IntHistogram

abstract def bucketCount(): Int

The number of buckets utilized by this Histogram.

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

CDF of the distribution.

abstract def foreachValue(f: (Int) ⇒ Unit): Unit

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

abstract def itemCount(item: Int): Long

Return the number of occurrences for 'item'.

abstract def maxBucketCount(): Int

Return the maximum number of buckets of this histogram.

abstract def maxValue(): Option[Int]

Return the largest item seen.

abstract def merge(histogram: Histogram[Int]): Histogram[Int]

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).

abstract def minValue(): Option[Int]

Return the smallest item seen.

abstract def mutable(): MutableHistogram[Int]

Return a mutable copy of this histogram.

abstract def quantileBreaks(num: Int): Array[Int]

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

abstract def rawValues(): Array[Int]

Return an array containing the values seen by this histogram.

abstract def totalCount(): Long

Return the total number of occurrences for all items.

abstract def values(): Array[Int]

Return a sorted array of values seen by this histogram.

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def binCounts(): Seq[(Int, Long)]

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

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def foreach(f: (Int, Long) ⇒ Unit): Unit

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

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def mean(): Option[Double]

Compute the mean of the distribution represented by the histogram.

def median(): Option[Int]

Compute the median of the distribution represented by the histogram.

def minMaxValues(): Option[(Int, Int)]

Return the smallest and largest items seen as a tuple.

def mode(): Option[Int]

Compute the mode of the distribution represented by the histogram.

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def statistics(): Option[Statistics[Int]]

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

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit