Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   Any

2.  final def ##(): Int

   Definition Classes

   Any

3.  final def ==(arg0: Any): Boolean

   Definition Classes

   Any

4.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

5.  def choice[A](xs: TraversableOnce[A]): A
6.  def choice[A](xs: Array[A]): A
7.  def getClass(): Class[_ <: AnyVal]

   Definition Classes

   AnyVal → Any

8.  final def isInstanceOf[T0]: Boolean

   Definition Classes

   Any

9.  def nextBytes(count: Int): Array[Byte]

   Creates an array of random bytes.

10.  def nextDouble(startInclusive: Double, endInclusive: Double): Double

    Returns a random double within the specified range.

11.  def nextExponential(lambda: Double): Double

    Exponential distribution.

    Exponential distribution. lambda is 1.0 divided by the desired mean. It should be nonzero. Returned values range from 0 to positive infinity if lambda is positive, and from negative infinity to 0 if lambda is negative.

12.  def nextFloat(startInclusive: Float, endInclusive: Float): Float

    Returns a random float within the specified range.

13.  def nextGaussian(mu: Double, sigma: Double): Double

    Gaussian distribution.

    Gaussian distribution. mu is the mean, and sigma is the standard deviation.

14.  def nextInt(startInclusive: Int, endExclusive: Int): Int

    Returns a random integer within the specified range.

15.  def nextLogNormal(mu: Double, sigma: Double): Double

    Log normal distribution.

    Log normal distribution. If you take the natural logarithm of this distribution, you’ll get a normal distribution with mean mu and standard deviation sigma. mu can have any value, and sigma must be greater than zero.

16.  def nextLong(startInclusive: Long, endExclusive: Long): Long

    Returns a random long within the specified range.

17.  def nextNormal(mu: Double, sigma: Double): Double
18.  def nextPareto(alpha: Double): Double

    Pareto distribution.

    Pareto distribution. alpha is the shape parameter.

19.  def nextTriangular(low: Double, high: Double, mode: Double): Double

    Triangular distribution.

    Triangular distribution. Continuous distribution bounded by given lower and upper limits, and having a given mode value in-between.

20.  def nextWeibull(alpha: Double, beta: Double): Double

    Weibull distribution.

    Weibull distribution. alpha is the scale parameter and beta is the shape parameter.

21.  val random: Random
22.  def randomAlphabetic(count: Int): String
23.  def randomAlphanumeric(count: Int): String
24.  def randomAscii(count: Int): String
25.  def randomNumeric(count: Int): String
26.  def randomString(count: Int, chars: String): String
27.  def randomString(count: Int, chars: Array[Char]): String
28.  def randomString(count: Int): String
29.  def sample[A, CC[X] <: TraversableOnce[X]](xs: CC[A], k: Int, withReplacement: Boolean = false)(implicit cbf: CanBuildFrom[CC[A], A, CC[A]]): CC[A]
30.  def sample[A](xs: Array[A], k: Int, withReplacement: Boolean)(implicit arg0: ClassTag[A]): Array[A]
31.  def sample[A](xs: Array[A], k: Int)(implicit arg0: ClassTag[A]): Array[A]
32.  def shuffleArray[A](xs: Array[A])(implicit arg0: ClassTag[A]): Array[A]
33.  def toString(): String

    Definition Classes

    Any