{
"cells": [
{
"cell_type": "markdown",
"id": "dcb015fd",
"metadata": {},
"source": [
"# gr007_multigraph\n",
"Allowing to overlay different graphs can be useful for comparing different datasets\n",
"or for plotting multiple related graphs on the same canvas.\n",
"\n",
"\n",
"\n",
"\n",
"**Author:** Rene Brun, Jamie Gooding \n",
"This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Tuesday, May 19, 2026 at 08:37 PM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "bd5b87ca",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:51.490303Z",
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"shell.execute_reply": "2026-05-19T20:37:52.633428Z"
}
},
"outputs": [],
"source": [
"import numpy as np\n",
"import ROOT\n",
"\n",
"ROOT.gStyle.SetOptFit()\n",
"c1 = ROOT.TCanvas(\"c1\", \"multigraph\", 700, 500)\n",
"c1.SetGrid()"
]
},
{
"cell_type": "markdown",
"id": "3ce00136",
"metadata": {},
"source": [
"Initialize a TMultiGraph to hold multiple graphs\n",
"This ensures the entire dataset from all added graphs is visible without manual range adjustments."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "8a4fc13a",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:52.636218Z",
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"shell.execute_reply": "2026-05-19T20:37:52.755471Z"
}
},
"outputs": [],
"source": [
"mg = ROOT.TMultiGraph()"
]
},
{
"cell_type": "markdown",
"id": "286b057b",
"metadata": {},
"source": [
"Create first graph"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0a996cc2",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:52.758183Z",
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"shell.execute_reply": "2026-05-19T20:37:53.016025Z"
}
},
"outputs": [],
"source": [
"n1 = 10\n",
"px1 = np.array([-0.1, 0.05, 0.25, 0.35, 0.5, 0.61, 0.7, 0.85, 0.89, 0.95])\n",
"py1 = np.array([-1, 2.9, 5.6, 7.4, 9, 9.6, 8.7, 6.3, 4.5, 1])\n",
"ex1 = np.array([0.05, 0.1, 0.07, 0.07, 0.04, 0.05, 0.06, 0.07, 0.08, 0.05])\n",
"ey1 = np.array([0.8, 0.7, 0.6, 0.5, 0.4, 0.4, 0.5, 0.6, 0.7, 0.8])\n",
"gr1 = ROOT.TGraphErrors(n1, px1, py1, ex1, ey1)\n",
"gr1.SetMarkerColor(ROOT.kBlue)\n",
"gr1.SetMarkerStyle(21)\n",
"\n",
"gr1.Fit(\"gaus\", \"q\")\n",
"func1 = gr1.GetListOfFunctions().FindObject(\"gaus\")\n",
"func1.SetLineColor(ROOT.kBlue)"
]
},
{
"cell_type": "markdown",
"id": "e577a751",
"metadata": {},
"source": [
"Add the first graph to the multigraph"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a4021d91",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:53.022696Z",
"iopub.status.busy": "2026-05-19T20:37:53.022549Z",
"iopub.status.idle": "2026-05-19T20:37:53.130025Z",
"shell.execute_reply": "2026-05-19T20:37:53.129433Z"
}
},
"outputs": [],
"source": [
"mg.Add(gr1)"
]
},
{
"cell_type": "markdown",
"id": "ae9b5754",
"metadata": {},
"source": [
"Create second graph"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ae2667d0",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:53.151376Z",
"iopub.status.busy": "2026-05-19T20:37:53.151230Z",
"iopub.status.idle": "2026-05-19T20:37:53.262449Z",
"shell.execute_reply": "2026-05-19T20:37:53.262089Z"
}
},
"outputs": [],
"source": [
"n2 = 10\n",
"x2 = np.array([-0.28, 0.005, 0.19, 0.29, 0.45, 0.56, 0.65, 0.80, 0.90, 1.01])\n",
"y2 = np.array([2.1, 3.86, 7, 9, 10, 10.55, 9.64, 7.26, 5.42, 2])\n",
"ex2 = np.array([0.04, 0.12, 0.08, 0.06, 0.05, 0.04, 0.07, 0.06, 0.08, 0.04])\n",
"ey2 = np.array([0.6, 0.8, 0.7, 0.4, 0.3, 0.3, 0.4, 0.5, 0.6, 0.7])\n",
"gr2 = ROOT.TGraphErrors(n2, x2, y2, ex2, ey2)\n",
"gr2.SetMarkerColor(ROOT.kRed)\n",
"gr2.SetMarkerStyle(20)\n",
"\n",
"gr2.Fit(\"pol5\", \"q\")\n",
"func2 = gr2.GetListOfFunctions().FindObject(\"pol5\")\n",
"func2.SetLineColor(ROOT.kRed)\n",
"func2.SetLineStyle(2)"
]
},
{
"cell_type": "markdown",
"id": "277ef65e",
"metadata": {},
"source": [
"Add the second graph to the multigraph"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "7fed05f8",
"metadata": {
"collapsed": false,
"execution": {
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"shell.execute_reply": "2026-05-19T20:37:53.384223Z"
}
},
"outputs": [],
"source": [
"mg.Add(gr2)\n",
"\n",
"mg.Draw(\"ap\")"
]
},
{
"cell_type": "markdown",
"id": "28fb4173",
"metadata": {},
"source": [
"Force drawing of canvas to generate the fit TPaveStats"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "a9fd84f4",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:53.407353Z",
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"shell.execute_reply": "2026-05-19T20:37:53.668686Z"
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"text/html": [
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"\n"
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"text/plain": [
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},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"c1.Update()\n",
"\n",
"stats1 = gr1.GetListOfFunctions().FindObject(\"stats\")\n",
"stats2 = gr2.GetListOfFunctions().FindObject(\"stats\")\n",
"\n",
"if stats1 and stats2:\n",
" stats1.SetTextColor(ROOT.kBlue)\n",
" stats2.SetTextColor(ROOT.kRed)\n",
" stats1.SetX1NDC(0.12)\n",
" stats1.SetX2NDC(0.32)\n",
" stats1.SetY1NDC(0.82)\n",
" stats2.SetX1NDC(0.72)\n",
" stats2.SetX2NDC(0.92)\n",
" stats2.SetY1NDC(0.75)\n",
" c1.Modified()"
]
},
{
"cell_type": "markdown",
"id": "f56ef6f8",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "3ca1f10b",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:53.706516Z",
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"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from ROOT import gROOT \n",
"gROOT.GetListOfCanvases().Draw()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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