public void ChangeText(string msg, string time)
{
MessageView.Text = msg;
TimeView.Text = "Roundtrip Time: " + time;
DataPointsBuffer.Enqueue(new DataPoint(TimePoint++, int.Parse(msg))); //DateTime.Now.ToUniversalTime().Millisecond
if (DataPointsBuffer.Count > 10)
{
DataPoint popPoint;
DataPointsBuffer.TryDequeue(out popPoint);
}
var series1 = new OxyPlot.Series.LineSeries
{
MarkerType = OxyPlot.MarkerType.Circle,
MarkerSize = 4,
MarkerStroke = OxyPlot.OxyColors.White
};
foreach (var datapoint in DataPointsBuffer)
{
series1.Points.Add(datapoint);
}
plotModel.Series.Clear();
plotModel.Series.Add(series1);
plotModel.InvalidatePlot(true);
}
public void DrawPoints()
{
if (Opt.Points == null)
throw new NullReferenceException("No any points!");
foreach (var poinInfo in Opt.Points)
{
if (poinInfo.IsPointVisible)
{
var pointLine = new LineSeries
{
StrokeThickness = 4,
Smooth = true,
Color = OxyColor.FromRgb(0, 0, 0),
Points = new List<IDataPoint>()
};
pointLine.Points.Add(new DataPoint(poinInfo.Point.X, poinInfo.Point.Y));
_mainPlot.Series.Add(pointLine);
}
if (poinInfo.Label != null)
{
var stringLabel = new OxyPlot.Annotations.TextAnnotation
{
Text = poinInfo.Label,
Position = new DataPoint(poinInfo.Point.X + 2, poinInfo.Point.Y + 2),
TextColor = OxyColor.FromArgb(0, 0, 0, 0),
StrokeThickness = 0,
Stroke = OxyColor.FromArgb(0, 255, 255, 255),
FontSize = 25
};
_mainPlot.Annotations.Add(stringLabel);
}
}
}
void _presenter_MetricsUpdated(object sender, Presenters.TeamCityMetricsEventArgs e)
{
Dispatcher.Invoke(new Action(() =>
{
messageText.Visibility = System.Windows.Visibility.Hidden;
graph.Visibility = System.Windows.Visibility.Visible;
var data = this.DataContext as ViewCommon.ZeroToAutoScaleByDateGraphModel;
if (data != null)
{
var series = data.Model.Series;
series.Clear();
foreach (var metricSeries in e.Series)
{
var seriesData = new OxyPlot.Series.LineSeries {
Title = metricSeries.Name
};
seriesData.MarkerType = OxyPlot.MarkerType.Circle;
seriesData.MarkerSize = 4;
foreach (var metricPoint in metricSeries.Points)
{
seriesData.Points.Add(OxyPlot.Axes.DateTimeAxis.CreateDataPoint(metricPoint.X, metricPoint.Y));
}
seriesData.StrokeThickness = 4;
series.Add(seriesData);
}
}
graph.Model.InvalidatePlot(true);
}));
}
public ChartVm(Cache cache, string name)
{
PlotData = new PlotModel {
Title = $"{Localization.Chart}: {name}"
};
_cache = cache;
_data = new LineSeries();
foreach (var element in cache.GetAll())
{
var time = DateTimeAxis.ToDouble(element.Stamp);
_data.Points.Add(new DataPoint(time, element.Value));
}
PlotData.Axes.Add(new DateTimeAxis {
StringFormat = "mm:ss"
});
PlotData.Axes.Add(new LinearAxis {
Maximum = 100, Minimum = 0
});
PlotData.Series.Add(_data);
_cache.OnValuesChanged += OnValuesChanged;
}
static void DisplayActions(NetworkModel model, OxyPlot.Series.LineSeries series = null)
{
Console.WriteLine("\n\nActions:");
Console.WriteLine("[Any key] Run | [Q]uit | [S]ave | [D]elete");
Console.WriteLine("");
switch (Console.ReadKey(true).Key)
{
case ConsoleKey.Q:
{
Environment.Exit(0);
break;
}
case ConsoleKey.S:
{
SaveModel(model, series);
Environment.Exit(0);
break;
}
case ConsoleKey.D:
{
DeleteModel(model);
Environment.Exit(0);
break;
}
}
}
static void SaveModel(NetworkModel model, OxyPlot.Series.LineSeries series = null)
{
Console.WriteLine("\nSaving model...");
if (series != null)
{
try
{
var graphPoints = new List <Vector <double> >();
foreach (var point in series.Points)
{
graphPoints.Add(Vector <double> .Build.Dense(new double[] { point.Y }));
}
DelimitedWriter.Write(model.Path("graph"), Matrix <double> .Build.DenseOfRowVectors(graphPoints));
Console.WriteLine("Saved graph data");
}
catch
{
Console.WriteLine("Unable to save graph data");
}
}
model.Save();
Console.WriteLine("Model has been saved.");
}
public void GetItemSalesChartForSingleItem()
{
try
{
PlotModel = new PlotModel();
SetUpModelNew();
var dataPerDetector = OrderDetails.Where(a => a.BeverageId == SelectedBeverage.BeverageId).Take(10).OrderBy(a => a.SaleDate.Date)
.GroupBy(m => m.SaleDate.Date).Select(g => new { Total = g.Sum(p => p.Quantity), date = g.Key, Item = g.Select(a => a.Beverage.Name).FirstOrDefault() }).ToList();
//string bevname = GetBeverageName(data.Key);
var lineSerie = new OxyPlot.Series.LineSeries
{
ToolTip = string.Format(" {0} Sales", dataPerDetector.Select(a => a.Item).FirstOrDefault()),
// LabelFormatString = string.Format("{0} Sales", dataPerDetector.Select(a => a.Item).FirstOrDefault()),
StrokeThickness = 1,
MarkerSize = 3,
//MarkerStroke = OxyColor.FromUInt32((uint)data.Key),
MarkerType = MarkerType.Diamond,// markerTypes[data.Key],
CanTrackerInterpolatePoints = false,
Title = string.Format("{0} Sales", dataPerDetector.Select(a => a.Item).FirstOrDefault())
};
dataPerDetector.ForEach(d => lineSerie.Points.Add(new DataPoint(OxyPlot.Axes.DateTimeAxis.ToDouble(d.date), d.Total)));
PlotModel.Series.Add(lineSerie);
}
catch (Exception ex)
{
throw ex;
}
}
public void GetItemSalesChart()
{
try
{
foreach (var item in Beverages)
{
var dataPerDetector = OrderDetails.Where(a => a.BeverageId == item.BeverageId).OrderByDescending(m => m.SaleDate.Date).GroupBy(m => m.SaleDate.Date).
Select(g => new { Total = g.Sum(p => p.Quantity), date = g.Key }).Take(100).ToList();
var lineSerie = new OxyPlot.Series.LineSeries
{
// LabelFormatString = item.ItemName,
StrokeThickness = 1,
MarkerSize = 3,
MarkerStroke = OxyColor.FromUInt32((UInt32)item.BeverageId),
MarkerType = MarkerType.Diamond,
CanTrackerInterpolatePoints = false,
Title = item.Name,
ToolTip = item.Name
};
foreach (var item2 in dataPerDetector)
{
lineSerie.Points.Add(new DataPoint(OxyPlot.Axes.DateTimeAxis.ToDouble(item2.date), (double)item2.Total));
}
PlotModel.Series.Add(lineSerie);
}
}
catch (Exception ex)
{
throw ex;
}
}
private void PlotLinearRegression(List <GPoint> points)
{
var ls = new OxyPlot.Series.LineSeries()
{
MarkerType = ShowMarker ? MarkerType.None : MarkerType.Plus,
MarkerStroke = OxyPlot.OxyColors.Blue
};
LinearFunction func;
if (LinearRegression.Regression(points.ToArray(), out func))
{
int TOTAL = 10;
double x = points.First().X;
double stepX = (points.Last().X - x) / TOTAL;
for (int i = 0; i <= TOTAL; i++)
{
double y = func.Slope * x + func.Intercept;
ls.Points.Add(new OxyPlot.DataPoint(x, y));
x += stepX;
}
ls.Title = $"Linear Regression(R: {func.CorrelationCoeff:f5})";
}
else
{
ls.Title = "Linear Regression(Failed)";
}
base.Series.Add(ls);
}
private void PlotBezierTangentByDegree(List <GPoint> points)
{
base.Axes.Add(new OxyPlot.Axes.LinearAxis
{
Title = "Tangent of Bezier(Degree)",
Position = OxyPlot.Axes.AxisPosition.Left
});
AddZeroLineAnnotation();
OxyPlot.Series.LineSeries ls = new OxyPlot.Series.LineSeries()
{
Title = "Tangent of Bezier(Degree)",
MarkerType = ShowMarker ? MarkerType.None : MarkerType.Plus,
MarkerStroke = OxyPlot.OxyColors.Blue
};
int degree = points.Count - 1;
NURBSCurve bspline = new NURBSCurve(points, degree);
for (double u = 0; u <= 1.0; u += 0.01)
{
double tangent = bspline.TangentByDegree(u);
ls.Points.Add(new OxyPlot.DataPoint(u * 100.0, tangent));
}
base.Series.Add(ls);
}
private void PlotSimplifyCurvature(List <GPoint> curvatures)
{
OxyPlot.Series.LineSeries ls = new OxyPlot.Series.LineSeries()
{
Title = "Direct Simplication",
MarkerType = ShowMarker ? MarkerType.None : MarkerType.Diamond,
MarkerStroke = OxyPlot.OxyColors.Pink
};
List <GPoint> simplified1 = SimplifyPolyline(curvatures, 0);
foreach (var p in simplified1)
{
ls.Points.Add(new OxyPlot.DataPoint(p.X, p.Y));
}
base.Series.Add(ls);
// Plot maneuvers
curvatures.ForEach(x => x.W = x.X); // X is distance
List <GPoint> simplified2 = SimplifyPolyline(curvatures, CurveManeuverParameter.CurveMinDistance);
List <GPoint> maneuvers = PolylineSimplication.SimplifyHeadingChange(simplified2.ToArray(), CurveManeuverParameter.YTolerance);
AddScatterSeries(maneuvers, "Maneuvers");
PlotSameRanges(maneuvers);
}
private void UpdateHistogram()
{
HistogramProcessing histogramProcessing = new HistogramProcessing();
int[] histogram = histogramProcessing.GetHistogram(Image);
PlotModel histogramModel = new PlotModel();
OxyPlot.Series.LineSeries columnSeries = new OxyPlot.Series.LineSeries()
{
Color = OxyColor.FromRgb(0, 0, 0),
};
for (int i = 0; i < histogram.Length; i++)
{
columnSeries.Points.Add(new DataPoint(i, histogram[i]));
}
histogramModel.Series.Clear();
histogramModel.Series.Add(columnSeries);
histogramModel.Axes.Add(new LinearAxis
{
Position = AxisPosition.Bottom,
Minimum = -1,
Maximum = 257
});
histogramModel.Axes.Add(new LinearAxis
{
Position = AxisPosition.Left,
Minimum = -1
});
histogramView.Model = histogramModel;
}
protected override void RemoveSignal(OxyPlot.Series.Series series)
{
if (series == null)
{
return;
}
PlotSignalModel signal = (PlotSignalModel)series.Tag;
//this.paneModel.Signals.Remove(signal);
PlotModel.Series.Remove(series);
OxyPlot.Series.LineSeries lax = series as OxyPlot.Series.LineSeries;
if (lax != null)
{
PlotModel.Axes.Remove(lax.YAxis);
}
if (SelectedSeries == series)
{
SelectedSeries = null;
}
PlotModel.InvalidatePlot(false);
}
//public static Series<DateTime, double> GetData(string filePath, string column = "open")
//{
// var frame = Deedle.Frame.ReadCsv(filePath);
// string key = frame.ColumnKeys.SingleOrDefault(_ => String.Equals(_, "date", StringComparison.CurrentCultureIgnoreCase));
// if (key == null)
// throw new Exception("no date column in data");
// var frameDate = frame.IndexRows<DateTime>(key).SortRowsByKey();
// return frameDate.GetColumn<double>(column);
//}
public static PlotModel GetPlotModel(Series <DateTime, double> series)
{
var model = new PlotModel()
{
LegendSymbolLength = 24
};
var s1 = new OxyPlot.Series.LineSeries()
{
Color = OxyColors.SkyBlue,
MarkerType = MarkerType.Square,
MarkerSize = 2,
MarkerStroke = OxyColors.White,
MarkerFill = OxyColors.Blue,
MarkerStrokeThickness = 1.5
};
model.Series.Add(s1);
//
foreach (var s in series.Observations)
{
s1.Points.Add(new DataPoint((s.Key - default(DateTime)).TotalHours, s.Value));
}
return(model);
}
public MainViewModel()
{
TempDataPoints = new ObservableCollection <DataPoint>();
HumiDataPoints = new ObservableCollection <DataPoint>();
Model = new PlotModel()
{
Title = "Simple Example", Subtitle = "using OxyPlot"
};
var series1 = new LineSeries {
Title = "梁業", MarkerType = MarkerType.Circle, Smooth = true
};
var series2 = new LineSeries {
Title = "物業", MarkerType = MarkerType.Star, Smooth = true, MarkerStroke = OxyColors.Red
};
var dateTimeAxis1 = new DateTimeAxis();
dateTimeAxis1.Title = "Time";
Model.Axes.Add(dateTimeAxis1);
Model.Series.Add(series1);
Model.Series.Add(series2);
Random rd = new Random();
Task.Run(
() =>
{
while (true)
{
series1.Points.Add(DateTimeAxis.CreateDataPoint(DateTime.Now, rd.Next(10, 30)));
series2.Points.Add(DateTimeAxis.CreateDataPoint(DateTime.Now, rd.Next(10, 30)));
if (series1.Points.Count > 100)
{
series1.Points.RemoveAt(0);
series2.Points.RemoveAt(0);
}
Model.InvalidatePlot(true);
Thread.Sleep(1000);
}
});
Task.Run(
() =>
{
while (true)
{
var date = DateTime.Now;
App.Current.Dispatcher.BeginInvoke(new Action(() =>
{
TempDataPoints.Add(DateTimeAxis.CreateDataPoint(date, (double)(rd.Next(100, 500) / 10.0)));
HumiDataPoints.Add(DateTimeAxis.CreateDataPoint(date, (double)(rd.Next(500, 800) / 10.0)));
if (TempDataPoints.Count > 300)
{
TempDataPoints.RemoveAt(0);
HumiDataPoints.RemoveAt(0);
}
}));
Thread.Sleep(1000);
}
});
}
public int AddLineSeries(string title, string description = "", bool isVisible = true)
{
//TODO: improve how to limit the number of plots
//For now, we just ignore series after the max number has been reached
if (Plot.Series.Count < m_maxNumSeries)
{
if (m_lineSeriesLock == null) //might be null if loaded from file
{
m_lineSeriesLock = new object();
}
lock (m_lineSeriesLock)
{
OxyPlot.Series.LineSeries newSeries = new OxyPlot.Series.LineSeries {
Title = title, MarkerType = MarkerType.None
};
newSeries.IsVisible = isVisible;
Plot.Series.Add(newSeries);
PlotLineSeriesPropertiesViewModel lineProps = Properties.LineSeriesByName(title);
if (lineProps == null)
{
Properties.AddLineSeries(title, description, newSeries);
}
else
{
lineProps.LineSeries = newSeries;
}
return(Plot.Series.Count - 1);;
}
}
return(-1);
}
public MainWindow()
{
InitializeComponent();
DataContext = new ViewModel();
plotModel = new PlotModel {
Title = "OxyPlot"
};
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis {
Position = OxyPlot.Axes.AxisPosition.Bottom
});
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis {
Position = OxyPlot.Axes.AxisPosition.Left, Maximum = 10, Minimum = 0
});
var series1 = new OxyPlot.Series.LineSeries
{
MarkerType = MarkerType.Circle,
MarkerSize = 5,
MarkerStroke = OxyColors.White
};
series1.Points.Add(new DataPoint(0, 6));
series1.Points.Add(new DataPoint(1, 2));
series1.Points.Add(new DataPoint(2, 4));
series1.Points.Add(new DataPoint(3, 2));
series1.Points.Add(new DataPoint(4, 7));
series1.Points.Add(new DataPoint(6, 6));
series1.Points.Add(new DataPoint(8, 8));
series1.Smooth = true;
plotModel.Series.Add(series1);
this.Content = new OxyPlot.Wpf.PlotView()
{
Model = plotModel
};
plotModel.MouseDown += PlotModel_MouseDown;
}
private void FillSerie(object data)
{
Task.Factory.StartNew(() =>
{
PlotModel.Series.Clear();
OxyPlot.Series.LineSeries lineSerie = new OxyPlot.Series.LineSeries
{
StrokeThickness = 2,
CanTrackerInterpolatePoints = true,
Smooth = true,
};
PlotModel.Series.Add(lineSerie);
double[] samples = data as double[];
var points = new List <DataPoint>();
double xPos = 0;
double xStep = 1;
for (int i = 0; i < samples.Length; i++)
{
double y = samples[i];
points.Add(new DataPoint(xPos, y));
xPos += xStep;
}
lineSerie.ItemsSource = points;
PlotModel.InvalidatePlot(true);
});
}
public void GetTotalSalesChart()
{
try
{
ChartHeader = "Sales Chart";
PlotModel.Title = ChartHeader;
var dataPerDetector = Orders.OrderBy(m => m.SaleDate.Date).GroupBy(m => m.SaleDate.Date).
Select(g => new { Total = g.Sum(p => p.TotalAmount), date = g.Key }).ToList();
var lineSerie = new OxyPlot.Series.LineSeries
{
// LabelFormatString = dataPerDetector.Select(a=>a.Total).FirstOrDefault().ToString(),
StrokeThickness = 1,
MarkerSize = 3,
//MarkerStroke = OxyColors.Red,
MarkerType = MarkerType.Diamond,
CanTrackerInterpolatePoints = false,
Title = "Sales",
Smooth = false,
};
foreach (var item in dataPerDetector)
{
lineSerie.Points.Add(new DataPoint(OxyPlot.Axes.DateTimeAxis.ToDouble(item.date), (double)item.Total));
}
PlotModel.Series.Add(lineSerie);
}
catch (Exception ex)
{
throw ex;
}
}
public PlotWindow(List <List <double> > results)
{
var plotModel = new OxyPlot.PlotModel();
plotModel.Title = "Mean Absolute Validation Error Per Fold";
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Left, Title = "Error"
});
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Bottom, Title = "Epochs"
});
var colors = new OxyPlot.OxyColor[] { OxyPlot.OxyColors.Blue, OxyPlot.OxyColors.Green, OxyPlot.OxyColors.Red, OxyPlot.OxyColors.Black };
for (int row = 0; row < results.Count; row++)
{
var lineSeries = new OxyPlot.Series.LineSeries();
lineSeries.ItemsSource = results[row].Select((value, index) => new OxyPlot.DataPoint(index, value));
lineSeries.Title = string.Format("Fold {0}/{1}", row + 1, results.Count);
lineSeries.Color = colors[row];
plotModel.Series.Add(lineSeries);
}
var plotView = new OxyPlot.Wpf.PlotView();
plotView.Model = plotModel;
Title = "Chart";
Content = plotView;
}
public PlotLineSeriesPropertiesViewModel(string name, string description, OxyPlot.Series.LineSeries lineSeries)
{
LineSeries = lineSeries;
Visible = true;
Name = Herd.Utils.OxyPlotMathNotation(name);
Description = description;
}
public DataLoading()
{
TestCommand = new RelayCommand(() => ShowActualPoints());
PlotModel = new PlotModel();
X = new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Bottom,
Minimum = 1,
Maximum = 5
};
Y = new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Left,
IsPanEnabled = false
};
FirstSeries = new OxyPlot.Series.LineSeries();
SecondSeries = new OxyPlot.Series.LineSeries();
FirstLoad();
PlotModel.Axes.Add(X);
PlotModel.Axes.Add(Y);
OxyPlot.Wpf.PlotView PV = new OxyPlot.Wpf.PlotView();
PlotModel.Axes[0].AxisChanged += (o, e) =>
{
double LastPoint = (from y in FirstSeries.Points select y.X).Min();
ShowActuals(LastPoint);
};
}
public TemperaturePlotWindow(float[] temperature)
{
var plotModel = new OxyPlot.PlotModel();
plotModel.Title = "Temperature";
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Left, Title = "Celcius"
});
//plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Title = "Epochs" });
var labels = new string[] { "Temperature" };
var colors = new OxyPlot.OxyColor[] { OxyPlot.OxyColors.Blue };
var lineSeries = new OxyPlot.Series.LineSeries();
lineSeries.ItemsSource = temperature.Select((value, index) => new OxyPlot.DataPoint(index, value));
lineSeries.Title = labels[0];
lineSeries.Color = colors[0];
plotModel.Series.Add(lineSeries);
var plotView = new OxyPlot.Wpf.PlotView();
plotView.Model = plotModel;
Content = plotView;
}
public void DrawCurves()
{
if (Opt.Curves == null)
throw new NullReferenceException("No any curves!");
foreach (var func in Opt.Curves)
{
var line = new LineSeries
{
StrokeThickness = 2,
Smooth = true,
Color = OxyColor.FromRgb(0, 0, 0),
LineStyle = func.Style,
Points = new List<IDataPoint>(),
Title = func.Caption
};
var i = (double)Opt.Diapason.FromX;
if (!func.InvertFunc)
while (i <= Opt.Diapason.ToX)
{
line.Points.Add(new DataPoint(i, func.Function(i)));
i += Opt.Step;
}
else
while (i <= Opt.Diapason.ToY)
{
line.Points.Add(new DataPoint(func.Function(i), i));
i += Opt.Step;
}
_mainPlot.Series.Add(line);
}
}
private void CreateSamplePointsLineSeries()
{
var lineSerie = new LineSeries
{
LineStyle = LineStyle.Solid,
Color = OxyColor.FromRgb(255, 0, 0),
DataFieldX = "xData",
DataFieldY = "yData"
};
var testLineSerie = new LineSeries
{
LineStyle = LineStyle.Solid,
Color = OxyColor.FromRgb(0, 255, 0),
DataFieldX = "xData",
DataFieldY = "yData"
};
for (var i = 0; i < _totalTestErrors.Count; i++)
{
var error = _totalTestErrors[i];
testLineSerie.Points.Add(new DataPoint(i, error));
}
for (var i = 0; i < _totalErrors.Count; i++)
{
var error = _totalErrors[i];
lineSerie.Points.Add(new DataPoint(i, error));
}
PlotModel.Series.Add(lineSerie);
PlotModel.Series.Add(testLineSerie);
}
public void LineSeries()
{
var s1 = new OxyPlot.Series.LineSeries();
var s2 = new LineSeries();
OxyAssert.PropertiesAreEqual(s1, s2);
}
public void saveChart(List <Individual> individuals)
{
var line1 = new OxyPlot.Series.LineSeries
{
Title = $"Y",
Color = OxyColors.Blue,
StrokeThickness = 1,
MarkerSize = 2,
MarkerType = MarkerType.Circle
};
for (int i = 0; i < individuals.Count; i++)
{
line1.Points.Add(new DataPoint(i + 1, individuals[i].FunctionResult));
}
var model = new PlotModel
{
Title = $"wykres wartosci funkcji w zaleznosci od epok",
};
model.Series.Add(line1);
var chartName = Directory.GetCurrentDirectory() + "\\results\\chart" + DateTime.Now.ToString("yyyy-dd-M--HH-mm-ss") + ".pdf";
using (var stream = File.Create(chartName))
{
var pdfExporter = new PdfExporter {
Width = 600, Height = 400
};
pdfExporter.Export(model, stream);
};
}
private PlotModel _createChart(SlackChannel channel)
{
PlotModel chart = new PlotModel {
LegendPosition = LegendPosition.RightTop, LegendPlacement = LegendPlacement.Outside
};
chart.Axes.Add(new LinearAxis {
Position = AxisPosition.Left, Minimum = 40, Maximum = 110
});
foreach (KeyValuePair <SlackUser, List <bool> > pair in _data[channel])
{
LineSeries series = new LineSeries {
MarkerType = MarkerType.Circle
};
int numberOfTimesThere = 0;
for (int j = 0; j < pair.Value.Count; j++)
{
numberOfTimesThere += pair.Value[j] ? 1 : 0;
DataPoint nextPoint = new DataPoint(j + 1, (float)numberOfTimesThere * 100 / (j + 1));
series.Points.Add(nextPoint);
}
series.Title = pair.Key.Name + " (" + Math.Round(series.Points.Last().Y, 2) + "%)";
chart.Series.Add(series);
}
return(chart);
}
private void RefreshZGraph()
{
_plot.Series.Clear();
var lineSeries1 = new LineSeries
{
Title = string.Empty,
MarkerFill = OxyColor.FromRgb(255, 0, 0),
MarkerSize = 1,
MarkerStroke = OxyColor.FromRgb(255, 0, 0),
MarkerStrokeThickness = 1.5,
MarkerType = MarkerType.Circle
};
_plot.Series.Add(lineSeries1);
var prof = Presenter.ThisProfile.Datapoints;
foreach (var tp1 in prof)
{
var x = DateTimeAxis.ToDouble(tp1.DateAndTime);
var y = tp1.Value;
var bottom = new DataPoint(x, y);
lineSeries1.Points.Add(bottom);
}
foreach (var axis in _plot.Axes)
{
axis.Reset();
}
_plot.InvalidatePlot(true);
}
private LineSeries GenerateSerieForGray(Image <Gray, byte> grayImage, int chanel, String color)
{
var chanelValues = new List <int>();
for (int x = 0; x < grayImage.Width; x++)
{
chanelValues.Add(grayImage.Data[(int)DataProvider.MousePosition.Y, x, chanel]);
}
if (color.Equals("Gray"))
{
var series = new LineSeries
{
MarkerType = MarkerType.None,
MarkerSize = 1,
MarkerStroke = OxyColors.Red,
MarkerFill = OxyColors.Red,
Color = OxyColors.Red
};
for (int index = 0; index < chanelValues.Count; ++index)
{
series.Points.Add(new DataPoint(index, chanelValues[index]));
}
return(series);
}
return(null);
}
private void AddBezierByNURBS(List <GPoint> points)
{
if (points.Count() < 3)
{
return;
}
int degree = points.Count - 1;
var ls = new OxyPlot.Series.LineSeries()
{
MarkerType = ShowMarker ? MarkerType.None : MarkerType.Plus,
MarkerStroke = OxyPlot.OxyColors.Blue
};
double duration = Util.Util.MeasureExecTime(() =>
{
const int INTERVAL_NUM = 100;
double step = 1.0 / INTERVAL_NUM;
NURBSCurve bspline = new NURBSCurve(points, degree);
for (double t = 0; t < 1.0; t += step)
{
GPoint p = bspline.NonRationalBSpline(t);
ls.Points.Add(new OxyPlot.DataPoint(p.X, p.Y));
}
});
ls.Title = $"NURBS(Bezier-{degree})({duration:0.###}ms)";
base.Series.Add(ls);
}
private void FillSerie(object data)
{
Task.Factory.StartNew(() =>
{
PlotModel.Series.Clear();
OxyPlot.Series.LineSeries lineSerie = new OxyPlot.Series.LineSeries
{
StrokeThickness = 2,
CanTrackerInterpolatePoints = true,
Smooth = true,
};
PlotModel.Series.Add(lineSerie);
double[] samples = data as double[];
var points = new List<DataPoint>();
double xPos = 0;
double xStep = 1;
for(int i = 0; i < samples.Length; i++)
{
double y = samples[i];
points.Add(new DataPoint(xPos, y));
xPos += xStep;
}
lineSerie.ItemsSource = points;
PlotModel.InvalidatePlot(true);
});
}
public PlotWindow(List <List <double> > results)
{
var plotModel = new OxyPlot.PlotModel();
plotModel.Title = "Training and Validation Accuracy";
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Left, Title = "Accuracy", Minimum = 0, Maximum = 1
});
plotModel.Axes.Add(new OxyPlot.Axes.LinearAxis()
{
Position = OxyPlot.Axes.AxisPosition.Bottom, Title = "Epochs"
});
var labels = new string[] { "Training", "Validation" };
var colors = new OxyPlot.OxyColor[] { OxyPlot.OxyColors.Blue, OxyPlot.OxyColors.Green };
for (int row = 0; row < results.Count; row++)
{
var lineSeries = new OxyPlot.Series.LineSeries();
lineSeries.ItemsSource = results[row].Select((value, index) => new OxyPlot.DataPoint(index, value));
lineSeries.Title = labels[row];
lineSeries.Color = colors[row];
plotModel.Series.Add(lineSeries);
}
var plotView = new OxyPlot.Wpf.PlotView();
plotView.Model = plotModel;
Title = "Chart";
Content = plotView;
}
public void DrawCurve(List<double> x, List<double> y, string title = null)
{
if (x.Count != y.Count)
throw new ArgumentException("X and Y must have the same count of elemrnts!");
var curve = new LineSeries
{
StrokeThickness = 2,
Smooth = true,
Color = OxyColor.FromRgb(0, 0, 0),
LineStyle = LineStyle.Solid,
Points = new List<IDataPoint>(),
Title = title
};
for (var i = 0; i < x.Count; i++)
{
curve.Points.Add(new DataPoint(x[i], y[i]));
}
_mainPlot.Series.Add(curve);
}
public void DrawLine(DataPoint start, DataPoint end, LineStyle style = LineStyle.Solid)
{
var line = new LineSeries
{
StrokeThickness = 2,
Smooth = true,
Color = OxyColor.FromRgb(0, 0, 0),
LineStyle = style,
Points = new List<IDataPoint>()
};
var deltaX = Math.Abs(start.X - end.X);
var deltaY = Math.Abs(start.Y - end.Y);
var k = deltaY / deltaX;
if (start.Y > end.Y)
k = -k;
var i = 0.0;
while (i <= deltaX)
{
var x = i;
if (start.X > end.X)
x = -i;
line.Points.Add(new DataPoint(start.X + x, (start.Y + k*i)));
i += Opt.Step;
}
//Shit for vertical line
if ((int)start.X == (int)end.X)
{
var startY = start.Y < end.Y ? start : end;
for (var j = startY.Y; j < startY.Y + deltaY; j += Opt.Step)
line.Points.Add(new DataPoint(start.X, j));
}
_mainPlot.Series.Add(line);
}
// Charge les résultats dans le graphique
private void LoadData(Dictionary<DateTime,ResultValue> plotResults, double payOff)
{
var lineSerie1 = new OxyPlot.Series.LineSeries
{
Title = "Portfolio Value",
StrokeThickness = 2,
MarkerSize = 3,
CanTrackerInterpolatePoints = false,
Smooth = false,
};
var lineSerie2 = new OxyPlot.Series.LineSeries
{
Title = "Option Value",
StrokeThickness = 2,
MarkerSize = 3,
CanTrackerInterpolatePoints = false,
Smooth = false,
};
var lineSerie3 = new OxyPlot.Series.LineSeries
{
Title = "PayOff",
StrokeThickness = 2,
MarkerSize = 3,
CanTrackerInterpolatePoints = false,
Smooth = false,
};
foreach (var data in plotResults)
{
lineSerie1.Points.Add(new DataPoint(DateTimeAxis.ToDouble(data.Key), data.Value.PortfolioValue));
lineSerie2.Points.Add(new DataPoint(DateTimeAxis.ToDouble(data.Key), data.Value.OptionValue));
lineSerie3.Points.Add(new DataPoint(DateTimeAxis.ToDouble(data.Key), payOff));
}
PlotModel.Series.Add(lineSerie1);
PlotModel.Series.Add(lineSerie2);
PlotModel.Series.Add(lineSerie3);
}
private void btn_CreateResultTable_Click(object sender, EventArgs e)
{
OxyColor EEGColor = OxyColors.Cyan;
OxyColor EDAColor = OxyColors.LightGreen;
OxyColor HRColor = OxyColors.Salmon;
//var tester = new List<double>
//{
// 0.01
//};
//var tester2 = new List<double>
//{
// 0.01, 0.01
//};
//var tester3 = new List<double>
//{
// 0.01, 0.01, 0.01
//};
//MessageBox.Show(tester.FisherCombineP().ToString("0.00000000") + "\n" + tester2.FisherCombineP().ToString("0.00000000") + "\n" + tester3.FisherCombineP().ToString("0.00000000"));
//var res1 = FisherCompare1(0.4, 10, 0.3, 12);
//var res2 = FisherCompare2(0.4, 10, 0.3, 12);
//MessageBox.Show("1)\n" + res1.Item1 + "\n" + res1.Item2 + "\n" + res1.Item3 + "\n\n2)\n" + res2.Item1 + "\n" + res2.Item2 + "\n" + res2.Item3);
string corrType = "Pearson";
//string corrType = "Kendall";
//string corrType = "Spearman";
double minMilliseconds = 10000;
FolderBrowserDialog fbd = new FolderBrowserDialog();
if (fbd.ShowDialog() == DialogResult.OK)
{
//sensor is first string
var timeTable = new Dictionary<string, Dictionary<int, List<Tuple<double, double>>>>();
var stimuliTable = new Dictionary<string, Dictionary<string, List<Tuple<double, double>>>>();
var totalList = new Dictionary<string, List<Tuple<double, double>>>();
var big5List = new Dictionary<string, List<Dictionary<Big5, int>>>();
List<string> sensors = new List<string>();
List<int> times = new List<int>();
List<string> stimulis = new List<string>();
List<string> resultFiles = new List<string>();
foreach (var folder in Directory.GetDirectories(fbd.SelectedPath))
{
if (folder.Contains("Stimuli high") ||
folder.Contains("Stimuli low") ||
folder.Contains("Time 0") ||
folder.Contains("Time 1") ||
folder.Contains("Time 2") ||
folder.Contains(".git") ||
folder.Split('\\').Last() == "3" ||
folder.Split('\\').Last() == "6" ||
folder.Split('\\').Last() == "13")
{
continue;
}
string subject = folder.Split('\\').Last();
var metaLines = File.ReadAllLines($"{folder}/meta.txt");
var big5 = GetBig5(metaLines);
int time = int.Parse(metaLines[0].Split('=').Last());
string stimuli = metaLines[1].Split('=').Last();
stimuli = stimuli == "neu" ? "low" : "high";
if (!times.Contains(time)) times.Add(time);
if (!stimulis.Contains(stimuli)) stimulis.Add(stimuli);
List<string> foldersToExamine = new List<string>();
foldersToExamine.Add(fbd.SelectedPath + "\\Time " + time);
if (time > 0)
{
foldersToExamine.Add(fbd.SelectedPath + "\\Stimuli " + stimuli);
}
if (!big5List.ContainsKey("time" + time))
{
big5List.Add("time" + time, new List<Dictionary<Big5, int>>());
}
if (!big5List.ContainsKey("stim" + stimuli))
{
big5List.Add("stim" + stimuli, new List<Dictionary<Big5, int>>());
}
if (!big5List.ContainsKey("total"))
{
big5List.Add("total", new List<Dictionary<Big5, int>>());
}
if (!big5List.ContainsKey("corr"))
{
big5List.Add("corr", new List<Dictionary<Big5, int>>());
}
if (!big5List.ContainsKey("revCorr"))
{
big5List.Add("revCorr", new List<Dictionary<Big5, int>>());
}
big5List["time" + time].Add(big5);
if (time != 0)
{
big5List["stim" + stimuli].Add(big5);
}
big5List["total"].Add(big5);
foreach (var folderToExamine in foldersToExamine)
{
foreach (var resultFile in Directory.GetFiles(folderToExamine).Where(f => f.Split('\\').Last().StartsWith(subject) && f.Split('\\').Last().EndsWith(".txt")))
{
if (resultFiles.Contains(resultFile.Split('\\').Last()) || !folderToExamine.Contains("Time") && !foldersToExamine.Contains("Stimuli") || resultFile.Contains("dtw"))
{
continue;
}
resultFiles.Add(resultFile.Split('\\').Last());
string sensor = new String(resultFile.Split('.').First().SkipWhile(x => x != '_').Skip(1).SkipWhile(x => x != '_').Skip(1).ToArray());
if (!sensors.Contains(sensor)) sensors.Add(sensor);
var resultLines = File.ReadAllLines(resultFile);
string correlationLine = resultLines.First(x => x.Contains("|" + corrType));
int corrId = resultLines.ToList().IndexOf(correlationLine);
int sigId = corrId + 2;
string significanceLine = resultLines[sigId];
string N = resultLines[sigId + 2];
double highPassThreshold = minMilliseconds / 1000;
if (sensor.Contains("EEG"))
{
highPassThreshold *= 128;
}
else if (sensor.Contains("GSR"))
{
highPassThreshold *= 20;
}
else if (sensor.Contains("HR"))
{
highPassThreshold *= 1;
}
string[] Nsplit = N.Split(new char[] { '|', ' ' }, StringSplitOptions.RemoveEmptyEntries);
if (correlationLine.Contains(".a") || significanceLine.Contains(".a") || int.Parse(Nsplit[2]) < highPassThreshold)
{
if (int.Parse(Nsplit[2]) < highPassThreshold)
{
Log.LogMessage("Removing - " + Nsplit[2] + ": " + resultFile);
}
continue;
}
int splitIndex = (corrType == "Pearson") ? 3 : 4;
double pearsCorrelation = double.Parse(correlationLine.Split(new char[] { '|', '*' }, StringSplitOptions.RemoveEmptyEntries)[splitIndex].Replace(',', '.'), System.Globalization.CultureInfo.InvariantCulture);
double pearsSignificance = double.Parse(significanceLine.Split(new char[] { '|', '*' }, StringSplitOptions.RemoveEmptyEntries)[splitIndex].Replace(',', '.'), System.Globalization.CultureInfo.InvariantCulture);
var result = Tuple.Create(pearsCorrelation, pearsSignificance);
if (!timeTable.ContainsKey(sensor))
{
timeTable.Add(sensor, new Dictionary<int, List<Tuple<double, double>>>());
stimuliTable.Add(sensor, new Dictionary<string, List<Tuple<double, double>>>());
totalList.Add(sensor, new List<Tuple<double, double>>());
}
if (!timeTable[sensor].ContainsKey(time))
{
timeTable[sensor].Add(time, new List<Tuple<double, double>>());
}
if (!stimuliTable[sensor].ContainsKey(stimuli))
{
stimuliTable[sensor].Add(stimuli, new List<Tuple<double, double>>());
}
timeTable[sensor][time].Add(result);
totalList[sensor].Add(result);
if (time != 0)
{
stimuliTable[sensor][stimuli].Add(result);
}
if (pearsCorrelation > 0)
{
big5List["corr"].Add(big5);
}
else
{
big5List["revCorr"].Add(big5);
}
}
}
}
//done gathering results
List<string> totalToWrite = new List<string>();
totalToWrite.Add("Sensor&Avg Corr&Avg Sig. \\\\");
foreach (var sensor in sensors)
{
double avgCorrelation = totalList[sensor].Average(x => x.Item1);
double stdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(totalList[sensor].Select(x => x.Item1).ToArray());
double avgSignificance = totalList[sensor].Average(x => x.Item2);
double stdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(totalList[sensor].Select(x => x.Item2).ToArray());
totalToWrite.Add($"{sensor}&{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})&{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")}) \\\\");
}
Dictionary<Big5, List<string>> big5Anova = new Dictionary<Big5, List<string>>();
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
big5Anova.Add(item, new List<string>());
totalToWrite.Add(item + " Mean: " + big5List["total"].Average(x => x[item]).ToString("0.00") + ", SD: " + MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(big5List["total"].Select(x => x[item]).ToArray()).ToString("0.00") + ".");
big5List["time0"].ForEach(x => big5Anova[item].Add("0;" + x[item]));
big5List["time1"].ForEach(x => big5Anova[item].Add("1;" + x[item]));
big5List["time2"].ForEach(x => big5Anova[item].Add("2;" + x[item]));
big5List["stimlow"].ForEach(x => big5Anova[item].Add("3;" + x[item]));
big5List["stimhigh"].ForEach(x => big5Anova[item].Add("4;" + x[item]));
}
foreach (var big5group in big5Anova)
{
File.WriteAllLines(fbd.SelectedPath + "/" + big5group.Key + "_anova.csv", big5group.Value);
}
File.WriteAllLines(fbd.SelectedPath + "/" + corrType + "_totals.txt", totalToWrite);
double width = 1 / (sensors.Count * 1.4);
double widthTime = 0.3;
var timeModel = new PlotModel() { Title = $"Time Groups Box Plot" };
var avgLineSeries = new OxyPlot.Series.LineSeries() { };
List<OxyColor> colors = new List<OxyColor>()
{
};
int small = sensors.Count / 3;
int mid = small * 2;
int stepsize = 255 / small;
for (int i = 0; i < sensors.Count; i++)
{
byte increaser = (byte)((i % small) * stepsize);
byte decreaser = (byte)(255 - increaser);
if (i < small)
{
colors.Add(OxyColor.FromRgb(increaser, decreaser, decreaser));
}
else if (i < mid)
{
colors.Add(OxyColor.FromRgb(decreaser, increaser, decreaser));
}
else
{
colors.Add(OxyColor.FromRgb(decreaser, decreaser, increaser));
}
}
List<string> sensorsAdded = new List<string>();
foreach (var sensor in sensors)
{
List<string> timeAnova = new List<string>();
foreach (var time in times)
{
timeTable[sensor][time].ForEach(x => timeAnova.Add(time + ";" + x.Item1));
}
File.WriteAllLines(fbd.SelectedPath + "/" + sensor + ".csv", timeAnova);
}
Dictionary<string, int[]> significantAmount = new Dictionary<string, int[]>();
Dictionary<string, int[]> significantAmountMax = new Dictionary<string, int[]>();
var significantCorr = new Dictionary<string, Tuple<double, double, double, double>[]>();
foreach (var sensor in sensors)
{
significantAmount.Add(sensor, new int[5]);
significantAmountMax.Add(sensor, new int[5]);
//significantCorr.Add(sensor, new Tuple<double, double>[5]);
}
significantCorr.Add("EEG", new Tuple<double, double, double, double>[5]);
significantCorr.Add("EDA", new Tuple<double, double, double, double>[5]);
significantCorr.Add("HR", new Tuple<double, double, double, double>[5]);
//significantCorr.Add("AVG", new Tuple<double, double, double, double>[5]);
Action<string, int, List<Tuple<double, double>>> AddCorrelation = (sens, id, correl) =>
{
//old average + sd
//significantCorr[sens][id] = Tuple.Create(correl.Average(x => x.Item1), correl.Select(x => x.Item1).STDEV(), correl.Average(x => x.Item2), correl.Select(x => x.Item2).STDEV());
//new fisher algorithms
significantCorr[sens][id] = Tuple.Create(FisherInverse(correl.Average(x => Fisher(x.Item1))), Math.Round((double)correl.Count), correl.Select(x => x.Item2).FisherCombineP(), Math.Round((double)correl.Count));
};
List<string> amountTimeSignificant = new List<string>();
List<double> timeSignificantPoints = new List<double>();
var TimeErrorModel = new PlotModel() { Title = $"Time Error Model" };
var timeErrorSeries = new OxyPlot.Series.ErrorColumnSeries() { };
TimeErrorModel.Series.Add(timeErrorSeries);
TimeErrorModel.Axes.Add(new OxyPlot.Axes.LinearAxis { Position = OxyPlot.Axes.AxisPosition.Left });
var axis = new OxyPlot.Axes.CategoryAxis { Position = OxyPlot.Axes.AxisPosition.Bottom };
axis.Labels.Add("Time 0");
axis.Labels.Add("Time 1");
axis.Labels.Add("Time 2");
TimeErrorModel.Axes.Add(axis);
TimeErrorModel.Annotations.Add(new OxyPlot.Annotations.LineAnnotation() { Y = 0, Type = OxyPlot.Annotations.LineAnnotationType.Horizontal });
var TimeErrorModel2 = new PlotModel() { Title = $"Time Error Model" };
TimeErrorModel2.Axes.Add(new OxyPlot.Axes.LinearAxis { Position = OxyPlot.Axes.AxisPosition.Left });
var axis2 = new OxyPlot.Axes.CategoryAxis { Position = OxyPlot.Axes.AxisPosition.Bottom };
axis2.Labels.Add("Time 0");
axis2.Labels.Add("Time 1");
axis2.Labels.Add("Time 2");
TimeErrorModel2.Axes.Add(axis2);
List<string> AnovaIndividual = new List<string>();
List<string> AnovaAvg = new List<string>();
int anovaIndividualId = 0;
int anovaAvgId = 0;
List<string> AnovaIndividualLegend = new List<string>();
List<string> AnovaAvgLegend = new List<string>();
foreach (var time in times)
{
int sensorId = 0;
List<string> timeToWrite = new List<string>();
timeToWrite.Add("Sensor&Avg Corr&Avg Sig. \\\\");
List<double> avgs = new List<double>();
List<double> sigPoints = new List<double>();
var errorSeries = new OxyPlot.Series.ErrorColumnSeries();
TimeErrorModel2.Series.Add(errorSeries);
var EEGAllCorrelations = new List<Tuple<double, double>>();
var GSRAllCorrelations = timeTable["GSR"][time];
var HRAllCorrelations = timeTable["HR"][time];
foreach (var sensor in sensors)
{
if (sensor.Contains("EEG"))
{
EEGAllCorrelations.AddRange(timeTable[sensor][time]);
}
double avgCorrelation = timeTable[sensor][time].Average(x => x.Item1);
double stdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Select(x => x.Item1).ToArray());
double avgSignificance = timeTable[sensor][time].Average(x => x.Item2);
double stdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Select(x => x.Item2).ToArray());
var orderedAll = timeTable[sensor][time].OrderBy(x => x.Item1).ToList();//timeTable[sensor][time].Where(x => x.Item2 * 100 < (int)5).OrderBy(x => x.Item1).ToList();
amountTimeSignificant.Add(time + " & " + sensor + " & " + orderedAll.Count);
significantAmount[sensor][time] = orderedAll.Count;
significantAmountMax[sensor][time] = timeTable[sensor][time].Count;
//significantCorr[sensor][time] = Tuple.Create(orderedAll.Average(x => x.Item1), MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(orderedAll.Select(x => x.Item1).ToArray()));
//var boxItem = new OxyPlot.Series.BoxPlotItem(time + sensorId * widthTime - (0.5 * widthTime * sensors.Count), orderedAll[0].Item1, orderedAll[(int)(orderedAll.Count * 0.25)].Item1, orderedAll[orderedAll.Count / 2].Item1, orderedAll[(int)(orderedAll.Count * 0.75)].Item1, orderedAll.Last().Item1);
//var boxItem = new OxyPlot.Series.BoxPlotItem(sensorId + time * widthTime - (0.5 * widthTime * (times.Count - 1)), orderedAll[0].Item1, orderedAll[(int)(orderedAll.Count * 0.25)].Item1, orderedAll[orderedAll.Count / 2].Item1, orderedAll[(int)(orderedAll.Count * 0.75)].Item1, orderedAll.Last().Item1);
//var boxSeries = new OxyPlot.Series.BoxPlotSeries() { };
//boxSeries.BoxWidth = widthTime;
//boxSeries.WhiskerWidth = widthTime;
//boxSeries.Items.Add(boxItem);
//boxSeries.Fill = colors[sensorId];
//timeModel.Series.Add(boxSeries);
errorSeries.Items.Add(new OxyPlot.Series.ErrorColumnItem(orderedAll.Average(x => x.Item1), MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(orderedAll.Select(x => x.Item1).ToArray()), time) { Color = colors[sensorId] });
//if (!sensorsAdded.Contains(sensor))
//{
// sensorsAdded.Add(sensor);
// boxSeries.Title = sensor;
//}
avgs.Add(orderedAll.Average(x => x.Item1));
sigPoints.AddRange(orderedAll.Select(x => x.Item1));
if (avgSignificance * 100 < (int)5)
{
timeToWrite.Add($"\\textbf{{{sensor}}}&\\textbf{{{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})}}&\\textbf{{{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")})}} \\\\");
}
else
{
timeToWrite.Add($"{sensor}&{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})&{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")}) \\\\");
}
sensorId++;
}
double boxWidth = 0.3;
//eeg
EEGAllCorrelations = EEGAllCorrelations.OrderBy(x => x.Item1).ToList();
var EEGSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = EEGColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (time == 0) EEGSeries.Title = "EEG";
var EEGItem = CreateBoxItem(EEGAllCorrelations);
EEGItem.X = time - EEGSeries.BoxWidth * 1;
EEGSeries.Items.Add(EEGItem);
timeModel.Series.Add(EEGSeries);
AddCorrelation("EEG", time, EEGAllCorrelations);
foreach (var cor in EEGAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=time_" + time + "_EEG");
//gsr
GSRAllCorrelations = GSRAllCorrelations.OrderBy(x => x.Item1).ToList();
var GSRSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = EDAColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (time == 0) GSRSeries.Title = "EDA";
var GSRItem = CreateBoxItem(GSRAllCorrelations);
GSRItem.X = time;
GSRSeries.Items.Add(GSRItem);
timeModel.Series.Add(GSRSeries);
AddCorrelation("EDA", time, GSRAllCorrelations);
foreach (var cor in GSRAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=time_" + time + "_GSR");
//hr
HRAllCorrelations = HRAllCorrelations.OrderBy(x => x.Item1).ToList();
var HRSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = HRColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (time == 0) HRSeries.Title = "HR";
var HRItem = CreateBoxItem(HRAllCorrelations);
HRItem.X = time + HRSeries.BoxWidth * 1;
HRSeries.Items.Add(HRItem);
timeModel.Series.Add(HRSeries);
AddCorrelation("HR", time, HRAllCorrelations);
foreach (var cor in HRAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=time_" + time + "_HR");
//avg
var AVGAllCorrelations = EEGAllCorrelations.Concat(GSRAllCorrelations.Concat(HRAllCorrelations)).ToList();
//AddCorrelation("AVG", time, AVGAllCorrelations);
foreach (var cor in AVGAllCorrelations)
{
AnovaAvg.Add(anovaAvgId + ";" + cor.Item1);
}
AnovaAvgLegend.Add(anovaAvgId++ + "=time_" + time);
double totalAvg = AVGAllCorrelations.Average(x => x.Item1);
var txtAvg = new OxyPlot.Annotations.TextAnnotation() { TextPosition = new OxyPlot.DataPoint(time, -1), Text = "Avg " + totalAvg.ToString(".000").Replace(",", "."), Stroke = OxyColors.White };
timeModel.Annotations.Add(txtAvg);
timeErrorSeries.Items.Add(new OxyPlot.Series.ErrorColumnItem(sigPoints.Average(), MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(sigPoints.ToArray()), time));
avgLineSeries.Points.Add(new OxyPlot.DataPoint(time, avgs.Average()));
File.WriteAllLines(fbd.SelectedPath + "/" + corrType + "_time" + time + ".txt", timeToWrite);
}
File.WriteAllLines(fbd.SelectedPath + "/significantTime.tex", amountTimeSignificant);
timeModel.LegendPlacement = LegendPlacement.Outside;
timeModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Left, Maximum = 1, Minimum = -1, Title = "Pearson's r" });
timeModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = 2.5, Minimum = -0.5, MajorStep = 1, Title = "Time", MinorTickSize = 0 });
//timeModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = sensors.Count - 0.5, Minimum = -0.5, MajorStep = 1, Title = "Sensors", MinorTickSize = 0 });
//boxModel.Series.Add(avgLineSeries);
PngExporter pnger = new PngExporter();
pnger.ExportToFile(timeModel, fbd.SelectedPath + "/timeBox.png");
pnger.ExportToFile(TimeErrorModel, fbd.SelectedPath + "/errorPlotTest.png");
pnger.ExportToFile(TimeErrorModel2, fbd.SelectedPath + "/errorPlotTest2.png");
/*
//correlation and reverse correlation
foreach (var time in times)
{
//Correlation
List<string> correlationTimeToWrite = new List<string>();
correlationTimeToWrite.Add("Sensor&Avg Corr&Avg Sig. \\\\");
//Reverse correlation
List<string> reverseCorrelationTimeToWrite = new List<string>();
reverseCorrelationTimeToWrite.Add("Sensor & Avg Corr & Avg Sig. \\\\");
foreach (var sensor in sensors)
{
double correlationAvgCorrelation = timeTable[sensor][time].Where(x => x.Item1 >= 0).Average(x => x.Item1);
double correlationStdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Where(x => x.Item1 >= 0).Select(x => x.Item1).ToArray());
double correlationAvgSignificance = timeTable[sensor][time].Where(x => x.Item1 >= 0).Average(x => x.Item2);
double correlationStdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Where(x => x.Item1 >= 0).Select(x => x.Item2).ToArray());
double reverseCorrelationAvgCorrelation = timeTable[sensor][time].Where(x => x.Item1 < 0).Average(x => x.Item1);
double reverseCorrelationStdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Where(x => x.Item1 < 0).Select(x => x.Item1).ToArray());
double reverseCorrelationAvgSignificance = timeTable[sensor][time].Where(x => x.Item1 < 0).Average(x => x.Item2);
double reverseCorrelationStdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Where(x => x.Item1 < 0).Select(x => x.Item2).ToArray());
correlationTimeToWrite.Add($"{sensor}&{correlationAvgCorrelation.ToString("0.000")}({correlationStdevCorrelation.ToString("0.000")})&{correlationAvgSignificance.ToString("0.000")}({correlationStdevSignificance.ToString("0.000")}) \\\\");
reverseCorrelationTimeToWrite.Add($"{sensor}&{reverseCorrelationAvgCorrelation.ToString("0.000")}({reverseCorrelationStdevCorrelation.ToString("0.000")})&{reverseCorrelationAvgSignificance.ToString("0.000")}({reverseCorrelationStdevSignificance.ToString("0.000")}) \\\\");
}
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
correlationTimeToWrite.Add(item + " Mean: " + big5List["corr"].Average(x => x[item]).ToString("0.00") + ", SD: " + MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(big5List["corr"].Select(x => x[item]).ToArray()).ToString("0.00") + ".");
reverseCorrelationTimeToWrite.Add(item + " Mean: " + big5List["revCorr"].Average(x => x[item]).ToString("0.00") + ", SD: " + MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(big5List["revCorr"].Select(x => x[item]).ToArray()).ToString("0.00") + ".");
}
File.WriteAllLines(fbd.SelectedPath + "/correlationTime" + time + ".txt", correlationTimeToWrite);
File.WriteAllLines(fbd.SelectedPath + "/reverseCorrelationTime" + time + ".txt", reverseCorrelationTimeToWrite);
}
*/
var Big5timeBox = new PlotModel() { Title = "Big5 Time Box Plots", LegendPlacement = LegendPlacement.Outside };
Dictionary<Big5, OxyPlot.Series.BoxPlotSeries> big5timeSeries = new Dictionary<Big5, OxyPlot.Series.BoxPlotSeries>();
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
big5timeSeries.Add(item, new OxyPlot.Series.BoxPlotSeries() { Fill = colors[(int)item * 2], Title = item.ToString(), BoxWidth = 0.1, WhiskerWidth = 0.1 });
Big5timeBox.Series.Add(big5timeSeries[item]);
}
Big5timeBox.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Left, Maximum = 50, Minimum = 10, Title = "Score" });
Big5timeBox.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = 2.5, Minimum = -0.5, MajorStep = 1, Title = "Time", MinorTickSize = 0 });
foreach (var time in times)
{
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
var orderino = big5List["time" + time].Select(x => x[item]).OrderBy(x => x).ToList();
big5timeSeries[item].Items.Add(new OxyPlot.Series.BoxPlotItem(time - 0.25 + (int)item * 0.1, orderino[0], orderino[(int)(orderino.Count * 0.25)], orderino[orderino.Count / 2], orderino[(int)(orderino.Count * 0.75)], orderino.Last()));
}
}
pnger.ExportToFile(Big5timeBox, fbd.SelectedPath + "/timeBoxBig5.png");
foreach (var time in times)
{
List<string> timeToWrite = new List<string>();
timeToWrite.Add("\\begin{table}");
timeToWrite.Add("\\centering");
timeToWrite.Add("{\\large \\textbf{Time " + time + "}}\\vspace{1pt}");
timeToWrite.Add("\\begin{tabular}{ccc}");
timeToWrite.Add("\\toprule");
timeToWrite.Add("Sensor&Avg Corr&Avg Sig. \\\\");
timeToWrite.Add("\\midrule");
foreach (var sensor in sensors)
{
double avgCorrelation = timeTable[sensor][time].Average(x => x.Item1);
double stdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Select(x => x.Item1).ToArray());
double avgSignificance = timeTable[sensor][time].Average(x => x.Item2);
double stdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(timeTable[sensor][time].Select(x => x.Item2).ToArray());
if (avgSignificance < 0.05)
{
timeToWrite.Add($"\\textbf{{{sensor}}}&\\textbf{{{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})}}&\\textbf{{{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")})}} \\\\");
}
else
{
timeToWrite.Add($"{sensor}&{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})&{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")}) \\\\");
}
}
timeToWrite.Add("\\bottomrule");
timeToWrite.Add("\\end{tabular}");
timeToWrite.Add("\\caption{Results from time " + time + ".");
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
timeToWrite.Add(item + " Mean: " + big5List["time" + time].Average(x => x[item]).ToString("0.00") + ", SD: " + MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(big5List["time" + time].Select(x => x[item]).ToArray()).ToString("0.00") + ".");
}
timeToWrite.Add("}");
timeToWrite.Add("\\label{[TABLE] res time" + time + "}");
timeToWrite.Add("\\end{table}");
File.WriteAllLines(fbd.SelectedPath + "/" + corrType + "_time" + time + ".txt", timeToWrite);
}
var stimModel = new PlotModel() { Title = "Stimuli Groups Box Plot" };
int stimId = 0;
sensorsAdded.Clear();
avgLineSeries.Points.Clear();
var Big5StimBox = new PlotModel() { Title = "Big5 Stimuli Box Plots", LegendPlacement = LegendPlacement.Outside };
Dictionary<Big5, OxyPlot.Series.BoxPlotSeries> big5Series = new Dictionary<Big5, OxyPlot.Series.BoxPlotSeries>();
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
big5Series.Add(item, new OxyPlot.Series.BoxPlotSeries() { Fill = colors[(int)item * 2], Title = item.ToString(), BoxWidth = 0.1, WhiskerWidth = 0.1 });
Big5StimBox.Series.Add(big5Series[item]);
}
Big5StimBox.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Left, Maximum = 50, Minimum = 10, Title = "Score" });
Big5StimBox.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = 1.5, Minimum = -0.5, MajorStep = 1, Title = "Category", MinorTickSize = 0 });
List<string> amountStimSignificant = new List<string>();
foreach (var stimuli in stimulis)
{
List<string> stimuliToWrite = new List<string>();
stimuliToWrite.Add("\\begin{table}");
stimuliToWrite.Add("\\centering");
stimuliToWrite.Add("{\\large \\textbf{Stimuli " + stimuli + "}}\\vspace{1pt}");
stimuliToWrite.Add("\\begin{tabular}{ccc}");
stimuliToWrite.Add("\\toprule");
stimuliToWrite.Add("Sensor&Avg Corr&Avg Sig. \\\\");
stimuliToWrite.Add("\\midrule");
List<double> avgs = new List<double>();
int sensorId = 0;
var EEGAllCorrelations = new List<Tuple<double, double>>();
var GSRAllCorrelations = stimuliTable["GSR"][stimuli];
var HRAllCorrelations = stimuliTable["HR"][stimuli];
foreach (var sensor in sensors)
{
if (sensor.Contains("EEG"))
{
EEGAllCorrelations.AddRange(stimuliTable[sensor][stimuli]);
}
double avgCorrelation = stimuliTable[sensor][stimuli].Average(x => x.Item1);
double stdevCorrelation = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(stimuliTable[sensor][stimuli].Select(x => x.Item1).ToArray());
double avgSignificance = stimuliTable[sensor][stimuli].Average(x => x.Item2);
double stdevSignificance = MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(stimuliTable[sensor][stimuli].Select(x => x.Item2).ToArray());
var orderedAll = stimuliTable[sensor][stimuli].Where(x => x.Item2 * 100 < (int)5).OrderBy(x => x.Item1).ToList();
amountStimSignificant.Add(stimuli + " & " + sensor + " & " + orderedAll.Count);
significantAmount[sensor][stimuli == "low" ? 3 : 4] = orderedAll.Count;
significantAmountMax[sensor][stimuli == "low" ? 3 : 4] = stimuliTable[sensor][stimuli].Count;
//significantCorr[sensor][stimuli == "low" ? 3 : 4] = Tuple.Create(orderedAll.Average(x => x.Item1), MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(orderedAll.Select(x => x.Item1).ToArray()));
var boxItem = new OxyPlot.Series.BoxPlotItem(((1 + stimId) % 2) + sensorId * width - (0.5 * width * sensors.Count), orderedAll[0].Item1, orderedAll[(int)(orderedAll.Count * 0.25)].Item1, orderedAll[orderedAll.Count / 2].Item1, orderedAll[(int)(orderedAll.Count * 0.75)].Item1, orderedAll.Last().Item1);
//var boxItem = new OxyPlot.Series.BoxPlotItem(sensorId + ((1 + stimId) % 2) * widthTime - (0.5 * widthTime), orderedAll[0].Item1, orderedAll[(int)(orderedAll.Count * 0.25)].Item1, orderedAll[orderedAll.Count / 2].Item1, orderedAll[(int)(orderedAll.Count * 0.75)].Item1, orderedAll.Last().Item1);
var boxSeries = new OxyPlot.Series.BoxPlotSeries() { };
boxSeries.BoxWidth = width;
boxSeries.WhiskerWidth = width;
//boxSeries.BoxWidth = widthTime;
//boxSeries.WhiskerWidth = widthTime;
boxSeries.Items.Add(boxItem);
boxSeries.Fill = colors[sensorId];
//stimModel.Series.Add(boxSeries);
avgs.Add(orderedAll.Average(x => x.Item1));
if (!sensorsAdded.Contains(sensor))
{
sensorsAdded.Add(sensor);
boxSeries.Title = sensor;
}
if (avgSignificance < 0.05)
{
stimuliToWrite.Add($"\\textbf{{{sensor}}}&\\textbf{{{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})}}&\\textbf{{{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")})}} \\\\");
}
else
{
stimuliToWrite.Add($"{sensor}&{avgCorrelation.ToString("0.000")}({stdevCorrelation.ToString("0.000")})&{avgSignificance.ToString("0.000")}({stdevSignificance.ToString("0.000")}) \\\\");
}
sensorId++;
}
double boxWidth = 0.3;
//eeg
EEGAllCorrelations = EEGAllCorrelations.OrderBy(x => x.Item1).ToList();
var EEGSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = EEGColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (stimuli == "low") EEGSeries.Title = "EEG";
var EEGItem = CreateBoxItem(EEGAllCorrelations);
EEGItem.X = (stimuli == "low" ? 0 : 1) - EEGSeries.BoxWidth * 1;
EEGSeries.Items.Add(EEGItem);
stimModel.Series.Add(EEGSeries);
AddCorrelation("EEG", stimuli == "low" ? 3 : 4, EEGAllCorrelations);
foreach (var cor in EEGAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=stimuli_" + stimuli + "_EEG");
//gsr
GSRAllCorrelations = GSRAllCorrelations.OrderBy(x => x.Item1).ToList();
var GSRSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = EDAColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (stimuli == "low") GSRSeries.Title = "EDA";
var GSRItem = CreateBoxItem(GSRAllCorrelations);
GSRItem.X = (stimuli == "low" ? 0 : 1);
GSRSeries.Items.Add(GSRItem);
stimModel.Series.Add(GSRSeries);
AddCorrelation("EDA", stimuli == "low" ? 3 : 4, GSRAllCorrelations);
foreach (var cor in GSRAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=stimuli_" + stimuli + "_GSR");
//hr
HRAllCorrelations = HRAllCorrelations.OrderBy(x => x.Item1).ToList();
var HRSeries = new OxyPlot.Series.BoxPlotSeries() { Fill = HRColor, BoxWidth = boxWidth, WhiskerWidth = boxWidth };
if (stimuli == "low") HRSeries.Title = "HR";
var HRItem = CreateBoxItem(HRAllCorrelations);
HRItem.X = (stimuli == "low" ? 0 : 1) + HRSeries.BoxWidth * 1;
HRSeries.Items.Add(HRItem);
stimModel.Series.Add(HRSeries);
AddCorrelation("HR", stimuli == "low" ? 3 : 4, HRAllCorrelations);
foreach (var cor in HRAllCorrelations)
{
AnovaIndividual.Add(anovaIndividualId + ";" + cor.Item1);
}
AnovaIndividualLegend.Add(anovaIndividualId++ + "=stimuli_" + stimuli + "_HR");
//avg
var AVGAllCorrelations = EEGAllCorrelations.Concat(GSRAllCorrelations.Concat(HRAllCorrelations)).ToList();
//AddCorrelation("AVG", stimuli == "low" ? 3 : 4, AVGAllCorrelations);
foreach (var cor in AVGAllCorrelations)
{
AnovaAvg.Add(anovaAvgId + ";" + cor.Item1);
}
AnovaAvgLegend.Add(anovaAvgId++ + "=stimuli_" + stimuli);
avgLineSeries.Points.Add(new OxyPlot.DataPoint(0, avgs.Average()));
stimuliToWrite.Add("\\bottomrule");
stimuliToWrite.Add("\\end{tabular}");
stimuliToWrite.Add("\\caption{Results from stimuli " + stimuli + ".");
foreach (Big5 item in Enum.GetValues(typeof(Big5)))
{
stimuliToWrite.Add(item + " Mean: " + big5List["stim" + stimuli].Average(x => x[item]).ToString("0.00") + ", SD: " + MathNet.Numerics.Statistics.ArrayStatistics.PopulationStandardDeviation(big5List["stim" + stimuli].Select(x => x[item]).ToArray()).ToString("0.00") + ".");
var orderino = big5List["stim" + stimuli].Select(x => x[item]).OrderBy(x => x).ToList();
big5Series[item].Items.Add(new OxyPlot.Series.BoxPlotItem(((1 + stimId) % 2) - 0.25 + (int)item * 0.1, orderino[0], orderino[(int)(orderino.Count * 0.25)], orderino[orderino.Count / 2], orderino[(int)(orderino.Count * 0.75)], orderino.Last()));
}
stimuliToWrite.Add("}");
stimuliToWrite.Add("\\label{[TABLE] res stimuli" + stimuli + "}");
stimuliToWrite.Add("\\end{table}");
File.WriteAllLines(fbd.SelectedPath + "/" + corrType + "_stimuli_" + stimuli + ".txt", stimuliToWrite);
stimId++;
}
File.WriteAllLines(fbd.SelectedPath + "/significantStim.tex", amountStimSignificant);
List<string> sigAmountLines = new List<string>();
foreach (var sensor in sensors)
{
string linerino = sensor;
for (int i = 0; i < 5; i++)
{
linerino += $" & {significantAmount[sensor][i]}/{significantAmountMax[sensor][i]}";
}
sigAmountLines.Add(linerino + "\\\\");
}
File.WriteAllLines(fbd.SelectedPath + "/significantTable.tex", sigAmountLines);
//File.WriteAllLines(fbd.SelectedPath + "/significantTable.tex", significantAmount.Select(x => $"{x.Key} & {x.Value[0]} & {x.Value[1]} & {x.Value[2]} & {x.Value[3]} & {x.Value[4]}").ToList());
File.WriteAllLines(fbd.SelectedPath + "/significantCorrTable.tex", significantCorr.Select(x => $"{x.Key} & {x.Value[0].Item1.ToString(".000")}({x.Value[0].Item2.ToString(".000")}) & {x.Value[1].Item1.ToString(".000")}({x.Value[1].Item2.ToString(".000")}) & {x.Value[2].Item1.ToString(".000")}({x.Value[2].Item2.ToString(".000")}) & {x.Value[3].Item1.ToString(".000")}({x.Value[3].Item2.ToString(".000")}) & {x.Value[4].Item1.ToString(".000")}({x.Value[4].Item2.ToString(".000")}) \\\\"));
File.WriteAllLines(fbd.SelectedPath + "/significantCorrTableTime.tex", significantCorr.Select(x => $"{x.Key} & {x.Value[0].Item1.ToString(".000")} (SD={x.Value[0].Item2.ToString(".000")}, p={x.Value[0].Item3.ToString(".000000")}) & {x.Value[1].Item1.ToString(".000")} (SD={x.Value[1].Item2.ToString(".000")}, p={x.Value[1].Item3.ToString(".000000")}) & {x.Value[2].Item1.ToString(".000")} (SD={x.Value[2].Item2.ToString(".000")}, p={x.Value[2].Item3.ToString(".000000")}) \\\\"));
File.WriteAllLines(fbd.SelectedPath + "/significantCorrTableStimuli.tex", significantCorr.Select(x => $"{x.Key} & {x.Value[3].Item1.ToString(".000")} (SD={x.Value[3].Item2.ToString(".000")}, p={x.Value[3].Item3.ToString(".000")}) & {x.Value[4].Item1.ToString(".000")} (SD={x.Value[4].Item2.ToString(".000")}, p={x.Value[4].Item3.ToString(".000")}) \\\\"));
List<string> timeLines = new List<string>() { "sensor & 0 vs 1 & 1 vs 2 & 0 vs 2" };
List<string> stimLines = new List<string>() { "sensor & 0 vs Low & Low vs High & 0 vs High" };
foreach (var item in significantCorr)
{
var z01 = ZCalc(item.Value[0].Item1, Convert.ToInt32(item.Value[0].Item2), item.Value[1].Item1, Convert.ToInt32(item.Value[1].Item2));
var z12 = ZCalc(item.Value[1].Item1, Convert.ToInt32(item.Value[1].Item2), item.Value[2].Item1, Convert.ToInt32(item.Value[2].Item2));
var z02 = ZCalc(item.Value[0].Item1, Convert.ToInt32(item.Value[0].Item2), item.Value[2].Item1, Convert.ToInt32(item.Value[2].Item2));
var p01 = ZtoP(z01);
var p12 = ZtoP(z12);
var p02 = ZtoP(z02);
timeLines.Add($"{item.Key} & z: {z01} | p: {p01} & z: {z12} | p: {p12} & z: {z02} | p: {p02}");
var z0Low = ZCalc(item.Value[0].Item1, Convert.ToInt32(item.Value[0].Item2), item.Value[3].Item1, Convert.ToInt32(item.Value[3].Item2));
var zLowHigh = ZCalc(item.Value[3].Item1, Convert.ToInt32(item.Value[3].Item2), item.Value[4].Item1, Convert.ToInt32(item.Value[4].Item2));
var z0High = ZCalc(item.Value[0].Item1, Convert.ToInt32(item.Value[0].Item2), item.Value[4].Item1, Convert.ToInt32(item.Value[4].Item2));
var p0Low = ZtoP(z0Low);
var pLowHigh = ZtoP(zLowHigh);
var p0High = ZtoP(z0High);
stimLines.Add($"{item.Key} & z: {z0Low} | p: {p0Low} & z: {zLowHigh} | p: {pLowHigh} & z: {z0High} | p: {p0High}");
}
File.WriteAllLines(fbd.SelectedPath + "/significantCorrCompareTime.tex", timeLines);
File.WriteAllLines(fbd.SelectedPath + "/significantCorrCompareStimuli.tex", stimLines);
pnger.ExportToFile(Big5StimBox, fbd.SelectedPath + "/stimBoxBig5.png");
stimModel.LegendPlacement = LegendPlacement.Outside;
//index 1 = low
var stimTxt0 = new OxyPlot.Annotations.TextAnnotation() { TextPosition = new OxyPlot.DataPoint(0, -1), Text = "Avg " + avgLineSeries.Points[1].Y.ToString(".000").Replace(",", "."), Stroke = OxyColors.White };
//index 0 = high
var stimTxt1 = new OxyPlot.Annotations.TextAnnotation() { TextPosition = new OxyPlot.DataPoint(1, -1), Text = "Avg " + avgLineSeries.Points[0].Y.ToString(".000").Replace(",", "."), Stroke = OxyColors.White };
stimModel.Annotations.Add(stimTxt0);
stimModel.Annotations.Add(stimTxt1);
stimModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Left, Maximum = 1, Minimum = -1, Title = "Pearson's r" });
stimModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = 1.5, Minimum = -0.5, MajorStep = 1, Title = "Stimuli", MinorTickSize = 0 });
//stimModel.Axes.Add(new OxyPlot.Axes.LinearAxis() { Position = OxyPlot.Axes.AxisPosition.Bottom, Maximum = sensors.Count - 0.5, Minimum = -0.5, MajorStep = 1, Title = "Sensors", MinorTickSize = 0 });
pnger.ExportToFile(stimModel, fbd.SelectedPath + "/stimBox.png");
File.WriteAllLines(fbd.SelectedPath + "/anovaIndividual.csv", AnovaIndividual);
File.WriteAllLines(fbd.SelectedPath + "/anovaIndividualLegend.csv", AnovaIndividualLegend);
File.WriteAllLines(fbd.SelectedPath + "/anovaAvg.csv", AnovaAvg);
File.WriteAllLines(fbd.SelectedPath + "/anovaAvgLegend.csv", AnovaAvgLegend);
Log.LogMessage("DonnoDK");
}
}
public int addLineSeries(string title)
{
var newSeries = new OxyPlot.Series.LineSeries { Title = title, MarkerType = MarkerType.None };
m_plot.Series.Add(newSeries);
int newSeriesId = m_numSeries;
m_numSeries++;
return newSeriesId;
}
public void CreateRocCurve()
{
RocCurve = _filterOptimizer.GetRocCurve(AllParameterResults);
string graphTitle = "ROC curve";
PlotModel plotModel = new PlotModel(graphTitle);
plotModel.TitleFontSize = 11;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < RocCurve.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(RocCurve.Xvalues[i], RocCurve.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "unlabeled count");
xAxis.Minimum = 0;
var yAxis = new LinearAxis(AxisPosition.Left, "labeled count");
yAxis.Minimum = 0;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
RocPlot = plotModel;
}
private void test_Load(object sender, EventArgs e)
{
testvar.Add(new RelationalDouble(7.9));
Plot plot = new Plot();
plot.Model = new OxyPlot.PlotModel();
plot.Dock = DockStyle.Fill;
Controls.Add(plot);
plot.Model.PlotType = OxyPlot.PlotType.XY;
var DS = new OxyPlot.Series.LineSeries();
/*Plot plot = new Plot();
plot.Model = new OxyPlot.PlotModel();
plot.Dock = DockStyle.Fill;
this.Controls.Add(plot);
plot.Model.PlotType = OxyPlot.PlotType.XY;
var DS = new OxyPlot.Series.LineSeries();
var US = new OxyPlot.Series.LineSeries();
var piolt = new OxyPlot.Series.StemSeries();
US.Color = OxyPlot.OxyColors.Green;
DS.Color = OxyPlot.OxyColors.Blue;
piolt.Color = OxyPlot.OxyColors.OrangeRed;
string[] tmp = "0,0,0,0,5,9,10,10,10,10,11,10,10,10,10,9,9,9,9,9,8,8,8,9,9,8,9,9,8,8,8,8,8,8,8,8,8,9,9,9,8,9,8,8,8,9,8,9,9,9,8,9,9,8,9,8,8,8,8,8,8,8,8,8,13,14,14,14,14,14,14,14,15,13,14,14,14,14,14,14,14,14,14,14,13,11,0,2,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,7,6,6,6,6,6,6,6,6,5,4,6,6,2,6,6,4,4,6,5,5,5,5,5,5,5,5,5,5,5,4,5,5,5,4,4,5,5,4,1,7,12,12,13,12,13,13,12,13,12,12,13,12,12,13,12,12,12,12,12,10,12,12,12,12,12,12,12,12,12,12,12,10,12,12,12,12,12,12,12,12,12,12,10,12,12,12,12,12,12,12,12,12,12,11,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0".Split(',');
int i = 0;
int c = 0;
string profile = "8b";
foreach (var item in tmp)
{
if (profile == "8b" && i < 2048)
{
if (c < 87 || c > 147)
{
DS.Points.Add(new OxyPlot.DataPoint((double)i, Convert.ToDouble(item)));
US.Points.Add(new OxyPlot.DataPoint((double)i, 0));
}
else
{
DS.Points.Add(new OxyPlot.DataPoint((double)i, 0));
US.Points.Add(new OxyPlot.DataPoint((double)i, Convert.ToDouble(item)));
}
if (c == 74)
{
piolt.Points.Add(new OxyPlot.DataPoint((double)i, 16));
}
i += 8;
c++;
}
}
plot.Model.Series.Add(DS);
plot.Model.Series.Add(US);
plot.Model.Series.Add(piolt);
*/
}
public MainViewModel()
{
var powerDistribution = ((App)App.Current).PowerDistribution;
var powerDistributionLogger = ((App) Application.Current).PowerDistributionLogger;
var viewSettings = ((App) Application.Current).ViewSettings;
// View Settings
this.PlotForeground = viewSettings
.ObserveProperty(self => self.PlotStyle).Select(style => style.ObserveProperty(self => self.PlotForeground))
.Switch()
.Select(color => new SolidColorBrush(color))
.ToReadOnlyReactiveProperty()
.AddTo(this.disposables);
this.PlotBackground = viewSettings
.ObserveProperty(self => self.PlotStyle).Select(style => style.ObserveProperty(self => self.PlotBackground))
.Switch()
.Select(color => new SolidColorBrush(color))
.ToReadOnlyReactiveProperty()
.AddTo(this.disposables);
this.CurrentSensors = powerDistribution.Sensors.ToReadOnlyReactiveCollection(sensor => new CurrentSensorViewModel(sensor)).AddTo(this.disposables);
this.TotalCurrent = powerDistribution.ObserveProperty(self => self.TotalCurrent).ToReadOnlyReactiveProperty(mode:ReactivePropertyMode.RaiseLatestValueOnSubscribe)
.AddTo(this.disposables);
this.Capacity = powerDistribution.ObserveProperty(self => self.Capacity).ToReadOnlyReactiveProperty().AddTo(this.disposables);
this.Usage = Observable.CombineLatest(
this.TotalCurrent,
this.Capacity,
(totalCurrent, capacity) => capacity > 0 ? totalCurrent / capacity : 0)
.ToReadOnlyReactiveProperty()
.AddTo(this.disposables);
this.AlertState = Observable.CombineLatest(
powerDistribution.ObserveProperty(self => self.IsWarningCondition),
powerDistribution.ObserveProperty(self => self.IsCriticalCondition),
(isWarning, isCritical) => isCritical ? ErrorAlertState : (isWarning ? WarningAlertState : NormalAlertState))
.ToReadOnlyReactiveProperty()
.AddTo(this.disposables);
this.CurrentPlotType = new ReactiveProperty<PlotType>().AddTo(this.disposables);
this.IsLive = this.CurrentPlotType.Select(type => type == PlotType.Live).ToReadOnlyReactiveProperty().AddTo(this.disposables);
this.IsCustom = this.CurrentPlotType.Select(type => type == PlotType.Custom).ToReadOnlyReactiveProperty().AddTo(this.disposables);
this.IsHistroy = this.IsLive.Select(value => !value).ToReadOnlyReactiveProperty().AddTo(this.disposables);
this.CurrentPlotModel = new OxyPlot.PlotModel()
{
Axes =
{
new OxyPlot.Axes.LinearAxis() { Unit = "A", Position = OxyPlot.Axes.AxisPosition.Left, Minimum = 0 },
new OxyPlot.Axes.DateTimeAxis() { Unit = "Time", Position = OxyPlot.Axes.AxisPosition.Bottom },
},
};
// Change plot model colors.
viewSettings
.ObserveProperty(self => self.PlotStyle).Select(style => style.ObserveProperty(self => self.PlotForeground))
.Switch()
.Subscribe(color_ =>
{
var color = color_.ToOxyColor();
this.CurrentPlotModel.TextColor = color;
this.CurrentPlotModel.PlotAreaBorderColor = color;
foreach (var axis in this.CurrentPlotModel.Axes)
{
axis.MajorGridlineColor = color;
axis.MinorGridlineColor = color;
axis.TextColor = color;
axis.AxislineColor = color;
axis.TicklineColor = color;
}
})
.AddTo(this.disposables);
var totalCurrentSeries = new OxyPlot.Series.LineSeries()
{
Title = "Total Current",
};
// Change plot series color.
viewSettings
.ObserveProperty(self => self.PlotStyle).Select(style => style.ObserveProperty(self => self.SeriesColor))
.Switch()
.Subscribe(color => totalCurrentSeries.Color = color.ToOxyColor())
.AddTo(this.disposables);
this.CurrentPlotModel.Series.Add(totalCurrentSeries);
var currentHistory = this.TotalCurrent
.Select(Value => new { Value, TimeStamp = DateTime.Now })
.ToObservationHistory(Observable.Empty<Unit>(), pair => (DateTime.Now - pair.TimeStamp) >= TimeSpan.FromSeconds(60))
.AddTo(this.disposables);
var livePlotSource = currentHistory.HistoryChanged
.Select(_ =>
{
var history = currentHistory.GetHistory();
return history.Select(pair => new OxyPlot.DataPoint() {X = OxyPlot.Axes.DateTimeAxis.ToDouble(pair.TimeStamp), Y = pair.Value});
});
var historicPlotPeriods = HistoricPlotTypeConditions
.Select(condition => this.CurrentPlotType
.Where(plotType => plotType == condition.PlotType)
.Select(_ => { var now_ = DateTimeOffset.Now; return new { From = condition.CalculateFrom(now_), To = condition.CalculateTo(now_)}; })
)
.ToArray();
var now = DateTimeOffset.Now;
var today = now.Subtract(now.TimeOfDay);
this.PlotFromDate = new ReactiveProperty<DateTimeOffset>(today).AddTo(this.disposables);
this.PlotToDate = new ReactiveProperty<DateTimeOffset>(today).AddTo(this.disposables);
this.PlotFromTime = new ReactiveProperty<TimeSpan>(now.TimeOfDay).AddTo(this.disposables);
this.PlotToTime = new ReactiveProperty<TimeSpan>(now.TimeOfDay).AddTo(this.disposables);
this.UpdatePlotPeriodCommand = new ReactiveCommand().AddTo(this.disposables);
var customPlotPeriod = this.UpdatePlotPeriodCommand
.Select(_ => new {From = this.PlotFromDate.Value.Add(this.PlotFromTime.Value), To = this.PlotToDate.Value.Add(this.PlotToTime.Value)});
var recordedPlotSource = Observable
.Merge(historicPlotPeriods.Concat(new[] {customPlotPeriod}))
.Select(period => powerDistributionLogger.GetPowerDistrubutionByPeriod(period.From, period.To))
.Select(dataPoints => dataPoints.Select(pair => new OxyPlot.DataPoint() {X = OxyPlot.Axes.DateTimeAxis.ToDouble(pair.TimeStamp.LocalDateTime), Y = pair.Consumption}));
var hasDataPointsSubject = new Subject<bool>().AddTo(this.disposables);
var accumulatedCurrentSubject = new Subject<float>().AddTo(this.disposables);
this.AccumulatedCurrent = accumulatedCurrentSubject.ToReadOnlyReactiveProperty().AddTo(this.disposables);
this.IsLive
.Select(isLive => isLive ? livePlotSource : recordedPlotSource)
.Switch()
.ObserveOnUIDispatcher()
.Do(dataPointsEnumerable =>
{
var dataPoints = dataPointsEnumerable.ToArray();
accumulatedCurrentSubject.OnNext(
(float)dataPoints.Pairwise().Sum(dataPoint =>
(dataPoint.OldItem.Y + dataPoint.NewItem.Y) * (OxyPlot.Axes.DateTimeAxis.ToDateTime(dataPoint.NewItem.X) - OxyPlot.Axes.DateTimeAxis.ToDateTime(dataPoint.OldItem.X)).TotalSeconds )
/ 3600.0f);
hasDataPointsSubject.OnNext(dataPoints.Length > 0);
totalCurrentSeries.Points.Clear();
totalCurrentSeries.Points.AddRange(dataPoints);
})
.Do(_ => this.CurrentPlotModel.InvalidatePlot(true))
.Subscribe()
.AddTo(this.disposables);
this.HasDataPoints = hasDataPointsSubject.ToReadOnlyReactiveProperty().AddTo(this.disposables);
}
private Series ConvertSeries(ChartSeriesViewModel series)
{
Series newSeries = null;
var valueSeries = series.GetScaleForProperty(series.ValueMemberPath);
var labelSeries = series.GetScaleForProperty(series.LabelMemberPath);
switch (series.SeriesType)
{
case( ChartSeriesType.Column):
{
newSeries = new ColumnSeries
{
ValueField = series.ValueMemberPath,
ItemsSource = series.DataSource.Data,
FillColor = valueSeries.Color.ToOxyColor(),
StrokeColor = valueSeries.Color.ToOxyColor(),
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case( ChartSeriesType.Line ):
{
newSeries = new LineSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
MarkerType = MarkerType.Circle,
Color = valueSeries.Color.ToOxyColor(),
MarkerFill = valueSeries.Color.ToOxyColor(),
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case( ChartSeriesType.Spline):
{
newSeries = new LineSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
MarkerType = MarkerType.Circle,
Color = valueSeries.Color.ToOxyColor(),
MarkerFill = valueSeries.Color.ToOxyColor(),
Smooth = true,
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case(ChartSeriesType.Area):
{
newSeries = new AreaSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
Color = valueSeries.Color.ToOxyColor(),
Fill = valueSeries.Color.ToOxyColor(),
MarkerFill = valueSeries.Color.ToOxyColor(),
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case( ChartSeriesType.SplineArea):
{
newSeries = new AreaSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
Color = valueSeries.Color.ToOxyColor(),
Fill = valueSeries.Color.ToOxyColor(),
MarkerFill = valueSeries.Color.ToOxyColor(),
Smooth = true,
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case(ChartSeriesType.Bubble):
{
newSeries = new ScatterSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
DataFieldSize = series.RadiusMemberPath,
MarkerFill = valueSeries.Color.ToOxyColor(),
MarkerType = MarkerType.Circle,
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
case( ChartSeriesType.StepLine):
{
newSeries = new StairStepSeries
{
ItemsSource = series.DataSource.Data,
DataFieldX = series.XMemberPath,
DataFieldY = series.YMemberPath,
Color = valueSeries.Color.ToOxyColor(),
YAxisKey = valueSeries.Name,
XAxisKey = labelSeries.Name,
};
break;
}
default:
{
return null;
}
}
newSeries.Title = series.Name;
return newSeries;
}
public void DrawCurve(List<DataPoint> points, string title = null, LineStyle style = LineStyle.Solid)
{
var curve = new LineSeries
{
StrokeThickness = 2,
Smooth = true,
Color = OxyColor.FromRgb(0, 0, 0),
LineStyle = style,
Points = new List<IDataPoint>(),
Title = title
};
for (var i = 0; i < points.Count; i++)
{
curve.Points.Add(new DataPoint(points[i].X, points[i].Y));
}
_mainPlot.Series.Add(curve);
}
private void CreateTheorIsotopicProfilePlot()
{
var theorProfileAligned = Workflow.Result.Target.IsotopicProfile.CloneIsotopicProfile();
double fwhm;
if (Workflow.Result.IsotopicProfile != null)
{
fwhm = Workflow.Result.IsotopicProfile.GetFWHM();
IsotopicProfileUtilities.AlignTwoIsotopicProfiles(Workflow.Result.IsotopicProfile, theorProfileAligned);
if (Workflow.SubtractedIso != null && Workflow.SubtractedIso.Peaklist.Count > 0)
{
SubtractedMassSpecXYData = TheorXYDataCalculationUtilities.GetTheoreticalIsotopicProfileXYData(Workflow.SubtractedIso, fwhm);
}
else
{
SubtractedMassSpecXYData = new XYData
{
Xvalues = new double[] { 400, 500, 600 },
Yvalues = new double[] { 0, 0, 0 }
};
}
}
else
{
fwhm = DefaultMsPeakWidth;
}
TheorProfileXyData = TheorXYDataCalculationUtilities.GetTheoreticalIsotopicProfileXYData(Workflow.Result.Target.IsotopicProfile, fwhm);
XYData xydata = new XYData();
xydata.Xvalues = TheorProfileXyData.Xvalues;
xydata.Yvalues = TheorProfileXyData.Yvalues;
//scale to 100;
for (int i = 0; i < xydata.Yvalues.Length; i++)
{
xydata.Yvalues[i] = xydata.Yvalues[i]*100;
}
string msGraphTitle = "Theoretical MS - m/z " +
Workflow.Result.Target.MZ.ToString("0.0000") + "; z=" +
Workflow.Result.Target.ChargeState;
PlotModel plotModel = new PlotModel(msGraphTitle);
plotModel.TitleFontSize = 11;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(50, 0, 0, 0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "m/z");
xAxis.Minimum = MsGraphMinX;
xAxis.Maximum = MsGraphMaxX;
var yAxis = new LinearAxis(AxisPosition.Left, "Intensity");
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
yAxis.Maximum = 105;
yAxis.AbsoluteMaximum = 105;
yAxis.StringFormat = "0.0E0";
//yAxis.Maximum = maxIntensity + (maxIntensity * .05);
//yAxis.AbsoluteMaximum = maxIntensity + (maxIntensity * .05);
yAxis.AxisChanged += OnYAxisChange;
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
TheorIsoPlot = plotModel;
}
private void CreateChromCorrPlot()
{
ChromCorrXYData = new XYData();
ChromCorrXYData.Xvalues = Workflow.ChromCorrelationRSquaredVals == null ? new double[] { 0, 1, 2, 3, 4 } : Workflow.ChromCorrelationRSquaredVals.Xvalues;
ChromCorrXYData.Yvalues = Workflow.ChromCorrelationRSquaredVals == null ? new double[] { 0, 0, 0, 0, 0 } : Workflow.ChromCorrelationRSquaredVals.Yvalues;
XYData xydata = new XYData();
xydata.Xvalues = ChromCorrXYData.Xvalues;
xydata.Yvalues = ChromCorrXYData.Yvalues;
string graphTitle = "Isotope peak correlation data";
PlotModel plotModel = new PlotModel(graphTitle);
plotModel.TitleFontSize = 10;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 3;
series.MarkerType = MarkerType.Square;
series.MarkerStrokeThickness = 1;
series.MarkerFill = OxyColors.DarkRed;
series.MarkerStroke = OxyColors.Black;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "isotopic peak #");
var yAxis = new LinearAxis(AxisPosition.Left, "correlation");
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
xAxis.FontSize = 8;
xAxis.MajorStep = 1;
xAxis.ShowMinorTicks = false;
xAxis.MinorStep = 1;
yAxis.FontSize = 8;
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
yAxis.Maximum = 1.02;
yAxis.AbsoluteMaximum = 1.02;
yAxis.AxisChanged += OnYAxisChange;
plotModel.Series.Add(series);
plotModel.Axes.Add(yAxis);
plotModel.Axes.Add(xAxis);
ChromCorrelationPlot = plotModel;
}
/// <summary>
/// Setups the oxyplot.
/// </summary>
private void SetupOxyPlot()
{
XAxis = new LinearAxis {
Key = "X",
Position = AxisPosition.Bottom,
AbsoluteMinimum = TimeSpan.FromSeconds (0).Ticks,
LabelFormatter = x => {
if (x <= TimeSpan.FromSeconds (0).Ticks) {
return "Start";
}
return string.Format ("+{0}", TimeSpan.FromSeconds (x).ToString ("c"));
},
MajorGridlineThickness = 1,
MajorGridlineStyle = LineStyle.Solid,
MinorGridlineColor = OxyColors.LightGray,
MinorGridlineStyle = LineStyle.Dot,
MinorGridlineThickness = .5,
};
var YAxis = new LinearAxis {
Position = AxisPosition.Left,
Minimum = -0.1,
Maximum = 1.1,
LabelFormatter = x => ((int)x == 0) ? "LOW" : "HIGH",
IsPanEnabled = false,
IsZoomEnabled = false,
AbsoluteMaximum = 1.1,
AbsoluteMinimum = -0.1,
MinorStep = 1,
MajorStep = 1,
};
sequenceSeries = new OxyPlot.Series.StairStepSeries () {
DataFieldX = "Time",
DataFieldY = "Value",
};
repeateSeries = new OxyPlot.Series.LineSeries () {
DataFieldX = "Time",
DataFieldY = "Value",
StrokeThickness = 2,
LineStyle = LineStyle.Dot
};
plotModel = new PlotModel {
PlotType = PlotType.XY,
Background = OxyPlot.OxyColors.White,
};
plotModel.Axes.Add (YAxis);
plotModel.Axes.Add (XAxis);
plotModel.Series.Add (sequenceSeries);
plotView = new PlotView (){ Name = "", Model = plotModel };
vboxOptions.Add (plotView);
((Box.BoxChild)(vboxOptions [plotView])).Position = 2;
plotView.SetSizeRequest (nvSequenceOptions.WidthRequest, this.HeightRequest / 3);
plotView.ShowAll ();
}
private void CreateObservedIsotopicProfilePlot()
{
XYData xydata = new XYData();
if (Workflow.MassSpectrumXYData == null)
{
xydata.Xvalues = Workflow.MassSpectrumXYData == null ? new double[] { 400, 1500 } : Workflow.MassSpectrumXYData.Xvalues;
xydata.Yvalues = Workflow.MassSpectrumXYData == null ? new double[] { 0, 0 } : Workflow.MassSpectrumXYData.Yvalues;
}
else
{
xydata.Xvalues = Workflow.MassSpectrumXYData.Xvalues;
xydata.Yvalues = Workflow.MassSpectrumXYData.Yvalues;
xydata = xydata.TrimData(Workflow.Result.Target.MZ - 100, Workflow.Result.Target.MZ + 100);
}
if (Workflow.Result.IsotopicProfile != null)
{
MsGraphMaxY = Workflow.Result.IsotopicProfile.getMostIntensePeak().Height;
}
else
{
MsGraphMaxY = (float)xydata.getMaxY();
}
string msGraphTitle = Workflow.Result.Target.Code + "; m/z " +
Workflow.Result.Target.MZ.ToString("0.0000") + "; z=" +
Workflow.Result.Target.ChargeState;
PlotModel plotModel = new PlotModel(msGraphTitle);
plotModel.TitleFontSize = 11;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "m/z");
xAxis.Minimum = MsGraphMinX;
xAxis.Maximum = MsGraphMaxX;
var yAxis = new LinearAxis(AxisPosition.Left, "Intensity");
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
yAxis.Maximum = MsGraphMaxY + MsGraphMaxY * 0.05;
yAxis.StringFormat = "0.0E0";
//yAxis.Maximum = maxIntensity + (maxIntensity * .05);
//yAxis.AbsoluteMaximum = maxIntensity + (maxIntensity * .05);
yAxis.AxisChanged += OnYAxisChange;
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
ObservedIsoPlot = plotModel;
}
static void SavePng(string path, string name, List<double> A, List<double> B, List<Tuple<int, int>> pairings = null)
{
PngExporter pngify = new PngExporter();
pngify.Width = 3200;
pngify.Height = 1200;
var model = new PlotModel() { Title = name };
var aSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Blue };
var bSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Red };
for (int i = 0; i < A.Count; i++)
{
aSeries.Points.Add(new OxyPlot.DataPoint(i, A[i]));
}
for (int i = 0; i < B.Count; i++)
{
bSeries.Points.Add(new OxyPlot.DataPoint(i, B[i]));
}
if (pairings != null)
{
for (int i = 0; i < pairings.Count; i += 10)
{
var lineSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Gray, StrokeThickness = 0.2 };
lineSeries.Points.Add(aSeries.Points[pairings[i].Item1]);
lineSeries.Points.Add(bSeries.Points[pairings[i].Item2]);
model.Series.Add(lineSeries);
}
}
model.Series.Add(aSeries);
model.Series.Add(bSeries);
model.Axes.Add(new OxyPlot.Axes.LinearAxis() { Minimum = 0, Maximum = 1, Position = OxyPlot.Axes.AxisPosition.Left });
//model.Axes.Add(new OxyPlot.Axes.LinearAxis() { Minimum = 0, Maximum = 1, Position = OxyPlot.Axes.AxisPosition.Bottom });
pngify.ExportToFile(model, path);
}
private void CreateChromatogramPlot()
{
var centerScan = Workflow.Result.Target.ScanLCTarget;
ChromGraphMinX = centerScan - ChromGraphXWindowWidth / 2;
ChromGraphMaxX = centerScan + ChromGraphXWindowWidth / 2;
XYData xydata = new XYData();
if (Workflow.ChromatogramXYData == null)
{
xydata.Xvalues = Workflow.ChromatogramXYData == null ? new double[] { 1, Run.MaxLCScan } : Workflow.ChromatogramXYData.Xvalues;
xydata.Yvalues = Workflow.ChromatogramXYData == null ? new double[] { 0, 0 } : Workflow.ChromatogramXYData.Yvalues;
}
else
{
xydata.Xvalues = Workflow.ChromatogramXYData.Xvalues;
xydata.Yvalues = Workflow.ChromatogramXYData.Yvalues;
}
string graphTitle = "TargetID=" + Workflow.Result.Target.ID + "; m/z " +
Workflow.Result.Target.MZ.ToString("0.0000") + "; z=" +
Workflow.Result.Target.ChargeState;
PlotModel plotModel = new PlotModel(graphTitle);
plotModel.TitleFontSize = 11;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "scan");
xAxis.Minimum = ChromGraphMinX;
xAxis.Maximum = ChromGraphMaxX;
var yAxis = new LinearAxis(AxisPosition.Left, "Intensity");
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
var maxY = xydata.getMaxY();
yAxis.Maximum = maxY + maxY * 0.05;
yAxis.AxisChanged += OnYAxisChange;
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
ChromatogramPlot = plotModel;
}
protected MainViewModel()
{
_model = new PlotModel
{
IsLegendVisible = false,
DefaultFontSize = 0,
PlotMargins = new OxyThickness(20, 0, 0, 10)
};
_series = new LineSeries
{
MarkerType = MarkerType.Circle,
MarkerSize = 1
};
_model.Series.Add(_series);
_emptyDataPoint = new DataPoint(-1.0, -1.0);
_newDataPoint = _emptyDataPoint;
_dispatcher = Dispatcher.CurrentDispatcher;
TimeRange = 10000;
_refreshPlot = true;
_updateThread = new Thread(Update);
_updateThread.SetApartmentState(ApartmentState.STA);
_updateThread.IsBackground = true;
_updateThread.Start();
}
private void CreateMsPlotForScanByScanAnalysis(ScanSet scanSet)
{
XYData xydata = new XYData();
xydata.Xvalues = MassSpecXyData == null ? new double[] { 400, 1500 } : MassSpecXyData.Xvalues;
xydata.Yvalues = MassSpecXyData == null ? new double[] { 0, 0 } : MassSpecXyData.Yvalues;
string msGraphTitle = "Observed MS - Scan: " + scanSet;
MsGraphMaxY = (float)xydata.getMaxY(MsGraphMinX, MsGraphMaxX);
PlotModel plotModel = new PlotModel(msGraphTitle);
plotModel.TitleFontSize = 11;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "m/z");
xAxis.Minimum = MsGraphMinX;
xAxis.Maximum = MsGraphMaxX;
var yAxis = new LinearAxis(AxisPosition.Left, "Intensity");
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
yAxis.Maximum = MsGraphMaxY + MsGraphMaxY * 0.05;
//yAxis.Maximum = maxIntensity + (maxIntensity * .05);
//yAxis.AbsoluteMaximum = maxIntensity + (maxIntensity * .05);
yAxis.AxisChanged += OnYAxisChange;
yAxis.StringFormat = "0.0E0";
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
ObservedIsoPlot = plotModel;
}
/// <summary>
/// Displaies the plot.
/// </summary>
private void DisplayPlot()
{
if (pinSequence != null) {
plotView.Model.Series.Clear ();
var current = new TimeSpan (0);
var data = new Collection<TimeValue> ();
for (int i = 0; i < pinSequence.Chain.Count; i++) {
data.Add (new TimeValue () {
Time = current,
Value = ((pinSequence.Chain [i].State == DPinState.HIGH) ? 1 : 0)
});
current = current.Add (pinSequence.Chain [i].Duration);
data.Add (new TimeValue () {
Time = current,
Value = ((pinSequence.Chain [i].State == DPinState.HIGH) ? 1 : 0)
});
}
sequenceSeries = new OxyPlot.Series.LineSeries () {
DataFieldX = "Time",
DataFieldY = "Value",
ItemsSource = data,
StrokeThickness = 2,
Color = ColorHelper.GdkColorToOxyColor (selectedPin.PlotColor)
};
repeateSeries.Color = ColorHelper.GdkColorToOxyColor (selectedPin.PlotColor);
//next Cycle Tease
// if ((rbRepeateContinously.Active || (rbStopAfter.Active && sbRadioBtnStopAfter.ValueAsInt > 1)) && data.Count > 0)
// {
// var repeateData = new Collection<TimeValue> ();
// repeateData.Add (data.Last ());
// repeateData.Add (
// new TimeValue {
// Time = data.Last ().Time,
// Value = ((pinSequence.Chain [0].State == DPinState.HIGH) ? 1 : 0)
// });
// repeateData.Add (
// new TimeValue {
// Time = data.Last ().Time.Add (pinSequence.Chain [0].Duration),
// Value = ((pinSequence.Chain [0].State == DPinState.HIGH) ? 1 : 0)
// });
// repeateSeries.ItemsSource = repeateData;
// plotView.Model.Series.Add (repeateSeries);
// }
plotView.Model.Series.Add (sequenceSeries);
plotView.InvalidatePlot (true);
plotView.Model.InvalidatePlot (true);
plotView.ShowAll ();
}
}
public void LineSeries()
{
var s1 = new OxyPlot.Series.LineSeries();
var s2 = new LineSeries();
OxyAssert.PropertiesAreEqual(s1, s2);
}
private void GetMassSpectrumForCurrentResult()
{
if (ObservedIsoPlot==null)
{
ObservedIsoPlot= CreateObservedIsoPlot();
}
XYData xydata = new XYData();
if (CurrentResultInfo.MassSpectrumXYData == null)
{
xydata.Xvalues = CurrentResultInfo.MassSpectrumXYData == null ? new double[] { 400, 1500 } : CurrentResultInfo.MassSpectrumXYData.Xvalues;
xydata.Yvalues = CurrentResultInfo.MassSpectrumXYData == null ? new double[] { 0, 0 } : CurrentResultInfo.MassSpectrumXYData.Yvalues;
}
else
{
xydata.Xvalues = CurrentResultInfo.MassSpectrumXYData.Xvalues;
xydata.Yvalues = CurrentResultInfo.MassSpectrumXYData.Yvalues;
xydata = xydata.TrimData(CurrentResultInfo.Result.Target.MZ - 2, CurrentResultInfo.Result.Target.MZ + 8);
}
double msGraphMaxY;
if (CurrentResultInfo.Result.IsotopicProfile != null)
{
msGraphMaxY = CurrentResultInfo.Result.IsotopicProfile.getMostIntensePeak().Height;
}
else
{
msGraphMaxY = (float)xydata.getMaxY();
}
string msGraphTitle = "TargetID= " + CurrentResultInfo.Result.Target.ID + "; m/z " + CurrentResultInfo.Result.Target.MZ.ToString("0.0000") + "; z=" +
CurrentResultInfo.Result.Target.ChargeState + "; Scan= " + CurrentResultInfo.Result.ScanSet??"[No scan selected]";
ObservedIsoPlot.Series.Clear();
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < xydata.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(xydata.Xvalues[i], xydata.Yvalues[i]));
}
ObservedIsoPlot.Axes[1].Maximum = msGraphMaxY + msGraphMaxY * 0.05;
ObservedIsoPlot.Series.Add(series);
}
private void CreateChromatogram()
{
bool canGenerateChrom = Run != null && Run.ResultCollection.MSPeakResultList != null &&
Run.ResultCollection.MSPeakResultList.Count > 0 && Peaks != null && Peaks.Count > 0
&& SelectedPeak != null;
if (!canGenerateChrom) return;
double scanWindowWidth = 600;
int lowerScan = (int)Math.Round(Math.Max(MinLcScan, CurrentLcScan - scanWindowWidth / 2));
int upperScan = (int)Math.Round(Math.Min(MaxLcScan, CurrentLcScan + scanWindowWidth / 2));
ChromXyData = _peakChromatogramGenerator.GenerateChromatogram(Run, lowerScan, upperScan,
SelectedPeak.XValue, ChromToleranceInPpm);
if (ChromXyData == null)
{
ChromXyData = new XYData();
ChromXyData.Xvalues = new double[] { lowerScan, upperScan };
ChromXyData.Yvalues = new double[] { 0, 0 };
}
var maxY = (float)ChromXyData.getMaxY();
string graphTitle = "XIC for most intense peak (m/z " + SelectedPeak.XValue.ToString("0.000") + ")";
PlotModel plotModel = new PlotModel(graphTitle);
plotModel.TitleFontSize = 9;
plotModel.Padding = new OxyThickness(0);
plotModel.PlotMargins = new OxyThickness(0);
plotModel.PlotAreaBorderThickness = 0;
var series = new OxyPlot.Series.LineSeries();
series.MarkerSize = 1;
series.Color = OxyColors.Black;
for (int i = 0; i < ChromXyData.Xvalues.Length; i++)
{
series.Points.Add(new DataPoint(ChromXyData.Xvalues[i], ChromXyData.Yvalues[i]));
}
var xAxis = new LinearAxis(AxisPosition.Bottom, "scan");
xAxis.Minimum = lowerScan;
xAxis.Maximum = upperScan;
var yAxis = new LinearAxis(AxisPosition.Left, "Intensity");
yAxis.Minimum = 0;
yAxis.AbsoluteMinimum = 0;
yAxis.Maximum = maxY + maxY * 0.05;
yAxis.AxisChanged += OnYAxisChange;
xAxis.AxislineStyle = LineStyle.Solid;
xAxis.AxislineThickness = 1;
yAxis.AxislineStyle = LineStyle.Solid;
yAxis.AxislineThickness = 1;
plotModel.Series.Add(series);
plotModel.Axes.Add(xAxis);
plotModel.Axes.Add(yAxis);
ChromatogramPlot = plotModel;
}
public void B11_Backgrounds()
{
var plot = new PlotModel("Backgrounds");
plot.Axes.Add(new LinearAxis(AxisPosition.Bottom, "X-axis"));
var yaxis1 = new LinearAxis(AxisPosition.Left, "Y1") { Key = "Y1", StartPosition = 0, EndPosition = 0.5 };
var yaxis2 = new LinearAxis(AxisPosition.Left, "Y2") { Key = "Y2", StartPosition = 0.5, EndPosition = 1 };
plot.Axes.Add(yaxis1);
plot.Axes.Add(yaxis2);
Action<LineSeries> addExamplePoints = ls =>
{
ls.Points.Add(new DataPoint(3, 13));
ls.Points.Add(new DataPoint(10, 47));
ls.Points.Add(new DataPoint(30, 23));
ls.Points.Add(new DataPoint(40, 65));
ls.Points.Add(new DataPoint(80, 10));
};
var ls1 = new LineSeries { Background = OxyColors.LightSeaGreen, YAxisKey = "Y1" };
addExamplePoints(ls1);
plot.Series.Add(ls1);
var ls2 = new LineSeries { Background = OxyColors.LightSkyBlue, YAxisKey = "Y2" };
addExamplePoints(ls2);
plot.Series.Add(ls2);
// OxyAssert.AreEqual(plot, "B11");
}
