void darkRate() {
//gROOT->SetBatch(true);
gROOT->SetStyle("Plain");
gStyle->SetOptStat(0000);
gStyle->SetOptTitle(0);
TFile * f1300 = new TFile("Spectra/08_12_16_1700V_LightsOff_Short.root", "READ");
TFile * f1500 = new TFile("Spectra/08_12_16_1800V_LightsOff_Short.root", "READ");
TFile * f1700 = new TFile("Spectra/08_12_16_1900V_LightsOff_Short.root", "READ");
TTree * t1300 = (TTree*)f1300->Get("Channel_1");
TTree * t1500 = (TTree*)f1500->Get("Channel_1");
TTree * t1700 = (TTree*)f1700->Get("Channel_1");
TGraphErrors * h1300 = integralHistogram(t1300);
TGraphErrors * h1500 = integralHistogram(t1500);
TGraphErrors * h1700 = integralHistogram(t1700);
h1300->GetYaxis()->SetTitle("Rate [Hz]");
h1300->GetYaxis()->SetRangeUser(0.5, 10e6);
h1300->GetXaxis()->SetTitle("Threshold [mV]");
h1300->GetXaxis()->SetRangeUser(0.5, 1000);
h1300->SetLineColor(kBlack);
h1500->SetLineColor(kRed);
h1700->SetLineColor(kBlue);
TLegend * leg = new TLegend(0.60, 0.70, 0.88, 0.88);
leg->SetHeader("PMT Voltage");
leg->AddEntry(h1300, "1700V", "l");
leg->AddEntry(h1500, "1800V", "l");
leg->AddEntry(h1700, "1900V", "l");
h1300->Draw("ALP");
h1500->Draw("LP");
h1700->Draw("LP");
leg->Draw();
}
void CvHOGEvaluator::setImage( const Mat &img, uchar clsLabel, int idx )
{
CV_DbgAssert( !hist.empty());
CvFeatureEvaluator::setImage( img, clsLabel, idx );
std::vector<Mat> integralHist;
for ( int bin = 0; bin < N_BINS; bin++ )
{
integralHist.push_back( Mat( winSize.height + 1, winSize.width + 1, hist[bin].type(), hist[bin].ptr<float>( (int) idx ) ) );
}
Mat integralNorm( winSize.height + 1, winSize.width + 1, normSum.type(), normSum.ptr<float>( (int) idx ) );
integralHistogram( img, integralHist, integralNorm, (int) N_BINS );
}
bool HOGEvaluator::setImage( const Mat& image, Size winSize )
{
int rows = image.rows + 1;
int cols = image.cols + 1;
origWinSize = winSize;
if( image.cols < origWinSize.width || image.rows < origWinSize.height )
return false;
hist.clear();
for( int bin = 0; bin < Feature::BIN_NUM; bin++ )
{
hist.push_back( Mat(rows, cols, CV_32FC1) );
}
normSum.create( rows, cols, CV_32FC1 );
integralHistogram( image, hist, normSum, Feature::BIN_NUM );
size_t featIdx, featCount = features->size();
for( featIdx = 0; featIdx < featCount; featIdx++ )
{
featuresPtr[featIdx].updatePtrs( hist, normSum );
}
return true;
}