source: trunk/sources/HeuristicLab.ExtLibs/HeuristicLab.ALGLIB/2.5.0/ALGLIB-2.5.0/ratint.cs @ 3932

/*************************************************************************
Copyright (c) 2007-2009, Sergey Bochkanov (ALGLIB project).

>>> SOURCE LICENSE >>>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation (www.fsf.org); either version 2 of the 
License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

A copy of the GNU General Public License is available at
http://www.fsf.org/licensing/licenses

>>> END OF LICENSE >>>
*************************************************************************/

using System;

namespace alglib
{
    public class ratint
    {
        /*************************************************************************
        Barycentric interpolant.
        *************************************************************************/
        public struct barycentricinterpolant
        {
            public int n;
            public double sy;
            public double[] x;
            public double[] y;
            public double[] w;
        };


        /*************************************************************************
        Barycentric fitting report:
            TaskRCond       reciprocal of task's condition number
            RMSError        RMS error
            AvgError        average error
            AvgRelError     average relative error (for non-zero Y[I])
            MaxError        maximum error
        *************************************************************************/
        public struct barycentricfitreport
        {
            public double taskrcond;
            public int dbest;
            public double rmserror;
            public double avgerror;
            public double avgrelerror;
            public double maxerror;
        };




        public const int brcvnum = 10;


        /*************************************************************************
        Rational interpolation using barycentric formula

        F(t) = SUM(i=0,n-1,w[i]*f[i]/(t-x[i])) / SUM(i=0,n-1,w[i]/(t-x[i]))

        Input parameters:
            B   -   barycentric interpolant built with one of model building
                    subroutines.
            T   -   interpolation point

        Result:
            barycentric interpolant F(t)

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static double barycentriccalc(ref barycentricinterpolant b,
            double t)
        {
            double result = 0;
            double s1 = 0;
            double s2 = 0;
            double s = 0;
            double v = 0;
            int i = 0;

            
            //
            // special case: N=1
            //
            if( b.n==1 )
            {
                result = b.sy*b.y[0];
                return result;
            }
            
            //
            // Here we assume that task is normalized, i.e.:
            // 1. abs(Y[i])<=1
            // 2. abs(W[i])<=1
            // 3. X[] is ordered
            //
            s = Math.Abs(t-b.x[0]);
            for(i=0; i<=b.n-1; i++)
            {
                v = b.x[i];
                if( (double)(v)==(double)(t) )
                {
                    result = b.sy*b.y[i];
                    return result;
                }
                v = Math.Abs(t-v);
                if( (double)(v)<(double)(s) )
                {
                    s = v;
                }
            }
            s1 = 0;
            s2 = 0;
            for(i=0; i<=b.n-1; i++)
            {
                v = s/(t-b.x[i]);
                v = v*b.w[i];
                s1 = s1+v*b.y[i];
                s2 = s2+v;
            }
            result = b.sy*s1/s2;
            return result;
        }


        /*************************************************************************
        Differentiation of barycentric interpolant: first derivative.

        Algorithm used in this subroutine is very robust and should not fail until
        provided with values too close to MaxRealNumber  (usually  MaxRealNumber/N
        or greater will overflow).

        INPUT PARAMETERS:
            B   -   barycentric interpolant built with one of model building
                    subroutines.
            T   -   interpolation point

        OUTPUT PARAMETERS:
            F   -   barycentric interpolant at T
            DF  -   first derivative
            
        NOTE


          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricdiff1(ref barycentricinterpolant b,
            double t,
            ref double f,
            ref double df)
        {
            double v = 0;
            double vv = 0;
            int i = 0;
            int k = 0;
            double n0 = 0;
            double n1 = 0;
            double d0 = 0;
            double d1 = 0;
            double s0 = 0;
            double s1 = 0;
            double xk = 0;
            double xi = 0;
            double xmin = 0;
            double xmax = 0;
            double xscale1 = 0;
            double xoffs1 = 0;
            double xscale2 = 0;
            double xoffs2 = 0;
            double xprev = 0;

            
            //
            // special case: N=1
            //
            if( b.n==1 )
            {
                f = b.sy*b.y[0];
                df = 0;
                return;
            }
            if( (double)(b.sy)==(double)(0) )
            {
                f = 0;
                df = 0;
                return;
            }
            System.Diagnostics.Debug.Assert((double)(b.sy)>(double)(0), "BarycentricDiff1: internal error");
            
            //
            // We assume than N>1 and B.SY>0. Find:
            // 1. pivot point (X[i] closest to T)
            // 2. width of interval containing X[i]
            //
            v = Math.Abs(b.x[0]-t);
            k = 0;
            xmin = b.x[0];
            xmax = b.x[0];
            for(i=1; i<=b.n-1; i++)
            {
                vv = b.x[i];
                if( (double)(Math.Abs(vv-t))<(double)(v) )
                {
                    v = Math.Abs(vv-t);
                    k = i;
                }
                xmin = Math.Min(xmin, vv);
                xmax = Math.Max(xmax, vv);
            }
            
            //
            // pivot point found, calculate dNumerator and dDenominator
            //
            xscale1 = 1/(xmax-xmin);
            xoffs1 = -(xmin/(xmax-xmin))+1;
            xscale2 = 2;
            xoffs2 = -3;
            t = t*xscale1+xoffs1;
            t = t*xscale2+xoffs2;
            xk = b.x[k];
            xk = xk*xscale1+xoffs1;
            xk = xk*xscale2+xoffs2;
            v = t-xk;
            n0 = 0;
            n1 = 0;
            d0 = 0;
            d1 = 0;
            xprev = -2;
            for(i=0; i<=b.n-1; i++)
            {
                xi = b.x[i];
                xi = xi*xscale1+xoffs1;
                xi = xi*xscale2+xoffs2;
                System.Diagnostics.Debug.Assert((double)(xi)>(double)(xprev), "BarycentricDiff1: points are too close!");
                xprev = xi;
                if( i!=k )
                {
                    vv = AP.Math.Sqr(t-xi);
                    s0 = (t-xk)/(t-xi);
                    s1 = (xk-xi)/vv;
                }
                else
                {
                    s0 = 1;
                    s1 = 0;
                }
                vv = b.w[i]*b.y[i];
                n0 = n0+s0*vv;
                n1 = n1+s1*vv;
                vv = b.w[i];
                d0 = d0+s0*vv;
                d1 = d1+s1*vv;
            }
            f = b.sy*n0/d0;
            df = (n1*d0-n0*d1)/AP.Math.Sqr(d0);
            if( (double)(df)!=(double)(0) )
            {
                df = Math.Sign(df)*Math.Exp(Math.Log(Math.Abs(df))+Math.Log(b.sy)+Math.Log(xscale1)+Math.Log(xscale2));
            }
        }


        /*************************************************************************
        Differentiation of barycentric interpolant: first/second derivatives.

        INPUT PARAMETERS:
            B   -   barycentric interpolant built with one of model building
                    subroutines.
            T   -   interpolation point

        OUTPUT PARAMETERS:
            F   -   barycentric interpolant at T
            DF  -   first derivative
            D2F -   second derivative

        NOTE: this algorithm may fail due to overflow/underflor if  used  on  data
        whose values are close to MaxRealNumber or MinRealNumber.  Use more robust
        BarycentricDiff1() subroutine in such cases.


          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricdiff2(ref barycentricinterpolant b,
            double t,
            ref double f,
            ref double df,
            ref double d2f)
        {
            double v = 0;
            double vv = 0;
            int i = 0;
            int k = 0;
            double n0 = 0;
            double n1 = 0;
            double n2 = 0;
            double d0 = 0;
            double d1 = 0;
            double d2 = 0;
            double s0 = 0;
            double s1 = 0;
            double s2 = 0;
            double xk = 0;
            double xi = 0;

            f = 0;
            df = 0;
            d2f = 0;
            
            //
            // special case: N=1
            //
            if( b.n==1 )
            {
                f = b.sy*b.y[0];
                df = 0;
                d2f = 0;
                return;
            }
            if( (double)(b.sy)==(double)(0) )
            {
                f = 0;
                df = 0;
                d2f = 0;
                return;
            }
            System.Diagnostics.Debug.Assert((double)(b.sy)>(double)(0), "BarycentricDiff: internal error");
            
            //
            // We assume than N>1 and B.SY>0. Find:
            // 1. pivot point (X[i] closest to T)
            // 2. width of interval containing X[i]
            //
            v = Math.Abs(b.x[0]-t);
            k = 0;
            for(i=1; i<=b.n-1; i++)
            {
                vv = b.x[i];
                if( (double)(Math.Abs(vv-t))<(double)(v) )
                {
                    v = Math.Abs(vv-t);
                    k = i;
                }
            }
            
            //
            // pivot point found, calculate dNumerator and dDenominator
            //
            xk = b.x[k];
            v = t-xk;
            n0 = 0;
            n1 = 0;
            n2 = 0;
            d0 = 0;
            d1 = 0;
            d2 = 0;
            for(i=0; i<=b.n-1; i++)
            {
                if( i!=k )
                {
                    xi = b.x[i];
                    vv = AP.Math.Sqr(t-xi);
                    s0 = (t-xk)/(t-xi);
                    s1 = (xk-xi)/vv;
                    s2 = -(2*(xk-xi)/(vv*(t-xi)));
                }
                else
                {
                    s0 = 1;
                    s1 = 0;
                    s2 = 0;
                }
                vv = b.w[i]*b.y[i];
                n0 = n0+s0*vv;
                n1 = n1+s1*vv;
                n2 = n2+s2*vv;
                vv = b.w[i];
                d0 = d0+s0*vv;
                d1 = d1+s1*vv;
                d2 = d2+s2*vv;
            }
            f = b.sy*n0/d0;
            df = b.sy*(n1*d0-n0*d1)/AP.Math.Sqr(d0);
            d2f = b.sy*((n2*d0-n0*d2)*AP.Math.Sqr(d0)-(n1*d0-n0*d1)*2*d0*d1)/AP.Math.Sqr(AP.Math.Sqr(d0));
        }


        /*************************************************************************
        This subroutine performs linear transformation of the argument.

        INPUT PARAMETERS:
            B       -   rational interpolant in barycentric form
            CA, CB  -   transformation coefficients: x = CA*t + CB

        OUTPUT PARAMETERS:
            B       -   transformed interpolant with X replaced by T

          -- ALGLIB PROJECT --
             Copyright 19.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentriclintransx(ref barycentricinterpolant b,
            double ca,
            double cb)
        {
            int i = 0;
            int j = 0;
            double v = 0;

            
            //
            // special case, replace by constant F(CB)
            //
            if( (double)(ca)==(double)(0) )
            {
                b.sy = barycentriccalc(ref b, cb);
                v = 1;
                for(i=0; i<=b.n-1; i++)
                {
                    b.y[i] = 1;
                    b.w[i] = v;
                    v = -v;
                }
                return;
            }
            
            //
            // general case: CA<>0
            //
            for(i=0; i<=b.n-1; i++)
            {
                b.x[i] = (b.x[i]-cb)/ca;
            }
            if( (double)(ca)<(double)(0) )
            {
                for(i=0; i<=b.n-1; i++)
                {
                    if( i<b.n-1-i )
                    {
                        j = b.n-1-i;
                        v = b.x[i];
                        b.x[i] = b.x[j];
                        b.x[j] = v;
                        v = b.y[i];
                        b.y[i] = b.y[j];
                        b.y[j] = v;
                        v = b.w[i];
                        b.w[i] = b.w[j];
                        b.w[j] = v;
                    }
                    else
                    {
                        break;
                    }
                }
            }
        }


        /*************************************************************************
        This  subroutine   performs   linear  transformation  of  the  barycentric
        interpolant.

        INPUT PARAMETERS:
            B       -   rational interpolant in barycentric form
            CA, CB  -   transformation coefficients: B2(x) = CA*B(x) + CB

        OUTPUT PARAMETERS:
            B       -   transformed interpolant

          -- ALGLIB PROJECT --
             Copyright 19.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentriclintransy(ref barycentricinterpolant b,
            double ca,
            double cb)
        {
            int i = 0;
            double v = 0;
            int i_ = 0;

            for(i=0; i<=b.n-1; i++)
            {
                b.y[i] = ca*b.sy*b.y[i]+cb;
            }
            b.sy = 0;
            for(i=0; i<=b.n-1; i++)
            {
                b.sy = Math.Max(b.sy, Math.Abs(b.y[i]));
            }
            if( (double)(b.sy)>(double)(0) )
            {
                v = 1/b.sy;
                for(i_=0; i_<=b.n-1;i_++)
                {
                    b.y[i_] = v*b.y[i_];
                }
            }
        }


        /*************************************************************************
        Extracts X/Y/W arrays from rational interpolant

        INPUT PARAMETERS:
            B   -   barycentric interpolant

        OUTPUT PARAMETERS:
            N   -   nodes count, N>0
            X   -   interpolation nodes, array[0..N-1]
            F   -   function values, array[0..N-1]
            W   -   barycentric weights, array[0..N-1]

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricunpack(ref barycentricinterpolant b,
            ref int n,
            ref double[] x,
            ref double[] y,
            ref double[] w)
        {
            double v = 0;
            int i_ = 0;

            n = b.n;
            x = new double[n];
            y = new double[n];
            w = new double[n];
            v = b.sy;
            for(i_=0; i_<=n-1;i_++)
            {
                x[i_] = b.x[i_];
            }
            for(i_=0; i_<=n-1;i_++)
            {
                y[i_] = v*b.y[i_];
            }
            for(i_=0; i_<=n-1;i_++)
            {
                w[i_] = b.w[i_];
            }
        }


        /*************************************************************************
        Serialization of the barycentric interpolant

        INPUT PARAMETERS:
            B   -   barycentric interpolant

        OUTPUT PARAMETERS:
            RA      -   array of real numbers which contains interpolant,
                        array[0..RLen-1]
            RLen    -   RA lenght

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricserialize(ref barycentricinterpolant b,
            ref double[] ra,
            ref int ralen)
        {
            int i_ = 0;
            int i1_ = 0;

            ralen = 2+2+3*b.n;
            ra = new double[ralen];
            ra[0] = ralen;
            ra[1] = brcvnum;
            ra[2] = b.n;
            ra[3] = b.sy;
            i1_ = (0) - (4);
            for(i_=4; i_<=4+b.n-1;i_++)
            {
                ra[i_] = b.x[i_+i1_];
            }
            i1_ = (0) - (4+b.n);
            for(i_=4+b.n; i_<=4+2*b.n-1;i_++)
            {
                ra[i_] = b.y[i_+i1_];
            }
            i1_ = (0) - (4+2*b.n);
            for(i_=4+2*b.n; i_<=4+3*b.n-1;i_++)
            {
                ra[i_] = b.w[i_+i1_];
            }
        }


        /*************************************************************************
        Unserialization of the barycentric interpolant

        INPUT PARAMETERS:
            RA  -   array of real numbers which contains interpolant,

        OUTPUT PARAMETERS:
            B   -   barycentric interpolant

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricunserialize(ref double[] ra,
            ref barycentricinterpolant b)
        {
            int i_ = 0;
            int i1_ = 0;

            System.Diagnostics.Debug.Assert((int)Math.Round(ra[1])==brcvnum, "BarycentricUnserialize: corrupted array!");
            b.n = (int)Math.Round(ra[2]);
            b.sy = ra[3];
            b.x = new double[b.n];
            b.y = new double[b.n];
            b.w = new double[b.n];
            i1_ = (4) - (0);
            for(i_=0; i_<=b.n-1;i_++)
            {
                b.x[i_] = ra[i_+i1_];
            }
            i1_ = (4+b.n) - (0);
            for(i_=0; i_<=b.n-1;i_++)
            {
                b.y[i_] = ra[i_+i1_];
            }
            i1_ = (4+2*b.n) - (0);
            for(i_=0; i_<=b.n-1;i_++)
            {
                b.w[i_] = ra[i_+i1_];
            }
        }


        /*************************************************************************
        Copying of the barycentric interpolant

        INPUT PARAMETERS:
            B   -   barycentric interpolant

        OUTPUT PARAMETERS:
            B2  -   copy(B1)

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentriccopy(ref barycentricinterpolant b,
            ref barycentricinterpolant b2)
        {
            int i_ = 0;

            b2.n = b.n;
            b2.sy = b.sy;
            b2.x = new double[b2.n];
            b2.y = new double[b2.n];
            b2.w = new double[b2.n];
            for(i_=0; i_<=b2.n-1;i_++)
            {
                b2.x[i_] = b.x[i_];
            }
            for(i_=0; i_<=b2.n-1;i_++)
            {
                b2.y[i_] = b.y[i_];
            }
            for(i_=0; i_<=b2.n-1;i_++)
            {
                b2.w[i_] = b.w[i_];
            }
        }


        /*************************************************************************
        Rational interpolant from X/Y/W arrays

        F(t) = SUM(i=0,n-1,w[i]*f[i]/(t-x[i])) / SUM(i=0,n-1,w[i]/(t-x[i]))

        INPUT PARAMETERS:
            X   -   interpolation nodes, array[0..N-1]
            F   -   function values, array[0..N-1]
            W   -   barycentric weights, array[0..N-1]
            N   -   nodes count, N>0

        OUTPUT PARAMETERS:
            B   -   barycentric interpolant built from (X, Y, W)

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricbuildxyw(ref double[] x,
            ref double[] y,
            ref double[] w,
            int n,
            ref barycentricinterpolant b)
        {
            int i_ = 0;

            System.Diagnostics.Debug.Assert(n>0, "BarycentricBuildXYW: incorrect N!");
            
            //
            // fill X/Y/W
            //
            b.x = new double[n];
            b.y = new double[n];
            b.w = new double[n];
            for(i_=0; i_<=n-1;i_++)
            {
                b.x[i_] = x[i_];
            }
            for(i_=0; i_<=n-1;i_++)
            {
                b.y[i_] = y[i_];
            }
            for(i_=0; i_<=n-1;i_++)
            {
                b.w[i_] = w[i_];
            }
            b.n = n;
            
            //
            // Normalize
            //
            barycentricnormalize(ref b);
        }


        /*************************************************************************
        Rational interpolant without poles

        The subroutine constructs the rational interpolating function without real
        poles  (see  'Barycentric rational interpolation with no  poles  and  high
        rates of approximation', Michael S. Floater. and  Kai  Hormann,  for  more
        information on this subject).

        Input parameters:
            X   -   interpolation nodes, array[0..N-1].
            Y   -   function values, array[0..N-1].
            N   -   number of nodes, N>0.
            D   -   order of the interpolation scheme, 0 <= D <= N-1.
                    D<0 will cause an error.
                    D>=N it will be replaced with D=N-1.
                    if you don't know what D to choose, use small value about 3-5.

        Output parameters:
            B   -   barycentric interpolant.

        Note:
            this algorithm always succeeds and calculates the weights  with  close
            to machine precision.

          -- ALGLIB PROJECT --
             Copyright 17.06.2007 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricbuildfloaterhormann(ref double[] x,
            ref double[] y,
            int n,
            int d,
            ref barycentricinterpolant b)
        {
            double s0 = 0;
            double s = 0;
            double v = 0;
            int i = 0;
            int j = 0;
            int k = 0;
            int[] perm = new int[0];
            double[] wtemp = new double[0];
            int i_ = 0;

            System.Diagnostics.Debug.Assert(n>0, "BarycentricFloaterHormann: N<=0!");
            System.Diagnostics.Debug.Assert(d>=0, "BarycentricFloaterHormann: incorrect D!");
            
            //
            // Prepare
            //
            if( d>n-1 )
            {
                d = n-1;
            }
            b.n = n;
            
            //
            // special case: N=1
            //
            if( n==1 )
            {
                b.x = new double[n];
                b.y = new double[n];
                b.w = new double[n];
                b.x[0] = x[0];
                b.y[0] = y[0];
                b.w[0] = 1;
                barycentricnormalize(ref b);
                return;
            }
            
            //
            // Fill X/Y
            //
            b.x = new double[n];
            b.y = new double[n];
            for(i_=0; i_<=n-1;i_++)
            {
                b.x[i_] = x[i_];
            }
            for(i_=0; i_<=n-1;i_++)
            {
                b.y[i_] = y[i_];
            }
            tsort.tagsortfastr(ref b.x, ref b.y, n);
            
            //
            // Calculate Wk
            //
            b.w = new double[n];
            s0 = 1;
            for(k=1; k<=d; k++)
            {
                s0 = -s0;
            }
            for(k=0; k<=n-1; k++)
            {
                
                //
                // Wk
                //
                s = 0;
                for(i=Math.Max(k-d, 0); i<=Math.Min(k, n-1-d); i++)
                {
                    v = 1;
                    for(j=i; j<=i+d; j++)
                    {
                        if( j!=k )
                        {
                            v = v/Math.Abs(b.x[k]-b.x[j]);
                        }
                    }
                    s = s+v;
                }
                b.w[k] = s0*s;
                
                //
                // Next S0
                //
                s0 = -s0;
            }
            
            //
            // Normalize
            //
            barycentricnormalize(ref b);
        }


        /*************************************************************************
        Weghted rational least  squares  fitting  using  Floater-Hormann  rational
        functions  with  optimal  D  chosen  from  [0,9],  with  constraints   and
        individual weights.

        Equidistant  grid  with M node on [min(x),max(x)]  is  used to build basis
        functions. Different values of D are tried, optimal D (least WEIGHTED root
        mean square error) is chosen.  Task  is  linear,  so  linear least squares
        solver  is  used.  Complexity  of  this  computational  scheme is O(N*M^2)
        (mostly dominated by the least squares solver).

        SEE ALSO
        * BarycentricFitFloaterHormann(), "lightweight" fitting without invididual
          weights and constraints.

        INPUT PARAMETERS:
            X   -   points, array[0..N-1].
            Y   -   function values, array[0..N-1].
            W   -   weights, array[0..N-1]
                    Each summand in square  sum  of  approximation deviations from
                    given  values  is  multiplied  by  the square of corresponding
                    weight. Fill it by 1's if you don't  want  to  solve  weighted
                    task.
            N   -   number of points, N>0.
            XC  -   points where function values/derivatives are constrained,
                    array[0..K-1].
            YC  -   values of constraints, array[0..K-1]
            DC  -   array[0..K-1], types of constraints:
                    * DC[i]=0   means that S(XC[i])=YC[i]
                    * DC[i]=1   means that S'(XC[i])=YC[i]
                    SEE BELOW FOR IMPORTANT INFORMATION ON CONSTRAINTS
            K   -   number of constraints, 0<=K<M.
                    K=0 means no constraints (XC/YC/DC are not used in such cases)
            M   -   number of basis functions ( = number_of_nodes), M>=2.

        OUTPUT PARAMETERS:
            Info-   same format as in LSFitLinearWC() subroutine.
                    * Info>0    task is solved
                    * Info<=0   an error occured:
                                -4 means inconvergence of internal SVD
                                -3 means inconsistent constraints
                                -1 means another errors in parameters passed
                                   (N<=0, for example)
            B   -   barycentric interpolant.
            Rep -   report, same format as in LSFitLinearWC() subroutine.
                    Following fields are set:
                    * DBest         best value of the D parameter
                    * RMSError      rms error on the (X,Y).
                    * AvgError      average error on the (X,Y).
                    * AvgRelError   average relative error on the non-zero Y
                    * MaxError      maximum error
                                    NON-WEIGHTED ERRORS ARE CALCULATED

        IMPORTANT:
            this subroitine doesn't calculate task's condition number for K<>0.

        SETTING CONSTRAINTS - DANGERS AND OPPORTUNITIES:

        Setting constraints can lead  to undesired  results,  like ill-conditioned
        behavior, or inconsistency being detected. From the other side,  it allows
        us to improve quality of the fit. Here we summarize  our  experience  with
        constrained barycentric interpolants:
        * excessive  constraints  can  be  inconsistent.   Floater-Hormann   basis
          functions aren't as flexible as splines (although they are very smooth).
        * the more evenly constraints are spread across [min(x),max(x)],  the more
          chances that they will be consistent
        * the  greater  is  M (given  fixed  constraints),  the  more chances that
          constraints will be consistent
        * in the general case, consistency of constraints IS NOT GUARANTEED.
        * in the several special cases, however, we CAN guarantee consistency.
        * one of this cases is constraints on the function  VALUES at the interval
          boundaries. Note that consustency of the  constraints  on  the  function
          DERIVATIVES is NOT guaranteed (you can use in such cases  cubic  splines
          which are more flexible).
        * another  special  case  is ONE constraint on the function value (OR, but
          not AND, derivative) anywhere in the interval

        Our final recommendation is to use constraints  WHEN  AND  ONLY  WHEN  you
        can't solve your task without them. Anything beyond  special  cases  given
        above is not guaranteed and may result in inconsistency.

          -- ALGLIB PROJECT --
             Copyright 18.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricfitfloaterhormannwc(ref double[] x,
            ref double[] y,
            ref double[] w,
            int n,
            ref double[] xc,
            ref double[] yc,
            ref int[] dc,
            int k,
            int m,
            ref int info,
            ref barycentricinterpolant b,
            ref barycentricfitreport rep)
        {
            int d = 0;
            int i = 0;
            double wrmscur = 0;
            double wrmsbest = 0;
            barycentricinterpolant locb = new barycentricinterpolant();
            barycentricfitreport locrep = new barycentricfitreport();
            int locinfo = 0;

            if( n<1 | m<2 | k<0 | k>=m )
            {
                info = -1;
                return;
            }
            
            //
            // Find optimal D
            //
            // Info is -3 by default (degenerate constraints).
            // If LocInfo will always be equal to -3, Info will remain equal to -3.
            // If at least once LocInfo will be -4, Info will be -4.
            //
            wrmsbest = AP.Math.MaxRealNumber;
            rep.dbest = -1;
            info = -3;
            for(d=0; d<=Math.Min(9, n-1); d++)
            {
                barycentricfitwcfixedd(x, y, ref w, n, xc, yc, ref dc, k, m, d, ref locinfo, ref locb, ref locrep);
                System.Diagnostics.Debug.Assert(locinfo==-4 | locinfo==-3 | locinfo>0, "BarycentricFitFloaterHormannWC: unexpected result from BarycentricFitWCFixedD!");
                if( locinfo>0 )
                {
                    
                    //
                    // Calculate weghted RMS
                    //
                    wrmscur = 0;
                    for(i=0; i<=n-1; i++)
                    {
                        wrmscur = wrmscur+AP.Math.Sqr(w[i]*(y[i]-barycentriccalc(ref locb, x[i])));
                    }
                    wrmscur = Math.Sqrt(wrmscur/n);
                    if( (double)(wrmscur)<(double)(wrmsbest) | rep.dbest<0 )
                    {
                        barycentriccopy(ref locb, ref b);
                        rep.dbest = d;
                        info = 1;
                        rep.rmserror = locrep.rmserror;
                        rep.avgerror = locrep.avgerror;
                        rep.avgrelerror = locrep.avgrelerror;
                        rep.maxerror = locrep.maxerror;
                        rep.taskrcond = locrep.taskrcond;
                        wrmsbest = wrmscur;
                    }
                }
                else
                {
                    if( locinfo!=-3 & info<0 )
                    {
                        info = locinfo;
                    }
                }
            }
        }


        /*************************************************************************
        Rational least squares fitting, without weights and constraints.

        See BarycentricFitFloaterHormannWC() for more information.

          -- ALGLIB PROJECT --
             Copyright 18.08.2009 by Bochkanov Sergey
        *************************************************************************/
        public static void barycentricfitfloaterhormann(ref double[] x,
            ref double[] y,
            int n,
            int m,
            ref int info,
            ref barycentricinterpolant b,
            ref barycentricfitreport rep)
        {
            double[] w = new double[0];
            double[] xc = new double[0];
            double[] yc = new double[0];
            int[] dc = new int[0];
            int i = 0;

            if( n<1 )
            {
                info = -1;
                return;
            }
            w = new double[n];
            for(i=0; i<=n-1; i++)
            {
                w[i] = 1;
            }
            barycentricfitfloaterhormannwc(ref x, ref y, ref w, n, ref xc, ref yc, ref dc, 0, m, ref info, ref b, ref rep);
        }


        /*************************************************************************
        Normalization of barycentric interpolant:
        * B.N, B.X, B.Y and B.W are initialized
        * B.SY is NOT initialized
        * Y[] is normalized, scaling coefficient is stored in B.SY
        * W[] is normalized, no scaling coefficient is stored
        * X[] is sorted

        Internal subroutine.
        *************************************************************************/
        private static void barycentricnormalize(ref barycentricinterpolant b)
        {
            int[] p1 = new int[0];
            int[] p2 = new int[0];
            int i = 0;
            int j = 0;
            int j2 = 0;
            double v = 0;
            int i_ = 0;

            
            //
            // Normalize task: |Y|<=1, |W|<=1, sort X[]
            //
            b.sy = 0;
            for(i=0; i<=b.n-1; i++)
            {
                b.sy = Math.Max(b.sy, Math.Abs(b.y[i]));
            }
            if( (double)(b.sy)>(double)(0) & (double)(Math.Abs(b.sy-1))>(double)(10*AP.Math.MachineEpsilon) )
            {
                v = 1/b.sy;
                for(i_=0; i_<=b.n-1;i_++)
                {
                    b.y[i_] = v*b.y[i_];
                }
            }
            v = 0;
            for(i=0; i<=b.n-1; i++)
            {
                v = Math.Max(v, Math.Abs(b.w[i]));
            }
            if( (double)(v)>(double)(0) & (double)(Math.Abs(v-1))>(double)(10*AP.Math.MachineEpsilon) )
            {
                v = 1/v;
                for(i_=0; i_<=b.n-1;i_++)
                {
                    b.w[i_] = v*b.w[i_];
                }
            }
            for(i=0; i<=b.n-2; i++)
            {
                if( (double)(b.x[i+1])<(double)(b.x[i]) )
                {
                    tsort.tagsort(ref b.x, b.n, ref p1, ref p2);
                    for(j=0; j<=b.n-1; j++)
                    {
                        j2 = p2[j];
                        v = b.y[j];
                        b.y[j] = b.y[j2];
                        b.y[j2] = v;
                        v = b.w[j];
                        b.w[j] = b.w[j2];
                        b.w[j2] = v;
                    }
                    break;
                }
            }
        }


        /*************************************************************************
        Internal subroutine, calculates barycentric basis functions.
        Used for efficient simultaneous calculation of N basis functions.

          -- ALGLIB --
             Copyright 17.08.2009 by Bochkanov Sergey
        *************************************************************************/
        private static void barycentriccalcbasis(ref barycentricinterpolant b,
            double t,
            ref double[] y)
        {
            double s2 = 0;
            double s = 0;
            double v = 0;
            int i = 0;
            int j = 0;
            int i_ = 0;

            
            //
            // special case: N=1
            //
            if( b.n==1 )
            {
                y[0] = 1;
                return;
            }
            
            //
            // Here we assume that task is normalized, i.e.:
            // 1. abs(Y[i])<=1
            // 2. abs(W[i])<=1
            // 3. X[] is ordered
            //
            // First, we decide: should we use "safe" formula (guarded
            // against overflow) or fast one?
            //
            s = Math.Abs(t-b.x[0]);
            for(i=0; i<=b.n-1; i++)
            {
                v = b.x[i];
                if( (double)(v)==(double)(t) )
                {
                    for(j=0; j<=b.n-1; j++)
                    {
                        y[j] = 0;
                    }
                    y[i] = 1;
                    return;
                }
                v = Math.Abs(t-v);
                if( (double)(v)<(double)(s) )
                {
                    s = v;
                }
            }
            s2 = 0;
            for(i=0; i<=b.n-1; i++)
            {
                v = s/(t-b.x[i]);
                v = v*b.w[i];
                y[i] = v;
                s2 = s2+v;
            }
            v = 1/s2;
            for(i_=0; i_<=b.n-1;i_++)
            {
                y[i_] = v*y[i_];
            }
        }


        /*************************************************************************
        Internal Floater-Hormann fitting subroutine for fixed D
        *************************************************************************/
        private static void barycentricfitwcfixedd(double[] x,
            double[] y,
            ref double[] w,
            int n,
            double[] xc,
            double[] yc,
            ref int[] dc,
            int k,
            int m,
            int d,
            ref int info,
            ref barycentricinterpolant b,
            ref barycentricfitreport rep)
        {
            double[,] fmatrix = new double[0,0];
            double[,] cmatrix = new double[0,0];
            double[] y2 = new double[0];
            double[] w2 = new double[0];
            double[] sx = new double[0];
            double[] sy = new double[0];
            double[] sbf = new double[0];
            double[] xoriginal = new double[0];
            double[] yoriginal = new double[0];
            double[] tmp = new double[0];
            lsfit.lsfitreport lrep = new lsfit.lsfitreport();
            double v0 = 0;
            double v1 = 0;
            double mx = 0;
            barycentricinterpolant b2 = new barycentricinterpolant();
            int i = 0;
            int j = 0;
            int relcnt = 0;
            double xa = 0;
            double xb = 0;
            double sa = 0;
            double sb = 0;
            double decay = 0;
            int i_ = 0;

            x = (double[])x.Clone();
            y = (double[])y.Clone();
            xc = (double[])xc.Clone();
            yc = (double[])yc.Clone();

            if( n<1 | m<2 | k<0 | k>=m )
            {
                info = -1;
                return;
            }
            for(i=0; i<=k-1; i++)
            {
                info = 0;
                if( dc[i]<0 )
                {
                    info = -1;
                }
                if( dc[i]>1 )
                {
                    info = -1;
                }
                if( info<0 )
                {
                    return;
                }
            }
            
            //
            // weight decay for correct handling of task which becomes
            // degenerate after constraints are applied
            //
            decay = 10000*AP.Math.MachineEpsilon;
            
            //
            // Scale X, Y, XC, YC
            //
            lsfit.lsfitscalexy(ref x, ref y, n, ref xc, ref yc, ref dc, k, ref xa, ref xb, ref sa, ref sb, ref xoriginal, ref yoriginal);
            
            //
            // allocate space, initialize:
            // * FMatrix-   values of basis functions at X[]
            // * CMatrix-   values (derivatives) of basis functions at XC[]
            //
            y2 = new double[n+m];
            w2 = new double[n+m];
            fmatrix = new double[n+m, m];
            if( k>0 )
            {
                cmatrix = new double[k, m+1];
            }
            y2 = new double[n+m];
            w2 = new double[n+m];
            
            //
            // Prepare design and constraints matrices:
            // * fill constraints matrix
            // * fill first N rows of design matrix with values
            // * fill next M rows of design matrix with regularizing term
            // * append M zeros to Y
            // * append M elements, mean(abs(W)) each, to W
            //
            sx = new double[m];
            sy = new double[m];
            sbf = new double[m];
            for(j=0; j<=m-1; j++)
            {
                sx[j] = (double)(2*j)/((double)(m-1))-1;
            }
            for(i=0; i<=m-1; i++)
            {
                sy[i] = 1;
            }
            barycentricbuildfloaterhormann(ref sx, ref sy, m, d, ref b2);
            mx = 0;
            for(i=0; i<=n-1; i++)
            {
                barycentriccalcbasis(ref b2, x[i], ref sbf);
                for(i_=0; i_<=m-1;i_++)
                {
                    fmatrix[i,i_] = sbf[i_];
                }
                y2[i] = y[i];
                w2[i] = w[i];
                mx = mx+Math.Abs(w[i])/n;
            }
            for(i=0; i<=m-1; i++)
            {
                for(j=0; j<=m-1; j++)
                {
                    if( i==j )
                    {
                        fmatrix[n+i,j] = decay;
                    }
                    else
                    {
                        fmatrix[n+i,j] = 0;
                    }
                }
                y2[n+i] = 0;
                w2[n+i] = mx;
            }
            if( k>0 )
            {
                for(j=0; j<=m-1; j++)
                {
                    for(i=0; i<=m-1; i++)
                    {
                        sy[i] = 0;
                    }
                    sy[j] = 1;
                    barycentricbuildfloaterhormann(ref sx, ref sy, m, d, ref b2);
                    for(i=0; i<=k-1; i++)
                    {
                        System.Diagnostics.Debug.Assert(dc[i]>=0 & dc[i]<=1, "BarycentricFit: internal error!");
                        barycentricdiff1(ref b2, xc[i], ref v0, ref v1);
                        if( dc[i]==0 )
                        {
                            cmatrix[i,j] = v0;
                        }
                        if( dc[i]==1 )
                        {
                            cmatrix[i,j] = v1;
                        }
                    }
                }
                for(i=0; i<=k-1; i++)
                {
                    cmatrix[i,m] = yc[i];
                }
            }
            
            //
            // Solve constrained task
            //
            if( k>0 )
            {
                
                //
                // solve using regularization
                //
                lsfit.lsfitlinearwc(y2, ref w2, ref fmatrix, cmatrix, n+m, m, k, ref info, ref tmp, ref lrep);
            }
            else
            {
                
                //
                // no constraints, no regularization needed
                //
                lsfit.lsfitlinearwc(y, ref w, ref fmatrix, cmatrix, n, m, k, ref info, ref tmp, ref lrep);
            }
            if( info<0 )
            {
                return;
            }
            
            //
            // Generate interpolant and scale it
            //
            for(i_=0; i_<=m-1;i_++)
            {
                sy[i_] = tmp[i_];
            }
            barycentricbuildfloaterhormann(ref sx, ref sy, m, d, ref b);
            barycentriclintransx(ref b, 2/(xb-xa), -((xa+xb)/(xb-xa)));
            barycentriclintransy(ref b, sb-sa, sa);
            
            //
            // Scale absolute errors obtained from LSFitLinearW.
            // Relative error should be calculated separately
            // (because of shifting/scaling of the task)
            //
            rep.taskrcond = lrep.taskrcond;
            rep.rmserror = lrep.rmserror*(sb-sa);
            rep.avgerror = lrep.avgerror*(sb-sa);
            rep.maxerror = lrep.maxerror*(sb-sa);
            rep.avgrelerror = 0;
            relcnt = 0;
            for(i=0; i<=n-1; i++)
            {
                if( (double)(yoriginal[i])!=(double)(0) )
                {
                    rep.avgrelerror = rep.avgrelerror+Math.Abs(barycentriccalc(ref b, xoriginal[i])-yoriginal[i])/Math.Abs(yoriginal[i]);
                    relcnt = relcnt+1;
                }
            }
            if( relcnt!=0 )
            {
                rep.avgrelerror = rep.avgrelerror/relcnt;
            }
        }
    }
}