public static void SaveGraph(System.Windows.Forms.DataVisualization.Charting.Chart ChartControl)
{
SaveFileDialog saveDialog = new SaveFileDialog();
saveDialog.Filter = "JPEG Image FIle (*.jpeg)|*.jpeg|PNG Image FIle (*.png)|*.png|GIF Image FIle (*.gif)|*.gif";
saveDialog.FilterIndex = 1;
if (saveDialog.ShowDialog() == System.Windows.Forms.DialogResult.OK)
{
if (saveDialog.FilterIndex == 1)
{
ChartControl.SaveImage(saveDialog.FileName, System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Jpeg);
}
if (saveDialog.FilterIndex == 2)
{
ChartControl.SaveImage(saveDialog.FileName, System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Png);
}
if (saveDialog.FilterIndex == 3)
{
ChartControl.SaveImage(saveDialog.FileName, System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Gif);
}
}
}
private string GeneratePlot(List <double[]> data, string title)
{
string file = "";
chart = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart.ChartAreas.Add(new System.Windows.Forms.DataVisualization.Charting.ChartArea());
foreach (var items in data)
{
int i = 1;
foreach (var item in items)
{
SetChart(title, i, item);
i++;
}
}
DateTime d = DateTime.Now;
var xxx = String.Format("{0}_{1}_{2}_{3}_{4}_{5}_{6}", d.Year, d.Month, d.Day, d.Hour, d.Minute, d.Second, d.Millisecond);
String chartFilename = ApplicationFolder + "\\" + xxx + ".bmp";
chart.Update();
chart.SaveImage(chartFilename, System.Drawing.Imaging.ImageFormat.Bmp);
file = chartFilename;
return(file);
}
private void PrintChartToFile(List <Tuple <int, long> > executions)
{
var chart =
new System.Windows.Forms.DataVisualization.Charting.Chart {
Size = new System.Drawing.Size(640, 320)
};
chart.ChartAreas.Add("ChartArea");
chart.Legends.Add("legend");
chart.Series.Add("executions");
chart.Series.Add("compare");
chart.Series["executions"].LegendText = "Clock cycles";
chart.Series["executions"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Spline;
chart.Series["compare"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Spline;
chart.Series["compare"].BorderWidth = 3;
chart.Series["compare"].LegendText = "n^2 log(n)";
foreach (var execution in executions)
{
chart.Series["executions"].Points.AddXY(execution.Item1, execution.Item2);
chart.Series["compare"].Points.AddXY(execution.Item1, _compareFunction(execution.Item1));
}
chart.SaveImage(@"..\..\TestFiles\ExecutionTimeChart.png", System.Drawing.Imaging.ImageFormat.Png);
}
//显示光谱图形
private void ShowSpectrumGraphic(Border rootBorder, string graphicBorderName, string graphicFile, double graphicWidth, double graphicHeight = double.MaxValue, double DPI = double.MaxValue)
{
Border graphicBorder = rootBorder.FindName(graphicBorderName) as Border;
if (graphicBorder != null)
{
System.Windows.Forms.DataVisualization.Charting.Chart graphicChart = new System.Windows.Forms.DataVisualization.Charting.Chart();
System.Windows.Forms.DataVisualization.Charting.ChartArea ca = new System.Windows.Forms.DataVisualization.Charting.ChartArea();
graphicChart.ChartAreas.Add(ca);
Common.CommonMethod.DrawSpectrumGraphic(graphicChart, ca, graphicFile, System.Drawing.Color.Black);
DPI = (DPI == double.MaxValue) ? 96: DPI;
graphicHeight = (graphicHeight == double.MaxValue) ? graphicBorder.Height * DPI / 96 : graphicHeight * DPI / 2.54;
graphicChart.Width = (int)(graphicWidth * DPI / 2.54); //1cm = 2.54inch = 96dpi
graphicChart.Height = (int)(graphicHeight);
System.IO.MemoryStream stream = new MemoryStream();
graphicChart.SaveImage(stream, System.Drawing.Imaging.ImageFormat.Png);
var bitmapImage = new BitmapImage();
bitmapImage.BeginInit();
bitmapImage.StreamSource = stream;
bitmapImage.EndInit();
Image img = new Image();
graphicBorder.Child = img;
img.Source = bitmapImage;
img.Stretch = Stretch.Uniform;
}
}
public static void ChartToPNG(System.Windows.Forms.DataVisualization.Charting.Chart chart)
{
string filename;
SaveFileDialog saveDialog = new SaveFileDialog();
saveDialog.Filter = "Portable Network Graphic (*.png)|*.png";
try
{
saveDialog.InitialDirectory = Properties.Settings.Default.lastFolder;
}
catch
{
saveDialog.InitialDirectory = Environment.SpecialFolder.MyDocuments.ToString();
}
if (saveDialog.ShowDialog() != DialogResult.OK)
{
return;
}
filename = saveDialog.FileName;
try
{
chart.SaveImage(filename, System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Png);
}
catch (Exception e)
{
Log.Error("Could not save image file: " + e.ToString());
MessageBox.Show("An error occoured while trying to export chart.");
}
}
public void addChart2(string bookmark, string chartType, string[][] data)
{
CHART c = ChartCreator.createChart(chartType, data);
string img = Path.GetFullPath(DateTime.Now.Ticks + ".bmp");
c.SaveImage(img,
System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Bmp);
replaceImage(bookmark, img);
try
{
File.Delete(img);
}
catch (Exception)
{
}
}
public static Image ToImage(this Control ctrl)
{
if (ctrl is System.Windows.Forms.DataVisualization.Charting.Chart)
{
System.Windows.Forms.DataVisualization.Charting.Chart chart = ctrl as
System.Windows.Forms.DataVisualization.Charting.Chart;
MemoryStream ms = new MemoryStream();
chart.SaveImage(ms, ImageFormat.Bmp);
Bitmap bmp1 = new Bitmap(ms);
return(bmp1);
}
Bitmap bmp = new Bitmap(ctrl.Width, ctrl.Height);
ctrl.DrawToBitmap(bmp, ctrl.ClientRectangle);
return(bmp);
}
private int CopyMSChart(System.Windows.Forms.DataVisualization.Charting.Chart oMSChart, int iChartRow)
{
//MS Chart 사용 로직 추가
string sImageFileName = null;
int iRowCnt = 0;
double dRowHeight = 0;
double dPicHeight = 0;
Excel.Pictures oPic;
sImageFileName = Environment.GetFolderPath(Environment.SpecialFolder.MyPictures)
+ @"\Tmp_Chart"
+ DateTime.Now.Year.ToString()
+ DateTime.Now.Month.ToString()
+ DateTime.Now.Day.ToString()
+ DateTime.Now.Hour.ToString()
+ DateTime.Now.Minute.ToString()
+ DateTime.Now.Second.ToString()
+ ".bmp";
//oChartFx.Export(SoftwareFX.ChartFX.FileFormat.Bitmap, sImageFileName);
oMSChart.SaveImage(sImageFileName, System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Bmp);
xlSheet.get_Range(xlSheet.Cells[iChartRow, 1], xlSheet.Cells[iChartRow, 1]).Select();
oPic = (Excel.Pictures)xlSheet.Pictures(Missing.Value);
oPic.Insert(sImageFileName, Missing.Value).Select(true);
dPicHeight = oPic.Insert(sImageFileName, Missing.Value).Height;
//Row의 폭
dRowHeight = Convert.ToDouble(xlSheet.get_Range(xlSheet.Cells[iChartRow, 1], xlSheet.Cells[iChartRow, 1]).Height);
//그림의 폭
iRowCnt = Convert.ToInt16((dPicHeight / dRowHeight)) + 2;
System.IO.File.Delete(sImageFileName);
return(iChartRow + iRowCnt);
}
private void save_as_png(System.Windows.Forms.DataVisualization.Charting.Chart ct, string folder, string prefix, string timestamp)
{
ct.SaveImage(Path.Combine(folder, prefix + timestamp + ".png"), System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Png);
}
void chartGraphConstruction(int Id1T, int Id2T, bool sum)
{
string Series1Name = NameIndex.IndexParse(Id1T);
string Series2Name = "";
if (!sum)
{
Series2Name = NameIndex.IndexParse(Id2T);
}
else if (sum)
{
Series2Name = "总计";
}
Font Title1Font = new Font("微软雅黑", 15);
// 表格真初始化
System.Windows.Forms.DataVisualization.Charting.Chart chart1 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart1.Size = new System.Drawing.Size(640, 320);
chart1.ChartAreas.Add("ChartArea1");
chart1.Legends.Add("Legend1");
System.Windows.Forms.DataVisualization.Charting.Chart chart2 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart2.Size = new System.Drawing.Size(640, 320);
chart2.ChartAreas.Add("ChartArea1");
chart2.Legends.Add("Legend1");
System.Windows.Forms.DataVisualization.Charting.Chart chart3 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart3.Size = new System.Drawing.Size(640, 320);
chart3.ChartAreas.Add("ChartArea1");
chart3.Legends.Add("Legend1");
System.Windows.Forms.DataVisualization.Charting.Chart chart4 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart4.Size = new System.Drawing.Size(640, 320);
chart4.ChartAreas.Add("ChartArea1");
chart4.Legends.Add("Legend1");
System.Windows.Forms.DataVisualization.Charting.Chart chart5 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart5.Size = new System.Drawing.Size(640, 320);
chart5.ChartAreas.Add("ChartArea1");
chart5.Legends.Add("Legend1");
System.Windows.Forms.DataVisualization.Charting.Chart chart6 = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart6.Size = new System.Drawing.Size(640, 320);
chart6.ChartAreas.Add("ChartArea1");
chart6.Legends.Add("Legend1");
#region 表格初始化
//击杀总量表
chart3.Series.Add(Series1Name);
chart3.Series.Add(Series2Name);
chart3.Legends["Legend1"].Docking = System.Windows.Forms.DataVisualization.Charting.Docking.Top;
chart3.Titles.Add("Title1");
chart3.Titles["Title1"].Text = "全等级击杀量对比";
chart3.Titles["Title1"].Font = Title1Font;
chart3.ChartAreas["ChartArea1"].AxisX.Title = "等级";
chart3.ChartAreas["ChartArea1"].AxisY.Title = "击杀量";
//单挑表
chart1.Series.Add("单挑流行度");
chart1.Series.Add("单挑胜率");
chart1.Series["单挑胜率"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["单挑流行度"].YAxisType = System.Windows.Forms.DataVisualization.Charting.AxisType.Secondary;
chart1.Series["单挑胜率"].BorderWidth = 5;
chart1.Series["单挑胜率"].Color = Color.DodgerBlue;
chart1.Series["单挑流行度"].Color = Color.Orange;
chart1.Legends["Legend1"].Docking = System.Windows.Forms.DataVisualization.Charting.Docking.Top;
chart1.Titles.Add("Title1");
chart1.Titles["Title1"].Text = "全等级单挑分析";
chart1.Titles["Title1"].Font = Title1Font;
chart1.ChartAreas["ChartArea1"].AxisX.Title = "等级";
chart1.ChartAreas["ChartArea1"].AxisY.Title = "胜率百分比";
chart1.ChartAreas["ChartArea1"].AxisY2.Title = "流行度百分比";
chart1.ChartAreas["ChartArea1"].AxisY2.MajorGrid.Enabled = false;
chart1.ChartAreas["ChartArea1"].AxisY.Maximum = 1.0;
//GANK表
chart2.Series.Add("GANK流行度");
chart2.Series.Add("GANK胜率");
chart2.Series["GANK胜率"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart2.Series["GANK流行度"].YAxisType = System.Windows.Forms.DataVisualization.Charting.AxisType.Secondary;
chart2.Series["GANK胜率"].BorderWidth = 5;
chart2.Series["GANK胜率"].Color = Color.DodgerBlue;
chart2.Series["GANK流行度"].Color = Color.Orange;
chart2.Legends["Legend1"].Docking = System.Windows.Forms.DataVisualization.Charting.Docking.Top;
chart2.Titles.Add("Title1");
chart2.Titles["Title1"].Text = "全等级GANK分析";
chart2.Titles["Title1"].Font = Title1Font;
chart2.ChartAreas["ChartArea1"].AxisX.Title = "等级";
chart2.ChartAreas["ChartArea1"].AxisY.Title = "胜率百分比";
chart2.ChartAreas["ChartArea1"].AxisY2.Title = "流行度百分比";
chart2.ChartAreas["ChartArea1"].AxisY2.MajorGrid.Enabled = false;
chart2.ChartAreas["ChartArea1"].AxisY.Maximum = 1.0;
//死亡表
chart4.Series.Add(Series1Name);
chart4.Series.Add(Series2Name);
chart4.Legends["Legend1"].Docking = System.Windows.Forms.DataVisualization.Charting.Docking.Top;
chart4.Titles.Add("Title1");
chart4.Titles["Title1"].Text = "全等级死亡量对比";
chart4.Titles["Title1"].Font = Title1Font;
chart4.ChartAreas["ChartArea1"].AxisX.Title = "等级";
chart4.ChartAreas["ChartArea1"].AxisY.Title = "死亡量";
//KDA表
chart5.Series.Add(Series1Name);
chart5.Series.Add(Series2Name);
chart5.Legends["Legend1"].Docking = System.Windows.Forms.DataVisualization.Charting.Docking.Top;
chart5.Titles.Add("Title1");
chart5.Titles["Title1"].Text = "全等级KDA对比";
chart5.Titles["Title1"].Font = Title1Font;
chart5.ChartAreas["ChartArea1"].AxisX.Title = "等级";
chart5.ChartAreas["ChartArea1"].AxisY.Title = "KDA";
#endregion
if (!sum)
{
for (int i = 1; i < 19; i++)
{
chart1.Series["单挑流行度"].Points.AddXY(i, statChart[i, 1]);
chart1.Series["单挑胜率"].Points.AddXY(i, statChart[i, 2]);
chart2.Series["GANK流行度"].Points.AddXY(i, statChart[i, 3]);
chart2.Series["GANK胜率"].Points.AddXY(i, statChart[i, 4]);
chart3.Series[Series1Name].Points.AddXY(i, statChart[i, 5]);
chart3.Series[Series2Name].Points.AddXY(i, statChart[i, 6]);
chart4.Series[Series1Name].Points.AddXY(i, statChart[i, 7]);
chart4.Series[Series2Name].Points.AddXY(i, statChart[i, 8]);
chart5.Series[Series1Name].Points.AddXY(i, statChart[i, 9]);
chart5.Series[Series2Name].Points.AddXY(i, statChart[i, 10]);
}
Directory.CreateDirectory(@"E:\lolLaneStat\" + Series1Name);
chart1.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "_1.png", System.Drawing.Imaging.ImageFormat.Png);
chart2.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "_2.png", System.Drawing.Imaging.ImageFormat.Png);
chart3.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "_3.png", System.Drawing.Imaging.ImageFormat.Png);
chart4.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "_4.png", System.Drawing.Imaging.ImageFormat.Png);
chart5.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "_5.png", System.Drawing.Imaging.ImageFormat.Png);
}
if (sum)
{
for (int i = 1; i < 19; i++)
{
chart1.Series["单挑流行度"].Points.AddXY(i, statSumChart[i, 1]);
chart1.Series["单挑胜率"].Points.AddXY(i, statSumChart[i, 2]);
chart2.Series["GANK流行度"].Points.AddXY(i, statSumChart[i, 3]);
chart2.Series["GANK胜率"].Points.AddXY(i, statSumChart[i, 4]);
chart3.Series[Series1Name].Points.AddXY(i, statSumChart[i, 5]);
chart3.Series[Series2Name].Points.AddXY(i, statSumChart[i, 6]);
chart4.Series[Series1Name].Points.AddXY(i, statSumChart[i, 7]);
chart4.Series[Series2Name].Points.AddXY(i, statSumChart[i, 8]);
chart5.Series[Series1Name].Points.AddXY(i, statSumChart[i, 9]);
chart5.Series[Series2Name].Points.AddXY(i, statSumChart[i, 10]);
}
Directory.CreateDirectory(@"E:\lolLaneStat\" + Series1Name);
chart1.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "1.png", System.Drawing.Imaging.ImageFormat.Png);
chart2.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "2.png", System.Drawing.Imaging.ImageFormat.Png);
chart3.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "3.png", System.Drawing.Imaging.ImageFormat.Png);
chart4.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "4.png", System.Drawing.Imaging.ImageFormat.Png);
chart5.SaveImage(@"E:\lolLaneStat\" + Series1Name + @"\" + Series2Name + "5.png", System.Drawing.Imaging.ImageFormat.Png);
}
chart1.Series.Clear();
chart1.Titles.Clear();
chart2.Series.Clear();
chart2.Titles.Clear();
chart3.Series.Clear();
chart3.Titles.Clear();
chart4.Series.Clear();
chart4.Titles.Clear();
chart5.Series.Clear();
chart5.Titles.Clear();
chart1.Dispose();
chart2.Dispose();
chart3.Dispose();
chart4.Dispose();
chart5.Dispose();
GC.Collect();
}
private void openFileDialog3_FileOk(object sender, CancelEventArgs e)
{
using (StreamReader sr = new StreamReader(openFileDialog3.FileName))
{
bool onlyOneRecord = checkBox1.Checked;
int m = 0;
int errors = 0;
float result = 0;
float sumActually = 0;
float sumPredicted = 0;
double error = 0;
while (!sr.EndOfStream)
{
DenseVector X = new DenseVector(network.GetInputs() - 1);
string[] str = sr.ReadLine().Split(separator);
for (int j = 0; j < network.GetInputs() - 1; j++)
{
switch (j)
{
case 6:
if (m != 0)
{
X[j] = result;
}
else
{
X[j] = float.Parse(str[j]);
}
break;
default:
X[j] = float.Parse(str[j]);
break;
}
}
network.Inputs = X;
if (onlyOneRecord)
{
int dayWeek = (int)Math.Round(1 / X[2]);
int month = (int)Math.Round(X[3] * 12);
for (int i = 1; i < maxDays; i++)
{
network.Inputs = X;
network.ForwardPropagation();
List <float> results = network.GetAswer();
X[X.Count - 10] = (float)(i) / maxDays;
dayWeek++;
if (dayWeek > 6)
{
dayWeek = 1;
}
if (i % 31 == 0)
{
month++;
}
X[X.Count - 9] = (float)(1f / (dayWeek));
if (month > 12)
{
month = 0;
}
X[X.Count - 8] = (float)(month) / 12;
X[X.Count - 1] = results[0];
sumPredicted += (float)(results[0] * maxBoxOffice);
chart1.Series[0].Points.Add((results[0]));
}
MessageBox.Show("Суммарные предсказанные сборы: " + Math.Round(sumPredicted).ToString());
chart1.SaveImage("Chart.png", System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Png);
chart1.Series[0].Points.Clear();
return;
}
network.ForwardPropagation();
List <float> h = network.GetAswer();
float diff = 0;
for (int j = 0; j < network.GetOutputs(); j++)
{
float Y = float.Parse(str[network.GetInputs() - 1 + j]);
result = (float)h[j];
diff += (float)Math.Abs(Y - h[j]);
sumPredicted += (result * maxBoxOffice);
sumActually += (Y * maxBoxOffice);
chart1.Series[0].Points.Add((result));
chart1.Series[1].Points.Add((Y));
}
error += Math.Pow(diff, 2);
if (diff / network.GetOutputs() > allowableError)
{
errors++;
}
m++;
}
float success = (1 - ((float)errors / m)) * 100;
double middleError = Math.Sqrt(error / (network.GetOutputs() * m));
chart1.SaveImage("Chart.png", System.Windows.Forms.DataVisualization.Charting.ChartImageFormat.Png);
chart1.Series[0].Points.Clear();
chart1.Series[1].Points.Clear();
MessageBox.Show("Суммарные предсказанные сборы: " + Math.Round(sumPredicted).ToString() + Environment.NewLine + "Суммарные сборы на самом деле: " + Math.Round(sumActually).ToString());
}
}
/// Main Code.
static void Main(string[] args)
{
///Defining variables
double[] UnderlyingPrice;
double[] CallPrice;
Random r = new Random(); ///this is the Class used to generate random variables
Discretization disc = new Discretization(); ///class that was coded above used to call the Euler function later in the code
System.Windows.Forms.DataVisualization.Charting.Chart chart = new System.Windows.Forms.DataVisualization.Charting.Chart(); ///class to set up Plot of underlying price
chart.ChartAreas.Add("ChartArea1"); ///set up the initial plot
///The following lines ask the user for the inputs needed to price the option and run the simulation
///Additionally, the inputs provided by the user are assigned the appropriate variables.
Console.WriteLine("Please Enter The Initial Asset Price:");
double X0 = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter The Strike Price of the Option:");
double K = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter The Time To Expiration:");
double T = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter mu:");
double mu = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter sigma:");
double sigma = Convert.ToDouble(Console.ReadLine());
/// Console.WriteLine("Please enter The Number of Simulations to Run:");
///int N = Convert.ToInt32(Console.ReadLine());
int N = 5000; ///Number of simulations
int m = 200; ///Number of increments between t = 0 and t = T
double delta = T / m; ///size of the increment
CallPrice = new double[N]; ///now allocating the size of array based on the number of simulations
UnderlyingPrice = new double[m + 1]; //now allocating the size of the array based on the number of increments
double U1; ///Represents uniform random variable between 0 and 1
double U2; ///Also represents uniform random variable between 0 and 1
double Z; ///Will represent the Normal Random Variable with mean 0 and variance 1
double sum1 = 0; //variable used to keep track of the sum in order to find the average of all the Call Prices for each of the simulations
double sum2 = 0; //variable used to keep track of the sum in order to ultimately find the Standard Error of the simulation
double OptionPrice; //Final European Call Option Price calculated
double StandardError; //Standard error of the simulation
for (int i = 0; i < N; i++) ///Each run through this loop represents 1 simulation
{
///Set up a new series that will be plotted on the graph
chart.Series.Add(Convert.ToString(i));
///Set chart type to Line graph
chart.Series[Convert.ToString(i)].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
///Initialize the Underlying Price array based on the input given by the user
UnderlyingPrice[0] = X0;
///Plot this initial t = 0 and Underlying price on the graph
chart.Series[Convert.ToString(i)].Points.AddXY(0, UnderlyingPrice[0]);
for (int j = 0; j < m; j++) ///Each run through this loop represents the next increment closer to t = T
{
///Because the Random() Class only allows the creation of uniform random variables between 0 and 1,
///a transform must be done to create a normal random variable with mean 0 and variance 1.
///The transform that was done is called the Box-Muller Transform
U1 = r.NextDouble(); ///Get first uniform random variable
U2 = r.NextDouble(); ///Get second uniform random variable
Z = Math.Sqrt(-2 * Math.Log(U1)) * Math.Cos(2 * Math.PI * U2); ///Box-Muller Transform to generate Z ~ N(0,1)
UnderlyingPrice[j + 1] = disc.Euler(UnderlyingPrice[j], mu, sigma, delta, Z); ///Generate the next X value based on the Euler Discretization
chart.Series[Convert.ToString(i)].Points.AddXY(delta*(j + 1), UnderlyingPrice[j + 1]); ///Plot the t value as well as X(t) value onto the graph for series i
}
CallPrice[i] = Math.Max(0, UnderlyingPrice[m] - K); ///Value of the call option.
}
///Find the sum of all the Call Prices that were simulated (used for the average)
for (int a = 0; a < N; a++ )
{
sum1 = sum1 + CallPrice[a];
}
//Calculate the average which represents the option price
OptionPrice = sum1 / N;
///Same procedure, but to calculate the Standard Error
for (int b = 0; b < N; b++)
{
sum2 = sum2 + Math.Pow((CallPrice[b] - OptionPrice), 2);
}
///SE = s / sqrt(N), where s is the sample standard deviation
StandardError = Math.Sqrt(sum2 / (N - 1)) / Math.Sqrt(N);
///Print out the required output: Price of the European Call Option and the Standard Error of the simulation
Console.WriteLine("The Price of the Option is: " + OptionPrice);
Console.WriteLine("The Standard Error of the Simulation is: " + StandardError);
///Save the graph of the Asset Prices for each simulation in a png file that is saved in the same folder as the location of the .exe
chart.SaveImage("StockPath.png", System.Drawing.Imaging.ImageFormat.Png);
///The console won't close until the user hits any key another time
Console.ReadKey();
}
private string GeneratePlot(List<double[]> data, string title)
{
string file = "";
chart = new System.Windows.Forms.DataVisualization.Charting.Chart();
chart.ChartAreas.Add(new System.Windows.Forms.DataVisualization.Charting.ChartArea());
foreach (var items in data)
{
int i = 1;
foreach (var item in items)
{
SetChart(title, i, item);
i++;
}
}
DateTime d = DateTime.Now;
var xxx = String.Format("{0}_{1}_{2}_{3}_{4}_{5}_{6}", d.Year, d.Month, d.Day, d.Hour, d.Minute, d.Second, d.Millisecond);
String chartFilename = ApplicationFolder + "\\" + xxx + ".bmp";
chart.Update();
chart.SaveImage(chartFilename, System.Drawing.Imaging.ImageFormat.Bmp);
file = chartFilename;
return file;
}
/// Main Code.
static void Main(string[] args)
{
///Defining variables
double[] UnderlyingPrice;
double[] CallPrice;
Random r = new Random(); ///this is the Class used to generate random variables
Discretization disc = new Discretization(); ///class that was coded above used to call the Euler function later in the code
System.Windows.Forms.DataVisualization.Charting.Chart chart = new System.Windows.Forms.DataVisualization.Charting.Chart(); ///class to set up Plot of underlying price
chart.ChartAreas.Add("ChartArea1"); ///set up the initial plot
///The following lines ask the user for the inputs needed to price the option and run the simulation
///Additionally, the inputs provided by the user are assigned the appropriate variables.
Console.WriteLine("Please Enter The Initial Asset Price:");
double X0 = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter The Strike Price of the Option:");
double K = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter The Time To Expiration:");
double T = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter mu:");
double mu = Convert.ToDouble(Console.ReadLine());
Console.WriteLine("Please Enter sigma:");
double sigma = Convert.ToDouble(Console.ReadLine());
/// Console.WriteLine("Please enter The Number of Simulations to Run:");
///int N = Convert.ToInt32(Console.ReadLine());
int N = 5000; ///Number of simulations
int m = 200; ///Number of increments between t = 0 and t = T
double delta = T / m; ///size of the increment
CallPrice = new double[N]; ///now allocating the size of array based on the number of simulations
UnderlyingPrice = new double[m + 1]; //now allocating the size of the array based on the number of increments
double U1; ///Represents uniform random variable between 0 and 1
double U2; ///Also represents uniform random variable between 0 and 1
double Z; ///Will represent the Normal Random Variable with mean 0 and variance 1
double sum1 = 0; //variable used to keep track of the sum in order to find the average of all the Call Prices for each of the simulations
double sum2 = 0; //variable used to keep track of the sum in order to ultimately find the Standard Error of the simulation
double OptionPrice; //Final European Call Option Price calculated
double StandardError; //Standard error of the simulation
for (int i = 0; i < N; i++) ///Each run through this loop represents 1 simulation
{
///Set up a new series that will be plotted on the graph
chart.Series.Add(Convert.ToString(i));
///Set chart type to Line graph
chart.Series[Convert.ToString(i)].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
///Initialize the Underlying Price array based on the input given by the user
UnderlyingPrice[0] = X0;
///Plot this initial t = 0 and Underlying price on the graph
chart.Series[Convert.ToString(i)].Points.AddXY(0, UnderlyingPrice[0]);
for (int j = 0; j < m; j++) ///Each run through this loop represents the next increment closer to t = T
{
///Because the Random() Class only allows the creation of uniform random variables between 0 and 1,
///a transform must be done to create a normal random variable with mean 0 and variance 1.
///The transform that was done is called the Box-Muller Transform
U1 = r.NextDouble(); ///Get first uniform random variable
U2 = r.NextDouble(); ///Get second uniform random variable
Z = Math.Sqrt(-2 * Math.Log(U1)) * Math.Cos(2 * Math.PI * U2); ///Box-Muller Transform to generate Z ~ N(0,1)
UnderlyingPrice[j + 1] = disc.Euler(UnderlyingPrice[j], mu, sigma, delta, Z); ///Generate the next X value based on the Euler Discretization
chart.Series[Convert.ToString(i)].Points.AddXY(delta * (j + 1), UnderlyingPrice[j + 1]); ///Plot the t value as well as X(t) value onto the graph for series i
}
CallPrice[i] = Math.Max(0, UnderlyingPrice[m] - K); ///Value of the call option.
}
///Find the sum of all the Call Prices that were simulated (used for the average)
for (int a = 0; a < N; a++)
{
sum1 = sum1 + CallPrice[a];
}
//Calculate the average which represents the option price
OptionPrice = sum1 / N;
///Same procedure, but to calculate the Standard Error
for (int b = 0; b < N; b++)
{
sum2 = sum2 + Math.Pow((CallPrice[b] - OptionPrice), 2);
}
///SE = s / sqrt(N), where s is the sample standard deviation
StandardError = Math.Sqrt(sum2 / (N - 1)) / Math.Sqrt(N);
///Print out the required output: Price of the European Call Option and the Standard Error of the simulation
Console.WriteLine("The Price of the Option is: " + OptionPrice);
Console.WriteLine("The Standard Error of the Simulation is: " + StandardError);
///Save the graph of the Asset Prices for each simulation in a png file that is saved in the same folder as the location of the .exe
chart.SaveImage("StockPath.png", System.Drawing.Imaging.ImageFormat.Png);
///The console won't close until the user hits any key another time
Console.ReadKey();
}
