| 1 | #include <TROOT.h>
|
|---|
| 2 | #include <TCanvas.h>
|
|---|
| 3 | #include <TProfile.h>
|
|---|
| 4 | #include <TTimer.h>
|
|---|
| 5 | #include <TH1F.h>
|
|---|
| 6 | #include <TH2F.h>
|
|---|
| 7 | #include <Getline.h>
|
|---|
| 8 | #include <TLine.h>
|
|---|
| 9 | #include <TMath.h>
|
|---|
| 10 | #include <TFile.h>
|
|---|
| 11 |
|
|---|
| 12 | #include <stdio.h>
|
|---|
| 13 | #include <stdint.h>
|
|---|
| 14 | #include <cstdio>
|
|---|
| 15 |
|
|---|
| 16 | #define HAVE_ZLIB
|
|---|
| 17 | #include "fits.h"
|
|---|
| 18 | #include "FOpenCalibFile.c"
|
|---|
| 19 |
|
|---|
| 20 | #include "zerosearch.C"
|
|---|
| 21 | #include "factfir.C"
|
|---|
| 22 |
|
|---|
| 23 | #define NPIX 1440
|
|---|
| 24 | #define NCELL 1024
|
|---|
| 25 |
|
|---|
| 26 | // data access and treatment
|
|---|
| 27 | #define FAD_MAX_SAMPLES 1024
|
|---|
| 28 |
|
|---|
| 29 | //vector<int16_t> data;
|
|---|
| 30 | //vector<int16_t> data_offset;
|
|---|
| 31 | //unsigned int data_num;
|
|---|
| 32 | //size_t data_n;
|
|---|
| 33 | //UInt_t data_px;
|
|---|
| 34 | //UInt_t data_roi;
|
|---|
| 35 | vector<int16_t> Data; // vector, which will be filled with raw data
|
|---|
| 36 | vector<int16_t> StartCells; // vector, which will be filled with DRS start positions
|
|---|
| 37 | unsigned int EventID; // index of the current event
|
|---|
| 38 | UInt_t RegionOfInterest; // Width of the Region, read out of the DRS
|
|---|
| 39 | UInt_t NumberOfPixels; // Total number of pixel, read out of the camera
|
|---|
| 40 | size_t PXLxROI; // Size of column "Data" = #Pixel x ROI
|
|---|
| 41 |
|
|---|
| 42 | int NEvents;
|
|---|
| 43 | int NBSLeve = 1000;
|
|---|
| 44 |
|
|---|
| 45 | size_t drs_n;
|
|---|
| 46 | vector<float> drs_basemean;
|
|---|
| 47 | vector<float> drs_gainmean;
|
|---|
| 48 | vector<float> drs_triggeroffsetmean;
|
|---|
| 49 |
|
|---|
| 50 | size_t FOpenDataFile(
|
|---|
| 51 | const char *datafilename, // path to fits file containing FACT raw data
|
|---|
| 52 | fits * * datafile, // pointer to pointer, where to return the fits object
|
|---|
| 53 | vector<int16_t> &Data, // vector, which will be filled with raw data
|
|---|
| 54 | vector<int16_t> &StartCells, // vector, which will be filled with DRS start positions
|
|---|
| 55 | unsigned int &EventID, // index of the current event
|
|---|
| 56 | UInt_t &RegionOfInterest, // Width of the Region, read out of the DRS
|
|---|
| 57 | UInt_t &NumberOfPixels, // Total number of pixel, read out of the camera
|
|---|
| 58 | size_t &PXLxROI, // Size of column "Data" = #Pixel x ROI
|
|---|
| 59 | // this can be used, to x-check RegionOfInterest and NumberOfPixels
|
|---|
| 60 | int VerbosityLevel=1
|
|---|
| 61 | );
|
|---|
| 62 |
|
|---|
| 63 |
|
|---|
| 64 | vector<float> Ameas(FAD_MAX_SAMPLES); // copy of the data (measured amplitude
|
|---|
| 65 | vector<float> N1mean(FAD_MAX_SAMPLES); // mean of the +1 -1 ch neighbors
|
|---|
| 66 | vector<float> N2mean(FAD_MAX_SAMPLES); // mean of the +2 -2 ch neighbors
|
|---|
| 67 | vector<float> Vcorr(FAD_MAX_SAMPLES); // corrected Values
|
|---|
| 68 | vector<float> Vdiff(FAD_MAX_SAMPLES); // numerical derivative
|
|---|
| 69 |
|
|---|
| 70 | vector<float> Vslide(FAD_MAX_SAMPLES); // sliding average result
|
|---|
| 71 | vector<float> Vcfd(FAD_MAX_SAMPLES); // CDF result
|
|---|
| 72 | vector<float> Vcfd2(FAD_MAX_SAMPLES); // CDF result + 2nd sliding average
|
|---|
| 73 |
|
|---|
| 74 |
|
|---|
| 75 | float getValue( int, int );
|
|---|
| 76 | void computeN1mean( int );
|
|---|
| 77 | void removeSpikes( int );
|
|---|
| 78 |
|
|---|
| 79 | // histograms
|
|---|
| 80 | const int Ntypes = 7;
|
|---|
| 81 | const unsigned int // arranged by Dominik
|
|---|
| 82 | tAmeas = 0,
|
|---|
| 83 | tN1mean = 1,
|
|---|
| 84 | tVcorr = 2,
|
|---|
| 85 | tVtest = 3,
|
|---|
| 86 | tVslide = 4,
|
|---|
| 87 | tVcfd = 5,
|
|---|
| 88 | tVcfd2 = 6;
|
|---|
| 89 |
|
|---|
| 90 | TH1F* h;
|
|---|
| 91 | TH2F hPixelCellData(
|
|---|
| 92 | "PixelPedestal", "PixelPedestal", NCELL, 0., NCELL, 200, -50., 150.);
|
|---|
| 93 | TH1F *hBaseline[ NPIX ]; // histograms for baseline extraction
|
|---|
| 94 | TH1F *hMeanBsl, *hpltMeanBsl;
|
|---|
| 95 | TH1F *hRmsBsl, *hpltRmsBsl;
|
|---|
| 96 | TObjArray hList;
|
|---|
| 97 | TObjArray hListBaseline;
|
|---|
| 98 |
|
|---|
| 99 | void BookHistos( int , int);
|
|---|
| 100 | void SaveHistograms( const char * );
|
|---|
| 101 |
|
|---|
| 102 | // Create a canvas
|
|---|
| 103 | TCanvas* CW;
|
|---|
| 104 | TCanvas* cFilter;
|
|---|
| 105 |
|
|---|
| 106 | int spikeDebug = 0;
|
|---|
| 107 | int searchSinglesPeaks = 0;
|
|---|
| 108 |
|
|---|
| 109 |
|
|---|
| 110 | int fbsl(
|
|---|
| 111 | const char *datafilename = "path-to-datafile.fits.gz",
|
|---|
| 112 | const char *drsfilename = "path-to-calibfile.drs.fits.gz",
|
|---|
| 113 | const char *TextOutFileName = "./appendfile.txt",
|
|---|
| 114 | const char *RootOutFileName = "./datafile.root",
|
|---|
| 115 | int firstevent = 0,
|
|---|
| 116 | int nevents = -1,
|
|---|
| 117 | int firstpixel = 0,
|
|---|
| 118 | int npixel = -1,
|
|---|
| 119 | bool produceGraphic = false
|
|---|
| 120 | ){
|
|---|
| 121 | fits * datafile = NULL;
|
|---|
| 122 | NEvents = FOpenDataFile(
|
|---|
| 123 | datafilename,
|
|---|
| 124 | &datafile,
|
|---|
| 125 | Data,
|
|---|
| 126 | StartCells,
|
|---|
| 127 | EventID,
|
|---|
| 128 | RegionOfInterest,
|
|---|
| 129 | NumberOfPixels,
|
|---|
| 130 | PXLxROI);
|
|---|
| 131 |
|
|---|
| 132 | printf("number of events in file: %d\n", NEvents);
|
|---|
| 133 |
|
|---|
| 134 | // compare the number of events in the data file with the nevents the
|
|---|
| 135 | // the user would like to read. nevents = -1 means: read all
|
|---|
| 136 | if ( nevents == -1 || nevents > NEvents ) nevents = NEvents;
|
|---|
| 137 |
|
|---|
| 138 | if ( npixel == -1 || npixel > (int)NumberOfPixels) npixel = NumberOfPixels;
|
|---|
| 139 |
|
|---|
| 140 | FOpenCalibFile(drsfilename, drs_basemean, drs_gainmean, drs_triggeroffsetmean, drs_n);
|
|---|
| 141 |
|
|---|
| 142 | BookHistos( RegionOfInterest, npixel );
|
|---|
| 143 |
|
|---|
| 144 | // loop over events
|
|---|
| 145 | for ( int ev = firstevent; ev < firstevent + nevents; ev++) {
|
|---|
| 146 |
|
|---|
| 147 | datafile->GetRow( ev );
|
|---|
| 148 |
|
|---|
| 149 | if ( ev % 100 == 0 ){
|
|---|
| 150 | cout << "Event ID: " << EventID << endl;
|
|---|
| 151 | }
|
|---|
| 152 |
|
|---|
| 153 | // loop over pixel
|
|---|
| 154 | for ( int pix = firstpixel ; pix < npixel+firstpixel ; pix++ ){
|
|---|
| 155 |
|
|---|
| 156 | // loop over DRS slices
|
|---|
| 157 | for ( unsigned int sl = 0; sl < RegionOfInterest; sl++){
|
|---|
| 158 | Ameas[ sl ] = getValue(sl, pix);
|
|---|
| 159 | }
|
|---|
| 160 |
|
|---|
| 161 | computeN1mean( RegionOfInterest ); // prepare spike removal
|
|---|
| 162 | removeSpikes (RegionOfInterest ); // output in Vcorr
|
|---|
| 163 |
|
|---|
| 164 | // filter Vcorr with sliding average using FIR filter function
|
|---|
| 165 | // 8 is here the HalfWidth of the sliding average window.
|
|---|
| 166 | sliding_avg(Vcorr, Vslide, 8);
|
|---|
| 167 |
|
|---|
| 168 | // factfir(b_slide , a_slide, k_slide, Vcorr, Vslide);
|
|---|
| 169 |
|
|---|
| 170 | for ( unsigned int sl = 0; sl <RegionOfInterest ; sl++){
|
|---|
| 171 | // hPixelCellData.Fill( sl, Vcorr[sl] );
|
|---|
| 172 | hBaseline[pix-firstpixel]->Fill( Vslide[sl] ) ;
|
|---|
| 173 | }
|
|---|
| 174 | }
|
|---|
| 175 | }
|
|---|
| 176 |
|
|---|
| 177 | FILE *fp;
|
|---|
| 178 | TString fName;
|
|---|
| 179 | fName = TextOutFileName;
|
|---|
| 180 |
|
|---|
| 181 | fp = fopen(fName, "a+");
|
|---|
| 182 | fprintf( fp, "FILE: %s\n", datafilename );
|
|---|
| 183 | fprintf( fp, "NEVENTS: %d\n", nevents);
|
|---|
| 184 | NBSLeve = nevents; // this has to be changed when computation on a subset of a run is implemented
|
|---|
| 185 | fprintf( fp, "NBSLEVE: %d\n", NBSLeve );
|
|---|
| 186 |
|
|---|
| 187 | for (int pix = firstpixel; pix < firstpixel+npixel; pix++) {
|
|---|
| 188 |
|
|---|
| 189 | float vmaxprob = hBaseline[pix]->GetXaxis()->GetBinCenter(
|
|---|
| 190 | hBaseline[pix-firstpixel]->GetMaximumBin() );
|
|---|
| 191 |
|
|---|
| 192 | fprintf( fp, "%8.3f", vmaxprob );
|
|---|
| 193 |
|
|---|
| 194 | hMeanBsl->Fill( vmaxprob );
|
|---|
| 195 | hpltMeanBsl->SetBinContent(pix+1, vmaxprob );
|
|---|
| 196 |
|
|---|
| 197 | hRmsBsl->Fill(hBaseline[pix-firstpixel]->GetRMS() );
|
|---|
| 198 | hpltRmsBsl->SetBinContent( pix+1, hBaseline[pix]->GetRMS() );
|
|---|
| 199 | }
|
|---|
| 200 | fprintf( fp, "\n" );
|
|---|
| 201 |
|
|---|
| 202 | fclose( fp );
|
|---|
| 203 |
|
|---|
| 204 | SaveHistograms( RootOutFileName );
|
|---|
| 205 | if (produceGraphic){
|
|---|
| 206 | TCanvas * cMeanBsl = new TCanvas();
|
|---|
| 207 | cMeanBsl->cd();
|
|---|
| 208 | hMeanBsl->Draw();
|
|---|
| 209 | cMeanBsl->Update();
|
|---|
| 210 |
|
|---|
| 211 | TCanvas * cRmsBsl = new TCanvas();
|
|---|
| 212 | cRmsBsl->cd();
|
|---|
| 213 | hRmsBsl->Draw();
|
|---|
| 214 | cMeanBsl->Update();
|
|---|
| 215 | }
|
|---|
| 216 | return( 0 );
|
|---|
| 217 | }
|
|---|
| 218 |
|
|---|
| 219 | void removeSpikes(int Samples){
|
|---|
| 220 |
|
|---|
| 221 | const float fract = 0.8;
|
|---|
| 222 | float x, xp, xpp;
|
|---|
| 223 |
|
|---|
| 224 | // assume that there are no spikes
|
|---|
| 225 | for ( int i = 0; i < Samples; i++) Vcorr[i] = Ameas[i];
|
|---|
| 226 |
|
|---|
| 227 | // find the spike and replace it by mean value of neighbors
|
|---|
| 228 | for ( int i = 2; i < Samples-2 ; i++) {
|
|---|
| 229 |
|
|---|
| 230 | x = Ameas[i] - N1mean[i];
|
|---|
| 231 |
|
|---|
| 232 | if ( x < -5. ){ // a spike candidate
|
|---|
| 233 | // check consistency with a single channel spike
|
|---|
| 234 | xp = Ameas[i+1] - N1mean[i+1];
|
|---|
| 235 | xpp = Ameas[i+2] - N1mean[i+2];
|
|---|
| 236 |
|
|---|
| 237 | if ( Ameas[i+2] - ( Ameas[i] + Ameas[i+3] )/2. > 10. ){
|
|---|
| 238 | // printf("double spike candidate\n");
|
|---|
| 239 | Vcorr[i+1] = ( Ameas[i] + Ameas[i+3] )/2.;
|
|---|
| 240 | Vcorr[i+2] = ( Ameas[i] + Ameas[i+3] )/2.;
|
|---|
| 241 | i = i + 3;
|
|---|
| 242 | }
|
|---|
| 243 | else{
|
|---|
| 244 |
|
|---|
| 245 | if ( ( xp > -2.*x*fract ) && ( xpp < -10. ) ){
|
|---|
| 246 | Vcorr[i+1] = N1mean[i+1];
|
|---|
| 247 | // printf("Vcorr[%d] = %f %f %f\n", i, Vcorr[i], Vcorr[i+1], Vcorr[i+2]);
|
|---|
| 248 | // N1mean[i+1] = (Ameas[i] - Ameas[i+2] / 2.);
|
|---|
| 249 | N1mean[i+2] = (Ameas[i+1] - Ameas[i+3] / 2.);
|
|---|
| 250 | i = i + 2;//do not care about the next sample it was the spike
|
|---|
| 251 | }
|
|---|
| 252 | // treatment for the end of the pipeline must be added !!!
|
|---|
| 253 | }
|
|---|
| 254 | }
|
|---|
| 255 | else{
|
|---|
| 256 | // do nothing
|
|---|
| 257 | }
|
|---|
| 258 | } // end of spike search and correction
|
|---|
| 259 | }
|
|---|
| 260 |
|
|---|
| 261 | void computeN1mean( int Samples ){
|
|---|
| 262 | // compute the mean of the left and right neighbors of a channel
|
|---|
| 263 |
|
|---|
| 264 | for( int i = 2; i < Samples - 2; i++){
|
|---|
| 265 | /* if (i == 0){ // use right sample es mean
|
|---|
| 266 | N1mean[i] = Ameas[i+1];
|
|---|
| 267 | }
|
|---|
| 268 | else if ( i == Samples-1 ){ //use left sample as mean
|
|---|
| 269 | N1mean[i] = Ameas[i-1];
|
|---|
| 270 | }
|
|---|
| 271 | else{
|
|---|
| 272 | N1mean[i] = ( Ameas[i-1] + Ameas[i+1] ) / 2.;
|
|---|
| 273 | }
|
|---|
| 274 | */
|
|---|
| 275 | N1mean[i] = ( Ameas[i-1] + Ameas[i+1] ) / 2.;
|
|---|
| 276 | }
|
|---|
| 277 | } // end of computeN1mean computation
|
|---|
| 278 |
|
|---|
| 279 | float getValue( int slice, int pixel ){
|
|---|
| 280 |
|
|---|
| 281 | const float dconv = 2000/4096.0;
|
|---|
| 282 |
|
|---|
| 283 | float vraw, vcal;
|
|---|
| 284 |
|
|---|
| 285 | unsigned int pixel_pt;
|
|---|
| 286 | unsigned int slice_pt;
|
|---|
| 287 | unsigned int cal_pt;
|
|---|
| 288 | unsigned int drs_cal_offset;
|
|---|
| 289 |
|
|---|
| 290 | // printf("pixel = %d, slice = %d\n", slice, pixel);
|
|---|
| 291 |
|
|---|
| 292 | pixel_pt = pixel * RegionOfInterest;
|
|---|
| 293 | slice_pt = pixel_pt + slice;
|
|---|
| 294 | drs_cal_offset = ( slice + StartCells[ pixel ] )%RegionOfInterest;
|
|---|
| 295 | cal_pt = pixel_pt + drs_cal_offset;
|
|---|
| 296 |
|
|---|
| 297 | vraw = Data[ slice_pt ] * dconv;
|
|---|
| 298 | vcal = ( vraw - drs_basemean[ cal_pt ] - drs_triggeroffsetmean[ slice_pt ] ) / drs_gainmean[ cal_pt ]*1907.35;
|
|---|
| 299 |
|
|---|
| 300 | return( vcal );
|
|---|
| 301 | }
|
|---|
| 302 |
|
|---|
| 303 | void BookHistos( int Samples , int NumberOfPixel){
|
|---|
| 304 | // booking and parameter settings for all histos
|
|---|
| 305 |
|
|---|
| 306 | // histograms for baseline extraction
|
|---|
| 307 | char hName[500];
|
|---|
| 308 | char hTitle[500];
|
|---|
| 309 |
|
|---|
| 310 | TH1F *h;
|
|---|
| 311 |
|
|---|
| 312 | printf("inside BookHistos\n");
|
|---|
| 313 |
|
|---|
| 314 | for( int i = 0; i < NumberOfPixel; i++ ) {
|
|---|
| 315 |
|
|---|
| 316 | // printf("call sprintf [%d]\n", i );
|
|---|
| 317 | sprintf(&hTitle[0],"all events all slices of pixel %d", i);
|
|---|
| 318 | sprintf(&hName[0],"base%d", i);
|
|---|
| 319 | // printf("call sprintf [%d] done\n", i );
|
|---|
| 320 |
|
|---|
| 321 | h = new TH1F( hName, hTitle, 400, -99.5 ,100.5 );
|
|---|
| 322 |
|
|---|
| 323 | // printf("histo booked\n");
|
|---|
| 324 | h->GetXaxis()->SetTitle( "Sample value (mV)" );
|
|---|
| 325 | h->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
|
|---|
| 326 | // printf("histo title set\n");
|
|---|
| 327 | hListBaseline.Add( h );
|
|---|
| 328 | // printf("histo added to List\n");
|
|---|
| 329 | hBaseline[i] = h;
|
|---|
| 330 | // printf("histo assigned to array\n");
|
|---|
| 331 | }
|
|---|
| 332 |
|
|---|
| 333 | printf("made HBaseline * 1440\n");
|
|---|
| 334 |
|
|---|
| 335 | hMeanBsl = new TH1F("histo_mean","Value of maximal probability",400,-99.5,100.5);
|
|---|
| 336 | hMeanBsl->GetXaxis()->SetTitle( "max value (mV)" );
|
|---|
| 337 | hMeanBsl->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
|
|---|
| 338 | hList.Add( hMeanBsl );
|
|---|
| 339 |
|
|---|
| 340 | hpltMeanBsl = new TH1F("hplt_mean","Value of maximal probability",1440,-0.5,1439.5);
|
|---|
| 341 | hpltMeanBsl->GetXaxis()->SetTitle( "pixel" );
|
|---|
| 342 | hpltMeanBsl->GetYaxis()->SetTitle( "max value in mV" );
|
|---|
| 343 | hList.Add( hpltMeanBsl );
|
|---|
| 344 |
|
|---|
| 345 | hRmsBsl = new TH1F("histo_rms","RMS in mV",2000,-99.5,100.5);
|
|---|
| 346 | hRmsBsl->GetXaxis()->SetTitle( "RMS (mV)" );
|
|---|
| 347 | hRmsBsl->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
|
|---|
| 348 | hList.Add( hRmsBsl );
|
|---|
| 349 |
|
|---|
| 350 | hpltRmsBsl = new TH1F("hplt_rms","Value of maximal probability",1440,-0.5,1439.5);
|
|---|
| 351 | hpltRmsBsl->GetXaxis()->SetTitle( "pixel" );
|
|---|
| 352 | hpltRmsBsl->GetYaxis()->SetTitle( "RMS in mV" );
|
|---|
| 353 | hList.Add( hpltRmsBsl );
|
|---|
| 354 | }
|
|---|
| 355 |
|
|---|
| 356 |
|
|---|
| 357 | void SaveHistograms( const char * loc_fname ){
|
|---|
| 358 |
|
|---|
| 359 | TString fName; // name of the histogram file
|
|---|
| 360 |
|
|---|
| 361 | /* create the filename for the histogram file */
|
|---|
| 362 | fName = loc_fname; // use the name of the tree file
|
|---|
| 363 | //fName.Remove(fName.Length() - 5); // remove the extension .root
|
|---|
| 364 | //fName += "_histo.root"; // add the new extension
|
|---|
| 365 | //fName += ".root";
|
|---|
| 366 |
|
|---|
| 367 | TFile tf( fName, "RECREATE"); // create the histogram file (replace if already existing)
|
|---|
| 368 |
|
|---|
| 369 | hList.Write(); // write the major histograms into the top level directory
|
|---|
| 370 | tf.mkdir("BaselineHisto"); tf.cd("BaselineHisto"); // go to new subdirectory
|
|---|
| 371 | hListBaseline.Write(); // write histos into subdirectory
|
|---|
| 372 |
|
|---|
| 373 | tf.Close(); // close the file
|
|---|
| 374 |
|
|---|
| 375 | } // end of function: void ana::SaveHistograms( void )
|
|---|
| 376 |
|
|---|
| 377 | size_t FOpenDataFile(
|
|---|
| 378 | const char *datafilename, // path to fits file containing FACT raw data
|
|---|
| 379 | fits * * datafile, // ptr to pointer, where to return the fits object
|
|---|
| 380 | vector<int16_t> &Data, // vector, which will be filled with raw data
|
|---|
| 381 | vector<int16_t> &StartCells, // vector, which will be filled with DRS start positions
|
|---|
| 382 | unsigned int &EventID, // index of the current event
|
|---|
| 383 | UInt_t &RegionOfInterest, // Width of the Region, read out of the DRS
|
|---|
| 384 | UInt_t &NumberOfPixels, // Total number of pixel, read out of the camera
|
|---|
| 385 | size_t &PXLxROI, // Size of column "Data" = #Pixel x ROI
|
|---|
| 386 | // this can be used, to x-check RegionOfInterest and NumberOfPixels
|
|---|
| 387 | int VerbosityLevel //
|
|---|
| 388 | ) {
|
|---|
| 389 | size_t NumberOfEvents;
|
|---|
| 390 | *datafile = new fits(datafilename);
|
|---|
| 391 | if (!(*(*datafile))) {
|
|---|
| 392 | if (VerbosityLevel > 0)
|
|---|
| 393 | cout << "Couldn't properly open the datafile: " << datafilename << endl;
|
|---|
| 394 | return 0;
|
|---|
| 395 | }
|
|---|
| 396 |
|
|---|
| 397 | NumberOfEvents = (*datafile)->GetNumRows();
|
|---|
| 398 | if (NumberOfEvents < 1){
|
|---|
| 399 | if (VerbosityLevel > 0){
|
|---|
| 400 | cout << "Warning in FOpenDataFile of file: " << datafilename << endl;
|
|---|
| 401 | cout << "the file contains no events." << endl;
|
|---|
| 402 | }
|
|---|
| 403 | }
|
|---|
| 404 |
|
|---|
| 405 | RegionOfInterest = (*datafile)->GetUInt("NROI");
|
|---|
| 406 | NumberOfPixels = (*datafile)->GetUInt("NPIX");
|
|---|
| 407 | PXLxROI = (*datafile)->GetN("Data");
|
|---|
| 408 |
|
|---|
| 409 | if ( RegionOfInterest * NumberOfPixels != PXLxROI) // something in the file went wrong
|
|---|
| 410 | {
|
|---|
| 411 | if (VerbosityLevel > 0){
|
|---|
| 412 | cout << "Warning in FOpenDataFile of file: " << datafilename << endl;
|
|---|
| 413 | cout << "RegionOfInterest * NumberOfPixels != PXLxROI" << endl;
|
|---|
| 414 | cout << "--> " << RegionOfInterest;
|
|---|
| 415 | cout << " * " << NumberOfPixels;
|
|---|
| 416 | cout << " = " << RegionOfInterest * NumberOfPixels;
|
|---|
| 417 | cout << ", but PXLxROI =" << PXLxROI << endl;
|
|---|
| 418 | }
|
|---|
| 419 | return 0;
|
|---|
| 420 | }
|
|---|
| 421 |
|
|---|
| 422 | //Set the sizes of the data vectors
|
|---|
| 423 | Data.resize(PXLxROI, 0);
|
|---|
| 424 | StartCells.resize(NumberOfPixels, 0);
|
|---|
| 425 |
|
|---|
| 426 | //Link the data to variables
|
|---|
| 427 | (*datafile)->SetRefAddress("EventNum", EventID);
|
|---|
| 428 | (*datafile)->SetVecAddress("Data", Data);
|
|---|
| 429 | (*datafile)->SetVecAddress("StartCellData", StartCells);
|
|---|
| 430 |
|
|---|
| 431 | return NumberOfEvents;
|
|---|
| 432 | }
|
|---|
| 433 |
|
|---|