public void initXSPCFunctions()
{
SPCFunctions sPCFunctions = new SPCFunctions();
sPCFunctions.setHistogramGroupNumber(this.SamplesByGroup.Length);
this.MeaninSampleGroup = new double[this.SamplesByGroup.Length];
this.RangeinSampleGroup = new double[this.SamplesByGroup.Length];
this.StddevSampleGroup = new double[this.SamplesByGroup.Length];
for (int i = 0; i < this.SamplesByGroup.Length; i++)
{
sPCFunctions.setSamples(this.SamplesByGroup[i]);
this.MeaninSampleGroup[i] = sPCFunctions.SPCMean();
this.RangeinSampleGroup[i] = sPCFunctions.SPCRange();
this.StddevSampleGroup[i] = sPCFunctions.SPCStdDev();
}
sPCFunctions.setSamples(this.MeaninSampleGroup);
this.Mean = sPCFunctions.SPCMean();
sPCFunctions.setSamples(this.RangeinSampleGroup);
this.Range = sPCFunctions.SPCRange();
sPCFunctions.setSamples(this.StddevSampleGroup);
this.Stddev = sPCFunctions.SPCStdDev();
this.XrCL = this.Mean;
double CLdiffer = (3.0 / (Math.Sqrt((double) this.SamplesByGroup[0].Length) * this.d2[this.SamplesByGroup[0].Length - 1])) * this.Range;
this.XrUCL = this.Mean + CLdiffer;
this.XrLCL = this.Mean - CLdiffer;
this.RangeCL = this.Range;
double d3byd2 = (3.0 * this.d3[this.SamplesByGroup[0].Length - 1]) / this.d2[this.SamplesByGroup[0].Length - 1];
this.RangeUCL = (1.0 + d3byd2) * this.Range;
this.RangeLCL = Math.Max((double) ((1.0 - d3byd2) * this.Range), (double) 0.0);
this.XsCL = this.Mean;
double a3s = (3.0 / (Math.Sqrt((double) this.SamplesByGroup[0].Length) * this.c4[this.SamplesByGroup[0].Length - 1])) * this.Stddev;
this.XsUCL = this.Mean + a3s;
this.XsLCL = this.Mean - a3s;
this.StddevCL = this.Stddev;
double b3b4 = (3.0 * Math.Sqrt(1.0 - Math.Pow(this.c4[this.SamplesByGroup[0].Length - 1], 2.0))) / this.c4[this.SamplesByGroup[0].Length - 1];
this.StddevUCL = this.Stddev * (1.0 + b3b4);
this.StddevLCL = Math.Max((double) (this.Stddev * (1.0 - b3b4)), (double) 0.0);
}
private void SPCFunction(HttpContext context)
{
DataTable spcindex = new DataTable();
if (spcindex.Columns.Count < 1)
{
DataColumn fds = new DataColumn("Source", Type.GetType("System.String"));
DataColumn fmean = new DataColumn("Mean", Type.GetType("System.String"));
DataColumn frange = new DataColumn("Range", Type.GetType("System.String"));
DataColumn fstd = new DataColumn("STD", Type.GetType("System.String"));
DataColumn fcp = new DataColumn("Cp", Type.GetType("System.String"));
DataColumn fcpk = new DataColumn("Cpk", Type.GetType("System.String"));
DataColumn fucl = new DataColumn("Ucl", Type.GetType("System.String"));
DataColumn flcl = new DataColumn("Lcl", Type.GetType("System.String"));
spcindex.Dispose();
spcindex.Columns.Add(fds);
spcindex.Columns.Add(fstd);
spcindex.Columns.Add(fmean);
spcindex.Columns.Add(frange);
spcindex.Columns.Add(fcp);
spcindex.Columns.Add(fcpk);
spcindex.Columns.Add(fucl);
spcindex.Columns.Add(flcl);
}
var parameters = getParameters(context.Request);
double[] datalist = new double[parameters.Count-4];
for (int i = 0; i < parameters.Count - 4; i++)
{
datalist[i] = Convert.ToDouble(parameters[i+1].Substring(parameters[i+1].IndexOf(',') + 1));
}
double USL = Convert.ToDouble(parameters["KEY[USL]"]);
double LSL =Convert.ToDouble( parameters["KEY[LSL]"]);
SPCFunctions ar = new SPCFunctions(datalist, USL, LSL);
double range = ar.SPCMax() - ar.SPCMin();
DataRow ind = spcindex.NewRow();
ind["Source"] = parameters["KEY[DS]"];
ind["Cp"] = ar.SPCCp().ToString("f2");
ind["Cpk"] = ar.SPCCpk().ToString("f2");
ind["Mean"] = ar.SPCMean().ToString("f2");
ind["Range"] = range.ToString("f2");
ind["STD"] = ar.SPCStdDev().ToString("f2");
ar.XbarChart();
ind["Ucl"] = ar.getUCL().ToString("f2");
ind["Lcl"] = ar.getLCL().ToString("f2");
spcindex.Rows.Add(ind);
// double[][] a = ar.HistogramStepUpperLowerMidCountNormCumu();
string result = Dtb2Json(spcindex);
context.Response.ContentType = "text/plain";
context.Response.Write(result);
}
