/// <summary>
/// Экпорт диаграммы в один из типов
/// </summary>
/// <param name="type">Тип для экспорта</param>
public void ExportDiagram(ExportType type)
{
SaveFileDialog saveDialog = new SaveFileDialog();
saveDialog.Filter = type + " файлы (*." + type + ")|*." + type;
bool? result = saveDialog.ShowDialog();
if (result == true)
switch (type)
{
case ExportType.pdf:
PdfExporter pdfExporter = new PdfExporter();
pdfExporter.Export(DiagramNetwork, saveDialog.FileName);
break;
case ExportType.svg:
SvgExporter svgExporter = new SvgExporter();
svgExporter.Export(DiagramNetwork, saveDialog.FileName);
break;
}
}
// TODO: Draw to pdf file
public void XLDrawMSMatchToPdf(Ms2ScanWithSpecificMass MsScanForDraw, PsmCross psmParentsForDraw, int order, string OutputFolder)
{
var x = MsScanForDraw.TheScan.MassSpectrum.XArray;
var y = MsScanForDraw.TheScan.MassSpectrum.YArray;
string scanNum = psmParentsForDraw.ScanNumber.ToString();
string sequence1 = psmParentsForDraw.FullSequence + "-" + psmParentsForDraw.XlPos.ToString();
string sequence2 = psmParentsForDraw.BetaPsmCross.FullSequence + "-" + psmParentsForDraw.BetaPsmCross.XlPos.ToString();
var matchedIonDic1 = psmParentsForDraw.MatchedIonInfo;
var matchedIonDic2 = psmParentsForDraw.BetaPsmCross.MatchedIonInfo;
PlotModel model = new PlotModel {
Title = "Spectrum anotation of Scan " + scanNum + " for Crosslinked Peptide", DefaultFontSize = 15
};
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Bottom, Title = "m/z", Minimum = 0, Maximum = x.Max() * 1.02, AbsoluteMinimum = 0
});
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Left, Title = "Intensity(counts)", Minimum = 0, Maximum = y.Max() * 1.2, AbsoluteMinimum = 0
});
var textAnnoSeq1 = new TextAnnotation()
{
};
//textAnnoSeq1.TextRotation=90;
textAnnoSeq1.FontSize = 12; textAnnoSeq1.TextColor = OxyColors.Red; textAnnoSeq1.StrokeThickness = 0; textAnnoSeq1.TextPosition = new DataPoint(x.Max() / 2, y.Max() * 1.15); textAnnoSeq1.Text = sequence1;
var textAnnoSeq2 = new TextAnnotation()
{
};
//textAnnoSeq2.TextRotation=90;
textAnnoSeq2.FontSize = 12; textAnnoSeq2.TextColor = OxyColors.Blue; textAnnoSeq2.StrokeThickness = 0; textAnnoSeq2.TextPosition = new DataPoint(x.Max() / 2, y.Max() * 1.1); textAnnoSeq2.Text = sequence2;
model.Annotations.Add(textAnnoSeq1);
model.Annotations.Add(textAnnoSeq2);
LineSeries[] s0 = new LineSeries[x.Length];
LineSeries[] s1 = new LineSeries[x.Length];
LineSeries[] s2 = new LineSeries[x.Length];
//Draw the ms/ms scan peaks
for (int i = 0; i < x.Length; i++)
{
s0[i] = new LineSeries();
s0[i].Color = OxyColors.DimGray;
s0[i].StrokeThickness = STROKE_THICKNESS_UNANNOTATED;
s0[i].Points.Add(new DataPoint(x[i], 0));
s0[i].Points.Add(new DataPoint(x[i], y[i]));
model.Series.Add(s0[i]);
}
//Draw the ms/ms scan matched peaks
for (int i = 0; i < matchedIonDic1.MatchedIonMz.Length; i++)
{
OxyColor ionColor = OxyColors.Red;
if (matchedIonDic1.MatchedIonMz[i] > 0)
{
s1[i] = new LineSeries();
s1[i].Color = ionColor;
s1[i].StrokeThickness = STROKE_THICKNESS_ANNOTATED;
s1[i].Points.Add(new DataPoint(matchedIonDic1.MatchedIonMz[i] + 1.007277, 0));
s1[i].Points.Add(new DataPoint(matchedIonDic1.MatchedIonMz[i] + 1.007277, matchedIonDic1.MatchedIonIntensity[i]));
var textAnno1 = new TextAnnotation();
//textAnno1.TextRotation=90;
textAnno1.FontSize = 12;
textAnno1.TextColor = ionColor;
textAnno1.StrokeThickness = 0;
textAnno1.TextPosition = s1[i].Points[1];
textAnno1.Text = matchedIonDic1.MatchedIonMz[i].ToString("f3");
var textAnno2 = new TextAnnotation();
//textAnno2.TextRotation=90;
textAnno2.FontSize = 12;
textAnno2.TextColor = ionColor;
textAnno2.StrokeThickness = 0;
textAnno2.TextPosition = new DataPoint(s1[i].Points[1].X, s1[i].Points[1].Y + y.Max() * 0.02);
textAnno2.Text = matchedIonDic1.MatchedIonName[i];
model.Annotations.Add(textAnno1);
model.Annotations.Add(textAnno2);
model.Series.Add(s1[i]);
}
}
for (int i = 0; i < matchedIonDic2.MatchedIonMz.Length; i++)
{
OxyColor ionColor = OxyColors.Blue;
if (matchedIonDic2.MatchedIonMz[i] > 0)
{
s2[i] = new LineSeries();
s2[i].Color = ionColor;
s2[i].StrokeThickness = STROKE_THICKNESS_ANNOTATED;
s2[i].Points.Add(new DataPoint(matchedIonDic2.MatchedIonMz[i] + 1.007277, 0));
s2[i].Points.Add(new DataPoint(matchedIonDic2.MatchedIonMz[i] + 1.007277, matchedIonDic2.MatchedIonIntensity[i]));
var textAnno1 = new TextAnnotation();
//textAnno1.TextRotation=90;
textAnno1.FontSize = 12;
textAnno1.TextColor = ionColor;
textAnno1.StrokeThickness = 0;
textAnno1.TextPosition = s2[i].Points[1];
textAnno1.Text = matchedIonDic2.MatchedIonMz[i].ToString("f3");
var textAnno2 = new TextAnnotation();
//textAnno2.TextRotation=90;
textAnno2.FontSize = 12;
textAnno2.TextColor = ionColor;
textAnno2.StrokeThickness = 0;
textAnno2.TextPosition = new DataPoint(s2[i].Points[1].X, s2[i].Points[1].Y + y.Max() * 0.02);
textAnno2.Text = matchedIonDic2.MatchedIonName[i];
model.Annotations.Add(textAnno1);
model.Annotations.Add(textAnno2);
model.Series.Add(s2[i]);
}
}
using (var stream = File.Create(OutputFolder + "\\" + order.ToString() + "_Scan" + scanNum + ".pdf"))
{
PdfExporter pdf = new PdfExporter {
Width = 500, Height = 210
};
pdf.Export(model, stream);
}
}
/// <summary>
/// Plots average fitness graph to pdf in defalut directory
/// </summary>
/// <param name="Data"> List of lists of every creatures' fitness in given generation</param>
public void AverageFitnessPerGeneration(List <List <float> > Data)
{
#region Functions
/// Licz średnią
double CalculateAverage(List <float> generation)
{
float sum = 0f;
foreach (float fitness in generation)
{
sum += fitness;
}
return((double)(sum / generation.Count));
}
///funkcja tworząca szereg funkcyjny funkcji avg(x)
FunctionSeries functionSeries(List <List <float> > list)
{
int Length = list.Count;
FunctionSeries function = new FunctionSeries();
for (int x = 0; x < Length; x++)
{
for (int y = 0; y < Length; y++)
{
DataPoint point = new DataPoint(x, CalculateAverage(list[x]));
function.Points.Add(point);
}
}
return(function);
}
#endregion
/// Tworzenie Osi wykresu
LinearAxis linearAxisX = new LinearAxis
{
Title = "Generation Number",
Position = AxisPosition.Bottom,
Minimum = 0,
Maximum = 300,
MajorGridlineStyle = LineStyle.Dot,
MajorGridlineColor = OxyColor.FromRgb(128, 128, 128)
};
LinearAxis linearAxisY = new LinearAxis
{
Title = "Average Fitness",
Position = AxisPosition.Left,
MajorGridlineStyle = LineStyle.Dot,
MajorGridlineColor = OxyColor.FromRgb(128, 128, 128)
};
PlotModel PM = new PlotModel();
PM.Axes.Add(linearAxisX);
PM.Axes.Add(linearAxisY);
PM.Series.Add(functionSeries(Data));
/// Przykład z dokumentacji OxyPlot na Tworzenie pdf
/// TODO: Dynamiczna nazwa PDFu, inne formatowanie?
using (var stream = File.Create("LatestAvgFit.pdf"))
{
var pdfExporter2 = new PdfExporter {
Width = 600, Height = 400
};
pdfExporter2.Export(PM, stream);
}
}
/*Задача 17. Пуассоновские потоки частиц из двух источников сначала соединяются в один поток,
* в котором частицы нумеруются в порядке поступления.Затем этот поток разделяется на два таким образом,
* что первый поток состоит из четных частиц, а второй из нечетных.
* Построить функцию распределения и функцию плотности распределения длительности
* интервала времени между двумя частицами первого потока на основании 1000 выборочных значений уже разделенного потока.*/
static void Main(string[] args)
{
//общий поток, ключ -- номер
Dictionary <int, double> stream = new Dictionary <int, double>();
//лямбда -- значение
double val = 0.1;
for (int i = 1; i <= 1000; i++)
{
stream.Add(i, val);
val += 0.000001;
}
//два потока для чётных и не
//деление по номеру
Dictionary <int, double> firstStream = new Dictionary <int, double>();
Dictionary <int, double> secondStream = new Dictionary <int, double>();
foreach (var particle in stream)
{
if (particle.Key % 2 == 0)
{
firstStream.Add(particle.Key, particle.Value);
}
else
{
secondStream.Add(particle.Key, particle.Value);
}
}
//сами значения
//цикл с 1 до 500 -- время
//флаг для определения потока: чёт или не
//вычисление значений для графиков
int time = 1;
IList <DataPoint> dataDensity = new List <DataPoint>();
IList <DataPoint> dataDistribution = new List <DataPoint>();
bool flagUseFirstStream = false;
while (time <= 500)
{
if (flagUseFirstStream)
{
double point = firstStream[time] * Math.Pow(2.7, -(firstStream[time] * time));
dataDensity.Add(new DataPoint(time, point));
point = 1 - Math.Exp(-firstStream[time] * time);
dataDistribution.Add(new DataPoint(time, point));
}
else
{
double point = secondStream[time] * Math.Pow(2.7, -(secondStream[time] * time));
dataDensity.Add(new DataPoint(time, point));
point = 1 - Math.Exp(-secondStream[time] * time);
dataDistribution.Add(new DataPoint(time, point));
}
flagUseFirstStream = !flagUseFirstStream;
time++;
}
var model = new PlotModel {
Title = "Graph", DefaultFont = "Arial"
};
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Bottom
});
model.Axes.Add(new LinearAxis {
Position = AxisPosition.Left
});
var areaSeries = new AreaSeries();
areaSeries.Points.AddRange(dataDensity);
model.Series.Add(areaSeries);
//график
// х -- время
// у -- лямбда от времени
//плотность
var exporter = new PdfExporter {
Width = 400, Height = 400
};
using (var streamGraph = File.Create("density.pdf"))
{
exporter.Export(model, streamGraph);
}
var modelDistribution = new PlotModel {
Title = "Graph", DefaultFont = "Arial"
};
modelDistribution.Axes.Add(new LinearAxis {
Position = AxisPosition.Bottom
});
modelDistribution.Axes.Add(new LinearAxis {
Position = AxisPosition.Left
});
var areaSeriesDistribution = new AreaSeries();
areaSeriesDistribution.Points.AddRange(dataDistribution);
modelDistribution.Series.Add(areaSeriesDistribution);
//распр
var exporterDistribution = new PdfExporter {
Width = 400, Height = 400
};
using (var streamGraph = File.Create("distribution.pdf"))
{
exporterDistribution.Export(modelDistribution, streamGraph);
}
}
public static void Plot(string inputFilename)
{
var sizeData = new List <double>();
var timeData = new List <double>();
var errorData = new List <double>();
using (var reader = new StreamReader(inputFilename))
{
reader.ReadLine();
while (!reader.EndOfStream)
{
var row = reader.ReadLine();
var cells = row.Split(',');
sizeData.Add(Convert.ToDouble(cells[1]));
timeData.Add(Convert.ToDouble(cells[2]));
errorData.Add(Convert.ToDouble(cells[3]));
}
}
for (var i = 0; i < 2; i++)
{
var title = i == 0 ? "Time" : "Error";
var data = i == 0 ? timeData : errorData;
var model = new PlotModel {
Title = $"{inputFilename.Replace('_', ' ').Replace(".csv", "")} {title.ToLower()} plot"
};
model.Axes.Add(new LinearAxis
{
Title = "Size",
Position = AxisPosition.Bottom,
Minimum = 0,
Maximum = sizeData.Last() + 1
});
model.Axes.Add(new LinearAxis
{
Title = title,
Position = AxisPosition.Left,
Minimum = 0,
Maximum = data.Max() + data.Max() / 10
});
var lineSeries = new LineSeries();
for (var j = 0; j < sizeData.Count; j++)
{
lineSeries.Points.Add(new DataPoint(sizeData[j], data[j]));
}
model.Series.Add(lineSeries);
using (var stream = File.Create($"{inputFilename}_{title}Plot.pdf"))
{
var pdfExporter = new PdfExporter {
Width = 600, Height = 400
};
pdfExporter.Export(model, stream);
}
}
}
// [ref] ${OxyPlot_HOME}/NET45/Examples/ExampleBrowser/ExampleBrowser.exe.
static void runMarketTypes()
{
var plotModel = new PlotModel();
plotModel.Title = "Marker types";
var linearAxis1 = new LinearAxis();
linearAxis1.Position = AxisPosition.Bottom;
plotModel.Axes.Add(linearAxis1);
var linearAxis2 = new LinearAxis();
plotModel.Axes.Add(linearAxis2);
var lineSeries1 = new LineSeries();
lineSeries1.MarkerStroke = OxyColors.Black;
lineSeries1.MarkerType = MarkerType.Circle;
lineSeries1.Title = "Circle";
lineSeries1.Points.Add(new DataPoint(11.8621869598805, 1.4144100893356));
lineSeries1.Points.Add(new DataPoint(18.1636718735861, 3.34725344383496));
lineSeries1.Points.Add(new DataPoint(26.1161091961507, 5.10126935043431));
lineSeries1.Points.Add(new DataPoint(29.99451482482, 6.99704349646207));
lineSeries1.Points.Add(new DataPoint(41.9055463103138, 8.21414295500803));
lineSeries1.Points.Add(new DataPoint(48.6674896314123, 9.55912132400978));
lineSeries1.Points.Add(new DataPoint(56.0143694207139, 10.8773872386093));
lineSeries1.Points.Add(new DataPoint(67.4011132397694, 12.2735980540857));
lineSeries1.Points.Add(new DataPoint(74.2207925069243, 13.5990719658318));
lineSeries1.Points.Add(new DataPoint(78.4307891402537, 14.9570749639334));
plotModel.Series.Add(lineSeries1);
var lineSeries2 = new LineSeries();
lineSeries2.MarkerStroke = OxyColors.Black;
lineSeries2.MarkerType = MarkerType.Cross;
lineSeries2.Title = "Cross";
lineSeries2.Points.Add(new DataPoint(10.2551460425626, 1.12034707615168));
lineSeries2.Points.Add(new DataPoint(17.2749783542356, 2.66979351810636));
lineSeries2.Points.Add(new DataPoint(21.436097549012, 4.12809186853845));
lineSeries2.Points.Add(new DataPoint(30.78668166268, 5.20108992848596));
lineSeries2.Points.Add(new DataPoint(33.2050538869598, 6.637421580794));
lineSeries2.Points.Add(new DataPoint(45.0304378052384, 7.66540479830718));
lineSeries2.Points.Add(new DataPoint(56.7345610422709, 9.54063240976102));
lineSeries2.Points.Add(new DataPoint(66.1928816270981, 10.7854569441571));
lineSeries2.Points.Add(new DataPoint(74.2900140398601, 12.665478166037));
lineSeries2.Points.Add(new DataPoint(79.0780252865879, 13.7934278663217));
plotModel.Series.Add(lineSeries2);
var lineSeries3 = new LineSeries();
lineSeries3.MarkerStroke = OxyColors.Black;
lineSeries3.MarkerType = MarkerType.Diamond;
lineSeries3.Title = "Diamond";
lineSeries3.Points.Add(new DataPoint(8.23705901030314, 1.04818704773122));
lineSeries3.Points.Add(new DataPoint(15.3159614062477, 2.61679908755086));
lineSeries3.Points.Add(new DataPoint(26.0893045543178, 3.88729132986036));
lineSeries3.Points.Add(new DataPoint(30.3871664714008, 5.60047892089955));
lineSeries3.Points.Add(new DataPoint(42.2880761336014, 6.83121995620021));
lineSeries3.Points.Add(new DataPoint(45.5782417531955, 8.70534298555243));
lineSeries3.Points.Add(new DataPoint(53.6039859063942, 9.76094881480604));
lineSeries3.Points.Add(new DataPoint(63.170427156226, 11.6268204346424));
lineSeries3.Points.Add(new DataPoint(74.2946957379089, 13.5075224840583));
lineSeries3.Points.Add(new DataPoint(83.4620100881262, 14.6444678658827));
plotModel.Series.Add(lineSeries3);
var lineSeries4 = new LineSeries();
lineSeries4.MarkerStroke = OxyColors.Black;
lineSeries4.MarkerType = MarkerType.Plus;
lineSeries4.Title = "Plus";
lineSeries4.Points.Add(new DataPoint(2.18957495232559, 1.11484250291942));
lineSeries4.Points.Add(new DataPoint(12.7289441883233, 2.66961399916076));
lineSeries4.Points.Add(new DataPoint(17.0745548555043, 4.11782511375743));
lineSeries4.Points.Add(new DataPoint(22.8202153084894, 5.77728548123375));
lineSeries4.Points.Add(new DataPoint(30.5445538696575, 7.4711353287432));
lineSeries4.Points.Add(new DataPoint(40.409529611659, 9.07308203357881));
lineSeries4.Points.Add(new DataPoint(42.8762574823928, 10.166131996627));
lineSeries4.Points.Add(new DataPoint(52.219228453105, 11.9434595531521));
lineSeries4.Points.Add(new DataPoint(60.3437968186772, 13.8768307444997));
lineSeries4.Points.Add(new DataPoint(69.0649180901539, 15.8224504216679));
plotModel.Series.Add(lineSeries4);
var lineSeries5 = new LineSeries();
lineSeries5.MarkerStroke = OxyColors.Black;
lineSeries5.MarkerType = MarkerType.Square;
lineSeries5.Title = "Square";
lineSeries5.Points.Add(new DataPoint(4.28512158723787, 1.0218708203276));
lineSeries5.Points.Add(new DataPoint(7.11419252451239, 2.83296700745493));
lineSeries5.Points.Add(new DataPoint(12.1873434279986, 3.94138236993057));
lineSeries5.Points.Add(new DataPoint(18.4414314499318, 5.85618886438021));
lineSeries5.Points.Add(new DataPoint(21.6272663146384, 7.73614930302657));
lineSeries5.Points.Add(new DataPoint(26.9512430769164, 9.46516049488688));
lineSeries5.Points.Add(new DataPoint(30.584140945498, 10.6070162377353));
lineSeries5.Points.Add(new DataPoint(33.6740629960196, 12.1158796358462));
lineSeries5.Points.Add(new DataPoint(37.6165642373341, 14.0689983791993));
lineSeries5.Points.Add(new DataPoint(42.9570739683495, 15.4981215794096));
plotModel.Series.Add(lineSeries5);
var lineSeries6 = new LineSeries();
lineSeries6.MarkerStroke = OxyColors.Black;
lineSeries6.MarkerType = MarkerType.Star;
lineSeries6.Title = "Star";
lineSeries6.Points.Add(new DataPoint(10.9592619701099, 1.57032582423199));
lineSeries6.Points.Add(new DataPoint(14.3667993193338, 2.86656694294259));
lineSeries6.Points.Add(new DataPoint(20.8092339303387, 4.3936368000664));
lineSeries6.Points.Add(new DataPoint(31.0837363531272, 5.90316125233805));
lineSeries6.Points.Add(new DataPoint(36.2968236749511, 7.88247782079618));
lineSeries6.Points.Add(new DataPoint(40.8309715077425, 9.86153348761682));
lineSeries6.Points.Add(new DataPoint(44.9168707304247, 11.6326452454704));
lineSeries6.Points.Add(new DataPoint(56.0012029614305, 13.6297319203754));
lineSeries6.Points.Add(new DataPoint(58.3205570533502, 14.6725726568478));
lineSeries6.Points.Add(new DataPoint(62.7951211122773, 15.7987183610903));
plotModel.Series.Add(lineSeries6);
var lineSeries7 = new LineSeries();
lineSeries7.MarkerStroke = OxyColors.Black;
lineSeries7.MarkerType = MarkerType.Triangle;
lineSeries7.Title = "Triangle";
lineSeries7.Points.Add(new DataPoint(2.2280231240336, 1.45975955084886));
lineSeries7.Points.Add(new DataPoint(9.6367919340901, 3.15223296831932));
lineSeries7.Points.Add(new DataPoint(15.2513136469067, 4.20971935065916));
lineSeries7.Points.Add(new DataPoint(21.6378828266812, 6.11453639488413));
lineSeries7.Points.Add(new DataPoint(33.4784604066417, 7.33997009384445));
lineSeries7.Points.Add(new DataPoint(41.3092347305777, 8.99930818704856));
lineSeries7.Points.Add(new DataPoint(49.3024369130388, 10.2422971139859));
lineSeries7.Points.Add(new DataPoint(51.7993717146103, 11.9004834484777));
lineSeries7.Points.Add(new DataPoint(62.6105425686625, 13.6871494234945));
lineSeries7.Points.Add(new DataPoint(68.2790698289308, 15.4673946567194));
plotModel.Series.Add(lineSeries7);
//
#if false
String output_filename = "../data/visualization/oxyplot/lineseries_marker_type.png";
using (var stream = File.Create(output_filename))
{
System.Windows.Threading.Dispatcher.CurrentDispatcher.Invoke(
System.Windows.Threading.DispatcherPriority.Normal,
new Action(
delegate
{
OxyPlot.Wpf.PngExporter.Export(plotModel, stream, 600, 400, OxyColors.White); // run-time error.
}
)
);
}
#elif true
String output_filename = "../data/visualization/oxyplot/lineseries_marker_type.pdf";
using (var stream = File.Create(output_filename))
{
PdfExporter.Export(plotModel, stream, 600, 400);
}
#elif true
// Copy to clipboard.
using (var stream = new MemoryStream())
{
OxyPlot.Wpf.PngExporter.Export(plotModel, stream, 600, 400, OxyColors.White); // run-time error.
}
#endif
}
private void exportButton_Click(object sender, EventArgs e)
{
if (exportHeightValue.BackColor == Color.Red)
{
const string message = "Please choose an integer value for the export height.";
const string caption = "Error";
var result = MessageBox.Show(message, caption,
MessageBoxButtons.OK,
MessageBoxIcon.Error);
return;
}
if (exportWidthValue.BackColor == Color.Red)
{
const string message = "Please choose an integer value for the export width.";
const string caption = "Error";
var result = MessageBox.Show(message, caption,
MessageBoxButtons.OK,
MessageBoxIcon.Error);
return;
}
if (exportAsComboBox.Text == "SVG")
{
SaveFileDialog saveParameters = new SaveFileDialog();
saveParameters.Filter = ".svg files|*.svg";
saveParameters.Title = "Export figure as .svg";
if (saveParameters.ShowDialog() == DialogResult.Cancel)
{
return;
}
using (var stream = File.Create(saveParameters.FileName))
{
var exporter = new SvgExporter {
Width = Convert.ToInt32(exportWidthValue.Text.ToString()),
Height = Convert.ToInt32(exportHeightValue.Text.ToString())
};
exporter.Export(plotViewMassSpectrum.Model, stream);
}
}
else if (exportAsComboBox.Text == "PDF")
{
SaveFileDialog saveParameters = new SaveFileDialog();
saveParameters.Filter = ".pdf files|*.pdf";
saveParameters.Title = "Export figure as .pdf";
if (saveParameters.ShowDialog() == DialogResult.Cancel)
{
return;
}
using (var stream = File.Create(saveParameters.FileName))
{
var exporter = new PdfExporter {
Width = Convert.ToInt32(exportWidthValue.Text.ToString()),
Height = Convert.ToInt32(exportHeightValue.Text.ToString())
};
exporter.Export(plotViewMassSpectrum.Model, stream);
}
}
else if (exportAsComboBox.Text == "PNG")
{
SaveFileDialog saveParameters = new SaveFileDialog();
saveParameters.Filter = "PNG files|*.png";
saveParameters.Title = "Export figure as .png";
if (saveParameters.ShowDialog() == DialogResult.Cancel)
{
return;
}
using (var stream = File.Create(saveParameters.FileName))
{
var exporter = new OxyPlot.WindowsForms.PngExporter
{
Width = Convert.ToInt32(exportWidthValue.Text.ToString()),
Height = Convert.ToInt32(exportHeightValue.Text.ToString())
};
exporter.Export(plotViewMassSpectrum.Model, stream);
}
}
}
///<summary>
/// Create and run a Fleet MSO that attempts to find the optimum fleet composition to raid this defense
///</summary>
static Defense Solve()
{
Random rand = new Random(0);
DefenseSwarm[] defenseSwarms = new DefenseSwarm[NumSwarms];
for (int i = 0; i < NumSwarms; i++)
{
defenseSwarms[i] = new DefenseSwarm();
}
Defense gBestDefense = new Defense();
double gBestError = double.MaxValue;
for (int i = 0; i < NumSwarms; ++i)
{
if (defenseSwarms[i].lBestError < gBestError)
{
gBestError = defenseSwarms[i].lBestError;
gBestDefense.CopyDefense(defenseSwarms[i].lBestDefense);
}
}
var gBestList = new List <(int, double)>
{
(-1, gBestError)
};
int epoch = 0;
while (epoch < MaxEpochsOuter)
{
++epoch;
if (epoch < MaxEpochsOuter)
{
Console.WriteLine("Outer Epoch " + epoch + ", gBestError " + gBestError.ToString("F1"));
}
for (int i = 0; i < NumSwarms; ++i) // each swarm
{
// Shuffle(sequence, rand); // move particles in random sequence
for (int j = 0; j < NumParticles; ++j) // each particle
{
//Death
double p1 = rand.NextDouble();
if (defenseSwarms[i].defenseParticles[j].consecutiveNonImproves * p1 > 20)
{
defenseSwarms[i].defenseParticles[j] = new DefenseParticle(); // new random position
if (defenseSwarms[i].defenseParticles[j].error < defenseSwarms[i].lBestError) // new swarm best by luck?
{
defenseSwarms[i].lBestError = defenseSwarms[i].defenseParticles[j].error;
defenseSwarms[i].lBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
if (defenseSwarms[i].defenseParticles[j].error < gBestError) // if a new swarm best, maybe also a new global best?
{
//must repeat defense evaluation to avoid outlier skewing results
double result1 = defenseSwarms[i].defenseParticles[j].error;
double result2 = defenseSwarms[i].defenseParticles[j].EvaluateDefense();
double result3 = defenseSwarms[i].defenseParticles[j].EvaluateDefense();
double maxResult = new[] { result1, result2, result3 }.Max();
if (maxResult < gBestError)
{
gBestError = maxResult;
gBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
}
}
}
}
//Immigration
double p2 = rand.NextDouble();
if (p2 < ProbImmigrate)
{
int otherSwarm = rand.Next(0, NumSwarms);
int otherParticle = rand.Next(0, NumParticles);
DefenseParticle tmp = defenseSwarms[i].defenseParticles[j];
defenseSwarms[i].defenseParticles[j] = defenseSwarms[otherSwarm].defenseParticles[otherParticle];
defenseSwarms[otherSwarm].defenseParticles[otherParticle] = tmp;
if (defenseSwarms[i].defenseParticles[j].pBestError < defenseSwarms[otherSwarm].lBestError) // new (other) swarm best?
{
defenseSwarms[otherSwarm].lBestError = defenseSwarms[i].defenseParticles[j].pBestError;
defenseSwarms[otherSwarm].lBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
}
if (defenseSwarms[otherSwarm].defenseParticles[otherParticle].pBestError < defenseSwarms[i].lBestError) // new (curr) swarm best?
{
defenseSwarms[i].lBestError = defenseSwarms[otherSwarm].defenseParticles[otherParticle].pBestError;
defenseSwarms[i].lBestDefense.CopyDefense(defenseSwarms[otherSwarm].defenseParticles[otherParticle].defense);
}
// not possible for a new global best
}
for (int k = 0; k < DefenseDims; ++k) // update velocity. each x position component
{
double r1 = rand.NextDouble();
double r2 = rand.NextDouble();
double r3 = rand.NextDouble();
defenseSwarms[i].defenseParticles[j].velocity[k]
= (
(Inertia * defenseSwarms[i].defenseParticles[j].velocity[k])
+ (GravityLocal * r1 * (defenseSwarms[i].defenseParticles[j].pBestDefense.DefenseCounts[k]
- defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k])
)
+ (GravitySwarm * r2 * (defenseSwarms[i].lBestDefense.DefenseCounts[k]
- defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k])
)
+ (GravityGlobal * r3 * (gBestDefense.DefenseCounts[k]
- defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k])
)
);
//constrain velocities
//if (defenseSwarms[i].defenseParticles[j].velocity[k] < minX)
// defenseSwarms[i].defenseParticles[j].velocity[k] = minX;
//else if (defenseSwarms[i].defenseParticles[j].velocity[k] > maxX)
// defenseSwarms[i].defenseParticles[j].velocity[k] = maxX;
}
for (int k = 0; k < DefenseDims; ++k) // update position
{
defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k] += (int)defenseSwarms[i].defenseParticles[j].velocity[k];
// constrain all xi
if (defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k] < 0 ||
defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k] > DefenseUnitsMaximums[k])
{
defenseSwarms[i].defenseParticles[j].defense.DefenseCounts[k] = (int)(rand.NextDouble() * DefenseUnitsMaximums[k]);
}
}
// update error
defenseSwarms[i].defenseParticles[j].EvaluateDefense();
// check if new best error for this particle
if (defenseSwarms[i].defenseParticles[j].error < defenseSwarms[i].defenseParticles[j].pBestError)
{
defenseSwarms[i].defenseParticles[j].pBestError = defenseSwarms[i].defenseParticles[j].error;
defenseSwarms[i].defenseParticles[j].pBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
if (defenseSwarms[i].defenseParticles[j].error < defenseSwarms[i].lBestError) // new swarm best?
{
defenseSwarms[i].lBestError = defenseSwarms[i].defenseParticles[j].error;
defenseSwarms[i].lBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
if (defenseSwarms[i].defenseParticles[j].error < gBestError) // new global best?
{
//must repeat defense evaluation to avoid outlier skewing results
double result1 = defenseSwarms[i].defenseParticles[j].error;
double result2 = defenseSwarms[i].defenseParticles[j].EvaluateDefense();
double result3 = defenseSwarms[i].defenseParticles[j].EvaluateDefense();
double maxResult = new[] { result1, result2, result3 }.Max();
if (maxResult < gBestError)
{
gBestError = maxResult;
gBestDefense.CopyDefense(defenseSwarms[i].defenseParticles[j].defense);
gBestList.Add((epoch, gBestError));
}
}
}
}
} // each particle
} // each swarm
} // while
string defenseStr = String.Join(", ", gBestDefense.DefenseCounts);
Console.WriteLine("\n****Best defense found: " + defenseStr + " ****");
var pm = new PlotModel {
Title = "DefenseMSO", PlotAreaBorderThickness = new OxyThickness(0)
};
var categoryAxis = new OxyPlot.Axes.CategoryAxis {
AxislineStyle = LineStyle.Solid, TickStyle = TickStyle.None
};
var value = new List <DataPoint>();
for (int i = 0; i < gBestList.Count; i++)
{
value.Add(new DataPoint(gBestList[i].Item1, gBestList[i].Item2));
}
pm.Axes.Add
(
new OxyPlot.Axes.LinearAxis
{
Position = AxisPosition.Left,
Minimum = -Math.Abs(gBestList[0].Item2),
Maximum = 1.05 * Math.Abs(gBestList[gBestList.Count - 1].Item2),
MajorStep = Math.Abs(gBestList[0].Item2 / 10),
MinorStep = Math.Abs(gBestList[0].Item2 / 50),
AxislineStyle = LineStyle.Solid,
TickStyle = TickStyle.Crossing,
StringFormat = "0,0"
}
);
pm.Axes.Add
(
new OxyPlot.Axes.LinearAxis
{
Position = AxisPosition.Bottom,
Minimum = -1,
Maximum = MaxEpochsOuter,
MajorStep = Program.MaxEpochsInner / 5,
MinorStep = Program.MaxEpochsInner / 20,
AxislineStyle = LineStyle.Solid,
TickStyle = TickStyle.Outside
}
);
pm.Series.Add
(
new OxyPlot.Series.ScatterSeries
{
ItemsSource = value,
MarkerType = MarkerType.Circle,
MarkerSize = 3.0,
MarkerFill = OxyColors.White,
MarkerStroke = OxyColors.Black,
DataFieldX = "X",
DataFieldY = "Y"
}
);
Stream stream = File.Create("C:\\Users\\admin\\source\\repos\\SpeedSimML\\SpeedSimML\\defenseplot.pdf");
var pdf = new PdfExporter();
PdfExporter.Export(pm, stream, 400.0, 400);
return(gBestDefense);
}
/// <summary>
/// "helper" funtion to generate CDF,PDF and histogram for a list.
/// </summary>
public void CDFPDF(List <double> source, string filename)
{
Operations functions = new Operations();
int count = 0;
PlotModel graf = new PlotModel {
Title = "Histogram " + filename
};
PlotModel graf_cdf = new PlotModel {
Title = "CDF " + filename
};
PlotModel graf_pdf = new PlotModel {
Title = "PDF " + filename
};
List <double> workData = new List <double>();
foreach (var petal in source)
{
workData.Add(petal);
}
workData.Sort();
double[] values = workData.ToArray();
var bucketeer = new Dictionary <double, double>();
var groups = workData.GroupBy(i => i);
List <string> kek = new List <string>();
var overlayData = new LineSeries();
var PDF = new LineSeries();
int z = 0;
foreach (var iris in groups)
{
bucketeer.Add(iris.Key, iris.Count());
kek.Add(iris.Key.ToString());
count = count + iris.Count();
z++;
overlayData.Points.Add(new DataPoint(z, count / 1.5));
PDF.Points.Add(new DataPoint(z, functions.PDF(functions.CDF(iris.Key, functions.Average(workData), functions.StandartDeviation(workData)))));
}
ColumnSeries ColSer = new ColumnSeries();
CategoryAxis Axis = new CategoryAxis();
foreach (var pair in bucketeer.OrderBy(x => x.Key))
{
ColSer.Items.Add(new ColumnItem(pair.Value));
}
Axis.ItemsSource = kek;
CategoryAxis Axis2 = new CategoryAxis();
Axis2.ItemsSource = kek;
CategoryAxis Axis3 = new CategoryAxis();
Axis3.ItemsSource = kek;
graf.Series.Add(ColSer);
graf.Axes.Add(Axis);
graf_cdf.Series.Add(overlayData);
graf_cdf.Axes.Add(Axis2);
graf_pdf.Series.Add(PDF);
graf_pdf.Axes.Add(Axis3);
using (var stream = File.Create(filename + "_histogram.pdf"))
{
var pdfExporter = new PdfExporter {
Width = 1000, Height = 400
};
pdfExporter.Export(graf, stream);
Console.WriteLine("Graph " + filename + "_histogram.pdf" + " generated!");
}
using (var stream = File.Create(filename + "_CDF.pdf"))
{
var pdfExporter = new PdfExporter {
Width = 1000, Height = 400
};
pdfExporter.Export(graf_cdf, stream);
Console.WriteLine("Graph " + filename + "_CDF.pdf" + " generated!");
}
using (var stream = File.Create(filename + "_PDF.pdf"))
{
var pdfExporter = new PdfExporter {
Width = 1000, Height = 400
};
pdfExporter.Export(graf_pdf, stream);
Console.WriteLine("Graph " + filename + "_PDF.pdf" + " generated!");
}
}
public void ExportPerformanceReportsAsPNG_PDF(List <IEnumerable <SecretSharingBenchmarkReport> > results, List <string> titles,
string PlotTitle, bool drawMinusPrimeTime, bool drawElapsedTime, Func <SecretSharingBenchmarkReport, long> selector, string selectorTitle,
Func <IEnumerable <long>, double> functionToDraw, string functionTitle, string ExportPNGFileName)
{
InitializeComponent();
InitPlotView();
var myModel = new PlotModel {
Title = string.Format("{0}", PlotTitle)
};
myModel.LegendPosition = LegendPosition.TopLeft;
int i = 0;
if (results == null || results.Count == 0)
{
return;
}
double minMs = double.MaxValue;
double maxMs = double.MinValue;
List <SecretSharingBenchmarkReport> temp = new List <SecretSharingBenchmarkReport>();
var a = results.Select(po => po.ToList()).Aggregate((current, next) =>
{
temp.AddRange(current);
temp.AddRange(next);
return(temp);
});
long minN;
long maxN;
if (temp.Count > 0)
{
minN = temp.Min(selector);
maxN = temp.Max(selector);
}
else
{
minN = results[0].Min(selector);
maxN = results[0].Max(selector);
}
foreach (var reports in results)
{
double sumPrimeGenTime, rmsPrimeTime = 0.0;
LineSeries lineNoPrimeSeries = null;
var lineSeries = new LineSeries(titles[i]);
lineSeries.MarkerType = MarkerType.Circle;
lineSeries.Smooth = true;
#if calcPrimeTime
if (drawMinusPrimeTime)
{
sumPrimeGenTime = reports.Select(po => Math.Pow(po.primeGenerationTime, 2.0)).Aggregate((current, next) => current + next);
rmsPrimeTime = Math.Sqrt(1.0 / (double)reports.Count() * (sumPrimeGenTime));
lineNoPrimeSeries = new LineSeries(titles[i] + "primeGen:" + rmsPrimeTime.ToString());
}
#endif
foreach (var report in reports)
{
// if we have all elapsd ticks we can view the graph as the f(x) that we wish otherwise only totalElapsed is available
var ElapsdToDraw = report.ElapsedTicks == null? report.TotalElapsedMilliseconds: functionToDraw(report.ElapsedTicks);
if (drawElapsedTime)
{
maxMs = Math.Max(maxMs, ElapsdToDraw);
minMs = Math.Min(minMs, ElapsdToDraw);
lineSeries.Points.Add(new DataPoint(selector(report), ElapsdToDraw));
}
#if calcPrimeTime
if (drawMinusPrimeTime)
{
//if (report.TotalElapsedMilliseconds - rmsPrimeTime <= 0) throw new Exception("rms is bigger than total elapsed time");
if (report.TotalElapsedMilliseconds - rmsPrimeTime /*report.primeGenerationTime*/ < minMs)
{
minMs = report.TotalElapsedMilliseconds - rmsPrimeTime /*report.primeGenerationTime*/;
}
if (report.TotalElapsedMilliseconds - rmsPrimeTime /*report.primeGenerationTime*/ > maxMs)
{
maxMs = report.TotalElapsedMilliseconds - rmsPrimeTime /* report.primeGenerationTime*/;
}
lineNoPrimeSeries.Points.Add(new DataPoint(report.n, report.TotalElapsedMilliseconds - rmsPrimeTime /*report.primeGenerationTime*/));
}
#endif
}
if (lineSeries.Points.Count > 0)
{
myModel.Series.Add(lineSeries);
}
if (lineNoPrimeSeries != null && lineNoPrimeSeries.Points.Count > 0)
{
myModel.Series.Add(lineNoPrimeSeries);
}
i++;
}
// myModel.Series.Add(new FunctionSeries(nloglogn, 0, 10, 0.1, "N log2(N)"));
myModel.Axes.Add(new OxyPlot.Axes.LinearAxis(OxyPlot.Axes.AxisPosition.Bottom, minN, maxN, selectorTitle));
myModel.Axes.Add(new OxyPlot.Axes.LinearAxis(OxyPlot.Axes.AxisPosition.Left, minMs - 3 < 0 ? 0 : minMs - 3, maxMs, functionTitle));
this.plot1.Model = myModel;
//if (ExportPdfFileName != null)
//{
using (var stream = File.Create(ExportPNGFileName + ".pdf"))
{
PdfExporter.Export(myModel, stream, 600, 400);
}
OxyPlot.WindowsForms.PngExporter.Export(myModel, ExportPNGFileName + ".png", 600, 400, Brushes.White);
//}
}