source: fact/tools/rootmacros/fbsl.C@ 12515

#include <TROOT.h>
#include <TCanvas.h>
#include <TProfile.h>
#include <TTimer.h>
#include <TH1F.h>
#include <TH2F.h>
#include <Getline.h>
#include <TLine.h>
#include <TMath.h>
#include <TFile.h>

#include <stdio.h>
#include <stdint.h>
#include <cstdio>

#define HAVE_ZLIB
#include "fits.h"

#include "openFits.h"
#include "openFits.c"

#include "DrsCalibration.h"
#include "DrsCalibration.C"

#include "SpikeRemoval.h"
#include "SpikeRemoval.C"

//#include "zerosearch.C"
#include "factfir.C"

#define NPIX  1440
#define NCELL 1024

// data access and treatment
#define FAD_MAX_SAMPLES 1024

int NEvents;
vector<int16_t> Data;                           // vector, which will be filled with raw data
vector<int16_t> StartCells;     // vector, which will be filled with DRS start positions
unsigned int EventID;                           // index of the current event
UInt_t RegionOfInterest;                // Width of the Region, read out of the DRS
UInt_t NumberOfPixels;                  // Total number of pixel, read out of the camera
size_t PXLxROI;                                                 // Size of column "Data" = #Pixel x ROI

int NBSLeve = 1000;

size_t TriggerOffsetROI, RC;
vector<float> Offset, Gain, TriggerOffset;


vector<float> Ameas(FAD_MAX_SAMPLES);  // copy of the data (measured amplitude
vector<float> N1mean(FAD_MAX_SAMPLES); // mean of the +1 -1 ch neighbors
vector<float> N2mean(FAD_MAX_SAMPLES); // mean of the +2 -2 ch neighbors
vector<float> Vcorr(FAD_MAX_SAMPLES);  // corrected Values
vector<float> Vdiff(FAD_MAX_SAMPLES);  // numerical derivative

vector<float> Vslide(FAD_MAX_SAMPLES);  // sliding average result
vector<float> Vcfd(FAD_MAX_SAMPLES);    // CDF result
vector<float> Vcfd2(FAD_MAX_SAMPLES);    // CDF result + 2nd sliding average



// histograms
const int Ntypes = 7;
const unsigned int  // arranged by Dominik
        tAmeas  = 0, 
        tN1mean = 1, 
        tVcorr  = 2,
        tVtest  = 3,
        tVslide = 4,
        tVcfd   = 5,
        tVcfd2  = 6;

TH1F* h;
TH2F hPixelCellData(
    "PixelPedestal", "PixelPedestal", NCELL, 0., NCELL, 200, -50., 150.);
TH1F *hBaseline[ NPIX ]; // histograms for baseline extraction
TH1F *hMeanBsl, *hpltMeanBsl;
TH1F *hRmsBsl, *hpltRmsBsl; 
TObjArray hList;
TObjArray hListBaseline;

void BookHistos( int , int);
void SaveHistograms( const char * );

// Create a canvas
TCanvas* CW;
TCanvas* cFilter;

int spikeDebug = 0;
int searchSinglesPeaks = 0;

int fbsl( 
        const char *datafilename                = "path-to-datafile.fits.gz",
        const char *drsfilename = "path-to-calibfile.drs.fits.gz",
        const char *TextOutFileName = "./appendfile.txt",
        const char *RootOutFileName = "./datafile.root",
        int firstevent                  = 0, 
        int nevents                     = -1, 
        int firstpixel          = 0,
        int npixel                              = -1,
        bool produceGraphic = true
){
        fits * datafile = NULL;

        NEvents = openDataFits(
                datafilename,
                &datafile,
                Data,
                StartCells,
                EventID,
                RegionOfInterest,
                NumberOfPixels,
                PXLxROI);

    printf("number of events in file: %d\n", NEvents);
        if (NEvents == 0){
                cout << "return code of openDataFits:" << datafilename<< endl;
                cout << "is zero -> aborting." << endl;
                return 1;
        }


    // compare the number of events in the data file with the nevents the
    // the user would like to read. nevents = -1 means: read all
    if ( nevents == -1 || nevents > NEvents ) nevents = NEvents;
        if ( npixel == -1 || npixel > (int)NumberOfPixels) npixel = NumberOfPixels;

        RC = openCalibFits( drsfilename, Offset, Gain, TriggerOffset, TriggerOffsetROI);
        if (RC == 0){
                cout << "return code of openCalibFits:" << drsfilename << endl;
                cout << "is zero -> aborting." << endl;
                return 1;
        }


  BookHistos( RegionOfInterest, npixel );
    
                // loop over events
    for ( int ev = firstevent; ev < firstevent + nevents; ev++) {

            datafile->GetRow( ev );
                
                if ( ev % 100 == 0 ){
                        cout << "Event ID: " << EventID << endl;
                }
                
                // loop over pixel
                for ( int pix = firstpixel ; pix < npixel+firstpixel ; pix++ ){


                        // get the data of this pixel from the  Data  vector
                        // apply the Drs Calibration and cut off 12 slices at the beginning
                        // and at the end.
                        applyDrsCalibration( Ameas,pix,12,12,
                                Offset, Gain, TriggerOffset,
                                RegionOfInterest, Data, StartCells);

                        // finds spikes in the raw data, and interpolates the value
                        // spikes are: 1 or 2 slice wide, positive non physical artifacts
                        removeSpikes (Ameas, Vcorr);

                        // filter Vcorr with sliding average using FIR filter function
                        // 8 is here the HalfWidth of the sliding average window.
                        sliding_avg(Vcorr, Vslide, 8);

            for ( unsigned int sl = 0; sl <RegionOfInterest ; sl++){
               // hPixelCellData.Fill( sl, Vcorr[sl] );
               hBaseline[pix-firstpixel]->Fill( Vslide[sl] ) ;
            }   
            }
    }

    FILE *fp;
    TString fName; 
    fName = TextOutFileName;

    fp = fopen(fName, "a+");
    fprintf( fp, "FILE: %s\n", datafilename );
    fprintf( fp, "NEVENTS: %d\n", nevents);
    NBSLeve = nevents; // this has to be changed when computation on a subset of a run is implemented
    fprintf( fp, "NBSLEVE:  %d\n", NBSLeve );

    for (int pix = firstpixel; pix < firstpixel+npixel; pix++) {

        float vmaxprob = hBaseline[pix]->GetXaxis()->GetBinCenter(
            hBaseline[pix-firstpixel]->GetMaximumBin() );

        fprintf( fp, "%8.3f", vmaxprob );

        hMeanBsl->Fill( vmaxprob );
        hpltMeanBsl->SetBinContent(pix+1, vmaxprob );

        hRmsBsl->Fill(hBaseline[pix-firstpixel]->GetRMS() );
        hpltRmsBsl->SetBinContent( pix+1, hBaseline[pix]->GetRMS() );   
    }
    fprintf( fp, "\n" );

    fclose( fp );

    SaveHistograms( RootOutFileName );
                if (produceGraphic){
        TCanvas * cMeanBsl = new TCanvas();
        cMeanBsl->cd();
        hMeanBsl->Draw();
        cMeanBsl->Update();

        TCanvas * cRmsBsl = new TCanvas();
        cRmsBsl->cd();
        hRmsBsl->Draw();
        cMeanBsl->Update();
                }
        return( 0 );
}

void BookHistos( int Samples , int NumberOfPixel){
// booking and parameter settings for all histos

    // histograms for baseline extraction
    char hName[500];
    char hTitle[500];

    TH1F *h;
    
    printf("inside BookHistos\n");

    for( int i = 0; i < NumberOfPixel; i++ ) {

        // printf("call sprintf [%d]\n", i );
        sprintf(&hTitle[0],"all events all slices of pixel %d", i);
        sprintf(&hName[0],"base%d", i);
        // printf("call sprintf [%d] done\n", i );

        h = new TH1F( hName, hTitle, 400, -99.5 ,100.5 );

        // printf("histo booked\n");
        h->GetXaxis()->SetTitle( "Sample value (mV)" );
        h->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
        // printf("histo title set\n");
        hListBaseline.Add( h );
        // printf("histo added to List\n");
        hBaseline[i] = h;
        // printf("histo assigned to array\n");
    }

    printf("made HBaseline * 1440\n");

    hMeanBsl = new TH1F("histo_mean","Value of maximal probability",400,-99.5,100.5);
    hMeanBsl->GetXaxis()->SetTitle( "max value (mV)" );
    hMeanBsl->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
    hList.Add( hMeanBsl );

    hpltMeanBsl = new TH1F("hplt_mean","Value of maximal probability",1440,-0.5,1439.5);
    hpltMeanBsl->GetXaxis()->SetTitle( "pixel" );
    hpltMeanBsl->GetYaxis()->SetTitle( "max value in mV" );
    hList.Add( hpltMeanBsl );

    hRmsBsl = new TH1F("histo_rms","RMS in mV",2000,-99.5,100.5);
    hRmsBsl->GetXaxis()->SetTitle( "RMS (mV)" );
    hRmsBsl->GetYaxis()->SetTitle( "Entries / 0.5 mV" );
    hList.Add( hRmsBsl );

    hpltRmsBsl = new TH1F("hplt_rms","Value of maximal probability",1440,-0.5,1439.5);
    hpltRmsBsl->GetXaxis()->SetTitle( "pixel" );
    hpltRmsBsl->GetYaxis()->SetTitle( "RMS in mV" );
    hList.Add( hpltRmsBsl );
}


void SaveHistograms( const char * loc_fname ){

  TString fName; // name of the histogram file

  /* create the filename for the histogram file */
  fName = loc_fname; // use the name of the tree file
  //fName.Remove(fName.Length() - 5); // remove the extension .root
  //fName += "_histo.root"; // add the new extension
  //fName += ".root"; 

  TFile tf( fName, "RECREATE"); // create the histogram file (replace if already existing)

  hList.Write(); // write the major histograms into the top level directory 
  tf.mkdir("BaselineHisto"); tf.cd("BaselineHisto"); // go to new subdirectory
  hListBaseline.Write(); // write histos into subdirectory
  
  tf.Close(); // close the file

} // end of function: void ana::SaveHistograms( void )