public ActionResult InputIntervalCalculation()
{
try
{
HttpFileCollectionBase files = Request.Files;
HttpPostedFileBase file = files[0];
string filename = file.FileName;
string savePath = Server.MapPath("/UploadExcel/") + filename;
file.SaveAs(savePath);
int s = filename.LastIndexOf(".");
var list_excels = ExcelHelper.ExcelToDataTable(savePath);
var eLower = list_excels.Select(x => x.Lower).ToArray();
var eProbability = list_excels.Select(x => x.Probability).ToArray();
var eStimulus = list_excels.Select(x => x.Stimulus).ToArray();
var eUpper = list_excels.Select(x => x.Upper).ToArray();
var econfidence = list_excels.Select(x => x.Confidence).ToArray();
LangleyPublic.aArray.Clear();
LangleyPublic.bArray.Clear();
LangleyPublic.cArray.Clear();
SideReturnData srd = new SideReturnData();
srd.responseProbability = eProbability;
srd.Y_Ceilings = eUpper;
srd.Y_LowerLimits = eLower;
srd.responsePoints = eStimulus;
double ceiling = srd.responsePoints.Min();
double lower = srd.responsePoints.Max();
for (int i = 0; i < srd.responseProbability.Length; i++)
{
LangleyPublic.aArray.Add("[" + srd.responsePoints[i] + "," + srd.responseProbability[i] + "]");
if (double.IsInfinity(srd.Y_Ceilings[i]))
{
LangleyPublic.bArray.Add("[" + lower + "," + srd.responseProbability[i] + "]");
}
else
{
LangleyPublic.bArray.Add("[" + srd.Y_Ceilings[i] + "," + srd.responseProbability[i] + "]");
}
if (double.IsInfinity(srd.Y_LowerLimits[i]))
{
LangleyPublic.cArray.Add("[" + ceiling + "," + srd.responseProbability[i] + "]");
}
else
{
LangleyPublic.cArray.Add("[" + srd.Y_LowerLimits[i] + "," + srd.responseProbability[i] + "]");
}
}
LangleyPublic.incredibleIntervalType = filename.Substring(0, s);
LangleyPublic.incredibleLevelName = econfidence[0].ToString();
}
catch (Exception ex)
{
return(Json(false));
}
return(Json(true));
}
public SideReturnData BatchIntervalCalculate(double Y_Ceiling, double Y_LowerLimit, int Y_PartitionNumber, double ConfidenceLevel, double favg, double fsigma, double[] xArray, int[] vArray, int intervalChoose)
{
SideReturnData sideReturnData = new SideReturnData();
double Y_ScaleLength = (DistributionSelection.QnormAndQlogisDistribution(Y_Ceiling) - DistributionSelection.QnormAndQlogisDistribution(Y_LowerLimit)) / Y_PartitionNumber;
sideReturnData.responseProbability = new double[Y_PartitionNumber + 1];
for (int i = 0; i <= Y_PartitionNumber; i++)
{
if (i == 0)
{
sideReturnData.responseProbability[i] = Y_LowerLimit;
}
else
{
sideReturnData.responseProbability[i] = DistributionSelection.PointIntervalDistribution(DistributionSelection.QnormAndQlogisDistribution(Y_LowerLimit) + i * Y_ScaleLength, 0, 1);
}
}
sideReturnData.Y_Ceilings = new double[sideReturnData.responseProbability.Length];
sideReturnData.Y_LowerLimits = new double[sideReturnData.responseProbability.Length];
sideReturnData.responsePoints = new double[sideReturnData.responseProbability.Length];
for (int i = 0; i < sideReturnData.responseProbability.Length; i++)
{
IntervalEstimation ie = new IntervalEstimation();
if (intervalChoose == 0)
{
ie = SingleSideEstimation(xArray, vArray, sideReturnData.responseProbability[i], ConfidenceLevel);
}
else
{
ie = DoubleSideEstimation(xArray, vArray, sideReturnData.responseProbability[i], ConfidenceLevel);
}
sideReturnData.Y_LowerLimits[i] = ie.Confidence.Down;
sideReturnData.Y_Ceilings[i] = ie.Confidence.Up;
double fq = sideReturnData.responseProbability[i];
sideReturnData.responsePoints[i] = StandardSelection.ProcessValue(StandardSelection.InverseProcessValue(favg) + (DistributionSelection.QnormAndQlogisDistribution(fq) * fsigma));
}
return(sideReturnData);
}
private SideReturnData GetSideReturnDataValue(double Y_Ceiling, double Y_LowerLimit, int Y_PartitionNumber)
{
SideReturnData sideReturnData = new SideReturnData();
double Y_ScaleLength = (LiftingDistributionSelection.QValue(Y_Ceiling) - LiftingDistributionSelection.QValue(Y_LowerLimit)) / Y_PartitionNumber;
sideReturnData.responseProbability = new double[Y_PartitionNumber + 1];
for (int i = 0; i <= Y_PartitionNumber; i++)
{
if (i == 0)
{
sideReturnData.responseProbability[i] = Y_LowerLimit;
}
else
{
sideReturnData.responseProbability[i] = LiftingDistributionSelection.PValue(LiftingDistributionSelection.QValue(Y_LowerLimit) + i * Y_ScaleLength, 0, 1);
}
}
sideReturnData.Y_Ceilings = new double[sideReturnData.responseProbability.Length];
sideReturnData.Y_LowerLimits = new double[sideReturnData.responseProbability.Length];
sideReturnData.responsePoints = new double[sideReturnData.responseProbability.Length];
return(sideReturnData);
}
