88     :
TH1(
name,title,nbinsx,xlow,xup)
 
   93   if (nbinsy <= 0) {
Warning(
"TH2",
"nbinsy is <=0 - set to nbinsy = 1"); nbinsy = 1; }
 
  122   if (nbinsy <= 0) {
Warning(
"TH2",
"nbinsy is <=0 - set to nbinsy = 1"); nbinsy = 1; }
 
  145     :
TH1(
name,title,nbinsx,xlow,xup)
 
  150   if (nbinsy <= 0) {
Warning(
"TH2",
"nbinsy is <=0 - set to nbinsy = 1"); nbinsy = 1; }
 
  179   if (nbinsy <= 0) {
Warning(
"TH2",
"nbinsy is <=0 - set to nbinsy = 1"); nbinsy = 1; }
 
  209   if (nbinsy <= 0) {
Warning(
"TH2",
"nbinsy is <=0 - set to nbinsy = 1"); nbinsy = 1; }
 
  251   if (nbentries == 0) 
return 0;
 
  252   if (nbentries < 0 && action == 0) 
return 0;    
 
  256      nbentries  = -nbentries;
 
  271      for (
Int_t i=1;i<nbentries;i++) {
 
  294   for (
Int_t i=0;i<nbentries;i++) {
 
  295      Fill(buffer[3*i+2],buffer[3*i+3],buffer[3*i+1]);
 
  322      nbentries  = -nbentries;
 
  360   Error(
"Fill", 
"Invalid signature - do nothing");
 
  384   Int_t binx, biny, bin;
 
  388   if (binx <0 || biny <0) 
return -1;
 
  428   Int_t binx, biny, bin;
 
  432   if (binx <0 || biny <0) 
return -1;
 
  472   Int_t binx, biny, bin;
 
  476   if (binx <0 || biny <0) 
return -1;
 
  519   Int_t binx, biny, bin;
 
  523   if (binx <0 || biny <0) 
return -1;
 
  564   Int_t binx, biny, bin;
 
  568   if (binx <0 || biny <0) 
return -1;
 
  611   Int_t binx, biny, bin, i;
 
  618      for (i=0;i<ntimes;i+=stride) {
 
  631   for (i=ifirst;i<ntimes;i+=stride) {
 
  635      if (binx <0 || biny <0) 
continue;
 
  679   Int_t bin, binx, biny, ibin, loop;
 
  683   if (!fobj) { 
Error(
"FillRandom", 
"Unknown function: %s",fname); 
return; }
 
  684   TF2 * 
f1 = 
dynamic_cast<TF2*
>(fobj);
 
  685   if (!
f1) { 
Error(
"FillRandom", 
"Function: %s is not a TF2, is a %s",fname,fobj->IsA()->
GetName()); 
return; }
 
  704   Int_t nbins  = nbinsx*nbinsy;
 
  710   for (biny=1;biny<=nbinsy;biny++) {
 
  711      for (binx=1;binx<=nbinsx;binx++) {
 
  714         integral[ibin] = integral[ibin-1] + fint;
 
  719   if (integral[nbins] == 0 ) {
 
  721      Error(
"FillRandom", 
"Integral = zero"); 
return;
 
  723   for (bin=1;bin<=nbins;bin++)  integral[bin] /= integral[nbins];
 
  726   for (loop=0;loop<ntimes;loop++) {
 
  730      binx = 1 + ibin - nbinsx*biny;
 
  758   if (!
h) { 
Error(
"FillRandom", 
"Null histogram"); 
return; }
 
  760      Error(
"FillRandom", 
"Histograms with different dimensions"); 
return;
 
  763   if (
h->ComputeIntegral() == 0) 
return;
 
  768   for (loop=0;loop<ntimes;loop++) {
 
  793      if (firstbin == 0 && lastbin == 0)  {
 
  798   if (firstbin < 0) firstbin = 0;
 
  799   if (lastbin < 0 || lastbin > nbins + 1) lastbin = nbins + 1;
 
  800   if (lastbin < firstbin) {firstbin = 0; lastbin = nbins + 1;}
 
  807   if (i1>=0 && i2>i1) {
 
  808      proj_opt += opt(i1,i2-i1+1);
 
  819   Int_t nstep = ngroup;
 
  829   if (npar <= 0) 
return;
 
  841   char *
name   = 
new char[2000];
 
  842   char *title  = 
new char[2000];
 
  848   Int_t nOutBins = lastOutBin-firstOutBin+1;
 
  850   if (bins->
fN == 0) nOutBins /= nstep;
 
  851   for (ipar=0;ipar<npar;ipar++) {
 
  858         hlist[ipar] = 
new TH1D(
name,title, nOutBins, &bins->
fArray[firstOutBin-1]);
 
  862         (*arr)[ipar] = hlist[ipar];
 
  870      hchi2 = 
new TH1D(
name,
"chisquare", nOutBins, &bins->
fArray[firstOutBin-1]);
 
  874      (*arr)[npar] = hchi2;
 
  884   for (bin=firstbin;bin+ngroup-1<=lastbin;bin += nstep) {
 
  886         hp= 
ProjectionX(
"_temp",bin,bin+ngroup-1,proj_opt);
 
  888         hp= 
ProjectionY(
"_temp",bin,bin+ngroup-1,proj_opt);
 
  889      if (hp == 0) 
continue;
 
  894               Info(
"DoFitSlices",
"Slice %d skipped, the number of entries is zero or smaller than the given cut value, n=%f",bin,
nentries);
 
  903      if (npfits > npar && npfits >= cut) {
 
  904         for (ipar=0;ipar<npar;ipar++) {
 
  912            Info(
"DoFitSlices",
"Fitted slice %d skipped, the number of fitted points is too small, n=%d",bin,npfits);
 
  981   DoFitSlices(
true, 
f1, firstybin, lastybin, cut, option, arr);
 
 1046   DoFitSlices(
false, 
f1, firstxbin, lastxbin, cut, option, arr);
 
 1053   if (biny < 0) biny = 0;
 
 1054   if (biny > ofy) biny = ofy;
 
 1086      Error(
"GetBinWithContent2",
"function is only valid for 2-D histograms");
 
 1089   if (firstxbin < 0) firstxbin = 1;
 
 1091   if (firstybin < 0) firstybin = 1;
 
 1094   for (
Int_t j = firstybin; j <= lastybin; j++) {
 
 1095      for (
Int_t i = firstxbin; i <= lastxbin; i++) {
 
 1097         if (diff <= 0) {binx = i; biny=j; 
return diff;}
 
 1098         if (diff < curmax && diff <= maxdiff) {curmax = diff, binx=i; biny=j;}
 
 1110   if (axis1 < 1 || axis2 < 1 || axis1 > 2 || axis2 > 2) {
 
 1111      Error(
"GetCorrelationFactor",
"Wrong parameters");
 
 1114   if (axis1 == axis2) 
return 1;
 
 1116   if (stddev1 == 0) 
return 0;
 
 1118   if (stddev2 == 0) 
return 0;
 
 1128   if (axis1 < 1 || axis2 < 1 || axis1 > 2 || axis2 > 2) {
 
 1129      Error(
"GetCovariance",
"Wrong parameters");
 
 1142   if (sumw == 0) 
return 0;
 
 1143   if (axis1 == 1 && axis2 == 1) {
 
 1144      return TMath::Abs(sumwx2/sumw - sumwx/sumw*sumwx/sumw);
 
 1146   if (axis1 == 2 && axis2 == 2) {
 
 1147      return TMath::Abs(sumwy2/sumw - sumwy/sumw*sumwy/sumw);
 
 1149   return sumwxy/sumw - sumwx/sumw*sumwy/sumw;
 
 1166   Int_t nbins  = nbinsx*nbinsy;
 
 1175   if (integral == 0 ) { 
x = 0; 
y = 0; 
return;}
 
 1182   Int_t biny = ibin/nbinsx;
 
 1183   Int_t binx = ibin - nbinsx*biny;
 
 1221      std::fill(stats, stats + 7, 0);
 
 1230            if (firstBinX == 1) firstBinX = 0;
 
 1234            if (firstBinY == 1) firstBinY = 0;
 
 1242      for (
Int_t biny = firstBinY; biny <= lastBinY; ++biny) {
 
 1244         for (
Int_t binx = firstBinX; binx <= lastBinX; ++binx) {
 
 1296   return DoIntegral(firstxbin,lastxbin,firstybin,lastybin,-1,0,err,option);
 
 1309   return DoIntegral(firstxbin,lastxbin,firstybin,lastybin,-1,0,error,option,
kTRUE);
 
 1317   Error(
"Interpolate",
"This function must be called with 2 arguments for a TH2");
 
 1336      Error(
"Interpolate",
"Cannot interpolate outside histogram domain.");
 
 1378   if(bin_x1<1) bin_x1=1;
 
 1382   if(bin_y1<1) bin_y1=1;
 
 1394   f = 1.0*q11/
d*(
x2-
x)*(y2-
y)+1.0*q21/
d*(
x-
x1)*(y2-
y)+1.0*q12/
d*(
x2-
x)*(
y-y1)+1.0*q22/
d*(
x-
x1)*(
y-y1);
 
 1404   Error(
"Interpolate",
"This function must be called with 2 arguments for a TH2");
 
 1439   if (h2 == 0) 
return 0;
 
 1451      Error(
"KolmogorovTest",
"Histograms must be 2-D\n");
 
 1457      Error(
"KolmogorovTest",
"Number of channels in X is different, %d and %d\n",ncx1,ncx2);
 
 1461      Error(
"KolmogorovTest",
"Number of channels in Y is different, %d and %d\n",ncy1,ncy2);
 
 1471   if (diff1 > difprec || diff2 > difprec) {
 
 1472      Error(
"KolmogorovTest",
"histograms with different binning along X");
 
 1477   if (diff1 > difprec || diff2 > difprec) {
 
 1478      Error(
"KolmogorovTest",
"histograms with different binning along Y");
 
 1483   Int_t ibeg = 1, jbeg = 1;
 
 1484   Int_t iend = ncx1, jend = ncy1;
 
 1485   if (opt.
Contains(
"U")) {ibeg = 0; jbeg = 0;}
 
 1486   if (opt.
Contains(
"O")) {iend = ncx1+1; jend = ncy1+1;}
 
 1493   for (i = ibeg; i <= iend; i++) {
 
 1494      for (j = jbeg; j <= jend; j++) {
 
 1507      Error(
"KolmogorovTest",
"Integral is zero for h1=%s\n",
h1->
GetName());
 
 1511      Error(
"KolmogorovTest",
"Integral is zero for h2=%s\n",h2->
GetName());
 
 1519      esum1 = sum1 * sum1 / w1;
 
 1524      esum2 = sum2 * sum2 / w2;
 
 1528   if (afunc2 && afunc1) {
 
 1529      Error(
"KolmogorovTest",
"Errors are zero for both histograms\n");
 
 1538   for (i=ibeg;i<=iend;i++) {
 
 1539      for (j=jbeg;j<=jend;j++) {
 
 1549   for (j=jbeg;j<=jend;j++) {
 
 1550      for (i=ibeg;i<=iend;i++) {
 
 1561   else             factnm = 
TMath::Sqrt(esum1*sum2/(esum1+esum2));
 
 1564   Double_t dfmax = 0.5*(dfmax1+dfmax2);
 
 1571   if (opt.
Contains(
"N")  && !(afunc1 || afunc2 ) ) {
 
 1575      Double_t chi2   = d12*d12/(esum1+esum2);
 
 1578      if (prb > 0 && prb2 > 0) prb = prb*prb2*(1-
TMath::Log(prb*prb2));
 
 1584      printf(
" Kolmo Prob  h1 = %s, sum1=%g\n",
h1->
GetName(),sum1);
 
 1585      printf(
" Kolmo Prob  h2 = %s, sum2=%g\n",h2->
GetName(),sum2);
 
 1586      printf(
" Kolmo Probabil = %f, Max Dist = %g\n",prb,dfmax);
 
 1588         printf(
" Kolmo Probabil = %f for shape alone, =%f for normalisation alone\n",prb1,prb2);
 
 1594   if(opt.
Contains(
"M"))      
return dfmax;  
 
 1606   return Rebin2D(ngroup, 1, newname);
 
 1616   return Rebin2D(1, ngroup, newname);
 
 1627   if (xbins != 
nullptr) {
 
 1628      Error(
"Rebin",
"Rebinning a 2-d histogram into variable bins is not supported (it is possible only for 1-d histograms). Return a nullptr");
 
 1631   Info(
"Rebin",
"Rebinning only the x-axis. Use Rebin2D for rebinning both axes");
 
 1632   return RebinX(ngroup, newname);
 
 1664   Int_t nx      = nxbins + 2; 
 
 1665   Int_t ny      = nybins + 2;
 
 1672      Error(
"Rebin2D", 
"Histogram must be TH2. This histogram has %d dimensions.", 
GetDimension());
 
 1675   if ((nxgroup <= 0) || (nxgroup > nxbins)) {
 
 1676      Error(
"Rebin2D", 
"Illegal value of nxgroup=%d",nxgroup);
 
 1679   if ((nygroup <= 0) || (nygroup > nybins)) {
 
 1680      Error(
"Rebin2D", 
"Illegal value of nygroup=%d",nygroup);
 
 1684   Int_t newxbins = nxbins / nxgroup;
 
 1685   Int_t newybins = nybins / nygroup;
 
 1686   Int_t newnx = newxbins + 2; 
 
 1687   Int_t newny = newybins + 2; 
 
 1701   if (newname && strlen(newname)) {
 
 1706   bool resetStat = 
false;
 
 1709   if(newxbins * nxgroup != nxbins) {
 
 1713   if(newybins * nygroup != nybins) {
 
 1745   if (nxgroup != 1 || nygroup != 1) {
 
 1752         hnew->
SetBins(newxbins, xbins, newybins, ybins); 
 
 1761      if (oldErrors) hnew->
fSumw2[0] = 0;
 
 1764      for(
Int_t binx = 1, oldbinx = 1; binx < newnx; ++binx, oldbinx += nxgroup){
 
 1765         Double_t binContent = 0.0, binErrorSq = 0.0;
 
 1766         for (
Int_t i = 0; i < nxgroup && (oldbinx + i) < nx; ++i) {
 
 1767            Int_t bin = oldbinx + i;
 
 1768            binContent += oldBins[bin];
 
 1769            if(oldErrors) binErrorSq += oldErrors[bin];
 
 1771         Int_t newbin = binx;
 
 1773         if (oldErrors) hnew->
fSumw2[newbin] = binErrorSq;
 
 1777      for(
Int_t biny = 1, oldbiny = 1; biny < newny; ++biny, oldbiny += nygroup){
 
 1778         Double_t binContent = 0.0, binErrorSq = 0.0;
 
 1779         for (
Int_t j = 0; j < nygroup && (oldbiny + j) < ny; ++j) {
 
 1780            Int_t bin = (oldbiny + j) * nx;
 
 1781            binContent += oldBins[bin];
 
 1782            if(oldErrors) binErrorSq += oldErrors[bin];
 
 1784         Int_t newbin = biny * newnx;
 
 1786         if (oldErrors) hnew->
fSumw2[newbin] = binErrorSq;
 
 1790      for (
Int_t binx = 1, oldbinx = 1; binx < newnx; ++binx, oldbinx += nxgroup) {
 
 1791         for (
Int_t biny = 1, oldbiny = 1; biny < newny; ++biny, oldbiny += nygroup) {
 
 1792            Double_t binContent = 0.0, binErrorSq = 0.0;
 
 1793            for (
Int_t i = 0; i < nxgroup && (oldbinx + i) < nx; ++i) {
 
 1794               for (
Int_t j = 0; j < nygroup && (oldbiny + j) < ny; ++j) {
 
 1795                  Int_t bin = oldbinx + i + (oldbiny + j) * nx;
 
 1796                  binContent += oldBins[bin];
 
 1797                  if (oldErrors) binErrorSq += oldErrors[bin];
 
 1800            Int_t newbin = binx + biny * newnx;
 
 1802            if (oldErrors) hnew->
fSumw2[newbin] = binErrorSq;
 
 1835   if (oldErrors) 
delete [] oldErrors;
 
 1850      cut = opt(i1,i2-i1+1);
 
 1853   bool originalRange = opt.
Contains(
"o");
 
 1858   const char *expectedName = ( onX ? 
"_pfx" : 
"_pfy" );
 
 1871      if (firstbin == 0 && lastbin == 0)
 
 1877   if (firstbin < 0) firstbin = 1;
 
 1878   if (lastbin  < 0) lastbin  = inN;
 
 1879   if (lastbin  > inN+1) lastbin  = inN;
 
 1882   char *pname = (
char*)
name;
 
 1883   if (
name && strcmp(
name, expectedName) == 0) {
 
 1885      pname = 
new char[nch];
 
 1893      if (h1obj->IsA() != TProfile::Class() ) {
 
 1894         Error(
"DoProfile",
"Histogram with name %s must be a TProfile and is a %s",
name,h1obj->
ClassName());
 
 1903      if (xbins->fN == 0) {
 
 1904         if ( originalRange )
 
 1913            h1->
SetBins(lastOutBin-firstOutBin+1,&xbins->fArray[firstOutBin-1]);
 
 1919      ((
TH2 *)
this)->GetPainter();
 
 1925      if (bins->
fN == 0) {
 
 1926         if ( originalRange )
 
 1940   if (pname != 
name)  
delete [] pname;
 
 1951   TArrayD & binSumw2 = *(
h1->GetBinSumw2());
 
 1964   for ( 
Int_t outbin = 0; outbin <= outAxis.
GetNbins() + 1;  ++outbin) {
 
 1970      if (binOut <0) 
continue;
 
 1972      for (
Int_t inbin = firstbin ; inbin <= lastbin ; ++inbin) {
 
 1974         if (onX) { binx = outbin; biny=inbin; }
 
 1975         else     { binx = inbin;  biny=outbin; }
 
 1987            if ( useWeights ) tmp = binSumw2.
fArray[binOut];
 
 2014      if (padsav) padsav->
cd();
 
 2125   const char *expectedName = 0;
 
 2127   const TAxis* outAxis;
 
 2128   const TAxis* inAxis;
 
 2135      cut = opt(i1,i2-i1+1);
 
 2138   bool originalRange = opt.
Contains(
"o");
 
 2142      expectedName = 
"_px";
 
 2149      expectedName = 
"_py";
 
 2166      if (firstbin == 0 && lastbin == 0)
 
 2172   if (firstbin < 0) firstbin = 0;
 
 2173   if (lastbin  < 0) lastbin  = inNbin + 1;
 
 2174   if (lastbin  > inNbin+1) lastbin  = inNbin + 1;
 
 2177   char *pname = (
char*)
name;
 
 2178   if (
name && strcmp(
name,expectedName) == 0) {
 
 2180      pname = 
new char[nch];
 
 2189      if (h1obj->IsA() != TH1D::Class() ) {
 
 2190         Error(
"DoProjection",
"Histogram with name %s must be a TH1D and is a %s",
name,h1obj->
ClassName());
 
 2199      if (xbins->fN == 0) {
 
 2200         if ( originalRange )
 
 2209            h1->
SetBins(lastOutBin-firstOutBin+1,&xbins->fArray[firstOutBin-1]);
 
 2215      ((
TH2 *)
this)->GetPainter();
 
 2221      if (bins->
fN == 0) {
 
 2222         if ( originalRange )
 
 2236   if (pname != 
name)  
delete [] pname;
 
 2264   for ( 
Int_t outbin = 0; outbin <= outAxis->
GetNbins() + 1;  ++outbin) {
 
 2269      for (
Int_t inbin = firstbin ; inbin <= lastbin ; ++inbin) {
 
 2271         if (onX) { binx = outbin; biny=inbin; }
 
 2272         else     { binx = inbin;  biny=outbin; }
 
 2279         if (computeErrors) {
 
 2293   bool reuseStats = 
false;
 
 2299      double eps = 1.E-12;
 
 2300      if (IsA() == TH2F::Class() ) eps = 1.E-6;
 
 2304   if (ncuts) reuseStats = 
false;
 
 2306   bool reuseEntries = reuseStats;
 
 2308   reuseEntries &= (firstbin==0 && lastbin == inNbin+1);
 
 2313         stats[2] = stats[4];
 
 2314         stats[3] = stats[5];
 
 2349      if (padsav) padsav->
cd();
 
 2482   const TAxis *outAxis = 0;
 
 2491   if (qname.
IsNull() || qname == 
"_qx" || qname == 
"_qy") {
 
 2492      const char * qtype = (onX) ? 
"qx" : 
"qy";
 
 2500      h1 = 
dynamic_cast<TH1D*
>(h1obj);
 
 2502         Error(
"DoQuantiles",
"Histogram with name %s must be a TH1D and is a %s",qname.
Data(),h1obj->
ClassName());
 
 2519      h1->
SetBins(lastOutBin-firstOutBin+1,&xbins->fArray[firstOutBin-1]);
 
 2526  for (
int ibin = outAxis->
GetFirst() ; ibin <= outAxis->
GetLast() ; ++ibin) {
 
 2531    if (slice->
GetSum() == 0) 
continue;
 
 2545  if (slice) 
delete slice;
 
 2573   if (bin < 0) 
return;
 
 2617   return (
TH1*)
gROOT->ProcessLineFast(
Form(
"TSpectrum2::StaticBackground((TH1*)0x%zx,%d,\"%s\")",
 
 2618                                            (
size_t)
this, niter, option));
 
 2633   return (
Int_t)
gROOT->ProcessLineFast(
Form(
"TSpectrum2::StaticSearch((TH1*)0x%zx,%g,\"%s\",%g)",
 
 2634                                             (
size_t)
this, 
sigma, option, threshold));
 
 2664   Double_t k5a[5][5] =  { { 0, 0, 1, 0, 0 },
 
 2668                           { 0, 0, 1, 0, 0 } };
 
 2669   Double_t k5b[5][5] =  { { 0, 1, 2, 1, 0 },
 
 2673                           { 0, 1, 2, 1, 0 } };
 
 2674   Double_t k3a[3][3] =  { { 0, 1, 0 },
 
 2679      Warning(
"Smooth",
"Currently only ntimes=1 is supported");
 
 2686   if (opt.
Contains(
"k5b")) kernel = &k5b[0][0];
 
 2688      kernel = &k3a[0][0];
 
 2703   Int_t bufSize  = (nx+2)*(ny+2);
 
 2710   for (i=ifirst; i<=ilast; i++){
 
 2711      for (j=jfirst; j<=jlast; j++){
 
 2719   Int_t x_push = (ksize_x-1)/2;
 
 2720   Int_t y_push = (ksize_y-1)/2;
 
 2723   for (i=ifirst; i<=ilast; i++){
 
 2724      for (j=jfirst; j<=jlast; j++) {
 
 2733               if ( (xb >= 1) && (xb <= nx) && (yb >= 1) && (yb <= ny) ) {
 
 2739                     content += k*buf[bin];
 
 2740                     if (ebuf) error   += k*k*ebuf[bin]*ebuf[bin];
 
 2746         if ( norm != 0.0 ) {
 
 2749               error /= (norm*norm);
 
 2765void TH2::Streamer(
TBuffer &R__b)
 
 2775      TH1::Streamer(R__b);
 
 2820           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ylow,yup)
 
 2835           :
TH2(
name,title,nbinsx,xbins,nbinsy,ylow,yup)
 
 2848           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ybins)
 
 2861           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 2874           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 2906   if (newval > -128 && newval < 128) {
fArray[bin] = 
Char_t(newval); 
return;}
 
 2907   if (newval < -127) 
fArray[bin] = -127;
 
 2908   if (newval >  127) 
fArray[bin] =  127;
 
 2946void TH2C::Streamer(
TBuffer &R__b)
 
 2958         TH1::Streamer(R__b);
 
 2959         TArrayC::Streamer(R__b);
 
 2966         TH2::Streamer(R__b);
 
 2967         TArrayC::Streamer(R__b);
 
 3080           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ylow,yup)
 
 3095           :
TH2(
name,title,nbinsx,xbins,nbinsy,ylow,yup)
 
 3108           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ybins)
 
 3121           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3134           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3166   if (newval > -32768 && newval < 32768) {
fArray[bin] = 
Short_t(newval); 
return;}
 
 3167   if (newval < -32767) 
fArray[bin] = -32767;
 
 3168   if (newval >  32767) 
fArray[bin] =  32767;
 
 3206void TH2S::Streamer(
TBuffer &R__b)
 
 3218         TH1::Streamer(R__b);
 
 3219         TArrayS::Streamer(R__b);
 
 3226         TH2::Streamer(R__b);
 
 3227         TArrayS::Streamer(R__b);
 
 3340           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ylow,yup)
 
 3355           :
TH2(
name,title,nbinsx,xbins,nbinsy,ylow,yup)
 
 3368           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ybins)
 
 3381           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3394           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3426   if (newval > -INT_MAX && newval < INT_MAX) {
fArray[bin] = 
Int_t(newval); 
return;}
 
 3427   if (newval < -INT_MAX) 
fArray[bin] = -INT_MAX;
 
 3428   if (newval >  INT_MAX) 
fArray[bin] =  INT_MAX;
 
 3565           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ylow,yup)
 
 3580           :
TH2(
name,title,nbinsx,xbins,nbinsy,ylow,yup)
 
 3593           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ybins)
 
 3606           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3619           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3631:
TH2(
"TMatrixFBase",
"",
m.GetNcols(),
m.GetColLwb(),1+
m.GetColUpb(),
m.GetNrows(),
m.GetRowLwb(),1+
m.GetRowUpb())
 
 3634   Int_t ilow = 
m.GetRowLwb();
 
 3635   Int_t iup  = 
m.GetRowUpb();
 
 3636   Int_t jlow = 
m.GetColLwb();
 
 3637   Int_t jup  = 
m.GetColUpb();
 
 3638   for (
Int_t i=ilow;i<=iup;i++) {
 
 3639      for (
Int_t j=jlow;j<=jup;j++) {
 
 3690void TH2F::Streamer(
TBuffer &R__b)
 
 3702         TH1::Streamer(R__b);
 
 3703         TArrayF::Streamer(R__b);
 
 3710         TH2::Streamer(R__b);
 
 3711         TArrayF::Streamer(R__b);
 
 3836           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ylow,yup)
 
 3851           :
TH2(
name,title,nbinsx,xbins,nbinsy,ylow,yup)
 
 3864           :
TH2(
name,title,nbinsx,xlow,xup,nbinsy,ybins)
 
 3877           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3890           :
TH2(
name,title,nbinsx,xbins,nbinsy,ybins)
 
 3902:
TH2(
"TMatrixDBase",
"",
m.GetNcols(),
m.GetColLwb(),1+
m.GetColUpb(),
m.GetNrows(),
m.GetRowLwb(),1+
m.GetRowUpb())
 
 3905   Int_t ilow = 
m.GetRowLwb();
 
 3906   Int_t iup  = 
m.GetRowUpb();
 
 3907   Int_t jlow = 
m.GetColLwb();
 
 3908   Int_t jup  = 
m.GetColUpb();
 
 3909   for (
Int_t i=ilow;i<=iup;i++) {
 
 3910      for (
Int_t j=jlow;j<=jup;j++) {
 
 3962void TH2D::Streamer(
TBuffer &R__b)
 
 3974         TH1::Streamer(R__b);
 
 3975         TArrayD::Streamer(R__b);
 
 3982         TH2::Streamer(R__b);
 
 3983         TArrayD::Streamer(R__b);
 
static const double x2[5]
 
static const double x1[5]
 
TH2C operator-(TH2C &h1, TH2C &h2)
Operator -.
 
TH2C operator+(TH2C &h1, TH2C &h2)
Operator +.
 
TH2C operator/(TH2C &h1, TH2C &h2)
Operator /.
 
TH2C operator*(Float_t c1, TH2C &h1)
Operator *.
 
R__EXTERN TRandom * gRandom
 
char * Form(const char *fmt,...)
 
Array of chars or bytes (8 bits per element).
 
void Set(Int_t n)
Set size of this array to n chars.
 
void Copy(TArrayC &array) const
 
Array of doubles (64 bits per element).
 
void Copy(TArrayD &array) const
 
void Set(Int_t n)
Set size of this array to n doubles.
 
Array of floats (32 bits per element).
 
void Copy(TArrayF &array) const
 
void Set(Int_t n)
Set size of this array to n floats.
 
Array of integers (32 bits per element).
 
void Set(Int_t n)
Set size of this array to n ints.
 
void Copy(TArrayI &array) const
 
Array of shorts (16 bits per element).
 
void Set(Int_t n)
Set size of this array to n shorts.
 
void Copy(TArrayS &array) const
 
virtual Color_t GetTitleColor() const
 
virtual Color_t GetLabelColor() const
 
virtual Int_t GetNdivisions() const
 
virtual Color_t GetAxisColor() const
 
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
 
virtual Style_t GetTitleFont() const
 
virtual Float_t GetLabelOffset() const
 
virtual void SetAxisColor(Color_t color=1, Float_t alpha=1.)
Set color of the line axis and tick marks.
 
virtual void SetLabelSize(Float_t size=0.04)
Set size of axis labels.
 
virtual Style_t GetLabelFont() const
 
virtual void SetTitleFont(Style_t font=62)
Set the title font.
 
virtual void SetLabelOffset(Float_t offset=0.005)
Set distance between the axis and the labels.
 
virtual void SetLabelFont(Style_t font=62)
Set labels' font.
 
virtual void SetTitleSize(Float_t size=0.04)
Set size of axis title.
 
virtual void SetTitleColor(Color_t color=1)
Set color of axis title.
 
virtual Float_t GetTitleSize() const
 
virtual Float_t GetLabelSize() const
 
virtual Float_t GetTickLength() const
 
virtual Float_t GetTitleOffset() const
 
virtual void SetTickLength(Float_t length=0.03)
Set tick mark length.
 
virtual void SetNdivisions(Int_t n=510, Bool_t optim=kTRUE)
Set the number of divisions for this axis.
 
virtual void SetLabelColor(Color_t color=1, Float_t alpha=1.)
Set color of labels.
 
virtual Color_t GetFillColor() const
Return the fill area color.
 
virtual void SetFillColor(Color_t fcolor)
Set the fill area color.
 
virtual Color_t GetLineColor() const
Return the line color.
 
virtual void SetLineColor(Color_t lcolor)
Set the line color.
 
virtual Style_t GetMarkerStyle() const
Return the marker style.
 
virtual void SetMarkerColor(Color_t mcolor=1)
Set the marker color.
 
virtual Color_t GetMarkerColor() const
Return the marker color.
 
virtual void SetMarkerStyle(Style_t mstyle=1)
Set the marker style.
 
Class to manage histogram axis.
 
virtual void SetBinLabel(Int_t bin, const char *label)
Set label for bin.
 
Bool_t IsAlphanumeric() const
 
virtual Double_t GetBinCenter(Int_t bin) const
Return center of bin.
 
const TArrayD * GetXbins() const
 
virtual Int_t FindBin(Double_t x)
Find bin number corresponding to abscissa x.
 
virtual Double_t GetBinLowEdge(Int_t bin) const
Return low edge of bin.
 
virtual void Set(Int_t nbins, Double_t xmin, Double_t xmax)
Initialize axis with fix bins.
 
virtual Int_t FindFixBin(Double_t x) const
Find bin number corresponding to abscissa x.
 
Int_t GetLast() const
Return last bin on the axis i.e.
 
virtual void ImportAttributes(const TAxis *axis)
Copy axis attributes to this.
 
const char * GetTitle() const
Returns title of object.
 
virtual Double_t GetBinWidth(Int_t bin) const
Return bin width.
 
virtual Double_t GetBinUpEdge(Int_t bin) const
Return up edge of bin.
 
Int_t GetFirst() const
Return first bin on the axis i.e.
 
THashList * GetLabels() const
 
Buffer base class used for serializing objects.
 
virtual Int_t ReadClassBuffer(const TClass *cl, void *pointer, const TClass *onfile_class=0)=0
 
virtual Version_t ReadVersion(UInt_t *start=0, UInt_t *bcnt=0, const TClass *cl=0)=0
 
virtual Int_t CheckByteCount(UInt_t startpos, UInt_t bcnt, const TClass *clss)=0
 
virtual Int_t WriteClassBuffer(const TClass *cl, void *pointer)=0
 
virtual void SetOwner(Bool_t enable=kTRUE)
Set whether this collection is the owner (enable==true) of its content.
 
virtual TH1 * GetHistogram() const
Return a pointer to the histogram used to visualise the function Note that this histogram is managed ...
 
virtual Double_t GetParError(Int_t ipar) const
Return value of parameter number ipar.
 
Double_t GetChisquare() const
 
virtual void SetRange(Double_t xmin, Double_t xmax)
Initialize the upper and lower bounds to draw the function.
 
virtual Int_t GetNpar() const
 
virtual Double_t Integral(Double_t a, Double_t b, Double_t epsrel=1.e-12)
IntegralOneDim or analytical integral.
 
virtual Int_t GetNumberFitPoints() const
 
virtual Double_t * GetParameters() const
 
virtual void GetRange(Double_t *xmin, Double_t *xmax) const
Return range of a generic N-D function.
 
virtual const char * GetParName(Int_t ipar) const
 
virtual void SetParameters(const Double_t *params)
 
virtual Double_t GetParameter(Int_t ipar) const
 
A 2-Dim function with parameters.
 
1-D histogram with a double per channel (see TH1 documentation)}
 
virtual void Reset(Option_t *option="")
Reset.
 
TH1 is the base class of all histogram classes in ROOT.
 
virtual void SetDirectory(TDirectory *dir)
By default, when a histogram is created, it is added to the list of histogram objects in the current ...
 
Double_t * fBuffer
[fBufferSize] entry buffer
 
virtual Double_t GetEffectiveEntries() const
Number of effective entries of the histogram.
 
virtual Bool_t Multiply(TF1 *f1, Double_t c1=1)
Performs the operation:
 
Int_t fNcells
Number of bins(1D), cells (2D) +U/Overflows.
 
Double_t fTsumw
Total Sum of weights.
 
Double_t fTsumw2
Total Sum of squares of weights.
 
virtual Int_t GetQuantiles(Int_t nprobSum, Double_t *q, const Double_t *probSum=0)
Compute Quantiles for this histogram Quantile x_q of a probability distribution Function F is defined...
 
virtual Double_t DoIntegral(Int_t ix1, Int_t ix2, Int_t iy1, Int_t iy2, Int_t iz1, Int_t iz2, Double_t &err, Option_t *opt, Bool_t doerr=kFALSE) const
Internal function compute integral and optionally the error between the limits specified by the bin n...
 
Double_t fTsumwx2
Total Sum of weight*X*X.
 
virtual Double_t GetStdDev(Int_t axis=1) const
Returns the Standard Deviation (Sigma).
 
virtual Int_t GetNbinsY() const
 
virtual void AddBinContent(Int_t bin)
Increment bin content by 1.
 
virtual Double_t GetBinError(Int_t bin) const
Return value of error associated to bin number bin.
 
virtual Double_t GetMean(Int_t axis=1) const
For axis = 1,2 or 3 returns the mean value of the histogram along X,Y or Z axis.
 
virtual Int_t GetDimension() const
 
@ kIsNotW
Histogram is forced to be not weighted even when the histogram is filled with weighted different than...
 
virtual Bool_t CanExtendAllAxes() const
Returns true if all axes are extendable.
 
virtual void Reset(Option_t *option="")
Reset this histogram: contents, errors, etc.
 
TAxis * GetXaxis()
Get the behaviour adopted by the object about the statoverflows. See EStatOverflows for more informat...
 
virtual Int_t GetNcells() const
 
virtual void PutStats(Double_t *stats)
Replace current statistics with the values in array stats.
 
TVirtualHistPainter * GetPainter(Option_t *option="")
Return pointer to painter.
 
TObject * Clone(const char *newname=0) const
Make a complete copy of the underlying object.
 
virtual TFitResultPtr Fit(const char *formula, Option_t *option="", Option_t *goption="", Double_t xmin=0, Double_t xmax=0)
Fit histogram with function fname.
 
virtual Int_t GetBin(Int_t binx, Int_t biny=0, Int_t binz=0) const
Return Global bin number corresponding to binx,y,z.
 
virtual Int_t GetNbinsX() const
 
virtual Bool_t Add(TF1 *h1, Double_t c1=1, Option_t *option="")
Performs the operation: this = this + c1*f1 if errors are defined (see TH1::Sumw2),...
 
Int_t fBufferSize
fBuffer size
 
virtual Double_t RetrieveBinContent(Int_t bin) const
Raw retrieval of bin content on internal data structure see convention for numbering bins in TH1::Get...
 
Int_t fDimension
! Histogram dimension (1, 2 or 3 dim)
 
virtual void SetBinError(Int_t bin, Double_t error)
Set the bin Error Note that this resets the bin eror option to be of Normal Type and for the non-empt...
 
static Int_t fgBufferSize
! Default buffer size for automatic histograms
 
virtual Int_t Fill(Double_t x)
Increment bin with abscissa X by 1.
 
virtual Double_t GetBinErrorSqUnchecked(Int_t bin) const
 
UInt_t GetAxisLabelStatus() const
Internal function used in TH1::Fill to see which axis is full alphanumeric i.e.
 
Double_t * fIntegral
! Integral of bins used by GetRandom
 
virtual void SetBinContent(Int_t bin, Double_t content)
Set bin content see convention for numbering bins in TH1::GetBin In case the bin number is greater th...
 
virtual Double_t GetBinLowEdge(Int_t bin) const
Return bin lower edge for 1D histogram.
 
virtual Double_t GetEntries() const
Return the current number of entries.
 
virtual void Copy(TObject &hnew) const
Copy this histogram structure to newth1.
 
virtual void Draw(Option_t *option="")
Draw this histogram with options.
 
virtual void ResetStats()
Reset the statistics including the number of entries and replace with values calculated from bin cont...
 
virtual void SetBuffer(Int_t buffersize, Option_t *option="")
Set the maximum number of entries to be kept in the buffer.
 
@ kNstat
Size of statistics data (up to TProfile3D)
 
Double_t fEntries
Number of entries.
 
virtual void SetName(const char *name)
Change the name of this histogram.
 
virtual void UpdateBinContent(Int_t bin, Double_t content)
Raw update of bin content on internal data structure see convention for numbering bins in TH1::GetBin...
 
virtual Double_t GetBinContent(Int_t bin) const
Return content of bin number bin.
 
TAxis fXaxis
X axis descriptor.
 
virtual void ExtendAxis(Double_t x, TAxis *axis)
Histogram is resized along axis such that x is in the axis range.
 
TArrayD fSumw2
Array of sum of squares of weights.
 
virtual void Scale(Double_t c1=1, Option_t *option="")
Multiply this histogram by a constant c1.
 
virtual void Paint(Option_t *option="")
Control routine to paint any kind of histograms.
 
virtual Int_t GetSumw2N() const
 
virtual Int_t FindBin(Double_t x, Double_t y=0, Double_t z=0)
Return Global bin number corresponding to x,y,z.
 
Bool_t GetStatOverflowsBehaviour() const
 
virtual Bool_t Divide(TF1 *f1, Double_t c1=1)
Performs the operation: this = this/(c1*f1) if errors are defined (see TH1::Sumw2),...
 
TAxis fYaxis
Y axis descriptor.
 
TVirtualHistPainter * fPainter
! Pointer to histogram painter
 
virtual void SetBins(Int_t nx, Double_t xmin, Double_t xmax)
Redefine x axis parameters.
 
virtual void Sumw2(Bool_t flag=kTRUE)
Create structure to store sum of squares of weights.
 
virtual void SetEntries(Double_t n)
 
static Bool_t fgDefaultSumw2
! Flag to call TH1::Sumw2 automatically at histogram creation time
 
Double_t fTsumwx
Total Sum of weight*X.
 
virtual Double_t ComputeIntegral(Bool_t onlyPositive=false)
Compute integral (cumulative sum of bins) The result stored in fIntegral is used by the GetRandom fun...
 
2-D histogram with a byte per channel (see TH1 documentation)
 
virtual void Reset(Option_t *option="")
Reset this histogram: contents, errors, etc.
 
virtual void AddBinContent(Int_t bin)
Increment bin content by 1.
 
virtual ~TH2C()
Destructor.
 
virtual void SetBinsLength(Int_t n=-1)
Set total number of bins including under/overflow Reallocate bin contents array.
 
TH2C & operator=(const TH2C &h1)
Operator =.
 
virtual void Copy(TObject &hnew) const
Copy.
 
2-D histogram with a double per channel (see TH1 documentation)}
 
virtual void SetBinsLength(Int_t n=-1)
Set total number of bins including under/overflow Reallocate bin contents array.
 
virtual ~TH2D()
Destructor.
 
virtual void Copy(TObject &hnew) const
Copy.
 
TH2D & operator=(const TH2D &h1)
Operator =.
 
2-D histogram with a float per channel (see TH1 documentation)}
 
TH2F & operator=(const TH2F &h1)
Operator =.
 
virtual ~TH2F()
Destructor.
 
virtual void SetBinsLength(Int_t n=-1)
Set total number of bins including under/overflow Reallocate bin contents array.
 
virtual void Copy(TObject &hnew) const
Copy.
 
2-D histogram with an int per channel (see TH1 documentation)}
 
virtual void Copy(TObject &hnew) const
Copy.
 
virtual void SetBinsLength(Int_t n=-1)
Set total number of bins including under/overflow Reallocate bin contents array.
 
virtual void AddBinContent(Int_t bin)
Increment bin content by 1.
 
virtual ~TH2I()
Destructor.
 
TH2I & operator=(const TH2I &h1)
Operator =.
 
2-D histogram with a short per channel (see TH1 documentation)
 
virtual void SetBinsLength(Int_t n=-1)
Set total number of bins including under/overflow Reallocate bin contents array.
 
TH2S & operator=(const TH2S &h1)
Operator =.
 
virtual ~TH2S()
Destructor.
 
virtual void Copy(TObject &hnew) const
Copy.
 
virtual void AddBinContent(Int_t bin)
Increment bin content by 1.
 
Service class for 2-D histogram classes.
 
virtual void PutStats(Double_t *stats)
Replace current statistics with the values in array stats.
 
TH1D * ProjectionY(const char *name="_py", Int_t firstxbin=0, Int_t lastxbin=-1, Option_t *option="") const
Project a 2-D histogram into a 1-D histogram along Y.
 
virtual Int_t BufferEmpty(Int_t action=0)
Fill histogram with all entries in the buffer.
 
virtual Double_t GetCorrelationFactor(Int_t axis1=1, Int_t axis2=2) const
Return correlation factor between axis1 and axis2.
 
virtual TProfile * DoProfile(bool onX, const char *name, Int_t firstbin, Int_t lastbin, Option_t *option) const
 
virtual Double_t GetBinWithContent2(Double_t c, Int_t &binx, Int_t &biny, Int_t firstxbin=1, Int_t lastxbin=-1, Int_t firstybin=1, Int_t lastybin=-1, Double_t maxdiff=0) const
compute first cell (binx,biny) in the range [firstxbin,lastxbin][firstybin,lastybin] for which diff =...
 
TProfile * ProfileX(const char *name="_pfx", Int_t firstybin=1, Int_t lastybin=-1, Option_t *option="") const
Project a 2-D histogram into a profile histogram along X.
 
TH1D * QuantilesY(Double_t prob=0.5, const char *name="_qy") const
Compute the Y distribution of quantiles in the other variable X name is the name of the returned hist...
 
TProfile * ProfileY(const char *name="_pfy", Int_t firstxbin=1, Int_t lastxbin=-1, Option_t *option="") const
Project a 2-D histogram into a profile histogram along Y.
 
virtual void Reset(Option_t *option="")
Reset this histogram: contents, errors, etc.
 
virtual TH1D * DoQuantiles(bool onX, const char *name, Double_t prob) const
Implementation of quantiles for x or y.
 
Double_t fTsumwxy
Total Sum of weight*X*Y.
 
Int_t Fill(Double_t)
Invalid Fill method.
 
virtual TH1 * ShowBackground(Int_t niter=20, Option_t *option="same")
This function calculates the background spectrum in this histogram.
 
virtual Int_t ShowPeaks(Double_t sigma=2, Option_t *option="", Double_t threshold=0.05)
Interface to TSpectrum2::Search the function finds peaks in this histogram where the width is > sigma...
 
virtual void DoFitSlices(bool onX, TF1 *f1, Int_t firstbin, Int_t lastbin, Int_t cut, Option_t *option, TObjArray *arr)
 
TH1D * QuantilesX(Double_t prob=0.5, const char *name="_qx") const
Compute the X distribution of quantiles in the other variable Y name is the name of the returned hist...
 
virtual TH2 * RebinX(Int_t ngroup=2, const char *newname="")
Rebin only the X axis see Rebin2D.
 
virtual void SetShowProjectionY(Int_t nbins=1)
When the mouse is moved in a pad containing a 2-d view of this histogram a second canvas shows the pr...
 
virtual TH2 * Rebin(Int_t ngroup=2, const char *newname="", const Double_t *xbins=0)
Override TH1::Rebin as TH2::RebinX Rebinning in variable binning as for TH1 is not allowed If a non-n...
 
Double_t fScalefactor
Scale factor.
 
virtual void GetStats(Double_t *stats) const
Fill the array stats from the contents of this histogram The array stats must be correctly dimensione...
 
virtual void FillRandom(const char *fname, Int_t ntimes=5000, TRandom *rng=nullptr)
Fill histogram following distribution in function fname.
 
virtual TH1D * DoProjection(bool onX, const char *name, Int_t firstbin, Int_t lastbin, Option_t *option) const
Internal (protected) method for performing projection on the X or Y axis called by ProjectionX or Pro...
 
Double_t fTsumwy2
Total Sum of weight*Y*Y.
 
virtual void GetRandom2(Double_t &x, Double_t &y, TRandom *rng=nullptr)
Return 2 random numbers along axis x and y distributed according to the cell-contents of this 2-D his...
 
virtual Double_t GetCovariance(Int_t axis1=1, Int_t axis2=2) const
Return covariance between axis1 and axis2.
 
virtual void Smooth(Int_t ntimes=1, Option_t *option="")
Smooth bin contents of this 2-d histogram using kernel algorithms similar to the ones used in the ras...
 
virtual void FillN(Int_t, const Double_t *, const Double_t *, Int_t)
Fill this histogram with an array x and weights w.
 
TH1D * ProjectionX(const char *name="_px", Int_t firstybin=0, Int_t lastybin=-1, Option_t *option="") const
Project a 2-D histogram into a 1-D histogram along X.
 
virtual void FitSlicesX(TF1 *f1=0, Int_t firstybin=0, Int_t lastybin=-1, Int_t cut=0, Option_t *option="QNR", TObjArray *arr=0)
Project slices along X in case of a 2-D histogram, then fit each slice with function f1 and make a hi...
 
virtual Int_t GetBin(Int_t binx, Int_t biny, Int_t binz=0) const
Return Global bin number corresponding to binx,y,z.
 
virtual Double_t Integral(Option_t *option="") const
Return integral of bin contents.
 
virtual Double_t IntegralAndError(Int_t binx1, Int_t binx2, Int_t biny1, Int_t biny2, Double_t &err, Option_t *option="") const
Return integral of bin contents in range [firstxbin,lastxbin],[firstybin,lastybin] for a 2-D histogra...
 
virtual Double_t KolmogorovTest(const TH1 *h2, Option_t *option="") const
Statistical test of compatibility in shape between THIS histogram and h2, using Kolmogorov test.
 
Double_t fTsumwy
Total Sum of weight*Y.
 
TH2()
2-D histogram default constructor.
 
virtual void SetShowProjectionX(Int_t nbins=1)
When the mouse is moved in a pad containing a 2-d view of this histogram a second canvas shows the pr...
 
virtual Double_t Interpolate(Double_t x) const
illegal for a TH2
 
virtual void FitSlicesY(TF1 *f1=0, Int_t firstxbin=0, Int_t lastxbin=-1, Int_t cut=0, Option_t *option="QNR", TObjArray *arr=0)
Project slices along Y in case of a 2-D histogram, then fit each slice with function f1 and make a hi...
 
virtual Double_t GetBinContent(Int_t bin) const
Return content of bin number bin.
 
virtual TH2 * Rebin2D(Int_t nxgroup=2, Int_t nygroup=2, const char *newname="")
Rebin this histogram grouping nxgroup/nygroup bins along the xaxis/yaxis together.
 
virtual Int_t BufferFill(Double_t x, Double_t y, Double_t w)
accumulate arguments in buffer.
 
virtual void SetBinContent(Int_t bin, Double_t content)
Set bin content.
 
virtual ~TH2()
Destructor.
 
virtual TH2 * RebinY(Int_t ngroup=2, const char *newname="")
Rebin only the Y axis see Rebin2D.
 
virtual void Copy(TObject &hnew) const
Copy.
 
static THLimitsFinder * GetLimitsFinder()
Return pointer to the current finder.
 
virtual Int_t FindGoodLimits(TH1 *h, Double_t xmin, Double_t xmax)
Compute the best axis limits for the X axis.
 
THashList implements a hybrid collection class consisting of a hash table and a list to store TObject...
 
virtual void SetTitle(const char *title="")
Set the title of the TNamed.
 
virtual const char * GetTitle() const
Returns title of object.
 
virtual const char * GetName() const
Returns name of object.
 
virtual void Expand(Int_t newSize)
Expand or shrink the array to newSize elements.
 
Collectable string class.
 
Mother of all ROOT objects.
 
virtual const char * GetName() const
Returns name of object.
 
R__ALWAYS_INLINE Bool_t TestBit(UInt_t f) const
 
virtual const char * ClassName() const
Returns name of class to which the object belongs.
 
virtual void Warning(const char *method, const char *msgfmt,...) const
Issue warning message.
 
virtual TObject * FindObject(const char *name) const
Must be redefined in derived classes.
 
void SetBit(UInt_t f, Bool_t set)
Set or unset the user status bits as specified in f.
 
virtual Bool_t InheritsFrom(const char *classname) const
Returns kTRUE if object inherits from class "classname".
 
virtual void Error(const char *method, const char *msgfmt,...) const
Issue error message.
 
virtual void Info(const char *method, const char *msgfmt,...) const
Issue info message.
 
This is the base class for the ROOT Random number generators.
 
virtual Double_t Rndm()
Machine independent random number generator.
 
void ToLower()
Change string to lower-case.
 
Ssiz_t First(char c) const
Find first occurrence of a character c.
 
const char * Data() const
 
TString & ReplaceAll(const TString &s1, const TString &s2)
 
void ToUpper()
Change string to upper case.
 
TString & Remove(Ssiz_t pos)
 
static TString Format(const char *fmt,...)
Static method which formats a string using a printf style format descriptor and return a TString.
 
Bool_t Contains(const char *pat, ECaseCompare cmp=kExact) const
 
Ssiz_t Index(const char *pat, Ssiz_t i=0, ECaseCompare cmp=kExact) const
 
virtual void SetShowProjection(const char *option, Int_t nbins)=0
 
virtual Int_t MakeCuts(char *cutsopt)=0
 
virtual Bool_t IsInside(Int_t x, Int_t y)=0
 
TVirtualPad is an abstract base class for the Pad and Canvas classes.
 
virtual TVirtualPad * GetSelectedPad() const =0
 
virtual TVirtualPad * cd(Int_t subpadnumber=0)=0
 
Double_t Gaus(Double_t x, Double_t mean=0, Double_t sigma=1, Bool_t norm=kFALSE)
Calculate a gaussian function with mean and sigma.
 
Short_t Max(Short_t a, Short_t b)
 
Double_t Prob(Double_t chi2, Int_t ndf)
Computation of the probability for a certain Chi-squared (chi2) and number of degrees of freedom (ndf...
 
Double_t QuietNaN()
Returns a quiet NaN as defined by IEEE 754
 
Double_t Floor(Double_t x)
 
Double_t Sqrt(Double_t x)
 
Double_t KolmogorovProb(Double_t z)
Calculates the Kolmogorov distribution function,.
 
Long64_t BinarySearch(Long64_t n, const T *array, T value)