{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eb8c3283-299e-402f-a331-3f2490f713a1",
   "metadata": {},
   "source": [
    "# Sections"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f6807c6-4b96-448b-a8a1-8d90b953411a",
   "metadata": {},
   "source": [
    "This section reviews more advanced functionality for creating and manipulating `pystrat.Section` objects and plotting stratigraphic sections.\n",
    "\n",
    "The example data utilized here comes from the references listed at the end of the guide.\n",
    "\n",
    "The example data files used in this guide can be found [here](https://github.com/pystrat-maintainers/pystrat/tree/main/docs/example-data)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8d5b6e81-b00c-4863-a35a-7d0ae5d48ba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pystrat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48a975cb-e763-43a0-b88e-a291757d6295",
   "metadata": {},
   "source": [
    "## Group, Formation, Member Labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfc05799-c0d9-40e6-8c11-f3dd2c5ca9f1",
   "metadata": {},
   "source": [
    "Intervals of stratigraphy can be labeled according to their classification within groups, formations, members, etc. Doing so requires specifying the names of these groupings as additional columns in the section spreadsheet. Every bed in the section must have a label in the relevant column. Intervals with shared labels will be labeled together. Furthermore, arbitrarily many levels can be simultaneously labeled, i.e., it is possible to label groups, formations, and members simultaneously. \n",
    "\n",
    "Labels are provided as an array of strings given to [`pystrat.Section`](api/pystrat.rst#pystrat.pystrat.Section). The order in which labels appear is set by the order of the columns in the array containing the labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "41438e5e-15c0-4074-acce-bf0163bef8eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in lithostratigraphy data\n",
    "litho_df = pd.read_csv('example-data/lithostratigraphy.csv')\n",
    "\n",
    "# create a pystrat Section from the lithostratigraphy data\n",
    "section_1 = pystrat.Section(litho_df['THICKNESS'],                         # unit thicknesses\n",
    "                            litho_df['FACIES'],                            # unit facies\n",
    "                            units=litho_df[['GROUP', 'FORMATION']].values) # group and formation names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af27b0f5-7e15-458a-afcd-9d5bfb941746",
   "metadata": {},
   "source": [
    "Create a `pystrat.Style` to plot the section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f4225106-e89c-4f6d-bea0-b5c8c39afd75",
   "metadata": {},
   "outputs": [],
   "source": [
    "style_df = pd.read_csv('example-data/style.csv')\n",
    "style_1 = pystrat.Style(style_df['facies'],                  # labels (must include all unique facies)\n",
    "                        style_df[['R','G','B']]/255,         # colors \n",
    "                        style_df['width'],                   # widths \n",
    "                        swatch_values=style_df['swatch'])    # swatches"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9f31c30-b799-4924-9c6b-6fcb4de25c70",
   "metadata": {},
   "source": [
    "Plot the section, now using the `label_units=True` and `unit_label_wid_tot=0.3` arguments. \n",
    "\n",
    "The `unit_label_wid_tot` parameter specifies the horizontal fraction of the axis that is used for the unit interval labels; increase this if the labels are too cramped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e4d3360e-467a-4b93-9544-c228afa13059",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(2, 7))\n",
    "ax = plt.axes(ylim=[0, 120])   \n",
    "section_1.plot(style_1, ax=ax, label_units=True, unit_label_wid_tot=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88061789-f5ca-4fa2-a7ca-3e9315090909",
   "metadata": {},
   "source": [
    "## Annotations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "402a1149-865a-4502-9304-d2856141dc53",
   "metadata": {},
   "source": [
    "Plotting annotations alongside stratigraphic columns is a conventional way of illustrating observations at given heights within the section, and `pystrat` is capable of plotting annotations.\n",
    "\n",
    "Annotations must be added to the `pystrat.Section` object as a `pandas.DataFrame`. This DataFrame must contain *height* and *annotation* columns:\n",
    "1. The *height* column contains the stratigraphic heights at which to plot the annotations.\n",
    "2. The *annotation* column contains the names of annotations that are mapped to `.png` graphics which are plotted as annotations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "73b8b0df-6ebf-4c50-b21c-baee7254fa51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
       "columns": [
        {
         "name": "index",
         "rawType": "int64",
         "type": "integer"
        },
        {
         "name": "height",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "annotation",
         "rawType": "object",
         "type": "string"
        }
       ],
       "conversionMethod": "pd.DataFrame",
       "ref": "481bd896-903c-49ef-a620-7b86783e360d",
       "rows": [
        [
         "0",
         "62.0",
         "stromatolite"
        ],
        [
         "1",
         "89.2",
         "stromatolite"
        ]
       ],
       "shape": {
        "columns": 2,
        "rows": 2
       }
      },
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>height</th>\n",
       "      <th>annotation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>62.0</td>\n",
       "      <td>stromatolite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>89.2</td>\n",
       "      <td>stromatolite</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   height    annotation\n",
       "0    62.0  stromatolite\n",
       "1    89.2  stromatolite"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ann = pd.read_csv('example-data/annotations.csv')\n",
    "ann"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cc63601d-519e-4eec-a87c-68cae636d9f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "section_2 = pystrat.Section(litho_df['THICKNESS'],                           # unit thicknesses\n",
    "                            litho_df['FACIES'],                              # unit facies\n",
    "                            units=litho_df[['GROUP', 'FORMATION']].values,   # group and formation names\n",
    "                            annotations=ann)                                 # add annotations "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd7968b1-4f7c-42fd-87f7-b4223511210b",
   "metadata": {},
   "source": [
    "### Default Annotations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a541cfc2-2de6-40c8-8859-8eae0a94912a",
   "metadata": {},
   "source": [
    "The mapping between annotations and graphics is specified in a `pystrat.Style` object. \n",
    "\n",
    "There are a couple ways of specifying which annotations to plot. `pystrat` comes with a small library of annotation illustrations. The available annotations can be visualized with `pystrat.Style.plot_default_annotations()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c2d03147-2a89-4a3f-99ad-9c171d3ab00f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pystrat.Style.plot_default_annotations()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9f647e2-e63c-4136-be6b-6b54a65a4847",
   "metadata": {},
   "source": [
    "In the section above, only stromatolites need to be annotated. A `Style` object with stromatolite annotations can be initialized by passing the `annotations=['stromatolite']` parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d46e8265-bafe-45c3-97f0-e589bd346470",
   "metadata": {},
   "outputs": [],
   "source": [
    "style_2 = pystrat.Style(style_df['facies'],                  # labels (must include all unique facies)\n",
    "                        style_df[['R','G','B']]/255,         # colors \n",
    "                        style_df['width'],                   # widths \n",
    "                        swatch_values=style_df['swatch'],    # swatches\n",
    "                        annotations=['stromatolite'])        # annotations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c51b212-e733-41f7-b6df-a1c077dc9f59",
   "metadata": {},
   "source": [
    "Now, the section can be plotted with annotations at the desired heights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cf946f3e-d3eb-497f-95a5-56ffd2e3bae2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(2, 7))\n",
    "ax = plt.axes(ylim=[0, 120])   \n",
    "section_2.plot(style_2, ax=ax, label_units=True, unit_label_wid_tot=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ddf7947-fc6a-47e1-af83-8a4feda9b65b",
   "metadata": {},
   "source": [
    "### Custom Annotations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6713b372-cffb-447f-9d9e-f44ed348f202",
   "metadata": {},
   "source": [
    "If an annotation is not available in the default library, custom graphics can be used by providing a dictionary that maps annotation names to `.png` paths."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "eb6aebe7-ee15-47af-a35b-0ec734e89606",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YPXo0devW5ezZs0yfPj3L8eWFjUllPq09iR0BP3Lr+dVM2+lq6dO4Yjscyriw8sIkLj48UiD711ZqF8mCN1ZGlZjWYj2e73nj7vgJZvqWXH18iv9i7jOi0XwcylTXaP8w8i73Xgbl6Uq/nrY+1S0b5HnKpXHFNsxrvY3qlg3SvZesSma7/w/UtHof13IZPxFmpGuCpaF1uq8KxnZ8WnsSx0N2EPzi30z3r1Ao6FZ9GFNbrMPS0DpPx6DRnyjp90tIUi6dPHmSli1bsuqjE9SzbpHj7YQQnL2/n12Bq5ngtpIKxv9bxSlFlcLj6HscDdmG36Nj2JhUoXWVj6lTvpnGvOfbKK0EvFns45NjGXegI5EJL/ip08kSdcHp0qNj7AxYxaSmqyijn/XJQWYOB2/hnwd/M8HtBwx1jPPUR+Czy3jsboCfnx/169fPsq2cRpCk/6dQKHivkjtPYx/y82UvPN/zRldLj5tPznPi3m4eRt6ldnk3xv9/Ic7rylklTWZn1DpKPRpVbENM4qsS9dRYQnI82/1/4L2K7TDTs8hTH/HJcVSzbMCRu1vZFbCavjXHoqUs3GkcWWwl6TXaSm06OA4kPCqUJf94kqJKRkupTXO7LnxaexLlDG3emfQHLaUWg+p8jUBV4Le75YeOli7dq3/B1psrKGtQnqZ2nTTmzVNUKcQnxxCXHEN8cizRia/4LzqM8OhQnsY85EXcf8QmRaMSKSSpEgmPDiU2KarQz9xlsZVKrXuvgjDI4NfD57Hh3I24Sd0KLTKcAngeG87Np+epXKYGThZ1qGJeE22lDi/i/uNF3H9FMXQNh4O3oKOlSyuHHkW+78zEJEby82UvPqs3HdMCuHiUW2b6FrSr2o9fry3gxpNzVDC241nsI57FPuJl/DNexT8nLjn6/2/xMsBcvzzljGww07PA2sQBMz1LzPQtMdY1RanQSl3JLCr34wh9GZB9o/8n52ylUufIkSPpHrqQpMIiY3Gkd1bafdI6H1dFq2LuV3sTkYkknXmEzoe2KPQK/3as7CRffQpaSrRr5W1+sjCI+GSSDoWh08YOhWHxlhHVk1gSf7vFpk2bcHFxKfL9y8BH6Z2nXacc2jVyX6BUT+NIuf0SnabWKIyKf65SRCeCjhY6LStm37iIiOgkUvyeou1WAaVZ8V4oTAl+ReJvt3Bxccn2joDiJO+zlSRJKgKy2EpF5vV1aktyLI8kFQZZbEuQ4sgiy4uCyAiztbUlPDycmjVrAv9bqPzly5f5H6AklUCy2L6FSmpKQW5oaWlRoUIFtLXlZQPp3SCLbTHYvn07tWrVwsDAAAsLC9q0acPEiRPZsGEDf/75JwqFAoVCga+vr/rX7a1bt9KqVSv09fXZtGkTKpWK2bNnU6lSJfT09Khbty4HDhxQ7+P17Zo3b46BgQGNGjXi1q1bXLx4kYYNG2JsbEz79u15+vSperuLFy/Stm1bLC0tMTMzo2XLlly+fFn9flaxO6tWraJq1aro6upSrVo1Nm7cmOln8Po0QmhoqHoFMHNzcxQKhTrpIicRPJL0NpDFtoiFh4fTr18/Bg8eTEBAAL6+vvTo0YOZM2fSu3dv2rdvT3h4OOHh4bi5uam3mzx5Mp6engQEBODu7s7y5cvx9vZm8eLFXL9+HXd3d7p06ZJuQZeZM2cybdo0Ll++jLa2Nv369WPSpEksX76cU6dOERwczIwZM9Tto6KiGDRoEKdOneLcuXM4OTnRsWNHoqJS7/jOLHZn165djBkzhvHjx/Pvv/8yfPhwPvvsM44fP57tZ2Jra8uOHTsACAoKIjw8nOXLlwNkG8EjSW8L+TtcEQsPDyc5OZkePXqo42xq1aoFpC6snZCQkGGczdixY+nR439PEC1evJjJkyfTt29fABYuXMjx48dZtmwZP/zwg7rdhAkTcHd3B2DMmDH069dPvfwiwJAhQ/Dx8VG3//DDDzX2u3r1aszNzTlx4gSdOnXKNHZn8eLFeHh4qKOGvvrqK86dO8fixYuzXbdWS0uLsmXLAqnLW6YtFZmTCJ6sJAe8gJjcpwGrIhMQz+NJvvwEhV7+/omI5P9Pf9DO23mNEALVvSjQVpJ8oXCeXhNCQJIKdJQ5fhRZxCejepVAypWnqAwL5/Y4oRKQogLtrMeV8vjtSDKWxbaI1alTh9atW1OrVi3c3d1p164dvXr1ynLNWdCMpomMjOTRo0fqgpmmadOmXLt2TeO11+N/ypcvD/yvuKe99noc0JMnT5gxYwbHjh3jv//+IyUlhdjYWMLCwrIcX0BAAMOGDUs3nrQz1LzISQRPVlTBr0h+mYe4eSFQVjImJTAC8rkOgupBNCSrUDrkI8ZHqQCVIPn6s3yNJVMJKaQERqDlWhZ0cvhDQQi07E1Iuf0y359Rprt4lYjqQRRa1cuCVub7EK8SCmX/BU0W2yKmpaXF4cOHOXv2LIcOHeL7779n6tSpnD9/Psvt3ozjgfSrNQkh0r32+pq5ae+9+drrcUAeHh48ffqUZcuWYW9vj56eHk2aNFFH8mQlJ+PJjZxE8GRFt1PlPD3UUJASD4VBfDK6XUpeWGQaVUQ8Cb/4ozegOgrj4n+II03KnZckHQxD7zMXFLqZP8mXEvyK5NPhRTiyvJFztsVAoVDQtGlTZs2axZUrV9DV1WXXrl3o6urmKM7G1NQUGxubdHE5Z8+ezffjiqdOncLT05OOHTtSo0YN9PT0ePZM84wqo9gdFxeXfI0noyii1yN4HB0dNb7SIoikUqyUra4mz2yL2Pnz5zl69Cjt2rXDysqK8+fP8/TpU1xcXIiPj+fgwYMEBQVhYWGRaRQPwMSJE5k5cyZVq1albt26rF+/nqtXr7J58+Z8jc/R0ZGNGzfSsGFDIiMjmThxYrqQxoxidyZOnEjv3r2pX78+rVu35q+//mLnzp0cOZKzJAN7e3sUCgV79+6lY8eOGBgY5CiCR5LeFvLMtoiZmppy8uRJOnbsiLOzM9OmTcPb25sOHTowdOhQqlWrRsOGDSlXrhxnzpzJtB9PT0/Gjx/P+PHjqVWrFgcOHGDPnj04OTnla3y//PILERER1KtXjwEDBuDp6YmVlZVGm4xid7p168by5ctZtGgRNWrUYPXq1axfv55WrVrlaL8VK1Zk1qxZTJkyhfLly6tDJ7OL4JFKsVK2IKFcYlEqddJicQzmvi/nbHMgbc5Wf3itkjVnG/yKpAP30BtaI9s529gJp3MUTVOc5JmtJElSEZDFVpIkqQjIC2RSqaV6GEOKfu7/iqsi4knafw/dHlVRGOTzoYancYjEFFKCX+W5j6TTj1BoK9F+P/3DLgVBRCamrk8bEpnjhcBFbDKJf9xC92OnQpt6UD2IRhWVSMrdSBRZ3P+rehBdKPsvaHLOVip1ZCzOO0ip4OzpM+onDUsieWYrlTpp9+xOHdUfF8fs40re9CziFX/s9eWzXu4YGugX9PBy7dDJS+joaPNBk7rFPRS1mNg4Vv++j8/7dMTUuHhjzkPuP2b6kvU5etClOMliK5Va7Zo3oEXjOrneLuzhf5y/Ekjvjq0wM02fzlvUXryMQl9Pl/5d2xT3UNQiXkWx7/gFerVvQTmLMsU6lsv/3mL6kvXFOoackBfIJEmSioAstpIkSUVAFlspVxwcHFi2bJn6+6LOFfPx8VEvwShJbxNZbN9RBZEj9qY3c8UkSfofWWwLWU6WJsytkppBJnPFJClzstgWsFatWjF69Gi++uorLC0tadu2Lf7+/nTs2BFjY2PKly/PgAEDNJYtVKlULFy4EEdHR/T09LCzs2PevHkAGWaQrVmzBlNT03RZXH/99RdGRkZERUWRmJjI6NGjsba2Rl9fHwcHB+bPnw9kniMWHBxM165dKV++PMbGxjRq1CjHq3a9Pta0aQQPDw91ntrrX76+vkDqD6JJkyZRsWJFjIyMeO+999TvpfHx8cHOzg5DQ0O6d+/O8+fPczweSSpJ5ClIIdiwYQMjRozgzJkzvHjxgpYtWzJ06FCWLFlCXFwckydPpnfv3hw7dgyAr7/+mrVr17J06VKaNWtGeHg4gYGBGn1OnjwZb29v1q9PvZ/w2rVrrF+/nl69eqnbpH1vYmLC4sWL2bNnD1u3bsXOzo779+9z//59IDVHzMrKivXr19O+fXu0tFIX+YiOjqZjx47MnTsXfX19NmzYQOfOnQkKCsLOLvf3qy5fvpwFCxaov1+wYAG///471atXB+Czzz4jNDSULVu2YGNjw65du2jfvj03btzAycmJ8+fPM3jwYL799lt69OjBgQMHmDlzZo73f+bSv7yMzH1kytPnL3n43zP2+17AyDB/99kmJqb+FqKrm7enrIQQ3AgKQVdHmz1HzuZrLJlRqVQkJCahr6eb48Xeo2Pi+O9ZBAdOXsTMJP3C9gUhJUVFUnIyero6WY4r+N7DQtl/QZPFthA4Ojry3XffATBjxgzq16/Pt99+q37/l19+wdbWllu3bmFtbc3y5ctZuXKlen3WqlWr0qxZM40+38wg+/zzz3Fzc+PRo0fY2Njw7Nkz9u7dy+HDhwEICwvDycmJZs2aoVAo1HlnQKY5YnXq1KFOnf/dlzp37lx27drFnj171Ese5oaZmZl6Td6dO3fy008/ceTIESpUqEBwcDC///47Dx48wMbGBkjNSztw4ADr16/n22+/Zfny5bi7uzNlyhQAnJ2dOXv2rEaKcFYu3bhF+NOIXI9bCEH1qracvXwzX0kTAAF37pGUnELt6nlf9UtLqSQlRcWRM5ezb5wHsXHxnL18k+aNaqH3/w+EZEcIQe3qVbhwLTDfn1Fmnj5/if+dezRrWFN9QpCRJ89z/2dcHGSxLQSv54X5+flx/PhxjI3T3xwfHBzMy5cvSUhIoHXr1jnuE6Bx48bUqFGDX3/9lSlTprBx40bs7Oxo0aIFkPorfNu2balWrRrt27enU6dOtGvXLst9xMTEMGvWLPbu3cujR49ITk4mLi4u2/yx7Fy5coWBAwfyww8/qH+IXL58GSEEzs7OGm0TEhKwsEhdFjEgIIDu3btrvN+kSZMcF9sxn/XI00MNBWnN73uJiY1n3JBe2TcuJo+fvmDsnB9YMGko5mYmxT0ctUvXg1j9+168p45AXy/zHwKX/73FH3t9i25geSSLbSF4PS9MpVLRuXNnFi5cmK6dtbU1d+/ezXWfaT7//HNWrlzJlClTWL9+PZ999pn6LKN+/fqEhITw999/c+TIEXr37k2bNm3SzfO+buLEiRw8eJDFixfj6OiIgYEBvXr1ytdFvsePH9OlSxeGDBnCkCFD1K+rVCq0tLTw8/NLd9aS9oNJLtvxbiusM+biIottIatfvz47duzAwcEhw6v0Tk5OGBgYcPToUT7//PNc9f3pp58yadIkVqxYwc2bN9PFxJiamtKnTx/69OlDr169aN++PS9evKBs2bIZ5oidOnUKDw8P9dlkdHQ0oaGhuTvg18THx9O1a1eqV6/OkiVLNN6rV68eKSkpPHnyhObNm2e4vaurK+fOndN47c3vJeltIe9GKGSjRo3ixYsX9OvXjwsXLnD37l0OHTrE4MGDSUlJQV9fn8mTJzNp0iR+/fVXgoODOXfuHOvWrcu2b3Nzc3r06MHEiRNp164dlSpVUr+3dOlStmzZQmBgILdu3WLbtm1UqFBB/UBAWo7Y48ePiYhInfNydHRk586dXL16lWvXrvHJJ59oJO/m1vDhw7l//z4rVqzg6dOnPH78mMePH5OYmIizszP9+/dn4MCB7Ny5k5CQEC5evMjChQvZv38/kBr9c+DAAb777jtu3brFypUrczyFIL39SttvNrLYFjIbGxvOnDlDSkoK7u7u1KxZkzFjxmBmZoZSmfrxT58+nfHjxzNjxgxcXFzo06cPT548yVH/Q4YMITExkcGDB2u8bmxszMKFC2nYsCGNGjUiNDSU/fv3q/eZUY7Y0qVLMTc3x83Njc6dO+Pu7p6vmJETJ04QHh6Oq6sr1tbW6q+zZ1Ovqq9fv56BAwcyfvx4qlWrRpcuXTh//rw6Off999/n559/5vvvv6du3bocOnSIadOm5Xk80tultE0jyPVs33KbN29mzJgxPHr0SL204LsuLYPsxJYl8gJZDqRdIFs1Z2yJukDmd+MWP/32F997fZntBbIGXUaU+AwyOWf7loqNjSUkJIT58+czfPhwWWglqYSTxfYt9d133zFv3jxatGjB119/XdzDKZGC7j7A2NCgWMcQ9vA/4hISufzvrWIdR1aeRbwi4lUU1wLuYGpcOA8o5EVg8D2eRbziys3b6GXxUEjAnfzdmlhU5DSCVOrIWJx3j5ZSyanTp2UsjiQVpbQplSndq1O9ommut38elcC2s/cZ2MoBQ73i/ydy+NpjdLSVtKphVdxDUYuJT+bno3f57MPKmBoUTuBjToU8iWHW1psyFkeSikub2hVo5lou19uFPYvl/J0X9HSzw8yweAsJwIvoRPR0tejb3D77xkUkIjqRv68+pvv7tpQzLd4id+VuBLO23izWMeSEvPVLkiSpCMhiK0mSVARksX0HeXl5Ubdu3eIehiS9U2SxfQdNmDCBo0ePFlh/rVq1YuzYsQXWnySVRvICWSmSmJiYo4cbjI2NM1zyUZKkwiPPbEuwqKgo+vfvj5GREdbW1ixdulTjLNLBwYG5c+fi4eGBmZkZQ4cOBVJTHZydnTE0NKRKlSpMnz5dI7fszWkEDw8PunXrxuLFi7G2tsbCwoJRo0ZpbPPjjz/i5OSEvr4+5cuXVydEeHh4cOLECZYvX66OvUlbKezEiRM0btwYPT09rK2tmTJlCsnJyeo+W7VqhaenJ5MmTaJs2bJUqFABLy8vjc/g1atXDBs2DCsrK0xNTfnwww+5du1aAX7KklQ0ZLEtwb766ivOnDnDnj17OHz4MKdOneLyZc3V+hctWkTNmjXx8/Nj+vTpAJiYmODj44O/vz/Lly9XR+5k5fjx4wQHB3P8+HE2bNiAj48PPj4+AFy6dAlPT09mz55NUFAQBw4cUC9Svnz5cpo0acLQoUMJDw8nPDwcW1tbHj58SMeOHWnUqBHXrl1j1apVrFu3jrlz52rsd8OGDRgZGXH+/Hm+++47Zs+erU6bEELw0Ucf8fjxY/bv369+9r1169a8ePGiID5iSSoychqhhIqKimLDhg389ttv6hSH9evXqyNk0nz44YdMmDBB47XXV8ZycHBg/Pjx/PHHH0yaNCnT/Zmbm7Ny5Uq0tLSoXr06H330EUePHmXo0KGEhYVhZGREp06dMDExwd7eXr1SmJmZGbq6uhgaGmpE7Pz444/Y2tqycuVKFAoF1atX59GjR0yePJkZM2aoVx+rXbu2OlfMycmJlStXcvToUdq2bcvx48e5ceMGT548Ud+wvnjxYnbv3s327dsZNmxYlp/h2cBnvIzNfRLx08gEHr2I48CVcIzy+VBDYnLqEpW62nk7rxFC8O/9V+hqK9l76VG+xpIZlRAkJKnQ11HmPIMsPpknL+M5dPVxod2LnKISJKWo0NPOelx3H0cXyv4Lmiy2JdTdu3dJSkqicePG6tfMzMyoVq2aRrs343IAtm/fzrJly7hz5w7R0dEkJydjapr1k1Q1atTQSEywtrbmxo0bALRt2xZ7e3uqVKlC+/btad++Pd27d8fQ0DDT/gICAmjSpInGP5KmTZsSHR3NgwcP1AGStWvX1tjO2tpavbykn58f0dHR6picNHFxcQQHB2d5PACX70bw+FV8tu3eJARUszHlXNBz8rvKX+DDSJJSBLXszPLch5ZSQYpKcOzGf/kbTCZiE1I4d+sZTauXQ08nZz8UhICa9mZcuvMi359RZp5GJhD4IBK36pZoKTPfydNXCYUzgAImi20JlbZkxZs/0d9cyuLNuJxz587Rt29fZs2ahbu7O2ZmZmzZsgVvb+8s96ejo3l2olAo1AuHm5iYcPnyZXx9fTl06BAzZszAy8uLixcvqhcjz2j8mY399dez2q9KpcLa2jpdvDmQ6X5fN7qjU56eICtIPx+5S2xCMp4fOWffuJg8fhnPRJ+rzP2kFubGJWf1OL/gF/x85C4LB9RBXzfzwMcrdyPY9s/9IhxZ3shiW0JVrVoVHR0dLly4oF5MOzIyktu3b9OyZctMtztz5gz29vZMnTpV/dq9e/fyPR5tbW3atGlDmzZtmDlzJmXKlOHYsWP06NEDXV3ddBE7rq6u7NixQ6Ponj17FhMTEypWrJijfdavX5/Hjx+jra2Ng4NDvo9BeruUtsXD5QWyEsrExIRBgwYxceJEjh8/zs2bNxk8eDBKZdbzV46OjoSFhbFlyxaCg4NZsWIFu3btytdY9u7dy4oVK7h69Sr37t3j119/RaVSqac0HBwcOH/+PKGhoTx79gyVSsXIkSO5f/8+X375JYGBgfz555/MnDmTr776Sj1fm502bdrQpEkTunXrxsGDBwkNDeXs2bNMmzaNS5cu5euYJKmoyWJbgi1ZsoQmTZrQqVMn2rRpQ9OmTXFxcUFfXz/Tbbp27cq4ceMYPXo0devW5ezZs+q7FPKqTJky7Ny5kw8//BAXFxd++uknfv/9d2rUqAGkPiShpaWFq6sr5cqVIywsjIoVK7J//34uXLhAnTp1+OKLLxgyZEiuYm0UCgX79++nRYsWDB48GGdnZ/r27UtoaCjly5fP1zFJJV9pW/1Vrmf7FomJiaFixYp4e3trxIJLmtJicY7MbCXnbHMgbc52xef1S9Sc7eW7Eaw9HMzSz+plO2fb5OsjMhZHyrsrV64QGBhI48aNefXqFbNnzwZSz14lSXq7yGJbwi1evJigoCB0dXVp0KABp06dwtLSsriHJUlSLsliW4LVq1cPPz+/4h7GW+tWeBRG+rn/Ky6EYN4Ofz5uYku1PCQ9vO7+sxjiElO4cjciz30cvfEf957E8NmHlQvlCv3zqAQiYhK5fu9lsacuvC7oYSTPoxK4GhKBnk7m0wiBDyOLcFR5J+dspVJHZpC9ewwNDAgIDFQ/LFMSyTNbqdRJW/msyQefYGGV+398QgiuXdhPZacGmJWtkP0GhezR/UCiI5/j5OpWqPeevnrxmFOHfdi0aRMuLi6Ftp/CYGlpWaILLchiK5ViDs4NsKuc+jiwKiWFxMQ49A2yX1pSCMG94CtUqd6YChWdCnuY2dLS0ub50/vUqNc6y2KbnJRIiioZPb3MH6NOiI9BW1sXLe300wWP7gdx6rAPLi4uJfqq/ttKFlup1BMqFRdObcP/6jG6fjItT2e7b3p0P5BH9/wLYHSpjEwtcHJpgrZO3m69SklJ5shfP/LiaRg9BsxC39AkXZsXzx6w94+FVK3WGLfWn2oUbqFScfPy4TyPX8peqX+oQaFQsHv3bgBCQ0NRKBRcvXo10/a+vr4oFApevnxZqOPKyVgKw5vH5+Pjk6N1Bt526sJSQL+GK1Ck9lVQXwUxJkXqyLJuU7oegX2blPoz2/DwcMzNzYt7GOnY2toSHh6uvo3L19eXDz74gIiIiEItfm5uboSHh2NmlvEqVF5eXuzevTtXPwQcHBwYO3ZsiY3GUSiVNGrWizqNP8rRNEJOWNtWw9q2WvYNi4iWljatO48kJSXzaYSylpXoPXg+2tq66YquQqmkRv22XP7nz6IY7jupVBfbxMREjTVWSxItLa1iGZuurm6J/UwKk1JLq8AKbUmlra2LtnbW0xB6+kaZvpfTNSukvClVn26rVq0YPXo0X331FZaWlrRt21ZjGiFNYGAgbm5u6OvrU6NGjQyX8Dtz5gx16tRBX1+f9957T722a5odO3ZQo0YN9PT0cHBwSLeEoYODA99++y2DBw/GxMQEOzs71qxZo37/9WmE0NBQPvjgAyB1EW+FQoGHhweQerHmu+++o0qVKhgYGFCnTh22b9+e5edw7949OnfujLm5OUZGRtSoUYP9+/cDWU+T+Pj4MGvWLK5du6aOuElLa/Dy8sLOzg49PT1sbGzw9PRUf+b37t1j3Lhx6m0K6jMCePjwIX369MHc3BwLCwu6du2qjt2RpLdJqSq2kBqzoq2tzZkzZ1i9enWGbSZOnMj48eO5cuUKbm5udOnShefPn6drs3jxYi5evIiVlRVdunRRZ3L5+fnRu3dv+vbty40bN/Dy8mL69OnqwpTG29ubhg0bcuXKFUaOHMmIESMIDAxMNx5bW1t27NgBQFBQEOHh4SxfvhxITV1Yv349q1at4ubNm4wbN45PP/2UEydOZPoZjBo1ioSEBE6ePMmNGzdYuHBhjgIe+/Tpw/jx46lRo4Y64qZPnz5s376dpUuXsnr1am7fvs3u3bupVasWADt37qRSpUrMnj1bvU1BfUaxsbF88MEHGBsbc/LkSU6fPo2xsTHt27cnMTEx2+ORpJKk1E0jODo68t1332XZZvTo0fTs2ROAVatWceDAAdatW6cRGzNz5kz1jfEbNmygUqVK7Nq1i969e7NkyRJat26tXk3L2dkZf39/Fi1apD4jBejYsSMjR44EUkMYly5diq+vL9WrV9cYj5aWFmXLlgXAyspKPWcbExPDkiVLOHbsGE2aNAGgSpUqnD59mtWrV2e6rm1YWBg9e/ZUF8QqVapk+7kBGBgYYGxsjLa2tsZUQ1hYGBUqVKBNmzbo6OhgZ2enTpAoW7YsWlpamJiYaGxTEJ/Rli1bUCqV/Pzzz+oz5vXr11OmTBl8fX1p165dlsfzIOQmCXF5iEwREPXqKffvXifq1dPcb/96V0KQkpyU+ut9Hq9NhT+4RXTkM277ny2cC1wCkpMT832sUtZKXbHNKCbmTWmFC1IXxW7YsCEBAQGZtilbtizVqlVTtwkICEi3GEzTpk1ZtmwZKSkp6niZ1yNfFAoFFSpUUEe+5IS/vz/x8fHpnoZKTExUZ4DVqFFDvTh48+bN+fvvv/H09GTEiBEcOnSINm3a0LNnz3TxM7nx8ccfs2zZMnUsTseOHencuTPa2pn/9SmIz8jPz487d+5gYqJ5G1N8fHyOYnEeP7xFbHTegiHLlLXh5YtHvIp4nKft0yQkxBJ+PwjbyrXQ0srbPzeVKgVdPQPCgq/mayyZSUlJ4n7Iv5hb2GTfWMqzUlds34yJyamcnDGktckq8uV1WUW+5ERa23379qVLN0gLQNy/f796esPAwACAzz//HHd3d/bt28ehQ4eYP38+3t7efPnllzne9+tsbW0JCgri8OHDHDlyhJEjR7Jo0SJOnDiR7hjTFMRnpFKpaNCgAZs3b063Xbly2S+d2LBZd/VDDcXl5YtwTh5cT6uOQ7N82KA4JcTHcHDXMlzrteFOwD/FPZxSq9TN2ebEuXPn1P+fnJyMn59ful/tX28TERHBrVu31G1cXV05ffq0RvuzZ8/i7OysEZqYG2mPmL4eL+Pq6oqenh5hYWE4OjpqfKVF5djb26tfe70g29ra8sUXX7Bz507Gjx/P2rVrczyONyNuILWQd+nShRUrVuDr68s///yjvmiYWSxOfj+j+vXrc/v2baysrNIdf2a3rklSSVXqzmxz4ocffsDJyQkXFxeWLl1KREQEgwcP1mgze/ZsLCwsKF++PFOnTsXS0pJu3boBMH78eBo1asScOXPo06cP//zzDytXruTHH3/M85js7e1RKBTs3buXjh07YmBggImJCRMmTGDcuHGoVCqaNWtGZGQkZ8+exdjYmEGDBmXY19ixY+nQoQPOzs5ERERw7NixHD/r7uDgQEhICFevXqVSpUqYmJjw+++/k5KSwnvvvYehoSEbN27EwMAAe3t79TYnT56kb9++6OnpYWlpWSCfUf/+/Vm0aBFdu3Zl9uzZVKpUibCwMHbu3MnEiROpVKlSjvuSpOL2Tp7ZLliwgIULF1KnTh1OnTrFn3/+mW6N2AULFjBmzBgaNGhAeHg4e/bsUZ991q9fn61bt7JlyxZq1qzJjBkzmD17tsaFn9yqWLEis2bNYsqUKZQvX57Ro0cDMGfOHGbMmMH8+fNxcXHB3d2dv/76i8qVK2faV0pKCqNGjcLFxYX27dtTrVq1HBe5nj170r59ez744APKlSvH77//TpkyZVi7di1Nmzaldu3aHD16lL/++ksdMT579mxCQ0OpWrWq+tf7gviMDA0NOXnyJHZ2dvTo0QMXFxcGDx5MXFxcttHsklTSyCUWpVInLRan33DvDOdsHz+4RWJCHLZVamc6V//g3k0UKKho75ruPSEEjx/eIikxnkoONVEqM58WSZuzde8xNts525ioCOLjorI5upzT0dXHtIxVtu1en7Pd4TOtxMfLvK3eyWkE6d2VlJTA8f1riY56zqdfLMPAKP0ZckJCLEf+XIlSqUXfoYvQ1TPQeD8xMQ7f/T8TF/uKXp/Nw9Qs/zlnQgjuBJ4j5FbBpQaXK+9A0zYDCqw/KX9ksZXeKdpaOrjW+5D42Mh0RTSNjo4eNRu0Q6FQZLgKl462XmofcdEYGKRfXSsvFAoFNeq2pnqtFgXSH6SudyCVHLLYSqXWi6cP0NVNX1DL2zgC8PS/0Ay3E0IQeucyLrVb8ST8boZt0vp4/vR+lmOIevWM+LgonjwKRkc38wj6rITevsyriMfUbtShUB5qSEyIIy42mpfPHhZ439L/yDlbqdSRsTh5p1AoOXPmtMZDPVLBkGe2UqmTdteIzQceGJazz/X2QgieXNyDmVNj9M2tC3p4uRZ9/yaJkc8wd21RqOvRxkeE8+DwGvUDM1LBksVWKrXKODbGtHJdAERKMimJcWjnYI5VCEFk8CXMnZtgVLH416xVaOkQ9/QelnXdsyy2qqQEhCoZLb3Mn6JMjo9Gqa2HMoNYnOj7ATw4vCaDraSCIIutVOoJlYpHp3/n+bVDOPWdg4GVQ777jL7vT1TYjewb5pCuiSXmLs1Q6uTtrFKVkkzo3mXEPb1HtQEL0DZIf5dF3LP7BG+bTRnnJlT88LN0sThPr/yd5/FL2XsrLlfKaJuC9baOOz8KOhYHBSUuFqdA+5IK3FtxZiujbQrWm+POLx8fH8aOHVvoP9zySqFUYt20L1aNuuZoGiEnjCu5Ylwp/QMPxUWppY1Dp7GIlKRMpxEMLG2p/tkylJnE4pSr14H/zmW9ML2UdyW+2Mpom5xLSkrKdBWu15W0cRcFhZZ2gRXakkqprQvZxOJoZxGLI+/LLVwl7tOV0Tb/s3btWmxtbTE0NKR79+4sWbJE44zZy8uLunXr8ssvv1ClShX09PQQQnDgwAGaNWtGmTJlsLCwoFOnThrrv745jZA27XL06FEaNmyIoaEhbm5uBAUFqbe5du0aH3zwASYmJpiamtKgQQMuXbqEr68vn332Ga9evVLH4nh5eQGpq6UNHDgQc3NzDA0N6dChA7dv31b3mZbse/DgQVxcXNQpDGlpD2nWr1+Pi4sL+vr6VK9ePV8L/khScSlxxRZktA2k/qD44osvGDNmDFevXqVt27bMmzcvXbs7d+6wdetWduzYoS6eMTExfPXVV1y8eJGjR4+iVCrp3r17tmvpTp06FW9vby5duoS2trbGSmj9+/enUqVKXLx4ET8/P6ZMmYKOjg5ubm4sW7YMU1NTdSzOhAkTAPDw8ODSpUvs2bOHf/75ByEEHTt2VP8ZQGr0zeLFi9m4cSMnT54kLCxMvT2k/sCZOnUq8+bNIyAggG+//Zbp06ezYcOGLI9FkkqaEjmNIKNt4Pvvv6dDhw7qwuPs7MzZs2fZu3evRrvExEQ2btyosZh22ueSZt26dVhZWeHv70/NmjUz/UznzZunHs+UKVP46KOPiI+PR19fn7CwMCZOnKg+bicnJ/V2ZmZm6pSFNLdv32bPnj2cOXMGNzc3ADZv3oytrS27d+/m448/BlKnPn766SeqVq0KpP65zp49W93PnDlz8Pb2pkePHgBUrlwZf39/Vq9enekSk2miQq+RHJ+HhV2EIOHVEyJDrpAQmfNkjYz7UqFKTkr9FT+PF6+iHwSQGPmUiICToCiE8yMhUCUnkihjcQpViSy2Mtrmb4KCgujevbvGNo0bN05XbO3t7dOlFgQHBzN9+nTOnTvHs2fP1Ge0YWFhWRbb14/V2jr1Zv4nT55gZ2fHV199xeeff87GjRtp06YNH3/8sbpAZiQgIABtbW3ee+899WsWFhYafwaQuozi6/1YW1urP9+nT59y//59hgwZwtChQ9VtkpOTc7R4ePTDIJKin2fbLiP6ZSsS/+IhCRGP8rR9mpSEWKIfBGDiUBdlHheWF6oUtPQMiQz2y9dYMqNKSSYq9Br6ZStm31jKsxJZbGW0Tc7Hl9Fn1blzZ2xtbVm7di02NjaoVCpq1qyZbSLt68eatu+08Xt5efHJJ5+wb98+/v77b2bOnMmWLVvS/UDIaqwZHVdGn2/atmn7Xrt2rUbRBnKU9mDdtLf6oYbiEv/iEfcPrca+w8gsHzYoTsnx0YTs/g7Luu2JCDyd/QZSnpTIYpsT586do0WL1BWS0qJt0hbcfr2NnZ0dUDKibTKbMkhLPHhd9erVuXDhgsZrly5lv/ze8+fPCQgIYPXq1TRv3hwg3XHmlbOzM87OzowbN45+/fqxfv16unfvnmksTnJyMufPn1dPIzx//pxbt27lODWifPnyVKxYkbt379K/f/8COQZJKi5vbbEt7dE2X375JS1atGDJkiV07tyZY8eO8ffff2d79m5ubo6FhQVr1qzB2tqasLAwpkyZkudjAoiLi2PixIn06tWLypUr8+DBAy5evKieG3ZwcCA6OpqjR49Sp04dDA0NcXJyomvXrgwdOpTVq1djYmLClClTqFixYrrpm6x4eXnh6emJqakpHTp0ICEhgUuXLhEREcFXX32Vr+OSpKJUIu9GyInSHm3TtGlTfvrpJ5YsWUKdOnU4cOAA48aNQ18/62X6lEolW7Zswc/Pj5o1azJu3DgWLVqU52OC1F/Znz9/zsCBA3F2dqZ379506NCBWbNmAeDm5sYXX3xBnz59KFeunPri5vr162nQoAGdOnWiSZMmCCHYv39/ju4FTvP555/z888/4+PjQ61atWjZsiU+Pj5ZfnaSVBLJJRbfIkOHDiUwMJBTp04V91BKtLRYHNehP2Y4Zxv9MJCUhFhMK9fL9DeFqHs3QAEmdrXSvSeEIOZhIKrEeEwcaqPIIhYnbc62SvdJ2c7ZJka9ICUuMuuDywWlrgF6Zcpn2+71OdugXyfIWJxC8tZOI7wLFi9eTNu2bTEyMuLvv/9mw4YN8ob+fFIlJRD290oSI59R44vV6Bimv6shJSGGkL+8USi1cB3yPVpvZIepEmMJO/ADybGvqDbIGz2z7HO+siOE4GXQGV7eOp/vvtIYlq9CpdaDs28oFQlZbEuwCxcu8N133xEVFUWVKlVYsWIFn3/+eXEP662m0NLBsq47ybGv0NLNOIBRqaNPufodUSiUGa7CpdTWS+0jLirD1bXyNC6FAss67Shb88MC6Q/k47cljSy2JdjWrVuLewhvtfhnYWhlEItjZO0MQNx/GUfeCCGIvHMJi9qtiQ2/k2GbtD7in97LcgyJkU9Jjosk5tHtDMeSE6/uXCQ+Ihyrhp0LZfHwlIRYkuOiiH/+oMD7lv5HFlup1Em7n/jurgX56qcg7zl9dTv/0wNPLuwqgJFk7tXt86BQkpCQUKj7eVfJYiuVOjIWJ29kLE7hksVWKrVkLE56Mhan+MhiK5V6MhYnlYzFKV6y2ErvhEKLxSlJZCxOiSaLbSmnUCjYtWsX3bp1IzQ0lMqVK3PlyhXq1q2bYfuiivbJyVgKiozFSSVjcYqXLLalnMxvSyVjcVLJWJziI4ttKSbz2ySp5JA/ykoRmd8mSSWXPLMtZTZs2MCIESM4c+YMQogM146dOHEiy5Ytw9XVlSVLltClSxdCQkKwsLDQaLN8+XIqVKjAN998Q5cuXbh16xY6Ojrq/DYvLy/69OnD2bNnGTlyJBYWFhqrpnl7ezNnzhy++eYbtm/fzogRI2jRokW6SKG0/LaePXsSFBSEqampehH1adOmsXPnTlatWoWTkxMnT57k008/pVy5cpmuD5xGxuLkkIzFKRKy2JYyMr/tf2QsTs7IWJyiIYttKfOu5bdlRcbi5IyMxSkastiWMu9afpskvS3kBbJ30Llz59T/n5bf9uav9q+3KQn5bY6Ojhpftra2edqPJBUXeWb7Dirt+W2SVBLJYvsOSstvu3LlClWrVs0yv+327dvUqVMnw/y2GTNmMGfOHKytrQs0v+2zzz5j4MCB+Pj4MGfOHKysrJg/fz53796lTJky1K9fn2+++SbP+yrKWJzcKK5YHKloyAwyqdTJKoNMlZRA4Ibx2cbi3Fw7KtNYnJSEGII2Ts5RLE5OM8iEEDz121sssTgyg6xoyDNb6Z0iY3Gk4iKLrVRq5TUWB8DUvg5AiYjFKWwyFqdoyGIrlToFFYtTkAoiFqewyVicwiWLrVTqpF3Ia/LBJ1hY2eV6+8SEOG74HaRGvTboGxgX9PByLSE+hn8vH6ZWA3d09Qrv7PjVi8ecOuwj72EuJLLYSqWWg3MD7CrXzr7hG+JiIwm7e5VqNZthbGqR/QaFLCYqgvsh16leqwUGRgUzR5yRxw9vc+qwT6H1/66TM+iSJElFQBZbSZKkIiCLbS45ODiwbNky9fevrxf7+hqthcXHxydfSQZeXl4aMTQeHh7qJ8MkSSo872yxzWhR7fxKi3qpWbNmgfZbkCZMmMDRo0czfb9Vq1aMHTs2x/0VxQ8YSSoNCr3Ypt2GU5CSkpIKvM+CkBb1oq1dcq87GhsbaywSLklS0SjwYptRNIu/vz8dO3bE2NiY8uXLM2DAAJ49e6beRqVSsXDhQhwdHdHT08POzo558+YB/ztz2rp1K61atUJfX581a9ZgamqaLh7lr7/+wsjIiKioKBITExk9ejTW1tbo6+vj4ODA/PnzgdSpAIDu3bujUCjU3wcHB9O1a1fKly+PsbExjRo14siRIzk+9jfP8jw8PFAoFOm+0mJoEhMTmTRpEhUrVsTIyIj33nsvXUSNj48PdnZ2GBoa0r17d54/z34xbF9fXxo3boyRkRFlypShadOm3LuXevP9m9MIr/Pw8ODEiRMsX75cPdbQ0FAiIiLo378/5cqVw8DAACcnJ9avXw9A5cqVAahXL3WdgVatWgGpf6azZ8+mUqVK6OnpUbduXQ4cOJDus9q5cycffPABhoaG1KlTh3/++UdjTGfPnqVFixYYGBhga2uLp6cnMTEx2X4GklTSFMqZ7YYNG9DW1ubMmTMsWLCAli1bUrduXS5dusSBAwf477//6N27t7r9119/zcKFC5k+fTr+/v789ttvlC+vuYDG5MmT8fT0JCAggO7du9O3b1/1P/g069evp1evXpiYmLBixQr27NnD1q1bCQoKYtOmTeqievHiRXX78PBw9ffR0dF07NiRI0eOcOXKFdzd3encuTNhYWF5+hyWL19OeHi4+mvMmDFYWVmplyr87LPPOHPmDFu2bOH69et8/PHHtG/fntu3bwNw/vx5Bg8ezMiRI7l69SoffPABc+fOzXKfycnJdOvWjZYtW3L9+nX++ecfhg0blqP1apcvX06TJk0YOnSoesy2trbqP5e///6bgIAAVq1apV645sKFCwAcOXKE8PBwdu7cqe7L29ubxYsXc/36ddzd3enSpYv62NJMnTqVCRMmcPXqVZydnenXrx/JyckA3LhxA3d3d3r06MH169f5448/OH36NKNHj87Fn4IklQyF8vvu69EsM2bMoH79+nz77bfq93/55RdsbW25desW1tbWLF++nJUrV6qXzKtatSrNmjXT6HPs2LH06NFD/f3nn3+Om5sbjx49wsbGhmfPnrF3714OHz4MQFhYGE5OTjRr1gyFQoG9vb1623LlygFQpkwZjYTXOnXqUKdOHfX3c+fOZdeuXezZsydP/8DNzMwwM0td6GTnzp389NNPHDlyhAoVKhAcHMzvv//OgwcPsLGxAVLnUw8cOMD69ev59ttvWb58Oe7u7kyZMgVIjZ85e/asxhnimyIjI3n16hWdOnWiatWqABnmkGU2Xl1dXQwNDTU+l7CwMOrVq6dOgUj7oQX/+ywtLCw0tlm8eDGTJ0+mb9++ACxcuJDjx4+zbNkyfvjhB3W7CRMm8NFHHwEwa9YsatSowZ07d6hevTqLFi3ik08+Uc8hOzk5sWLFClq2bMmqVavQ19fP8ngehNwkIS46R8f+usSEOKIjnxNy6xL6hvmLPxdCkJKchLa2LuQtgoz4uGiiI59z99YFdPUyXs8hv1SqFCKePSyUvqVUhVJsX49m8fPz4/jx4xgbp38SJzg4mJcvX5KQkEDr1q1z3CdA48aNqVGjBr/++itTpkxh48aN2NnZ0aJFCyD1V+K2bdtSrVo12rdvT6dOnWjXrl2W+4iJiWHWrFns3buXR48ekZycTFxcXJ7PbNNcuXKFgQMH8sMPP6h/iFy+fBkhBM7OzhptExIS1HOqaWfxr2vSpIm62IaFheHq6qp+75tvvuGbb77Bw8MDd3d32rZtS5s2bejduzfW1tZ5Hv+IESPo2bMnly9fpl27dnTr1g03N7dM20dGRvLo0SOaNm2q8XrTpk25du2axmuvR+ekjfHJkydUr14dPz8/7ty5w+bNm9VthBCoVCpCQkKy/SHy+OEtYqNf5Pg4X9+HhZUdjx/eztFvBFmJj4vi8cPb2FetiyKPYY1p43kUFpjv8WQm8uVTXjy7Xyh9S6kKpdi+Hs2iUqno3LkzCxcuTNfO2tqau3czXwwksz7TfP7556xcuZIpU6awfv16PvvsM/Vfxvr16xMSEsLff//NkSNH6N27N23atMkyBnvixIkcPHiQxYsX4+joiIGBAb169crXRb7Hjx/TpUsXhgwZwpAhQ9Svq1QqtLS08PPzS5dukPaDKbvVL21sbDTuAkgLTVy/fj2enp4cOHCAP/74g2nTpnH48GHef//9PB1Dhw4duHfvHvv27ePIkSO0bt2aUaNGsXjx4iy3yyg6583XXo/OSXsvLQ5HpVIxfPhwPD090/VtZ5f9Y7gNm3XP0xNkBenZk3ucObKR1p1G5jnwsSjcvXWRfy8f4fmT/J1YSJkr9Mvm9evXZ8eOHTg4OGR4ld7JyQkDAwOOHj3K559/nqu+P/30UyZNmsSKFSu4efNmupX7TU1N6dOnD3369KFXr160b9+eFy9eULZsWXR0dDQiWABOnTqFh4eH+mwyOjqa0NDQ3B3wa+Lj4+natSvVq1dnyZIlGu/Vq1ePlJQUnjx5QvPmzTPc3tXVVSOeBjTjarS1tXF0dMxw23r16lGvXj2+/vprmjRpwm+//ZajYqurq5vuc4HU6QIPDw88PDxo3rw5EydOZPHixRnG2ZiammJjY8Pp06fVv2lA6sWuxo0bZzuGNPXr1+fmzZuZHqMkvU0KvdiOGjWKtWvX0q9fPyZOnIilpSV37txhy5YtrF27Fn19fSZPnsykSZPQ1dWladOmPH36lJs3b2qcCWbE3NycHj16MHHiRNq1a0elSpXU7y1duhRra2vq1q2LUqlk27ZtVKhQQf1AgIODA0ePHqVp06bo6elhbm6Oo6MjO3fupHPnzigUCqZPn56rgMI3DR8+nPv373P06FGePn2qfr1s2bI4OzvTv39/Bg4ciLe3N/Xq1ePZs2ccO3aMWrVq0bFjRzw9PXFzc+O7776jW7duHDp0KMv5WoCQkBDWrFlDly5dsLGxISgoiFu3bjFw4MAcjdnBwYHz588TGhqKsbExZcuWxcvLiwYNGlCjRg0SEhLYu3ev+ld4KysrDAwMOHDgAJUqVUJfXx8zMzMmTpzIzJkzqVq1KnXr1mX9+vVcvXpVY0ogO5MnT+b9999n1KhRDB06FCMjIwICAjh8+DDff/99jvuRpJKg0O+ztbGx4cyZM6SkpODu7k7NmjUZM2YMZmZmKP9/cePp06czfvx4ZsyYgYuLC3369Mlx5PWQIUNITExMl6FlbGzMwoULadiwIY0aNSI0NJT9+/er9+nt7c3hw4extbVVx2IvXboUc3Nz3Nzc6Ny5M+7u7vlasf7EiROEh4fj6uqKtbW1+uvs2bNA6q/7AwcOZPz48VSrVo0uXbpw/vx5dZjh+++/z88//8z3339P3bp1OXToENOmTctyn4aGhgQGBtKzZ0+cnZ0ZNmwYo0ePZvjw4Tka84QJE9DS0sLV1ZVy5coRFhaGrq4uX3/9NbVr16ZFixZoaWmxZcsWIPXsesWKFaxevRobGxt1xLmnpyfjx49n/Pjx1KpViwMHDrBnzx6cnJxy/PnVrl2bEydOcPv2bZo3b069evWYPn16vuafJam4vPWxOJs3b2bMmDE8evRI/Sut9G5Li8XpN9y7xMzZdu7z9VsxZxtw9ZiMxSkkJfdRp2zExsYSEhLC/PnzGT58uCy0kiSVaG/t2gjfffcddevWpXz58nz99dfFPRxJkqQsvbVntl5eXnh5eRX3MKQS7MXTB+jmIfcrLjaKCye38l7LPvlOanj5Ipz42CgeP7qNMo+R508eBXP31gUaNf8YLa3C+Scb8ewR8bEFF6MupffWz9lK0puOHDlC27Zti3sYbyUDA0MCAwNydB+zlDtv7ZmtJGUmbf6+devWWFlZ5Xr7+Ph4/Pz8aNiwYYnI43r69CmhoaHUr18/3QMwr3vx4gUHDx5k06ZNOX5E+02Wlpay0BYSWWylUsvJyUm9PkRuREdHc/fuXWrXrp3hk4tFLSQkhJiYGOrVq5fl8p0PHjzg4MGDuLi4yLsJSqC39gKZJEnS26TAiu2b8Sq5XfH/bRAYGMj777+Pvr4+devWLdUpBaX52CSpOBRYsV2+fDk+Pj6Zvv9mdld2fH19USgUvHz5Mt9jKygzZ87EyMiIoKAgjh49+lbE4BQFWZglKXsFNmebtm5raRYcHMxHH32ksTbu62u4SpIkZSZXZ7bbt2+nVq1aGBgYYGFhQZs2bdQRJVmltLZq1Yp79+4xbtw4ddwKwL179+jcuTPm5uYYGRlRo0YN9u/fT2hoKB988AGQutiMQqHAw8MDSF3v1dPTEysrK/T19WnWrJk6aQH+d0Z89OhRGjZsiKGhIW5ubgQFBWmM6a+//qJBgwbo6+tTpUoVZs2apU4IyIhCocDPz4/Zs2ejUCjw8vJKd0ZXWPvOKuYmJ1E+Dg4OfPvttwwePBgTExPs7OxYs2aNRpsLFy5Qr1499PX1adiwIVeuXNF4X0bjSFL+5LjYhoeH069fPwYPHkxAQAC+vr706NEj2zVXITWloFKlSsyePVsdtwKpK4IlJCRw8uRJbty4wcKFCzE2NsbW1pYdO3YAEBQURHh4OMuXLwdg0qRJ7Nixgw0bNnD58mUcHR1xd3fnxQvNRaKnTp2Kt7c3ly5dQltbW2OhmoMHD/Lpp5/i6emJv78/q1evxsfHR517ltnx16hRg/HjxxMeHs6ECRMybVuQ+84u5ianUT7e3t7qIjpy5EhGjBhBYGAgkLpoeqdOnahWrRp+fn54eXmlOz4ZjSNJ+ZPjaYTw8HCSk5Pp0aOH+tfoWrVq5WjbsmXLoqWlhYmJSbq4lZ49e6r7qVKlisY2kLqEX9qyiDExMaxatQofHx86dOgAwNq1azl8+DDr1q1j4sSJ6u3nzZtHy5YtAZgyZQofffQR8fHx6OvrM2/ePKZMmaJe/7ZKlSrMmTOHSZMmMXPmzAyPIS0119jYWH0Mr4dWvq4g951dzE1Oo3w6duzIyJEjgdSlC5cuXYqvry/Vq1dn8+bNpKSk8Msvv2BoaEiNGjV48OABI0aMUG//NkbjhIaGEh8fn+n7mYmLiyMyMpLAwMBso3eyo1KpUKlU+UpcfvLkCREREfj7+2d5n21OwkCl4pPjvwF16tShdevW1KpVC3d3d9q1a0evXr0wNzfP8849PT0ZMWIEhw4dok2bNvTs2VMjJuVNwcHBJCUlacSt6Ojo0LhxYwICAjTaZha3Ymdnh5+fHxcvXtQ4m0xJSSE+Pp7Y2Fi++uorNm3apH4vOjp3OVb52behoWbGVNmyZbOMuclplM/rY1IoFFSoUEG9jGVAQAB16tTR2HeTJk00tn8bo3EePHhAVFRUpu9nxcrKivv38x8T8+rVK16+fKkxz59bKpUKMzOzbFNNcvv3VCpaOS62WlpaHD58mLNnz3Lo0CG+//57pk6dyvnz59Vzdrn1+eef4+7uzr59+zh06BDz58/H29ubL7/8MsP2aVMWBRG3MmvWLI0AyTT6+vrMnj07y2mC7ORn3xnJKuYmp1E+r48pbVxpY8rJVNDbGI3TrFmzPD3UUJBu3bpFYGAgXbp0KfR9PXjwIN0PMqnkyNUFMoVCQdOmTZk1axZXrlxBV1eXXbt25WjbzOJWbG1t+eKLL9i5cyfjx49n7dq16vagGbfi6OiIrq4up0+fVr+WlJTEpUuXcvV4Yv369QkKCsLR0THdl1KpxMrKSuO1gpTdvjOTFnFz9uxZatasyW+//QZoRvnUqlWLChUq5DrKx9XVlWvXrhEXF6d+7c04HvhfNM6mTZtYtmyZ+iJbdtE4rzt79myu/6zSonHe/JLLakpvkxyf2Z4/f56jR4/Srl07rKysOH/+PE+fPs3xPxwHBwdOnjxJ37590dPTw9LSkrFjx9KhQwecnZ2JiIjg2LFj6v7s7e1RKBTs3buXjh07YmBggLGxMSNGjGDixImULVsWOzs7vvvuO2JjY7ON0HndjBkz6NSpE7a2tnz88ccolUquX7/OjRs3mDt3bo77yYvc7ju7mJuCiPL55JNPmDp1KkOGDGHatGmEhoamO2OdMWOGjMaRpHzI8ZmtqakpJ0+epGPHjjg7OzNt2jS8vb3VF6qyM3v2bEJDQ6latar6gkpKSgqjRo3CxcWF9u3bU61aNX788UcAKlasyKxZs5gyZQrly5dXX+xZsGABPXv2ZMCAAdSvX587d+5w8ODBXM0du7u7s3fvXg4fPkyjRo14//33WbJkSb7m1Qpr39nF3BRElI+xsTF//fUX/v7+1KtXj6lTp6ZLQ5bROJKUP3KJRanUSYvF+eKLL965Odvly5fLWJsSSi5EI0mSVARksZUkSSoCcj1bqdR69uxZsS/+/fTpU6Kjo3nw4EGh7yvtvmmpZJLFVip10u4x3r59e4H2q6+vT0JCQo7uS37Tm2tNFBaFQkFCQkKR7EvKHVlspVIn7f7bJh98goVVwUS8pCQn8V/oJcqUr4ahSdkC6bOgvXrxmFOHfYr9bF7KmCy2Uqnl4NwAu8qZP/6dG0mJ8cRHPqSqy3uULVcyM7oeP7zNqcM+xT0MKRPyApkkSVIRkMX2LZDblIs0Pj4+6hXTALy8vKhbt26W22S1LnFByslY8islOZnkpMQsv1KSk7LsQ902OREhVKhSkrLtM9f7SM5dfxl+JSdmuQ+p+MlphFKsT58+dOzYsbiHkaEJEyZoLDjk4eHBy5cv2b17d4HtI+TmUZ7dv5plG6My1rjWz/gpyOTkRK7/s42U5ASEUPHy6T1uXT2Ajq5BrsZhYm6DY80P0dZJv5ZDQnwsd24cJjYqf8sj6ugZU96+br76kAqXLLYlWGJiYp4XW0lKSsLAwAADg9wVhqJibGyMsbFxoe7DsqIr5W2yXkhIV9cw0/e0lNrYOr2HSpW6wI599eZ5GoeuniHKTNah1dbRpYJ9HZKT8ncHgZaWDskZLPQklRxyGiGPWrVqxZdffsnYsWMxNzenfPnyrFmzhpiYGD777DNMTEyoWrUqf//9N5C6DsSQIUOoXLkyBgYGVKtWTZ0+kSbtV/j58+djY2ODs7NzjsaSFi+zdetWWrVqhb6+Pps2bUo3jZBm9erV2NraYmhoyMcff5xhqOasWbOwsrLC1NSU4cOHayzZWBDRRK9PI3h5ebFhwwb+/PNPdWySr68vAA8fPqRPnz6Ym5tjYWFB165dc7yqWRlLW8pXrJbll3k520y3VyiVlLN2zLaPbPdhaYtSmXGx1dLSxsLKId/7sKxQJcP+pZJDFtt82LBhA5aWlly4cIEvv/ySESNG8PHHH+Pm5sbly5dxd3dnwIABxMbGolKpqFSpElu3bsXf358ZM2bwzTffsHXrVo0+jx49ql7Vau/evbkaz+TJk/H09CQgIAB3d/cM29y5c4etW7fy119/ceDAAa5evcqoUaMyHMPx48f5/fff2bVrF7NmzVK/XxDRRK+bMGECvXv3pn379urYJDc3N2JjY/nggw8wNjbm5MmTnD59GmNjY9q3b59uvV5JKulksc2HOnXqMG3aNJycnPj6668xMDDA0tKSoUOH4uTkxIwZM3j+/DnXr19HR0eHWbNm0ahRIypXrkz//v3x8PBIV2yNjIz4+eefqVGjRq4j0seOHUuPHj2oXLkyNjY2GbaJj49nw4YN1K1blxYtWvD999+zZcsWHj9+rG6jq6vLL7/8Qo0aNfjoo4+YPXs2K1asQKVSqaOJFi1aRIcOHXB1dWXt2rUYGBiwbt06jX2lxQO5uroyZcoUzp49m2FMjbGxMQYGBujp6VGhQgUqVKiArq4uW7ZsQalU8vPPP1OrVi1cXFxYv349YWFh6jPfkioxIY7Il/KJLul/ZLHNh9fjXLS0tLCwsNDIZStfvjzwv8cof/rpJxo2bEi5cuUwNjZm7dq16eJratWqleU87RdffKGe73xzzjMtHywrdnZ2VKpUSf19kyZNUKlUGr/iZxSREx0dzf379wskmiin0iJxTExM1MdbtmxZ4uPjCQ4OznE/xeHFs/vcuXG0uIchlSDyAlk+ZBQ1k1nEy9atWxk3bhze3t40adIEExMTFi1axPnz5zX6MDIyynKfWUX2ZLdtRtLG+GZUTWZtCyqaKCdUKhUNGjTIcLHxtDWRSypVSjJJCXHZN5TeGbLYFpFTp07h5uamTrgF8nR2ZmVlhZWVVZ7HERYWxqNHj9TTDP/88w9KpVLjYlxaRE7anQznzp3D2NiYSpUqYWFhoY4m+uSTT4D/RROlJeDmRUaxSfXr1+ePP/5QX6iTpLeZnEYoIo6Ojly6dImDBw9y69Ytpk+frnEFv6jo6+szaNAgrl27xqlTp/D09KR3794aEeSJiYkMGTIEf39//v77b2bOnMno0aNRKpUYGRmpo4kOHDiAv78/Q4cOzXU00ZscHBy4fv06QUFBPHv2jKSkJPr374+lpSVdu3bl1KlThISEcOLECcaMGVMkq2hJUkGSZ7ZF5IsvvuDq1av06dMHhUJBv379GDlypPrWsKLi6OhIjx496NixIy9evKBjx47qKKI0rVu3xsnJiRYtWpCQkEDfvn3x8vJSv79gwQJUKhUDBgwgKiqKhg0b5jqa6E1Dhw7F19eXhg0bEh0dzfHjx2nVqhUnT55k8uTJ9OjRg6ioKCpWrEjr1q1zfab78kU4oYFnSElJzvMYAYxNLani2hwdnfSLvSQlxhPsf4qYqOfEx74iNvIpfqe25HofOroG1GrUGUUmAaABVw4RG/0i3esxUelfk0oOGYsjlTppsTj9hnurF6KJiY7gv/uBqFT5K7b6hmZY27mipZX+PCUlOYnw+/7Ex0bmax/aOvrYOzXMdB79/t1rJMSl38fLF485um+NjMUpoeSZrfROMDI2p4pLk0Ldh5a2DpUq1ynUfQDYVsl4H48f3i70fUt5J+dsJUmSioA8s5VKrRdPH6Cby0Vj0kS9fIK2rj4Ghm/PXRDPn4Rl30gqNrLYSqVO2qO8B3cuLdB+8xOLU1QUCqWMxSmhZLGVSh0ZiyNjcUoiWWylUkvG4kglibxAJkmSVATkma1UaqXF4mRFoVCgpa2T6ftp278Zi5Mb2e4jORHyOw2c/dIWUjGTxVZ6qzg4ODB27NgcrcMgY3GkkkQWW6nUkrE4Ukkii630VshLHltaLE5epcXiFKa0WJyCIJ8gK9nkBTIp30pSHpsklVSy2EoFoqTlsRU3GYsjvUkWW6lAlLQ8tuImY3GkN8k5W6lA5CWP7eeff+bevXvExcWRmJiojjZPk10eW0kmY3GkN8kzW6lA5CWPbfDgwRw6dIirV6/y2WefpYsnz0ummiSVVPLMVipyBZXHJklvE1lspSLn6OjIr7/+ysGDB6lcuTIbN27k4sWLVK5cudD2KWNxpOImi61U5Iojj01HVx9T84oFEoujVGb8gIJSqYWxmRXaOvqYla2Y531o6+hDFtHyxmblM3yKTZDxuKSSQWaQSaVORhlk74LHD2+z4fuRMoOshJIXyCRJkoqAnEaQSi0ZiyOVJLLYSqVOYcXivA0MDAyxtLQs7mFIGZDFVip10h6EmDp1Ki4uLkW675CQEKZPn86mTZuKfN8AlpaW2NmVzCSJd50stlKp1a5dO1q0aFGk+7x8+TLTp0/HxcVFXqSSNMgLZJIkSUVAFltJkqQiIIutJElSEZDFVpIkqQjIYiu9td5cJUySSjJZbKUcU6lULFy4EEdHR/T09LCzs2PevHkA3Lhxgw8//BADAwMsLCwYNmwY0dHRABw8eBB9fX1evnyp0Z+npyctW7ZUf3/27FlatGiBgYEBtra2eHp6EhMTo37fwcGBuXPn4uHhgZmZGUOHDi38g5akAiKLrZRjX3/9NQsXLmT69On4+/vz22+/Ub58eWJjY2nfvj3m5uZcvHiRbdu2ceTIEUaPHg1AmzZtKFOmDDt27FD3lZKSwtatW+nfvz+QWqzd3d3p0aMH169f548//uD06dPqPtIsWrSImjVr4ufnx/Tp04vu4CUpv4Qk5UBkZKTQ09MTa9euTffemjVrhLm5uYiOjla/tm/fPqFUKsXjx4+FEEJ4enqKDz/8UP3+wYMHha6urnjx4oUQQogBAwaIYcOGafR76tQpoVQqRVxcnBBCCHt7e9GtW7dsx3rixAkBiBMnTuT+QPPJz89PAMLPz6/I9y2VbPLMVsqRgIAAEhISaN26dYbv1alTRyNZoWnTpqhUKoKCggDo378/vr6+PHr0CIDNmzfTsWNHzM3NAfDz88PHxwdjY2P1l7u7OyqVipCQEHW/DRs2LMzDlKRCI58gk3LEwCDzBV2EEOrYmzelvd64cWOqVq3Kli1bGDFiBLt27WL9+vXqdiqViuHDh+Pp6Zmuj9cfP5VROdLbShZbKUecnJwwMDDg6NGjfP755xrvubq6smHDBmJiYtTF8MyZMyiVSpydndXtPvnkEzZv3kylSpVQKpV89NFH6vfq16/PzZs3cXR0LJoDkqQiJqcRpBzR19dn8uTJTJo0iV9//ZXg4GDOnTvHunXr6N+/P/r6+gwaNIh///2X48eP8+WXXzJgwAB1qi6kTiVcvnyZefPm0atXL/T19dXvTZ48mX/++YdRo0Zx9epVbt++zZ49e/jyyy+L43AlqcDJM1spx6ZPn462tjYzZszg0aNHWFtb88UXX2BoaMjBgwcZM2YMjRo1wtDQkJ49e7JkyRKN7Z2cnGjUqBEXL15k2bJlGu/Vrl2bEydOMHXqVJo3b44QgqpVq9KnT58iPEJJKjwyFkcqddJicU6cOFEsq341aNBARtNI6chpBEmSpCIgi60kSVIRkHO2UqmTNjN29erVIt932n3F0dHRREZGFvn+peJhYmKS6e2PaeScrVTqnD9/nvfff7+4hyG9Q169eoWpadbhoLLYSqWOSqXi4sWLxMfHZ3u2URgsLCywtbUt8v1KxUee2UqSJJUQ8gKZlGMODg4a98cqFAp2794NQGhoKAqFoljmSbNy//599u/fz/bt2zl27JicR5WKjbxAJuXYxYsX36q1CaKioti4cSPz588nPj4eKysrli5dSs+ePdHS0iru4UnvGFlspRwrV65ccQ8hV2JjY7l27Zp6EfNHjx5x9OhR6tSpg5aWFhYWFupVxySpsMlpBEmtVatWjB49mtGjR1OmTBksLCyYNm2a+laqN6cRsnPixAkaN26Mnp4e1tbWTJkyheTkZAD++usvypQpg0qlAlJv01IoFEycOFG9/fDhw+nXr1+ej8fU1JTatWurL1xoa2sTHx/P2LFjGTBgADNnzuT06dPIyxZSUZDFVtKwYcMGtLW1OX/+PCtWrGDp0qX8/PPPue7n4cOHdOzYkUaNGnHt2jVWrVrFunXrmDt3LgAtWrQgKiqKK1euAKmF2dLSkhMnTqj78PX11YjNyS0DAwPee+89rKysgNSlGoOCgjhw4ADnzp1j5cqV/Prrrzx79izP+5CknJLFVtJga2vL0qVLqVatGv379+fLL79k6dKlue7nxx9/xNbWlpUrV1K9enW6devGrFmz8Pb2RqVSYWZmRt26dfH19QVSC+u4ceO4du0aUVFRPH78mFu3btGqVas8H0tcXBzGxsYMHDgQNzc37OzsePz4sfp9IQQhISEaOWeSVFhksZU0vP/++xr3CzZp0oTbt2+TkpKSq34CAgJo0qSJRl9NmzYlOjqaBw8eAKnTFr6+vgghOHXqFF27dqVmzZqcPn2a48ePU758eapXr56n44iIiGDbtm0MGTKElStXcv/+fRo2bIihoaFGu2rVqlGmTJk87UOSckMWW6lQZJTekDY3mvZ6q1atOHXqFNeuXUOpVOLq6qperSu/UwjXr1/nm2++wd/fn7i4OO7fv8/PP/9M9erVUSpT/9rr6urSuHHjbJ/8kaSCIIutpOHcuXPpvndycsr1rVKurq6cPXtW4+LT2bNnMTExoWLFisD/5m2XLVtGy5YtUSgUtGzZEl9f33wXW2tra7p06aIR5/Py5UvCwsKoWbMmAI0aNaJevXrq4itJhUn+LZM03L9/n6+++oqgoCB+//13vv/+e8aMGZPrfkaOHMn9+/f58ssvCQwM5M8//2TmzJl89dVX6uKWNm+7adMm9dxsixYtuHz5cr7na52dnZk0aRK//PILgwYNonLlyujo6HDt2jUcHR2xsLBg6NCheZ6mkKTckvfZShoGDhxIXFwcjRs3RktLiy+//JJhw4blup+KFSuyf/9+Jk6cSJ06dShbtixDhgxh2rRpGu0++OADLl++rC6s5ubmuLq68ujRI1xcXPJ1LA4ODtjb29O6dWuCg4MJDQ0lKCiI58+fs2DBApo3b46Ojk6+9iFJOSXXRpDUWrVqRd26dXN1L+3bJiEhgVevXpGQkEClSpWKZaEa6d0kz2yld4qenp76vltJKkpyzlaSJKkIyGkESZKkIiDPbCVJkoqALLaSJElFQBZbSZKkIiCLrSRJUhGQxVbKMV9fXxQKBS9fvizuoeRJWhCkvCYsFQdZbKV3RmBgIFOnTOHOnTvFPRTpHSSLrVSokpKSinsIQOpZrc/69dwNvsuvGzbIs1upyMli+xaJioqif//+GBkZYW1tzdKlS2nVqhVjx44FIDExkUmTJlGxYkWMjIx477331Itzp9mxYwc1atRAT08PBwcHvL29Nd5PSEhg0qRJ2Nraoqenh5OTE+vWrdNo4+fnp14b1s3NjaCgIPV7Xl5e1K1bl19++YUqVaqgp6eHEIKwsDC6du2KsbExpqam9O7dm//++y/ddhs3bsTBwQEzMzP69u1LVFRUvj6z5ORkoqKiOHfuHEcOHgLgwL79XLp0iejo6Fyv0ytJeSUf132LfPXVV5w5c4Y9e/ZQvnx5ZsyYweXLl6lbty4An332GaGhoWzZsgUbGxt27dpF+/btuXHjBk5OTvj5+dG7d2+8vLzo06cPZ8+eZeTIkVhYWODh4QGkLkTzzz//sGLFCurUqUNISEi62JipU6fi7e1NuXLl+OKLLxg8eDBnzpxRv3/nzh22bt3Kjh071EszduvWDSMjI06cOEFycjIjR46kT58+Gj8MgoOD2b17N3v37iUiIoLevXuzYMEC5s2bl+vP6vHjx6z8/nvu3L7Nk/+eEPHihbpwR0REMGzwEMwtLChvZYVzNWe+HDMGS0vLXO9HknJMSG+FyMhIoaOjI7Zt26Z+7eXLl8LQ0FCMGTNG3LlzRygUCvHw4UON7Vq3bi2+/vprIYQQn3zyiWjbtq3G+xMnThSurq5CCCGCgoIEIA4fPpzhGI4fPy4AceTIEfVr+/btE4CIi4sTQggxc+ZMoaOjI548eaJuc+jQIaGlpSXCwsLUr928eVMA4sKFC+rtDA0NRWRkpMbY3nvvvZx/SK9JSUkRmzdvFnVq1hSODpVFVXuHdF+ODpVF3Zq1xNatW0VKSkqe9iNJOSWnEd4Sd+/eJSkpicaNG6tfMzMzo1q1agBcvnwZIQTOzs4YGxurv06cOEFwcDCQGlXTtGlTjX6bNm2qjr25evUqWlpa2S7aXbt2bfX/W1tbA/DkyRP1a/b29hqx5wEBAdja2mJra6t+zdXVlTJlyhAQEKB+zcHBARMTE42+X+83N5RKJX379mXGrFkafb6uTJkyzJ43l169eskFxKVCJ6cR3hLijUiZN19XqVRoaWnh5+eXLlXB2NhY3Taz7QGNVIOsvL4GbFp/aZHkAEZGRun2kdFShm++/ubasgqFQqPf3FIqlXTv3p0rfpfZ8ttv6S6KdevZg06dO8tlFqUiIX+cvyWqVq2Kjo4OFy5cUL8WGRnJ7du3AahXrx4pKSk8efIER0dHja8KFSoAqWeTp0+f1uj37NmzODs7o6WlRa1atVCpVBpx4gXB1dWVsLAw7t+/r37N39+fV69e5XuB8Jx4/vyZurCnfQE8e/pUFlqpyMhi+5YwMTFh0KBBTJw4kePHj3Pz5k0GDx6MUqlEoVDg7OxM//79GThwIDt37iQkJISLFy+ycOFC9u/fD8D48eM5evQoc+bM4datW2zYsIGVK1cyYcIEIPXX+EGDBjF48GB2795NSEgIvr6+bN26NV9jb9OmDbVr16Z///5cvnyZCxcuMHDgQFq2bEnDhg3z/dlkJSEhgXv3wlAqlVSrXp0hw4bi6OSEUqkkNCSUxMTEQt2/JKWRxfYtsmTJEpo0aUKnTp1o06YNTZs2xcXFBX19fQDWr1/PwIEDGT9+PNWqVaNLly6cP39ePVdav359tm7dypYtW6hZsyYzZsxg9uzZ6jsRAFatWkWvXr0YOXIk1atXZ+jQocTExORr3AqFgt27d2Nubk6LFi1o06YNVapU4Y8//shXvznx6tUrzMzMmO41k81bfmfK11/z2x9b+Gb6NIyMjYmMjCz0MUgSyPVs32oxMTFUrFgRb29vhgwZUtzDKZESExOJj4/PMK781atXGBoayhwyqUjIC2RvkStXrhAYGEjjxo159eoVs2fPBqBr167FPLKSS1dXF11d3QzfMzMzK+LRSO8yWWzfMosXLyYoKAhdXV0aNGjAqVOn5M34kvQWkNMIkiRJRUBeIJMkSSoCsthKkiQVAVlsJUmSioAstpIkSUVAFtu3yOtr10qS9HaRxVbKFQcHB5YtW1bcw8i3uLg4/vzzT+bMmcO2bduIjo4u7iFJpZy8z7aUSExMzPTmfUlTQkIC48aNw8fHh8TERLS1tenVqxdr165Nt2KZJBUUeWZbQsXExDBw4ECMjY2xtrZOF1/j4ODA3Llz8fDwwMzMjKFDhwLZx944ODgwZ84cPvnkE4yNjbGxseH777/XaOPl5YWdnR16enrY2Njg6ekJpE5j3Lt3j3HjxmmsnpXT/X777bcMHjwYExMT7OzsWLNmjUabhw8f0qdPH8zNzbGwsKBr166Ehobm63PMyKFDh9iwYQMJCQkIIUhKSmL79u3s2LGjwPclSWrFsWK5lL0RI0aISpUqiUOHDonr16+LTp06CWNjYzFmzBghhBD29vbC1NRULFq0SNy+fVvcvn1bXLp0SSiVSjF79mwRFBQk1q9fLwwMDMT69evV/drb2wsTExMxf/58ERQUJFasWCG0tLTEoUOHhBBCbNu2TZiamor9+/eLe/fuifPnz4s1a9YIIYR4/vy5qFSpkpg9e7YIDw8X4eHhQgiR4/2WLVtW/PDDD+L27dti/vz5QqlUioCAACGEEDExMcLJyUkMHjxYXL9+Xfj7+4tPPvlEVKtWTSQkJBTY56pSqcTQoUOFQqEQgPpLoVCIHj16yMQGqdDIYlsCRUVFCV1dXbFlyxb1a8+fPxcGBgYaxbZbt24a22UXe5O2Xfv27TXa9OnTR3To0EEIIYS3t7dwdnYWiYmJGY7N3t5eLF26NE/7/fTTT9Xfq1QqYWVlJVatWiWEEGLdunWiWrVqQqVSqdskJCQIAwMDcfDgwQzHkhfJycmiQ4cOGoU27eu9997L9LglKb/knG0JFBwcTGJiIk2aNFG/VrZsWXUETpo314INCAhItyhN06ZNWbZsGSkpKeoEh9f7Tfs+7aLXxx9/zLJly6hSpQrt27enY8eOdO7cGW3tzP+q5HS/r8fpKBQKKlSooI698fPz486dO+kibOLj49WxPrnh5+fHzp071ekMSqWStm3b0rRpU2xtbVEoFBrJDQqFgkqVKgFw/vx59u3bR3Jysvr9jh070qxZs1yPQ5LSyGJbAokcLleRk/iZnPaVtp2trS1BQUEcPnyYI0eOMHLkSBYtWsSJEycyXYowp/vNKvZGpVLRoEEDNm/enG671/PMcio2NpaHDx+qxxETE8OmTZuYOHEiHTt2ZOPGjcTFxanba2tr06VLFzZv3sysWbOoU6eOxqpg8m4FKb9ksS2BHB0d0dHR4dy5c9jZ2QGp8du3bt3KMowxu9ibNOfOndNoc+7cOapXr67+3sDAgC5dutClSxdGjRpF9erVuXHjBvXr10dXV5eUlJQ87Tcr9evX548//sDKyirDtWdzq2nTpjRq1AilUom2tjZCCHbv3s2ECRPo1q0bnTt35s8//yQxMREdHR3atm3LtWvX2LFjB3PmzKFfv35oa2uTnJxMSkpKlmf2kpQT8m9QCWRsbMyQIUOYOHEiFhYWlC9fnqlTp2abADt+/HgaNWrEnDlz6NOnD//88w8rV67kxx9/1Gh35swZvvvuO7p168bhw4fZtm0b+/btA8DHx4eUlBTee+89DA0N2bhxIwYGBtjb2wOpdxWcPHmSvn37oqenh6WlZY73m5X+/fuzaNEiunbtyuzZs6lUqRJhYWHs3LmTiRMnqn/Fz6nAwEBGjRqFUqnE0tKS6tWr06JFC+bNm8f27duZOnUqAwcO5Pr161SrVo3KlSszd+5cvv32W6pWrcoPP/yAv78/jx49IiYmhqFDh9KvX79cjUGSXieLbQm1aNEioqOj6dKlCyYmJowfP55Xr15luU1a7M2MGTOYM2cO1tbW6WJvILUo+/n5Mev/Y769vb1xd3cHUuO9FyxYwFdffUVKSgq1atXir7/+wsLCAoDZs2czfPhwqlatqr51Kqf7zYqhoSEnT55k8uTJ9OjRg6ioKCpWrEjr1q3zdKZboUIFdaTPo0ePuH79Or/99hu6uro0b96cyMhIGjduTIsWLYiOjubu3btUrlyZxYsXExERgaOjIzVq1OCDDz7AzMyMunXr5noMkvQ6uZ7tO8bBwYGxY8e+c4/9pqSk8PTpU86fP8+2bds4f/48QggMDAyIiYlBqVRSu3ZtevbsiZubGxUrVpQPiUgFSp7ZSu8ELS0tKlSoQNeuXenUqRP//fcfISEhREZGYmVlRYUKFShfvrycm5UKjfybJb1ztLS0sLGxwcbGpriHIr1D5DSCJElSEZBrI0iSJBUBWWwlSZKKgCy2kiRJRUAWW0mSpCIgi61UoGR0jyRlTBZbSZKkIiDvs5XeCU+fPmX//v3cunWLBg0a0LZt23TLOUpSYZJntlKBU6lUTJo0ibJly1KhQgW8vLzU7718+ZJhw4ZRvnx59PX1qVmzJnv37gXg3r17dO7cGXNzc4yMjKhRowb79+/P11hSUlI4cOAA7u7uTJo0iX379jFs2DB69OiBn59fjpeglKT8kme2UoHbsGEDX331FefPn+eff/7Bw8ODpk2b0rp1azp06EBUVBSbNm2iatWq+Pv7q5dhHDVqFImJiZw8eRIjIyP8/f0xNjbO8zji4+Px9vZm2bJltGrVih9//BE9PT1u377NihUr6NatG/PmzaN///45XgpSkvJKFlupwNWuXZuZM2cC4OTkxMqVKzl69ChCCC5cuEBAQADOzs4AVKlSRb1dWFgYPXv2pFatWuney62oqCimTp3Kli1bmDx5MtWqVWPSpEn8+++/mJiY4OLigoWFBZ6enjx58gRPT89sF54RQhAdHS2nH6Q8kdMIUoF7Pf4GwNramidPnnD16lUqVaqkLrRv8vT0ZO7cuTRt2pSZM2dy/fr1PI/Bx8eHHTt24O3tTbly5Rg+fDhlypTBx8eHSZMmkZCQwN27d4mOjmb69OnMmDGDmJiYTPtLSkpizZo1dOnShefPn+d5XNK7SxZbqcBlFn9jYGCQ5Xaff/45d+/eZcCAAdy4cYOGDRumi1nPqU6dOvHnn38SHR3NhAkT6NOnD5s2bVKnT+zbt48tW7bQrl07lEolS5YswdPTk2fPnqXrKzY2lgULFjB16lRatmxZIEkS0rtHFlupyNSuXZsHDx5w69atTNvY2tryxRdfsHPnTsaPH8/atWvztC8HBwdu377NlClT1BfiwsLCiIyMJDExEV1dXT788EOWL1/OqFGj0NbWxsfHhx49enDmzBlSUlIQQhAcHMyQIUP4/vvvmTFjBlOnTs00i02SsiLnbKUi07JlS1q0aEHPnj1ZsmQJjo6OBAYGolAoaN++PWPHjqVDhw44OzsTERHBsWPHcHFxydO+zp8/z+TJk2ncuDHJyclMnTqVlJQULCwssLGxwcjIiP/++49Hjx4RGxuLs7Mz9erV48KFC3Tp0oWePXtSpkwZduzYgZGRET4+Pri7u8sLaVKeyWIrFakdO3YwYcIE+vXrR0xMDI6OjixYsABIvU1r1KhRPHjwAFNTU9q3b8/SpUvztJ8bN27QqlUrli9fjpGREeHh4fj7+3Pjxg3u3btHdHQ0NWvWpHr16tStW5cqVapgbGzM48ePWbduHfv27SMxMZE+ffowYsQIbG1tC/JjkN5Bcj1bqVRKTk5GpVLlOdomLi4OlUqFoaFhuph2ScoLWWwlSZKKgLxAJkmSVARksZUkSSoCsthKkiQVAVlsJUmSioAstpIkSUVAFltJkqQiIIutJElSEZDFVlJzcHBg2bJlBdqnr68vCoWCly9fFmi/kvS2kY/rSmoXL17EyMiouIdRJKKjozl79izXr1+nbdu2uLq6ygVmpEIli62kXgWrXLlyxT2UQqVSqXjw4AF//vknv/32G0+fPsXGxoaVK1dSr149Bg4cSKtWrTA3Ny/uoUqlkJxGKEB//fUXZcqUQaVSAXD16lUUCgUTJ05Utxk+fDj9+vUD4Pnz5/Tr149KlSphaGhIrVq1+P3339VtV69eTcWKFdX9penSpQuDBg3S2G+DBg3Q19enSpUqzJo1i+Tk5EzH6eHhQbdu3Zg/fz42NjbqxbzfnEZQKBSsWrWKDh06YGBgQOXKldm2bZv6/dDQUBQKBVu2bMHNzQ19fX1q1KiBr69vlp/T2bNnadGiBQYGBtja2uLp6amxcPePP/6Ik5MT+vr6lC9fnl69emXZX3bi4uI4ffo0I0eO5MMPP2TLli3079+fffv2sXHjRrZv346zszNTp07lww8/ZN68eQQFBZGSkpKv/UqSBiEVmJcvXwqlUikuXbokhBBi2bJlwtLSUjRq1EjdxtnZWaxatUoIIcSDBw/EokWLxJUrV0RwcLBYsWKF0NLSEufOnRNCCPH8+XOhq6srjhw5ot7+xYsXQldXVxw8eFAIIcSBAweEqamp8PHxEcHBweLQoUPCwcFBeHl5ZTrOQYMGCWNjYzFgwADx77//ihs3bgghhLC3txdLly5VtwOEhYWFWLt2rQgKChLTpk0TWlpawt/fXwghREhIiABEpUqVxPbt24W/v7/4/PPPhYmJiXj27JkQQojjx48LQERERAghhLh+/bowNjYWS5cuFbdu3RJnzpwR9erVEx4eHkIIIS5evCi0tLTEb7/9JkJDQ8Xly5fF8uXL8/Tn8ezZM/HLL7+IDz/8UDg4OIgBAwaIgwcPijt37oj169eLNm3aiCpVqqR7vXXr1sLBwUF8+umn4uDBgyI+Pj5P+5ek18liW8Dq168vFi9eLIQQolu3bmLevHlCV1dXREZGivDwcAGIgICATLfv2LGjGD9+vPr7Ll26iMGDB6u/X716tahQoYJITk4WQgjRvHlz8e2332r0sXHjRmFtbZ3pPgYNGiTKly8vEhISNF7PqNh+8cUXGm3ee+89MWLECCHE/4rtggUL1O8nJSWJSpUqiYULFwoh0hfbAQMGiGHDhmn0eerUKaFUKkVcXJzYsWOHMDU1FZGRkZmOP6dmzJgh6tevL7799ltx48YNcfHiRTFp0iTh4uIi6tatK+bMmSP2798vhg8fLqpWrSrc3NzE999/L4KCgsTJkyfFiBEjhIuLizh27Fi+xyJJchqhgLVq1QpfX1+EEJw6dYquXbtSs2ZNTp8+zfHjxylfvjzVq1cHUtdvnTdvHrVr18bCwgJjY2MOHTpEWFiYur/+/fuzY8cOEhISANi8eTN9+/ZVL2Lt5+fH7NmzMTY2Vn8NHTqU8PBwYmNjMx1nrVq1crT8YJMmTdJ9HxAQkGkbbW1tGjZsmK5NGj8/P3x8fDTG6+7ujkqlIiQkhLZt22Jvb0+VKlUYMGAAmzdvzvI4sjJu3Di2b9+Ok5MTU6dOpVevXgQFBTFnzhx27NiBq6sr//zzDwMGDGDfvn306dOHzZs389FHH/H777/zySef8Pfff+Pm5pan/UvS6+QFsgLWqlUr1q1bx7Vr11Aqlbi6utKyZUtOnDhBREQELVu2VLf19vZm6dKlLFu2jFq1amFkZMTYsWNJTExUt+ncuTMqlYp9+/bRqFEjTp06xZIlS9Tvq1QqZs2aRY8ePdKNRV9fP9Nx5ueug5ys75pZG5VKxfDhw/H09Ez3np2dHbq6uly+fBlfX18OHTrEjBkz8PLy4uLFi5QpUyZX4zxw4AALFiwgMTGRLl26MGPGDPT09NizZw9z584lPj4eBwcHNm7ciJOTE59++imbNm3i9u3bbNq0iQEDBuDk5MSyZctwdXXN1b4l6U2y2BawFi1aEBUVxbJly2jZsiUKhYKWLVsyf/58IiIiGDNmjLpt2pnvp59+CqQWotu3b2tEwRgYGNCjRw82b97MnTt3cHZ2pkGDBur369evT1BQEI6OjoVyPOfOnWPgwIEa39erVy9dmxYtWgCpi3b7+fkxevToDPurX78+N2/ezHK82tratGnThjZt2jBz5kzKlCnDsWPHMvyBkhUTExPGjx+Pm5sbd+7cYdmyZZw+fZqqVasyZswY2rdvj4WFBcHBwWzbto0lS5awcOFCunTpwrhx45g8eTLHjh2Tt4RJBaO45zFKo/r16wstLS2xcuVKIUTqRS0dHR0BiJs3b6rbjR07Vtja2oozZ86oLy6ZmpqKrl27avR36NAhoaenJ6pVqybmzJmj8d6BAweEtra2mDlzpvj333+Fv7+/2LJli5g6dWqm4xs0aFC6fQiR8ZytpaWlWLdunQgKChIzZswQSqVSfQxpc7Z2dnZi586dIiAgQAwbNkwYGxuLp0+fCiHSz9leu3ZNGBgYiJEjR4orV66IW7duiT///FOMHj1aCCHEX3/9JZYvXy6uXLkiQkNDxY8//iiUSqX4999/c/TZvy48PFwsX75cvP/++8LR0VGMGDFCnDlzRsTFxWXY/vnz52Lbtm2iS5cuwt7eXnTr1k3s3LlTxMbG5nrfkvQmWWwLwfjx4wWgUSDq1KkjypUrJ1Qqlfq158+fi65duwpjY2NhZWUlpk2bJgYOHJiuECYnJwtra2sBiODg4HT7O3DggHBzcxMGBgbC1NRUNG7cWKxZsybT8eWm2P7www+ibdu2Qk9PT9jb24vff/9d/X5asf3tt9/Ee++9J3R1dYWLi4s4evSous2bxVYIIS5cuCDatm0rjI2NhZGRkahdu7aYN2+eECL1YlnLli2Fubm5MDAwELVr1xZ//PFHpseSlZkzZ4qmTZuK77//Xty7d0+kpKTkaLvExERx+fJlMWnSJFGnTh15gUwqEDIWR8qUQqFg165ddOvWLcP3Q0NDqVy5MleuXKFu3bpFOraciI6ORqFQ5Hl+WgjBq1evMDIyklMJUr7JOVup1DI2Ns7X9gqFItcX5SQpM/LWL0mSpCIgpxEkSZKKgDyzlSRJKgKy2EqSJBUBWWwlSZKKgCy2kiRJRUDe+iUVCC8vL3bv3s3Vq1dzvI2DgwNjx45l7NixhTauNLGxsdy6dYuAgABiYmIwMTGhWrVqODo65vsWMUnKCVlspVItKSmJv/76i6VLl3LlyhX1CmIKhQIDAwOcnZ3p378/AwYMwMrKqphHK5VmchpBKrXi4+OZPn06AwYM4MyZM8TExCBSH1FHpVIRExPD1atXmTRpEu3atePo0aPIOyGlwiKL7TuoVatWeHp6MmnSJMqWLUuFChXw8vJSvx8WFkbXrl0xNjbG1NSU3r17899//2n0sWDBAsqXL4+JiQlDhgwhPj4+3T7enB7o1q0bHh4emY7r1atXDBs2DCsrK0xNTfnwww+5du1ano5RCMGKFStYsmQJsbGxmRbRtMJ7/fp1+vXrx4EDB/K0P0nKjiy276gNGzZgZGTE+fPn+e6775g9ezaHDx9GCEG3bt148eIFJ06c4PDhwwQHB9OnTx/1tlu3bmXmzJnMmzePS5cuYW1tzY8//piv8Qgh+Oijj3j8+DH79+/Hz8+P+vXr07p1a168eJHr/u7evcvSpUuzzGJ7c//Pnj1jwoQJPH36NNf7k6TsyDnbd1Tt2rWZOXMmAE5OTqxcuZKjR48CcP36dUJCQrC1tQVg48aN1KhRg4sXL9KoUSOWLVvG4MGD+fzzzwGYO3cuR44cSXd2mxvHjx/nxo0bPHnyBD09PQAWL17M7t272b59O8OGDctVfydPnuTJkye5mhYQQhAUFMTZs2fp2rVrrvYnSdmRZ7bvqNq1a2t8b21tzZMnTwgICMDW1lZdaAFcXV0pU6aMOuomICAgw7ic/PDz8yM6OlodD5T2FRISQnBwcK77e/z4cZ7nX5VK+c9CKnjyzPYd9eaSgQqFApVKhRAiw0ibzF7PjFKpTFfskpKSMm2vUqmwtrbOMAY9LytvNWzYEH19feLi4nK8jUKhoHLlyjRq1CjX+5Ok7Mgf4ZIGV1dXwsLCuH//vvo1f39/Xr16pY7rcXFx4dy5cxrbvfl9uXLlCA8PV3+fkpLCv//+m+l+69evz+PHj9HW1sbR0VHjy9LSMtfH0bJlSwYMGKAOxsxO2rq3s2bNokKFCrnenyRlRxZbSUObNm2oXbs2/fv35/Lly1y4cIGBAwfSsmVLGjZsCMCYMWP45Zdf+OWXX7h16xYzZ87k5s2bGv18+OGH7Nu3j3379hEYGMjIkSN5+fJllvtt0qQJ3bp14+DBg4SGhnL27FmmTZvGpUuXcn0curq6LF68mLFjx2JiYpLlWblCocDS0pKlS5dqXAiUpIIki62kQaFQsHv3bszNzWnRogVt2rShSpUq/PHHH+o2ffr0YcaMGUyePJkGDRpw7949RowYodHP4MGDGTRokLpQV65cmQ8++CDL/e7fv58WLVowePBgnJ2d6du3L6GhoZQvXz5Px2JiYsLChQv5888/6d69O2XLlkWpVKJQKNRfpqamdO3alb179zJkyJAcnwlLUm7J9Wyld0JycjIhISGcP3+emzdvkpKSQtWqVWnSpAkuLi4y9kYqdLLYSpIkFQE5jSBJklQEZLGVJEkqArLYSpIkFQFZbCVJkoqALLaSJElFQBZbSZKkIiCLrSRJUhGQxVYqcUJDQ1EoFLnKM8sJIQT//fdfntbHlaT8ksVWyrWUlBRUKlW61xMTE4thNDm3f/9+3NzcaNGiBT4+PrlaEUyS8ksW23eESqVi4cKFODo6oqenh52dHfPmzcPX1xeFQqGxSMzVq1dRKBSEhoYC4OPjQ5kyZdi7dy+urq7o6elx7949HBwcmDt3Lh4eHpiZmTF06FAAzp49S4sWLTAwMMDW1hZPT09iYmLU/Ts4OPDtt98yePBgTExMsLOzY82aNer3K1euDEC9evVQKBS0atUq38cfHh7O119/TceOHenduzfTp09n4MCB3Lx5U+aOSUVDSO+ESZMmCXNzc+Hj4yPu3LkjTp06JdauXSuOHz8uABEREaFue+XKFQGIkJAQIYQQ69evFzo6OsLNzU2cOXNGBAYGiujoaGFvby9MTU3FokWLxO3bt8Xt27fF9evXhbGxsVi6dKm4deuWOHPmjKhXr57w8PBQ929vby/Kli0rfvjhB3H79m0xf/58oVQqRUBAgBBCiAsXLghAHDlyRISHh4vnz5/n69hTUlLE5MmTRcOGDcXTp09FSkqKWLhwodDT0xP29vZixYoVIioqKl/7kKTsyGL7DoiMjBR6enpi7dq16d7LabEFxNWrVzW2tbe3F926ddN4bcCAAWLYsGEar506dUoolUoRFxen3u7TTz9Vv69SqYSVlZVYtWqVEEKIkJAQAYgrV67k9ZA1nD9/XlSqVEns2rVLCCHEs2fPRMOGDcX48ePFihUrhIODg3B3dxfnz58XKSkpBbJPSXqTnEZ4BwQEBJCQkEDr1q3z3Ieurm66KB1AvcZtGj8/P3x8fDSibdzd3VGpVISEhKjbvd6XQqGgQoUKPHnyJM/jy0xsbCxz586lWbNmdOjQASEE69evJzY2lq+++orRo0eza9cuAgMD6dSpEwsWLMhy3V1JyisZi/MOMDAwyPS9tLwt8dq8ZUbxNQYGBhkuwG1kZKTxvUqlYvjw4Xh6eqZra2dnp/7/zGJ5CtrWrVu5fv06e/fuRU9Pjzt37rBq1Sq+/vprbGxsAHj69CnJyckMGzaMDRs2cODAAebMmUOzZs3k+rZSgZFntu8AJycnDAwM1Om5rytXrhyARoRNfm65ql+/Pjdv3kwXbePo6Iiurm6O+khrl5KSkudxANy7d4+FCxcycuRIatSoQUpKCkuWLMHOzk6dyBAXF4e3tzcfffQRXl5e/P333zg6OvLJJ58wderUQjnblt5Nsti+A/T19Zk8eTKTJk3i119/JTg4mHPnzrFu3TocHR2xtbXFy8uLW7dusW/fPry9vfO8r8mTJ/PPP/8watQorl69yu3bt9mzZw9ffvlljvuwsrLCwMCAAwcO8N9///Hq1atcjyM5OZmFCxdiaWnJ0KFDUSgUnD9/nj///JOvv/4aExMTAP7++2/8/f3x9PREW1ubKlWq8NNPP7FixQr2799Px44d2b9/P8nJybkegyS9Thbbd8T06dMZP348M2bMwMXFhT59+vDkyRN0dHT4/fffCQwMpE6dOixcuJC5c+fmeT+1a9fmxIkT3L59m+bNm1OvXj2mT5+OtbV1jvvQ1tZmxYoVrF69GhsbG7p27Zrrcfj6+vLnn3/i5eWFubk58fHxzJ8/n9atW6vjeaKioliyZAn9+vVTh1lC6pl1z549OXDgAE2bNmXIkCGMGzcuT0VfktSK+wqdJBUGHx8fMXPmTJGcnCyEEOLFixfik08+Ef7+/uo24eHhon///uLevXuZ9pOUlCQOHjwounbtqr41TZLyQsbiSKVS2sW2tAuAkDq1oK2teU04JSUlRxfBMtpWknJDFltJkqQiIOdsJUmSioAstpIkSUVAFltJkqQiIIutJElSEZDFVpIkqQjIYisVGg8PD7p161bcw5CkEkEWW+mdIIQgKiqquIchvcNksZXeCffv3+ejjz5i5cqVsuhKxUIW23fQ9u3bqVWrFgYGBlhYWNCmTRuuXbuGUqnk2bNnAERERKBUKvn444/V282fP58mTZoAqU9eDRkyhMqVK2NgYEC1atVYvnz5/7V351FNHusfwL8xQIAgiBRwDwqyWDC4VsULKJdFLHXHghVQ3AoqUhQPWrdqa7UFUWr1iteAy3UXFyzWlk0QGxFXFrHggsVU0IKoSFjy/P7wkJ8RRDZDK/M5J0feybwz88ZzHobJ+87TYL9EhI0bN6JPnz7Q0NCAUCjEkSNH5O+ZmJjg+++/VzgnMzMTHTp0QH5+fouuuXv37ggMDIRIJMLEiRORmpra4l3FGKYpWLBtZyQSCTw8PDBz5kzk5OQgKSkJEydORJ8+faCnp4fk5GQAwLlz56Cnp4dz587Jz01KSoKdnR2Al4/D9ujRA4cOHUJ2djZWrlyJZcuW4dChQ2/s+8svv4RIJMK2bduQlZWFwMBAfPbZZ0hOTgaHw8HMmTMhEokUztm1axf+9a9/wdjYuEXXXVxcDH19fRw/fhxDhgyBt7c3AgMD5XnWGOada8N9GZg2kJGRQQDo7t27dd6bOHEizZ8/n4iIFi1aREFBQfTBBx9QVlYWVVVVkZaWFsXFxb2xbT8/P5o0aZL82Nvbm8aNG0dERM+ePSN1dXVKS0tTOMfX15c8PDyIiOjBgwfE5XJJLBYTEVFlZSXp6+tTVFRUi66ZiOjChQtkZmZGPj4+dPPmTRKLxTRhwgQyNzenzZs3K6QFYph3gc1s2xmhUAgHBwdYWVlhypQpiIyMRElJCQDA3t4eSUlJAIDk5GSMGjUKtra2SE5ORnp6Ol68eAEbGxt5W9u3b8fgwYOhr68PLS0tREZGoqCgoN5+s7OzUVFRAUdHR4WUObX76wJA165dMXbsWOzatQsAEBsbi4qKCoWljOb66KOPEBMTg8rKSowbNw7p6enYtm0b1q5di71798LNzQ2nT59m6c2Zd4ZtRNMOERHS0tJw9uxZxMTE4M8//4RYLMazZ88gFApx69Yt9OvXD48ePUJUVBTS0tIgFApx/PhxiMViAC/TzXh7eyM0NBTDhw9Hx44d8d1330EsFsszPfj4+KC0tFR+3rBhw5CUlITu3bsrjIfH46Fnz54AgFOnTmH69OmQSCSYOnUqDA0NERkZ2eRrvHXrFs6cOQMNDQ3w+Xx5cFdRUcGvv/6KHTt2oG/fvli2bBmEQiF2794NkUiELl26YNKkSbC1tYWxsTH4fL7CzmEM01xsz7h2iMPhwMbGBjY2Nli5ciUEAgFiYmIQGBgIPT09rFu3DkKhENra2rCzs8P69etRUlIiX68FgJSUFIwYMQJ+fn7ysoa+xOrXrx94PB4KCgoU2nmdq6sr+Hw+tm3bhri4OIU146YoLi5GSkoKnj17hvLycrx48QIvXrxAZWUlZDIZVFRUkJmZiWnTpsHV1RVLly6Fh4cHYmNjcfLkSWzZsgV8Ph8WFhb49NNP2f3CTIuxYNvOiMVixMfHw8nJCQYGBhCLxSguLoaFhQU4HA5sbW2xd+9eBAYGAniZeaGyshLx8fEICAiQt2NiYoLdu3fj559/Ru/evbFnzx6kp6ejd+/e9fbbsWNHLF68GIGBgZDJZBg5ciTKysqQlpYGLS0teHt7AwC4XC58fHwQEhICExMT+d0PTdWpUyc4OjqCy+VCVVVV/gJefrlX+yorK8OePXvg4uKCmTNnwsPDAzNmzMCjR4+QmZmJy5cvswwNTKtgwbad0dbWxrlz5xAeHo6ysjIIBAKEhoZizJgxAIBRo0bh2LFjsLe3B/ByFvyvf/0LsbGxGDlypLydefPm4erVq5g6dSo4HA48PDzg5+eHuLi4N/a9du1aGBgYYP369bh9+zY6deqEgQMHYtmyZQr1fH198c0332DmzJnNvs7c3FwcO3YMUqkUUqkUVVVVqK6uRk1NjUKwlclkqKqqglQqRUREBP773//C2toaDg4OGDZsGGbNmiVPiskwLcHWbJm/nfPnz8Pe3h5//PEHDA0Nm9UGEUEmk4GI5K+ampoGX9XV1Xj8+DHOnTuHpKQk/P7775DJZFi7dq08Gy/DNBcLtszfhlQqxf379zFnzhx07doV+/bta7OxVFdX48mTJygoKED37t1hYGDQZmNh3g8s2DJ/G1FRUfD19YW1tTVOnjxZ564FhvknY8GWYRhGCdgNhAzDMErAgi3DMIwSsGDLMAyjBCzYMgzDKAELtgzDMErAgu1r7t69Cw6HI99MJSkpCRwOB6WlpS1q18jICOHh4Q3W4XA4OH78eIv6aa6oqCh06tSp1du1t7fHokWLWr3d1pKXl4eioqK2HgbTDrDHdd9ixIgRkEgk0NHReed9SSQS6OrqvvN+6jN16lS4urq2Sd9t5enTp5g+fTpUVVUhEolavEE5wzSEzWzfQk1NDV26dAGHw3nnfXXp0gU8Hu+d9/O6qqoqaGhovLdPSWVlZSE0NLTODPbcuXN4+PAhtLS04OnpiZycnDYaIdMetMtgK5PJsGHDBpiYmIDH46FXr174+uuv6637+jJC7Z/bsbGxMDMzg6amJiZPnoznz58jOjoaRkZG0NXVxYIFC+rkuHr69Ck8PT2hpaWFbt26ISIiQuH9V5cRapczjh07hlGjRkFTUxNCoRAXLlxQOCcyMhI9e/aEpqYmJkyYgLCwsAaXA2rbPXToEOzt7aGuro69e/fWWUZYvXo1rK2t8Z///Efe/pQpUxSWU2pTla9ZswYGBgbQ1tbG3LlzUVlZ+cb+KysrERwcjO7du4PP5+Ojjz6Sb1gOAPfu3YObmxt0dXXB5/Px4Ycf4qeffnpje28jlUoRHByMDRs2wMfHBxKJBMDLXzBRUVGYMGECvvzyS2RnZ8PDwwNXrlxpdl8M06A2yA7R5oKDg0lXV5eioqIoLy+PUlJSKDIykoiI7ty5QwDoypUrRESUmJhIAORpU0QiEamqqpKjoyNdvnyZkpOTSU9Pj5ycnMjd3Z2ysrLo1KlTpKamRgcOHJD3KRAIqGPHjrR+/XrKzc2lLVu2EJfLpbNnz8rrAKCYmBiFcZibm1NsbCzl5ubS5MmTSSAQUFVVFRERpaamUocOHei7776j3Nxc2rp1K3Xu3Jl0dHTeeO217RoZGdHRo0fp9u3bVFhYSCKRSOG8VatWEZ/Pp9GjR9OVK1coOTmZTExMyNPTU17H29ubtLS0aOrUqZSZmUmxsbGkr69Py5Ytk9exs7OjgIAA+bGnpyeNGDGCzp07R3l5efTdd98Rj8ejW7duERHR2LFjydHRka5fv075+fl06tQpSk5ObvT/7evS09PJyMiIzpw5Q8bGxuTs7EyFhYV0/fp1EggElJGRQStWrCBHR0fy9fUlc3NzunDhQrP7Y5g3aXfBtqysjHg8njy4vq4xwRYA5eXlyc+ZO3cuaWpq0tOnT+Vlzs7ONHfuXPmxQCAgFxcXhb6mTp1KY8aMkR/XF2x37twpfz8rK4sAUE5Ojvz8sWPHKrQ5bdq0RgXb8PBwhfL6gi2Xy6X79+/Ly+Li4qhDhw4kkUiI6GWw7dy5Mz1//lxeZ9u2baSlpUU1NTVEpBhs8/LyiMPhUGFhoULfDg4OFBISQkREVlZWtHr16jeOvylkMhl98cUX5O7uTteuXaMePXrQoEGDyMnJiXx9fcnNzY0ePnxIQqGQ9u3bRzt37iQdHR0yNTWlxMTEVhkDw9Rqd8sIOTk5kEqlcHBwaHYbmpqaCl+mGBoawsjICFpaWgplr68Rvr4R9vDhw9+6Tti/f3/5z127dgUAebu5ubkYOnSoQv3Xj99k8ODBb63Tq1cv9OjRQ2G8MpkMubm58jKhUAhNTU2FOs+ePcP9+/frtHf58mUQEUxNTRXykCUnJ8uzPCxcuBDr1q2DjY0NVq1ahevXrzfqeupTVFSEn376CdOmTcPp06fRr18/HDhwAPn5+di9ezcmTZqEixcvQiqVws7ODidOnICfnx88PDwwa9YsxMXFgdjWIUwraXd3I2hoaLS4jdod/2txOJx6y2Qy2VvbetsXb6+2W1u3tl0iqnN+Y4MDn89vVL1X1fbVmC8L66sjk8nA5XKRkZEBLper8F7tL6pZs2bB2dkZp0+fxtmzZ7F+/XqEhoZiwYIFTR7v2bNnoa6ujoEDB+Lrr7/G7NmzUVVVhcrKSlhbWyM6OhpqampwdnbG8+fPcePGDaxevRpWVlbg8/nw9/dHaGgoxo8fr5QvSJn3W7ub2fbt2xcaGhqIj49Xet+//fZbnWNzc/Nmt2dubo6LFy8qlF26dKnZ7b2uoKAADx48kB9fuHABHTp0gKmpqbzs2rVrChlpf/vtN2hpaSnMiGsNGDAANTU1KCoqgomJicKrS5cu8no9e/bEvHnzcOzYMQQFBTUr4aNUKsW+ffswadIk5OXl4fHjx3B2dsaZM2dgbGyMw4cPg8/nIykpCU5OTjh79ix69uwJCwsLqKqqIjAwEEFBQfjiiy+wf//+Rv3iZJiGtLuZrbq6OpYuXYrg4GCoqanBxsYGxcXFyMrKgq+v7zvt+/z589i4cSPGjx+PX375BYcPH8bp06eb3d6CBQtga2uLsLAwuLm5ISEhAXFxca02C1NXV4e3tze+//57lJWVYeHChXB3d1cIjJWVlfD19cWXX36Je/fuYdWqVZg/f369GWlNTU0xbdo0eHl5ITQ0FAMGDMCjR4+QkJAAKysruLq6YtGiRRgzZgxMTU1RUlKChIQEWFhYNHnsN27cQG5uLsLCwvDDDz9g5MiR0NPTw4kTJzB+/HgIBAJERkZi9uzZ2LBhA54/fw4PDw/5Xz4qKiqYN28eNDU1sXHjRowcORK9evVq/ofJtHvtbmYLACtWrEBQUBBWrlwJCwsLTJ06VSlPEQUFBSEjIwMDBgzA2rVrERoaCmdn52a3Z2Njg+3btyMsLAxCoRBnzpxBYGAg1NXVW2W8JiYmmDhxIlxdXeHk5ARLS0v8+OOPCnUcHBzQt29f2Nrawt3dHW5ubli9evUb2xSJRPDy8kJQUBDMzMzwySefQCwWy1OZ19TUwN/fHxYWFnBxcYGZmVmdPhvj119/xbBhw9C1a1dcvHgRn376Kf78808UFxfL86116dIFu3btQufOnXH//v06D3VwuVx4e3vj5MmT6NatW5PHwDCvYpuHv2dmz56NmzdvIiUlpUXtrF69GsePH5c/tlwfHx8flJaWttkjxg35448/AADdunXDjRs3YG5uDg6Hg1u3bqFfv34KM++SkhLcunULQ4YMqXdGzjCtod0tI7xvvv/+ezg6OoLP5yMuLg7R0dHNmgm+b15dMxYKhfKfLS0t69TV1dXFRx99pJRxMe0XC7b/cBcvXsTGjRvx9OlT9OnTB1u2bMGsWbPaelgMw7yGLSMwDMMoAVugYhiGUQIWbBmGYZSABVuGYRglYMGWYRhGCViwZRpUu2ctwzAtw279Yt5bNTU1Ld7TQEVFhW1Cw7QKFmyZ95JUKsX8+fORmZnZ7DY4HA4CAwMxZcqUVhwZ016xYMsAAI4cOYI1a9YgLy8PmpqaGDBgAE6cOFGnnpGRERYtWqSQMdfa2hrjx4+X74nA4XCwfft2nDp1CgkJCRAIBNi1axf09fUxa9YspKeno3///ti7d698X+Dax4M///xzrFu3Do8fP8bYsWMRGRnZrKy/qqqqmD59Oh4+fAipVIpLly7hxYsXcHBwaPRMlcPhNGrfX4ZpDBZsGUgkEnh4eGDjxo2YMGECnj59ipSUlBZtnL127VqEhYUhLCwMS5cuhaenJ/r06YOQkBD06tULM2fOxPz58xEXFyc/Jy8vD4cOHcKpU6dQVlYGX19f+Pv7Y9++fU3uv0OHDrC1tUVmZiZWrlyJ69evY9KkSTA0NASfz2dBlFE69gUZA4lEgurqakycOBFGRkawsrKCn5+fQuaJppoxYwbc3d1hamqKpUuX4u7du5g2bRqcnZ1hYWGBgIAAhUSPAFBRUYHo6GhYW1vD1tYWEREROHDgAP78889mjSE/Px+fffYZDAwMEBwcjPPnz2P27Nl19gBmGGVgwZaBUCiEg4MDrKysMGXKFERGRqKkpKRFbb6azsfQ0BAAYGVlpVBWUVGBsrIyeVlj0vA0hUgkgqmpKWbMmIGNGzfCxcUFiYmJmDdvXrPaY5iWYMGWAZfLxS+//IK4uDj069cPERERMDMzw507d+rU7dChQ53lhaqqqjr16kvn01CKn/o0JQ1PffLz8zF06FBIJBJUVlbC0NAQT548wePHj1FRUYHq6mr5HQsymQz0MgGqwothWgtbs2UAvAxoNjY2sLGxwcqVKyEQCBATE1Onnr6+PiQSify4rKys3qDcHLVpeGo36q4vDU9TDBw4EAcPHsTq1avh6+uL6OhorF+/HqqqqtDS0oK2tja0tbWhqakJLper8AJe/hLp378/AgIC6uRMY5imYsGWgVgsRnx8PJycnGBgYACxWIzi4mJYWFjUyW47evRoREVFwc3NDbq6ulixYkWrBaLGpOFpirlz56KkpAQBAQHQ19eHpaUlRo8ejc6dO8tntNXV1aioqKgzu61N4tmjRw92ny3TKliwZaCtrY1z584hPDwcZWVlEAgECA0NxZgxY3Dw4EGFuiEhIbh9+zY+/vhj6OjoYO3ata02s301Dc9ff/0FV1fXFm2Erq2tjXXr1mHOnDlITU3FxYsXkZaWhj/++APV1dXgcDjQ0NCAhoYG1NXVoa6uLv+Zy+WCw+FAW1ubLScwrYLtZ8v8LTQmDU9rqKqqwrNnz1BaWorS0lI8fvwYz58/R3l5ufzf8vJy1NTUAADMzMwwceJEli6HaTE2s2XaFVVVVejq6kJXV7eth8K0M+zXNcMwjBKwZQSGYRglYDNbhmEYJWDBlmEYRglYsGUYhlECFmwZhmGUgAXbNmBvb6+wH2x9jIyMEB4ertQ+G+vu3bvgcDgtvie2NcfEMH93LNgyDMMoAXuogXlvpaent3jv2mHDhmHQoEGtNCKmXSNG6ezs7Mjf35/8/f1JR0eHOnfuTMuXLyeZTCavIxAIaNOmTfLj0NBQsrS0JE1NTerRowd9/vnn9PTpU4V2U1NTydbWljQ0NKhTp07k5OREf/31l7zPgIAAed24uDjS1tam6Ojoesf4119/kaenJ33wwQekrq5OJiYmtGvXLiIiunPnDgGgo0ePkr29PWloaFD//v0pLS1Nfv6jR4/o008/pe7du5OGhgZZWlrS//73vzqfw6tjkkqltGTJEurWrRtpamrS0KFDKTExsSkfrYLp06cTh8MhAM16cTgcmjlzZrP7Z5hXsWWENhIdHQ0VFRWIxWJs2bIFmzZtws6dO99Yv0OHDtiyZQsyMzMRHR2NhIQEBAcHy9+/evUqHBwc8OGHH+LChQtITU2Fm5ub/Bn/Vx04cADu7u7YvXs3vLy86u1vxYoVyM7ORlxcHHJycrBt2zZ88MEHCnWWL1+OxYsX4+rVqzA1NYWHhweqq6sBvMy6MGjQIMTGxiIzMxNz5szB9OnTIRaL33iNM2bMwPnz53HgwAFcv34dU6ZMgYuLC37//fcGP8s3qampadEmMkRU7+fHMM3S1tG+PbKzsyMLCwuFmezSpUvJwsJCfvz6zPZ1hw4dIj09Pfmxh4cH2djYNNhnQEAAbd26lXR0dCghIaHBMbq5udGMGTPqfa92Zrtz5055WVZWFgGgnJycN7bp6upKQUFBdcZERJSXl0ccDocKCwsVznFwcKCQkJAGx/omnp6ezZ7V1r68vb2b1TfDvI6t2baRYcOGKeyTOnz4cISGhqKmpqbe/WETExPxzTffIDs7G2VlZfJ9WJ8/fw4+n4+rV6++NeX20aNH8fDhQ6SmpmLo0KEN1v38888xadIkXL58GU5OThg/fjxGjBihUOfV1Dddu3YFABQVFcHc3Bw1NTX49ttvcfDgQRQWFkIqlUIqlYLP59fb3+XLl0FEdTYKl0ql0NPTa3CsDPNPwJYR/gHu3bsHV1dXWFpa4ujRo8jIyMDWrVsB/H9KGg0Njbe2Y21tDX19fYhEorf+eT1mzBjcu3cPixYtwoMHD+Dg4IDFixcr1GkozU1oaCg2bdqE4OBgJCQk4OrVq3B2dkZlZWW9/clkMnC5XGRkZODq1avyV05ODjZv3vzWa2OYvzsWbNvIb7/9Vue4b9++9c5qL126hOrqaoSGhmLYsGEwNTXFgwcPFOr0798f8fHxDfZpbGyMxMREnDhxAgsWLHjrGPX19eHj44O9e/ciPDwcO3bsaMSVvZSSkoJx48bhs88+g1AoRJ8+fRpcex0wYABqampQVFQEExMThVdzMzUwzN8JC7Zt5P79+/jiiy+Qm5uL/fv3IyIiAgEBAfXWNTY2RnV1NSIiInD79m3s2bMH27dvV6gTEhKC9PR0+Pn54fr167h58ya2bduGR48eKdQzNTVFYmIijh492uADBStXrsSJEyeQl5eHrKwsxMbGwsLCotHXZ2Jigl9++QVpaWnIycnB3LlzG0xJbmpqimnTpsHLywvHjh3DnTt3kJ6ejg0bNuCnn35qdL8M83fFgm0b8fLywosXLzB06FD4+/tjwYIFmDNnTr11ra2tERYWhg0bNsDS0hL79u3D+vXrFeqYmpri7NmzuHbtGoYOHYrhw4fjxIkTUFGpuyxvZmaGhIQE7N+/H0FBQfX2qaamhpCQEPTv3x+2trbgcrk4cOBAo69vxYoVGDhwIJydnWFvb48uXbpg/PjxDZ4jEong5eWFoKAgmJmZ4ZNPPoFYLEbPnj0b3W9rY/nHmNbC9rNl3ltHjhzB6dOnW9TGJ598ggkTJrTSiJj2jAVbhmEYJWDLCAzDMErAgi3DMIwSsGDLMAyjBCzYMgzDKAELtgzDMErAgi3DMIwSsGDLvBMcDgfHjx8H0HppdBjmn4zt+tVGfHx8UFpaKg9If1ccDgcxMTFvffqrIT179oREIpHvh5uUlIRRo0ahpKQEnTp1ap2BvsWLFy+Qn5+P27dv49GjR1BTU4Oenh7MzMzQo0cPqKmpKWUcTPvFgu3fXFVVlcLuWv9EXC63zTaTKS8vx+HDh7F//35wuVwYGxtDX18flZWVKC4uRn5+Pjp27IgZM2bAxcXlH/9ZM39jbbmZbntw+PBhsrS0JHV1dercuTM5ODjQ4sWL62xSnZiYKN+U++DBg2RnZ0c8Ho927dpFNTU1tGbNGurevTupqamRUCikuLg4eR+vnjdy5EhSV1enwYMHU25uLl28eJEGDRpEfD6fnJ2dqaioSH7exYsX6d///jfp6emRtrY22draUkZGhvx9gUCgMEaBQCB/78cff6Q+ffqQqqoqmZqa0u7duxWuGwDFxMQojO/KlSvyn1HPBt0ymYw2bNhAvXv3JnV1derfvz8dPny42Z99cXExeXl5kY+PD125coWePHlCDx8+pNu3b1NBQQEVFxdTaWkpJSUl0YQJE2jhwoX05MmTZvfHMA1hwfYdevDgAamoqFBYWBjduXOHrl+/Tlu3bqWnT5+Su7s7ubi4kEQiIYlEQlKpVB6IjIyM6OjRo3T79m0qLCyksLAw0tbWpv3799PNmzcpODiYVFVV6datW0T0/8HM3Nyczpw5Q9nZ2TRs2DAaOHAg2dvbU2pqKl2+fJlMTExo3rx58vHFx8fTnj17KDs7m7Kzs8nX15cMDQ2prKyMiIiKiooIAIlEIpJIJPJAfezYMVJVVaWtW7dSbm4uhYaGEpfLVcj+8KZgW11dTUePHiUAlJubSxKJhEpLS4mIaNmyZfJryM/PJ5FIRDwej5KSkpr82VdUVJCvry+tWbOGbty4QatWrSIXFxcaPXo0OTk5kaOjI40aNYrGjRtHmzdvptzcXFq8eDH5+/uTVCpt1v83wzSEBdt3KCMjgwDQ3bt367zn7e1N48aNUyirDUrh4eEK5d26daOvv/5aoWzIkCHk5+encN6raWr2799PACg+Pl5etn79ejIzM3vjeKurq6ljx4506tQpedmrQbPWiBEjaPbs2QplU6ZMIVdX13rPezXYEhElJiYSACopKZHXf/bsGamrqyskjSQi8vX1JQ8PjzeO+U1+//13mjVrFoWHh5OtrS2FhYVRdnY2lZaWUnl5OT1//pweP35Mly5douXLl5OdnR1FRUXR7Nmz5b/EGKY1sTXbd0goFMLBwQFWVlZwdnaGk5MTJk+eDF1d3QbPGzx4sPznsrIyPHjwADY2Ngp1bGxscO3aNYWyV9PUGBoaAgCsrKwUyoqKiuTHRUVFWLlyJRISEvDw4UPU1NSgvLwcBQUFDY4vJyenznaQNjY2LcqokJ2djYqKCjg6OiqUV1ZWYsCAAU1ur3fv3jA3N0dycjJ27NiBx48f48iRI7h16xZKS0uhoqKCTp06wdraGu7u7pg8eTJCQkIwbtw49OnTp9nXwTBvwoLtO8TlcuUbaJ89exYRERFYvnx5gxlmAdSbp+v1fVWJqE5ZfWlqXi+rTVsDvLwjori4GOHh4RAIBODxeBg+fPgbU9c0dTxNUTuu06dPo3v37grv8Xi8JrdXUFCAM2fOIDAwECtWrEBlZSWcnJwwd+5c6OnpoaqqCsXFxUhPT8fixYshEAiwZMkSfPPNN3B2dkbv3r2bfS0MUx92n+07xuFwYGNjgzVr1uDKlStQU1NDTEwM1NTUGpUmW1tbG926dUNqaqpCeVpaWpMyJ9QnJSUFCxcuhKurKz788EPweLw6mR1UVVXrjNPCwqJF46m9zerVdvv16wcej4eCgoI6aXGas3m4oaEhvLy88O2332Lq1KnYsWMHBg0ahLt37+LMmTNISUnBo0eP8PHHH2Pv3r0YMmQIvvrqK/j5+cn/KmCY1sRmtu+QWCxGfHw8nJycYGBgALFYjOLiYlhYWKCiogI///wzcnNzoaenBx0dnTe2s2TJEqxatQrGxsawtraGSCTC1atXsW/fvhaNz8TEBHv27MHgwYNRVlaGJUuW1EkcaWRkhPj4eNjY2IDH40FXVxdLliyBu7s7Bg4cCAcHB5w6dQrHjh3Dr7/+2qh+BQIBOBwOYmNj4erqCg0NDXTs2BGLFy9GYGAgZDIZRo4cibKyMqSlpUFLSwve3t5Nurby8nJERUUhODgYd+/ehYeHBzp16gRzc3MYGBigvLwc6enp2L17NwBg2rRpWLhwIbZt2wZbW1toamo2qT+Geau2XjR+n2VnZ5OzszPp6+sTj8cjU1NTioiIIKKX3/Q7OjqSlpZWnVu/ar9IqvXqrV+qqqpvvPXr1fPq+xJKJBKRjo6O/Pjy5cs0ePBg4vF41LdvXzp8+DAJBALatGmTvM7JkyfJxMSEVFRUWuXWr1pfffUVdenShTgcjsKtX5s3byYzMzNSVVUlfX19cnZ2puTk5EZ/5rUkEgn98MMPNHnyZPL396fc3FyqqqqqU08qlVJ6ejp5enrSzJkzaceOHfTgwYMm98cwb8MyNTDvpYqKCsyePRvW1tZYuHDhWx9WePHiBb799lsUFhbihx9+gLq6upJGyrQXbM2WeS8VFhZCX18f8+fPb9RTYRoaGggJCUHHjh1x//59JYyQaW/YzJZhGEYJ2MyWYRhGCViwZRiGUQIWbBmGYZSABVuGYRglYMGWYRhGCViwZRiGUQIWbBmGYZSABVuGYRglYMGWYRhGCViwZRiGUYL/A3J16vL0qqphAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ann_paths_df = pd.read_csv('example-data/annotation_paths.csv')\n",
    "ann_paths_dict = dict(zip(ann_paths_df['name'], ann_paths_df['path']))\n",
    "style_3 = pystrat.Style(style_df['facies'],                  # labels (must include all unique facies)\n",
    "                        style_df[['R','G','B']]/255,         # colors \n",
    "                        style_df['width'],                   # widths \n",
    "                        swatch_values=style_df['swatch'],    # swatches\n",
    "                        annotations=ann_paths_dict)          # annotations\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(2, 3))\n",
    "style_3.plot_legend(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e039d37e-5522-4896-b357-d31f9dee9f4b",
   "metadata": {},
   "source": [
    "### Annotation Size"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ea4e806-48f3-4311-9948-3429d39f131b",
   "metadata": {},
   "source": [
    "The size of the annotations can be controlled by the `annotation_height` parameter, which sets the annotation height in inches. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "12ebe139-bc6c-458b-87ed-8aa3e7aab4a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(2, 7))\n",
    "ax = plt.axes(ylim=[0, 120])   \n",
    "section_2.plot(style_2, ax=ax, label_units=True, unit_label_wid_tot=0.3, annotation_height=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c844799-cef0-4807-9606-5a908a9bab7d",
   "metadata": {},
   "source": [
    "## Style Compatibility"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10220814-af5f-4589-8d54-3b4cd0c8c969",
   "metadata": {},
   "source": [
    "It is possible to check the compatibility of a `pystrat.Section` with a `pystrat.Style`.\n",
    "\n",
    "Use the [`pystrat.Section.style_compatibility`](api/pystrat.rst#pystrat.pystrat.Section.style_compatibility) function. \n",
    "\n",
    "This function checks that all facies present in the section are defined within the style object. If the section and the style object both have annotations, it will also check that the annotations in the section are defined in the style object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a289430a-e7c9-4de9-b0eb-b246c155ade4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_2.style_compatibility(style_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4224a076-7994-4e2d-9373-65937bec4c67",
   "metadata": {},
   "source": [
    "If the style object does not have annotations but the facies are well-defined, then the check will pass and annotations wouldn't be plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fc63d28e-a4b2-4632-834e-a43b990ed44e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_2.style_compatibility(style_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7393c557-0011-4a76-a46e-bb5492f9ded5",
   "metadata": {},
   "source": [
    "## Stratigraphic Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d181d2a6-5fc5-47ea-90dd-43feff7f52f2",
   "metadata": {},
   "source": [
    "`pystrat` allows adding other types of data to `pystrat.Section` objects. There are three different types of data:\n",
    "1. facies attributes: These data are defined on a per-bed basis; there must be one entry per bed in the section\n",
    "2. data attributes: These data are defined at stratigraphic heights and are not explicitly tied to particular beds\n",
    "3. generic attributes: These data are not tied to specific beds or stratigraphic height and instead describe other aspects of the section."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "486c9382-35a2-4f06-bacf-bdde72533028",
   "metadata": {},
   "source": [
    "### Facies Attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a352fb84-b636-4757-9730-012463f7334c",
   "metadata": {},
   "source": [
    "Facies attributes are added to a section object with `pystrat.Section.add_facies_attribute`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "70a94f8e-52d9-443a-b2d8-f8db612d5878",
   "metadata": {},
   "outputs": [],
   "source": [
    "section_1.add_facies_attribute('lithology', litho_df['LITHOLOGY'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd270cac-cb76-4be5-ac71-eb156484ccf8",
   "metadata": {},
   "source": [
    "Once added, the attributes can be accessed as any other attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2bc33937-e834-40b7-a59f-584e5beff42b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['dolomite', 'dolomite', 'dolomite', 'dolomite', 'dolomite',\n",
       "       'dolomite', 'dolomite', 'dolomite', 'dolomite', 'marl', 'dolomite',\n",
       "       'dolomite', 'dolomite', 'dolomite', 'dolomite', 'dolomite',\n",
       "       'dolomite', 'dolomite', 'dolomite', 'dolomite', 'dolomite',\n",
       "       'dolomite', 'dolomite', 'dolomite', 'dolomite', 'cover',\n",
       "       'siliciclastic', 'dolomite', 'dolomite', 'siliciclastic',\n",
       "       'dolomite', 'dolomite', 'dolomite', 'marl', 'dolomite', 'dolomite',\n",
       "       'limestone', 'marl', 'limestone', 'marl', 'limestone', 'marl',\n",
       "       'marl', 'limestone'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.lithology"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0025b3b1-8e12-412d-a6f5-56bfe0a2ac52",
   "metadata": {},
   "source": [
    "A dataframe representing the current state of the section object can be returned with `pystrat.Section.return_facies_dataframe`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ad315a81-1e72-4bad-bc35-d5ff382bdec2",
   "metadata": {},
   "outputs": [
    {
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        {
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       "      <td>ribbonite-siltstone</td>\n",
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       "      <td>ribbonite</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "   unit_number  thicknesses  base_height  top_height               facies  \\\n",
       "0            0          4.9          0.0         4.9       recrystallized   \n",
       "1            1          1.8          4.9         6.7  ribbonite-siltstone   \n",
       "2            2          0.8          6.7         7.5            ribbonite   \n",
       "3            3          0.7          7.5         8.2  ribbonite-siltstone   \n",
       "4            4          1.4          8.2         9.6            ribbonite   \n",
       "\n",
       "  lithology  \n",
       "0  dolomite  \n",
       "1  dolomite  \n",
       "2  dolomite  \n",
       "3  dolomite  \n",
       "4  dolomite  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "section_1.return_facies_dataframe().head()"
   ]
  },
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   "cell_type": "markdown",
   "id": "10c42b96-b6e3-442c-92b4-df47e24f26cf",
   "metadata": {},
   "source": [
    "### Data Attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ba2f97d-c5cb-4597-9659-ccfd6e5a70e6",
   "metadata": {},
   "source": [
    "Data attributes refer to stratigraphic observations that are not uniquely tied to beds in the stratigraphy. `pystrat` handles these data with the [`pystrat.Section.Data`](api/pystrat.rst#pystrat.pystrat.Section.Data) subclass.\n",
    "\n",
    "This example uses carbonate chemostratigraphy."
   ]
  },
  {
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   "execution_count": 17,
   "id": "8c92000b-c0b3-48bb-958f-11b3fcf6b86b",
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       "  CARB_SAMPLE  CARB_HEIGHT  CARB_d13C  CARB_d18O  CARB_87Sr/86Sr  CARB_Al_ppm  \\\n",
       "0     T46-1.2          1.2   1.820429   0.130692             NaN    682.46931   \n",
       "1     T46-2.1          2.1   1.597633   0.134841             NaN          NaN   \n",
       "2     T46-3.8          3.8   0.102096  -0.195867             NaN          NaN   \n",
       "3     T46-5.9          5.9   1.090520  -1.066232             NaN          NaN   \n",
       "4     T46-7.1          7.1   2.194324  -0.630248             NaN          NaN   \n",
       "\n",
       "   CARB_Ca_ppm  CARB_Fe_ppm  CARB_Mg_ppm  CARB_Mn_ppm  CARB_Sr_ppm  \n",
       "0  313906.3927   293.408791  197499.6646   443.552746   539.226752  \n",
       "1          NaN          NaN          NaN          NaN          NaN  \n",
       "2          NaN          NaN          NaN          NaN          NaN  \n",
       "3          NaN          NaN          NaN          NaN          NaN  \n",
       "4          NaN          NaN          NaN          NaN          NaN  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chemo = pd.read_csv('example-data/chemostratigraphy.csv')\n",
    "chemo.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e866b7c7-1a73-476b-85d0-c72d526d4bd7",
   "metadata": {},
   "source": [
    "Add the $\\delta^{13}$C data using the `pystrat.Section.add_data_attribute()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "eb51e8c7-1bc8-4c56-b1aa-3acd4878ee53",
   "metadata": {},
   "outputs": [],
   "source": [
    "section_1.add_data_attribute('d13C', chemo['CARB_HEIGHT'], chemo['CARB_d13C'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ace5610-75c5-47ac-b51f-57ca78f2a4ca",
   "metadata": {},
   "source": [
    "This creates an instance of `pystrat.Section.Data`. It is possible to add attributes to these objects as well. For example, add the the sample names for the $\\delta^{13}$C as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1a8b8ac9-4169-4b4e-83dd-172171876317",
   "metadata": {},
   "outputs": [],
   "source": [
    "section_1.d13C.add_height_attribute('sample', chemo['CARB_SAMPLE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "645c8654-67fd-4bc7-97ad-53261a6e99f0",
   "metadata": {},
   "source": [
    "Data can be returned as a DataFrame with `pystrat.Section.Data.return_data_dataframe()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c6aaad8f-10a9-44a6-a4a8-94a0992153ab",
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       "      <td>1.820429</td>\n",
       "      <td>T46-1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.1</td>\n",
       "      <td>1.597633</td>\n",
       "      <td>T46-2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.8</td>\n",
       "      <td>0.102096</td>\n",
       "      <td>T46-3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.9</td>\n",
       "      <td>1.090520</td>\n",
       "      <td>T46-5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.1</td>\n",
       "      <td>2.194324</td>\n",
       "      <td>T46-7.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   height    values   sample\n",
       "0     1.2  1.820429  T46-1.2\n",
       "1     2.1  1.597633  T46-2.1\n",
       "2     3.8  0.102096  T46-3.8\n",
       "3     5.9  1.090520  T46-5.9\n",
       "4     7.1  2.194324  T46-7.1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.d13C.return_data_dataframe().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d61d4cc-165e-4c0e-97c6-10ebe1de13b8",
   "metadata": {},
   "source": [
    "Note that this function is defined for the `Data` sub-class and therefore acts on the `section_1.d13C` attribute in this case."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5cde08f-b307-413a-ac25-977f71504ab3",
   "metadata": {},
   "source": [
    "Add another data attribute, this time the $\\delta^{18}$O measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c2e0e278-ff50-4d4f-b789-5abca07edc79",
   "metadata": {},
   "outputs": [],
   "source": [
    "# d18O\n",
    "section_1.add_data_attribute('d18O', chemo['CARB_HEIGHT'], chemo['CARB_d18O'])\n",
    "section_1.d18O.add_height_attribute('sample', chemo['CARB_SAMPLE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3894a157-9d2e-4084-920a-71bd75912f71",
   "metadata": {},
   "source": [
    "All data attributes that have been added can be listed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7f4fc0cf-9af7-4136-ac01-b5e4c6c916a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['d13C', 'd18O']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.data_attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a695cdc6-38cb-4df0-98cf-6b67332b95dd",
   "metadata": {},
   "source": [
    "#### Data Attribute Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3710f93-b4cd-40b8-bfd5-aa545c977f26",
   "metadata": {},
   "source": [
    "Data attributes can be plotted by directly accessing them from the section object. Alternatively, `pystrat` also provides [`pystrat.Section.plot_data_attribute`](api/pystrat.rst#pystrat.pystrat.Section.plot_data_attribute):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "de94cdb1-9681-49ea-a397-23abd62cf7e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 3, figsize=(4, 8), sharey=True, constrained_layout=True)\n",
    "ax[0].set_ylim([0, 120]) # remember to set y limits!\n",
    "\n",
    "section_1.plot(style_1, ax=ax[0])\n",
    "\n",
    "# plot data attributes\n",
    "section_1.plot_data_attribute('d13C', ax=ax[1])\n",
    "section_1.plot_data_attribute('d18O', ax=ax[2])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "019c5f80-c7a2-4687-aa5a-c8483911c9d1",
   "metadata": {},
   "source": [
    "### Generic Attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fc9216f-1e46-449f-a763-88732ec5d079",
   "metadata": {},
   "source": [
    "Generic attributes are not tied to specific beds or stratigraphic heights and instead describe other aspects of a section.\n",
    "\n",
    "They are added with `pystrat.Section.add_generic_attribute`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e118c953-a7ce-4fc1-a130-9167a7c5920a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'West Samre'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.add_generic_attribute('locality', 'West Samre')\n",
    "section_1.locality"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "688a005f-3076-4665-b351-1f84b8b4d698",
   "metadata": {},
   "source": [
    "## Helper Functions and Attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8f41921-0cf2-4212-980a-569eb5a1a276",
   "metadata": {},
   "source": [
    "The `pystrat.Section` class also provides various helpful functions and attributes relevant to stratigraphic sections."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdf58feb-979a-4d60-8cfa-9f57176e1f7f",
   "metadata": {},
   "source": [
    "### Units at Heights"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56b7368a-85c0-480e-baa1-5b007c6e4f69",
   "metadata": {},
   "source": [
    "Use `pystrat.Section.get_units()` to return the unit(s) at given stratigraphic height(s). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a78d735d-4445-4921-b93b-64a14a4e0bc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['GROUP 1', 'FM 2'],\n",
       "       ['GROUP 2', 'FM 4']], dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.get_units(np.array([50, 100]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06e516ac-f547-4f6c-8a6b-d86ea9857b3c",
   "metadata": {},
   "source": [
    "### Total Thickness"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8547eaa-074a-4689-b0eb-ef68934053e4",
   "metadata": {},
   "source": [
    "Use `pystrat.Section.total_thickness` to return the total thickness of the section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4c279c8b-8328-4066-a768-c54312f225f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "118.4"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.total_thickness"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28e9a89a-4154-4ed4-ba36-a6465cb9b590",
   "metadata": {},
   "source": [
    "### Unique Facies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39a44f15-7765-4903-97b7-317ecfb99678",
   "metadata": {},
   "source": [
    "Use `pystrat.Section.unique_facies` to return the unique facies in the section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0d315221-8fd4-49ea-b507-f97285515659",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['cover', 'grainstone', 'intraclast breccia', 'marl',\n",
       "       'marl-ribbonite', 'recrystallized', 'recrystallized-siltstone',\n",
       "       'ribbonite', 'ribbonite-grainstone', 'ribbonite-siltstone',\n",
       "       'siltstone-fine sandstone', 'stromatolite'], dtype=object)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_1.unique_facies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "003410f7-9a55-4062-ae36-d974e54d15f6",
   "metadata": {},
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
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    "> Swanson-Hysell, N.L., Maloof, A.C., Condon, D.J., Jenkin, G.R., Alene, M., Tremblay, M.M., Tesema, T., Rooney, A.D., and Haileab, B., 2015, Stratigraphy and geochronology of the Tambien Group, Ethiopia: Evidence for globally synchronous carbon isotope change in the Neoproterozoic: Geology, v. 43, p. 323-326, https://doi.org/10.1130/G36347.1.\n",
    "\n",
    "> MacLennan, S.A., Park, Y., Swanson-Hysell, N.L., Maloof, A.C., Schoene, B., Gebreslassie, M., Antilla, E., Tesema, T., Alene, M., and Haileab, B., 2018, The arc of the Snowball: U-Pb dates constrain the Islay anomaly and the initiation of the Sturtian glaciation: Geology, v. 46, p. 539-542, https://doi.org/10.1130/G40171.1.\n",
    "\n",
    ">Park, Y., Swanson-Hysell, N.L., MacLennan, S.A., Maloof, A.C., Gebreslassie, M., Tremblay, M.M., Schoene, B., Alene, M., Anttila, E.S.C., Tesema, T., Condon, D.J., Haileab, B., 2020, The lead-up to the Sturtian Snowball Earth: Neoproterozoic chemostratigraphy time-calibrated by the Tambien Group of Ethiopia: GSA Bulletin, vol. 132, pp. 1119–1149, https://doi.org/10.1130/B35178.1"
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