spark.timeseries

Run

class Run [T] extends AnyRef

A Class that represents a measurement run, containing the measurements inside. Usage:

import scala.collection.mutable.ArrayBuffer
import spark.timeseries.Run

var data = new ArrayBuffer[Array[Double]]
data += Array(0.0,0.1,0.2,0.3,0.4)
data += Array(1.0,1.1,1.2,1.3,1.4)
val run = new Run[Double](data.toArray: _*)
for (k <- run.list) {
  println(k.mkString("[", ", ", "]"))
}
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Instance Constructors

  1. new Run (list: Array[T]*)(implicit arg0: ClassManifest[T])

    Creates a new Run with the specified lines of data.

Value Members

  1. def != (arg0: AnyRef): Boolean

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  10. def finalize (): Unit

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  11. def getClass (): java.lang.Class[_]

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  12. def hashCode (): Int

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  13. def isInstanceOf [T0] : Boolean

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  14. def length : Int

  15. var list : Array[T]*

  16. def ne (arg0: AnyRef): Boolean

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  17. def notify (): Unit

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  19. def synchronized [T0] (arg0: ⇒ T0): T0

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  20. def toString (): String

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  21. def wait (): Unit

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

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  23. def wait (arg0: Long): Unit

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