Packages

trait Histogram[T <: AnyVal] extends Serializable

Data object representing a histogram of values.

Linear Supertypes
Serializable, Serializable, AnyRef, Any
Known Subclasses
FastMapHistogram, IntHistogram, MutableHistogram, MutableIntHistogram, StreamingHistogram
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  1. Histogram
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Abstract Value Members

  1. abstract def bucketCount(): Int

    The number of buckets utilized by this Histogram.

  2. abstract def cdf(): Array[(Double, Double)]

    CDF of the distribution.

  3. abstract def foreach(f: (T, Long) ⇒ Unit): Unit

    Execute the given function on the value and count of each bucket in the histogram.

  4. abstract def foreachValue(f: (T) ⇒ Unit): Unit

    Execute the given function on the value of each bucket in the histogram.

    Execute the given function on the value of each bucket in the histogram.

    f

    A unit function of one parameter

  5. abstract def itemCount(item: T): Long

    Return the number of occurrences for 'item'.

  6. abstract def maxBucketCount(): Int

    Return the maximum number of buckets of this histogram.

  7. abstract def maxValue(): Option[T]

    Return the largest item seen.

  8. abstract def mean(): Option[Double]

    Compute the mean of the distribution represented by the histogram.

  9. abstract def median(): Option[T]

    Compute the median of the distribution represented by the histogram.

  10. abstract def merge(histogram: Histogram[T]): Histogram[T]

    Return the sum of this histogram and the given one (the sum is the histogram that would result from seeing all of the values seen by the two antecedent histograms).

  11. abstract def minValue(): Option[T]

    Return the smallest item seen.

  12. abstract def mode(): Option[T]

    Compute the mode of the distribution represented by the histogram.

  13. abstract def mutable(): MutableHistogram[T]

    Return a mutable copy of this histogram.

  14. abstract def quantileBreaks(num: Int): Array[T]

    Compute the quantile breaks of the histogram, where the latter are evenly spaced in 'num' increments starting at zero percent.

  15. abstract def rawValues(): Array[T]

    Return an array containing the values seen by this histogram.

  16. abstract def statistics(): Option[Statistics[T]]

    Return a statistics object for the distribution represented by the histogram.

    Return a statistics object for the distribution represented by the histogram. Contains among other things: mean, mode, median, and so-forth.

  17. abstract def totalCount(): Long

    Return the total number of occurrences for all items.

  18. abstract def values(): Array[T]

    Return a sorted array of values seen by this histogram.

Concrete 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
    Definition Classes
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  5. def binCounts(): Seq[(T, Long)]

    Return sequence of tuples pairing bin label value and to its associated count.

  6. def clone(): AnyRef
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    protected[lang]
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    @throws( ... ) @native()
  7. final def eq(arg0: AnyRef): Boolean
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  8. def equals(arg0: Any): Boolean
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  9. def finalize(): Unit
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  10. final def getClass(): Class[_]
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  11. def hashCode(): Int
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  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
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  13. def minMaxValues(): Option[(T, T)]

    Return the smallest and largest items seen as a tuple.

  14. final def ne(arg0: AnyRef): Boolean
    Definition Classes
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  15. final def notify(): Unit
    Definition Classes
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    @native()
  16. final def notifyAll(): Unit
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    @native()
  17. final def synchronized[T0](arg0: ⇒ T0): T0
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  18. def toString(): String
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  19. final def wait(): Unit
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    @throws( ... )
  20. final def wait(arg0: Long, arg1: Int): Unit
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    @throws( ... )
  21. final def wait(arg0: Long): Unit
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