{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "26a5f0c1",
   "metadata": {},
   "source": [
    "# rf712_lagrangianmorphfit\n",
    "Performing a simple fit with RooLagrangianMorphFunc.\n",
    "a morphing function is setup as a function of three variables and\n",
    "a fit is performed on a pseudo-dataset.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Rahul Balasubramanian  \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 08:35 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5c69dc05",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:10.207040Z",
     "iopub.status.busy": "2026-05-19T20:35:10.206928Z",
     "iopub.status.idle": "2026-05-19T20:35:10.222510Z",
     "shell.execute_reply": "2026-05-19T20:35:10.221980Z"
    }
   },
   "outputs": [],
   "source": [
    "%%cpp -d\n",
    "#include <RooDataHist.h>\n",
    "#include <RooFitResult.h>\n",
    "#include <RooLagrangianMorphFunc.h>\n",
    "#include <RooPlot.h>\n",
    "#include <RooRealVar.h>\n",
    "\n",
    "#include <TAxis.h>\n",
    "#include <TCanvas.h>\n",
    "#include <TH2.h>\n",
    "#include <TStyle.h>\n",
    "\n",
    "using namespace RooFit;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a34c0ee9",
   "metadata": {},
   "source": [
    "Create variables for\n",
    "morphing function\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c6d9e09",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:10.224015Z",
     "iopub.status.busy": "2026-05-19T20:35:10.223899Z",
     "iopub.status.idle": "2026-05-19T20:35:10.577657Z",
     "shell.execute_reply": "2026-05-19T20:35:10.576872Z"
    }
   },
   "outputs": [],
   "source": [
    "std::string observablename = \"pTV\";\n",
    "RooRealVar obsvar(observablename.c_str(), \"observable of pTV\", 10, 600);\n",
    "RooRealVar kSM(\"kSM\", \"sm modifier\", 1.0);\n",
    "RooRealVar cHq3(\"cHq3\", \"EFT modifier\", -10.0, 10.0);\n",
    "cHq3.setAttribute(\"NewPhysics\", true);\n",
    "RooRealVar cHl3(\"cHl3\", \"EFT modifier\", -10.0, 10.0);\n",
    "cHl3.setAttribute(\"NewPhysics\", true);\n",
    "RooRealVar cHDD(\"cHDD\", \"EFT modifier\", -10.0, 10.0);\n",
    "cHDD.setAttribute(\"NewPhysics\", true);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00b00cf0",
   "metadata": {},
   "source": [
    "Inputs needed for config\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a1a3fae0",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:10.579326Z",
     "iopub.status.busy": "2026-05-19T20:35:10.579208Z",
     "iopub.status.idle": "2026-05-19T20:35:10.803149Z",
     "shell.execute_reply": "2026-05-19T20:35:10.802312Z"
    }
   },
   "outputs": [],
   "source": [
    "std::string infilename = std::string(gROOT->GetTutorialDir()) + \"/roofit/roofit/input_histos_rf_lagrangianmorph.root\";\n",
    "std::vector<std::string> samplelist = {\"SM_NPsq0\",        \"cHq3_NPsq1\",     \"cHq3_NPsq2\", \"cHl3_NPsq1\",\n",
    "                                       \"cHl3_NPsq2\",      \"cHDD_NPsq1\",     \"cHDD_NPsq2\", \"cHl3_cHDD_NPsq2\",\n",
    "                                       \"cHq3_cHDD_NPsq2\", \"cHl3_cHq3_NPsq2\"};"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "921deef1",
   "metadata": {},
   "source": [
    "Setup Config\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "60a1c990",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:10.805298Z",
     "iopub.status.busy": "2026-05-19T20:35:10.805177Z",
     "iopub.status.idle": "2026-05-19T20:35:11.136668Z",
     "shell.execute_reply": "2026-05-19T20:35:11.136018Z"
    }
   },
   "outputs": [],
   "source": [
    "RooLagrangianMorphFunc::Config config;\n",
    "config.fileName = infilename;\n",
    "config.observableName = observablename;\n",
    "config.folderNames = samplelist;\n",
    "config.couplings.add(cHq3);\n",
    "config.couplings.add(cHl3);\n",
    "config.couplings.add(cHDD);\n",
    "config.couplings.add(kSM);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b0134ed",
   "metadata": {},
   "source": [
    "Create morphing function\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "72e3ac15",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:11.138803Z",
     "iopub.status.busy": "2026-05-19T20:35:11.138678Z",
     "iopub.status.idle": "2026-05-19T20:35:11.348019Z",
     "shell.execute_reply": "2026-05-19T20:35:11.347367Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[#0] PROGRESS:InputArguments -- initializing physics inputs from file /github/home/ROOT-CI/build/tutorials/roofit/roofit/input_histos_rf_lagrangianmorph.root with object name(s) 'pTV'\n"
     ]
    }
   ],
   "source": [
    "RooLagrangianMorphFunc morphfunc(\"morphfunc\", \"morphed dist. of pTV\", config);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8c99348",
   "metadata": {},
   "source": [
    "Create pseudo data histogram\n",
    "for fit\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c84974cd",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:11.349655Z",
     "iopub.status.busy": "2026-05-19T20:35:11.349524Z",
     "iopub.status.idle": "2026-05-19T20:35:11.559107Z",
     "shell.execute_reply": "2026-05-19T20:35:11.558478Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[#0] PROGRESS:Caching -- creating cache from getCache function for 0x7fa67d14e000\n",
      "[#0] PROGRESS:Caching -- current storage has size 10\n",
      "[#0] PROGRESS:ObjectHandling -- observable: pTV\n",
      "[#0] PROGRESS:ObjectHandling -- binWidth: binWidth_pTV\n",
      "[#1] INFO:DataHandling -- RooDataHist::adjustBinning(pseudo_dh): fit range of variable pTV expanded to nearest bin boundaries: [10,600] --> [0,600]\n"
     ]
    }
   ],
   "source": [
    "morphfunc.setParameter(\"cHq3\", 0.01);\n",
    "morphfunc.setParameter(\"cHl3\", 1.0);\n",
    "morphfunc.setParameter(\"cHDD\", 0.2);\n",
    "\n",
    "auto pseudo_hist = morphfunc.createTH1(\"pseudo_hist\");\n",
    "auto pseudo_dh = new RooDataHist(\"pseudo_dh\", \"pseudo_dh\", RooArgList(obsvar), pseudo_hist);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1d77398",
   "metadata": {},
   "source": [
    "reset parameters to zeros before fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fc936e72",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:11.560875Z",
     "iopub.status.busy": "2026-05-19T20:35:11.560755Z",
     "iopub.status.idle": "2026-05-19T20:35:11.769779Z",
     "shell.execute_reply": "2026-05-19T20:35:11.769059Z"
    }
   },
   "outputs": [],
   "source": [
    "morphfunc.setParameter(\"cHq3\", 0.0);\n",
    "morphfunc.setParameter(\"cHl3\", 0.0);\n",
    "morphfunc.setParameter(\"cHDD\", 0.0);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b312346",
   "metadata": {},
   "source": [
    "error set used as initial step size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a760b019",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:11.771813Z",
     "iopub.status.busy": "2026-05-19T20:35:11.771683Z",
     "iopub.status.idle": "2026-05-19T20:35:11.980723Z",
     "shell.execute_reply": "2026-05-19T20:35:11.979978Z"
    }
   },
   "outputs": [],
   "source": [
    "cHq3.setError(0.1);\n",
    "cHl3.setError(0.1);\n",
    "cHDD.setError(0.1);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08bcbf35",
   "metadata": {},
   "source": [
    "Wrap pdf on morphfunc and\n",
    "fit to data histogram\n",
    "---------------------------------------------\n",
    "wrapper pdf to normalise morphing function to a morphing pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e0b6b8e5",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:11.982542Z",
     "iopub.status.busy": "2026-05-19T20:35:11.982420Z",
     "iopub.status.idle": "2026-05-19T20:35:12.204397Z",
     "shell.execute_reply": "2026-05-19T20:35:12.203735Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[#0] PROGRESS:Caching -- creating cache from getCache function for 0x7fa62e1f58e0\n",
      "[#0] PROGRESS:Caching -- current storage has size 10\n",
      "[#0] PROGRESS:ObjectHandling -- observable: pTV\n",
      "[#0] PROGRESS:ObjectHandling -- binWidth: binWidth_pTV\n",
      "\n",
      "[#1] INFO:Fitting -- RooAbsPdf::fitTo(wrap_pdf_over_wrap_pdf_Int[pTV]) fixing normalization set for coefficient determination to observables in data\n",
      "[#1] INFO:Fitting -- using generic CPU library compiled with no vectorizations\n",
      "[#1] INFO:Fitting -- Creation of NLL object took 7.36155 ms\n",
      "[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_wrap_pdf_over_wrap_pdf_Int[pTV]_pseudo_dh) Summation contains a RooNLLVar, using its error level\n",
      "[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.22238\tcHl3=2.00088\tcHq3=0.00780325\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.0889525, denominator=wrap_pdf_Int[pTV]=4479.59\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.0889525, denominator=wrap_pdf_Int[pTV]=4479.59\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0889525, denominator=wrap_pdf_Int[pTV]=4479.59\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0889525, denominator=wrap_pdf_Int[pTV]=4479.59\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=1.16153\tcHl3=8.6965\tcHq3=0.0408466\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.894368, denominator=wrap_pdf_Int[pTV]=3980.01\n",
      "    ... (remaining 4 messages suppressed)\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.607791\tcHl3=5.23432\tcHq3=0.0213386\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.315769, denominator=wrap_pdf_Int[pTV]=237.773\n",
      "    ... (remaining 16 messages suppressed)\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.330108\tcHl3=2.94627\tcHq3=0.0115846\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.131032, denominator=wrap_pdf_Int[pTV]=2465.37\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.191157\tcHl3=1.72296\tcHq3=0.00670752\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.0801556, denominator=wrap_pdf_Int[pTV]=5193.38\n",
      "     p.d.f value is less than zero, trying to recover @ numerator=wrap_pdf=0.0801556, denominator=wrap_pdf_Int[pTV]=5193.38\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0801556, denominator=wrap_pdf_Int[pTV]=5193.38\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0801556, denominator=wrap_pdf_Int[pTV]=5193.38\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.138238\tcHl3=1.24892\tcHq3=0.00485049\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0688277, denominator=wrap_pdf_Int[pTV]=6538.46\n",
      "\n",
      "RooAbsMinimizerFcn: Minimized function has error status.\n",
      "Returning maximum FCN so far (39620.3) to force MIGRAD to back out of this region. Error log follows.\n",
      "Parameter values: \tcHDD=0.121667\tcHl3=1.24299\tcHq3=0.004269\n",
      "RooFit::Detail::RooNormalizedPdf::wrap_pdf_over_wrap_pdf_Int[pTV][ numerator=wrap_pdf denominator=wrap_pdf_Int[pTV] ]\n",
      "     getLogVal() top-level p.d.f evaluates to NaN @ numerator=wrap_pdf=0.0667251, denominator=wrap_pdf_Int[pTV]=6553.34\n",
      "\n",
      "[#1] INFO:Fitting -- RooAbsPdf::fitTo(wrap_pdf) Calculating sum-of-weights-squared correction matrix for covariance matrix\n"
     ]
    }
   ],
   "source": [
    "RooWrapperPdf model(\"wrap_pdf\", \"wrap_pdf\", morphfunc);\n",
    "auto fitres = model.fitTo(*pseudo_dh, SumW2Error(true), Save(), PrintLevel(-1));\n",
    "auto hcorr = fitres->correlationHist();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1021400",
   "metadata": {},
   "source": [
    "Extract postfit distribution\n",
    "and plot with initial\n",
    "histogram\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b7a2b405",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:12.206226Z",
     "iopub.status.busy": "2026-05-19T20:35:12.206097Z",
     "iopub.status.idle": "2026-05-19T20:35:12.412228Z",
     "shell.execute_reply": "2026-05-19T20:35:12.411891Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[#1] INFO:InputArguments -- RooAbsData::plotOn(pseudo_dh) INFO: dataset has non-integer weights, auto-selecting SumW2 errors instead of Poisson errors\n",
      "[#1] INFO:Plotting -- RooPlot::updateFitRangeNorm: New event count of 7389.24 will supersede previous event count of 7388.38 for normalization of PDF projections\n"
     ]
    }
   ],
   "source": [
    "auto postfit_hist = morphfunc.createTH1(\"morphing_postfit_hist\");\n",
    "RooDataHist postfit_dh(\"morphing_postfit_dh\", \"morphing_postfit_dh\", RooArgList(obsvar), postfit_hist);\n",
    "\n",
    "auto frame0 = obsvar.frame(Title(\"Fitted histogram of p_{T}^{V}\"));\n",
    "postfit_dh.plotOn(frame0, Name(\"postfit_dist\"), DrawOption(\"C\"), LineColor(kBlue), DataError(RooAbsData::None),\n",
    "                  XErrorSize(0));\n",
    "pseudo_dh->plotOn(frame0, Name(\"input\"));"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c2fb079",
   "metadata": {},
   "source": [
    "Draw plots on canvas\n",
    "---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d1f9d560",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:12.418446Z",
     "iopub.status.busy": "2026-05-19T20:35:12.418315Z",
     "iopub.status.idle": "2026-05-19T20:35:12.624322Z",
     "shell.execute_reply": "2026-05-19T20:35:12.623828Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "<div id=\"root_plot_1779222912609\" style=\"width: 800px; height: 400px; position: relative\">\n",
       "</div>\n",
       "\n",
       "</div>\n",
       "<script>\n",
       "   function process_root_plot_1779222912609() {\n",
       "      function execCode(Core) {\n",
       "         Core.settings.HandleKeys = false;\n",
       "         \n",
       "Core.unzipJSON(36109,'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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779222912609', obj, '');\n",
       "});\n",
       "\n",
       "      }\n",
       "      const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
       "            path = 'build/jsroot';\n",
       "      if (typeof JSROOT !== 'undefined')\n",
       "         execCode(JSROOT);\n",
       "      else if (typeof requirejs !== 'undefined') {\n",
       "         servers.forEach((s,i) => { servers[i] = s + path; });\n",
       "         requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'],  execCode);\n",
       "      } else {\n",
       "         const config = document.getElementById('jupyter-config-data');\n",
       "         if (config)\n",
       "            servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
       "         else\n",
       "            servers.shift();\n",
       "         function loadJsroot() {\n",
       "            return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
       "         }\n",
       "         loadJsroot();\n",
       "      }\n",
       "   }\n",
       "   process_root_plot_1779222912609();\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Info in <TCanvas::Print>: png file rf712_lagrangianmorphfit.png has been created\n"
     ]
    }
   ],
   "source": [
    "TCanvas *c1 = new TCanvas(\"fig3\", \"fig3\", 800, 400);\n",
    "c1->Divide(2, 1);\n",
    "\n",
    "c1->cd(1);\n",
    "gPad->SetLeftMargin(0.15);\n",
    "gPad->SetRightMargin(0.05);\n",
    "\n",
    "model.paramOn(frame0, Layout(0.50, 0.75, 0.9), Parameters(config.couplings));\n",
    "frame0->GetXaxis()->SetTitle(\"p_{T}^{V}\");\n",
    "frame0->Draw();\n",
    "\n",
    "c1->cd(2);\n",
    "gPad->SetLeftMargin(0.15);\n",
    "gPad->SetRightMargin(0.15);\n",
    "gStyle->SetPaintTextFormat(\"4.1f\");\n",
    "gStyle->SetOptStat(0);\n",
    "hcorr->SetMarkerSize(3.);\n",
    "hcorr->SetTitle(\"correlation matrix\");\n",
    "hcorr->GetYaxis()->SetTitleOffset(1.4);\n",
    "hcorr->GetYaxis()->SetLabelSize(0.1);\n",
    "hcorr->GetXaxis()->SetLabelSize(0.1);\n",
    "hcorr->GetYaxis()->SetBinLabel(1, \"c_{HDD}\");\n",
    "hcorr->GetYaxis()->SetBinLabel(2, \"c_{Hl^{(3)}}\");\n",
    "hcorr->GetYaxis()->SetBinLabel(3, \"c_{Hq^{(3)}}\");\n",
    "hcorr->GetXaxis()->SetBinLabel(3, \"c_{HDD}\");\n",
    "hcorr->GetXaxis()->SetBinLabel(2, \"c_{Hl^{(3)}}\");\n",
    "hcorr->GetXaxis()->SetBinLabel(1, \"c_{Hq^{(3)}}\");\n",
    "hcorr->Draw(\"colz text\");\n",
    "c1->SaveAs(\"rf712_lagrangianmorphfit.png\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e16a3d7",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "17ce9610",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:35:12.625945Z",
     "iopub.status.busy": "2026-05-19T20:35:12.625824Z",
     "iopub.status.idle": "2026-05-19T20:35:12.841193Z",
     "shell.execute_reply": "2026-05-19T20:35:12.840621Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "<div id=\"root_plot_1779222912742\" style=\"width: 800px; height: 400px; position: relative\">\n",
       "</div>\n",
       "\n",
       "</div>\n",
       "<script>\n",
       "   function process_root_plot_1779222912742() {\n",
       "      function execCode(Core) {\n",
       "         Core.settings.HandleKeys = false;\n",
       "         \n",
       "Core.unzipJSON(36109,'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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779222912742', obj, '');\n",
       "});\n",
       "\n",
       "      }\n",
       "      const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
       "            path = 'build/jsroot';\n",
       "      if (typeof JSROOT !== 'undefined')\n",
       "         execCode(JSROOT);\n",
       "      else if (typeof requirejs !== 'undefined') {\n",
       "         servers.forEach((s,i) => { servers[i] = s + path; });\n",
       "         requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'],  execCode);\n",
       "      } else {\n",
       "         const config = document.getElementById('jupyter-config-data');\n",
       "         if (config)\n",
       "            servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
       "         else\n",
       "            servers.shift();\n",
       "         function loadJsroot() {\n",
       "            return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
       "         }\n",
       "         loadJsroot();\n",
       "      }\n",
       "   }\n",
       "   process_root_plot_1779222912742();\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%jsroot on\n",
    "gROOT->GetListOfCanvases()->Draw()"
   ]
  }
 ],
 "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
}