public static double[] AntiSpike(DataPointCollection points, double num = 4)
{
double disp = Statistics.CalcRMS(points);
double mean = Statistics.CalcAVG(points);
double[] values = points.Select(y => y.YValues[0]).ToArray();
for (int i = 0; i < values.Length; i++)
{
if (values[i] > mean + Math.Sqrt(num * disp) || values[i] < -(mean + Math.Sqrt(num * disp)))
{
if (i != 0 && i != values.Length - 1)
{
values[i] = (values[i - 1] + values[i + 1]) / 2;
}
else if (i == 0)
{
values[i] = (values[i + 1] + values[i + 2]) / 2;
}
else
{
values[i] = (values[i - 1] + values[i - 2]) / 2;
}
}
}
return(values);
}
public static void AntiShift(DataPointCollection points)
{
double c = Statistics.CalcAVG(points);
foreach (var point in points)
{
point.YValues[0] -= c;
}
}
public void Kurs_Model()
{
//x(t) = c * exp((µ – σ2 / 2) * t + σ * r(t))
//где c – положительная константа > 1,
//r(t) - случайный процесс например в интервале[0, c],
//µ -среднее значение r(t), σ – стандартное отклонение r(t).
//double[] data = new double[5000];
double[] data = Parser.GetData("DataSheet.txt");
pointsClear();
double c = 0.015;
Random r = new Random(5);
for (int i = 0; i < data.Length; i++)
{
data[i] = r.NextDouble() * c;
}
double avg = Statistics.CalcAVG(data);
double sigma = Math.Sqrt(Statistics.CalcDispersion(data));
mainTitle.Text = "Model";
foreach (var area in chart.ChartAreas)
{
area.AxisX.Maximum = data.Length;
area.AxisX.Minimum = 0;
}
foreach (var series in chart.Series)
{
series.Points.SuspendUpdates();
}
//fill top left series
titleTopLeft.Text = "Input Random [0, " + c + "]";
seriesTopLeft.ChartType = SeriesChartType.Spline;
seriesTopLeft.BorderDashStyle = ChartDashStyle.Solid;
Plots.minX = 0;
Plots.maxX = data.Length;
//x(t) = c * exp((avg – sigma^2 / 2) * i + sigma * data(i))
for (int i = 0; i < data.Length; i++)
{
seriesTopLeft.Points.AddXY(i, c * Math.Pow(Math.E, ((avg - Math.Pow(sigma, 2) / 2) * i + sigma * data[i])));
}
messageTopLeft = Statistics.GetStatistics(seriesTopLeft.Points);
data = seriesTopLeft.Points.Select(y => y.YValues[0]).ToArray();
//fill top right series
titleTopRight.Text = "AntiTrend Input";
seriesTopRight.ChartType = SeriesChartType.FastLine;
seriesTopRight.BorderDashStyle = ChartDashStyle.Solid;
double[] output = Plots.Antitrend(data);
for (int i = 0; i < data.Length; i++)
{
seriesTopRight.Points.AddXY(i, output[i]);
}
messageTopRight = Statistics.GetStatistics(seriesTopRight.Points);
//fill bottom left series
titleBottomLeft.Text = "AntiSpike Input";
seriesBottomLeft.ChartType = SeriesChartType.FastLine;
seriesBottomLeft.BorderDashStyle = ChartDashStyle.Solid;
output = Plots.AntiSpike(seriesTopRight.Points, 4);
for (int i = 0; i < output.Length; i++)
{
seriesBottomLeft.Points.AddXY(i, output[i]);
}
messageBottomLeft = Statistics.GetStatistics(seriesBottomLeft.Points);
//fill bottom right series
titleBottomRight.Text = "Auto Correlation";
seriesBottomRight.ChartType = SeriesChartType.FastLine;
seriesBottomRight.BorderDashStyle = ChartDashStyle.Solid;
Plots.AutoCrossCorrelation(seriesBottomRight.Points, seriesTopRight.Points, seriesTopRight.Points);
messageBottomRight = "";
}
public void Kurs_Model_My()
{
double[] data_real = Parser.GetData("DataSheet.txt");
double[] data = new double[data_real.Length];
for (int i = 0; i < data_real.Length; i++)
{
data[i] = data_real[i];
}
pointsClear();
Random r = new Random(555555);
data[0] = 0;
double rand = 0;
for (int i = 1; i < data.Length; i++)
{
rand = r.NextDouble();
if (rand > 0.5)
{
data[i] = data[i - 1] + r.NextDouble();
}
else
{
data[i] = data[i - 1] - r.NextDouble();
}
}
for (int i = 0; i < data.Length; i++)
{
data[i] = -data[i];
}
//replce first part with another randomization
for (int i = 0; i < 400; i++)
{
rand = r.NextDouble();
if (rand > 0.8)
{
data[i] = data[401] + r.NextDouble();
}
else if (rand > 0.7)
{
data[i] = data[401] - r.NextDouble();
}
else
{
data[i] = data[i - 1];
}
}
//scale model to real
double scale = 0;
for (int i = 0; i < data.Length; i++)
{
scale += data_real[i] / data[i];
}
scale = scale / data.Length;
for (int i = 0; i < data.Length; i++)
{
data[i] *= scale;
}
double avg = Statistics.CalcAVG(data);
double sigma = Math.Sqrt(Statistics.CalcDispersion(data));
mainTitle.Text = "Model";
foreach (var area in chart.ChartAreas)
{
area.AxisX.Maximum = data.Length;
area.AxisX.Minimum = 0;
}
foreach (var series in chart.Series)
{
series.Points.SuspendUpdates();
}
//fill top left series
titleTopLeft.Text = "Input Random";
seriesTopLeft.ChartType = SeriesChartType.Spline;
seriesTopLeft.BorderDashStyle = ChartDashStyle.Solid;
Plots.minX = 0;
Plots.maxX = data.Length;
for (int i = 0; i < data.Length; i++)
{
seriesTopLeft.Points.AddXY(i, data[i]);
}
messageTopLeft = Statistics.GetStatistics(seriesTopLeft.Points);
data = seriesTopLeft.Points.Select(y => y.YValues[0]).ToArray();
//fill top right series
titleTopRight.Text = "AntiTrend Input";
seriesTopRight.ChartType = SeriesChartType.FastLine;
seriesTopRight.BorderDashStyle = ChartDashStyle.Solid;
double[] output = Plots.Antitrend(data);
for (int i = 0; i < data.Length; i++)
{
seriesTopRight.Points.AddXY(i, output[i]);
}
messageTopRight = Statistics.GetStatistics(seriesTopRight.Points);
//fill bottom left series
titleBottomLeft.Text = "AntiSpike Input";
seriesBottomLeft.ChartType = SeriesChartType.FastLine;
seriesBottomLeft.BorderDashStyle = ChartDashStyle.Solid;
output = Plots.AntiSpike(seriesTopRight.Points, 4);
for (int i = 0; i < output.Length; i++)
{
seriesBottomLeft.Points.AddXY(i, output[i]);
}
messageBottomLeft = Statistics.GetStatistics(seriesBottomLeft.Points);
//fill bottom right series
titleBottomRight.Text = "Auto Correlation";
seriesBottomRight.ChartType = SeriesChartType.FastLine;
seriesBottomRight.BorderDashStyle = ChartDashStyle.Solid;
Plots.AutoCrossCorrelation(seriesBottomRight.Points, seriesTopRight.Points, seriesTopRight.Points);
messageBottomRight = "";
}