anchor.diff:  
   ///fits a spline with two extrema present, where the first one is a maximum
   let minMaxSpline = 
  -    Hermite.splineIncreasing x_Values (Hermite.calcMeanOfRep y_Values 3) weighting 2  
  +    TemporalClassification.splineIncreasing x_Values (TemporalClassification.calcMeanOfRep y_Values 3) weighting 2  
       |> fun (constraintMatrices,result) -> result
   
   //returns a list of tuples that describe extrema. The first item defines if the extremum
   //is a maximum (1) or minimum (-1) and the second item defines the corresponding x value.
   let isolateExtrema = 
  -    Hermite.getExtrema x_Values minMaxSpline.TraceA minMaxSpline.TraceC
  +    TemporalClassification.getExtrema x_Values minMaxSpline.TraceA minMaxSpline.TraceC
       |> fun extrema -> sprintf "Location of extrema are: %A" extrema
   
   (*** include-value:isolateExtrema ***)
  +
  +(**
  +To classify a signal according to its shape, a specially tailored function can be used. In this case the extrema list is empty because the 
  +best spline is monotonically and since the parentClass is In0 the spline is monotonically increasing.
  +*)
  +
  +//returns the shape class that matches the given case best. (constraints for 2 extrema are investigated)
  +let bestFit = 
  +    TemporalClassification.getBestFit x_Values y_Values 3 weightingMethod
  +    |> fun spline ->
  +        let parentShape = TemporalClassification.getParentShape x_Values spline.TraceA spline.TraceC
  +        let extrema     = TemporalClassification.getExtrema x_Values spline.TraceA spline.TraceC
  +        sprintf "ParentShape: %A\nLocation of extrema are: %A" parentShape extrema
  +
  +
  +(*** include-value:bestFit ***)
  
positive.code: let rawDataChart =   
      //calculates the means and standard deviations of the three replicates and plots it as line
      let line =
          Hermite.calcMeanOfRep y_Values 3
          |> Seq.indexed
          |> Chart.Line
          |> Chart.withTraceName (sprintf "means")
          |> Chart.withYErrorStyle(Array=Hermite.calcStDevOfRep y_Values 3)
  
      //plots all measurements as points 
      let points =
  
negative.code: a lower weight to these points as their importance in the shape determination should be decreased.
  
  *)
  let weightingMethod = TemporalClassification.WeightingMethod.StandardDeviationAdj
  
  //calculate the points weighting according to the specified weightingmethod
  let weighting = TemporalClassification.getWeighting x_Values y_Values weightingMethod 3
  
  let weightingColumnChart = 
      Matrix.getDiag weighting
  