599enum EInconsistencyBits {
600 kFullyConsistent = 0,
601 kDifferentLabels =
BIT(0),
602 kDifferentBinLimits =
BIT(1),
603 kDifferentAxisLimits =
BIT(2),
604 kDifferentNumberOfBins =
BIT(3),
605 kDifferentDimensions =
BIT(4)
701 if (nbins <= 0) {
Warning(
"TH1",
"nbins is <=0 - set to nbins = 1"); nbins = 1; }
723 if (nbins <= 0) {
Warning(
"TH1",
"nbins is <=0 - set to nbins = 1"); nbins = 1; }
745 if (nbins <= 0) {
Warning(
"TH1",
"nbins is <=0 - set to nbins = 1"); nbins = 1; }
764 Draw(
b ?
b->GetDrawOption() :
"");
829 Error(
"Add",
"Attempt to add a non-existing function");
849 for (
Int_t i = 0; i < 10; ++i)
s1[i] = 0;
855 Int_t bin, binx, biny, binz;
860 for (binz = 0; binz < ncellsz; ++binz) {
862 for (biny = 0; biny < ncellsy; ++biny) {
864 for (binx = 0; binx < ncellsx; ++binx) {
868 bin = binx + ncellsx * (biny + ncellsy * binz);
887 if (inconsistency & kDifferentDimensions) {
889 Info(
name,
"Histograms have different dimensions - trying to use TH1::Merge");
891 Error(
name,
"Histograms have different dimensions");
893 }
else if (inconsistency & kDifferentNumberOfBins) {
895 Info(
name,
"Histograms have different number of bins - trying to use TH1::Merge");
897 Error(
name,
"Histograms have different number of bins");
899 }
else if (inconsistency & kDifferentAxisLimits) {
901 Info(
name,
"Histograms have different axis limits - trying to use TH1::Merge");
903 Warning(
name,
"Histograms have different axis limits");
904 }
else if (inconsistency & kDifferentBinLimits) {
906 Info(
name,
"Histograms have different bin limits - trying to use TH1::Merge");
908 Warning(
name,
"Histograms have different bin limits");
909 }
else if (inconsistency & kDifferentLabels) {
912 Info(
name,
"Histograms have different labels - trying to use TH1::Merge");
914 Info(
name,
"Histograms have different labels");
917 return inconsistency;
957 Error(
"Add",
"Attempt to add a non-existing histogram");
964 bool useMerge =
false;
968 if(inconsistency >= kDifferentNumberOfBins && !considerMerge) {
972 if(inconsistency > kFullyConsistent) {
973 useMerge = considerMerge;
978 l.Add(
const_cast<TH1*
>(
h1));
1021 if (e1sq) w1 = 1. / e1sq;
1026 double sf = (s2[0] != 0) ? s2[1]/s2[0] : 1;
1030 if (e2sq) w2 = 1. / e2sq;
1035 double sf = (
s1[0] != 0) ?
s1[1]/
s1[0] : 1;
1040 double y = (w1*
y1 + w2*
y2)/(w1 + w2);
1043 double err2 = 1./(w1 + w2);
1044 if (err2 < 1.E-200) err2 = 0;
1060 if (i == 1)
s1[i] +=
c1*
c1*s2[i];
1061 else s1[i] +=
c1*s2[i];
1108 Error(
"Add",
"Attempt to add a non-existing histogram");
1116 if (
h1 == h2 &&
c2 < 0) {
c2 = 0; normWidth =
kTRUE;}
1119 bool useMerge =
false;
1128 if(inconsistency >= kDifferentNumberOfBins && !considerMerge) {
1132 if(inconsistency > kFullyConsistent) {
1133 useMerge = considerMerge;
1139 l.Add(
const_cast<TH1*
>(
h1));
1140 l.Add(
const_cast<TH1*
>(h2));
1162 Bool_t resetStats = (
c1*
c2 < 0) || normWidth;
1169 if (i == 1) s3[i] =
c1*
c1*
s1[i] +
c2*
c2*s2[i];
1171 else s3[i] =
c1*
s1[i] +
c2*s2[i];
1187 Int_t bin, binx, biny, binz;
1188 for (binz = 0; binz < nbinsz; ++binz) {
1190 for (biny = 0; biny < nbinsy; ++biny) {
1192 for (binx = 0; binx < nbinsx; ++binx) {
1194 bin =
GetBin(binx, biny, binz);
1210 Double_t e2sq = h2->GetBinErrorSqUnchecked(i);
1215 if (e1sq) w1 = 1./ e1sq;
1219 double sf = (
s1[0] != 0) ?
s1[1]/
s1[0] : 1;
1223 if (e2sq) w2 = 1./ e2sq;
1224 else if (h2->fSumw2.fN) {
1227 double sf = (s2[0] != 0) ? s2[1]/s2[0] : 1;
1232 double y = (w1*
y1 + w2*
y2)/(w1 + w2);
1235 double err2 = 1./(w1 + w2);
1236 if (err2 < 1.E-200) err2 = 0;
1312 return ((next &&
x > 0.) || (!next &&
x <= 0.)) ? std::ldexp(std::copysign(1., f2), nn)
1313 : std::ldexp(std::copysign(1., f2), --nn);
1326 return (
Int_t)std::ldexp(1., nn);
1366 Double_t rr = (xhma - xhmi) / (xma - xmi);
1376 Int_t nbup = (xhma - xma) / bw;
1379 if (nbup != nbside) {
1381 xhma -= bw * (nbup - nbside);
1382 nb -= (nbup - nbside);
1386 Int_t nblw = (xmi - xhmi) / bw;
1389 if (nblw != nbside) {
1391 xhmi += bw * (nblw - nbside);
1392 nb -= (nblw - nbside);
1422 if (nbentries == 0) {
1432 if (nbentries < 0 && action == 0)
return 0;
1435 if (nbentries < 0) {
1436 nbentries = -nbentries;
1448 for (
Int_t i=0;i<nbentries;i++) {
1451 if (!std::isfinite(
x))
continue;
1460 "inconsistency found by power-of-2 autobin algorithm: fallback to standard method");
1478 DoFillN(nbentries,&buffer[2],&buffer[1],2);
1512 if (nbentries < 0) {
1515 nbentries = -nbentries;
1547 if ( h2Array->
fN != fN ) {
1551 for (
int i = 0; i < fN; ++i ) {
1582 for (
int i = 1; i <= a1->
GetNbins(); ++i) {
1585 if (label1 != label2) {
1614 ::Info(
"CheckEqualAxes",
"Axes have different number of bins : nbin1 = %d nbin2 = %d",a1->
GetNbins(),a2->
GetNbins() );
1618 ::Info(
"CheckEqualAxes",
"Axes have different limits");
1622 ::Info(
"CheckEqualAxes",
"Axes have different bin limits");
1628 ::Info(
"CheckEqualAxes",
"Axes have different labels");
1643 Int_t nbins1 = lastBin1-firstBin1 + 1;
1651 if (firstBin2 < lastBin2) {
1653 nbins2 = lastBin1-firstBin1 + 1;
1658 if (nbins1 != nbins2 ) {
1659 ::Info(
"CheckConsistentSubAxes",
"Axes have different number of bins");
1667 ::Info(
"CheckConsistentSubAxes",
"Axes have different limits");
1679 if (
h1 == h2)
return kFullyConsistent;
1682 return kDifferentDimensions;
1692 if (nbinsx != h2->GetNbinsX() ||
1693 (dim > 1 && nbinsy != h2->GetNbinsY()) ||
1694 (dim > 2 && nbinsz != h2->GetNbinsZ()) ) {
1695 return kDifferentNumberOfBins;
1704 if (!ret)
return kDifferentAxisLimits;
1710 if (!ret)
return kDifferentBinLimits;
1713 if ( !
h1->
IsEmpty() && !h2->IsEmpty() ) {
1717 if (!ret)
return kDifferentLabels;
1720 return kFullyConsistent;
2013 Int_t ndf = 0, igood = 0;
2021 printf(
"Chi2 = %f, Prob = %g, NDF = %d, igood = %d\n", chi2,prob,ndf,igood);
2024 if (ndf == 0)
return 0;
2072 Int_t i_start, i_end;
2073 Int_t j_start, j_end;
2074 Int_t k_start, k_end;
2088 const TAxis *xaxis2 = h2->GetXaxis();
2090 const TAxis *yaxis2 = h2->GetYaxis();
2092 const TAxis *zaxis2 = h2->GetZaxis();
2103 Error(
"Chi2TestX",
"Histograms have different dimensions.");
2108 if (nbinx1 != nbinx2) {
2109 Error(
"Chi2TestX",
"different number of x channels");
2111 if (nbiny1 != nbiny2) {
2112 Error(
"Chi2TestX",
"different number of y channels");
2114 if (nbinz1 != nbinz2) {
2115 Error(
"Chi2TestX",
"different number of z channels");
2119 i_start = j_start = k_start = 1;
2150 ndf = (i_end - i_start + 1) * (j_end - j_start + 1) * (k_end - k_start + 1) - 1;
2157 if (scaledHistogram && !comparisonUU) {
2158 Info(
"Chi2TestX",
"NORM option should be used together with UU option. It is ignored");
2165 Double_t effEntries1 = (s[1] ? s[0] * s[0] / s[1] : 0.0);
2169 Double_t effEntries2 = (s[1] ? s[0] * s[0] / s[1] : 0.0);
2171 if (!comparisonUU && !comparisonUW && !comparisonWW ) {
2173 if (
TMath::Abs(sumBinContent1 - effEntries1) < 1) {
2174 if (
TMath::Abs(sumBinContent2 - effEntries2) < 1) comparisonUU =
true;
2175 else comparisonUW =
true;
2177 else comparisonWW =
true;
2181 if (
TMath::Abs(sumBinContent1 - effEntries1) >= 1) {
2182 Warning(
"Chi2TestX",
"First histogram is not unweighted and option UW has been requested");
2185 if ( (!scaledHistogram && comparisonUU) ) {
2186 if ( (
TMath::Abs(sumBinContent1 - effEntries1) >= 1) || (
TMath::Abs(sumBinContent2 - effEntries2) >= 1) ) {
2187 Warning(
"Chi2TestX",
"Both histograms are not unweighted and option UU has been requested");
2193 if (comparisonUU && scaledHistogram) {
2194 for (
Int_t i = i_start; i <= i_end; ++i) {
2195 for (
Int_t j = j_start; j <= j_end; ++j) {
2196 for (
Int_t k = k_start; k <= k_end; ++k) {
2201 Double_t cnt2 = h2->RetrieveBinContent(bin);
2203 Double_t e2sq = h2->GetBinErrorSqUnchecked(bin);
2205 if (e1sq > 0.0) cnt1 =
TMath::Floor(cnt1 * cnt1 / e1sq + 0.5);
2208 if (e2sq > 0.0) cnt2 =
TMath::Floor(cnt2 * cnt2 / e2sq + 0.5);
2219 if (sumw1 <= 0.0 || sumw2 <= 0.0) {
2220 Error(
"Chi2TestX",
"Cannot use option NORM when one histogram has all zero errors");
2225 for (
Int_t i = i_start; i <= i_end; ++i) {
2226 for (
Int_t j = j_start; j <= j_end; ++j) {
2227 for (
Int_t k = k_start; k <= k_end; ++k) {
2232 sum2 += h2->RetrieveBinContent(bin);
2235 if ( comparisonUW || comparisonWW ) sumw2 += h2->GetBinErrorSqUnchecked(bin);
2241 if (sum1 == 0.0 || sum2 == 0.0) {
2242 Error(
"Chi2TestX",
"one histogram is empty");
2246 if ( comparisonWW && ( sumw1 <= 0.0 && sumw2 <= 0.0 ) ){
2247 Error(
"Chi2TestX",
"Hist1 and Hist2 have both all zero errors\n");
2257 for (
Int_t i = i_start; i <= i_end; ++i) {
2258 for (
Int_t j = j_start; j <= j_end; ++j) {
2259 for (
Int_t k = k_start; k <= k_end; ++k) {
2264 Double_t cnt2 = h2->RetrieveBinContent(bin);
2266 if (scaledHistogram) {
2269 Double_t e2sq = h2->GetBinErrorSqUnchecked(bin);
2271 if (e1sq > 0) cnt1 =
TMath::Floor(cnt1 * cnt1 / e1sq + 0.5);
2274 if (e2sq > 0) cnt2 =
TMath::Floor(cnt2 * cnt2 / e2sq + 0.5);
2278 if (
Int_t(cnt1) == 0 &&
Int_t(cnt2) == 0) --ndf;
2285 if (res) res[i - i_start] = (cnt1 - nexp1) /
TMath::Sqrt(nexp1);
2294 Double_t delta = sum2 * cnt1 - sum1 * cnt2;
2295 chi2 += delta * delta / cntsum;
2300 chi2 /= sum1 * sum2;
2305 Info(
"Chi2TestX",
"There is a bin in h1 with less than 1 event.\n");
2309 Info(
"Chi2TestX",
"There is a bin in h2 with less than 1 event.\n");
2320 if ( comparisonUW ) {
2321 for (
Int_t i = i_start; i <= i_end; ++i) {
2322 for (
Int_t j = j_start; j <= j_end; ++j) {
2323 for (
Int_t k = k_start; k <= k_end; ++k) {
2328 Double_t cnt2 = h2->RetrieveBinContent(bin);
2329 Double_t e2sq = h2->GetBinErrorSqUnchecked(bin);
2332 if (cnt1 * cnt1 == 0 && cnt2 * cnt2 == 0) {
2338 if (cnt2 * cnt2 == 0 && e2sq == 0) {
2342 e2sq = sumw2 / sum2;
2347 Error(
"Chi2TestX",
"Hist2 has in bin (%d,%d,%d) zero content and zero errors\n", i, j, k);
2353 if (e2sq > 0 && cnt2 * cnt2 / e2sq < 10)
n++;
2355 Double_t var1 = sum2 * cnt2 - sum1 * e2sq;
2356 Double_t var2 = var1 * var1 + 4. * sum2 * sum2 * cnt1 * e2sq;
2361 while (var1 * var1 + cnt1 == 0 || var1 + var2 == 0) {
2364 var1 = sum2 * cnt2 - sum1 * e2sq;
2365 var2 = var1 * var1 + 4. * sum2 * sum2 * cnt1 * e2sq;
2369 while (var1 + var2 == 0) {
2372 var1 = sum2 * cnt2 - sum1 * e2sq;
2373 var2 = var1 * var1 + 4. * sum2 * sum2 * cnt1 * e2sq;
2374 while (var1 * var1 + cnt1 == 0 || var1 + var2 == 0) {
2377 var1 = sum2 * cnt2 - sum1 * e2sq;
2378 var2 = var1 * var1 + 4. * sum2 * sum2 * cnt1 * e2sq;
2383 Double_t probb = (var1 + var2) / (2. * sum2 * sum2);
2391 chi2 += delta1 * delta1 / nexp1;
2394 chi2 += delta2 * delta2 / e2sq;
2399 Double_t temp1 = sum2 * e2sq / var2;
2400 Double_t temp2 = 1.0 + (sum1 * e2sq - sum2 * cnt2) / var2;
2401 temp2 = temp1 * temp1 * sum1 * probb * (1.0 - probb) + temp2 * temp2 * e2sq / 4.0;
2414 Info(
"Chi2TestX",
"There is a bin in h1 with less than 1 event.\n");
2418 Info(
"Chi2TestX",
"There is a bin in h2 with less than 10 effective events.\n");
2428 for (
Int_t i = i_start; i <= i_end; ++i) {
2429 for (
Int_t j = j_start; j <= j_end; ++j) {
2430 for (
Int_t k = k_start; k <= k_end; ++k) {
2434 Double_t cnt2 = h2->RetrieveBinContent(bin);
2436 Double_t e2sq = h2->GetBinErrorSqUnchecked(bin);
2440 if (cnt1 * cnt1 == 0 && cnt2 * cnt2 == 0) {
2445 if (e1sq == 0 && e2sq == 0) {
2447 Error(
"Chi2TestX",
"h1 and h2 both have bin %d,%d,%d with all zero errors\n", i,j,k);
2452 Double_t delta = sum2 * cnt1 - sum1 * cnt2;
2453 chi2 += delta * delta /
sigma;
2456 Double_t temp = cnt1 * sum1 * e2sq + cnt2 * sum2 * e1sq;
2469 res[i - i_start] = z;
2472 if (e1sq > 0 && cnt1 * cnt1 / e1sq < 10)
m++;
2473 if (e2sq > 0 && cnt2 * cnt2 / e2sq < 10)
n++;
2479 Info(
"Chi2TestX",
"There is a bin in h1 with less than 10 effective events.\n");
2483 Info(
"Chi2TestX",
"There is a bin in h2 with less than 10 effective events.\n");
2501 Error(
"Chisquare",
"Function pointer is Null - return -1");
2550 Int_t nbins = nbinsx * nbinsy * nbinsz;
2555 for (
Int_t binz=1; binz <= nbinsz; ++binz) {
2556 for (
Int_t biny=1; biny <= nbinsy; ++biny) {
2557 for (
Int_t binx=1; binx <= nbinsx; ++binx) {
2560 if (onlyPositive &&
y < 0) {
2561 Error(
"ComputeIntegral",
"Bin content is negative - return a NaN value");
2572 Error(
"ComputeIntegral",
"Integral = 0, no hits in histogram bins (excluding over/underflow).");
2628 hintegrated->
Reset();
2632 for (
Int_t binz = firstZ; binz <= lastZ; ++binz) {
2633 for (
Int_t biny = firstY; biny <= lastY; ++biny) {
2634 for (
Int_t binx = firstX; binx <= lastX; ++binx) {
2635 const Int_t bin = hintegrated->
GetBin(binx, biny, binz);
2646 for (
Int_t binz = lastZ; binz >= firstZ; --binz) {
2647 for (
Int_t biny = lastY; biny >= firstY; --biny) {
2648 for (
Int_t binx = lastX; binx >= firstX; --binx) {
2649 const Int_t bin = hintegrated->
GetBin(binx, biny, binz);
2680 ((
TH1&)obj).fDirectory =
nullptr;
2694 delete [] ((
TH1&)obj).fBuffer;
2695 ((
TH1&)obj).fBuffer =
nullptr;
2701 ((
TH1&)obj).fBuffer = buf;
2731 ((
TH1&)obj).fXaxis.SetParent(&obj);
2732 ((
TH1&)obj).fYaxis.SetParent(&obj);
2733 ((
TH1&)obj).fZaxis.SetParent(&obj);
2743 ((
TH1&)obj).fFunctions->UseRWLock();
2771 oldparent = oldstats->GetParent();
2772 oldstats->SetParent(
nullptr);
2778 oldstats->SetParent(oldparent);
2790 if(newname && strlen(newname) ) {
2845 Error(
"Divide",
"Attempt to divide by a non-existing function");
2863 Int_t bin, binx, biny, binz;
2868 for (binz = 0; binz < nz; ++binz) {
2870 for (biny = 0; biny < ny; ++biny) {
2872 for (binx = 0; binx < nx; ++binx) {
2876 bin = binx + nx * (biny + ny * binz);
2913 Error(
"Divide",
"Input histogram passed does not exist (NULL).");
2976 Error(
"Divide",
"At least one of the input histograms passed does not exist (NULL).");
2989 Error(
"Divide",
"Coefficient of dividing histogram cannot be zero");
3002 Double_t b2 = h2->RetrieveBinContent(i);
3011 Double_t e2sq = h2->GetBinErrorSqUnchecked(i);
3026 fSumw2.
fArray[i] = c1sq * c2sq * (e1sq * b2sq + e2sq * b1sq) / (c2sq * c2sq * b2sq * b2sq);
3085 if (!
gPad->IsEditable())
gROOT->MakeDefCanvas();
3087 if (
gPad->GetX1() == 0 &&
gPad->GetX2() == 1 &&
3088 gPad->GetY1() == 0 &&
gPad->GetY2() == 1 &&
3096 gPad->IncrementPaletteColor(1, opt1);
3121 if (name_postfix) newName.
Form(
"%s%s",
GetName(), name_postfix);
3125 if (
gPad)
gPad->IncrementPaletteColor(1, opt);
3150 Error(
"DrawNormalized",
"Sum of weights is null. Cannot normalize histogram: %s",
GetName());
3162 if (opt.
IsNull() || opt ==
"SAME") opt +=
"HIST";
3197 Int_t range, stat, add;
3217 for (
Int_t binz = 1; binz <= nbinsz; ++binz) {
3219 for (
Int_t biny = 1; biny <= nbinsy; ++biny) {
3221 for (
Int_t binx = 1; binx <= nbinsx; ++binx) {
3319 if (!fft)
return nullptr;
3321 for (
Int_t binx = 1; binx<=ndim[0]; binx++) {
3322 for (
Int_t biny=1; biny<=ndim[1]; biny++) {
3323 for (
Int_t binz=1; binz<=ndim[2]; binz++) {
3353 if (bin <0)
return -1;
3386 if (bin <0)
return -1;
3419 if (bin <0)
return -1;
3455 for (i=0;i<ntimes;i+=stride) {
3462 auto weights =
w ? &
w[i] :
nullptr;
3463 DoFillN((ntimes-i)/stride,&
x[i],weights,stride);
3483 for (i=0;i<ntimes;i+=stride) {
3485 if (bin <0)
continue;
3490 if (bin == 0 || bin > nbins) {
3523 Int_t bin, binx, ibin, loop;
3527 if (!
f1) {
Error(
"FillRandom",
"Unknown function: %s",fname);
return; }
3537 Info(
"FillRandom",
"Using function axis and range [%g,%g]",
xmin,
xmax);
3543 Int_t nbinsx = last-first+1;
3547 for (binx=1;binx<=nbinsx;binx++) {
3549 integral[binx] = integral[binx-1] + fint;
3553 if (integral[nbinsx] == 0 ) {
3555 Error(
"FillRandom",
"Integral = zero");
return;
3557 for (bin=1;bin<=nbinsx;bin++) integral[bin] /= integral[nbinsx];
3560 for (loop=0;loop<ntimes;loop++) {
3566 +xAxis->
GetBinWidth(ibin+first)*(r1-integral[ibin])/(integral[ibin+1] - integral[ibin]);
3594 if (!
h) {
Error(
"FillRandom",
"Null histogram");
return; }
3596 Error(
"FillRandom",
"Histograms with different dimensions");
return;
3598 if (std::isnan(
h->ComputeIntegral(
true))) {
3599 Error(
"FillRandom",
"Histograms contains negative bins, does not represent probabilities");
3607 Int_t nbins = last-first+1;
3608 if (ntimes > 10*nbins) {
3610 if (inconsistency != kFullyConsistent)
return;
3611 Double_t sumw =
h->Integral(first,last);
3612 if (sumw == 0)
return;
3614 for (
Int_t bin=first;bin<=last;bin++) {
3615 Double_t mean =
h->RetrieveBinContent(bin)*ntimes/sumw;
3626 if (sumgen < ntimes) {
3628 for (i =
Int_t(sumgen+0.5); i < ntimes; ++i)
3634 else if (sumgen > ntimes) {
3636 i =
Int_t(sumgen+0.5);
3637 while( i > ntimes) {
3654 if (
h->ComputeIntegral() ==0)
return;
3657 for (loop=0;loop<ntimes;loop++) {
3683 return binx + nx*biny;
3691 return binx + nx*(biny +ny*binz);
3716 return binx + nx*biny;
3724 return binx + nx*(biny +ny*binz);
3742 Warning(
"FindFirstBinAbove",
"Invalid axis number : %d, axis x assumed\n",axis);
3756 for (
Int_t binx = firstBin; binx <= lastBin; binx++) {
3757 for (
Int_t biny = 1; biny <= nbinsy; biny++) {
3758 for (
Int_t binz = 1; binz <= nbinsz; binz++) {
3764 else if (axis == 2) {
3768 for (
Int_t biny = firstBin; biny <= lastBin; biny++) {
3769 for (
Int_t binx = 1; binx <= nbinsx; binx++) {
3770 for (
Int_t binz = 1; binz <= nbinsz; binz++) {
3776 else if (axis == 3) {
3780 for (
Int_t binz = firstBin; binz <= lastBin; binz++) {
3781 for (
Int_t binx = 1; binx <= nbinsx; binx++) {
3782 for (
Int_t biny = 1; biny <= nbinsy; biny++) {
3806 Warning(
"FindFirstBinAbove",
"Invalid axis number : %d, axis x assumed\n",axis);
3820 for (
Int_t binx = lastBin; binx >= firstBin; binx--) {
3821 for (
Int_t biny = 1; biny <= nbinsy; biny++) {
3822 for (
Int_t binz = 1; binz <= nbinsz; binz++) {
3828 else if (axis == 2) {
3832 for (
Int_t biny = lastBin; biny >= firstBin; biny--) {
3833 for (
Int_t binx = 1; binx <= nbinsx; binx++) {
3834 for (
Int_t binz = 1; binz <= nbinsz; binz++) {
3840 else if (axis == 3) {
3844 for (
Int_t binz = lastBin; binz >= firstBin; binz--) {
3845 for (
Int_t binx = 1; binx <= nbinsx; binx++) {
3846 for (
Int_t biny = 1; biny <= nbinsy; biny++) {
3903 linear= (
char*)strstr(fname,
"++");
3907 TF1 f1(fname, fname, xxmin, xxmax);
3911 TF2 f2(fname, fname);
3912 return Fit(&f2,
option,goption,xxmin,xxmax);
3915 TF3 f3(fname, fname);
3916 return Fit(&f3,
option,goption,xxmin,xxmax);
3921 if (!
f1) {
Printf(
"Unknown function: %s",fname);
return -1; }
4289 gROOT->MakeDefCanvas();
4292 Error(
"FitPanel",
"Unable to create a default canvas");
4299 if (handler && handler->
LoadPlugin() != -1) {
4301 Error(
"FitPanel",
"Unable to create the FitPanel");
4304 Error(
"FitPanel",
"Unable to find the FitPanel plug-in");
4361 asym->
Divide(top,bottom);
4368 if (h2->fBuffer) h2->BufferEmpty(1);
4375 for(
Int_t k=1; k<= zmax; k++){
4380 Double_t b = h2->RetrieveBinContent(bin);
4390 Double_t dbsq = h2->GetBinErrorSqUnchecked(bin);
4454 return (s[1] ? s[0]*s[0]/s[1] :
TMath::Abs(s[0]) );
4466 Info(
"SetHighlight",
"Supported only 1-D or 2-D histograms");
4483 return ((
TH1*)
this)->GetPainter()->GetObjectInfo(px,py);
4584 Error(
"GetQuantiles",
"Only available for 1-d histograms");
4594 Int_t nq = nprobSum;
4595 if (probSum ==
nullptr) {
4599 for (i=1;i<nq;i++) {
4604 for (i = 0; i < nq; i++) {
4606 while (ibin < nbins-1 &&
fIntegral[ibin+1] == prob[i]) {
4607 if (
fIntegral[ibin+2] == prob[i]) ibin++;
4615 if (!probSum)
delete [] prob;
4633 Double_t allcha, sumx, sumx2,
x, val, stddev, mean;
4644 allcha = sumx = sumx2 = 0;
4645 for (bin=hxfirst;bin<=hxlast;bin++) {
4648 if (val > valmax) valmax = val;
4653 if (allcha == 0)
return;
4655 stddev = sumx2/allcha - mean*mean;
4658 if (stddev == 0) stddev = binwidx*(hxlast-hxfirst+1)/4;
4665 Double_t constant = 0.5*(valmax+binwidx*allcha/(sqrtpi*stddev));
4673 if ((mean < xmin || mean >
xmax) && stddev > (
xmax-
xmin)) {
4694 Int_t nchanx = hxlast - hxfirst + 1;
4715 Int_t nchanx = hxlast - hxfirst + 1;
4718 if (nchanx <=1 || npar == 1) {
4741 const Int_t idim = 20;
4752 if (
m > idim ||
m >
n)
return;
4755 for (
l = 2;
l <=
m; ++
l) {
4757 b[
m +
l*20 - 21] = zero;
4764 for (k = hxfirst; k <= hxlast; ++k) {
4769 for (
l = 2;
l <=
m; ++
l) {
4772 da[
l-1] += power*yk;
4774 for (
l = 2;
l <=
m; ++
l) {
4776 b[
m +
l*20 - 21] += power;
4779 for (i = 3; i <=
m; ++i) {
4780 for (k = i; k <=
m; ++k) {
4781 b[k - 1 + (i-1)*20 - 21] =
b[k + (i-2)*20 - 21];
4786 for (i=0; i<
m; ++i)
a[i] = da[i];
4806 xbar = ybar = x2bar = xybar = 0;
4811 for (i = hxfirst; i <= hxlast; ++i) {
4815 if (yk <= 0) yk = 1
e-9;
4824 det = fn*x2bar - xbar*xbar;
4832 a0 = (x2bar*ybar - xbar*xybar) / det;
4833 a1 = (fn*xybar - xbar*ybar) / det;
4844 Int_t a_dim1, a_offset, b_dim1, b_offset;
4846 Int_t im1, jp1, nm1, nmi;
4852 b_offset = b_dim1 + 1;
4855 a_offset = a_dim1 + 1;
4858 if (idim <
n)
return;
4861 for (j = 1; j <=
n; ++j) {
4862 if (
a[j + j*a_dim1] <= 0) { ifail = -1;
return; }
4863 a[j + j*a_dim1] = one /
a[j + j*a_dim1];
4864 if (j ==
n)
continue;
4866 for (
l = jp1;
l <=
n; ++
l) {
4867 a[j +
l*a_dim1] =
a[j + j*a_dim1] *
a[
l + j*a_dim1];
4868 s1 = -
a[
l + (j+1)*a_dim1];
4869 for (i = 1; i <= j; ++i) {
s1 =
a[
l + i*a_dim1] *
a[i + (j+1)*a_dim1] +
s1; }
4870 a[
l + (j+1)*a_dim1] = -
s1;
4875 for (
l = 1;
l <= k; ++
l) {
4876 b[
l*b_dim1 + 1] =
a[a_dim1 + 1]*
b[
l*b_dim1 + 1];
4879 for (
l = 1;
l <= k; ++
l) {
4880 for (i = 2; i <=
n; ++i) {
4882 s21 = -
b[i +
l*b_dim1];
4883 for (j = 1; j <= im1; ++j) {
4884 s21 =
a[i + j*a_dim1]*
b[j +
l*b_dim1] + s21;
4886 b[i +
l*b_dim1] = -
a[i + i*a_dim1]*s21;
4889 for (i = 1; i <= nm1; ++i) {
4891 s22 = -
b[nmi +
l*b_dim1];
4892 for (j = 1; j <= i; ++j) {
4894 s22 =
a[nmi + nmjp1*a_dim1]*
b[nmjp1 +
l*b_dim1] + s22;
4896 b[nmi +
l*b_dim1] = -s22;
4934 if (binx < 0) binx = 0;
4935 if (binx > ofx) binx = ofx;
4950 binx = binglobal%nx;
4956 binx = binglobal%nx;
4957 biny = ((binglobal-binx)/nx)%ny;
4962 binx = binglobal%nx;
4963 biny = ((binglobal-binx)/nx)%ny;
4964 binz = ((binglobal-binx)/nx -biny)/ny;
4983 Error(
"GetRandom",
"Function only valid for 1-d histograms");
4993 integral = ((
TH1*)
this)->ComputeIntegral(
true);
4995 if (integral == 0)
return 0;
5034 if (bin < 0) bin = 0;
5060 Error(
"GetBinWithContent",
"function is only valid for 1-D histograms");
5066 if (firstx <= 0) firstx = 1;
5070 for (
Int_t i=firstx;i<=lastx;i++) {
5072 if (diff <= 0) {binx = i;
return diff;}
5073 if (diff < curmax && diff <= maxdiff) {curmax = diff, binminx=i;}
5108 return y0 + (
x-x0)*((
y1-y0)/(
x1-x0));
5117 Error(
"Interpolate",
"This function must be called with 1 argument for a TH1");
5126 Error(
"Interpolate",
"This function must be called with 1 argument for a TH1");
5154 Int_t binx, biny, binz;
5176 Error(
"IsBinOverflow",
"Invalid axis value");
5186 Int_t binx, biny, binz;
5193 return (binx <= 0 || biny <= 0);
5195 return (binx <= 0 || biny <= 0 || binz <= 0);
5206 Error(
"IsBinUnderflow",
"Invalid axis value");
5218 TAxis *axis =
nullptr;
5223 Error(
"LabelsDeflate",
"Invalid axis option %s",ax);
5234 while ((obj = next())) {
5236 if (ibin > nbins) nbins = ibin;
5238 if (nbins < 1) nbins = 1;
5241 if (nbins==axis->
GetNbins())
return;
5266 Int_t bin,binx,biny,binz;
5267 for (bin=0; bin < hold->
fNcells; ++bin) {
5288 TAxis *axis =
nullptr;
5316 Int_t bin,ibin,binx,biny,binz;
5317 for (ibin =0; ibin < hold->
fNcells; ibin++) {
5320 bin =
GetBin(binx,biny,binz);
5355 TAxis *axis =
nullptr;
5366 Warning(
"LabelsOption",
"Axis %s has no labels!",axis->
GetName());
5409 Error(
"LabelsOption",
"%s is an invalid label placement option!",opt.
Data());
5423 Int_t lastLabelBin = -1;
5424 for (
Int_t i = 0; i <
n; ++i) {
5426 if (bin < firstLabelBin) firstLabelBin = bin;
5427 if (bin > lastLabelBin) lastLabelBin = bin;
5429 if (firstLabelBin != 1 || lastLabelBin-firstLabelBin +1 !=
n) {
5430 Error(
"LabelsOption",
"%s of Histogram %s contains bins without labels. Sorting will not work correctly - return",
5436 Warning(
"LabelsOption",
"axis %s of Histogram %s has extra following bins without labels. Sorting will work only for first label bins",
5439 std::vector<Int_t>
a(
n);
5440 std::vector<Int_t>
b(
n);
5444 std::vector<Double_t> cont;
5445 std::vector<Double_t> errors2;
5447 TIter nextold(labels);
5462 for (i = 0; i <
n; i++) {
5464 if (!errors2.empty())
5473 for (i = 0; i <
n; i++) {
5477 Info(
"LabelsOption",
"setting bin %d value %f from bin %d label %s at pos %d ",
5479 if (!errors2.empty())
5482 for (i = 0; i <
n; i++) {
5483 obj = labold->
At(
a[i]);
5488 std::vector<Double_t> pcont(
n + 2);
5491 cont.resize((nx + 2) * (ny + 2));
5493 errors2.resize((nx + 2) * (ny + 2));
5494 for (i = 0; i < nx; i++) {
5495 for (j = 0; j < ny; j++) {
5498 if (!errors2.empty())
5504 if (k >= 0 && k <
n) {
5505 pcont[k] += cont[i + nx * j];
5514 for (i = 0; i <
n; i++) {
5518 while ((obj = next())) {
5526 R__ASSERT(
"LabelsOption - No corresponding bin found when ordering labels");
5532 std::cout <<
" set label " << obj->
GetName() <<
" to bin " << i + 1 <<
" from order " <<
a[i] <<
" bin "
5533 <<
b[
a[i]] <<
"content " << pcont[
a[i]] << std::endl;
5537 for (i = 0; i <
n; i++) {
5542 for (i = 0; i <
n; i++) {
5544 for (j = 0; j < ny; j++) {
5547 if (!errors2.empty())
5553 for (i = 0; i < nx; i++) {
5554 for (j = 0; j <
n; j++) {
5558 if (!errors2.empty())
5565 std::vector<Double_t> pcont(
n + 2);
5570 cont.resize((nx + 2) * (ny + 2) * (nz + 2));
5572 errors2.resize((nx + 2) * (ny + 2) * (nz + 2));
5573 for (i = 0; i < nx; i++) {
5574 for (j = 0; j < ny; j++) {
5575 for (k = 0; k < nz; k++) {
5584 if (
l >= 0 &&
l <
n) {
5588 cont[i + nx * (j + ny * k)] =
c;
5589 if (!errors2.empty())
5598 for (i = 0; i <
n; i++) {
5603 while ((obj = next())) {
5611 R__ASSERT(
"LabelsOption - No corresponding bin found when ordering labels");
5616 std::cout <<
" set label " << obj->
GetName() <<
" to bin " << i + 1 <<
" from bin " <<
a[i] <<
"content "
5617 << pcont[
a[i]] << std::endl;
5622 for (i = 0; i <
n; i++) {
5627 for (i = 0; i <
n; i++) {
5629 for (j = 0; j < ny; j++) {
5630 for (k = 0; k < nz; k++) {
5633 if (!errors2.empty())
5640 for (i = 0; i < nx; i++) {
5641 for (j = 0; j <
n; j++) {
5643 for (k = 0; k < nz; k++) {
5646 if (!errors2.empty())
5653 for (i = 0; i < nx; i++) {
5654 for (j = 0; j < ny; j++) {
5655 for (k = 0; k <
n; k++) {
5659 if (!errors2.empty())
5670 std::vector<std::string> vecLabels(
n);
5671 for (i = 0; i <
n; i++) {
5672 vecLabels[i] = labold->
At(i)->
GetName();
5679 for (i = 0; i <
n; i++) {
5681 labels->
Add(labold->
At(
a[i]));
5685 std::cout <<
"bin " << i + 1 <<
" setting new labels for axis " << labold->
At(
a[i])->
GetName() <<
" from "
5686 <<
b[
a[i]] << std::endl;
5692 errors2.resize(
n + 2);
5693 for (i = 0; i <
n; i++) {
5695 if (!errors2.empty())
5698 for (i = 0; i <
n; i++) {
5700 if (!errors2.empty())
5706 cont.resize(nx * ny);
5708 errors2.resize(nx * ny);
5711 for (i = 0; i < nx; i++) {
5712 for (j = 0; j < ny; j++) {
5715 if (!errors2.empty())
5720 for (i = 0; i <
n; i++) {
5721 for (j = 0; j < ny; j++) {
5724 if (!errors2.empty())
5729 for (i = 0; i < nx; i++) {
5730 for (j = 0; j <
n; j++) {
5733 if (!errors2.empty())
5743 cont.resize(nx * ny * nz);
5745 errors2.resize(nx * ny * nz);
5746 for (i = 0; i < nx; i++) {
5747 for (j = 0; j < ny; j++) {
5748 for (k = 0; k < nz; k++) {
5751 if (!errors2.empty())
5758 for (i = 0; i <
n; i++) {
5759 for (j = 0; j < ny; j++) {
5760 for (k = 0; k < nz; k++) {
5763 if (!errors2.empty())
5770 for (i = 0; i < nx; i++) {
5771 for (j = 0; j <
n; j++) {
5772 for (k = 0; k < nz; k++) {
5775 if (!errors2.empty())
5782 for (i = 0; i < nx; i++) {
5783 for (j = 0; j < ny; j++) {
5784 for (k = 0; k <
n; k++) {
5787 if (!errors2.empty())
5797 bool labelsAreSorted =
kFALSE;
5798 for (i = 0; i <
n; ++i) {
5800 labelsAreSorted =
kTRUE;
5804 if (labelsAreSorted) {
5812 }
else if (iaxis == 2) {
5817 }
else if (iaxis == 3) {
5853 bool isEquidistant =
true;
5855 for (
int i = 1; i < axis.
GetNbins(); ++i) {
5858 isEquidistant &= match;
5862 return isEquidistant;
5888 if (width1 == 0 || width2 == 0)
5934 printf(
"TH1::RecomputeAxisLimits - Impossible\n");
6022 Error(
"Multiply",
"Attempt to multiply by a non-existing function");
6044 for (
Int_t binz = 0; binz < nz; ++binz) {
6046 for (
Int_t biny = 0; biny < ny; ++biny) {
6048 for (
Int_t binx = 0; binx < nx; ++binx) {
6052 Int_t bin = binx + nx * (biny + ny *binz);
6084 Error(
"Multiply",
"Attempt to multiply by a non-existing histogram");
6137 Error(
"Multiply",
"Attempt to multiply by a non-existing histogram");
6160 Double_t b2 = h2->RetrieveBinContent(i);
6250 if ((ngroup <= 0) || (ngroup > nbins)) {
6251 Error(
"Rebin",
"Illegal value of ngroup=%d",ngroup);
6256 Error(
"Rebin",
"Operation valid on 1-D histograms only");
6259 if (!newname && xbins) {
6260 Error(
"Rebin",
"if xbins is specified, newname must be given");
6264 Int_t newbins = nbins/ngroup;
6266 Int_t nbg = nbins/ngroup;
6267 if (nbg*ngroup != nbins) {
6268 Warning(
"Rebin",
"ngroup=%d is not an exact divider of nbins=%d.",ngroup,nbins);
6288 for (bin=0;bin<nbins+2;bin++) oldErrors[bin] =
GetBinError(bin);
6293 Warning(
"Rebin",
"underflow entries will not be used when rebinning");
6294 if (xbins[newbins] >
fXaxis.
GetXmax() && oldBins[nbins+1] != 0 )
6295 Warning(
"Rebin",
"overflow entries will not be used when rebinning");
6301 if ((newname && strlen(newname) > 0) || xbins) {
6311 bool resetStat =
false;
6313 if(!xbins && (newbins*ngroup != nbins)) {
6361 Int_t oldbin = startbin;
6363 for (bin = 1;bin<=newbins;bin++) {
6366 Int_t imax = ngroup;
6374 Warning(
"Rebin",
"Bin edge %d of rebinned histogram does not match any bin edges of the old histogram. Result can be inconsistent",bin);
6376 for (i=0;i<ngroup;i++) {
6377 if( (oldbin+i > nbins) ||
6382 binContent += oldBins[oldbin+i];
6383 if (oldErrors) binError += oldErrors[oldbin+i]*oldErrors[oldbin+i];
6393 for (i = 0; i < startbin; ++i) {
6394 binContent += oldBins[i];
6395 if (oldErrors) binError += oldErrors[i]*oldErrors[i];
6402 for (i = oldbin; i <= nbins+1; ++i) {
6403 binContent += oldBins[i];
6404 if (oldErrors) binError += oldErrors[i]*oldErrors[i];
6413 if (!resetStat) hnew->
PutStats(stat);
6415 if (oldErrors)
delete [] oldErrors;
6439 while (point <
xmin) {
6445 while (point >=
xmax) {
6503 if (axis == &
fXaxis) iaxis = 1;
6504 if (axis == &
fYaxis) iaxis = 2;
6505 if (axis == &
fZaxis) iaxis = 3;
6506 bool firstw =
kTRUE;
6507 Int_t binx,biny, binz = 0;
6508 Int_t ix = 0,iy = 0,iz = 0;
6511 for (
Int_t bin = 0; bin < ncells; ++bin) {
6525 if (content == 0)
continue;
6528 Warning(
"ExtendAxis",
"Histogram %s has underflow or overflow in the axis that is extendable"
6529 " their content will be lost",
GetName() );
6589 if (i == 1) s[i] =
c1*
c1*s[i];
6590 else s[i] =
c1*s[i];
6598 if (ncontours == 0)
return;
6600 for (
Int_t i = 0; i < ncontours; ++i) levels[i] *=
c1;
6639 return oldExtendBitMask;
6700 str1 = str1(isc+1, lns);
6701 isc = str1.
Index(
";");
6704 str2.ReplaceAll(
"#semicolon",10,
";",1);
6707 str1 = str1(isc+1, lns);
6708 isc = str1.
Index(
";");
6711 str2.ReplaceAll(
"#semicolon",10,
";",1);
6714 str1 = str1(isc+1, lns);
6741 ::Error(
"SmoothArray",
"Need at least 3 points for smoothing: n = %d",nn);
6746 std::array<double, 3> hh{};
6748 std::vector<double> yy(nn);
6749 std::vector<double> zz(nn);
6750 std::vector<double> rr(nn);
6752 for (
Int_t pass=0;pass<ntimes;pass++) {
6754 std::copy(xx, xx+nn, zz.begin() );
6756 for (
int noent = 0; noent < 2; ++noent) {
6759 for (
int kk = 0; kk < 3; kk++) {
6760 std::copy(zz.begin(), zz.end(), yy.begin());
6761 int medianType = (kk != 1) ? 3 : 5;
6762 int ifirst = (kk != 1 ) ? 1 : 2;
6763 int ilast = (kk != 1 ) ? nn-1 : nn -2;
6767 for ( ii = ifirst; ii < ilast; ii++) {
6768 zz[ii] =
TMath::Median(medianType, yy.data() + ii - ifirst);
6775 hh[2] = 3*zz[1] - 2*zz[2];
6780 hh[2] = 3*zz[nn - 2] - 2*zz[nn - 3];
6795 std::copy ( zz.begin(), zz.end(), yy.begin() );
6798 for (ii = 2; ii < (nn - 2); ii++) {
6799 if (zz[ii - 1] != zz[ii])
continue;
6800 if (zz[ii] != zz[ii + 1])
continue;
6801 const double tmp0 = zz[ii - 2] - zz[ii];
6802 const double tmp1 = zz[ii + 2] - zz[ii];
6803 if (tmp0 * tmp1 <= 0)
continue;
6805 if ( std::abs(tmp0) > std::abs(tmp0) ) jk = -1;
6806 yy[ii] = -0.5*zz[ii - 2*jk] + zz[ii]/0.75 + zz[ii + 2*jk] /6.;
6807 yy[ii + jk] = 0.5*(zz[ii + 2*jk] - zz[ii - 2*jk]) + zz[ii];
6812 for (ii = 1; ii < nn - 1; ii++) {
6813 zz[ii] = 0.25*yy[ii - 1] + 0.5*yy[ii] + 0.25*yy[ii + 1];
6816 zz[nn - 1] = yy[nn - 1];
6821 std::copy(zz.begin(), zz.end(), rr.begin());
6824 for (ii = 0; ii < nn; ii++) {
6825 zz[ii] = xx[ii] - zz[ii];
6833 for (ii = 0; ii < nn; ii++) {
6834 if (
xmin < 0) xx[ii] = rr[ii] + zz[ii];
6836 else xx[ii] = std::max((rr[ii] + zz[ii]),0.0 );
6852 Error(
"Smooth",
"Smooth only supported for 1-d histograms");
6857 Error(
"Smooth",
"Smooth only supported for histograms with >= 3 bins. Nbins = %d",nbins);
6864 Int_t firstbin = 1, lastbin = nbins;
6871 nbins = lastbin - firstbin + 1;
6875 for (i=0;i<nbins;i++) {
6881 for (i=0;i<nbins;i++) {
6905 if (
b.IsReading()) {
6907 Version_t R__v =
b.ReadVersion(&R__s, &R__c);
6911 b.ReadClassBuffer(
TH1::Class(),
this, R__v, R__s, R__c);
6919 while ((obj=next())) {
6944 Float_t maximum, minimum, norm;
6949 Int_t n =
b.ReadArray(contour);
6963 b.CheckByteCount(R__s, R__c,
TH1::IsA());
6987 else if (opt.
Contains(
"range")) all = 1;
6988 else if (opt.
Contains(
"base")) all = 2;
6991 Int_t bin, binx, biny, binz;
6992 Int_t firstx=0,lastx=0,firsty=0,lasty=0,firstz=0,lastz=0;
7004 printf(
" Title = %s\n",
GetTitle());
7015 for (binx=firstx;binx<=lastx;binx++) {
7019 if(
fSumw2.
fN) printf(
" fSumw[%d]=%g, x=%g, error=%g\n",binx,
w,
x,
e);
7020 else printf(
" fSumw[%d]=%g, x=%g\n",binx,
w,
x);
7024 for (biny=firsty;biny<=lasty;biny++) {
7026 for (binx=firstx;binx<=lastx;binx++) {
7031 if(
fSumw2.
fN) printf(
" fSumw[%d][%d]=%g, x=%g, y=%g, error=%g\n",binx,biny,
w,
x,
y,
e);
7032 else printf(
" fSumw[%d][%d]=%g, x=%g, y=%g\n",binx,biny,
w,
x,
y);
7037 for (binz=firstz;binz<=lastz;binz++) {
7039 for (biny=firsty;biny<=lasty;biny++) {
7041 for (binx=firstx;binx<=lastx;binx++) {
7042 bin =
GetBin(binx,biny,binz);
7046 if(
fSumw2.
fN) printf(
" fSumw[%d][%d][%d]=%g, x=%g, y=%g, z=%g, error=%g\n",binx,biny,binz,
w,
x,
y,z,
e);
7047 else printf(
" fSumw[%d][%d][%d]=%g, x=%g, y=%g, z=%g\n",binx,biny,binz,
w,
x,
y,z);
7108 if (opt ==
"ICES")
return;
7162 }
else if (fname.
EndsWith(
".tsv")) {
7165 }
else if (fname.
EndsWith(
".txt")) {
7182 out <<
"#\tBinLowEdge\tBinUpEdge\t"
7184 <<
"\tey" << std::endl;
7186 out <<
"#\tBinLowEdge\tBinUpEdge\t" <<
GetYaxis()->
GetTitle() <<
"\tey" << std::endl;
7216 static Int_t nxaxis = 0;
7217 static Int_t nyaxis = 0;
7218 static Int_t nzaxis = 0;
7219 TString sxaxis=
"xAxis",syaxis=
"yAxis",szaxis=
"zAxis";
7230 if (i != 0) out <<
", ";
7233 out <<
"}; " << std::endl;
7246 if (i != 0) out <<
", ";
7249 out <<
"}; " << std::endl;
7262 if (i != 0) out <<
", ";
7265 out <<
"}; " << std::endl;
7269 out <<
" "<<std::endl;
7279 static Int_t hcounter = 0;
7286 histName += hcounter;
7289 const char *hname = histName.
Data();
7290 if (!strlen(hname)) hname =
"unnamed";
7296 out << hname <<
" = new " <<
ClassName() <<
"(" << quote
7297 << hname << quote <<
"," << quote<< t.
Data() << quote
7300 out <<
", "<<sxaxis;
7307 out <<
", "<<syaxis;
7315 out <<
", "<<szaxis;
7320 out <<
");" << std::endl;
7324 for (bin=0;bin<
fNcells;bin++) {
7327 out<<
" "<<hname<<
"->SetBinContent("<<bin<<
","<<bc<<
");"<<std::endl;
7333 for (bin=0;bin<
fNcells;bin++) {
7336 out<<
" "<<hname<<
"->SetBinError("<<bin<<
","<<be<<
");"<<std::endl;
7353 out<<
" "<<hname<<
"->SetBarOffset("<<
GetBarOffset()<<
");"<<std::endl;
7356 out<<
" "<<hname<<
"->SetBarWidth("<<
GetBarWidth()<<
");"<<std::endl;
7359 out<<
" "<<hname<<
"->SetMinimum("<<
fMinimum<<
");"<<std::endl;
7362 out<<
" "<<hname<<
"->SetMaximum("<<
fMaximum<<
");"<<std::endl;
7365 out<<
" "<<hname<<
"->SetNormFactor("<<
fNormFactor<<
");"<<std::endl;
7368 out<<
" "<<hname<<
"->SetEntries("<<
fEntries<<
");"<<std::endl;
7371 out<<
" "<<hname<<
"->SetDirectory(nullptr);"<<std::endl;
7374 out<<
" "<<hname<<
"->SetStats(0);"<<std::endl;
7377 out<<
" "<<hname<<
"->SetOption("<<quote<<
fOption.
Data()<<quote<<
");"<<std::endl;
7382 if (ncontours > 0) {
7383 out<<
" "<<hname<<
"->SetContour("<<ncontours<<
");"<<std::endl;
7385 for (
Int_t bin=0;bin<ncontours;bin++) {
7386 if (
gPad->GetLogz()) {
7391 out<<
" "<<hname<<
"->SetContourLevel("<<bin<<
","<<zlevel<<
");"<<std::endl;
7397 static Int_t funcNumber = 0;
7399 auto obj = lnk->GetObject();
7400 obj->SavePrimitive(out,
TString::Format(
"nodraw #%d\n",++funcNumber).Data());
7403 fname.
Form(
"%s%d",obj->GetName(),funcNumber);
7404 out <<
" " << fname <<
"->SetParent(" << hname <<
");\n";
7405 out<<
" "<<hname<<
"->GetListOfFunctions()->Add("
7406 << fname <<
");"<<std::endl;
7407 }
else if (obj->InheritsFrom(
"TPaveStats")) {
7408 out<<
" "<<hname<<
"->GetListOfFunctions()->Add(ptstats);"<<std::endl;
7409 out<<
" ptstats->SetParent("<<hname<<
");"<<std::endl;
7410 }
else if (obj->InheritsFrom(
"TPolyMarker")) {
7411 out<<
" "<<hname<<
"->GetListOfFunctions()->Add("
7412 <<
"pmarker ,"<<quote<<lnk->GetOption()<<quote<<
");"<<std::endl;
7414 out<<
" "<<hname<<
"->GetListOfFunctions()->Add("
7416 <<
","<<quote<<lnk->GetOption()<<quote<<
");"<<std::endl;
7431 out<<
" "<<hname<<
"->Draw("
7432 <<quote<<
option<<quote<<
");"<<std::endl;
7475 while ((obj = next())) {
7507 if (axis<1 || (axis>3 && axis<11) || axis>13)
return 0;
7511 if (stats[0] == 0)
return 0;
7513 Int_t ax[3] = {2,4,7};
7514 return stats[ax[axis-1]]/stats[0];
7519 return ( neff > 0 ? stddev/
TMath::Sqrt(neff) : 0. );
7579 if (axis<1 || (axis>3 && axis<11) || axis>13)
return 0;
7584 if (stats[0] == 0)
return 0;
7585 Int_t ax[3] = {2,4,7};
7586 Int_t axm = ax[axis%10 - 1];
7587 x = stats[axm]/stats[0];
7589 stddev2 =
TMath::Max( stats[axm+1]/stats[0] -
x*
x, 0.0 );
7596 return ( neff > 0 ?
TMath::Sqrt(stddev2/(2*neff) ) : 0. );
7644 if (axis > 0 && axis <= 3){
7648 Double_t stddev3 = stddev*stddev*stddev;
7659 if (firstBinX == 1) firstBinX = 0;
7663 if (firstBinY == 1) firstBinY = 0;
7667 if (firstBinZ == 1) firstBinZ = 0;
7675 for (
Int_t binx = firstBinX; binx <= lastBinX; binx++) {
7676 for (
Int_t biny = firstBinY; biny <= lastBinY; biny++) {
7677 for (
Int_t binz = firstBinZ; binz <= lastBinZ; binz++) {
7683 sum+=
w*(
x-mean)*(
x-mean)*(
x-mean);
7690 else if (axis > 10 && axis <= 13) {
7697 Error(
"GetSkewness",
"illegal value of parameter");
7716 if (axis > 0 && axis <= 3){
7720 Double_t stddev4 = stddev*stddev*stddev*stddev;
7731 if (firstBinX == 1) firstBinX = 0;
7735 if (firstBinY == 1) firstBinY = 0;
7739 if (firstBinZ == 1) firstBinZ = 0;
7747 for (
Int_t binx = firstBinX; binx <= lastBinX; binx++) {
7748 for (
Int_t biny = firstBinY; biny <= lastBinY; biny++) {
7749 for (
Int_t binz = firstBinZ; binz <= lastBinZ; binz++) {
7755 sum+=
w*(
x-mean)*(
x-mean)*(
x-mean)*(
x-mean);
7762 }
else if (axis > 10 && axis <= 13) {
7766 return ( neff > 0 ?
TMath::Sqrt(24./neff ) : 0. );
7769 Error(
"GetKurtosis",
"illegal value of parameter");
7816 for (bin=0;bin<4;bin++) stats[bin] = 0;
7822 if (firstBinX == 1) firstBinX = 0;
7825 for (binx = firstBinX; binx <= lastBinX; binx++) {
7832 stats[1] += err*err;
7891 Int_t bin,binx,biny,binz;
7896 bin =
GetBin(binx,biny,binz);
7953 if (binx1 < 0) binx1 = 0;
7954 if (binx2 >= nx || binx2 < binx1) binx2 = nx - 1;
7958 if (biny1 < 0) biny1 = 0;
7959 if (biny2 >= ny || biny2 < biny1) biny2 = ny - 1;
7961 biny1 = 0; biny2 = 0;
7966 if (binz1 < 0) binz1 = 0;
7967 if (binz2 >= nz || binz2 < binz1) binz2 = nz - 1;
7969 binz1 = 0; binz2 = 0;
7982 for (
Int_t binx = binx1; binx <= binx2; ++binx) {
7984 for (
Int_t biny = biny1; biny <= biny2; ++biny) {
7986 for (
Int_t binz = binz1; binz <= binz2; ++binz) {
8040 printf(
" AndersonDarlingTest Prob = %g, AD TestStatistic = %g\n",pvalue,advalue);
8042 if (opt.
Contains(
"T") )
return advalue;
8053 Error(
"AndersonDarlingTest",
"Histograms must be 1-D");
8155 if (h2 ==
nullptr)
return 0;
8157 const TAxis *axis2 = h2->GetXaxis();
8163 Error(
"KolmogorovTest",
"Histograms must be 1-D\n");
8169 Error(
"KolmogorovTest",
"Histograms have different number of bins, %d and %d\n",ncx1,ncx2);
8179 Error(
"KolmogorovTest",
"Histograms are not consistent: they have different bin edges");
8193 if (opt.
Contains(
"O")) ilast = ncx1 +1;
8194 for (bin = ifirst; bin <= ilast; bin++) {
8196 sum2 += h2->RetrieveBinContent(bin);
8198 ew2 = h2->GetBinError(bin);
8203 Error(
"KolmogorovTest",
"Histogram1 %s integral is zero\n",
h1->
GetName());
8207 Error(
"KolmogorovTest",
"Histogram2 %s integral is zero\n",h2->GetName());
8216 esum1 = sum1 * sum1 / w1;
8221 esum2 = sum2 * sum2 / w2;
8225 if (afunc2 && afunc1) {
8226 Error(
"KolmogorovTest",
"Errors are zero for both histograms\n");
8235 Double_t dfmax =0, rsum1 = 0, rsum2 = 0;
8237 for (bin=ifirst;bin<=ilast;bin++) {
8239 rsum2 += s2*h2->RetrieveBinContent(bin);
8244 Double_t z, prb1=0, prb2=0, prb3=0;
8259 if (opt.
Contains(
"N") && !(afunc1 || afunc2 ) ) {
8263 Double_t chi2 = d12*d12/(esum1+esum2);
8266 if (prob > 0 && prb2 > 0) prob *= prb2*(1-
TMath::Log(prob*prb2));
8280 int numpos = opt.
Index(
"X=") + 2;
8283 while( (numpos+numlen<
len) && isdigit(opt[numpos+numlen]) )
8285 TString snum = opt(numpos,numlen);
8286 int num = atoi(snum.
Data());
8288 Warning(
"KolmogorovTest",
"invalid number of toys given: %d - use 1000",num);
8296 if (afunc1 || esum1 > esum2 )
h1->
Copy(hparent);
8297 else h2->Copy(hparent);
8305 Warning(
"KolmogorovTest",
"Detected bins with negative weights, these have been ignored and output might be "
8306 "skewed. Reduce number of bins for histogram?");
8322 for (
Int_t i=0; i < nEXPT; i++) {
8339 if (dSEXPT>dfmax) prb3 += 1.0;
8348 printf(
" Kolmo Prob h1 = %s, sum bin content =%g effective entries =%g\n",
h1->
GetName(),sum1,esum1);
8349 printf(
" Kolmo Prob h2 = %s, sum bin content =%g effective entries =%g\n",h2->GetName(),sum2,esum2);
8350 printf(
" Kolmo Prob = %g, Max Dist = %g\n",prob,dfmax);
8352 printf(
" Kolmo Prob = %f for shape alone, =%f for normalisation alone\n",prb1,prb2);
8354 printf(
" Kolmo Prob = %f with %d pseudo-experiments\n",prb3,nEXPT);
8358 if (
TMath::Abs(rsum2-1) > 0.002)
Warning(
"KolmogorovTest",
"Numerical problems with h2=%s\n",h2->GetName());
8360 if(opt.
Contains(
"M"))
return dfmax;
8361 else if(opt.
Contains(
"X"))
return prb3;
8412 if (level <0 || level >=
fContour.
fN)
return 0;
8419 if (zlevel <= 0)
return 0;
8435 if (buffersize <= 0) {
8439 if (buffersize < 100) buffersize = 100;
8466 for (level=0; level<nlevels; level++)
fContour.
fArray[level] = levels[level];
8471 if ((zmin == zmax) && (zmin != 0)) {
8477 if (zmax <= 0)
return;
8478 if (zmin <= 0) zmin = 0.001*zmax;
8481 dz = (zmax-zmin)/
Double_t(nlevels);
8483 for (level=0; level<nlevels; level++) {
8494 if (level < 0 || level >=
fContour.
fN)
return;
8522 Int_t bin, binx, biny, binz;
8530 for (binz=zfirst;binz<=zlast;binz++) {
8531 for (biny=yfirst;biny<=ylast;biny++) {
8532 for (binx=xfirst;binx<=xlast;binx++) {
8533 bin =
GetBin(binx,biny,binz);
8549 Int_t locmax, locmay, locmaz;
8561 Int_t bin, binx, biny, binz;
8570 locm = locmax = locmay = locmaz = 0;
8571 for (binz=zfirst;binz<=zlast;binz++) {
8572 for (biny=yfirst;biny<=ylast;biny++) {
8573 for (binx=xfirst;binx<=xlast;binx++) {
8574 bin =
GetBin(binx,biny,binz);
8576 if (
value > maximum) {
8612 Int_t bin, binx, biny, binz;
8620 for (binz=zfirst;binz<=zlast;binz++) {
8621 for (biny=yfirst;biny<=ylast;biny++) {
8622 for (binx=xfirst;binx<=xlast;binx++) {
8623 bin =
GetBin(binx,biny,binz);
8625 if (value < minimum && value > minval) minimum =
value;
8637 Int_t locmix, locmiy, locmiz;
8649 Int_t bin, binx, biny, binz;
8658 locm = locmix = locmiy = locmiz = 0;
8659 for (binz=zfirst;binz<=zlast;binz++) {
8660 for (biny=yfirst;biny<=ylast;biny++) {
8661 for (binx=xfirst;binx<=xlast;binx++) {
8662 bin =
GetBin(binx,biny,binz);
8664 if (
value < minimum) {
8706 Int_t bin, binx, biny, binz;
8716 for (binz=zfirst;binz<=zlast;binz++) {
8717 for (biny=yfirst;biny<=ylast;biny++) {
8718 for (binx=xfirst;binx<=xlast;binx++) {
8719 bin =
GetBin(binx,biny,binz);
8740 Error(
"SetBins",
"Operation only valid for 1-d histograms");
8767 Error(
"SetBins",
"Operation only valid for 1-d histograms");
8793 Error(
"SetBins",
"Operation only valid for 2-D histograms");
8821 Error(
"SetBins",
"Operation only valid for 2-D histograms");
8848 Error(
"SetBins",
"Operation only valid for 3-D histograms");
8857 fNcells = (nx+2)*(ny+2)*(nz+2);
8878 Error(
"SetBins",
"Operation only valid for 3-D histograms");
8887 fNcells = (nx+2)*(ny+2)*(nz+2);
9000 Warning(
"Sumw2",
"Sum of squares of weights structure already created");
9035 if (bin < 0) bin = 0;
9055 if (bin < 0) bin = 0;
9065 Warning(
"GetBinErrorLow",
"Histogram has negative bin content-force usage to normal errors");
9070 if (
n == 0)
return 0;
9085 if (bin < 0) bin = 0;
9095 Warning(
"GetBinErrorUp",
"Histogram has negative bin content-force usage to normal errors");
9114 Error(
"GetBinCenter",
"Invalid method for a %d-d histogram - return a NaN",
fDimension);
9125 Error(
"GetBinLowEdge",
"Invalid method for a %d-d histogram - return a NaN",
fDimension);
9136 Error(
"GetBinWidth",
"Invalid method for a %d-d histogram - return a NaN",
fDimension);
9163 Error(
"GetLowEdge",
"Invalid method for a %d-d histogram ",
fDimension);
9178 if (bin < 0 || bin>=
fNcells)
return;
9196 if (bin < 0)
return;
9260 (
size_t)
this, niter,
option).Data());
9291 if (!fft || !fft->
GetN() ) {
9292 ::Error(
"TransformHisto",
"Invalid FFT transform class");
9297 ::Error(
"TransformHisto",
"Only 1d and 2D transform are supported");
9319 if (
type.Contains(
"2C") ||
type.Contains(
"2HC")) {
9321 for (binx = 1; binx<=hout->
GetNbinsX(); binx++) {
9322 for (biny=1; biny<=hout->
GetNbinsY(); biny++) {
9323 ind[0] = binx-1; ind[1] = biny-1;
9329 for (binx = 1; binx<=hout->
GetNbinsX(); binx++) {
9330 for (biny=1; biny<=hout->
GetNbinsY(); biny++) {
9331 ind[0] = binx-1; ind[1] = biny-1;
9338 if (
type.Contains(
"2C") ||
type.Contains(
"2HC")) {
9340 for (binx = 1; binx<=hout->
GetNbinsX(); binx++) {
9341 for (biny=1; biny<=hout->
GetNbinsY(); biny++) {
9342 ind[0] = binx-1; ind[1] = biny-1;
9348 ::Error(
"TransformHisto",
"No complex numbers in the output");
9353 if (
type.Contains(
"2C") ||
type.Contains(
"2HC")) {
9355 for (binx = 1; binx<=hout->
GetNbinsX(); binx++) {
9356 for (biny=1; biny<=hout->
GetNbinsY(); biny++) {
9357 ind[0] = binx-1; ind[1] = biny-1;
9363 for (binx = 1; binx<=hout->
GetNbinsX(); binx++) {
9364 for (biny=1; biny<=hout->
GetNbinsY(); biny++) {
9365 ind[0] = binx-1; ind[1] = biny-1;
9372 if (
type.Contains(
"2C") ||
type.Contains(
"2HC")){
9374 for (binx = 1; binx<=hout->
GetNbinsX(); binx++){
9375 for (biny=1; biny<=hout->
GetNbinsY(); biny++){
9376 ind[0] = binx-1; ind[1] = biny-1;
9397 printf(
"Pure real output, no phase");
9427std::string cling::printValue(
TH1 *val) {
9428 std::ostringstream strm;
9429 strm << cling::printValue((
TObject*)val) <<
" NbinsX: " << val->
GetNbinsX();
9455:
TH1(
name,title,nbins,xlow,xup)
9501 h1c.TH1C::Copy(*
this);
9521 if (newval > -128 && newval < 128) {
fArray[bin] =
Char_t(newval);
return;}
9522 if (newval < -127)
fArray[bin] = -127;
9523 if (newval > 127)
fArray[bin] = 127;
9560 h1.TH1C::Copy(*
this);
9641:
TH1(
name,title,nbins,xlow,xup)
9687 h1s.TH1S::Copy(*
this);
9707 if (newval > -32768 && newval < 32768) {
fArray[bin] =
Short_t(newval);
return;}
9708 if (newval < -32767)
fArray[bin] = -32767;
9709 if (newval > 32767)
fArray[bin] = 32767;
9746 h1.TH1S::Copy(*
this);
9828:
TH1(
name,title,nbins,xlow,xup)
9874 h1i.TH1I::Copy(*
this);
9894 if (newval > -INT_MAX && newval < INT_MAX) {
fArray[bin] =
Int_t(newval);
return;}
9895 if (newval < -INT_MAX)
fArray[bin] = -INT_MAX;
9896 if (newval > INT_MAX)
fArray[bin] = INT_MAX;
9933 h1.TH1I::Copy(*
this);
10016:
TH1(
name,title,nbins,xlow,xup)
10062 h1l.TH1L::Copy(*
this);
10082 if (newval > -LLONG_MAX && newval < LLONG_MAX) {
fArray[bin] = newval;
return;}
10083 if (newval < -LLONG_MAX)
fArray[bin] = -LLONG_MAX;
10084 if (newval > LLONG_MAX)
fArray[bin] = LLONG_MAX;
10121 h1.TH1L::Copy(*
this);
10203:
TH1(
name,title,nbins,xlow,xup)
10241:
TH1(
"TVectorF",
"",
v.GetNrows(),0,
v.GetNrows())
10245 Int_t ivlow =
v.GetLwb();
10259 h1f.TH1F::Copy(*
this);
10303 h1f.TH1F::Copy(*
this);
10384:
TH1(
name,title,nbins,xlow,xup)
10422:
TH1(
"TVectorD",
"",
v.GetNrows(),0,
v.GetNrows())
10426 Int_t ivlow =
v.GetLwb();
10552 if(hid >= 0) hname.
Form(
"h%d",hid);
10553 else hname.
Form(
"h_%d",hid);
Option_t Option_t SetLineWidth
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char filename
Option_t Option_t SetFillStyle
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t del
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t np
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t index
Option_t Option_t SetLineColor
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void value
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h Atom_t Int_t ULong_t ULong_t unsigned char prop_list Atom_t Atom_t Atom_t Time_t UChar_t len
Option_t Option_t TPoint TPoint const char x1
Option_t Option_t TPoint TPoint const char y2
Option_t Option_t SetFillColor
Option_t Option_t SetMarkerStyle
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h Atom_t Int_t ULong_t ULong_t unsigned char prop_list Atom_t Atom_t Atom_t Time_t type
Option_t Option_t TPoint TPoint const char y1
static bool IsEquidistantBinning(const TAxis &axis)
Test if the binning is equidistant.
void H1LeastSquareLinearFit(Int_t ndata, Double_t &a0, Double_t &a1, Int_t &ifail)
Least square linear fit without weights.
void H1InitGaus()
Compute Initial values of parameters for a gaussian.
void H1InitExpo()
Compute Initial values of parameters for an exponential.
TH1C operator+(const TH1C &h1, const TH1C &h2)
Operator +.
TH1C operator-(const TH1C &h1, const TH1C &h2)
Operator -.
TH1C operator/(const TH1C &h1, const TH1C &h2)
Operator /.
void H1LeastSquareSeqnd(Int_t n, Double_t *a, Int_t idim, Int_t &ifail, Int_t k, Double_t *b)
Extracted from CERN Program library routine DSEQN.
static Bool_t AlmostEqual(Double_t a, Double_t b, Double_t epsilon=0.00000001)
Test if two double are almost equal.
static Bool_t AlmostInteger(Double_t a, Double_t epsilon=0.00000001)
Test if a double is almost an integer.
TH1 * R__H(Int_t hid)
return pointer to histogram with name hid if id >=0 h_id if id <0
TH1C operator*(Double_t c1, const TH1C &h1)
Operator *.
void H1LeastSquareFit(Int_t n, Int_t m, Double_t *a)
Least squares lpolynomial fitting without weights.
void H1InitPolynom()
Compute Initial values of parameters for a polynom.
R__EXTERN TVirtualMutex * gROOTMutex
R__EXTERN TRandom * gRandom
void Printf(const char *fmt,...)
Formats a string in a circular formatting buffer and prints the string.
R__EXTERN TStyle * gStyle
#define R__LOCKGUARD(mutex)
#define R__WRITE_LOCKGUARD(mutex)
Class describing the binned data sets : vectors of x coordinates, y values and optionally error on y ...
class describing the range in the coordinates it supports multiple range in a coordinate.
void AndersonDarling2SamplesTest(Double_t &pvalue, Double_t &testStat) const
Performs the Anderson-Darling 2-Sample Test.
Array of chars or bytes (8 bits per element).
void Set(Int_t n) override
Set size of this array to n chars.
Array of doubles (64 bits per element).
Double_t GetAt(Int_t i) const override
void Streamer(TBuffer &) override
Stream a TArrayD object.
void Copy(TArrayD &array) const
void Set(Int_t n) override
Set size of this array to n doubles.
const Double_t * GetArray() const
Array of floats (32 bits per element).
void Set(Int_t n) override
Set size of this array to n floats.
Array of integers (32 bits per element).
void Set(Int_t n) override
Set size of this array to n ints.
Array of long64s (64 bits per element).
void Set(Int_t n) override
Set size of this array to n long64s.
Array of shorts (16 bits per element).
void Set(Int_t n) override
Set size of this array to n shorts.
Abstract array base class.
virtual void Set(Int_t n)=0
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 void ResetAttAxis(Option_t *option="")
Reset axis attributes.
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.
Fill Area Attributes class.
virtual void Streamer(TBuffer &)
virtual Color_t GetFillColor() const
Return the fill area color.
void Copy(TAttFill &attfill) const
Copy this fill attributes to a new TAttFill.
virtual Style_t GetFillStyle() const
Return the fill area style.
virtual void SaveFillAttributes(std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1001)
Save fill attributes as C++ statement(s) on output stream out.
virtual void Streamer(TBuffer &)
virtual Color_t GetLineColor() const
Return the line color.
virtual void SetLineStyle(Style_t lstyle)
Set the line style.
virtual Width_t GetLineWidth() const
Return the line width.
virtual Style_t GetLineStyle() const
Return the line style.
void Copy(TAttLine &attline) const
Copy this line attributes to a new TAttLine.
virtual void SaveLineAttributes(std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1, Int_t widdef=1)
Save line attributes as C++ statement(s) on output stream out.
virtual void SaveMarkerAttributes(std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1, Int_t sizdef=1)
Save line attributes as C++ statement(s) on output stream out.
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 Size_t GetMarkerSize() const
Return the marker size.
virtual void SetMarkerStyle(Style_t mstyle=1)
Set the marker style.
void Copy(TAttMarker &attmarker) const
Copy this marker attributes to a new TAttMarker.
virtual void Streamer(TBuffer &)
virtual void SetMarkerSize(Size_t msize=1)
Set the marker size.
Class to manage histogram axis.
virtual void GetCenter(Double_t *center) const
Return an array with the center of all bins.
virtual Bool_t GetTimeDisplay() const
Bool_t IsAlphanumeric() const
const char * GetTitle() const override
Returns title of object.
virtual Double_t GetBinCenter(Int_t bin) const
Return center of bin.
virtual void SetParent(TObject *obj)
const TArrayD * GetXbins() const
void SetCanExtend(Bool_t canExtend)
void Copy(TObject &axis) const override
Copy axis structure to another axis.
const char * GetBinLabel(Int_t bin) const
Return label for bin.
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 SetTimeDisplay(Int_t value)
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.
void SaveAttributes(std::ostream &out, const char *name, const char *subname) override
Save axis attributes as C++ statement(s) on output stream out.
Int_t GetLast() const
Return last bin on the axis i.e.
virtual void SetLimits(Double_t xmin, Double_t xmax)
void Streamer(TBuffer &) override
Stream an object of class TAxis.
virtual void GetLowEdge(Double_t *edge) const
Return an array with the low edge of all bins.
virtual void SetRange(Int_t first=0, Int_t last=0)
Set the viewing range for the axis using bin numbers.
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
Using a TBrowser one can browse all ROOT objects.
Buffer base class used for serializing objects.
void * New(ENewType defConstructor=kClassNew, Bool_t quiet=kFALSE) const
Return a pointer to a newly allocated object of this class.
ROOT::NewFunc_t GetNew() const
Return the wrapper around new ThisClass().
Collection abstract base class.
virtual bool UseRWLock(Bool_t enable=true)
Set this collection to use a RW lock upon access, making it thread safe.
virtual void AddAll(const TCollection *col)
Add all objects from collection col to this collection.
virtual Bool_t IsEmpty() const
TObject * Clone(const char *newname="") const override
Make a clone of an collection using the Streamer facility.
virtual Int_t GetSize() const
Return the capacity of the collection, i.e.
Describe directory structure in memory.
virtual void Append(TObject *obj, Bool_t replace=kFALSE)
Append object to this directory.
virtual TObject * Remove(TObject *)
Remove an object from the in-memory list.
virtual Int_t GetValue(const char *name, Int_t dflt) const
Returns the integer value for a resource.
static void RejectPoint(Bool_t reject=kTRUE)
Static function to set the global flag to reject points the fgRejectPoint global flag is tested by al...
virtual TH1 * GetHistogram() const
Return a pointer to the histogram used to visualise the function Note that this histogram is managed ...
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 void InitArgs(const Double_t *x, const Double_t *params)
Initialize parameters addresses.
virtual void GetRange(Double_t *xmin, Double_t *xmax) const
Return range of a generic N-D function.
virtual Double_t EvalPar(const Double_t *x, const Double_t *params=nullptr)
Evaluate function with given coordinates and parameters.
virtual void SetParLimits(Int_t ipar, Double_t parmin, Double_t parmax)
Set lower and upper limits for parameter ipar.
static Bool_t RejectedPoint()
See TF1::RejectPoint above.
virtual Double_t Eval(Double_t x, Double_t y=0, Double_t z=0, Double_t t=0) const
Evaluate this function.
virtual void SetParameter(Int_t param, Double_t value)
virtual Bool_t IsInside(const Double_t *x) const
return kTRUE if the point is inside the function range
A 2-Dim function with parameters.
A 3-Dim function with parameters.
Provides an indirection to the TFitResult class and with a semantics identical to a TFitResult pointe...
1-D histogram with a byte per channel (see TH1 documentation)
~TH1C() override
Destructor.
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
TH1C & operator=(const TH1C &h1)
Operator =.
void Copy(TObject &hnew) const override
Copy this to newth1.
void AddBinContent(Int_t bin) override
Increment bin content by 1.
void Reset(Option_t *option="") override
Reset.
1-D histogram with a double per channel (see TH1 documentation)
~TH1D() override
Destructor.
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
void Copy(TObject &hnew) const override
Copy this to newth1.
TH1D & operator=(const TH1D &h1)
Operator =.
void Reset(Option_t *option="") override
Reset.
1-D histogram with a float per channel (see TH1 documentation)
Double_t RetrieveBinContent(Int_t bin) const override
Raw retrieval of bin content on internal data structure see convention for numbering bins in TH1::Get...
TH1F & operator=(const TH1F &h1)
Operator =.
void Copy(TObject &hnew) const override
Copy this to newth1.
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
~TH1F() override
Destructor.
1-D histogram with an int per channel (see TH1 documentation)
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
void AddBinContent(Int_t bin) override
Increment bin content by 1.
~TH1I() override
Destructor.
void Copy(TObject &hnew) const override
Copy this to newth1.
TH1I & operator=(const TH1I &h1)
Operator =.
1-D histogram with a long64 per channel (see TH1 documentation)
TH1L & operator=(const TH1L &h1)
Operator =.
void AddBinContent(Int_t bin) override
Increment bin content by 1.
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
~TH1L() override
Destructor.
void Copy(TObject &hnew) const override
Copy this to newth1.
1-D histogram with a short per channel (see TH1 documentation)
TH1S & operator=(const TH1S &h1)
Operator =.
void Copy(TObject &hnew) const override
Copy this to newth1.
void SetBinsLength(Int_t n=-1) override
Set total number of bins including under/overflow Reallocate bin contents array.
~TH1S() override
Destructor.
void AddBinContent(Int_t bin) override
Increment bin content by 1.
TH1 is the base class of all histogram classes in ROOT.
~TH1() override
Histogram default destructor.
virtual void SetError(const Double_t *error)
Replace bin errors by values in array error.
virtual void SetDirectory(TDirectory *dir)
By default, when a histogram is created, it is added to the list of histogram objects in the current ...
virtual void FitPanel()
Display a panel with all histogram fit options.
Double_t * fBuffer
[fBufferSize] entry buffer
virtual Int_t AutoP2FindLimits(Double_t min, Double_t max)
Buffer-based estimate of the histogram range using the power of 2 algorithm.
virtual Double_t GetEffectiveEntries() const
Number of effective entries of the histogram.
char * GetObjectInfo(Int_t px, Int_t py) const override
Redefines TObject::GetObjectInfo.
virtual void Smooth(Int_t ntimes=1, Option_t *option="")
Smooth bin contents of this histogram.
virtual Double_t GetBinCenter(Int_t bin) const
Return bin center for 1D histogram.
virtual void Rebuild(Option_t *option="")
Using the current bin info, recompute the arrays for contents and errors.
virtual void SetBarOffset(Float_t offset=0.25)
Set the bar offset as fraction of the bin width for drawing mode "B".
static Bool_t fgStatOverflows
! Flag to use under/overflows in statistics
virtual Int_t FindLastBinAbove(Double_t threshold=0, Int_t axis=1, Int_t firstBin=1, Int_t lastBin=-1) const
Find last bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold i...
Int_t DistancetoPrimitive(Int_t px, Int_t py) override
Compute distance from point px,py to a line.
virtual Bool_t Multiply(TF1 *f1, Double_t c1=1)
Performs the operation:
@ kNoAxis
NOTE: Must always be 0 !!!
Int_t fNcells
Number of bins(1D), cells (2D) +U/Overflows.
virtual void GetStats(Double_t *stats) const
fill the array stats from the contents of this histogram The array stats must be correctly dimensione...
void Copy(TObject &hnew) const override
Copy this histogram structure to newth1.
void SetTitle(const char *title) override
Change/set the title.
Double_t fTsumw
Total Sum of weights.
virtual Float_t GetBarWidth() const
Double_t fTsumw2
Total Sum of squares of weights.
static void StatOverflows(Bool_t flag=kTRUE)
if flag=kTRUE, underflows and overflows are used by the Fill functions in the computation of statisti...
virtual Float_t GetBarOffset() const
TList * fFunctions
->Pointer to list of functions (fits and user)
static Bool_t fgAddDirectory
! Flag to add histograms to the directory
static int CheckConsistency(const TH1 *h1, const TH1 *h2)
Check histogram compatibility.
static Int_t GetDefaultBufferSize()
Static function return the default buffer size for automatic histograms the parameter fgBufferSize ma...
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).
TH1()
Histogram default constructor.
static TH1 * TransformHisto(TVirtualFFT *fft, TH1 *h_output, Option_t *option)
For a given transform (first parameter), fills the histogram (second parameter) with the transform ou...
void UseCurrentStyle() override
Copy current attributes from/to current style.
virtual void LabelsOption(Option_t *option="h", Option_t *axis="X")
Sort bins with labels or set option(s) to draw axis with labels.
virtual Int_t GetNbinsY() const
Short_t fBarOffset
(1000*offset) for bar charts or legos
virtual Double_t Chi2TestX(const TH1 *h2, Double_t &chi2, Int_t &ndf, Int_t &igood, Option_t *option="UU", Double_t *res=nullptr) const
The computation routine of the Chisquare test.
static bool CheckBinLimits(const TAxis *a1, const TAxis *a2)
Check bin limits.
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.
static Int_t FitOptionsMake(Option_t *option, Foption_t &Foption)
Decode string choptin and fill fitOption structure.
virtual Int_t GetNbinsZ() const
virtual Double_t GetNormFactor() const
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 Double_t GetSkewness(Int_t axis=1) const
virtual void ClearUnderflowAndOverflow()
Remove all the content from the underflow and overflow bins, without changing the number of entries A...
virtual Double_t GetContourLevelPad(Int_t level) const
Return the value of contour number "level" in Pad coordinates.
virtual TH1 * DrawNormalized(Option_t *option="", Double_t norm=1) const
Draw a normalized copy of this histogram.
@ kNeutral
Adapt to the global flag.
virtual Int_t GetDimension() const
void Streamer(TBuffer &) override
Stream a class object.
static void AddDirectory(Bool_t add=kTRUE)
Sets the flag controlling the automatic add of histograms in memory.
@ kIsAverage
Bin contents are average (used by Add)
@ kUserContour
User specified contour levels.
@ kNoStats
Don't draw stats box.
@ kAutoBinPTwo
different than 1.
@ kIsNotW
Histogram is forced to be not weighted even when the histogram is filled with weighted.
@ kIsHighlight
bit set if histo is highlight
virtual void SetContourLevel(Int_t level, Double_t value)
Set value for one contour level.
virtual Bool_t CanExtendAllAxes() const
Returns true if all axes are extendable.
TDirectory * fDirectory
! Pointer to directory holding this histogram
virtual void Reset(Option_t *option="")
Reset this histogram: contents, errors, etc.
void SetNameTitle(const char *name, const char *title) override
Change the name and title of this histogram.
virtual void GetBinXYZ(Int_t binglobal, Int_t &binx, Int_t &biny, Int_t &binz) const
Return binx, biny, binz corresponding to the global bin number globalbin see TH1::GetBin function abo...
TH1 * GetCumulative(Bool_t forward=kTRUE, const char *suffix="_cumulative") const
Return a pointer to a histogram containing the cumulative content.
static Double_t AutoP2GetPower2(Double_t x, Bool_t next=kTRUE)
Auxiliary function to get the power of 2 next (larger) or previous (smaller) a given x.
virtual Int_t GetNcells() const
virtual Int_t ShowPeaks(Double_t sigma=2, Option_t *option="", Double_t threshold=0.05)
Interface to TSpectrum::Search.
static Bool_t RecomputeAxisLimits(TAxis &destAxis, const TAxis &anAxis)
Finds new limits for the axis for the Merge function.
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 * FindObject(const char *name) const override
Search object named name in the list of functions.
virtual void FillRandom(const char *fname, Int_t ntimes=5000, TRandom *rng=nullptr)
Fill histogram following distribution in function fname.
void Print(Option_t *option="") const override
Print some global quantities for this histogram.
static Bool_t GetDefaultSumw2()
Return kTRUE if TH1::Sumw2 must be called when creating new histograms.
virtual Int_t FindFirstBinAbove(Double_t threshold=0, Int_t axis=1, Int_t firstBin=1, Int_t lastBin=-1) const
Find first bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold ...
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 Double_t GetMaximum(Double_t maxval=FLT_MAX) const
Return maximum value smaller than maxval of bins in the range, unless the value has been overridden b...
virtual Int_t GetNbinsX() const
virtual void SetMaximum(Double_t maximum=-1111)
virtual TH1 * FFT(TH1 *h_output, Option_t *option)
This function allows to do discrete Fourier transforms of TH1 and TH2.
virtual void LabelsInflate(Option_t *axis="X")
Double the number of bins for axis.
virtual TH1 * ShowBackground(Int_t niter=20, Option_t *option="same")
This function calculates the background spectrum in this histogram.
static Bool_t SameLimitsAndNBins(const TAxis &axis1, const TAxis &axis2)
Same limits and bins.
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),...
Double_t fMaximum
Maximum value for plotting.
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...
virtual Double_t IntegralAndError(Int_t binx1, Int_t binx2, Double_t &err, Option_t *option="") const
Return integral of bin contents in range [binx1,binx2] and its error.
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...
EBinErrorOpt fBinStatErrOpt
Option for bin statistical errors.
static Int_t fgBufferSize
! Default buffer size for automatic histograms
virtual void SetBinsLength(Int_t=-1)
Double_t fNormFactor
Normalization factor.
virtual Int_t Fill(Double_t x)
Increment bin with abscissa X by 1.
TArrayD fContour
Array to display contour levels.
virtual Double_t GetBinErrorLow(Int_t bin) const
Return lower error associated to bin number bin.
void Browse(TBrowser *b) override
Browse the Histogram object.
virtual void SetContent(const Double_t *content)
Replace bin contents by the contents of array content.
void Draw(Option_t *option="") override
Draw this histogram with options.
virtual void SavePrimitiveHelp(std::ostream &out, const char *hname, Option_t *option="")
Helper function for the SavePrimitive functions from TH1 or classes derived from TH1,...
Short_t fBarWidth
(1000*width) for bar charts or legos
virtual Double_t GetBinErrorSqUnchecked(Int_t bin) const
Int_t AxisChoice(Option_t *axis) const
Choose an axis according to "axis".
virtual void SetMinimum(Double_t minimum=-1111)
Bool_t IsBinUnderflow(Int_t bin, Int_t axis=0) const
Return true if the bin is underflow.
void SavePrimitive(std::ostream &out, Option_t *option="") override
Save primitive as a C++ statement(s) on output stream out.
static bool CheckBinLabels(const TAxis *a1, const TAxis *a2)
Check that axis have same labels.
virtual Double_t Interpolate(Double_t x) const
Given a point x, approximates the value via linear interpolation based on the two nearest bin centers...
static void SetDefaultSumw2(Bool_t sumw2=kTRUE)
When this static function is called with sumw2=kTRUE, all new histograms will automatically activate ...
Bool_t IsBinOverflow(Int_t bin, Int_t axis=0) const
Return true if the bin is overflow.
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
Double_t fMinimum
Minimum value for plotting.
virtual Double_t Integral(Option_t *option="") const
Return integral of bin contents.
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 void DirectoryAutoAdd(TDirectory *)
Perform the automatic addition of the histogram to the given directory.
virtual void GetLowEdge(Double_t *edge) const
Fill array with low edge of bins for 1D histogram Better to use h1.GetXaxis()->GetLowEdge(edge)
virtual Double_t GetBinLowEdge(Int_t bin) const
Return bin lower edge for 1D histogram.
void Build()
Creates histogram basic data structure.
virtual Double_t GetEntries() const
Return the current number of entries.
virtual TF1 * GetFunction(const char *name) const
Return pointer to function with name.
virtual TH1 * Rebin(Int_t ngroup=2, const char *newname="", const Double_t *xbins=nullptr)
Rebin this histogram.
virtual Int_t BufferFill(Double_t x, Double_t w)
accumulate arguments in buffer.
virtual Double_t GetBinWithContent(Double_t c, Int_t &binx, Int_t firstx=0, Int_t lastx=0, Double_t maxdiff=0) const
Compute first binx in the range [firstx,lastx] for which diff = abs(bin_content-c) <= maxdiff.
virtual UInt_t SetCanExtend(UInt_t extendBitMask)
Make the histogram axes extendable / not extendable according to the bit mask returns the previous bi...
TList * GetListOfFunctions() const
void SetName(const char *name) override
Change the name of this histogram.
virtual TH1 * DrawCopy(Option_t *option="", const char *name_postfix="_copy") const
Copy this histogram and Draw in the current pad.
Bool_t IsEmpty() const
Check if a histogram is empty (this is a protected method used mainly by TH1Merger )
virtual Double_t GetMeanError(Int_t axis=1) const
Return standard error of mean of this histogram along the X axis.
void Paint(Option_t *option="") override
Control routine to paint any kind of histograms.
virtual Double_t AndersonDarlingTest(const TH1 *h2, Option_t *option="") const
Statistical test of compatibility in shape between this histogram and h2, using the Anderson-Darling ...
virtual void ResetStats()
Reset the statistics including the number of entries and replace with values calculated from bin cont...
static void SetDefaultBufferSize(Int_t buffersize=1000)
Static function to set the default buffer size for automatic histograms.
virtual void SetBinErrorOption(EBinErrorOpt type)
virtual void SetBuffer(Int_t buffersize, Option_t *option="")
Set the maximum number of entries to be kept in the buffer.
virtual void DrawPanel()
Display a panel with all histogram drawing options.
virtual Double_t GetRandom(TRandom *rng=nullptr) const
Return a random number distributed according the histogram bin contents.
virtual Double_t Chisquare(TF1 *f1, Option_t *option="") const
Compute and return the chisquare of this histogram with respect to a function The chisquare is comput...
virtual Double_t Chi2Test(const TH1 *h2, Option_t *option="UU", Double_t *res=nullptr) const
test for comparing weighted and unweighted histograms.
virtual void DoFillN(Int_t ntimes, const Double_t *x, const Double_t *w, Int_t stride=1)
Internal method to fill histogram content from a vector called directly by TH1::BufferEmpty.
virtual void GetMinimumAndMaximum(Double_t &min, Double_t &max) const
Retrieve the minimum and maximum values in the histogram.
@ kNstat
Size of statistics data (up to TProfile3D)
virtual Int_t GetMaximumBin() const
Return location of bin with maximum value in the range.
static Int_t AutoP2GetBins(Int_t n)
Auxiliary function to get the next power of 2 integer value larger then n.
Double_t fEntries
Number of entries.
virtual Long64_t Merge(TCollection *list)
void ExecuteEvent(Int_t event, Int_t px, Int_t py) override
Execute action corresponding to one event.
virtual Double_t * GetIntegral()
Return a pointer to the array of bins integral.
TAxis fZaxis
Z axis descriptor.
EStatOverflows fStatOverflows
Per object flag to use under/overflows in statistics.
TClass * IsA() const override
virtual void FillN(Int_t ntimes, const Double_t *x, const Double_t *w, Int_t stride=1)
Fill this histogram with an array x and weights w.
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...
static bool CheckEqualAxes(const TAxis *a1, const TAxis *a2)
Check that the axis are the same.
@ kPoisson2
Errors from Poisson interval at 95% CL (~ 2 sigma)
@ kNormal
Errors with Normal (Wald) approximation: errorUp=errorLow= sqrt(N)
virtual Double_t GetBinContent(Int_t bin) const
Return content of bin number bin.
virtual Int_t GetContour(Double_t *levels=nullptr)
Return contour values into array levels if pointer levels is non zero.
TAxis fXaxis
X axis descriptor.
virtual Bool_t IsHighlight() const
virtual void ExtendAxis(Double_t x, TAxis *axis)
Histogram is resized along axis such that x is in the axis range.
virtual Double_t GetBinWidth(Int_t bin) const
Return bin width for 1D histogram.
TArrayD fSumw2
Array of sum of squares of weights.
TH1 * GetAsymmetry(TH1 *h2, Double_t c2=1, Double_t dc2=0)
Return a histogram containing the asymmetry of this histogram with h2, where the asymmetry is defined...
virtual Double_t GetContourLevel(Int_t level) const
Return value of contour number level.
virtual void SetContour(Int_t nlevels, const Double_t *levels=nullptr)
Set the number and values of contour levels.
virtual void SetHighlight(Bool_t set=kTRUE)
Set highlight (enable/disable) mode for the histogram by default highlight mode is disable.
virtual Int_t GetQuantiles(Int_t nprobSum, Double_t *q, const Double_t *probSum=nullptr)
Compute Quantiles for this histogram Quantile x_q of a probability distribution Function F is defined...
virtual Double_t GetBinErrorUp(Int_t bin) const
Return upper error associated to bin number bin.
virtual void Scale(Double_t c1=1, Option_t *option="")
Multiply this histogram by a constant c1.
virtual Int_t GetMinimumBin() const
Return location of bin with minimum value in the range.
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
void SaveAs(const char *filename="hist", Option_t *option="") const override
Save the histogram as .csv, .tsv or .txt.
TObject * Clone(const char *newname="") const override
Make a complete copy of the underlying object.
virtual Double_t GetStdDevError(Int_t axis=1) const
Return error of standard deviation estimation for Normal distribution.
virtual Bool_t Divide(TF1 *f1, Double_t c1=1)
Performs the operation: this = this/(c1*f1) if errors are defined (see TH1::Sumw2),...
virtual Double_t GetMinimum(Double_t minval=-FLT_MAX) const
Return minimum value larger than minval of bins in the range, unless the value has been overridden by...
int LoggedInconsistency(const char *name, const TH1 *h1, const TH1 *h2, bool useMerge=false) const
static bool CheckConsistentSubAxes(const TAxis *a1, Int_t firstBin1, Int_t lastBin1, const TAxis *a2, Int_t firstBin2=0, Int_t lastBin2=0)
Check that two sub axis are the same.
void RecursiveRemove(TObject *obj) override
Recursively remove object from the list of functions.
TAxis fYaxis
Y axis descriptor.
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.
virtual Double_t GetSumOfWeights() const
Return the sum of weights excluding under/overflows.
static void SmoothArray(Int_t NN, Double_t *XX, Int_t ntimes=1)
Smooth array xx, translation of Hbook routine hsmoof.F.
virtual void GetCenter(Double_t *center) const
Fill array with center of bins for 1D histogram Better to use h1.GetXaxis()->GetCenter(center)
TVirtualHistPainter * fPainter
! Pointer to histogram painter
virtual void SetBins(Int_t nx, Double_t xmin, Double_t xmax)
Redefine x axis parameters.
virtual Int_t FindFixBin(Double_t x, Double_t y=0, Double_t z=0) const
Return Global bin number corresponding to x,y,z.
virtual void Sumw2(Bool_t flag=kTRUE)
Create structure to store sum of squares of weights.
virtual void SetEntries(Double_t n)
virtual Bool_t FindNewAxisLimits(const TAxis *axis, const Double_t point, Double_t &newMin, Double_t &newMax)
finds new limits for the axis so that point is within the range and the limits are compatible with th...
static bool CheckAxisLimits(const TAxis *a1, const TAxis *a2)
Check that the axis limits of the histograms are the same.
static Bool_t AddDirectoryStatus()
Static function: cannot be inlined on Windows/NT.
static Bool_t fgDefaultSumw2
! Flag to call TH1::Sumw2 automatically at histogram creation time
Double_t fTsumwx
Total Sum of weight*X.
virtual void LabelsDeflate(Option_t *axis="X")
Reduce the number of bins for the axis passed in the option to the number of bins having a label.
virtual Double_t ComputeIntegral(Bool_t onlyPositive=false)
Compute integral (normalized cumulative sum of bins) w/o under/overflows The result is stored in fInt...
TString fOption
Histogram options.
virtual void Eval(TF1 *f1, Option_t *option="")
Evaluate function f1 at the center of bins of this histogram.
virtual void SetBarWidth(Float_t width=0.5)
Set the width of bars as fraction of the bin width for drawing mode "B".
virtual Int_t BufferEmpty(Int_t action=0)
Fill histogram with all entries in the buffer.
virtual void SetStats(Bool_t stats=kTRUE)
Set statistics option on/off.
virtual Double_t GetKurtosis(Int_t axis=1) const
2-D histogram with a double per channel (see TH1 documentation)
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...
void Clear(Option_t *option="") override
Remove all objects from the list.
void Streamer(TBuffer &) override
Stream all objects in the collection to or from the I/O buffer.
TObject * FindObject(const char *name) const override
Find an object in this list using its name.
void RecursiveRemove(TObject *obj) override
Remove object from this collection and recursively remove the object from all other objects (and coll...
void Add(TObject *obj) override
TObject * Remove(TObject *obj) override
Remove object from the list.
TObject * First() const override
Return the first object in the list. Returns 0 when list is empty.
virtual TObjLink * FirstLink() const
void Delete(Option_t *option="") override
Remove all objects from the list AND delete all heap based objects.
TObject * At(Int_t idx) const override
Returns the object at position idx. Returns 0 if idx is out of range.
The TNamed class is the base class for all named ROOT classes.
void Copy(TObject &named) const override
Copy this to obj.
virtual void SetTitle(const char *title="")
Set the title of the TNamed.
const char * GetName() const override
Returns name of object.
void Streamer(TBuffer &) override
Stream an object of class TObject.
const char * GetTitle() const override
Returns title of object.
virtual void SetName(const char *name)
Set the name of the TNamed.
Mother of all ROOT objects.
void AbstractMethod(const char *method) const
Use this method to implement an "abstract" method that you don't want to leave purely abstract.
virtual const char * GetName() const
Returns name of object.
R__ALWAYS_INLINE Bool_t TestBit(UInt_t f) const
virtual UInt_t GetUniqueID() const
Return the unique object id.
virtual const char * ClassName() const
Returns name of class to which the object belongs.
virtual void UseCurrentStyle()
Set current style settings in this object This function is called when either TCanvas::UseCurrentStyl...
virtual void Warning(const char *method, const char *msgfmt,...) const
Issue warning message.
virtual void AppendPad(Option_t *option="")
Append graphics object to current pad.
virtual void SaveAs(const char *filename="", Option_t *option="") const
Save this object in the file specified by filename.
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 SetUniqueID(UInt_t uid)
Set the unique object id.
@ kCanDelete
if object in a list can be deleted
@ kInvalidObject
if object ctor succeeded but object should not be used
@ kMustCleanup
if object destructor must call RecursiveRemove()
virtual void Info(const char *method, const char *msgfmt,...) const
Issue info message.
Longptr_t ExecPlugin(int nargs)
Int_t LoadPlugin()
Load the plugin library for this handler.
This is the base class for the ROOT Random number generators.
Double_t Rndm() override
Machine independent random number generator.
virtual Double_t PoissonD(Double_t mean)
Generates a random number according to a Poisson law.
virtual ULong64_t Poisson(Double_t mean)
Generates a random integer N according to a Poisson law.
void ToLower()
Change string to lower-case.
Bool_t EndsWith(const char *pat, ECaseCompare cmp=kExact) const
Return true if string ends with the specified string.
void Clear()
Clear string without changing its capacity.
const char * Data() const
TString & ReplaceAll(const TString &s1, const TString &s2)
void ToUpper()
Change string to upper case.
TString & Remove(Ssiz_t pos)
virtual void Streamer(TBuffer &)
Stream a string object.
TString & Append(const char *cs)
static TString Format(const char *fmt,...)
Static method which formats a string using a printf style format descriptor and return a TString.
void Form(const char *fmt,...)
Formats a string using a printf style format descriptor.
Bool_t Contains(const char *pat, ECaseCompare cmp=kExact) const
Ssiz_t Index(const char *pat, Ssiz_t i=0, ECaseCompare cmp=kExact) const
void SetOptStat(Int_t stat=1)
The type of information printed in the histogram statistics box can be selected via the parameter mod...
void SetHistFillColor(Color_t color=1)
Color_t GetHistLineColor() const
Float_t GetBarOffset() const
void SetHistLineStyle(Style_t styl=0)
Style_t GetHistFillStyle() const
Color_t GetHistFillColor() const
Float_t GetBarWidth() const
Bool_t GetCanvasPreferGL() const
void SetHistLineColor(Color_t color=1)
void SetBarOffset(Float_t baroff=0.5)
Style_t GetHistLineStyle() const
void SetBarWidth(Float_t barwidth=0.5)
void SetHistFillStyle(Style_t styl=0)
Width_t GetHistLineWidth() const
void SetHistLineWidth(Width_t width=1)
TVirtualFFT is an interface class for Fast Fourier Transforms.
static TVirtualFFT * FFT(Int_t ndim, Int_t *n, Option_t *option)
Returns a pointer to the FFT of requested size and type.
virtual Int_t GetNdim() const =0
static TVirtualFFT * SineCosine(Int_t ndim, Int_t *n, Int_t *r2rkind, Option_t *option)
Returns a pointer to a sine or cosine transform of requested size and kind.
virtual Option_t * GetType() const =0
virtual void Transform()=0
virtual void GetPointComplex(Int_t ipoint, Double_t &re, Double_t &im, Bool_t fromInput=kFALSE) const =0
virtual Int_t * GetN() const =0
virtual Double_t GetPointReal(Int_t ipoint, Bool_t fromInput=kFALSE) const =0
virtual void SetPoint(Int_t ipoint, Double_t re, Double_t im=0)=0
Abstract Base Class for Fitting.
virtual Int_t GetXlast() const
virtual TObject * GetObjectFit() const
virtual Int_t GetXfirst() const
static TVirtualFitter * GetFitter()
static: return the current Fitter
virtual TObject * GetUserFunc() const
Abstract interface to a histogram painter.
virtual void DrawPanel()=0
Int_t DistancetoPrimitive(Int_t px, Int_t py) override=0
Computes distance from point (px,py) to the object.
void ExecuteEvent(Int_t event, Int_t px, Int_t py) override=0
Execute action corresponding to an event at (px,py).
virtual void SetHighlight()=0
static TVirtualHistPainter * HistPainter(TH1 *obj)
Static function returning a pointer to the current histogram painter.
void Paint(Option_t *option="") override=0
This method must be overridden if a class wants to paint itself.
virtual void SetParent(TObject *)=0
double gamma_quantile_c(double z, double alpha, double theta)
Inverse ( ) of the cumulative distribution function of the upper tail of the gamma distribution (gamm...
double gamma_quantile(double z, double alpha, double theta)
Inverse ( ) of the cumulative distribution function of the lower tail of the gamma distribution (gamm...
R__ALWAYS_INLINE bool HasBeenDeleted(const TObject *obj)
Check if the TObject's memory has been deleted.
TFitResultPtr FitObject(TH1 *h1, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption, const char *goption, ROOT::Fit::DataRange &range)
fitting function for a TH1 (called from TH1::Fit)
double Chisquare(const TH1 &h1, TF1 &f1, bool useRange, EChisquareType type)
compute the chi2 value for an histogram given a function (see TH1::Chisquare for the documentation)
void FitOptionsMake(EFitObjectType type, const char *option, Foption_t &fitOption)
Decode list of options into fitOption.
void FillData(BinData &dv, const TH1 *hist, TF1 *func=nullptr)
fill the data vector from a TH1.
R__EXTERN TVirtualRWMutex * gCoreMutex
Int_t Nint(T x)
Round to nearest integer. Rounds half integers to the nearest even integer.
Short_t Max(Short_t a, Short_t b)
Returns the largest of a and 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 Median(Long64_t n, const T *a, const Double_t *w=nullptr, Long64_t *work=nullptr)
Same as RMS.
Double_t QuietNaN()
Returns a quiet NaN as defined by IEEE 754.
Double_t Floor(Double_t x)
Rounds x downward, returning the largest integral value that is not greater than x.
Double_t ATan(Double_t)
Returns the principal value of the arc tangent of x, expressed in radians.
Double_t Ceil(Double_t x)
Rounds x upward, returning the smallest integral value that is not less than x.
T MinElement(Long64_t n, const T *a)
Returns minimum of array a of length n.
Double_t Log(Double_t x)
Returns the natural logarithm of x.
Double_t Sqrt(Double_t x)
Returns the square root of x.
LongDouble_t Power(LongDouble_t x, LongDouble_t y)
Returns x raised to the power y.
Short_t Min(Short_t a, Short_t b)
Returns the smallest of a and b.
Bool_t AreEqualRel(Double_t af, Double_t bf, Double_t relPrec)
Comparing floating points.
Bool_t AreEqualAbs(Double_t af, Double_t bf, Double_t epsilon)
Comparing floating points.
Double_t KolmogorovProb(Double_t z)
Calculates the Kolmogorov distribution function,.
void Sort(Index n, const Element *a, Index *index, Bool_t down=kTRUE)
Sort the n elements of the array a of generic templated type Element.
Long64_t BinarySearch(Long64_t n, const T *array, T value)
Binary search in an array of n values to locate value.
Double_t Log10(Double_t x)
Returns the common (base-10) logarithm of x.
Short_t Abs(Short_t d)
Returns the absolute value of parameter Short_t d.
Double_t Infinity()
Returns an infinity as defined by the IEEE standard.
static uint64_t sum(uint64_t i)