{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Jit compilation with Numba\n", "\n", "This is a rendered copy of [advanced_numba.ipynb](https://github.com/scikit-hep/coffea/blob/master/binder/advanced_numba.ipynb). You can optionally run it interactively on [binder at this link](https://mybinder.org/v2/gh/coffeateam/coffea/master?filepath=binder%2Fadvanced_numba.ipynb)\n", "\n", "The purpose of this notebook is to teach you how to express operations that are hard to express in an array-oriented way in an imperative way and then jit compile them using numba and execute them as part of your coffea workflow.\n", "\n", "It heavily builds on top of [processing.ipynb](https://github.com/scikit-hep/coffea/blob/master/binder/processing.ipynb), so please read that one first." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [] }, "outputs": [], "source": [ "import hist\n", "import hist.dask\n", "import dask\n", "import awkward as ak\n", "import dask_awkward as dak\n", "import matplotlib.pyplot as plt\n", "\n", "from coffea import processor\n", "from coffea.nanoevents import BaseSchema\n", "from coffea.nanoevents.methods import candidate\n", "from coffea.dataset_tools import (\n", " apply_to_fileset,\n", " preprocess,\n", ")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Connection method: Cluster objectCluster type: distributed.LocalCluster
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LocalCluster

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Scheduler

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\n" ], "text/plain": [ "BokehUserWarning: reference already known 'p1361'\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from dask.distributed import Client\n", "\n", "# here we connect to the cluster of our analysis facility.\n", "# if you are on coffea-casa for example, that should be something like\n", "# client = Client(\"tls://localhost:8786\")\n", "# locally we can make our own cluster though\n", "from dask.distributed import LocalCluster\n", "\n", "cluster = LocalCluster(threads_per_worker=1)\n", "client = Client(cluster)\n", "\n", "client" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [] }, "outputs": [], "source": [ "fileset = {\n", " \"DoubleMuon\": {\n", " \"files\": {\n", " \"/Users/iason/work/pyhep_dev/uscms-idap-training/coffea/Run2012B_DoubleMuParked.root\": \"Events\",\n", " # \"root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/Run2012B_DoubleMuParked.root\": \"Events\",\n", " \"/Users/iason/work/pyhep_dev/uscms-idap-training/coffea/Run2012C_DoubleMuParked.root\": \"Events\",\n", " # \"root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/Run2012C_DoubleMuParked.root\": \"Events\",\n", " },\n", " \"metadata\": {\n", " \"is_mc\": False,\n", " },\n", " },\n", " \"ZZ to 4mu\": {\n", " \"files\": {\n", " \"/Users/iason/work/pyhep_dev/uscms-idap-training/coffea/ZZTo4mu.root\": \"Events\",\n", " # \"root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/ZZTo4mu.root\": \"Events\",\n", " },\n", " \"metadata\": {\n", " \"is_mc\": True,\n", " },\n", " },\n", "}\n", "\n", "dataset_runnable, dataset_updated = preprocess(\n", " fileset,\n", " align_clusters=False,\n", " step_size=100_000,\n", " files_per_batch=1,\n", " skip_bad_files=True,\n", " save_form=False,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting fancy\n", "Let's flesh out the processor from the `procesing.ipynb` notebook into a 4-muon analysis, searching for diboson events:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [] }, "outputs": [], "source": [ "import numba\n", "\n", "\n", "@numba.njit\n", "def find_4lep_kernel(events_leptons, builder):\n", " \"\"\"Search for valid 4-lepton combinations from an array of events * leptons {charge, ...}\n", "\n", " A valid candidate has two pairs of leptons that each have balanced charge\n", " Outputs an array of events * candidates {indices 0..3} corresponding to all valid\n", " permutations of all valid combinations of unique leptons in each event\n", " (omitting permutations of the pairs)\n", " \"\"\"\n", " for leptons in events_leptons:\n", " builder.begin_list()\n", " nlep = len(leptons)\n", " for i0 in range(nlep):\n", " for i1 in range(i0 + 1, nlep):\n", " if leptons[i0].charge + leptons[i1].charge != 0:\n", " continue\n", " for i2 in range(nlep):\n", " for i3 in range(i2 + 1, nlep):\n", " if len({i0, i1, i2, i3}) < 4:\n", " continue\n", " if leptons[i2].charge + leptons[i3].charge != 0:\n", " continue\n", " builder.begin_tuple(4)\n", " builder.index(0).integer(i0)\n", " builder.index(1).integer(i1)\n", " builder.index(2).integer(i2)\n", " builder.index(3).integer(i3)\n", " builder.end_tuple()\n", " builder.end_list()\n", "\n", " return builder\n", "\n", "\n", "def find_4lep(events_leptons):\n", " if ak.backend(events_leptons) == \"typetracer\":\n", " # here we fake the output of find_4lep_kernel since\n", " # operating on length-zero data returns the wrong layout!\n", " ak.typetracer.touch_data(events_leptons.charge) # force touching of the necessary data\n", " return ak.Array(ak.Array([[(0, 0, 0, 0)]]).layout.to_typetracer(forget_length=True))\n", " return find_4lep_kernel(events_leptons, ak.ArrayBuilder()).snapshot()\n", "\n", "\n", "class FancyDimuonProcessor(processor.ProcessorABC):\n", " def __init__(self, mode=\"virtual\"):\n", " assert mode in [\"eager\", \"virtual\", \"dask\"]\n", " self._mode = mode\n", "\n", " def process(self, events):\n", " dataset_axis = hist.axis.StrCategory([], growth=True, name=\"dataset\", label=\"Primary dataset\")\n", " mass_axis = hist.axis.Regular(300, 0, 300, name=\"mass\", label=r\"$m_{\\mu\\mu}$ [GeV]\")\n", " pt_axis = hist.axis.Regular(300, 0, 300, name=\"pt\", label=r\"$p_{T,\\mu}$ [GeV]\")\n", "\n", " if self._mode == \"dask\":\n", " hist_class = hist.dask.Hist\n", " else:\n", " hist_class = hist.Hist\n", "\n", " h_nMuons = hist_class(\n", " dataset_axis,\n", " hist.axis.IntCategory(range(6), name=\"nMuons\", label=\"Number of good muons\"),\n", " storage=\"weight\",\n", " label=\"Counts\",\n", " )\n", " h_m4mu = hist_class(dataset_axis, mass_axis, storage=\"weight\", label=\"Counts\")\n", " h_mZ1 = hist_class(dataset_axis, mass_axis, storage=\"weight\", label=\"Counts\")\n", " h_mZ2 = hist_class(dataset_axis, mass_axis, storage=\"weight\", label=\"Counts\")\n", " h_ptZ1mu1 = hist_class(dataset_axis, pt_axis, storage=\"weight\", label=\"Counts\")\n", " h_ptZ1mu2 = hist_class(dataset_axis, pt_axis, storage=\"weight\", label=\"Counts\")\n", "\n", " cutflow = dict()\n", "\n", " dataset = events.metadata[\"dataset\"]\n", " muons = ak.zip(\n", " {\n", " \"pt\": events.Muon_pt,\n", " \"eta\": events.Muon_eta,\n", " \"phi\": events.Muon_phi,\n", " \"mass\": events.Muon_mass,\n", " \"charge\": events.Muon_charge,\n", " \"isolation\": events.Muon_pfRelIso03_all,\n", " },\n", " with_name=\"PtEtaPhiMCandidate\",\n", " behavior=candidate.behavior,\n", " )\n", "\n", " # make sure they are sorted by transverse momentum\n", " muons = muons[ak.argsort(muons.pt, axis=1)]\n", "\n", " cutflow[\"all events\"] = ak.num(muons, axis=0)\n", "\n", " # impose some quality and minimum pt cuts on the muons\n", " muons = muons[(muons.pt > 5) & (muons.isolation < 0.2)]\n", " cutflow[\"at least 4 good muons\"] = ak.sum(ak.num(muons) >= 4)\n", " h_nMuons.fill(dataset=dataset, nMuons=ak.num(muons))\n", "\n", " # reduce first axis: skip events without enough muons\n", " muons = muons[ak.num(muons) >= 4]\n", "\n", " # find all candidates with helper function\n", " if self._mode == \"dask\":\n", " fourmuon = dak.map_partitions(find_4lep, muons)\n", " else:\n", " fourmuon = find_4lep_kernel(ak.materialize(muons), ak.ArrayBuilder()).snapshot()\n", " fourmuon = [muons[fourmuon[idx]] for idx in \"0123\"]\n", "\n", " fourmuon = ak.zip(\n", " {\n", " \"z1\": ak.zip(\n", " {\n", " \"lep1\": fourmuon[0],\n", " \"lep2\": fourmuon[1],\n", " \"p4\": fourmuon[0] + fourmuon[1],\n", " }\n", " ),\n", " \"z2\": ak.zip(\n", " {\n", " \"lep1\": fourmuon[2],\n", " \"lep2\": fourmuon[3],\n", " \"p4\": fourmuon[2] + fourmuon[3],\n", " }\n", " ),\n", " }\n", " )\n", "\n", " cutflow[\"at least one candidate\"] = ak.sum(ak.num(fourmuon) > 0)\n", "\n", " # require minimum dimuon mass\n", " fourmuon = fourmuon[(fourmuon.z1.p4.mass > 60.0) & (fourmuon.z2.p4.mass > 20.0)]\n", " cutflow[\"minimum dimuon mass\"] = ak.sum(ak.num(fourmuon) > 0)\n", "\n", " # choose permutation with z1 mass closest to nominal Z boson mass\n", " bestz1 = ak.singletons(ak.argmin(abs(fourmuon.z1.p4.mass - 91.1876), axis=1))\n", " fourmuon = ak.flatten(fourmuon[bestz1])\n", "\n", " h_m4mu.fill(\n", " dataset=dataset,\n", " mass=(fourmuon.z1.p4 + fourmuon.z2.p4).mass,\n", " )\n", " h_mZ1.fill(\n", " dataset=dataset,\n", " mass=fourmuon.z1.p4.mass,\n", " )\n", " h_mZ2.fill(\n", " dataset=dataset,\n", " mass=fourmuon.z2.p4.mass,\n", " )\n", " h_ptZ1mu1.fill(\n", " dataset=dataset,\n", " pt=fourmuon.z1.lep1.pt,\n", " )\n", " h_ptZ1mu2.fill(\n", " dataset=dataset,\n", " pt=fourmuon.z1.lep2.pt,\n", " )\n", " return {\n", " \"nMuons\": h_nMuons,\n", " \"mass\": h_m4mu,\n", " \"mass_z1\": h_mZ1,\n", " \"mass_z2\": h_mZ2,\n", " \"pt_z1_mu1\": h_ptZ1mu1,\n", " \"pt_z1_mu2\": h_ptZ1mu2,\n", " \"cutflow\": {dataset: cutflow},\n", " }\n", "\n", " def postprocess(self, accumulator):\n", " pass" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "11.421343088150024"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "tstart = time.time()\n",
    "\n",
    "run = processor.Runner(\n",
    "    executor=processor.DaskExecutor(client=client, compression=None),\n",
    "    schema=BaseSchema,\n",
    "    chunksize=100_000,\n",
    ")\n",
    "\n",
    "out = run(\n",
    "    fileset,\n",
    "    processor_instance=FancyDimuonProcessor(\"virtual\"),\n",
    ")\n",
    "\n",
    "elapsed = time.time() - tstart\n",
    "elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Events/s: 5801716.61849036\n"
     ]
    }
   ],
   "source": [
    "nevt = out[\"cutflow\"][\"ZZ to 4mu\"][\"all events\"] + out[\"cutflow\"][\"DoubleMuon\"][\"all events\"]\n",
    "print(\"Events/s:\", nevt / elapsed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What follows is just us looking at the output, you can execute it if you wish"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# scale ZZ simulation to expected yield\n",
    "lumi = 11.6  # 1/fb\n",
    "zzxs = 7200 * 0.0336**2  # approximate 8 TeV ZZ(4mu)\n",
    "nzz = out[\"cutflow\"][\"ZZ to 4mu\"][\"all events\"]\n",
    "\n",
    "scaled = {}\n",
    "for name, h in out.items():\n",
    "    if isinstance(h, hist.Hist):\n",
    "        scaled[name] = h.copy()\n",
    "        scaled[name].view()[1, :] *= lumi * zzxs / nzz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"nMuons\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_ylim(1, None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass\"][:, :: hist.rebin(4)].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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hrUFCH6tfv77X+2zYsKHZp6VRo0amFSM5OVnCw92PW7uKrly5IkWKFHG7Py4uTg4fPnzTvjWwzJgxw7ToaBBp3769vPfeez69Zt1vUlKS3Hvvvc77tLj57rvvNq/VVa1atZzXdWVupbU4/qy7IcAAWYTVaAHP9EM6s904+v2Z3Udm6Ad2hQoVvNo2V65cN/090CCQGRpeNBh46qaKjY296T5t0dHun5EjR8qTTz5pamP8eZwabCxWKPP3yC26kIAs7OcHkPOsXr3adBt16dLFDFE+fvy4uVj27dtnCmy1JUZpHYiOZHK1c+fOm/a7ZcsWt9ubN282XUMpW1+UFhSfOnXKBJHKlSu7XbQAOCWtT3nggQdM11Zq3UfpHWelSpUkMjLSrZZFA452lVmvNZAIMAAAuIy60aDw22+/yY8//ihvvfWWKdrVYdTdu3eXVq1aSc2aNU0Lhz6udSl6v9Z/aG2KVfSrRblaG/Pzzz/Lq6++Knv27LnpHOtopoEDB5oRO/PmzZPJkyebIdue6PNqF5OOGlqxYoWpx9E6Ey2e1efyRGtfzp49a+p3PEnvOHVIdt++fWXw4MGybNkyE9S0wPjatWum+DjQCDCAH6x4sSnnFbAh/aDWrhqd8E1H7qxZs0beffddM5RaW0a0e0SvFypUSJo2bWqChRbMzp8/37kPHaWjQ6K1C0drYi5fvmxCTkp6n9awaE2JjmTS8KIjkTzR5/3mm2/Mcz799NNy++23S9euXeXXX39NdXSRFtumrJlx5c1xjhkzxrQ8aTeUtgLp6KPly5eb1x9oYY4c2nF/6dIlM8zs4sWLZrw84G9nr8Q7Cw6/H9JCmoxdk2XDOAE70dEnR44cMTUjOndIVkwOye9R6LxHLnn5+c1fVQBAUNLgf3RMh0AfBoIUXUgAAMB2CDAAAMB2CDBAFnGtc4mOzJrJswAAnhFgAACA7RBgAACA7RBgAACA7RBgAADBKfGqyMiCf130OuCCAAMAAGyHAAMAAGyHAAMACHlr16416w2ldmnRooU5R82bN09zO139ObWFFWNjY7P0PDscDmnXrp153kWLFoXcz5ClBAAAIe+ee+6RkydP3nQevvrqK+nTp48899xz5vaXX34piYmJbtvo7Q4dOpg1fRo0aJBt53LixIkmvIQqWmAAAP6lawZrEa7Pl2t/70OvZ2QfXq5XHBkZKSVLlnS7nD9/XgYNGiSvvPKK/POf/zTbFS5c+KbtXn/9dTl79qwsXLjQ4+KV2rqjK0jr4oRWS83IkSPNY/ocugK0ru4cExNjWlR+/vnndI93586d8vbbb8v06dM9Pp8+h64aXadOHbMq9X333SdnzpyRpUuXSrVq1cwiid26dZNr1/4+x7oCt4YiV3feeafzWIMNLTAAAP9KuibyVunM7WN85Yx93yu/i0Tm9fnbLly4IJ06dTJdRhpQUjNlyhSZPXu2rFmzRsqUKZNq644GgxEjRsjBgwfNffny5TNfn3rqKRNYtKVHQ8XLL78s7du3l3379klERITH/Wno6Natm7z//vsmQKVGg8d7771ngtEjjzxiLlFRUTJ37ly5cuWKPPjggzJ58mTznHZEgAEAwMWNGzdMQMidO7fMmTMn1W6a7777Tl588UUTYjSkpNW6U7BgQbMf18BhBZcNGzY4v1+fr2zZsqamxWr1SWnAgAFmew1YaXnjjTfk3nvvNdd79uwpw4YNk8OHD0vFihXNfQ8//LAJXgQYAAA8iYj5qyXEV9ptZLW8DDokEhmTsef2kXYZbdq0SbZu3Sr58+f3uM2xY8dMAOjdu7c8++yzvh+XiOzfv9+EJNe6mSJFikiVKlXMY55o4Fm9erXs2LEj3f3XqlXLeb1EiRKmJcYKL9Z9+hpDogZm9OjRUr9+ffMDLV68uHTu3NnZHGbxVKGtBVApf/Ba8KQnU/czePBguX79+k19eHfddZdp7qpcubKp4AYA2JC2YGg3js8Xl/Ch1zOyDx+LXD/99FMZP368+Xrbbbd53CYuLs50v9SoUeOmmhF/0/CirSixsbEm/OhFdenSxXz+unLtgtLP4pRdUnqftjZZcuXKZUY2uUpKSpJg5VOA0eFh/fr1k82bN8vKlSvNC2vdurVcveo+Q2KvXr1MNbd1GTt2rPOx5ORkE160anvjxo0ya9YsE060b9By5MgRs40OW9NCJW2i04SrBUkAAPiDft5oV8uYMWOkTZs2qW6nn0d//vmnLFiwwBkg0qPdSPr550qLafU/71u2bHHed+7cOdMwUL16dY/7GTp0qOzatcscq3VREyZMkBkzZkhmFCtWzG0k1qVLl8zncY6ogVm2bJnbbQ0e2oKyfft2adq0qfN+bVlJrbBoxYoVpjjp22+/Nc1XWuGsBVLaB6cFR/pDnjZtmlSoUMFUWFs/5PXr15sfUGpvqoSEBHNxPfEAAHhDRxFpr4K2YjzxxBNy6tQpt8fDw8PNB/y4ceNMcPn6669N+Ei5nda66KiflHSEjxbOrlq1SmrXrm0+J7WFR+tY9D/9H3zwgend0IByyy23pFrfYo18SqlcuXLmczMzdKSSfq537NjRtPBow4K+7hw5jFqHhFnDylxpEVLRokXljjvuMEVDrsO0tF+xZs2aJrxYNJRo4Ni7d69zm1atWrntU7fR+9Pq3tI3jnXRIigAALyxZMkS+fXXX+Wbb76RUqVK3XTR8gmlBbva+9C2bVuP282fP9/j/rXoVsspHn30UROErJ4JbTWpW7eu3H///dKoUSPThaPHkNoIJH8aNmyYNGvWzByL9oJooKtUqZIEqzBHyg4vL2m/2QMPPGCGmmnriOXDDz+U8uXLS+nSpU0zl7as3H333WbyH6UFT/omce0O0oCTN29e80PTMfC33367GTOvJ9Oij+kJ1W09pVtPLTAaYjRk6dA0wJ+uJV6X6iP+fk9vG95K6r3xrbm+b1QbiYlkwB9CR3x8vOl60BYBT/OieE3ncbGGX2dwODTs9x7Rz29tiEjv8zvDf1W1FmbPnj1u4cUKKBZtadFE2rJlS1N05M8kp8W+egEA5BAaWEb+1dIPZEkXUv/+/WXx4sVpTtxjsYaHHTp0yHzVvrvTp0+7bWPdtvr1UttGk5in1hcAABBafAow2tuk4UWnS9ahXN4UDFkV0toSo7SPb/fu3WZKY4uOaNJwYlVd6zZa6ORKt9H7AQAAcvnabfTJJ5+YaYi1Wlqrr/WiY+KVdhPpiCIdlXT06FEz4Y6u8aAjlKwJdXTYtQaVJ598Un766SdTCzN8+HCzb6sLSAudfvnlFxkyZIgcOHDAFE199tlnZvZBINhosNcaGABAkAaYqVOnmqIaHWbmqepah0Dr8GgNKVWrVpWXXnrJTK6jw80sOiRLu5/0q7ao6HA1DTmjRo1ybqMtO1oRrq0uOtxMh1N/9NFHaY7LBwIlLilZ6r3h3mII4K9wD/jrvZE7K59QR/3oZHfp0VFKOqooLRqSvJkqGQAQXKy5Q3TCUuoW4Yk1vUpmhoszthPIYtuGt5ToiOCd/AnwN52dVidq++OPP8wHlE5RDzi73K9dM3WwOlleZibKI8AAWYw5XxDqdI0dLS/QeT503i8gJQ0vqc3Y7y0CDAAgy2lNpE6Vr91IgCttlcuKJQoIMAAAv9Cuo0zNxAukgY5JAABgOwQYIAux7hEAZA8CDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB0CDOAHros7stAjAGQ9AgwAALAdAgwAALAdAgwAALAdAgzgZ3GJN8wKrACArEOAAfysydg1EpeUzHkGgCxEgAEAALZDgAH8IDoi80vFAwBSR4AB/CAsLIzzCgB+RIABAAC2Q4ABAAC2Q4ABAAC2Q4AB/CAmMrfsG9WGcwsAfkKAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAATLhWuJ1qT5iOecQALIZAQYAANgOAQYAANgOAQYAANgOAQbIBIfDwfkDgAAgwACZEJeUzPkDgAAgwAAAANshwABZ5PshLSQ6IpzzCQDZgAADZJHoyFwSFhbG+QSAbECAAQAAtkOAAQAAtkOAAQAAtkOAATIhJjK3x+sAAP8iwAAAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAgJwdYEaPHi3169eX/PnzS/HixaVz585y8OBBt23i4+OlX79+UqRIEcmXL5906dJFTp8+7bbNsWPHpEOHDhITE2P2M3jwYLl+/brbNmvXrpW77rpLoqKipHLlyjJz5szMvE4AABCqAWbdunUmnGzevFlWrlwpSUlJ0rp1a7l69apzmwEDBsjXX38tCxYsMNv//vvv8tBDDzkfT05ONuElMTFRNm7cKLNmzTLhZMSIEc5tjhw5YrZp0aKF7Ny5U1588UV59tlnZfny5Vn1ugEAgI2FORwOR0a/+Y8//jAtKBpUmjZtKhcvXpRixYrJ3Llz5eGHHzbbHDhwQKpVqyabNm2Shg0bytKlS+X+++83waZEiRJmm2nTpsnLL79s9hcZGWmuL1myRPbs2eN8rq5du8qFCxdk2bJlHo8lISHBXCyXLl2SsmXLmmMqUKBARl8ikKZridel+oi/gvW+UW3cJrNL6zEAgGf6+V2wYMF0P78zVQOjO1eFCxc2X7dv325aZVq1auXcpmrVqlKuXDkTYJR+rVmzpjO8qDZt2pgD3rt3r3Mb131Y21j7SK17S1+wddHwAgAAcqYMB5gbN26Yrp17771X7rjjDnPfqVOnTAtKbGys27YaVvQxaxvX8GI9bj2W1jYacuLi4jwez7Bhw0ygsi7Hjx/P6EsDAABBLsNt2loLo10869evl2Cgxb56AQAAOV+GWmD69+8vixcvljVr1kiZMmWc95csWdIU52qtiisdhaSPWdukHJVk3U5vG+0Li46OzsghAwCAUA0wWu+r4WXhwoWyevVqqVChgtvjdevWlYiICFm1apXzPh1mrcOmGzVqZG7r1927d8uZM2ec2+iIJg0n1atXd27jug9rG2sfAAAgtOXytdvok08+MaOMdC4YrVXRi1WXosWzPXv2lIEDB5rWGS3qffrpp03w0BFISodda1B58skn5aeffjJDo4cPH272bXUB9enTR3755RcZMmSIGcU0ZcoU+eyzz8wQbcCOdDSSjkoCAAQgwEydOtUUyDZv3lxKlSrlvMyfP9+5zYQJE8wwaZ3ATodWa3fQl19+6Xw8PDzcdD/pVw02TzzxhHTv3l1GjRrl3EZbdnQYtba61K5dW95++2356KOPzEgkAAAAn4p4vZkyJk+ePPL++++bS2rKly8v33zzTZr70ZC0Y8cOfkIAAOAmrIUEAABshwADZBOtgcnExNcAABcEGCCb1HtjlcQlJXO+ASALEGAAAIDtEGCADHJdrNGT6Ihw2Ta8JecXAPyAAAP4SVhYGCtQA4CfEGAAAIDtEGAAAIDtEGCADNDh0N4sDRATmVv2jWIGaQDIagQYIAN0OLQOiwYABAYBBgAA2A4BBsgCOlxah00DALIHAQbIAlrrosOmAQDZgwADAABshwADAABshwADZJIOk9YuJABA9iHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAD66lnhdqo9YznkDgAAiwAAAANshwAAAANshwAA+cjgcnDMACDACDOCjuKRkzhkABBgBBgAA2A4BBsiE74e0kOiIcM4hAGQzAgyQCdGRuSQsLIxzCADZjAADAABshwADAABshwAD+CgmMrfH6wCA7EOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAfzsWuJ1j9cBABlHgAF8oAGk+ojlnDMACDACDAAAsB0CDJCN4hJviMPh4JwDQCYRYAAvafDIbA1Lk7FrJC4pmXMOAJlEgAG8pMGj3hurOF8AEAQIMICfRUeEc44BIIsRYIAM2ja8pVfhJCwsjHMMAFmMAANkkC7kSDgBgMAgwABeYP4XALB5gPnuu++kY8eOUrp0afO/z0WLFrk9/tRTT5n7XS9t27Z12+bPP/+Uxx9/XAoUKCCxsbHSs2dPuXLlits2u3btkiZNmkiePHmkbNmyMnbs2Iy+RiDgLTX7RrXhpwAAgQwwV69eldq1a8v777+f6jYaWE6ePOm8zJs3z+1xDS979+6VlStXyuLFi00o6t27t/PxS5cuSevWraV8+fKyfft2GTdunIwcOVI+/PBDXw8X8AsNJBpMAACB4fNf4Hbt2plLWqKioqRkyZIeH9u/f78sW7ZMfvjhB6lXr565b/LkydK+fXsZP368admZM2eOJCYmyvTp0yUyMlJq1KghO3fulHfeecct6ADZhcnnACAEamDWrl0rxYsXlypVqkjfvn3l3Llzzsc2bdpkuo2s8KJatWoluXLlki1btji3adq0qQkvljZt2sjBgwfl/PnzHp8zISHBtNy4XoCswuRzAJDDA4x2H82ePVtWrVol//M//yPr1q0zLTbJyX/NPnrq1CkTblzlzp1bChcubB6ztilRooTbNtZta5uURo8eLQULFnRetG4GAADkTFneid+1a1fn9Zo1a0qtWrWkUqVKplWmZcuW4i/Dhg2TgQMHOm9rCwwhBv7w/ZAWTE4HADl9GHXFihWlaNGicujQIXNba2POnDnjts3169fNyCSrbka/nj592m0b63ZqtTVad6OjmlwvgD9ER+Zi/hcAyOkB5sSJE6YGplSpUuZ2o0aN5MKFC2Z0kWX16tVy48YNadCggXMbHZmUlJTk3EZHLGlNTaFChfx9yAAAIKcFGJ2vRUcE6UUdOXLEXD927Jh5bPDgwbJ582Y5evSoqYPp1KmTVK5c2RThqmrVqpk6mV69esnWrVtlw4YN0r9/f9P1pCOQVLdu3UwBr84Po8Ot58+fL5MmTXLrIgIAAKHL5wCzbds2qVOnjrkoDRV6fcSIERIeHm4moHvggQfk9ttvNwGkbt268v3335suHosOk65ataqpidHh040bN3ab40WLcFesWGHCkX7/Sy+9ZPbPEGoEahZe11Womf8FAGxYxNu8efM058RYvnx5uvvQEUdz585Ncxst/tXgAwAAkBJrIQGptLrcOnSJueh1AEBwIcAA6YhL/GsOIwBA8CDAACloF6lrq0uTsWs5RwAQZAgwgIdlA1yLdgEAwYcAA/hg2/CWzMILAEGAAAP4QIdQh4WFcc4AIMAIMAAAwHYIMICX9o1qwyR2ABAkCDAAAMB2CDCAFyjeBYDgQoABvEDxLgAEFwIMAADI+Ys5AtlBZ8KtPmJ5wItnKdwFgOBECwwAALAdAgyCdj0i19YY19sAABBgELTrEVl0XaIKw75xW2ARABDaCDBAKrU3/qL7J4wBQOYQYGAb564kyK1Dl5iLPwJAdoQXAEDWYBQSbKPJ2LV+2S/BBQDshxYY2JYGD3+2yPgThckAkDkEGNhSVgaAQIxw0sJk10JlAIBvCDAISulNXKcB4FpissdA42vLTGpB4vshLSQ6ItznYwcA+B8BBrZ1/mrSTUOtz16JT7cQ19uAEx2ZS8LCwrLkWDUI6YKQAICsQYBBjqJBJqu6mrKy9UWDUKCWQwCAnIgAg6CXWsuFNzUkrrUmVsuLawuNXo9z6YpyXQMpb1REpo4bAOA/BBjYVqf3N2TJUOnsquHVFhgNRgCAzKNNG0FPP/iPjulgrmuNS8puosxqOm6tW2tP0Xx5snT/AICsR4CBrWSkLkVbWOKSvJsnhjoVALAHAgxsJSOjgmq8yvIAAJDTUAMDAABshwADW7F7IazrvDN2W/4AAIIJXUjIETTUuNavpLdAoxbrZnUxMAAg+9ACg5AMOzrS6Mjo9m5zzOj17Fw6IC7xRkDWYQKAnIAAA9tJOS2/L8HDtaUm5ey4ej2rlg7wRpOxa1jQEQAyiAAD28lo8GBxRgDIOaiBQY5upXGtcymcN+KmoOM6SV52HRcAIPMIMLCl9IKHp8UTs7N7KDXBcAwAkBPQhYSQHKUEALA3/qIjx8ru7iFf5rFJa4g3ACB9tMAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAICcH2C+++476dixo5QuXdqsrLto0SK3xx0Oh4wYMUJKlSol0dHR0qpVK/n555/dtvnzzz/l8ccflwIFCkhsbKz07NlTrly54rbNrl27pEmTJpInTx4pW7asjB07NqOvEQAAhHqAuXr1qtSuXVvef/99j49r0Hj33Xdl2rRpsmXLFsmbN6+0adNG4uPjndtoeNm7d6+sXLlSFi9ebEJR7969nY9funRJWrduLeXLl5ft27fLuHHjZOTIkfLhhx9m9HUCAIBQXo26Xbt25uKJtr5MnDhRhg8fLp06dTL3zZ49W0qUKGFaarp27Sr79++XZcuWyQ8//CD16tUz20yePFnat28v48ePNy07c+bMkcTERJk+fbpERkZKjRo1ZOfOnfLOO++4BR0AABCasrQG5siRI3Lq1CnTbWQpWLCgNGjQQDZt2mRu61ftNrLCi9Ltc+XKZVpsrG2aNm1qwotFW3EOHjwo58+f9/jcCQkJpuXG9QIEu+ojlsu1xOuBPgwACO0Ao+FFaYuLK71tPaZfixcv7vZ47ty5pXDhwm7beNqH63OkNHr0aBOWrIvWzQAAgJwpx4xCGjZsmFy8eNF5OX78eKAPCfCKtsBo9ysAIEABpmTJkubr6dOn3e7X29Zj+vXMmTNuj1+/ft2MTHLdxtM+XJ8jpaioKDOqyfUC2EG9N1ZJXFJyoA8DAEI3wFSoUMEEjFWrVjnv01oUrW1p1KiRua1fL1y4YEYXWVavXi03btwwtTLWNjoyKSkpybmNjliqUqWKFCpUKCsPGQAAhEKA0fladESQXqzCXb1+7NgxMy/Miy++KG+88YZ89dVXsnv3bunevbsZWdS5c2ezfbVq1aRt27bSq1cv2bp1q2zYsEH69+9vRijpdqpbt26mgFfnh9Hh1vPnz5dJkybJwIEDs/r1A9kuOiJctg1vyZkHgOwcRr1t2zZp0aKF87YVKnr06CEzZ86UIUOGmLlidLiztrQ0btzYDJvWCeksOkxaQ0vLli3N6KMuXbqYuWMsWoS7YsUK6devn9StW1eKFi1qJsdjCDVyAg36MZE+/+oBAFyEOXJo9aB2XWkQ0oJe6mHsWdiqQ4zVvlFtctwHvuvry6mvEQD8+fmdY0YhAXaiYcW1G4m5YADANwQYAABgOwQYIAjEJd5gLhgA8AEBBggCTcauYS4YAPABAQYAANgOAQYI4HwwAICMIcAAAZwPBgCQMQQYIIBDqXX+FwCA7wgwAADAdggwAADAdggwAADAdggwAADAdggwAADAdggwAADAdggwQJCoPmI5q1IDgJcIMAAAwHYIMEAQuZZ4nVWpAcALBBggiNR7YxWrUgOAFwgwAADAdggwQIBXpN42vCU/AwDwEQEGCPCK1LqoIwDANwQYIMBYlRoAfEeAAQAAtkOAAQAAtkOAAYJk/hdP1wEAnhFggCATl3iDyewAIB0EGCDINBm7hsnsACAdBBggCLGwIwCkjQADBMmEdgAA7xFggCCZ0C4lFnYEgNQRYIAgxcKOAJA6AgwQBJiNFwB8Q4ABggQLOwKA9wgwQJBgYUcA8B4BBgiyrqRtw1s6bzMrLwB4RoABghiz8gKAZwQYIIgxKy8AeEaAAQAAtkOAAYIMs/ICQPoIMIANZuUFALgjwABBhkntACB9BBgAAGA7BBgAAGA7BBgAAGA7BBgAAGA7BBgAAGA7BBggyFUfsZw1kQAgBQIMYAO6qKPD4Qj0YQBA0CDAADZQ741VEpeUHOjDAICgQYABAAC2k+UBZuTIkWYqdNdL1apVnY/Hx8dLv379pEiRIpIvXz7p0qWLnD592m0fx44dkw4dOkhMTIwUL15cBg8eLNevX8/qQwWCej2kbcNbBvowACC0WmBq1KghJ0+edF7Wr1/vfGzAgAHy9ddfy4IFC2TdunXy+++/y0MPPeR8PDk52YSXxMRE2bhxo8yaNUtmzpwpI0aM8MehAkFJg3/RfHlk36g2gT4UAAhKuf2y09y5pWTJkjfdf/HiRfn4449l7ty5ct9995n7ZsyYIdWqVZPNmzdLw4YNZcWKFbJv3z759ttvpUSJEnLnnXfK66+/Li+//LJp3YmMjPTHIQNBW7xrOXclUaILhbPYIwD4qwXm559/ltKlS0vFihXl8ccfN11Cavv27ZKUlCStWrVybqvdS+XKlZNNmzaZ2/q1Zs2aJrxY2rRpI5cuXZK9e/em+pwJCQlmG9cLkJM0GbuGQl4A8FeAadCggenyWbZsmUydOlWOHDkiTZo0kcuXL8upU6dMC0psbKzb92hY0ceUfnUNL9bj1mOpGT16tBQsWNB5KVu2bFa/NAAAkFO7kNq1a+e8XqtWLRNoypcvL5999plER0eLvwwbNkwGDhzovK0tMIQY5IRiXgBAAIZRa2vL7bffLocOHTJ1MVqce+HCBbdtdBSSVTOjX1OOSrJue6qrsURFRUmBAgXcLkBOKOYFAAQgwFy5ckUOHz4spUqVkrp160pERISsWrXK+fjBgwdNjUyjRo3Mbf26e/duOXPmjHOblStXmkBSvXp1fx8uEFRiInMzEgkAsqMLadCgQdKxY0fTbaRDpF999VUJDw+Xxx57zNSm9OzZ03T1FC5c2ISS559/3oQWHYGkWrdubYLKk08+KWPHjjV1L8OHDzdzx2grCxDq6yIpHV6t4QYAQlWW/wU8ceKECSvnzp2TYsWKSePGjc0Qab2uJkyYILly5TIT2OnIIR1hNGXKFOf3a9hZvHix9O3b1wSbvHnzSo8ePWTUqFFZfaiArYdXa30MXUwAQlWYI4euEKdFvNrio3PPUA9jzw9oWhtuPheuaIUBEMqf36yFBAAAbIcAA9h0XSRtlXGdqRcAQgkBBghyWueSWsGuBpgc2gsMAGkiwAA2oAHm6JgONw2prvfGKpYXABCSCDAAAMB2CDCAzethqIMBEIoIMIDN6mGK5svjFmLiEm9QBwMg5BBgAJtrMnYNdTAAQg4BBgAA2A4BBrBpLQwAhDICDGBDeaMi3IZU66R2tw5dImevxFMPAyAkEGCAHIR5YQCECgIMAACwHQIMkMPWSAKAUECAAXLYGklaD0MtDICcjgAD2BhrJAEIVQQYAABgOwQYIAegHgZAqCHAADlojSTXuWEAICcjwAAAANshwAA5yLXE687r564kMisvgByLAAPk4FWqKwz7hiHVAHIkAgyQw7G8AICciAAD5CCsUg0gVBBggBy2SvWR0e1ZYgBAjkeAAUJgSPXVhOty69Al5sIyAwByAgIMEAIjkn6/EO+8Tk0MgJyAAAOEgE7vbwj0IQBAliLAAAAA2yHAADkUI5IA5GQEGCAHj0hibSQAOVXuQB8AAP+2wlgh5lpistR741tzvfqI5c5t9r7W2oQdALATAgyQw4dUx0Sm/Wsel5RMgAFgOwQYIMTFJd5wDrnWFhsNPQAQ7KiBAUKEhpNtw1t6XPRRu5T0cu5qQkCODQB8RQsMEGIz9B4d08G0uLjWwbhOcmehNgZAMKMFBoBHNV5dwbIDAIIWAQYI4dFJetk2vFWq26VcdsDhcJhQY62r9MfleNOaoxd9DACyC11IQIiPTkptqLXF6mr6fkgLyRMRLvXf/LubyfW61tdoFxUAZAcCDBDiPIUZT0FGi33Tog0wrgtIWhjZBMAfCDAAfJo3JjXxSTek/ps3FwbTMgPAH6iBAeCTFS829Xh/ai001jwz1MkAyEq0wAC4iWtdjFWba81v502troac1hO/uynYaB1NkXyRN+1Tw401hJvh2wC8QYAB4FNXko42SqvoV0VHhnv83vTqaKzh2xp0CueNdAYc1zoafX7XkVHU2AChiQADwC9Fv5mRMujoc+hzaXBJ+VzU2AChiQADINNhxrXLyZuh2a6seWjS2kb3kdp+rBob126plF1UnlppaMkB7C3MkUNnn7p06ZIULFhQLl68KAUKFAj04cBHrlPd6wdhRkfGIPBcg4L+tdHrfwWKvx7X68pT60pWsWpvXKXVkpMy3FjHyUKXQPB8fvOpACBb62nyRnn+s+NLSHUtEvaGN7U3rqtyewpSP/x3K4mJdA9e+tpoyQECgxYYBCVaYEJTytYalaLnx7DqYZS/Wm28bdVJ+fzW/a7HmPKYU2uJ8lcLT0ZCFq1QSO/9sXDhQmnevLkULlxYAtECQ4BBUCLAwFuuH7SewozW2GjLyd/vrewJPBpkUg4hT6slSI/TCjmuwSY1aQW8lNvoPt27y/4+J57ClDfnMq0QlFr4sY4l5f10zdnP7t27pVatWpI/f3554YUXZMCAAVkWZHJEgHn//fdl3LhxcurUKaldu7ZMnjxZ7r77bq++lxoYeyPAICO8aTVIrybHfX9/fZDXfzP7W3iCXcpg6Cq18KPS65rzhTchLuXPWaV3PbVWP09BK7VWQ0+F5Cnfm2ntN7XnyOjxZPa5Urbg7dixQ+rWrStdunSRpUuXSnh4eJYFGdsHmPnz50v37t1l2rRp0qBBA5k4caIsWLBADh48KMWLFw9ogLl25WKW7g8eznFisvN/q9vNH0rKtRAY3gQe6379Y9p07BrzNV7+KgjOI/GS8iPD9fEoiZcED9ddpXZ/atvoc4rLc6S3n7T27+mxtLa3Xm9qrzG17TPL9fk8Hafr86T38/FEW9A8BTbXv1VpWTmgmfxjwjqv95vec3yfgePJ6HOlPHbdz8F9u6Vxk+ayfft2KVOmjIwfP940OmRFkLF9gNHQUr9+fXnvvffM7Rs3bkjZsmXl+eefl6FDh960fUJCgrlY9IWXK1dOjh8/nvWjkEaXydr9AYANXHNEyt0JU831rVF9JSYsMVPbuz7ual3kC9IscVKG7k/5PJ6eQ7dRKe9Puf/Uns91P+k9lzfHn9p+09rfVg/beLP/tM5VWq8j5ff93+k4aTbzmgkwd911l7n/zJkzbkGmT58+5jNbw4ivAUY/7y9cuJD29zqCUEJCgiM8PNyxcOFCt/u7d+/ueOCBBzx+z6uvvqpBjAvngPcA7wHeA7wHeA9I9pyD7du33/R5vHv3bkexYsUyve/jx4+nmRWCsl3+7NmzkpycLCVKlHC7X28fOHDA4/cMGzZMBg4c6LytLTZ//vmnFClSJEsLxKxk6JeWnRyI88W54n3F76Bd8PfKexs2bJD27du73actMFq3OmXKFNMCM3jw4Ay1wGjH0OXLl6V06dJpbheUASYjoqKizMVVbGys355PwwsBhvPFeyuw+D3kXPG+Coy8efOmGly0MSGzxbzehJ6gDDBFixY1J+H06dNu9+vtkiVLBuy4AADA39566y3nKKSsCC6+yCVBKDIy0gzPWrVqlVuXkN5u1KhRQI8NAIBQFxERYb6uWLHCBJejR4/K66+/nm3hJWhbYJSekB49eki9evXM3C86jPrq1avy9NNPB/S4tJvq1Vdfvam7Cpwv3lv8HgYj/mZxrvyhTp068sgjj5jP5lKlSkkgBO0waqVDqK2J7O6880559913zfBqAAAQ2oI6wAAAANimBgYAACAtBBgAAGA7BBgAAGA7BBgAAGA7BBgf6SJVt956q+TJk8eMiNq6dauEupEjR5rlGlwvVatWdT4eHx8v/fr1M8s65MuXzyy/nnKSwpzqu+++k44dO5opsfW8LFq0yO1xraEfMWKEGYYYHR0trVq1kp9//tltG10S4/HHHzezzurs0j179pQrV65IqJ2rp5566qb3Wdu2bUPyXI0ePdosdps/f34pXry4dO7cWQ4ePOi2jTe/d8eOHZMOHTpITEyM2Y9O/X79+nUJtXPVvHnzm95buhBhqJ2rqVOnSq1atZwzXOu8azpJXbC+pwgwPpg/f76Zn0bngfnxxx+ldu3a0qZNGzONcqirUaOGnDx50nlZv3698zGdmfHrr7+WBQsWyLp16+T333+Xhx56SEKBzl2k7xMNvp6MHTvWTA8wbdo02bJli5meW99T+ofCoh/Ie/fulZUrV8rixYvNB33v3r0l1M6V0sDi+j6bN2+e2+Ohcq7090g/SDZv3mxea1JSkrRu3dqcQ29/73S9Of2gSUxMlI0bN8qsWbNk5syZJlCH2rlSvXr1cntv6e9mqJ2rMmXKyJgxY8wK09u2bZP77rtPOnXqZH6ngvI9lallo0PM3Xff7ejXr5/zdnJysqN06dKO0aNHO0KZrgReu3Ztj49duHDBERER4ViwYIHzvv3795uVRjdt2uQIJfqaXVdYv3HjhqNkyZKOcePGuZ2vqKgox7x588ztffv2me/74YcfnNssXbrUERYW5vjtt98coXKuVI8ePRydOnVK9XtC9VypM2fOmNe+bt06r3/vvvnmG0euXLkcp06dcm4zdepUR4ECBRwJCQmOUDlXqlmzZo4XXngh1e8J1XOlChUq5Pjoo4+C8j1FC4yXNFFqKtUmfkuuXLnM7U2bNkmo024PbfqvWLGi+V+wNiMqPWf6Px7X86bdS+XKlQv583bkyBEzSaPrudEFzLRr0npP6VftCtEZqS26vb73tMUm1Kxdu9Y0S1epUkX69u0r586dcz4Wyufq4sWL5qs1jbs3v3f6tWbNmlKiRAnnNtr6pysyW//jDoVzZZkzZ45Zh++OO+6QYcOGybVr15yPheK5Sk5Olk8//dS0VGlXUjC+p4J2KYFgc/bsWfMDdf3BKL194MABCWX6gavNhPqhok2vr732mjRp0kT27NljPqB1bauUK4PredPHQpn1+j29p6zH9Kt+YLvKnTu3+eMbaudPu4+0ubpChQpy+PBheeWVV6Rdu3bmj6YuJBeq50rXiXvxxRfl3nvvNR++ypvfO/3q6b1nPRYq50p169ZNypcvb/4TtmvXLnn55ZdNncyXX34Zcudq9+7dJrBoN7bWuSxcuFCqV68uO3fuDLr3FAEGmaYfIhYtANNAo38MPvvsM1OYCmSFrl27Oq/r//L0vVapUiXTKtOyZcuQPcla36H/WXCtO4Nv58q1TkrfW1pUr+8pDcr6HgslVapUMWFFW6o+//xzsyah1rsEI7qQvKRNi/q/vJQV13q7ZMmS/vjZ2JYm9Ntvv10OHTpkzo12v124cMFtG86bON83ab2n9GvKInGt6NfRNqH+vtPuSv291PdZqJ6r/v37m2LlNWvWmAJMize/d/rV03vPeixUzpUn1pp7ru+tUDlXkZGRUrlyZalbt64ZwaWF9ZMmTQrK9xQBxocfqv5AV61a5dYcqbe1uQ1/02Gr+j8X/V+MnjNddt31vGnTrNbIhPp5064Q/aV2PTfaV6z1Gta50a/6B0P7ny2rV682771QX9j0xIkTpgbGWgk3lM6V1jnrB7I27+tr1PeSK29+7/Srdhe4hj4dpaPDZ7XLIFTOlSfaAqFc31uhcK480d+fhISE4HxPZXlZcA726aefmhEiM2fONCMeevfu7YiNjXWruA5FL730kmPt2rWOI0eOODZs2OBo1aqVo2jRoqbaX/Xp08dRrlw5x+rVqx3btm1zNGrUyFxCweXLlx07duwwF/11e+edd8z1X3/91Tw+ZswY8x76z3/+49i1a5cZZVOhQgVHXFyccx9t27Z11KlTx7FlyxbH+vXrHbfddpvjsccec4TSudLHBg0aZEY76Pvs22+/ddx1113mXMTHx4fcuerbt6+jYMGC5vfu5MmTzsu1a9ec26T3e3f9+nXHHXfc4WjdurVj586djmXLljmKFSvmGDZsmCOUztWhQ4cco0aNMudI31v6u1ixYkVH06ZNQ+5cDR061IzO0vOgf4/0to7iW7FiRVC+pwgwPpo8ebL5AUZGRpph1Zs3b3aEukcffdRRqlQpc05uueUWc1v/KFj0w/i5554zw/FiYmIcDz74oPkDEgrWrFljPoxTXnRIsDWU+l//+pejRIkSJhy3bNnScfDgQbd9nDt3znwI58uXzwxHfPrpp80HeiidK/2w0T+K+sdQh3KWL1/e0atXr5v+8xAq58rTedLLjBkzfPq9O3r0qKNdu3aO6Oho858O/c9IUlKSI5TO1bFjx0xYKVy4sPkdrFy5smPw4MGOixcvhty5euaZZ8zvlv4t1981/XtkhZdgfE+F6T9Z364DAADgP9TAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAALCF5s2bS1hYmLlYi+0FwlNPPeU8jkWLFgXsOIBQR4ABYBu9evWSkydPyh133OF2/6lTp+SFF16QypUrS548eaREiRJy7733ytSpU+XatWte7btjx47Stm1bj499//33JrDs2rVLJk2aZI4BQGDlDvDzA4DXYmJipGTJkm73/fLLLyasxMbGyltvvSU1a9aUqKgo2b17t3z44Ydyyy23yAMPPJDuvnv27CldunSREydOSJkyZdwemzFjhtSrV09q1aplbhcsWJCfGhBgtMAA8MnRo0dNa8QXX3whTZs2lejoaKlfv74cO3bMtFQ0bNjQBI2WLVvKhQsX/H52n3vuOcmdO7ds27ZNHnnkEalWrZpUrFhROnXqJEuWLDEtK+rGjRsyevRoqVChgjnm2rVry+eff+7cz/333y/FihWTmTNnuu3/ypUrsmDBAhNwAAQPAgwAn/z000/mq3bPaIvHxo0b5fTp0/LEE0/ImDFj5L333pM1a9aY7bTlwp/OnTsnK1askH79+knevHk9bqNhS2l4mT17tkybNk327t0rAwYMMMe8bt0687iGoO7du5sA43A4nN+v4SU5OVkee+wxv74WAL6hCwmAT7SAtnDhwjJ//nwpUqSIua9Zs2ayfv16Ewy09UVpq4zWpvjToUOHTNioUqWK2/1FixaV+Ph4c13DzahRo0zY+vbbb6VRo0bmfm2l0WP+4IMPzPGrZ555RsaNG2dCjRYNKw1h2rVEtxEQXGiBAeATbVl58MEHneFFaffRo48+6gwv1n3aXRMIW7duNUGrRo0akpCQYIKOFvP+4x//kHz58jkv2iJz+PBh5/dVrVpV7rnnHpk+fbq5rd+n3WJ0HwHBhwADwCcaDBo0aHBTqNHaF4u2fhw8eNDUmSht9bBaY3788UfTopHW/d7SUUfaRaTP5UpbV/QxrXWx6liU1sTo8VuXffv2udXBKA0rWt9z+fJl0/pSqVIlZwsNgOBBgAHgtUuXLpki3jp16jjvO3LkiFy8eNHtPh0BpF07OiJIv545c8Y5ekgf09E8qd3vC20F0lYVrbu5evVqqttVr17djEzSViENNq6XsmXLum2rhcC5cuWSuXPnmhYa7Vay6mgABA9qYAB4TVtawsPD3eZhsWpiypcv73aftlxoN4120bh2JWlQ0W4aHf7s6X5fTZkyxQyj1mHOI0eONCFIA8gPP/wgBw4ckLp160r+/Pll0KBBpnBXRyM1btzYhK4NGzZIgQIFpEePHs796TFrd9iwYcNMYNOJ6wAEH1pgAPgUYLRgVieLc73PtfXFus/qPtLJ37QlxrJjxw5zO7X7faVBSb+3VatWJnTo82qYmTx5sgktr7/+utlOv/7rX/8yo5F0qLVOWqddSp7qdLQb6fz589KmTRspXbq0z8cEwP/CHK7jBQEgi7322mumzkWHXWurSIsWLUzLhgYKT/dr64knOirozjvvlIkTJwbFz0i7lRYuXCidO3cO9KEAIYkWGAB+pS0tGky0ZUSLYkuVKmXqS1K7P73uIu3i0e6mQOnTp485BgCBRQsMAL/S7hrt4nHtdkrr/tT89ttvEhcXZ66XK1dOIiMjJRC08FiDl9LQldoEegD8iyJeAH6jI4O06DdlSEnt/rTomkbBoHjx4uYCILBogQEAALZDDQwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAALAdAgwAABC7+f/+d47aPWCecQAAAABJRU5ErkJggg==",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass_z1\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass_z2\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "ax.set_xlim(2, 300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"pt_z1_mu1\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"pt_z1_mu2\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.73838996887207"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "tstart = time.time()\n",
    "\n",
    "to_compute = apply_to_fileset(\n",
    "    FancyDimuonProcessor(\"dask\"),\n",
    "    dataset_runnable,\n",
    "    schemaclass=BaseSchema,\n",
    ")\n",
    "(out,) = dask.compute(to_compute)\n",
    "\n",
    "elapsed = time.time() - tstart\n",
    "elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Events/s: 2228210.6082191938\n"
     ]
    }
   ],
   "source": [
    "nevt = out[\"ZZ to 4mu\"][\"cutflow\"][\"ZZ to 4mu\"][\"all events\"] + out[\"DoubleMuon\"][\"cutflow\"][\"DoubleMuon\"][\"all events\"]\n",
    "print(\"Events/s:\", (nevt / elapsed))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What follows is just us looking at the output, you can execute it if you wish"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# scale ZZ simulation to expected yield\n",
    "lumi = 11.6  # 1/fb\n",
    "zzxs = 7200 * 0.0336**2  # approximate 8 TeV ZZ(4mu)\n",
    "nzz = out[\"ZZ to 4mu\"][\"cutflow\"][\"ZZ to 4mu\"][\"all events\"]\n",
    "\n",
    "scaled = {}\n",
    "for (name1, h1), (nam2, h2) in zip(out[\"DoubleMuon\"].items(), out[\"ZZ to 4mu\"].items()):\n",
    "    if isinstance(h1, hist.Hist) and isinstance(h2, hist.Hist):\n",
    "        scaled[name1] = h1.copy() + h2.copy()\n",
    "        scaled[name1].view()[1, :] *= lumi * zzxs / nzz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"nMuons\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_ylim(1, None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass\"][:, :: hist.rebin(4)].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass_z1\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"mass_z2\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "ax.set_xlim(2, 300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"pt_z1_mu1\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "scaled[\"pt_z1_mu2\"].plot1d(ax=ax, overlay=\"dataset\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "awkward-coffea",
   "language": "python",
   "name": "awkward-coffea"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}