{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Tau Collections\n",
    "\n",
    "```{warning}\n",
    "The examples on this page have not been updated to use r22 and ServiceX 3 yet. \n",
    "```\n",
    "\n",
    "Taus are complex jet-like objects that are reconstructed and calibrated with their own algorithms. They are a lot like jets, from a data model point-of-view."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from config import deliver_files\n",
    "from config import sx_f\n",
    "from func_adl_servicex_xaodr22 import FuncADLQueryPHYSLITE, cpp_float, cpp_vfloat\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import uproot\n",
    "import awkward as ak"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default we fetch tau-jets from the `Tight` working point (you can change the working point by passing the `working_point` argument)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7f6a9dd29fd0407f84a0ab9a673d5477",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[01/22/25 16:20:20] </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">ERROR   </span> Transform <span style=\"color: #008000; text-decoration-color: #008000\">\"sx_f\"</span> completed with failures: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> files failed. Will not <a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">query_core.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#210\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">210</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         cache.                                                               <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[01/22/25 16:20:20]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR   \u001b[0m Transform \u001b[32m\"sx_f\"\u001b[0m completed with failures: \u001b[1;36m1\u001b[0m/\u001b[1;36m1\u001b[0m files failed. Will not \u001b]8;id=990616;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\u001b\\\u001b[2mquery_core.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=825782;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#210\u001b\\\u001b[2m210\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m                    \u001b[0m         cache.                                                               \u001b[2m                 \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">ERROR   </span> Transform Request id: <span style=\"color: #ffff00; text-decoration-color: #ffff00\">4790e2c7-b444-4137-9241-ae9d5aca3a3c</span>           <a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">query_core.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#215\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">215</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR   \u001b[0m Transform Request id: \u001b[93m4790e2c7-b444-4137-9241-ae9d5aca3a3c\u001b[0m           \u001b]8;id=587212;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\u001b\\\u001b[2mquery_core.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=969609;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#215\u001b\\\u001b[2m215\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">ERROR   </span> More information of <span style=\"color: #008000; text-decoration-color: #008000\">'sx_f'</span> <a href=\"https://atlas-kibana.mwt2.org:5601/s/servicex/app/dashboards?auth_provider_hint=anonymous1#/view/6d069520-f34e-11ed-a6d8-9f6a16cd6d78?embed=true&_g=(time:(from:now-30d%2Fd,to:now))&_a=(filters:!((query:(match_phrase:(requestId:'4790e2c7-b444-4137-9241-ae9d5aca3a3c'))),(query:(match_phrase:(level:'error')))))&show-time-filter=true\" target=\"_blank\"><span style=\"color: #800000; text-decoration-color: #800000; background-color: #c0c0c0; font-weight: bold\">HERE</span></a>                                      <a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">query_core.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#224\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">224</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR   \u001b[0m More information of \u001b[32m'sx_f'\u001b[0m \u001b]8;id=738837;https://atlas-kibana.mwt2.org:5601/s/servicex/app/dashboards?auth_provider_hint=anonymous1#/view/6d069520-f34e-11ed-a6d8-9f6a16cd6d78?embed=true&_g=(time:(from:now-30d%2Fd,to:now))&_a=(filters:!((query:(match_phrase:(requestId:'4790e2c7-b444-4137-9241-ae9d5aca3a3c'))),(query:(match_phrase:(level:'error')))))&show-time-filter=true\u001b\\\u001b[1;31;47mHERE\u001b[0m\u001b]8;;\u001b\\                                      \u001b]8;id=817738;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py\u001b\\\u001b[2mquery_core.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=396956;file:///home/rjanusia/.local/lib/python3.9/site-packages/servicex/query_core.py#224\u001b\\\u001b[2m224\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "query = FuncADLQueryPHYSLITE()\n",
    "jets_per_event = query.Select(lambda e: e.TauJets())\n",
    "jet_info_per_event = jets_per_event.Select(\n",
    "    lambda jets: {\n",
    "        'pt': jets.Select(lambda j: j.pt() / 1000),\n",
    "    }\n",
    ")\n",
    "\n",
    "files = deliver_files(jet_info_per_event,sx_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ba59afe5b0648218f562f33e41f18f8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a155ac238cd94fc39594c500c30c4622",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3bf2106e26fe498d80a76447f67690d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c577f2edd477468390d6f847cc32599e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "taus = (ds\n",
    "        .Select(lambda e: e.TauJets())\n",
    "        .Select(lambda ts: {\n",
    "            'pt': [t.pt()/1000.0 for t in ts],\n",
    "            'eta': [t.eta() for t in ts],\n",
    "            'phi': [t.phi() for t in ts],\n",
    "        })\n",
    "        .AsAwkwardArray()\n",
    "        .value())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vlTQE+BbwIFnvrNndOOYHgZUR0R4RLwE3A0cAQ1L1FsBIYF2aXkc2/Dxp+e5kDezb0stss52ImBkRbRHRNmzYsG5k3czM8qo1rA8DiIiL0vxNkm4FBkXE09045p+A8ZJ2ISvlHAUsAu4GTiHroTUFmJfWn5/mf5+W3xURIWk+cL2ky8hKNGOB+7qRL+uH8veMgO8bMetp1YLI7pJOLrdAEhFxc5EDRsRCSXPJSjVbgYfIHnZ1GzBH0jdS2tVpk6uBn0paDmwk65FFRCxOPbuWpP2c5Z5ZZmaNVTWIACeQ9cjqKMiqoQqJiOnA9A7JKyjTuyoiXiDrEVZuPxcDFxfNh5mZdU+1ILI6Ij7VsJyYmVnTqdY7q1wJxMzMbJtqQeSTDcuFmZk1pYpBJCIebWRGzMys+dRys6GZmVlZ1W42vDP99fPUzcysrGq9s/aR9HfAiZLm0KGhPSIerGvOzMysz6sWRL4GfJVsOJHLOiwLslF3zcyshVUMIhExF5gr6au5oU/MmpofnWvWs2p5suFFkk4E3peS7omIW+ubLTMzawa1PJTqm8A5ZGNULQHOkfS/650xMzPr+2p5PO7xwCER8QqApFlkAyReUM+MmZlZ31frfSJDctO71yEfZmbWhGopiXwTeEjS3WTdfN8HTKtrrszMrCnU0rA+W9I9wLtT0nkR8URdc2VmZk2hlpIIEbGe7AmDZmZm29QURMz6I98zYtZ9HoDRzMwKqxpEJA2Q9FijMmNmZs2lahCJiJeBxyXt26D8mJlZE6mlTWQPYLGk+4DnSokRcWLdcmVmZk2hliDy1brnwszMmlIt94n8RtJ+wNiI+LWkXYAB9c+amZn1dbUMwPhPwFzgRylpBHBLHfNkZmZNopYuvmcBRwB/A4iIZcAbunNQSUMkzZX0mKSlkt4jaaikBZKWpb97pHUlaYak5ZIekXRobj9T0vrLJE3pTp7MzKzragkiL0bEltKMpIFkTzbsjiuAX0bEW4F3AEvJxuO6MyLGAnfy6vhcxwJj02sqcGXKx1BgOnA4cBgwvRR4zMysMWoJIr+RdAEwWNKHgJ8BPy96QEm7kw3ieDVARGyJiKeAScCstNos4KQ0PQm4NjL3AkMk7QMcAyyIiI0RsQlYAEwsmi8zM+u6WoLINKAd+APwP4Hbga9045hj0v5+LOkhSVdJ2hXYO43RBfAEsHeaHgGsyW2/NqVVSn8NSVMlLZK0qL29vRtZNzOzvFp6Z72SHkS1kKwa6/GI6E511kDgUOBzEbFQ0hV0GFo+IkJSd6vM8vubCcwEaGtr67H9Wv/hcbTMiqmld9bxwB+BGcD3gOWSju3GMdcCayNiYZqfSxZUNqRqKtLfJ9PydcCo3PYjU1qldDMza5BaqrO+DXwgIiZExPuBDwCXFz1gehbJGkkHpKSjyJ7dPh8o9bCaAsxL0/OB01MvrfHA06na6w7gaEl7pAb1o1OamZk1SC13rD8TEctz8yuAZ7p53M8B10naKe3vDLKAdqOkM4HVwMfSurcDxwHLgc1pXSJio6SLgPvTehdGxMZu5svMzLqgYhCRdHKaXCTpduBGsjaRj/LqF3chEfEw0FZm0VFl1g2ye1XK7eca4Jru5MXMzIqrVhL5cG56A/D+NN0ODK5bjszMrGlUDCIRcUYjM2JmZs2n0zYRSWPI2jBG59f3UPDWX7m7r1ntamlYv4Xs7vKfA6/UNTdmZtZUagkiL0TEjLrnxMzMmk4tQeQKSdOBXwEvlhIj4sG65crMzJpCLUHkYOCTwJG8Wp0Vad7MzFpYLUHko8Cb8sPBm5mZQW3DnjwKDKlzPszMrAnVUhIZAjwm6X62bxNxF18zsxZXSxCZXvdcmJlZU6rleSK/aURGzMys+dRyx/ozvPpM9Z2AHYHnIuL19cyYmZn1fbWURHYrTUsS2TPPx9czU2Zm1hxqaRPZJg3Lfku6+XBaZ+ubNTuPo2VWXS3VWSfnZncgew7IC3XLkZmZNY1aSiL554psBVaRVWmZmVmLq6VNxM8VMTOzsqo9HvdrVbaLiLioDvkxM7MmUq0k8lyZtF2BM4E9AQcRM7MWV+3xuN8uTUvaDTgHOAOYA3y70nZmZtY6qraJSBoK/AtwGjALODQiNjUiY2Zm1vdVaxP5FnAyMBM4OCKebViuzMysKVQriXyRbNTerwBfzm5WB0BkDese9sRaim88NHutis8TiYgdImJwROwWEa/PvXbriQAiaYCkhyTdmubHSFooabmkGyTtlNJ3TvPL0/LRuX2cn9Ifl3RMd/NkZmZdU8tDqerlHGBpbv5S4PKI2B/YRNYLjPR3U0q/PK2HpHHAZOBAYCLwA0kDGpR3MzOjl4KIpJHA8cBVaV5kz2yfm1aZBZyUpieledLyo3IDQc6JiBcjYiWwHDisISdgZmZA75VEvgOcC7yS5vcEnoqIrWl+LTAiTY8A1gCk5U+n9bell9lmO5KmSlokaVF7e3sPnoaZWWtreBCRdALwZEQ80KhjRsTMiGiLiLZhw4Y16rBmZv1el4aC7yFHACdKOg4YBLweuAIYImlgKm2MBNal9dcBo4C1kgYCuwN/zaWX5LcxM7MGaHhJJCLOj4iRETGarGH8rog4DbgbOCWtNgWYl6bnp3nS8rvSc03mA5NT760xwFjgvgadhrW40dNu2/Yya2W9URKp5DxgjqRvAA8BV6f0q4GfSloObCQLPETEYkk3AkvIhqg/KyJebny2zcxaV68GkYi4B7gnTa+gTO+qiHgB+GiF7S8GLq5fDs3MrJrevE/EzMyanIOImZkV5iBiZmaFOYiYmVlhDiJmZlZYX+ria9aUPES8tTKXRMzMrDAHETMzK8xBxMzMCnMQMTOzwhxEzMysMAcRMzMrzF18zXqQu/taq3FJxMzMCnMQMTOzwhxEzMysMAcRMzMrzA3rZnXiRnZrBS6JmJlZYQ4iZmZWmIOImZkV5iBiZmaFOYiYmVlhDiJmZlZYw4OIpFGS7pa0RNJiSeek9KGSFkhalv7ukdIlaYak5ZIekXRobl9T0vrLJE1p9LmY1Wr0tNu2vcz6k94oiWwFvhgR44DxwFmSxgHTgDsjYixwZ5oHOBYYm15TgSshCzrAdOBw4DBgeinwmJlZYzQ8iETE+oh4ME0/AywFRgCTgFlptVnASWl6EnBtZO4FhkjaBzgGWBARGyNiE7AAmNi4MzEzs15tE5E0GngnsBDYOyLWp0VPAHun6RHAmtxma1NapfRyx5kqaZGkRe3t7T13AmZmLa7Xhj2R9DrgJuDzEfE3SduWRURIip46VkTMBGYCtLW19dh+zYrwcCjWn/RKSUTSjmQB5LqIuDklb0jVVKS/T6b0dcCo3OYjU1qldDMza5De6J0l4GpgaURclls0Hyj1sJoCzMuln556aY0Hnk7VXncAR0vaIzWoH53SzMysQXqjOusI4JPAHyQ9nNIuAC4BbpR0JrAa+FhadjtwHLAc2AycARARGyVdBNyf1rswIjY25AzMzAzohSASEf8XUIXFR5VZP4CzKuzrGuCansudmZl1hZ8nYtaL3Mhuzc7DnpiZWWEuiZj1ES6VWDNyScTMzApzEDEzs8IcRMzMrDC3iZj1QW4fsWbhkoiZmRXmkohZH+dSifVlLomYmVlhLomYNRGXSqyvcUnEzMwKc0nErEnlSyV5LqFYIzmImPUzrvKyRnJ1lpmZFeaSiFk/5lKJ1ZuDiFmLcECxenAQMWtBHRvlHVSsKAcRM3MpxQpzEDGz7VTqOpznQGMlDiJm1mUuuViJg4iZdYsDSmtzEDGzHlNLVVglDkDNyUHEzPqErgYgB52+oemDiKSJwBXAAOCqiLikl7NkZg3Q1Q4AHmusPpo6iEgaAHwf+BCwFrhf0vyIWNK7OTOzvqCWQNOdKrgi+lvQauogAhwGLI+IFQCS5gCTAAcRM+uTGh20SuoVvJo9iIwA1uTm1wKHd1xJ0lRgapp9VtLjBY+3F/CXgts2K59za2i1c26180WXdvuc9yuX2OxBpCYRMROY2d39SFoUEW09kKWm4XNuDa12zq12vlC/c272oeDXAaNy8yNTmpmZNUCzB5H7gbGSxkjaCZgMzO/lPJmZtYymrs6KiK2SPgvcQdbF95qIWFzHQ3a7SqwJ+ZxbQ6udc6udL9TpnBUR9divmZm1gGavzjIzs17kIGJmZoU5iNRA0kRJj0taLmlab+enHiSNknS3pCWSFks6J6UPlbRA0rL0d4/ezmtPkzRA0kOSbk3zYyQtTNf7htRpo9+QNETSXEmPSVoq6T39/TpL+kL6XD8qabakQf3tOku6RtKTkh7NpZW9rsrMSOf+iKRDix7XQaQTuaFVjgXGAadKGte7uaqLrcAXI2IcMB44K53nNODOiBgL3Jnm+5tzgKW5+UuByyNif2ATcGav5Kp+rgB+GRFvBd5Bdu799jpLGgGcDbRFxEFknXAm0/+u80+AiR3SKl3XY4Gx6TUVuLLoQR1EOrdtaJWI2AKUhlbpVyJifUQ8mKafIftiGUF2rrPSarOAk3olg3UiaSRwPHBVmhdwJDA3rdKvzlnS7sD7gKsBImJLRDxFP7/OZD1RB0saCOwCrKefXeeI+C2wsUNypes6Cbg2MvcCQyTtU+S4DiKdKze0yoheyktDSBoNvBNYCOwdEevToieAvXsrX3XyHeBc4JU0vyfwVERsTfP97XqPAdqBH6cqvKsk7Uo/vs4RsQ74d+BPZMHjaeAB+vd1Lql0XXvse81BxLYj6XXATcDnI+Jv+WWR9QfvN33CJZ0APBkRD/R2XhpoIHAocGVEvBN4jg5VV/3wOu9B9st7DDAc2JXXVvv0e/W6rg4inWuZoVUk7UgWQK6LiJtT8oZSMTf9fbK38lcHRwAnSlpFVk15JFl7wZBU7QH973qvBdZGxMI0P5csqPTn6/xBYGVEtEfES8DNZNe+P1/nkkrXtce+1xxEOtcSQ6uktoCrgaURcVlu0XxgSpqeAsxrdN7qJSLOj4iRETGa7LreFRGnAXcDp6TV+ts5PwGskXRASjqK7NEJ/fY6k1VjjZe0S/qcl865317nnErXdT5weuqlNR54Olft1SW+Y70Gko4jqzsvDa1yce/mqOdJei/wn8AfeLV94AKydpEbgX2B1cDHIqJj413TkzQB+FJEnCDpTWQlk6HAQ8A/RMSLvZi9HiXpELKOBDsBK4AzyH5Q9tvrLOnrwMfJeiE+BHyarA2g31xnSbOBCWTD3G8ApgO3UOa6pmD6PbJqvc3AGRGxqNBxHUTMzKwoV2eZmVlhDiJmZlaYg4iZmRXmIGJmZoU5iJiZWWEOImZmVpiDiJmZFeYgYgZI2lPSw+n1hKR1ufmGP2dC0mhJz0t6OJe2t6TrJa2Q9ICk30v6SCf7uVvSMR3SPi/pSkmD0/ltkbRXnU7F+jkHETMgIv4aEYdExCHAD8meM3FIem3ppWz9MeWnNCzNLcBvI+JNEfEusqFaRnayj9lpvbzJwOyIeD7t/889mWlrLQ4iZjWQdEv69b9Y0tSUNrrDU+S+JOnfymw7Oz057z5JqyUdXyALRwJbIuKHpYSIWB0R380d5x/SMR6W9KP0QLW5wPGl0lQa5n842RA3Zt3mIGJWm0+lX/9twNmS9uzCtu8AVkTEYcBpZGMaddWBwIOVFkp6G9nYUEek0sXLwGlp/Kv7yJ5kB1kp5MbweEfWQwZ2voqZkQWOUvvDKLLHij7R2UaSBgHDgK+npCVA6TnXZwCHA8cAdwAPRcSPasmMpO8D7yUrnbybbGTadwH3ZzVfDObVYb9LVVrz0t9mfwys9SEOImadSCP8fhB4T0RslnQPMIhsRNh8aX5Qmc0PApZFxAtp/lDgvwAi4seS5gE7RsRnOsnGYuDvSzMRcVZqDC+NvCpgVkScX2bbecDlkg4Fdmmxh3BZnbk6y6xzuwObUgB5KzA+pW8A3pB6du0MnFBm23cA+0oalB5D+3Xg8tzyd5E9qrUzdwGDJP2vXNouuek7gVMkvQFA0lBJ+wFExLNkz864hqxUYtZjHETMOvdLYKCkpcAlwL0A6Sl5F5K1OSwAHiuz7TvInqS3kOwBZ1dGxO9yy2sKIqkN4yTg/ZJWSroPmAWcl5YvAb4C/ErSIyk/++R2MTvlxUHEepSfJ2JWR5J+A0yNiMcrLJ9N1mj/fIf00cCtEXFQA/K4CmiLiL/U+1jW/7gkYlZfbwaWVVoYEad2DCDJy8Du+ZsNe1rpZkNgR159mqVZl7gkYmZmhbkkYmZmhTmImJlZYQ4iZmZWmIOImZkV5iBiZmaFOYiYmVlhDiJmZlbY/wexTnQsDGYNRQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(ak.flatten(taus.pt), bins=100, range=(0, 100))\n",
    "plt.xlabel('Tau $p_T$ [GeV]')\n",
    "plt.ylabel('Number of Taus')\n",
    "_ = plt.title('Tau $p_T$ distribution for $Z\\\\rightarrow \\\\tau \\\\tau$ events')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calibration\n",
    "\n",
    "By default the taus we pulled from above are calibrated, and the best central value for the tau collection you request is returned. We use the standard approach to get both uncalibrated versions of the collection and systematic error variations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To grab the raw jets (without calibration) we just set the `uncalibrated_collection` parameter to `TauJets` (there is very little reason one will do this normally):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6bf6c0ccf35a477eb8e644421a404d62",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e5e764da707a4da88d9724b4fed05040",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ac7a578446b8463c87f1d80653ffdc01",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c97c6456458543eabb95ed31a84aef67",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "raw_taus = (ds\n",
    "            .Select(lambda e: e.TauJets(uncalibrated_collection=\"TauJets\"))\n",
    "            .Select(lambda ts: {\n",
    "                'pt': [t.pt()/1000.0 for t in ts],\n",
    "                'eta': [t.eta() for t in ts],\n",
    "                'phi': [t.phi() for t in ts],\n",
    "            })\n",
    "            .AsAwkwardArray()\n",
    "            .value())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of taus and the number of calibrated taus are quite different, so we'll need to match them in $\\eta$ and $\\phi$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_taus_matched = match_objects(taus, raw_taus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(ak.flatten(taus.pt-raw_taus_matched.pt), bins=100, range=(-10, 10))\n",
    "plt.xlabel('$\\Delta p_T$ for calibrated taus matched to their raw taus [GeV]')\n",
    "plt.ylabel('Number of Taus')\n",
    "_ = plt.title('The effect of tau calibration on tau $p_T$ in $Z\\\\rightarrow \\\\tau\\\\tau$ events')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we instead want a particular systematic error, we need only name that error to get it back. Knowing what the names of the systematic errors, however, is not something that can be programmatically determined ahead of time. See the further information section at the end of this chapter to links to the ATLAS jet calibration info twiki."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d1a128d6162483cb01e8249b8061cc0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "abd835a6fbfa4d30830200dbc0f4aa74",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b64cadc803da4dcb94a4f8074a20d18a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "rucio://mc16_13TeV:m...:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fdfb56e56c004533b8ae4af576124765",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "        rucio://mc16_13TeV:m... Downloaded:   0%|          | 0/9000000000.0 [00:00]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sys_taus = (calib_tools.query_sys_error(ds, 'TAUS_TRUEHADTAU_SME_TES_DETECTOR__1up')\n",
    "            .Select(lambda e: e.TauJets())\n",
    "            .Select(lambda ts: {\n",
    "                'pt': [t.pt()/1000.0 for t in ts],\n",
    "                'eta': [t.eta() for t in ts],\n",
    "                'phi': [t.phi() for t in ts],\n",
    "            })\n",
    "            .AsAwkwardArray()\n",
    "            .value())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sys_taus_matched = match_objects(taus, sys_taus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SNxlJuqJ4eGlx/6KvA7eQRtPN7XhkZmY2ZjQawDAJICK+VDy/UNKlwPiIcP+YmZm1TaNkNEHSAbVekEREXNShmJry0G4zs/7SMBkB+5BG0FULIFsy8tBuM7P+0igZ3R0RH+xaJGZmNmY1Gk1Xq0VkZmbWdo2S0Xu7FkWLfJ6RmVl/qZuMImJhvddy83lGZmb9pcxJr2ZmZh3V6KTXK4v/X+teOGZmNhY1Gk33IkmvB/aVdB5VAxoi4paORtaAzzMyM+svjZLRZ4HPkO7E+o2q1wLYo1NBNePzjMzM+kvdZBQRFwAXSPpMxSWBzMzM2q7MnV6/JGlf4F+KSVdHxKWdDcvMzMaSMjfX+ypwJLC4+DtS0n90OjAzMxs7ytx2fG9gx4hYCyDpTOBW4FOdDMzMzMaOsucZTax47DNNzcysrcq0jL4K3CrpKtLw7n8BjutoVE14aLeZWX9p2jKKiLnArqRbRlwIvC4iftTpwJrE5MsBmZn1kTItIyLiXuCSDsdiZmZjlK9NZ2Zm2TkZmZlZdg2TkaRxkm7vVjBmZjY2NUxGEfE0cIekKV2Kx8zMxqAyAxj+CVgk6UbgkcGJEbFvx6IyM7MxpUwy+kzHo2iRzzMyM+svZc4zugZYDmxQPL4JyHYvoyImn2dkZtZHylwo9RDgAuA7xaStgIs7GJOZmY0xZYZ2HwbsBjwEEBF/BLboZFBmZja2lDlm9EREPCmlu45LWp90p1czqzD1uMtyh2DWs8q0jK6R9ClgI0l7AT8G5nU2LDMzG0vKJKPjgFXA74EPAZcDx3cyKDMzG1vK3HZ8bXFDvd+SuufuiAh305mZWds0TUaS9gZOA+4k3c9oW0kfioifdTo4s9HOx4nM2qPMAIYTgTdFxFIASS8BLgOcjMzMrC3KHDNaM5iICsuANR2Kx8zMxqC6LSNJBxQPb5Z0OXA+6ZjRO0lXYTAzM2uLRt10Myse3we8sXi8Ctio3YFIegVwJLA5cGVEfLvdyzBrBx8nMmu/uskoIj4w0sIlnQ7sA9wfETtUTJ8BfBMYB3wvIk6IiCXAoZLWA84CnIzMzMaIMqPptgU+CkytfH/JW0icAZxCSi6D5Y0DTgX2AlYCN0m6JCIWS9oX+DBwdvlVMOs8t4bMOqvMaLqLge+TrrqwtpXCI+JaSVOrJu8CLI2IZQCSzgP2AxZHxCXAJZIuA86tVaak2cBsgClTfM8/M7N+UCYZPR4RJ7dxmVsBKyqerwReK2l34ABgQ9JVHmqKiDnAHICBgQGffGtm1gfKJKNvSvoccAXwxODEiGjrPY0i4mrg6naWaWZmvaFMMpoOvBfYg2e66aJ4Phz3AJMrnm9dTCvNd3q1bvBxIrPuKZOM3gm8OCKebNMybwJeWgyMuAc4EDiolQIiYh4wb2Bg4JA2xWQGOAGZ5VLmCgwLgYnDKVzSXOAGYDtJKyUdHBFPAYcDvwCWAOdHxKIWy50pac7q1auHE5aZmY0yZVpGE4HbJd3E0GNGTYd2R8SsOtMvp8EghRLlumVkZtZHyiSjz3U8CrOM3DVnll+Z+xld041AWuEBDGZm/aXpMSNJayQ9VPw9LulpSQ91I7h6ImJeRMyeMGFCzjDMzKxNyrSMNh18LEmkqyXs2smgzMxsbClzzGid4nbjFxcnwR7XmZCaczedjZSPE5mNLmUulHpAxdP1gAHg8Y5FVIJH09lwOAGZjV5lWkaV9zV6ClhO6qozG/WcgMx6Q5ljRiO+r5GZmVkjjW47/tkG80VEfKkD8ZTiY0Z5VbY2lp+wd8ZIanNryKz3NBra/UiNP4CDgWM7HFdDHtptZtZfGt12/MTBx5I2BY4EPgCcB5xYbz4zM7NWNTxmJGkz4GPAu4EzgZ0i4sFuBGajy2jv+hrt8ZlZY42OGX2ddOfVOcD0iHi4a1HZqFDmC360Hz8ys97Q6JjRx4EtgeOBP1dcEmhN7ssB+RYSZmb9pdExozL3OsrCJ70auGvOrJ+0dDkgs9ycgMz6k5ORDeEvezPLwcnI2qY6kXlAg5mV5WRko5JbaGZjy6gdpNCIR9OZmfWXnmwZeTTdyI3G84PcGjIbu3oyGVl7OQmYWW492U1nZmb9xS0j67rR2EVoZnk5GVlW7iI0M3A3nZmZjQJuGY0h3W6FuDvOzMpyMuoTo/2L391xZtZIT3bT+aRXM7P+0pMtI5/02phbIWbWa3oyGVnipGNm/aInu+nMzKy/OBmZmVl2TkZmZpadjxn1GB8nMrN+5JaRmZll52RkZmbZORmZmVl2TkZmZpadk5GZmWU3qkbTSXo7sDfwPOD7EXFF3ohGB4+gM7N+1/GWkaTTJd0vaWHV9BmS7pC0VNJxABFxcUQcAhwKvKvTsZmZ2ejQjZbRGcApwFmDEySNA04F9gJWAjdJuiQiFhdvOb54fUwZ7beBMDPrlI4no4i4VtLUqsm7AEsjYhmApPOA/SQtAU4AfhYRt9QqT9JsYDbAlClTOhZ3bu6aM7OxJNcAhq2AFRXPVxbTPgrsCbxD0qG1ZoyIORExEBEDkyZN6nykZmbWcaNqAENEnAyc3Ox9kmYCM6dNm9b5oMzMrONytYzuASZXPN+6mFZKRMyLiNkTJkxoe2BmZtZ9uVpGNwEvlbQtKQkdCByUKZasfGzIzKw7Q7vnAjcA20laKengiHgKOBz4BbAEOD8iFrVQ5kxJc1avXt2ZoM3MrKu6MZpuVp3plwOXD7PMecC8gYGBQ0YSm5mZjQ6+HJCZmWXXk8nI3XRmZv1lVA3tLms0d9OVuYqCBy2YmQ3Vk8moV/jyPmZm5bibzszMsuvJZOSTXs3M+ou76dqgzDEgHycyM6vPyagBH/MxM+uOnuym8zEjM7P+0pPJyMeMzMz6S08mIzMz6y9ORmZmlp2TkZmZZdeTo+ly3OnVI+vMzDqnJ5NRJ69N5/OBzMy6z910ZmaWXU+2jHJz68nMrL3cMjIzs+zcMsItHTOz3HqyZeTLAZmZ9ZeeTEa+HJCZWX/pyWRkZmb9xcnIzMyyG7MDGDxowcxs9HDLyMzMsnMyMjOz7JyMzMwsOycjMzPLrieTkU96NTPrLz2ZjHzSq5lZf+nJZGRmZv3FycjMzLJzMjIzs+wUEbljGDZJq4C7c8cxDJsDD+QOosvG2jqPtfUFr3Mv2SYiJuUOolJPJ6NeJenmiBjIHUc3jbV1HmvrC15nGxl305mZWXZORmZmlp2TUR5zcgeQwVhb57G2vuB1thHwMSMzM8vOLSMzM8vOycjMzLJzMspI0sclhaTNc8fSaZK+Lul2SbdJ+omkiblj6hRJMyTdIWmppONyx9NpkiZLukrSYkmLJB2ZO6ZukTRO0q2SLs0dS69zMspE0mTgX4E/5Y6lS34J7BARrwL+AHwyczwdIWkccCrwVmB7YJak7fNG1XFPAR+PiO2BXYHDxsA6DzoSWJI7iH7gZJTPScAngDExgiQiroiIp4qnvwG2zhlPB+0CLI2IZRHxJHAesF/mmDoqIu6NiFuKx2tIX85b5Y2q8yRtDewNfC93LP3AySgDSfsB90TE73LHkskHgZ/lDqJDtgJWVDxfyRj4Yh4kaSrwv4DfZg6lG/6T9INybeY4+sL6uQPoV5L+G3hhjZc+DXyK1EXXVxqtc0T8tHjPp0ndOud0MzbrPEnPBS4EjoqIh3LH00mS9gHuj4j5knbPHE5fcDLqkIjYs9Z0SdOBbYHfSYLUXXWLpF0i4i9dDLHt6q3zIEnvB/YB3hz9e4LbPcDkiudbF9P6mqQNSInonIi4KHc8XbAbsK+ktwHjgedJ+mFEvCdzXD3LJ71mJmk5MBARvXjl39IkzQC+AbwxIlbljqdTJK1PGqDxZlISugk4KCIWZQ2sg5R+VZ0J/C0ijsocTtcVLaOjI2KfzKH0NB8zsm45BdgU+KWkBZJOyx1QJxSDNA4HfkE6kH9+Pyeiwm7Ae4E9in27oGgxmJXmlpGZmWXnlpGZmWXnZGRmZtk5GZmZWXZORmZmlp2TkZmZZedkZGZm2TkZmZlZdmM+GUl6e3FPoZe3oawjJC2R1LXrrkl6uOLxr4v/UyUtHEGZEyV9ZBjzfV7S0e0qr1vKxteG7dq27VM9z3BiG6wvLc6zv6RvtTrfaNDpeljsg8ckLaiY9gJJ50paJmm+pBsk7d+knKskvaVq2lGSvi1po+Kk4if77T5oYz4ZAbOAm4v/I/URYK+IeHeZNytp2z6IiNeXfW+TZU8krUu7tLu8dptI3viGs/zhzDNErfpSok7uBNwykuW2os2fkYl0fj/fGRE7wrrLJF0MXBsRL46InYEDaX77lLnF+yodCMyNiMeK8v/czqBHhYgYs3/Ac4H7gFcDf6iYPhf4EXAjcDewd4myTgOeBH4P/Hsx7WPAwuLvqGLaVOAO4CxgEbBNVTnvA24DfgecXTH9YmB+Mc/siukPVz8ulnE76crYS4ALgI1rLbtWuaR78DwGLAC+Xkx7T7E9FgDfAcYV0z9Nuhbb/xTb7ega26ZWebWWOxVYWDHf0cDngU2Ay4ptshB4V41lDK7zGUU85wB7AtcDfwR2abDcWvE9az8Uy1gCfLeY/wpgow5tn2fVnUbzDDO2yvpSt04W73kZ6QaJa4DltWIq+Zk7FjibdLmku+tsj2fFU2e/HQMcUTw+CfhV8XgP0gVbm22zZ5U5knpYY743A9c02R7P2jfAZsD9wHMqyv0TxRVzimnLgc07/R3Zzb/sAWRdeXj3YKUl/drbuXi8GPhq8fgNwI0ly1tXQYCdSYlpE1LSW0S6z8tU0v1Pdq0x/ytJX1yDZWxW8dpmxf+Nig/C84vn9ZJRALsVz08vPlDPWnatcmt8qF4BzAM2KJ7/F+nLenAdNwaeByyl/pfLwqppZZY7+CXwb8B3K6ZPqLOMp4DppBb//GK9Rbq53cUtLLfmfqhYxo7F8/NJXyZt3T7UqTtN5mkpthr1pWadLF7fkPRlOR1YRrpNyN+A8cP4zP2QdFHVccBLgdvqbI8y9XRX4MfF9OtIX+obAJ8DPlRiO9f7TFW/r1Q9rDHfEcBJDbZFo31zKbBf8fg44P/V+67pl7+xfguJWaRfkpA+vLMkLQImAV8opi8G/glA0geA1wJvIf2yuzUivlOn7DcAP4mIR4p5LwL+GbgEuDsiflNjnj1IH64HACLibxWvHVHR1zyZ9EH+a4N1WxER1xePf0j6YFxQY9m1yq2+lcWbSV+QNxW3vdiI9Mtts2IdHy3W8ZIG8VQrs9xBvwdOlPQ14NKIuK7O++6KiN8XsSwCroyIkPR70hdF2eU22g93RcSC4vH8otyJtHf71Ks7tzaZr5XYqtWrkwB7kVoDfwYeioi/SHqclFAoYmx6L6vCdOCAiHha0tOkpFZLmXo6H9hZ0vOAJ0g/KAdI2+qIOuVWavUzVbYe1iTpVNK+fTIiXkP9zxU801X30+L/wa0sqxeN2WQkaTNSYvm3YtL5wDWk7rk/RsTjxfSdSB9EIuIHkn5K+iVz6AgW/0iLse5O6nJ6XUQ8Kulq0j1UGqm+Au7g83XLbqFcAWdGxCer4jqqTPzPKqz+cp9i6HHM8QAR8QdJOwFvA74s6cqI+GKNop+oeLy24vlaYP1hbsdGy3ia9AXS1u0zAqVjq6FRnXw16Yv4VcBtkrYA1gwmS2h+LytYd8+jSRFxZzHpVUW5DeOpt98i4h+S7gLeD/ya1K36JmAaqcuyUSw1yyxeHmk9HLSIZ75fiIjDikEHNw+GQf1981PgpGJ5G0fE/Ebr0w/G8gCGdwCXR8QTABGxDLiXVNGmSBovaRNSC+mkivl2Jv0ia+Y64O2SNi7K2b+Y1sivgHdKej6sS5gAE4AHiw/Ny0ndE81MkfS64vFBpGMW1eqVu4Z0u4dBVwLvKL6EkLSZpG2Aa4t13EjSpsDMOrFUl1dvufcBW0h6vqQNSTfiQ9KWwKMR8UNSX/9OJda/lrLrW28/1NPu7VOm7lTP02psrVgDvJyUlG4jfSZObbEMgO0YmiR2pPih10Sj+n8dqRvt2uLxoaQei1q3I6jcZo3KbFc9/BUwXtKHK6ZtXPG47r6JiIeBq0hdzXObLKcvjNmWEamL7tVKN7cb9HxSorkI+C2p//k/Krq7ICWjq5oVHhG3SDqD1I8N8L2IuFXS1AbzLJL0FeCaogvjVtKvvp8Dh0paQjqwW687pdIdwGGSTid1NX4b2KLqPTXLjYi/SrpeaajwzyLiGEnHA1cUI5v+ARwWEb+R9CPSF8r9pBvJ1VqvIeUBx9dZ7j8kfbHYZveQBiRA6tr5uqS1xbI/XL2MklpZ31r7oaaIWNzO7VMs/wyq6k6jeaiTHOrFRho8UNYPgZ8ABwAPkgYCDGd493RSMhu0I2lAQDON6v91pEEiN0TEI0X3Yc0ffVXb7Jek1vKzymxXPSy6iN9OauF8AlhFavEdW7zebN/MJW336pF1fcn3M6oi6RrSyJo76rw+F/hgRDzW3cjM8lI6f2bPaNNdiSUtBab3y2ep+KF5aUTs0IVlLafP7hA9lrvp6nkJaShwTRExq18+PGZlFd1VE9qYiCaSDuT302fpaWCCKk56bbeiy3cBqddmbaeWk4NbRmZmlp1bRmZmlp2TkZmZZedkZGZm2TkZmZlZdk5GZmaWnZORmZll52RkZmbZ/X+BX677UrZ2WwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(ak.flatten(taus.pt-sys_taus_matched.pt), bins=100, range=(-5, 5))\n",
    "plt.xlabel(r'$\\Delta p_T$ for calibrated taus matched to their $\\phi-\\eta$ raw taus [GeV]')\n",
    "plt.ylabel('Number of Taus')\n",
    "plt.yscale('log')\n",
    "_ = plt.title(r'The effect of a tau calibration sys error on tau $p_T$ in $Z\\rightarrow \\tau\\tau$ events')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Datamodel\n",
    "\n",
    "The data model when this documentation was last built was:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on class TauJet_v3 in module func_adl_servicex_xaodr21.xAOD.taujet_v3:\n",
      "\n",
      "class TauJet_v3(builtins.object)\n",
      " |  A class\n",
      " |  \n",
      " |  Methods defined here:\n",
      " |  \n",
      " |  ROIWord(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  allTauTrackLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_tautrack_v1___.vector_ElementLink_DataVector_xAOD_TauTrack_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  allTauTrackLinksNonConst(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_tautrack_v1___.vector_ElementLink_DataVector_xAOD_TauTrack_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  charge(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  chargedPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  chargedPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  clearDecorations(self) -> 'bool'\n",
      " |      A method\n",
      " |  \n",
      " |  cluster(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.iparticle.IParticle'\n",
      " |      A method\n",
      " |  \n",
      " |  clusterLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_iparticle___.vector_ElementLink_DataVector_xAOD_IParticle___'\n",
      " |      A method\n",
      " |  \n",
      " |  e(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  eta(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaDetectorAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaFinalCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaIntermediateAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaJetSeed(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaPanTauCellBased(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaPanTauCellBasedProto(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaTauEnergyScale(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaTauEtaCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  etaTrigCaloOnly(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  hadronicPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  hadronicPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  hasNonConstStore(self) -> 'bool'\n",
      " |      A method\n",
      " |  \n",
      " |  hasStore(self) -> 'bool'\n",
      " |      A method\n",
      " |  \n",
      " |  index(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  jet(self) -> 'func_adl_servicex_xaodr21.xAOD.jet_v1.Jet_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  jetLink(self) -> 'func_adl_servicex_xaodr21.elementlink_datavector_xaod_jet_v1__.ElementLink_DataVector_xAOD_Jet_v1__'\n",
      " |      A method\n",
      " |  \n",
      " |  m(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mDetectorAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mFinalCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mIntermediateAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mJetSeed(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mPanTauCellBased(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mPanTauCellBasedProto(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mTauEnergyScale(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mTauEtaCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  mTrigCaloOnly(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  nAllTracks(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nChargedPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nClusters(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nHadronicPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nNeutralPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nPi0PFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nPi0s(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nProtoChargedPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nProtoNeutralPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nProtoPi0PFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nShotPFOs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nTracksCharged(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nTracksIsolation(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  nTracksWithMask(self, classification: 'int') -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  neutralPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  neutralPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  p4(self) -> 'func_adl_servicex_xaodr21.tlorentzvector.TLorentzVector'\n",
      " |      A method\n",
      " |  \n",
      " |  phi(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiDetectorAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiFinalCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiIntermediateAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiJetSeed(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiPanTauCellBased(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiPanTauCellBasedProto(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiTauEnergyScale(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiTauEtaCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  phiTrigCaloOnly(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  pi0(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.iparticle.IParticle'\n",
      " |      A method\n",
      " |  \n",
      " |  pi0ConeDR(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  pi0Links(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_iparticle___.vector_ElementLink_DataVector_xAOD_IParticle___'\n",
      " |      A method\n",
      " |  \n",
      " |  pi0PFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  pi0PFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  protoChargedPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  protoChargedPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  protoNeutralPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  protoNeutralPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  protoPi0PFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  protoPi0PFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  pt(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptDetectorAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptFinalCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptIntermediateAxis(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptJetSeed(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptPanTauCellBased(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptPanTauCellBasedProto(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptTauEnergyScale(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptTauEtaCalib(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  ptTrigCaloOnly(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  rapidity(self) -> 'float'\n",
      " |      A method\n",
      " |  \n",
      " |  secondaryVertex(self) -> 'func_adl_servicex_xaodr21.xAOD.vertex_v1.Vertex_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  secondaryVertexLink(self) -> 'func_adl_servicex_xaodr21.elementlink_datavector_xaod_vertex_v1__.ElementLink_DataVector_xAOD_Vertex_v1__'\n",
      " |      A method\n",
      " |  \n",
      " |  shotPFO(self, i: 'int') -> 'func_adl_servicex_xaodr21.xAOD.pfo_v1.PFO_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  shotPFOLinks(self) -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_pfo_v1___.vector_ElementLink_DataVector_xAOD_PFO_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  tauTrackLinksWithMask(self, noname_arg: 'int') -> 'func_adl_servicex_xaodr21.vector_elementlink_datavector_xaod_tautrack_v1___.vector_ElementLink_DataVector_xAOD_TauTrack_v1___'\n",
      " |      A method\n",
      " |  \n",
      " |  trackFilterProngs(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  trackFilterQuality(self) -> 'int'\n",
      " |      A method\n",
      " |  \n",
      " |  trackWithMask(self, i: 'int', mask: 'int', container_index: 'int') -> 'func_adl_servicex_xaodr21.xAOD.tautrack_v1.TauTrack_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  usingPrivateStore(self) -> 'bool'\n",
      " |      A method\n",
      " |  \n",
      " |  usingStandaloneStore(self) -> 'bool'\n",
      " |      A method\n",
      " |  \n",
      " |  vertex(self) -> 'func_adl_servicex_xaodr21.xAOD.vertex_v1.Vertex_v1'\n",
      " |      A method\n",
      " |  \n",
      " |  vertexLink(self) -> 'func_adl_servicex_xaodr21.elementlink_datavector_xaod_vertex_v1__.ElementLink_DataVector_xAOD_Vertex_v1__'\n",
      " |      A method\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Readonly properties defined here:\n",
      " |  \n",
      " |  auxdataConst\n",
      " |      A method\n",
      " |  \n",
      " |  isAvailable\n",
      " |      A method\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors defined here:\n",
      " |  \n",
      " |  __dict__\n",
      " |      dictionary for instance variables (if defined)\n",
      " |  \n",
      " |  __weakref__\n",
      " |      list of weak references to the object (if defined)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from func_adl_servicex_xaodr21.xAOD.taujet_v3 import TauJet_v3\n",
    "help(TauJet_v3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Further Information\n",
    "\n",
    "* The [`xAOD::TauJet_v3` C++ header file](https://gitlab.cern.ch/atlas/athena/-/blob/21.2/Event/xAOD/xAODTau/xAODTau/versions/TauJet_v3.h) with all the inline documentation.\n",
    "* The [Tau Recommendation Pages for R21](https://twiki.cern.ch/twiki/bin/view/AtlasProtected/TauRecommendationsR21) on the ATLAS TWiki"
   ]
  }
 ],
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