i = 0; i < 1000; i++) {
            points.add(new Point(rand.nextDouble()*6-3, rand.nextDouble()*6-3));
        }


        // Triangulate (Delaunay)
        ArrayList<Triangle> triangulation = Delaunay.randomizedIncremental(points);
    }

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        points.add(new Point(-3, 3));
        points.add(new Point(3, -3));
        points.add(new Point(3, 3));


        for (int i = 0; i < 1000; i++) {
            points.add(new Point(rand.nextDouble()*6-3, rand.nextDouble()*6-3));
        }


        // Triangulate (Delaunay)
        ArrayList<Triangle> triangulation = Delaunay.randomizedIncremental(points);
    }

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                points.add(new ProjectedPoint3D(-3, 3, 0));
                points.add(new ProjectedPoint3D(3, -3, 0));
                points.add(new ProjectedPoint3D(3, 3, 0));
                
                for (int i = 0; i < (Integer)pointCount.getValue(); i++) {
                    points.add(new ProjectedPoint3D(rand.nextDouble()*6-3,
                            rand.nextDouble()*6-3, rand.nextDouble()*0.5-0.25));
                }
                
                // Triangulate (Delaunay)
                triangulation = Delaunay.randomizedIncremental(points);

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