Class

org.dianahep.histogrammar

FractionedHistogramMethods

Related Doc: package histogrammar

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class FractionedHistogramMethods extends AnyRef

Methods that are implicitly added to container combinations that look like fractioned histograms.

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Instance Constructors

  1. new FractionedHistogramMethods(fractioned: Fractioned[Selected[Binned[Counted, Counted, Counted, Counted]], Selected[Binned[Counted, Counted, Counted, Counted]]])

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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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  6. def confidenceIntervalNanflow(confidenceInterval: (Double, Double, Double) ⇒ Double, absz: Double = 1.0): (Double, Double, Double)

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    Low-central-high confidence interval triplet for the nanflow bin, given a confidence interval function.

    Low-central-high confidence interval triplet for the nanflow bin, given a confidence interval function.

    confidenceInterval

    confidence interval function, which takes (numerator entries, denominator entries, z) as arguments, where z is the "number of sigmas:" z = 0 is the central value, z = -1 is the 68% confidence level below the central value, and z = 1 is the 68% confidence level above the central value.

    absz

    absolute value of z to evaluate.

    returns

    confidence interval evaluated at (-absz, 0, absz).

  7. def confidenceIntervalOverflow(confidenceInterval: (Double, Double, Double) ⇒ Double, absz: Double = 1.0): (Double, Double, Double)

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    Low-central-high confidence interval triplet for the overflow bin, given a confidence interval function.

    Low-central-high confidence interval triplet for the overflow bin, given a confidence interval function.

    confidenceInterval

    confidence interval function, which takes (numerator entries, denominator entries, z) as arguments, where z is the "number of sigmas:" z = 0 is the central value, z = -1 is the 68% confidence level below the central value, and z = 1 is the 68% confidence level above the central value.

    absz

    absolute value of z to evaluate.

    returns

    confidence interval evaluated at (-absz, 0, absz).

  8. def confidenceIntervalUnderflow(confidenceInterval: (Double, Double, Double) ⇒ Double, absz: Double = 1.0): (Double, Double, Double)

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    Low-central-high confidence interval triplet for the overflow bin, given a confidence interval function.

    Low-central-high confidence interval triplet for the overflow bin, given a confidence interval function.

    confidenceInterval

    confidence interval function, which takes (numerator entries, denominator entries, z) as arguments, where z is the "number of sigmas:" z = 0 is the central value, z = -1 is the 68% confidence level below the central value, and z = 1 is the 68% confidence level above the central value.

    absz

    absolute value of z to evaluate.

    returns

    confidence interval evaluated at (-absz, 0, absz).

  9. def confidenceIntervalValues(confidenceInterval: (Double, Double, Double) ⇒ Double, absz: Double = 1.0): Seq[(Double, Double, Double)]

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    Low-central-high confidence interval triplet for all bins, given a confidence interval function.

    Low-central-high confidence interval triplet for all bins, given a confidence interval function.

    confidenceInterval

    confidence interval function, which takes (numerator entries, denominator entries, z) as arguments, where z is the "number of sigmas:" z = 0 is the central value, z = -1 is the 68% confidence level below the central value, and z = 1 is the 68% confidence level above the central value.

    absz

    absolute value of z to evaluate.

    returns

    confidence interval evaluated at (-absz, 0, absz).

  10. def denominatorBinned: Binned[Counted, Counted, Counted, Counted]

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  11. final def eq(arg0: AnyRef): Boolean

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  12. def equals(arg0: Any): Boolean

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  13. def finalize(): Unit

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  14. val fractioned: Fractioned[Selected[Binned[Counted, Counted, Counted, Counted]], Selected[Binned[Counted, Counted, Counted, Counted]]]

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  15. final def getClass(): Class[_]

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  16. def hashCode(): Int

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  17. def high: Double

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  18. final def isInstanceOf[T0]: Boolean

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  19. def low: Double

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  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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  23. def num: Int

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  24. def numeratorBinned: Binned[Counted, Counted, Counted, Counted]

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  25. def numericalNanflow: Double

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    Nanflow fraction as a number.

  26. def numericalOverflow: Double

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    Overflow fraction as a number.

  27. def numericalUnderflow: Double

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    Underflow fraction as a number.

  28. def numericalValues: Seq[Double]

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    Bin fractions as numbers.

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

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  30. def toString(): String

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  31. final def wait(): Unit

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

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

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