Examples of java.util.Random.nextFloat()

java.util.Random.nextFloat()
Returns the next pseudorandom, uniformly distributed {@code float}value between {@code 0.0} and {@code 1.0} from this randomnumber generator's sequence.
The general contract of {@code nextFloat} is that one{@code float} value, chosen (approximately) uniformly from therange {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), ispseudorandomly generated and returned. All 2²⁴ possible {@code float} valuesof the form m x 2^-24, where m is a positive integer less than 2²⁴ , are produced with (approximately) equal probability.
The method {@code nextFloat} is implemented by class {@code Random}as if by:
```
  {@code}public float nextFloat()  return next(24) / ((float)(1 << 24)); }}
```
The hedge "approximately" is used in the foregoing description only because the next method is only approximately an unbiased source of independently chosen bits. If it were a perfect source of randomly chosen bits, then the algorithm shown would choose {@code float}values from the stated range with perfect uniformity.
[In early versions of Java, the result was incorrectly calculated as:
```
  {@code return next(30) / ((float)(1 << 30));}
```
This might seem to be equivalent, if not better, but in fact it introduced a slight nonuniformity because of the bias in the rounding of floating-point numbers: it was slightly more likely that the low-order bit of the significand would be 0 than that it would be 1.] @return the next pseudorandom, uniformly distributed {@code float}value between {@code 0.0} and {@code 1.0} from thisrandom number generator's sequence

    final Random random = newRandom();
    final RepeatingTokenStream ts = new RepeatingTokenStream(val);


    Analyzer analyzer = new Analyzer() {
      public TokenStream tokenStream(String fieldName, Reader reader) {
        if (random.nextFloat() < percentDocs) ts.num = random.nextInt(maxTF)+1;
        else ts.num=0;
        return ts;
      }
    };

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            insertSQL.append(i);
            insertSQL.append(',');
            insertSQL.append(r.nextLong());
            insertSQL.append(',');


            insertSQL.append(r.nextFloat());
            insertSQL.append(',');
            insertSQL.append(r.nextFloat());
            insertSQL.append(',');
            insertSQL.append(r.nextDouble());
            insertSQL.append(',');

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            insertSQL.append(r.nextLong());
            insertSQL.append(',');


            insertSQL.append(r.nextFloat());
            insertSQL.append(',');
            insertSQL.append(r.nextFloat());
            insertSQL.append(',');
            insertSQL.append(r.nextDouble());
            insertSQL.append(',');


            insertSQL.append("462.54");

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            break;
        case DataType.DOUBLE:
            runTest(r.nextDouble(),inner);
            break;
        case DataType.FLOAT:
            runTest(r.nextFloat(),inner);
            break;
        case DataType.INTEGER:
            runTest(r.nextLong(),inner);
            break;
        case DataType.LONG:

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      byte[] family;
      byte[] qualifier;
      byte[] value;


      // generate it or repeat, it should compress well
      if (0 < i && randomizer.nextFloat() < CHANCE_TO_REPEAT) {
        row = keyValues.get(randomizer.nextInt(keyValues.size())).getRow();
      } else {
        row = new byte[FIELD_LENGTH];
        randomizer.nextBytes(row);
      }

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        family = new byte[FIELD_LENGTH];
        randomizer.nextBytes(family);
      } else {
        family = keyValues.get(0).getFamily();
      }
      if (0 < i && randomizer.nextFloat() < CHANCE_TO_REPEAT) {
        qualifier = keyValues.get(
            randomizer.nextInt(keyValues.size())).getQualifier();
      } else {
        qualifier = new byte[FIELD_LENGTH];
        randomizer.nextBytes(qualifier);

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            randomizer.nextInt(keyValues.size())).getQualifier();
      } else {
        qualifier = new byte[FIELD_LENGTH];
        randomizer.nextBytes(qualifier);
      }
      if (0 < i && randomizer.nextFloat() < CHANCE_TO_REPEAT) {
        value = keyValues.get(randomizer.nextInt(keyValues.size())).getValue();
      } else {
        value = new byte[FIELD_LENGTH];
        randomizer.nextBytes(value);
      }

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        value = keyValues.get(randomizer.nextInt(keyValues.size())).getValue();
      } else {
        value = new byte[FIELD_LENGTH];
        randomizer.nextBytes(value);
      }
      if (0 < i && randomizer.nextFloat() < CHANCE_TO_REPEAT) {
        timestamp = keyValues.get(
            randomizer.nextInt(keyValues.size())).getTimestamp();
      } else {
        timestamp = randomizer.nextLong();
      }

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    int remaining = (int)Math.ceil(items.length * ratio);


    List<T> selectedItems = new ArrayList<T>(remaining);


    for (int i=0; i<items.length && remaining > 0; i++) {
      if (random.nextFloat() < ((float)remaining/(items.length-i))) {
        selectedItems.add(items[i]);
        remaining--;
      }
    }

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    int cols = 100;
    float[][] matrix = new float[rows][cols];
    Random random = new Random();
    for (int i = 0; i < rows; i++) {
      for (int j = 0; j < cols; j++) {
        matrix[i][j] = random.nextFloat();
      }
    }


    // Test that inverting a transformed matrix gives the original matrix.
    RegionPlacementMaintainer.RandomizedMatrix rm =

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