CTBuild

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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 buildTable(data: DRData, nb: Pair[NTuple[Int]], randomize: Boolean = false): CTable[Int]

   

   Method for constructing contingency table from a set of n-dim data points.

   Method for constructing contingency table from a set of n-dim data points.

   Note: no weight is applied to the data

   data

   container for dose-response data

   nb

   one-dimensional bin numbers for row and column values resp.

   randomize

   shuffles the data to produce a table with randomized data

   returns

   contingency table for ordered pair data points

6. def clone(): AnyRef

   

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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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   @throws( classOf[java.lang.Throwable] )

10. def findIndex(value: Double, dim: Tree[Bin]): Int

    

    Returns the index of the bin for insertion of a value into the table.

    Returns the index of the bin for insertion of a value into the table.

    value

    The number to be inserted.

    dim

    The binary tree specifying the bounds of each bin.

    returns

    The index of the bin that should contain the value.

11. def findVectIndex(tuple: NTuple[Double], binDelims: NTuple[Tree[Bin]], m: Map[NTuple[Int], Int]): Int

    

    Returns index for insertion of data point into contingency table

    Returns index for insertion of data point into contingency table

    tuple

    (possibly multidimensional) data point to be inserted into contingency table

    binDelims

    tuple of delimiting trees used to determine respective bin indices

    m

    mapping of bin indices, whose index is used for insertion into the contingency table

    returns

    index of 2D bin

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

    

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13. def hashCode(): Int

    

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14. final def isInstanceOf[T0]: Boolean

    

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15. def keyFromDimLengths(dLs: Vector[Int], acc: Vector[NTuple[Int]] = Vector(Vector())): Vector[NTuple[Int]]

    

    Produces a vector of bin index vectors in order to find the bin number for some arbitrary ndim data point

    Produces a vector of bin index vectors in order to find the bin number for some arbitrary ndim data point

    dLs

    vector of dimension lengths (bins or values)

    acc

    accumulator for building key

    returns

    key of bin indices

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    @tailrec()

16. final def ne(arg0: AnyRef): Boolean

    

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17. final def notify(): Unit

    

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18. final def notifyAll(): Unit

    

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19. def partitionList(v: Vector[Double], numBins: Int): List[Bin]

    

    Divides list into sublists with approximately equal numbers of elements.

    Divides list into sublists with approximately equal numbers of elements.

    If the items in the list v can be divided equally into numBins sublists, each sublist will contain k = len(v) / numBins items. If the elements cannot be divided evenly, then there are r = len(v) mod numBins elements forming the remainder. In this case the last r bins will contain k+1 elements, while all preceding bins will contain k elements. Therefore the number of elements in the bins will not differ by more than one.

    Note that the maximum from each List element becomes a bin delimiter, so if the sequence of Doubles is partitioned such that the maximum in more than one distinct List elements is identical, the bins in question are effectively collapsed into one bin

    v

    The list of doubles to be partitioned.

    numBins

    The number of bins to divide the list into.

    returns

    A list of length numBins containing each of the sublists.

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

    

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21. def toString(): String

    

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22. final def wait(): Unit

    

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

    

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

    

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