{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da98b36a",
   "metadata": {},
   "source": [
    "# rf510_wsnamedsets\n",
    "Organization and simultaneous fits: working with named parameter sets and parameter\n",
    "snapshots in workspaces\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Wouter Verkerke  \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 08:32 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b3f25a80",
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    "execution": {
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   "source": [
    "%%cpp -d\n",
    "#include \"RooRealVar.h\"\n",
    "#include \"RooDataSet.h\"\n",
    "#include \"RooGaussian.h\"\n",
    "#include \"RooChebychev.h\"\n",
    "#include \"RooAddPdf.h\"\n",
    "#include \"RooWorkspace.h\"\n",
    "#include \"RooPlot.h\"\n",
    "#include \"TCanvas.h\"\n",
    "#include \"TAxis.h\"\n",
    "#include \"TFile.h\"\n",
    "#include \"TH1.h\"\n",
    "\n",
    "using namespace RooFit;\n",
    "\n",
    "void fillWorkspace(RooWorkspace &w);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1714f882",
   "metadata": {},
   "source": [
    " Definition of a helper function: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "98608349",
   "metadata": {
    "collapsed": false,
    "execution": {
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     "shell.execute_reply": "2026-05-19T20:32:32.555031Z"
    }
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   "outputs": [],
   "source": [
    "%%cpp -d\n",
    "void fillWorkspace(RooWorkspace &w)\n",
    "{\n",
    "   // C r e a t e   m o d e l\n",
    "   // -----------------------\n",
    "\n",
    "   // Declare observable x\n",
    "   RooRealVar x(\"x\", \"x\", 0, 10);\n",
    "\n",
    "   // Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters\n",
    "   RooRealVar mean(\"mean\", \"mean of gaussians\", 5, 0, 10);\n",
    "   RooRealVar sigma1(\"sigma1\", \"width of gaussians\", 0.5);\n",
    "   RooRealVar sigma2(\"sigma2\", \"width of gaussians\", 1);\n",
    "\n",
    "   RooGaussian sig1(\"sig1\", \"Signal component 1\", x, mean, sigma1);\n",
    "   RooGaussian sig2(\"sig2\", \"Signal component 2\", x, mean, sigma2);\n",
    "\n",
    "   // Build Chebychev polynomial pdf\n",
    "   RooRealVar a0(\"a0\", \"a0\", 0.5, 0., 1.);\n",
    "   RooRealVar a1(\"a1\", \"a1\", 0.2, 0., 1.);\n",
    "   RooChebychev bkg(\"bkg\", \"Background\", x, RooArgSet(a0, a1));\n",
    "\n",
    "   // Sum the signal components into a composite signal pdf\n",
    "   RooRealVar sig1frac(\"sig1frac\", \"fraction of component 1 in signal\", 0.8, 0., 1.);\n",
    "   RooAddPdf sig(\"sig\", \"Signal\", RooArgList(sig1, sig2), sig1frac);\n",
    "\n",
    "   // Sum the composite signal and background\n",
    "   RooRealVar bkgfrac(\"bkgfrac\", \"fraction of background\", 0.5, 0., 1.);\n",
    "   RooAddPdf model(\"model\", \"g1+g2+a\", RooArgList(bkg, sig), bkgfrac);\n",
    "\n",
    "   // Import model into pdf\n",
    "   w.import(model);\n",
    "\n",
    "   // E n c o d e   d e f i n i t i o n   o f   p a r a m e t e r s   i n   w o r k s p a c e\n",
    "   // ---------------------------------------------------------------------------------------\n",
    "\n",
    "   // Define named sets \"parameters\" and \"observables\", which list which variables should be considered\n",
    "   // parameters and observables by the users convention\n",
    "   //\n",
    "   // Variables appearing in sets _must_ live in the workspace already, or the autoImport flag\n",
    "   // of defineSet must be set to import them on the fly. Named sets contain only references\n",
    "   // to the original variables, therefore the value of observables in named sets already\n",
    "   // reflect their 'current' value\n",
    "   std::unique_ptr<RooArgSet> params{model.getParameters(x)};\n",
    "   w.defineSet(\"parameters\", *params);\n",
    "   w.defineSet(\"observables\", x);\n",
    "\n",
    "   // E n c o d e   r e f e r e n c e   v a l u e   f o r   p a r a m e t e r s   i n   w o r k s p a c e\n",
    "   // ---------------------------------------------------------------------------------------------------\n",
    "\n",
    "   // Define a parameter 'snapshot' in the pdf\n",
    "   // Unlike a named set, a parameter snapshot stores an independent set of values for\n",
    "   // a given set of variables in the workspace. The values can be stored and reloaded\n",
    "   // into the workspace variable objects using the loadSnapshot() and saveSnapshot()\n",
    "   // methods. A snapshot saves the value of each variable, any errors that are stored\n",
    "   // with it as well as the 'Constant' flag that is used in fits to determine if a\n",
    "   // parameter is kept fixed or not.\n",
    "\n",
    "   // Do a dummy fit to a (supposedly) reference dataset here and store the results\n",
    "   // of that fit into a snapshot\n",
    "   std::unique_ptr<RooDataSet> refData{model.generate(x, 10000)};\n",
    "   model.fitTo(*refData, PrintLevel(-1));\n",
    "\n",
    "   // The true flag imports the values of the objects in (*params) into the workspace\n",
    "   // If not set, the present values of the workspace parameters objects are stored\n",
    "   w.saveSnapshot(\"reference_fit\", *params, true);\n",
    "\n",
    "   // Make another fit with the signal component forced to zero\n",
    "   // and save those parameters too\n",
    "\n",
    "   bkgfrac.setVal(1);\n",
    "   bkgfrac.setConstant(true);\n",
    "   bkgfrac.removeError();\n",
    "   model.fitTo(*refData, PrintLevel(-1));\n",
    "\n",
    "   w.saveSnapshot(\"reference_fit_bkgonly\", *params, true);\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81948562",
   "metadata": {},
   "source": [
    "Create model and dataset\n",
    "-----------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "240bd80a",
   "metadata": {
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    "execution": {
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     "shell.execute_reply": "2026-05-19T20:32:33.071153Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[#0] WARNING:InputArguments -- The parameter 'sigma1' with range [-inf, inf] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range.\n",
      "[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-inf, inf] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::model\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooChebychev::bkg\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::x\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a0\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a1\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::bkgfrac\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::sig\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig1\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::mean\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma1\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sig1frac\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig2\n",
      "[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma2\n",
      "[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) 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 934.644 μs\n",
      "[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level\n",
      "[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only\n",
      "[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data\n",
      "[#1] INFO:Fitting -- Creation of NLL object took 181.441 μs\n",
      "[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level\n",
      "[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only\n",
      "[#0] ERROR:Minimization -- RooMinimizer::calculateHessErrors() Error when calculating Hessian\n"
     ]
    }
   ],
   "source": [
    "RooWorkspace *w = new RooWorkspace(\"w\");\n",
    "fillWorkspace(*w);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53f444f6",
   "metadata": {},
   "source": [
    "Exploit convention encoded in named set \"parameters\" and \"observables\"\n",
    "to use workspace contents w/o need for introspected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "63193497",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:32:33.080632Z",
     "iopub.status.busy": "2026-05-19T20:32:33.080486Z",
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     "shell.execute_reply": "2026-05-19T20:32:33.285210Z"
    }
   },
   "outputs": [],
   "source": [
    "RooAbsPdf *model = w->pdf(\"model\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf2c837",
   "metadata": {},
   "source": [
    "Generate data from pdf in given observables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f48e5dff",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:32:33.288025Z",
     "iopub.status.busy": "2026-05-19T20:32:33.287903Z",
     "iopub.status.idle": "2026-05-19T20:32:33.496454Z",
     "shell.execute_reply": "2026-05-19T20:32:33.495842Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "input_line_71:2:2: warning: 'data' shadows a declaration with the same name in the 'std' namespace; use '::data' to reference this declaration\n",
      " std::unique_ptr<RooDataSet> data{model->generate(*w->set(\"observables\"), 1000)};\n",
      " ^\n"
     ]
    }
   ],
   "source": [
    "std::unique_ptr<RooDataSet> data{model->generate(*w->set(\"observables\"), 1000)};"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "738a3125",
   "metadata": {},
   "source": [
    "Fit model to data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3946b05b",
   "metadata": {
    "collapsed": false,
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     "shell.execute_reply": "2026-05-19T20:32:33.706459Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "input_line_72:2:16: error: reference to 'data' is ambiguous\n",
      " model->fitTo(*data, PrintLevel(-1));\n",
      "               ^\n",
      "input_line_71:2:30: note: candidate found by name lookup is 'data'\n",
      " std::unique_ptr<RooDataSet> data{model->generate(*w->set(\"observables\"), 1000)};\n",
      "                             ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:344:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(initializer_list<_Tp> __il) noexcept\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:312:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(_Container& __cont) noexcept(noexcept(__cont.data()))\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:323:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(const _Container& __cont) noexcept(noexcept(__cont.data()))\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:334:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(_Tp (&__array)[_Nm]) noexcept\n",
      "    ^\n"
     ]
    }
   ],
   "source": [
    "model->fitTo(*data, PrintLevel(-1));"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ee413f0",
   "metadata": {},
   "source": [
    "Plot fitted model and data on frame of first (only) observable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "821f6c60",
   "metadata": {
    "collapsed": false,
    "execution": {
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     "iopub.status.busy": "2026-05-19T20:32:33.708751Z",
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     "shell.execute_reply": "2026-05-19T20:32:33.917348Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "input_line_73:3:1: error: reference to 'data' is ambiguous\n",
      "data->plotOn(frame);\n",
      "^\n",
      "input_line_71:2:30: note: candidate found by name lookup is 'data'\n",
      " std::unique_ptr<RooDataSet> data{model->generate(*w->set(\"observables\"), 1000)};\n",
      "                             ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:344:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(initializer_list<_Tp> __il) noexcept\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:312:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(_Container& __cont) noexcept(noexcept(__cont.data()))\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:323:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(const _Container& __cont) noexcept(noexcept(__cont.data()))\n",
      "    ^\n",
      "/usr/lib/gcc/x86_64-redhat-linux/14/../../../../include/c++/14/bits/range_access.h:334:5: note: candidate found by name lookup is 'std::data'\n",
      "    data(_Tp (&__array)[_Nm]) noexcept\n",
      "    ^\n"
     ]
    }
   ],
   "source": [
    "RooPlot *frame = ((RooRealVar *)w->set(\"observables\")->first())->frame();\n",
    "data->plotOn(frame);\n",
    "model->plotOn(frame);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60df2e03",
   "metadata": {},
   "source": [
    "Overlay plot with model with reference parameters as stored in snapshots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b6d74037",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:32:33.919454Z",
     "iopub.status.busy": "2026-05-19T20:32:33.919330Z",
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     "shell.execute_reply": "2026-05-19T20:32:34.127837Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "input_line_74:3:32: error: cannot take the address of an rvalue of type 'EColor'\n",
      "model->plotOn(frame, LineColor(kRed));\n",
      "                               ^~~~\n",
      "Error while creating dynamic expression for:\n",
      "  model->plotOn(frame, LineColor(kRed))\n",
      "input_line_74:5:32: error: cannot take the address of an rvalue of type 'EColor'\n",
      "model->plotOn(frame, LineColor(kRed), LineStyle(kDashed));\n",
      "                               ^~~~\n",
      "Error while creating dynamic expression for:\n",
      "  model->plotOn(frame, LineColor(kRed), LineStyle(kDashed))\n"
     ]
    }
   ],
   "source": [
    "w->loadSnapshot(\"reference_fit\");\n",
    "model->plotOn(frame, LineColor(kRed));\n",
    "w->loadSnapshot(\"reference_fit_bkgonly\");\n",
    "model->plotOn(frame, LineColor(kRed), LineStyle(kDashed));"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49878346",
   "metadata": {},
   "source": [
    "Draw the frame on the canvas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3249ccd2",
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     "shell.execute_reply": "2026-05-19T20:32:34.476587Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IncrementalExecutor::executeFunction: symbol '_ZN5cling7runtime8internal9EvaluateTIvEET_PNS1_15DynamicExprInfoEPN5clang11DeclContextE' unresolved while linking [cling interface function]!\n",
      "You are probably missing the definition of void cling::runtime::internal::EvaluateT<void>(cling::runtime::internal::DynamicExprInfo*, clang::DeclContext*)\n",
      "Maybe you need to load the corresponding shared library?\n"
     ]
    }
   ],
   "source": [
    "new TCanvas(\"rf510_wsnamedsets\", \"rf503_wsnamedsets\", 600, 600);\n",
    "gPad->SetLeftMargin(0.15);\n",
    "frame->GetYaxis()->SetTitleOffset(1.4);\n",
    "frame->Draw();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "306ffb9c",
   "metadata": {},
   "source": [
    "Print workspace contents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c5b2108f",
   "metadata": {
    "collapsed": false,
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     "shell.execute_reply": "2026-05-19T20:32:34.686727Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RooWorkspace(w) w contents\n",
      "\n",
      "variables\n",
      "---------\n",
      "(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2,x)\n",
      "\n",
      "p.d.f.s\n",
      "-------\n",
      "RooChebychev::bkg[ x=x coefList=(a0,a1) ] = 0.8\n",
      "RooAddPdf::model[ bkgfrac * bkg + [%] * sig ] = 0.9/1\n",
      "RooAddPdf::sig[ sig1frac * sig1 + [%] * sig2 ] = 1/1\n",
      "RooGaussian::sig1[ x=x mean=mean sigma=sigma1 ] = 1\n",
      "RooGaussian::sig2[ x=x mean=mean sigma=sigma2 ] = 1\n",
      "\n",
      "parameter snapshots\n",
      "-------------------\n",
      "reference_fit = (a0=0.500613 +/- 0.023199,a1=0.160315 +/- 0.0373121,bkgfrac=0.504699 +/- 0.0113933,mean=5.01883 +/- 0.0101222,sigma1=0.5[C],sig1frac=0.8179 +/- 0.0374037,sigma2=1[C])\n",
      "reference_fit_bkgonly = (a0=0.474264 +/- 0,a1=6.8252e-12 +/- 0,bkgfrac=1[C],mean=5.01883 +/- 0,sigma1=0.5[C],sig1frac=0.8179 +/- 0,sigma2=1[C])\n",
      "\n",
      "named sets\n",
      "----------\n",
      "observables:(x)\n",
      "parameters:(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "w->Print();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cb62ec4",
   "metadata": {},
   "source": [
    "Workspace will remain in memory after macro finishes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "079640dc",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:32:34.688805Z",
     "iopub.status.busy": "2026-05-19T20:32:34.688689Z",
     "iopub.status.idle": "2026-05-19T20:32:34.896468Z",
     "shell.execute_reply": "2026-05-19T20:32:34.896010Z"
    }
   },
   "outputs": [],
   "source": [
    "gDirectory->Add(w);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4985df86",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d6514c74",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:32:34.898788Z",
     "iopub.status.busy": "2026-05-19T20:32:34.898672Z",
     "iopub.status.idle": "2026-05-19T20:32:35.129810Z",
     "shell.execute_reply": "2026-05-19T20:32:35.129213Z"
    }
   },
   "outputs": [],
   "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
}