How to use GenY class of B package

1using System;2using System.Collections.Generic;3using System.Linq;4using System.Text;5using System.Threading.Tasks;6using System.Diagnostics;7namespace Genetic_ShortPath8{9    class Program10    {11        static int osobi, cities, geny, StartCity, EndCity;12        static void Main(string[] args)13        {14            var sw = new Stopwatch();15            cities = 300;16            Console.WriteLine("Кол-во городов: " + cities);17            Random rand = new Random();18            int[,] MatrDistance = new int[cities, cities];  //матрица растояний19            for (int i = 0; i < cities; i++)20                for (int j = i + 1; j < cities; j++)21                    MatrDistance[i, j] = rand.Next(5, 150);22            for (int i = 0; i < cities; i++)23                for (int j = 0; j < i; j++)24                    MatrDistance[i, j] = MatrDistance[j, i];2526            /*    Console.WriteLine("Длина пути от одного города к другому: ");27              Console.Write("   | ");28               for (int i = 0; i < cities; i++)29               {30                   if (i < 9)31                       Console.Write("{0}   ", i + 1);32                   else33                       Console.Write("{0}  ", i + 1);34               }353637               Console.WriteLine();38               Console.Write("---");39               for (int i = 0; i < cities; i++)40                   Console.Write("----");414243               Console.WriteLine();44               for (int i = 0; i < cities; i++)45               {46                   if (i < 9)47                       Console.Write("{0}  | ", i + 1);48                   else49                       Console.Write("{0} | ", i + 1);50                   for (int j = 0; j < cities; j++)51                   {52                       if (MatrDistance[i, j] > 9)53                           Console.Write("{0}  ", MatrDistance[i, j]);54                       else55                           Console.Write("{0}   ", MatrDistance[i, j]);56                   }57                   Console.WriteLine();58               }*/5960            StartCity = rand.Next(1, cities);61            EndCity = rand.Next(1, cities);62            if (StartCity == EndCity)63                StartCity = rand.Next(1, cities);64            Console.WriteLine("Город-отправитель: {0}, Город-получатель: {1}", StartCity, EndCity);65            osobi = 8;  66            Console.WriteLine("Кол-во особей в популяции: " + osobi);67            geny = 6;  68            Console.WriteLine("Кол-во генов у особи: " + geny);69            sw.Start();70            int[,] Individi = new int[osobi, geny];  //особи71            for (int i = 0; i < osobi; i++)72                for (int j = 0; j < geny; j++)73                    Individi[i, j] = rand.Next(0, cities);74            int[,] allFitnesses = new int[osobi, 2];  //пригодность каждой особи и её номер75            Console.WriteLine();76            Console.WriteLine("Поколение 1:");77            for (int i = 0; i < osobi; i++)78            {79                int fitness = 0;80                fitness += MatrDistance[StartCity - 1, Individi[i, 0]];81                Console.Write("Особь {0}, её гены: ", i + 1);82                for (int j = 0; j < geny; j++)83                {84                    if (Individi[i, j] < 9)85                        Console.Write("{0},  ", Individi[i, j] + 1);86                    else87                        Console.Write("{0}, ", Individi[i, j] + 1);88                    if (j > 0)89                        fitness += MatrDistance[Individi[i, j - 1], Individi[i, j]];90                }91                fitness += MatrDistance[Individi[i, geny - 1], EndCity - 1];92                Console.WriteLine(" Пригодность: " + fitness);93                allFitnesses[i, 0] = i;94                allFitnesses[i, 1] = fitness;95            }96            Console.WriteLine();97            int iterations = 0;98            do99            {100                iterations++;101                List<int[]> newIndividi = new List<int[]>(); //массив из потомства102                do103                {104                    int[] parent_1 = new int[geny];  //родители105                    int[] parent_2 = new int[geny];106                    //выбор родителей 107                    ViborParents(Individi, allFitnesses, ref parent_1, ref parent_2);108                    int[] child_1 = new int[geny];  //потомоки109                    int[] child_2 = new int[geny];110                    //скрещивание 111                    Crossing(parent_1, parent_2, ref child_1, ref child_2);112                    newIndividi.Add(child_1);113                    newIndividi.Add(child_2);114                } while (newIndividi.Count < osobi);  //формируем новую популяцию115                Mutation(ref newIndividi);  //мутация обменом соседних генов116                for (int i = 0; i < osobi; i++)  //объединение родителей и потомков117                {118                    newIndividi.Add(new int[geny]);119                    for (int j = 0; j < geny; j++)120                        newIndividi.Last()[j] = Individi[i, j];121                }122                Selection(MatrDistance, ref newIndividi);  //отбор особей в новое поколение методом усечения123                Console.WriteLine("Поколение {0}:", iterations + 1);124                OutputPopulation(MatrDistance, ref allFitnesses, newIndividi);125                int counter = 0;126                for (int i = 1; i < osobi; i++)  //подсчёт кол-ва особей с одинаковой пригодностью для остановки алгоритма127                    if (allFitnesses[i, 1] == allFitnesses[0, 1])128                        counter++;129                if (counter >= osobi * 0.75)130                    break;131                for (int i = 0; i < osobi; i++)132                    for (int j = 0; j < geny; j++)133                        Individi[i, j] = newIndividi[i][j];134            } while (iterations < 50);135            Console.WriteLine("Кол-во поколений: " + (iterations + 1));136            Console.Write("Найденный путь: " + StartCity);137            for (int i = 0; i < geny; i++)138                Console.Write(" -> " + (Individi[0, i] + 1));139            Console.WriteLine(" -> {0}, его длина: " + allFitnesses[0, 1], EndCity);140            Console.WriteLine("Длина прямого пути от {0} города к {1}: " + MatrDistance[StartCity - 1, EndCity - 1], StartCity, EndCity);141            142            sw.Stop();143            Console.WriteLine($"Времени потрачено - {sw.ElapsedMilliseconds} млс");144            Console.ReadLine();145        }146        static void Selection(int[,] MatrDistance, ref List<int[]> Individi)  //отбор усечением147        {148            Random rand = new Random();149            double T = 0.4;  //порог для отбора150            int fitness = 0;151            int[,] allFitnesses = new int[Individi.Count, 2];  //пригодность каждой особи и её номер152            for (int i = 0; i < Individi.Count; i++)  //вычисление пригодности каждой особи153            {154                fitness += MatrDistance[StartCity - 1, Individi[i][0]];155                for (int j = 1; j < geny; j++)156                    fitness += MatrDistance[Individi[i][j - 1], Individi[i][j]];157                fitness += MatrDistance[Individi[i][geny - 1], EndCity - 1];158                allFitnesses[i, 0] = i;159                allFitnesses[i, 1] = fitness;160                fitness = 0;161            }162            int[] temp = new int[Individi.Count];  //сортировка особей в порядке убывания их пригодности163            for (int i = 0; i < Individi.Count; i++)164                temp[i] = allFitnesses[i, 1];165            Array.Sort(temp);166            for (int i = 0; i < Individi.Count; i++)167                for (int j = 0; j < Individi.Count; j++)168                    if (temp[i] == allFitnesses[j, 1])169                    {170                        Swap(ref allFitnesses[i, 1], ref allFitnesses[j, 1]);171                        Swap(ref allFitnesses[i, 0], ref allFitnesses[j, 0]);172                        break;173                    }174            int countNewIndividi = (int)(Individi.Count * T);  //кол-во особей, прошедших через отбор175            List<int[]> newIndividi = new List<int[]>();176            int numberNewIndividi = 0;177            do  //отбор особей в новую популяцию178            {179                numberNewIndividi = rand.Next(0, countNewIndividi - 1);180                newIndividi.Add(new int[geny]);181                for (int i = 0; i < geny; i++)182                    newIndividi.Last()[i] = Individi[allFitnesses[numberNewIndividi, 0]][i];183            } while (newIndividi.Count < osobi);184            Individi.Clear();185            Individi = newIndividi;186        }187        static void ViborParents(int[,] Individi, int[,] allFitnesses, ref int[] parent_1, ref int[] parent_2)  //выбор родителей 188        {189            Random rand = new Random();190            int numberParent_1 = rand.Next(0, osobi - 1);  //выбор первого родителя          191            for (int i = 0; i < geny; i++)192                parent_1[i] = Individi[allFitnesses[numberParent_1, 0], i];193            double[] euclidDistance = new double[osobi];194            double mineuclidDistance = double.MaxValue;195            int numberParent_2 = 0;196            for (int i = 0; i < osobi; i++)  //вычисление Евклидова расстояния для выбора второго родителя197            {198                for (int j = 0; j < geny; j++)199                    euclidDistance[i] += Math.Pow(parent_1[j] - Individi[allFitnesses[i, 0], j], 2);200                euclidDistance[i] = Math.Sqrt(euclidDistance[i]);201                if (euclidDistance[i] < mineuclidDistance && euclidDistance[i] != 0)202                {203                    mineuclidDistance = euclidDistance[i];204                    numberParent_2 = i;205                }206            }207            for (int i = 0; i < geny; i++)208                parent_2[i] = Individi[allFitnesses[numberParent_2, 0], i];209        }210        static void Crossing(int[] parent_1, int[] parent_2, ref int[] child_1, ref int[] child_2)  //скрещивание методом дискретной рекомбинации211        {212            Random rand = new Random();213            int[,] mask_for_cross = new int[2, geny];  //маска для замены генов214            for (int i = 0; i < 2; i++)    //выбираем номера особи для замены генов215                for (int j = 0; j < geny; j++)216                    mask_for_cross[i, j] = rand.Next(0, 2);217            for (int i = 0; i < geny; i++)218            {219                if (mask_for_cross[0, i] == 1)  //замена генов для первого потомка220                    child_1[i] = parent_2[i];221                else222                    child_1[i] = parent_1[i];223                if (mask_for_cross[1, i] == 0)   //замена генов для второго потомка224                    child_2[i] = parent_1[i];225                else226                    child_2[i] = parent_2[i];227            }228        }229        static void Mutation(ref List<int[]> newIndividi)  //мутация методом обмена соседних генов230        {231            Random rand = new Random();232            double T = 0.3;  //вероятность мутации - порог233            double[] veroyatnost_mutation = new double[newIndividi.Count];234            for (int i = 0; i < newIndividi.Count; i++)235            {236                veroyatnost_mutation[i] = ((double)rand.Next(1, 100) / 100);  //случайно выбирается вероятность мутации для каждой особи237                if (veroyatnost_mutation[i] <= T)  //если вероятность мутации особи меньше порога238                {239                    int numOFgen = rand.Next(1, geny - 1);  //номер гена для мутации                    240                    if (newIndividi[i][numOFgen - 1] == newIndividi[i][numOFgen + 1])241                        numOFgen = rand.Next(0, geny - 1);242                    if (numOFgen == 0)243                        numOFgen++;244                    Swap(ref newIndividi[i][numOFgen - 1], ref newIndividi[i][numOFgen + 1]);245                }246            }247        }248        static void OutputPopulation(int[,] MatrDistance, ref int[,] allFitnesses, List<int[]> newIndividi)249        {250            int fitness = 0;251            for (int i = 0; i < osobi; i++)252            {253                fitness += MatrDistance[StartCity - 1, newIndividi[i][0]];254                Console.Write("Особь {0}, её гены: ", i + 1);255                for (int j = 0; j < geny; j++)256                {257                    if (newIndividi[i][j] < 9)258                        Console.Write("{0},  ", newIndividi[i][j] + 1);259                    else260                        Console.Write("{0}, ", newIndividi[i][j] + 1);261                    if (j > 0)262                        fitness += MatrDistance[newIndividi[i][j - 1], newIndividi[i][j]];263                }264                fitness += MatrDistance[newIndividi[i][geny - 1], EndCity - 1];265                Console.WriteLine(" пригодность: " + fitness);266                allFitnesses[i, 0] = i;267                allFitnesses[i, 1] = fitness;268                fitness = 0;269            }270            Console.WriteLine();271        }272        static void Swap<T>(ref T a, ref T b)273        {274            T temp = a;275            a = b;276            b = temp;277        }278    }279}...

12namespace Zygotine.WebExpo3{4    using System;5    using System.Text;6    using Zygotine.Statistics.Distribution;7    using Zygotine.Util;8    internal class TrueValuesGen9    {10        internal double[] LogY = new double[0];11        internal double[] Y = new double[0];12        internal double[] LogGT { get; set; } = new double[0];13        internal double[] GT { get; set; } = new double[0];14        internal double[] LogLT { get; set; } = new double[0];15        internal double[] LT { get; set; } = new double[0];16        internal double[] LogI { get; set; } = new double[0];17        internal double[] I = new double[0];18        private TrueValuesGen()19        {20        }21        public string Show()22        {23            string fmt = "Y={0}, GT={1}, LT={2}, I={3}";24            string fmt2 = "{0}, **LOG: {1}";25            StringBuilder sb = new StringBuilder();26            sb.AppendFormat(fmt2, string.Format(fmt, Y.ShowR(), GT.ShowR(), LT.ShowR(), I.ShowR()), string.Format(fmt, LogY.ShowR(), LogGT.ShowR(), LogLT.ShowR(), LogLT.ShowR()));27            return sb.ToString();28        }29        private TrueValuesGen(YGen genY, DataSummary data, double mu, double sigma, MeasurementError me, bool logNormalDistrn = true, GenObject o = null)30        {31            if (me.ThroughSD && !logNormalDistrn)32            {33                double meSD = me.Parm;34                double tauStar = 1 / Math.Pow(sigma, 2) + 1 / Math.Pow(meSD, 2);35                double sdStar = 1 / Math.Sqrt(tauStar);36                if (data.YLength > 0)37                {38                    double[] tmpMean = (data.Y.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);39                    this.Y = NormalDistribution.RNorm(data.YLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));40                }41                if (data.GTLength > 0)42                {43                    double[] tmpMean = (genY.GT.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);44                    this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));45                }46                if (data.LTLength > 0)47                {48                    double[] tmpMean = (genY.LT.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);49                    this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));50                }51                if (data.IntervalLength > 0)52                {53                    double[] tmpMean = (genY.I.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);54                    this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));55                }56            }57            else58            {59                o.A.Sigma2 = sigma * sigma;60                this.Y = new double[data.YLength];61                this.GT = new double[data.GTLength];62                this.LT = new double[data.LTLength];63                this.I = new double[data.IntervalLength];64                for (int j = 0; j < data.YLength; j++)65                {66                    this.Y[j] = TrueValueGen(o, me, data.Y[j], mu, logY: logNormalDistrn ? data.LogY[j] : Tools.ND);67                }68                for (int j = 0; j < data.GTLength; j++)69                {70                    this.GT[j] = TrueValueGen(o, me, genY.GT[j], mu, logY: logNormalDistrn ? genY.LogGT[j] : Tools.ND);71                }72                for (int j = 0; j < data.LTLength; j++)73                {74                    this.LT[j] = TrueValueGen(o, me, genY.LT[j], mu, logY: logNormalDistrn ? genY.LogLT[j] : Tools.ND);75                }76                for (int j = 0; j < data.IntervalLength; j++)77                {78                    this.I[j] = TrueValueGen(o, me, genY.I[j], mu, logY: logNormalDistrn ? genY.LogI[j] : Tools.ND);79                }80                if (logNormalDistrn)81                {82                    this.LogY = this.Y.Log();83                    this.LogGT = this.GT.Log();84                    this.LogLT = this.LT.Log();85                    this.LogI = this.I.Log();86                }87            }88        } //# end of truevalues.gen   89        internal static TrueValuesGen GetInstance(YGen genY, DataSummary data, double mu, double sigma, MeasurementError me, bool logNormalDistrn = true, GenObject o = null)90        {91            return new TrueValuesGen(genY, data, mu, sigma, me, logNormalDistrn, o);92        }93        private double TrueValueGen(GenObject genO, MeasurementError me, double y, double mu, double logY)94        {95            SGNFnAParam localA = genO.A.Clone();96            localA.Mu = mu;97            if (genO.LogNormalDistrn)98            {99                localA.LogY = logY;100            }101            localA.Y = y;102            localA.Y2 = y * y;103            if (genO.ThroughSD)104            {105                localA.Ksi = me.Parm;106                localA.Ksi2 = me.Parm * me.Parm;107            }108            else109            {110                localA.CV2 = me.Parm * me.Parm;111            }112            double[] start = genO.Start(localA);113            //start.Any(zz => !zz.IsFinite());114            Icdf icdf = new Icdf(genO, localA, range: genO.Range);115            double x = icdf.Bidon(start, inestLowerLim: !genO.LogNormalDistrn);116            if (genO.LogNormalDistrn)117            {118                x = Math.Exp(x);// # new_0.11119            }120            return x;121        } //# end of truevalue.gen122    }123}...

1using System;2using System.Collections.Generic;3using System.ComponentModel;4using System.Data;5using System.Drawing;6using System.Linq;7using System.Text;8using System.Threading;9using System.Threading.Tasks;10using System.Windows.Forms;11using System.Windows.Forms.DataVisualization.Charting;12namespace rbfNeuro13{14    public partial class Form1 : Form15    {16        public Form1()17        {18            InitializeComponent();19            generator = new Generator();20        }21        private const int Count = 20;22        private static Generator generator;23        private static double[] genY, genYNotSort,24                                chartVal = new double[Count],25                                chartX = new double[Count];26        double deltaX;27        private void GetXArray(double[] generated, out double[] masX, out double[] masY)28        {29            int i = 0;30            masX = new double[Count];31            masY = new double[Count];32           // generated = generated.Select(o => o / 10).ToArray();33            deltaX = (generated.Max() - generated.Min()) / Count;34            for (double val1 = generated[0], val2 = val1 + deltaX; i < Count; maasss[i] = val1, masX[i] = val1 + deltaX / 2, val1 = val2, val2 += deltaX, i++)35                for (int k = 0; k < generated.Length; k++)36                    if (generated[k] >= val1 && generated[k] < val2)37                        masY[i]++;38            double minY = masY.Min();39            double dif = masY.Max() - minY;40            for (int k = 0; k < masY.Length; k++)41            {42                //masY[k] = masY[k] / masY.Length;43                masY[k] = (masY[k] - minY) / dif;44            }45        }46        double[] maasss = new double[Count];47        Layer layer;48        List<double> errors = new List<double>();49        private void button3_Click(object sender, EventArgs e)50        {51          52            double error = 0;53            layer.Neurons.ForEach(o => o.Impulse = 0);54            layer.Output = 0;55            double[] masX;56            double[] masY;57            GetXArray(generator.Generate(5000, Generator.rand.NextDouble() * 3).OrderBy(o => o).Select(o => o / 1.1).ToArray(), out masX, out masY);58            double[] neuroOutput = new double[Count];59            for (int i = 0; i < masX.Length; i++)60            {61                layer.LinearSum(masX[i]);62                neuroOutput[i] = layer.Output;63                error += (Math.Pow(masY[i] - layer.Output, 2));64            }65            errors.Add(Math.Sqrt(error / (Count - 1)));66            // ToChart(2, masX, masY);67            ToChart(3, masX, neuroOutput);68        }69        private void button2_Click(object sender, EventArgs e)70        {71            layer = new Layer(Count, chartX, deltaX / Math.Sqrt(45));72            double n = 0.0012;///////////////////////////////////////////////73            for (int p = 0; p < 80; p++)74            {75                genYNotSort = generator.Generate(5000, 1 /*Generator.rand.NextDouble() * 3*/);76                genY = genYNotSort.OrderBy(o => o).ToArray();77                GetXArray(genY, out chartX, out chartVal);78                int Iter = 8000;79                double[] err = new double[Iter * Count];80                double[] indexes = new double[Iter * Count];81                for (int i = 0; i < Iter * Count; i++)82                    indexes[i] = i;83                label1.Text = "....";84                ////Thread t = new Thread(() =>85                ////{86                    for (int i = 0; i < Iter; i++)87                    {88                        double[] m = new double[Count];89                        for (int k = 0; k < Count; k++)90                        {91                            layer.GoLearn(n, chartVal[k],/* chartX*/ maasss[k]);92                            layer.CalcE(chartVal[k], 0.00001);93                        /// { label1.Text = "готово"; return; }94                        err[k * i] = layer.E;95                            m[k] = layer.Output;96                        }97                       // chart1.Invoke((MethodInvoker)delegate ()98                        //{99                            ToChart(1, chartX, m);100                       // });101                    }102                    //label1.Invoke((MethodInvoker)delegate ()103                    //{104                        label1.Text = "готово";105                    //});106               // });107                //t.Start();108            }109        }110        private void ToChart(int ind, double[] x, double[] y)111        {112            chart1.Series[0].ChartType = SeriesChartType.Line;113            chart1.Series[0].Points.DataBindXY(x, y);114        }115        private void button1_Click(object sender, EventArgs e)116        {117            genYNotSort = generator.Generate(5000, 1/* Generator.rand.NextDouble() * 3*/);118            genY = genYNotSort.OrderBy(o => o).ToArray();119            GetXArray(genY, out chartX, out chartVal);120            ToChart(0, chartX, chartVal);121        }122    }123}...

1using System;2using System.Collections.Generic;3using System.Linq;4using System.Text;5using UnityEngine;67public class ScanrangeCalc8{9    public ScanrangeCalc()10    {11        InitializeTables();12    }1314    private sbyte[,,] pTablesOffset = new sbyte[41, 41, 2];15    private int[,] pTablesCost = new int[41, 41];16    public int[,] pTablesVision = new int[41, 41];1718    public byte ScanShift = 7;1920    private bool SetCell(int x, int y, int height_origin, int height_cell)21    {22        int vision_previous = pTablesVision[x + pTablesOffset[x, y, 0], y + pTablesOffset[x, y, 1]];23        int cost = pTablesCost[x, y];24        pTablesVision[x, y] = vision_previous - (height_cell - height_origin + cost);25        return (pTablesVision[x, y] >= 0);26    }2728    public void InitializeTables()29    {30        uint ulScanShifted = 1u << ScanShift;3132        for (int i = 0; i <= 20; ++i)33        {34            for (int j = 0; j <= 20; ++j)35            {36                int v1 =  i > 0 || j > 0 ?  (int)(Math.Pow((j * j + i * i), 0.5) / Math.Max(i,j) * ulScanShifted) : 0;3738                pTablesCost[20 + i, 20 + j] = v1;39                pTablesCost[20 + i, 20 - j] = v1;40                pTablesCost[20 - i, 20 + j] = v1;41                pTablesCost[20 - i, 20 - j] = v1;4243                if (j < (i / 2))44                {45                    pTablesOffset[20 + i, 20 + j, 0] = -1;46                    pTablesOffset[20 + i, 20 + j, 1] = 0;47                    pTablesOffset[20 - i, 20 - j, 0] = 1;48                    pTablesOffset[20 - i, 20 - j, 1] = 0;49                    pTablesOffset[20 + i, 20 - j, 0] = -1;50                    pTablesOffset[20 + i, 20 - j, 1] = 0;51                    pTablesOffset[20 - i, 20 + j, 0] = 1;52                    pTablesOffset[20 - i, 20 + j, 1] = 0;5354                } 55                else if (j > (i * 2))56                {57                    pTablesOffset[20 + i, 20 + j, 0] = 0;58                    pTablesOffset[20 + i, 20 + j, 1] = -1;59                    pTablesOffset[20 - i, 20 - j, 0] = 0;60                    pTablesOffset[20 - i, 20 - j, 1] = 1;61                    pTablesOffset[20 + i, 20 - j, 0] = 0;62                    pTablesOffset[20 + i, 20 - j, 1] = 1;63                    pTablesOffset[20 - i, 20 + j, 0] = 0;64                    pTablesOffset[20 - i, 20 + j, 1] = -1;65                }66                else67                {68                    pTablesOffset[20 + i, 20 + j, 0] = -1;69                    pTablesOffset[20 + i, 20 + j, 1] = -1;70                    pTablesOffset[20 - i, 20 - j, 0] = 1;71                    pTablesOffset[20 - i, 20 - j, 1] = 1;72                    pTablesOffset[20 + i, 20 - j, 0] = -1;73                    pTablesOffset[20 + i, 20 - j, 1] = 1;74                    pTablesOffset[20 - i, 20 + j, 0] = 1;75                    pTablesOffset[20 - i, 20 + j, 1] = -1;76                }77            }78        }7980        pTablesCost[20, 20] = 0;81    }8283    private bool CheckValid(int x, int y)84    {85        return (x >= 8 && y >= 8 && x < MapLogic.Instance.Width - 8 && y < MapLogic.Instance.Height - 8);86    }8788    private int GetHeight(int x, int y)89    {90        if (x < 0 || y < 0 || x >= MapLogic.Instance.Width || y >= MapLogic.Instance.Height)91            return 0;92        return MapLogic.Instance.Nodes[x, y].Height;93    }9495    public void CalculateVision(int x, int y, float scanrangef)96    {97        // we need to make scanshifted scanrange from float.98        int scanrange = (int)scanrangef;99        scanrange = (scanrange << 8) | (int)((scanrangef - scanrange) * 255);100101        for (int ly = 0; ly < 41; ly++)102            for (int lx = 0; lx < 41; lx++)103                pTablesVision[lx, ly] = 0;104105        int vision = scanrange;106        int vision2 = (1 << (ScanShift - 1)) + (vision >> (8 - ScanShift));107108        int genX = x - 20;109        int genY = y - 20;110        int ht_origin = GetHeight(x, y);111112        pTablesVision[20, 20] = vision2;113        for(int i = 1; i < 20; i++)114        {115            bool fdisp = false;116            for(int j = -i; j < i+1; j++)117            {118                if(CheckValid(genX+(20+j), genY+(20-i)) &&119                   SetCell(20+j, 20-i, ht_origin, GetHeight(genX+(20+j), genY+(20-i))))120                    fdisp = true;121                if(CheckValid(genX+(20+j), genY+(20+i)) &&122                   SetCell(20+j, 20+i, ht_origin, GetHeight(genX+(20+j), genY+(20+i))))123                    fdisp = true;124                if(CheckValid(genX+(20-i), genY+(20+j)) &&125                   SetCell(20-i, 20+j, ht_origin, GetHeight(genX+(20-i), genY+(20+j))))126                    fdisp = true;127                if(CheckValid(genX+(20+i), genY+(20-j)) &&128                   SetCell(20+i, 20-j, ht_origin, GetHeight(genX+(20+i), genY+(20-j))))129                    fdisp = true;130            }131132		    if(!fdisp) break;133        }134    }
...

1using Terraria;2using Terraria.ID;3using Terraria.ModLoader;4using Microsoft.Xna.Framework;5using TrelamiumTwo.Content.Items.Materials;6using TrelamiumTwo.Helpers;7namespace TrelamiumTwo.Common.Tiles8{9	public class TrelamiumTile : GlobalTile10	{11		private const float nutSpawnChance = 0.05f;12		private const float leafSpawnChance = 0.025f;13		private Player player;14		public override void RandomUpdate(int i, int j, int type)15		{16			if (Main.tile[i, j].nactive())17			{18				if ((type == TileID.Grass || type == TileID.HallowedGrass) && Main.rand.Next(55) == 0)19				{20					TryBloomRose(i, j);21				}22			}23		}24		public override void FloorVisuals(int type, Player player)25		{26			player.GetModPlayer<Players.TrelamiumPlayer>().onSand =27				(TileID.Sets.Conversion.Sand[type] || TileID.Sets.Conversion.Sandstone[type] || TileID.Sets.Conversion.HardenedSand[type]);28		}29		private void TryBloomRose(int genX, int genY)30		{31			int scatteredFlowerRadiusCheck = 5;32			int scatteredFlowerType = ModContent.TileType<Content.Tiles.Ambience.BloomRose>();33			if (genX < 95 || genX > Main.maxTilesX - 95 || genY < 95 || genY > Main.worldSurface)34			{35				return;36			}37			Tile topTile = Framing.GetTileSafely(genX, genY - 1);38			if (topTile.active() && topTile.type != scatteredFlowerType)39			{40				return;41			}42			int minX = Utils.Clamp(genX - scatteredFlowerRadiusCheck, 1, Main.maxTilesX - 2);43			int maxX = Utils.Clamp(genX + scatteredFlowerRadiusCheck, 1, Main.maxTilesX - 2);44			int minY = Utils.Clamp(genY - scatteredFlowerRadiusCheck, 1, Main.maxTilesY - 2);45			int maxY = Utils.Clamp(genY + scatteredFlowerRadiusCheck, 1, Main.maxTilesY - 2);46			for (int x = minX; x < maxX; ++x)47			{48				for (int y = minY; y < maxY; ++y)49				{50					Tile t = Framing.GetTileSafely(x, y);51					if (t.active() && t.type == scatteredFlowerType)52					{53						return;54					}55				}56			}57			WorldGen.PlaceTile(genX, genY - 1, scatteredFlowerType, true);58		}59		public override void KillTile(int i, int j, int type, ref bool fail, ref bool effectOnly, ref bool noItem)60		{61			player = Main.LocalPlayer;62			if (!effectOnly)63			{64				if (player.ZoneForest())65				{66					if (Main.netMode != NetmodeID.MultiplayerClient && type == TileID.Trees)67					{68						TrySpawnLeaf(i, j);69						TrySpawnNut(i, j, fail);70					}71				}72			}73		}74		private void TrySpawnNut(int x, int y, bool fail)75		{76			if (fail || Main.rand.NextFloat() > nutSpawnChance)77			{78				return;79			}80			while (y > 10 && Main.tile[x, y].active() && Main.tile[x, y].type == TileID.Trees)81			{82				y--;83			}84			y++;85			if (!IsTileALeafyTreeTop(x, y) || Collision.SolidTiles(x - 2, x + 2, y - 2, y + 2))86			{87				return;88			}89			Item.NewItem(new Vector2(x * 16, y * 16), ModContent.ItemType<Nut>(), Main.rand.Next(5));90		}91		private void TrySpawnLeaf(int x, int y)92		{93			if (Main.rand.NextFloat() > leafSpawnChance)94			{95				return;96			}97			while (y > 10 && Main.tile[x, y].active() && Main.tile[x, y].type == TileID.Trees)98			{99				y--;100			}101			y++;102			if (!IsTileALeafyTreeTop(x, y) || Collision.SolidTiles(x - 2, x + 2, y - 2, y + 2))103			{104				return;105			}106			int velocityXDir = Main.rand.Next(2) * 2 - 1;107			int projectileType = ModContent.ProjectileType<Content.Projectiles.Typeless.FallingLeaf>();108			Projectile.NewProjectile(x * 16, y * 16, Main.rand.NextFloat(2f) * velocityXDir, 0f, projectileType, 0, 0f, Player.FindClosest(new Vector2(x * 16, y * 16), 16, 16));109		}110		private bool IsTileALeafyTreeTop(int i, int j)111		{112			Tile tileSafely = Framing.GetTileSafely(i, j);113			if (tileSafely.active() && tileSafely.type == TileID.Trees)114			{115				if (tileSafely.frameX == 22 && tileSafely.frameY >= 198 && tileSafely.frameY <= 242)116				{117					return true;118				}119			}120			return false;121		}122	}123}...

12namespace Zygotine.WebExpo3{4    using System.Linq;5    using Zygotine.Util;6    internal class MEParmGen7    {8        public double Parm { get; private set; }9        private MEParmGen()10        {11        }12        internal static MEParmGen GetInstance(GenObject o, MeasurementError me, DataSummary data, YGen genY, TrueValuesGen genTV)13        {14            MEParmGen instance = new MEParmGen();15            double b;16            double[] tmpY, tmpT;17            if (me.ThroughCV)18            {19                if (o.LogNormalDistrn)20                {21                    tmpY = Tools.Combine(data.LogY, genY.LogGT, genY.LogLT, genY.LogI);22                    tmpT = Tools.Combine(genTV.LogY, genTV.LogGT, genTV.LogLT, genTV.LogI);23                    b = tmpY.Substract(tmpT).Exp().Substract(1.0).Sqr().Sum();24                    b /= 2.0;25                }26                else27                {28                    tmpY = Tools.Combine(data.Y, genY.GT, genY.LT, genY.I);29                    tmpT = Tools.Combine(genTV.Y, genTV.GT, genTV.LT, genTV.I);30                    b = tmpY.Divide(tmpT).Substract(1.0).Sqr().Reverse().Sum();31                    b /= 2.0;32                }33                SGNFnAParam localA = o.A.Clone();34                localA.B = b;35                localA.Range = me.GetRange();36                double[] range = me.GetRange();37                Icdf icdf = new Icdf(o, localA, range);38                instance.Parm = icdf.Bidon(o.Start(localA), inestLowerLim: range[0] == 0);39            }40            else41            {42                tmpY = Tools.Combine(data.Y, genY.GT, genY.LT, genY.I);43                tmpT = Tools.Combine(genTV.Y, genTV.GT, genTV.LT, genTV.I);44                b = tmpY.Substract(tmpT).Sqr().Sum();45                b /= 2.0;46                if (o.LogNormalDistrn)47                {48                    SGNFnAParam localA = o.A.Clone();49                    localA.B = b;50                    localA.Range = me.GetRange();51                    localA.Truevalues = Tools.Copy(tmpT);52                    //me.parm <- dens.gen.icdf(o, A, range=me$range, inestimable.lower.limit=me$range[1]==0)53                    double[] range = me.GetRange();54                    Icdf icdf = new Icdf(o, localA, range);55                    instance.Parm = icdf.Bidon(inestLowerLim: range[0] == 0.0);56                }57                else58                {59                    instance.Parm = WebExpoFunctions3.SqrtInvertedGammaGen(data.N, b, me.GetRange(), o);60                }61            }62            return instance;63        }64    }65}...

1namespace Zygotine.WebExpo2{3    using System.Linq;4    using Zygotine.Util;5    internal class OutLogoutMoments6    {7        public double Sum { get; private set; }8        public double Sum2 { get; private set; }9        private OutLogoutMoments()10        {11        }12        public static OutLogoutMoments Get(bool anyME, bool logNormalDistrn, DataSummary data, YGen genY, TrueValuesGen genTV)13        {14            OutLogoutMoments olm = new OutLogoutMoments();15            if (anyME)16            {17                double[] y;18                if (logNormalDistrn)19                {20                    y = Tools.Combine(genTV.LogY, genTV.LogGT, genTV.LogLT, genTV.LogI);21                }22                else23                {24                    y = Tools.Combine(genTV.Y, genTV.GT, genTV.LT, genTV.I);25                }26                olm.Sum = y.Sum();27                olm.Sum2 = y.Sqr().Sum();28                return olm;29            }30            else if (logNormalDistrn)31            {32                olm.Sum = data.LogUncensoredSum;33                olm.Sum2 = data.LogUncensoredSum2;34                olm.Sum += genY.LogGT.Sum() + genY.LogLT.Sum() + genY.LogI.Sum();35                olm.Sum2 += genY.LogGT.Sqr().Sum() + genY.LogLT.Sqr().Sum() + genY.LogI.Sqr().Sum();36            }37            else38            {39                olm.Sum = data.UncensoredSum;40                olm.Sum2 = data.UncensoredSum2;41                olm.Sum += genY.GT.Sum() + genY.LT.Sum() + genY.I.Sum();42                olm.Sum2 += genY.GT.Sqr().Sum() + genY.LT.Sqr().Sum() + genY.I.Sqr().Sum();43            }44            return olm;45        }46    }47}...

1using System;2using System.Collections.Generic;3using System.ComponentModel;4using System.Data;5using System.Drawing;6using System.Text;7using System.Windows.Forms;8namespace MethodCaller9{10    public partial class GenyDriverMethodCaller : MethodCaller.MethodCallerMain11    {12        public GenyDriverMethodCaller()13        {14            InitializeComponent();15            this.Load += new EventHandler(GenyDriverMethodCaller_Load);16        }17        void GenyDriverMethodCaller_Load(object sender, EventArgs e)18        {19            this.label2.Visible = false;20            this.label3.Visible = false;21            this.cbbSerialPorts.Visible = false;22            this.tbSerialPortConfig.Visible = false;23        }24        protected override object GetDriver()25        {26            return new DeviceDriver.Driver(24);27        }28        protected override System.Reflection.MethodInfo[] GetMethods()29        {30            return ReflectUtil.GetMethod(typeof(DeviceDriver.Driver));31        }32    }33}...

1using B;2{3    {4        public static void Main()5        {6            GenY gy = new GenY();7            gy.Show();8        }9    }10}11using C;12{13    {14        public void Show()15        {16            GenZ gz = new GenZ();17            gz.Show();18        }19    }20}21using C;22{23    {24        public void Show()25        {26            GenZ gz = new GenZ();27            gz.Show();28        }29    }30}31using C;32{33    {34        public void Show()35        {36            GenZ gz = new GenZ();37            gz.Show();38        }39    }40}41using C;42{43    {44        public void Show()45        {46            GenZ gz = new GenZ();47            gz.Show();48        }49    }50}51using C;52{53    {54        public void Show()55        {56            GenZ gz = new GenZ();57            gz.Show();58        }59    }60}61using C;62{63    {64        public void Show()65        {66            GenZ gz = new GenZ();67            gz.Show();68        }69    }70}71using C;72{73    {74        public void Show()75        {76            GenZ gz = new GenZ();77            gz.Show();78        }79    }80}81using C;82{83    {84        public void Show()85        {86            GenZ gz = new GenZ();

1using B;2{3public void show()4{5Console.WriteLine("GenY");6}7}8using C;9{10public void show()11{12Console.WriteLine("GenZ");13}14}15using A;16{17public void show()18{19Console.WriteLine("GenA");20}21}22using B;23{24public void show()25{26Console.WriteLine("GenB");27}28}29using C;30{31public void show()32{33Console.WriteLine("GenC");34}35}36using D;37{38public void show()39{40Console.WriteLine("GenD");41}42}43using E;44{45public void show()46{47Console.WriteLine("GenE");48}49}50using F;51{52public void show()53{54Console.WriteLine("GenF");55}56}57using G;58{59public void show()60{61Console.WriteLine("GenG");62}63}64using H;65{66public void show()67{68Console.WriteLine("GenH");69}70}71using I;72{73public void show()74{75Console.WriteLine("GenI");76}77}78using J;79{80public void show()81{82Console.WriteLine("GenJ");83}84}

1using B;2{3public static void Main()4{5GenY obj = new GenY();6obj.print();7}8}9Microsoft (R) Visual C# Compiler version 1.1.4322.240810Microsoft (R) Visual C# Compiler version 1.1.4322.2408

1using B;2{3  public static void Main()4  {5    GenY g = new GenY();6  }7}8GenX.Show()9GenY.Show()

1using B;2{3    public GenY()4    {5        Console.WriteLine("GenY");6    }7}8using C;9{10    public GenZ()11    {12        Console.WriteLine("GenZ");13    }14}15using C;16{17    public static void Main()18    {19        GenZ obj = new GenZ();20        Console.ReadLine();21    }22}

1using B;2{3    static void Main()4    {5        GenY g = new GenY();6        g.ShowXY();7    }8}9{10    public unsafe void ShowXY()11    {12        Console.WriteLine("XY");13    }14}