{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5efbd85a-a55f-41a9-a34e-452151c0a9a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import servicex as sx\n",
    "import awkward as ak\n",
    "from func_adl_servicex import ServiceXSourceUpROOT\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['figure.dpi'] = 200 # make figures bigger and more readable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1caae859-3d03-44c1-ba5c-88da8b576dd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "[root://eospublic.ce...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        [root://eospublic.ce... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset_name = [\"root://eospublic.cern.ch//eos/root-eos/benchmark/Run2012B_SingleMu.root\"]\n",
    "sx_dataset = sx.ServiceXDataset(dataset_name, \"uproot\")\n",
    "ds = ServiceXSourceUpROOT(sx_dataset, \"Events\")\n",
    "best_trijet_pt_6 = ds.Where(lambda event: event.nJet >= 3)\\\n",
    "                     .Select(lambda event: {'pt': event.Jet_pt,\n",
    "                                            'eta': event.Jet_eta,\n",
    "                                            'phi': event.Jet_phi,\n",
    "                                            'mass': event.Jet_mass}.Zip().ToFourMomenta()\n",
    "                                           .Choose(3)\n",
    "                                           .Select(lambda triplet: triplet[0] + triplet[1] + triplet[2])\n",
    "                                           .OrderBy(lambda trijet: abs(trijet.m - 172.5))\n",
    "                                           .First()\n",
    "                                           .Select(lambda best_trijet: best_trijet.pt)).AsAwkwardArray().value()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "60ef3cd2-a47a-4dfc-8633-e6ec1fb045e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Array [26, 33, 21.2, ... 21.5, 29.7, 36.5] type='23752864 * float32'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_trijet_pt_6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4cd0af13-76b9-4859-bf65-3a8eb19aa18e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(best_trijet_pt_6, bins=100, range=(0, 100))\n",
    "plt.xlabel(r'Trijet $p_\\mathrm{T}$ [GeV]')\n",
    "plt.ylabel('Events')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}