public NormalDistributionInfo GetNormalDistributionFitWithNumOfSamePoints(int index)
{
PR.SetData(PD.GetDataArr());
if (PR is INormalDistributionFit)
{
return(PR.GetNormalDistributionFitWithNumOfSamePoints(index));
}
NormalDistributionInfo n = new NormalDistributionInfo();
n.mean = -1;
n.SD = -1;
return(n);
}
public NormalDistributionInfo GetPeakNormalDistribution(double peak, int index, int numOfPoints)
{
NormalDistributionInfo Info = new NormalDistributionInfo();
List <double> ls = new List <double>();
Dictionary <double, int> dict = CalculateTimesEachX(index);
double[] keyArr = dict.Keys.ToArray();
int i = 0;
for (i = 0; i < keyArr.Length; i++)
{
if (keyArr[i] == peak)
{
break;
}
}
for (int j = i - numOfPoints; j < i; j++)
{
if (j < 0)
{
j = 0;
}
int value = dict[keyArr[j]];
for (int k = 0; k < value; k++)
{
ls.Add(keyArr[j]);
}
}
for (int j = i; j < i + numOfPoints + 1; j++)
{
if (j >= keyArr.Length)
{
break;
}
int value = dict[keyArr[j]];
for (int k = 0; k < value; k++)
{
ls.Add(keyArr[j]);
}
}
NormalDistribution ND = new NormalDistribution();
ND.Fit(ls.ToArray());
Info.mean = ND.Mean;
Info.SD = ND.StandardDeviation;
return(Info);
}
public NormalDistributionInfo GetNormalDistributionFitWithNumOfSamePoints(int index)
{
NormalDistributionInfo Info = new NormalDistributionInfo();
int length = MD.Length;
double[] arr = new double[length];
for (int i = 0; i < length; i++)
{
arr[i] = MD[i].GetParameters()[index];
}
NormalDistribution ND = new NormalDistribution();
ND.Fit(arr);
Info.mean = ND.Mean;
Info.SD = ND.StandardDeviation;
return(Info);
}
private void drawButton_Click(object sender, EventArgs e)
{
string algorName = algorithmsAndResult.GetCurrentAlgorithm();
GraphChart.Series["dataPoints"].Points.Clear();
GraphChart.Series["predictGraph"].Points.Clear();
GraphChart.Series["NormalFit"].Points.Clear();
GraphChart.Series["Peaks"].Points.Clear();
GraphChart.Series["NormalFitPeak1"].Points.Clear();
GraphChart.Series["NormalFitPeak2"].Points.Clear();
double numOfData = 0;
points[] dataPoints = algorithmsAndResult.GetPoints();
if (dataPoints == null)
{
return;
}
for (int i = 0; i < dataPoints.Length; i++)
{
GraphChart.Series["dataPoints"].Points.AddXY(dataPoints[i].x, dataPoints[i].y);
numOfData = numOfData + dataPoints[i].y;
}
GraphChart.Series["dataPoints"].Color = Color.Red;
double startX = dataPoints[0].x;
double endX = dataPoints[dataPoints.Length - 1].x;
int numOfTestPoints = dataPoints.Length * 10;
double diff = (endX - startX) / numOfTestPoints;
if (algorName == "Normal Distribution Fit")
{
NormalDistributionInfo ndi = algorithmsAndResult.GetNDinfo();
if (ndi.SD != -1 && ndi.mean != -1)
{
// double rate = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((ndi.mean - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
// rate = ndi.mean / rate;
for (int i = 0; i <= numOfTestPoints; i++)
{
double testX = startX + i * diff;
double testY = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((testX - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
testY = testY * numOfData;
GraphChart.Series["NormalFit"].Points.AddXY(testX, testY);
}
GraphChart.Series["NormalFit"].Color = Color.Green;
}
}
else if (algorName == "Polynomial Fit")
{
double[,] paramsResult = algorithmsAndResult.GetEquationParmas();
if (paramsResult == null)
{
return;
}
for (int i = 0; i <= numOfTestPoints; i++)
{
double testX = startX + i * diff;
double testY = 0;
for (int j = 0; j < paramsResult.GetLength(0); j++)
{
testY = testY + Math.Pow(testX, j) * paramsResult[j, 0];
}
GraphChart.Series["predictGraph"].Points.AddXY(testX, testY);
}
GraphChart.Series["predictGraph"].Color = Color.Blue;
}
else if (algorName == "Peak" || algorName == "Two Peaks")
{
points[] pts = algorithmsAndResult.GetPeakPoints();
foreach (var pt in pts)
{
GraphChart.Series["Peaks"].Points.AddXY(pt.x, pt.y);
}
GraphChart.Series["Peaks"].Color = Color.Purple;
}
if (algorName == "Two Peaks")
{
TwoDictInfo TDinfo = algorithmsAndResult.GetTDinfo();
NormalDistributionInfo ndi = TDinfo.peak1Info;
if (TDinfo.peak1value == -1 || TDinfo.peak2value == -1)
{
return;
}
double y = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((TDinfo.peak1value - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
double rate = TDinfo.peak1times / y;
if (ndi.SD != -1 && ndi.mean != -1)
{
for (int i = 0; i < TDinfo.peak2value; i++)
{
double testX = i;
double testY = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((testX - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
testY = testY * rate;
GraphChart.Series["NormalFitPeak1"].Points.AddXY(testX, testY);
}
GraphChart.Series["NormalFitPeak1"].Color = Color.Green;
}
ndi = TDinfo.peak2Info;
y = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((TDinfo.peak2value - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
rate = TDinfo.peak2times / y;
if (ndi.SD != -1 && ndi.mean != -1)
{
for (int i = (int)TDinfo.peak1value; i < TDinfo.last; i++)
{
double testX = i;
double testY = (1 / (ndi.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((testX - ndi.mean), 2) / (2 * Math.Pow(ndi.SD, 2)));
testY = testY * rate;
GraphChart.Series["NormalFitPeak2"].Points.AddXY(testX, testY);
}
GraphChart.Series["NormalFitPeak2"].Color = Color.Red;
}
}
if (algorithmsAndResult.GetCurrentAlgorithm() != "Two Peaks")
{
algorithmsAndResult.clear();
}
}
private void GetResultButton_Click(object sender, EventArgs e)
{
Settings.Default["AlgorName"] = label3.Text;
ResultBox.Items.Clear();
if (label3.Text == "Statics")
{
if (!(PF is Istatics))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
Settings.Default["Parameter"] = textBox1.Text;
int numOfParmas = PF.GetData()[0].GetNumOfParams();
double mean, sd;
for (int i = 0; i < numOfParmas; i++)
{
mean = PF.GetMean(i);
ResultBox.Items.Add("Mean of param " + i + ": " + mean);
sd = PF.GetStandardDeviation(i);
ResultBox.Items.Add("StandardDeviation of param " + i + ": " + sd);
if (textBox1.Text != "")
{
double number = Double.Parse(textBox1.Text);
double Threshold = PF.GetThreshold(number);
ResultBox.Items.Add("Threshold of param " + i + ": " + Threshold);
ResultBox.Items.Add("");
}
}
}
else if (label3.Text == "Peak")
{
if (!(PF is Ipeek))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
if (XaxiscomboBox.Text == "" && YaxiscomboBox.Text == "")
{
return;
}
sortData();
Settings.Default["NumOfPoints"] = numBox.Text;
Settings.Default["Range"] = rangeBox.Text;
if (YaxiscomboBox.Text.Contains("#"))
{
string text = YaxiscomboBox.Text.Substring(10).Trim();
int num = Int32.Parse(text);
int numOfpoints = 3;
double percentage = 0.2;
if (numBox.Text != "")
{
numOfpoints = Int32.Parse(numBox.Text);
}
if (rangeBox.Text != "")
{
percentage = double.Parse(rangeBox.Text);
}
dataDict = PF.CalculateTimesEachX(num);
List <PeekValleyData> peaks = PF.GetPeaksWithNumOfSamePoints(num, numOfpoints, percentage);
peaksData = peaks;
/*
* for (int i = 0; i < PF.GetData().Length; i++)
* {
* ResultBox.Items.Add(PF.GetData()[i].WriteToLine());
* }*/
if (peaksData.Count() == 0)
{
ResultBox.Items.Add("No Peak found yet.");
}
foreach (var item in peaks)
{
ResultBox.Items.Add("Peak Value: " + item.value + " Times: " + item.times);
}
}
else if (YaxiscomboBox.Text != "")
{
string text = YaxiscomboBox.Text.Substring(5).Trim();
int Yindex = Int32.Parse(text);
// MessageBox.Show(Yindex.ToString());
int numOfpoints = 3;
double percentage = 0.2;
if (numBox.Text != "")
{
numOfpoints = Int32.Parse(numBox.Text);
}
if (rangeBox.Text != "")
{
percentage = double.Parse(rangeBox.Text);
}
text = XaxiscomboBox.Text.Substring(5).Trim();
int Xindex;
if (XaxiscomboBox.Text.Contains("TimeSpan"))
{
Xindex = -1;
}
else
{
Xindex = Int32.Parse(text);
}
MyData[] MD = PF.GetData();
dataPoints = new points[MD.Count()];
for (int i = 0; i < MD.Count(); i++)
{
dataPoints[i].x = MD[i].GetParameters()[Xindex];
dataPoints[i].y = MD[i].GetParameters()[Yindex];
}
List <PeekValleyData> peaks = PF.GetPeaksWithXY(Yindex, Xindex, numOfpoints, percentage);
peaksData = peaks;
/*
* for (int i = 0; i < PF.GetData().Length; i++)
* {
* ResultBox.Items.Add(PF.GetData()[i].WriteToLine());
* }
* */
foreach (var item in peaks)
{
ResultBox.Items.Add("X: " + item.x + " Y: " + item.y);
}
}
}
else if (label3.Text == "Polynomial Fit")
{
if (!(PF is Ipolyfit))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
if (XaxiscomboBox.Text == "" && YaxiscomboBox.Text == "")
{
return;
}
sortData();
int power = 1;
if (powerBox.Text != "")
{
power = Int32.Parse(powerBox.Text);
}
if (YaxiscomboBox.Text.Contains("#"))
{
string text = YaxiscomboBox.Text.Substring(10).Trim();
int num = Int32.Parse(text);
Dictionary <double, int> dict = PF.CalculateTimesEachX(num);
dataDict = dict;
double[,] x = new double[dict.Keys.Count(), power];
double[] keys = dict.Keys.ToArray();
for (int i = 0; i < dict.Keys.Count(); i++)
{
for (int j = 0; j < power; j++)
{
x[i, j] = Math.Pow(keys[i], j + 1);
}
}
double[] y = new double[keys.Length];
for (int i = 0; i < keys.Length; i++)
{
y[i] = dict[keys[i]];
}
double[,] result = PF.GetPolyFit(x, y, power);
paramsResult = result;
string r = "y=";
r = r + result[0, 0].ToString("#.000");
for (int i = 1; i <= power; i++)
{
r = r + "+ " + result[i, 0].ToString("#.000") + "x^" + i.ToString();
}
ResultBox.Items.Add(r);
}
else if (YaxiscomboBox.Text != "")
{
string text = YaxiscomboBox.Text.Substring(5).Trim();
int Yindex = Int32.Parse(text);
int Xindex;
if (XaxiscomboBox.Text.Contains("TimeSpan"))
{
MessageBox.Show("We have not support Timespan in this algorithm yet.");
return;
}
else
{
text = XaxiscomboBox.Text.Substring(5).Trim();
Xindex = Int32.Parse(text);
}
MyData[] MD = PF.GetData();
dataPoints = new points[MD.Count()];
double[,] x = new double[MD.Count(), power];
for (int i = 0; i < MD.Count(); i++)
{
dataPoints[i].x = MD[i].GetParameters()[Xindex];
for (int j = 0; j < power; j++)
{
x[i, j] = Math.Pow(MD[i].GetParameters()[Xindex], j + 1);
}
}
double[] y = new double[MD.Count()];
for (int i = 0; i < y.Length; i++)
{
y[i] = MD[i].GetParameters()[Yindex];
dataPoints[i].y = y[i];
}
double[,] result = PF.GetPolyFit(x, y, power);
paramsResult = result;
string r = "y=";
r = r + result[0, 0].ToString("#.000");
for (int i = 1; i <= power; i++)
{
r = r + "+ " + result[i, 0].ToString("#.000") + "x^" + i.ToString();
}
ResultBox.Items.Add(r);
}
if (xvalueBox.Text != "")
{
double x = Convert.ToDouble(xvalueBox.Text);
double y = 0;
for (int j = 0; j < paramsResult.GetLength(0); j++)
{
y = y + Math.Pow(x, j) * paramsResult[j, 0];
}
ResultBox.Items.Add("X-value: " + x.ToString("#.000") + " Y-value: " + y.ToString("#.000"));
Settings.Default["Xvalue"] = xvalueBox.Text;
}
Settings.Default["Power"] = powerBox.Text;
}
else if (label3.Text == "Normal Distribution Fit")
{
if (!(PF is INormalDistributionFit))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
if (XaxiscomboBox.Text == "" && YaxiscomboBox.Text == "")
{
return;
}
sortData();
/*
* for (int i = 0; i < PF.GetData().Length; i++)
* {
* ResultBox.Items.Add(PF.GetData()[i].WriteToLine());
* }*/
if (YaxiscomboBox.Text.Contains("#"))
{
string text = YaxiscomboBox.Text.Substring(10).Trim();
int num = Int32.Parse(text);
dataDict = PF.CalculateTimesEachX(num);
NormalDistributionInfo ndi = PF.GetNormalDistributionFitWithNumOfSamePoints(num);
NDinfo = ndi;
ResultBox.Items.Add("Mean: " + ndi.mean.ToString() + " SD: " + ndi.SD.ToString());
}
else
{
if (XaxiscomboBox.Text == "" || YaxiscomboBox.Text == "")
{
return;
}
string text = YaxiscomboBox.Text.Substring(5).Trim();
int Yindex = Int32.Parse(text);
int Xindex;
if (XaxiscomboBox.Text.Contains("TimeSpan"))
{
MessageBox.Show("We have not support Timespan in this algorithm yet.");
return;
}
else
{
text = XaxiscomboBox.Text.Substring(5).Trim();
Xindex = Int32.Parse(text);
}
MyData[] MD = PF.GetData();
dataPoints = new points[MD.Count()];
for (int i = 0; i < MD.Count(); i++)
{
dataPoints[i].x = MD[i].GetParameters()[Xindex];
dataPoints[i].y = MD[i].GetParameters()[Yindex];
}
int num = Int32.Parse(text);
dataDict = PF.CalculateTimesEachX(num);
NormalDistributionInfo ndi = PF.GetNormalDistributionFitWithNumOfSamePoints(num);
NDinfo = ndi;
ResultBox.Items.Add("Mean: " + ndi.mean.ToString() + " SD: " + ndi.SD.ToString());
}
if (xvalueBox.Text != "")
{
double x = Convert.ToDouble(xvalueBox.Text);
double y = 0;
y = (1 / (NDinfo.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x - NDinfo.mean), 2) / (2 * Math.Pow(NDinfo.SD, 2)));
int numberOfdata = 0;
foreach (var item in dataDict)
{
numberOfdata = numberOfdata + item.Value;
}
y = y * numberOfdata;
ResultBox.Items.Add("X-value: " + x.ToString("#.000") + " Y-value: " + y.ToString("#.000"));
Settings.Default["Xvalue"] = xvalueBox.Text;
}
}
else if (label3.Text == "Logistic Regression")
{
if (!(PF is ILogisticRegression))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
if (comboBox2.Text != "")
{
string text = comboBox2.Text.Substring(5).Trim();
int index = Int32.Parse(text);
dataDict = PF.CalculateTimesEachX(index);
double percentage = 0.1;
PF.SortData(index);
if (rangeBox.Text != "")
{
percentage = double.Parse(rangeBox.Text);
}
LogisticRegression LR = PF.GetLogisticRegressionParams(index, percentage);
LogisticInfo LI = new LogisticInfo();
LI.LogisticParams = new double[2];
LI.LogisticParams[0] = LR.Intercept;
LI.LogisticParams[1] = LR.GetOddsRatio(1) - 1;
ResultBox.Items.Add("Param0: " + LI.LogisticParams[0] + " Parma1: " + LI.LogisticParams[1]);
if (xvalueBox.Text != "")
{
double x = Convert.ToDouble(xvalueBox.Text);
double[] valueArr = new double[] { x, 0 };
ResultBox.Items.Add("Value: " + x + " Probability: " + LR.Probability(valueArr) + " Conclusion:" + LR.Decide(valueArr));
}
MyData[] MD = PF.GetData();
double threshold = -1;
/*
* for (int i = 0; i < MD.Length; i++)
* {
* double value = MD[i].GetParameters()[index];
* double[] valueArr = new double[] { value, 0 };
* ResultBox.Items.Add("Value: " + value + " Probability: " + LR.Probability(valueArr) + " Conclusion:" + LR.Decide(valueArr));
* }*/
Dictionary <double, int> lowerDict = new Dictionary <double, int>();
Dictionary <double, int> higherDict = new Dictionary <double, int>();
for (int i = 0; i < MD.Length; i++)
{
double value = MD[i].GetParameters()[index];
double[] valueArr = new double[] { value, 0 };
if (threshold == -1 && LR.Decide(valueArr) == true)
{
threshold = value;
}
if (threshold == -1)
{
if (lowerDict.ContainsKey(value))
{
lowerDict[value]++;
}
else
{
lowerDict.Add(value, 1);
}
}
else
{
if (higherDict.ContainsKey(value))
{
higherDict[value]++;
}
else
{
higherDict.Add(value, 1);
}
}
}
ResultBox.Items.Add("Threshold: " + threshold);
}
}
else if (label3.Text == "Two Peaks")
{
if (!(PF is Ipeek))
{
MessageBox.Show("Production Facade doesn't have this interface yet");
return;
}
if (peak1Box.Text != "" && peak2Box.Text != "")
{
string text = YaxiscomboBox.Text.Substring(10).Trim();
int index = Int32.Parse(text);
double peak1 = Convert.ToDouble(peak1Box.Text);
double peak2 = Convert.ToDouble(peak2Box.Text);
int numOfpoints = 5;
if (numBox.Text != "")
{
numOfpoints = Int32.Parse(numBox.Text);
}
NormalDistributionInfo peak1Info = PF.GetPeakNormalDistribution(peak1, index, numOfpoints);
ResultBox.Items.Add("Mean: " + peak1Info.mean.ToString("#.000") + " SD: " + peak1Info.SD.ToString("#.000"));
NormalDistributionInfo peak2Info = PF.GetPeakNormalDistribution(peak2, index, numOfpoints);
ResultBox.Items.Add("Mean: " + peak2Info.mean.ToString("#.000") + " SD: " + peak2Info.SD.ToString("#.000"));
if (xvalueBox.Text != "")
{
double x = Convert.ToDouble(xvalueBox.Text);
double end = 0;
double y = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
if (y < 0.01)
{
double x1 = x - 1;
double y1 = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x1 - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
if (y1 < y)
{
end = x1;
}
else
{
end = x + 1;
}
}
else
{
double x1 = x - 1;
double y1 = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x1 - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
if (y1 < y)
{
end = x1;
while (y1 > 0.01)
{
end--;
y1 = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
}
}
else
{
end = x + 1;
y1 = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
while (y1 > 0.01)
{
end++;
y1 = (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
}
}
}
Func <double, double> f1 = (a) => (1 / (peak1Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((a - peak1Info.mean), 2) / (2 * Math.Pow(peak1Info.SD, 2)));
double result1 = MathNet.Numerics.Integration.NewtonCotesTrapeziumRule.IntegrateTwoPoint(f1, x, end);
if (x <= peak1)
{
result1 = 1 - Math.Abs(result1);
if (result1 > 1)
{
result1 = 1;
}
}
ResultBox.Items.Add("Probablity of keeping bad chips: " + Math.Abs(result1).ToString("#.000"));
double end1 = 0;
y = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
if (y < 0.01)
{
double x1 = x - 1;
double y1 = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x1 - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
if (y1 < y)
{
end1 = x1;
}
else
{
end1 = x + 1;
}
}
else
{
double x1 = x - 1;
double y1 = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((x1 - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
if (y1 < y)
{
end1 = x1;
while (y1 > 0.01)
{
end1--;
y1 = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end1 - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
}
}
else
{
end1 = x + 1;
y1 = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end1 - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
while (y1 > 0.01)
{
end1++;
y1 = (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((end1 - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
}
}
}
Func <double, double> f2 = (a) => (1 / (peak2Info.SD * Math.Sqrt(2 * Math.PI))) * Math.Exp(-Math.Pow((a - peak2Info.mean), 2) / (2 * Math.Pow(peak2Info.SD, 2)));
double result2 = MathNet.Numerics.Integration.NewtonCotesTrapeziumRule.IntegrateTwoPoint(f2, x, end1);
if (x >= peak2)
{
result2 = 1 - Math.Abs(result2);
if (result2 > 1)
{
result2 = 1;
}
}
ResultBox.Items.Add("probability of losing good chips: " + Math.Abs(result2).ToString("#.000"));
}
dataDict = PF.CalculateTimesEachX(index);
TDinfo = new TwoDictInfo();
TDinfo.peak1Info = peak1Info;
TDinfo.peak2Info = peak2Info;
TDinfo.peak1value = peak1;
TDinfo.peak2value = peak2;
TDinfo.peak1times = dataDict[peak1];
TDinfo.peak2times = dataDict[peak2];
TDinfo.last = dataDict.Keys.ToList().Last();
//peak1Box.Text = "";
// peak2Box.Text = "";
}
else
{
if (XaxiscomboBox.Text == "" && YaxiscomboBox.Text == "")
{
return;
}
sortData();
Settings.Default["NumOfPoints"] = numBox.Text;
Settings.Default["Range"] = rangeBox.Text;
if (YaxiscomboBox.Text.Contains("#"))
{
string text = YaxiscomboBox.Text.Substring(10).Trim();
int num = Int32.Parse(text);
int numOfpoints = 3;
double percentage = 0.2;
if (numBox.Text != "")
{
numOfpoints = Int32.Parse(numBox.Text);
}
if (rangeBox.Text != "")
{
percentage = double.Parse(rangeBox.Text);
}
dataDict = PF.CalculateTimesEachX(num);
List <PeekValleyData> peaks = PF.GetPeaksWithNumOfSamePoints(num, numOfpoints, percentage);
peaksData = peaks;
/*
* for (int i = 0; i < PF.GetData().Length; i++)
* {
* ResultBox.Items.Add(PF.GetData()[i].WriteToLine());
* }*/
if (peaksData.Count() == 0)
{
ResultBox.Items.Add("No Peak found yet.");
}
foreach (var item in peaks)
{
ResultBox.Items.Add("Peak Value: " + item.value + " Times: " + item.times);
}
}
else if (YaxiscomboBox.Text != "")
{
string text = YaxiscomboBox.Text.Substring(5).Trim();
int Yindex = Int32.Parse(text);
// MessageBox.Show(Yindex.ToString());
int numOfpoints = 3;
double percentage = 0.2;
if (numBox.Text != "")
{
numOfpoints = Int32.Parse(numBox.Text);
}
if (rangeBox.Text != "")
{
percentage = double.Parse(rangeBox.Text);
}
text = XaxiscomboBox.Text.Substring(5).Trim();
int Xindex;
if (XaxiscomboBox.Text.Contains("TimeSpan"))
{
Xindex = -1;
}
else
{
Xindex = Int32.Parse(text);
}
MyData[] MD = PF.GetData();
dataPoints = new points[MD.Count()];
for (int i = 0; i < MD.Count(); i++)
{
dataPoints[i].x = MD[i].GetParameters()[Xindex];
dataPoints[i].y = MD[i].GetParameters()[Yindex];
}
List <PeekValleyData> peaks = PF.GetPeaksWithXY(Yindex, Xindex, numOfpoints, percentage);
peaksData = peaks;
/*
* for (int i = 0; i < PF.GetData().Length; i++)
* {
* ResultBox.Items.Add(PF.GetData()[i].WriteToLine());
* }
* */
foreach (var item in peaks)
{
ResultBox.Items.Add("X: " + item.x + " Y: " + item.y);
}
}
if (peaksData.Count() < 2)
{
ResultBox.Items.Add("We need at least two peaks in this algorithm");
}
else
{
peak1Box.Show();
peak2Box.Show();
label13.Show();
label12.Show();
xvalueBox.Show();
label10.Show();
peak1Box.Items.Clear();
peak2Box.Items.Clear();
points[] pts = GetPeakPoints();
foreach (var point in pts)
{
if (!peak1Box.Items.Contains(point.x))
{
peak1Box.Items.Add(point.x);
}
if (!peak2Box.Items.Contains(point.x))
{
peak2Box.Items.Add(point.x);
}
}
}
}
}
Settings.Default.Save();
}
