{
"cells": [
{
"cell_type": "markdown",
"id": "990ff640",
"metadata": {},
"source": [
"# gr010_approx_smooth\n",
"\n",
"See the [TGraphSmooth documentation](https://root.cern/doc/master/classTGraphSmooth.html)\n",
"\n",
"\n",
"\n",
"**Author:** Christian Stratowa, 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": "ed57ade9",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:55.030191Z",
"iopub.status.busy": "2026-05-19T20:37:55.030051Z",
"iopub.status.idle": "2026-05-19T20:37:56.109300Z",
"shell.execute_reply": "2026-05-19T20:37:56.108856Z"
}
},
"outputs": [],
"source": [
"from ctypes import c_double\n",
"\n",
"import numpy as np\n",
"import ROOT"
]
},
{
"cell_type": "markdown",
"id": "b87cb922",
"metadata": {},
"source": [
"vC1 = ROOT.TCanvas()\n",
"# grxy = ROOT.TGraph()\n",
"grin = ROOT.TGraph()\n",
"grout = ROOT.TGraph()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "f00d1f4c",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.121449Z",
"iopub.status.busy": "2026-05-19T20:37:56.121240Z",
"iopub.status.idle": "2026-05-19T20:37:56.231978Z",
"shell.execute_reply": "2026-05-19T20:37:56.231591Z"
}
},
"outputs": [],
"source": [
"def DrawSmooth(pad, title, xt, yt):\n",
" vC1.cd(pad)\n",
" vFrame = ROOT.gPad.DrawFrame(0, 0, 15, 150)\n",
" vFrame.SetTitle(title)\n",
" vFrame.SetTitleSize(0.2)\n",
" vFrame.SetXTitle(xt)\n",
" vFrame.SetYTitle(yt)\n",
" grxy.SetMarkerColor(ROOT.kBlue)\n",
" grxy.SetMarkerStyle(21)\n",
" grxy.SetMarkerSize(0.5)\n",
" grxy.Draw(\"P\")\n",
" grin.SetMarkerColor(ROOT.kRed)\n",
" grin.SetMarkerStyle(5)\n",
" grin.SetMarkerSize(0.7)\n",
" grin.Draw(\"P\")\n",
" grout.DrawClone(\"LP\")"
]
},
{
"cell_type": "markdown",
"id": "9eec6f48",
"metadata": {},
"source": [
"Test data (square)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "ce4981e0",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.241176Z",
"iopub.status.busy": "2026-05-19T20:37:56.241043Z",
"iopub.status.idle": "2026-05-19T20:37:56.357442Z",
"shell.execute_reply": "2026-05-19T20:37:56.356927Z"
}
},
"outputs": [],
"source": [
"n = 11\n",
"x = np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 6.0, 6.0, 8.0, 9.0, 10.0])\n",
"y = np.array([1.0, 4.0, 9.0, 16.0, 25.0, 25.0, 36.0, 49.0, 64.0, 81.0, 100.0])\n",
"\n",
"grxy = ROOT.TGraph(n, x, y)"
]
},
{
"cell_type": "markdown",
"id": "87c6bbfc",
"metadata": {},
"source": [
"X values, for which y values should be interpolated"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0afbbfac",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.359387Z",
"iopub.status.busy": "2026-05-19T20:37:56.359256Z",
"iopub.status.idle": "2026-05-19T20:37:56.487883Z",
"shell.execute_reply": "2026-05-19T20:37:56.473333Z"
}
},
"outputs": [],
"source": [
"nout = 14\n",
"xout = np.array([1.2, 1.7, 2.5, 3.2, 4.4, 5.2, 5.7, 6.5, 7.6, 8.3, 9.7, 10.4, 11.3, 13])"
]
},
{
"cell_type": "markdown",
"id": "2e93f8c4",
"metadata": {},
"source": [
"Create Canvas"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "850aaef6",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.495750Z",
"iopub.status.busy": "2026-05-19T20:37:56.495570Z",
"iopub.status.idle": "2026-05-19T20:37:56.640523Z",
"shell.execute_reply": "2026-05-19T20:37:56.639914Z"
}
},
"outputs": [],
"source": [
"vC1 = ROOT.TCanvas(\"vC1\", \"square\", 200, 10, 700, 700)\n",
"vC1.Divide(2, 2)"
]
},
{
"cell_type": "markdown",
"id": "45c541f0",
"metadata": {},
"source": [
"Initialize graph with data"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "b541be81",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.642290Z",
"iopub.status.busy": "2026-05-19T20:37:56.642155Z",
"iopub.status.idle": "2026-05-19T20:37:56.745550Z",
"shell.execute_reply": "2026-05-19T20:37:56.744893Z"
}
},
"outputs": [],
"source": [
"grin = ROOT.TGraph(n, x, y)"
]
},
{
"cell_type": "markdown",
"id": "a9fda1f7",
"metadata": {},
"source": [
"Interpolate at equidistant points (use mean for tied x-values)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "67f6d7ae",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:56.747403Z",
"iopub.status.busy": "2026-05-19T20:37:56.747277Z",
"iopub.status.idle": "2026-05-19T20:37:56.996854Z",
"shell.execute_reply": "2026-05-19T20:37:56.996470Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"
\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs = ROOT.TGraphSmooth(\"normal\")\n",
"grout = gs.Approx(grin, \"linear\")\n",
"DrawSmooth(1, \"Approx: ties = mean\", \"X-axis\", \"Y-axis\")"
]
},
{
"cell_type": "markdown",
"id": "8565641e",
"metadata": {},
"source": [
"Re-initialize graph with data\n",
"(since graph points were set to unique vales)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "cef299a6",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.004581Z",
"iopub.status.busy": "2026-05-19T20:37:57.004438Z",
"iopub.status.idle": "2026-05-19T20:37:57.113247Z",
"shell.execute_reply": "2026-05-19T20:37:57.112580Z"
}
},
"outputs": [],
"source": [
"grin = ROOT.TGraph(n, x, y)"
]
},
{
"cell_type": "markdown",
"id": "a6e5feda",
"metadata": {},
"source": [
"Interpolate at given points xout"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f276a209",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.115416Z",
"iopub.status.busy": "2026-05-19T20:37:57.115275Z",
"iopub.status.idle": "2026-05-19T20:37:57.225793Z",
"shell.execute_reply": "2026-05-19T20:37:57.225169Z"
}
},
"outputs": [],
"source": [
"grout = gs.Approx(grin, \"linear\", 14, xout, 0, 130)\n",
"DrawSmooth(2, \"Approx: ties = mean\", \"\", \"\")"
]
},
{
"cell_type": "markdown",
"id": "198b53e5",
"metadata": {},
"source": [
"Print output variables for given values xout"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "42ce4ec7",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.227567Z",
"iopub.status.busy": "2026-05-19T20:37:57.227433Z",
"iopub.status.idle": "2026-05-19T20:37:57.355221Z",
"shell.execute_reply": "2026-05-19T20:37:57.344277Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"k= 0 vXout[k]= 1.2 vYout[k]= 1.5999999999999999\n",
"k= 1 vXout[k]= 1.7 vYout[k]= 3.0999999999999996\n",
"k= 2 vXout[k]= 2.5 vYout[k]= 6.5\n",
"k= 3 vXout[k]= 3.2 vYout[k]= 10.400000000000002\n",
"k= 4 vXout[k]= 4.4 vYout[k]= 19.6\n",
"k= 5 vXout[k]= 5.2 vYout[k]= 27.333333333333336\n",
"k= 6 vXout[k]= 5.7 vYout[k]= 33.166666666666664\n",
"k= 7 vXout[k]= 6.5 vYout[k]= 43.5\n",
"k= 8 vXout[k]= 7.6 vYout[k]= 58.53333333333333\n",
"k= 9 vXout[k]= 8.3 vYout[k]= 69.10000000000001\n",
"k= 10 vXout[k]= 9.7 vYout[k]= 94.29999999999998\n",
"k= 11 vXout[k]= 10.4 vYout[k]= 130.0\n",
"k= 12 vXout[k]= 11.3 vYout[k]= 130.0\n",
"k= 13 vXout[k]= 13.0 vYout[k]= 130.0\n"
]
}
],
"source": [
"vNout = grout.GetN()\n",
"vXout = c_double()\n",
"vYout = c_double()\n",
"for k in range(vNout):\n",
" grout.GetPoint(k, vXout, vYout)\n",
" print(f\"k= {k} vXout[k]= {vXout.value} vYout[k]= {vYout.value}\")"
]
},
{
"cell_type": "markdown",
"id": "35910f0c",
"metadata": {},
"source": [
"Re-initialize graph with data"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "7b63147b",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.367050Z",
"iopub.status.busy": "2026-05-19T20:37:57.366894Z",
"iopub.status.idle": "2026-05-19T20:37:57.470287Z",
"shell.execute_reply": "2026-05-19T20:37:57.469812Z"
}
},
"outputs": [],
"source": [
"grin = ROOT.TGraph(n, x, y)"
]
},
{
"cell_type": "markdown",
"id": "1c7e225e",
"metadata": {},
"source": [
"Interpolate at equidistant points (use min for tied x-values)\n",
" _grout = gs.Approx(grin,\"linear\", 50, 0, 0, 0, 1, 0, \"min\")_"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "30bfb4f9",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.472841Z",
"iopub.status.busy": "2026-05-19T20:37:57.472684Z",
"iopub.status.idle": "2026-05-19T20:37:57.583642Z",
"shell.execute_reply": "2026-05-19T20:37:57.583016Z"
}
},
"outputs": [],
"source": [
"grout = gs.Approx(grin, \"constant\", 50, 0, 0, 0, 1, 0.5, \"min\")\n",
"DrawSmooth(3, \"Approx: ties = min\", \"\", \"\")"
]
},
{
"cell_type": "markdown",
"id": "e6f2406d",
"metadata": {},
"source": [
"Re-initialize graph with data"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "0af23ac5",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.585548Z",
"iopub.status.busy": "2026-05-19T20:37:57.585412Z",
"iopub.status.idle": "2026-05-19T20:37:57.688824Z",
"shell.execute_reply": "2026-05-19T20:37:57.688327Z"
}
},
"outputs": [],
"source": [
"grin = ROOT.TGraph(n, x, y)"
]
},
{
"cell_type": "markdown",
"id": "fd1db2a4",
"metadata": {},
"source": [
"Interpolate at equidistant points (use max for tied x-values)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "acff91a9",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.691678Z",
"iopub.status.busy": "2026-05-19T20:37:57.691525Z",
"iopub.status.idle": "2026-05-19T20:37:57.803618Z",
"shell.execute_reply": "2026-05-19T20:37:57.802989Z"
}
},
"outputs": [],
"source": [
"grout = gs.Approx(grin, \"linear\", 14, xout, 0, 0, 2, 0, \"max\")\n",
"DrawSmooth(4, \"Approx: ties = max\", \"\", \"\")"
]
},
{
"cell_type": "markdown",
"id": "73e25fe6",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "01162611",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:37:57.807715Z",
"iopub.status.busy": "2026-05-19T20:37:57.807568Z",
"iopub.status.idle": "2026-05-19T20:37:57.922101Z",
"shell.execute_reply": "2026-05-19T20:37:57.921453Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"
\n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%jsroot on\n",
"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
}