Package org.apache.commons.math4.random

Class RandomUtils.DataGenerator

  • Enclosing class:
    RandomUtils
    public static class RandomUtils.DataGenerator
extends java.lang.Object
    Various random data generation routines.

    • Method Summary

      Modifier and Type Method Description
      java.lang.String nextHexString​(int len, boolean useSha1)
      Generates a random string of hex characters of length len.
      long nextLong​(long lower, long upper)
      Generates a uniformly distributed random long integer between lower and upper (endpoints included).
      double nextUniform​(double lower, double upper)
      Generates a uniformly distributed random value from the open interval (lower, upper) (i.e., endpoints excluded).
      double nextUniform​(double lower, double upper, boolean lowerInclusive)
      Generates a uniformly distributed random value from the interval (lower, upper) or the interval [lower, upper).

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Method Detail

      • nextHexString

        public java.lang.String nextHexString​(int len,
                                      boolean useSha1)
        Generates a random string of hex characters of length len. Algorithm Description: how hexadecimal strings are generated depends on the value of the useSha1 argument.
        • If useSha1 == false, a 2-step process is used:
          1. len / 2 + 1 binary bytes are generated using the underlying generator.
          2. Each binary byte is translated into 2 hex digits.
        • If useSha1 == true, hex strings are generated in 40-byte segments using a 3-step process:
          1. 20 random bytes are generated using the underlying generator.
          2. SHA-1 hash is applied to yield a 20-byte binary digest.
          3. Each byte of the binary digest is converted to 2 hex digits.
        Parameters:
        len - Length of the generated string.
        useSha1 - Whether to use a digest. If true (resp. false), the 3-step (resp. 2-step) process will be used.
        Returns:
        the random string.
        Throws:
        NotStrictlyPositiveException - if len <= 0.

      • nextLong

        public long nextLong​(long lower,
                     long upper)
        Generates a uniformly distributed random long integer between lower and upper (endpoints included).
        Parameters:
        lower - Lower bound for generated long integer.
        upper - Upper bound for generated long integer.
        Returns:
        a random long integer greater than or equal to lower and less than or equal to upper
        Throws:
        NumberIsTooLargeException - if lower >= upper

      • nextUniform

        public double nextUniform​(double lower,
                          double upper)
        Generates a uniformly distributed random value from the open interval (lower, upper) (i.e., endpoints excluded).

        Definition: Uniform Distribution lower and upper - lower are the location and scale parameters, respectively.

        Algorithm Description: scales the output of Random.nextDouble(), but rejects 0 values (i.e., will generate another random double if Random.nextDouble() returns 0). This is necessary to provide a symmetric output interval (both endpoints excluded).

        Parameters:
        lower - Lower bound of the support (excluded).
        upper - Upper bound of the support (excluded).
        Returns:
        a uniformly distributed random value between lower and upper (both excluded).
        Throws:
        NumberIsTooLargeException - if lower >= upper.
        NotFiniteNumberException - if one of the bounds is infinite.
        NotANumberException - if one of the bounds is NaN.

      • nextUniform

        public double nextUniform​(double lower,
                          double upper,
                          boolean lowerInclusive)
        Generates a uniformly distributed random value from the interval (lower, upper) or the interval [lower, upper). The lower bound is thus optionally included, while the upper bound is always excluded.

        Definition: Uniform Distribution lower and upper - lower are the location and scale parameters, respectively.

        Algorithm Description: if the lower bound is excluded, scales the output of "nextDouble()", but rejects 0 values (i.e. it will generate another random double if "nextDouble()" returns 0). This is necessary to provide a symmetric output interval (both endpoints excluded).

        Parameters:
        lower - Lower bound of the support.
        upper - Exclusive upper bound of the support.
        lowerInclusive - true if the lower bound is inclusive.
        Returns:
        a uniformly distributed random value in the (lower, upper) interval, if lowerInclusive is false, or in the [lower, upper) interval, if lowerInclusive is true.
        Throws:
        NumberIsTooLargeException - if lower >= upper.
        NotFiniteNumberException - if one of the bounds is infinite.
        NotANumberException - if one of the bounds is NaN.