notebooks/tests.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0926d399-e4f7-4ac0-a5ee-9660717c1978",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "# Tests for study rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8e0686e9-faab-43ba-aadc-25bd54bfd38a",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "65d9919d-a359-4f91-af8f-112619c195c3",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6e5eab79-e64f-4742-8e48-3e2676fc048a",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9c7ae2ce-7010-4679-abf6-d176af00046f",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f7ff3f59-243f-4216-8d36-16866a4c5990",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "10386758-83fd-478a-ba88-d0f4c670105d",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "11ceb0e5-c2a0-4e68-af13-7e84755256a7",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "from influenzanet.api.management_api import ManagementAPIClient"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "902db5f6-3913-46d2-84f3-4de1f1f4c238",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Fill this object using the credential of a staging platform you own:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a6f593bd-af53-4154-ab65-cd93c6da9c23",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "credentials = {\n",
    "    \"management_api_url\": \"\",\n",
    "    \"participant_api_url\": \"\",\n",
    "    \"login_credentials\": {\n",
    "        \"email\": \"\",\n",
    "        \"password\": \"\",\n",
    "        \"instanceId\": \"\",\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfac227e-6844-487f-9623-3dabfe31b596",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Fill these variables with a `profile_id`/`participant_id` present on your staging infrastructure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "027c2177-8b6c-4c5a-a4ad-f8c940556d5d",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "profile_id = ''\n",
    "participant_id = ''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dd96fab8-416b-4426-9c6f-656c1cd517f3",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def login():\n",
    "    global api\n",
    "    \n",
    "    try:\n",
    "        api.renew_token()\n",
    "    except:\n",
    "        api = ManagementAPIClient(**credentials, verbose=False)\n",
    "    \n",
    "    return api"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d66563db-e397-466a-bee3-750a723cef44",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "def run_rule(rule, participant_id=participant_id):\n",
    "    \"\"\"\n",
    "    Run a custom rule against a `participant_id`. If `rule` is a dict it is used\n",
    "    directly, otherwise a file named `rule` is searched among the defined custom rules\n",
    "    for the study\n",
    "    \"\"\"\n",
    "    api = login()\n",
    "\n",
    "    if type(rule) is str:\n",
    "        rules_path = \"../output/verdi/customRules\"\n",
    "        rule_file = f\"{rules_path}/{rule}.json\"\n",
    "        with open(rule_file) as f:\n",
    "            rule = json.load(f)\n",
    "\n",
    "    api.run_custom_study_rules_for_single_participant(\"common\", rule, participant_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f2d6e848-6801-4efe-9dd2-13c35671f2b9",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "def get_reports(reportKey, profile_id=profile_id):\n",
    "    \"\"\"\n",
    "    Download reports with key `reportKey` for `profile_id`\n",
    "    \"\"\"\n",
    "    api = login()\n",
    "    \n",
    "    reports = requests.get(\n",
    "        f\"{credentials['participant_api_url']}/v1/reports\",\n",
    "        headers=api.auth_header,\n",
    "        params={\"profileId\": profile_id, \"reportKey\": reportKey},\n",
    "    ).json()\n",
    "\n",
    "    if \"reports\" not in reports:\n",
    "        return pd.DataFrame()\n",
    "    \n",
    "    dates = pd.DataFrame(\n",
    "        [\n",
    "            {data[\"key\"]: data[\"value\"] for data in report[\"data\"]}\n",
    "            for report in reports[\"reports\"]\n",
    "        ]\n",
    "    )\n",
    "\n",
    "    for col in dates.columns:\n",
    "        dates[col] = pd.to_datetime(dates[col].astype(float), unit=\"s\")\n",
    "\n",
    "    dates = dates.sort_values('referenceDate').reset_index(drop=True)\n",
    "        \n",
    "    return dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f8f60269-4816-4c74-a059-279f6fccac1e",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def setTestDate(testDate):\n",
    "    \"\"\"\n",
    "    Set `intervalTestDate` to `testDate`\n",
    "    \"\"\"\n",
    "    timestamp = int(datetime.timestamp(testDate))\n",
    "\n",
    "    rule = {\n",
    "        \"name\": \"DO\",\n",
    "        \"data\": [\n",
    "            {\n",
    "                \"dtype\": \"exp\",\n",
    "                \"exp\": {\n",
    "                    \"name\": \"UPDATE_FLAG\",\n",
    "                    \"data\": [\n",
    "                        {\"dtype\": \"str\", \"str\": \"intervalTestDate\"},\n",
    "                        {\n",
    "                            \"dtype\": \"exp\",\n",
    "                            \"exp\": {\n",
    "                                \"name\": \"timestampWithOffset\",\n",
    "                                \"data\": [\n",
    "                                    {\"dtype\": \"num\", \"num\": 0},\n",
    "                                    {\"dtype\": \"num\", \"num\": timestamp},\n",
    "                                ],\n",
    "                            },\n",
    "                        },\n",
    "                    ],\n",
    "                },\n",
    "            }\n",
    "        ],\n",
    "    }\n",
    "\n",
    "    return [rule]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e975b1c-9ebd-4284-a1bf-b6624990c9f1",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Test entry, reassign, expire rules"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64ea5397-734f-4456-a8a8-4a33b52025be",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Starting from today, for each day in the following 365 days, simulate:\n",
    "\n",
    "1. study entry\n",
    "2. survey reassign (1 week after the first assignation)\n",
    "3. survey expire (4 weeks after the second assignation)\n",
    "\n",
    "Each rule stores the dates of interest into a participant report."
   ]
  },
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   "metadata": {
    "collapsed": false,
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     "outputs_hidden": false
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      "\n"
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    }
   ],
   "source": [
    "testDate = datetime.now()\n",
    "run_rule(\"testCleanupTestDate\")\n",
    "run_rule(\"testCleanupIntervalAndSurvey\")\n",
    "for i in tqdm(range(365)):\n",
    "    run_rule(setTestDate(testDate))\n",
    "    run_rule(\"testEntryRule\")\n",
    "    run_rule(\"testReassignRule\")\n",
    "    run_rule(\"testExpireRule\")\n",
    "    run_rule(\"testCleanupIntervalAndSurvey\")\n",
    "    testDate += timedelta(days=1)\n",
    "run_rule(\"testCleanupTestDate\")\n",
    "run_rule(\"testCleanupIntervalAndSurvey\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3e6e2be8-ea21-4aad-88f7-9dd46b4225ed",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "entryDates = get_reports(\"testEntryRule\")\n",
    "reassignDates = get_reports(\"testReassignRule.after\")\n",
    "expireDates = get_reports(\"testExpireRule.after\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d3b89e62-e1ad-4d06-8fc0-498d161078df",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotDates(dates, x='referenceDate', y='startDate'):\n",
    "    \"\"\"\n",
    "    Plot dates outlining every 13 week window from the beginning of the year\n",
    "    \"\"\"\n",
    "    \n",
    "    xQuarters = pd.date_range(\n",
    "        f\"{dates[x].min().year}\",\n",
    "        dates[x].max(),\n",
    "        freq=\"13W-MON\",\n",
    "    )\n",
    "\n",
    "    yQuarters = pd.date_range(\n",
    "        f\"{dates[y].min().year}\",\n",
    "        dates[y].max() + pd.Timedelta(weeks=1),\n",
    "        freq=\"13W-MON\",\n",
    "    )\n",
    "\n",
    "    dates.set_index(x).sort_index()[y].plot(\n",
    "        figsize=(15, 5), style=\"x\", xticks=xQuarters, yticks=yQuarters, grid=True\n",
    "    )\n",
    "\n",
    "    plt.vlines(xQuarters - pd.Timedelta(\"2W\"), *plt.ylim(), colors=\"green\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d2db36e8-bb3c-42a7-8050-741aef8dcda2",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Entry assignation')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotDates(entryDates)\n",
    "plt.title(\"Entry assignation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58788462-8061-460a-b8f6-d08f26c0745f",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "As shown in the above figure, participants are assigned in the next quarter (13\n",
    "weeks window) wrt the day of enrollment + 2 weeks. The assignation week is\n",
    "randomized inside the quarter and kept as reference for future assignations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1099d79-be6a-471e-bf03-52ba205a5cbe",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "`startDate` is always on Mondays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b696f18a-ba1c-430e-b012-bd3e8db1e404",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assert entryDates['startDate'].dt.weekday.value_counts().index == [0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f6e8e69-7044-402f-b3ad-9d68c611803e",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The plot below shows re-assignation dates as a result of running the\n",
    "re-assignation rule after one week of the first assignation date:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0c490784-dfcb-4a85-b7d6-89101cc46855",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reassignation on submit')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7DZWVlVizZg2GDh3qdKCGL66++mpMmTIFL730Ek6fPo2bbroJ//73v/Hqq69i/PjxSElJ8Us/9913H06dOoXU1FT07t0b3377LVatWoUhQ4ZIKwfT09PRp08fTJs2DXPnzoXZbMY//vEPdO/eHd99951Lm/3798e0adPw+eefo0ePHvjHP/6BEydOqK6c9Kdrr70WAPDYY49h4sSJCA0Nxa233iol/oiIiCh4MMFHRERE5MYdd9wBi8WC559/HtOnT8cVV1yBL774AosXL8aGDRtQW1uL6Oho/OEPf8ATTzwhPffoo4+irq4OhYWFeOutt3DNNdfgo48+wiOPPOLU/v3334833ngDy5cvx6+//orevXsjJycHCxYsAAC0a9cOM2bMwPbt27Fp0yY4HA4kJCRgzZo1ePDBBzXjNpvN+OijjzBr1iy8+uqrCAkJwZ/+9CcsXLgQI0aMkEp/jUhNTcUrr7yC//3f/8Xs2bMRFxeHZ555BkeOHHFJ8C1fvhyZmZlYsGABfvvtN0yZMkU1wQcAixYtQvfu3VFQUIA5c+YgMjISmZmZePrppxEaGmo4Ti0vv/wy4uPjsWHDBrz33nuIiYnB/PnznfY79NVf//pXvPTSS1izZg1Onz6NmJgY3HXXXVi0aJF0SnBoaCjee+89zJgxA48//jhiYmIwe/ZsdO3aFffcc49Lm4mJiVi1ahXmzp2LyspKxMXF4a233kJGRobf4lYzdOhQ/P3vf8fatWuxdetWOBwOHD58mAk+IiKiIGQSuLsuERER0SVj8+bN+NOf/oTdu3djxIgRzR0OEREREfkBE3xERERErdRvv/2GiIgI6Xe73Y709HR88cUXOH78uNNrRERERNRysUSXiIiIqJWaOXMmfvvtNwwfPhwNDQ3YtGkTysrK8PTTTzO5R0RERNSKcAUfERERUStVWFiIZcuWobq6GvX19UhISMCDDz6I7Ozs5g6NiIiIiPyICT4iIiIiIiIiIqIWLKS5AyAiIiIiIiIiIiLvMcFHRERERERERETUgvGQjSDicDhw7NgxdOzYESaTqbnDISIiIiIiIiKiZiIIAn755Rf06tULISHu1+gxwRdEjh07htjY2OYOg4iIiIiIiIiIgsTRo0fRu3dvt/cwwRdEOnbsCKDxjevUqVMzR9P62Gw2bN++Henp6QgNDW3ucIhIgd9RouDF7ydRcON3lCh48ftJvjh79ixiY2OlfJE7TPAFEbEst1OnTkzwBYDNZkO7du3QqVMn/g8rURDid5QoePH7SRTc+B0lCl78fpI/6NnGjYdsEBERERERERERtWBM8BEREREREREREbVgTPARERERERERERG1YEzwERERERERERERtWBM8BEREREREREREbVgTPARERERERERERG1YEzwERERERERERERtWBM8BEREREREREREbVgTPARERERERERERG1YEzwERERERERERERtWBM8BEREREREREREbVgTPARERERERERERG1YEzwUcDUna+DabEJpsUm1J2va+5wiEiG30+i4MXvJ1Fw43eUKHjx+0mXMib4iIiIiIiIiIiIWjAm+IiIiIiIiIiIiFowJviIiIiIiIiIiIhaMEMJvqVLl2Lo0KHo2LEjoqOjMX78eFRWVjrdU19fj6ysLERFRaFDhw6YMGECTpw4Ib2+f/9+3H333YiNjUVERAQGDhyIvLw8pzZ27twJk8nk8s/x48fdxicIAp544gn07NkTERERGD16NKqqqpzu+fLLLzFmzBh06dIFUVFRyMzMxK+//uq23Z07d+L2229Hz5490b59ewwZMgRvvPGG0z02mw1LliyBxWJBeHg4rr76amzdutVtu0RERERERERERL4ylODbtWsXsrKyUFFRgeLiYthsNqSnp6Ou7uLmlXPmzMG//vUvvP3229i1axeOHTuGO+64Q3p97969iI6OxsaNG3Hw4EE89thjmD9/PgoKClz6q6ysxI8//ij9Ex0d7Ta+Z599Fvn5+Vi7di327NmD9u3bIyMjA/X19QCAY8eOYfTo0UhISMCePXuwdetWHDx4EFOnTnXbbllZGa666iq8++67+M9//oN77rkHkydPxocffijds2DBArz44otYtWoVvvnmGzzwwAP405/+hK+++krP1BIREREREREREXmljZGblSvSNmzYgOjoaOzduxcjR47EmTNn8Morr6CwsBCpqakAgPXr12PgwIGoqKhAUlIS7r33Xqc24uPjUV5ejk2bNiE7O9vptejoaHTp0kVXbIIgYOXKlViwYAFuv/12AMBrr72GHj16YPPmzZg4cSI+/PBDhIaGYvXq1QgJacxtrl27FldddRWqq6uRkJCg2vajjz7q9PusWbOwfft2bNq0CX/84x8BAK+//joee+wxjBs3DgDw4IMP4uOPP8ayZcuwceNGXWMgIiIiIiIiIiIyylCCT+nMmTMAgMjISACNq/NsNhtGjx4t3TNgwAD06dMH5eXlSEpK0mxHbENuyJAhaGhowODBg7Fo0SKMGDFCM5bDhw/j+PHjTn137twZw4YNQ3l5OSZOnIiGhga0bdtWSu4BQEREBABg9+7dmgk+rZgHDhwo/d7Q0IDw8HCneyIiIrB7927NNhoaGtDQ0CD9fvbsWQCN5b42m013LMFKPgabzQabqXnHJMbTGuaWyFfB9v0U45D/SXSp4veTKLjxO0oUvNS+n/ml1QgxmZCdYnG5v2CHFeU1tRgeH6X5ukMQkJOqnitQa1u8BgAOQcCDN/aV4lG25yk2Zd9G79cbo/wZX+fEX7wZa2tk5H/XvU7wORwOzJ49GyNGjMDgwYMBAMePH0fbtm1dVt316NFDc/+8srIyvPXWW/joo4+kaz179sTatWtx3XXXoaGhAS+//DJGjRqFPXv24JprrlFtR2y/R48emn2npqYiNzcXzz33HGbNmoW6ujo88sgjAIAff/xR99j/+c9/4vPPP8eLL74oXcvIyMDy5csxcuRIWCwWlJSUYNOmTbDb7ZrtLF26FIsXL3a5vn37drRr1053PMGq3l4v/bxt2zaEm8Pd3N10iouLmzsEomYXrN9PgN9RIn4/iYIbv6NEwUvt+2n93oSio2ZUVR1CRm/h4usXrid2ciDvyGnN18fF2lFUf0i1P7W2xWsAMC7WjuILzz68/mOX9jzFpuzb6P16YxSf8cec+Is3Y22Nzp07p/terxN8WVlZOHDggNsVap4cOHAAt99+OxYuXIj09HTp+uWXX47LL79c+j05ORlWqxUrVqzA66+/jjfeeAP333+/9PqWLVtgNps99jdo0CC8+uqryM3Nxfz582E2m5GTk4MePXpIq/oGDRqEb7/9FgBw4403YsuWLU5t7NixA/fccw/WrVuHQYMGSdfz8vIwffp0DBgwACaTCRaLBffccw/+8Y9/aMYzf/585ObmSr+fPXsWsbGxSE9PR6dOnTyOJ9jVna8Dvm78OSMjA+3btm/WeGw2G4qLizFmzBiEhoY2ayxEzS3Yvp8Av6NEIn4/iYIbv6NEwUvt+zkOQOIOK/JKrUhMtCA7xYKCHVYUHbViVurF3929rkWt7ZodVuCoFQCQmNgfY27oIyX3lO3pic1Tf55i1RPjOD/Oib94M9bWSKz01MOrBF92djY+/PBDfPLJJ+jdu7d0PSYmBufPn8fp06edVvGdOHECMTExTm188803SEtLQ2ZmJhYsWOCxz+uvv15KJt52220YNmyY9Npll10mrcA7ceIEevbs6dT3kCFDpN8nTZqESZMm4cSJE2jfvj1MJhOWL1+O+Ph4AEBRUZG0BFIs3xXt2rULt956K1asWIHJkyc7vda9e3ds3rwZ9fX1qK2tRa9evfDII49I7aoJCwtDWFiYy/XQ0NBW8RdzqHBxDME0pmCKhai5BOv3Ewi+eIiaGr+fRMGN31Gi4KX1/ZyTPgBmsxnLiw/hhV2Hcd7uQO6Y/shJS9T1ujtazwLA8uJDWLOrBjZ7Y3JvTvoA3c9r9S2/v2BHDeyC4HJ/fkkV7A4Bcy7E4SlGf8+JUSuKD8EcYnJpe076AHz+7WnklVoDHkOwMvK/6YZO0RUEAdnZ2XjvvfdQWlqKuLg4p9evvfZahIaGoqSkRLpWWVmJ7777DsOHD5euHTx4ECkpKZgyZQqeeuopXX3v27dPStx17NgRCQkJ0j8RERGIi4tDTEyMU99nz57Fnj17nPoW9ejRAx06dMBbb72F8PBwjBkzBgDQt29fqd3LLrtMun/nzp245ZZb8MwzzyAzM1MzzvDwcFx22WX4/fff8e6770oHfhARERERERFR88hJS0RbcwjO2x1oaw5xSRJ5et1o2+I1m12A2SS4XXFmtO+ctESYTSbYBQFmk8klubf8QsJMb4yBmBMjzCEmLC8+hPySKqfr+SVVKLPWwmwyBTyG1sBQgi8rKwsbN25EYWEhOnbsiOPHj+P48eP47bffADQeajFt2jTk5uZix44d2Lt3L+655x4MHz5cOmDjwIEDSElJQXp6OnJzc6U2fvrpJ6mflStX4v3330d1dTUOHDiA2bNno7S0FFlZWZqxmUwmzJ49G08++SQ++OADfP3115g8eTJ69eqF8ePHS/cVFBTgyy+/xKFDh7B69WpkZ2dj6dKlbk/r3bFjB2655Rbk5ORgwoQJUsynTp2S7tmzZw82bdqEmpoafPrpp7j55pvhcDgwb948I1NMRERERERERH6WX1IlJYnO2x2qySR3rxttW7wWajbBLphQsMPqdWxq94vJPbsgYNK6Cun68uJDqqvc3MUYiDkxIictEblj+jsl+cSxJFuiYBeEgMfQGhgq0X3hhRcAAKNGjXK6vn79ekydOhUAsGLFCoSEhGDChAloaGhARkYG1qxZI937zjvv4KeffsLGjRuxceNG6Xrfvn1x5MgRAMD58+fx0EMP4YcffkC7du1w1VVX4eOPP0ZKSorb+ObNm4e6ujpkZmbi9OnTuOGGG7B161an023//e9/Y+HChfj1118xYMAAvPjii/jb3/7mtt1XX30V586dw9KlS7F06VLp+k033YSdO3cCAOrr67FgwQLU1NSgQ4cOGDduHF5//XW3iUMiIiIiIiIiCixl4mviS+VYXtx4QENOWqLT6wDw1uffOb2ubEte/qpsW/wdAHLH9MeDI/th1ktbkFdqbTwHQKU9refVVqsp75+0rgJl1lpY5hepluvqiVGtX6NxibTKbdXmTk68f3nxIRSUVuO83YFkSxTKrLWGY7hUGUrwCYLg8Z7w8HCsXr0aq1evVn190aJFWLRokds25s2b59XKN5PJhCVLlmDJkiWa97z22muG292wYQM2bNjg9p6bbroJ33zzjeG2iYiIiIiIiCgw1Fa1JVu6oaLmFJYXH0JFTa2URAIgrRr74XS9SzJJmQh0t2JOLqO3gMREi9v2xGvyRJf8d637C6cnSck9ZbmukRjl/crnRE9ccmK5rbvY3cUgJvfMJpPXMVyqvD5Fl4iIiIiIiIgomNkdrqva5Imib2vrnJJ7ytViZdaTqivatNoWr4k/i7JTLDCbzU7X1J6Xxye/V+t+ZblufkmVajx6YhTv+az6pKG41O5xtxpQi7IkONkS5VUMlyom+IiIiIiIiIioVVIrBwXUS0K1Vov1f2yL6gmuam0rr9lsNpc+PcWmdq/a/XrKaPXEqOxXz0o/dzzNrRqtsSgTlnpjuBQxwUdERERERERElxx5SajWKbLi64pDaZ1o7S23ovgQIDgQb+AZvYyW9zY1I3NXZj2JippTQTuWlsLQKbpERERERERERK2BkVNkHQKcTnmV37P8wsESSuYQE/JKrdj2vUn3M3q5K+/NHdO/2UtYjcwdgKAeS0vBFXxEREREREREdEnxVN6q9bqRveVy0hJht9uRV2pF4g4r5qQP0L0fnSdGy3ubkj/mTtTcY2lJmOAjIiIiIiIiokuGp/JWT6fIGtlbLjvFgqqqQ8grteKFXYd1PdMcVlxYUagWl5FyYk9za2TumiLe1oQlukRERERERER0ydBT3urudbPJpLlvn5qM3gJCzcaeaWrmEJPhEmQ1/p67QMfbmnAFHxERERERERFdMnw5RRYA7ILgtG+fp/u3fW+CzW7smaamdqiFN+XEnlbNGZ27QMfbmjDBR0RERERERETkgad9+9QU7LCi6KgZs1ItTnvwaT3jr9JTb9qRJ838UUar7NPo3HkSyHhbIpboEhERERERERG5obW3XO6Y/qqlouIzeaVWjIu1IzvFousZf5WeettOTlqitMLOX+XE3sydXoGIt6XiCj4iIiIiIiIiIjfc7S0nvq72zKxUC+J/q9T9jL9KT71tJ7+kSkqW+auc2Ju50ysQ8bZUTPAREREREREREbnhad8+rWdsNhuKiipdXnOXhPJX6anRdgJRRgt4N3d6BCreloolukRERERERETUqqwqrdIs/cwvqcKKC4kguRVuykW1ngkUf5We6m0nkGW0gdDS4m0KTPARERERERERUavizR50/tr/zh/USk8D2Y67MtrcMf19KqMNhJYWb1NgiS4RERERERERtSozRiUgzNzO0B50/tr/zlf+Kj010k6gymgDpaXF2xSY4CMiIiIiIiKiFm9VqfPqNHnCLu/jKtgF9VVfWs/4sv+dt7RKT8WY5L83RTsrLqxcVLs3v6QKdofgNtlmlNH+mjq+YMYSXSIiIiIiIiJq8dRKaHPSEmE2mWAXBJhN6okgtWf8sf+dN/xVeuqvdpq6bNlof8FUVt3cuIKPiIiIiIiIiFq8GaMSMK+88ec1O6sxN/1qTFpXISX37IKA/JIqjwk7tX3rmirJ56/SU3+109Rly0b7C5ay6mDABB8RERERERERtSqrSquxdscPsAsCki1RKJyepGsvO3/tf9eUAl2m6s+yZSOxKvuzO9QTtDlpiaioqW22supgwRJdIiIiIiIiImpV5GW5hdOTAFwsT1Ur6QS0961z90wwaIoyVX+VLeuNVa0/d8+WWWthNpmapaw6WHAFHxERERERERG1KnZBQKhKWa74p9oedO72rdN6Jhg0RZmqv8qW9cbqrj+1Z5MtUSiz1jZLWXWwYIKPiIiIiIiIiFqVmakJmJt+tWqJrVbiR62MVa2kdIVspZmy/LW5T5Y1Wqaqp21x5ZyybLnMehLJlm6GS4M9lfzqKZOWPysm91pSWXUgsESXiIiIiIiIiFq8NTurpZ9njEoA4HuJrVpZqHhNWf7a3CfLelNG66ntz4+c0ixbrqg55XVpsFasesqk5c+aTSan5J7a/ZcKruAjIiIiIiIiohZPq4TWlxJbtbJQNcFwsqw3ZbSe2rY7BCTFR2mWLZdZT3pVGqwVq54yaeWzyRbt+IK1rDoQmOAjIiIiIiIiohZvZmoi5u9Rf82XpJtWSanatUCVhPqjrNXbtt09J+9L77PuYnVX2qyWQBR/1zpd91LCBB8RERERERERkRs5aYlSAkteUipec1eVu+17E6pLq/FQxkDd++mp3SePwWwyaSb3xHsB55V57voG4PYUWl+eVY5RT6z+fvZSwD34iIiIiIiIiIjcUCsplV9zCFDd861ghxVFR80IMTVmAPXup6d2n9gfAOl0YMD96b9ima2evu2C4DQ+OV+eldMbq7+fvRRwBR8RERERERERkQZ3JaXKa8r96PJKrRgXa0d2ikW6DnjeT095n/xneXkw4LmsVfmzWt9qY5E/48uzcnpjVePLs5cCJviIiIiIiIiIiFToPTRCngCT70c3K9WC+N8qkV9ajdA2baR968R7xfuS4iM195CTJ/mUcRgtTVXrW9muVtmrL8+q0VuuTPqwRJeIiIiIiIiISIVaWah4TVkWKpaKyvejE1fuhZicS1xz0hKlklYASLZ0U+0/Jy1R2t9Pub+dt6Wp8r5DTK5JQ3dt+/Kskt5yZdKHK/iIiIiIiIiIiFSorSDztKpMvh9dwQ4r4gFkp1hgNpudVuOJyT138kuq4BDgtL+dWtmtEcr9BLVorazz9lmtezyVK5M+TPARERERERERUasX6JJQrb36xsWaMA7aJbdl1pOqJa3i80nxkXgzc7jH/e30jE9cNad3zzy18SXFR0orDsVnxbbFn+UnAcuvKeOZI9tPUCz7VSb3WMqrj6ES3aVLl2Lo0KHo2LEjoqOjMX78eFRWVjrdU19fj6ysLERFRaFDhw6YMGECTpw4Ib2+f/9+3H333YiNjUVERAQGDhyIvLw8pzZ27twJk8nk8s/x48fdxicIAp544gn07NkTERERGD16NKqqXE9v+eijjzBs2DBERESga9euGD9+vNt2KysrkZKSgh49eiA8PBzx8fFYsGABbDab031vv/02BgwYgPDwcFx55ZUoKipy2y4RERERERERNY1AloRqHZQxK9WCoqNmFOywujwjltzKk2VibPLEm/i6WPqqNgY94/v8yCnVGN21qTa+ZEs3p8M15G2rnQSsnFvlfMvLfpVlyHrGxVLeRoZW8O3atQtZWVkYOnQofv/9dzz66KNIT0/HN998g/bt2wMA5syZg48++ghvv/02OnfujOzsbNxxxx347LPPAAB79+5FdHQ0Nm7ciNjYWJSVlSEzMxNmsxnZ2dlO/VVWVqJTp07S79HR0W7je/bZZ5Gfn49XX30VcXFxePzxx5GRkYFvvvkG4eHhAIB3330X06dPx9NPP43U1FT8/vvvOHDggNt2Q0NDMXnyZFxzzTXo0qUL9u/fj+nTp8PhcODpp58GAJSVleHuu+/G0qVL8cc//hGFhYUYP348vvzySwwePNjINBMRERERERGRnwWyJFRtrz6gsTS3quoQHELjfnRl1pMA1EtulxcfQpn1JHLSEqX7lG2KP6vtb+dpfHaHgKT4KM3DPNztmac2PrFdcRWiHmrzrSz71SpDZimve4YSfFu3bnX6fcOGDYiOjsbevXsxcuRInDlzBq+88goKCwuRmpoKAFi/fj0GDhyIiooKJCUl4d5773VqIz4+HuXl5di0aZNLgi86OhpdunTRFZsgCFi5ciUWLFiA22+/HQDw2muvoUePHti8eTMmTpyI33//HbNmzcJzzz2HadOmSc9eccUVbtuOj49HfHy89Hvfvn2xc+dOfPrpp9K1vLw83HzzzZg7dy4A4O9//zuKi4tRUFCAtWvX6hoDEREREREREQWO2kmw/kgSuSsRzegtYFxqAvJLqlBRc8pteezy4kPo/9gWt3HpPc3XyPg8va4cn7wfMTGXq1Fu6y4erbJmZUyBet9aE5/24Dtz5gwAIDIyEkDj6jybzYbRo0dL9wwYMAB9+vRBeXk5kpKSNNsR25AbMmQIGhoaMHjwYCxatAgjRozQjOXw4cM4fvy4U9+dO3fGsGHDUF5ejokTJ+LLL7/EDz/8gJCQEPzhD3/A8ePHMWTIEDz33HOGVtlVV1dj69atuOOOO6Rr5eXlyM3NdbovIyMDmzdv1mynoaEBDQ0N0u9nz54FANhsNpfy35ZIPgabzQabqXnHJMbTGuaWyFfB9v0U45D/SXSp4veTKLjlffz/pJ+V39GCHVY4BAE5qQk+9ZFfWo0QkwnZKRann5V9iD8/eGNfbDkagmrFqhd5XOU1tRgeHyW1o3zdH3E3FeWcyMnH4st94jUALnPT0uYrkLTmOL+0Gp8f+RlD+3V1mSdf58/d+7qq5OIWYu7+Dn1wZD+sKm1cNRZqNuHBkf0C9nec2G5+SRVW7TyMWakWqb8HR/aD3W7H8uJDsNvtyE6x+CWuphqfWj8AdF2z2Wwo2GFFXqnV45w09biCiZHxeZ3gczgcmD17NkaMGCElx44fP462bdu6rLrr0aOH5v55ZWVleOutt/DRRx9J13r27Im1a9fiuuuuQ0NDA15++WWMGjUKe/bswTXXXKPajth+jx49NPuuqakBACxatAjLly9Hv379sGzZMowaNQqHDh1STTLKJScn48svv0RDQwMyMzOxZMkSp/7d9a1m6dKlWLx4scv17du3o127dm5jaQnq7fXSz9u2bUO4ObwZo7mouLi4uUMganbB+v0E+B0l4veTKLgdPnrx/6CXf0e3fW9C0VEzxsXaUVR/SOtxXawX2qqqamxH+fO4WDtmVVdJPxfXH0KIyYRVOw/Daq1GRu+LZXZiXImdHMg7chpVVYdUX/dH3E1FPj/uxuLLfeI1AE5z0xLnK5C05njrwRBUnQ1BbW0tEmTz5I/5c/e+fnjUBkRc+N3N36HbvjfBZjfDbBJgswOzXtri1FYgVFVbMS5WQPxvlSgqupiIjAcwLtaEykNVmFV1yC9xNdX41PoBoOtaRm8BlUdDPM5J0W+VbvsL9PvW3M6dO6f7Xq8TfFlZWThw4AB2797tbRM4cOAAbr/9dixcuBDp6enS9csvvxyXX3659HtycjKsVitWrFiB119/HW+88Qbuv/9+6fUtW7bAbDZ77M/haDzC+bHHHsOECRMANJYQ9+7dG2+//Tbuv/9+DBo0CN9++y0A4MYbb8SWLVuk59966y388ssv2L9/P+bOnYvnn38e8+bN83r88+fPd1r1d/bsWcTGxiI9Pd1p78GWqu58HfB1488ZGRlo37Z9s8Zjs9lQXFyMMWPGIDQ0tFljIWpuwfb9BPgdJRLx+0kU3G46X4eXn2/8+XBEIh4afSUKdlhRdLRxFYraqiKjxgFIlK1smZUI5JU2btA/K7WxffG17BRL4wqP4mJYLHFYtfMwEhMbryvjElfLaL3eUsjnx91YfLmvZocVONo454mJ/TGuBc9XIGnNcdVZK5LiuqLi8M+oiUj06+fN3fs646bemP/vxvu0/g719L3wN/Hv0OX3pmn+HTruQlzy77W3cTXV+LT6AaDrWmKiBavu145nXDONK9iIlZ56eJXgy87OxocffohPPvkEvXv3lq7HxMTg/PnzOH36tNMqvhMnTiAmJsapjW+++QZpaWnIzMzEggULPPZ5/fXXS8nE2267DcOGDZNeu+yyy/Djjz9KffXs2dOp7yFDhgCAdF2+515YWBji4+Px3XffAQCKioqkJZARERFOMcTGxkrP2+12ZGZm4qGHHoLZbEZMTIzTacFa45YLCwtDWFiYy/XQ0NBW8S/PocLFMQTTmIIpFqLmEqzfTyD44iFqavx+EgU3+Xd0za7D+MfuEwHZC2pO+gCYzWZpfyvRC7sOa/aXk5aI0NBQLC8+pHqfvE3x9WRLFOakD3DpP7+kCnaH4HZfsaa04sJJmWpjKdhRA7ugfsCB2piN3AfA6VpSfCTMZrPq/xaqzZkybq379d7nq0D0426OJ75UjrxSq+rc+zIurT6n3dhLSvCp/Z2VX1KFvFKr5vfCbDYHbE83d3+H+iuuphqfWj/yRVfid0TtWjCPKxgZ+feuEM+3XCQIArKzs/Hee++htLQUcXFxTq9fe+21CA0NRUlJiXStsrIS3333HYYPHy5dO3jwIFJSUjBlyhQ89dRTuvret2+flKDr2LEjEhISpH8iIiIQFxeHmJgYp77Pnj2LPXv2SH1fe+21CAsLQ2Wlc13+kSNH0LdvXwCNB2iI7V522WWa8TgcDthsNmlV4PDhw536BhrLWOTjJiIiIiKi1kPcWL6tOSQg/3GZk5bo1Iee/pTPqCUBxdfNJhPKrLXIL6lyukfc5N4cYvL7mLxlDjFhefEhp1hz0hJhNplgFwSYTepJK/E+b+dOeS3Z0s0lDkB7ztTiVrtf732+ClQ/WnOcbOkGAC7X/TEuve+rnNZJtzlpidIps83BX3E11fjU+hGvyftRu+ZNPMH6vgUbQyv4srKyUFhYiPfffx8dO3aU9pfr3LkzIiIi0LlzZ0ybNg25ubmIjIxEp06dMHPmTAwfPlw6YOPAgQNITU1FRkYGcnNzpTbMZjO6d+8OAFi5ciXi4uIwaNAg1NfX4+WXX0ZpaSm2b9+uGZvJZMLs2bPx5JNPIjExEXFxcXj88cfRq1cvjB8/HgDQqVMnPPDAA1i4cCFiY2PRt29fPPfccwCAO++8U7PtN954A6GhobjyyisRFhaGL774AvPnz8ddd90lZVNnzZqFm266CcuWLcMtt9yCN998E1988QVeeuklI1NMREREREQtxHm7A+EXEgz5Ggdc+CK/pEpKXpy3Ny4saOuhP+UzyvuUrydbopxOrFSeaBks5Cdoir9PWlchJffsguD1nLi7D4DLe5A7pr/uOVOLW+1+vff5KlD96Jlj+Zz6Y1xqfU67sZfbZ9ytFmzOz7u/4mqq8an1o/eaN/EE6/sWbAwl+F544QUAwKhRo5yur1+/HlOnTgUArFixAiEhIZgwYQIaGhqQkZGBNWvWSPe+8847+Omnn7Bx40Zs3LhRut63b18cOXIEAHD+/Hk89NBD+OGHH9CuXTtcddVV+Pjjj5GSkuI2vnnz5qGurg6ZmZk4ffo0brjhBmzduhXh4Rc31nzuuefQpk0b/O1vf8Nvv/2GYcOGobS0FF27dtVst02bNnjmmWdw6NAhCIKAvn37Ijs7G3PmzJHuSU5ORmFhIRYsWIBHH30UiYmJ2Lx5s6HTeYmIiIiIqOWYmZqAuelXSwkSwH//sSlPugAXEzLZF04eXV58CGXWk0i2dJNOqRT3pBKfKbOedJvIEX8Xk3wFpdUBKTf2F3lyKu/jKtgFAcmWKBROT8LEl8pV3wNxjEnxkXgzc7jme6U1NwCQFB8prUQT7xGTfGIc7uZMHre7OdZ7nztGSnDl/SRborwu29Wau4qaWpRZa50+w+Kc+tKfuz4b7PoPJCBqbQwl+ATB87LH8PBwrF69GqtXr1Z9fdGiRVi0aJHbNubNm+fV4RUmkwlLlixxOt1WKTQ0FM8//zyef/553e3edddduOuuuzzed+edd7pdCUhERERERC3bmp3V0s8zRjUm29RWRflCLbmn/FlMMFXUnILdbkfV9yYUHbW63CeWlMqTLWqrxswmU0DLjf0lJy1RSqqZTSYUTm+sFEu2dENFzSnVhKb4ungdMLaCLcRkcpn33DH9dZUHy+MWk2meyoT13KdFLMGVjxVw/UzJ+5GXart7Ro3WakTx8yZP5In9AfC6P3d9AsDzxf+RTtElutR4fYouERERERHRpUZrrycxweCPvaDk+02tUEk8yVc4lVlPIq/UioROJumEXbVk1WfVJzVXjYnJGE8lrMEgv6RKtSxXnrgrs55ETloiyqwnAcBl3Mr3yt1+YuLPSfFRTkm+f35xVFd5sDxub8uEjbwXehOY/irV1tobbWi/SKc/lf317hrhdZmwu/3YGuznMK9c11QRtTpM8BEREREREek0MzUR8/eov+avpJi8PFFZqqhMVOWkJWLF9v+HvFIr1uyqgc3umvyQJ8CU8kuqnFb2BaLc2F/cldEqk3z9H9vitsRVfs3I3mHiakd5ebCnOfMUt9H7PPFU6uvPUm2teZJf93dpuLvy3RmjEpjgo0sWE3xEREREREQtWHaKBQU7qmGzNx7CYXdoryib+FJj9kO+H5088SKujgq2JJ/egyl8LXF1R6s82F2Jtqe4xX0Uxd+VSa6k+Eivk3xq8yCPR/k5kZdqm00mv6xGber+iC5lIc0dABEREREREXmvYIcVdsGEUHNjsuTzI4170YknloryS6pQUXMKFTWnnJJ58lVV4gENYkImWLgry5THqnUSrj+olQdrxaE3buBiok9tlV2ypZtX74XWPMjjEffrE5NuyZYop/F9fuSU4TlSaur+iC5lXMFHRERERETUQuWXVCGv1IpxsXbkZY7FC58ccSp/BFz3OAOgWjKptsosWLgry/RUeiq/x1t62lbrw1PcziWr3VT78mes8njkK+nkh2LI//R1P8am7o/oUsYEHxERERERkRfW7KzG3PSrseLCyje7Q4A5xATg4kEYYklssqWb0+EYAKRVdO6SQO6IiZtZqRbE/1YJwDmJ4mmPM3evrZCt5lPr15e4A0FvKazaGAG4fW/0lgfrpZxbeVtiCbD89FnlON3NvdFY5YesiKfpKhODanOnNx4lPf0pY1SbM19iIGqtWKJLRERERETkhVWl1cgvqZJKD8XSWLHUVV4Su1yWTAIuJmLk14wSyx+zUyxO18Xyz6H9IqUSTeV+dDlpiZqvAXAqp5TzR9yBoLcUVj4ecYye3hu95cF6qc1tTlqiVKpqAqTVbHJ65t6bWIf2i5T6ln8W3M2d3njUeOpPLcaW9nkkag5cwUdEREREROSFmakJ0mop+cEUAFxKEOV8LcEUiSuWbDaby2viiijlPmzyclat18TnAedVX/6KOxCMlMKK19SojVFPebARanM7aV2F03507kqs3fXpTazmkIvJNuVnQWvufPkseOrPXewt5fNI1ByY4CMiIiIiIvLCjFEJCDO3w/LiQ2hrvlgcJZYeyksQAeeS2KT4SM12PZUc6ilXFFc8qZU/irF4Ko2UJ1W0Snm1eFNSGegyTK3xqF0LdMJIqyy3cHqSbE8+9yXW/qC1X5+yLFctXm/i0duf8hn5e9/U7xVRS8ESXSIiIiIiIi8pS13bmkNgFxpLDOUliMr7ki3dvC451CpXLNhhdSoVVu7DJq4ydPeask1PpbxGY3Q3vqYow1Qbj7dj9Ecs4oo9s8mEwulJ0vXcMf2lJHGg4tLary93TH+prFyrjNhsUk/E+rM/+TPie99c7xVRS8AVfERERERERF5SlroCcEqCiCWIAFzuk5f1Gik5VJYrPjiyH7Z9b0LRUau0h1lSvOshDTlpiSiznnRqQ9mmcv8zT6W8emPUM76mKMNUGw8Ar8boj1jkZbnKUlWxzDtQcbnbrw8Ayqwn3ZYRG43HaH9q7723n0eiSwETfERERERERF5Ys7Maq0u/dyrzBCCVW4p78InXlWWJ8r37jJYcypNhq0qrYLObMSvV4vHZNzOHe2xTpFVOqXavpxj1js+XsmBP3I3H2zEGIhbxd70nzHrLyL6FWmXERuIx0p/ae+/r55GotWOCj4iIiIiIyAurSqvx8JirAEDaM008UMMhS/KpSYqPlJIV3pYc5qQlSokQs0lwOU3XF1rllAAM7Zkmj1Hv+OwOQbM01du9+PSuBLQ7XA+48LVvPbHI51Zcuaf1ujKuQMpJS5SSe8oyYmU8/thDUevz4mnO5L8TXaq4Bx8REREREZEXZqYmICctUSo9HNovUlqVBwBl1lr07hqBpPhIqXT24gEK3S7ss3ZStWRUD7FcMdRsgl0woWCH1W9jc1dOKV+x6GnPNK2SWHc+P3JKtcTZl7341MYjXhPfG6BxH0Bx5aW8XNmf+wB6mls9rzcVtTJirXj8sYei1uclmOaEKFhxBR8REREREZEXZoxKAKBeeigvIfzLdbGqe4rll1ShouaUVyWH8rYeHNkPs17agrxSK8xms19WMhkpp1SOV60UWe/4xNJUZYmz2qo2X8ej9b4BjcnLpPgoKSZ/7gOoZ27dvd5U9Lx/8nh83UPRXX+e5oyImOAjIiIiIiIKCHf7yaklPvSWhyqftdlsyOgtIDHREpByRa3SS/EgCPkebcrx9e4agTLrSafElRijOGYxeaOV4DGbLq6q0zMuX0tF/bEPoD/KVY2091n1SYxI8FwyrZe3JbHezh1LcIl8xxJdIiIiIiKiAMlJS1TdY0+t5FBveahWuWJ2iiUg5YruSi/LrLUwAVIZpzJZ+f3Pv6Gi5pT0rFhSKZ6YKi/bVI5LnDux7aH9In2OV2+pqNb7ppc/YjDanj/786Uk1pu5Ywkuke+4go+IiIiIiChA1PYUy0lL9Kk8tKnLFd2VXoqltOIebZPWVaBwepKUrFSeMCy2JS9NFinHpZw7vUkqX0tF1foW3ze9/BGD0fY8lUwb4ctnzJu5Ywkuke+Y4CMiIiIiIgoAb/ag80d5qFFGyknlcYnJPTG+SesqUGathWV+kVO5rsjImPTMnbu4gYsnFRudR2/eNzVq76VWmbHR0mFlSbT4ulgyLR+zeLiLr+W7ej4n4kpCX+bO3+XNRJcKlugSERERERH5mdaeYrlj+quWUsr5Wh5qlN7yTnlc4r548vEVTk+SVvLJy3WNjknv3HmKO9nSzfA8+vK+qVGbM19Lh7XmWCyZFk8fFsfsr/JdT+18fuSUX+bO3+XGRJcKruAjIiIiIiLyM3d7iomva/G1PNQoveWkyriUq9HyS6qkxJNdcF41ZmRMeufOU9wADM+jL++bGrU587V0WD7HYkm0smRabcy+lu96asfuEJAU77pC0ejc+bu8mehSwQQfERERERGRn3m7p5i/ykON8lQarBWXmEByF7fYrt4xGZk7rbiN9ulN355ozYmY5PO1dFhZEq0smVYbs6+l396201T9EF3KmOAjIiIiIiIKAlrloYDrIRWBkJOWKCVT5CWtnuKqqKl1KddVxh3IMSnjFtturnkEPM+ZsozWm/YKpydJyT0T4PIeiCcZy8cszpPZZPL6ZNqctESs/PiQZvz+2idP6/NIROq4Bx8REREREVEQcFceKpZABpJaGa3euLReT4qPRFJ8ZEDHpIy7zHqyWecRcD9nyZYo2AXBZZ6Nticv1xUAl5Jp8STjZEuUdNCGlNwTBHx+5JRXY8svqYI4hcr4/blPntbnkYjUcQUfERERERFREPBneahR7kpsPcXlLrY3M4e7fdZX2mWw3QLWpx5acyYehOFr6bCnkml5e2L7YrJP/qfR/R2VexwuLz6kWYrti+YqVSdqyZjgIyIiIiIiuoQZKQ1ecWF1llqSxV+lmYGIuyl4mpsy60lU1JwyFK9am/K9/NwdOCL+KZZQK08+Npo00zroQp7kC0Ryz934iOgiJviIiIiIiIguYUZOjjWHmFSTLMqVXU3B3yfe+srT3CTFRxqOV61NcW+9MmstkuKjPLYztF8k9tScksqClUkzvfOkNt/Kff38kXgLtveVqKVggo+IiIiIiOgS5u2pteLvWiu7Aq05S5rd9enN3Gi9ptamuLeeuySYnDnE5LLnnzLJp4fafKvtk+fr3Afb+0rUUjDBR0RERERE1ATUyi3FawBcylvlJa/uyj8LdlhReTQE4wI/BADOSSdx9ZaR5J58LMpxycecX1KFz6pPYkRCt6AoCZbTej/Eklhv50aNL/MdyL3s/NG2v0q+xXam3djLp3aIWjKeoktERERERNQExHJL+Wmg4jXlyaPK00jVnhXvyyu1IsTUtGWLOWmJ0qotedmnHvKxyH+Wj1n+s9a4/XVaqzfcxSXud+fN3GjxZr619rLLHdNfNXYj/NW2v95fsZ01O6t9aoeoJeMKPiIiIiIioiag96AAvYcMiPfNSrUg/rfKQIfvEqO3pZnyseSO6S8lhQA4nc6qtTKsuUqCtcagjEvcH8+fZavezHcg97LzV9v+KvkW73u++D9AROO1NTursbr0+2b9nBA1JSb4iIiIiIiImohWuaXaNXf738nve3BkPxQVuSb4vCl/1POMuFpKmYArs55EskW7nFZebisfS1vzxcIytfH7WhLs65xokceV93EV7MLFwy/E+Catq/C5JFarFNbTfLvrU+u63vnx5z55Wu+v3SFoJjLVyrdz0hLRYD+HeeWN96wqrcbDY65ico8uGYZKdJcuXYqhQ4eiY8eOiI6Oxvjx41FZ6fwXSX19PbKyshAVFYUOHTpgwoQJOHHihPT6/v37cffddyM2NhYREREYOHAg8vLynNrYuXMnTCaTyz/Hjx93G58gCHjiiSfQs2dPREREYPTo0aiqcl7qe9ttt6FPnz4IDw9Hz5498be//Q3Hjh1z2+7u3bsxYsQIREVFISIiAgMGDMCKFSuc7vnkk09w6623olevXjCZTNi8ebPbNomIiIiI6NKkVm6ptwTTSKmmN+WPnp75/MgpzdLMippTHvuTvy4fCwC3Za2+lAT7Oifu5KQlwmxqPMTCBDgl98Ry3WRLlNclse5KYfXMt1HNVRKt9v7qiUX5+oxRCRfH4qdTfYlaCkMr+Hbt2oWsrCwMHToUv//+Ox599FGkp6fjm2++Qfv27QEAc+bMwUcffYS3334bnTt3RnZ2Nu644w589tlnAIC9e/ciOjoaGzduRGxsLMrKypCZmQmz2Yzs7Gyn/iorK9GpUyfp9+joaLfxPfvss8jPz8err76KuLg4PP7448jIyMA333yD8PBwAEBKSgoeffRR9OzZEz/88AMefvhh/PnPf0ZZWZlmu+3bt0d2djauuuoqtG/fHrt378b999+P9u3bIzMzEwBQV1eHq6++Gvfeey/uuOMOI9NKRERERESXELVySwC6SjDVnn1wZD/Vfrwpf/T0jN0hICk+SnN1YZn1pNv+5OW24phFWie9ao3bm+SNv08Bzi9pXLknJvliu0ZojtubklhPpbCe5tsof8+PXu7eX72fp5y0RNyz/t9Sm3ZBewUgUWtkKMG3detWp983bNiA6Oho7N27FyNHjsSZM2fwyiuvoLCwEKmpqQCA9evXY+DAgaioqEBSUhLuvfdepzbi4+NRXl6OTZs2uST4oqOj0aVLF12xCYKAlStXYsGCBbj99tsBAK+99hp69OiBzZs3Y+LEiQAaE5Civn374pFHHsH48eNhs9kQGhqq2vYf/vAH/OEPf5B+79evHzZt2oRPP/1USvCNHTsWY8eO1RUrERERERFdmtwlKDydRqr1rN1uR7xGf96Ut3pbEiuuRBTj8lRuKxLLWgEgOzXB6XU9SR2j/FXyq4xr0roKlFlrYZlfBLsgqI7bKE+lsJ7m2xv+LInWQ8/7q+fzlPdxFWzCb9IefDNTE/x2YjBRS+DTHnxnzpwBAERGRgJoXJ1ns9kwevRo6Z4BAwagT58+KC8vR1JSkmY7YhtyQ4YMQUNDAwYPHoxFixZhxIgRmrEcPnwYx48fd+q7c+fOGDZsGMrLy6UEn9ypU6fwxhtvIDk5WTO5p+arr75CWVkZnnzySd3PqGloaEBDQ4P0+9mzZwEANpsNNpvNp7aDgXwMNpsNNlPzjkmMpzXMLZGvgu37KcYh/5PoUtVU38/80mqEmEzITrG4vFawwwqHICDnwn9oK7+fRp5t6liDXXOOpSX1rXa/eA2A0/35pdX4/MjPGNqvq0v8gRiXL9/Rgh1W5JVaMSvVggdH9oPNZoPdbpdet9vtsNlseHBkP9jtdil5l51iUX1WvC+v1IpxsSaM0fg79MGR/bCqtHGFVKjZJD3vjjfP6H1WPuYQU2NZ66zUxvdaPDRkVqqlcZ+56p9Qcfhn1XHL58coX8YHqL+Xr069FgOe2H5hRR8Mt+ktX8fSVG2qcfe5lr+/7mJ5cGQ/rPz4EOyCAHkF8fQRfdEGYT59TvyB/45LvjDyufE6wedwODB79myMGDECgwcPBgAcP34cbdu2dVl116NHD83988rKyvDWW2/ho48+kq717NkTa9euxXXXXYeGhga8/PLLGDVqFPbs2YNrrrlGtR2x/R49enjs+3/+539QUFCAc+fOISkpCR9++KGuMffu3Rs//fQTfv/9dyxatAj33Xefrue0LF26FIsXL3a5vn37drRr186ntoNBvb1e+nnbtm0IN4c3YzQXFRcXN3cIRM0uWL+fAL+jRE31/bR+b0LRUTOqqg4ho/fFsrFtF66Pi7WjqP6Q0zPi99ObZ5s61mDVnGNpSX2r3S9eA+B0/9aDIag6G4La2lokyNoI1Lh8+Y5WHg3BuFgB8b9VSodiiNcAoPJQFYounIYbD2BcrEm6pvas/D6HYNL8O3Tb9ybY7GaYTQJsdmDWS1uc3gd/PaP32Y8OhgAIgdkkwC6YkNjJIZ0CLI55bKyj8eeTpzAu1qE5bvmcGeHL+AD193Lb9ybYBTNC0Dguo216y9exNFWbajx9risPVWFW1SG3sWz73gSHYIYJAuyyELdt24Z4c7hPnxN/4r/jkjfOnTun+16vE3xZWVk4cOAAdu/e7W0TOHDgAG6//XYsXLgQ6enp0vXLL78cl19+ufR7cnIyrFYrVqxYgddffx1vvPEG7r//fun1LVu2wGw26+537ty5mDZtGr799lssXrwYkydPxocffgiTyYQOHTpI9/31r3/F2rVrpd8//fRT/Prrr6ioqMAjjzyChIQE3H333d4OH/Pnz0dubq70+9mzZxEbG4v09HSnvQdbqrrzdcDXjT9nZGSgfdv2zRqPzWZDcXExxowZY2jFJlFrFGzfT4DfUSJRU30/xwFIvLByIjHRIq0QKjrauJJCvtJB+f008mxTxxrsmnMsLalvtftrdliBo1YAQGJif4y70EbVWSuS4rqi4vDPqIlIDPi4fPmOjtN5Te01d/eNcfN3qHIuChTzqsabZ/Q+W7DDiuqzrq+L753eMet53dsY9VD27Y82vRGIfptyLJ4+//IVflqfJ3msyz7+GvMvbMMnfj+9/Zz4C/8dl3whVnrq4VWCLzs7Gx9++CE++eQT9O7dW7oeExOD8+fP4/Tp006r+E6cOIGYmBinNr755hukpaUhMzMTCxYs8Njn9ddfLyUTb7vtNgwbNkx67bLLLsOPP/4o9dWzZ0+nvocMGeLUVrdu3dCtWzf0798fAwcORGxsLCoqKjB8+HDs27dPuk+ZZIuLiwMAXHnllThx4gQWLVrkU4IvLCwMYWFhLtdDQ0NbxRc/VLg4hmAaUzDFQtRcgvX7CQRfPERNLRDfzxUXThtU7kE0J30APv/2NPJKrXhh12GP+yzJ45mTPgBmsxnLiw/pelZvjHaH4BJrfkkVYApBsiVKNVat8YnP2h2C232smpq/506NN+95oOdxTvoA7Dnys0vfdoeAFz45AgBOfchjLdhRI+1pBsBp7pLiI/Fm5nBp3y5v5tTI2FvS36H5JVXIK7U6zYX882c2m13G7M0zep/9/NvTTqfMGmnbX3wZX1O2eamNxZtY1D5PM9MulxJ86z77FnPTr26SWPUItv+9oJbByGfGUIJPEATMnDkT7733Hnbu3CklvETXXnstQkNDUVJSggkTJgBoPAn3u+++w/Dhw6X7Dh48iNTUVEyZMgVPPfWUrr737dsnJe46duyIjh07Or0eFxeHmJgYlJSUSAm9s2fPYs+ePXjwwQc123U4Gk9tEvfCS0jQtz+Hw+Fw2j+PiIiIKFiZQ0yaG/aXWWthNpmk0wuN/IdbTlqitOm50We1YpRvti/fbF28rharu/GJG7cHG3/OnRpv3vOmmMdkSzdU1Jxy6lt5yIQyVhMgnVIqxiXOndimGLO3c9oSP0N6eDqBVe1UV2+e0fvsZ9UnvW7bX3wZX1O22Vz9NtdYvIlF6/Mkf57oUmIowZeVlYXCwkK8//776Nixo7S3XefOnREREYHOnTtj2rRpyM3NRWRkJDp16oSZM2di+PDh0gEbBw4cQGpqKjIyMpCbmyu1YTab0b17dwDAypUrERcXh0GDBqG+vh4vv/wySktLsX37ds3YTCYTZs+ejSeffBKJiYmIi4vD448/jl69emH8+PEAgD179uDzzz/HDTfcgK5du8JqteLxxx+HxWJxSkAqrV69Gn369MGAAQMAAJ988gmef/555OTkSPf8+uuvqK6uln4/fPgw9u3bh8jISPTp08fINBMRERH5lfLUSrXEWVtzCM7bHcgvqdKdGMkvqZKSKUafdRdjsiUKy4sPoaKmFmXWWilGrVjdjS+QJz/6wp9zp8ab97yp51HsW41aYtcuCJi0rgJJ8VFSck/5jLdz2hI/Q3p4OoHVX8/ofVbPyb2B5sv4mrLN5uq3ucaixpfPEwDMTG2Z31sibxlK8L3wwgsAgFGjRjldX79+PaZOnQoAWLFiBUJCQjBhwgQ0NDQgIyMDa9aske5955138NNPP2Hjxo3YuHGjdL1v3744cuQIAOD8+fN46KGH8MMPP6Bdu3a46qqr8PHHHyMlJcVtfPPmzUNdXR0yMzNx+vRp3HDDDdi6dSvCwxs3vm3Xrh02bdqEhQsXoq6uDj179sTNN9+MBQsWqJbKihwOB+bPn4/Dhw+jTZs2sFgseOaZZ5z2Afziiy+c4hP31psyZQo2bNjgNm4iIiIif1OWHMoTGHkfV8EuCFLyRExgTHypXHUVE9C4iXl1aTUeyhgI4GICJik+UlpBpXxWrazTXSkkACTFR0oJHfmfyljlq76UySlxFVeyJSooy3aViSPlWPxFa06MzqO/ElzK1XDLiw+5rNxzF+ukdRUos9ZKKzzlz4jJYF/mNJBjJyIiCjTDJbqehIeHY/Xq1Vi9erXq64sWLcKiRYvctjFv3jzMmzfPSGgAGlfxLVmyBEuWLFF9/corr0RpaanhdmfOnImZM2e6vWfUqFG65oeIiIioKaiVHOakJUrJPRPgsneRWD6pfK5xE3MzZiWaAKgnanLH9EfumP7Ss/LrnuJStvnlt6elFVpiaaYyVrUVV/ISTfEZ5Squ5i65VFsVpjYWf1GbEyPz6K/yYbVxy8ts9cSaFH+xfFteritf6enrnAa6dJqIiChQvD5Fl4iIiIiCl1qCY9K6CilhJq7gkycw5M+UWU9KK6HySq0YF2uXTk9U2xdJnuQrs55ERc0pt3snaZVCApASPO5ilbcl7rOkLNEUS33V+mmuxE1T72+lNidG59Ef5cPKcSv7KLOeBAC3sYr3iJ8JMa6h/SIBQPpTa1x6BLp0moiIKFCY4CMiIiJqpbTKcgunJ0nJLmUCQ/5M/8e24LzdgVmpFsT/VindoyxtlT8jJkbcJdG0SiHFa8o998Q/1ZIt8oSRWtmrmOQLlpLLptzfSmtOvJlHX+OTj1urD3lSWBlrfkmV6uvKtpWMxNxUpdNERESBwAQfERERUZBzt2+dp/3k5GW5ZpMJhdOTpOuAegmjvEwxxKQdl7xvu0OQTmZVPiO/T/6zvBRSjEVrjzjlajxl++7KXr09Jbi5+fK+e1MKrPcZf8elRt6vcn89PWMxqqlLp4mIiPyNCT4iIiKiIKdn3zot+SVVTqWu8tVbWiWMyjLFxhJdE8Yp7pH3/fmRU079qO3FJ39GrUQz90KiMCnedS818bpauaW7slcxOdQSSy59ed+9KQXW+4y/4xKvKeMS7/ms+mTAy5qbunSaiIjI35jgIyIiIgpynvat00pY6Sk59LSKS/y96KgZiTusmJM+QPUetZJatRNSlT87r9Lrprryy1NCzt1qMV9PVm1O3r7vgHdlq3qf8XdcnvrVs9LPV01ZOk1ERBQITPARERERBalVpVVoF9reKckh308vKT7SqWQSgFMprFjaKq4+8lRuqZa4szsEzEq1IK/UirxSKwp21MAuCKoltEP7RSIpPkoqi7ULjf2q7bMX6FJI+VjsDueVi8rElLuS0uamtV9hcyedgjUuIiKiS1VIcwdAREREROrEUsj8kioAjUkVeeIs2dLN6b7likSfuJLOLNsULyctUUp6KfuQlymKCTJziAnZKRaMi7XDBEhluPLSRXk/OWmJaGsOke5T7n/nrhRSHpev5P3IxyjvRz7GYCbOabDtIxiscREREV2KuIKPiIiIKEjNGJWAMHM7p/3sxOQeAFTU1GomVcwhJpeDCURa5ZbK5J74u81mAwAIgJRgnLSuAoXTk1z6Ue6tB8Bp/7umKoWU9+NLSWkwUM5psOwjGKxxERERXYqY4CMiIiIKYsrkFNC4p514eIRlfpFUMiveZ7Rk0lO5ZcEOK4qOmjEr1YI56QMwaV2FS9/KpJk85uzUBKfffUkCiSXFdofgcpKruApRfF0ryedrSakvp8gapWcfRV94O5ZAx0VERETGsESXiIiIqAURSyELpydJq+nEkllfSia1ns0vqbpwiq4d2SkWAFDtWy25lzumP3LH9Hc6bENecuwNsdz28yOnnNoS+xevq5Xd+qukVFk6LfJ3ya/aKkOxxNjXeRR5M5amiIuIiIiM4Qo+IiIioiBXZj0JwLnUFbi4H55dEKRr3pZMapVbiodsxP9W6XSvsm/5nncrVEpf5SvBfNlnT74SL9nSeKCHuJpR3AtQa2Wev0pKm6rk191+heLrvvJmLE0RFxERERnDBB8RERFREMsvqUJFzSnVUki91zwlnNyVW84Z0x82mw1FRZVu75UnfJQlnWp7/vlCnpQymxr3ABT/dJfc82dJaVOcIttU+xUaHUtTxUVERET6McFHREREFKTW7KzG6tLvvUocqa3MUttvTUx0JVuipJVXymcfHNkPQONefHmlVpfSTGU/TSEnLVFKRgGNqxm1ym61SkqVcRvdj04eQzCcIuvL3oDyscircpVtytvx1KaneD6rPokRCd2aZC9DPfH4uz8iIqKmxAQfERERUZBSK4UUr4k/a10DXEsmxf3WlK+Jpa1J8VGazwKAQwie0kyx3Fa+F6BW2a3eklK1+RH7ku8vqIwhWE6RNRq/nHIsYjvyNoGLeyvqadNTPGKJtTfxesOX+SEiIgp2TPARERERBamZqYlo37a90zW1FUZ6SybVVq2ZQ7RLW8XfbTZb4++pCQgNDfXYT6DJE0Tyvfe0Eka+zI/WfnTBeIqst3sDao1F66AUsQ9PK0v1xKOct0DsZWgkHiIiopaKCT4iIiKiFsjbcsOm2DsukJTJPWWiSCvJp5fW/NgdgrRCTy1JJa4SXF58CGXWk0i2dIPdIUjvkfh+AZCu6y119Uf8yrmQx6OW4EqKj0RFTeOJxG3NIdJ1o58ZT/E09edRrb9kS5RTf8r3Sv6+5JdU4ZytLiCxERER+SLE8y1EREREFGzEckPx9FyRmHwyyzdSU8hJS5RKMYNh7zgjxETa0H6RLoki+XVfT+pVzo98vuUlv/L5FmMAGhNInx85JT0jPi+/bg4x6Xq//BG/khhPmfWk0zxeTJR2Q+6Y/lLpc1tziNefGU/xNPXnUd6feDiL/Hskf6/k70sg3isiIiJ/4Qo+IiIiohbIl3LDYNs7zoimOMHV3fx4OkE4Jy1RdUVhsuXi/obiykNle/6i5/2VjyfZ0k16zmVl4oXDS8TDTLz5zHiKp6k/j8r+9Kz6lM/NtBt7YV55wMIjIiLyChN8RERERC2UN+WNzbV3nFpJsadSSKNlq0bKlrXuFecjKT4Sb2YOV50fPfMtv1dcJSYeCAJAszxU7/h9iV8tRuV4lAdPiG1kpyY4/S4vUVaL1eiee3o/j96WqGv1Jyb55PMgjjPv48ZEp/hM3fmLJbqrSqvwyM1DNOMkIiJqKizRJSIiImrBjJQ3aq04E/eOU5b7+pNaSbG/SyGNlC2r3StPLomr2pTzY2S+xXvFpJ64Gs5deaje8Xsbv1aM8vGoJffEFYjywzaWFx/CpHUVmrF6+ryJz3rzefSmRN1dPGICVj4POWmJTqc0a5U6ExERBQOu4CMiIiJqwYyUN8r3jpMTf/dl3zpP1EqK1fhyqqmRsmW1e8usJwFA817xoA298y3eK08SKUtdleWhesfvbfxaMcrHI/+crFBZ7VZmPYk3M4ejoqZW8wRmsT93n7fPqk96/Xn0pkTdXTziWOTzAEB63+yCgEnrKlA4PQlrdlZLz84YlaAZIxERUVNigo+IiIiohTJa3tgU+9e5o1USqnbN23i8LaPVc6+R+Vae9iv+KZKXuqqVh+oZvzdjVYvR3Z6C8s+MvL/+j23xGKunz5ueBKY7RkvUteLJL6lSPZEZuJgsnbSuAmXWWljmF8Em/AZEeAyPiIioSbFEl4iIiKgFas5yW1+olYT6+xRVrfZWqMyL/F6tMkxAe76T4iM1S2Vju0ZIiaOk+IuHbMhX7WmVh8qpxS1nAjSfzS+pwooLfekZj6fPj7/fK1/J43FXLWtkHtQUTk9yWolJREQUbJjgIyIiImqB3JUb5o7pH9ByW1+olYSqXfN3H4D2vnVi2axdEDT71ppvca87sTxWvDfZEoWjP/8mHaIhPp87pj+G9ouU3qOctEQkW6KcTqtVxuBpvznxnVY+624/Om8/P/5+r3wlj8chwPC+fGrzIH+vxHkQTxSWH5RCREQUTFiiS0RERNQCNXe5rTfclbj661RfPWW0y2UrueT9y39X9q013/I2xf34zCEml73pvCkPla+sU8amnDvxdeXYtFamefP5aa4TmLVoxWNkXz61eVBeU7bx3Pb9mFcemDERERF5iwk+IiIioiCyqlR7RZR4AIK75Iw/rLiw2klr3za9McjbUUvGyFe9ifQexqFGq+xUrT15IkyZ/JHfa2QujO6jJ8abFB+pOX4ALn3kfVwlrSKT9yMeFKFMmvqDp7kts55EsqWbz58Zf8UjnydxFaUyHnOIyWNcav3MGJUgJfjW7KzG3PSr/TYuIiIib7FEl4iIiCiIqJURAu7LDAMRg1qpY8EOq6EY5O3ISyGVq8+UJaHelhnrLTvNSUuU9mtT7iOnvNdTeaw4F97sTSfGm2zp5tSHGEOZ9aRLH2KJqAnOCTxxJaC4P5y7/QS94WluAePlsYGMxwRI81RmrZXiEuP5/MgpXXFp9SN/nYiIKBhwBR8RERFREFFbHaT3IAB/Ua4ie3BkP2z73oSio1ZDMcjbcXdSq7tnjdBbdppfUgWHAKd95JRJPrUxiL+rjUFtbzpPY1DGq1xlWFFzyqUP+T5wFTW1TvGIJ/UaiUEvPSfiKkt2A/m59bQaUACkeYrtGoHlxYekFY7iPOmJy1M/M1ODsxyeiIguPUzwEREREQWpVaXVWLfrmO6ST8B/5bXyxNaq0irY7GbMSrUYTtTI2zFSvurPsSif87SPnLJf+RjEsk9l4k1MsBVOT1JNdHmK1dM8KeOetK4CZdZaWOYXSWWonvbyCzRf3mt/0ZoncSWf2eS6PyIREVFrwBJdIiIioiBltOQT0F9SqodYdmqzCzCbBGSnWAzFr2ynOccif065b1vumP5O/aj1Ky+PlZe/KlfPiavmxDYnravQHavWPKnFXTg9yalcV5m0UhtXU/D2vfYHd/MkFtKKpxUzuUdERK0NE3xEREREQUpZ8qmHWmLH21JJsew01GyCXTChYIfVq3Gola829VgAY3v0KfudtK7CqTxWvC62WTg9yemZnLREQ6Wg4tjU5kktbnm5rgC4HCShNq6m4O177Q/u5klMr5pNpiaPi4iIqCmwRJeIiIgoSM1MTXDagw/QV27pj1JJeSLtwZH9MOulLcgrtcJsNvt0sm1zjEWkd48+Zb/y01iVJbjyNn2J1d08KePWuldtz73mXEHX1GXCWvMkJlrlfzZ1+TIREVGgGVrBt3TpUgwdOhQdO3ZEdHQ0xo8fj8rKSqd76uvrkZWVhaioKHTo0AETJkzAiRMnpNf379+Pu+++G7GxsYiIiMDAgQORl5en2ednn32GNm3aYMiQIR7j27RpE9LT0xEVFQWTyYR9+/Y5vX7q1CnMnDkTl19+OSIiItCnTx/k5OTgzJkzbtutrKxESkoKevTogfDwcMTHx2PBggWw2WxO97399tsYMGAAwsPDceWVV6KoqMhjzERERERya3ZWSz/PGJUAwLtyS19KJdVWyWX0FjAr1WIoBr0lsYEciycrPMQhnsZqNplQOD1JikdrDN7EKp8nu0NwKfOVr16c+FK5oTl1N778kiqsuJDo8saKYteVlUnxkdLv4oo6MS49/fkrXmVyT77KssxaKx28oVb+rdZHIOeRiIjIHwwl+Hbt2oWsrCxUVFSguLgYNpsN6enpqKurk+6ZM2cO/vWvf+Htt9/Grl27cOzYMdxxxx3S63v37kV0dDQ2btyIgwcP4rHHHsP8+fNRUFDg0t/p06cxefJkpKWl6Yqvrq4ON9xwA5555hnV148dO4Zjx47h+eefx4EDB7BhwwZs3boV06ZNc9tuaGgoJk+ejO3bt6OyshIrV67EunXrsHDhQumesrIy3H333Zg2bRq++uorjB8/HuPHj8eBAwd0xU5EREQEQLOc0mi5pS+lklqlrNkpFkMx6C2J9SSQZZ+e9vmTn8aq3JNPbQzexCqfJ3k88j7kq+GMzKm/9zHUalscQ7KlG5YXH5LaFuMqs57U1Z+/4hXjGdov0iUZmmyJwtGff0OyJcppvtz1oRXXmp3VPs8jERGRPxgq0d26davT7xs2bEB0dDT27t2LkSNH4syZM3jllVdQWFiI1NRUAMD69esxcOBAVFRUICkpCffee69TG/Hx8SgvL8emTZuQnZ3t9NoDDzyASZMmwWw2Y/PmzR7j+9vf/gYAOHLkiOrrgwcPxrvvviv9brFY8NRTT+Gvf/0rfv/9d7Rpoz4d8fHxiI+Pl37v27cvdu7ciU8//VS6lpeXh5tvvhlz584FAPz9739HcXExCgoKsHbtWo+xExEREQHAzNREzN+j/prelWu+lkoaKWUNdDuBLvuUl9WKv6sl09T6VfbvbaxaZb7KeDyV+6q95kt7nsjblo9ZTUXNKV39+Sted589eZl1UnwUAM97O8rjarCfk66vKq3Gw2OuYqkvERE1O5/24BNLWyMjG5fi7927FzabDaNHj5buGTBgAPr06YPy8nIkJSVptiO2IVq/fj1qamqwceNGPPnkk76E6daZM2fQqVMnzeSemurqamzdutVpZWJ5eTlyc3Od7svIyHCbmGxoaEBDQ4P0+9mzZwEANpvNpfy3JZKPwWazwWZq3jGJ8bSGuSXyVVN8P/NLqxFiMqmeulmwwwqHICAnNcElJn98R4323dJ4M75APtMU8x3IPprq86K3H1+/nwU7rMgrtWJWqgUPjuwHm82GB0f2g91ux/LiQ7Db7YZPw22uv0MDMRY18jZXlVbBZm9c1WWkX3/GqhaPvF1/jM+X9vS0DcDr/gIZry99iM+sKD0IRDRem3FTnF/j8hb/PZeoUbD9N6gYh/xPIiOMfG68TvA5HA7Mnj0bI0aMwODBgwEAx48fR9u2bdGlSxene3v06IHjx4+rtlNWVoa33noLH330kXStqqoKjzzyCD799FNDiTejTp48ib///e/IzMzUdX9ycjK+/PJLNDQ0IDMzE0uWLJFeO378OHr06OF0v7txA417Gi5evNjl+vbt29GuXTudowhe9fZ66edt27Yh3BzejNFcVFxc3NwhEDW7pvh+Wr83oeioGVVVh5DR+2IJ1LYL18fF2lFU77pnkT++o9723VJ4M75APtMU8x3IPprq86K3H1+/n5VHQzAuVkD8b5UoKrq4V3I8gHGxJlQeqkLRb5XaDbjR1H+HBnIsSvEAzCYzbHbABAFjYx2G+vV3rPJ4zCbXdn0Znz/a89Q2fOwvkPH60kfjMxe/v3G/VaGo6Khf4/IF/z2XLnXB+t+gAL+f5J1z5855vukCr7NnWVlZOHDgAHbv3u1tEzhw4ABuv/12LFy4EOnp6QAAu92OSZMmYfHixejfX31p/RtvvIH7779f+n3Lli248cYbDfV99uxZ3HLLLbjiiiuwaNEi6fqgQYPw7bffAgBuvPFGbNmyRXrtrbfewi+//IL9+/dj7ty5eP755zFv3jxD/crNnz/fadXf2bNnERsbi/T0dHTq1MnrdoNF3fk64OvGnzMyMtC+bftmjcdms6G4uBhjxoxBaGhos8ZC1Nya4vs5DkDihRUtiYkWZKdYULDDiqKjjStclCtZ/PkdNdp3S+PN+AL5TFPMdyD7aKrPi95+fP1+jvPyNXea6+/QQIxFS8EOK+yCFaFmE2x2IDGxP8ZpfC+MxuNNrMp4aiIu9+mz6O/2PLUNwKf+AhmvL300PnNQ+v1wRCIeGn2lX+PyBv89l6hRsP03KMDvJ/lGrPTUw6sEX3Z2Nj788EN88skn6N27t3Q9JiYG58+fx+nTp51W8Z04cQIxMTFObXzzzTdIS0tDZmYmFixYIF3/5Zdf8MUXX+Crr76S9uRzOBwQBAFt2rTB9u3bcdttt2HYsGHSM5dddpmh+H/55RfcfPPN6NixI9577z2nL1lRUZG0BDIiIsLpudjYWADAFVdcAbvdjszMTDz00EMwm82IiYlxOi1Ya9xyYWFhCAsLc7keGhraKr74ocLFMQTTmIIpFqLm0lTfzznpA2A2m7G8+BBe2HUY5+0OJMVHwmw2q/a57XsTqj/9Fg9lDHTb7grZ5u3Ka0Dj5uryvgt21MAuqG/239zUxiISN64X95KS36s1t3PSB2j2pfaMpzmZkz4Ae478jLxSq+ozUoxetG10TuakD8Dn357WjMUX/ozfaD/Jliin903+/Vz76RE8cvMQv8bgi9b6d2h+SRXySq0ue+eZzeZm+d8Mf8cTyPFptQ247l+ot7+meD+86UN8ZmZqAuaVN15bs+sw2rXtGDR/t7TW7yiRXsH636BA8MVDLYORz4yhU3QFQUB2djbee+89lJaWIi4uzun1a6+9FqGhoSgpKZGuVVZW4rvvvsPw4cOlawcPHkRKSgqmTJmCp556yqmNTp064euvv8a+ffukfx544AFcfvnl2LdvH4YNG4aOHTsiISFB+keZiHPn7NmzSE9PR9u2bfHBBx8gPNx5yW7fvn2ldt0lDh0OB2w2GxwOBwBg+PDhTuMGGpfgysdNRHQpyklLlE6TbGsOkU5YVG7E3riSyYwQk+eTCNVOMxSvyU8zzElLlE6/NJvUk2jNzciJkcp75XMLAMmWbh77U74feuZEbFf5jDJGb9pW425Oyqy1MJtMPvehxl/xG+nHbDKhzFqreTABT+YMPLXDFcSTX9U+hy0tnkCOz8jhH3r7a4r3w5s+5M/MGHVxT86ZqQnN8jkhIiJSMrSCLysrC4WFhXj//ffRsWNHaX+5zp07IyIiAp07d8a0adOQm5uLyMhIdOrUCTNnzsTw4cOlAzYOHDiA1NRUZGRkIDc3V2rDbDaje/fuCAkJkfb0E0VHRyM8PNzlutKpU6fw3Xff4dixYwAak4tA48rCmJgYKbl37tw5bNy4EWfPnpWWO3bv3h1ms1m13TfeeAOhoaG48sorERYWhi+++ALz58/HXXfdJWVTZ82ahZtuugnLli3DLbfcgjfffBNffPEFXnrpJSNTTETU6uSXVEkJEzERJf5HFHDxhMS8UivGxerbhF7tlEU1k9ZVSMk9uyAgv6Qq6JJ8Rk6MVN4LQJpTvZTvh9E5EZ8R41Cu5vOlbZG7OUm2RKHMWutzH2r8Fb/RfpItUU5jXbOzWrpXnkigwLA71Ff3ir/bHYLaYy0mnkCOT61t8Zqybb39NcX74U0f8mfqztdJ12eMSkCYuV2Tf06IiIiUDCX4XnjhBQDAqFGjnK6vX78eU6dOBQCsWLECISEhmDBhAhoaGpCRkYE1a9ZI977zzjv46aefsHHjRmzcuFG63rdvXxw5csS7UVzwwQcf4J577pF+nzhxIgBg4cKFWLRoEb788kvs2bMHAJCQ4PwvzIcPH0a/fv1U223Tpg2eeeYZHDp0CIIgoG/fvsjOzsacOXOke5KTk1FYWIgFCxbg0UcfRWJiIjZv3uwxKUlE1BpolVSKSZnLuoTjrqF9AFxMColJvryPq2AXGk8vjDewAb08CVRQWi2VVIrXxHaTLVEonJ7kVDYWzEk+cSxJ8ZGa91bU1Dol+eTjlrenpEwc6pkT+TNiH8ryO/l9SfGR0oo/ZdvKkmNA+7MjH6c4J2Jyz0j8enkzN/7sR0zyFZRWo95+TjqhkwJP/nlUao7/rfB3PIEcn1rbvvbXFO+HN30E2+eEiIhIyVCCTxA8/z9T4eHhWL16NVavXq36+qJFi5wOtdBD7zNTp06VEo1qRo0apWsMSnfddRfuuusuj/fdeeeduPPOOw23T0TU0okllQBcEj4A0DeqvUtiL3dMf6fy2ewUi+ETEnPSEqXkj7ykUkzumU0mFE5PcoormJN88rGIpcziayKxTFWkLCXVGp9WSZrRZ8QYte4T25O/1/LYchX/kaz22ZGPUyzHFUtZjcSvlzdzE4h+5KXHRERERERGeH2KLhERkUgtGVJmPQnAdZN1MfHzzy+OOpXPFuywIt5gv2ollQA0y3Kbq+ROD72lzMuLD6F31wh8//NvLqWkesvL5Iw8o4yxzHoSOWmJqm3L3+sy60lU1Jxy27+ectxkS1STlRn6q229/VTU1EpjrTdYdk1ERERExAQfERH5hVbJrNZKJbXy2XGxJozT2Z+7kkp3ZZbBtnIP0B6LfBWc3jJVf5aXyZ/RijG/pMqlbfl7LSbn3G3Cr/bZ0Rqn2r54gSgz9FfbevoRVyuKY31u+37phE4iIiIiIj2Y4CMiusSt2VmNuelXu1xX2y/NE62SWfnrauWzdoeApLiuKDr8MxJ3WDEnfYDbOIyc3Ag0T1mu2t5y4jUA0pjkq9XElWLyuHPH9Hc5cTXQpaRK3pSw2h2C5mm3au+p/LPTVOPU2v9PK0Z/tiP/LLj7LGt9P4mIiIiI5LjJCxHRJW5VabVU2ioSEzpiAkIvrZJZ+evK8lmgcR+2isM/I7GTAw7ZXqlacbg7uTF3TH+XkxuV15qCuLecfA7Ea8sViT5xtZp8nGLcZdaT0pyKqx7VEqeBHKO70lKtfj8/ckp6r+WfBa33VP7Zaapxqr1H7mL0ZzviM2XWky5l0KtKL56iG4zl5EREREQUfLiCj4joEjczNUF1/zNPq+OUPJ1C6ul1u92OvFIrxplMqu3JBeLkRn/Tu+LMHOK6Wk1OvnddIMtU3TE6t2LJqZi4FE+IFfeZU47VXflvIMfpbv8/I59/b9qRPyOeOiw+MzM1QSrRnZkafCXlRERERBR8mOAjIrrEzRiVgDBzO8298/TwVMKplthRJkWyUyyoqjqEvFIrXth12Ks4go3WvoRq17w99dZfZab+opWsE8tulSvzPI2zzHoSyZZuASujFQ+48OXzr4xZbztaz0y7sRf34CMiIiIiQ1iiS0REyElLlMpq1fbO80RPCaeeEs+M3gJCzer7trVUanOrZ771zpm/ykz9RRm3OFaxXHdov0i394vEcQIIeBltmbVWc79AI7z5Hvn63SMiIiIiAriCj4iIoL53npFEg6cSTj2rmGw2G7Z9b4LNLngdRzDS2pfQ03zrLYv1V5mpvyjjVo5fmZDT89nxVO6th7t5EkuJff3cefM9Untm2o29DPdNRERERJc2JviIiC5xa3ZWY3Xp96p749kdglTWqCxxlJdH+qMUtGCHFUVHzZiVasGc9AFSHL6WaBotYdV7+q1WG/LnlYmoSesqpLlNio+U9l5T7tMnb9NI/L6Wmfqbp30X9VIrZVU7hEPsU+szodWOvHzc2xi9GavWMw32c7r7JSIiIiICWKJLRHTJW1Va7VJSmTumP5YXH8LnR05JZY3yEkd5eaQ/SkHzS6oaD9iItSM7xeIUR0XNKZ9KNI2WsOo9/VarDfFeMZknT96UWWul+0JMJikBJM63cm6NxB9spZ5ae+vJx2qEfHzifn7efCbU2vE1Rm/G6u4Z+Sm6RERERER6cAUfEdElbmZqguZJpXaHgKT4KCkRISYsADjtj+brajG7Q8CsVAvif6tUjaPMetLrEk2jJax6T7/VasP5dNQop/7kq/bU5rbMetLp1Fwj8ftaZu1v7vbWE183Qjk+8WResU29nwm1dnyN0ZuxunumwX6Oh2wQERERkSFM8BERXeJmjEpQva5MPCwvPoS25osLv/1ZCjpnTH/YbDYUFVW6vKbch82bfo2ecKp1v9425M/3f2yLx/7EudW6z1P8/iqF9Se9ewjqoTU+Mcmn9zOh1Y5aMtSfe1AafWbGqAQm+IiIiIjIECb4iIguQatKtUsP80uq8Fn1SYxIuLjvXU5aopREMZsayx99LQX1tLecpxiMrgCTP68nbq379bahtz9f79Mq9QQ8r0L0hdG9Db3laXx6T79tinmSz4n4s7iPJQCXPSvF1/0xT0RERER0aeMefERElyCtPcrke5jJ9w4TyxrNJhPsggC7ILicCutNDGr7kxXssOqK4fMjpwz1p3WarZH7jbSh915f73NX6pk7pr/hRKheRvc29Ja78SVbonR/FptinuRzIv4s7mOp3LNSvO6veSIiIiKiSxtX8BERXYLkJYBrdlZjbvrVmuWLFTW1KLPWSqeNirJTG0t7vV39pFw99eDIftj2vQlFR60eYxD/1LvPnNESVnf362lDb3/+uM+fpbBGGN3b0Fta4xMPLdH7njbFPMnnRLlnJQCXz3EwnHRMRERERK0DE3xERJe4VaXVWLfrmMseZjlpiVJCQjxtFHA9XEOexPAlybeqtAo2uxmzUi1uY0i2RKFwepJLQkerLFQt6WR3CC6HNIgmratwm3wps550iV0egy8HZajFJd9vTlxlptaeryWz3jyvd29Df5fzNldZsh7yOOR7VoqfX7WTe4mIiIiIfMUEHxHRJU4sb1Tbw2xov0jsqTkFuyAgxATMHu2clJAnZrwtcXTeW09AdopFMwYxOSJfuWd3CE4JHyW10kxzyMVkoTxucVWY8mRVsQ3A9URfZQxJ8ZG6TlTVG5eY9Cuz1iIpPkqzPbEkVP6aOCatuZHz9nk9ewj6GpuSv0/o9TflnACNe1YCkEqKmdwjIiIiIn9igo+I6BJ33u5AuGwPM2XCSb7HmZz8Pl+SFeLecqFmE2z2xj345qQP0IxBa4Wb1oootZVh8lVWYtLMXTvyNtTKQfWWpspf0xuXmPRzl9BSPms0Ll+eV9sbUCtOf5XzNldZsl7KOQEg7R0pHgqit7yciIiIiEgPJviIiC5xM1MTMDf9akx8qVwzAQOor1zzlbyPB0f2w6yXtiCv1Aqz2ayaBJKXq3oqC/VET3mpVmmpWDrsawzexhWIZ7153sjehr7Mt9iXWimv8rRa+bMTX2rcaDLZ0s3lWV9P+tWKVb6SM9nSTZoPuyA47SHZ3KXERERERNS68BRdIqJL0Jqd1dLPM0Y1HpaRbOkGoDEBM2ldhVNyrzGp1k3ab8/bk3Pl1FZwZfQWMCvV4hKDfJ+13DH9pb3M3JWF6pGTlui2RNndSbH+isGbuAL1rJHntfbBc/cZ8WW+tU6cVZ5WKz91uaLmFCpqXE+r9cdJv2qxyhOcISaTlIwWJcVHSZ9fMcnnj+8SERERERFX8BERXYLU9iiTr7D6trbO5TAN5Z50/ohBbXVYdooFZrMZn1Wf1CxLFQ/ecFcWqoen8lJ3paXiaixfY/AmrkA9a+R5b/bB82W+tVYSyp8Rk2ZaJz+LMfjjpF+1WMUDWHLH9IfdISApPkr6U5wT+Z6V4utERERERL5igo+I6BI0MzUR8/e4XtdTRumvJJanfdTcrRyT70nnrizUHb3lpWpzIiaOfI3Bl7j8/azR543ug+fLfOvd23B58SHV02qNtqeXtyXRLMslIiIiIn9jgo+IiJx4OhXVm33S/EWrLBSAT4ks4OJptVrtiOW48sSRLzH4e3xGx6R8r/w1t+5iS4qPlK4p2xbjnXOhf08n8yrJnwFcT6s12h6g/7PuTdvu+pt2Yy+3/RERERERKXEPPiIicqJWRinnzT5p/uKuLFQsi/S2HfG02mSLc9mkOC4xYSQeluBrDP4enzdjkr9X/ppbd7GJh06In52LeyqedIrH02dQjfiM2dTYhvy0Wm/aA/R91r1t211/8j0ylf0REREREanhCj4iIpLoKaP0Zp80fzFaFmqkHfm4xD3T5ONXzona3nS+jt2X8Rkdk/K98tfc6olN+ZmqqDnlMr9GyoyV+yKqnVbrTdmyp8+6+Jq/SrXFZ54v/g8Q0Xhtzc5qrC79PuDfLSIiIiJq2ZjgIyIiAMZKNL3de8yTLUdDULPDijnpA1TjC3SJotq4APhcttqcZc3u3qvmiEseT97HVbALgkuCTL7i0NN8K5N7ask2rf7V2nN3v3wPRvGa8nOfFB/pc5KvwX4O88obf19VWo2Hx1zF5B4RERERucUSXSIiAmC8RDMnLVEqS/R17zFRiElAXqm1Wcp/RfJxhZjgl7LV5ixrBrTfq+aKKyctEWaTCXZBgNl0McEo7hlYZq116tvdfIuf26H9Il0SsUnxkUiKj3R51uj7J58/cQ/GMqvzKc8XE43dfC5pnjEqQfrZX98tIiIiImrduIKPiIgAeHcqqnLvMV8TERm9BSQmWpql/FekHJcWI7E0Z1kzoP1eNVdc+SVVUnLPLgiYtK4ChdOTpD0DtZKqatx9bt/MHK75mpGxKefvYglwN+l1f86ZfA8+f323iIiIiKh1Y4KPiIgMc7dPmt0h+FT2mZ1igdls1l3+688yU2/2f9MrUGXNauRzohzTpHUVWF58CBU1tSicnqQaV1J8ZECTe8p4yqy1sMwvcirX9YW7z8TElxprX9WSf2qfF63PhLi/n7/fy/ySKqwqrZb24JuZmuC3zyARERERtV4s0SUiIkO09urLHdMfy4sP4fMjp3wu+zRS/uuvMlNP4/LldFRRIMqa1YhzIibz5MmpMmstYrtGoMxai0nrKlziAiCtTPM3tTkunJ6kWq7rC3efiYqaU6ioOaXr8+LuM1FmrZVO6vXXeyn2NzP1YonujFEJfv0MEhEREVHrxBV8RERkiLu9+sTXk+KjnFYdGS1hNFL+668yUz3j8lUgyprVyOck2RKluZKvzForJY3clSP7i9ocK8t1/TEnek+/VXtN3re7z0RFTS3KrLV+fS/F/qbd2Es6ZEM+Hn98BomIiIiodWKCj4iIDDGyV583JYwFO6zIK7UaKpP1R/mr0T0IjQpk+a8a+Zz0f2yLy5wUTk9yOWlWLfnlT8o5bu6SaE+fF63PhLgS0t9xi/3Vna/THA8RERERkRpDJbpLly7F0KFD0bFjR0RHR2P8+PGorKx0uqe+vh5ZWVmIiopChw4dMGHCBJw4cUJ6ff/+/bj77rsRGxuLiIgIDBw4EHl5eZp9fvbZZ2jTpg2GDBniMT5BEPDEE0+gZ8+eiIiIwOjRo1FV5VzO8uWXX2LMmDHo0qULoqKikJmZiV9//dVtu5WVlUhJSUGPHj0QHh6O+Ph4LFiwADabzem+t99+GwMGDEB4eDiuvPJKFBUVeYyZiKglW+GhbNBoCeO2701OyT1Af5msp/JXtVjFa/klVVghS3QBUL2mJD6v1rb8+sSXygNe/qvGSEmw+Lp4kq1WietdL5ZrxqtnzuT3NmdJtNZrnj4nyvdS3LePZbRERERE1JwMJfh27dqFrKwsVFRUoLi4GDabDenp6airu/j/NM+ZMwf/+te/8Pbbb2PXrl04duwY7rjjDun1vXv3Ijo6Ghs3bsTBgwfx2GOPYf78+SgoKHDp7/Tp05g8eTLS0tJ0xffss88iPz8fa9euxZ49e9C+fXtkZGSgvr4eAHDs2DGMHj0aCQkJ2LNnD7Zu3YqDBw9i6tSpbtsNDQ3F5MmTsX37dlRWVmLlypVYt24dFi5cKN1TVlaGu+++G9OmTcNXX32F8ePHY/z48Thw4ICu2ImIWiJP+9/ZBcGphNETh2DCrFSLaklk7pj+bksU1cpfPcUqXtPae83T/n3i88p9B8XnxesANEs9PY3LF57mpMx6EgCcXhdPsk22RDnFJZ8Tf+x56K781V9z4m78Wq95+pwAcFm5Jx7oEcj3koiIiIjIHUMlulu3bnX6fcOGDYiOjsbevXsxcuRInDlzBq+88goKCwuRmpoKAFi/fj0GDhyIiooKJCUl4d5773VqIz4+HuXl5di0aROys7OdXnvggQcwadIkmM1mbN682W1sgiBg5cqVWLBgAW6//XYAwGuvvYYePXpg8+bNmDhxIj788EOEhoZi9erVCAlpzG2uXbsWV111Faqrq5GQkKDadnx8POLj46Xf+/bti507d+LTTz+VruXl5eHmm2/G3LlzAQB///vfUVxcjIKCAqxdu9Zt7ERELZW7vc4A10SI/Bk1Y2MdGJdicduXGj2lnmqx6mnLHeVed+LptGKCTF7G6akNf/M0J+KBE8rXc8f0l1ajJcVH6W7L6J6HzVkSDcDj50Xrc5Js6aY5ZpbREhEREVFz8WkPvjNnzgAAIiMjATSuzrPZbBg9erR0z4ABA9CnTx+Ul5cjKSlJsx2xDdH69etRU1ODjRs34sknn/QYy+HDh3H8+HGnvjt37oxhw4ahvLwcEydORENDA9q2bSsl9wAgIiICALB7927NBJ9SdXU1tm7d6rQysby8HLm5uU73ZWRkuE1MNjQ0oKGhQfr97NmzAACbzeZS/tsSycdgs9lgMzXvmMR4WsPctiT5pdUIMZmQrZK0KdhhhUMQkJOq77vXUjTVmH3px5/fzwdH9oPdbsfy4kNYVVoFm71xBdOsVAseHNkPNpvN6R673a4as7ffUXHPPj39qcU6K7XxNeU1sS29488rtSLEhAunqzb+aaQdf/I0J2XVP6Hi8M+ar89KtWBWqkVzTrTmsTnG6s34Ac+fT39/TowItr8/xTjkfxJdyvgdJQpe/H5Sa2Pkc+N1gs/hcGD27NkYMWIEBg8eDAA4fvw42rZtiy5dujjd26NHDxw/fly1nbKyMrz11lv46KOPpGtVVVV45JFH8Omnn6JNG30hiu336NFDs+/U1FTk5ubiueeew6xZs1BXV4dHHnkEAPDjjz967CM5ORlffvklGhoakJmZiSVLljj1765vNUuXLsXixYtdrm/fvh3t2rXzGE+wq7fXSz9v27YN4ebwZozmouLi4uYO4ZJi/d6EoqNmVFUdQkbvi6Vr2y5cHxdrR1G9vj27WoqmGrMv/fj7+xkPwGwyw2YHTBAwNtaB+N8qUVRU6XTPuFgTKg9Voei3Ss22jH5HK4+GYFysoLs/eaxmU+NzULkmb8sTsU27YAIgwC6YvGrHXzzOyclTGOfhPRob63A7J2rz2BxjVeNu/AmdGv9PPk+fl0B8TvQK1r8/Af4dSgTwO0oUzPj9pNbm3Llzuu/1OsGXlZWFAwcOYPfu3d42gQMHDuD222/HwoULkZ6eDgCw2+2YNGkSFi9ejP791ct33njjDdx///3S71u2bIHZbPbY36BBg/Dqq68iNzcX8+fPh9lsRk5ODnr06CGt6hs0aBC+/fZbAMCNN96ILVu2SM+/9dZb+OWXX7B//37MnTsXzz//PObNm+f1+OfPn++06u/s2bOIjY1Feno6OnXq5HW7waLufB3wdePPGRkZaN+2fbPGY7PZUFxcjDFjxiA0NLRZY7mUjAOQeGE1TWKiBdkpFhTssKLoaOPqGrWVXC1dU43Zl378/f0s2GGFXbAi1GyCzQ4kJvZXLbUd56YNb7+j7tpUe00Za03E5QDgcs3I+yS2GWJq3EfQbALsgslwO/5idE7UXlebJ/lYPL3enNyO382L8pcC8TnRK9j+/gT4dyiRHL+jRMGL309qbcRKTz28SvBlZ2fjww8/xCeffILevXtL12NiYnD+/HmcPn3aaRXfiRMnEBMT49TGN998g7S0NGRmZmLBggXS9V9++QVffPEFvvrqK2lPPofDAUEQ0KZNG2zfvh233XYbhg0bJj1z2WWXSSvwTpw4gZ49ezr1LT+Bd9KkSZg0aRJOnDiB9u3bw2QyYfny5dIee0VFRdISSLF8VxQbGwsAuOKKK2C325GZmYmHHnoIZrMZMTExTqcFa41bLiwsDGFhYS7XQ0NDW8UXP1S4OIZgGlMwxXKpmJM+AGazGcuLD+GFXYdx3u5AsiUKc9IHuNwrnkjpbn+u5rJCtpm+kjJutTEb2Z9MLyP9yONXfj9f+OSI1/OeX1LldPKtdPCA2ezVeAP5HdWKFVA5OEFn/GKb4p578j/zSq1ez0Nz8vSe+vs9DzaB+JwYEax/fwLBFw9Rc+B3lCh48ftJrY2Rz4yhU3QFQUB2djbee+89lJaWIi4uzun1a6+9FqGhoSgpKZGuVVZW4rvvvsPw4cOlawcPHkRKSgqmTJmCp556yqmNTp064euvv8a+ffukfx544AFcfvnl2LdvH4YNG4aOHTsiISFB+iciIgJxcXGIiYlx6vvs2bPYs2ePU9+iHj16oEOHDnjrrbcQHh6OMWPGAGg8QENs97LLLtOcC4fDAZvNBofDAQAYPny4U99A4xJctb6JLkU5aYnSaZVmU+Mpnb6ewtnUjJ4eKh9zW3NIwBIfevvRin/Nzmqv513roAHxkAY9J+c2Fb0HQRiJX2xTfqBG4fQk5I7pLyX5gm0ePPH0nk5aV9Fi3nNvBOJzQkREREQUaIZW8GVlZaGwsBDvv/8+OnbsKO0v17lzZ0RERKBz586YNm0acnNzERkZiU6dOmHmzJkYPny4dMDGgQMHkJqaioyMDOTm5kptmM1mdO/eHSEhIdKefqLo6GiEh4e7XJczmUyYPXs2nnzySSQmJiIuLg6PP/44evXqhfHjx0v3FRQUIDk5GR06dEBxcTHmzp2L//3f/3XZN1DujTfeQGhoKK688kqEhYXhiy++wPz583HXXXdJ2dRZs2bhpptuwrJly3DLLbfgzTffxBdffIGXXnrJyBQTtVr5JVVSAkpcwefrKZxNzd2JsWpxK8ecX1IVkLHp7Ucef4P94l4Oq0qr8fCYq7yKze4QVMcu/m53CGqPNQu1WMVr4s8ivfGLz9sdApLio1xOUxWvB9M8eOLpPf2s+mSLec+9EYjPCRERERFRoBlK8L3wwgsAgFGjRjldX79+PaZOnQoAWLFiBUJCQjBhwgQ0NDQgIyMDa9aske5955138NNPP2Hjxo3YuHGjdL1v3744cuSId6O4YN68eairq0NmZiZOnz6NG264AVu3bkV4+MWNNf/9739j4cKF+PXXXzFgwAC8+OKL+Nvf/ua23TZt2uCZZ57BoUOHIAgC+vbti+zsbMyZM0e6Jzk5GYWFhViwYAEeffRRJCYmYvPmzW6TkkSXCmUSTL7qaXnxIRSUVgeshNXf5Ekyd3FrjVnehj8Y7Ue89nzxf4ALuxDMTE3wOiZ3Jb3B9l6qxepr/C1p/Hp5GpOnVW0tXSA+J0REREREgWYowScInv8f6vDwcKxevRqrV69WfX3RokVYtGiRkW51P2MymbBkyRKn022VXnvtNUN9A8Bdd92Fu+66y+N9d955J+68807D7RO1ZlrlfkBjksxsMgW8hNXfctISpeSeWtyexiz/XQ+tvf/EfpLiIw31k5OWiPzSA9LvM0Yl6I6FiIiIiIiIgo+hPfiIiIxyV+6XbImCXRCcSktbArWSWDl3YxbLOY3Q2juvzHoSAJBs6WaoHzF+0Zqd1YbiISIiIiIiouDi1Sm6RER6aZW25ZdUSYcSBLKE1d/0lMT6u5xPa++/ippTmmXNWv2I8c5MTcC88sZrq0qrEWZuF9TzTkRERERERNqY4COiJudNCatWmarYnt0huE2stfS49e79pzf+aTf2khJ8M1MTWkRylYiIiIiIiNSxRJeImpw3JaxaZapi0socYgpozEDzx52TliiVBXuzZ6FW/DNGJXhVOkxERERERETBgSv4iKjJeVPCqlWmqlxRF0jNHbfa3n9GnudJoERERERERK0TE3xEFHS0ylpz0hJRUVPrU5mqrzEAxkuC/V1eq2fPQk/xn7PV6e6biIiIiIiIghtLdIko6Lgray2z1sJsMnldpuqPGLwpCfalvFZr77/cMf1VYwxE/ERERERERBS8uIKPiIKOu7LWZEsUyqy1Xpep+iMGb1YN+lJe627vP/F1o/HLD9kgIiIiIiKilo0JPiIKSmplrWJyT1mmWmY9iWRLN7+fsOuP0loxBr3ltWqltWLsamNxF4u7+OvOs0SXiIiIiIiotWCJLhEFLXlZq9lkckruia/njumPippTAStH9fXkWqPltcFUGkxEREREREQtA1fwEVHQUpa1JluiNMtUy6wnA3LCrq8n1xotrw2m0mAiIiIiIiJqGZjgI6KgpFXWqpagyklLdLrHXyfsGj25Vo270mCtNpqiNHjajb0MtUVERERERETBiwk+IgoK8r3n1BJT4ko4dwm2nLRErPz4kGY5qtZ+fGr73okx9O4agTLrSSmJCFxcXQfA6/39PMlJS5SSe76WBtsdglNidHnxITTYz0n3riqtwiM3D/Fn+ERERERERNSEuAcfEQUF+d5z8rJW+d5z4t51aqfGAo1JLfElsRxV/prWHnZq+97ZHQKSLVH4/uffUFFzSnpNjEEsCfZlfz931EprjZDPoXx8anMYqDEQERERERFR0+AKPiIKCvLVZcrknvKACjXye8V25Cvt3O1hp7bvnTnk4qEeytcAoKLmlM8lwFr8XRqsNr7ntu+XXp8xKsFfoRMREREREVEzYIKPiIKGt3vPaR1CIU/yqR3QIT4rltmKq/LU+q6oqVV9Ta28V61tvdwlNY0m+eSUc1tvPwdEGG6GiIiIiIiIghBLdIkoqOSkJUplqXr3nlM7qVZsBwBMAMqstS5lrsqy3WRLNwBw6Tu/pApl1lqYTSaX19TKe9Xa1svdqbvuypP1UM4tERERERERtQ5cwUdEQUVt7zlPST61FXLKdpItUU4r4LRW/Ynk+94tLz6EZEsUyqy1LnGpra7z1LbRsYh8LQeWz0m93eFTW0RERERERBQ8mOAjoiahp5RVXA3ny95zYntq7YhJPrHMVl62K3+moqYWZdZap/JecT8+tbiMlhb7u6zXm7l9bvt+zCvX3QUREREREREFMSb4iKhJiAkmwDlZJ0++yZNo8vuMJPk87WEnltmaTSansl35AR1iOa5dEKTfPcWVk5YoJfc8lRZ7motcA8k9Pe2pze2MUQlSgm/NzmrMTb/aUJ9EREREREQUPJjgI6Im4amU1e4QkBTvehCG+Lvevefc7WEnrsxTlu0mxUc6nZarLMft3TXCY1xGSov9Xdbr7dzK54yIiIiIiIhaLib4iKjJeHtKrpGEl1Zpq3hQhlrZbpm1Fl9+e1pK+qndp5awUyvv1Vta7O1caPGlvZmpvu3tR0RERERERM2LxygSUZMyckruCpXTaUX5JVW468Vyt6+vuJBkU65mE5N1uWP6O52OK562qyzHzR3TX/WkXGXbep/xZi708Hd7RERERERE1DIwwUdETUqtlFWLuLec8h4xqabndcC5bFf+TE5aIpItUbALAswmEwQAsRrluGJyUMldSbDWM97MhR7+bo+IiIiIiIhaBpboElGTMVrKqmevOmUbaivq5GW78jbFPfnEslzxT3fluEruTrt1t4LOm7Jed/zdHhEREREREbUcTPARUZPwdLqt/Hc5T3vLebP3nPzADfE0XV8TYysurBhUeya/pAp2hyAlA72dC61+5PsJiisGvTmBmIiIiIiIiFomJviIqEm4K2UVX9eSk5YoJe/U9pbz9Lqaof0isafmFOyC4PSM0VN7RWLpr7wNwDmZJ/JlLtT6sTsEafVhUnyUofaIiIiIiIio5WOCj4iahLelrID63nLKJJq719WYQ0xSck/5jDer3fSUE4t8mQu1fswhJpfDQfS2R0RERERERC0fE3xE5DdGylT1UibJJr5UrplEA4Ay60mPZamB2q/OXbmwp7n5rPokRiR00zV3vvTjzXtAREREREREwY2n6BKR3+g91VYvtRVwyZZuABqTW5PWVTgl9xr3oeuG3DH9VePQalM88VbrGSNy0hKlVYHy0l9/nQjsj36IiIiIiIiodeEKPiLyGyNlqnqo7VUn7+Pb2jqn5J7yXrW953zZ/04PrXJhf50I7I9+iIiIiIiIqHVhgo+I/MqbU221aJWS6ulDqz9f9r/zxFPCzl8nAvvaDxEREREREbUuhkp0ly5diqFDh6Jjx46Ijo7G+PHjUVlZ6XRPfX09srKyEBUVhQ4dOmDChAk4ceKE9Pr+/ftx9913IzY2FhERERg4cCDy8vI0+/zss8/Qpk0bDBkyxGN8giDgiSeeQM+ePREREYHRo0ejqupimdrOnTthMplU//n888/dtr1z505cc801CAsLQ0JCAjZs2OD0+ieffIJbb70VvXr1gslkwubNmz3GS9Ra2R0CzCaT6qm2+SVVWHEhGbXCTUms/D41WiWqIl/a9kStbTHJlmyJklYBqpX+yuNWq5aVv65WTOtNP3pPFiYiIiIiIqKWyVCCb9euXcjKykJFRQWKi4ths9mQnp6Ouro66Z45c+bgX//6F95++23s2rULx44dwx133CG9vnfvXkRHR2Pjxo04ePAgHnvsMcyfPx8FBQUu/Z0+fRqTJ09GWlqarvieffZZ5OfnY+3atdizZw/at2+PjIwM1NfXAwCSk5Px448/Ov1z3333IS4uDtddd51mu4cPH8Ytt9yClJQU7Nu3D7Nnz8Z9992Hbdu2SffU1dXh6quvxurVq3XFStSafX7kFOzCxSSfmHRS7gPny35xaiWqcoHci06tbbtDQLIlCmXWWqe2xeSbmIyTx+0Q4NKO+DoACHB93Zt+1OaHiIiIiIiIWg9DJbpbt251+n3Dhg2Ijo7G3r17MXLkSJw5cwavvPIKCgsLkZqaCgBYv349Bg4ciIqKCiQlJeHee+91aiM+Ph7l5eXYtGkTsrOznV574IEHMGnSJJjNZo8r4gRBwMqVK7FgwQLcfvvtAIDXXnsNPXr0wObNmzFx4kS0bdsWMTEx0jM2mw3vv/8+Zs6cCZNJ+z/2165di7i4OCxbtgwAMHDgQOzevRsrVqxARkYGAGDs2LEYO3as2xiJLgX5JVUos9ZKSahkSxSWFx9CRU0tyqy1miWp4u969ovTcwpuIPeiU2vbHGJyGZ/yfq24l8tWE4o/y/cW9Fc/8nuIiIiIiIio9fBpD74zZ84AACIjIwE0rs6z2WwYPXq0dM+AAQPQp08flJeXIykpSbMdsQ3R+vXrUVNTg40bN+LJJ5/0GMvhw4dx/Phxp747d+6MYcOGoby8HBMnTnR55oMPPkBtbS3uuecet22Xl5c7tQsAGRkZmD17tse43GloaEBDQ4P0+9mzZwE0Jh5tNptPbQcD+RhsNhtspuYdkxhPa5jbYFWww4q8UitmpVqQnWKRfjebgDJrLZLiuuLBkf2c3oMHR/aD3W7H8uJDWFVaBZtdwKxUi8t9an2I98jbsNvtyE6xeNW2Ef6MO6/U6pTkE+8B4PS6P+cn2L6fYhzyP4kuVfx+EgU3fkeJghe/n9TaGPnceJ3gczgcmD17NkaMGIHBgwcDAI4fP462bduiS5c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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotDates(reassignDates)\n",
    "plt.title(\"Reassignation on submit\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e19d945-e7e2-4063-85b1-f1143d6d5c09",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "As we can see they are correctly shifted one quarter in the future, always on Mondays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4c352f95-2d4b-4049-b872-d84d36a0683f",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assert reassignDates['startDate'].dt.weekday.value_counts().index == [0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a95ab69-edd2-4eae-8958-f88968552903",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The plot below shows re-assignation dates as a result of running the\n",
    "re-assignation rule after four weeks from the second assignation date (survey expired): "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "385b93fa-d413-4e0b-9d6f-ef72a46a3dc4",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reassignation on expire')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotDates(expireDates)\n",
    "plt.title(\"Reassignation on expire\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "699a94f6-7b41-4644-a780-051e5cafdc56",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "As we can see they are correctly shifted one more quarter in the future, always on Mondays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "882311b8-dbc5-4524-ab60-0a94b8e6d5b2",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assert expireDates['startDate'].dt.weekday.value_counts().index == [0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2006891-3111-424f-be03-0b63cb4a0a61",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Test manual assignation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4416ffe2-c76d-4fd8-809f-cda0e4304f74",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The rationale behind the manual assignation rule is to assign surveys taking as\n",
    "reference the start of the current quarter. Surveys will be assigned randomly in\n",
    "the 13 weeks of the quarter.\n",
    "\n",
    "Surveys assigned in the past and already expired will be shifted one quarter in\n",
    "the future by the first timer rule run and so on for other surveys expiring\n",
    "soon.\n",
    "\n",
    "Let's check that the manual assignation rules assigns them randomly in the\n",
    "current quarter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0d5f8221-b1f2-4bc9-9c96-9b0d8e6f7237",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0% 0/500 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0% 1/500 [00:00<03:08,  2.65it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0% 2/500 [00:00<02:58,  2.79it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  1% 3/500 [00:01<02:51,  2.90it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "  1% 4/500 [00:01<02:47,  2.95it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "  1% 5/500 [00:01<02:50,  2.91it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  1% 6/500 [00:02<02:53,  2.85it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "  1% 7/500 [00:02<02:50,  2.89it/s]"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "  2% 8/500 [00:02<02:50,  2.88it/s]"
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    },
    {
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      "\r",
      "  2% 9/500 [00:03<02:48,  2.92it/s]"
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    },
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      "\r",
      "  2% 11/500 [00:03<02:47,  2.91it/s]"
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    },
    {
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     "output_type": "stream",
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      "\r",
      "  2% 12/500 [00:04<02:49,  2.88it/s]"
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    },
    {
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      "\r",
      "  3% 13/500 [00:04<02:49,  2.87it/s]"
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     "text": [
      "\r",
      " 99% 494/500 [03:37<00:02,  2.82it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 99% 495/500 [03:37<00:01,  2.80it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 99% 496/500 [03:38<00:01,  2.85it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 99% 497/500 [03:38<00:01,  2.82it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100% 498/500 [03:38<00:00,  2.85it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100% 499/500 [03:40<00:00,  1.52it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100% 500/500 [03:40<00:00,  1.59it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100% 500/500 [03:40<00:00,  2.26it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "testDate = datetime.now()\n",
    "run_rule(\"testCleanupTestDate\")\n",
    "run_rule(\"testCleanupIntervalAndSurvey\")\n",
    "for i in tqdm(range(500)):\n",
    "    run_rule(setTestDate(testDate))\n",
    "    run_rule(\"testAssignRule\")\n",
    "    run_rule(\"testCleanupIntervalAndSurvey\")\n",
    "run_rule(\"testCleanupTestDate\")\n",
    "run_rule(\"testCleanupIntervalAndSurvey\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3b8c4aa4-4dfb-4919-818d-1b0ebe7c9189",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assignDates = get_reports(\"testAssignRule\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f297927-40b6-4d03-bfec-a0fb77819ff3",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "As always, on mondays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2ba64b48-cd23-472f-8ff5-a003183da608",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assert assignDates.startDate.dt.weekday.value_counts().index == [0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4a95b82-bfcd-46f7-9875-a242bdd1473c",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Inside the current quarter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "95c8c990-54f6-4f63-b3f9-19b814dede84",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                    500\n",
       "mean     2024-02-12 19:38:23\n",
       "min      2024-01-01 22:59:59\n",
       "25%      2024-01-22 22:59:59\n",
       "50%      2024-02-12 22:59:59\n",
       "75%      2024-03-04 22:59:59\n",
       "max      2024-03-25 22:59:59\n",
       "Name: startDate, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assignDates.startDate.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3da55bf7-730a-4e7c-8b08-dc83015074c3",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Distributed randomly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "42deb020-1c5c-45ab-8e13-9946fb7b7061",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='week'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "assignDates.startDate.dt.isocalendar().week.value_counts().sort_index().plot(kind='bar', figsize=(15, 5))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "argv": [
    "python",
    "-m",
    "ipykernel_launcher",
    "-f",
    "{connection_file}"
   ],
   "display_name": "Python 3 (ipykernel)",
   "env": null,
   "interrupt_mode": "signal",
   "language": "python",
   "metadata": {
    "debugger": true
   },
   "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": "3.11.7"
  },
  "name": "tests.ipynb"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}