{
"cells": [
{
"cell_type": "markdown",
"id": "a56deeb3",
"metadata": {},
"source": [
"# rf106_plotdecoration\n",
"Basic functionality: adding boxes with parameters to RooPlots and decorating with arrows, etc...\n",
"\n",
"\n",
"\n",
"\n",
"**Author:** Clemens Lange, Wouter Verkerke (C++ version) \n",
"This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Tuesday, May 19, 2026 at 08:29 PM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "99b97e9c",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:03.110079Z",
"iopub.status.busy": "2026-05-19T20:29:03.109964Z",
"iopub.status.idle": "2026-05-19T20:29:04.069123Z",
"shell.execute_reply": "2026-05-19T20:29:04.068513Z"
}
},
"outputs": [],
"source": [
"import ROOT"
]
},
{
"cell_type": "markdown",
"id": "72fa77ef",
"metadata": {},
"source": [
"Set up model\n",
"---------------------"
]
},
{
"cell_type": "markdown",
"id": "586af1d5",
"metadata": {},
"source": [
"Create observables"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d1b42969",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.071584Z",
"iopub.status.busy": "2026-05-19T20:29:04.071452Z",
"iopub.status.idle": "2026-05-19T20:29:04.232332Z",
"shell.execute_reply": "2026-05-19T20:29:04.231746Z"
}
},
"outputs": [],
"source": [
"x = ROOT.RooRealVar(\"x\", \"x\", -10, 10)"
]
},
{
"cell_type": "markdown",
"id": "60588fee",
"metadata": {},
"source": [
"Create Gaussian"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "fef92f02",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.234399Z",
"iopub.status.busy": "2026-05-19T20:29:04.234271Z",
"iopub.status.idle": "2026-05-19T20:29:04.361262Z",
"shell.execute_reply": "2026-05-19T20:29:04.360648Z"
}
},
"outputs": [],
"source": [
"sigma = ROOT.RooRealVar(\"sigma\", \"sigma\", 1, 0.1, 10)\n",
"mean = ROOT.RooRealVar(\"mean\", \"mean\", -3, -10, 10)\n",
"gauss = ROOT.RooGaussian(\"gauss\", \"gauss\", x, mean, sigma)"
]
},
{
"cell_type": "markdown",
"id": "5ee82821",
"metadata": {},
"source": [
"Generate a sample of 1000 events with sigma=3"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "9083f5a8",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.363804Z",
"iopub.status.busy": "2026-05-19T20:29:04.363677Z",
"iopub.status.idle": "2026-05-19T20:29:04.500773Z",
"shell.execute_reply": "2026-05-19T20:29:04.500116Z"
}
},
"outputs": [],
"source": [
"data = gauss.generate({x}, 1000)"
]
},
{
"cell_type": "markdown",
"id": "3a92a0e3",
"metadata": {},
"source": [
"Fit pdf to data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "35af5dc7",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.503379Z",
"iopub.status.busy": "2026-05-19T20:29:04.503254Z",
"iopub.status.idle": "2026-05-19T20:29:04.699256Z",
"shell.execute_reply": "2026-05-19T20:29:04.698519Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[#1] INFO:Fitting -- RooAbsPdf::fitTo(gauss_over_gauss_Int[x]) fixing normalization set for coefficient determination to observables in data\n",
"[#1] INFO:Fitting -- using generic CPU library compiled with no vectorizations\n",
"[#1] INFO:Fitting -- Creation of NLL object took 6.67798 ms\n",
"[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_gauss_over_gauss_Int[x]_gaussData) Summation contains a RooNLLVar, using its error level\n",
"[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only\n"
]
}
],
"source": [
"gauss.fitTo(data, PrintLevel=-1)"
]
},
{
"cell_type": "markdown",
"id": "9d9c963a",
"metadata": {},
"source": [
"Plot pdf and data\n",
"-------------------------------------"
]
},
{
"cell_type": "markdown",
"id": "3eb1a709",
"metadata": {},
"source": [
"Overlay projection of gauss on data"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "2ffe5661",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.701171Z",
"iopub.status.busy": "2026-05-19T20:29:04.701043Z",
"iopub.status.idle": "2026-05-19T20:29:04.881051Z",
"shell.execute_reply": "2026-05-19T20:29:04.880416Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"frame = x.frame(Name=\"xframe\", Title=\"RooPlot with decorations\", Bins=40)\n",
"data.plotOn(frame)\n",
"gauss.plotOn(frame)"
]
},
{
"cell_type": "markdown",
"id": "36d97e00",
"metadata": {},
"source": [
"Add box with pdf parameters\n",
"-----------------------------------------------------"
]
},
{
"cell_type": "markdown",
"id": "3f20767e",
"metadata": {},
"source": [
"Left edge of box starts at 55% of Xaxis)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "0520a6c1",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:04.883122Z",
"iopub.status.busy": "2026-05-19T20:29:04.882999Z",
"iopub.status.idle": "2026-05-19T20:29:05.012663Z",
"shell.execute_reply": "2026-05-19T20:29:05.011935Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gauss.paramOn(frame, Layout=0.55)"
]
},
{
"cell_type": "markdown",
"id": "4514e524",
"metadata": {},
"source": [
"Add box with data statistics\n",
"-------------------------------------------------------"
]
},
{
"cell_type": "markdown",
"id": "768ef7b3",
"metadata": {},
"source": [
"X size of box is from 55% to 99% of Xaxis range, of box is at 80% of\n",
"Yaxis range)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "7c4eb2f2",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.014501Z",
"iopub.status.busy": "2026-05-19T20:29:05.014376Z",
"iopub.status.idle": "2026-05-19T20:29:05.140310Z",
"shell.execute_reply": "2026-05-19T20:29:05.139747Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.statOn(frame, Layout=(0.55, 0.99, 0.8))"
]
},
{
"cell_type": "markdown",
"id": "84146129",
"metadata": {},
"source": [
"Add text and arrow\n",
"-----------------------------------"
]
},
{
"cell_type": "markdown",
"id": "eea49fb0",
"metadata": {},
"source": [
"Add text to frame"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "fa9dde67",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.142488Z",
"iopub.status.busy": "2026-05-19T20:29:05.142366Z",
"iopub.status.idle": "2026-05-19T20:29:05.261445Z",
"shell.execute_reply": "2026-05-19T20:29:05.260897Z"
}
},
"outputs": [],
"source": [
"txt = ROOT.TText(2, 100, \"Signal\")\n",
"txt.SetTextSize(0.04)\n",
"txt.SetTextColor(\"kRed\")\n",
"frame.addObject(txt)"
]
},
{
"cell_type": "markdown",
"id": "5de25608",
"metadata": {},
"source": [
"Add arrow to frame"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "cf0ee468",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.263480Z",
"iopub.status.busy": "2026-05-19T20:29:05.263355Z",
"iopub.status.idle": "2026-05-19T20:29:05.379810Z",
"shell.execute_reply": "2026-05-19T20:29:05.379163Z"
}
},
"outputs": [],
"source": [
"arrow = ROOT.TArrow(2, 100, -1, 50, 0.01, \"|>\")\n",
"arrow.SetLineColor(\"kRed\")\n",
"arrow.SetFillColor(\"kRed\")\n",
"arrow.SetLineWidth(3)\n",
"frame.addObject(arrow)"
]
},
{
"cell_type": "markdown",
"id": "2fb1b63b",
"metadata": {},
"source": [
"Persist frame with all decorations in ROOT file\n",
"---------------------------------------------------------------------------------------------"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "8fe40ca8",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.381915Z",
"iopub.status.busy": "2026-05-19T20:29:05.381753Z",
"iopub.status.idle": "2026-05-19T20:29:05.632363Z",
"shell.execute_reply": "2026-05-19T20:29:05.631649Z"
}
},
"outputs": [],
"source": [
"f = ROOT.TFile(\"rf106_plotdecoration.root\", \"RECREATE\")\n",
"frame.Write()\n",
"f.Close()"
]
},
{
"cell_type": "markdown",
"id": "fbcc2426",
"metadata": {},
"source": [
"To read back and plot frame with all decorations in clean root session do\n",
"root> ROOT.TFile f(\"rf106_plotdecoration.root\")\n",
"root> xframe.Draw()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "92e86493",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.634857Z",
"iopub.status.busy": "2026-05-19T20:29:05.634681Z",
"iopub.status.idle": "2026-05-19T20:29:05.843279Z",
"shell.execute_reply": "2026-05-19T20:29:05.842688Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Info in : png file rf106_plotdecoration.png has been created\n"
]
}
],
"source": [
"c = ROOT.TCanvas(\"rf106_plotdecoration\", \"rf106_plotdecoration\", 600, 600)\n",
"ROOT.gPad.SetLeftMargin(0.15)\n",
"frame.GetYaxis().SetTitleOffset(1.6)\n",
"frame.Draw()\n",
"\n",
"c.SaveAs(\"rf106_plotdecoration.png\")"
]
},
{
"cell_type": "markdown",
"id": "b787ec73",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "a3df2018",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:29:05.844884Z",
"iopub.status.busy": "2026-05-19T20:29:05.844761Z",
"iopub.status.idle": "2026-05-19T20:29:06.017438Z",
"shell.execute_reply": "2026-05-19T20:29:06.016832Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"
\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from ROOT import gROOT \n",
"gROOT.GetListOfCanvases().Draw()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}