add notebook and binder environment

cms-opendata-analyses · Jun 13, 2019 · 0673a51 · 0673a51
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diff --git a/.gitignore b/.gitignore
@@ -5,3 +5,4 @@
 *.pyc
 *.root
 *.pdf
+.ipynb*
diff --git a/README.md b/README.md
@@ -20,6 +20,18 @@ git clone git://github.com/cms-opendata-analyses/DimuonSpectrumNanoAODOutreachAn
 
 The analysis code itself is provided in Python and C++. The instructions to run the scripts is shown below:
 
+**Python (notebook):**
+
+The notebook can either be run locally or via [binder](https://mybinder.org/) in the browser. To run locally, use the following command.
+
+```bash
+jupyter notebook
+```
+
+To run via binder, you just have to click the following link and follow the instructions.
+
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/stwunsch/DimuonSpectrumNanoAODOutreachAnalysis/master)
+
 **Python (interactive):**
 
 Note the `-i` flag, which keeps the Python interpreter alive after the end of the script so that the interactive plot can still be explored.

diff --git a/dimuonSpectrum.ipynb b/dimuonSpectrum.ipynb
@@ -0,0 +1,297 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analysis of the di-muon spectrum using data from the CMS detector\n",
+    "\n",
+    "This analysis takes data from the CMS experiment recorded in 2012 during Run B and C and extracts the di-muon spectrum. The di-muon spectrum is computed from the data by calculating the invariant mass of muon pairs with opposite charge. In the resulting plot, you are able to rediscover particle resonances in a wide energy range from the [eta meson](https://en.wikipedia.org/wiki/Eta_meson) at about 548 MeV up to the [Z boson](https://en.wikipedia.org/wiki/W_and_Z_bosons) at about 91 GeV.\n",
+    "\n",
+    "The analysis code opens an interactive plot, which allows to zoom and navigate in the spectrum. Note that the bump at 30 GeV is not a resonance but an effect of the data taking due to the used trigger. The technical description of the dataset can be found in the respective record linked below.\n",
+    "\n",
+    "The result of this analysis can be compare with [an official result of the CMS collaboration using data taken in 2011](https://cds.cern.ch/record/1456510), see the plot below:\n",
+    "\n",
+    "![](http://cds.cern.ch/record/1456510/files/pictures_samples_dimuonSpectrum_40pb-1_mod-combined.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Dataset description\n",
+    "\n",
+    "The dataset consists of the following columns.\n",
+    "\n",
+    "| Column name | Data type | Description |\n",
+    "|-------------|-----------|-------------|\n",
+    "| `nMuon` | `unsigned int` | Number of muons in this event |\n",
+    "| `Muon_pt` | `float[nMuon]` | Transverse momentum of the muons stored as an array of size `nMuon` |\n",
+    "| `Muon_eta` | `float[nMuon]` | Pseudo-rapidity of the muons stored as an array of size `nMuon` |\n",
+    "| `Muon_phi` | `float[nMuon]` | Azimuth of the muons stored as an array of size `nMuon` |\n",
+    "| `Muon_charge` | `int[nMuon]` | Charge of the muons stored as an array of size `nMuon` and either -1 or 1 |\n",
+    "| `Muon_mass` | `float[nMuon]` | Mass of the muons stored as an array of size `nMuon` |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Data-analysis\n",
+    "\n",
+    "The following part of the dataset performs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Enable multi-threading"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ROOT.ROOT.EnableImplicitMT()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create dataframe from NanoAOD files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = ROOT.RDataFrame(\"Events\", \"root://eospublic.cern.ch//eos/opendata/cms/derived-data/AOD2NanoAODOutreachTool/Run2012BC_DoubleMuParked.root\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Select events with exactly two muons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_2mu = df.Filter(\"nMuon == 2\", \"Events with exactly two muons\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Select events with two muons of opposite charge"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_os = df_2mu.Filter(\"Muon_charge[0] != Muon_charge[1]\", \"Muons with opposite charge\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compute invariant mass of the dimuon system\n",
+    "\n",
+    "The following code just-in-time compiles the C++ function to compute the invariant mass, so that the function can be called in the Define node of the ROOT dataframe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ROOT.gInterpreter.Declare(\n",
+    "\"\"\"\n",
+    "using namespace ROOT::VecOps;\n",
+    "float computeInvariantMass(RVec<float>& pt, RVec<float>& eta, RVec<float>& phi, RVec<float>& mass) {\n",
+    "    ROOT::Math::PtEtaPhiMVector m1(pt[0], eta[0], phi[0], mass[0]);\n",
+    "    ROOT::Math::PtEtaPhiMVector m2(pt[1], eta[1], phi[1], mass[1]);\n",
+    "    return (m1 + m2).mass();\n",
+    "}\n",
+    "\"\"\")\n",
+    "df_mass = df_os.Define(\"Dimuon_mass\", \"computeInvariantMass(Muon_pt, Muon_eta, Muon_phi, Muon_mass)\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Book histogram of dimuon mass spectrum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = 30000 # Number of bins in the histogram\n",
+    "low = 0.25 # Lower edge of the histogram\n",
+    "up = 300.0 # Upper edge of the histogram\n",
+    "hist = df_mass.Histo1D(ROOT.RDF.TH1DModel(\"\", \"\", bins, low, up), \"Dimuon_mass\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Request cut-flow report"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "report = df_mass.Report()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create canvas for plotting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ROOT.gStyle.SetOptStat(0)\n",
+    "ROOT.gStyle.SetTextFont(42)\n",
+    "c = ROOT.TCanvas(\"c\", \"\", 800, 700)\n",
+    "c.SetLogx()\n",
+    "c.SetLogy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Draw histogram"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hist.GetXaxis().SetTitle(\"m_{#mu#mu} (GeV)\")\n",
+    "hist.GetXaxis().SetTitleSize(0.04)\n",
+    "hist.GetYaxis().SetTitle(\"N_{Events}\")\n",
+    "hist.GetYaxis().SetTitleSize(0.04)\n",
+    "hist.SetStats(False)\n",
+    "hist.Draw()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Draw labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "label = ROOT.TLatex()\n",
+    "label.SetTextAlign(22)\n",
+    "label.DrawLatex(0.55, 3.0e4, \"#eta\")\n",
+    "label.DrawLatex(0.77, 7.0e4, \"#rho,#omega\")\n",
+    "label.DrawLatex(1.20, 4.0e4, \"#phi\")\n",
+    "label.DrawLatex(4.40, 1.0e5, \"J/#psi\")\n",
+    "label.DrawLatex(4.60, 1.0e4, \"#psi'\")\n",
+    "label.DrawLatex(12.0, 2.0e4, \"Y(1,2,3S)\")\n",
+    "label.DrawLatex(91.0, 1.5e4, \"Z\")\n",
+    "label.SetNDC(True)\n",
+    "label.SetTextAlign(11)\n",
+    "label.SetTextSize(0.04)\n",
+    "label.DrawLatex(0.10, 0.92, \"#bf{CMS Open Data}\")\n",
+    "label.SetTextAlign(31)\n",
+    "label.DrawLatex(0.90, 0.92, \"#sqrt{s} = 8 TeV, L_{int} = 11.6 fb^{-1}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Draw interactive canvas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%jsroot on\n",
+    "c.Draw()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Print cut-flow report"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "report.Print()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/environment.yml b/environment.yml
@@ -0,0 +1,5 @@
+name: analysis
+channels:
+  - conda-forge
+dependencies:
+  - root=6.16.00
-Original file line number
+Diff line change
@@ Expand Up / @@ -5,3 +5,4 @@ @@
     *.pyc
     *.root
     *.pdf
+    .ipynb*