Class

breeze.stats.random

HaltonSequence

Related Doc: package random

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class HaltonSequence extends Rand[DenseVector[Double]]

Generates a quasi-random sequence of dim-dimensional vectors

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  1. HaltonSequence
  2. Rand
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Instance Constructors

  1. new HaltonSequence(dim: Int)

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  6. def condition(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

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    Definition Classes
    Rand
  7. def draw(): DenseVector[Double]

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    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to sample()

    Definition Classes
    HaltonSequenceRand
  8. def drawOpt(): Option[DenseVector[Double]]

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    Overridden by filter/map/flatmap for monadic invocations.

    Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here

    Definition Classes
    Rand
  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def filter(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

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    Definition Classes
    Rand
  12. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  13. def flatMap[E](f: (DenseVector[Double]) ⇒ Rand[E]): Rand[E]

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    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  14. def foreach(f: (DenseVector[Double]) ⇒ Unit): Unit

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    Samples one element and qpplies the provided function to it.

    Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage:

     for(x <- Rand.uniform) { println(x) } 
    

    f

    the function to be applied

    Definition Classes
    Rand
  15. def get(): DenseVector[Double]

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    Definition Classes
    Rand
  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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    Definition Classes
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  19. def map[E](f: (DenseVector[Double]) ⇒ E): Rand[E]

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    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_*2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2*x

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  20. final def ne(arg0: AnyRef): Boolean

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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    Definition Classes
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  23. val primes: Array[Long]

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  24. def sample(n: Int): IndexedSeq[DenseVector[Double]]

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    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  25. def sample(): DenseVector[Double]

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    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to get()

    Definition Classes
    Rand
  26. def samples: Iterator[DenseVector[Double]]

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    An infinitely long iterator that samples repeatedly from the Rand

    An infinitely long iterator that samples repeatedly from the Rand

    returns

    an iterator that repeatedly samples

    Definition Classes
    Rand
  27. def samplesVector[U >: DenseVector[Double]](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

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    Return a vector of samples.

    Return a vector of samples.

    Definition Classes
    Rand
  28. final def synchronized[T0](arg0: ⇒ T0): T0

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  29. def toString(): String

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  30. final def wait(): Unit

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    @throws( ... )
  31. final def wait(arg0: Long, arg1: Int): Unit

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  32. final def wait(arg0: Long): Unit

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    @throws( ... )
  33. def withFilter(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

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    Definition Classes
    Rand

Inherited from Rand[DenseVector[Double]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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