//    $Revision: 1.1 $

using System;
using System.Collections.Generic;
using System.Text;
using fvalgcli;

namespace TC
{
    public partial class FIE
    {
        [FvPluginExecute]
        public void fnFIE_ga_open()
        {
            int status = (int)fvalgcli.f_err.F_ERR_NONE;

            FHANDLE hGa = FHANDLE.Zero;                            // Descriptor of GA
            F_GA_RANGE_PTR taGeneRange = F_GA_RANGE_PTR.Zero;    // Range of value for every gene    
            INT_PTR iaChrom = INT_PTR.Zero;                        // Essence of chromosome
            DOUBLE_PTR daFitness = DOUBLE_PTR.Zero;                // Fitness
            PNT_T_PTR taCoord = PNT_T_PTR.Zero;                    // Set of coordinates   (positions of cities)

            double dExpArrage = 0.75;        // Expected fitness value (>0.75)

            const int GENE_N = 20;            // Maximal number of genes
            const int PICK_N = 3;            // Number of chrosomoses picked out

            try
            {
                // allocate memory    
                taGeneRange = F_GA_RANGE_PTR.alloc(GENE_N);
                iaChrom = INT_PTR.alloc(PICK_N * GENE_N);
                daFitness = DOUBLE_PTR.alloc(PICK_N);
                taCoord = PNT_T_PTR.alloc(GENE_N);

                /*****    Parameters of GA function    *****/
                int iGeneNum = GENE_N;
                int iMaxAlterCnt = 1000;
                f_ga_type tGeneType = f_ga_type.F_GA_ORDER_TYPE;
                for (int i = 0; i < iGeneNum; i++)
                {
                    F_GA_VALUE ga_min = F_GA_VALUE.init(0);
                    F_GA_VALUE ga_max = F_GA_VALUE.init(0);
                    taGeneRange[i] = F_GA_RANGE.init(ga_min, ga_max);
                }

                /* Cost function    */
                F_GA_FUNC fpCostFunc = cost_func;    // Cost function

                /* Set the fixed value      */
                int iChromNum = 200;                                        /* Number of chromosomes        */
                f_ga_select tSelect = f_ga_select.F_GA_PROPORT_SELECT;        /* Method of seletion            */
                f_ga_cross tCrossover = f_ga_cross.F_GA_PARTIAL_CROSS;        /* Method of crossover            */
                double dCrossRate = 0.9;                                    /* Rate of crossover            */
                double dMutatRate = 0.05;                                    /* Rate of mutation                */
                f_ga_alter tAlternate = f_ga_alter.F_GA_ELITE_ALTERNATE;    /* Method of alternation        */
                f_ga_end tEndCond = f_ga_end.F_GA_NO_CONDITION_END;            /* End condition                  */
                double dThresh = 0.001;                                        /* Threshold of end condition   */

                /* Create the coordinates of positions */
                for (int i = 0; i < iGeneNum; i++)
                    taCoord[i] = PNT_T.init(20*i+5, i);

                // generate table of distance
                generate_table( iGeneNum, taCoord );

                /****** GA Test begin ******/

                /* GA open */
                hGa = api.fnFIE_ga_open( tGeneType, iGeneNum, iChromNum, taGeneRange, tSelect, tCrossover,
                                      dCrossRate, dMutatRate, tAlternate, fpCostFunc, tEndCond, dThresh, iMaxAlterCnt );
                Assert.IsTrue(hGa != FHANDLE.Zero, "エラーが発生しました。");

                m_dMaxFitness = 0.0;

                /* GA execute */
                int iRet = 0;
                status = api.fnFIE_ga_execute(hGa, PICK_N, iaChrom, daFitness, ref iRet);
                Assert.IsTrue(status == (int)f_err.F_ERR_NONE, "エラーが発生しました。({0})", (f_err)status);

                for ( int i = 0; i < PICK_N; i++ )
                {
                    if ( daFitness[i] < dExpArrage )
                    {
                        Assert.Fail("エラーが発生しました。(daFitness[{0}]={1})", i, daFitness[i]);
                    }
                }
            }
            finally
            {
                hGa.Dispose();
                taGeneRange.Dispose();
                iaChrom.Dispose();
                daFitness.Dispose();
                taCoord.Dispose();
            }
        }

        /// <summary>
        /// Cost function of genetic algorithm
        /// </summary>
        /// <param name="tGeneType">Type of gene</param>
        /// <param name="iGeneNum">Number of gene</param>
        /// <param name="vpChrom">Descriptor of chromosome</param>
        /// <returns>
        /// </returns>
        private static double cost_func(f_ga_type tGeneType, int iGeneNum, IntPtr vpChrom)
        {
            double dFitness, dMax, dLength;
            int iLength = 0;
            INT_PTR iaChrom = vpChrom;

            for (int i = 0; i < iGeneNum; i++)
                iLength += m_waLength[iaChrom[i],iaChrom[(i+1)%iGeneNum]];

            dLength = (double)iLength;
            dMax = (double)(iGeneNum * 500);

            if( dMax < dLength )
                dFitness = 0.0;
            else
                dFitness = 1.0 - dLength / dMax;

            if( m_dMaxFitness < dFitness )
                m_dMaxFitness = dFitness;

            return dFitness;
        }

        /// <summary>
        /// Table of distance  (distance of cities)
        /// </summary>
        private static int[,] m_waLength = new int[20, 20];

        /// <summary>
        /// Maximal value of fitness
        /// </summary>
        private static double m_dMaxFitness = 0.0;

        /// <summary>
        /// Generate the distance table
        /// </summary>
        /// <param name="iDataNum">Input data num</param>
        /// <param name="taCoord">Coordinate of point</param>
        private static void generate_table(int iDataNum, PNT_T_PTR taCoord)
        {
            for( int i = 0; i < iDataNum; i++ )
                for( int j = 0; j < iDataNum; j++ )
                    m_waLength[i, j] = calc_length(taCoord[i].x, taCoord[i].y, taCoord[j].x, taCoord[j].y);
        }

        /// <summary>
        /// Calculate the diatance of two points
        /// </summary>
        /// <param name="iXs">X-coordinate of start point</param>
        /// <param name="iYs">Y-coordinate of start point</param>
        /// <param name="iXe">X-coordinate of end point</param>
        /// <param name="iYe">Y-coordinate of end point</param>
        /// <returns>
        /// </returns>
        private static int calc_length(int iXs, int iYs, int iXe, int iYe)
        {
            int iXd = iXe - iXs + 1;
            int iYd = iYe - iYs + 1;
            return ((int)System.Math.Sqrt((double)(iXd * iXd + iYd * iYd)));
        }
    }
}

'    $Revision: 1.1 $

Imports System.Collections.Generic
Imports System.Text
Imports fvalgcli

Public Partial Class FIE
    <FvPluginExecute> _
    Public Sub fnFIE_ga_open()
        Dim status As Integer = CInt(fvalgcli.f_err.F_ERR_NONE)

        Dim hGa As FHANDLE = FHANDLE.Zero
        ' Descriptor of GA
        Dim taGeneRange As F_GA_RANGE_PTR = F_GA_RANGE_PTR.Zero
        ' Range of value for every gene    
        Dim iaChrom As INT_PTR = INT_PTR.Zero
        ' Essence of chromosome
        Dim daFitness As DOUBLE_PTR = DOUBLE_PTR.Zero
        ' Fitness
        Dim taCoord As PNT_T_PTR = PNT_T_PTR.Zero
        ' Set of coordinates   (positions of cities)
        Dim dExpArrage As Double = 0.75
        ' Expected fitness value (>0.75)
        Const  GENE_N As Integer = 20
        ' Maximal number of genes
        Const  PICK_N As Integer = 3
        ' Number of chrosomoses picked out
        Try
            ' allocate memory    
            taGeneRange = F_GA_RANGE_PTR.alloc(GENE_N)
            iaChrom = INT_PTR.alloc(PICK_N * GENE_N)
            daFitness = DOUBLE_PTR.alloc(PICK_N)
            taCoord = PNT_T_PTR.alloc(GENE_N)

            '****    Parameters of GA function    ****

            Dim iGeneNum As Integer = GENE_N
            Dim iMaxAlterCnt As Integer = 1000
            Dim tGeneType As f_ga_type = f_ga_type.F_GA_ORDER_TYPE
            For i As Integer = 0 To iGeneNum - 1
                Dim ga_min As F_GA_VALUE = F_GA_VALUE.init(0)
                Dim ga_max As F_GA_VALUE = F_GA_VALUE.init(0)
                taGeneRange(i) = F_GA_RANGE.init(ga_min, ga_max)
            Next

            ' Cost function    

            Dim fpCostFunc As F_GA_FUNC = AddressOf cost_func
            ' Cost function
            ' Set the fixed value      

            Dim iChromNum As Integer = 200
            ' Number of chromosomes        
            Dim tSelect As f_ga_select = f_ga_select.F_GA_PROPORT_SELECT
            ' Method of seletion            
            Dim tCrossover As f_ga_cross = f_ga_cross.F_GA_PARTIAL_CROSS
            ' Method of crossover            
            Dim dCrossRate As Double = 0.9
            ' Rate of crossover            
            Dim dMutatRate As Double = 0.05
            ' Rate of mutation                
            Dim tAlternate As f_ga_alter = f_ga_alter.F_GA_ELITE_ALTERNATE
            ' Method of alternation        
            Dim tEndCond As f_ga_end = f_ga_end.F_GA_NO_CONDITION_END
            ' End condition                  
            Dim dThresh As Double = 0.001
            ' Threshold of end condition   

            ' Create the coordinates of positions 

            For i As Integer = 0 To iGeneNum - 1
                taCoord(i) = PNT_T.init(20 * i + 5, i)
            Next

            ' generate table of distance
            generate_table(iGeneNum, taCoord)

            '***** GA Test begin *****


            ' GA open 

            hGa = api.fnFIE_ga_open(tGeneType, iGeneNum, iChromNum, taGeneRange, tSelect, tCrossover, _
                dCrossRate, dMutatRate, tAlternate, fpCostFunc, tEndCond, dThresh, _
                iMaxAlterCnt)
            Assert.IsTrue(hGa <> FHANDLE.Zero, "エラーが発生しました。")

            m_dMaxFitness = 0.0

            ' GA execute 

            Dim iRet As Integer = 0
            status = api.fnFIE_ga_execute(hGa, PICK_N, iaChrom, daFitness, iRet)
            Assert.IsTrue(status = CInt(f_err.F_ERR_NONE), "エラーが発生しました。({0})", CType(status, f_err))

            For i As Integer = 0 To PICK_N - 1
                If daFitness(i) < dExpArrage Then
                    Assert.Fail("エラーが発生しました。(daFitness[{0}]={1})", i, daFitness(i))
                End If
            Next
        Finally
            hGa.Dispose()
            taGeneRange.Dispose()
            iaChrom.Dispose()
            daFitness.Dispose()
            taCoord.Dispose()
        End Try
    End Sub

    ''' <summary>
    ''' Cost function of genetic algorithm
    ''' </summary>
    ''' <param name="tGeneType">Type of gene</param>
    ''' <param name="iGeneNum">Number of gene</param>
    ''' <param name="vpChrom">Descriptor of chromosome</param>
    ''' <returns>
    ''' </returns>
    Private Shared Function cost_func(tGeneType As f_ga_type, iGeneNum As Integer, vpChrom As IntPtr) As Double
        Dim dFitness As Double, dMax As Double, dLength As Double
        Dim iLength As Integer = 0
        Dim iaChrom As INT_PTR = vpChrom

        For i As Integer = 0 To iGeneNum - 1
            iLength += m_waLength(iaChrom(i), iaChrom((i + 1) Mod iGeneNum))
        Next

        dLength = CDbl(iLength)
        dMax = CDbl(iGeneNum * 500)

        If dMax < dLength Then
            dFitness = 0.0
        Else
            dFitness = 1.0 - dLength / dMax
        End If

        If m_dMaxFitness < dFitness Then
            m_dMaxFitness = dFitness
        End If

        Return dFitness
    End Function

    ''' <summary>
    ''' Table of distance  (distance of cities)
    ''' </summary>
    Private Shared m_waLength As Integer(,) = New Integer(19, 19) {}

    ''' <summary>
    ''' Maximal value of fitness
    ''' </summary>
    Private Shared m_dMaxFitness As Double = 0.0

    ''' <summary>
    ''' Generate the distance table
    ''' </summary>
    ''' <param name="iDataNum">Input data num</param>
    ''' <param name="taCoord">Coordinate of point</param>
    Private Shared Sub generate_table(iDataNum As Integer, taCoord As PNT_T_PTR)
        For i As Integer = 0 To iDataNum - 1
            For j As Integer = 0 To iDataNum - 1
                m_waLength(i, j) = calc_length(taCoord(i).x, taCoord(i).y, taCoord(j).x, taCoord(j).y)
            Next
        Next
    End Sub

    ''' <summary>
    ''' Calculate the diatance of two points
    ''' </summary>
    ''' <param name="iXs">X-coordinate of start point</param>
    ''' <param name="iYs">Y-coordinate of start point</param>
    ''' <param name="iXe">X-coordinate of end point</param>
    ''' <param name="iYe">Y-coordinate of end point</param>
    ''' <returns>
    ''' </returns>
    Private Shared Function calc_length(iXs As Integer, iYs As Integer, iXe As Integer, iYe As Integer) As Integer
        Dim iXd As Integer = iXe - iXs + 1
        Dim iYd As Integer = iYe - iYs + 1
        Return CInt(Math.Truncate(System.Math.Sqrt(CDbl(iXd * iXd + iYd * iYd))))
    End Function
End Class