{
"cells": [
{
"cell_type": "markdown",
"id": "ae765b83",
"metadata": {},
"source": [
"# df016_vecOps\n",
"Process collections in RDataFrame with the help of RVec.\n",
"\n",
"This tutorial shows the potential of the VecOps approach for treating collections\n",
"stored in datasets, a situation very common in HEP data analysis.\n",
"\n",
"\n",
"\n",
"\n",
"**Author:** 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 08:09 PM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "fa82bead",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:09:45.319793Z",
"iopub.status.busy": "2026-05-19T20:09:45.319673Z",
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"shell.execute_reply": "2026-05-19T20:09:46.664538Z"
}
},
"outputs": [],
"source": [
"import ROOT\n",
"\n",
"df = ROOT.RDataFrame(1024)\n",
"coordDefineCode = '''ROOT::RVecD {0}(len);\n",
" std::transform({0}.begin(), {0}.end(), {0}.begin(), [](double){{return gRandom->Uniform(-1.0, 1.0);}});\n",
" return {0};'''\n",
"d = df.Define(\"len\", \"gRandom->Uniform(0, 16)\")\\\n",
" .Define(\"x\", coordDefineCode.format(\"x\"))\\\n",
" .Define(\"y\", coordDefineCode.format(\"y\"))"
]
},
{
"cell_type": "markdown",
"id": "214843da",
"metadata": {},
"source": [
"Now we have in our hands d, a RDataFrame with two columns, x and y, which\n",
"hold collections of coordinates. The sizes of these collections vary.\n",
"Let's now define radii radii from the x and y coordinates. We'll do it treating \n",
"the collections stored in the columns without looping on the individual elements."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e52d91cd",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:09:46.675391Z",
"iopub.status.busy": "2026-05-19T20:09:46.675249Z",
"iopub.status.idle": "2026-05-19T20:09:46.794113Z",
"shell.execute_reply": "2026-05-19T20:09:46.793218Z"
}
},
"outputs": [],
"source": [
"d1 = d.Define(\"r\", \"sqrt(x*x + y*y)\")"
]
},
{
"cell_type": "markdown",
"id": "92c044e2",
"metadata": {},
"source": [
"Now we want to plot 2 quarters of a ring with radii .5 and 1.\n",
"Note how the cuts are performed on RVecs, comparing them with integers and\n",
"among themselves."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "7b7ddbd0",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:09:46.800301Z",
"iopub.status.busy": "2026-05-19T20:09:46.800127Z",
"iopub.status.idle": "2026-05-19T20:09:48.412113Z",
"shell.execute_reply": "2026-05-19T20:09:48.411769Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Info in : png file df016_ring.png has been created\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Saved figure to df016_ring.png\n"
]
}
],
"source": [
"ring_h = d1.Define(\"rInFig\", \"r > .5 && r < 1 && x*y < 0\")\\\n",
" .Define(\"yFig\", \"y[rInFig]\")\\\n",
" .Define(\"xFig\", \"x[rInFig]\")\\\n",
" .Histo2D((\"fig\", \"Two quarters of a ring\", 64, -1.1, 1.1, 64, -1.1, 1.1), \"xFig\", \"yFig\")\n",
"\n",
"cring = ROOT.TCanvas()\n",
"ring_h.Draw(\"Colz\")\n",
"cring.SaveAs(\"df016_ring.png\")\n",
"\n",
"print(\"Saved figure to df016_ring.png\")"
]
},
{
"cell_type": "markdown",
"id": "607d0869",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "9eb13d65",
"metadata": {
"collapsed": false,
"execution": {
"iopub.execute_input": "2026-05-19T20:09:48.413744Z",
"iopub.status.busy": "2026-05-19T20:09:48.413593Z",
"iopub.status.idle": "2026-05-19T20:09:48.592446Z",
"shell.execute_reply": "2026-05-19T20:09:48.591687Z"
}
},
"outputs": [
{
"data": {
"text/html": [
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"\n",
"\n"
],
"text/plain": [
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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",
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