{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1c8492ed",
   "metadata": {},
   "source": [
    "# tmva002_RDataFrameAsTensor\n",
    "This tutorial shows how the content of an RDataFrame can be converted to an\n",
    "RTensor object.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Stefan Wunsch  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:22 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "80c6bf3e",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:22:30.570947Z",
     "iopub.status.busy": "2026-05-19T20:22:30.570824Z",
     "iopub.status.idle": "2026-05-19T20:22:30.891197Z",
     "shell.execute_reply": "2026-05-19T20:22:30.890539Z"
    }
   },
   "outputs": [],
   "source": [
    "using namespace TMVA::Experimental;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af21f3d5",
   "metadata": {},
   "source": [
    "Creation of an RDataFrame with five entries filled with ascending numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "80156dcc",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:22:30.892929Z",
     "iopub.status.busy": "2026-05-19T20:22:30.892813Z",
     "iopub.status.idle": "2026-05-19T20:22:31.097059Z",
     "shell.execute_reply": "2026-05-19T20:22:31.096389Z"
    }
   },
   "outputs": [],
   "source": [
    "ROOT::RDataFrame df(5);\n",
    "auto df2 = df.Define(\"x\", \"1.f*rdfentry_\").Define(\"y\", \"-1.f*rdfentry_\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ccb23b1",
   "metadata": {},
   "source": [
    "Convert content of columns to an RTensor object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "210144bc",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:22:31.098716Z",
     "iopub.status.busy": "2026-05-19T20:22:31.098580Z",
     "iopub.status.idle": "2026-05-19T20:22:32.469614Z",
     "shell.execute_reply": "2026-05-19T20:22:32.469034Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RTensor from an RDataFrame:\n",
      "{ { 0, -0 } { 1, -1 } { 2, -2 } { 3, -3 } { 4, -4 } }\n",
      "\n"
     ]
    }
   ],
   "source": [
    "auto x = AsTensor<float>(df2);\n",
    "\n",
    "std::cout << \"RTensor from an RDataFrame:\\n\" << x << \"\\n\\n\";"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a7d706a",
   "metadata": {},
   "source": [
    "The utility also supports reading only a part of the RDataFrame and different\n",
    "memory layouts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c5e7487d",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:22:32.471475Z",
     "iopub.status.busy": "2026-05-19T20:22:32.471357Z",
     "iopub.status.idle": "2026-05-19T20:22:32.716766Z",
     "shell.execute_reply": "2026-05-19T20:22:32.716251Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RTensor from a single column of the RDataFrame:\n",
      "{ { 0 } { 1 } { 2 } { 3 } { 4 } }\n",
      "\n"
     ]
    }
   ],
   "source": [
    "auto x2 = AsTensor<float>(df2, {\"x\"}, MemoryLayout::ColumnMajor);\n",
    "\n",
    "std::cout << \"RTensor from a single column of the RDataFrame:\\n\" << x2 << \"\\n\\n\";"
   ]
  }
 ],
 "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
}