{
"cells": [
{
"cell_type": "markdown",
"id": "cca9479b",
"metadata": {},
"source": [
"# df101_h1Analysis\n",
"Show how to express ROOT's standard H1 analysis with RDataFrame.\n",
"\n",
"\n",
"\n",
"\n",
"**Author:** Axel Naumann, Danilo Piparo (CERN) \n",
"This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Tuesday, May 19, 2026 at 08:10 PM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7c224420",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.213561Z",
"iopub.status.busy": "2026-05-19T20:10:25.213442Z",
"iopub.status.idle": "2026-05-19T20:10:25.551641Z",
"shell.execute_reply": "2026-05-19T20:10:25.551260Z"
}
},
"outputs": [],
"source": [
"%%cpp -d\n",
"\n",
"auto Select = [](ROOT::RDataFrame &dataFrame) {\n",
" using namespace ROOT;\n",
"\n",
" auto ret = dataFrame.Filter(\"TMath::Abs(md0_d - 1.8646) < 0.04\")\n",
" .Filter(\"ptds_d > 2.5\")\n",
" .Filter(\"TMath::Abs(etads_d) < 1.5\")\n",
" .Filter([](int ik, int ipi, RVecI& nhitrp) { return nhitrp[ik - 1] * nhitrp[ipi - 1] > 1; },\n",
" {\"ik\", \"ipi\", \"nhitrp\"})\n",
" .Filter([](int ik, RVecF& rstart, RVecF& rend) { return rend[ik - 1] - rstart[ik - 1] > 22; },\n",
" {\"ik\", \"rstart\", \"rend\"})\n",
" .Filter([](int ipi, RVecF& rstart, RVecF& rend) { return rend[ipi - 1] - rstart[ipi - 1] > 22; },\n",
" {\"ipi\", \"rstart\", \"rend\"})\n",
" .Filter([](int ik, RVecF& nlhk) { return nlhk[ik - 1] > 0.1; }, {\"ik\", \"nlhk\"})\n",
" .Filter([](int ipi, RVecF& nlhpi) { return nlhpi[ipi - 1] > 0.1; }, {\"ipi\", \"nlhpi\"})\n",
" .Filter([](int ipis, RVecF& nlhpi) { return nlhpi[ipis - 1] > 0.1; }, {\"ipis\", \"nlhpi\"})\n",
" .Filter(\"njets >= 1\");\n",
"\n",
" return ret;\n",
"};\n",
"\n",
"const Double_t dxbin = (0.17 - 0.13) / 40; // Bin-width"
]
},
{
"cell_type": "markdown",
"id": "5179519d",
"metadata": {},
"source": [
" Definition of a helper function: "
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "9ad63a1f",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.558273Z",
"iopub.status.busy": "2026-05-19T20:10:25.558137Z",
"iopub.status.idle": "2026-05-19T20:10:25.561594Z",
"shell.execute_reply": "2026-05-19T20:10:25.561186Z"
}
},
"outputs": [],
"source": [
"%%cpp -d\n",
"Double_t fdm5(Double_t *xx, Double_t *par)\n",
"{\n",
" Double_t x = xx[0];\n",
" if (x <= 0.13957)\n",
" return 0;\n",
" Double_t xp3 = (x - par[3]) * (x - par[3]);\n",
" Double_t res =\n",
" dxbin * (par[0] * pow(x - 0.13957, par[1]) + par[2] / 2.5066 / par[4] * exp(-xp3 / 2 / par[4] / par[4]));\n",
" return res;\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "973cd0b7",
"metadata": {},
"source": [
" Definition of a helper function: "
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "746d039a",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.562707Z",
"iopub.status.busy": "2026-05-19T20:10:25.562533Z",
"iopub.status.idle": "2026-05-19T20:10:25.565219Z",
"shell.execute_reply": "2026-05-19T20:10:25.564854Z"
}
},
"outputs": [],
"source": [
"%%cpp -d\n",
"Double_t fdm2(Double_t *xx, Double_t *par)\n",
"{\n",
" static const Double_t sigma = 0.0012;\n",
" Double_t x = xx[0];\n",
" if (x <= 0.13957)\n",
" return 0;\n",
" Double_t xp3 = (x - 0.1454) * (x - 0.1454);\n",
" Double_t res = dxbin * (par[0] * pow(x - 0.13957, 0.25) + par[1] / 2.5066 / sigma * exp(-xp3 / 2 / sigma / sigma));\n",
" return res;\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "bf0f3dd2",
"metadata": {},
"source": [
" Definition of a helper function: "
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "254b88f9",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.566249Z",
"iopub.status.busy": "2026-05-19T20:10:25.566138Z",
"iopub.status.idle": "2026-05-19T20:10:25.579043Z",
"shell.execute_reply": "2026-05-19T20:10:25.578625Z"
}
},
"outputs": [],
"source": [
"%%cpp -d\n",
"void FitAndPlotHdmd(TH1 &hdmd)\n",
"{\n",
" // create the canvas for the h1analysis fit\n",
" gStyle->SetOptFit();\n",
" auto c1 = new TCanvas(\"c1\", \"h1analysis analysis\", 10, 10, 800, 600);\n",
"\n",
" hdmd.GetXaxis()->SetTitleOffset(1.4);\n",
"\n",
" auto hdraw = (TH1 *) hdmd.DrawClone();\n",
"\n",
" // fit histogram hdmd with function f5 using the loglikelihood option\n",
" auto f5 = new TF1(\"f5\", fdm5, 0.139, 0.17, 5);\n",
" f5->SetParameters(1000000, .25, 2000, .1454, .001);\n",
" hdraw->Fit(\"f5\", \"lr\");\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "e4cf6a7b",
"metadata": {},
"source": [
" Definition of a helper function: "
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "83ee01b1",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.583475Z",
"iopub.status.busy": "2026-05-19T20:10:25.583353Z",
"iopub.status.idle": "2026-05-19T20:10:25.591049Z",
"shell.execute_reply": "2026-05-19T20:10:25.590451Z"
}
},
"outputs": [],
"source": [
"%%cpp -d\n",
"void FitAndPlotH2(TH2 &h2)\n",
"{\n",
" // create the canvas for tau d0\n",
" auto c2 = new TCanvas(\"c2\", \"tauD0\", 100, 100, 800, 600);\n",
"\n",
" c2->SetGrid();\n",
" c2->SetBottomMargin(0.15);\n",
"\n",
" // Project slices of 2-d histogram h2 along X , then fit each slice\n",
" // with function f2 and make a histogram for each fit parameter\n",
" // Note that the generated histograms are added to the list of objects\n",
" // in the current directory.\n",
" auto f2 = new TF1(\"f2\", fdm2, 0.139, 0.17, 2);\n",
" f2->SetParameters(10000, 10);\n",
" h2.FitSlicesX(f2, 0, -1, 1, \"qln\");\n",
"\n",
" // See TH2::FitSlicesX documentation why h2_1 name is used\n",
" auto h2_1 = (TH1D *)gDirectory->Get(\"h2_1\");\n",
" h2_1->SetDirectory(nullptr);\n",
" h2_1->GetXaxis()->SetTitle(\"#tau [ps]\");\n",
" h2_1->SetMarkerStyle(21);\n",
" h2_1->Draw();\n",
" c2->Update();\n",
"\n",
" auto line = new TLine(0, 0, 0, c2->GetUymax());\n",
" line->Draw();\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5a7deed0",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:25.592311Z",
"iopub.status.busy": "2026-05-19T20:10:25.592191Z",
"iopub.status.idle": "2026-05-19T20:10:26.761156Z",
"shell.execute_reply": "2026-05-19T20:10:26.751040Z"
}
},
"outputs": [],
"source": [
"TChain chain(\"h42\");\n",
"chain.Add(\"root://eospublic.cern.ch//eos/root-eos/h1/dstarmb.root\");\n",
"chain.Add(\"root://eospublic.cern.ch//eos/root-eos/h1/dstarp1a.root\");\n",
"chain.Add(\"root://eospublic.cern.ch//eos/root-eos/h1/dstarp1b.root\");\n",
"chain.Add(\"root://eospublic.cern.ch//eos/root-eos/h1/dstarp2.root\");\n",
"\n",
"ROOT::EnableImplicitMT(4);\n",
"\n",
"ROOT::RDataFrame dataFrame(chain);\n",
"auto selected = Select(dataFrame);"
]
},
{
"cell_type": "markdown",
"id": "300a47be",
"metadata": {},
"source": [
"Note: The title syntax is \";<Label x axis>;<Label y axis>\""
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "6822b4fd",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:26.780134Z",
"iopub.status.busy": "2026-05-19T20:10:26.779940Z",
"iopub.status.idle": "2026-05-19T20:10:29.057698Z",
"shell.execute_reply": "2026-05-19T20:10:29.036907Z"
}
},
"outputs": [
{
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').then(json => {\n",
" const obj = Core.parse(json);\n",
" Core.draw('root_plot_1779221428991', obj, '');\n",
"});\n",
"\n",
" }\n",
" const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
" path = 'build/jsroot';\n",
" if (typeof JSROOT !== 'undefined')\n",
" execCode(JSROOT);\n",
" else if (typeof requirejs !== 'undefined') {\n",
" servers.forEach((s,i) => { servers[i] = s + path; });\n",
" requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'], execCode);\n",
" } else {\n",
" const config = document.getElementById('jupyter-config-data');\n",
" if (config)\n",
" servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
" else\n",
" servers.shift();\n",
" function loadJsroot() {\n",
" return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
" }\n",
" loadJsroot();\n",
" }\n",
" }\n",
" process_root_plot_1779221428991();\n",
"</script>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"****************************************\n",
"Minimizer is Minuit2 / Migrad\n",
"MinFCN = 10684\n",
"Chi2 = 21368.1\n",
"NDf = 26\n",
"Edm = 6.40741e-07\n",
"NCalls = 210\n",
"p0 = 959914 +/- 88769 \n",
"p1 = 0.351114 +/- 0.0227896 \n",
"p2 = 1185.03 +/- 59.224 \n",
"p3 = 0.145569 +/- 5.93973e-05 \n",
"p4 = 0.00124388 +/- 6.60206e-05 \n"
]
}
],
"source": [
"auto hdmdARP = selected.Histo1D({\"hdmd\", \"Dm_d;m_{K#pi#pi} - m_{K#pi}[GeV/c^{2}]\", 40, 0.13, 0.17}, \"dm_d\");\n",
"auto selectedAddedBranch = selected.Define(\"h2_y\", \"rpd0_t / 0.029979f * 1.8646f / ptd0_d\");\n",
"auto h2ARP = selectedAddedBranch.Histo2D({\"h2\", \"ptD0 vs Dm_d\", 30, 0.135, 0.165, 30, -3, 6}, \"dm_d\", \"h2_y\");\n",
"\n",
"FitAndPlotHdmd(*hdmdARP);\n",
"FitAndPlotH2(*h2ARP);"
]
},
{
"cell_type": "markdown",
"id": "3d8b8cd9",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "6cc90e2c",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:10:29.068129Z",
"iopub.status.busy": "2026-05-19T20:10:29.067956Z",
"iopub.status.idle": "2026-05-19T20:10:29.273863Z",
"shell.execute_reply": "2026-05-19T20:10:29.273343Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"<div id=\"root_plot_1779221429205\" style=\"width: 800px; height: 600px; position: relative\">\n",
"</div>\n",
"\n",
"</div>\n",
"<script>\n",
" function process_root_plot_1779221429205() {\n",
" function execCode(Core) {\n",
" Core.settings.HandleKeys = false;\n",
" \n",
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').then(json => {\n",
" const obj = Core.parse(json);\n",
" Core.draw('root_plot_1779221429205', obj, '');\n",
"});\n",
"\n",
" }\n",
" const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
" path = 'build/jsroot';\n",
" if (typeof JSROOT !== 'undefined')\n",
" execCode(JSROOT);\n",
" else if (typeof requirejs !== 'undefined') {\n",
" servers.forEach((s,i) => { servers[i] = s + path; });\n",
" requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'], execCode);\n",
" } else {\n",
" const config = document.getElementById('jupyter-config-data');\n",
" if (config)\n",
" servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
" else\n",
" servers.shift();\n",
" function loadJsroot() {\n",
" return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
" }\n",
" loadJsroot();\n",
" }\n",
" }\n",
" process_root_plot_1779221429205();\n",
"</script>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
"<div id=\"root_plot_1779221429207\" style=\"width: 800px; height: 600px; position: relative\">\n",
"</div>\n",
"\n",
"</div>\n",
"<script>\n",
" function process_root_plot_1779221429207() {\n",
" function execCode(Core) {\n",
" Core.settings.HandleKeys = false;\n",
" \n",
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').then(json => {\n",
" const obj = Core.parse(json);\n",
" Core.draw('root_plot_1779221429207', obj, '');\n",
"});\n",
"\n",
" }\n",
" const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
" path = 'build/jsroot';\n",
" if (typeof JSROOT !== 'undefined')\n",
" execCode(JSROOT);\n",
" else if (typeof requirejs !== 'undefined') {\n",
" servers.forEach((s,i) => { servers[i] = s + path; });\n",
" requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'], execCode);\n",
" } else {\n",
" const config = document.getElementById('jupyter-config-data');\n",
" if (config)\n",
" servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
" else\n",
" servers.shift();\n",
" function loadJsroot() {\n",
" return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
" }\n",
" loadJsroot();\n",
" }\n",
" }\n",
" process_root_plot_1779221429207();\n",
"</script>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gROOT->GetListOfCanvases()->Draw()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "ROOT C++",
"language": "c++",
"name": "root"
},
"language_info": {
"codemirror_mode": "text/x-c++src",
"file_extension": ".C",
"mimetype": " text/x-c++src",
"name": "c++"
}
},
"nbformat": 4,
"nbformat_minor": 5
}