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)abbrev domain E04FDFA e04fdfAnnaType
++ Author: Brian Dupee
++ Date Created: February 1996
++ Date Last Updated: February 1996
++ References:
++ Dupe95 Using Computer Algebra to Choose and Apply Numerical Routines
++ Dewa92 Using Computer Algebra to Select Numerical Algorithms
++ Description:
++ \axiomType{e04fdfAnnaType} is a domain of \axiomType{NumericalOptimization}
++ for the NAG routine E04FDF, a general optimization routine which
++ can handle some singularities in the input function.  The function
++ \axiomFun{measure} measures the usefulness of the routine E04FDF
++ for the given problem.  The function \axiomFun{numericalOptimization}
++ performs the optimization by using \axiomType{NagOptimisationPackage}.

e04fdfAnnaType() : SIG == CODE where

  DF  ==> DoubleFloat
  EF  ==> Expression Float
  EDF  ==> Expression DoubleFloat
  PDF  ==> Polynomial DoubleFloat
  VPDF  ==> Vector Polynomial DoubleFloat
  LDF  ==> List DoubleFloat
  LOCDF  ==> List OrderedCompletion DoubleFloat
  MDF  ==> Matrix DoubleFloat
  MPDF  ==> Matrix Polynomial DoubleFloat
  MF  ==> Matrix Float
  MEF  ==> Matrix Expression Float
  LEDF  ==> List Expression DoubleFloat
  VEF  ==> Vector Expression Float
  NOA  ==> Record(fn:EDF, init:LDF, lb:LOCDF, cf:LEDF, ub:LOCDF)
  LSA  ==> Record(lfn:LEDF, init:LDF)
  EF2  ==> ExpressionFunctions2
  MI  ==> Matrix Integer
  INT  ==> Integer
  F  ==> Float
  NNI  ==> NonNegativeInteger
  S  ==> Symbol
  LS  ==> List Symbol
  MVCF  ==> MultiVariableCalculusFunctions
  ESTOOLS2 ==> ExpertSystemToolsPackage2
  SDF  ==> Stream DoubleFloat
  LSDF  ==> List Stream DoubleFloat
  SOCDF  ==> Segment OrderedCompletion DoubleFloat
  OCDF  ==> OrderedCompletion DoubleFloat

  SIG ==> NumericalOptimizationCategory 

  CODE ==> Result add

    Rep:=Result
    import Rep, NagOptimisationPackage
    import e04AgentsPackage,ExpertSystemToolsPackage

    measure(R:RoutinesTable,args:NOA) ==
      argsFn := args.fn
      string:String := "e04fdf is "
      positive?(#(args.cf) + #(args.lb) + #(args.ub)) =>
        string := concat(string,"unsuitable for constrained problems. ")
        [0.0,string]
      n:NNI := #(variables(argsFn)$EDF)
      (n>1)@Boolean => 
        string := concat(string,_
               "unsuitable for single instances of multivariate problems. ")
        [0.0,string]
      sumOfSquares(argsFn) case "failed" =>
        string := concat(string,"unsuitable.")
        [0.0,string]
      string := concat(string,_
                    "recommended since the function is a sum of squares.")
      [getMeasure(R,e04fdf@Symbol)$RoutinesTable, string]

    measure(R:RoutinesTable,args:LSA) ==
      string:String := "e04fdf is recommended"
      [getMeasure(R,e04fdf@Symbol)$RoutinesTable, string]

    numericalOptimization(args:NOA) ==
      argsFn := args.fn
      lw:INT := 14
      x := mat(args.init,1)
      (a := sumOfSquares(argsFn)) case EDF => 
        ArgsFn := vector([edf2ef(a)])$VEF
        f:Union(fn:FileName,fp:Asp50(LSFUN1)):= [retract(ArgsFn)$Asp50(LSFUN1)]
        out:Result := e04fdf(1,1,1,lw,x,-1,f)
        changeNameToObjf(fsumsq@Symbol,out)
      empty()$Result

    numericalOptimization(args:LSA) ==
      argsFn := copy args.lfn
      m:INT := #(argsFn)
      n:NNI := #(variables(args))
      nn:INT := n
      lw:INT := 
        (nn = 1) => 9+5*m
        nn*(7+n+2*m+((nn-1) quo 2)$INT)+3*m
      x := mat(args.init,n)
      ArgsFn:=vector([edf2ef(i)$ExpertSystemToolsPackage for i in argsFn])$VEF
      f:Union(fn:FileName,fp:Asp50(LSFUN1)) := [retract(ArgsFn)$Asp50(LSFUN1)]
      out:Result := e04fdf(m,n,1,lw,x,-1,f)
      changeNameToObjf(fsumsq@Symbol,out)