{ "cells": [ { "cell_type": "markdown", "id": "6c9f7944", "metadata": {}, "source": [ "# rf404_categories\n", "Data and categories: working with ROOT.RooCategory objects to describe discrete variables\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 08:31 PM." ] }, { "cell_type": "code", "execution_count": 1, "id": "55cfc809", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:43.840667Z", "iopub.status.busy": "2026-05-19T20:31:43.840524Z", "iopub.status.idle": "2026-05-19T20:31:44.828458Z", "shell.execute_reply": "2026-05-19T20:31:44.827784Z" } }, "outputs": [], "source": [ "import ROOT" ] }, { "cell_type": "markdown", "id": "70324421", "metadata": {}, "source": [ "Construct a category with labels\n", "--------------------------------------------" ] }, { "cell_type": "markdown", "id": "f7069135", "metadata": {}, "source": [ "Define a category with labels only" ] }, { "cell_type": "code", "execution_count": 2, "id": "f2918d04", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:44.830587Z", "iopub.status.busy": "2026-05-19T20:31:44.830446Z", "iopub.status.idle": "2026-05-19T20:31:45.001242Z", "shell.execute_reply": "2026-05-19T20:31:44.995412Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "RooCategory::tagCat = Lepton(idx = 0)\n", "\n" ] } ], "source": [ "tagCat = ROOT.RooCategory(\"tagCat\", \"Tagging category\")\n", "tagCat.defineType(\"Lepton\")\n", "tagCat.defineType(\"Kaon\")\n", "tagCat.defineType(\"NetTagger-1\")\n", "tagCat.defineType(\"NetTagger-2\")\n", "tagCat.Print()" ] }, { "cell_type": "markdown", "id": "c8964218", "metadata": {}, "source": [ "Construct a category with labels and indices\n", "------------------------------------------------" ] }, { "cell_type": "markdown", "id": "8a35504e", "metadata": {}, "source": [ "Define a category with explicitly numbered states" ] }, { "cell_type": "code", "execution_count": 3, "id": "e8eb426e", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.002966Z", "iopub.status.busy": "2026-05-19T20:31:45.002838Z", "iopub.status.idle": "2026-05-19T20:31:45.111854Z", "shell.execute_reply": "2026-05-19T20:31:45.111088Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "RooCategory::b0flav = B0(idx = -1)\n", "\n" ] } ], "source": [ "b0flav = ROOT.RooCategory(\"b0flav\", \"B0 flavour eigenstate\", {\"B0\": -1, \"B0bar\": 1})\n", "b0flav.Print()" ] }, { "cell_type": "markdown", "id": "03a4722d", "metadata": {}, "source": [ "Generate dummy data for tabulation demo\n", "------------------------------------------------" ] }, { "cell_type": "markdown", "id": "b46e1de7", "metadata": {}, "source": [ "Generate a dummy dataset" ] }, { "cell_type": "code", "execution_count": 4, "id": "c0ed185f", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.113430Z", "iopub.status.busy": "2026-05-19T20:31:45.113307Z", "iopub.status.idle": "2026-05-19T20:31:45.303262Z", "shell.execute_reply": "2026-05-19T20:31:45.302464Z" } }, "outputs": [], "source": [ "x = ROOT.RooRealVar(\"x\", \"x\", 0, 10)\n", "data = ROOT.RooPolynomial(\"p\", \"p\", x).generate({x, b0flav, tagCat}, 10000)" ] }, { "cell_type": "markdown", "id": "24f67e5c", "metadata": {}, "source": [ "Print tables of category contents of datasets\n", "--------------------------------------------------" ] }, { "cell_type": "markdown", "id": "eae32f64", "metadata": {}, "source": [ "Tables are equivalent of plots for categories" ] }, { "cell_type": "code", "execution_count": 5, "id": "269d12c9", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.305126Z", "iopub.status.busy": "2026-05-19T20:31:45.304995Z", "iopub.status.idle": "2026-05-19T20:31:45.419678Z", "shell.execute_reply": "2026-05-19T20:31:45.418904Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Roo1DTable::b0flav = (B0=5040,B0bar=4960)\n", "\n", " Table b0flav : pData\n", " +-------+------+\n", " | B0 | 5040 |\n", " | B0bar | 4960 |\n", " +-------+------+\n", "\n" ] } ], "source": [ "btable = data.table(b0flav)\n", "btable.Print()\n", "btable.Print(\"v\")" ] }, { "cell_type": "markdown", "id": "0c547e9b", "metadata": {}, "source": [ "Create table for subset of events matching cut expression" ] }, { "cell_type": "code", "execution_count": 6, "id": "0e9837f6", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.421217Z", "iopub.status.busy": "2026-05-19T20:31:45.421092Z", "iopub.status.idle": "2026-05-19T20:31:45.558043Z", "shell.execute_reply": "2026-05-19T20:31:45.557276Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Roo1DTable::tagCat = (Lepton=487,Kaon=433,NetTagger-1=439,NetTagger-2=406)\n", "\n", " Table tagCat : pData(x>8.23)\n", " +-------------+-----+\n", " | Lepton | 487 |\n", " | Kaon | 433 |\n", " | NetTagger-1 | 439 |\n", " | NetTagger-2 | 406 |\n", " +-------------+-----+\n", "\n" ] } ], "source": [ "ttable = data.table(tagCat, \"x>8.23\")\n", "ttable.Print()\n", "ttable.Print(\"v\")" ] }, { "cell_type": "markdown", "id": "fcc3be85", "metadata": {}, "source": [ "Create table for all (tagCat x b0flav) state combinations" ] }, { "cell_type": "code", "execution_count": 7, "id": "24ff1990", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.559594Z", "iopub.status.busy": "2026-05-19T20:31:45.559462Z", "iopub.status.idle": "2026-05-19T20:31:45.676301Z", "shell.execute_reply": "2026-05-19T20:31:45.675579Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " Table (tagCat x b0flav) : pData\n", " +---------------------+------+\n", " | {Lepton;B0} | 1281 |\n", " | {Kaon;B0} | 1253 |\n", " | {NetTagger-1;B0} | 1234 |\n", " | {NetTagger-2;B0} | 1272 |\n", " | {Lepton;B0bar} | 1269 |\n", " | {Kaon;B0bar} | 1255 |\n", " | {NetTagger-1;B0bar} | 1219 |\n", " | {NetTagger-2;B0bar} | 1217 |\n", " +---------------------+------+\n", "\n" ] } ], "source": [ "bttable = data.table({tagCat, b0flav})\n", "bttable.Print(\"v\")" ] }, { "cell_type": "markdown", "id": "0dd615b8", "metadata": {}, "source": [ "Retrieve number of events from table\n", "Number can be non-integer if source dataset has weighed events" ] }, { "cell_type": "code", "execution_count": 8, "id": "5b176704", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.680900Z", "iopub.status.busy": "2026-05-19T20:31:45.680770Z", "iopub.status.idle": "2026-05-19T20:31:45.788984Z", "shell.execute_reply": "2026-05-19T20:31:45.788362Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of events with B0 flavor is 5040.0\n" ] } ], "source": [ "nb0 = btable.get(\"B0\")\n", "print(\"Number of events with B0 flavor is \", nb0)" ] }, { "cell_type": "markdown", "id": "b4042084", "metadata": {}, "source": [ "Retrieve fraction of events with \"Lepton\" tag" ] }, { "cell_type": "code", "execution_count": 9, "id": "fd1cd440", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.793542Z", "iopub.status.busy": "2026-05-19T20:31:45.793414Z", "iopub.status.idle": "2026-05-19T20:31:45.901638Z", "shell.execute_reply": "2026-05-19T20:31:45.900924Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fraction of events tagged with Lepton tag is 0.27592067988668556\n" ] } ], "source": [ "fracLep = ttable.getFrac(\"Lepton\")\n", "print(\"Fraction of events tagged with Lepton tag is \", fracLep)" ] }, { "cell_type": "markdown", "id": "3d462ff0", "metadata": {}, "source": [ "Defining ranges for plotting, fitting on categories\n", "------------------------------------------------------------------------------------------------------" ] }, { "cell_type": "markdown", "id": "c09fff5a", "metadata": {}, "source": [ "Define named range as comma separated list of labels" ] }, { "cell_type": "code", "execution_count": 10, "id": "1cd789a8", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:45.903391Z", "iopub.status.busy": "2026-05-19T20:31:45.903264Z", "iopub.status.idle": "2026-05-19T20:31:46.010433Z", "shell.execute_reply": "2026-05-19T20:31:46.010085Z" } }, "outputs": [], "source": [ "tagCat.setRange(\"good\", \"Lepton,Kaon\")" ] }, { "cell_type": "markdown", "id": "d165e657", "metadata": {}, "source": [ "Or add state names one by one" ] }, { "cell_type": "code", "execution_count": 11, "id": "ec592d82", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:46.012407Z", "iopub.status.busy": "2026-05-19T20:31:46.012288Z", "iopub.status.idle": "2026-05-19T20:31:46.119566Z", "shell.execute_reply": "2026-05-19T20:31:46.119139Z" } }, "outputs": [], "source": [ "tagCat.addToRange(\"soso\", \"NetTagger-1\")\n", "tagCat.addToRange(\"soso\", \"NetTagger-2\")" ] }, { "cell_type": "markdown", "id": "05712932", "metadata": {}, "source": [ "Use category range in dataset reduction specification" ] }, { "cell_type": "code", "execution_count": 12, "id": "ed751899", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:31:46.121219Z", "iopub.status.busy": "2026-05-19T20:31:46.121103Z", "iopub.status.idle": "2026-05-19T20:31:46.254715Z", "shell.execute_reply": "2026-05-19T20:31:46.254285Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " Table tagCat : pData\n", " +-------------+------+\n", " | Lepton | 2550 |\n", " | Kaon | 2508 |\n", " | NetTagger-1 | 0 |\n", " | NetTagger-2 | 0 |\n", " +-------------+------+\n", "\n" ] } ], "source": [ "goodData = data.reduce(CutRange=\"good\")\n", "goodData.table(tagCat).Print(\"v\")" ] } ], "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 }