void DataSignal :: WriteSmartPeakInfoToXML (RGTextOutput& text, const RGString& indent, const RGString& bracketTag, const RGString& locationTag) {
int peak;
Endl endLine;
RGString suffix;
// if (HasCrossChannelSignalLink ()) {
if (HasAlleleName () && (!mDoNotCall)) {
peak = (int) floor (Peak () + 0.5);
if (mOffGrid)
suffix = " OL";
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<mean>" << GetMean () << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
text << indent << "\t<BPS>" << GetBioID () << "</BPS>" << endLine;
// text << indent << "\t<" << locationTag << ">" << (int) floor (GetApproximateBioID () + 0.5) << "</" << locationTag << ">" << endLine;
text << indent << "\t<" << locationTag << ">" << GetApproximateBioID () << "</" << locationTag << ">" << endLine;
text << indent << "\t<PeakArea>" << TheoreticalArea () << "</PeakArea>" << endLine;
text << indent << "\t<allele>" << GetAlleleName () << suffix << "</allele>" << endLine;
text << indent << "\t<width>" << 4.0 * GetStandardDeviation () << "</width>" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}
// }
}
bool DataSignal :: ReportSmartNoticeObjects (RGTextOutput& text, const RGString& indent, const RGString& delim) {
if (NumberOfSmartNoticeObjects () > 0) {
int msgLevel = GetHighestMessageLevelWithRestrictionSM ();
RGDListIterator it (*mSmartMessageReporters);
SmartMessageReporter* nextNotice;
text.SetOutputLevel (msgLevel);
if (!text.TestCurrentLevel ()) {
text.ResetOutputLevel ();
return false;
}
Endl endLine;
text << endLine;
text << indent << "Notices for curve with (Mean, Sigma, Peak, 2Content, Fit) = " << delim << delim << delim << delim << delim << delim;
text << GetMean () << delim << GetStandardDeviation () << delim << Peak () << delim << GetScale (2) << delim << Fit << endLine;
while (nextNotice = (SmartMessageReporter*) it ())
text << indent << nextNotice->GetMessage () << nextNotice->GetMessageData () << endLine;
text.ResetOutputLevel ();
text.Write (1, "\n");
}
else
return false;
return true;
}
void RejectOutlierMatches(vector<Point3f> &matches1, vector<Point3f> &matches2, vector<float> &matchDistances, float maxStdDev)
{
float distanceStandardDev = GetStandardDeviation(matchDistances);
vector<Point3f> filteredMatches1;
vector<Point3f> filteredMatches2;
for (size_t i = 0; i < matches1.size(); i++)
{
if (matchDistances[i] > maxStdDev * distanceStandardDev)
continue;
filteredMatches1.push_back(matches1[i]);
filteredMatches2.push_back(matches2[i]);
}
matches1 = filteredMatches1;
matches2 = filteredMatches2;
}
void DataSignal :: WriteSmartArtifactInfoToXML (RGTextOutput& text, const RGString& indent, const RGString& bracketTag, const RGString& locationTag) {
int peak;
Endl endLine;
RGString suffix;
RGString label;
SmartMessageReporter* notice;
int i;
RGString virtualAllele;
int reportedMessageLevel;
reportedMessageLevel = GetHighestMessageLevelWithRestrictionSM ();
bool thisIsFirstNotice = true;
if ((!DontLook ()) && (NumberOfSmartNoticeObjects () != 0)) {
peak = (int) floor (Peak () + 0.5);
if (mOffGrid)
suffix = " OL";
virtualAllele = GetVirtualAlleleName ();
RGDListIterator it (*mSmartMessageReporters);
i = 0;
while (notice = (SmartMessageReporter*) it ()) {
if (!notice->GetDisplayOsirisInfo ())
continue;
if (thisIsFirstNotice) {
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<level>" << reportedMessageLevel << "</level>" << endLine;
text << indent << "\t<mean>" << GetMean () << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
// text << indent << "\t<" << locationTag << ">" << (int) floor (GetApproximateBioID () + 0.5) << "</" << locationTag << ">" << endLine;
text << indent << "\t<" << locationTag << ">" << GetApproximateBioID () << "</" << locationTag << ">" << endLine;
text << indent << "\t<PeakArea>" << TheoreticalArea () << "</PeakArea>" << endLine;
if (virtualAllele.Length () > 0)
text << indent << "\t<equivAllele>" << virtualAllele << suffix << "</equivAllele>" << endLine;
text << indent << "\t<width>" << 4.0 * GetStandardDeviation () << "</width>" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
label = indent + "\t<label>";
thisIsFirstNotice = false;
}
if (i > 0)
label << " ";
label += notice->GetMessage ();
label += notice->GetMessageData ();
i++;
}
RGString temp = GetVirtualAlleleName () + suffix;
if (temp.Length () > 0) {
if (i > 0)
label << " ";
label += "Allele " + temp;
}
if (i > 0) {
label << "</label>";
text << label << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}
/*if ((signalLink != NULL) && (!signalLink->xmlArtifactInfoWritten)) {
signalLink->xmlArtifactInfoWritten = true;
peak = signalLink->height;
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<mean>" << signalLink->mean << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
text << indent << "\t<" << locationTag << ">" << signalLink->bioID << "</" << locationTag << ">" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
label = indent + "\t<label>";
mNoticeObjectIterator.Reset ();
i = 0;
while (notice = (Notice*) mNoticeObjectIterator ()) {
if (i > 0)
label << " ";
label += notice->GetLabel ();
i++;
}
if (temp.Length () > 0) {
if (i > 0)
label << " ";
label += "Allele " + temp;
}
label << "</label>";
text << label << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}*/
}
}
void MgFeatureNumericFunctions::CalculateDistribution(VECTOR& values, VECTOR& distValues)
{
STRING funcName;
int numCats;
double dataMin, dataMax;
INT32 funcCode = -1;
// Get the arguments from the FdoFunction
STRING propertyName;
bool supported = MgServerFeatureUtil::FindCustomFunction(m_customFunction, funcCode);
if (supported)
{
switch(funcCode)
{
case EQUAL_CATEGORY: // Equal Category
{
MgServerFeatureUtil::GetArguments(m_customFunction, propertyName, numCats, dataMin, dataMax, m_type);
GetEqualCategories(values, numCats, dataMin, dataMax, distValues);
break;
}
case STDEV_CATEGORY: // StdDev Category
{
MgServerFeatureUtil::GetArguments(m_customFunction, propertyName, numCats, dataMin, dataMax, m_type);
GetStandardDeviationCategories(values, numCats, dataMin, dataMax, distValues);
break;
}
case QUANTILE_CATEGORY: // Quantile Category
{
MgServerFeatureUtil::GetArguments(m_customFunction, propertyName, numCats, dataMin, dataMax, m_type);
GetQuantileCategories(values, numCats, dataMin, dataMax, distValues);
break;
}
case JENK_CATEGORY: // Jenk Category
{
MgServerFeatureUtil::GetArguments(m_customFunction, propertyName, numCats, dataMin, dataMax, m_type);
GetJenksCategories(values, numCats, dataMin, dataMax, distValues);
break;
}
case MINIMUM:
{
GetMinimum(values,distValues);
break;
}
case MAXIMUM:
{
GetMaximum(values,distValues);
break;
}
case MEAN:
{
GetMeanValue(values,distValues);
break;
}
case STANDARD_DEV:
{
GetStandardDeviation(values,distValues);
break;
}
case UNIQUE:
{
MgUniqueFunction<double>::Execute(values, distValues);
break;
}
}
}
}
// This function builds the mass function based on lane features
// \param lateralOffset: current lateral offset
// \param intervalTime: the interval time between the two consective frames
//! Assign the mass from lane source
//! Standard deviation reflects the extent of wave about car. It will show the fatigue.
void GenerateLaneIndicators(const int &sampleIdx, const int &TIME_SAMPLING_WINDOW, int &muWindowSize, int &sigmaWindowSize,
const double &lateralOffset, std::deque<InfoCar> &lateralOffsetDeque, std::deque <InfoCar> &LANEXDeque,
std::deque<InfoTLC> &TLCDeque, LaneFeature &laneFeatures, const double &intervalTime)
{
double LATMEAN=laneFeatures.LATMEAN, LANEDEV=laneFeatures.LANEDEV, LATSD=0, LANEX=0, TLC=0, TLC_min=0;
int TLC_2s = 0, TLC_halfs = 0;
double TLCF_2s = 0, TLCF_halfs = 0;
//! lateralOffsetDeque
InfoCar infoLO;
infoLO.lateralOffset = lateralOffset;
infoLO.intervalTime = intervalTime;
if(!lateralOffsetDeque.empty())
{
infoLO.winTime = lateralOffsetDeque.back().winTime + intervalTime;
} else {
infoLO.winTime = intervalTime;
}
while (infoLO.winTime > TIME_SAMPLING_WINDOW && !lateralOffsetDeque.empty())
{
infoLO.winTime -= lateralOffsetDeque.front().intervalTime;
lateralOffsetDeque.pop_front();
}
lateralOffsetDeque.push_back(infoLO);
//! Need to reset \param muWindowSize and \param sigmaWindowSize.
GetEWMA(sampleIdx, muWindowSize, lateralOffset, LATMEAN);
GetEWVAR(sampleIdx, sigmaWindowSize, lateralOffset, LATMEAN, LANEDEV);
GetStandardDeviation(lateralOffsetDeque, LATSD);
std::cout << "LO: " << lateralOffset << "LATSD: " << LATSD << std::endl;
//! Considering the sampling Time of LANEX different that of lateralOffset
//! Rebuild the InfoCar struct
InfoCar infoLANEX;
infoLANEX.lateralOffset = lateralOffset;
infoLANEX.intervalTime = intervalTime;
if(!LANEXDeque.empty())
{
infoLANEX.winTime = LANEXDeque.back().winTime + intervalTime;
} else {
infoLANEX.winTime = intervalTime;
}
while (infoLANEX.winTime > TIME_SAMPLING_WINDOW)
{
infoLANEX.winTime -= LANEXDeque.front().intervalTime;
LANEXDeque.pop_front();
}
LANEXDeque.push_back(infoLANEX);
double sumTime_LANEX = 0, sumTime = 0;
for(std::deque<InfoCar>::size_type i = 0; i != LANEXDeque.size(); ++i)
{
if(LANEXDeque[i].lateralOffset == 1)
{
sumTime_LANEX += LANEXDeque[i].intervalTime;
}
sumTime += LANEXDeque[i].intervalTime;
}
LANEX = sumTime_LANEX / sumTime;
//! Time-to-Lane-Crossing
//! Simple TLC
CV_Assert((int)lateralOffsetDeque.size() > 1);
double lastLateralOffset = lateralOffsetDeque.at(lateralOffsetDeque.size()-2).lateralOffset;
double lateralVelocity = lateralOffset - lastLateralOffset;
double TLC_Frame = 0;
if (lateralVelocity < 0)//direct to left
TLC_Frame = std::abs((1 + lateralOffset) / lateralVelocity);
else if(lateralVelocity > 0)//direct to right
TLC_Frame = std::abs((1 - lateralOffset) / lateralVelocity);
else
TLC_Frame = 10000;//Max TLC shows a safe deviation
TLC = TLC_Frame * intervalTime;//sec
TLC = TLC < 1000 ? TLC : 1000;
InfoTLC infoTLC;
infoTLC.TLC = TLC;
infoTLC.intervalTime = intervalTime;
if(!TLCDeque.empty())
{
infoTLC.winTime = TLCDeque.back().winTime + intervalTime;
} else {
infoTLC.winTime = intervalTime;
}
while (infoTLC.winTime > TIME_SAMPLING_WINDOW)
{
infoTLC.winTime -= TLCDeque.front().intervalTime;
TLCDeque.pop_front();
}
TLCDeque.push_back(infoTLC);
//! Number of times that TLC below a threshold
for(std::deque<double>::size_type i = 0; i != TLCDeque.size(); ++i)
{
//!TLC with signal falling below 2s in a given time interval
if(TLCDeque[i].TLC < 2.0)
{
TLC_2s ++;
}
//!TLC with signal falling below 0.5s in a given time interval
if(TLCDeque[i].TLC < 0.5)
{
TLC_halfs ++;
}
}
//! Fraction of TLC_2s and TLC_halfs
TLCF_2s = (double)TLC_2s / (double)TLCDeque.size();
TLCF_halfs = (double)TLC_halfs / (double)TLCDeque.size();
//! Global minimum of TLC over a given time interval;
std::deque<InfoTLC> cmpTLCDeque = TLCDeque;
sort(cmpTLCDeque.begin(), cmpTLCDeque.end(), TLC_cmp);
TLC_min = cmpTLCDeque.back().TLC;
std::deque<InfoTLC>::iterator iter = cmpTLCDeque.end();
while (TLC_min == 0)
{
--iter;
TLC_min = iter->TLC;
}
//!Update the LaneFeature struct
laneFeatures.frame = sampleIdx;
laneFeatures.lateralOffset = lateralOffset;
laneFeatures.LATMEAN = LATMEAN; //EWMA
laneFeatures.LANEDEV = LANEDEV; //EWVAR
laneFeatures.LATSD = LATSD;
laneFeatures.LANEX = LANEX;
laneFeatures.TLC = TLC;
laneFeatures.TLC_2s = TLC_2s;
laneFeatures.TLC_halfs = TLC_halfs;
laneFeatures.TLC_min = TLC_min;
laneFeatures.TLCF_2s = TLCF_2s;
laneFeatures.TLCF_halfs = TLCF_halfs;
}//end GenerateLaneIndicators
void GetLaneBaseline(const int &sampleIdx,
const int &TIME_SAMPLING_WINDOW,
int &muWindowSize, int &sigmaWindowSize,
const double &lateralOffset,
std::vector<double> &LATSD_Baseline,
std::deque<InfoCar> &lateralOffsetDeque,
std::deque<InfoCar> &LANEXDeque,
std::deque<InfoTLC> &TLCDeque,
LaneFeature &laneFeatures,
const double &intervalTime)
{
laneFeatures.frame = sampleIdx;
laneFeatures.lateralOffset = lateralOffset;
//! lateralOffsetDeque
InfoCar infoLO;
infoLO.lateralOffset = lateralOffset;
infoLO.intervalTime = intervalTime;
if(!lateralOffsetDeque.empty())
{
infoLO.winTime = lateralOffsetDeque.back().winTime + intervalTime;
} else {
infoLO.winTime = intervalTime;
}
while (infoLO.winTime > TIME_SAMPLING_WINDOW && !lateralOffsetDeque.empty())
{
infoLO.winTime -= lateralOffsetDeque.front().intervalTime;
lateralOffsetDeque.pop_front();
}
lateralOffsetDeque.push_back(infoLO);
//! Need to reset \param muWindowSize and \param sigmaWindowSize.
GetEWMA(sampleIdx, muWindowSize, lateralOffset , laneFeatures.LATMEAN);
GetEWVAR(sampleIdx, sigmaWindowSize, lateralOffset , laneFeatures.LATMEAN, laneFeatures.LANEDEV);
//! Standard Deviation of LATSD for Baseline
GetStandardDeviation(lateralOffsetDeque, laneFeatures.LATSD);
LATSD_Baseline.push_back(laneFeatures.LATSD);
sort(LATSD_Baseline.begin(), LATSD_Baseline.end(), LATSD_cmp);
//! Considering the sampling Time of LANEX different that of lateralOffset
//! Rebuild the InfoCar struct
InfoCar infoLANEX;
infoLANEX.lateralOffset = lateralOffset;
infoLANEX.intervalTime = intervalTime;
if(!LANEXDeque.empty())
{
infoLANEX.winTime = LANEXDeque.back().winTime + intervalTime;
} else {
infoLANEX.winTime = intervalTime;
}
while (infoLANEX.winTime > TIME_SAMPLING_WINDOW)
{
infoLANEX.winTime -= LANEXDeque.front().intervalTime;
LANEXDeque.pop_front();
}
LANEXDeque.push_back(infoLANEX);
double sumTime_LANEX = 0;
for(std::deque<InfoCar>::size_type i = 0; i != LANEXDeque.size(); ++i)
{
if(LANEXDeque[i].lateralOffset == 1)
{
sumTime_LANEX += LANEXDeque[i].intervalTime;
}
}
double LANEX = sumTime_LANEX / LANEXDeque.back().winTime;
if(sampleIdx > 1)
{
//! Add TLC into deque. Simple TLC
double TLC = 0, TLC_min = 0;
int TLC_2s = 0, TLC_halfs = 0;
double TLCF_2s = 0, TLCF_halfs = 0;
CV_Assert((int)lateralOffsetDeque.size() > 1);
double lastLateralOffset = lateralOffsetDeque.at(lateralOffsetDeque.size()-2).lateralOffset;
double lateralVelocity = lateralOffset - lastLateralOffset;
double TLC_Frame = 0;
if (lateralVelocity < 0)//direct to left
TLC_Frame = std::abs((1 + lateralOffset) / lateralVelocity);
else if(lateralVelocity > 0)//direct to right
TLC_Frame = std::abs((1 - lateralOffset) / lateralVelocity);
else
TLC_Frame = 10000;//Max TLC shows a safe deviation
TLC = TLC_Frame / intervalTime;//sec
TLC = TLC < 1000 ? TLC : 1000;
InfoTLC infoTLC;
infoTLC.TLC = TLC;
infoTLC.intervalTime = intervalTime;
if(!TLCDeque.empty())
{
infoTLC.winTime = TLCDeque.back().winTime + intervalTime;
} else {
infoTLC.winTime = intervalTime;
}
while (infoTLC.winTime > TIME_SAMPLING_WINDOW)
{
infoTLC.winTime -= TLCDeque.front().intervalTime;
TLCDeque.pop_front();
}
TLCDeque.push_back(infoTLC);
//! Number of times that TLC below a threshold
for(std::deque<double>::size_type i = 0; i != TLCDeque.size(); i++)
{
//!TLC with signal falling below 2s in a given time interval
if(TLCDeque[i].TLC < 2.0)
{
TLC_2s ++;
}
//!TLC with signal falling below 0.5s in a given time interval
if(TLCDeque[i].TLC < 0.5)
{
TLC_halfs ++;
}
}
//! Fraction of TLC_2s and TLC_halfs
TLCF_2s = (double)TLC_2s / (double)TLCDeque.size();
TLCF_halfs = (double)TLC_halfs / (double)TLCDeque.size();
//! Global minimum of TLC over a given time interval;
std::deque<InfoTLC> cmpTLCDeque = TLCDeque;
sort(cmpTLCDeque.begin(), cmpTLCDeque.end(), TLC_cmp);
TLC_min = cmpTLCDeque.back().TLC;
std::deque<InfoTLC>::iterator iter = cmpTLCDeque.end();
while (TLC_min == 0)
{
--iter;
TLC_min = iter->TLC;
}
//! Calculate the Baseline
//!Baseline of LATSD should be the median value.
laneFeatures.LATSD_Baseline = LATSD_Baseline.at(cvRound(LATSD_Baseline.size()/2.0));
//!Others
laneFeatures.LATMEAN_Baseline = laneFeatures.LATMEAN_Baseline > laneFeatures.LATMEAN ? laneFeatures.LATMEAN_Baseline : laneFeatures.LATMEAN;
laneFeatures.LANEDEV_Baseline = laneFeatures.LANEDEV_Baseline > laneFeatures.LANEDEV ? laneFeatures.LANEDEV_Baseline : laneFeatures.LANEDEV;
laneFeatures.LANEX = LANEX;
laneFeatures.TLC = TLC;
laneFeatures.TLC_2s = TLC_2s;
laneFeatures.TLC_halfs = TLC_halfs;
laneFeatures.TLC_min = TLC_min;
laneFeatures.TLCF_2s = TLCF_2s;
laneFeatures.TLCF_halfs = TLCF_halfs;
} else {
laneFeatures.LATMEAN_Baseline = 0;
laneFeatures.LANEDEV_Baseline = 0;
laneFeatures.LATSD_Baseline = 0;
laneFeatures.LANEX = 0;
laneFeatures.TLC = 0;
laneFeatures.TLC_2s = 0;
laneFeatures.TLC_halfs = 0;
laneFeatures.TLC_min = 0;
laneFeatures.TLCF_2s = 0;
laneFeatures.TLCF_halfs = 0;
}
}//end GetLaneBaseline
