public void ExecuteRecipe(Plot plt)
{
Random rand = new Random(0);
double[] xs = DataGen.Random(rand, 50);
double[] ys = DataGen.Random(rand, 50);
var scatter = plt.AddScatterPoints(xs, ys, Color.Blue, 10);
var vlines = new ScottPlot.Plottable.VLineVector();
vlines.Xs = new double[] { xs[1], xs[12], xs[35] };
vlines.Color = Color.Red;
vlines.PositionLabel = true;
vlines.PositionLabelBackground = vlines.Color;
var hlines = new ScottPlot.Plottable.HLineVector();
hlines.Ys = new double[] { ys[1], ys[12], ys[35] };
hlines.Color = Color.DarkCyan;
hlines.PositionLabel = true;
hlines.PositionLabelBackground = hlines.Color;
hlines.DragEnabled = true;
plt.Add(scatter);
plt.Add(vlines);
plt.Add(hlines);
}
public void ExecuteRecipe(Plot plt)
{
// display some sample data
plt.AddSignal(DataGen.Sin(51));
plt.AddSignal(DataGen.Cos(51));
// display an image with 3 different alignments
Bitmap monaLisa = DataGen.SampleImage();
var ip1 = new ScottPlot.Plottable.Image()
{
Bitmap = monaLisa, X = 10
};
var ip2 = new ScottPlot.Plottable.Image()
{
Bitmap = monaLisa, X = 25, Alignment = Alignment.MiddleCenter
};
var ip3 = new ScottPlot.Plottable.Image()
{
Bitmap = monaLisa, X = 40, Alignment = Alignment.LowerRight
};
plt.Add(ip1);
plt.Add(ip2);
plt.Add(ip3);
plt.AddPoint(ip1.X, ip1.Y, Color.Magenta, size: 20);
plt.AddPoint(ip2.X, ip2.Y, Color.Magenta, size: 20);
plt.AddPoint(ip3.X, ip3.Y, Color.Magenta, size: 20);
}
public void ExecuteRecipe(Plot plt)
{
//Generate a single signal containing 3 harmonic signals
int sampleCount = 500;
double[] signal1 = ScottPlot.DataGen.Sin(sampleCount, 10);
double[] signal2 = ScottPlot.DataGen.Sin(sampleCount, 20);
double[] signal3 = ScottPlot.DataGen.Sin(sampleCount, 30);
double[] signal = new double[sampleCount];
for (int index = 0; index < sampleCount; index++)
{
signal[index] = signal1[index] + signal2[index] + signal3[index];
}
// Plot the signal
plt.AddSignal(signal);
// Create a draggable RepeatingVLine with 5 lines spaced evenly by 50 X units, starting at position 0
// The first line will be thicker than the others
ScottPlot.Plottable.RepeatingVLine vlines1 = new();
vlines1.DragEnabled = true;
vlines1.count = 5;
vlines1.shift = 50;
vlines1.Color = System.Drawing.Color.Magenta;
vlines1.LineWidth = 2;
vlines1.LineStyle = LineStyle.Dash;
vlines1.PositionLabel = true;
vlines1.PositionLabelBackground = vlines1.Color;
vlines1.relativeposition = false;
plt.Add(vlines1);
// Create a draggable RepeatingVLine with 5 lines spaced evenly by 50 X units, starting at position 0, with a -4 offset
// The first line will be thicker than the others
ScottPlot.Plottable.RepeatingVLine vlines2 = new();
vlines2.DragEnabled = true;
vlines2.count = 3;
vlines2.shift = 50;
vlines2.offset = -1;
vlines2.Color = System.Drawing.Color.DarkGreen;
vlines2.LineWidth = 2;
vlines2.LineStyle = LineStyle.Dot;
vlines2.PositionLabel = true;
vlines2.PositionLabelBackground = vlines2.Color;
vlines2.relativeposition = false;
plt.Add(vlines2);
plt.SetAxisLimitsX(-100, 300);
}
public GraphicsPage()
{
Title = "Graphics";
var physics = new Physics();
var points = new List <Vector2>();
var position = new Vector2(0, 0);
for (int i = 0; i < 20; i++)
{
position = physics.Trajectory(position, i, 45f, 100f);
points.Add(position);
}
var xValues = points.Select(x => x.X.ToDouble()).ToArray();
var yValues = points.Select(x => x.Y.ToDouble()).ToArray();
var signalPlot = new ScatterPlot(xValues, yValues)
{
};
var wpfPlot = new WpfPlot();
var plot = new Plot();
plot.Add(signalPlot);
wpfPlot.Plot.Add(signalPlot);
var view = new Grid();
view.Children.Add(wpfPlot);
Content = view;
}
public void ExecuteRecipe(Plot plt)
{
// plot sample data
double[] xs = ScottPlot.DataGen.Consecutive(20);
double[] ys = ScottPlot.DataGen.Sin(20);
var scatter = new ScottPlot.Plottable.ScatterPlotListDraggable();
scatter.AddRange(xs, ys);
scatter.MarkerSize = 5;
plt.Add(scatter);
public void ExecuteRecipe(Plot plt)
{
double[] xs = ScottPlot.DataGen.Consecutive(51);
double[] ys = ScottPlot.DataGen.Sin(51);
var scatter = new ScottPlot.Plottable.ScatterPlotListDraggable();
scatter.AddRange(xs, ys);
plt.Add(scatter);
}
public void ExecuteRecipe(Plot plt)
{
double[] x = ScottPlot.DataGen.Consecutive(50);
double[] y = ScottPlot.DataGen.Cos(50);
var scatter = new ScottPlot.Plottable.ScatterPlotDraggable(x, y)
{
DragCursor = Cursor.Crosshair,
DragEnabled = true,
};
plt.Add(scatter);
}
public void ExecuteRecipe(Plot plt)
{
double[] x = ScottPlot.DataGen.Consecutive(50);
double[] y = ScottPlot.DataGen.Cos(50);
var scatter = new ScottPlot.Plottable.ScatterPlotDraggable(x, y)
{
DragCursor = Cursor.Crosshair,
DragEnabled = true, // controls whether anything can be dragged
DragEnabledX = false, // controls whether points can be dragged horizontally
DragEnabledY = true, // controls whether points can be dragged vertically
};
plt.Add(scatter);
}
private void AddValueToPlot(Plot plot, float val)
{
if (plot != null)
{
plot.Add(val);
if (val > MaxY)
{
MaxY = val;
}
if (val < MinY)
{
MinY = val;
}
}
}
public void ExecuteRecipe(Plot plt)
{
// display some sample data
plt.AddSignal(DataGen.Sin(51));
plt.AddSignal(DataGen.Cos(51));
// place a rotated image on the plot
Bitmap monaLisa = DataGen.SampleImage();
var ip1 = new ScottPlot.Plottable.Image()
{
Bitmap = monaLisa, X = 10, Y = .5, Rotation = 30
};
plt.Add(ip1);
plt.AddPoint(ip1.X, ip1.Y, color: Color.Magenta, size: 20);
}
public void ExecuteRecipe(Plot plt)
{
double[] xs = DataGen.Consecutive(51);
double[] sin = DataGen.Sin(51);
// instantiate a plottable
var splt = new ScottPlot.Plottable.ScatterPlot(xs, sin);
// customize its style or change its data as desired
splt.Color = Color.Navy;
splt.MarkerSize = 10;
splt.MarkerShape = MarkerShape.filledDiamond;
// add it to the plot
plt.Add(splt);
}
public void ExecuteRecipe(Plot plt)
{
// display some sample data
plt.AddSignal(DataGen.Sin(51));
plt.AddSignal(DataGen.Cos(51));
// place an image on the plot
plt.Add(new ScottPlot.Plottable.Image()
{
Bitmap = DataGen.SampleImage(),
X = 10,
Y = .5,
Rotation = 30,
BorderColor = Color.Magenta,
BorderSize = 5,
});
}
public void ExecuteRecipe(Plot plt)
{
// display some sample data
plt.AddSignal(DataGen.Sin(51));
plt.AddSignal(DataGen.Cos(51));
// create the bitmap we want to display
Bitmap monaLisa = DataGen.SampleImage();
// create the image plottable and add it to the plot
var imagePlot = new ScottPlot.Plottable.Image()
{
Bitmap = monaLisa, X = 10, Y = .5
};
plt.Add(imagePlot);
}
public void ExecuteRecipe(Plot plt)
{
plt.AddSignal(ScottPlot.DataGen.Sin(51));
plt.AddSignal(ScottPlot.DataGen.Cos(51));
var myDraggableMarker = new ScottPlot.Plottable.DraggableMarkerPlot()
{
X = 25,
Y = .57,
Color = Color.Magenta,
MarkerShape = MarkerShape.filledDiamond,
MarkerSize = 15,
Text = "drag the point!",
};
myDraggableMarker.TextFont.Size = 16;
plt.Add(myDraggableMarker);
}
public void ExecuteRecipe(Plot plt)
{
// create random data and display it with a scatter plot
double[] xs = DataGen.Consecutive(50);
double[] ys = DataGen.Random(new Random(0), 50);
plt.AddScatter(xs, ys, label: "data");
// add a draggable marker that "snaps" to data values in that scatter plot
var dmpv = new ScottPlot.Plottable.DraggableMarkerPlotInVector()
{
Xs = xs,
Ys = ys,
DragEnabled = true,
IsVisible = true,
MarkerSize = 15,
MarkerShape = MarkerShape.filledDiamond,
MarkerColor = Color.Magenta,
Label = "marker",
};
plt.Add(dmpv);
plt.Legend();
}
public void Render(Plot plt)
{
// rather than call Plot.PlotText(), create the Plottable manually
var customPlottable = new Plottable.Text()
{
text = "test",
x = 2,
y = 3,
FontColor = System.Drawing.Color.Magenta,
FontName = "arial",
FontSize = 26,
FontBold = true,
alignment = Alignment.MiddleCenter,
rotation = 0,
frame = false,
frameColor = System.Drawing.Color.Green
};
// you can access properties which may not be exposed by a Plot method
customPlottable.rotation = 45;
// add the custom plottable to the list of plottables like this
plt.Add(customPlottable);
}
public void AddValue(float val)
{
plotObject.Add(val);
UpdatePlotArea();
}
static async Task Main(string[] args)
{
IStockDataService yahooService = new YahooService();
_priceManager = new PriceManager(yahooService);
var prices = CsvExtensions.ReadCsv(
@"Data\\all_stocks_5yr.csv",
new Dictionary <string, string>
{
{ "date", "StartTime" },
{ "open", "Open" },
{ "close", "Close" },
{ "high", "High" },
{ "low", "Low" },
{ "volume", "Volume" },
{ "Name", "Symbol" }
});
var aalPrice = prices.Where(c => c.Symbol.Equals("AAL")).SortByStartTime();
var open = aalPrice.Select(c => (double)c.Open).ToArray();
var high = aalPrice.Select(c => (double)c.High).ToArray();
var low = aalPrice.Select(c => (double)c.Low).ToArray();
var close = aalPrice.Select(c => (double)c.Close).ToArray();
var volume = aalPrice.Select(c => c.Volume).ToArray();
var lstm = new Lstm(open, high, low, close, volume);
lstm.Print();
var scale = lstm.CalculateScale();
var min = lstm.CalculateMin();
var stochasticOsc = new StochasticOsc();
var sData = stochasticOsc.Run(GetData());
var plt = new Plot(600, 400);
var slow = sData.Select(c => c.SlowValue).ToArray();
var vals = sData.Select(c => c.Value).ToArray();
//var xs = sData.Select(p => p.StartTime.ToOADate()).ToArray();
plt.PlotSignalXY(sData.Select(p => p.StartTime.ToOADate()).ToArray(), slow, label: "slow", color: Color.Red,
lineWidth: 2, lineStyle: LineStyle.Solid, markerSize: 0);
plt.PlotSignalXY(sData.Select(p => p.StartTime.ToOADate()).ToArray(), vals, label: "fast",
color: Color.Black, lineWidth: 2, lineStyle: LineStyle.Solid);
plt.Title("IBM Stochastic");
plt.YLabel("Stochastic Unit");
plt.XLabel("Date");
plt.Ticks(dateTimeX: true);
//plt.Legend();
plt.AxisBounds(minY: 0, maxY: 100);
plt.AxisAuto(verticalMargin: 0.01);
plt.Add(new PlottableHLine(20, Color.Black, 1, "", false, 20, 20, LineStyle.Solid));
plt.Add(new PlottableHLine(80, Color.Black, 1, "", false, 80, 80, LineStyle.Solid));
plt.SaveFig("IBM Slow Stochastic Chart.png");
return;
//var list = stochasticService.Run(sData);
//await TargilAsync();
//var tickerManager = new TickerManager(yahooService, _priceManager);
//var tickers = CsvExtensions.ReadConstituentsAsync("Data\\constituents.csv", new Dictionary<string, string>
//{
// {"Symbol", "Symbol"},
// {"Name", "Name"},
// {"Sector", "Sector"},
//}).Result;
//var msftTicker = tickerManager.GetTickerBySymbol(tickers, "MSFT");
//var prices = await _priceManager.GetPricesAsync(
// msftTicker,
// new DateTime(2020, 4, 13),
// new DateTime(2020, 6, 26),
// Interval.OneDay,
// false);
//var offsetPercent = 1;
//var vals = stochasticService.Run(prices);
//var plt = new ScottPlot.Plot(600, 400);
//plt.PlotSignal(vals.Select(c => (double)c.Value).ToArray());
//plt.Title("Signal Plot Quickstart (5 million points)");
//plt.YLabel("Vertical Units");
//plt.XLabel("Horizontal Units");
//plt.SaveFig("Quickstart_Quickstart_Signal_5MillionPoints.png");
return;
//var offsetPercent = 0.5;
//var supportPoints = _priceManager.GetSupportExtremaGroups(prices, ExtremaType.Minimum, offsetPercent);
//var p = prices.Last();
//Console.WriteLine($"Curret value: {p.Close}");
//Console.WriteLine("Support Points");
//supportPoints.Print(ExtremaType.Minimum);
//Console.WriteLine();
//Console.WriteLine("Reject Points");
//rejectPoints.Print(ExtremaType.Maximum);
//var daysMomentum = _priceManager.GetDaysMomentum(prices);
//daysMomentum.Print();
}
static void Main()
{
//Random r = new Random();
//double[] array = new double[10000000];
//for (int i = 0; i < array.Length; i++)
// array[i] = r.NextDouble() - 0.5;
//Stopwatch sw = new Stopwatch();
//sw.Start();
////var min = array.Where(e => e > 0).Min();
////var max = array.Where(e => e > 0).Max();
//double min = double.MaxValue;
//double max = double.MinValue;
//for (int i = 0; i < array.Length; i++)
//{
// if(array[i] > 0)
// {
// if (min > array[i]) min = array[i];
// if (max < array[i]) max = array[i];
// }
//}
//sw.Stop();
Application.EnableVisualStyles();
Application.SetCompatibleTextRenderingDefault(false);
double[] sin0 = new double[100];
double[] sin1 = new double[sin0.Length];
double[] sin2 = new double[sin0.Length];
for (int i = 0; i < sin0.Length; i++)
{
sin0[i] = Math.Sin(2 * Math.PI * i * 0.01);
sin1[i] = Math.Sin(2 * Math.PI * (i + 5) * 0.01) + 0.1;
sin2[i] = Math.Sin(2 * Math.PI * (i + 10) * 0.01) + 0.2;
}
double[] norm1 = new double[10];
double[] norm2 = new double[norm1.Length];
double sigma1 = 2;
double sigma2 = 3;
double avg1 = 5;
double avg2 = 3;
for (int i = 0; i < norm1.Length; i++)
{
norm1[i] = 1 / (sigma1 * Math.Sqrt(2 * Math.PI)) * Math.Exp(-1 * (i - avg1) * (i - avg1) / 2 / sigma1 / sigma1);
norm2[i] = 1 / (sigma2 * Math.Sqrt(2 * Math.PI)) * Math.Exp(-1 * (i - avg2) * (i - avg2) / 2 / sigma2 / sigma2);
}
double[] freq = new double[] { 10000, 10232, 10471, 10715, 10964, 11220, 11481, 11748, 12022, 12302, 12589, 12882,
13182, 13489, 13803, 14125, 14454, 14791, 15135, 15488, 15848, 16218, 16595, 16982, 17378, 17782, 18197, 18620,
19054, 19498, 19952, 20417, 20892, 21379, 21877, 22387, 22908, 23442, 23988, 24547, 25118, 25703, 26302, 26915,
27542, 28183, 28840, 29512, 30199, 30902, 31622, 32359, 33113, 33884, 34673, 35481, 36307, 37153, 38018, 38904,
39810, 40738, 41686, 42657, 43651, 44668, 45708, 46773, 47863, 48977, 50118, 51286, 52480, 53703, 54954, 56234,
57543, 58884, 60255, 61659, 63095, 64565, 66069, 67608, 69183, 70794, 72443, 74131, 75857, 77624, 79432, 81283,
83176, 85113, 87096, 89125, 91201, 93325, 95499, 97723, 100000, 102329, 104712, 107151, 109647, 112201, 114815,
117489, 120226, 123026, 125892, 128824, 131825, 134896, 138038, 141253, 144543, 147910, 151356, 154881, 158489,
162181, 165958, 169824, 173780, 177827, 181970, 186208, 190546, 194984, 199526, 204173, 208929, 213796, 218776,
223872, 229086, 234422, 239883, 245470, 251188, 257039, 263026, 269153, 275422, 281838, 288403, 295120, 301995,
309029, 316227, 323593, 331131, 338844, 346736, 354813, 363078, 371535, 380189, 389045, 398107, 407380, 416869,
426579, 436515, 446683, 457088, 467735, 478630, 489778, 501187, 512861, 524807, 537031, 549540, 562341, 575439,
588843, 602559, 616595, 630957, 645654, 660693, 676082, 691830, 707945, 724435, 741310, 758577, 776247, 794328,
812830, 831763, 851138, 870963, 891250, 912010, 933254, 954992, 977237, 1000000 };
double[] fresp = new double[] { 0.034, 0.035, 0.037, 0.039, 0.041, 0.043, 0.045, 0.047, 0.049, 0.052, 0.054, 0.057,
0.059, 0.062, 0.065, 0.068, 0.071, 0.075, 0.078, 0.082, 0.086, 0.090, 0.094, 0.099, 0.104, 0.109, 0.114, 0.119,
0.125, 0.131, 0.137, 0.144, 0.150, 0.158, 0.165, 0.173, 0.181, 0.190, 0.199, 0.209, 0.219, 0.229, 0.240, 0.251,
0.264, 0.276, 0.289, 0.303, 0.318, 0.333, 0.349, 0.366, 0.384, 0.402, 0.422, 0.442, 0.464, 0.486, 0.510, 0.535,
0.561, 0.588, 0.617, 0.647, 0.679, 0.712, 0.747, 0.784, 0.823, 0.863, 0.906, 0.952, 0.999, 1.049, 1.102, 1.158,
1.216, 1.278, 1.343, 1.412, 1.484, 1.561, 1.642, 1.728, 1.818, 1.914, 2.016, 2.123, 2.237, 2.358, 2.487, 2.624,
2.770, 2.925, 3.090, 3.267, 3.456, 3.658, 3.876, 4.109, 4.360, 4.631, 4.924, 5.243, 5.589, 5.966, 6.380, 6.836,
7.340, 7.902, 8.531, 9.243, 10.057, 11.000, 12.111, 13.449, 15.114, 17.283, 20.339, 25.358, 37.682, 28.041, 21.125,
17.147, 14.314, 12.091, 10.247, 8.660, 7.261, 6.003, 4.856, 3.798, 2.813, 1.889, 1.016, 0.187, -0.602, -1.360,
-2.088, -2.790, -3.469, -4.127, -4.767, -5.390, -5.998, -6.591, -7.173, -7.742, -8.301, -8.850, -9.390, -9.922,
-10.446, -10.963, -11.473, -11.977, -12.475, -12.967, -13.455, -13.938, -14.416, -14.890, -15.360, -15.827, -16.290,
-16.750, -17.207, -17.661, -18.112, -18.561, -19.007, -19.451, -19.893, -20.332, -20.770, -21.206, -21.640, -22.073,
-22.504, -22.933, -23.362, -23.788, -24.214, -24.638, -25.062, -25.484, -25.905, -26.325, -26.745, -27.163, -27.581,
-27.998, -28.414, -28.829, -29.244, -29.658, -30.071, -30.484, -30.897, -31.309, -31.720 };
Random r = new Random();
double[] randoms = new double[100];
double[] quantiles = new double[randoms.Length];
for (int i = 0; i < randoms.Length; i++)
{
randoms[i] = r.NextDouble();
quantiles[i] = QNorm(((double)i + 1.0 - 0.375) / ((double)randoms.Length + 0.25));
}
Array.Sort(randoms);
Plot plot0 = new Plot {
Height = 300, Width = 500
};
plot0.Title = "Sin example";
plot0.Add(sin0);
plot0.Add(sin1);
plot0.Add(sin2);
plot0.LegendStyle = LegendStyle.Inside;
var im0 = plot0.ToImage();
Plot plot1 = new Plot {
Height = 300, Width = 500
};
plot1.Title = "Histogram example";
plot1.Add(norm1, ps: PlotStyle.VerticalBars);
plot1.Add(norm2, ps: PlotStyle.VerticalBars);
plot1.LegendStyle = LegendStyle.Inside;
var im1 = plot1.ToImage();
Plot plot2 = new Plot {
Height = 300, Width = 500
};
plot2.Title = "Frequency response example";
plot2.Add(freq, fresp);
plot2.GetHorizontalAxis().Title = "F, Hz";
plot2.GetHorizontalAxis().Logarithmic = true;
plot2.GetHorizontalAxis().MinorTickNumber = 10;
plot2.GetHorizontalAxis().GridStyle = GridStyle.Both;
plot2.GetVerticalAxis().Title = "Vout, dB";
plot2.GetVerticalAxis().GridStyle = GridStyle.Both;
var im2 = plot2.ToImage();
Plot plot3 = new Plot {
Height = 300, Width = 500
};
plot3.Title = "Probability plot example";
plot3.GetHorizontalAxis().GridStyle = GridStyle.Both;
plot3.GetVerticalAxis().GridStyle = GridStyle.Both;
plot3.GetVerticalAxis().CustomTicks = new double[] { -2.326347874, -1.644853627, -1.281551566, -0.841621234,
-0.524400513, -0.253347103, 0, 0.253347103, 0.524400513, 0.841621234, 1.281551566, 1.644853627, 2.326347874 };
plot3.GetVerticalAxis().CustomTicksLabels = new string[] { "1", "5", "10", "20", "30", "40", "50", "60", "70", "80", "90", "95", "99" };
plot3.Add(randoms, quantiles, ps: PlotStyle.Markers);
plot3.Add(randoms, LinearRegression(randoms, quantiles, false)).LineWidth = 2;
var im3 = plot3.ToImage();
Image im = new Bitmap(1000, 600);
Graphics g = Graphics.FromImage(im);
g.DrawImage(im0, 0, 0);
g.DrawImage(im1, 500, 0);
g.DrawImage(im2, 0, 300);
g.DrawImage(im3, 500, 300);
im.Save("plot.png");
/*OMPlot.Plot p = new Plot();
* p.Height = 500;
* p.Width = 500;
* var plot0 = p.Add(dataX, dataY1);
* plot0.MarkStyle = Data.MarkerStyle.SolidCircle;
*
* var plot1 = p.Add(dataX, dataY2);
* plot1.LineStyle = Data.LineStyle.None;
* plot0.FillPlot = plot1;*/
/*foreach (Data.PlotInterpolation inter in Enum.GetValues(typeof(Data.PlotInterpolation)))
* foreach (Data.FillStyle fill in Enum.GetValues(typeof(Data.FillStyle)))
* PlotStyleTestBitmap(p, plot0, inter, fill);*/
//AxisTestBitmap(p, "Title", AxisPosition.Center, LabelsPosition.Near, Alignment.Center, LabelsPosition.Far, Alignment.Near, Alignment.Center, TicksLabelsRotation.Tilted);
/*foreach (AxisPosition ap in Enum.GetValues(typeof(AxisPosition)))
* foreach (LabelsPosition tp in Enum.GetValues(typeof(LabelsPosition)))
* foreach (Alignment ta in Enum.GetValues(typeof(Alignment)))
* foreach (LabelsPosition tlp in new LabelsPosition[] { LabelsPosition.Near, LabelsPosition.Far })
* foreach (Alignment tla in Enum.GetValues(typeof(Alignment)))
* foreach (Alignment tlla in Enum.GetValues(typeof(Alignment)))
* foreach (TicksLabelsRotation tlr in Enum.GetValues(typeof(TicksLabelsRotation)))
* try
* {
* AxisTestBitmap(p, "Title", ap, tp, ta, tlp, tla, tlla, tlr);
* }
* catch
* { }*/
/*dataX = new double[11];
* dataY1 = new double[dataX.Length];
* dataY2 = new double[dataX.Length];
* for (int i = 0; i < dataX.Length; i++)
* {
* dataX[i] = i - 5;
* dataY1[i] = 25 - dataX[i] * dataX[i];
* dataY2[i] = 25 - (dataX[i] - 2) * (dataX[i] - 2);
* }
*
* p.Clear();
* plot0 = p.Add(dataX, dataY1);
* plot0.LineStyle = Data.LineStyle.None;
* plot0.BarStyle = Data.BarStyle.Vertical;
* plot0.BarDuty = 1.0f;
* plot0.BarFillColor = Color.Red;
*
* plot1 = p.Add(dataX, dataY2);
* plot1.LineStyle = Data.LineStyle.None;
* plot1.BarStyle = Data.BarStyle.Vertical;
* plot1.BarDuty = 1.0f;
* plot1.BarFillColor = Color.Blue;
*
* p.ToImage().Save("Bar_Vertical_Fill.png");
*
* plot0.BarStacking = true;
* plot1.BarStacking = true;
* p.ToImage().Save("Bar_Vertical_Stacking_Fill.png");
*
* plot0.BarDuty = 0.5f;
* plot1.BarDuty = 0.5f;
* p.ToImage().Save("Bar_Vertical_Stacking_Duty_Fill.png");
*
*
* plot0.BarFillColor = Color.FromArgb(0, 0, 0,0);
* plot1.BarFillColor = Color.FromArgb(0, 0, 0, 0);
* plot0.BarLineColor = Color.Red;
* plot1.BarLineColor = Color.Blue;
* p.ToImage().Save("Bar_Vertical_Stacking_Duty_Line.png");
*
*
*
* p.Clear();
* plot0 = p.Add(dataY1, dataX);
* plot0.LineStyle = Data.LineStyle.None;
* plot0.BarStyle = Data.BarStyle.Horisontal;
* plot0.BarDuty = 1.0f;
* plot0.BarFillColor = Color.Red;
*
* plot1 = p.Add(dataY2, dataX);
* plot1.LineStyle = Data.LineStyle.None;
* plot1.BarStyle = Data.BarStyle.Horisontal;
* plot1.BarDuty = 1.0f;
* plot1.BarFillColor = Color.Blue;
*
* p.ToImage().Save("Bar_Horisontal_Fill.png");
*
* plot0.BarStacking = true;
* plot1.BarStacking = true;
* p.ToImage().Save("Bar_Horisontal_Stacking_Fill.png");
*
* plot0.BarDuty = 0.5f;
* plot1.BarDuty = 0.5f;
* p.ToImage().Save("Bar_Horisontal_Stacking_Duty_Fill.png");
*
*
* plot0.BarFillColor = Color.FromArgb(0, 0, 0, 0);
* plot1.BarFillColor = Color.FromArgb(0, 0, 0, 0);
* plot0.BarLineColor = Color.Red;
* plot1.BarLineColor = Color.Blue;
* p.ToImage().Save("Bar_Horisontal_Stacking_Duty_Line.png");
*
* p.Clear();
* double[] sinX = new double[100];
* double[] sinY1 = new double[sinX.Length];
* double[] sinY2 = new double[sinX.Length];
* double[] sinY3 = new double[sinX.Length];
* double[] sinY4 = new double[sinX.Length];
* double[] sinY5 = new double[sinX.Length];
* double[] sinY6 = new double[sinX.Length];
* double[] sinY7 = new double[sinX.Length];
* double[] sinY8 = new double[sinX.Length];
* double[] sinY9 = new double[sinX.Length];
* double[] sinY11 = new double[sinX.Length];
* double[] sinY12 = new double[sinX.Length];
* double[] sinY13 = new double[sinX.Length];
* double[] sinY14 = new double[sinX.Length];
* double[] sinY15 = new double[sinX.Length];
* double[] sinY16 = new double[sinX.Length];
* double[] sinY17 = new double[sinX.Length];
* double[] sinY18 = new double[sinX.Length];
* double[] sinY19 = new double[sinX.Length];
*
* double f = 3;
* double dt = 2.0 / sinX.Length;
*
* for (int i = 0; i < sinX.Length; i++)
* {
* sinX[i] = (sinX.Length - 1 - i) * dt;
* sinY1[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.1;
* sinY2[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.2;
* sinY3[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.3;
* sinY4[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.4;
* sinY5[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.5;
* sinY6[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.6;
* sinY7[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.7;
* sinY8[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.8;
* sinY9[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 0.9;
* sinY11[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.1;
* sinY12[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.2;
* sinY13[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.3;
* sinY14[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.4;
* sinY15[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.5;
* sinY16[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.6;
* sinY17[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.7;
* sinY18[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.8;
* sinY19[i] = Math.Sin(2 * Math.PI * sinX[i] * f) + 1.9;
* }
*
* var pl1 = p.Add(sinX, sinY1, "Plot1");
* var pl2 = p.Add(sinX, sinY2, "Plot2");
* var pl3 = p.Add(sinX, sinY3, "Plot3");
* var pl4 = p.Add(sinX, sinY4, "Plot4");
* var pl5 = p.Add(sinX, sinY5, "Plot5Plot5Plot5");
* var pl6 = p.Add(sinX, sinY6, "Plot6");
* var pl7 = p.Add(sinX, sinY7, "Plot7");
* var pl8 = p.Add(sinX, sinY8, "Plot8");
* var pl9 = p.Add(sinX, sinY9, "Plot9");
* var pl11 = p.Add(sinX, sinY11, "Plot11");
* var pl12 = p.Add(sinX, sinY12, "Plot12");
* var pl13 = p.Add(sinX, sinY13, "Plot13");
* var pl14 = p.Add(sinX, sinY14, "Plot14");
* var pl15 = p.Add(sinX, sinY15, "Plot15");
* var pl16 = p.Add(sinX, sinY16, "Plot16");
* var pl17 = p.Add(sinX, sinY17, "Plot17");
* var pl18 = p.Add(sinX, sinY18, "Plot18");
* var pl19 = p.Add(sinX, sinY19, "Plot19");
*
* pl1.BarStyle = Data.BarStyle.Vertical;
* pl1.BarFillColor = Color.Red;
* pl2.MarkStyle = Data.MarkerStyle.SolidCircle;
* pl3.LineStyle = Data.LineStyle.Dash;
* pl4.LineStyle = Data.LineStyle.DashDot;
* pl5.LineStyle = Data.LineStyle.DashDotDot;
* pl6.LineStyle = Data.LineStyle.Dot;
*
* p.LegendStyle = LegendStyle.Outside;
* p.LegendPosition = LegendPosition.Top; p.ToImage().Save("Legend_Outside_Top.png");
* p.LegendPosition = LegendPosition.Bottom; p.ToImage().Save("Legend_Outside_Bottom.png");
* p.LegendPosition = LegendPosition.Left; p.ToImage().Save("Legend_Outside_Left.png");
* p.LegendPosition = LegendPosition.Right; p.ToImage().Save("Legend_Outside_Right.png");
*
* p.LegendStyle = LegendStyle.Inside;
* p.LegendAlign = LegendAlign.Near;
* p.LegendPosition = LegendPosition.Top; p.ToImage().Save("Legend_Inside_Near_Top.png");
* p.LegendPosition = LegendPosition.Bottom; p.ToImage().Save("Legend_Inside_Near_Bottom.png");
* p.LegendPosition = LegendPosition.Left; p.ToImage().Save("Legend_Inside_Near_Left.png");
* p.LegendPosition = LegendPosition.Right; p.ToImage().Save("Legend_Inside_Near_Right.png");
*
* p.LegendStyle = LegendStyle.Inside;
* p.LegendAlign = LegendAlign.Center;
* p.LegendPosition = LegendPosition.Top; p.ToImage().Save("Legend_Inside_Center_Top.png");
* p.LegendPosition = LegendPosition.Bottom; p.ToImage().Save("Legend_Inside_Center_Bottom.png");
* p.LegendPosition = LegendPosition.Left; p.ToImage().Save("Legend_Inside_Center_Left.png");
* p.LegendPosition = LegendPosition.Right; p.ToImage().Save("Legend_Inside_Center_Right.png");
*
* p.LegendStyle = LegendStyle.Inside;
* p.LegendAlign = LegendAlign.Far;
* p.LegendPosition = LegendPosition.Top; p.ToImage().Save("Legend_Inside_Far_Top.png");
* p.LegendPosition = LegendPosition.Bottom; p.ToImage().Save("Legend_Inside_Far_Bottom.png");
* p.LegendPosition = LegendPosition.Left; p.ToImage().Save("Legend_Inside_Far_Left.png");
* p.LegendPosition = LegendPosition.Right; p.ToImage().Save("Legend_Inside_Far_Right.png");*/
Application.Run(new Form1());
}
private Result Calculate(Tab tab)
{
var resultTable = new decimal?[4, 2];
//------ input data -------
var jobPalette = tab.DurationByWork;
var mashines = GenerateInputMashines(tab.DeviceProductivities);
//-------- get chains ----------
List <List <int> > chains = ChainsAlgorithm.GetChains(jobPalette);
//------ get jobsScheduling -------
decimal C_1;
decimal?Cmax1;
var jobsScheduling1 = ScheduleAlgorithm.BuildedSchedule(chains, mashines, AlgorithmType.A1, out C_1, out Cmax1);
decimal C_2;
decimal?Cmax2;
var jobsScheduling2 = ScheduleAlgorithm.BuildedSchedule(chains, mashines, AlgorithmType.A2, out C_2, out Cmax2);
decimal C_3;
decimal?Cmax3;
var jobsScheduling3 = ScheduleAlgorithm.BuildedSchedule(chains, mashines, AlgorithmType.A3, out C_3, out Cmax3);
decimal C_4;
decimal?Cmax4;
var jobsScheduling4 = ScheduleAlgorithm.BuildedSchedule(chains, mashines, AlgorithmType.A4, out C_4, out Cmax4);
//----- for result --------
var ChainResult = new decimal[tab.DurationByWork.GetLength(0) * tab.DurationByWork.GetLength(1), 2];
var index = 0;
var chainNumber = 1;
foreach (var job in chains)
{
decimal currentNum = chainNumber;
foreach (var jobDuration in job)
{
currentNum += .1m;
ChainResult[index, 0] = currentNum;
ChainResult[index, 1] = decimal.Round(jobDuration, 0);
index++;
}
chainNumber++;
}
var plot1 = new Plot();
foreach (var val in jobsScheduling1)
{
plot1.Add(val.Key, val.Value);
}
var plot2 = new Plot();
foreach (var val in jobsScheduling2)
{
plot2.Add(val.Key, val.Value);
}
var plot3 = new Plot();
foreach (var val in jobsScheduling3)
{
plot3.Add(val.Key, val.Value);
}
var plot4 = new Plot();
foreach (var val in jobsScheduling4)
{
plot4.Add(val.Key, val.Value);
}
return(new Result
{
Chain = ChainResult,
AlgorithSummaries = new AlgorithSummary[]
{
new AlgorithSummary
{
Type = AlgorithmType.A1,
Cstar = decimal.Round(C_1, 2),
Cmax = decimal.Round((decimal)Cmax1, 2)
},
new AlgorithSummary
{
Type = AlgorithmType.A2,
Cstar = decimal.Round(C_2, 2),
Cmax = decimal.Round((decimal)Cmax2, 2)
},
new AlgorithSummary
{
Type = AlgorithmType.A3,
Cstar = decimal.Round(C_3, 2),
Cmax = decimal.Round((decimal)Cmax3, 2)
},
new AlgorithSummary
{
Type = AlgorithmType.A4,
Cstar = decimal.Round(C_4, 2),
Cmax = decimal.Round((decimal)Cmax4, 2)
},
},
PlotData = new Dictionary <AlgorithmType, Plot>
{
{ AlgorithmType.A1,
plot1 },
{ AlgorithmType.A2,
plot2 },
{ AlgorithmType.A3,
plot3 },
{ AlgorithmType.A4,
plot4 },
}
});
}