void XYViewValueCell::UpdateText()
{
if (m_pGrid->gXY == 0)
{
SetNullStr();
return;
}
const DC_XYData& currXY = *(m_pGrid->gXY);
if (m_rowIndex >= currXY.Size())
{
SetNullStr();
return;
}
char tempStr[80];
CopyString(tempStr, "null", 80);
if (isX)
{
double currVal = currXY.xData[m_rowIndex];
if (!RealIsNull(currVal))
m_pGrid->xFormat.RealToString(currVal, tempStr, 80);
}
else
{
double currVal = currXY.yData[m_rowIndex];
if (!RealIsNull(currVal))
m_pGrid->yFormat.RealToString(currVal, tempStr, 80);
}
SetText(tempStr);
}
bool DC_XYData::IsClean() const
{
for (int i = 0; i < Size(); i++)
if (RealIsNull(xData[i]) || RealIsNull(yData[i]))
return false;
return true;
}
Limit3D PFO_Scatterplot::GetPlotObjLimits()
{
Limit3D currLimits;
DoStatusChk();
if (StatusNotOK() || (!doPlot))
return currLimits;
bool xLin, yLin;
GetAxesTypes(xLin, yLin);
{
const SC_DoubleArray& xData = scatterDataDC->dataTable[plotIVIndx];
const SC_DoubleArray& yData = scatterDataDC->dataTable[plotDVIndx + nplotIV];
for (int j = 0; j < xData.Size(); j++)
{
double xVal = xData[j];
double yVal = yData[j];
if ((xLin || (xVal > stdEps)) && (yLin || (yVal > stdEps)))
currLimits.AddToLimits(Coord3D(xVal, yVal, nullReal));
}
}
if (plotXGridLines)
{
const SC_DoubleArray& xData = xGridLinesDC->dataTable[plotIVIndx];
for (int j = 0; j < xData.Size(); j++)
{
double xVal = xData[j];
if ((!RealIsNull(xVal)) && (xLin || (xVal > stdEps)))
currLimits.AddToLimits(Coord3D(xVal, nullReal, nullReal));
}
}
if (plotYGridLines)
{
const SC_DoubleArray& yData = yGridLinesDC->dataTable[plotDVIndx];
for (int j = 0; j < yData.Size(); j++)
{
double yVal = yData[j];
if ((!RealIsNull(yVal)) && (yLin || (yVal > stdEps)))
currLimits.AddToLimits(Coord3D(nullReal, yVal, nullReal));
}
}
return currLimits;
}
double DC_Normalize::Normalize(double inNorm)
{
if (RealIsNull(inNorm))
return nullReal;
double outVal = inNorm;
if (normalizeOp != noPower)
{
if (outVal <= inputMinimum)
outVal = outputMinimum;
else if (outVal >= inputMaximum)
outVal = outputMaximum;
else
outVal = (inNorm - inputMinimum) * spanMult + outputMinimum;
}
if ((normalizeOp != noLimit) && (fabs(outVal) > stdEps))
{
if (outVal < stdEps)
outVal = pow(outVal, intPower);
else
outVal = pow(outVal, normPower);
}
return outVal;
}
double ParameterCurve::GetMetricCurveY(const double& metricXVal,
DC_Curve& curve)
{
// sanity checks
if (!curve.IsCreated())
GenAppInternalError("ParameterCurve::GetMetricPointCurveY #1");
if (RealIsNull(metricXVal))
GenAppInternalError("ParameterCurve::GetMetricPointCurveY #2");
// convert metric x to user x
double userX = xUnitIndex.MetricToUser(metricXVal);
// take log if required
if (xIsLog10)
{
if (userX < stdEps)
GenAppInternalError("ParameterCurve::GetMetricPointCurveY #3");
userX = log10(userX);
}
// get curve value
double userY = curve.GetCurveY(userX);
// if log then transform
if (yIsLog10)
{
if ((userY < -99.0) || (userY > 99.0))
GenAppInternalError("ParameterCurve::GetMetricPointCurveY #4");
userY = pow(10.0, userY);
}
// convert units && return
return yUnitIndex.UserToMetric(userY);
}
void WorkingCaptureDataBase::ApplySpec(const double& testTime)
{
for (int i = 0; i < capturedVals.Size(); i++)
{
// get ref
SC_DoubleArray& currVec = (*currCapturedData)[i+1];
double lastVal = 0.0; // no production at start
if (!currVec.IsEmpty())
lastVal = currVec.LastIndex();
double newVal = capturedVals[i];
// for first flow in sequence
if (RealIsNull(lastVal))
currVec.SetLastIndex(newVal);
currVec += newVal;
}
if ((nextRestart < productionRestartTimes.Size()) && (!(*currCapturedData)[0].IsEmpty()))
{
if (testTime > productionRestartTimes[nextRestart])
{
for (int i = 0; i < productionCapture.Size(); i++)
(*currCapturedData)[productionCapture[i] + 1].SetLastIndex(0.0);
nextRestart++;
}
}
}
void ValueCell::UpdateText()
{
DC_ColorMap& currCM = m_pGrid->gColorMap;
if (m_rowIndex >= currCM.ncolorMap)
{
SetNullStr();
return;
}
SC_ColorSpec& currSpec = currCM.colorMapColors[m_rowIndex];
double currVal;
switch (m_colIndex )
{
case 0 : {currVal = currSpec.RH; break;}
case 1 : {currVal = currSpec.GS; break;}
case 2 : {currVal = currSpec.BV; break;}
}
if (RealIsNull(currVal) || (currVal < 0.0) || (currVal > 1.0))
{
SetNullStr();
}
else
{
char tempStr[80];
SC_DecFormat rForm(3);
rForm.RealToString(currVal, tempStr, 80);
SetText(tempStr);
}
}
void GridViewValueCell::UpdateText()
{
if (m_pGrid->gGrid == 0)
{
SetNullStr();
return;
}
const DC_GridData& currTab = *(m_pGrid->gGrid);
if ((m_colIndex >= currTab.yData.Size()) || (m_rowIndex >= currTab.xData.Size()))
{
SetNullStr();
return;
}
double currVal = currTab.gData[m_rowIndex][m_colIndex];
if (RealIsNull(currVal))
{
SetNullStr();
}
else
{
char tempStr[80];
m_pGrid->gridFormat.RealToString(currVal, tempStr, 80);
SetText(tempStr);
}
}
void DC_XYData::CleanUp()
{
int nOK = 0;
for (int i = 0; i < xData.Size(); i++)
{
if (RealIsNull(xData[i]) || RealIsNull(yData[i]))
continue;
if (nOK < i)
{
xData[nOK] = xData[i];
yData[nOK] = yData[i];
}
nOK++;
}
SetSize(nOK);
}
void DC_DataLimit::AddToLimit(const double& inVal)
{
if (RealIsNull(inVal))
return;
if (RealIsNull(minLimit))
{
minLimit = inVal;
maxLimit = inVal;
return;
}
if (inVal < minLimit)
minLimit = inVal;
else if (inVal > maxLimit)
maxLimit = inVal;
}
bool DC_XYData::SetNDX(SC_SetupErr& err,
SC_DoubleArray& ndxData)const
{
int n = 0;
for (int i = 0; i < Size(); i++)
{
double x = xData[i];
double y = yData[i];
if (RealIsNull(x) || RealIsNull(y))
{
err.SetConstantError("all x and y must be non null");
return false;
}
if ((x < 0.5) || (x > 999))
{
err.SetConstantError("all x values must be integers > 0 and < 1000");
return false;
}
if (y < 1.0E-5)
{
err.SetConstantError("all y values must be > 1E-5");
return false;
}
n += int(x);
}
if (n > 10000)
{
err.SetConstantError("total number of x/y ndx calculated nodes points be < 10000");
return false;
}
ndxData.Alloc(n);
for (int i = 0; i < Size(); i++)
{
n = int(xData[i]);
double y = yData[i];
for (int j = 0; j < n; j++)
ndxData += y;
}
return true;
}
void SC_Statistics::CalcMode(const SC_DoubleArray& data)
{
if (nOK == 0)
return;
// min == max
if (realResults[soVar] < stdEps)
{
realResults[soMode] = realResults[soMean];
return;
}
// Scott, 1979 algorithm for bin width
// W = (3.49)(std.dev.)[(#samples)^(-1/3)]
double width = 3.49 * realResults[soStdDev] * (pow(realResults[soN], -0.3333));
if (width < stdEps)
{
realResults[soMode] = realResults[soMean];
return;
}
double maxNBins = (realResults[soMax] - realResults[soMin]) / width;
if (maxNBins > 10000.0)
return;
int nbins = int(ceil(maxNBins));
// note just linear bins
width = (realResults[soMax] - realResults[soMin]) / double(nbins);
SC_IntArray binCount(nbins, 0);
for (int i = 0; i < data.Size(); i++)
{
double dVal = data[i];
if (RealIsNull(dVal) || (dVal < realResults[soMin])) // can happen if stats calc was log
continue;
int binIndex = int(floor((dVal - realResults[soMin]) / width));
// pathological case == maxVal
if (binIndex == nbins)
binIndex--;
binCount[binIndex]++;
}
int maxBin = 0;
int maxCount = binCount[0];
for (int i = 1; i < nbins; i++)
if (binCount[i] > maxCount)
{
maxBin = i;
maxCount = binCount[i];
}
realResults[soMode] = realResults[soMin] + (double(maxBin) + 0.5) * width;
}
bool SC_SetupErr::NullDataErr(const char* valDesc,
const double& chkVal)
{
if (RealIsNull(chkVal))
{
SetErrText(valDesc, " is not set");
return true;
}
return false;
}
void DataCaptureErrorListing::CreateListing()
{
StdTitle("Simulation Results Setup Errors");
SC_SetupErr dcErr;
if (dataCaptureData.IsEmpty())
AddError("no output data specified");
for (int i = 0; i < dataCaptureData.Size(); i++)
if (dataCaptureData.IsNotValid(i))
{
AddError("Null capture spec found");
}
else
{
if (!dataCaptureData.GetRef(i).SetupOK(dcErr))
{
AddError(dcErr);
}
}
if (productionRestartTimes.Size() > 0)
{
double prev = productionRestartTimes[0];
for (int i = 1; i < productionRestartTimes.Size(); i++)
{
double next = productionRestartTimes[i];
if (RealIsNull(prev) || RealIsNull(next))
{
AddError("Null production restart time found");
break;
}
if (prev >= next)
{
AddError("Production restart times must be ascending");
break;
}
}
}
}
void ValueGridCell::UpdateText()
{
CString sText;
if (RealIsNull(m_dval))
{
sText = "---";
}
else
{
SC_DecFormat corrRF(3);
corrRF.RealToString(m_dval, sText);
}
SetText(sText);
}
void YCell::UpdateText()
{
char tempStr[80];
if (m_nIndex >= xyData.Size()) {
CopyString(tempStr, "---", 80);
} else {
double yVal = xyData[m_nIndex].y;
if (RealIsNull(yVal)) {
CopyString(tempStr, "---", 80);
} else {
m_pGrid->yForm.RealToString(yVal, tempStr, 80);
}
}
SetText(tempStr);
}
void Parameter::ParValToString(const double& metricVal,
CString& parString)
{
if (useUnitFormat)
{
parVal.UnitIndex::GetUserString(metricVal, parString);
}
else if (RealIsNull(metricVal))
{
parString = nullStr;
}
else
{
format.RealToString(parVal.MetricToUser(metricVal), parString);
}
}
bool PointsCurveValue::SetupOK(SC_SetupErr& errData,
bool pIsLog)
{
if (IsOpt())
return pOptData->OptimizeSetupOK(errData);
else if (IsVary())
return pVaryData->VarySetupOK(errData);
SC_SetupErr parErr;
if (RealIsNull(pVal))
parErr.SetConstantError("data value not set");
else if (pIsLog && (pVal <= 1.0E-40))
parErr.SetConstantError("log curve is -ve");
return errData.SetupOK(pID, parErr);
}
bool DC_DataLimit::TransformValueForRange(double& inVal,
bool clipToRange) const
{
if (RealIsNull(inVal))
return false;
if (logRange)
{
if (inVal < stdEps)
{
if (clipToRange)
return false;
inVal = minLimit;
}
inVal = log10(inVal);
}
return true;
}
void SampleErrorListing::CreateListing()
{
StdTitle("Sampler Setup Errors");
SC_SetupErr sampErr;
SampVarArray currSamp;
if (currSamp.Size() < 1)
{
sampErr.SetConstantError("at least 1 variable must be sampled");
AddError(sampErr);
}
for (int i = 0; i < currSamp.Size(); i++)
if (!currSamp[i]->SampleSetupOK(sampErr))
AddError(sampErr);
//for FOSM or PEM - check to make sure all vars belong to same corr group
if (!IsMonteCarlo())
{
int uncertCorrGroup = currSamp[0]->GetCorrGroup();
if (!forceCorrelationsToZero)
{
//case where no correlations are set
if ((currSamp[0]->GetnCorrGroup(uncertCorrGroup) > 1) && (currSamp[0]->correlations.Size() == 0))
AddError("correlations not set or forced to zero");
}
for (int i = 1; i < currSamp.Size(); i++)
{
int currCorrGroup = currSamp[i]->GetCorrGroup();
if (currCorrGroup != uncertCorrGroup)
AddError("FOSM/PEM: all uncertain vars must belong to same correlation group");
if (!forceCorrelationsToZero)
{
//case where individual correlations are not set
for (int j = 0; j < currSamp[i]->correlations.Size(); j++)
{
if (RealIsNull(currSamp[i]->correlations[j].correlationValue))
AddError("correlations not set or forced to zero");
}
}
}
}
}
void nsCollect::CollectRange()
{
GenAppInfoMsg("nPreX", "collecting range");
IO_RangeSimResults baseRngFile;
DC_RangeSimResults baseRngData;
CopyString(baseRngFile.fileName, ProcessData::spawnData[0].rngFile, stdFileStrLen);
if (!baseRngFile.ReadSimResults(baseRngData))
GenAppInternalError("collecting base range");
RangeSimRunResults& baseRange = baseRngData[0];
for (int i = 1; i < ProcessData::spawnData.Size(); i++)
{
IO_RangeSimResults nextRngFile;
DC_RangeSimResults nextRngData;
CopyString(nextRngFile.fileName, ProcessData::spawnData[i].rngFile, stdFileStrLen);
if (!nextRngFile.ReadSimResults(nextRngData))
GenAppInternalError("collecting range data");
RangeSimRunResults& nextRange = nextRngData[0];
for (int j = 0; j < baseRange.Size(); j++)
{
SC_DoubleArray& baseData = baseRange[j].gridCubeData;
SC_DoubleArray& nextData = nextRange[j].gridCubeData;
for (int k = 0; k < baseData.Size(); k++)
if (RealIsNull(baseData[k]))
baseData[k] = nextData[k];
}
}
CopyString(baseRngFile.fileName, rangeOutputFile.fileName, stdFileStrLen);
if (!baseRngFile.AddSimRun(baseRange, rangeOutputDesc.addExisting))
GenAppInternalError("writing collected range");
GenAppInfoMsg("nPreX", "range collection complete");
}
bool Parameter::ParValOK(const double& pVal,
const char rangeID[],
SC_SetupErr& errData)
{
SC_SetupErr rangeErr;
char rangeErrMsg[80];
if (RealIsNull(pVal))
rangeErr.SetConstantError("value not set");
else if ((pVal < minLimit) || (pVal > maxLimit))
{
char minStr[80];
ParValToString(minLimit, minStr, 80);
char maxStr[80];
ParValToString(maxLimit, maxStr, 80);
MakeString(rangeErrMsg, "must be > ", minStr, " and < ", maxStr, 80);
rangeErr.SetConstantError(rangeErrMsg);
}
return errData.SetupOK(rangeID, rangeErr);
}
void DC_Normalize::DoNormalize(SC_DoubleArray& inData)
{
if (normalizeOp != noPower)
{
if (autoLimit)
{
inData.CalcMinMax(inputMinimum, inputMaximum);
if (RealIsNull(inputMinimum))
return;
}
if (fabs(inputMaximum - inputMinimum) < stdEps)
spanMult = 0.0;
else
spanMult = (outputMaximum - outputMinimum) / (inputMaximum - inputMinimum);
}
intPower = double(int(normPower));
for (int i = 0; i < inData.Size(); i++)
inData[i] = Normalize(inData[i]);
}
void DFO_TableCalibrationStatistics:: CalcOutput(FOcalcType calcType)
{
DoStatusChk();
if (!StatusOK())
return;
const SC_DoubleArray& xIn = *selectedColData;
const SC_DoubleArray& yIn = inputData->dataTable[selectedYCol];
double sumRes = 0.0;
double absRes = 0.0;
double sumSqr = 0.0;
double maxRes, minRes, maxY, minY;
int numRes = 0;
for (int i = 0; i < xIn.Size(); i++)
{
double nextX = xIn[i];
double nextY = yIn[i];
if (RealIsNull(nextX) || RealIsNull(nextY))
continue;
double currRes = nextX - nextY;
if (numRes == 0)
{
maxRes = currRes;
minRes = currRes;
maxY = nextY;
minY = nextY;
}
else
{
maxRes = DMax(maxRes, currRes);
minRes = DMin(minRes, currRes);
maxY = DMax(maxY, nextY);
minY = DMin(minY, nextY);
}
numRes++;
absRes += fabs(currRes);
sumRes += currRes;
sumSqr += Sqr(currRes);
}
if (numRes < 2)
{
SetObjErrMsg("Less than two points to calculate statistics for");
return;
}
maxOverPredictionDO.InitLabelAndValue(maxRes);
maxUnderPredictionDO.InitLabelAndValue(-minRes);
averageResidualDO.InitLabelAndValue(sumRes/double(numRes));
averageAbsResidualDO.InitLabelAndValue(absRes/double(numRes));
numMeasurementsDO.InitLabelAndValue(double(numRes));
normalizedResidualRMSDO.InitLabelAndValue(0.0);
if (sumSqr > 0.0)
{
double rms = sqrt(sumSqr/double(numRes));
residualRMSDO.InitLabelAndValue(rms);
double dy = maxY - minY;
if (dy > 0.0)
normalizedResidualRMSDO.InitLabelAndValue(rms / dy * 100.0);
}
else
{
residualRMSDO.InitLabelAndValue(0.0);
}
correlationCoefficientDO.InitLabelAndValue(PearsonR(xIn, yIn));
}
void DFO_TableColumnCorrelation:: CalcOutput(FOcalcType calcType)
{
DoStatusChk();
if (!StatusOK())
return;
xcolumnIDDO.SetValueLabel(inputData->GetTitle(selectedCol));
ycolumnIDDO.SetValueLabel(inputData->GetTitle(selectedYCol));
const SC_DoubleArray& xIn = *selectedColData;
const SC_DoubleArray& yIn = inputData->dataTable[selectedYCol];
SC_DoubleArray& xCorr = outputDataDC.xData;
SC_DoubleArray& yCorr = outputDataDC.yData;
xCorr.Alloc(xIn.Size());
yCorr.Alloc(xIn.Size());
int nOK = 0;
int i;
for (i = 0; i < xIn.Size(); i++)
{
double nextX = xIn[i];
double nextY = yIn[i];
if (RealIsNull(nextX) || RealIsNull(nextY))
continue;
if (logX)
{
if (nextX < stdEps)
continue;
nextX = log10(nextX);
}
if (logY)
{
if (nextY < stdEps)
continue;
nextY = log10(nextY);
}
xCorr[nOK] = nextX;
yCorr[nOK++] = nextY;
}
if (nOK < 2)
{
SetObjErrMsg("Less than two points to correlate");
return;
}
xCorr.SetSize(nOK);
yCorr.SetSize(nOK);
pearsonRDO.InitLabelAndValue(PearsonR(xCorr, yCorr));
spearmanRDO.InitLabelAndValue(SpearmanR(xCorr, yCorr));
// make correlation line
DC_Curve corrLine;
corrLine.curveType = Curve::ctPolynomial;
corrLine.polyOrder = 1;
SC_SetupErr crvErr;
outputLineDC.CreateFrom(xCorr, yCorr);
if (!corrLine.CreateCurve(outputLineDC, crvErr))
{
SetObjErrMsg(crvErr.GetErrorText());
return;
}
outputLineDC.xData.Sort(true);
corrLine.GetCurveY(outputLineDC.xData, outputLineDC.yData);
// unlog data
if (logX)
{
outputLineDC.xData.InvLog10();
outputDataDC.xData.InvLog10();
}
if (logY)
{
outputLineDC.yData.InvLog10();
outputDataDC.yData.InvLog10();
}
lineSlopeDO.InitLabelAndValue(corrLine.GetPolyCoefficients()[1]);
lineYInterceptDO.InitLabelAndValue(corrLine.GetPolyCoefficients()[0]);
}
void SC_Statistics::CalcStatistics(const SC_DoubleArray& data,
bool logData, bool baseTen)
{
Init();
if (data.IsEmpty())
return;
int nData = data.Size();
double sum = 0.0;
double geoSum = 0.0, harmSum = 0.0; //for geometric and harmonic means
double minV, maxV, minAV;
int minIndx, maxIndx, minAbsIndx;
double minPV = nullReal;
int minPosIndx = -1;
nOK = 0;
nPositive = 0;
int nnegZero = 0;
for (int i = 0; i < nData; i++)
{
double dVal = data[i];
if (dVal < 1.0E-99)
nnegZero++;
if (RealIsNull(dVal) || (logData && (dVal < 1.0E-99)))
continue;
// this used to be calculated after min/max
// changed for SyView 1.2 - Mar 06
// minVal, maxVal, minAV, and minIndxs now based/reported on logged data
if (logData)
{
if (baseTen)
{
dVal = log10(dVal);
}
else
{
dVal = log(dVal);
}
}
double absVal = fabs(dVal);
if (nOK == 0)
{
minV = dVal;
maxV = dVal;
minAV = absVal;
minIndx = i;
minAbsIndx = i;
maxIndx = i;
}
if (dVal < minV)
{
minV = dVal;
minIndx = i;
}
else if (dVal > maxV)
{
maxV = dVal;
maxIndx = i;
}
if (absVal < minAV)
{
minAV = absVal;
minAbsIndx = i;
}
if (dVal > 0.0)
{
if (minPosIndx < 0)
{
minPV = dVal;
minPosIndx = i;
}
else if (dVal < minPV)
{
minPV = dVal;
minPosIndx = i;
}
}
sum += dVal;
if(dVal > 0)
{
geoSum += log(dVal);
harmSum += 1/dVal;
nPositive++;
}
nOK++;
}
double dOK = double(nOK);
double dPositive = double(nPositive);
realResults[soN] = dOK;
realResults[soNnull] = double(nData - nOK);
realResults[soNnegZero] = double(nnegZero);
intResults[soN] = nOK;
intResults[soNnull] = nData - nOK;
intResults[soNnegZero] = nnegZero;
if (nData > 0)
realResults[soPercentNonNull] = dOK / double(nData) * 100.0;
if (nOK == 0)
return;
resultsOK = true;
realResults[soSum] = sum;
realResults[soMin] = minV;
realResults[soMax] = maxV;
realResults[soMinAbs] = minAV;
realResults[soMinPos] = minPV;
intResults[soMinIndx] = minIndx;
intResults[soMaxIndx] = maxIndx;
intResults[soMinAbsIndx] = minAbsIndx;
intResults[soMinPosIndx] = minPosIndx;
realResults[soMinIndx] = double(minIndx);
realResults[soMaxIndx] = double(maxIndx);
realResults[soMinAbsIndx] = double(minAbsIndx);
realResults[soMinPosIndx] = double(minPosIndx);
if (nOK > 0)
{
// pathological
realResults[soRange] = maxV - minV;
if (realResults[soRange] < stdEps)
{
realResults[soMean] = (minV + maxV) / 2.0;
realResults[soMeanGeo] = (minV + maxV) / 2.0;
realResults[soMeanHarm] = (minV + maxV) / 2.0;
realResults[soVar] = 0.0;
realResults[soStdDev] = 0.0;
}
else
{
realResults[soMean] = sum / dOK;
realResults[soMeanGeo] = exp(geoSum / dPositive);
realResults[soMeanHarm] = dPositive / harmSum;
// variance and std dev
if (nOK > 1)
{
double var = 0.0;
double mean = realResults[soMean];
for (int i = 0; i < data.Size(); i++)
{
double dVal = data[i];
if (RealIsNull(dVal) || (logData && (dVal < 1.0E-99)))
continue;
if (logData) {
if (baseTen) {
dVal = log10(dVal);
}
else {
dVal = log(dVal);
}
}
double dx = dVal - mean;
var += dx * dx;
}
var /= double(nOK - 1);
realResults[soVar] = var;
realResults[soStdDev] = sqrt(var);
}
}
}
/*
mean results now log data
if (logData) {
if (baseTen) {
realResults[soMean] = InvLgt(realResults[soMean]);
}
else {
realResults[soMean] = exp(realResults[soMean]);
}
} */
}
