{ "cells": [ { "cell_type": "markdown", "id": "e12b4b19", "metadata": {}, "source": [ "# rf108_plotbinning\n", "Basic functionality: plotting unbinned data with alternate and variable binnings\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 08:29 PM." ] }, { "cell_type": "code", "execution_count": 1, "id": "f9c7a7ff", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:14.235239Z", "iopub.status.busy": "2026-05-19T20:29:14.235127Z", "iopub.status.idle": "2026-05-19T20:29:15.210182Z", "shell.execute_reply": "2026-05-19T20:29:15.209519Z" } }, "outputs": [], "source": [ "import ROOT" ] }, { "cell_type": "markdown", "id": "7cf4b972", "metadata": {}, "source": [ "Set up model\n", "---------------------" ] }, { "cell_type": "markdown", "id": "d1391b1c", "metadata": {}, "source": [ "Build a B decay pdf with mixing" ] }, { "cell_type": "code", "execution_count": 2, "id": "b9084a7f", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.219281Z", "iopub.status.busy": "2026-05-19T20:29:15.219145Z", "iopub.status.idle": "2026-05-19T20:29:15.391616Z", "shell.execute_reply": "2026-05-19T20:29:15.391021Z" } }, "outputs": [], "source": [ "dt = ROOT.RooRealVar(\"dt\", \"dt\", -20, 20)\n", "dm = ROOT.RooRealVar(\"dm\", \"dm\", 0.472)\n", "tau = ROOT.RooRealVar(\"tau\", \"tau\", 1.547)\n", "w = ROOT.RooRealVar(\"w\", \"mistag rate\", 0.1)\n", "dw = ROOT.RooRealVar(\"dw\", \"delta mistag rate\", 0.0)\n", "\n", "mixState = ROOT.RooCategory(\"mixState\", \"B0/B0bar mixing state\", {\"mixed\": -1, \"unmixed\": 1})\n", "tagFlav = ROOT.RooCategory(\"tagFlav\", \"Flavour of the tagged B0\", {\"B0\": 1, \"B0bar\": -1})" ] }, { "cell_type": "markdown", "id": "e43b9402", "metadata": {}, "source": [ "Build a gaussian resolution model" ] }, { "cell_type": "code", "execution_count": 3, "id": "07a8c9bd", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.393601Z", "iopub.status.busy": "2026-05-19T20:29:15.393479Z", "iopub.status.idle": "2026-05-19T20:29:15.515391Z", "shell.execute_reply": "2026-05-19T20:29:15.514771Z" } }, "outputs": [], "source": [ "dterr = ROOT.RooRealVar(\"dterr\", \"dterr\", 0.1, 1.0)\n", "bias1 = ROOT.RooRealVar(\"bias1\", \"bias1\", 0)\n", "sigma1 = ROOT.RooRealVar(\"sigma1\", \"sigma1\", 0.1)\n", "gm1 = ROOT.RooGaussModel(\"gm1\", \"gauss model 1\", dt, bias1, sigma1)" ] }, { "cell_type": "markdown", "id": "5b05a58d", "metadata": {}, "source": [ "Construct Bdecay (x) gauss" ] }, { "cell_type": "code", "execution_count": 4, "id": "07571f07", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.517148Z", "iopub.status.busy": "2026-05-19T20:29:15.517028Z", "iopub.status.idle": "2026-05-19T20:29:15.648146Z", "shell.execute_reply": "2026-05-19T20:29:15.647491Z" } }, "outputs": [], "source": [ "bmix = ROOT.RooBMixDecay(\"bmix\", \"decay\", dt, mixState, tagFlav, tau, dm, w, dw, gm1, type=\"DoubleSided\")" ] }, { "cell_type": "markdown", "id": "86df2d5e", "metadata": {}, "source": [ "Sample data from model\n", "--------------------------------------------" ] }, { "cell_type": "markdown", "id": "a9aa1f3d", "metadata": {}, "source": [ "Sample 2000 events in (dt,mixState,tagFlav) from bmix" ] }, { "cell_type": "code", "execution_count": 5, "id": "b77ea4cd", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.650042Z", "iopub.status.busy": "2026-05-19T20:29:15.649903Z", "iopub.status.idle": "2026-05-19T20:29:15.802762Z", "shell.execute_reply": "2026-05-19T20:29:15.802082Z" } }, "outputs": [], "source": [ "data = bmix.generate({dt, mixState, tagFlav}, 2000)" ] }, { "cell_type": "markdown", "id": "f8c3e755", "metadata": {}, "source": [ "Show dt distribution with custom binning\n", "-------------------------------------------------------------------------------" ] }, { "cell_type": "markdown", "id": "b8934a07", "metadata": {}, "source": [ "Make plot of dt distribution of data in range (-15,15) with fine binning\n", "for dt>0 and coarse binning for dt<0" ] }, { "cell_type": "markdown", "id": "b6dd541c", "metadata": {}, "source": [ "Create binning object with range (-15,15)" ] }, { "cell_type": "code", "execution_count": 6, "id": "081bca98", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.804470Z", "iopub.status.busy": "2026-05-19T20:29:15.804352Z", "iopub.status.idle": "2026-05-19T20:29:15.917451Z", "shell.execute_reply": "2026-05-19T20:29:15.916797Z" } }, "outputs": [], "source": [ "tbins = ROOT.RooBinning(-15, 15)" ] }, { "cell_type": "markdown", "id": "f46bc0d9", "metadata": {}, "source": [ "Add 60 bins with uniform spacing in range (-15,0)" ] }, { "cell_type": "code", "execution_count": 7, "id": "85164bed", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:15.919286Z", "iopub.status.busy": "2026-05-19T20:29:15.919076Z", "iopub.status.idle": "2026-05-19T20:29:16.026444Z", "shell.execute_reply": "2026-05-19T20:29:16.025776Z" } }, "outputs": [], "source": [ "tbins.addUniform(60, -15, 0)" ] }, { "cell_type": "markdown", "id": "a8868aaf", "metadata": {}, "source": [ "Add 15 bins with uniform spacing in range (0,15)" ] }, { "cell_type": "code", "execution_count": 8, "id": "85ffd2aa", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.028124Z", "iopub.status.busy": "2026-05-19T20:29:16.028006Z", "iopub.status.idle": "2026-05-19T20:29:16.131364Z", "shell.execute_reply": "2026-05-19T20:29:16.130759Z" } }, "outputs": [], "source": [ "tbins.addUniform(15, 0, 15)" ] }, { "cell_type": "markdown", "id": "d5aab88e", "metadata": {}, "source": [ "Make plot with specified binning" ] }, { "cell_type": "code", "execution_count": 9, "id": "235952b6", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.133123Z", "iopub.status.busy": "2026-05-19T20:29:16.133004Z", "iopub.status.idle": "2026-05-19T20:29:16.322933Z", "shell.execute_reply": "2026-05-19T20:29:16.322373Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[#1] INFO:Plotting -- RooAbsReal::plotOn(bmix) plot on dt integrates over variables (mixState,tagFlav)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dtframe = dt.frame(Range=(-15, 15), Title=\"dt distribution with custom binning\")\n", "data.plotOn(dtframe, Binning=tbins)\n", "bmix.plotOn(dtframe)" ] }, { "cell_type": "markdown", "id": "860a6c59", "metadata": {}, "source": [ "NB: Note that bin density for each bin is adjusted to that of default frame binning as shown\n", "in Y axis label (100 bins -. Events/0.4*Xaxis-dim) so that all bins\n", "represent a consistent density distribution" ] }, { "cell_type": "markdown", "id": "42ab4698", "metadata": {}, "source": [ "Show mixstate asymmetry with custom binning\n", "------------------------------------------------------------------------------------" ] }, { "cell_type": "markdown", "id": "c467ae94", "metadata": {}, "source": [ "Make plot of dt distribution of data asymmetry in 'mixState' with\n", "variable binning" ] }, { "cell_type": "markdown", "id": "29ab3974", "metadata": {}, "source": [ "Create binning object with range (-10,10)" ] }, { "cell_type": "code", "execution_count": 10, "id": "d3dd2154", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.324991Z", "iopub.status.busy": "2026-05-19T20:29:16.324870Z", "iopub.status.idle": "2026-05-19T20:29:16.428186Z", "shell.execute_reply": "2026-05-19T20:29:16.427565Z" } }, "outputs": [], "source": [ "abins = ROOT.RooBinning(-10, 10)" ] }, { "cell_type": "markdown", "id": "469addf4", "metadata": {}, "source": [ "Add boundaries at 0, (-1,1), (-2,2), (-3,3), (-4,4) and (-6,6)" ] }, { "cell_type": "code", "execution_count": 11, "id": "8c26b6d1", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.430131Z", "iopub.status.busy": "2026-05-19T20:29:16.430011Z", "iopub.status.idle": "2026-05-19T20:29:16.539620Z", "shell.execute_reply": "2026-05-19T20:29:16.539177Z" } }, "outputs": [], "source": [ "abins.addBoundary(0)\n", "abins.addBoundaryPair(1)\n", "abins.addBoundaryPair(2)\n", "abins.addBoundaryPair(3)\n", "abins.addBoundaryPair(4)\n", "abins.addBoundaryPair(6)" ] }, { "cell_type": "markdown", "id": "d6e0ce96", "metadata": {}, "source": [ "Create plot frame in dt" ] }, { "cell_type": "code", "execution_count": 12, "id": "aff4046f", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.541720Z", "iopub.status.busy": "2026-05-19T20:29:16.541581Z", "iopub.status.idle": "2026-05-19T20:29:16.645172Z", "shell.execute_reply": "2026-05-19T20:29:16.644533Z" } }, "outputs": [], "source": [ "aframe = dt.frame(Range=(-10, 10), Title=\"mixState asymmetry distribution with custom binning\")" ] }, { "cell_type": "markdown", "id": "ee31cfb6", "metadata": {}, "source": [ "Plot mixState asymmetry of data with specified customg binning" ] }, { "cell_type": "code", "execution_count": 13, "id": "02cc4d76", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.646799Z", "iopub.status.busy": "2026-05-19T20:29:16.646680Z", "iopub.status.idle": "2026-05-19T20:29:16.769751Z", "shell.execute_reply": "2026-05-19T20:29:16.768992Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.plotOn(aframe, Asymmetry=mixState, Binning=abins)" ] }, { "cell_type": "markdown", "id": "ead56ede", "metadata": {}, "source": [ "Plot corresponding property of pdf" ] }, { "cell_type": "code", "execution_count": 14, "id": "43f52caf", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.771320Z", "iopub.status.busy": "2026-05-19T20:29:16.771199Z", "iopub.status.idle": "2026-05-19T20:29:16.886201Z", "shell.execute_reply": "2026-05-19T20:29:16.885648Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[#1] INFO:Plotting -- RooAbsReal::plotAsymOn(bmix) plot on dt projects variables (tagFlav)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bmix.plotOn(aframe, Asymmetry=mixState)" ] }, { "cell_type": "markdown", "id": "4ec63ea2", "metadata": {}, "source": [ "Adjust vertical range of plot to sensible values for an asymmetry" ] }, { "cell_type": "code", "execution_count": 15, "id": "5d127876", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.888155Z", "iopub.status.busy": "2026-05-19T20:29:16.888029Z", "iopub.status.idle": "2026-05-19T20:29:16.997668Z", "shell.execute_reply": "2026-05-19T20:29:16.997119Z" } }, "outputs": [], "source": [ "aframe.SetMinimum(-1.1)\n", "aframe.SetMaximum(1.1)" ] }, { "cell_type": "markdown", "id": "97b18ca9", "metadata": {}, "source": [ "NB: For asymmetry distributions no density corrects are needed (and are\n", "thus not applied)" ] }, { "cell_type": "markdown", "id": "00bcc5eb", "metadata": {}, "source": [ "Draw plots on canvas" ] }, { "cell_type": "code", "execution_count": 16, "id": "01a285a2", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:16.999757Z", "iopub.status.busy": "2026-05-19T20:29:16.999633Z", "iopub.status.idle": "2026-05-19T20:29:17.214616Z", "shell.execute_reply": "2026-05-19T20:29:17.214070Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Info in : png file rf108_plotbinning.png has been created\n" ] } ], "source": [ "c = ROOT.TCanvas(\"rf108_plotbinning\", \"rf108_plotbinning\", 800, 400)\n", "c.Divide(2)\n", "c.cd(1)\n", "ROOT.gPad.SetLeftMargin(0.15)\n", "dtframe.GetYaxis().SetTitleOffset(1.6)\n", "dtframe.Draw()\n", "c.cd(2)\n", "ROOT.gPad.SetLeftMargin(0.15)\n", "aframe.GetYaxis().SetTitleOffset(1.6)\n", "aframe.Draw()\n", "\n", "c.SaveAs(\"rf108_plotbinning.png\")" ] }, { "cell_type": "markdown", "id": "6a073cae", "metadata": {}, "source": [ "Draw all canvases " ] }, { "cell_type": "code", "execution_count": 17, "id": "da932ccf", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:29:17.216685Z", "iopub.status.busy": "2026-05-19T20:29:17.216538Z", "iopub.status.idle": "2026-05-19T20:29:17.397093Z", "shell.execute_reply": "2026-05-19T20:29:17.396530Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "
\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "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 }