notebooks/27_random_var_generation.ipynb

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   "source": [
    "# Section 2.7 — Random variable generation\n",
    "\n",
    "This notebook contains the code examples from [Section 2.7 Random variable generation](https://minireference.com/static/excerpts/noBSstats/noBSstats_ch02_PROB.pdf#page=200) of the **No Bullshit Guide to Statistics**.\n",
    "\n"
   ]
  },
  {
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   "metadata": {
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   },
   "source": [
    "#### Notebook setup"
   ]
  },
  {
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   "source": [
    "# load Python modules\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import random\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "074e7b9a-e7db-4b29-87ec-6b22d75a2406",
   "metadata": {},
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   "source": [
    "# Figures setup\n",
    "sns.set_theme(\n",
    "    context=\"paper\",\n",
    "    style=\"whitegrid\",\n",
    "    palette=\"colorblind\",\n",
    "    rc={'figure.figsize': (7,4)},\n",
    ")\n",
    "\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "259b99fa-4aeb-4141-afcd-d29ba95f95b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set random seed for repeatability\n",
    "random.seed(16)\n",
    "np.random.seed(16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "715bb601-3b5f-426c-9532-f0941db50f0e",
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "78b94478-a1e2-4dc9-a380-7b6d3885999d",
   "metadata": {},
   "source": [
    "## Why simulate?\n",
    "\n",
    "Running simulations of random variables is super useful:\n",
    "\n",
    "- fake data generation\n",
    "- probability calculations\n",
    "- statistical procedures\n",
    "\n",
    "(see book)\n",
    "\n",
    "\n",
    "General procedure to simulate $\\mathbb{E}_X(g)$:\n",
    "\n",
    "```Python\n",
    "n = 30\n",
    "\n",
    "gvalues = []\n",
    "for i in range(0,n):\n",
    "    xi = gen_x()\n",
    "    gi = g(xi)\n",
    "    gvalues.append(gi)\n",
    "\n",
    "expg = sum(gvalues) / n\n",
    "```\n",
    "\n",
    "We'll see different variations of this procedure (for loop that generates many random observations and does something with them)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "088ab8ff-09e9-4c98-bd09-587f7adf264d",
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  },
  {
   "cell_type": "markdown",
   "id": "9d372301-e4da-4051-83de-4e2183bf12c0",
   "metadata": {},
   "source": [
    "## Random variable generation using a computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "87d688b8-c9ce-459c-8afc-e4dd75cf1ffc",
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    {
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       "0.36152277491407514"
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "random.random()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "324f55f9-7363-4b48-b58d-f07c33307442",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # ALT.\n",
    "# import numpy as np\n",
    "# np.random.rand()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9925c29-2645-4f9f-bc09-ad960aac7023",
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  {
   "cell_type": "markdown",
   "id": "597ac3fb-da31-45f3-a7c8-cb6c768e3013",
   "metadata": {},
   "source": [
    "### Discrete random variable generation\n",
    "\n",
    "Splitting up the uniform random variable ..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6eef5596-b7bc-42e3-8ac0-3c7a2c5a2c50",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Example 1: generating Bernoulli observations\n",
    "\n",
    "Consider the Bernoulli random variable $B \\sim \\textrm{Bernoulli}(p)$,\n",
    "which corresponds to a coin toss with probability of heads (outcome 1) equal to $p$,\n",
    "and probability of tails (outcome 0) $(1-p)$.\n",
    "\n",
    "The function `gen_b` defined below is a generator of observations from the random variable $B$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8bce456c-ea68-403f-aebf-09def0d2de58",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_b(p=0.5):\n",
    "    u = random.random()\n",
    "    if u < p:\n",
    "        return 1\n",
    "    else:\n",
    "        return 0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20a2a8e4-18c1-40ce-9b60-c92915f61024",
   "metadata": {},
   "source": [
    "To generate a random observation from $B \\sim \\textrm{Bernoulli}(p=0.3)$,\n",
    "we simply need to call the function `gen_b` with the keyword argument `p=0.3`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   ],
   "source": [
    "gen_b(p=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2856c93e-d59e-45ba-ae92-f3b99074c1b2",
   "metadata": {},
   "source": [
    "Let's now generates `n=1000` observations from $B \\sim \\textrm{Bernoulli}(p=0.3)$,\n",
    "and compute the proportion of the outcome $1$ (heads) in the list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d7fb1c7c-4829-4876-8a04-3b14c469eaf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "0.316"
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 1000\n",
    "bsample = [gen_b(p=0.3) for i in range(0,n)]\n",
    "bsample.count(1) / n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0ecabf78-f691-40ba-9508-af72cedb55c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # ALT. Use regular for-loop, instead of list comprehension syntax\n",
    "# n = 1000\n",
    "# bsample = []\n",
    "# for i in range(0,n):\n",
    "#     b = gen_b(p=0.3)\n",
    "#     bsample.append(b)\n",
    "# bsample.count(1) / n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53505ef5-4c0d-4dcb-ad78-fe39c7cad77b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e07ca2b9-04c0-4819-93b4-a750b64a1df2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b9a93315-a0fb-4532-b3f6-cfa45916fae8",
   "metadata": {},
   "source": [
    "### Continuous random variable generation\n",
    "\n",
    "See the book or explanations of the the invers-CDF trick.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24291429-637a-4767-ab4d-88d98015afde",
   "metadata": {},
   "source": [
    "#### Example 2: generating observations from a shifted uniform distribution\n",
    "\n",
    "\n",
    "\n",
    "$V \\sim \\mathcal{U}(\\alpha=100,\\beta=120)$\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97c9793d-d7b3-4ec0-af6c-5860b3483599",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_v():\n",
    "    u = random.random()\n",
    "    v = 100 + 20*u\n",
    "    return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b7033c1b-d877-453e-8797-b912f16c89f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "107.26199234069637"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gen_v()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "86d8f9d9-afbb-44f7-b200-78af246c7fe8",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 100\n",
    "vsample = [gen_v() for i in range(0,n)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "031ea4f9-7ae0-4d0c-a2b0-4953dfdcfaaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[103.6386436977451, 117.34140363667541, 113.35634072970831]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsample[0:3]  # first three observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "51b37927-af77-42dc-ad9f-88ef31f05fea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100.32987267319582, 119.88187770589093)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(vsample), max(vsample)  # Range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2a26742b-4753-4380-8675-363d478a67cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 249,
       "width": 443
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot a histogram of data in `vsample`\n",
    "sns.histplot(vsample, stat=\"density\")\n",
    "\n",
    "# plot the pdf of the model\n",
    "from scipy.stats import uniform\n",
    "rvV = uniform(100,20)\n",
    "xs = np.linspace(90,130,1000)\n",
    "sns.lineplot(x=xs, y=rvV.pdf(xs), color=\"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d54ca54-b923-45bc-9259-f3002ec63485",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "89092fbc-1c47-4f51-95bf-cb33760cc7d8",
   "metadata": {},
   "source": [
    "#### Example 3: generating observations from an exponential distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dd8c6be5-92d7-4627-a011-153374ddbe8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_e(lam):\n",
    "    u = random.random()\n",
    "    e = -1 * np.log(1-u) / lam\n",
    "    return e"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b02c68ff-2a4c-49ba-bd07-f098d531828a",
   "metadata": {},
   "source": [
    "Where `lam` is the $\\lambda$ (lambda) parameter chosen for exponential model family."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2568d8cc-b822-43b4-ba4b-4c5a6b69aa7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(6)\n",
    "\n",
    "n = 1000  # number of observations to generate\n",
    "esample = [gen_e(lam=0.2) for i in range(0,n)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4b74232b-b5bd-4808-8c54-ae1d6380d29c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.5024273707608603, 10.625297726488984, 2.731193337322976]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esample[0:3]  # first three observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e8826a24-82c5-42ae-82ca-a3b02b01aa53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YsYKXX34Zq9XKxIkTy7WtS9mzZ4/T1lURkZGRxCal88DiX8s17nmfFjTN3M2ubz/i1SPXX7b/f0beSGSAB7GxsVdYqZTEarUCVefnScpHx8+96fi5Nx0/96dj6N50/CqPWwRAu91+yeUXB7WKWLFiBV5eXtx9993Flt18881YLBbGjx/vCJb9+/dn5MiRzJkzhxEjRhAQEOC0WtzZ9oDONM3cTbOM37HknSPT7O/qkkREREREajy3CIAWiwWA7OzsYsuys7Px8/Nzynbsdjvr16/n5ptvLnGd3bp1o1u3bkXaDAYDQ4cOZfPmzfz+++9FHhlRES1atHDKeirKarViMBjwPX8Mympvndvh1DxM2Lgh5zc2B/S+ZH+j0YiPj0+V2e/qovCvZvq+uicdP/em4+fedPzcn46he9Pxu7QtW7Zc8Vi3mASmXr16wB/3Al4oISGB2rVrO2U7e/bs4cyZM/Ts2bNc40JCQgDIzc11Sh3VwWnvCBK8GwLQJmWji6sRERERERFwkwAYGBhIgwYN2Lt3b5H2vLw89u/fT8uWLZ2ynW3btgHQqVPJz6576KGHijwWotCRI0cAiIiIcEod1YLBwI7ggrOhLVM3YbbluLggERERERFxiwAI0Lt3b9avX8/x48cdbStXriQzM5N+/fo5ZRv79u3Dz8+vyLMGLxQUFMSGDRuKBNH09HQ+/PBDWrVqRZMmTZxSR3XxW8gtAPjkZ9Ls7GYXVyMiIiIiIm5xDyDAuHHjWLVqFaNHj+aBBx4gOTmZefPm0aNHD8cZu23bthEXF0evXr0c9w2WR1xcHHXr1sVgMJS4/IknnmDdunWMGTOGP/3pT3h6evLJJ5+QkJDAq6++WqH9q46O+LXmrEcogblJtEtez+7gm11dkoiIiIhIjeY2ZwBr1arFwoULiYyMZNasWSxfvpxhw4Yxa9YsR5+PP/6YZ555huTk5CvaRmpq6iUnlAkPD2fx4sW0bt2a999/n3feeYfatWuzcOFCOnbseEXbrM7sBiO/BxdMmtMmZSNGe56LKxIRERERqdnc5gwgQNOmTZk/f36py2fMmMGMGTNKXT5kyBCGDBlS6vJVq1ZdtoZrr72WDz744LL9pMBvIbfSLWEV/nmpNEn7nQOBl38moIiIiIiIVA63OQMo7ml/wPVkmAqeAXhdynoXVyMiIiIiUrMpAEqlshnNjtlAr0tej8Fuc3FFIiIiIiI1lwKgVLrfQm4FIDgnkYj0PS6uRkRERESk5lIAlEq3N+hGso0+ALRL1mWgIiIiIiKuogAolS7X6MWuoM7A+fsA7XYXVyQiIiIiUjMpAMpVUXgZaO2s49S3HnZxNSIiIiIiNZMCoFwVu4I6k2vwAAomgxERERERkatPAVCuiiyzL/sCbwAUAEVEREREXEUBUK6a7ecvAw3PPEitrOMurkZEREREpOZRAJSrZkdwV2znf+R0FlBERERE5OpTAJSrJsMjiAMB7QA9DkJERERExBUUAOWqKpwNNCp9F4E5iS6uRkRERESkZlEAlKuqMAACtEv63nWFiIiIiIjUQAqAclWd9QzjkH9bAK5PXufiakREREREahYFQLnqtobcBkCTc78TlJ3g4mpERERERGoOBUC56raHdseGAYB2yd+5uBoRERERkZpDAVCuurOeYRwuvAw0SZeBioiIiIhcLQqA4hJbQ28HoHH6ToKzT7m4GhERERGRmkEBUFxiW8gfl4G2T/7etcWIiIiIiNQQCoDiEuc8Qzl4/qHw7ZPWurYYEREREZEaQgFQXGZrSMFloFHpu7EnH3VxNSIiIiIi1Z8CoLjMbyG3Yjv/I2j/baWLqxERERERqf4UAMVlznmGcCCgPQA2BUARERERkUqnACgutTW04KHwHN9KTsJh1xYjIiIiIlLNKQCKS114GWjar8tcXI2IiIiISPWmACgule4RzP7A6wFI+/kTF1cjIiIiIlK9KQCKyxXOBpp1dCs5pw+6uBoRERERkepLAVBc7reQW8FoAuDsLzoLKCIiIiJSWRQAxeUyPAIxNO0BQNpPS11cjYiIiIhI9aUAKFWCod1QALKP7yDr2A4XVyMiIiIiUj0pAEqVYGgzEIOHNwBnNy1xcTUiIiIiItWTAqBUCQbvAPzbDQQg7eePsNtsLq5IRERERKT6UQCUKiOg83AAcs8cxXpwk4urERERERGpfhQApcrwa9sXoyUIgLObFru2GBERERGRakgBUKoMo4cXATcUTAaT9ssn2PNyXVyRiIiIiEj1ogAoVUrg+ctA89OTSN/1jYurERERERGpXhQApUqxNL8Fc3ADQJeBioiIiIg4m1sFwNjYWCZMmEDHjh3p3Lkz06ZNIyMjo8zjjx49Sps2bdi+fXuxZevWraN58+YlfuTl5Tn6paen849//IOuXbvSvn17xo8fT1xcnDN2TwCD0URAp/sAOLdlFbbssh9fERERERG5NLOrCyirpKQkRo8ejdlsZuLEiaSlpREdHU1cXBxz58697Pj09HQee+wxcnJySlx+8OBBPDw8+Oc//1lsmclkAsBut/PEE0/w66+/MmbMGIKDg4mOjmbkyJF8/vnnBAUFVWgfpUBg5+Ekfz0Le04m57Z+TmDn+11dkoiIiIhIteA2ATA6OpqUlBRiYmIIDw8HIDw8nKlTp7Jp0yY6d+5c6tijR4/y6KOPsn///lL7HDx4kIiICAYNGlRqnw0bNrBx40ZmzZrFgAEDAOjWrRt33nknCxYs4Mknn7yynZMivCPb41nvWnJO7uXspsUKgCIiIiIiTuI2l4DGxMTQpUsXR/gDGDx4MBaLhZiYmFLHrVmzhoEDB5KQkMDQoUNL7Xfw4EGioqIuW0NAQAD9+vVztDVp0oSbbrrpkjVI+RgMBsdkMOk715B37oyLKxIRERERqR7cIgCmpqYSHx9Pq1atirSbzWaaN2/Orl27Sh174MABevbsyerVq+nQoUOJfex2O4cPH6Zx48YAZGVlYbPZivXbtWsX1157LUZj0W9bq1atiI2NLdf9iHJpgTedP+uXn0far8tdW4yIiIiISDXhFpeAJiQkAFCnTp1iy8LCwti6dWupYx9++GE8PT0vuf7jx49jtVo5fPgw/fr14/Dhw3h7e3PnnXfyl7/8BR8fH0cdzZo1K7EGgFOnTtGkSZMy79el7NmzxynrqajIyEjsdjsZmZmVuh2bzYbVaiU2NvaPxvpt4cTvnFr7Aafr3Vqp26+urFYrUHV+nqR8dPzcm46fe9Pxc386hu5Nx6/yuEUALDyz5u3tXWyZl5cXmZcIJ5cLfwCHDh0C4LfffmP8+PHUrVuXjRs38vHHH3P8+HGio6MddRSGwQsV1lX4gypO0rI/nPgdjm/FnnocQ1D45ceIiIiIiEip3CIA2u32Sy6/+JLM8goPD+eRRx5h8ODBREREANCrVy+CgoKYM2cOGzdupGvXrpddT0XruFCLFi2ctq6KsFqtGAwGfC2WSt2O0WjEx8enyH7n1X+C/eteBVs+Yac3Edb5r5VaQ3VU+FezqvLzJOWj4+fedPzcm46f+9MxdG86fpe2ZcuWKx7rFvcAWs6Hj+zs7GLLsrOz8fPzq9D6r7nmGp544glH+Ct07733AvDLL7846sjKyio2vrCtonVIUebAOvi17QtA6g8fXvYPASIiIiIicmluEQDr1asH/HEv4IUSEhKoXbt2pWw3JCQEgNzcXADq1q1LYmJiiTUYjUZCQ0MrpY6aLKjrnwDITTiE9cCPLq5GRERERMS9uUUADAwMpEGDBuzdu7dIe15eHvv376dly5YVWv8777xDz549i91LWDghSeGZwZYtW7J3795iZ6J2795No0aN8PX1rVAdUpxfu4EYfYMBSN34HxdXIyIiIiLi3twiAAL07t2b9evXc/z4cUfbypUryczMLPJcvitRt25djh07xsqVKx1tdrud2bNn4+3tTc+ePR01pKam8tVXXzn6HTp0iJ9++qnCNUjJjB5eBHa6D4C0Xz7GlqOJdkRERERErpRbTAIDMG7cOFatWsXo0aN54IEHSE5OZt68efTo0YNOnToBsG3bNuLi4ujVq5fjvsGyuOuuu1i6dCkvv/wyR44cISoqirVr1/LDDz8wZcoUx2MeevToQceOHXnhhRc4fPgw/v7+zJ8/nzp16jBy5MhK2W+BwC6jSVk3G5s1jXNbPyPwpvtcXZKIiIiIiFtymzOAtWrVYuHChURGRjJr1iyWL1/OsGHDmDVrlqPPxx9/zDPPPENycnK51u3h4cHcuXO56667+PLLL5kxYwZnzpzh5Zdf5qGHHnL0MxgMvPfee/Tt25cPP/yQd999l5YtW7JgwQKCg4Odtq9SlE+TTnjWLXj+4tkfPnRxNSIiIiIi7stg19SKVUrhlK4dOnRwcSUFrFYrR9NyeWTFzkrdzpyhbWkWVvosqomrp5O4/AUwGGn65nE8gupVaj3VhaZQdm86fu5Nx8+96fi5Px1D96bjd2kVyQxucwZQaragm0eBwQB2G2d/XOzqckRERERE3JICoLgFj9CG+La4DYCzP/xHzwQUEREREbkCCoDiNgK7jAYg+/hOso5uc3E1IiIiIiLuRwFQ3EZAxyEYvAqetajJYEREREREyk8BUNyG0duPgBuGAnB20xLsebkurkhERERExL0oAIpbCer6JwDyzyWS/nuMi6sREREREXEvCoDiVizNb8WjViQAqf+LdnE1IiIiIiLuRQFQ3IrBaCSo6xgAzm3/gtzUky6uSERERETEfSgAitsJumVMwTMBbfmaDEZEREREpBwUAMXteIRG4Nu6NwCp6+fpmYAiIiIiImWkAChuKfiWsQDknD5A5r7/ubgaERERERH3oAAobsmv/Z2Y/GsBkLp+rourERERERFxDwqA4paMHl4E3jwKgLTNy8nPSHVtQSIiIiIibkABUNxW0PnLQO05Vs7+9JGLqxERERERqfoUAMVteYe3wqfJTQCkbpjn4mpERERERKo+BUBxa4VnAbNit5B1dLtrixERERERqeIUAMWtBXQahsHLF4AUnQUUEREREbkkBUBxayYffwI7DQPg7I+LsOVYXVyRiIiIiEjVpQAobi/o1nEA2DJTObdlpYurERERERGpuhQAxe35NLkJz/otAEj5/gMXVyMiIiIiUnUpAIrbMxgMBJ8/C5i593uyT+x1cUUiIiIiIlWTAqBUC4Fd/4TBwwuAlO//7eJqRERERESqJgVAqRbMfqEE3FgwGUzqxgWaDEZEREREpAQKgFJtBN82AQBbRgppv3zi4mpERERERKoeBUCpNnya3IRXxHUApKyb4+JqRERERESqHgVAqTYMBgPBPQrOAloP/UTW0e2uLUhEREREpIpRAJRqJbDzCIzefgCkfKezgCIiIiIiF1IAlGrF5ONPYOeRAKT+uIh8a5qLKxIRERERqToUAKXaKZwMxp6dwdkfF7u4GhERERGRqkMBUKod74jr8GlyEwAp62Zjt9tdXJGIiIiISNWgACjVUvBtEwHIPr4D68FNLq5GRERERKRqUACUaingxnsw+gYDeiSEiIiIiEghBUCployePgR1GwNA2q+fkHfujIsrEhERERFxPQVAqbaCe4wHwJ6bTeqGeS6uRkRERETE9RQApdryqtsM39a9AUhZ+x72/DwXVyQiIiIi4loKgFKthfR6HIDcpDjObfvcxdWIiIiIiLiWWwXA2NhYJkyYQMeOHencuTPTpk0jIyOjzOOPHj1KmzZt2L59e7Flqamp/PWvf6Vr1660bt2aO+64g/nz5xd7hMCMGTNo3rx5sY/777+/orsnlcCvbV88ajcBIPmbd1xcjYiIiIiIa5ldXUBZJSUlMXr0aMxmMxMnTiQtLY3o6Gji4uKYO3fuZcenp6fz2GOPkZOTU2yZzWZjwoQJ7Nq1ixEjRhAZGcnGjRuZMWMGCQkJPPvss46+Bw4coHnz5owdO7bIOkJDQyu+k+J0BqORkJ6PcnrJJDL3fk9W3O94R7R1dVkiIiIiIi7hNgEwOjqalJQUYmJiCA8PByA8PJypU6eyadMmOnfuXOrYo0eP8uijj7J///4Sl8fExLBt2zZef/11+vfvD8D999/P5MmT+fDDDxkzZgy1a9cG4NChQ3Tv3p1BgwY5eQ+lsgR1G0PCp1OxZ2eQ/O2/qP/gv11dkoiIiIiIS7jNJaAxMTF06dLFEf4ABg8ejMViISYmptRxa9asYeDAgSQkJDB06NAS+/z88894enrSt2/fIu19+/YlLy+PnTt3AgVnEU+ePElUVJQT9kiuFpMlkKAuowE4u2kR+enJLq5IRERERMQ13CIApqamEh8fT6tWrYq0m81mmjdvzq5du0ode+DAAXr27Mnq1avp0KFDiX0mTZrE8uXLMRqLfjtSUlIAMJlMQMHZP4DGjRsDkJmZeWU7JFddSM9HAbDnWEnRIyFEREREpIZyiwCYkJAAQJ06dYotCwsL49SpU6WOffjhh3n99dcdl3CWJDg4mObNmxdps9vtLF26FLPZTJs2bQA4ePAgUHBW8eabb6Z9+/Z06dKFBQsWlHeX5CJ1/b0qdf1eDVri26onAClr38Vuy6/U7YmIiIiIVEVucQ9g4Uyf3t7exZZ5eXld8kycp6fnFW1zzpw57Ny5k/vuu4+QkBDgjwC4d+9ennvuOYxGIytWrODll1/GarUyceLEK9pWSfbs2eO0dVVEZGQkdrudjEo+2+lpMpKVm09sctlndS0v+w3jYNe35J45yp7V72Fo1rPStlVVWK1WoOr8PEn56Pi5Nx0/96bj5/50DN2bjl/lcYsAePGjGC528aWbFbVs2TLeeustrrnmGp5++mlH+80334zFYmH8+PGOYNm/f39GjhzJnDlzGDFiBAEBAU6tpSY5mmLlT4t+qbT1G+xBRIdEQvJR2LIYakAAFBERERG5kFsEQIvFAkB2dnaxZdnZ2fj5+TltW4sXL+bFF1+kfv36zJ07t8i6u3XrRrdu3Yr0NxgMDB06lM2bN/P777/TtWtXp9TRokULp6ynoqxWKwaDAd/zx6AyGQxU+naMXcZjW/08HP2ZKP98vMNbV+r2XK3wr2ZV5edJykfHz73p+Lk3HT/3p2Po3nT8Lm3Lli1XPNYt7gGsV68e8Me9gBdKSEi45P195fHBBx8wbdo0GjRowMKFCx3bvZzCS0Rzc3OdUodUHsONozB4FoTM5P++7eJqRERERESuLrcIgIGBgTRo0IC9e/cWac/Ly2P//v20bNmywttYunQpr732Go0aNWLx4sU0aNCgWJ+HHnqICRMmFGs/cuQIABERERWuQyqXwSeIoK5/AuDsjwvJS0t0cUUiIiIiIlePWwRAgN69e7N+/XqOHz/uaFu5ciWZmZn069evQuveu3cvL730EvXr1+fDDz+kbt26JfYLCgpiw4YNRYJoeno6H374Ia1ataJJkyYVqkOujpA7ngSDAXtuFilr33N1OSIiIiIiV41b3AMIMG7cOFatWsXo0aN54IEHSE5OZt68efTo0YNOnToBsG3bNuLi4ujVq5fjvsGyePvtt8nNzeXWW2/lp59+Kra8Y8eONGjQgCeeeIJ169YxZswY/vSnP+Hp6cknn3xCQkICr776qtP2VSqXV91m+LUbSPq2z0le+y6h/Z/B6Onj6rJERERERCqd2wTAWrVqsXDhQqZPn86sWbPw9/dn2LBhTJo0ydHn448/ZuXKlaxdu7ZcAfCXXwpmnvzoo4/46KOPii1//fXXadCgAeHh4SxevJhZs2bx/vvvA9CmTRtefvll2rdvX8E9lKsptM9k0rd9Tv65RM7+uIjg7g+5uiQRERERkUrnNgEQoGnTpsyfP7/U5TNmzGDGjBmlLh8yZAhDhgwp1r558+Yy13DttdfywQcflLm/VE2W5t3wjupI1pHNJK15g6BbxmJw8uNERERERESqGv3GKzWSwWAgtM9kAHJO7CF9x9curkhEREREpPIpAEqNFXDDUDxCC2ZuTfp6lourERERERGpfAqAUmMZTGZCej8BQObudWQd3e7agkREREREKpkCoNRoQbeOw+jtD+gsoIiIiIhUfwqAUqOZfAIIOj8D6Nmfl5KbfPwyI0RERERE3JdTA+Btt93G22+/zbFjx5y5WpFKFdr7CTCaID+P5G/ecXU5IiIiIiKVxqkBMDg4mPfee4/evXszYsQIPv30UzIyMpy5CRGn8wiNIOCGewBI+f598q1pLq5IRERERKRyODUAfvrpp3z55ZeMHTuW+Ph4XnjhBbp27cqzzz7Lpk2bnLkpEacK7TsFAFvmWVK+e9/F1YiIiIiIVA6n3wPYpEkTpkyZwnfffce8efPo1asX69at48EHH+S2227jrbfe0iWiUuX4RHXAt1UvAJK/fh1bTpaLKxIRERERcb5KmwTGYDDQpUsXXn31VWJiYrjzzjs5ceIEs2fP5o477mDs2LFs2bKlsjYvUm61BjwHQN7ZU5z94UMXVyMiIiIi4nyVFgAzMjJYsWIFY8aMoXv37nz22Wc0atSIp556ismTJ3P8+HFGjRrFsmXLKqsEkXKxtOiBd+MbATjz1avY8/NcXJGIiIiIiHOZnbmy/Px8NmzYwOeff853331HVlYWfn5+DB48mCFDhtC+fXtH3xEjRnDXXXfxzjvvcM899zizDJErYjAYqNX/OY6/M4TchEOkbf6UwE7DXF2WiIiIiIjTODUAdu3aldTUVAA6derEkCFD6N27N97e3sX6ent707JlS00OI1WK//WD8Kx3LTkn93Lmi5cJuPFeDAaDq8sSEREREXEKpwZAi8XCiBEjGDx4MA0aNLhs/+HDh/PQQw85swSRCjEYjdTq/ywn5o4hO+430n//Gv/r+rq6LBERERERp3DqPYAvv/wyw4cPLzX8nThxgpUrVzped+zYkRYtWjizBJEKC+w8HHNIQwCSvpzh4mpERERERJzHqQHwT3/6Ez/++GOpy3/44Qf+/ve/O3OTIk5nMHs6nguYuW8DmQdK/5kWEREREXEnFboENC4ujg8++MDx2m63s2zZMn7++edifW02Gz/99BO+vr4V2aTIVRF861jOfDaN/PQkznwxg4hJn7u6JBERERGRCqtQAIyIiODAgQNs374dKJhF8eeffy4xAAKYTCaefvrpimxS5KowevkS0vsJElf8lfTtq8k6tgPvhm1cXZaIiIiISIVUeBKYuXPncvbsWex2Oz179uT555/n9ttvL9bPZDIRHByMl5dXRTcpclWE3P5nkr56FVtWOmdW/5PwR5a6uiQRERERkQqpcAD08/PDz88PKJgEpmPHjmWaAVSkqjP5hRB8+59J+vIV0n75hOy7/oZXfU1aJCIiIiLuy6mTwAwePJiGDRs6c5UiLhXaZzIGTwvY7Zz5/J+uLkdEREREpEIqdAawdevWvPLKK/Tv39/xuix27txZkc2KXDXmgDBCbn+EpJjXOPvTR9S666941W3m6rJERERERK5IhQJg+/btCQkJKfJapLoJ7TuF5LXvYs+xcubzf9Lg4f+4uiQRERERkStSoQC4cOHCS74WqQ7MgXUI7jGB5DVvcHbTYsIG/R+eda5xdVkiIiIiIuXm1HsAS3Pw4EGOHDlyNTYlUilC+z2NwcMLbPmcWT3d1eWIiIiIiFwRpwfAhQsX8re//c3x+tFHH2XgwIH069ePiRMnkpOT4+xNilQ6j6B6BHd/GIDUHz4kJ1F/0BARERER9+PUAPjJJ5/wz3/+kx07dgCwbt06vv32W66//nqGDBnC999/z9y5c525SZGrJrTfsxjMnjoLKCIiIiJuy+kBsF27dixdWvDA7DVr1mA2m3n33Xf55z//yd13382XX37pzE2KXDUeIQ0IunUcAKkbF5Bz5qiLKxIRERERKR+nBsBDhw4xaNAgPD09Afjhhx9o06YNQUFBAFx33XUcP37cmZsUuapq9X8OTB6Qn0fSFy+7uhwRERERkXJxagA0m80YDAYA9u7dy5kzZ+jcubNjeXp6Or6+vs7cpEi51PX3qtB4j9CGBN/yIAApG+bpXkARERERcSsVegzExZo0acK6deu47777+PjjjzEYDHTv3h2AjIwMVqxYQZMmTZy5SZFy8TQZycrNJy7VesXrsHd5EjbMh/wcDi2dium+94v1iQjywdvDVIFKRUREREScz6kBcMSIETz99NN06NCBjIwM2rRpQ9u2bdmxYwePPPIIZ86c4d1333XmJkXKLS7VyoTlv1doHXeHDaLHqWXkb17KtNz+nPZpVGT5nKFtaRbmV6FtiIiIiIg4m1MvAR04cCCvv/46HTt25L777mPOnDkAeHt7ExAQwKxZs7jtttucuUkRl/hv/dFkG70xYqPfsXmuLkdEREREpEycegYQoF+/fvTr169IW9OmTTX7p1Qr5zxDWF93KL1PLKJD8jr+mzGKeN9mri5LREREROSSnP4geJGa4tv6I7CaCiY1GnBMz7cUERERkarPqWcAc3Nz+de//sWqVas4c+YMNputWB+DwcDu3buduVkRl8g0B7C23v0MOD6XNqk/0OjcTmL9W7u6LBERERGRUjk1AP7rX//i/fffJzAwkHbt2jmeByhSXX1X7166n1qGX95ZBhz7gH+1fMvVJYmIiIiIlMqpAfDzzz/n+uuvZ/78+Xh5Vex5ayWJjY1lxowZbN68GQ8PD/r27cvkyZPL/GzBo0ePMmDAABYuXEi7du2KLf/Pf/7D4sWLOX36NNdccw2TJk2ia9euRfqkp6cza9YsvvnmGzIyMrjxxht54YUXiIiIcMYuipvJNvnyTf2RDI57l2vTNtP07BYOBHZwdVkiIiIiIiVy6j2AZ86c4a677qqU8JeUlMTo0aPZv38/EydO5N5772XZsmU88cQTZRqfnp7OY489Rk5OTonL58yZw/Tp02nfvj3PPfccZrOZ8ePHs2XLFkcfu93OE088waeffsrdd9/NE088wZ49exg5ciSpqanO2E1xQxvq3s1Zj1AABh77N9jtLq5IRERERKRkTj0D2LBhQ5KSkpy5Sofo6GhSUlKIiYkhPDwcgPDwcKZOncqmTZvo3LlzqWOPHj3Ko48+yv79+0tcnpKSwuzZsxk2bBjTpk0DYPDgwQwaNIhZs2axZMkSADZs2MDGjRuZNWsWAwYMAKBbt27ceeedLFiwgCeffNKJeyzuItfoxdcNHmBY7Cwap++kTcpG4DpXlyUiIiIiUoxTzwDef//9LF68mMTERGeuFoCYmBi6dOniCH9QENIsFgsxMTGljluzZg0DBw4kISGBoUOHltjnu+++Iysri2HDhjnavL29ufvuu9myZQunT5921BAQEFDkMRdNmjThpptuumQNUv39WHsgiV71Abjz2Bzs+XkurkhEREREpDinngG02+14eXnRu3dvOnXqRGhoKEZj0YxpMBgcZ9nKKjU1lfj4eAYPHlyk3Ww207x5c3bt2lXq2AMHDtCzZ0+ee+45Nm7cyPLly4v12b17NyaTiebNmxdpb9myJQB79uyhTp067Nq1i2uvvbbYPrVq1YqNGzeSkZFR5vsRpXrJN3rwRcPxjDn4N+pZY7FvXgQDHnV1WSIiIiIiRTg1AE6fPt3x9ffff19inysJgAkJCQDUqVOn2LKwsDC2bt1a6tiHH374srORJiQkEBoaitlc9NsRFhYGwMmTJx39mjUr/rDvwn6nTp2iSZMml9yWVF9bQ2/j9pNLiMjYh23NdGy9HsToZXF1WSIiIiIiDk4NgGvXrnXm6hwyMjKAgssyL+bl5UVmZmapY8vyKIqMjAx8fHyKtRduz2q1lqufM+zZs8dp66qIyMhI7HY7GZf4HjuL3Y7bb2dpnbE8c/gZSDvJ6S9nktri3krZTlkV/kxWlZ8nKR8dP/em4+fedPzcn46he9PxqzxODYANGjRw5uoc7JeZVfHiSzJdtf6K1iHub49fe373v4G2534ldc0s7JE9MVhCXF2WiIiIiAjg5ABYKCYmhm+++YYTJ07w/PPPY7FY+P777xk+fDgWS/kviSsck52dXWxZdnY2fn5+FarXYrGQlZVVrL2wrfC+vsv1q2gdF2rRooXT1lURVqsVg8GA7xUct/IyGKgW2/mi0aO03fkA9qxzhOz5hLojXfdw+MK/mlWVnycpHx0/96bj5950/NyfjqF70/G7tAsfVVdeTj1llZ+fz5///GeeeuopvvrqK3777TcyMjI4ePAgr732GqNGjeLcuXPlXm+9evWAP+4FvFBCQgK1a9euUN1169YlOTkZm81WbN2AY/1169YtcYbThIQEjEYjoaGhFapDqocTvtdg6HA/AMnrZpOTcNjFFYmIiIiIFHBqAIyOjmbt2rU88cQTxMTEOC6t7NGjB48++ii7d+9m7ty55V5vYGAgDRo0YO/evUXa8/Ly2L9/v2O2zivVsmVLcnNzOXDgQJH2wr88tGrVytFv7969xS4Z3b17N40aNdIMoOJgvGMqBg8vyM8lYfkLri5HRERERARwcgBctWoVd9xxBxMmTCAoKMjR7uXlxaOPPsrAgQNZs2bNFa27d+/erF+/nuPHjzvaVq5cSWZmZpHn8l2J7t274+npyeLFix1tWVlZfPrpp9x4443UqlXLUUNqaipfffWVo9+hQ4f46aefKlyDVC+G4IaE9HocgLSfl2I9/KuLKxIRERERcfI9gHFxcYwcObLU5R07drziADhu3DhWrVrF6NGjeeCBB0hOTmbevHn06NGDTp06AbBt2zbi4uLo1atXue41DAkJYezYscyePZu8vDyuu+46Vq5cSXx8PDNmzHD069GjBx07duSFF17g8OHD+Pv7M3/+fOrUqXPJ/ZaaqdaAv5Cyfi62jBROL51C5F++x2AwuLosEREREanBnHoG0NfXl7Nnz5a6PD4+/oomgQGoVasWCxcuJDIyklmzZrF8+XKGDRvGrFmzHH0+/vhjnnnmGZKTk8u9/scff5wnn3ySH3/8kenTp5Ofn88HH3xA+/btHX0MBgPvvfceffv25cMPP+Tdd9+lZcuWLFiwgODg4CvaL6m+TL7BhA36KwCZ+zZwbvMKF1ckIiIiIjWdU88AdurUiU8++YRRo0YVW3bixAmWLl3KjTfeeMXrb9q0KfPnzy91+YwZM4qcsbvYkCFDGDJkSInLjEYjEydOZOLEiZesITAwkJdffpmXX365bEVLjRZy+yOkrJtNzqn9nP74afyu64/Rs/jzLEVERERErganngF8/PHHSUlJ4a677uLdd9/FYDDw3XffMWPGDO68806sVutlA5ZIdWIwe1Ln/oKz1LmJR0j+xnWPhBARERERcWoAbNKkCfPnz8fDw4NFixZht9v58MMPWbBgAQEBAcyePbvCM3aKuBu/6/rj26oXAGc+/yd5qadcXJGIiIiI1FROfxB8u3bt+Oqrr9i7dy9HjhzBbrcTHh5O69atMRqdmjdF3ILBYKDO8Nc5PPU6bFnnSFjxf9R/8ANXlyUiIiIiNZDTAuAvv/zCunXr2LVrF8nJyRgMBkJCQmjdujXh4eEKf1KjeYe3JrjHeFLWzSZ1wzxCbv8z3pHtXF2WiIiIiNQwFQ6AycnJPPnkk/z666/FHpAOBcFw/vz5dO3alVdeeYWQkJCKblLELYUN/gdnf1qCLfMsp5Y8SeRz3+mxECIiIiJyVVUoAGZmZjJ8+HBiY2Pp378/d999N82bNycoKIi8vDySk5PZtWsXn3/+Of/9738ZPXo0y5Ytw8fHx1n1i7gNc0AYYYP+yumPJpO5dz3ntqwioONgV5clIiIiIjVIha7LjI6OJjY2lldeeYVZs2Zx8803ExoaislkwsvLi3r16tGzZ0/efvtt3njjDQ4dOsSiRYucVbuI2wnp+SiedZoCcHrpZGw5WS6uSERERERqkgoFwG+//ZaePXsyaNCgy/bt27cvPXr04Ntvv63IJkXc2sWPhUj66lUXVyQiIiIiNUmFAuCxY8e44YYbytz/xhtv5PDhwxXZpIjb82s3AL/r+gFw5ouXyUk84uKKRERERKSmqFAAzMrKIjAwsMz9g4KCyMjIqMgmRdyewWCg7oi3MJg9sedmcXrJJFeXJCIiIiI1RIUCYH5+PiaTqewbMxpLnClUpKbxrHMNof2eAeDc1s8499tXLq5IRERERGoCPZxPxEVqDfgLHrUiATi16HFNCCMiIiIila7CzwHcvHkz+fn5Zeq7devWim5OpNowelmoM/xNjr89mNyEQyTFvEbYoKmuLktEREREqrEKB8BPPvmETz75pEx97Xa7HnwtcgH/6wfh26YPGTu+5swX0wm8eSSeYY1cXZaIiIiIVFMVCoCPPvqos+oQqVbq+nuVqZ/BYKDuyLc5/EJr7DlWTi+ZRMMnVlZydSIiIiJSUykAilQCT5ORrNx84lKtl+9sqge3PgFrZ3Ju6yr2bvgUY4s7yrytiCAfvD3KPhmTiIiIiNRcFb4EVERKFpdqZcLy38vU1yO/D1M9FxKac4rEhY/yz+sWkWPyKdPYOUPb0izMryKlioiIiEgNoVlARaqAXJM3y6KeAiA05xR9j0e7uCIRERERqY4UAEWqiJ3BXdga0gOA205+TIOM/S6uSERERESqGwVAkSrk00ZPYDX5YiKf+w+/isFetkesiIiIiIiUhQKgSBVy1jOMzxpOBKBRxh5uOb3CxRWJiIiISHWiAChSxfxQZxCH/VoDMODYvwnKTnBxRSIiIiJSXSgAilQxdoORjxo/S77BhE9+JkNj33B1SSIiIiJSTSgAilRBJy2N+bbecADapWygTfL/XFyRiIiIiFQHCoAiVdTX4WNI9KoPwLAjr+GTd87FFYmIiIiIu1MAFKmico1efNT4WQCCcs8w+Oi/XFyRiIiIiLg7BUCRKmx/YEd+qH0nADcnfkGL1J9dXJGIiIiIuDMFQJEqbmXEn0nxrA3A/YdfwTsvw8UViYiIiIi7UgAUqeKyzH58FPUMACE5p7kr7l0XVyQiIiIi7koBUMQN7A7uzE+1+gLQNeEzmp3d4uKKRERERMQdKQCKuIlPGz3OWY9QAIYfnoFnfqaLKxIRERERd6MAKOImrOYAlkY9DUCt7BPceex9F1ckIiIiIu5GAVDEjewI6cbm0F4AdD+1nKZnt7q4IhERERFxJwqAIm5mWaMnSfMIAWDUoZewW8+6uCIRERERcRcKgCJuJsMjiCWNnwMKZgW1ffaMiysSEREREXehACjihnYGd+GH2gMBsG9eQtrmlS6uSERERETcgQKgiJtaEfkYZ7zqA3BywcPkpZ5ycUUiIiIiUtW5VQCMjY1lwoQJdOzYkc6dOzNt2jQyMjIuO2716tUMGDCA6667jgEDBrB69eoiy0eNGkXz5s1L/VixYoWj72OPPVZinylTpjh9f0UuJdvky4dNpoLBQP65M5yY/xB2u93VZYmIiIhIFWZ2dQFllZSUxOjRozGbzUycOJG0tDSio6OJi4tj7ty5pY5bvXo1U6ZMoUePHowYMYJ169YxZcoUTCYT/fr1A2DChAkMHTq02Ng33niDtLQ0brjhBkfbgQMH6Ny5M4MHDy7St2HDhk7aU5GyOxxwHYbuT2L/7g3St39B6vq5BHd/yNVliYiIiEgV5TYBMDo6mpSUFGJiYggPDwcgPDycqVOnsmnTJjp37lxsTG5uLjNnzqRr167Mnj0bg8HAsGHDGDVqFK+99hp9+vTBaDTSpUuXYmNXrVrFyZMnmT59uiPc5eTkcOzYMe6++24GDRpUuTssUkbGO17AfHAt2cd+59SSSfi2uA3POk1cXZaIiIiIVEFucwloTEwMXbp0cYQ/gMGDB2OxWIiJiSlxzNatWzl9+jTDhg3DYDAAYDQaGT58OPHx8fz2228ljsvIyOCVV16hXbt23H333Y722NhY8vLyiIqKcuKeiVSMwexFg/GLMJg9sWdnEP/+COx5ua4uS0RERESqILcIgKmpqcTHx9OqVasi7WazmebNm7Nr164Sx+3evRuAli1bFmkvfF24/GIffvghycnJPP3000XaDx48CEDjxo0ByMzMLOeeiFQO74ZtqH3PywBYD/1M4qq/u7YgEREREamS3CIAJiQkAFCnTp1iy8LCwjh1quTZD0sbFxYWBsDJkyeLjcnOzmbBggV06tSJjh07FllWGAAXLlxIx44dad++PbfddhtffPFFOfdIxPlCej+Jb5s7ADjzxctk7F7n4opEREREpKpxi3sAC2f69Pb2LrbMy8ur1DNxGRkZmM1mPDw8irQXrsdqtRYb8/XXX5Oamsro0aOLLSsMgHFxcbz00ktkZmayaNEiJk+ejM1m48477yzfjl3Cnj17nLauioiMjMRut5NxFc522u1oO1fAZrNhtVqJjY3F3v0FOLQZMpM4+u59ZA3/CHyCq8zPk5RP4b9ROn7uScfPven4uT8dQ/em41d53CIAXm5qe6Ox5BOZlxtXeF/ghVasWEG9evW47bbbii3r06cPrVu35qGHHnKMHTBgAP379+e1115j4MCBJa5TpDLVC/DBy8tEo0aNgEZkjo3m9DuDID2R4E2vU3viJ6W+R8orJyeHEydOOGVdIiIiInL1uUUAtFgsQMHlmRfLzs7Gz8+v1HF5eXnk5eVhNv+xq1lZWQDFxqWnp7Nlyxbuu+++En9hLnxsxIU8PT0ZNGgQ77zzDrGxsU6bIKZFixZOWU9FWa1WDAYDvuePQWUyGNB2roCX2UhOvp1j6fkFDZG3Ybj1cezr38a64yvi1szG1G1ChbcTEeRDoI8PgYGBFV6XlE3hXz2ryr8HUj46fu5Nx8/96Ri6Nx2/S9uyZcsVj3WLAFivXj3gj3v6LpSQkEDt2rUvOS4xMdHx9YXruXjcpk2byM3N5fbbby9XfcHBwUDBYydEXCEu1cqE5b87XptsQ5jsu4aIjH3kfP48rx0OI963aYW2MWdoW5qFlfzHFhERERFxD24xCUxgYCANGjRg7969Rdrz8vLYv39/sVk+CxX+xeDia4cLX188q+i2bdvw8PCgQ4cOxdaVl5fHkCFD+Nvf/lZsWWxsLAaDgYiIiLLvlEglyjd6MP+af5Bl9MbDnsuYA3/DM1+z1oqIiIjUdG4RAAF69+7N+vXrOX78uKNt5cqVZGZmlnhpJkCHDh0IDQ1lyZIljjabzcaSJUto2LAhbdq0KdJ/3759REVF4enpWWxdZrMZb29vvvjiC06fPu1oP336NCtWrKBnz54lTlIj4iqJPg1Z2OBxAOpmHeX+w68WzEwjIiIiIjWW2wTAcePGYbFYGD16NB9++CFvvvkm06ZNo0ePHnTq1AkoOIP32WefOWYFNZvNTJo0if/973888sgjLFu2jAkTJrB582amTJlS7D6/uLi4IpeKXuy5554jKyuL4cOHM3/+fObMmcPQoUMxGo089dRTlbfzIlfox+Be/C+44NEQNyR9Q9eEVa4tSERERERcym0CYK1atVi4cCGRkZHMmjWL5cuXM2zYMGbNmuXo8/HHH/PMM8+QnJzsaLvnnnuYNm0ahw4d4sUXX+TkyZO88cYb9OnTp9g2UlNTS51QBqBt27ZER0dTr1493njjDT744ANatWrF0qVLHQ+HF6lqFjV4lHhLEwDujn2Lhul7LzNCRERERKort5gEplDTpk2ZP39+qctnzJjBjBkzirUPGzaMYcOGXXb9v/7662X7dOrUyXHGUcQd5Bi9mdf0JZ7eORaf/EzGHvg/XmkzD6s5wNWliYiIiMhV5jZnAEXkyiX4RLCk8V8AqJV9gpGHput+QBEREZEaSAFQpIbYFnob39cdCsB1Kf/j9pMfubgiEREREbnaFABFapCVEY8S61vw2JQ74+bQJG27awsSERERkatKAVCkBsk3ejCv2YtkmAMwkc/YA1MJyk5wdVkiIiIicpUoAIrUMCledZl/zd+xYSQgN4Vx+5/HbMt2dVkiIiIichUoAIrUQHuDOvF5xAQAGmXsYdiRWZoURkRERKQGUAAUqaG+rTecLSG3AdA58Uu6nV7p4opEREREpLIpAIrUVAYDi5s873hI/NCjb9I47TcXFyUiIiIilUkBUKQGyzH58EGz6WSY/DHZ8xl3YCqBOYmuLktEREREKokCoEgNd8Y7nAVN/4ENAwG5yTy87zk88rNcXZaIiIiIVAIFQBFhT1AnPm9YMClMZMZeRh36Jwa7zcVViYiIiIizKQCKCADf1h/Bz7X6AHB98jr6HZ/n4opERERExNkUAEWkgMHAR42f5ZB/WwD6xi+g45n/urgoEREREXEmBUARccgzevJBs+mc8aoHwIhDLxN1bqeLqxIRERERZ1EAFJEi0j2CmdP8VawmCx72HB7a/xzB2adcXZaIiIiIOIECoIgUc8rSmOimL2LDSEBuChP2PYM965yryxIRERGRClIAFJES7Qm6iU8jHwegQeYhbIsewJ6f5+KqRERERKQiFABFpFTr6w5lQ53BANj3/peT/5mI3W53cVUiIiIicqUUAEWkdAYDyxs9yc6gmwFIXT+XM6umubgoEREREblSCoAickk2g5noptOgYQcAElf9nZT1ekagiIiIiDtSABSRy8ox+WB6cBketZsAcHLBeM799pWLqxIRERGR8lIAFJEyMfiHETnla0z+YWDL5/i/7sF6+FdXlyUiIiIi5aAAKCJl5lnnGiImfYHB04I9J5O41/uTc/qQq8sSERERkTJSABSRcvFpciPhf/4EjCbyzyVydGZvclNPurosERERESkDBUARKTf/dv2p96c5AOQmHiZuZm/y05NdXJWIiIiIXI4CoIhckeDu46h97wwAso/vJO71ftiy0l1clYiIiIhcigKgiFyxWv2fJbT/cwBYD/3MsbfuwpaT5eKqRERERKQ0CoAiUiG175lOcI8JAGTsXkv87Puw5+e5uCoRERERKYkCoIhUiMFgoO7odwm46X4Azm39jBNzH8Rus7m4MhERERG5mAKgiFSYwWikwUP/we+6/gCc/XEhpxY9jt1ud3FlIiIiInIhBUARcQqD2YPwR5dhufZWAFLWvsvpJU8pBIqIiIhUIQqAIuI0Rk8fGj75OT5NbgIg+b9vcnrp0wqBIiIiIlWEAqCIOJXJJ4CIKV/j3fhGAJK/nkXCJ88pBIqIiIhUAQqAIuJ0JksgkVPW4B3VEYCkr14lYfkLCoEiIiIiLqYAKCKVwuQbROTT/8U78noAkr54mcQVf1UIFBEREXEhBUARqTQm32Ain/kG74h2AJz5/CUSV/5dIVBERETERRQARaRM6vp7XdE4k18IEc9+i1fEdQCc+Wya7gkUERERcRGzqwsoj9jYWGbMmMHmzZvx8PCgb9++TJ48GV9f30uOW716Ne+//z7Hjh2jYcOGjB8/noEDBxbps3DhQl566aViY+vUqcOGDRscrxMTE5kxYwY//PAD+fn53HLLLTz//POEhoY6ZydFqihPk5Gs3HziUq1XMNoL+9hV8P4gOPE7SV+9SnJqKsa7ZmIwFv07VESQD94eJqfULCIiIiJFuU0ATEpKYvTo0ZjNZiZOnEhaWhrR0dHExcUxd+7cUsetXr2aKVOm0KNHD0aMGMG6deuYMmUKJpOJfv36OfodOHCA2rVrM2XKlCLjLRaL4+usrCzGjh3L6dOnGTNmDAaDgblz53Lw4EGWLVuGp6en83dcpAqJS7UyYfnvVzzep/4rPJI2maj03dh//DcbD8SzpPGz2A1/BL45Q9vSLMzPGeWKiIiIyEXcJgBGR0eTkpJCTEwM4eHhAISHhzN16lQ2bdpE586di43Jzc1l5syZdO3aldmzZ2MwGBg2bBijRo3itddeo0+fPhjPn304dOgQ1157LYMGDSq1hhUrVrBv3z4++ugjrr++YGKLNm3aMGbMGD777DPuueeeSthzkerDag7gXy3eZMLeZ2h6bjudE7/Ew5bNh03+D5vRbf45EhEREXFbbnMPYExMDF26dHGEP4DBgwdjsViIiYkpcczWrVs5ffo0w4YNw2AwAGA0Ghk+fDjx8fH89ttvjr4HDx4kKirqsjU0a9bMEf4Abr75ZqKiovj6668rsnsiNUa2yZf3rp3FnsCC5wR2TPqWsQemYrbluLgyERERkerPLQJgamoq8fHxtGrVqki72WymefPm7Nq1q8Rxu3fvBqBly5ZF2gtfFy4/c+YMqampNG7cGACr1VriBBW7d+8uVgNAq1atSq1BRIrLNXnzfvNX+D24KwDXpfyP8fuexTM/08WViYiIiFRvbnHNVUJCAlAwIcvFwsLC2Lp1a7nGhYWFAXDy5Emg4OwfwObNm3n//fc5ceIEAQEBDB8+nMcffxyTyURGRgbp6eml1pCSkkJ2djZeXlc2U+LF9uzZ45T1VFRkZCR2u52MzMr/xdxuR9tx8rZs+fmA8+pw9j69Hf4CD9leodPZ72lx9hf+vPMx8vt9hdXPRGxsrNO2466s1oIJd6rKvwdSPjp+7k3Hz/3pGLo3Hb/K4xYBMCMjAwBvb+9iy7y8vMgs5RfSjIwMzGYzHh4eRdoL11P4g3Xo0CEAduzYwSOPPIK/vz9r1qxhzpw5JCUl8dJLL122BoDMzEynBUCRmiDfYOb9iOewxlvonvwVTax7sb93B7lPrnZ1aSIiIiLVklsEwMs9L8xoLPlK1suNK7wvsGXLlkyYMIEHHniA4OBgAPr06YPJZGL58uU8+OCDl33UxKXquBItWrRw2roqwmq1YjAY8L1gNtTKYjCg7Th5W4Vn65xVR2Xt0/Kmz2M9Xpu+8Qsg8QCnZt5G1NNr8A5v7fRtuZPCv3pWlX8PpHx0/Nybjp/70zF0bzp+l7Zly5YrHusW9wAWPoohOzu72LLs7Gz8/EqeMt5isZCXl0deXl6R9qysLADHuPbt2zNp0iRH+Ct07733Yrfb+fXXXx0BsHDsxTVcuD4RKSeDgS8bPsQnjSaBwUBe6gli/9mNzP0bXV2ZiIiISLXiFgGwXr16wB/39F0oISGB2rVrX3JcYmJisTFAqeMKhYSEAAWPk/Dz88Pf37/YugrXFxoaismkh1eLVMSGukMxjliAweyJLTOVo6/24tzWz11dloiIiEi14RYBMDAwkAYNGrB3794i7Xl5eezfv7/YLJ+FCk8ZX3zzaOHrwhk9p06dypAhQ4qNL5yEIiIiwrG+i2uAgtlBS6tBRMrH2G4IEZNjMHr7Y8/N4tjbg0le+56ryxIRERGpFtwiAAL07t2b9evXc/z4cUfbypUryczMpF+/fiWO6dChA6GhoSxZssTRZrPZWLJkCQ0bNqRNmzYA1KpVi127dvH99987+uXm5vLBBx9Qu3ZtOnXq5Khh165dbN++3dHvxx9/5MiRI6XWICLl59vyNiL/8j2mwDpgt3Hqwz9zaslT2G35ri5NRERExK25xSQwAOPGjWPVqlWMHj2aBx54gOTkZObNm0ePHj0cAW3btm3ExcXRq1cvLBYLZrOZSZMmMXXqVB555BF69OjBN998w+bNm3nrrbcck7Y8+OCDfPbZZ0yaNInRo0cTGhrK6tWr2bFjB7NmzXLM7HnvvfeyaNEiJkyYwLhx47DZbHzwwQe0atWKAQMGuOx7I1Id+TS6nqj/+4ljr/cn+8Rukte8QW7iYRpMWIzR6/KTMomIiIhIcW5zBrBWrVosXLiQyMhIZs2axfLlyxk2bBizZs1y9Pn444955plnSE5OdrTdc889TJs2jUOHDvHiiy9y8uRJ3njjDfr06ePoExAQwMKFC7n11ltZsmQJr732GgaDgdmzZ9O/f39HPy8vLxYsWMANN9zAu+++S3R0NN27d+ff//43np6eV+cbIVKDeIY1otHUH/BteTsA57Z+Ruz0W8lNPeniykRERETck9ucAQRo2rQp8+fPL3X5jBkzmDFjRrH2YcOGMWzYsEuuOzw8nDfffPOyNdSrV4933nnnsv1ExDlMvkFETI7h5H8mkLohmqzYLRz5RycinvoS74ZtXF2eiIiIiFtxmzOAIlJzGcwe1HtwLrWHTgcgL/kYsS914dw2PTBeREREpDwUAEXELRgMBmoN/AsNHlmKwcMLW9Y5jr01iMTV07Hb7a4uT0RERMQtKACKiFsJ7DSMyL+sxxxUD+x2Epe/QPzs+7FlZ7q6NBEREZEqTwFQRNyOpUknov6+Ge/GNwKQ9vPHxP6zK7lJcS6uTERERKRqUwAUEbfkEVyfRn9ZT2DXPwGQdXQbh//WkYx9/3NxZSIiIiJVlwKgiLgto6c39cfNp87wN8BgJP9cIkdfuY2k/76t+wJFRERESqAAKCJuzWAwEHrHk0RM+RqjbzDk53F68RPEz76ffOs5V5cnIiIiUqUoAIpIteDXuheN/7EF78jrgYL7Ao/840ay43e7uDIRERGRqkMBUESqDc+wKBpN/YGgWx8CIOfkXg7/40bObvrIxZWJiIiIVA0KgCJSrRg9van/4L+p/9ACDJ4+2LMziJ8znJMf/hlbbraryxMRERFxKQVAEamWgrr+iaj/+wnPOtcAkLL2PWL/2Y2c04dcXJmIiIiI6ygAiki15R3Rlqi/b8a/4xAAso78yuG/tiP1h0UurkxERETENRQARaRaM1kCCX90OXVGvIXB7IktK50T/x5F/PujyLemubo8ERERkatKAVBEqj2DwUBo78eJ+uvPeNa7FoCzPy7i8F+vx3r4VxdXJyIiInL1KACKSJVS19+r0tbtHdmOxv/YTNCt4wDITTjEkZdu5syXr2C32SptuyIiIiJVhdnVBYiIXMjTZCQrN5+4VGvlbWTgGxgjboHlj2GzniXhk+dI37GG+uPm41krsvK2KyIiIuJiCoAiUuXEpVqZsPz3St5KE2ZP+hGfTx7CevBHMvd8x+EX2lBn+BsE3fIgBoOhkrcvIiIicvXpElARqbEMIRE0en49YXe/BCYPbFnnOBk9jmNv3klu6klXlyciIiLidAqAIlJj1fX3wmAyE3bnCzT+2y94hbcBIH37Fxx+vjVnf/7ExRWKiIiIOJcuARWRGqvI/YaWa7A/+h2G/07H/t2b5GckE//eME78uAzj4JkYfGtd8XYignzw9jA5sXIRERGRK6MAKCI1WvH7De8mqmUzRh16idpZx7FvX07qzm9Z3uhJtoT2hCu4N3DO0LY0C/NzXtEiIiIiV0iXgIqIXOSIfxtmtFnA+jp3A+Cfl8qYg39nwr6nCc4+5eLqRERERK6cAqCISAlyTD4si3qK11vN5pR3waMhWqdu4oXfRnLLqeUY7HpuoIiIiLgfBUARkUs47N+WGW3nE9PgAfINJrxtVu6NfYMndz1C3cwjri5PREREpFwUAEVELiPP6MWXDR/ilTbzifVtCUCT9B08t+MBBsbNwTO/Eh9aLyIiIuJECoAiImV0wtKEWa3nsDzycbKN3pjtedxxYiFTfxtB2+QNYLeXOK6uv9cVba9Ro0Y0atSoAhWLiIiIFKVZQEVEysFuMPF9vWH8FnIrd8e+RbuUDYTknObh/X9hZ1Bnljd6kjPe4UXGFHncRDnYbAX3GRrT88vUX4+bEBERkctRABQRuQIpXnWZ2/xlWqZs4p7YNwjLjqd16iaa/7aF/zYYxTf1R5Bn/OPMX/HHTVxeRmYmAL4WS5n663ETIiIicjm6BFREpAJ2B3fmn9ct5MvwseQaPPGw59D/+Dym/jaCdknflXpZqIiIiIgrKACKiFRQntGLmPAH+ed1C9kZ1BmAWtknGXdgKk/u/jPZsVtcXKGIiIhIAQVAEREnOeMdzpzmM5nT/FVOezcE4JpzvxH/z5vIXzqBwJxEF1coIiIiNZ0CoIiIMxkM7AzuwvS2C1ke+TiZJn+w27FvXsxft9/PHccX4GHLdnWVIiIiUkMpAIqIVIJ8owff1xvGP9p9TMBtfwajCS+blYHHP+D/tt9Pp4QvMdjLNruniIiIiLMoAIqIVKIMj0BqDX8L01M/sSvoJgBCck4z6vB0nv99NG2S/6eJYkREROSqUQAUEbkKDHWvZfa1s3j32lkct1wDQD1rLOP3P8fkXeO5Jm2biysUERGRmkDPARQRuYr2BN3E3sAbuT5pLQOO/Zuw7BNEpe/iyd2PsivwJj6PGE+8bzNXlykiIiLVlAKgiMhVZjcY2VKrF9tDutM54Qv6xs8nMDeJVmd/otWOn9gSchtfh4/hIHVdXaqIiIhUM251CWhsbCwTJkygY8eOdO7cmWnTppGRkXHZcatXr2bAgAFcd911DBgwgNWrVxfrc+LECSZPnkynTp1o06YNAwcOZNWqVcX6PfbYYzRv3rzYx5QpU5yxiyJSg+QbPdhYdzD/aPcxnzccT6bJD4AOyet44fdRTDz6Ig2yjpR5fXX9vSqrVBEREakm3OYMYFJSEqNHj8ZsNjNx4kTS0tKIjo4mLi6OuXPnljpu9erVTJkyhR49ejBixAjWrVvHlClTMJlM9OvXD4DMzExGjx5NamoqI0eOJCwsjK+//ppnn32WjIwMRowY4VjfgQMH6Ny5M4MHDy6ynYYNG1bOjotItZdj8uG/DUazsc5d3H5iCbeeWo63zcqNZzdw49kNbA3pwdfhYzhhaXLJ9XiajGTl5hOXaq30miOCfPD2MFX6dkRERMS53CYARkdHk5KSQkxMDOHh4QCEh4czdepUNm3aROfOnYuNyc3NZebMmXTt2pXZs2djMBgYNmwYo0aN4rXXXqNPnz4YjUYWLVrEsWPHWLp0Ke3btwdg+PDhDB8+nDfffJN7770XDw8PcnJyOHbsGHfffTeDBg26qvsvItVfpjmA1RETWFfvfm47uZRbTi3Dx2bl+uTvuD75O7aFdCemwRhO+F5T6jriUq1MWP57pdc6Z2hbmoX5Vfp2RERExLnc5hLQmJgYunTp4gh/AIMHD8ZisRATE1PimK1bt3L69GmGDRuGwWAAwGg0Mnz4cOLj4/ntt98A+Pnnn2nUqJEj/AEYDAb69OlDWloahw8fBgouQc3LyyMqKqqydlNEhAyPQFZHjOfpaxexuvZwrCYLAO2Tv+f5HX9iwt4pNEnbrsdHiIiISLm5xRnA1NRU4uPji112aTabad68Obt27Spx3O7duwFo2bJlkfbC17t376Z9+/bMmDGDtLS0YuNTUlIc2wE4ePAgAI0bNwYKLh21WCxXulsiIpeUYQ5gRd0x/C9iFD1OLqX7qWX45GfSOnUTrVM3ccSvFf+tP4qdwV2wG9zm73kiIiLiQm4RABMSEgCoU6dOsWVhYWFs3bq1XOPCwsIAOHnypON1YVuh7OxsVqxYQVBQEI0aNQL+CIALFy5k9erVnDt3jgYNGvDUU08xYMCAK9y7ku3Zs8ep67tSkZGR2O12MjIzK31bdjvajpO3ZcvPB5xXR0363lWF7RQev8QcM5+EjuSLwEH0SF5NrzMrCcxLJSp9F+P3P0e8VwRfh92DPa/9Vdsfm82G1WolNja20rflrqzWgnsxq8q/51I+On7uT8fQven4VR63+JNx4Uyf3t7exZZ5eXmRWcovOxkZGZjNZjw8PIq0F66n8AerJC+++CKnT59m7NixmEwFEx0UBsC4uDheeuklXn75ZYKCgpg8eTKff/55+XdMRKQcMs3+fFl7OE9fu4gPGzxOgmc9ABpkxzH2+Czi/tIU23ev45tX/IoGEREREXCTM4D2y9znYjSWnGMvN67wvsCLvfnmmyxbtoxOnToxduxYR3ufPn1o3bo1Dz30kGPsgAED6N+/P6+99hoDBw4sdZ3l1aJFC6esp6KsVisGgwHfq3Cpq8GAtuPkbRWeCXJWHTXpe1cVtlP68bPwi98wNoffTbuk7+l1YhENMw+QnxIPX/2N141e/FKrD9/XvYdTlsq5Z9loNOLj41Nl/q2qigr/aq3vkXvS8XN/OobuTcfv0rZs2XLFY90iABbeZ5ednV1sWXZ2Nn5+Jc9EZ7FYyMvLIy8vz3EfH0BWVhZAieNmzpzJ3LlzadmyJe+++67j7B/geGzEhTw9PRk0aBDvvPMOsbGxmiBGRK4am8HM1lo92Rp6Oy3O/sIUUwzWXd/gacuma8JndE34jD2BN/Jd3XvZE9RJ9wmKiIiIe1wCWq9ewWVOhff0XSghIYHatWtfclxiYmKxMUCRcXa7nWnTpjF37lxat27NggUL8Pf3L1N9wcHBQMFjJ0RErjqDgT1Bnag3KQbTlF/ZWHsQOcaCh8K3OPsLj+ybwtTfhnPLqU/xys9wcbEiIiLiSm4RAAMDA2nQoAF79+4t0p6Xl8f+/fuLzfJZqPCU8cU3jxa+btWqlaPt9ddfZ/HixbRr144FCxYQGBhYbFtDhgzhb3/7W7HtxMbGYjAYiIiIKP/OiYg4kaHutSxt/AxTr1/FqoYTSfEs+ENXnaxj3Bv7Ov/cMohhh2fSIGO/iysVERERV3CLAAjQu3dv1q9fz/Hjxx1tK1euJDMzs8RLMwE6dOhAaGgoS5YscbTZbDaWLFlCw4YNadOmDQDr16/n3//+Ny1btmTevHklnvkzm814e3vzxRdfcPr0aUf76dOnWbFiBT179ixxkhoREVfINAfwbYOR/K3dMuY1ncYhv4J/77xtVrolrOIvO8YweedDdEr4Eo/8LBdXKyIiIleLW9wDCDBu3DhWrVrF6NGjeeCBB0hOTmbevHn06NGDTp06AbBt2zbi4uLo1asXFosFs9nMpEmTmDp1Ko888gg9evTgm2++YfPmzbz11luOyWNef/11ALp3787atWuLbbtbt26EhITw3HPPcf/99zN8+HBGjhxJdnY2ixcvxmg08tRTT129b4aISBnZjGa2hd7OttDbCc/YT9fTq7jhzH/xslmJSt9NVPpu7j76Dj+H9eGH2oMqbdIYERERqRrcJgDWqlWLhQsXMn36dGbNmoW/vz/Dhg1j0qRJjj4ff/wxK1euZO3atY6JY+655x5sNhvR0dFs3LiRyMhI3njjDfr06QNAWlqa49LS9957r8Rtf/zxx4SEhNC2bVuio6N55513eOONN/Dw8OCGG27g6aefdjwcXkSkqjru24yljZ9hVcSf6Zj0X7qeXkV45kEs+efocWoZPU4t45BfG36q3Y9tIbeTZfYtdV11/b2uYuUiIiLiLG4TAAGaNm3K/PnzS10+Y8YMZsyYUax92LBhDBs2rMQxAQEB7Nu3r8w1dOrUyXHGUUTEHWWZfdlYZzAba99FZPpuuiZ8Roekb/G0ZdMkfQdN0ndwT+ybbA/pzk9h/TgQcH2xGUQ9TUaycvOJSy39earOEBHkg7eH6fIdRUREpEzcKgCKiIgTGQwc9W/FUf9WrIh8lBvO/JebEr8iImMfnrZsbjyzhhvPrCHZsw4/h/Xl57C+nPEOdwyPS7UyYfnvlVrinKFtaRZW8qN+REREpPwUAEVEBKs5gA11h7Kh7lDqZx6iU+JX3HBmDQG5KYTknKZv/AL6xi/gkF8bttTqRX5aFFC2R+WIiIhI1aEAKCIiRZywNGFl5GN81nAirVI30SnxK9qk/oDJnu+4RPTolLcwNO1Bp7xO/BZ86yXvFxQREZGqQwFQRERKZDOa2RHSjR0h3fDLTaHDmW/pmPQNUem7wJaPfd+3jOJb7jPMZGfwzWwJ7cnO4JvJM2qCGBERkapKAVBERC4r3SOY9fXuYX29ewjNiuftqH2k/LgETu/Bw55D++TvaZ/8PVaThZ1BXdge2p3dgTeRa9LzUUVERKoSBUARESmXJO8GBPcfwrkuTzLtw5V0OPMNHZK+pVb2SXzyM7kh6RtuSPqGbKM3u4NuYntId3YF3azLREVERKoABUAREbliJyxNOBHRhNUNxxOVvovrk77luuQNhOScxsuW5TgzmGvwYF/gDWwP6c6O4K5keAS6unQREZEaSQFQREQqzmDgiH9rjvi35tPIJ4jI2Eu75O9pl/w9tbOO42HPpXXqj7RO/ZF8TBz2b8PO4JvZGdyF096RYDC4eg9ERERqBAVAERFxLoOBOL8WxPm14POGE6hvPUy7pIIwWN96GBP5ND23nabntjM47j0SvRo4wuBB/3bkGz1cvQciIiLVlgKgiIhUHoOh4DJRSxO+ajiW2tY42qRspHXKjzQ+9zsm8gnLjqfHqWX0OLUMq8nCnsBO7Aq+md2BN7m6ehERkWpHAVBERK6aBJ8I1voMZ2394Vjy0miR+jOtU36gZepP+Oafwyc/k+uTv+P65O8AyDvVhtPt+uLbujeWpl0wempWURERkYpQABQREZfINAewpVYvttTqhdGeR9S5nbRO+YE2KT9QN+toQacTO0g6sYOkr17F4OmDpfmt+LW5A7/WvfGs3wKD7h0UEREpFwVAERFxOZvBzKGAdhwKaMdnkX8mNCueFmd/4X7ffRgOrcdmTcOeYyVjx9dk7Pia04A5uAG+rXrh26IHvi264xEa4erdKKJRo0auLkFERKQYBUAREalykrwbsNF7MCOHtqVpiDfWQz+TvvO/ZOz8L9bDv4DdRl5KPGc3LuDsxgUAeIQ1xrdFdyzXdsf32u54hDYs1zazcvOJS7U6bR9sNhsAxvR8R1tEkA/eHianbUNERKS8FABFRKRKM5jMWJp1wdKsCwz5B/kZKWTsXkf6jjVk7v2OnNMHAchNPExq4mFSN0QD4FG7Cb7Xng+ELbrjERJ+ye3EpVqZsPx3p9WdkZkJgK/F4mhbNeYGBUAREXEpBUAREXErJt9gAm64m4Ab7gYgN+kYGXvXk7n3ezL2fEdu4uGC9oRDpCYcInXDPAA8QiPwadoFyzU349OsC97hbTCYru5/g54mo9PPNJZGZxtFRKQkCoAiIuLWPEIbEtRlJEFdRgKQmxRXEAj3fEfG3u/JTTziaM9NiiPtp48AMHr74dO4U0EobHoz9sDWV6VeZ59pLM2coW1pFuZX6dsRERH3ogAoIiLVikdoBEFdRhHUZRQAOWeOkrnvf1gP/kjmgR/IPr4D7HZsWelk7F5Lxu61BQMNBp7zaUKsXyuO+rXgqG8LTlkaYTPov0oREak+9L+aiIhUa561IvGsFek4Q5hvTcN68CcyD/6I9cAPWA/9hC0rHex2wjMPEp55kK4JnwGQbfTmuG8zjvpey1G/lhz1a8EZrwagx0+IiIibUgAUEZEaxeQTgF+b3vi16Q2A3ZZP9rEdxG5bxy8bviYyfTdh2fEAeNmyaHLud5qc++OSzQyTP3F+1xLn24I4v+YctzQlyau+QqGIiLgFBUAREanRDEYT3pHtMFquYcHJmwCw5KURkb6HyPQ9RGYUfA7MTQLAN/8cLc7+SouzvzrWYTX5ctzSlOO+TR2fD9nrkG/0cMk+iYiIlEYBUERE5CKZ5gD2BnVib1AnR1tgTmJBIEzfQ2TGbiLS92HJPweAT34GTc9tp+m57Y7+eQYzJ7wiOOF/LcctTYm3XEP+uSaA71XeGxERkT8oAIqIiJTBWc8wfg8J4/eQWwoa7HZCsk8RnnmA8IwDhGfuJzzjACE5pwEw2/OIyDpMRNZhxzqOTnoM/GvzmKEhJy1RnPRpfP5zFFazvyt2S0REahgFQBERkSthMJDsXY9k73p/hEIKLh9tkHGA2qm7icg6RGT2EepZj2Cy5xd0OJdAcxJonralyOpSPMM45VMQBk9YGnPSJ4oEnwgFQxERcSoFQBERESfKNAdwILAD2z1aAOBrsWC2ZVPHepTXO5k4c3g7v2/7mXqZR6iVfcIxLjgnkeCcRFqc/aXI+tI8gknwjuC0TwQJ3hEkeDfktE8EZ7waYDPqv3ERESkf/c8hIiJSyfKMXsT7NsP/pk6kXDuY9zMLZhX1zM+krvUo9TIPU896hHqZBWcLCy8jBQjITSEgN4Vrzv1WZJ35BhNnvOqT4BPB6QsC4hnvBqR5hF7V/RMREfehACgiIlVWXX8vV5dQqXJMFuL8WhDn16JIu3deOnWtsdTJiqO29Ri1s+KoY40jLOs4HvYcAEz2fOpkHaNO1jHa8EPR9Ro8yTsSRVy9a/Cs3QSP2o3xrN0Ez7DGeIRFYfT0uWr76K4aNWrk6hJERCqFAqCIiFRZniYjWbn5xKVaK3U719SqWjNzZpn9iPVvTax/6yLtBns+IdmnqZ11jNrWuPMBseBzcE6Co5+nPQcS9pGesK/E9ZuD6hcJhh61GuERGoFHaCQewQ0wmPX4CoPZk9jkDIzp+ZW2jYggH7w9TJW2fhGRkigAiohIlRaXamXC8t8v37ECvhrX6fKdqgC7wUSSd32SvOuzJ6hozZ75VsKyjhOafYJaWSe4u0EWlvRj5CYcIudMLOTnOfrmpZ4gL/UE7P9f8Y0YjJiD6+MREoFHrcg/gmHoH69NPgGVvKeuF5ucwZ8W/YKvxVJp25gztC3Nwvwqbf0iIiVRABQREakGckw+xPs2Jd63KQD33t2WyPPhwp6fR27ycXITD5OTcIichMMFwfD8a1tm6h8rstvISz5OXvJxrAd/LHFbRktQQSAMCccc1ACP4AaYz394BNfHHNwAk18oBoOhsndbRETKSQFQRESkmjOYzHiGNcIzrBG+LW8rtjzfmkZuUhy5Z44WfE46+sfr5DjyUuLBbnf0t2Wmkp2ZSvax0s/MGjy8MAcVhEGPws8XBsWg+pgD62D01hkwEZGrSQFQRESkGirPBDomnwBM4a3xDm9d4nJ7Xi65KceLhcS8lHhyU+LJS4knPz2p6JjcbHITj5CbeIRL3cFp8PLFHFAHc2AdzIF1MQfUwRRY53xb3YL288sVFkVEKk4BUEREpBpy/gQ6YRAaBqEdirReU8uXnDwbRxNTIO0UpJ3AfvYknD2BPe0knD2J/eyJgmVnT0BeVpHx9uwMchMPk5t4+LIVFAmLAXUw+Ydh8q+F2b8WJr9aBV+f/2zyr4XR21+XoYqIXEQBUEREpJq6WhPoxKVamfjZ/vMtfkDT8x+A9/mPOoDdjiX/HEE5iQTmnME/Nxn/3GQCclPwz00iIDcZ/9wU/HOT8ctNxYi9yLbKExYBMHmUGg5NfueDo28IRt9gTL7BmCwFnw0m/XokItWX/oUTERGRq8NgINMcQKY5gBOWJpfsarTn4Zt7loDcZAJyk3msnS+17GfJO3ua/LOnyEs7TX56EnnnzpB/LhF7blbxleTnkpd6krzUk+Uq0+jth807mH9keZDlGUimyZ9McwBWsz+ZZv/zr//4+sJ2m1G/Wl2NR7foERoiV07/SomIiEiVYzOYOecZyjnPUOIBY8e21LrEIxNs2Znkp585HwjP/PF1+vnX586Ql150Gfm5Ja8rKx2y0okAKCFXXkqOwZMssy9ZpoIPq+mPr4u0mX2xbd3LuTq1MXoHYLIEYvQJwOgTgMk7wK2fxXg1zjzrERoiV86tAmBsbCwzZsxg8+bNeHh40LdvXyZPnoyv76Uf4Lt69Wref/99jh07RsOGDRk/fjwDBw4s0icnJ4f33nuPzz77jJSUFNq0acOzzz5L69ZFb4hPTExkxowZ/PDDD+Tn53PLLbfw/PPPExoa6vT9FRERkbIxelkwekXgERpRpv52ux2bNY38jGTyM1LIz0jBlpni+Doh8RTf/bafAKxY8s9hyTv/kX8On7x0jNhKXK+nPQfP3BwCclMuW4PtCBwrZZnB0+d8GPTH4OWL0csPo7dfwWcv30t+bXD0vXCcLwYPb90TKSLuEwCTkpIYPXo0ZrOZiRMnkpaWRnR0NHFxccydO7fUcatXr2bKlCn06NGDESNGsG7dOqZMmYLJZKJfv36Ofi+++CLLly9nxIgRREVFsXjxYkaPHs3KlSuJjIwEICsri7Fjx3L69GnGjBmDwWBg7ty5HDx4kGXLluHp6Vnp3wcREZGaqDyzmpaFwWDAZAnEZAmEsKhiy5MSzvFh0s8lPgjeYLfhlZ/pCIQF4TAN7/wMvPMz8Dn/2Ts/A++8i17nZ+KTn45XfmaxexwvZM+xkp9jJf/saSfutLFIMDR4WTB6+Dg+Gz0tBcGz1M9l6WPBbi99v0TE9dwmAEZHR5OSkkJMTAzh4eEAhIeHM3XqVDZt2kTnzp2LjcnNzWXmzJl07dqV2bNnYzAYGDZsGKNGjeK1116jT58+GI1GDh48yCeffMJTTz3F+PHjAejbty99+vThX//6FzNnzgRgxYoV7Nu3j48++ojrr78egDZt2jBmzBg+++wz7rnnnqv03RAREalZnD+raemuqeULlH6mzG4wkmX2I8vsRzL1rmgbBruNT4e3xNdmxWY9S741DZs1DVtWGvmZZwvOTlrPYs/OwJaVji07/fznjAu+Pv86Kx17TublN2q3FWzDmnZFNZfH6wZPck3e5Bi9yDN4kGf0JM/gSa7RkzyjB7kGL/KMHn8sM55fZvA4/7mgX5Fx5/vmGj2xHUwl82wwBrMXRg9vDGYvDB5eBWc5zV4YzJ7Y7TYMBmOF9+Vq/NwVzqZ7NX6+df+kuE0AjImJoUuXLo7wBzB48GCmT59OTExMiQFw69atnD59mqlTpzoueTAajQwfPpynnnqK3377jfbt2xMTE4PBYODee+91jA0JCaFPnz6sXr2anJwcPD09iYmJoVmzZo7wB3DzzTcTFRXF119/rQAoIiJSia7GvWVQMLNpZbMbjHj7BpJPIHH5geAJBJZ/PQbABNht+ZCTef4jHbIzICcDe04GdT3zOHUmiY9+PoCXzYpXfiZe+VY8bVl42LLxsOU4vv7jc3ax1+Xhac/BMy+HS9+kc+VseyG2DP3sBhN7PDwxmDwwmD0xmDwxmD0KPp9vw3zB8gu/NhX0S8szsCE2jTyjB/kG8/kPD/KMf3ydbzCff31hHzM2gwmbwUS+47P5j9eYHMs/uK8DJ9LzeDbmQJH+NoOZ/PP9cNLlu7p/UtwiAKamphIfH8/gwYOLtJvNZpo3b86uXbtKHLd7924AWrZsWaS98PXu3btp3749u3bton79+gQHBxfp16pVKz7++GOOHj1K06ZN2b17N7169Sq2nVatWvHDDz9c8f6JiIhIzVS5odYX8OWrcZ0wplr539EKbMdux8OeUxAG84uGxQsD41+6NSDpbBrLNh90tJttOZjtuXjYchxfm205mG25eNizCz7bcjDbc0rua8+rQN352HOs2KnYmbVuFRp9ecd+K/g8/RJ9bBjPB0PzBQGxaJi8OGgWDZMm8jFj/k8IcWYzBqMJjKaCs6RG0x+vjSYwFL42Ol4X72Ms+rq0dsMfy0sdU0IddfPy8AxvU8nf+ZrJLQJgQkICAHXq1Cm2LCwsjK1bt5ZrXFhYGAAnT5509Ktdu3aJ6y7sV79+fdLT00utISUlhezsbLy8nHuPgoiIiIjLGQzkGrzINXqRaQ4otZv/zZ1ISbXyXbzzQq3BbjsfGv8Ii//sHUWkvwl7bja2vGzsuVnYCz/nZmPPz+XE8aOQn0udWqHY83Ow5+Vgz88t+jkvBy742p6fW6yvNSub48lpmG25mOx5mOx5mO3nv7blYrLn42HPcdr+lsaIDaPdBvaSZ68tq6wdTiroagioh+n5nQVnakuhy2fLz2B3gzt1t23bxn333cfMmTO58847iyybMmUKa9euZdu2bcXG/fWvf+XTTz8tdoYwLy+PVq1aMXLkSP7v//6PO+64g/r16zN//vwi/X788UfGjBnD22+/Tfv27enWrRtPPvkkEydOLNLvjTfeYM6cOfz000/FziKW15YtWyo0XkREREREaoYOHTqUe0zF74y9Ci6XUY3GknfjcuPKOhWy0Wgs04xWpdUhIiIiIiJSFbjFJaCW81MwZ2cXvwE5OzsbP7+Sb2S1WCzk5eWRl5eH2fzHrmZlFTzVtXCcxWJxtF3own6FzxosqV9hXaXVUR5XkuJFRERERETKwi1OWdWrVzDFcuE9fRcq7f69C8clJiYWGwM4xtWtW7dYn4v7+fn54e/vX2q/0NBQTCb3vyZYRERERESqL7cIgIGBgTRo0IC9e/cWac/Ly2P//v3FZvks1KJFCwD27NlTpL3wdatWrYCCWUHj4+NJSyv6XJzdu3djsViIiopyrO/iGgr7lVaDiIiIiIhIVeEWARCgd+/erF+/nuPHjzvaVq5cSWZmJv369StxTIcOHQgNDWXJkiWONpvNxpIlS2jYsCFt2hRMLdurVy9sNhtLly519EtOTubrr7/mjjvucNzb17t3b3bt2sX27dsd/X788UeOHDlSag0iIiIiIiJVhVvMAgpw5swZBgwYgMVi4YEHHiA5OZl58+bRpUsX5syZAxTMFhoXF0evXr0c9w0uW7aMqVOncvvtt9OjRw+++eYb1q9fz1tvvUWfPn0c63/66af58ssvGT16NBERESxatIjExESWL19OZGQkUHCv35133snZs2cZN24cNpuNDz74gIYNG7J06VI8PUufolZERERERMTV3CYAAhw4cIDp06ezdetW/P396dOnD5MmTXJM0PLcc8+xcuVK1q5dS3h4uGPcxx9/THR0NCdPniQyMpKJEycWO2OXnZ3NG2+8weeff47VaqVNmzY8++yzjstEC508eZLp06ezceNGvLy86NatG88++yy1atWq/G+AiIiIiIhIBbhVABQREREREZEr5zb3AIqIiIiIiEjFKACKiIiIiIjUEAqAIiIiIiIiNYQCoIiIiIiISA2hACgiIiIiIlJDKACKiIiIiIjUEAqAIiIiIiIiNYQCoIiIiIiISA2hACgiIiIiIlJDKABKiWJjY5kwYQIdO3akc+fOTJs2jYyMDFeXJeUwZMgQmjdvXuzjjTfecHVpcgkPPPAAf/3rX4u179ixg1GjRtG+fXtuueUW3nrrLfLy8lxQoVxKacevU6dOJb4fly1b5oIq5ULffvst99xzD23btqVjx45MnDiRw4cPF+mzceNGhg4dSrt27ejZsyf/+c9/XFStXOxyxy89Pb3E917z5s358ccfXVi5FNqwYQP33HMP7du357bbbuNf//oXubm5RfroPehcZlcXIFVPUlISo0ePxmw2M3HiRNLS0oiOjiYuLo65c+e6ujwpA5vNxuHDh+nXrx/du3cvsqx58+auKUou65133mHTpk1EREQUaT906BB/+tOfCA8PZ9KkScTFxTFnzhySk5P5xz/+4aJq5WKlHb/ExERSU1MZOXIkbdu2LbKsffv2V7NEucj69ev585//TNu2bZkyZQrp6el8+OGH3H///axcuZL69evzyy+/MH78eNq1a8fTTz/N9u3bmT59OtnZ2Tz88MOu3oUarSzH7+DBgwA89thjNGzYsMj4pk2buqJsucAPP/zAww8/zPXXX8+UKVM4fPgw7733HseOHeOVV14B0HuwEigASjHR0dGkpKQQExNDeHg4AOHh4UydOpVNmzbRuXNnF1colxMfH4/VaqVXr17069fP1eXIZeTk5PDqq6+ycOHCEpe/8847eHt7s2jRIgICAgDw9fXl3//+N2PGjKFRo0ZXsVq52OWOX+EvoIMGDSoWAMW1Xn75ZZo1a8ZHH32E2VzwK1GvXr246667mDt3Ln/961+ZOXMmjRs3Zv78+Xh6ejJixAjsdjuzZ8/mvvvuc7wn5eory/ErfP/df//9hIaGurJcKcHMmTOJjIxkwYIFeHp6AuDj48PcuXN59NFHadiwod6DlUCXgEoxMTExdOnSxRH+AAYPHozFYiEmJsaFlUlZFf6H17hxYxdXIpdz9uxZBg4cyMKFCxk3blyx5Tk5OXz77bf069evyH9yI0aMwGazsWbNmqtZrlzkcscPCs7gAkRFRV3N0uQyEhMTOXLkCP3793eEByg4K9S0aVO2b9/O8ePH+f333xkyZIjjl1OAkSNHkpmZyYYNG1xRulC24wcF77/AwECFvyooKyuL0NBQ7r333iLvr44dO2K329m3b5/eg5VEAVCKSE1NJT4+nlatWhVpN5vNNG/enF27drmoMimPAwcOYDQaadSoEXa7nczMTFeXJKU4d+4cBoOBuXPn8vTTTxdbfuDAAXJzc2nZsmWR9tq1axMWFqb3pItd7vhBwTEMCwvD39+f/Px8srKyrnKVUpLg4GC+/vpr7rnnnmLLUlNTMZlM7N69G6DY+6/wtd5/rlOW4wcF77/CP77k5uaSk5NzVeuU0nl7ezNv3jzGjh1bpH3v3r0A1KtXT+/BSqIAKEUkJCQAUKdOnWLLwsLCOHXq1NUuSa7AoUOH8Pf3529/+xvt27enffv2DBgwgB9++MHVpclF6taty1dffUW3bt1KXH6p92Tt2rX1nnSxyx0/KHg/WiwWHnnkEdq1a8d1113HsGHD9IuLi5nNZqKiooqdGfruu+84efIk7du3L/X95+npSVBQkN5/LlSW4wcF77/8/HxGjx7teP+NHTuWuLg4V5QtpbDb7Rw7doxFixbx3nvv0bVrV1q1aqX3YCVRAJQiCmf69Pb2LrbMy8tLZ5LcxMGDBzl79iy5ubm89tprTJs2jZycHB5++GF++eUXV5cnFzCbzRiNpf9TfLn3pNVqrbTa5PIud/yg4P0YFxdHnTp1ePPNN3n++ec5duwYI0eOLDbbpLhWYmIif//73/H29mbUqFGO95+Pj0+xvnr/VT0lHb+TJ0+yd+9e2rdvz9tvv80TTzzB1q1bGTFiBMnJya4uWc47evQoPXv25MUXX8TX15dnn30WQO/BSqJJYKQIu91+yeWX+0VHqoZ77rmHu+++m+HDhzvaevXqxR133MHrr7/O0qVLXVidlMfl3pMGg+EqVSJXIj8/n3HjxlGvXj369+/vaO/atSuDBg3i3XffZdasWS6sUAqlpqYybtw4Tp06xUsvvUTDhg31/nMjJR2/c+fOMWnSJFq2bOk4S3/77bfTtm1bxowZw4IFC3jqqadcXLkAWCwW3nrrLc6dO8fcuXMZNmwY8+fP13uwkigAShEWiwWA7OzsYsuys7Px8/O72iXJFbjvvvuKtYWEhNCzZ09WrVpFdnY2Xl5eLqhMykvvSfdmMplKnBymSZMmtG/fnp9//tkFVcnFEhMTefDBB9m/fz+PPfaY476ywvdfSfdt6v1XdZR2/Pz9/Rk/fnyx/jfffDMNGjTQFTFVSO3atenTpw8APXr0oG/fvrz55pvcdtttgN6DzqbTOVJEvXr1gD/uO7pQQkICtWvXvtoliRMFBwdjs9n0AHE3ovdk9RUSElLsYcdy9Z06dYqRI0eyf/9+Hn/8cR599FHHssL3X2JiYpExOTk5pKam6v1XBVzq+F1KSEiIJoSpomrVqkXHjh3Zs2eP3oOVRAFQiggMDKRBgwaOGZgK5eXlsX///mKzMEnVk5iYSP/+/Zk9e3axZbGxsdSqVQtfX18XVCZXokmTJnh5eRV7TyYkJJCYmKj3ZBW3e/du+vTpw6pVq4oti42NJTIy8uoXJQ5paWk8+OCDxMbGMnnyZP785z8XWd6iRQsA9uzZU6S9cGbCi2fMlqvrcsfv+++/p3fv3mzatKlIe35+PseOHdP7z8UOHTrEbbfdxvLly4sty8zMxNvbW+/BSqIAKMX07t2b9evXc/z4cUfbypUryczM1EPF3UBYWBjp6eksW7asyKQ9e/bs4fvvv2fAgAEurE7Ky8vLi1tvvZUvvviCtLQ0R/vixYsxGo307dvXhdXJ5TRq1IgTJ06wZMkSbDabo33dunXs3btX70cX+9vf/sahQ4d44oknePjhh4stDw8Pp1WrVixbtqzI2dpFixbh6+vLLbfccjXLlYtc7vhFRUURFxfHRx99VKR9yZIl/9/eHbukFoZxHP81uFRSQ4dCSGgS+gdaSioJcnEIIoxjGThERWQFBTY15NDUFkgQHKOghkQQkf6EQ1sGRVFNNRTRLvdO90Jc6zbcOl3e72c8Z3ng5R2+4HPU8/Mz989jwWBQLy8v2t/fV61W+/387OxMrusqHA5zBz8JO4D4QyqV0vHxsSYmJpRMJvX09KSdnR0NDAyop6fH6/HwAWtra5qbm1M8Htfo6KgeHx/lOI7a29vr7kPge/u102LbtuLxuK6urrS3t6fx8XF1dnZ6PR7e0djYqMXFRWWzWU1OTioajeru7k75fF7d3d1193XxNc7Pz1UqlWRZlgKBgAqFwqv3fr9fg4ODWlpaUiqV0tTUlGKxmFzXVbFY1MrKCvtHHvro+dm2LcdxNDs7q97eXlWrVR0eHiocDisSiXg0PSTJ5/Mpk8lodXVVyWRS0WhUDw8PchxHlmVpfn5ekriDn6Dhx98+rwMjXV5eamNjQ6enp/L7/RoeHlY6neang/+RSqWi7e1tXVxcqKmpSX19fVpeXlZHR4fXo+EdoVBIY2NjWl9ff/XcdV1tbm6qWq2qra1NIyMjmp6els/n82hS1PPW+R0cHMhxHN3e3qq1tVVDQ0NaWFhQS0uLR5Nid3dX2Wz2zfddXV0ql8uSpJOTE21tbenm5kaBQEC2bSuRSHzVqKjjo+dXq9WUy+V0dHSk+/t7WZalWCymmZkZPob2TRSLReVyOV1fX6u5uVn9/f1Kp9Ov/vuPO/hvEYAAAAAAYAh2AAEAAADAEAQgAAAAABiCAAQAAAAAQxCAAAAAAGAIAhAAAAAADEEAAgAAAIAhCEAAAAAAMAQBCAAAAACGIAABAAAAwBAEIAAAAAAYggAEAAAAAEMQgAAAAABgCAIQAAAAAAxBAAIAAACAIQhAAAAAADAEAQgAAAAAhiAAAQAAAMAQPwFo4FsGuaeG4AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 249,
       "width": 448
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot a histogram of data in `esample`\n",
    "sns.histplot(esample, stat=\"density\")\n",
    "\n",
    "# plot the pdf of the model\n",
    "from scipy.stats import expon\n",
    "lam = 0.2\n",
    "rvE = expon(0,1/lam)\n",
    "xs = np.linspace(0,30,1000)\n",
    "sns.lineplot(x=xs, y=rvE.pdf(xs), color=\"r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4a998da-292c-4f51-81fa-51efd09ced3d",
   "metadata": {},
   "source": [
    "We'll develop various way to analyze this \"goodness of fit\" between the sample `esample` data we generated\n",
    "and the theoretical model $f_E$ in the remainder of this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90b2cf50-340d-4dfd-b4bf-d884068f1bc0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e5049831-4ade-4c2c-959c-ba0c93a51379",
   "metadata": {},
   "source": [
    "## Empirical distributions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52923c66-0877-40ee-a017-520a3d704d40",
   "metadata": {},
   "source": [
    "Let's write a function that compute the value empirical cumulative distribution (eCDF) \n",
    "of the sample `data`. The function takes two inputs: `data` the sample of observations,\n",
    "and `b`, the value where we want to evaluate the function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4597ac74-450c-448c-b7e4-5d46d46c0a3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ecdf(data, b):\n",
    "    sdata = np.sort(data)\n",
    "    count = sum(sdata <= b)    # num. of obs. <= b\n",
    "    return count / len(data)   # proportion of total"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c708957-46b4-4b37-bfab-40a00d2ffd63",
   "metadata": {},
   "source": [
    "Note the sorting step is not strictly necessary,\n",
    "but it guarantees the `sdata` is a NymPy `array` object which allows the comparison to work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d6152e0b-eee2-481e-bfe4-3517033367f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.48"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecdf(vsample, 110)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "52064677-b597-4c4f-a1e6-0591e84fd54e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.606"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecdf(esample, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b512e12c-d039-444b-ab7d-746da1988836",
   "metadata": {},
   "source": [
    "### Visualizing the empirical cumulative distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5dca3802-702f-41ba-8d75-e1e6ac3d11e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Proportion'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 252,
       "width": 438
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.ecdfplot(vsample, label=\"ecdf(vsample)\")\n",
    "\n",
    "from scipy.stats import uniform\n",
    "rvV = uniform(100,20)\n",
    "bs = np.linspace(80,140)\n",
    "sns.lineplot(x=bs, y=rvV.cdf(bs), label=\"$F_V$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f784cd3c-f573-4d4d-9714-48f83375f5f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # ALT. manually plot ecdf using lineplot\n",
    "# bs = np.linspace(80,140,1000)\n",
    "# empFvs = [ecdf(vsample,b) for b in bs]\n",
    "# sns.lineplot(x=bs, y=empFvs, drawstyle='steps-post')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dc4368e8-a84b-4c13-ae62-270bc10575ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Proportion'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 252,
       "width": 438
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.ecdfplot(esample, label=\"eCDF(esample)\")\n",
    "\n",
    "bs = np.linspace(-1,30)\n",
    "sns.lineplot(x=bs, y=rvE.cdf(bs), label=\"$F_E$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96b63811-bb22-4723-8fce-fb396f506f4c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a398a0e5-1c5e-4ab7-b6d5-320b8db25773",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "316775cb-4c2a-47af-be0a-0b9a41ccd3be",
   "metadata": {},
   "source": [
    "## Measuring data-model fit\n",
    "\n",
    "Want to measure if `vsample` comes from $\\mathcal{U}(100,120)$.\n",
    "Here are the first five values we simulated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ca1c6769-43a4-4ae5-a088-41758daee86b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[103.6386436977451, 117.34140363667541, 113.35634072970831]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsample[0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5f2c821-bca4-4db9-9853-be7bc6880b12",
   "metadata": {},
   "source": [
    "We also want to check if the data we generated `esample` comes from $\\textrm{Expon}(\\lambda=0.2)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a1e3a6cf-8a0c-4ab5-8fe7-eedd7aab7491",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.5024273707608603, 10.625297726488984, 2.731193337322976]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esample[0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd113da9-ef42-43ab-83d5-781a05f50337",
   "metadata": {},
   "source": [
    "Let's also generate an additional sample `nsample`\n",
    "from the normal distribution $\\mathcal{N}(1000,100)$\n",
    "so we'll be able to make a variety of comparisons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "75555d92-3e99-4bea-a068-fffe9e054833",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2013a63b-83e8-40b5-a49d-6f124c155b81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 968.82163265, 1072.90039236, 1021.78207881])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import norm\n",
    "rvN = norm(1000, 100)\n",
    "nsample = rvN.rvs(100)\n",
    "nsample[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1a4aa53-1a41-48b2-9f9a-f8b19765889a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c6e30729-5db1-49a8-8467-2a98c6038d4b",
   "metadata": {},
   "source": [
    "### Visual comparison between data and model distributions\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8336ff75-34ea-425f-8fce-fb452c46c3c3",
   "metadata": {},
   "source": [
    "#### Shifted uniform distribution\n",
    "\n",
    "Here is the code for comparison of `vsample` and the theoretical model `rvV` $= \\mathcal{U}(100,120)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "aba4546f-d041-4731-84c3-da38ab5964fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import uniform\n",
    "rvV = uniform(100,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e364dcc6-233a-4b69-a793-05719414e7de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.05, 1.05)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WZnvbtm259tprKyxTOit7RkZGhfMNVPU7A+Cqq65qUL81fH19yzxwEcfLT/yVtM9eBeBzj2v5j2fJddcpwJckx6+OLA7gNIl5Wloa4eHhmEwmpkyZQmZmJlFRUSQmJrJs2bJKy8XExDBz5kxCQkIYN24c27ZtY+bMmbi5udmW5Zg8eTIjR44sV3bhwoVkZmZqeYla0KNHDy666CI+++wz2w1zwIABtu5szz33HOPHj+ezzz5j+/btbNq0ifXr1zNr1iwmTpzIoUOHGDt2LFarlWuvvZYRI0bQrVs3/vjjD2bPnl3u9Uym8pf635/MV8Td3b3cttIbckV1lt6k586dW+EauxWVERER59PYy8ThZ26qoCu7p8NiqklX9tL718yZMytdiq5z5854eXnx888/V1pPfn4+EyZMYNiwYdx9993n9drx8fEYDIYy3dHPl8FgKJfowrl/Z0DD+q1hsVgwGjW1VH1htVg4vnISWIopdvcl0vcBALZN7lftz7A4P6f5Lx8VFcXp06eJjY0lODgYKOkOFBERwY4dO+jXr1+5MkVFRcybN48BAwawePFiDAYDYWFhjB8/nvnz5zNkyBCMRiP9+/cvV3bjxo0cP36cOXPm0LZt21p/fw1RaGgoq1at4sCBA+zfv58HHij5UkpLSyMhIYF+/foxZcoUpkyZQkpKCuHh4axcuZKJEyeybNkycnJy+Pzzz2nTpo2tznfeeceuMSYlJZXblpiYiLu7O61atSq3r3Sbv79/uaf8f1/TVUREnFtjLxO9gpsCf7XgNmrUyIERVV/p/atx48bl7l87duzAaDTi6+vLddddx9dff01ycnKZ+2+pL7/8kt27dzNgwIDzet3s7Gy+/fZbrrzyynItzufD39+/0knSKvudAQ3vt0ZGRgYXX3yxnSKWmjr99TvkHSoZ0jDXcywn3Up6OSgpb9ic5tFZbGws/fv3tyXlAMOHD8fb27vStTLj4uJISUkhLCzM9sTSaDQyduxYkpOT+eWXXyosl5OTw9y5c7nyyivLjPkR+xo2bBi5ubm88sorNGrUyDZ2LSYmhgkTJvC///3PdmxQUBBBQUG2p8CnT5/G19eXoKAg2zHZ2dls2LABALPZbJcYjx07xn/+8x/b3+np6XzyySdcc801FQ6h6N+/P+7u7ixfvrzMGLz//e9/TJkyhY8++sgucYmIiNhT9+7d8ff3Z9WqVeTn59u2Hz9+nKlTp/L2228DJZP0FRcX89RTT5GTk1OmjmPHjvHyyy/j5+fH2LFjz/maVquVOXPmkJubW+2Z9lu1akVOTg5ZWeX7/lb2OwPq32+Ns2eQt/dvjeLiYk6ePGkbVy+OZc44Qeq6pwD4n+lSPvIaCpTMEdEpQA04DZlTPJbJyMggOTmZ4cOHl9luMpno3Lkze/bsqbDc3r17AejatWuZ7aV/7927l549e5Yrt2rVKtLT03njjTfsEb5UomPHjnTq1In//Oc/hIaG4u3tDcCtt97KsmXLmDx5MuPGjcPf358ff/yRH374gRkzZgBw/fXX89VXXzF16lRuuukm0tPT+fjjj0lNTQUo92Ohutzd3XnyySdtcURHR1NcXMysWbMqPN7f359HHnmEBQsWcPfddxMaGkpmZiarV6+madOmTJkyxS5xiYiI2JOHhwdPP/00s2bNYtSoUQwfPhyr1coHH3xAcXGx7f7buXNnZs+ezXPPPcfQoUMZPnw4rVu35vDhw6xbtw6z2cybb75ZrvV7//79bNq0CShJFE+dOsWXX37JL7/8wpgxY2xjvy9Unz59eOutt/j111/L9YCs7HcG1L/fGo8//jjh4eH4+fnZ/bfGgQMHyMvL45prrrFLvFIzJ6KnY8k9g9Vg5AXfh7AY3Fg1pie3d2upFvMGzin+65d+AZ79xLJUYGCgbb3J8y0XGBgIlDwF/ruCggJWrlxJ3759yyyNUR90adGYnx677twH1kEc9jJs2DBeffVVbrnlFts2f39/Vq5cyWuvvcb7779PZmYm7du357nnnrM9gR8zZgwZGRl8/PHHfP/99wQGBtK3b18mTpzILbfcwo8//sg//vGPGscXHBzMgw8+yOuvv86ZM2e46qqrePPNN6scB/fggw/SokULVq1axbx58/D19eXqq6/mscce07AIERGpt2699VaaNGnCkiVLeP311/Hw8KB79+4sXLiwzNrlo0aNolOnTkRFRRETE0NqaipNmjQhJCSEyZMn29YlP9uWLVvYsmULUDLuukmTJlx22WXMmzeP2267rdoxX3XVVXh7e7Nr164KhyZW9DsD6t9vjWnTprFgwQIyMjLs/lsjLi4ONze3SifSk7qT/dsXZP5Q0qOhuN8k4g9cAkCXoOrPDyGuw2CtaMaMemb37t2MHj26wi/vmTNnsnXrVnbv3l2u3HPPPcf/+3//r1yLutlsplu3btx99908++yzZfZt2rSJJ554grfeesuu66aWrrN59tPavysoKMDX17fCMVvu7u62STtK/5Odz4QitcVisdiWN3FV999/P2lpaaxfvx6gTiZNSU5OJjs7G09Px00e5GjOPk6zNrRv357fM4u45/3KV4+ojvfu7sNFjU3s27dP57sO2esaL12qqVevXjWOqaEqvTdXdQ6PHDkClF2iqyL67qpbZ5/v5557jp9++qnSoY312fjx4zl58mSZZdrs7e6776Z58+a8/vrrVR5X1bUeHx8PQJcuXewfYANhKczj0DOXU3TyMKbmwWRN+y9XL/4ZgJ8eu842XwXofDuCvc75+dxXKuMUj2bO9eygsoTpXOUqSmzXr19Pq1atyqxFWR+cnQSXzsap2TVFRESkoZswYQJr167lt99+o3v37o4Op15JTk5m586dfPjhh44OpcE79cm/KDp5GICW414ny9N+PVDFNThFYl7aylxQUFBuX2krc2XlzGYzZrO5zNIRpZOa/L1cdnY2u3btYvTo0bWW9Fb1FKb0SeW5nrbrqXzdcHNzw2Aw2K6Fujjfbm5u+Pn5nbNlxpXpKXHFjNnF+FTR46ZadRqNGAwGGjVqpPNdh+z9VF6kobv44osZPnw4y5YtY9GiRY4Op15Zvnw5119/fYVzKkndKUjey6nNrwDg2/M2Gve6A5LPODYoqXecosm1dFmI0jHjZ0tNTa1wDcezy508ebJcGaBcuR07dlBUVFRm1k4RERERqd9mzZrFjz/+yP79+x0dSr2RkpLCv//973LDNqVulaxZPhmKizB4+tD4roXEJZ8hPiXb0aFJPeMULeZ+fn60adOGffv2ldluNptJSEiodNKQ0taI+Pj4MutAlrZWdOvWrczxu3fvxt3dXeP1BIDVq1cDf/VQEBERkfqpefPm7Nixw9FhXLDS3xq1ISgoiB9/tO/cJHLhMr5dSW7CNwA0ufV5Oi1JIC3XtedpkupxihZzgMGDB7N9+3aSkpJs2zZs2EBubi6hoaEVlunVq5dtiatSFouF6Oho2rZtW24c0v79++nQoQMeHh618yZERERERKRBMGeeJPWjkmXvPC/qwYkr7i2XlGv9cinlFC3mABMnTmTjxo2Eh4czYcIE0tPTWb58OSEhIfTt2xcoafFOTExk0KBBeHt7YzKZmD59OhEREUydOpWQkBC2bNnCzp07WbRoUblx5ImJiQ16bK+IiIiIiNhHykczKc5JB4OB1hPeIcPtr9Rr1ZiedAnypVOAlkqTEk5zFQQEBLB69WrmzJnDggULaNy4MWFhYUyfPt12zJo1a9iwYQNbt261TRg3atQoLBYLUVFRfPvtt7Rr146FCxcyZMiQcq+RkZFR6URyIiIiIiIi5yMn/ivOfLcKgGYDp9Dokj6QlGHb3yXIt8wSaSJOk5gDdOzYkRUrVlS6PzIyksjIyHLbw8LCCAsLO2f9P/30U43iExERERGRhs1SVFAy4Rtg8mtJi5FzHByROAOnGWMuIiIiIiJS36V9OpfCEwkABI1bhJu3H1n5Zs3ELlVyqhZzERERERGR+qrgRAKnYv4FgE/3ITTpM4qsfDMXz/lSs7FLldRiLiIiIiIiUkNWq5Xj703Bai7E4O5Fq/C3MBgMJJzKLpOUayZ2qYhazEVERERERGrozH8/IHfvNgACb38OjxYXA5CVb7Yds2pMT27v1lIzsUs5ajEXERERERGpgeLsdFI+fBwAzzbd8B86AyhJygcu2WE7rkuQlkeTiikxFxERERERqYGUtU9SnHUSgFYTlmIweQCQcKrshG/qwi6V0eMacbgtW7awZMkSjhw5Qk5ODosWLapwnXkRERGpXcePH+eGG26odP8HH3xA79696y4gESeQm/AtGduXAdD0HxPx7tQfoNxM7Nsm91NruVRKV4Y41M8//8zDDz9M//79efrpp/Hw8OCaa65xdFgiIiIN0p49ewAYM2YMPXv2LLf/8ssvr+uQROo1q7nQtma5W+NAgu6aC1DhTOxKyqUqujrEodasWYOXlxdvvPEG3t7ejg5HRESkQYuPjwdg9OjRXHbZZQ6ORqT+S4tdQEFyyQOtoDGv4ubbHEAzscsFU2IuDhUXF0f37t2VlIuIiNQDe/bswcvLi0svvdTRoYjUe4Wphzm5aTYAPl1vxO/acUD5LuyaiV3Oh64OcYh58+axbFnJWJyjR4/SuXNnAD755BPbv0VEROqz4rwsCk8kAFBQkF+y0dPLYfF4tOyEW6PGNaojPj6eSy65hMzMzDLb3d3dady4ZnWLuBKr1crxVQ9hLcrHYPKg5T1vYzAYKuzCrpnY5XzoCnESrnbzHzhwII0aNeKNN95g9OjRXHXVVQBcfPHF9gpRRESk1hTnZXFwZgeKs9McHYqNm68/l84/Uu37c3p6OidOnODEiRP069evzL7Q0FAWLlxojzBFXELmj+vI+e0zAAKGPYNny06AurBL9SkxdwKuePPv1asXv//+OwB33nknV1xxhT3DExERkQu0d+9eAKZMmUKfPn3K7AsODnZESCL1UnFOBikfPAqUNFb5D3sKUBd2qRldJeIw8fHxmEwmdV0XERGn49aoMZfOP1KuN5unE/dmK03MhwwZUuXEb7169eKtt94qt4rK6tWree+999i8eTMeHh7VjkOkvkv9f//EfOYEAK0mLMHo7qku7FJjulKcgCve/KEkMe/QoQOenp62bbrZi4iIs3Br1JhGHXqV/JGXB0CjRo0cGFHN7N27F3d393MOK+vYsSOHDh0qc68+c+YMb775Ji+99JLu0+LS8g79yOltiwHw6x+OT5cQQF3YpeaUmDsJV7v5W61W9u3bxw033FBmu272IiIijrF37146dOhwznttp06dOHDgQJltb731Fl26dGHQoEG1GaKIQ1mLzRxb+SBYrbj5NCdo9Hyy8s0knMpWF3apMV0t4hBJSUlkZWXRpUuXMtt1sxcREal72dnZJCYmcsstt5zz2M6dOxMbG2v7+8iRI6xZs4Z169bVZogiDpf+xSIKEn8BoMXoeeR5NCvXfR3UhV2qx+joAKRhKh3H9vfEvHPnzhw8eND2d+nN/plnnqnT+ERERBqS+Ph4rFbrec378veH6HPnzmXkyJF06tSpNkMUcaiitERS1z8HgHen62h63b3luq+DurBL9elRjjhEfHw8QLnJZTp16sTrr79u+1s3exERkdpX+sD8fBPzjIwMTp06xYEDB9i9ezeRkZG1HaKIQx1f/TDWwlxwc6fVhCUYDIYy+1eN6UmXIF86Bai1XKpHV404RHx8PEFBQTRv3rzMdt3sRURE6t4999zDPffcc17H+vn5ERQUxP79+5k7dy6PPPIITZs2rd0ARRwoc9dGsnd/AkBA6BN4tula7pguQb70Cm5ax5GJK1FiLg6xdOnSCrfrZi8iIlL/derUiQULFmC1Whk9erSjwxGpNcV5WZxYPQ0A9xaXEHDbPx0ckbgqjTGXekc3exERkfqtU6dO7Nmzh2eeeQY3NzdHhyNSa06ufw7z6WQAWoW/jdHDeVdFkvpNibnUO7rZi4iI1G9PPPEE+/fvp1+/fo4ORaTW5B2NI31LydxHTfqOxrf7YAdHJK5MibnUO7rZi4iIiIgjWS3FHF85CawWjN5+tBy70NEhiYtTYi4iIiIiInKW01vfJv/ITgBajIrE1LRlmf1Z+WbiU7IdEZq4KE3+JiIiIiIi8qei9GRSPy6Z5K3RJdfQ7IYHy+zPyjdz8Zwvy61hLlITajEXERERERH504nox7DkZ4HRjVYTlmIwlk2ZEk5ll0nK/b3d6RTgW9dhiotRi7mIiIhIJQwGA8XFxY4OQ6TWWSwWTboLZP38KVk/fQyA/5DH8broivLH5Jtt/141pie3d2tJYy+lVVIzTtVifvToUSZPnkzv3r3p168fs2fPJicn55zlYmJiGDZsGD169GDYsGHExMSUO8ZqtfLee+9x8803c8UVVzBs2DA2bNhQG2+jUgaDAYvFUqevKfVLcXExRqNTfSxFRFyap6cnhYWFFBWpy6q4rqKiIgoLC/H09HR0KA5lKcjhxOqHAHAPaEfgHc+XOyYr38zAJTtsf3cJ8lVSLnbhNBlAWloa4eHhJCQkMGXKFO666y7WrVvHo48+WmW5mJgYZs6cSXBwME899RStWrVi5syZbN68ucxx8+fPZ86cOfTs2ZOnn36aFi1a8NRTT7F+/frafFtl6ObfsBUXF2M2mzGZ9OUuIq6nOg/XrVYrK1euZNCgQVx++eXceOONLF++HKvVWkdRQ5MmTQA4fvy47s/ikoqKijh+/Djw1/XeUJ3cOJuiU78D0HL8mxg9fcodk3Cq7IRv6sIu9uI0GUBUVBSnT58mNjaW4OBgAIKDg4mIiGDHjh0VLq1VVFTEvHnzGDBgAIsXL8ZgMBAWFsb48eOZP38+Q4YMwWg0cvDgQaKioggPD+ef/yyZ6GH06NGMGjWKxYsXM2LEiDp5j02aNCEjI4Pjx4/TqlUr3N3d6+R1xfGsVisnT57EarU2+JuiiLie0ofrJpOJKVOmkJmZSVRUFImJiSxbtqzScitXriQyMpJ//OMf3Hvvvfzwww+88sorZGVl8dhjj9VJ7N7e3gQEBHDq1CkOHjyIh4dHhT2bSru7qytw3dD5tg+LxUJhYSEAAQEBeHt7Ozgix8n/4zfSPn8VgMa976TxlcNs+7LyzbaE/OyZ2LdN7qfWcrEbp7mSYmNj6d+/vy0pBxg+fDhz5swhNja2wsQ8Li6OlJQUIiIiMBgMABiNRsaOHcvjjz/OL7/8Qs+ePdm0aRNubm5MmzbNVtZgMPDYY4/xyy+/UFRUVCdJsm7+9VNdnG+z2YzZbMbHxwdfXz15FRHXUp2H6wCLFy+mZ8+eLF26FIPBwNixY5k8eTLLly/ngQcewMenfGuWvRkMBlvCkpmZSUFBQYUt9tnZJT/W/fz8aj0m0fm2Fzc3N5o2bUqTJk3w9va2/V5uaKwWC8dXPAjFZoxejWk5bpFtX1UzsCspF3tyiqspIyOD5ORkhg8fXma7yWSic+fO7Nmzp8Jye/fuBaBr165ltpf+vXfvXnr27ElcXByXX3657cs9NzeXRo0aMWDAAAYMGGDvt1Mp3fzrp7o43x4eHjRv3pymTZs22JuiiLiu6jxcT0tL48yZM/Tr16/M9+KAAQP46quvSExMpEuXLnUSv8FgwMfHp8oHAfHx8QB06NChTmJq6HS+xZ4ytr9L3qHvAQi88yXcm7ex7fv7DOylNBO72JtTJOapqakABAUFldsXGBhIXFzcBZULDAwEsI2n+f3337n66qvZvHkzCxcuJDExkSZNmnD//fczefJku70P+OtGUhOlE8Tl5+fXuC45t7o637m5ubZrtiHLy8sD7PNZcRXt27fHYrGQk5tr13otFgtWq5G8vDyd7zrU0K7x6j5c9/Pzo3Hjxhw9erTM9qSkJNuDbBGRmjKfSSFl7VMAeLXvRfObHrLty8o3l+m6vmpMT7oElSTjnQI06ZvYl1NcTaWTw3h5eZXb5+npSW4lP1ZzcnIwmUzluqGX1lP64ygzM5PffvuNr7/+mkmTJtGhQwc+/fRTFi5ciMViYerUqfZ8OyIiIg1GdR+um0wmnnzySf7v//6P1atXExISwq5du/jwww+5/fbbbQ/Z7cEeD0ka2gMXR9P5rluufL6tn8yC3AwwGMm/4Sn27U8AIKfQwuC1R8ko+GvFJK/ck3hnZQGQlFV7Mbny+a6v6sM5d4rE/Fyzr1a2vNS5ypV2jSsqKuKPP/7gjTfeYPDgwQDcfPPN3HfffbzzzjuEh4fbbdyvPbrdlV4wddWFr6HT+a5bOt8VM2YX42PnSXmMRiMGg4FGjRrpfNche13ju3btskc4ta66D9cBBg4cyJYtW3jppZd46aWXAOjZsyezZ8+unWBFpEGxHvkO9n5a8kevcRhadrPtO5pZWCYpb+pppH0Tj7oOURoQp0jMS2eILCgoKLevoKCg0qTZ29vbNqnW2UtQlXZJLi3n5eWFm5ubLSkvddttt/Hdd9/x22+/VToxjYiIiFSuug/Xc3JyGDt2LMnJyUyePJnu3buzd+9e28Rvy5Ytw8PDPj+S9dDc+eh81y1XPN+WwjwORd1KEWBq1oZLJr6FW6PGQEkX9l25J4AkoKQL++3dWtZZ13VXPN/1XX14aO4UiXmrVq0AKhx/m5qaSosWLaosd/LkSdu/z66ntFxQUJBtHPHZmjVrBnDOdVZFRESkYtV9uL5p0yaOHj3KSy+9xKhRowC46aabuOyyy3j44Yf5+OOPGTt2bO0FLiIu7VTMHIpSDwHQ8u7XyyTlf5+FvUuQxpNL7av4MXU94+fnR5s2bdi3b1+Z7WazmYSEhHKzrpcqfeLx97ECpX9369bN9v/Hjx8v150uOTkZgJYtW9b8TYiIiDRA1X24fuDAAQwGA7fcckuZ7YMGDcLb25uffvrJ/sGKSINQcCyeU5/OBcD3yltp3OuvySn/Pgu7Zl+XuuIUiTnA4MGD2b59O0lJSbZtGzZsIDc3l9DQ0ArL9OrVC39/f6Kjo23bLBYL0dHRtG3blu7duwMwdOhQCgsLef/9923HFRUVsWbNGlq3bm1L4EVEROTCVPfhuoeHB1artVyPNqvVavufiMiFslqtHF85GYqLMHh403L8G7Z5pyqahf3wMzeptVzqhNNcZRMnTmTjxo2Eh4czYcIE0tPTWb58OSEhIfTt2xeA3bt3k5iYaHuabjKZmD59OhEREUydOpWQkBC2bNnCzp07WbRokW1c20033URISAgLFy4kOTmZTp068e9//5v9+/fzxhtvaF1pERGRGhg8eDDR0dEkJSXZ1jI/18P1a6+9lpUrV7JmzRruv/9+2/aYmBjy8vLo06dPncQuIq7lzDcryd3/HwACh7+AR0A7QF3YxfGc5koLCAhg9erVzJkzhwULFtC4cWPCwsKYPn267Zg1a9awYcMGtm7dahvTNmrUKCwWC1FRUXz77be0a9eOhQsXMmTIkDL1v/766yxevJgNGzawYcMGLr30Ut5++20GDhxYp+9TRETE1VTn4fr1119PSEgI8+bN4/Dhw/To0YP9+/fz0Ucf0a1bN0aOHOngdyUizsacdYqUNbMA8Gx7Bf6DH7XtUxd2cTSnScwBOnbsyIoVKyrdHxkZSWRkZLntYWFhhIWFVVm3h4cHjz76KI8++miVx4mIiMiFqc7DdYPBYHtovmnTJjZt2kSzZs0YM2YMjz32mN1mZBeRhiPlo1kUZ6eBwUCrCUsxmNyBiruw1+Us7CLgZIm5iIiIOKfqPFzXQ3MRsZec+K858+1KAJqFTMb70msAdWGX+sNpJn8TkYajdevWjg5BREREXISlqIDj700GwOTXkhYj59j2qQu71Bd6FCRygfKLiknMyLN7vZcG+FBotti97ouaNsLL3c2uddY2Dw+PWjvPzng+REREpPrSNr9C4fH9AASNXYibT1Oy8s0knMpWF3apN3TViVygxIw8Jn/8q93r3Tyxb63UvWTkFXQKdL4nv7V1np31fIiIiMiFKzhxgFMx/wLAp/vNNOkbVmH3dVAXdnEsdWUXERERERGXY7VaOfHeFKxFBRjcvWgV/jYGg6Fc93VQF3ZxPD0SEhERERERl5O5I5qcvVsBCLj9WQqaXMRvSRnluq93CfKlU4Bay8WxdPWJiIiIiIhLKc45zYkPHwfAs3VXPEMeq7T7eq/gpg6IUKQsdWUXERERERGXkrL2KYozUwFode9SDmQUqvu61GtqMRcREREREZeRm/AdGV+/A0DT6+/Hu9MAsg6esu1X93Wpj3QlioiIiIiIS7Cai2xrlrs1DqBF2Fyy8s0MXLLDdoy6r0t9pK7sIiIiIiLiEtI+f5WCpP8BEDTmVUy+/iScyi5zjLqvS32kxFxERERERJxe4ckjnNz4AgDeXQfid+3dAGTlm23HbJvcT93XpV5SYi4iIiIiIk7NarVyYtVDWAvzMJg8bGuW/70bu5Jyqa+UmIuIiIiIiFPL+uljsn+NBcB/2NN4tuoMoG7s4jSUmIuIiIiIiNMqzj3DiQ8eBcCjZScCbnkKKOnCHp/yV2KubuxSn+nKFBERERERp5X68T8xZxwHoNWEJRg9vMjKN3PxnC/LrF2upFzqM7WYi4iIiIiIU8o79COnt70NgN+14/HpEgKUdGE/Oyn393ZXN3ap1/TYSEREREREnI612MzxlZPAasXo04ygMfOB8l3YV43pye3dWqrFXOo1XZ0iIiIiIuJ00re8QX7izwAEhc3D1KRFhV3YuwT5KimXek9d2UVERERExKkUpSWSuv5ZABp1GkDT6+4F1IVdnJceHYmIiIiIiFM58f4jWAtywGji9JBXSD+WCaAu7OK0dJWKiIiIiIjTyIrbRFbcJgBW+97J3A9PAd+UO05d2MWZ6EoVERERERGnUJyXxfHV0wCwNG/Pa8aRFR6nLuzibJSYi4iIiIhIvZWVbybhVEkXdffN/8SUngTAoetepOC/nkBJt/UuQX8l4p0C1FouzkVXq4iIiIiI1Etnz7J+WdEh1mQsASDW8zpm/dfPdlyXIF96BTd1UJQiNadZ2UVEREREpF4qnWXdaC3m+ey3ccNCpsGHuT73245Rt3VxBWoxFxERERGReikr3wzAXfmf0d18AACvW18gtu/ttmPUbV1cgVNdwUePHiUyMpKdO3fi7u7O0KFDmTFjBj4+PlWWi4mJYenSpfzxxx+0bduWSZMmceutt5Y5ZvXq1bz00kvlygYFBfGf//zHru9DRERERESqlpVvZuCSHQQWp/FYzioAGl3Sly7Dp2MwquOvuBanSczT0tIIDw/HZDIxZcoUMjMziYqKIjExkWXLllVaLiYmhpkzZxISEsK4cePYtm0bM2fOxM3NjdDQUNtxBw4coEWLFsycObNMeW9v71p7TyIiIiIiUrHSCd+ezFmGrzUPjG60mrBUSbm4JKdJzKOiojh9+jSxsbEEBwcDEBwcTEREBDt27KBfv37lyhQVFTFv3jwGDBjA4sWLMRgMhIWFMX78eObPn8+QIUMw/vnBPnToEJdddhm33357uXpERERERKTuXVewkyEF3wHgf/N0vC7q4eCIRGqH0zxuio2NpX///rakHGD48OF4e3sTGxtbYZm4uDhSUlIICwvDYDAAYDQaGTt2LMnJyfzyyy+2Yw8ePEiHDh1q902IiIiIiMj5Kczln9kls7BbmgYTOPz/HBuPSC1yihbzjIwMkpOTGT58eJntJpOJzp07s2fPngrL7d27F4CuXbuW2V769969e+nZsyenTp0iIyODiy++GIC8vDy8vLxsybw0bFarBfIyMGeeLPk7OxvfotN2f53irJNYs/PsXrc1+yRmzzy71lmbrLnpFGf5YM0prpXz7Gzno1RtXHfW7JMUW92wFuXbtV4RERF7sGyJJNiSCkDRsFcwelY9r5SIM3OKxDw1teQDGRQUVG5fYGAgcXFxF1QuMDAQgOPHjwMlreUAO3fuZOnSpRw7dowmTZowduxYHnnkEdzc3OzzRoD4+Pga15GXl2e3uqRq1uJCLMtHYEw/TMJZ2yNr4bV+31U7dRfvokzsziDxz/+vjfPsjOejVG1cG4mA1d2bvaOXYWhzpZ1fQSqi73ARkXNLO/QzHv99G4AvPa6hf5ehDo5IpHY5RWKek5MDgJeXV7l9np6e5ObmVlrOZDLh7u5eZntpPaU/jg4dOgTAb7/9xtSpU2ncuDGff/45S5YsIS0trcLZ2qWBSDuCMf2wo6MQqVWGolw4/C0oMRcRkXrAarFwbOUk3Ckmx9CIl30fJEHrlIuLc4rE3Gq1VrnfWMnMjOcqV9pVvWvXrkyePJkJEybQrFkzAIYMGYKbmxsff/wx9913n62be0116dKlxnWUtrLYoy6pWr5PIaVpeYu7IvEI6sSxzDyW7Pjd7q/17E2dOJlTYPe6J/drR+smjexaZ21KSkqiRYtATuVbauU8O9v5KFUb193kfu1g3UNYcjMICAykhb5T6oS9vsN37dplj3BEROqVrHwzhza/iUfijwC84T2ODx+6VeuUi8tziiu8dMmygoKCcvsKCgrw9a34CZq3tzdmsxmz2YzJ9Ndbzc8vGU9ZWq5nz5707NmzXPm77rqLmJgYfvrpJ7sl5uJkznq4433ZDXhf0pcTJ7P5df+vdn8pn6v6kpaRZ/e6jd2voEmg8zxlNvjE49O+PenZxbVynp3tfJSqjevO2P0KrBtnlPxxjgeZIiIitS0r30yvF9fxXnIEHsAe0yVEN7qFR5WUSwPgFLOyt2rVCvhrzPjZUlNTadGiRZXlTp48Wa4MUGm5Us2bNwdKll0TEREREZHak3Aqm4knl+JnzaEYIy/4PkQzHy86qRu7NABOkZj7+fnRpk0b9u3bV2a72WwmISGh3KzrpUq7Cf59gp3Sv7t16wZAREQEI0aMKFf+6NGjAFx00UU1il+cl5W/WhENaJZ+cUWl17VazEVExHGy8s0k/RTLsILtAKT1mMB7s+7l8DM3qRu7NAhOkZgDDB48mO3bt5OUlGTbtmHDBnJzcwkNDa2wTK9evfD39yc6Otq2zWKxEB0dTdu2benevTsAAQEB7Nmzh6+//tp2XFFREe+++y4tWrSgb9++tfOmREREREQauKx8M5f9azMeMSXDq1KMzWl82/P0Cm6qpFwaDKe50idOnMjGjRsJDw9nwoQJpKens3z5ckJCQmyJ8+7du0lMTGTQoEF4e3tjMpmYPn06ERERTJ06lZCQELZs2cLOnTtZtGiRbdK4++67j02bNjF9+nTCw8Px9/cnJiaG3377jQULFuDp6enIty6OdPa4W61rL66o9LrWGHMREXGQhFPZjDgVTbvikqWM32w+hZXBrR0clUjdcprEPCAggNWrVzNnzhwWLFhA48aNCQsLY/r06bZj1qxZw4YNG9i6dattwrhRo0ZhsViIiori22+/pV27dixcuJAhQ4bYyjVp0oTVq1czf/58oqOjKSgo4LLLLmPx4sWEhITU+XsVEREREXE1WflmEk5ll9t+OP5nJub+PwDOtL+JFU89r5ZyaXCc6orv2LEjK1asqHR/ZGQkkZGR5baHhYURFhZWZd3BwcG89tprNQ1RRETEaX333Xds3LiRU6dOUVxcXG6/wWDgvffec0BkIuLssvLNXDznS9Jy/zapstXKijP/xB0zuXjiOXIBTRq5OyZIEQdyqsRcpM6pK7u4OnVllz9t2LCBZ555Buuf14Kbm1u5Ywz6HhSRako4lV0+KQduL9jG1UX/A+C9pnczp2PFkzqLuDol5iIiIsKKFSto1aoVr732Gt26daswMRcRqY6sfDPxKX91YV81piddgnwhJw2v1yYAYAnqyr+ef0Nd2KXB0pUvUqWzWxHVUiSuSMulSYkjR44wY8YMrrjiCkeHIiIupKIu7F2CfOkV3JRjyx4nIzcdDAYufnAZ3j6NHBipiGM5zXJpIiIiUnuaNWtmW62kNhw9epTJkyfTu3dv+vXrx+zZs8nJyTlnuW+++YawsDB69OjBwIEDWbBgAQUFBbUWp4jY19+7sPt7u9MpwJecfdvJ+KZk7qhmN0zC+9J+jgpRpF5QYi5SFY0xF1f353Vt1RjzBm/IkCFs3LgRi8Vi97rT0tIIDw8nISGBKVOmcNddd7Fu3ToeffTRKst99dVXPPjgg7i5ufHUU08xYMAA3n33XZ5//nm7xygitW/VmJ4cfuYmfNyKOb5yMgBufkG0GPWygyMTcTx1ZRcRERFuvvlmtm7dSlhYGEOHDsXf37/CFvRbb731guuOiori9OnTxMbGEhwcDJSshhIREcGOHTvo1698S1lRUREvvPACl19+OStXrsTDwwMAHx8foqKieOyxx2jZsuUFxyIijtMlyJfGXiZOboqk8Pg+AFqOWYibT1PHBiZSDygxF6mKWszFxRnQrOxSYty4cQAkJyfz22+/lZuB3Wq1YjAYqpWYx8bG0r9/f1tSDjB8+HDmzJlDbGxshYn5999/z/Hjx3nhhRdsSTnA6NGj8fLyorCw8ILjEBHHK0w5yKmYlwDwuXwwTa4Z7eCIROoHJeYiIiLCyy/XTlfSjIwMkpOTGT58eJntJpOJzp07s2fPngrLxcXFYTKZ6NOnDwAFBQUYjUbatWt3zi7wIlJPWa0cf28q1qICDO5etAp/W8swivxJiblIFaxnzVRt0Kzs4ooMmpVdSvw9cbaX1NRUAIKCgsrtCwwMJC4ursJyv//+O02bNuXo0aPMnj2buLg43N3dCQ0N5bnnnsPX19duMcbHx9e4jry8PLvVJeem8123anK+j5zKt/077cvFNNqzBQBrvwc5lF4I6fpv+He6vutefTjnSsxFRETEJjk5mS1btpCUlIS7uzutW7fmxhtvpHXr1tWqr3TmdS8vr3L7PD09yc3NrbBcZmYmRUVFTJgwgZtvvpl7772X3377jeXLl3Py5ElWrFhRrXhExDGaWLJp+f2Ckj/8L4a+9zk2IJF6Rom5iIiIALBy5Urmz5+P2Wwus33u3Lk8/vjj3Hffhf+QPteM/5Ut0VZUVMSZM2cYP348ERERAAwePBgfHx8WLlzIf//7X6699toLjqciXbp0qXEdpa0s9qhLzk3nu27V5HynHDwFJPFYzipM+ekAtHtwBT6X9bBniC5F13fds9c537VrV7XL2nW5tIEDB/L666/zxx9/2LNaEcdxgcnfWjb2dHQIUp8ZNPmblPj666+JjIykffv2zJs3j40bN7J+/foy27755psLrtfb2xugwrXHCwoKKu2S3qhRIwBGjBhRZvttt90GwI8//njBsYhI3crKNzNwyQ6uLIrnrvzPAGh6/X34XHa9gyMTqX/s2mLerFkz3n77bRYvXsxVV13FiBEjGDJkCD4+PvZ8GRG5AB5uRvKLiknMyLN73Rc1bYSXu5vd6xWRurd8+XI6dOjAxx9/XKbbedeuXbn55pu58847WbFiBdddd90F1duqVSvgr7HmZ0tNTaVFixYVlivd7u/vX2Z78+bNgb+6yItI/ZVwKhuT1cxzWW8DYPQNoEXYKw6OSqR+smti/v/+3//j0KFDbNiwgX//+9/885//5KWXXmLw4MHccccdFS6HIlK/nd2K6Jwt5gCJGXlM/vhXu9e7ZOQVdAq03wRM4gia/E1K7Nmzh8mTJ1c4FrxRo0bccccdLFu27ILr9fPzo02bNuzbt6/MdrPZTEJCgq0F/O+6desGwOHDh8tMHJecnAz8lfCLSP2UlW8mPiWb8Xmb6FT8OwAtxyzA5Ot/jpIiDZNdu7IDXHLJJcycOZOvvvqK5cuXM2jQILZt28Z9993HwIEDWbRokbq6i4iI1DPFxcVl1gv/Ow8Pj2qvHT548GC2b99OUlKSbduGDRvIzc0lNDS0wjI33ngjnp6eLF++vMw49dWrV2M0Ghk4cGC1YhGR2peVb+biOV/y1PufMTXnQwCKL74Ov/7jHRyZSP1l98S8lMFgoH///rzyyivExsZy2223cezYMRYvXszNN9/M/fffX6PB8SJ1wgXGmItUSWPM5U+dOnXis88+q3CyNovFQmxsLJdcckm16p44cSLe3t6Eh4ezatUqXnvtNWbPnk1ISAh9+/YFYPfu3WzatMk2S3tAQADTp0/nm2++YeLEiXz44YfMmjWLDz/8kPHjx9O+fftqv1cRqV0Jp7JJyykkInspjSikEBNt7lmsNctFqlBriXlOTg7r16/n3nvv5YYbbmDTpk20b9+exx9/nBkzZpCUlMT48eNZt25dbYUgIiIi52nMmDH8/PPPTJkyhd9++428vDzy8vL49ddfmTJlCr/++iujR4+uVt0BAQGsXr2adu3asWDBAj7++GPCwsJYsGCB7Zg1a9bwxBNPkJ6ebtt27733MnfuXFJTU5kzZw5xcXHMnDmTp59+usbvV0Rq16DC/3J94U4AAm55iubtuzk4IpH6za5jzIuLi/nPf/7DJ598wldffUV+fj6+vr4MHz6cESNG0LNnT9ux48aN44477uCNN95g1KhR9gxDxH7UYi4ur+S6PteSVuL6RowYwS+//MKaNWvYvn17mX1Wq5WRI0fW6H7dsWPHKtcej4yMJDIystz2O+64gzvuuKParysiDpCfyVPZ7wJg8b+E1nf808EBidR/dk3MBwwYQEZGBgB9+/ZlxIgRDB48uMKJZLy8vOjatSs7duywZwgiIiJSTS+88AK33HILn332GUlJSVitVtq2bcvgwYO55pprHB2eiDgJ9y//RZClpPdL0e2vYvQonwuISFl2Tcy9vb0ZN24cw4cPp02bNuc8fuzYsTzwwAP2DEFERERqoE+fPvTp08fRYYiIk8o7/BNuO0pay2M8b+CmS7Rmucj5sGti/vLLL3PppZfa1hj9u2PHjvHDDz8wfPhwAHr37m3PlxepBa6xXJpIpQxaLq2hiomJ4aqrrrI9SI+JiTmvcrfeemtthiUiTsxabCYp6kEMWDlj8GWe733c5OigRJyEXRPze+65h3nz5jFs2LAK93/33Xe89NJLtsRcREREHGPWrFnMmzfPlpjPmjXLNmPy3+ccMBgMWK1WDAaDEnMRqVT6l29S9MfPALzqM4F0Y1M6Bfg6NigRJ1GjxDwxMZF3333X9rfVamXdunX88MMP5Y61WCx8//33+Pj41OQlRerU2T9OtcSHuCKDlktrsF5++eUyk7LOmTNH33MiUm1FaX9wcv2zAMSZurDe6ya2Te5HYy+7tgOKuKwafVIuuugiDhw4wM8//wyU/MD74YcfKkzMAdzc3Jg1a1ZNXlJERETs4O+910aMGFHl8WazmeTk5NoMSUSc2In3H8GSn00RbrzQ+CGsBqOScpELUONPy7Jlyzhz5gxWq5WbbrqJZ555hhtvvLHccW5ubjRr1gxPT8+avqRI3dFyaeLy1GIuJbp06VLlcLSNGzfy8ssvs2vXrjqOTETqu6y4T8iK2wjAe43u4JDpIgB1Yxe5ADVOzH19ffH1LfnQvfzyy/Tu3fu8ZmQXERERx0lJSeHHH3+0/W21WomLi6twTXuLxcKnn36KxWKpyxBFxAlY8rM5vnoaAMVN27HENBpA3dhFLpBdPy2a1E1cj2ZlFxenWdkbrKZNm7Jw4UKOHz8OlAxH+/DDD/nwww/LHVuarN922211GqOI1H+pG/4Pc/ofAEy1TiDfUNI7Vkm5yIWp0Sfm8ssvZ+7cudxyyy22v8/H//73v2q93tGjR4mMjGTnzp24u7szdOhQZsyYcc4J5WJiYli6dCl//PEHbdu2ZdKkSVXOKnv69GlCQ0P5xz/+QWRkZLViFRERqc88PT1588032b9/P1arlWeeeYa77rqrzIRwpYxGIwEBAVxzzTUOiFRE6qv8338m/YvXADB3H853J3rZ9qkbu8iFqVFi3rNnzzJrlld0M7eXtLQ0wsPDMZlMTJkyhczMTKKiokhMTGTZsmWVlouJiWHmzJmEhIQwbtw4tm3bxsyZM3FzcyM0NLTCMi+//DLp6em19VZEXEbLxvafM6J9+/Ylc1Fk59q9bhEpq2vXrnTt2hWArVu3cuedd9KjRw8HRyUizsBqKebYyklgKcbYqAkZN86GD44A6sYuUh01+sSsXr26yr/tKSoqitOnTxMbG0twcDAAwcHBREREsGPHDvr161euTFFREfPmzWPAgAEsXrwYg8FAWFgY48ePZ/78+QwZMgSj0VimzHfffcenn35abrs0UJr8rUoebkbyi4pJzMizW50Wi4VOLbzsVl9dsve5KHVpQG0uM6nJ36REfHw833//vRJzETkvp79aSv7hknkqmtzxEl3/TMpB3dhFqqNOPjUHDx7Ezc2NDh06VLuO2NhY+vfvb0vKoWRM+5w5c4iNja0wMY+LiyMlJYWIiAjb2qxGo5GxY8fy+OOP88svv5Rp5c/Ly+O5555jwoQJrFq1qtqxijQkiRl5TP74V7vVl5Oby/ZHQuxWX12y97kotXliX7vXKfJ3J0+eLNMLTkSkMkUZx0ld9zQAXhf34XjXsfDlf2371Y1d5MLZvVl49erVPP/887a/p02bxq233kpoaChTpkyhsLDwguvMyMggOTmZbt26ldluMpno3Lkze/bsqbDc3r17AWzd9EqV/l26v9SiRYtsMYuUUIu5uDhN/iZ/uuqqq/jmm28cHYaIOIGUDx7DkpcJRjcyhs4n/uRfvcXUjV2keuz6qVm7di3/+te/bInvtm3b+PLLL+nVqxft27dn/fr1LFu2jKlTp15QvampqQAEBQWV2xcYGEhcXNwFlQsMDASwzUQLJRPSrVq1iqVLl9KoUaMLiu9CxMfH17iOvLw8u9UlVbP+/rvt34cOHaKDX1ssFgs5ubUz/tlqpVbqrq16a6NuS3Ex1lqo11a/xUJeXh5Hjx61a73t27d3umvDYrHg9ue/09PTOa3vlDpRX7/Dhw4dyiuvvMKwYcPo06cP/v7+uLm5lTnGYDAwadIkB0UoIvVB9q+fkfnjWgA+8r2dl9ZmALtt+5WUi1SP3RPzK6+80tYN/PPPP8dkMvHWW2/RtGlTDAYDn3766QUn5jk5OQB4eZUfd+rp6UluJT9Wc3JyMJlMuLu7l9leWk/pjyOz2UxERARDhw7luuuuu6DYxMVp3K00FLrWG7z/+7//A0qGnx08eLDCY5SYizRsloJcjq8q+R1v8WvDAvewMvv9vd3VjV2kmuyamB86dIgnnngCDw8PoGQite7du9O0aVMAevToQUxMzAXXaz3HD8bKJmo7V7nScedRUVEcO3aM5cuXX3BsF6pLly41rqO0lcUedUnVcqzHKW0zv+SSS/Fs1AhjdjE+3t618noGA7VSd23VWxt15+TmYqiFeksZjUYaNWpUK58fZ7s2jEajrSt7s+bNaaXvlDphr+/wXbt22SMcG82tIiLncnLTixSdLJnk7ch1s8n7oaSX6aoxPekS5EunAF+1mItUk10/OSaTyZbs7tu3j1OnTnHXXXfZ9mdnZ59zzfGKeP/5Y7SgoKDcvoKCAnx9K34y5+3tjdlsxmw2YzL99Vbz8/MB8PX1JTExkTfffJNHHnkEg8FQZpm0wsJC0tPT8fX1tT1skIbl7Ic7Bo0xF5ekWdmlRJ8+fRwdgojUY9aTB0iLnQ/AVo9rePSHQNu+LkG+9Apu6qDIRFyDXRPzSy65hG3btjF69GjWrFmDwWDghhtuAEq6la9fv55LLrnkgutt1aoV8NeY8bOlpqbSokWLKsudPHnS9u+z62nRogU7d+6koKCAefPmMW/evDLlP/30Uz799FNefvllRowYccFxi4iIOJtdu3YRGxtLUlISHh4etG7dmsGDB3PVVVc5OjQRcRCr1QKfvwAWMzmGRrzs+4Btn7qvi9iHXRPzcePGMWvWLHr16kVOTg7du3fniiuu4LfffmPq1KmcOnWKt95664Lr9fPzo02bNuzbt6/MdrPZTEJCArfddluF5Uq7CcbHx5dJzEu7EXbr1o1WrVqxYsWKcmUffPBB+vbty/3338+ll156wTGLqzi7FVEt5uKCNCu7nGXOnDmsXr263FCw9957j7Fjx/Lss886KDIRcahf10NSyWTLb3iP5YRboLqvi9iZXT9Ft956K25ubmzatIlWrVrx8MMPAyWTrTVp0oSnn36agQMHVqvuwYMHEx0dTVJSkm0t8w0bNpCbm0toaGiFZXr16oW/vz/R0dG217VYLERHR9O2bVu6d++O0WissMXdYDAQGBjItddeW614RUREnMnGjRtZtWoV1157LdOmTaNjx45YLBYOHDjA22+/TXR0NFdeeSW33nqro0MVkTpkzkyFr0q6sFtaXcGHRcMAdV8XsTe7P94KDQ0tlyh37NiRTz/9tEb1Tpw4kY0bNxIeHs6ECRNIT09n+fLlhISE0LdvXwB2795NYmIigwYNwtvbG5PJxPTp04mIiGDq1KmEhISwZcsWdu7cyaJFiyqdNE5ERKSh+eCDD+jevTvLli0rc3/s3bs37777LmPGjCE6OlqJuUgDk/LhDMjPBAwU3rGQ4o9zHB2SiEtymsw0ICCA1atX065dOxYsWMDHH39MWFgYCxYssB2zZs0annjiiTITuI0aNYrZs2dz6NAhXnzxRY4fP87ChQsZMmSII96GOJuzu3Nq8jdxQQZN/iZ/OnDgALfcckuFD63d3NwIDQ0lISHBAZGJiKNk79nKmf++D0Ba1zD2undycEQirsuuLeZFRUW8+eabbNy4kVOnTmGxWModYzAY2Lt3b7Xq79ixY4XjwUtFRkYSGRlZbntYWBhhYWEVlKjcb7/9dsHxiYiIOCuj0UhhYWGl+wsLC8+5DKmIuA5LYT4n3psCwEljc4al3EHOh7sdHJWI67JrYv7mm2+ydOlS/Pz8uPLKK7XEmDg/tZiLq7PN/aaEq6Hr1q0bn3zyCRMmTCh3/y4oKGDTpk01XntdRJzHqX+/TGHKAQDm+D5AjtHbtk8zsYvYn10T808++YSrrrqKFStW4Onpac+qRUREpBbde++9TJ06ldGjR/Pggw/aViQ5cOAA77zzDocPH+b11193cJQiUhcKju8n7dOSXqgFl97EloySyZA1E7tI7bHrJ+rUqVNMmTJFSbm4EC2XJi5Oy6XJnwYOHMjjjz/O66+/zvTp08vsMxgMPPLIIwwaNMhB0YlIXbFarRxfORmruRCDeyNuTQ8Dt5J7hWZiF6k9dk3M27ZtS1pamj2rFBERkTry4IMPMnToUL744guSkpKwWq20bduWQYMGcdFFFzk6PBGpA2e+W03uvq8BKBz4JMfigmz71H1dpPbYNTEfM2YMS5cuZeTIkQQGBtqzahHH0Bhzl9OysXr0lFVyXWtSLynVtm1b7r//fkeHISIOYM5OI+WjGQB4BncntdeDELcTgBWhrdV9XaQW2fXTZbVa8fT0ZPDgwfTt2xd/f/9yy64YDAZmz55tz5cVETlvHm5G8ouKSczIs2u9lwb42LU+EUfIzc1lxYoVfPHFFyQmJmIymbj44osZOnQod999NyaTfpSLuLLUNU9QnHUKAL+xb9Hx3Z22fT7uTrPKsohTsusdds6cObZ/f/311xUeo8RcRBwtMSOPyR//atc6N0/sa9f6ROpaeno6Y8aM4ffff8fPz49LL72U4uJijhw5QmRkJJs3b2bVqlV4eXk5OlQRqQU5+78h4z9RADQLmcTvft2Bb2z72zfRaksitcmuifnWrVvtWZ2Iw53dvdegruziikqva3Vlb/BeffVV/vjjD5599llGjx6Nm5sbAGazmQ8++IDIyEjeeustZsyY4eBIRcTeMrNzSXz3AYyA1SeQY/2fIj4l27Z/RWhrfDzUYi5Sm+yamLdp08ae1YmIiEgd+frrrwkLC2PcuHFltptMJu655x4OHjzIp59+qsRcxMVk5Zt5/p9TeCBjPwBPGsPZvPS3MseoG7tI7auVT1lsbCyPP/44o0eP5tdff+XgwYMsW7aM3Nzc2ng5kVqk5dLE1Wm5NCmRk5NjW7u8Il26dCE9Pb0OIxKRunBg/2+Mz/gIgP+6X8lmz+vL7Pf3dlc3dpE6YNcW8+LiYh555BG2bduG1WrFYDCQk5PDsWPHmD9/PrGxsaxcuZLGjRvb82VFRESkhnr27MmWLVvKtZiX2rFjB927d6/jqESkNlmtVgwbH8eTQgpwx2/M6/zUueznvFOAL0lHDjgoQpGGw64t5lFRUWzdupVHH32U2NhY2/jckJAQpk2bxt69e1m2bJk9X1Kkdmm5NHF1GmMuf3ruuec4fPgw06ZNIz4+nsLCQiwWC4mJiTz//PN88803TJs2jZSUlDL/ExHnlfLNB3ge/hqApd53cXHn7vQKblrmf1oiTaRu2PWTtnHjRm6++WYmT57M6dOnbds9PT2ZNm0aiYmJfP7550yfPt2eLysiIiI1NHz4cMxmM19++SVbt27FYDBgNBopLi4GSlrWJkyYUKaMwWBg7969DohWRGqqOCeDtDUzMACH3YJZ4T2CeQG+jg5LpMGya2KemJjI3XffXen+3r178/nnn9vzJUVqmcaYi6vTGHMpcfPNN2v1CZEGJHXd0xiyUwF4wXcqn0+5Xq3jIg5k10+fj48PZ86cqXR/cnIy3t7e9nxJERERsYPIyEhHhyAidST34A5Of70UgA1eN7LL43Il5SIOZtcx5n379mXt2rXk5OSU23fs2DE++ugjevfubc+XFBERETvbu3cvX3zxBV9//TX79+93dDgiYkdWcxHHV0wCq5XThsYs8LkXKJnkTUQcx66Pxh555BFGjhzJHXfcwT/+8Q8MBgNfffUV27dv5+OPP6awsJApU6bY8yVFapcmfxMXZ9Dkb3KWuLg4nnnmGX7//fcy2y+66CL+9a9/6eG6iAtI++I1CpJK1imf73sfGcYmbJvcTy3mIg5m10/gJZdcwooVK3jmmWd4//33AVi1ahUArVu35sUXX6Rr1672fEkRERGxg4MHD3L//fdTXFzMyJEjufTSS7FarSQkJPDvf/+bBx54gI8//phLLrnE0aGKSDUVnvqdkxv+D4Cf3C9nk+dAACXlIvWA3T+FV155JZs3b2bfvn0cOXIEq9VKcHAwl19+OUajXXvOi9Q+tZiLq/vzuraqxbzBe/PNNzGZTKxfv54OHTqU2ffAAw9w1113sWTJEubNm+egCEWkJqxWKydWPYS1MJciTMz2nQoGA/7e7urGLlIP2C0x//HHH9m2bRt79uwhPT0dg8FA8+bNufzyywkODlZSLiIiUo/98MMPjB07tlxSDtChQwfGjBnD+vXrHRCZiNhD1s71ZP/yKQDLvO/kiCmYVWN6cnu3lmoxF6kHavwpTE9P57HHHuOnn36qsMXlxx9/ZMWKFQwYMIC5c+fSvHnzmr6kSB3665o2aLk0cUlaLk1KZGVl0bJly0r3t2zZssqVV87l6NGjREZGsnPnTtzd3Rk6dCgzZszAx8fnvOuYMGECiYmJbNu2rdpxiDRExXmZnHj/EQAs/hfzrmEUAF2CfJWUi9QTNfok5ubmMnbsWI4ePcott9zCnXfeSefOnWnatClms5n09HT27NnDJ598whdffEF4eDjr1q2jUaNG9opfRERE7KBNmzb89NNPjBkzpsL9P/30E61bt65W3WlpaYSHh2MymZgyZQqZmZlERUWRmJjIsmXLzquOjz/+mB07dtCmTZtqxSDSkJ38f89izjgGQNFtCyj8t5uDIxKRv6tRYh4VFcXRo0eZO3cut99+e5l9bm5utGrVilatWnHTTTcRGxvL448/zvvvv88DDzxQo6BF6opVY8zF1WlWdvlTaGgoS5YsoUuXLtx7772YTCU/EcxmM1FRUXz22Wc8+OCD1ao7KiqK06dPExsbS3BwMADBwcFERESwY8cO+vXrV2X5U6dO8corr+Du7l6t1xdpqLLyzRz4+Rs8v3wTA2DuMYo9jXsDux0dmoj8TY0Gfn/55ZfcdNNN5ZLyigwdOpSQkBC+/PLLmrykiIiI1IJJkybRtWtXFixYwLXXXsvIkSMZOXIk1157La+++iqdO3dm0qRJ1ao7NjaW/v3725JygOHDh+Pt7U1sbOw5y7/00kt06NCBPn36VOv1RRqirHwzHf/1OYfefQCD1cIZgw83Jg0j/EMl5SL1UY0S8z/++IOrr776vI/v06cPhw8frslLitQttZiLy1OLuZTw8vLi/fffZ9q0aQQFBXHw4EEOHDhAixYtmDp1KtHR0Xh7e19wvRkZGSQnJ9OtW7cy200mE507d2bPnj1Vlt+2bRtbtmxh9uzZGPQ9LHLeEk5lMzhtI93MhwB41WcCacZmtv2ajV2kfqlRV/b8/Hz8/PzO+/imTZuSk5NTk5cUERGRWvDJJ5/Qp08fpk2bxrRp0+xWb2pqKgBBQUHl9gUGBhIXF1dp2ezsbF544QXuu+8+OnfubLeYRFxdVr6ZgwcP8HDuBwBkt7qap6bO5qmzVknqFKCJ30Tqkxp9GouLi3FzO//JI4xGo9bKFRERqYdefPFFxo4dy/Tp0+1ab+kDeS8vr3L7PD09yc3NrbTsq6++ioeHBw899JBdY/q7+Pj4GteRl5dnt7rk3HS+K5dTaGHw2qM8n/ovulvzKMKNlH6zuDQnpcxxSVnnX6fOd93S+a579eGcO9Xi4kePHmXy5Mn07t2bfv36MXv27PNqgY+JiWHYsGH06NGDYcOGERMTU+6YlJQUZs6cSf/+/enduzcPPfQQiYmJtfE2xKmc/SBJXSjFBRm0XJqUsFqttGjRolbqrYrRWPFPkd27d/Phhx/ywgsvVJjUi0jFjmYW0iPzewYV7gBgTePhtGrf1cFRici51Lj/ys6dOykuLj6vY6vqrnYu1V1qJSYmhpkzZxISEsK4cePYtm0bM2fOxM3NjdDQUKBk2bd77rmH06dPM2HCBLy8vHjvvfcYPXo0n3zyCQEBAdWOW0RExBncc889rFixgu7du3PFFVfYrd7ScekFBQXl9hUUFODrW36Ma1FREREREYSEhHDZZZeRnp4OlMwQb7FYSE9Px9PT84LWQK9Kly5dalxHaSuLPeqSc9P5rlhWvpndZw7zz+ylABQ0acuT/1qOX5MmNapX57tu6XzXPXud8127dlW7bI0T87Vr17J27drzOtZqtVZ74pbqLLVSVFTEvHnzGDBgAIsXL8ZgMBAWFsb48eOZP38+Q4YMwWg0sm7dOo4cOcLq1attM75ef/31hIaGEh0dzSOPPFKtmMUFaPI3cXVaLk3+tG/fPtLT0wkLC6NRo0Y0b968wuFqn3/++QXV26pVK+CvseZnS01NrbCVPiUlhYMHD3Lw4EG2bt1abn+/fv0YPnw4kZGRFxSLiCvLyjdz8ZwvmZD6DvdaTpZsvGNBjZNyEakbNUrM7Tk5zLlUttTKnDlziI2NrTAxj4uLIyUlhYiICNsDAaPRyNixY3n88cf55Zdf6NmzJ4WFhfTp06fMMiyXXHIJzZo1Y//+/bX/5kRERBwsPj6epk2b0rRpUwAsFgsWi6XG9fr5+dGmTRv27dtXZrvZbCYhIYHbbrutXJnAwEBWrFhRbvuCBQs4ceIE8+bNq5Vu9yLOLOFUNgGZCYzP2wTAV97XEd5/uIOjEpHz5RSJeelSK8OHl/1yOddSK3v37gWga9ey42pK/967dy89e/bkgQce4IEHHihzTEpKChkZGbYn/dJQqcVcXF3JdW3VGPMGb9u2bbVW9+DBg4mOjiYpKcn2gH3Dhg3k5ubahpWdzdPTk2uvvbbc9uXLl3P69OkK94k0dFm5BTyX9RYmLBR7NGbc8+9r1nURJ+IUn9bqLrVSWbnAwEAAjh8/Xq5MRkYGe/bsYd68eXh7ezNu3Lgaxf53mvnVuViTkmz/TkhIoEOXK7FYLORUMYtwjV7PSq3UXVv11kbdluJirLVQ79l0nktYLBZKOypnnjmj75Q6Up++w/ft28eiRYvYuXMnZrOZK664gsmTJ1fYC60mJk6cyMaNGwkPD2fChAmkp6ezfPlyQkJC6Nu3L1Ay2VtiYiKDBg2q1nrpIg1ZVr6ZpYv+j2fNCQAU3/wsTVte5OCoRORCOEViXt2lVnJycjCZTLi7u5fZXlpP6Y+js02ePJndu3cDMHPmTDp06FCj2MXZqRVRXJx6gjRY+/fvZ8yYMeTl5eHj44PJZOKHH37gp59+4tVXX2XIkCF2e62AgABWr17NnDlzWLBgAY0bNyYsLKzM0mxr1qxhw4YNbN26VYm5yAXaHb+PR3NWA/CbqSNDQzU/koizcYrEvLpLrZyrXEUT0d13331YrVa++OIL5s+fT1paGk899dT5B3sOmvnVuWRm/Y/SNvPOnTrj1qgRxuxifGrpR6PBQK3UXVv11kbdObm5GGqh3rPpPJcwGo22RQCbNGlCsL5T6kR9mPkV4J133sFgMPDmm29y0003AfDrr7/y+OOP2yZItaeOHTtWOG68VGRk5Dknc1u+fLldYxJxBVn5Zn5aPJWh1hyKMdJmwhKaeHs6OiwRuUBOsY55dZZaKS1nNpsxm81ltufn5wNUWG7w4MHcfPPNLFiwgGHDhvHee++RnJxc07cgIiJSr+zatYu7777blpQDXHHFFTzxxBMkJydz7NgxB0YnIufr4I5NDC34BoD3G91Kj6uvd3BEIlIdTpGYV2eplbPLnTx5slwZ4Jwzug4ZMgSLxUJCQsIFxyyuwarl0sTlabm0hiotLY327duX2969e3esVisnTpyo+6BE5IJYCvNw/2QmAMeNAYQ+8pomfBNxUk6RmJ9rqZW/z7peqrSb4N8n2Cn9u1u3bgBMnTqVe++9t1z5qsa2i4iIOLOioqJyc7DAX/e8wsLCug5JRC7QqU9ewph+FIA5vg/i26SpQ+MRkepzisQcSrqYb9++naSzZsmuaqkVgF69euHv7090dLRtm8ViITo6mrZt29K9e3egZNb277//3ra8GpT8YPnggw9o0qQJPXr0qKV3JfXf2a2IajEXF2TrCaIWcynrXPO0iIhj5Sft4dTmVwDY6tGXrzyvcXBEIlITTtPXpTpLrZhMJqZPn05ERARTp04lJCSELVu2sHPnThYtWmSbNG7atGl88cUX3H///YSHh+Pt7c2mTZvYu3cvc+fO1eywIiIiIlJvWC0Wjr83GYrNFLt787Lvg44OSURqyGkS8+outTJq1CgsFgtRUVF8++23tGvXjoULF5aZbdbf358PPviAefPm8e6772I2m+nWrRvvvPMO11+vCTQaNI0xF1dn0Bjzhmznzp0UFxeX2VY6jOu7774jJSWlXJk77rijLkITkSpkfLOCvIRvAZjvMYYTboEOjkhEasppEnOo/lIrYWFhhIWFVVl3+/bteeutt2oco4iIiLNYu3Yta9eurXDf35cms1qtGAwGJeYiDmbOTCVlzSwA4k0diG40DAB/b3c6BVS8UpGI1H9OlZiL1Dm1mIvLU4t5QzVt2jRHhyAi1ZD0weNYck5jxcALvg9RbHBj1Zie3N6tpWZkF3Fi+vSKiIg0QErMRZzPyZ+3kPv9BwBEe4XyP/dOAHQJ8lVSLuLknGZWdhERERGRhspSVEDK6qkApBqb84bP3YC6sIu4Cj1aE6mSlksTF/fnEA2rlksTEXGorHwzCaeyK91v2joX91MHAYj0ncjb4wbQJciXTgFqLRdxBfoUi4iIiIg4UFa+mYvnfElablGF+9ubk1h/ej4A//HoxRce/flXkC+9gpvWYZQiUpvUlV2kKmdNiGXQ5G/ikjT5m4iIoyWcyq40KcdqJSJ7CR6YycODf/lOwt/HQ93XRVyMWsxFREREROqJVWN60iXor6TbbfdHeHz8KwCmm59m4/Wj1H1dxAXpEy1SBauWSxNXZ7uu1WIuIlIfdDmri7o5O41Dnz9LMeAZfDld7vonBpO7Q+MTkdqhruwiIiIiIvVQ6ponKc46BUCrCUuVlIu4MCXmIlXSrOzi2mxzJ2iMuYiIw2Tlm8tty9n/DRn/WQ5A0xsexLvjtXUdlojUISXmIiIiIiIOkpVvZuCSHWW2Wc2FnFg5GQC3Ji0IuivSEaGJSB1SYi5SFY0xl4ZCLeYiIg7x97XLOwX4kha7gIJjewFoOeZV3HyaOSI0EalDSsxFREREROqBbZP74Xnmd05umg2AT7ebaNJvrIOjEpG6oMRcRERERKQeaOzpxvHVD2Etysfg7kmrexb/NReIiLg0JeYiVdLkb+LitFyaiEi94fbbBnJ++xyAgFv/iUfQpQ6OSETqihJzEREREREHKZ2RvbElG/dPnwbAo1Vn/EOfcGRYIlLHTI4OQKRe0+Rv4vJKrmurJn8TEalzZ8/I/mjOagz5qUDJmuVGd09HhiYidUwt5iIiIiIiDlA6I3v3ov3clf8ZAH4DJuBz2T8cGZaIOIBazEWqclYroiZfEZdUel2rxVxEpM5k5ZtJOJVNfEo2JquZ/8t6CyNW3Hz9CRo9z9HhiYgDKDEXEREREakjWflmLp7zJWm5RQBMyIuhc/FRAILC5mFqHODA6ETEUdSVXaQKVs3KLq5Os7KLiNSphFPZtqS8VXEqU3OiAfDseB1+101wYGQi4khqMRcRERERqWVnd18HwGplnd9HeKcXgJs7wfe9o2FzIg2YEnMRERERkVr09+7rADcWfk/TI18CEHDLk3i2vsxR4YlIPaCu7CJV0XJp4vI0+ZuISG07u/s6gLcll3/mvAOAe4tLCLj1GUeFJiL1hBJzEREREZE6smpMT/7b+WtaFKcB0OqexRg9Gjk4KhFxNCXmIlVRi7m4OIMmfxMRqVNdzYcw7ShpLW/Sbyy+lw9ycEQiUh8oMRcRERERqQNGazEeGx8DqwWjd1NajnnV0SGJSD3hVIn50aNHmTx5Mr1796Zfv37Mnj2bnJycc5aLiYlh2LBh9OjRg2HDhhETE1PumGPHjjFjxgz69u1L9+7dufXWW9m4cWMtvAtxLlouTVydxpiLiNSVMXmbMR77GYCguyIx+QU5NiARqTecZlb2tLQ0wsPDMZlMTJkyhczMTKKiokhMTGTZsmWVlouJiWHmzJmEhIQwbtw4tm3bxsyZM3FzcyM0NBSA3NxcwsPDycjI4O677yYwMJDPPvuMJ598kpycHMaNG1dXb1NEREREXFCL4jQezn0fgEaX9qPpPx5wcEQiUp84TWIeFRXF6dOniY2NJTg4GIDg4GAiIiLYsWMH/fr1K1emqKiIefPmMWDAABYvXozBYCAsLIzx48czf/58hgwZgtFo5P333+ePP/7go48+omfPngCMHTuWsWPH8tprr3HXXXfh7u5ep+9X6gmNMRdX9+d1bVWLuYhIrXoq+118rXlYjSZaTViKwehUHVdFpJY5zTdCbGws/fv3tyXlAMOHD8fb25vY2NgKy8TFxZGSkkJYWJhtgiOj0cjYsWNJTk7ml19+AeCHH36gffv2tqQcSiZEGjJkCJmZmRw+fLgW35mIiIiIuLKCXzczuPC/AJj7T8WrbXcHRyQi9Y1TJOYZGRkkJyfTrVu3MttNJhOdO3dmz549FZbbu3cvAF27di2zvfTv0v2RkZG8/fbb5cqfPn3a9joiIiIiIhfqzJkz5K57DIAkYwvMA59wbEAiUi85RWKempoKQFBQ+QkyAgMDOXHixAWVCwwMBOD48eO2vy+55JIyxxQUFLB+/XqaNm1K+/btaxS/OLO/uvca1JVdXJKWSxMRqU1H1z1La8tJAP7lO5lOrTXhm4iU5xRNwaUzr3t5eZXb5+npSW5ubqXlTCZTufHhpfXk5eVV+povvvgiKSkpzJgxAzc3t+qGXk58fHyN6yiN2x51SdWsfz68gZLz3b59eywWCzmVXHM1fj0rtVJ3bdVbG3Vbioux1kK9Z9N5LmGxWGz/zsnO0XdKHdF3uEjDkZ/4K6ZvS3plfu5xLS88+jCNvZzi57eI1DGnaDE/16RExkomzzhXucpaQF977TXWrVtH3759uf/++88vSHFRakUUF2dQi7mISG2wWiwkRT2IwVpMtqERkb4PKCkXkUo5xbeDt7c3UNK9/O8KCgrw9fWttJzZbMZsNpcZJ56fnw9QYbl58+axbNkyunbtyltvvWXX1nKALl261LiO0lYWe9QlVUs/3orSgRKl59uYXYzPn9ekvRkM1ErdtVVvbdSdk5uLoRbqPZvOc4mzH2r6+PjQTt8pdcJe3+G7du2yRzgiUktOf/0OhUd+AGCRz3hOuvnTKaDi36wiIk7RYt6qVSvgrzHjZ0tNTaVFixZVljt58mS5MkCZclarldmzZ7Ns2TIuv/xyVq5cSePGje0SvzgxW68LjS8XF1XaYq7l0kRE7MaccYLUdU8B8D/TpazxGsq2yf3UYi4ilXKKxNzPz482bdqwb9++MtvNZjMJCQnlZl0vVdoa8fdxfKV/nz3L+6uvvsoHH3zAlVdeycqVK/Hz87PnWxAREWnQjh49yuTJk+nduzf9+vVj9uzZtjlkKpOfn8+8efMICQnh8ssvZ+DAgSxcuJDCwsI6ilqkek58+DiW3DMUY+QF34ewGNyUlItIlZzmG2Lw4MFER0eTlJRkW8t8w4YN5ObmEhoaWmGZXr164e/vT3R0NAMHDgRKJjuKjo6mbdu2dO9esobk9u3beeedd+jatSvLly+vtGu8NER/tiJqRnZxWRpjLrUvLS2N8PBwTCYTU6ZMITMzk6ioKBITE1m2bFml5Z5++mk+++wzRo4cSdeuXfnll19YunQpR44c4fXXX6/DdyBy/rJ/+4LM7z8E4INGw4h3L1n5R93YRaQqTpOYT5w4kY0bNxIeHs6ECRNIT09n+fLlhISE0LdvXwB2795NYmIigwYNwtvbG5PJxPTp04mIiGDq1KmEhISwZcsWdu7cyaJFi2zjK1999VUAbrjhBrZu3Vruta+77jqaN29ed29WRETEhURFRXH69GliY2NtD9eDg4OJiIhgx44d9OvXr1yZn3/+mc2bNzNjxgwefPBBAMaMGUNQUBBLlizht99+sz1gF6kvzmRm8UfUJIxAoW8r3vQcC6Bu7CJyTk7zDREQEMDq1auZM2cOCxYsoHHjxoSFhTF9+nTbMWvWrGHDhg1s3brVNmHcqFGjsFgsREVF8e2339KuXTsWLlzIkCFDAMjMzLR1kX/77bcrfO01a9YoMW+oNMZcXJ3GmEsdiI2NpX///rakHGD48OHMmTOH2NjYChPzH3/8EYDbb7+9zPahQ4eyZMkSfv75ZyXmUq9k5Zt5+Z8PEp55FICZxnvJNZb8HlVSLiLn4lTfEh07dmTFihWV7o+MjCQyMrLc9rCwMMLCwios06RJE/bv32+3GEVEROQvGRkZJCcnM3z48DLbTSYTnTt3Zs+ePRWWGzt2LAMGDCg3wevp06cB7L5qikhNHdi7kzGZHwOwzaMP2zyvAcDf213d2EXknJwqMRcRERHnUroSSlBQULl9gYGBxMXFVVjO19e3wsldP/ywZOzuVVddZccoRaovK99MQmom5nWP4oWZXLwIHPc6P13aGSgZW64WcxE5F31LiFTFqsnfxLUZ/hymYdXkb1JLSmde9/LyKrfP09OT3Nzc867rk08+4fPPP+e6667jsssus1uMf1+9pTry8vLsVpecW3053zmFFgavPUpIxue8mF0y/OJNn7EMc/PAO+s4AElZjozQPurL+W4odL7rXn04506xXJqIiIg4J+s55i8onYj1XLZv384zzzxDYGAgL730kj1CE6mxo5mFGPJOMyNnJQDxpg582vR22jfxcGxgIuJ01GIuUiW1IoqL0+RvUstKJ2MtKCgot6+goOC8lijdsmULjz/+ON7e3ixbtoyWLVvaNcYuXbrUuI7SVhZ71CXnVl/Od8rBU8zInklTaxZWDHSY+C6He/7D5bqu15fz3VDofNc9e53zXbt2VbusWsxFRESk1rRq1Qr4a6z52VJTU8tN7vZ3//73v3nsscfw9vbmvffes2sXdpGayMo38+TrS7mjYBsAxX3v56p+N7pcUi4idUOJuUgVrBpjLq5OLeZSy/z8/GjTpo1tadJSZrOZhISECid4K7V9+3aeeOIJ/Pz8WLVqlVqPpF5JOJHGc9mLAUg1NqfdmPIrA4mInC8l5iIiIlKrBg8ezPbt20lKSrJt27BhA7m5uYSGhlZYJjU1lZkzZ+Lt7c2KFSvo3LlzXYUrcl6Kty2kQ3EyAJ53zMWvmb+DIxIRZ6a+NiJVKm1FVIu5uKrSa1st5lJ7Jk6cyMaNGwkPD2fChAmkp6ezfPlyQkJC6Nu3LwC7d+8mMTGRQYMG4e3tzbvvvktmZiY333wz+/btK9fi3rVrVzp27OiItyNC+u97cd/+KgDfuF9F76vudHBEIuLslJiLiIhIrQoICGD16tXMmTOHBQsW0LhxY8LCwpg+fbrtmDVr1rBhwwa2bt2Kt7c3P/5YsvTU559/zueff16uzhkzZigxF4ewWq0kr5yCJ0Xk4cFLjSezN7Cxo8MSESenxFxERERqXceOHVmxYkWl+yMjI4mM/GuM7qZNm+oiLJELlrJ9FW6H/wPAEp/RrH5ouCZ8E5Ea0xhzkapo8jdxdZr8TUTkvGWkpXLovUcBOOB2Ee81ukNJuYjYhRJzEREREZHzkBj9BM0sZwCY3Xgqfj6N6BTg6+CoRMQV6BGfSFWsmvxNXJ1azEVEzsep/32Naed7AKzzGsz08HHc3q2lWsxFxC7UYi4iIiIiUoXM7Fy+f20CAGkGPxb63EOXIF8l5SJiN0rMRaqkMebi4v68tq1aLk1EpFJHNs3l4qLfAZjnex/uvs3VhV1E7EqP+UREREREKlGYehjTtlcA2OHeg7smTOeDy1uptVxE7Eot5iJV0bhbcXWalV1EpFJWq5Xjqx7CYM6nAHde8p1Ml5aNlZSLiN0pMRcRERERqUDmj+vI+e0zAN71HsXvpjYOjkhEXJUe94mIiIiI/M2Z02kkrXoEA5Df7BKWu93p6JBExIWpxVykClarJn8T12bQcmkiIuVk5Zt5M2IChuwUAKZY7qPI4O7gqETElSkxFxERERE5y4Hd27k9+1MANnoO5CeP7gD4e7trNnYRqRXqyi5SpdJWRLWYi4uy9QZRi7mICIC12IzHpukYsZJhaEyH8IX81P4iADoFaO1yEakd+mYREREREflT+pbXMR7/DYAFPhN4pv1F9Apu6tigRMTlqSu7SFU0xlxcnsaYi4iUKkpLJPX/PQvAT+7d2OB1k4MjEpGGQom5iIiIiAhwfPXDWAtzsRrdedF3qh7Mi0idUWIuUiWNMRcXZ7u01WIuIg1b5q6NZO/+BIB3vIZz2NTWwRGJSEOiMeYiIiIi0qAV52Vx4v2HAbA078A7xlG2fZqFXUTqglO1mB89epTJkyfTu3dv+vXrx+zZs8nJyTlnuZiYGIYNG0aPHj0YNmwYMTExVR6/adMmunfvbq+wxZlZ1WIuLu7PbppWjTEXkQbs5PrnMKcnAXDouhcpMHgCsG1yP83CLiJ1wmm+adLS0ggPD8dkMjFlyhQyMzOJiooiMTGRZcuWVVouJiaGmTNnEhISwrhx49i2bRszZ87Ezc2N0NDQcsfv27eP2bNn1+ZbEREREZF6Iu9oHOlbXgfgU8/refK/TWz7lJSLSF1xmm+bqKgoTp8+TWxsLMHBwQAEBwcTERHBjh076NevX7kyRUVFzJs3jwEDBrB48WIMBgNhYWGMHz+e+fPnM2TIEIzGvzoNbN++nZkzZ5KdnY2Hh0edvTcRERERqXtWSzHHV04Cq4VMgw+v+N5v2+fv7a5u7CJSZ5ymK3tsbCz9+/e3JeUAw4cPx9vbm9jY2ArLxMXFkZKSQlhYGIY/u2sajUbGjh1LcnIyv/zyi+3YuXPn8uCDD9KmTRsGDBhQu29GnIdtuTTHhiFSe7Rcmog0XMc/f5P8IzsBeM0nnDRjM1aN6clPj13H4WduUou5iNQZp0jMMzIySE5Oplu3bmW2m0wmOnfuzJ49eyost3fvXgC6du1aZnvp36X7AQ4dOsTUqVNZu3YtgYGB9gxfREREROqZ08d/J3nN0wD8bOrMOq+bAegS5Euv4KZKykWkTjnFN05qaioAQUFB5fYFBgYSFxd3QeVKE+/jx4/btr355pvqvi7lWLVcmrg62xq9ajEXkYYl6f1H8bHmYcbI7MZTsRqM6r4uIg7jFIl56czrXl5e5fZ5enqSm5tbaTmTyYS7u3uZ7aX15OXl2bbVVVIeHx9f4zpK47ZHXVI1658Pd6yUnO/27dtjsVjIqeSaq/HrWamVumur3tqo21JcjLUW6j2bznMJi8Viy8fz8/L1nVJH9B0u4nhZv2zG7X+bAFjV6HYixo+gS5AvnQJ81VIuIg7hFN8851rG5+wJ3C6knMGgVlA5F7UiiotTi7mINDCWghxOrJoKQLKxBYt9xvCfP7uvi4g4ilMk5t7e3gAUFBSU21dQUICvb8Vdjry9vTGbzZjNZkymv95qfn4+QKXlalOXLl1qXEdpK4s96pKqnTzQgpOUPMQpPd/G7GJ8/rwm7c1goFbqrq16a6PunNxcDLVQ79l0nkuc/VDTy8uLi/WdUifs9R2+a9cue4Qj0mBk5ZtJOJWN6bPncT/1OwBzfCeRZyjfI1NEpK45RWLeqlUr4K8x42dLTU2lRYsWVZY7efKk7d9n11NZOREbq8aYi2uz9RzSrOwi4sKy8s1cPOdLmmceYO3ptwD4wuNatnte7eDIRERKOMWs7H5+frRp04Z9+/aV2W42m0lISCg363qp0taIv4/jK/3777O8i4iIiIjrSTiVTXpOAc9nvY07xWQbGhHp+wCg9cpFpH5wihZzgMGDBxMdHU1SUpJtLfMNGzaQm5tLaGhohWV69eqFv78/0dHRDBw4ECiZ7Cg6Opq2bdvSvXv3OotfRERERBwjK9/MyPwvuNJc0sjjccv/8Wm/OwA04ZuI1AtO8y00ceJENm7cSHh4OBMmTCA9PZ3ly5cTEhJC3759Adi9ezeJiYkMGjQIb29vTCYT06dPJyIigqlTpxISEsKWLVvYuXMnixYtqnTSOJG//Nm9VxMFiqvS5G8i4uKy8s2Menszn+S8B4ClTU963DkDg9HNwZGJiPzFaRLzgIAAVq9ezZw5c1iwYAGNGzcmLCyM6dOn245Zs2YNGzZsYOvWrbYJ40aNGoXFYiEqKopvv/2Wdu3asXDhQoYMGeKotyIiIiIidSThVDazsqPws+ZQjJHWE5YoKReResdpEnOAjh07smLFikr3R0ZGEhkZWW57WFgYYWFh5/06ldUjDZAmfxOXp8nfRMS1GQ9+xbCC7QAU9JmIf6c+Do5IRKQ89eUWEREREZdkKczDfdMMAE4Y/TEMiXBwRCIiFVNiLlKV0lZENZiLq/pzjLlVY8xFxAWdipmDMf0IAC/7PgiejR0ckYhIxZyqK7uIiIiIyLlk5Zs5sHcXnp/OxQB85dGHrR7XODosEZFKqcVcpAp/tSKqyVxclcaYi4hryco3c/G/tvDb2/djKC4iF0/m+D6oFVZEpF5TYi4iIiIiLiPhVDbXnf6Mq4v2APCWz1iOu7XA39udTgG+Do5ORKRi6souIiIiIq4jJ40Z2SWr+OQGdGXaI68wzc1EpwBfGnvpp6+I1E/6dhKpim3yN3V/ExdlUFd2EXEt7p89RyNrFhYMGEcu4qp2AY4OSUTknNSVXURERERcQk7815jiogFY6zUEa9veDo5IROT8KDEXqZImfxNXV3ptq8VcRJybpaiA4+9NBuCksRmLfMY7OCIRkfOnxFxEREREnF7a5lcoPL4fgLk+E8kyaqI3EXEeSsxFqqIx5uLiDBpjLiIuoODEAU7F/AuAb9178pnnAADNwi4iTkOJuYiIiIg4LavVyolVU7EWFWBx8+SlxlPAYGDb5H6ahV1EnIYSc5GqWDXGXFycWsxFxMll7ogmZ8+XALzudRdJbi0BlJSLiFNRYi4iIiK17ujRo0yePJnevXvTr18/Zs+eTU5OzjnLxcTEMGzYMHr06MGwYcOIiYmpg2jFWRTnnObEh48DcNCtLSsb3QGAv7e7urGLiFPRo0SRKpWOMXdsFCK1p+TitmpWdqlFaWlphIeHYzKZmDJlCpmZmURFRZGYmMiyZcsqLRcTE8PMmTMJCQlh3LhxbNu2jZkzZ+Lm5kZoaGgdvgOpr1LWPkVxZioALzR+CLPBnVVjenJ7t5ZqMRcRp6JvLBEREalVUVFRnD59mtjYWIKDgwEIDg4mIiKCHTt20K9fv3JlioqKmDdvHgMGDGDx4sUYDAbCwsIYP3488+fPZ8iQIRiN6vjXkFmT4sj4+h0APvYazG73rgB0CfJVUi4iTkd3NBEREalVsbGx9O/f35aUAwwfPhxvb29iY2MrLBMXF0dKSgphYWG21QOMRiNjx44lOTmZX375pU5il/rJWlwEn78AQJrBj1d97gHUhV1EnJceJ4pUwarJ38TVafI3qWUZGRkkJyczfPjwMttNJhOdO3dmz549FZbbu3cvAF27di2zvfTvvXv30rNnz1qIuHqslmKwFGMpKnB0KA3D98vh5AEA5vveR6axsbqwi4hT0zeXiIiI1JrU1JLxv0FBQeX2BQYGEhcXd0HlAgMDATh+/LjdYoyPj69ReWvyL1jXTcaQf4Z9dopJzk9O66uJKbwBAK/ckyQdyXJsQC4qLy8PqPlnRc6Pznfdqw/nXF3ZRaqiFnNxeaXXtlrMpXaUzrzu5eVVbp+npye5ubmVljOZTLi7u5fZXlpP6Y+oeiHtEIb8M46OosGxevhivPl5mnq50dTTSPsmHo4OSUSk2tRiLiIiIrXGeo5hEpVN4HaucqXjzu2hS5cuNSpv7fwU8b6BkH2K1q1b2ykqqcqxEykY2vam1zU38vs1ZkDrltem0lbEmn5W5PzofNc9e53zXbt2VbusvsFEqlS6XJpazMVFaYy51DJvb28ACgrKj70uKCjA17fiibq8vb0xm82YzWZMpr9+ruTn5wNUWs4RDEY3DBdfB0BT/ZCuE8fP6m6qhFxEXIG6souIiEitadWqFfDXmPGzpaam0qJFiyrLnTx5slwZoNJyIiIizkiJuUhVNMZcXJ1azKWW+fn50aZNG/btKzstmtlsJiEhodys66VKuxP+fSKe0r+7detWC9GKiIg4hhJzERERqVWDBw9m+/btJCUl2bZt2LCB3NxcQkNDKyzTq1cv/P39iY6Otm2zWCxER0fTtm1bunfvXutxi4iI1BUNyhEREZFaNXHiRDZu3Eh4eDgTJkwgPT2d5cuXExISQt++fQHYvXs3iYmJDBo0CG9vb0wmE9OnTyciIoKpU6cSEhLCli1b2LlzJ4sWLap00jgRERFnpMRcpEqa/E1cnZZLk9oXEBDA6tWrmTNnDgsWLKBx48aEhYUxffp02zFr1qxhw4YNbN261TZh3KhRo7BYLERFRfHtt9/Srl07Fi5cyJAhQxz1VkRERGqFEnMRERGpdR07dmTFihWV7o+MjCQyMrLc9rCwMMLCwmozNBEREYdzqn5gR48eZfLkyfTu3Zt+/foxe/ZscnJyzlkuJiaGYcOG0aNHD4YNG0ZMTEy5YwoLC3nttdcICQnhyiuvZPz48fzvf/+rjbchzkQTYomLK10L+lxrRouIiIhI7XGaxDwtLY3w8HASEhKYMmUKd911F+vWrePRRx+tslxMTAwzZ84kODiYp556ilatWjFz5kw2b95c5rgXX3yRpUuXcuONNzJr1izb6/3++++1+bZERERERESkgXOaruxRUVGcPn2a2NhYgoODAQgODiYiIoIdO3bQr1+/cmWKioqYN28eAwYMYPHixRgMBsLCwhg/fjzz589nyJAhGI1GDh48yNq1a3n88ceZNGkSAEOHDmXIkCG8+eabzJs3r07fq9QftlZEjTEXl6Xl0kREREQczWlazGNjY+nfv78tKQcYPnw43t7exMbGVlgmLi6OlJQUwsLCbN01jUYjY8eOJTk5mV9++cVWt8Fg4K677rKVbd68OUOGDOHLL7+ksLCwFt+ZiIiIiIiINGRO0WKekZFBcnIyw4cPL7PdZDLRuXNn9uzZU2G5vXv3AtC1a9cy20v/3rt3Lz179mTPnj20bt2aZs2alTmuW7durFmzht9//52OHTva6+3UmDXzBOSmkeeV6+hQXF7xmRN//kst5uKiSseYF+WTd2SXg4NpGKwnkyHgUkeHISIiIvWIweoEM/4kJCRw66238uKLL5Zp1QZ4+OGHiYuL47vvvitXbu7cuURFRfG///0Pd3d32/bs7Gx69erFAw88wMyZMxkxYgQeHh589NFHZcpv27aNKVOm8O6773L99dfX6D3s2qUfvCIiYn+9evVydAhOS/dmERGpDdW5NztFV/bSmde9vLzK7fP09CQ3t+KW45ycHEwmU5mk/Ox68vLybMc1atSoXPm/HyciIiIiIiJib07Rlf1cjfpGY8XPF85VznCeE3pVVv+FUIuGiIhI/aJ7s4iI1BdO0WLu7e0NQEFBQbl9BQUF+Pr6VlrObDZjNpvLbM/PzwewlfP29rZtq+o4EREREREREXtzisS8VatWAKSmppbbl5qaSosWLaosd/LkyXJlAFu5li1bljumouNERERERERE7M0pEnM/Pz/atGnDvn37ymw3m80kJCSUm3W9VJcuXQCIj48vs730727dugEls7QnJyeTmZlZ5ri9e/fi7e1Nhw4d7PI+RERERERERP7OKRJzgMGDB7N9+3aSkpJs2zZs2EBubi6hoaEVlunVqxf+/v5ER0fbtlksFqKjo2nbti3du3cHYNCgQVgsljKzsqenp/PZZ59x880322WMuYiIiIiIiEhFnGK5NIBTp04xbNgwvL29mTBhAunp6Sxfvpz+/fuzZMkSAHbv3k1iYiKDBg2yjUtft24dERER3HjjjYSEhLBlyxa2b9/OokWLGDJkiK3+WbNm8emnnxIeHs5FF13E+++/z8mTJ/n4449p166dQ96ziIiIiIiIuD6nScwBDhw4wJw5c4iLi6Nx48YMGTKE6dOn4+PjA8BTTz3Fhg0b2Lp1K8HBwbZya9asISoqiuPHj9OuXTumTJlSrpW9oKCAhQsX8sknn5CXl0f37t158sknbd3dRURERERERGqDUyXmIiIiIiIiIq5Gg6dFREREREREHEiJuYiIiIiIiIgDKTEXERERERERcSAl5iIiIiIiIiIOpMRcRERERERExIGUmIuIiIiIiIg4kBJzEREREREREQdSYi4iIiIiIiLiQErM67EdO3YwatQorrjiCgYOHMgbb7xBYWFhmWO+/fZbRo4cyZVXXslNN93Ee++956BondeECRN47rnnym3/7bffGD9+PD179uT6669n0aJFmM3mcsfFxMQwbNgwevTowbBhw4iJiamLsJ1aZecc4Pfff6d79+78/PPPFe5/7733GDx4MD169ODOO+/k22+/rcVIXUNl53vdunXceuutXH755fTt25eZM2eSmppa7jhd4xemsvO9adMmbrvtNnr06MHNN9/M+++/j9VqLXecznf9pntz3dC9ue7p3ly3dG+uW85wb1ZiXk999913TJw4kbS0NB555BFuueUWli5dyiOPPGI75scff2TSpEl4enoya9YsevbsyZw5c3jnnXccGLlzeeONN9ixY0e57YcOHeKee+7hzJkzTJ8+ncGDB7NkyRJefPHFMsfFxMQwc+ZMgoODeeqpp2jVqhUzZ85k8+bNdfUWnE5l5xwgOzubhx9+uNyP3FJLlixhzpw59OzZk6eeegqTycSkSZPYtWtXbYbs1Co73x9++CERERG0aNGCp59+mrCwMLZu3cq4cePIzs62Hadr/MJUdr7XrVvHE088QevWrXnqqafo0aMHL774Im+88UaZ43S+6zfdm+uG7s11T/fmuqV7c91ymnuzVeqloUOHWnv16mVNSUmxbdu0aZO1U6dO1i+++MJqtVqtI0eOtA4bNsxaUFBgO2bGjBnWK6+80nrmzJk6j9mZFBQUWF988UVrp06drJ06dbI+++yzZfY/+uij1n79+pU5j6+++qr1sssusx45csRqtVqthYWF1uuuu8563333WS0Wi9VqtVqLi4utY8eOtYaEhFiLi4vr7P04g3Od86NHj1qHDRtm27979+4y+9PT061XXHFFmXJ5eXnWwYMHW8eMGVMXb8GpVHW+CwoKrD179rTef//9Zcp8++231k6dOlmXLVtmtVp1jV+Iqs632Wy29unTx3r33XeXKfPYY49Ze/ToYc3+/+3dbUhT7R8H8O98mKYmMR8yU5Tbh0qJKCUSNQuCHlALzSxbQSoSSkpIRSD1IhSlFyIGEaZvzKFEhKSBZE8ShaVFUSrJClIxJ4bWrW5urPtF7NyO2X92/7dzzuT7eed1ncnV71zu689tV3///fPnT9bbFTCbnYvZLD5ms7iYzeJytWzmK+YyNDo6Cq1Wi+zsbAQHBwvjGRkZUKlUaG9vx+joKN69e4esrCwolUrhGrVajbm5OfT09EixdJcwMzODjIwMNDc3o7Cw0GZ+YWEB3d3dOHDgAPz9/YXx48ePw2w2o6urCwDw+vVrTExMIDc3FwqFAgDg5uaGvLw8jI2N4e3bt+L8g1yAvZp3dXUhIyMDOp0Ohw8fXvJ7PH78GHq9Hrm5ucKYt7c3srOz0d/fj4mJCaet39XYq/fAwABmZ2dx8OBBq/Hk5GT4+/sLb1XkHl8ee/WenJxEbGys1d4FgMTERMzPz2NkZAQA6y13zGbnYjaLj9ksLmazuFwxm9mYy5DlSSw6OtpqXKFQICwsDIODgxgYGAAAxMXFWV1j+frDhw8irNQ1/fjxAwqFAjdv3sS5c+ds5oeHh2E0Gm1qGxwcjKCgIKG29u6BZZ6WV/M9e/bg3r17SEhIWPJ7DAwMwN3dHRs2bLAat9R7cHDQ8Qt3UfbqHRcXh87OTqSlpVmNGwwGzM/Pw93dHQD3+HLZq3dISAiam5uRnp5uNT40NAQ3NzehyWO95Y3Z7FzMZvExm8XFbBaXK2azh8O+EzmMj48PAGB2dtZmbmZmBlNTU8IhEGvXrrWaVyqVWLNmDb5+/er8hbqokJAQ3L9/H25uS/9d6ne1BX79AmCp7e+uCwoKAgCMj487bM2uzl7Ni4qKrF5dWopOp0NAQAA8PKyftlhvW/bqrVQqbZoL4NdnrYxGI7Zu3QqAe3y57NV7MZPJhNHRUXR0dOD27ds4cuQIVCoVANZb7pjNzsVsFh+zWVzMZnG5YjbzFXMZioqKgo+PD7q7u63GtVotRkZGYDAYhF8MVq1aZfN4Ly8vzM/Pi7JWV+Th4fE/f0gttfX29raZW1zb2dlZeHh4wNPT0+oay+N4D/5lr+b2gh/4Ve+l9jvrbctevZei1WpRW1uLwMBAZGdnA+AeX64/qXdvby/27t2L+vp6REREoLi4WJhjveWN2exczGbxMZvFxWwWlytmMxtzGVIqlVCr1Xj16hUuX74MrVaLvr4+lJWVwc/PD+7u7kse47+Y5TMQ9OeWW1veA3HZq/efhh39a3R0FAUFBdDr9aiuroafnx8A7nFnWL9+Pa5du4aKigrMzs4iKysLX758AcB6yx2zWVrMZnliNjsPs1k8cslmvpVdpkpLSzE1NYXW1la0trbCw8MDarUaOp0OL1++FN5Sp9frbR5rMBiEH176c5baGgwGm7nFtfXx8YHJZILJZLJ6C5flnvAeOJaPj8+S+90y5uvrK/aSVoRPnz4hPz8fExMTqKysRGpqqjDHPe54kZGRiIyMBADs2LEDhw4dwo0bN1BZWcl6uwBms3SYzfLEbHYOZrO45JLN/DOWTHl6eqKqqgpPnz5FS0sLenp6cPHiRYyPjyMsLAzr1q0D8OtEwcUWFhYwPT1tdWIs/RlLbS2fKVlMp9MJtf3dPbA8jvfAsUJCQvDt2zeYzWarcdb7v/v48SPUarUQ/FlZWVbz3OPOFRMTg6ioKOFwJNZb/pjN0mE2yxOz2fGYzdKSMpvZmMtUR0cH+vv7ERISgsTERAQEBGB+fh6Dg4PYtm0bNm3aBMD2tEvLyYDx8fGir3mliIqKgpeXF4aGhqzGdTodJicnhVMYf3cPLF/zHjhWXFwcjEYjhoeHrcZZ7/9mbGwM+fn5mJ6eRk1NjU3wA9zjjvLixQukpqbi+fPnNnNzc3PC59RYb/ljNkuH2SxPzGbHYjaLR47ZzMZcppqamlBTU2P1uYaGhgYsLCwgJycHYWFhiI+PF05qtLh16xZ8fX2xc+dOKZa9Inh5eSEtLQ0dHR34/v27MN7S0gI3Nzfs378fAJCQkICAgABoNBrhGrPZDI1Gg/DwcGzevFn0ta9ku3btglKpREtLizCm1+tx584dbN++HYGBgRKuzrWYzWaUl5djcnISVVVVyMzMXPI67nHHiI6OxtTUlFUdAeDhw4cYGRkRnq9Zb/ljNkuH2SxPzGbHYTaLS47ZzM+Yy1R+fj7Ky8tRVlaGlJQUvH//Hm1tbSgqKsJff/0FACgvL0dhYSFOnTqFzMxM9PX14d69e7hw4QI/X/J/OnPmDHJycqBWq3Hs2DFotVq0tLQgLy8P4eHhAH6d9nj27FlUVFSguLgYu3fvxoMHD9DX14e6ujoeeOJgKpUKBQUFuH79OkwmE7Zs2YK7d+9ibGwM1dXVUi/PpTx69Ahv3rxBTEwMFAoF2tvbreaDg4ORlJTEPe4gQUFBKC4uRn19PUpKSpCSkoLPnz9Do9Fg48aNOHnyJAA+p7gCZrO0mM3yw2x2HGazuOSYzWzMZSo9PR1GoxGNjY3o6elBaGgoLl26hLy8POGa5ORk1NfXo66uDleuXEFoaCgqKipw4sQJCVe+MsTGxqKxsRFXr15FVVUVAgMDUVxcjNOnT1tdl5OTA7PZjKamJjx79gwRERGora3Fvn37JFr5ylZaWgovLy+0tbWhs7MTsbGxaGhoEP5vT1qe3t5eAMDw8DDOnz9vM5+SkoKkpCQA3OOOUlJSgtWrV0Oj0eDJkydQqVQ4evQoysrKhEOtANZb7pjN0mI2yxOz2TGYzeKTWzYrfto7A56IiIiIiIiInIbvdSAiIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKSEBtzIiIiIiIiIgmxMSciIiIiIiKS0D8PIvLMvuEVEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 194,
       "width": 499
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1,2, figsize=(8,3))\n",
    "xs = np.linspace(90,130,1000)\n",
    "\n",
    "# plot histogram of `vsample`\n",
    "sns.histplot(vsample, stat=\"density\", ax=axs[0], label=\"vsample\")\n",
    "\n",
    "# plot the pdf of rvV \n",
    "sns.lineplot(x=xs, y=rvV.pdf(xs), color=\"r\", ax=axs[0], label=\"$f_V$\")\n",
    "lines, labels = axs[0].get_legend_handles_labels()\n",
    "axs[0].legend(reversed(lines[0:2]), reversed(labels[0:2]))\n",
    "\n",
    "# plot a empirical cumulative distribution\n",
    "sns.ecdfplot(vsample, ax=axs[1], label=\"eCDF(vsample)\")\n",
    "\n",
    "# plot the CDF of rvV\n",
    "sns.lineplot(x=xs, y=rvV.cdf(xs), color=\"r\", ax=axs[1], label=\"$F_V$\")\n",
    "axs[1].set_ylim(-0.05, 1.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e66ff66a-7b1e-4a0f-a968-df5ac885103c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "eadcca0d-1151-4926-a8b3-0d842c0d6dff",
   "metadata": {},
   "source": [
    "#### Exponential distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c94fd888-b7a5-4224-bba3-c03065b93407",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import expon\n",
    "lam = 0.2\n",
    "rvE = expon(0,1/lam)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbc2f41b-2f4a-44be-833c-83c667d30444",
   "metadata": {},
   "source": [
    "Here is the code for visual comparison of `esample` and the theoretical model `rvE` $=\\mathrm{Expon}(\\lambda=0.2)$, based on the probability density and cumulative probability distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6dc97dd5-1a89-4fda-8472-61ab2272c155",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.05, 1.05)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 194,
       "width": 504
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1,2, figsize=(8,3))\n",
    "xs = np.linspace(0,30,1000)\n",
    "\n",
    "# plot histogram of `esample`\n",
    "sns.histplot(esample, stat=\"density\", ax=axs[0], label=\"vsample\")\n",
    "\n",
    "# plot the pdf of rvE\n",
    "sns.lineplot(x=xs, y=rvE.pdf(xs), color=\"r\", ax=axs[0], label=\"$f_E$\")\n",
    "lines, labels = axs[0].get_legend_handles_labels()\n",
    "axs[0].legend(reversed(lines[0:2]), reversed(labels[0:2]))\n",
    "\n",
    "# plot a empirical cumulative distribution\n",
    "sns.ecdfplot(esample, ax=axs[1], label=\"eCDF(esample)\")\n",
    "\n",
    "# plot the CDF of rvE\n",
    "sns.lineplot(x=xs, y=rvE.cdf(xs), color=\"r\", ax=axs[1], label=\"$F_E$\")\n",
    "axs[1].set_ylim(-0.05, 1.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5febf1ed-f854-44b6-ba02-18e0025d3bc8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "52ae75e6-850e-420a-8bfa-064fefed0a04",
   "metadata": {},
   "source": [
    "### Using Q-Q plots to compare quantiles\n",
    "\n",
    "The quantile-quantile plot `qqplot(data, dist)`\n",
    "is used to compare the positions of the quantiles of the dataset `data`\n",
    "against the quantiles of the theoretical distribution `dist`,\n",
    "which is an instance of one of the probability models in `scipy.stats`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d746e70-94ae-4a72-987b-392bf0697a7f",
   "metadata": {},
   "source": [
    "The easiest way to generate a Q-Q plot is to use\n",
    "the function `qqplot` defined in the the `statsmodels` package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ae23a281-1364-420b-8ca3-d9058aa299b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.graphics.api import qqplot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92394d04-a0d8-4103-8ff6-0af499e5b32b",
   "metadata": {},
   "source": [
    "#### Examples of good fit\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4309897-f359-422f-b065-e8dfb609f3b3",
   "metadata": {},
   "source": [
    "##### Normal data vs. the true normal model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "869f0e52-7f49-4f31-8729-96905a679793",
   "metadata": {},
   "source": [
    "Let's look at the quantiles of the data in `nsample`,\n",
    "plotted versus the quantiles of the theoretical model $\\mathcal{N}(1000,100)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3c327c0c-6f1e-4d84-93bd-61b2c6db7342",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 262,
       "width": 445
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qqplot(nsample, dist=norm(1000,100), line='q');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "448e439e-20db-4457-9ba7-ea2d198e8c73",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b56b64c5-5c41-40f2-b660-4057b626ef65",
   "metadata": {},
   "source": [
    "#### Normal data vs. the standard normal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "62dae6e2-2b9a-49c6-a17c-5116c0894142",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1aqXo6GjNnj07x72zZ89WbGysmjVrJknq2rWrPB6P5syZ422XnJys5cuXq1u3bryzBwAAgIDk3LNRB1/tq71PNNPJDR9KpkdGcKgir7tbl72wW7Xu/EChtZpo8tq9Stx6ON++Erce1uS1e0to5vizgHmyt3r1av3www9q2LChDMPQwoULc1yvWrWqrr32WgUFBenBBx/U3//+d91zzz3q3LmzVq5cqU2bNunVV1/1hrgrrrhCN910kyZPnqzk5GTVqVNHs2bNkmmauvvuu/3xEQEAAIBiYZqmHL98pROLJipt2ypv3QgNV9R1dyuq+0MKjji3Ks7tMTVl3b4C9T11/T6Wc/pJwIS97777TpK0e/du/e1vf8t1vV27drr22mslSQkJCfJ4PHrnnXe0bt06xcXF6ZVXXlH37t1z3PPvf/9b0dHR+uyzz+R0OtWsWTNNmjRJcXFxxf+BAAAAgGJmmqbO/HexTiyaKOeeb711S3ikors+oKiuY2WtEJXrvk0HU3UgtWBHke1PcWrTwVS1iYv02bxRMGU27O3cuTPHz0888YSeeOKJAt8/ePBgDR48ON82oaGhevTRR/Xoo48WaY4AAABAaWS6s3RqY6JOLH5WGb//5K0HVa6u6BsfVkSnO2S1Vbzg/ckO1wWv+aI9fKPMhj0AAAAAhePJzFDKug90+LNnZUk+twwzOKauons+ooh2I2QJCbtoP1H2kEKNW9j28A3CHgAAABDgPBlpSvrybR1c+LzCHEe9uzT+ao3Vp1WG6Mput+uBTo1kKeB7dfGxEaoTYSvQUs64SJviYyOKPnkUGWEPAAAACFDutFQlr5qq5M8ny30mSdnP7H4Oukxv2wfpy5DWMt0Waekufff76QIfk2C1GBrbrp4mLM597MKf3de2Hpuz+AlhDwAAAAgwWSePKmnFZKV88Zo86ae99Y3BzTTdPlDfBP9FMnIGsMSth9V67V6N79SgQGOM61BfGw+k5Hv8QkLzGhrXoX6RPgMuHWEPAAAACBCZSQd0Yukkpa6ZLjMz3Vv/LvwaTQnup/8GN873/sIck2C1GJo9tJVar92rqev3aX/KuSWdcZE23de2Hkcu+BlhDwAAACgj3B5Tmw6mKtnhUpQ9RPGxEbJaDGUc3qmkJc8r9ZuZkjvrbGPDUKXWg3S41b0alZhaoP4Le0yC1WJofKcGGtehfp7zgn8R9gAAAIBSzu0xNXntXk1Zty/HpiidbYf0uOUz1di/XDLNs0VrsCLa3qbonn9TaPVG+mnHUUkbCzxWUY5JsFoMztErhQh7AAAAQCnm9pgaMmtzjnfjrsrcrjGORHU4vtlbM0Jsiux0h6K7j1dwdKy3zjEJ5RdhDwAAACjFJq/dezbomab+mvmDxjgSdXXmNu/104ZdH9l6qkGfhzW2e+tc93NMQvlF2AMAAABKKbfH1NSv96hLxjca40hU06w93mtJRmXNtN+kOWE9dMYSrrjNp3TPDWaud+U4JqH8IuwBAAAApZCZlan/LpmuKfsmqr77d2/9iCVG79r6aZ7tBqUbod56fpurcExC+UTYAwAAAEoRj8up1K/fVdLSF2Q7sV/Z8es3a03NsA3QorBOyjKC87z3QpurcExC+UTYAwAAAErQhY5PcDtPK2X1G0pa8bLcJ4962/9iradp9gStDL1WHsOab9/5ba7CMQnlD2EPAAAAKAEXOj7hykqZ+lfFL3X5rlnyOFK9ddtlf1VUr8fVY3GIDpxMz6PHnAq6uQrHJJQfhD0AAACgiC70lC6vdn8+PqGKO0nDnZ9q0PEVsitdnv/Vw5t1U0yvx2W/vL0Mw9DYk3vYXAVFQtgDAAAACulCT+ku9P6b9/gESbXdRzTSMV9901cpRFneNitDrpW92980ZmDfHGOxuQqKirAHAAAAFEJeT+my7U9xasLi7dp4IEWzh7Y6+y6ex9SUdft0WdZ+jXbM1Y0ZX8v6v+d4WbJoSWhHzbAP0N6gOorbadNIT87jE9hcBUVF2AMAAAAK4fyndBeSuPWwWq/dq/GdGmjLhi80fv/fdb3rO+/1DAVrQVgXvWPvrz+s1bz1Cx2fwOYqKArCHgAAAFBA2U/pLso0tXblAg34boXCt6/S9f8rpxk2fRzWXR/Y+uiENSrPWy90fILE5iooHMIeAAAAcJ78Nl3ZdDA1xzt6uZimOrq+1xhHov6StVOO/5VTjYqaZeut2baeOmWpmO/4+R2fABQGYQ8AAABQwTZdudBTN4vpVreMdRrjmKtG7v3eelaFaqrRa4L6f99Iu05dfA4FPT4BKAjCHgAAAMq9gm668sCfdrwMNjN1U/qXGumcpzj3uXsPWqrpHfsAPfTg31XlshoaY+P4BJQ8wh4AAADKvYJuuhIfG6E6ETYdT0nRAOcKjXB+quqeJG+bX62xmmZP0PLQ9qodVUHx9atL4vgE+AdhDwAAAOVagTddkfT+1z/rlUprVPXXGYo0T3vrPwU11DR7gr4MaS3TsEjK+ZSO4xPgD4Q9AAAAlAsX2njlopuuSIr2pGiY4zPdfGKpKpjn2n4X3EzT7An6NriFZJwLank9peP4BJQ0wh4AAAAC2sU2XrmiaoUL3lvDfUwjHAs0IH2lwnRuc5bwFr20qvZt+vfuyEI/peP4BJQUwh4AAAACVkE2Xrnusuhc1+pm/a5RjnnqlfGVguU+25csWhHaVh1HPaMmbdprlKQR+RzTAPgbYQ8AAABlWn7n4hVk45XVvyYpwhasVGemGmfu0WhHorq6NsgiU5KUqSB9FtZZM2wDZFRpoAevbue9l6d0KM0IewAAACiTLrY8c2y7egXeeKV5+s+6JfUjtc/c4q05FaK5tm5639ZXR6xVJEmTOBoBZQhhDwAAAGVOQZZnLvvlaP4br5im2mZu0RhHouIzz52Bd9qw6yNbT82y9VayJcJb52gElDWEPQAAAJQ5BV2emRfD9Oh617ca40hU06w93rrbHq1fG4/Q31Pba8cpi7fO0Qgoqwh7AAAAKFMKcy7e+YLMLPXIWKPRjnmq7/7dWz9sidG79v4aO+7/1K9hLd3EpisIEIQ9AAAAlCkFORfvfKFmhvqmf6GRjvmq5Tnmre+z1tIM+wAtDu2oWlGV9H6DmpLYdAWBg7AHAACAUiuvnTaTHa6L3ygp3OPQoPRlGu5YqBgz1Vv/xVpP0+wJWhl6rTyGVZJ0HxuvIAAR9gAAAFDq5LfT5k1NquV7b4TnlG51LtIQ52JVNtO89R+CrtDb9kH6OqSVZJwLdmy8gkBF2AMAAECpcrGdNqes/032YKscme4c16q6kzTc+akSnMtlV4a3br/yBq2OHaF//Rqj/anp3jobryDQEfYAAABQqhRkp83zg16s+7Bud8xX3/QvFKIsb31lyLWyd/ubxgzsq5GShrPxCsoZwh4AAABKjcLstNlMB3XrqU90Y8bXssojScqSRUtCO2qGfYBatWyj2f1beduz8QrKG8IeAAAASo2C7LTZLHOnxjgSdZ1ro7eWoWB9Gna93rH3V1BMPZZnAiLsAQAAoBS54E6bpqnWmVs1xjFX12b+6C17QsIVff3dOnjlSF1jjVIPlmcCXoQ9AAAAlBpR9pAcPxumRx1d32uMI1EtsnZ566lGRc2y9dbw+/+lKxvXV42SnihQBhD2AAAAUGrEx0aoToRNh1LO6IaMdRrjmKtG7v3e68csUXrf1kef2LqralSUplxez4+zBUo3wh4AAABKDcPt0vNVvlPlPVNVx3PEWz9oqaZ37AO0MOw6uYyzT/84CB3IH2EPAAAAfufJSFPKV9OUtOxFNUs55K3/ao3VdPtALQvtILdh9dY5CB24OMIeAAAA/MadlqrkVVOV/Plkuc8keethdeO1vv4oPXmwvn5LPXdAOgehAwVH2AMAAECJyzp5VEkrJivli9fkST/trduv6KyYmx5XeJPrVd8wNISD0IEiI+wBAACg2Lj/FNZa2E4qZcVLSl0zXWZmurfdVyFXa5o9Qameq3Tf8XoaZ0pWg4PQgUtB2AMAAIDPuT2mJq/dqynr9ulAqlN1s37XKMc82TK+UpDcZ9vIohWhbTXDPlA7g/63q2aKUxMWb9fGAymaPbQVT/GAS0DYAwAAgE+5PaaGzNqsxK2HdUXmHr3kSFRX1wZZZEqSMhWkhWHX6R1bfx0IqplnH4lbD6v12r0a36lBSU4dCCiEPQAAAPjU5LV79evmL/S6I1EdXJu9dadClGjrrvdtfXXUGnPRfqau38dGLMAlIOwBAADAJ0zT1OmtyxX70SOamf6Tt37KCNccWw/NtN2kFEvlAve3P8WpTQdTeWcPKCLCHgAAAC6J6fHo9OYFOrFootL3b9GV/6snGZX1gb2PPg67UWcs4UXqO9nh8t1EgXKGsAcAAIAiMbMydfLb2Tqx+Dm5Dv/irR+2xOhde3/ND+uqdCP0ksaIsodc6jSBcouwBwAAgELxuJxKXfuOkpa+oMykA956ZlQDHWhxlwb8VF9ZRvAljxMXaVN8bMQl9wOUV4Q9AAAAFIjbeUopq99Q0vKX5T51zFvfE1Jfr4cO1ErLtfL8bJXVakge85LHu69tPTZnAS4BYQ8AAAD5yjp9Qskr/6PklVPkcaR66wcqN9ezZl99HdJKMs6FMrcPgl5C8xoa16H+JfcDlGeEPQAAAOQpM/mQkpa/pJQv35LpcnjrWZddp+8vG6UxmyrkCHmFMbBZdbWuE6nXvvlN+1Oc3npcpE33ta3HkQuADxD2AAAAIOnsE7mtx9KVcWK/MlY9r9D/fiQz69xumCtDrtV0+0BtO9lQ1h8Mybj4EzyrxcjxpO/PYe7Bjg206WCqkh0uRdlDFB8bQcgDfISwBwAAUM65PaYmr92rRV+sVo+jH+rGjK9llUemJLcsWhzaUTPsA7Q3qE6Oewra9/SEFqpRKTTPMGe1GJyjBxQTwh4AAEA55vaYmvDa+6q/9Q297trorWcoWAvCuugde3/9Ya12SWPUqBSqGxtfWh8ACo+wBwAAUA6ZpinHji+1+YN/aPThb7z1NMOmT8K6631bH52wRvlkLM7KA/yDsAcAAFCOmB6Pzvy4RCcWPSPnnu8U8796qlFRs2y9NdvWU6csFX02HmflAf5j8fcELsWIESP0f//3f3le279/v5o1a6b//ve/eV5///33dcMNN6hFixYaMGCA1q1bl6vNmTNn9M9//lPt2rXTVVddpTvvvFMHDhzIozcAAIDSzXRn6eSGj7T3H3/Rwck3ybnnO0nSMUuUXggfqa7R0/Vm+M0+DXoSZ+UB/lRmw96UKVO0YcOGPK+dOXNGY8eOlcvlyvP6m2++qYkTJ+qqq67So48+qqCgIN15553avHmzt41pmnrggQc0b948DRgwQA888IB27NihoUOHKjU1tTg+EgAAgM95MjOU8tU0/froFTr05hBl/P6TJCm4Sj0ldXte3aPe1gf2vnIaNp+PzVl5gH+VuWWcLpdLL7zwgmbOnJnn9f379+u+++7Trl278ryekpKiN954Q4MHD9bTTz8tSerXr5/69Omjl156SbNnz5YkrV27VuvWrdNLL72kXr16SZLat2+vm266Se+9957GjRvn+w8HAADgI56MNKV8+baSlr2orNQ/vPXQWk0V0+sxVWozWMm/n5ZrS+7VTYV1seMVAPhHmQp7J0+e1KBBg/Tbb79p9OjRmj59eo7rK1as0IQJE2Sz2TRw4EDNnTs3Vx9ffvml0tPTNXjwYG8tLCxMAwYM0EsvvaSjR4+qWrVqWrZsmSpVqqQePXp42zVo0EDXXHONli1bRtgDAAClkjstRcmrXlPy55PlPpPkrYfVu1pVbnpCFf7SW4bl7OKu+NgI1Ymw6UCq80LdFcjEG69Qh/rRnJUHlDI+DXvZQUmSDhw4oDlz5ig4OFgDBw5UbGzsJfd/+vRpGYah6dOnq3379rnC3u7du9WlSxc9+uijWrduXZ5hb/v27bJarbr88stz1Js0aSJJ2rFjh6pVq6Zt27bpiiuukMWSc6Vr06ZNtW7dOqWlpSk8PPySPxMAAIAvZJ08qqQVryjli9flST/trdsbd1ZM7ycU3uQ6GcbZAOb2mN6DzPs0raYp638r8rgJzWvooY4NCHdAKeSTsJecnKwxY8bINE3Nnz9fJ0+e1ODBg5WSkiJJmjNnjj766CPVr39pa7arV6+upUuX5gpg2e644w6FhOS/te+xY8cUHR2toKCcH71KlSqSpMOHD3vbNWrUKNf92e2OHDmiBg0aFPozAAAA+FL6sd/0S+IzCtoyS5asdG89/C+9dSz+Xu2P+cvZp22mJPPs4elT1u3L8TTPHmyVI9N9wTGa16iok+lZ2p9y7h6WagKln0/C3tSpU7Vjxw6NGTNGkrRgwQKlpKTokUceUbNmzfTQQw/ptdde00svvXRpkw3Kf7oXC3qSlJaWJpst9wvIYWFhkiSn01modr6wY8cOn/VVlmX/mfLnAX/iewh/4zuI/Lg9pradyNDJDLdiHPtl3ThD9Q59rhCdDWpuWbQ2vJ02xA7Vl6m1dXihS9LZg9JrhFtVKdSqncm5N7DLDnphQYbSs869e1ezQpBubVJZw5pGSJJ37MqhVjWNCZXV4tKunb8U74dGucPfg77jk7D31Vdf6ZZbbtGDDz7o/TkiIkIjRoyQYRi6+eab9eGHH/piqEtmmma+1y/01LCo7QAAAC6V22Nq5rZUzdp2UhGpOzXGkahGrg2y6Oy/azIVpM/COmuGbYAOBNWUkiQpK0cfh9PcOpx24ad3kpSeZWpwI7v+WtOmqhVt/wt0557aNa8a5uuPBqAY+STsHT9+3PvOW3p6urZs2aJOnTp514VXrVpVp0+fzq+LEmO325Wenp6rnl3Lfg/vYu0qVKjgszk1btzYZ32VZdm/veHPA/7E9xD+xncQUs536iqHBWvy13u1d9Na/Z8jUe0zt3jbORWiRFt3vW/rq6PWmHx6LLiv/3DpibY1dGXTJj7pDygs/h7M6fzj4QrLJ2EvOjpaycnJkqQNGzbI5XKpbdu23ut79uzxvuvmb9WrV9dXX30lj8eT4+ncsWPHJJ0Nptntjh8/nuv+Y8eOyWKxKDo6umQmDAAAyg2350/v1Jmm2mZu0R1piWqVtd3b7pQRro9sPTXL1lsplso+ncMfZ7K07USGrvRprwD8wSdhr3nz5po9e7bq1KmjN954Q1arVZ07d1ZWVpZWrVqlTz75RN26dfPFUJesSZMmyszM1O7du3PsyJn9G4SmTZt623355ZcyTdP7hFI6u5tn3bp12YkTAAD4lNtjasiszUrceliG6VEX17ca40hU06w93jZJRmXNtN+kOWE9dMZSfP8WOZmR/3JPAGWDT148e/jhh2Waph544AH98ssvGjNmjKpWrarvv/9e48aNU+XKlXXvvff6YqhL1qlTJ4WEhOR4hzA9PV3z5s1T69atFRNzdgnEDTfcoNTUVC1dutTbbs+ePfr2229znL0HAABQVG6Pqe/2p2jZjqN6aOHPWvDjQd2U/oUWptynyaee8wa9w5YYPVPhDnWLnq7p9oRiDXqSVDnUWqz9AygZPnmyV6dOHS1cuFAbNmxQzZo11bx5c0lSw4YN9fDDD6t///6KioryxVCXLCoqSqNGjdIbb7yhrKwstWjRQgsWLNChQ4f03HPPedt17txZ8fHxeuKJJ7R3715VrFhR7777rqpVq6ahQ4f68RMAAICy6M/v4X3zW7Kmrv9NB1KdCjUz1C99lZY65qum59xrJPustTTDPkCLQzsqywgukXnWrBCkpjGhJTIWgOLls0PVK1eurO7du+eoxcTEaPTo0b4awmfuv/9+hYaG6uOPP9aSJUvUqFEjTZs2TVdddZW3jWEYev311/Xcc8/pgw8+kCTFx8frscceU2RkpL+mDgAAyphc7+GdJ9zj0O3pyzTcsVAxZqq3viOonqbbErQy9Fp5jJJ9ynZrk8qcmwcECMO82FkEBeRyufTBBx9o5cqVOnTokCZPnqywsDDNmzdP99xzT6nZoKU0yd5Zp1WrVn6eSenAzksoDfgewt/4DgaG7Kd4x89kaPLX+7T61xM5rkd4TulW5yINcS5WZTPNW/8h6Aq9bR+kr0NaSUbJB66E5jX0j1Z2WS0G30H4DX8P5nQpmcEnT/acTqeGDx+urVu3Kjw8XA6HQ5mZmUpKStJHH32kr7/+WrNnz/budAkAABCI8nuKJ0lV3Uka7vxUCc7lsivDW18ffJXetidoc3DTYg95zWtU1Mn0LO1POTe/uEib7mtbT+M61OeQdCCA+CTsvfHGG/r55581adIktW3bVn/9618lSd26ddOzzz6rf/zjH3rrrbf0j3/8wxfDAQAAlBoXe4onSbHuPzTSMV9901cr+LzDzleGXKtp9gRtD77MZ/OpExGm5jUq66cjpy4Y6CR53x+MsocoPjaCpZtAAPJJ2Fu2bJn69eun3r17KyUlJce1fv36aevWrVqzZg1hDwAAlGn5bbKSl4ZZv2m0Y666Z6yTVR5JUpYsWhLaUTPsA7Q3qM4lzScu0qZ7/lpXbetF6aQzM0dwO3+ueQW6NnHsQQAEOp+EvSNHjnh34MxLkyZNNG/ePF8MBQAAUOIutjzzz5pl7tQYR6Kuc2301jIUrAVhXfSOvb/+sFYr0jwGNquucR0b5Ap2ebFaDAIdUM75JOxFRETo6NGjF7y+Z88eVa5c2RdDAQAAlKjzDzvPl2mqTeZWjXEk6prMrd5ymmHTnLAb9YG9j5IsRQtf5y/BZLklgILySdhr166d5syZo0GDBik0NOe5LD///LPmzJmjbt26+WIoAACAEpG9DHL6d/vzDXqG6VFH1/e6w5Go5lm7vPVUo6Jm2Xprtq2nTlkqFnr8sW3rqvsVVXmnDkCR+STsPfDAA1qzZo369Omjq6++WoZhaO7cuZo9e7a+/PJL2Ww23Xfffb4YCgAAoFgVdMmm1XSrW8Y6jXbMVSP3fm/9mCVK79n6KtHWTU7DVqQ5JDSvoZf7XEnAA3BJfBL2qlevro8//lhPPfWUvvjiC5mmqSVLlkiSWrZsqSeffFKxsbG+GAoAAOCS5LVxiaSL7qiZLdjMVJ/0LzTKMV+xniPe+kFLNb1jH6CFYdfJZYQUaW4s1wTgSz4Je5IUGxurGTNm6NSpU/rtt99kmqZq1aqlmJgYXw0BAABQaOcfjbBy13Et3HY0xxO7SFuQTBlKdWbm24/NTFeCc7mGOz9VNU+yt77bWkcz7AO0LLSD3Ia1wPPKbydNAPAFn4W9bJUqVcp3Z04AAICSUNDlmCnOrAtek6RKnjO6xblYQ52LFGme9tZ/Cmqot+0J+iqktUzDUqA5XXdZtB7s0EAx4QQ7AMWvSGGvKOflGYahp59+uijDAQAAFEhBDjgvqGhPioY5PtPN6UtVwTwXFjcGN9Pb9gR9G9xCMgoW1lieCcAfihT2EhMTC30PYQ8AABSXwp6Dl58a7mO63TFf/dNXKUwub/3LkNaabh+oH4OvKFA/PMUD4G9FCntffPGFr+cBAABQJAU+B+8i6mX9rlGOueqZsUbBcp/tWxYtD22nGfYB2hVUr0D98BQPQGlRpLBXq1YtX88DAACgSCav3XtJQa9J5q8a7ZirLq4NssiUJGUqSJ+GXad37P110FrzgveyyQqA0qxIYW/RokVq2bKlN/QtWrSoQPf17t27KMMBAADkyZXl0Utr9hTp3paubRrjSFT7zC3emlMhSrR11/u2vjpqvfCO4qNax2p0mziCHYBSrUhhb8KECZo0aZI37E2YMEFGPi8om6YpwzAIewAAwCey39F78as9Onomo+A3mqbaubZojCNRrbK2e8unjHB9ZOupWbbeSrFUzreLhOY19ObAFoQ8AKVekcLes88+q6uuusr788SJE/MNewAAAL5SlHf0LKZb17u+1RhHoppk7fXWk4zK+sDeRx+H3agzlvB8++BdPABlTZHCXr9+/XL83L9//3zbZ2Vl6dChQ0UZCgAAQNK5YxWmf7e/wEEvyMxSz4w1GuWYq/ruc/8WOWyJ0Tv2/loQ1lXpRugF72dHTQBlmU8OVW/cuLEmTZqkXr165Xn9008/1bPPPqvNmzf7YjgAAFCOFOVYhVAzQ/3TV+p2xwLV9Bz31vdZa+kdW38tCuukLCNYkhRpC5JkKMWZ6W3HUzwAgaBIYe/o0aPauHGj92fTNLVlyxaZppmrrcfj0ZIlS+TxeIo+SwAAUC4VdslmuMehwenLNNzxqaLNk976jqB6mmZP0KqQa1U7Mlx3N62uGy6v6n1iJ0mbDqYq2eFiR00AAaNIYS8iIkKvvPKKDh8++xevYRj66KOP9NFHH+Vqmx0Ab7rppkuYJgAAKI8KeqxChOeUhjo/0y3OJapspnnrPwRdobftgxTc5AY92PEy/TOf5Zht4iJ9OncA8Lcihb3Q0FBNnTpVO3fulGmaevzxxzVo0KAcm7Zks1gsiomJ0TXXXHPJkwUAAOWH22Nqyrp9+bap6k7ScOenSnAul13nduVcH3yV3rYn6FB0K43v2IDlmADKpSK/s9ekSRM1adJEkvT9999rwIABatGihc8mBgAAyo/szVfOX0b53YGUC76jF+v+QyMd89U3fbWClSVJ8sjQqpBrNd0+UNuDL1P1iqH67YkuCgmylORHAYBSwycbtDz77LO+6AYAAJQT2eHu+JkMrdx1XAu3Hc0R7CJtQXK5c+8F0DDrN412zFX3jHWy6ux+AFmyaEloR82wD9TeoFhv2/EdGxD0AJRrPgl7krR371599tlnOnHihNxud67rhmFo4sSJvhoOAACUQQXdWTPFmZXj52aZOzXGkajrXOc2iMtQsBaEddE79v76w1otR/uE5jU0rkN9304eAMoYn4S9NWvW6J577skz5GUj7AEAUL4V+jB001TrzK26w5GoazK3estphk1zwm7UB/Y+SrLk3FSFIxMA4ByfhL3XXntNFSpU0JNPPqlmzZopJCTEF90CAIAAUtCdNQ3To46u7zXGkagWWbu89VSjombZemu2rZdOWSrkuGdU61iNbhPHkQkAcB6fhL1ffvlF9913n3r06OGL7gAAQIApyM6aVtOtbhnrNNoxV43c+731Y5YovWfrq0RbNzkNW677EprX0JsDWxDyAOBPfBL2wsPDFR4e7ouuAABAANp0MPWC7+gFm5nqk/6FRjnmK9ZzxFs/aKmuGfb++izsOrmM3KuGqlYI0YROl7FkEwAuwCdhr1OnTvr888916623+qI7AABQhuR1bIKkHLVjZzJy3WcznUpwrtBw56eq5kn21ndb62iaPUErQtvJbVgvOO784Vfrr/WifP55ACBQ+CTs3XnnnRo1apTuv/9+9ezZU9HR0bJYcm913LJlS18MBwAA/KggxyaYMpTqzPTWzn/wVslzRkOcizXUuUgR5mlvfWtQI02zD9RXIa1lGvkfmRAXaVObuMh82wBAeeeTsNe9e3dJ0qFDh7Ry5coLttuxY4cvhgMAAH5Q1GMTJMljStGeFN3mWKib05cp3Dx3/7fBzTXNnqDvgptLRsGWY97Xth5LNwHgInwS9u69914ZBfzLGQAAlD2FPjbhPDXcx3S7Y776p69SmFze+lchV+tte4K2Bl9RqP44Qw8ACsYnYW/s2LG+6AYAAJRCbo+phxb+XOigVy/rd41yzFXPjDUK1tmzeN2yaHloO82wD9CuoHoXvDfSFiTJUMp5S0E5Qw8ACscnYa8gfvzxR7Vo0aKkhgMAAJcoe9nmf77eq4Mn0wt8X+PMPRrtSFRX1wZZZEqSMhWkhWHXaYa9vw5aa+a6p1qFEA1qUVM3XF5VMeF5b/LCGXoAUDg+CXtut1v/+c9/9NVXX8nhcMjj8eS4dvr0aTkcDt7ZAwCgDHB7TH23P0WPLt2hdfuSL37D/7R0bdMdjk/ULvMHb82hUM21ddP7tr46ao254L3TElqoV9PquepswgIAReeTsPfmm2/qrbfeUmhoqCpWrKgTJ06odu3aSk5OlsPhUFhYmO644w5fDAUAAC7Rn49KuKpWZf1w6OQFd9fMl2mqnWuLxjgS1Spru7d8ygjXbFtPfWjrrRRL5Yt2U6VCaFE/DgDgAnwS9pYsWaJGjRpp9uzZSk5O1g033KB3331XtWrV0qxZszRx4kRdeeWVvhgKAAAU0YV207RaDLk9ZqH6sphuXe/6VmMciWqStddbTzIq6wN7H80J66E0i71AfcVF2rzLNgEAvuOTsHfo0CE98MADqlChgvf/fvjhB8XGxuq2227Td999pw8++EBdu3b1xXAAAKCQ8ttNszBBL8jMUs+MNRrlmKv67kPe+mFLjN6x99eCsK5KNwr3lI5jFACgePgk7BmGocqVzy3RqFOnjnbt2uX9uW3btnr99dd9MRQAACiCyWv3FunYhGyhZob6p6/U7Y4Fquk57q3vs9bSdPtALQntoCwjuND9cowCABQfn4S92rVr69dff/X+HBsbmyPsmaapM2fO+GIoAABQSG6PqSnr9hXp3nCPQ4PTl2m441NFmye99e1B9TXNnqAvQq6Rx7DmuCevYxP+vFSUYxQAoPj5JOx17txZs2bNUlxcnAYOHKj4+HhNmjRJGzdu1GWXXaZ58+apVq1avhgKAAAU0qaDqQXfcOV/IjynNNT5mW5xLlFlM81b3xLUWG/bB2ldSEvJOBvS6kSEqU/T6vkem5C9CQzHKABAyfFJ2BszZoy+/vpr/fOf/1SPHj3Uv39/vfXWWxo+fLi3zRNPPOGLoQAAQCElO1wFblvVnaThzk+V4FwuuzK89a+DW2q6faA2h+TccG1s27p6uc+VeQa3Px+bwDEKAFCyfBL2KlWqpLlz52rNmjWqVKmSJOmjjz7Sm2++qdTUVHXu3FkDBw70xVAAAKCQouwhF20T6z6skY556pu+WsHKkiR5ZGhlyLWabk/QjuAGue5JaF7jgkEPAOB/Pgl7khQUFKTrr7/e+3NsbKyeeeYZX3UPAACKKD42QnUibHku5WyY9ZtGOebpxoyvZZVHkpQlixaHdtI79gHaGxSb6x7etwOAssEnYe/o0aMFaletWjVfDAcAAAqpT9NqmrL+N+/PzTJ3aowjUde5NnprGQrWvLCues/eT39Yc/83u13dSD3Xq4na1Ikk5AFAGeCTsNexY0cZxsX/0t+xY4cvhgMAAPlwe0xtOpiq42cytHLXcS3cdvTsUz3TVJvMrRrjSNQ1mVu97dMMm+aE3agP7H2UZMn9Xh1P8gCgbPJJ2Ovbt2+usJeVlaUTJ05oy5Ytio2NVUJCgi+GAgAAF+D2mJq8dq+mrNuXY8mmYXrUyfW97nAkqnnWuaORUo2KmmnrrY/DeytV4d56XrtrEvIAoOzxSdh77rnnLnjt4MGDuuWWW7wbtwAAAN9ze0wNmbU5x8HpVtOtbhnrNNoxV43c+731Y5YovWfrq0RbN41u11hHejflWAQACEA+26DlQmJjY3XLLbfonXfeUb9+/Yp7OAAAyqXJa/d6g16wmamb0ldrlGOe6niOeNsctFTTDPsALQy7XplGsCTps+1H9XKfKzkWAQACULGHPUmKiYnR/v37L94QAADkkv0O3oUOKG9eo5JeWrNHNjNdA50rNMK5QNU8yd77d1vraLp9oJaHtpfbsOboe3+KU5sOphL2ACAAFXvYy8jI0KeffqqYmJjiHgoAgIByoXfwrBZDbo/p/bmyeUY3OxZrqHORIs3T3vpPQQ31tj1BX4W0lmlYLjhOYQ5dBwCUHT4JeyNHjsyznp6erj179ujUqVO68847fTEUAADlQl7v4J1/TZKiPSm6zbFQN6cvU7h5Lgx+G9xc0+wJ+i64uVSA3bILcug6AKDs8UnY++abb/KsW61WVa1aVUOGDNG9997ri6EAAAh4bo+phxb+nGfQk6Qa7mMa6Ziv/ukrFapMb/3LkNaaZh+orcFXFHisuEib4mMjLnXKAIBSyCdh75dffvFFNwAAlAsXegfv+JkMffzdcX3x2xkdcbhz3Vc/66BGOuapZ8YaBevsdbcsWhbaXjPsA7Q7qG6h53Jf23rsvAkAAapENmgBAKA8u+Ah5//z53fw/qxJ5q8a7ZirLq4Nsuhsu0wFaWHYdZph76+D1ppFmldC8xoa16F+ke4FAJR+lxz2XC6XVq9erY0bN+ro0aNyu92KiYlRfHy8unTpogoVKkiS/vWvfykmJkZ33333JU8aAICy4EIbrOTVLi+tXD9rjCNR7TJ/8NYcClWirbs+sPXRUWvRNj+Li7Tpvrb1NK5DfZ7qAUAAu6Sw9/nnn+upp55SSkqKTDPnf6jmzZunZ599Vn/7298UHx+vTz75RE8++eQlTRYAgLLA7TH13f4UPbp0h9btS774DeczTbVzbdEYR6JaZW33lk8Z4frI1lOzbL2VYqlcqC6rVQjRoBY1dcPlVRUTzqHpAFBeFDnsJSYm6h//+IcqV66s22+/XW3btlW1atVkGIaOHTumb7/9Vp988on+/ve/KyYmRnFxcerbt68Ppw4AQOlS0Cd5ebGYbnVxbdAYR6IaZ+3z1pOMynrf3lcfh92oNIu90HOqXjFUvz3RRSFBFz56AQAQmIoU9vbv36+nn35aV111lV577TVFRUXluN6gQQNde+21GjlypIYPH66dO3fq4YcfVlAQrwgCAAJTfkcl5CfIzFLPjDUa5Zir+u5D3vphS4zesffX/LCuyjBCizyv8R0bEPQAoJwqUvr68MMPZbPZ9MYbbygiIuKC7dLT0/X7779LkjZt2qQ+ffoUaZIAAJR2k9fuLVTQCzUz1D99pW53LFBNz3Fvfa+1lmbYB2pJaAdlGcGXNCc2YAGA8q1IYW/9+vW66aab8g16kjRr1iyFhITohhtu0MaNG4syFAAApZ4ry6OX1uwpUNsKnjQNTl+m2xwLFW2e9Na3B9XXdPtArQq5Vh7Dmm8ff969888/swELAEAqYtj7448/1KhRo4u2u+yyyzR27FgFBQVp2bJlRRnqgkaMGKE6dero6aefzlH/6aef9MILL+jnn39WxYoVNWDAAN177725lpAuWrRIb731lg4ePKjY2Fjdeeed6t27d442LpdLr7/+uhYuXKiUlBQ1a9ZMjzzyiK688kqffhYAQNmU/Y7ei1/t0dEzGfm2jfSc1FDnIt3iXKJKZpq3vim4iabZE7Q+uKVkXDyYjW1bV5N6N9UPh07mOqcv+2c2YAEASEUMezabTS6X66Ltspdtzpo1S2FhYUUZKk9TpkzRhg0bVKdOnRz1PXv2aPjw4apdu7YefPBBHThwQG+++aaSk5P1z3/+09tu0aJFevjhh9W5c2fdeuutWr16tR5++GFZrVb16NHD2+5f//qX5s6dq1tvvVX16tXThx9+qNtuu00LFixQXFyczz4PAKDsKeg7etXcJzTc+akGOlfIrnOB8OvglppmT9CWkKYFHjOheQ293OdKWS2G2sRF5rj2558BAChS2IuLi9N3332noUOHFqj9t99+q7p16xZlqBxcLpdeeOEFzZw5M8/rU6ZMUVhYmGbNmqVKlSpJksLDw/X222/r9ttvV926dZWZmalJkyapXbt2euONN2QYhgYPHqxhw4bpxRdfVPfu3WWxWPTrr7/qk08+0UMPPaQ777xTknTjjTeqe/fumjp1qiZNmnTJnwcAUHZd7B29WPcfGuWYrz7pqxWsLEmSR4ZWhVyrafYE7QhuUOCxWJYJACiKIm3P1atXL61evVo//PDDRdt+//33Wr16da4lkoV18uRJ9e7dWzNnztTo0aNzXXe5XFq1apV69OjhDXqSdOutt8rj8WjFihWSpC1btujo0aMaPHiwjP8tl7FYLBoyZIgOHTqkH3/8UZK0bNkyGYahQYMGefuKiopS9+7dtWrVqgI92QQABIbsc/OW7Tiq7/anyOlyX/AdvYZZv+mFU5O0OPkeDUz/XMHKUpYs+jT0OvWNnKqHKj+aK+j9OcDVCLdqbNu6WjSytTaMbadfH7te4zs1IOgBAAqlSE/2+vXrpw8++EB33XWXnnnmGXXp0iXPdkuWLNFTTz2lunXrql+/fpc00dOnT8swDE2fPl3t27fX9OnTc1zfvXu3MjMz1aRJkxz1qlWrqkqVKtq2bZskafv2swfU/rld9s/bt2/XVVddpW3btqlmzZqKjMy5LKZp06b6+OOPtX//fjVs2PCSPhMAoHRye0xtOpiq42cytHLXcS3cdjTHuXkWQzpvPxRJUrPMnbrDkajOrnMbkmUoWPPCuuo9ez/9Ya3mrdeJCFOfptW9h5yf/87dqWN/qGlMqK5smvO/UwAAFFaRwp7dbtdrr72mUaNGaezYsYqNjVWrVq1UtWpVmaapY8eO6fvvv9cff/yhatWq6bXXXpPNZrukiVavXl1Lly6VxZL3w8hjx45JkqpVq5brWtWqVXXkyJF821WpUkWSdPjwYW+7qlWr5urr/HaEPQAo+7KDXbLDpcphwfrmt2RNXf9bvoeie4OeaapN5laNcSTqmsyt3utphk1zwm7UB/Y+SrKc+6Vhu7qReq5XE7WpE5nrKV32O3c7lOy7DwcAKNeKfMr5ZZddpsWLF2vy5MlavHixFixYkON6pUqVdMstt+jBBx9UxYoVL32iFzmQPS3t7M5meW0EExoaqjNnznjbBQUFKTg459lF2fc5nU5vu8qVK+fq68/tfGHHjh0+66ssy/4z5c8D/sT3sPxwe0zN3JaqWdtO6nBaVqHuNUyPOrk2aoxjrppn7fLWU42KmmnrrY9svXTKUsFbj7FZdXuzCA1rGiGr86h27Tx6wb75DsLf+A7C3/gO+k6Rw54kVaxYUf/4xz/06KOPaseOHTp69Ox/vKpVq6YrrrhCISEhPplkQZimme/17PfzCtruYi70hBEAUPq5PaYmfHVUK/adKdR9VtOt7hlfa7Rjrhq6D3jrRy1Res/WT3NtN8hp5FzJEmOzauWgOIUE8d8NAEDJuqSwly04OFjNmzf3RVdFZrfbJUkZGbnPOcrIyFCFChW87bKyspSVlZXjaWF6erok5WiXXTvfn9v5QuPGjX3WV1mW/dsb/jzgT3wPA5/bY+qhhT8XKugFm5nqk/6FRjnmK9ZzxFs/aKmuGfb+Whh2vTKN4DzvfeT6y9WiWcF33uQ7CH/jOwh/4zuY0+bNm4t8r0/CXmlQo0YNSefeyTvfsWPHFB8fn6Pd8ePHvf/7/Puy39OrXr26du/enWdf57cDAJQN2Qeg/+frvTp4Mvcv8/JiM51KcK7QCOenquo59y7dbmsdTbMnaEVoO7kN6wXvT2heQ+M61L/kuQMAUBQBE/YaNGig0NBQ/fLLLznqx44d0/Hjx727bWb/hmDHjh05wl72bxCaNj17uG2TJk301Vdf6dSpUzmOcti+fbvsdrvq1atXrJ8HAOA7BT0APVslzxnd4lysoc5FijRPe+tbgxrpbXuC1oRcLdO48LLM6hVDNb5jA87FAwD4VcC8QBAaGqqOHTtq8eLFOnXqlLf+4YcfymKx6MYbb5QktWrVStHR0Zo9e7a3jcfj0ezZsxUbG6tmzZpJkrp27SqPx6M5c+Z42yUnJ2v58uXq1q0b7+wBQBmRvWyzIEEv2pOiB8+8p5XJozTWMdsb9L4Nbq5Rlf+lIRGT9FVom4sGvd+e6MK5eAAAvwuYJ3uSNHbsWCUkJGjo0KG65ZZbtGfPHn344YcaMmSIYmNjJZ3d1fPBBx/U3//+d91zzz3q3LmzVq5cqU2bNunVV1/1hrgrrrhCN910kyZPnqzk5GTVqVNHs2bNkmmauvvuu/35MQEABVCYZZs13Ud1u2OB+qevVKgyvfUvQ1prmn2gtgZfUeBxx3dswGYsAIBSIaDCXqNGjTRjxgxNmjRJEydOVExMjO655x7dddddOdolJCTI4/HonXfe0bp16xQXF6dXXnlF3bt3z9Hu3//+t6Kjo/XZZ5/J6XSqWbNmmjRpkuLi4kryYwEACsHtMfXd/hQ9unSH1u3L/8y6+lkHNcoxVz0z1ihInrP3y6Jloe01wz5Au4PqFmps3tEDAJQmPg17R48e1Zdffqk//vhDAwYMkN1u1+HDh4tlp86dO3fmWY+Pj9fHH3980fsHDx6swYMH59smNDRUjz76qB599NEizREAUPyyD0U/fiZDK3cd18JtR/M9EF2SGmfu0RhHorq4Nsiis0fyZCpIn4Zdp3fs/XXQWjPf+60WQ27PuaN84iJtuq9tPd7RAwCUKj4Le++9955eeuklZWZmyjAMXXvttUpPT9c999yjQYMG6Z///KevhgIAlGNFCXfZWrl+1hhHotpl/uCtORSqRFt3vW/rq2PW6DzvqxMRpj5Nq+uGy6sqJjxEV9WqrB8OnVSyw6Uoe4jiYyMIeQCAUscnYW/VqlV67rnn1K5dO/Xo0UOPP/64JKlhw4Zq06aNPvnkEzVt2lSDBg3yxXAAgHIo+x28Kev2FTjcSZJMU+1cWzTGkahWWdu95VNGuD609dKHtt5KtZzbdTku0qZ7/lpXbetF6aQz84Jhrk1c5CV/JgAAipNPwt6MGTPUrFkzvf322zp58qS3Xrt2bb3zzjsaOnSo5syZQ9gDABRJYY9OkCSL6VYX1waNcSSqcdY+bz3JqKz37X31cdiNSrPYc9wztm1dvdznSp7SAQACgk/C3i+//KL7778/z+MILBaLevbsqZdfftkXQwEAyqHJa/cWOOgFmVnqmbFGoxxzVd99yFs/bInRO/b+mh/WVRlGaK77EprXIOgBAAKKT8KeYRj5njvncDhkmuYFrwMAcCFuj6kp6/ZdtF2omaH+6St1u2OBanqOe+t7rbU0wz5QS0I7KMsIznUfm6sAAAKVT8Je06ZNtWLFCg0fPjzXNZfLpc8++0yNGzf2xVAAgHJm08HUfN/Rq+BJ0+D0ZbrNsVDR5rlXCbYH1dc0e4K+CLlGHsOa570s2wQABDKfhL1Ro0bprrvu0gMPPKBu3bpJko4cOaLVq1frrbfe0q+//qrJkyf7YigAQDmT7HDlWY/0nNRQ5yLd4lyiSmaat745qIneDk/Q+uCWknHhEMeyTQBAoPNJ2OvUqZOeeOIJPf/88/r8888lybsjp2EYuvfee70hEACAwoiyh+T4uZr7hIY7P9VA5wrZleGtrwu+Sm/bB2lLSNN8+2PZJgCgvPDZOXvDhg1T165dtXz5cu3fv18ej0e1a9dW165dVbduXV8NAwAoZ+JjI1QnwiYzaY9GOearT/pqBStLkuSRoVUh12qaPUE7ghvk20+7upF6rlcTtakTScgDAJQLPgt7klS9enWNGDHCl10CAMoxt8fUlk3f6OW0l9Qw+XNZ5ZEkZcmiJaEdNcM+UHuDYvPtgyd5AIDyqkhhb8uWLUUarGXLlkW6DwBQPrg9pjYdTNXxMxn68dtVqrH5NV2T9q2u+N/1DAVrXlhXvWfvpz+s1fLso05EmPo0ra4bLq+qmPC8D0QHAKA8KFLYGzJkiIx8Xnq/kB07dhRlOABAgHN7TE1eu1dTvt6rmse/1RhHovpl/uS9fsaw6eOwG/WBvY+SLJE57iXcAQCQtyKFvXvvvbdIYQ8AgPO5Paa+25+ix5ZsU9DO5XrOMVfNs3Z5r6cYFTXTdpPm2HrqlKVCjntHtY7V6DZxhDsAAC6gSGFv7Nixvp4HAKAcyX6S99rXv6rJ0ZV60DFXjdz7vdePWqL0nq2f5tpukNOw5dnHqt0n9ObAFgQ9AAAuwKcbtDgcDn3zzTc6cOCArFar6tevr2uuuUbBwcG+HAYAUIa5PaaGfbBBWd9/qDcc8xXrOeK9dtBSXdPtA/RZ2HXKNPL/b8f+FKc2HUxVm7jIfNsBAFBe+SzszZkzRy+++KLS0tJkmqaks2fsRUZG6qmnntINN9zgq6EAAGWQ22Nq06+/a8v8yRqz8z1V8yR7r+2yxmm6faBWhLaT27AWuM8LHbgOAAB8FPaWLVump556SrVr19Z9992nevXqyePxaM+ePfrwww/10EMP6d1339XVV1/ti+EAAGWI22Nq6sofdGT5q+qdskAdzdPea1uDGulte4LWhFwt07AUuu8/H7gOAADO8UnYmz59uho2bKhPPvlENtu5dys6d+6sm2++WQkJCXrttdf03nvv+WI4AEAZkZFyWB+88qj+eiBR4abTW98Q3ELT7AO1Mbi5VMQNv+IibYqPjfDRTAEACDw+CXt79uzRuHHjcgS9bBUqVNDAgQP12muv+WIoAEAZ4Dr+m5KWTdKJr6arrfvcUsvVIa013T5QW4OvyOfugrmvbT02ZwEAIB8+CXuRkZE6efLkBa+7XC6Fh4f7YigAQCmW8ccOnVj8nE5u+FDyuGWV5JZFy0Pbabp9oHYH1fXJOAnNa2hch/o+6QsAgEDlk7A3ZMgQvfnmm+rSpYuaNm2a49rvv/+uDz/8UMOHD/fFUACAUsi5b7NOLJ6o05sXSP/bpCtTQVoYdp1m2PvroLWmT8aJi7Tpvrb1NK5DfZ7qAQBwET4Je1arVRERERo0aJA6duyohg0bKjg4WPv379fnn38uwzC0f/9+/eMf//DeYxiGnn76aV8MDwDwA9M05dj5tU4snqi0n1Z46y5LmD4K7ab3bX11zBp9SWPUiQhTn6bVdcPlVRUTHsIB6gAAFIJPwt4LL7zg/d+rV6/W6tWrc7WZO3dujp8JewBQNpmmqVP/Xar98/+loAPfnauHVdJ3tQfp4ZROSrVUuqQx2tWN1HO9mqhNnUjCHQAAReSTsPfFF1/4ohsAgJ+5PaY2HUxVssOlKHuId7fLTQdTlXzGqZh9K5T1xSRVTt7h/Q9IklFZs8L7aHZoD6WdtEuFP0HBi2WaAAD4jk/CXq1atXzRDQDAT9weU5PX7tWUdft0IPXcEQmRtiBZzSy1S12lUY55Cncf8l47bInRO/b+mh/WVRlG6CWNP6p1rEa3iWOZJgAAPuSTsCdJaWlp+umnn3T06FGZ/3s5/8/69u3rq+EAAD7i9pgaMmuzErcezlEPNTPUPXmxRjrmq4bnhLe+11pL79gHaHFoR2UZwZc8fkLzGnpzYAtCHgAAPuaTsPff//5X9957r5KTkyUpR9gzDEOmacowDMIeAJQybo+phxb+nCPoVfCkaXD6Mt3mWKho89yxOtuD6muaPUFfhFwjj2G95LGrVwzV+I4NWLIJAEAx8UnYe+655+RwOHTnnXeqbt26slgu4YUNAECxy162+Z+v9+rgyXRJUqTnpIY6F+kW5xJVMtO8bTcHNdHb4QlaH9xSMnwTyqpXDNVvT3RRSBD/vQAAoLj4JOzt3LlTd955p+666y5fdAcAKAbZm68cP5OhyV/v0+pfzy7NrOY+oRHOBRroXCGbXN72Xwe31DR7graENL1Ql0U2vmMDgh4AAMXMJ2EvIiJC4eHhvugKAOBjF9p8Jdb9h0Y55qtP+moFK0uS5JGhlSHXaro9QTuCGxTLfBKa19C4DvWLpW8AAHCOT8LegAEDNH/+fA0ePFghISG+6BIAcAku9BRPkhpl7dNox1x1y1gvqzySpCxZtDi0k2bYB2pfUO1imRPHKgAAULJ8Evbuvvtu/fjjj+rWrZs6duyomJiYXG0Mw9C9997ri+EAAOc5/2y8ymHB+ua3ZE1d/1uOp3iS1CLzF41xJKqT63tvLV0hmh/WRe/Z++kPa7VimR/HKgAA4B8+O1R9w4YNysrK0pw5c/JsQ9gDgILL93Dz/9WuqlVZU9bty7U8MwfT1DWZP2qMI1FtMn/yls8YNs0J66GZ9puUZIksts/BsQoAAPiPT8Lef/7zH1WsWFH333+/GjRoIKv10rfkBoDyKL/DzU0ZSnVmemv2YKscme48+zFMjzq5NmqMY66aZ+3y1lOMipppu0lzbD11ylLBZ/O2Wgy5PeeO3WHJJgAA/ueTsHfgwAE99NBDuuWWW3zRHQCUSxc63FySUpxZuWp5BT2r6Vb3jK812jFXDd0HvPWjlii9Z+unubYb5DRsBZ5TpC1IkqGU80JmXKRN9/y1rtrWi9JJZ6b3KeMPh07meBJJyAMAwL98EvaqV6+e4yB1AEDhTV67N8+gVxDBZqb6pH+hUY75ivUc8dYPWqprun2APgu7TplGcKH6HNu2rl7uc6Uk5VpSmleQaxNXfMtBAQBA4fkk7N1yyy368MMP1bt37zw3ZwEAXJjbY+q7/Sl64ctfC32vzXQqwblCI5yfqqon2VvfZY3TNPtAfR7aTm6j8EvrE5rX0Mt9rvSGOoIcAABlj0/CnmEYcrvd6tq1q1q1aqUqVaooKCgoV5unn37aF8MBQEC40Pt5BVHJc1pDnEs01LlIEeZpb31rUCO9bU/QmpCrZRqFP7Scd+0AAAgcPgl7zz33nPd/r1u3Ls82hD0AOCe/9/PyE+NO1m3OhRqcvlzh5rmAuCG4habZB2pjcHPJKFxIu+6yaD3YoYFiwnnXDgCAQOKzoxcAAAVX2PfzarqPaqRjvvqlr1Kozm2WsjqktabbB2pr8BWFngNP8QAACGw+CXu1atXyRTcAUC64PaamrNtXoLb1sw5qlGOuemasUZA8Z++XRctC22uGfYB2B9Ut1Ng8xQMAoPzwSdiTJI/Ho507dyotLS3HzpxZWVk6c+aM1q1bp3/+85++Gg4AyqxNB1Mv+o5ek8xfNcaRqOtd38qis3+nZipIn4Zdp3fs/XXQWrNQY/IUDwCA8sdn5+yNGDFChw/nvySJsAcAUrLDlfcF01SrzG0a40hUu8wfvGWHQpVo6673bX11zBqd67Y/H66e1zl4PMUDAKD88UnYe+WVV3T48GH16NFDYWFhmjdvnu655x4lJSVp+fLlysjI0Jw5c3wxFACUWW6PqU0HU/XLsTM5L5im2rs2a4wjUS2zdnjLJ41wfWTrqVm2m2SER0kypD8dbn5f23oa264eB5oDAIBcfBL2Nm7cqF69emnSpEk6ffq05s2bp3bt2qlly5YaPXq0BgwYoGXLlumKKwq/gQAAlHUXOmLBYrrVxbVBYxyJapx17h2+E0aE3rf30SdhNyq8UoQWj7habeqcPefuQoebcw4eAAD4M5+EvZMnTyo+Pl6SVLFiRVWvXl3btm1Ty5YtFRsbqwEDBmj16tV68MEHfTEcAJRq2U/wkh0uVQ4L1uSv92rueTtvBpmZ6pWxRqMc81TPfchbP2Spqnft/bQgrIsyjFBJ0lOdLtNf60Z52xDqAABAQfkk7IWHh8vtPve+SO3atbV7927vzw0aNFBiYqIvhgKAUuP8UBdlD9FVtSpryrp9FzwkPczMUP/0lbrdMV81PCe89b3WWppuH6iloR2VZZz7azmheQ2N61C/RD4LAAAIPD4Je1dccYW+/PJLDRkyRJJUr149/fjjj97rhw4dktVq9cVQAOB3F1qW+eeNUrJV8KRpcPoy3eZYqGjzpLe+Pai+3rYP0uqQNvIY5/6OZOdMAADgCz4Je4MGDdL48eN18803a9q0aerWrZsSExP12GOPqWHDhpo5c6aaN2/ui6EAwK/cHlNDZm3O80D0Pwe9SM9JDXUu0i3OJapkpnnrm4KbaJo9QeuDW0rGuTD3cu8murZuFBusAAAAn/BJ2OvZs6cOHz6s6dOnKywsTO3atVP37t21YMECSVLlypU1fvx4XwwFAH41ee3ePIPe+aq5T2iEc4EGOlfIpnPHLKwNaaXptoHaEtI0z/sur1qBd/IAAIDP+OxQ9dGjR2vkyJGyWCySpMmTJ2vTpk1KTU1Vy5YtFRUVdZEeAKB0c3tMTVm374LX62T9oZHO+eqTvlrBypIkeWTo89C/arptoH4JbpBv/1H2EJ/OFwAAlG8+C3uSvEEvW/YOnQBQlmVvxPLNb8l5brzSKGufRjvmqlvGelnlkSRlyqoloR01wz5Q+4JqX3SMuEib4mMjfD11AABQjl1S2Dt8+LC2bNminj17emunTp3Sa6+9pu+++05hYWG68cYbNXToUDZoAVAq/HkHzez347LrPx5MU+VQqxpdbkpSnhuxZGuR+YvGOBLVyfW9t5ahYM0L66p37f112Fq1wPO6r2093tMDAAA+VeSw99577+nFF1+Ux+NRjx49ZBiGXC6Xhg0bpl27dslqtSoiIkLPPvusvvnmG7311lu+nDcAFMqFdtCsExGm5jUqa+vhUznqj3x9QhG2EG09fCpnR6apazJ/1B2ORLXO/MlbTjNs+iish2bab1KSpXDv3XHEAgAAKA5FCnubNm3Sc889p7p162rYsGHe+syZM7Vz507Vrl1bs2bNUvXq1bV8+XI99NBDmjdvngYMGOCziQNAQeW3g+aB1HQdSE2/aN0wPers2qgxjkQ1yzp3jmiKUVEzbTdpjq2nTlkqFGpeHLEAAACKU5HCXnaQmz9/vux2u7f+6aefyjAM3XfffapevbokqXv37lqyZIk+/fRTwh4AvyjIDpoXYjXd6p7xtUY75qqh+4C3ftQSpfds/TTX1k1OI6xAfQ1sVl3jOjbQSWdmjiWkAAAAxaFIYe+HH35Q//79cwS9Y8eOaffu3QoKClKXLl1ytG/durWmTp16aTMFgAI6/728ymHB+e6geSEhpkt90ldrpGOeYj1HvfWDluqabh+gz8KuU6YRnOe9fz5cnSd4AADAH4oU9pKTk1WrVq0ctU2bNkmSmjZtqgoVci5lstvtcjgcRZwiABTMhd7LKwyb6dQg53INdy5UVU+yt77LGqdp9oH6PLSd3EbeG05lh7qx7erph0Mnc20CAwAAUJKKFPbsdrvOnDmTo/b999/LMAy1bt06V/s//vhDERERRZogABREfu/lFUQlz2kNcS7RUOciRZinvfUfgxrpbfsgrQ2Jl2lY8rz35d5NdG3dqByhjsPRAQCAvxUp7DVq1EibNm3SiBEjJEkej0dffPGFJKl9+/Y52pqmqRUrVujyyy+/tJkCQD6K+l5ejDtZtzkXanD6coWb554GbghuoWn2gdoY3FwyLvxULi7SprHtWZ4JAABKnyKFvZtuuklPPvmk3n33XXXs2FGzZ8/WsWPHFBcXp6uvvtrbzjRNTZo0SXv27NHtt9/us0kDwPncHrPQ7+XVch/R7Y4F6pe+SqHK9NZXh7TWdPtAbQ2+okD9cD4eAAAorYoU9gYMGKDVq1fr+eef1wsvvCDTNGWz2fT888/L+N9vwD/++GO99dZbOnz4sFq2bKn+/fv7dOIAkG3TwdQCv6NXP+ugRjvmqkfGGgXJI0lyy6Jloe013T5QvwbFFXhczscDAAClWZHCnsVi0euvv67ly5dr8+bNCg8P14ABA1SnTh1vmz/++ENJSUkaNGiQHnnkEW8IBABfS3a4LtqmaeZujXbM1fWub2WRKUlyKUifhl2vd+39ddBaI8/7mteoqJPpWdqfci5MsrsmAAAoC4oU9iTJMAzdeOONuvHGG/O8ftddd+mBBx6QxZL3hgbFacOGDXr55Ze1c+dOxcTEqF+/frrzzjsVEhLibbNu3TpNnjxZv/76q2JiYjRs2DANHz48V1/vv/++PvzwQx09elSXXXaZHnzwQbVr164kPw6Ai4iyh+R9wTQVn7lNYxyJapv5g7fsUKgSbd31vq2vwqJrqUWNyrIcOXXBQCfJe5QDu2sCAICyoshh72JsNltxdZ2v9evX64477lC1atV0//336+TJk3rrrbe0bds2vfnmm5KkjRs36s4779Rf/vIXTZgwQf/97381ceJEZWRk6I477vD29eabb+qVV15R37599Ze//EWffvqp7rzzTn3wwQdq1aqVXz4fgNziYyNUJ8J2bimnaaqDa5PGOBJ1VdYv3nYnjXAtieyrnqOfVCdLJfU/L7hln8334849qhxq1cD2f8kR6NhdEwAAlDXFFvb85ZlnnpHNZtOcOXNUtWpVSVLDhg01YcIErVy5Ul27dtWkSZNUv359vfvuuwoJCdGtt94q0zT1xhtv6Oabb1alSpWUkpKiN954Q4MHD9bTTz8tSerXr5/69Omjl156SbNnz/bnxwTKtfMPTc9+0ja2XT09sugndc3YoDGORF3hPrdhywkjQu/b++iTsBv11E3xurZpg1x9Wi2G2sRFqpIj3PszAABAWRZQYe/333/Xnj17NGLECG/Qk6TevXvr2Wef1cKFC9W4cWNt3bpVjz76aI5lnUOHDtWiRYu0du1a9erVS19++aXS09M1ePBgb5uwsDANGDBAL730ko4ePapq1aqV6OcDAkVeYe38cHWh6xc6NL1BRJCervpffZn2pqKdB7z1PyxV9I69vxaEdVGGEcqGKgAAoFwJqLB39OhRSdJll12Wo24YhmrXrq0dO3Zo+/btkqQmTZrkaJP987Zt29SrVy9t375dVqs11/mA2e127NhB2AMK6UJhLfv9uLHt6mnKun15Xr/nr3X1/cFUzT3vLL0wM0MDnJ/r9qQFqr77hLd+MDhWb4T119LQjsoygthQBQAAlEsBFfbsdrskKS0tLde1kydPKikpSceOHZOkXEEtJCREEREROnLkiCTp2LFjio6OVlBQzj+iKlWqSJIOHy784c0XsmPHDp/1VZY5nWf/cc+fR2Bye0xN+OqoVuw7k+va/hSnJizerhe/3KWjaVl5Xn9kybnvRQVPmm5OX6phjs8UbZ701rcFNdCx5rer43U36ZbkLPXIcKtyqFVNY0Jltbi0a+cvufr+M76H8De+g/A3voPwN76DvhNQYa9Bgway2+1atWqVRowY4a3v2bNHBw8elHQuCOa1gUxoaKj3y5WWlpZnm7CwMEnnvoQACmbmttQ8g9758gp654v0nNRQ5yLd4lyiSua5X+psCm6it+2D9E3wVaqZEqyOFquaVw2ov94AAAAKLaD+NRQSEqKhQ4fq7bff1pNPPqnbbrtNKSkpeuqpp1ShQgU5nU6ZpplvH9nnAV6snS+PlGjcuLHP+irLsn97w59H4HF7TH0874si31/dfVzDnZ9qoHOFbDp3pt7XwS01zZ6gLSFNvbU/zmQprUKNIu+eyfcQ/sZ3EP7GdxD+xncwp82bNxf53oAKe5J0//33KykpSXPmzNGcOXMUFBSkoUOH6tixY9q4caN3qWd6enquezMyMlShQgVJZ5eE5tUmuxYeHl6MnwIILJsOpuZ4B6+g6mT9oVHOebop/UsF6+xTP48MrQy5VtPsCfolOPeumlLBDlkHAAAIdAEX9oKDgzVx4kTdf//9+v3331WvXj1FR0fr5ptvVu3atVWjRg1J0vHjxxUXF+e9z+VyKTU11buLZ/Xq1fXVV1/J4/HkeIqX/c7f+bt9AshfYcNXo6x9Gu2Yq24Z62WVR5KUKasWh3bSO/YB2hdUO9/7L3jIOgAAQDkScGFv8eLFqlGjhlq1aqXq1atLOvt+3Y4dOzRkyBDv4+AdO3YoPj7ee1/2Lp1Nm55dDtakSRNlZmZq9+7dOXbkzH6snN0OwMUVNHy1yPxFYxyJ6uT63lvLULDmhXXVu/b+Omy9+C9Z4iJtio+NKOpUAQAAAobvXjwrJd555x09//zzOd65mzZtmlwulxISElS7dm01bdpUiYmJyszM9LaZNWuWwsPD1aFDB0lSp06dFBISog8//NDbJj09XfPmzVPr1q0VExNTch8KKOPiYyNUJyL3hkeSJNPUta4f9E7qE/ow9W/eoHfGsGmGrb9uiJ6uiRXvKlDQk6T72tbjeAUAAAAF4JO9kSNHavz48XrggQfUrl07/fzzz/r44491xx13qH79s4cpjx8/XqNHj9btt9+um266SZs2bdKiRYv0yCOPeN/Zi4qK0qhRo/TGG28oKytLLVq00IIFC3To0CE999xz/vyIQJljtRga266eJize7q0ZpkedXRs1xpGoZlm7vfUUo6Jm2m7SHFtPnbJUKNQ4HJoOAABwTsCFvV69eikzM1MzZszQ2rVrVbNmTf3f//2fhgwZ4m3Ttm1bTZkyRa+++qr+9a9/qWbNmvr73/+uYcOG5ejr/vvvV2hoqD7++GMtWbJEjRo10rRp03TVVVeV9McCyrxxHepr44EUzf/xd92YsVajHXN1mfug9/pRS5Q+jUrQdF0vpxGWZx8Dm1VX6zqReu2b37Q/Jfeh7ByaDgAAcE7AhT1J6tevn/r165dvmy5duqhLly75trFYLLr77rt19913+3J6QEBze0xtOpiqZIdLUfYQxcdGyGoxZGRl6PVa32vCd8/KfuZcyDtgqa5PY27R5d1Ha1LHK1Rn3T5NXb8v3zD3YMcGeY4BAACAcwIy7AEoeW6Pqclr92rKun05jlm4vLL078hvdOXu9+VOPSx7dvuqjZV8zf2KvGqAXqsb4w1r4zs10LgO9fMNc1aLUeRz9AAAAMoLwh6AS+b2mBoya7MStx721ip5TutW52INPbFIlc0zcv+vbmvQRjG9n1CFFj1lWPLeI4owBwAAcOkIewAu2eS1e71BL8adrOHOhRqUvlzh5rknfBuCW8hy/cMacfOtMgyWXAIAABQ3wh6AS+L2mJqybp9quY9opGO++qZ/oVCdO9bki5A2mm4fqJ+CL1fcXptuMyUrWQ8AAKDYEfYAXJItm7/VXQcmqkfGGgXJI0lyy6Jloe013T5QvwbFedvuT3Fq08FUlmgCAACUAMIegCJx7tukE4smKnzzAt30v5pLQfo0rIvetffTQWuNPO9LdrhKbpIAAADlGGEPQIGZpinHzrU6sWii0n7+3Ft3KFSf2LrrA1tfHbNG59tHlD2kuKcJAAAAEfYAFIBpmjqzdZlOLJoo5+713rrFHqHILmN1888t9PPpi4e4uEib4mMjinGmAAAAyEbYA3BBpsetU9/P04nFE5Vx4Edv3Vq5mqK7PaTI6+6S1VZJw6P3aMLi7Rft77629Tj8HAAAoIQQ9gDkYma5lPrNLCUtfk6uo7u99eCYOEX3+Jsi2t8uS4jNWx/Xob42HkjJcc7enyU0r6FxHeoX67wBAABwDmEPgJcnw6GUNdOVtGySspJ/99ZDalyumF6PqfI1Q2QEBee6z2oxNHtoK7Veu1dT1+/T/pRz5+vFRdp0X9t6GtehPk/1AAAAShBhD4DcjpNK+eJ1Ja14Re7Tx731sLirFNP7CVVs1VeGxZpvH1aLofGdGmhch/radDBVyQ6Xouwhio+NIOQBAAD4AWEPKMeyTh1X8ueTlbxqqjzOU966vVF7xfR+XOHNuskwChfUrBaDc/QAAABKAcIeUA5lJh1U0vKXlPLV2zJd55ZchjfrfjbkXd4+z/vcHpOndgAAAGUEYQ8oRzKO7FbSkueVuv4DyZ15tmgYymzSWyeuvk8V6serdh5HI7g9piav3asp6/bpQCrv4wEAAJQFhD2gHEg/8KNOLH5WpzYmSqbnbNEapN/r9dHTmT30zbEq0pJ0SetyBTi3x9SQWZvz3Glzf4pTExZv18YDKZo9tBWBDwAAoBQh7AEBzPHrBp347Bmd+XGJt2YEh6lyh1F6ytlN03fnvufPAW7y2r35HqkgSYlbD6v12r0a36mBrz8CAAAAioiwBwQY0zSVtm2VTiyaKMcvX3nrlrCKirz+XkV3G6dXfzij6Rc5BD1x62HFr9mj19b/VqBxp67fx3JOAACAUoSwBwQI0+PR6S0LdWLxRKXv2+StWytEK6rbg4q6/l5ZwyPk9piasu6nAvX5ytq9OnI6o0Bt96c4telgKjtxAgAAlBKEPaCMM91ZOvntHCUtflYZf5x7WhcUWUvR3ccrsvMdsoSGe+ubDqbm2GQlPwUNetmSHa5CtQcAAEDxIewBZZTHla7Ude8paekLyjy+z1sPrtpAUT0e0a91emuPy1DUEZfiY+3e5ZXFGcii7CHF1jcAAAAKh7AHlDGe9DNKXv2mkpe/pKyTR7z10NrNFNXrMb3rbKn/rD+oA0u+9147f4fNwgay6hVDC/SELy7Spvg8jm0AAACAfxD2gDLCfSZZySunKGnlq/KkpXjrtgZtFNP7Cdma9dCts39Q4tZdue49f4fNmUNaqk6ErUBLOeMibbr3r3X1tyU7Ltr2vrb12JwFAACgFCHsAaVcRvIf2jH3WQVtfEeWTIe3Ht7kesX0flz2xp1lGIZe+mpPwY5IqLNPY9vV04SL7MYpyfs08PuDqfn2ndC8hsZ1qF/wDwUAAIBiR9gDSinn0b1aM+Mfqr4rUSFmpre+IfyvMjs/pNsH9Pc+STu7w+a+C3WVw9T1+7Tzkeu08UBKgQKc1WJo9tBWar12r6au36f9KeeeCP75AHYAAACUHoQ9oIS4PaY2HUxVssOlKHuI4mMj8gxIGYe26/ji55S6YbbqmO6z98qiZaHtNd0+UL8GxUnfSSudmzV7aCtZLUahdtjcn+LUD4dOFirAWS2GxndqoHEd6hfoMwAAAMD/CHtAMXN7TE1eu1dT1u3LEcj+HKqc+zbpxKKJOr15gSTJIsmlIH0adr3etffXQWuNHP0mbj2s1mv3anynBoXeYTPZ4SpSgLNaDM7RAwAAKCMIe0AxcntMDZm1Oc/lkvtTnJqwaJuO/rhK92TMl2Pb595r6UaY5oR10we2vjpmjb5g/1PX7yvSDpvntyfAAQAABCbCHlCMJq/dm/d7caap9q7NGuNIVMsTO5S97YrFHiFn6zHq8lMLpVoqXbT//SlObTqYqvjYiELtsMkRCQAAAIGPsAcUk7w2TbGYbnXN2KAxjkRd4T53LcUaqYb9H1H09Xfr89+cSt22scDjZC/JLMwOm7xnBwAAEPgIe0AxOX/TlCAzU70y1miUY57quQ952xyyVNU79v76NOx6fdXselW1VVKU3V2ocbKXZI7rUL/AO2wCAAAg8BH2gGKS7HApzMxQ//SVut0xXzU8J7zX9lpra7p9oJaGdlCWEeRtL6nISzI5IgEAAADnI+wBxcDtOKnqm17TiqT/KNo86a1vC2qgafYEfRFyjUzDkuOe7Cd0l7IkkyMSAAAAkI2wB/hQ1qnjSv58spJXTVWo85RC/1f/PripptkT9E3wVZKRO3T9edOUS12SyQ6bAAAAIOwBPpCZdFBJy19Syldvy3SdWz55rHYnjT/TXT8EN8n3/rye0LEkEwAAAJeCsAdcgowju5W05Hmlrv9AcmeeLRqGKsUPVHTvx3R57F902azN+qEIT+hYkgkAAIBLQdgDiiD9wI86sfhZndqYKJmes0VrkCL+OkzRPR9RaI3LvW0v9QkdSzIBAABQFIQ9oBAcv27QiUUTdea/i701IzhMkZ3GKPrGhxUcXSfXPTyhAwAAgD8Q9oCLME1TadtW6cSiiXL88pW3bgmrqMjr71V0t3EKqlztov3whA4AAAAlibAHXIDp8ej0loU6sXii0vdt8tatFWMUdcM4RV1/r6zhEf6bIAAAAJAPwh7wJ6Y7Sye/naOkxc8q449zZ90FRdZS9I0PK7LTGFlCw/04QwAAAODiCHvA/3hc6Upd956Slr6gzOP7vPXgqg0U0/NRVW47TJbg0Hx6AAAAAEoPwh7KPU/6GSWvflPJy19S1skj3npo7WaK6f24Kl09UIaV/1cBAABA2cK/YFFuuc8kK3nlFCWtfFWetBRv3dagjWJ6P6EKf+klw2C3TAAAAJRNhD2UO5mph5W8/GUlr35DZkaatx7etItiej8u+xWdCHkAAAAo8wh7KDdcx/cpackLSl33rszMDG+9Ysu+iun1mGwNWvtxdgAAAIBvEfYQ8DIObdeJxc/q5LcfSR732aJhUeVrblF0r0cVVvtK/04QAAAAKAaEPQQs597vdWLxszq9eYG3ZgSFKKL97Yq+cYJCqjXw4+wAAACA4kXYQ0AxTVOOX9boxKKJStu20ls3QuyKvO4uRXd7SMFRtfw4QwAAAKBkEPYQEEzT1Jkfl+rEooly/vqNt26xRyiq6/2KuuF+BVWI9uMMAQAAgJJF2EOZZnrcOvX9XJ1YNFEZB7d669bK1RTd7SFFXneXrLZKfpwhAAAA4B+EPZRJZpZLqetnKmnJ83Id3e2tB8fEKbrH3xTR/nZZQmx+nCEAAADgX4Q9lCmeDIdS1kxX0rJJykr+3VsPqXGFYno9psrX3CIjKNiPMwQAAABKB8IeygR3WqqSV7+u5BWvyH36hLceFtdSMb0fV8VW/WRYLH6cIQAAAFC6EPZQqmWdOqbkz19V8qqp8jhPeev2yzsopvfjCr/yBhmG4ccZAgAAAKUTYQ+lUmbSQSUte1Epa6bJdDm99QrNb1RM78dlb9TOj7MDAAAASj/CHkoVM/k3/THjJaWu/0ByZ54tGoYqxQ9UdO/HZIu7yr8TBAAAAMoIwh5KhfQDP8pc+Jj0ywqlmp6zRWuQIv46TNE9H1Fojcv9O0EAAACgjCHswa8cv27Qic+e0Zkfl3hrRnCYIjqOVkyPCQqOruPH2QEAAABlF2EPJc40TaVtW6UTiybK8ctX5y6EhEstb1HDIf9WUOVqfpsfAAAAEAgIeygxpsej01sW6sTiiUrft8lbt1aIVlS3B3U8touMsEoEPQAAAMAHCHsodqY7Sye/naOkxc8q44/t3npQZC1F3/iwIjuNkSU0XCd27PDjLAEAAIDAEpCnUG/dulXDhg1TixYtdPXVV+uhhx7SsWPHcrT56aefNGzYMF111VXq0KGDXn31VWVlZeXqa9GiRerVq5datGihXr16adGiRSX1Mco8jytdyavf1K+PNNIfbw/zBr3gqg1U4/ZpumzSHkV3GydLaLifZwoAAAAEnoB7snfo0CGNGDFCFSpU0Lhx45SWlqYZM2Zo27ZtWrhwocLCwrRnzx4NHz5ctWvX1oMPPqgDBw7ozTffVHJysv75z396+1q0aJEefvhhde7cWbfeeqtWr16thx9+WFarVT169PDjpyzdPOlnlLz6TSUvf0lZJ49466G1r1RMr8dVqXWCDGvAffUAAACAUiXg/sX9/vvvy+l0KjExUQ0aNJAkNWzYUPfff78WLVqkhIQETZkyRWFhYZo1a5YqVaokSQoPD9fbb7+t22+/XXXr1lVmZqYmTZqkdu3a6Y033pBhGBo8eLCGDRumF198Ud27d5fFEpAPRovMfSZZySunKGnlq/KkpXjrtgZtFNP7CVVo0VMGf2YAAABAiQi4f3nv27dP1apV8wY9SWrXrp0kadeuXXK5XFq1apV69OjhDXqSdOutt8rj8WjFihWSpC1btujo0aMaPHiwDMOQJFksFg0ZMkSHDh3Sjz/+WIKfqnTLTD2so3MmaNdDdXT806e8QS+8aRfFPbpadf+xQRWv6k3QAwAAAEpQwD3Zi42N1YYNG3T69GlVrFhRkvT7779LkqpUqaLdu3crMzNTTZo0yXFf1apVVaVKFW3btk2StH372ffL/twu++ft27frqquuKtbPUtq5ju9T0pIXlLruXZmZGd56xZZ9FdPrMdkatPbj7AAAAIDyLeDC3ujRo/XFF1/o4Ycf1oQJE5Senq4nn3xS0dHR6tevn37++WdJUrVqubf3r1q1qo4cOfuOWfaGLn9uV6VKFUnS4cOHi/NjlGoZh7brxOLndPLb2ZLHfbZoWFT5mlsU3etRhdW+0r8TBAAAABB4Ya9mzZoaPXq0Jk6cqK+++kqSZLPZ9N5776lKlSpKS0uTJIWFheW6NzQ0VGfOnJEkpaWlKSgoSMHBwTnaZN/ndDp9NucdZeTIAfPwz9KGt6Vdq84VrcFSs35Sm5E6FVlHp05LKuLnyf4zLSt/HghMfA/hb3wH4W98B+FvfAd9J+DC3ssvv6y33npL7dq104ABA+RwOPTuu+9q1KhReu+992SaZr73Z7+fV9B2gc40TengprMhb9/6cxeCbdJfBkmtb5dRsar/JggAAAAgTwEV9k6dOqV3331XrVq10vTp072BrHv37urRo4eefvpp3XXXXZKkjIyMXPdnZGSoQoUKkiS73a6srCxlZWUpKOjcH1N6erokedv5QuPGjX3Wl6+YpqkzPy7ViUUT5fz1G2/dYo9QVNf7FXXD/QqqEO3TMbN/e1Ma/zxQfvA9hL/xHYS/8R2Ev/EdzGnz5s1Fvjegwt5vv/0ml8ulnj175njyVqFCBV1//fX66KOPFBUVJUm5DlnPrsXHx0uSatSoIUk6fvy493+ff1/VqoH5NMv0uHXq+7k6sfhZZRw4t+OotXI1RXcfr8jOd8lqq+jHGQIAAAAoiIAKeyEhIZIkj8eT65rb7ZZpmrriiisUGhqqX375Jcf1Y8eO6fjx497dNrN/k7Bjx44cYS/7Nw1NmzYtls/gL2aWS6nfzFLS4ufkOrrbWw+OiVN0j0cU0X6ELCE2P86w4NweU5sOpirZ4VKUPUTxsRGyWi5t2W1x9AkAAAAUp4AKew0bNlSVKlU0f/583Xzzzd7NVVJSUrRq1So1b95cNptNHTt21OLFi3XPPfd4z9r78MMPZbFYdOONN0qSWrVqpejoaM2ePVvXXXedpLMhcvbs2YqNjVWzZs388yF9zJPhUMqa6UpaNklZyb976yE1rlBMr8dU+ZpbZAQF59PDxZVUUHJ7TE1eu1dT1u3TgdRzG+jERdp0X9t6GtehfqHHLY4+AQAAgJIQUGHParXq8ccf10MPPaTBgwerf//+cjqd+uijj3Tq1ClNmTJFkjR27FglJCRo6NChuuWWW7Rnzx59+OGHGjJkiGJjYyVJQUFBevDBB/X3v/9d99xzjzp37qyVK1dq06ZNevXVV2Up4weEu9NSlbz6dSWvmCz36ePeeljdVorp/bgqtux7yYegl2RQcntMDZm1WYlbcx+JsT/FqQmLt2vjgRTNHtqqwGMWR58AAABASQmosCdJPXr0UIUKFfT6669r0qRJslgsatmypSZPnqzmzZtLkho1aqQZM2Zo0qRJmjhxomJiYnTPPfd4N2/JlpCQII/Ho3feeUfr1q1TXFycXnnlFXXv3t0fH80nsk4dU/Lnryp51VR5nKe8dfvlHRTT+wmFX9nVJzuNlnRQmrx2b55jnS9x62G1XrtX4zs18FufAAAAQEkJuLAnSR06dFCHDh3ybRMfH6+PP/74on0NHjxYgwcP9tXU/CYz6aCSlr2olDXTZLrOPWWr0KKHYno9Jnujdj4drySDkttjasq6fQVqO3X9vgI9USyOPgEAAICSFJBhD+dkHNmtpCXPK3X9B5I782zRMFTp6gTF9HpMYXF/8fmYJR2UNh1MzbFMND/7U5zadDBVbeIiS7xPAAAAoCQR9gJU+oEfdWLxszq1MVEy/7c7qTVIEW1vU3SPvym0xuXFNnZJB6Vkh8vn7YujTwAAAKAkEfYCjGP3NzqxaKLO/LjEWzOCwxTZaYyib3xYwdF1in0OJR2UouwhPm9fHH0CAAAAJYmwFwBM01TatlU6segZOX5Z461bbJUUef29iu42TkGVSu4Q+JIOSvGxEaoTYSvQ08S4SJviYyP80icAAABQksr2+QHlnOnx6NSmBdr3z9Y6MOkGb9CzVoxRlYHPqOFL+1UtYWKJBj3pXFAqCF8EJavF0Nh29QrU9r629Qr0fmBx9AkAAACUJJ7slVFnfl6pox+OU8Yf2721oMhaiu4xQZEdR8sSGu63uWUHpQmLt1+0ra+C0rgO9bXxQEq+O4AmNK+hcR3q+7VPAAAAoKQQ9sqo36cO9J6TF1LtMkX3fFQRbYfJCCod746VdFCyWgzNHtpKrdfu1dT1+7Q/5dIPcS+OPgEAAICSQtgroyKvu1vpv21RRMdRqnT1QBkWq7+nlIM/gpLVYmh8pwYa16G+Nh1MVbLDpSh7iOJjI4o8TnH0CQAAAJQEwl4ZVW3Qc/6ewkX5KyhZLYbPz7wrjj4BAACA4kTYQ7EjKAEAAAAlj904AQAAACAAEfYAAAAAIAAR9gAAAAAgABH2AAAAACAAEfYAAAAAIAAR9gAAAAAgABH2AAAAACAAEfYAAAAAIAAR9gAAAAAgABH2AAAAACAAEfYAAAAAIAAR9gAAAAAgABH2AAAAACAABfl7Aig8t8fUpoOpSna4FGUPUXxshKwWw9/TAgAAAFCKEPbKELfH1OS1ezVl3T4dSHV663GRNt3Xtp7GdahP6AMAAAAgibBXZrg9pobM2qzErYdzXduf4tSExdu18UCKZg9tReADAAAAwDt7ZcXktXvzDHrnS9x6WJPX7i2hGQEAAAAozQh7ZYDbY2rKun0Fajt1/T65PWYxzwgAAABAaUfYKwM2HUzN8Y5efvanOLXpYGrxTggAAABAqUfYKwOSHa5ibQ8AAAAg8BD2yoAoe0ixtgcAAAAQeAh7ZUB8bITqRNgK1DYu0qb42IjinRAAAACAUo+wVwZYLYbGtqtXoLb3ta3H0QsAAAAACHtlxbgO9ZXQvEa+bRKa19C4DvVLaEYAAAAASjPCXhlhtRiaPbSVJvVqorjInEs64yJtmtSrCQeqAwAAAPAK8vcEUHBWi6HxnRpoXIf62nQwVckOl6LsIYqPjSDkAQAAAMiBsFcGWS2G2sRF+nsaAAAAAEoxlnECAAAAQAAi7AEAAABAACLsAQAAAEAAIuwBAAAAQAAi7AEAAABAACLsAQAAAEAAIuwBAAAAQAAi7AEAAABAACLsAQAAAEAAIuwBAAAAQAAi7AEAAABAADJM0zT9PYnyavPmzf6eAgAAAIAyoFWrVoW+hyd7AAAAABCAeLIHAAAAAAGIJ3sAAAAAEIAIewAAAAAQgAh7AAAAABCACHsAAAAAEIAIewAAAAAQgAh7AAAAABCACHsAAAAAEIAIewAAAAAQgAh7AAAAABCACHsAAAAAEIAIewAAAAAQgAh7AAAAABCACHsAAAAAEIAIewAAAAAQgAh7AAAAABCACHsolXbt2qW77rpLrVq1UvPmzTVo0CCtWbPG39NCOfX666+re/fu/p4GyoHffvtNd911l+Lj43Xttdfq6aefVlpamr+nhXJqxIgR+r//+z9/TwPlzKpVq5SQkKDmzZsrPj5ed999t/bu3evvaZVZhD2UOseOHdPQoUP1888/a8yYMRo/frxcLpfuuusurV692t/TQzmzfv16vf766/6eBsqBpKQk3Xbbbdq1a5fuvvtuDRo0SImJiXrggQf8PTWUQ1OmTNGGDRv8PQ2UM2vWrNG9994rSXr44Yc1cuRI/fDDD7rlllv0xx9/+Hl2ZVOQvycA/NnUqVOVnp6u+fPnq3bt2pKkwYMHq3fv3nr55Zd13XXX+XmGKC/mz5+vJ598UpmZmf6eCsqBd955RykpKVq2bJn3777atWvr73//uzZs2KBrr73WzzNEeeByufTCCy9o5syZ/p4KyqFnn31WjRo10kcffaSgoLMxpWvXrurbt6+mT5/Ok+Yi4MkeSp2NGzcqPj7e+48dSQoLC1Pnzp21e/dunTlzxo+zQ3lx//3367HHHlN8fLyaNm3q7+mgHFi2bJnatm2b4+++fv36yW63a9myZX6cGcqLkydPqnfv3po5c6ZGjx7t7+mgnDl+/Lj27dunnj17eoOeJDVs2FANGzbUf//7X/9NrgzjyR5KnXfffTfPJykpKSmSJKvVWtJTQjn0+++/6/HHH9ewYcM0fPhwORwOf08JASw1NVWHDh1Sv379ctSDgoJ0+eWXa9u2bX6aGcqT06dPyzAMTZ8+Xe3bt9f06dP9PSWUI5GRkVq+fLkqVaqU61pqaqqqVKnih1mVfYQ9lDo1atTIVTtx4oRWrVqlxo0by2az+WFWKG/mzJmjkJAQf08D5cSxY8ckSdWqVct1rUqVKtqyZUtJTwnlUPXq1bV06VJZLCz8QskLCgpSvXr1ctW//PJLHT58WDfccIMfZlX2EfZQYo4fP57v9cqVK+f5j2u3261HH31UDodDd9xxR3FND+VAYb6DBD2UpOwdN8PCwnJdCw0N5ckySsT5S+eA0uD48eN66qmnFBYWpmHDhvl7OmUS/1+NEtOuXbt8r7/66qu5trf3eDx64okn9PXXX6tPnz7q0aNHcU4RAa4o30GgJJimme91nrQAKG9SU1M1evRoHTlyRP/+978VGxvr7ymVSYQ9lJh///vf+V6/8sorc/yclZWlRx55RIsXL1b79u31zDPPFOf0UA4U9jsIlBS73S5JysjIyHUtIyNDFSpUKOkpAYDfHD9+XCNHjtSuXbs0duxYJSQk+HtKZRZhDyWmMP+P6nK59OCDD2rVqlXq2LGjpk6dquDg4GKcHcoD/mOB0ir7XeXsd/fOd+zYMVWtWrWkpwQAfnHkyBENHz5cv/32m+6//37vuXsoGtaFoNQxTVOPPfaYVq1apeuuu05Tp07l/SkAAa1y5cqqVauWfvnllxz1rKws7dq1S02aNPHTzACg5Jw6dUojR47Ub7/9pvHjxxP0fICwh1Jnzpw53qWb//nPfwh6AMqFG264QWvWrNHvv//urS1YsEAOh4P3lQGUC08++aT27NmjBx54gE35fIRlnChVXC6XpkyZIovFonbt2mnp0qW52nTv3l2hoaF+mB0AFJ/Ro0fr008/1W233aYRI0YoOTlZM2bMUOfOndWmTRt/Tw8AitWOHTu0dOlSValSRTVr1tTChQtzXK9YsaKuu+46P82u7CLsoVTZs2ePkpKSJEnPPvtsnm3++te/crAmgIATExOjmTNnauLEiXrppZdUsWJFDR48WA8++KC/pwYAxe67776TdHZzlkceeSTX9Xr16hH2isAwL7bfMwAAAACgzPn/9u49KOrq/+P4E0FAvCB4H4z5KilkSyqCM5qGSghpKpgKCKaCFUnaMCYjOVneKDMdETO8lUaKSKLjhbyO6HgJL5OUGZN4G2QSEwQFFG/7+8Mf+3NFc7X8mvt7PWb4w7Pvz+ecPcuMvOZ8zlnt2RMREREREbFCCnsiIiIiIiJWSGFPRERERETECinsiYiIiIiIWCGFPRERERERESuksCciIiIiImKFFPZERERERESskMKeiIiIiIiIFVLYExERERERsUIKeyIiIiIiIlZIYU9ERERERMQKKeyJiIiIiIhYIYU9ERF5qJSUFDw9PS36ycrKAsDT05NRo0Y93YH/A27dukVhYaHp37m5uXh6erJw4cIn1uekSZPw9PTk/PnzFtVfv36ddevWMXLkSHr06EHHjh0JCgriww8/5Pjx409snH+XJXNrLb9HIiJPg93THoCIiPz7BQYG4u7ubtaWkJCAi4sLiYmJZu0+Pj7/zaE9UUVFRbz99tv079+fsWPHAuDh4cHnn3/OCy+88JRHd0dxcTHjxo0jLy+Pbt26ER0dTYMGDTh9+jQbNmwgKyuL9957j7i4OGxsbJ72cE2ehbkVEXnWKeyJiMhDeXl54eXlZdaWkJCAk5MTgwYNekqjevLOnTtHQUGBWVvTpk3/Ne/5xo0bxMbGUlBQQEpKCn379jV7ffz48XzwwQekpKRQr149YmJintJIa/u3z62IiDXQY5wiIiLPqLS0NI4fP058fHytoAdQr1495s6di7u7O/PmzbP4sVAREbEOCnsiIvJEZWdnExISgre3Nz169GDGjBlUVFSY1dy6dYvly5czYMAAvL296dq1K3FxceTn59e6X1FREYmJifTo0QODwUCfPn2YOXMmZWVlZnV9+vRh7NixzJ8/ny5duuDr68v69est7i8lJYU333wTgOTkZDw9PTl37twD9+zt3buX6Oho/Pz88PX1JTIykt27d5vVFBcXM23aNAIDA/H29qZTp04MHDiQ77777rHmNisrCycnJyIiIh5Y4+DgwKhRo7h+/TobN240m5/AwMBa9TX7Mw8fPmxqq66uJjU1ldDQUDp37ozBYCAgIICkpCQqKyvNxlNzbVJSEj179sRgMDBgwADTXs6aPh5lbu9VVlbGzJkz6d27NwaDAX9/f6ZOnUppaalZXUlJCYmJifTp0weDwUDPnj1JSEgw2ycoImLN9BiniIg8MXl5eRw7dozIyEjCw8PZsWMHaWlplJaWMnfuXACMRiPx8fFs27aN/v37ExERQUlJCRkZGYSFhbFs2TJ8fX0BKCgoIDIykqtXrxIWFkbbtm35+eefSUtLIycnh4yMDFxdXU39HzhwgPz8fOLj47lw4QJdu3a1uL/AwEBu3rxJamoqQUFBBAQE4OrqSlFRUa33mZmZyUcffYS7uzsxMTE0aNCAzMxM3nnnHebPn0/fvn25fPkyQ4cOpbq6moiICNzc3Lh48SKZmZlMnz6dunXrEhYWZvHclpSUcOLECfz8/KhXr95f1nbv3h2AgwcP8tZbb1ncR43x48ezZ88ehg4dSkREBFVVVWzdupUVK1ZQUlLCnDlzzOoTEhJwdnYmJiYGo9HIihUrSExMpFmzZvTs2fOR5vZeZWVlhIWFceHCBYYNG0abNm0oKCggIyODPXv2kJmZiaurKzdv3iQ6Opo//viDqKgoWrVqxenTp1m5ciU//vgjW7ZswcnJ6ZHnQkTkWaKwJyIiT0xVVRWZmZm89NJLAAwdOpR+/fqxbds2rl+/jr29PdnZ2WzdupXJkyebVnsAIiMjGThwIFOmTCE7OxuAqVOnUl5ezsqVK+nSpQsAERER+Pn5kZiYyBdffEFSUpJZ/19//TWdO3c2tW3evNmi/ry8vCgvLyc1NRUvL68H7iWrqKggKSmJ559/njVr1pgCREhICMHBwaawt27dOoqLi1m8eDH+/v6m64ODgwkODmbXrl2PFPZqHsls3rz5Q2tbtGgB3FlZfFT5+fnk5OQQExNDQkKCqT0qKorAwEB27dpV65rGjRuzZs0a7Ozu/Jnh4+PDsGHDWL9+PT179rR4bu9n7ty5FBUVkZ6ejre3t6k9KCiIESNGkJyczNSpUzl+/Dj5+flMnDiRMWPGmOrc3NxYvXo1BQUFpt9LERFrpcc4RUTkiWnbtq3ZH9S2trYYDAZu3Lhheuxy8+bN2NjY8Oqrr1JaWmr6AejVqxcnT57k5MmTlJaWcujQIXr06GEKejUGDx7Mf/7zH7Zt28bt27dN7U5OTnTs2NGs1tL+LLV//36qqqqIiIgwWylq0KABK1asIDU1FYCRI0eyf/9+XnnlFVON0Wjkxo0b2NjYUFVVZXGfdzMajQ+tqVPnzn/3t27deuT7e3l5ceTIEcaNG2fWfvHiRZydne877n79+pmCHsCLL75ouubvMBqNbNmyhXbt2uHm5mb2+Xl4eNC2bVu2b98O3Am4tra2rFq1ik2bNnHlyhXgTqjfuHGjgp6I/L+glT0REXlimjZtWqvN0dERuPPdcABnzpzBaDTSu3fvB96nqKiIyspKjEYj7dq1u2+Nh4cHZ86coayszPQop4uLiyno1LC0Pw8Pj79+c//r3LlzwJ1ge78x3Wvx4sXk5eVRWFhIYWEhV69eBSwLbXerWa27cOHCQ2trVvTu93lYwt7eng0bNnDgwAHOnj1LYWFhrT2Sd7u3Hzs7O2xtbc2C+OMoLS2lvLyc8vJyunXr9sC66upqWrRoweTJk/nss8+YMGECdnZ2eHt74+/vT2hoKC1btvxbYxEReRYo7ImIyBNja2v70Jrbt2/TqFEjkpOTH1jj5eX10EM1aoKEvb39X/ZvaX+WunnzpkV1R48eJTo6GqPRSLdu3ejTpw/t27fH19eXXr16WdxfjaZNm+Lh4cGvv/5KZWUl9evXf2Btbm4ugGnv41+59/2UlZURHh7O2bNn8fPzw8fHh7CwMDp27MiMGTNM977bk/o+v5rPuGvXrrz77rsPrKv53CMjI+nXrx85OTns3buX3Nxc5s2bx6JFi1i2bFmtFWIREWujsCciIk9V69atOXPmDAaDgUaNGpm9dvToUSoqKnB0dKR169YAnDhxotY9jEYjp06dolGjRjRo0OAf6c9Sbm5uwJ0Vw3tXm9LT0/nll1+YNGkS8+bN49q1a2zevJk2bdqYai5evPjYK16DBw9m9uzZpKWlERsba2rft28fO3fuJCoqitatW7N8+XLq1q1LSEiIqcbW1pZr167Vuue9j1quWrWK06dPM3PmTIYMGWL22p9//vlY435crq6uODk5ceXKFdOhM3fbtWsXDRs2xM7OjrKyMn7//Xe8vLwIDQ0lNDQUo9HIDz/8QHx8PCtWrFDYExGrpz17IiLyVAUFBWE0Gpk/f75Ze0lJCXFxcUyYMIE6derQpEkTfH192bt3L0eOHDGrXb9+PWfPnr3vVwk8bn/wfytEfxXGunfvjqOjI2vWrKG6utrUXllZyZIlSzh8+DCNGjXi0qVL1K9f3xQOayxZsgSwfIXwbiNHjqRDhw4sWLDAdIgN3Dk0ZteuXQwaNIioqChOnjzJmDFjeO6550w1zZs35+LFi2aHtpSXl5OTk2PWx6VLlwBo3769WfuOHTs4derUY4/dkrm93zUBAQH89ttvpr15NXJzc4mNjTXtkdy/fz8jRowgIyPDVGNjY2M6rMeSVWcRkWedVvZEROSpCg0NJTs7m7S0NM6cOUOvXr2oqqpi9erVlJSUMGvWLNNK25QpU4iKimL06NGEh4fTpk0bjh07RlZWFm5ubkyYMOEf7a9JkyYA7Ny5kxYtWtw3TLq4uJCQkMC0adMYMmQIISEh2NnZsXbtWs6fP28Kc7179+arr75izJgxvPbaa9y4cYPt27dz6NAh7O3ta333oCXq1q1Lamoq48ePJz4+njVr1uDv70/Dhg3p27cvaWlp5OXl4ejoWGuPYkhICIcPHyY6Oprhw4dz9epVMjIycHZ2Nlvd6927N99++y0TJkxg+PDhODk5ceTIETZt2oSDgwPV1dVcuXIFFxeXRxq7JXN7PxMnTuTgwYO8//77vPHGGxgMBs6ePUt6ejrOzs6mE0MDAgLo0KEDycnJFBYWYjAYuHz5MpmZmdStW5cRI0Y80nhFRJ5FCnsiIvJU2dnZsWjRIr755hs2btzIrFmzqF+/Pl5eXkyfPp2XX37ZVOvp6cnatWtZsGABmzdvpry8nJYtWzJq1ChiY2Nxdnb+R/tr06YNo0eP5vvvv2fmzJm0bt261oEvcGdvWKtWrVi6dCkpKSk4ODjQoUMHPvnkE3x8fACIi4ujTp06bNiwgaSkJBo3bkz79u1Zvnw5mZmZZGdnU1xcbDp4xVItWrQgLS2N7OxssrKyWLp0KZcvX6ZZs2YEBwfj7+9Peno64eHh9O3bl9mzZ2Nvb8+QIUOoqKhg9erVfPrpp7Rs2ZLw8HDc3d3NTt7s3r07c+bMYcmSJSQnJ+Pg4IC7uzsff/wxcCeA79u3j9dff/2Rxm3p3N7v/a5du5Yvv/ySnJwc1q1bR5MmTQgICGDs2LGmg3IcHBxYtmwZCxcuZPfu3axfvx5HR0c6d+7MrFmz6NSp0yONV0TkWWRjfNTjv0REROSZcvv2bbZs2cJPP/3E5MmTn/ZwRETkv0RhT0RERERExArpgBYRERERERErpLAnIiIiIiJihRT2RERERERErJDCnoiIiIiIiBVS2BMREREREbFCCnsiIiIiIiJWSGFPRERERETECinsiYiIiIiIWCGFPRERERERESuksCciIiIiImKFFPZERERERESskMKeiIiIiIiIFVLYExERERERsUIKeyIiIiIiIlZIYU9ERERERMQK/Q8hp7/c2fWpGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 262,
       "width": 445
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qqplot(nsample, dist=norm(0,1), line='q');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87daddc0-68d4-4b84-bc75-c8b1a54c2885",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "135ec893-21ee-4a9b-a751-e281a43dd432",
   "metadata": {},
   "source": [
    "#### Examples of bad fit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "582f6ae2-6809-408b-89ec-04aba5f37748",
   "metadata": {},
   "source": [
    "##### Shifted uniform data vs. standard normal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4b2e4b6e-af2e-4c9b-a99f-012411a902fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 440
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsample = np.array(vsample)\n",
    "qqplot(vsample, dist=norm(0,1), line=\"q\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b153d26b-2cd7-4bef-9701-811ce832907f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1ba48fe6-637c-4cc7-9bc9-20964314939f",
   "metadata": {},
   "source": [
    "##### Exponential data vs. standard normal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "51dd8813-5f47-48cf-bc4b-d62db69fab27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 262,
       "width": 441
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "esample = np.array(esample)\n",
    "qqplot(esample, dist=norm(0,1), line=\"q\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef2f5a7c-750c-4fd9-998e-30e0e2c1ac6b",
   "metadata": {},
   "source": [
    "Note the lowest quantiles don't match (exponential data limited to zero),\n",
    "and the high quantiles don't match either (exponential data has a long tail)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "537f5bad-87a6-485d-a59e-9ddb42382714",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7a5fc499-8910-468b-b368-8e89e9e5cd7e",
   "metadata": {},
   "source": [
    "#### Shifted uniform sample vs. true model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7b33b8b1-876d-4db0-8829-29ac4f2ef4be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 262,
       "width": 448
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsample = np.array(vsample)\n",
    "qqplot(vsample, dist=rvV, line=\"q\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0dd1662a-9627-48f5-a8fe-9c695b0ce163",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "bcde3b00-0bff-4492-820f-9e2f00eeafdd",
   "metadata": {},
   "source": [
    "#### Exponential sample vs. true exponential model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "b534f7c4-4090-4569-b697-7b35dea8eb99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 262,
       "width": 438
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qqplot(esample, dist=rvE, line=\"q\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6cfcf56-d48a-4555-b60a-75cfd28e8935",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ef1aef8-52eb-4e6c-bbf7-94f6fe3a502a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "558eaae7-305d-43ea-a0dc-87b372d6b4ad",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "95c2e884-cfd7-4de9-8a62-9b0026f07de7",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Generating a Q-Q plot manually (bonus material)\n",
    "\n",
    "If want to know how the Q-Q plot is generated,\n",
    "you can look at the following function `qq_plot` which the same way as `qqplot`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9049c093-8127-44c0-b01f-9c2079e331a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def qq_plot(sample, dist, line=\"q\"):\n",
    "    qs = np.linspace(0, 1, len(sample))\n",
    "    xs = dist.ppf(qs)\n",
    "    ys = np.quantile(sample, qs)\n",
    "    ax = sns.scatterplot(x=xs, y=ys, alpha=0.2)\n",
    "    if line == \"q\":\n",
    "        # compute the parameters m and b for the diagonal\n",
    "        xq25, xq75 = dist.ppf([0.25, 0.75])\n",
    "        yq25, yq75 = np.quantile(sample, [0.25,0.75])\n",
    "        m = (yq75-yq25)/(xq75-xq25)\n",
    "        b = yq25 - m * xq25\n",
    "        # add the line  y = m*x+b  to the plot\n",
    "        linexs = np.linspace(min(xs[1:]),max(xs[:-1]))\n",
    "        lineys = m*linexs + b\n",
    "        sns.lineplot(x=linexs, y=lineys, ax=ax, color=\"r\")\n",
    "    return ax\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "18412c2b-b3c9-4319-bc2a-84dde1548e13",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # ALT2. use the `probplot` from the `scipy.stats` module\n",
    "# from scipy.stats import probplot\n",
    "# probplot(nsample, dist=norm(1000,100), plot=plt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4693344a-5f47-4a79-801c-0e7bdaf8dfbe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22a92c41-76a2-41d9-8e71-d0c8265f9688",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7ec5fb9c-fa25-45a4-8f84-03c45271920f",
   "metadata": {},
   "source": [
    "### Comparing moments\n",
    "\n",
    "A simple way to measure how well the data sample $\\mathbf{x} = (x_1, x_2, \\ldots , x_n)$\n",
    "fits the probability model $f_X$ is to check if the data distribution\n",
    "and the probability distribution have the same moments."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a660d315-beeb-4d2a-80f6-ac1c27d0fcf3",
   "metadata": {},
   "source": [
    "In order to easily be able to calculate the moments of the data samples,\n",
    "we'll convert `vsample` and `esample` into Pandas series objects,\n",
    "which have all the necessary methods.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2e098501-5450-4cd9-b745-d085ef4d8d85",
   "metadata": {},
   "outputs": [],
   "source": [
    "vseries = pd.Series(vsample)\n",
    "eseries = pd.Series(esample)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5ef9563-933a-4409-a304-68b2fa7000c8",
   "metadata": {},
   "source": [
    "#### Moments of uniform distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "3b10240f-35fc-4ef9-9a83-ec6819e45ef9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(110.21271847666772, 110.0)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vseries.mean(), rvV.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1e7e7adb-68bc-445d-9c99-945d3b69e89f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35.95736108409104, 33.33333333333333)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vseries.var(), rvV.var()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03ccc62a-85fb-4ae6-98e0-73d073970b54",
   "metadata": {},
   "source": [
    "Let's now compare the [skew](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.skew.html) of dataset and the [skew](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.stats.html#scipy.stats.rv_continuous.stats) of the distribution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cb211121-3ce6-4f9e-9be5-218a1b1b5b56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.03970716302600479, array(0.))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vseries.skew(), rvV.stats(\"s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6b6528c-dcb0-4f26-a2a7-da79cad51cf6",
   "metadata": {},
   "source": [
    "Finally,\n",
    "let's compare the [kurtosis](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.kurt.html) of dataset and the [kurtosis](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.stats.html#scipy.stats.rv_continuous.stats) of the distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6419dc79-3abf-42ae-aa68-8f7ef803f480",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.2584390506748377, array(-1.2))"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vseries.kurt(), rvV.stats(\"k\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02a2eabd-542f-4f7b-851d-adb32c40e0e2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d7f7c363-9107-405c-b5a5-1ea0b4293e52",
   "metadata": {},
   "source": [
    "#### Moments of exponential distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "b3617f15-a176-4258-9e31-d3e44a00099b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5.343224374466268, 5.0)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.mean(), rvE.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3502aa81-bd5d-4631-b678-6626f0aa3134",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(27.53085874882216, 25.0)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.var(), rvE.var()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc613fb8-a131-4775-afaf-f505d8c015aa",
   "metadata": {},
   "source": [
    "Let's now compare the [skew](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.skew.html) of dataset and the [skew](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.stats.html#scipy.stats.rv_continuous.stats) of the distribution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5316d53c-b2ad-4404-a525-2457fcef5938",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.7338627932228903, array(2.))"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.skew(), rvE.stats(\"s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9064296-d903-4ae7-932c-a6c80e5500ae",
   "metadata": {},
   "source": [
    "Finally,\n",
    "let's compare the [kurtosis](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.kurt.html) of dataset and the [kurtosis](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.stats.html#scipy.stats.rv_continuous.stats) of the distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f49f28e1-10d5-4a78-a972-f8d8c4fabdf8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3.557504048617028, array(6.))"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.kurt(), rvE.stats(\"k\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "455e367c-c340-4d49-8a25-46e2b8e2db82",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e2ef9712-0113-4fc0-a56f-e42d5901ffe3",
   "metadata": {},
   "source": [
    "#### Example of bad fit between higher moments\n",
    "\n",
    "Define the random variable `rvNE` as the best normal approximation to random variable `rvE`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "da458f12-f737-4b21-ab00-b9cefd893820",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5.0, 25.0)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rvNE = norm(5,5)\n",
    "rvNE.mean(), rvNE.var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "013f3d77-22fc-480b-80f0-892ef8dfce3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.7338627932228903, array(0.))"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.skew(), rvNE.stats(\"s\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "9df7d927-9587-46ef-b1f3-8cf35c4b536b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3.557504048617028, array(0.))"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eseries.kurt(), rvNE.stats(\"k\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "741c4f52-149b-4e3a-9d77-bd095a484c68",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a44f48c-ce5c-40b0-813d-c3173c5a94c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a2cfecae-7320-4c69-87ca-47e87e5389d1",
   "metadata": {},
   "source": [
    "### Kolmogorov–Smirnov test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b50f3c81-d415-45db-8cf3-948a3c38e395",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ks_1samp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff631eab-f34e-40d4-9d85-759c8d2cfa0a",
   "metadata": {},
   "source": [
    "Let's jump right ahead and compute the KS distance for the data and distribution of interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "cccc95cd-47d4-4d38-a0a8-3d90689af2f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07815466189999987"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(nsample, rvN.cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "81756697-d437-41b1-84c7-752f48d3d103",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.03597247001342496"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(esample, rvE.cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "de414317-ceb8-430c-8e84-86b73b85e49b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05707018183377044"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(vsample, rvV.cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "278bcfe2-7a87-49c1-b865-120d62338860",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3d65b3e1-d07c-4402-8312-041a21cfaacb",
   "metadata": {},
   "source": [
    "#### Example of big distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5295208c-356b-40b0-b97c-eb618a9a81c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15871546070321535"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(esample, rvNE.cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9e965e06-1957-42da-8bd2-abe4858c95bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Proportion'>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 252,
       "width": 438
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.ecdfplot(esample, label=\"eCDF(esample)\")\n",
    "bs = np.linspace(-10,35)\n",
    "sns.lineplot(x=bs, y=rvNE.cdf(bs), label=\"$F_{N_E}$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39b734eb-c0a1-49c0-9461-72ac93921481",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ee184d61-dd55-4522-b86d-bf556a50bd57",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "#### KS distances after standardization (optional)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b2e8e9d-047f-402f-8aa1-8769f790e8d4",
   "metadata": {},
   "source": [
    "Define the function `standardize` that transforms any dataset\n",
    "so it will have mean zero, and standard deviation one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b6e87f7c-19a7-47f3-874c-6f4e10401690",
   "metadata": {},
   "outputs": [],
   "source": [
    "def standardize(data):\n",
    "    xbar = data.mean()\n",
    "    s = data.std()\n",
    "    return (data-xbar)/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "263e08f2-e73f-40fe-81af-452b1e8f370e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ALT. Use existing function that does the same as `standardize`\n",
    "from scipy.stats import zscore"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94920993-79c5-4fd8-9908-6ed375f796c1",
   "metadata": {},
   "source": [
    "We can now report the KS distances,\n",
    "between the standardized version so `nsample`, `esample`, and `vsample` and\n",
    "standard normal $\\mathcal{N}(0,1)$,\n",
    "to check how \"normal\" they are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "bf622f1b-5260-4bf6-877d-94bd12399a7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.037541386171241364"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(zscore(nsample), norm(0,1).cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "32c4a090-7c68-41c0-a8fd-70bad29df1ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.10026891576437313"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(zscore(vsample), norm(0,1).cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "a2bd9512-0c96-4844-886b-e4180d64155c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15419311135216357"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(zscore(esample), norm(0,1).cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e0c1be1-5091-430e-9d3c-2c468f913058",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "d01ef856-6433-41e3-a1e3-4b840a84549a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1781210103950946"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = expon(0,10).rvs(100)\n",
    "ks_1samp(zscore(data), norm(0,1).cdf).statistic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cd91186-5d97-4ac5-b937-6174c45b0040",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "#### Calculating the KS distance manually (optional)\n",
    "\n",
    "The computation is a little tricky since the eCDF is a stepwise function,\n",
    "so we need to two differences $|F_X(x_i) - F_{\\mathbf{x}}(x_i)|$\n",
    "and $|F_X(x_i) - F_{\\mathbf{x}}(x_{i-1})|$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "609f1081-5a41-498e-aecb-4060c1aae9bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ks_dist(sample, rv=norm(0,1)):\n",
    "    \"\"\"\n",
    "    Compute the KS distance between observed data in `sample`\n",
    "    and the theoretical distribution of random variable `rv`.\n",
    "    \"\"\"\n",
    "    sample = sorted(sample)\n",
    "    ks_dists = []\n",
    "\n",
    "    x0 = sample[0]\n",
    "    ks_dist0 = rv.cdf(x0)\n",
    "    ks_dists.append(ks_dist0)\n",
    "\n",
    "    n = len(sample)\n",
    "    for i in range(1,n):\n",
    "        # xi\n",
    "        xi = sample[i]\n",
    "        eCDFxi = ecdf(sample, b=xi)\n",
    "        ks_dist1 = abs(eCDFxi - rv.cdf(xi))\n",
    "        ks_dists.append(ks_dist1)\n",
    "        # x(i-1)\n",
    "        xim1 = sample[i-1]\n",
    "        eCDFxim1 = ecdf(sample, b=xim1)\n",
    "        ks_dist2 = abs(eCDFxim1 - rv.cdf(xi))\n",
    "        ks_dists.append(ks_dist2)\n",
    "\n",
    "    # find max\n",
    "    max_ks_dist = max(ks_dists)\n",
    "    return max_ks_dist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec8c578-c1a3-4c30-bee0-5a3c16c7bcea",
   "metadata": {},
   "source": [
    "##### Test 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d4075799-15b2-4ff6-9678-1299128d38e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07815466189999987"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_dist(nsample, rv=norm(1000,100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "307b9eda-ddb3-4f8f-a143-66272def3c07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07815466189999987"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(nsample, norm(1000,100).cdf).statistic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a05a4637-4bc8-4aeb-acbf-15285ee63994",
   "metadata": {},
   "source": [
    "##### Test 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "e65be42e-0361-4d15-8cf0-d104db27dce9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.037541386171241364"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_dist(standardize(nsample), rv=norm(0,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "63c0bdd9-c897-4cba-a268-c1fa6f483708",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.037541386171241364"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ks_1samp(standardize(nsample), norm(0,1).cdf).statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "776fce35-6f1d-4ff6-8e4d-d732cc3d6c84",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b6e5d21-a0cd-4d2c-997f-c24eb601575b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3132eeb4-6b58-458b-8768-4ff5add461ac",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c50fd8e9-d26c-4c25-96ad-49555f33304c",
   "metadata": {},
   "source": [
    "## Bootstrap sample generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "38dc57d4-cc38-457c-a51d-a035ae0a3543",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1031.85454991,  932.04405655,  779.16115305, 1059.02401628,\n",
       "       1167.47660438,  833.40440269,  917.56612626, 1054.52603422,\n",
       "       1000.11861932,  924.29694777, 1062.95451919,  990.43682345,\n",
       "        849.21393503,  949.99869847, 1171.40102725,  877.62327349,\n",
       "       1139.59050836, 1041.44763431, 1151.96667669, 1139.0063404 ,\n",
       "        891.5999061 ,  957.46318231,  937.81775307, 1145.86005158,\n",
       "        872.50054515, 1112.86094852, 1179.05765281,  948.13164741,\n",
       "        932.89197563, 1073.67607886])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import norm\n",
    "rvN = norm(1000, 100)\n",
    "\n",
    "np.random.seed(72)\n",
    "sample = rvN.rvs(30)\n",
    "sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "1bb2b116-770a-4563-a36f-12085d6007fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1031.85, 932.04, 779.16, 1059.02]\n"
     ]
    }
   ],
   "source": [
    "print([round(val, 2) for val in sample[0:4]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6e0632a8-b4ac-4428-92e2-7231059bc987",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1004.1657229506349"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9527f8f9-8473-4afc-8ebb-3e4ee365732a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2471e77e-8b6e-4575-a617-74c9d96372fd",
   "metadata": {},
   "source": [
    "Let's generate a bootstrap sample and compute its mean:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "50b1c7b2-e178-48bf-8145-c7965b741df8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "989.8642131674898"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bsample = np.random.choice(sample,30)\n",
    "bsample.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47d14f2d-361f-4345-be30-eb8bd22905ef",
   "metadata": {},
   "source": [
    "Let's compute the means of $10$ bootstrap samples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "5f1cf015-408e-4bf2-9cfe-ccbc44a6f3b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "B = 10\n",
    "bmeans = []\n",
    "for k in range(0,B):\n",
    "    bsample = np.random.choice(sample, 30)\n",
    "    bmean = bsample.mean() \n",
    "    bmeans.append(bmean)\n",
    "\n",
    "# bmeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "29b1f043-2d11-4345-b20c-fe4b60c01e73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1002.72, 968.09, 995.78, 964.45, 1011.08, 1013.17, 1027.03, 1041.01, 969.77, 1029.55]\n"
     ]
    }
   ],
   "source": [
    "print([round(bmean, 2) for bmean in bmeans])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "8b44df54-1326-4b12-b782-10157c9d6c8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39.719674810092215"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(abs(bmeans - sample.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4fe7532-f019-43f1-afbf-9054e9505e6c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32cb556e-72cc-40fa-9693-f22ab78354d1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "7d0c0b3c-8ac9-4537-b9d0-b0ef7e7f7a9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # BONUS: draw B=1000 bootstrap samples ot obtain a full histogram\n",
    "# B = 1000\n",
    "# bmeans = []\n",
    "# for i in range(0,B):\n",
    "#     bsample = np.random.choice(sample, 30)\n",
    "#     bmean = bsample.mean() \n",
    "#     bmeans.append(bmean)\n",
    "\n",
    "# ax = sns.histplot(bmeans, stat=\"density\")\n",
    "# ax.set_xlim(600,1400)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aff49cb-a23a-4db9-ae30-69d0097f5ed1",
   "metadata": {},
   "source": [
    "#### Clarification: empirical distribution of `sample` is not the same as $f_N$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "d5af9f96-5d54-439d-9bdf-dd931d204663",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(600.0, 1400.0)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 252,
       "width": 458
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the pmf of uknown distritbuon f_N\n",
    "from scipy.stats import norm\n",
    "rvN = norm(1000, 100)\n",
    "xs = np.linspace(600,1400)\n",
    "ax = sns.lineplot(x=xs, y=rvN.pdf(xs))\n",
    "\n",
    "# plot histogram from a single samples of size 30\n",
    "sns.histplot(sample, binwidth=25, stat=\"density\", ax=ax)\n",
    "ax.set_xlim(600,1400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "249a84f1-0236-4c86-bb13-c91fbbba83b4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "86e262ed-aece-4478-bbe6-68d6218cbbd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: stem plot of sample\n",
    "# TODO: stem plot alpha=0.1 of bsamples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b74b175b-bd5c-4339-906f-2e43c7d5b499",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "fd6ecb85-18f1-46de-bdfd-e43200997b83",
   "metadata": {},
   "source": [
    "## Discussion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f5a7cde-c85f-4a4b-b15e-8d4206b18ab7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "071703fb-7798-4eb4-95d0-ab05c6f2d3ad",
   "metadata": {},
   "source": [
    "set random seed for repeatability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b2ef428f-ab80-4603-84df-d42215c81fa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6394267984578837"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "random.seed(42)\n",
    "random.random()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bc409a9e-1dda-4091-b18d-9eced50d81f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11505456638977896"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.random.seed(43)\n",
    "np.random.rand()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db3f6f22-c1e8-4660-a0f0-0e24849f6773",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}