{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "growing-madonna",
   "metadata": {},
   "source": [
    "# Size and shape of signatures\n",
    "\n",
    "This notebook explores sizes and shapes of individual signatures depending on their signature type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "referenced-affiliation",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "import pandas\n",
    "import dask_geopandas\n",
    "import momepy\n",
    "import seaborn\n",
    "import pygeos\n",
    "import pandas\n",
    "import numpy\n",
    "import dask.dataframe\n",
    "from dask.distributed import Client, LocalCluster\n",
    "import matplotlib.pyplot as plt\n",
    "from itertools import product"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acting-bridal",
   "metadata": {},
   "source": [
    "## Measure size and shape characters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "secure-teacher",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://127.0.0.1:41929</li>\n",
       "  <li><b>Dashboard: </b><a href='http://127.0.0.1:8787/status' target='_blank'>http://127.0.0.1:8787/status</a></li>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>4</li>\n",
       "  <li><b>Cores: </b>16</li>\n",
       "  <li><b>Memory: </b>134.80 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:41929' processes=4 threads=16, memory=134.80 GB>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client = Client()\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "united-minneapolis",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.9'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pygeos.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aging-channels",
   "metadata": {},
   "outputs": [],
   "source": [
    "signatures = dask_geopandas.from_geopandas(geopandas.read_parquet(\"../../urbangrammar_samba/spatial_signatures/signatures/signatures_combined_levels_orig.pq\"), npartitions=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "statewide-object",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><strong>Dask-GeoPandas GeoDataFrame Structure:</strong></div>\n",
       "<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>kmeans10gb</th>\n",
       "      <th>geometry</th>\n",
       "      <th>level2</th>\n",
       "      <th>signature_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=32</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>float64</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3022</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93682</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96703</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: from_pandas, 32 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 32 tasks | 32 npartitions>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "signatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "celtic-fitness",
   "metadata": {},
   "outputs": [],
   "source": [
    "signatures[\"area\"] = signatures.area\n",
    "signatures[\"perimeter\"] = signatures.length\n",
    "signatures[\"eri\"] = signatures.map_partitions(lambda p: momepy.EquivalentRectangularIndex(p).series, meta=pandas.Series(dtype=\"float\"))\n",
    "signatures[\"circular_compactness\"] = signatures.map_partitions(lambda p: momepy.CircularCompactness(p).series, meta=pandas.Series(dtype=\"float\"))\n",
    "signatures[\"donut_index\"] = signatures.map_partitions(lambda p: momepy.CourtyardIndex(p, momepy.CourtyardArea(p).series).series, meta=pandas.Series(dtype=\"float\"))\n",
    "signatures[\"fractality\"] = signatures.map_partitions(lambda p: momepy.FractalDimension(p).series, meta=pandas.Series(dtype=\"float\"))\n",
    "signatures[\"convexity\"] = signatures.map_partitions(lambda p: momepy.Convexity(p).series, meta=pandas.Series(dtype=\"float\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "reserved-amsterdam",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 12.8 s, sys: 5.15 s, total: 17.9 s\n",
      "Wall time: 32.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "signatures = signatures.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "native-pakistan",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-15-9c695be00e9b>:1: UserWarning: this is an initial implementation of Parquet/Feather file support and associated metadata.  This is tracking version 0.1.0 of the metadata specification at https://github.com/geopandas/geo-arrow-spec\n",
      "\n",
      "This metadata specification does not yet make stability promises.  We do not yet recommend using this in a production setting unless you are able to rewrite your Parquet/Feather files.\n",
      "\n",
      "To further ignore this warning, you can do: \n",
      "import warnings; warnings.filterwarnings('ignore', message='.*initial implementation of Parquet.*')\n",
      "  signatures.drop(columns=[\"kmeans10gb\", \"geometry\", \"level2\"]).to_parquet(\"../../urbangrammar_samba/spatial_signatures/esda/sizeshape.pq\")\n"
     ]
    }
   ],
   "source": [
    "signatures.drop(columns=[\"kmeans10gb\", \"geometry\", \"level2\"]).to_parquet(\"../../urbangrammar_samba/spatial_signatures/esda/sizeshape.pq\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "governing-drunk",
   "metadata": {},
   "outputs": [],
   "source": [
    "signatures.drop(columns=[\"kmeans10gb\", \"geometry\", \"level2\"]).to_csv(\"../../urbangrammar_samba/spatial_signatures/esda/sizeshape.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dominican-salad",
   "metadata": {},
   "source": [
    "## Exploration of results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "addressed-pioneer",
   "metadata": {},
   "outputs": [],
   "source": [
    "signatures = pandas.read_parquet(\"../../urbangrammar_samba/spatial_signatures/esda/sizeshape.pq\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "hollywood-spyware",
   "metadata": {},
   "outputs": [],
   "source": [
    "types = {\n",
    "    \"0_0\": \"Countryside agriculture\",\n",
    "    \"1_0\": \"Accessible suburbia\",\n",
    "    \"3_0\": \"Open sprawl\",\n",
    "    \"4_0\": \"Wild countryside\",\n",
    "    \"5_0\": \"Warehouse/Park land\",\n",
    "    \"6_0\": \"Gridded residential quarters\",\n",
    "    \"7_0\": \"Urban buffer\",\n",
    "    \"8_0\": \"Disconnected suburbia\",\n",
    "    \"2_0\": \"Dense residential neighbourhoods\",\n",
    "    \"2_1\": \"Connected residential neighbourhoods\",\n",
    "    \"2_2\": \"Dense urban neighbourhoods\",\n",
    "    \"9_0\": \"Local urbanity\",\n",
    "    \"9_1\": \"Concentrated urbanity\",\n",
    "    \"9_2\": \"Regional urbanity\",\n",
    "    \"9_4\": \"Metropolitan urbanity\",\n",
    "    \"9_5\": \"Hyper concentrated urbanity\",\n",
    "}\n",
    "\n",
    "signatures[\"signature_type\"] = signatures[\"signature_type\"].map(types)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "animated-bracelet",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>signature_type</th>\n",
       "      <th>area</th>\n",
       "      <th>perimeter</th>\n",
       "      <th>eri</th>\n",
       "      <th>circular_compactness</th>\n",
       "      <th>donut_index</th>\n",
       "      <th>fractality</th>\n",
       "      <th>convexity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.826984e+07</td>\n",
       "      <td>29577.575163</td>\n",
       "      <td>0.601828</td>\n",
       "      <td>0.439852</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>1.065559</td>\n",
       "      <td>0.788857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.235908e+04</td>\n",
       "      <td>555.207264</td>\n",
       "      <td>0.892662</td>\n",
       "      <td>0.254347</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.047118</td>\n",
       "      <td>0.983245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>7.234542e+05</td>\n",
       "      <td>5746.792461</td>\n",
       "      <td>0.602136</td>\n",
       "      <td>0.339522</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.077707</td>\n",
       "      <td>0.629428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.229467e+06</td>\n",
       "      <td>6161.670240</td>\n",
       "      <td>0.731125</td>\n",
       "      <td>0.306803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.046892</td>\n",
       "      <td>0.799648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>7.604014e+06</td>\n",
       "      <td>22500.262066</td>\n",
       "      <td>0.539593</td>\n",
       "      <td>0.252670</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>1.089988</td>\n",
       "      <td>0.641429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96699</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.070783e+04</td>\n",
       "      <td>824.963123</td>\n",
       "      <td>1.020075</td>\n",
       "      <td>0.453320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.004137</td>\n",
       "      <td>0.999224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96700</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.523702e+03</td>\n",
       "      <td>270.956057</td>\n",
       "      <td>0.959089</td>\n",
       "      <td>0.334764</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.032331</td>\n",
       "      <td>0.995177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96701</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.236944e+05</td>\n",
       "      <td>1525.262336</td>\n",
       "      <td>1.017609</td>\n",
       "      <td>0.370246</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.013789</td>\n",
       "      <td>0.965269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96702</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.526104e+03</td>\n",
       "      <td>189.735084</td>\n",
       "      <td>0.954954</td>\n",
       "      <td>0.277671</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.052956</td>\n",
       "      <td>0.921173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96703</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.444304e+04</td>\n",
       "      <td>477.377607</td>\n",
       "      <td>1.026855</td>\n",
       "      <td>0.615717</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.998544</td>\n",
       "      <td>0.999986</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96704 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                signature_type          area     perimeter       eri  \\\n",
       "0      Countryside agriculture  1.826984e+07  29577.575163  0.601828   \n",
       "1      Countryside agriculture  1.235908e+04    555.207264  0.892662   \n",
       "2      Countryside agriculture  7.234542e+05   5746.792461  0.602136   \n",
       "3      Countryside agriculture  1.229467e+06   6161.670240  0.731125   \n",
       "4      Countryside agriculture  7.604014e+06  22500.262066  0.539593   \n",
       "...                        ...           ...           ...       ...   \n",
       "96699                      NaN  4.070783e+04    824.963123  1.020075   \n",
       "96700                      NaN  3.523702e+03    270.956057  0.959089   \n",
       "96701                      NaN  1.236944e+05   1525.262336  1.017609   \n",
       "96702                      NaN  1.526104e+03    189.735084  0.954954   \n",
       "96703                      NaN  1.444304e+04    477.377607  1.026855   \n",
       "\n",
       "       circular_compactness  donut_index  fractality  convexity  \n",
       "0                  0.439852     0.000071    1.065559   0.788857  \n",
       "1                  0.254347     0.000000    1.047118   0.983245  \n",
       "2                  0.339522     0.000000    1.077707   0.629428  \n",
       "3                  0.306803     0.000000    1.046892   0.799648  \n",
       "4                  0.252670     0.000281    1.089988   0.641429  \n",
       "...                     ...          ...         ...        ...  \n",
       "96699              0.453320     0.000000    1.004137   0.999224  \n",
       "96700              0.334764     0.000000    1.032331   0.995177  \n",
       "96701              0.370246     0.000000    1.013789   0.965269  \n",
       "96702              0.277671     0.000000    1.052956   0.921173  \n",
       "96703              0.615717     0.000000    0.998544   0.999986  \n",
       "\n",
       "[96704 rows x 8 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "signatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "blocked-finding",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop outlier clusters\n",
    "signatures = signatures.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "identified-punch",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-6-955dbae783e0>:20: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  signatures[\"signature_type\"] = pandas.Categorical(signatures[\"signature_type\"], categories=order, ordered=True)\n"
     ]
    }
   ],
   "source": [
    "order = [\n",
    "    \"Wild countryside\",\n",
    "    \"Countryside agriculture\",\n",
    "    \"Urban buffer\",\n",
    "    \"Open sprawl\",\n",
    "    \"Disconnected suburbia\",\n",
    "    \"Accessible suburbia\",\n",
    "    \"Warehouse/Park land\",\n",
    "    \"Gridded residential quarters\",\n",
    "    \"Connected residential neighbourhoods\",\n",
    "    \"Dense residential neighbourhoods\",\n",
    "    \"Dense urban neighbourhoods\",\n",
    "    \"Local urbanity\",\n",
    "    \"Regional urbanity\",\n",
    "    \"Metropolitan urbanity\",\n",
    "    \"Concentrated urbanity\",\n",
    "    \"Hyper concentrated urbanity\",\n",
    "]\n",
    "\n",
    "signatures[\"signature_type\"] = pandas.Categorical(signatures[\"signature_type\"], categories=order, ordered=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "excellent-squad",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">area</th>\n",
       "      <th colspan=\"2\" halign=\"left\">perimeter</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">fractality</th>\n",
       "      <th colspan=\"8\" halign=\"left\">convexity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>signature_type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Wild countryside</th>\n",
       "      <td>6214.0</td>\n",
       "      <td>1.469363e+07</td>\n",
       "      <td>5.997410e+08</td>\n",
       "      <td>0.057032</td>\n",
       "      <td>1499.198526</td>\n",
       "      <td>6508.082021</td>\n",
       "      <td>45560.114847</td>\n",
       "      <td>3.944223e+10</td>\n",
       "      <td>6214.0</td>\n",
       "      <td>5262.662128</td>\n",
       "      <td>...</td>\n",
       "      <td>1.087244</td>\n",
       "      <td>6.436920</td>\n",
       "      <td>6214.0</td>\n",
       "      <td>0.847012</td>\n",
       "      <td>0.144665</td>\n",
       "      <td>0.171730</td>\n",
       "      <td>0.749014</td>\n",
       "      <td>0.897610</td>\n",
       "      <td>0.967863</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Countryside agriculture</th>\n",
       "      <td>10882.0</td>\n",
       "      <td>8.624893e+06</td>\n",
       "      <td>7.140831e+08</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>955.663816</td>\n",
       "      <td>3089.140723</td>\n",
       "      <td>15668.089578</td>\n",
       "      <td>7.438020e+10</td>\n",
       "      <td>10882.0</td>\n",
       "      <td>6103.812918</td>\n",
       "      <td>...</td>\n",
       "      <td>1.088969</td>\n",
       "      <td>13.445506</td>\n",
       "      <td>10882.0</td>\n",
       "      <td>0.850269</td>\n",
       "      <td>0.143361</td>\n",
       "      <td>0.174666</td>\n",
       "      <td>0.756614</td>\n",
       "      <td>0.902827</td>\n",
       "      <td>0.966824</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Urban buffer</th>\n",
       "      <td>10636.0</td>\n",
       "      <td>2.969990e+06</td>\n",
       "      <td>6.339222e+07</td>\n",
       "      <td>0.000879</td>\n",
       "      <td>774.805352</td>\n",
       "      <td>3084.529241</td>\n",
       "      <td>27159.387001</td>\n",
       "      <td>4.103858e+09</td>\n",
       "      <td>10636.0</td>\n",
       "      <td>6339.599043</td>\n",
       "      <td>...</td>\n",
       "      <td>1.088700</td>\n",
       "      <td>17.908917</td>\n",
       "      <td>10636.0</td>\n",
       "      <td>0.851529</td>\n",
       "      <td>0.138671</td>\n",
       "      <td>0.206889</td>\n",
       "      <td>0.754072</td>\n",
       "      <td>0.900720</td>\n",
       "      <td>0.966431</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Open sprawl</th>\n",
       "      <td>17357.0</td>\n",
       "      <td>2.927622e+05</td>\n",
       "      <td>3.818980e+06</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>643.323344</td>\n",
       "      <td>1612.151800</td>\n",
       "      <td>9317.120739</td>\n",
       "      <td>3.672014e+08</td>\n",
       "      <td>17357.0</td>\n",
       "      <td>2309.238110</td>\n",
       "      <td>...</td>\n",
       "      <td>1.101593</td>\n",
       "      <td>268.246039</td>\n",
       "      <td>17357.0</td>\n",
       "      <td>0.820230</td>\n",
       "      <td>0.159341</td>\n",
       "      <td>0.209074</td>\n",
       "      <td>0.708346</td>\n",
       "      <td>0.878782</td>\n",
       "      <td>0.953845</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Disconnected suburbia</th>\n",
       "      <td>9418.0</td>\n",
       "      <td>7.528544e+04</td>\n",
       "      <td>3.305071e+05</td>\n",
       "      <td>0.001150</td>\n",
       "      <td>616.810183</td>\n",
       "      <td>1447.681618</td>\n",
       "      <td>8060.213460</td>\n",
       "      <td>9.032649e+06</td>\n",
       "      <td>9418.0</td>\n",
       "      <td>1017.207867</td>\n",
       "      <td>...</td>\n",
       "      <td>1.091667</td>\n",
       "      <td>4.022005</td>\n",
       "      <td>9418.0</td>\n",
       "      <td>0.843098</td>\n",
       "      <td>0.132009</td>\n",
       "      <td>0.292148</td>\n",
       "      <td>0.740525</td>\n",
       "      <td>0.888421</td>\n",
       "      <td>0.957065</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessible suburbia</th>\n",
       "      <td>10919.0</td>\n",
       "      <td>2.055632e+05</td>\n",
       "      <td>1.280101e+06</td>\n",
       "      <td>0.009560</td>\n",
       "      <td>588.376394</td>\n",
       "      <td>1507.000971</td>\n",
       "      <td>18570.817476</td>\n",
       "      <td>5.079366e+07</td>\n",
       "      <td>10919.0</td>\n",
       "      <td>1627.488939</td>\n",
       "      <td>...</td>\n",
       "      <td>1.090873</td>\n",
       "      <td>5.549176</td>\n",
       "      <td>10919.0</td>\n",
       "      <td>0.844585</td>\n",
       "      <td>0.123035</td>\n",
       "      <td>0.375821</td>\n",
       "      <td>0.753064</td>\n",
       "      <td>0.877346</td>\n",
       "      <td>0.951271</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Warehouse/Park land</th>\n",
       "      <td>10675.0</td>\n",
       "      <td>2.306844e+05</td>\n",
       "      <td>3.414580e+06</td>\n",
       "      <td>0.016327</td>\n",
       "      <td>732.048897</td>\n",
       "      <td>1865.205005</td>\n",
       "      <td>8534.309518</td>\n",
       "      <td>2.257328e+08</td>\n",
       "      <td>10675.0</td>\n",
       "      <td>1484.178936</td>\n",
       "      <td>...</td>\n",
       "      <td>1.095447</td>\n",
       "      <td>3.629490</td>\n",
       "      <td>10675.0</td>\n",
       "      <td>0.833803</td>\n",
       "      <td>0.152972</td>\n",
       "      <td>0.216611</td>\n",
       "      <td>0.718129</td>\n",
       "      <td>0.894513</td>\n",
       "      <td>0.962252</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gridded residential quarters</th>\n",
       "      <td>2561.0</td>\n",
       "      <td>1.020215e+05</td>\n",
       "      <td>5.970954e+05</td>\n",
       "      <td>0.003155</td>\n",
       "      <td>510.032001</td>\n",
       "      <td>1176.434329</td>\n",
       "      <td>6925.344211</td>\n",
       "      <td>1.790986e+07</td>\n",
       "      <td>2561.0</td>\n",
       "      <td>1101.256942</td>\n",
       "      <td>...</td>\n",
       "      <td>1.087953</td>\n",
       "      <td>1.630874</td>\n",
       "      <td>2561.0</td>\n",
       "      <td>0.864575</td>\n",
       "      <td>0.121242</td>\n",
       "      <td>0.342705</td>\n",
       "      <td>0.775185</td>\n",
       "      <td>0.906935</td>\n",
       "      <td>0.968370</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connected residential neighbourhoods</th>\n",
       "      <td>5802.0</td>\n",
       "      <td>9.745088e+04</td>\n",
       "      <td>6.036783e+05</td>\n",
       "      <td>0.485844</td>\n",
       "      <td>644.482072</td>\n",
       "      <td>1501.473957</td>\n",
       "      <td>7804.156901</td>\n",
       "      <td>1.960757e+07</td>\n",
       "      <td>5802.0</td>\n",
       "      <td>1211.006013</td>\n",
       "      <td>...</td>\n",
       "      <td>1.093833</td>\n",
       "      <td>4.665447</td>\n",
       "      <td>5802.0</td>\n",
       "      <td>0.838442</td>\n",
       "      <td>0.145711</td>\n",
       "      <td>0.268105</td>\n",
       "      <td>0.729141</td>\n",
       "      <td>0.892645</td>\n",
       "      <td>0.962229</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dense residential neighbourhoods</th>\n",
       "      <td>6815.0</td>\n",
       "      <td>1.404605e+05</td>\n",
       "      <td>1.047595e+06</td>\n",
       "      <td>0.000205</td>\n",
       "      <td>649.122630</td>\n",
       "      <td>1617.513549</td>\n",
       "      <td>6993.079521</td>\n",
       "      <td>4.613231e+07</td>\n",
       "      <td>6815.0</td>\n",
       "      <td>1572.557494</td>\n",
       "      <td>...</td>\n",
       "      <td>1.091611</td>\n",
       "      <td>5.789690</td>\n",
       "      <td>6815.0</td>\n",
       "      <td>0.843006</td>\n",
       "      <td>0.149689</td>\n",
       "      <td>0.267939</td>\n",
       "      <td>0.739355</td>\n",
       "      <td>0.902421</td>\n",
       "      <td>0.964749</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dense urban neighbourhoods</th>\n",
       "      <td>3344.0</td>\n",
       "      <td>1.706542e+05</td>\n",
       "      <td>3.442472e+06</td>\n",
       "      <td>0.099989</td>\n",
       "      <td>532.894544</td>\n",
       "      <td>1272.170461</td>\n",
       "      <td>4448.501438</td>\n",
       "      <td>1.930257e+08</td>\n",
       "      <td>3344.0</td>\n",
       "      <td>1400.642709</td>\n",
       "      <td>...</td>\n",
       "      <td>1.072876</td>\n",
       "      <td>3.028465</td>\n",
       "      <td>3344.0</td>\n",
       "      <td>0.873944</td>\n",
       "      <td>0.132032</td>\n",
       "      <td>0.239345</td>\n",
       "      <td>0.792542</td>\n",
       "      <td>0.929865</td>\n",
       "      <td>0.977628</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local urbanity</th>\n",
       "      <td>1598.0</td>\n",
       "      <td>1.446739e+05</td>\n",
       "      <td>2.727705e+06</td>\n",
       "      <td>0.307900</td>\n",
       "      <td>501.241702</td>\n",
       "      <td>1324.764741</td>\n",
       "      <td>4277.220397</td>\n",
       "      <td>1.071213e+08</td>\n",
       "      <td>1598.0</td>\n",
       "      <td>1092.282020</td>\n",
       "      <td>...</td>\n",
       "      <td>1.068875</td>\n",
       "      <td>5.857685</td>\n",
       "      <td>1598.0</td>\n",
       "      <td>0.888981</td>\n",
       "      <td>0.124262</td>\n",
       "      <td>0.369595</td>\n",
       "      <td>0.817659</td>\n",
       "      <td>0.944655</td>\n",
       "      <td>0.983643</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Regional urbanity</th>\n",
       "      <td>316.0</td>\n",
       "      <td>2.419051e+05</td>\n",
       "      <td>2.256797e+06</td>\n",
       "      <td>0.041376</td>\n",
       "      <td>492.984923</td>\n",
       "      <td>1230.743132</td>\n",
       "      <td>3552.061623</td>\n",
       "      <td>3.865336e+07</td>\n",
       "      <td>316.0</td>\n",
       "      <td>1803.643697</td>\n",
       "      <td>...</td>\n",
       "      <td>1.070887</td>\n",
       "      <td>3.260720</td>\n",
       "      <td>316.0</td>\n",
       "      <td>0.894825</td>\n",
       "      <td>0.133988</td>\n",
       "      <td>0.128971</td>\n",
       "      <td>0.836158</td>\n",
       "      <td>0.951919</td>\n",
       "      <td>0.987714</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metropolitan urbanity</th>\n",
       "      <td>135.0</td>\n",
       "      <td>1.228652e+05</td>\n",
       "      <td>1.138579e+06</td>\n",
       "      <td>0.269200</td>\n",
       "      <td>356.672983</td>\n",
       "      <td>1030.773091</td>\n",
       "      <td>3819.015313</td>\n",
       "      <td>1.318199e+07</td>\n",
       "      <td>135.0</td>\n",
       "      <td>1375.312753</td>\n",
       "      <td>...</td>\n",
       "      <td>1.085932</td>\n",
       "      <td>4.011579</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0.920512</td>\n",
       "      <td>0.112035</td>\n",
       "      <td>0.476495</td>\n",
       "      <td>0.900620</td>\n",
       "      <td>0.966404</td>\n",
       "      <td>0.994193</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Concentrated urbanity</th>\n",
       "      <td>11.0</td>\n",
       "      <td>7.167404e+05</td>\n",
       "      <td>2.371545e+06</td>\n",
       "      <td>3.496111</td>\n",
       "      <td>218.266828</td>\n",
       "      <td>349.147183</td>\n",
       "      <td>1527.810889</td>\n",
       "      <td>7.867210e+06</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3700.784089</td>\n",
       "      <td>...</td>\n",
       "      <td>1.090851</td>\n",
       "      <td>2.924473</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.934777</td>\n",
       "      <td>0.100749</td>\n",
       "      <td>0.654358</td>\n",
       "      <td>0.929441</td>\n",
       "      <td>0.970923</td>\n",
       "      <td>0.990041</td>\n",
       "      <td>0.999957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hyper concentrated urbanity</th>\n",
       "      <td>6.0</td>\n",
       "      <td>3.823119e+05</td>\n",
       "      <td>5.858664e+05</td>\n",
       "      <td>1797.907262</td>\n",
       "      <td>2096.072097</td>\n",
       "      <td>15499.678131</td>\n",
       "      <td>747712.533029</td>\n",
       "      <td>1.271663e+06</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3097.160016</td>\n",
       "      <td>...</td>\n",
       "      <td>1.096803</td>\n",
       "      <td>1.125311</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.869961</td>\n",
       "      <td>0.142417</td>\n",
       "      <td>0.625078</td>\n",
       "      <td>0.824920</td>\n",
       "      <td>0.896392</td>\n",
       "      <td>0.977088</td>\n",
       "      <td>0.996822</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         area                              \\\n",
       "                                        count          mean           std   \n",
       "signature_type                                                              \n",
       "Wild countryside                       6214.0  1.469363e+07  5.997410e+08   \n",
       "Countryside agriculture               10882.0  8.624893e+06  7.140831e+08   \n",
       "Urban buffer                          10636.0  2.969990e+06  6.339222e+07   \n",
       "Open sprawl                           17357.0  2.927622e+05  3.818980e+06   \n",
       "Disconnected suburbia                  9418.0  7.528544e+04  3.305071e+05   \n",
       "Accessible suburbia                   10919.0  2.055632e+05  1.280101e+06   \n",
       "Warehouse/Park land                   10675.0  2.306844e+05  3.414580e+06   \n",
       "Gridded residential quarters           2561.0  1.020215e+05  5.970954e+05   \n",
       "Connected residential neighbourhoods   5802.0  9.745088e+04  6.036783e+05   \n",
       "Dense residential neighbourhoods       6815.0  1.404605e+05  1.047595e+06   \n",
       "Dense urban neighbourhoods             3344.0  1.706542e+05  3.442472e+06   \n",
       "Local urbanity                         1598.0  1.446739e+05  2.727705e+06   \n",
       "Regional urbanity                       316.0  2.419051e+05  2.256797e+06   \n",
       "Metropolitan urbanity                   135.0  1.228652e+05  1.138579e+06   \n",
       "Concentrated urbanity                    11.0  7.167404e+05  2.371545e+06   \n",
       "Hyper concentrated urbanity               6.0  3.823119e+05  5.858664e+05   \n",
       "\n",
       "                                                                              \\\n",
       "                                              min          25%           50%   \n",
       "signature_type                                                                 \n",
       "Wild countryside                         0.057032  1499.198526   6508.082021   \n",
       "Countryside agriculture                  0.000150   955.663816   3089.140723   \n",
       "Urban buffer                             0.000879   774.805352   3084.529241   \n",
       "Open sprawl                              0.000160   643.323344   1612.151800   \n",
       "Disconnected suburbia                    0.001150   616.810183   1447.681618   \n",
       "Accessible suburbia                      0.009560   588.376394   1507.000971   \n",
       "Warehouse/Park land                      0.016327   732.048897   1865.205005   \n",
       "Gridded residential quarters             0.003155   510.032001   1176.434329   \n",
       "Connected residential neighbourhoods     0.485844   644.482072   1501.473957   \n",
       "Dense residential neighbourhoods         0.000205   649.122630   1617.513549   \n",
       "Dense urban neighbourhoods               0.099989   532.894544   1272.170461   \n",
       "Local urbanity                           0.307900   501.241702   1324.764741   \n",
       "Regional urbanity                        0.041376   492.984923   1230.743132   \n",
       "Metropolitan urbanity                    0.269200   356.672983   1030.773091   \n",
       "Concentrated urbanity                    3.496111   218.266828    349.147183   \n",
       "Hyper concentrated urbanity           1797.907262  2096.072097  15499.678131   \n",
       "\n",
       "                                                                  perimeter  \\\n",
       "                                                75%           max     count   \n",
       "signature_type                                                                \n",
       "Wild countryside                       45560.114847  3.944223e+10    6214.0   \n",
       "Countryside agriculture                15668.089578  7.438020e+10   10882.0   \n",
       "Urban buffer                           27159.387001  4.103858e+09   10636.0   \n",
       "Open sprawl                             9317.120739  3.672014e+08   17357.0   \n",
       "Disconnected suburbia                   8060.213460  9.032649e+06    9418.0   \n",
       "Accessible suburbia                    18570.817476  5.079366e+07   10919.0   \n",
       "Warehouse/Park land                     8534.309518  2.257328e+08   10675.0   \n",
       "Gridded residential quarters            6925.344211  1.790986e+07    2561.0   \n",
       "Connected residential neighbourhoods    7804.156901  1.960757e+07    5802.0   \n",
       "Dense residential neighbourhoods        6993.079521  4.613231e+07    6815.0   \n",
       "Dense urban neighbourhoods              4448.501438  1.930257e+08    3344.0   \n",
       "Local urbanity                          4277.220397  1.071213e+08    1598.0   \n",
       "Regional urbanity                       3552.061623  3.865336e+07     316.0   \n",
       "Metropolitan urbanity                   3819.015313  1.318199e+07     135.0   \n",
       "Concentrated urbanity                   1527.810889  7.867210e+06      11.0   \n",
       "Hyper concentrated urbanity           747712.533029  1.271663e+06       6.0   \n",
       "\n",
       "                                                   ... fractality              \\\n",
       "                                             mean  ...        75%         max   \n",
       "signature_type                                     ...                          \n",
       "Wild countryside                      5262.662128  ...   1.087244    6.436920   \n",
       "Countryside agriculture               6103.812918  ...   1.088969   13.445506   \n",
       "Urban buffer                          6339.599043  ...   1.088700   17.908917   \n",
       "Open sprawl                           2309.238110  ...   1.101593  268.246039   \n",
       "Disconnected suburbia                 1017.207867  ...   1.091667    4.022005   \n",
       "Accessible suburbia                   1627.488939  ...   1.090873    5.549176   \n",
       "Warehouse/Park land                   1484.178936  ...   1.095447    3.629490   \n",
       "Gridded residential quarters          1101.256942  ...   1.087953    1.630874   \n",
       "Connected residential neighbourhoods  1211.006013  ...   1.093833    4.665447   \n",
       "Dense residential neighbourhoods      1572.557494  ...   1.091611    5.789690   \n",
       "Dense urban neighbourhoods            1400.642709  ...   1.072876    3.028465   \n",
       "Local urbanity                        1092.282020  ...   1.068875    5.857685   \n",
       "Regional urbanity                     1803.643697  ...   1.070887    3.260720   \n",
       "Metropolitan urbanity                 1375.312753  ...   1.085932    4.011579   \n",
       "Concentrated urbanity                 3700.784089  ...   1.090851    2.924473   \n",
       "Hyper concentrated urbanity           3097.160016  ...   1.096803    1.125311   \n",
       "\n",
       "                                     convexity                                \\\n",
       "                                         count      mean       std       min   \n",
       "signature_type                                                                 \n",
       "Wild countryside                        6214.0  0.847012  0.144665  0.171730   \n",
       "Countryside agriculture                10882.0  0.850269  0.143361  0.174666   \n",
       "Urban buffer                           10636.0  0.851529  0.138671  0.206889   \n",
       "Open sprawl                            17357.0  0.820230  0.159341  0.209074   \n",
       "Disconnected suburbia                   9418.0  0.843098  0.132009  0.292148   \n",
       "Accessible suburbia                    10919.0  0.844585  0.123035  0.375821   \n",
       "Warehouse/Park land                    10675.0  0.833803  0.152972  0.216611   \n",
       "Gridded residential quarters            2561.0  0.864575  0.121242  0.342705   \n",
       "Connected residential neighbourhoods    5802.0  0.838442  0.145711  0.268105   \n",
       "Dense residential neighbourhoods        6815.0  0.843006  0.149689  0.267939   \n",
       "Dense urban neighbourhoods              3344.0  0.873944  0.132032  0.239345   \n",
       "Local urbanity                          1598.0  0.888981  0.124262  0.369595   \n",
       "Regional urbanity                        316.0  0.894825  0.133988  0.128971   \n",
       "Metropolitan urbanity                    135.0  0.920512  0.112035  0.476495   \n",
       "Concentrated urbanity                     11.0  0.934777  0.100749  0.654358   \n",
       "Hyper concentrated urbanity                6.0  0.869961  0.142417  0.625078   \n",
       "\n",
       "                                                                              \n",
       "                                           25%       50%       75%       max  \n",
       "signature_type                                                                \n",
       "Wild countryside                      0.749014  0.897610  0.967863  1.000000  \n",
       "Countryside agriculture               0.756614  0.902827  0.966824  1.000000  \n",
       "Urban buffer                          0.754072  0.900720  0.966431  1.000000  \n",
       "Open sprawl                           0.708346  0.878782  0.953845  1.000000  \n",
       "Disconnected suburbia                 0.740525  0.888421  0.957065  1.000000  \n",
       "Accessible suburbia                   0.753064  0.877346  0.951271  1.000000  \n",
       "Warehouse/Park land                   0.718129  0.894513  0.962252  1.000000  \n",
       "Gridded residential quarters          0.775185  0.906935  0.968370  1.000000  \n",
       "Connected residential neighbourhoods  0.729141  0.892645  0.962229  1.000000  \n",
       "Dense residential neighbourhoods      0.739355  0.902421  0.964749  1.000000  \n",
       "Dense urban neighbourhoods            0.792542  0.929865  0.977628  1.000000  \n",
       "Local urbanity                        0.817659  0.944655  0.983643  1.000000  \n",
       "Regional urbanity                     0.836158  0.951919  0.987714  1.000000  \n",
       "Metropolitan urbanity                 0.900620  0.966404  0.994193  1.000000  \n",
       "Concentrated urbanity                 0.929441  0.970923  0.990041  0.999957  \n",
       "Hyper concentrated urbanity           0.824920  0.896392  0.977088  0.996822  \n",
       "\n",
       "[16 rows x 56 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = signatures.groupby(\"signature_type\").describe()\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "consecutive-working",
   "metadata": {},
   "outputs": [],
   "source": [
    "seaborn.set_theme(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "about-supervision",
   "metadata": {},
   "source": [
    "### Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "instructional-request",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='area', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.set_yscale(\"log\")\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "rocky-sussex",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"area\"].reset_index(),\n",
    "                 x_vars=grouped[\"area\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ahead-watershed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"area\"].reset_index(),\n",
    "                 x_vars=grouped[\"area\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "g.set(xscale='log')\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "following-committee",
   "metadata": {},
   "source": [
    "### Perimeter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "convinced-medication",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='perimeter', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.set_yscale(\"log\")\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "bibliographic-myanmar",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"perimeter\"].reset_index(),\n",
    "                 x_vars=grouped[\"perimeter\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "tender-computer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"perimeter\"].reset_index(),\n",
    "                 x_vars=grouped[\"perimeter\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "g.set(xscale='log')\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "arctic-picnic",
   "metadata": {},
   "source": [
    "### ERI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "handled-demonstration",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='eri', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "ahead-relaxation",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"eri\"].reset_index(),\n",
    "                 x_vars=grouped[\"eri\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pending-treatment",
   "metadata": {},
   "source": [
    "### Circlular compactness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "initial-subdivision",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tXctf+OuiNCfLppj4k9sBfo0UFRFtVETAEBTXAADglOXk5avXXVVPq/rRcuMnBJgze4by8wtks6Vr5py/VmXMOJGuxIQ4NWrkq2lcAMCNKK4BAECDlZ9foDEPVF7kL3iJdRfgXhTXAOrEjNkxSks/rvX/3K7iYrtmzI5RdESy0bFQx5L+t5Lkvxf8UwVZWUqanaDpEXFGxwJML2XODBXkFciWYdO0mKnO/em2dM1IiJOvn6+mTKOF3RNQXAP/M3tWjHJzM+Uotmvxsv8oK6dIs2fFKCKSgvB05ORm6pZH/+obvu31PwxMg/qSnZerK8c96tzet+xNA9MAnqMgr0DTH6n8+yZpEYPXPQXFNfA/ubmZuuv25pKaO/ctX3fUuEAAAMDjUFwDAGAiSbOTlJWbp3SbTVsWP+lyrCDrhKbFRSvI30/TI+grDJgRxTUAACaSlZun1sMeV+sqzvntzefrLQ+AU8MiMgAAAICbUFwDAAAAbkJxDQAAALgJfa4BwMQSZ8crKzdH6bZ0bfvnv5z7C7NyNDVuqoL8AxQbEW9cQACAC4rrKhw9dlQxC5/T0Qyb0VEAnKGycnMUfmdvhVdyPPWND+s1DwCganQLqYKP1VuJdz8oHyvXIAAAAKgexTUAAADgJjTJAgDOCImzEpWZlytJstnSlfHSIuexouwsTYmLVLCfv2IjY42KCKABoLgGAJwRMvNy1XzwXZKk5pWcc/St5fUXCECDRLcQAAAAwE1ouUadmjMzWnk5mcqwpen/VqY792fm2JUQM05+AcGaFjXDwISeY+asaOXknJDNlqaVr//1u8zJtitm+lhJUkBAY0VF8vsEAMAo9VZcHzhwQBEREbLZbAoNDdWcOXN03nnnlTvv3Xff1YIFC+RwOGSxWLR06VI1a9asvmLCzfJyMjWmd7Ck4AqPL/gws34DebCcnBPq3TdAUkCl53y44UT9BQIAAOXUW3EdFxenESNGqH///lq7dq1iY2P16quvupyze/duPf/883rllVfUvHlzZWZmytfXt74iAjiDJM6K1Ym8TKXb0mV76WPn/qLsAk2Om6jGfsGKjUw0MKFnSZyVoMy8nP/9Pv/6bC/KztaUuGkK9gtQbGScgQkBlDU3OUkFWXlGx5BvkJ+mxkw3Oobb1Etxffz4cf3www9aunSpJKlv375KSkpSWlqamjRp4jzv5Zdf1gMPPKDmzU8ONQkOrri1E39JmRUne1GR4pevly07Vymz4jQlMsHoWDiDJc+KVnbuCaXb0vTRy391X8nPtisydqwC/RsrxgRdV07kZSp4SIdK7qlIJ1b+WK95PF1mXo6aDL5dTSo5nvbWunrNA6B6BVl5iuz4qNExNOuH+UZHcKt6Ka4PHz6sFi1ayGq1SpKsVqvCw8N1+PBhl+J63759at26te666y7l5OSod+/eGjNmjCwWS33E9EgFOdn6v3tuc24nbthuYBrPNGtmtPJyT/ZlfnlFmsux7NxixU0fKz//xoqkb3iNZOee0CWDKu++snsVXVcAAA2XqQY02u12/fTTT1q6dKkKCgr00EMP6ayzztKAAQNq/DOaNg2qk2zNm5uzFd3Laim3baasVmvVF0ZWE+QtyM/U4Jv9JJ1V6TmrP8w0PKfVWv3kPlarl+lzmiGjJFm9qsnpZY6cZd/jFR03Q06rVzXvdS/jc1aXseQco3N61eC97mWC95HH/D6ryellgoySMe/16p6zvpjlc8xd6qW4btWqlY4cOSK73S6r1Sq73a7U1FS1atXK5byzzjpLffr0ka+vr3x9fXXjjTdq165dp1RcHz+epeJih5v/H0hHj5pz4F2x3VFu20xZ7faqXwu7CfLW5O+luNj4nHZ7cY3OMXtOM2SUJHtxNTmLzZGz7Hu8ouNmyGmv5n1kN8N7qAbvdTPkLK7Be73YBO8jj/l9VpPTDJ/vkjHv9eqes76Y5XPsVHh5WSpt0K2X4rpp06bq0KGDNmzYoP79+2vDhg3q0KGDS5cQ6WRf7M2bN6t///4qKirStm3bdPPNN9dHRAAAUIUZs5KVnZvv3LbZbFr3UtWDfvOybYqK/WugWqB/I0VHxtRZRk8yd9YM5Zf6fWbYbEp4LrrS8zMybUqK/Wv10Eb+jTQ1svLzG5K5yQkqyM41NINvoL+mxtRsUHa9dQuJj49XRESE5s+fr8aNG2vOnDmSpFGjRmncuHG65JJLdNttt+m7777TrbfeKi8vL3Xv3l2DBw+ur4gAAKAS2bn5+scdtSvmdq5h7EqJ/Nx8Tep3+jPozFt/5kxeUJCdq+hLja0HZ3z7Vo3Prbfiun379lq5cmW5/YsXL3b+28vLS5GRkYqMjKyvWAAAoAGZPWuG8kq3sGfY9OzCylvLM7Nsii/VIixJfv6NFHGGtArD/Uw1oBEAAKA28nLzNXJQ7eZUX7bqzGkVhvtRXAMAYKCEWUnKzP2rP2m6zab0V/+vysfYczI1OTbKuR3s76+4yIazCAfgySiuAQAwUGZurgJuf8S5XfEM8dX8jHWL3BcIQK1UP5kmAAAAgBqhuAYAAADchOIaAAAAcBOKawAAAMBNGNAIACaSMCtOJ3KzndvptnSlvfp2pecXZ+dpUuxk53Zj/0DFRTKNGAAYheIaAEzkRG62rP27Obebnerj1251byAAwCmhW0glUmYlqLioSNNfXqzioiKlzKIlCAAAAFWj5boSBbm5eu6BMc7t2LdXGJgGAAAAnoCWawAAAMBNKK4BAAAAN6lxt5Cff/5ZoaGhatasmbKzs/Xiiy/Ky8tLDz74oPz9/esyIwAApyxhVoJO5OQ6t9Nt6Upf/lKVjynOztak6RHO7cYB/oqLjKuzjAAanhoX15MmTdLTTz+tZs2aac6cOTpw4IAaNWqk2NhYpaSk1GVG4Iw0Y2aUcnIynNs223Gte6vqm015ucWKjnnMuR0QEKLoqJl1lhFnpvhZ8crMyXHZl2ZLV/ryNyt9jD07V5OmT3VuBwcEKD4yvq4iSpJO5OTKu99g53bz0/kZ699yXyAAZ4QaF9e///672rVrJ4fDoY8++kgbNmyQn5+fbrzxxrrMB5yxcnIydG3vglJ7gmv4yL8e89mHGVWcB5yezJwcWfrd5LKv6an+jPUfuC8QAJhIjYtrX19fZWVlad++fWrZsqWaNGmioqIi5efn12U+ACaXNCtKWS4t7Gn64nVLpecX5jg0bfpjLvuCAkI0PZIWdgCA56txcd23b1/de++9ys7O1siRIyVJP/zwg1q3bl1n4QCYX1ZOhtr1LSy1pyYt7IUuW/s30MIOAGgYalxcR0VFacuWLfL29lbXrl0lSRaLRZGRkXUWDpVLmRmr/JwsZdjSlfjWR879ttwCJcc8oUYBQZoSlVivmebMiFJezgmXfTbbcT2/7nilj8nMK1ZC9OPObb+AxpoWTQsmAADwTKe0iEz37t2d/z506JCaNGmiSy65xO2hUL38nCxNv/HiSo8nbfquHtOclJdzQg9d6yizt0kNHvnXY5Z8dqKK8wAAAMytxsX1E088oZEjR+ryyy/XqlWrlJCQIC8vL0VHR2vIkCF1mRFwq1kzo5Rbuo9w+nEtf7vyPsKSlJPrUGypWTj8A0IUySwcHiV+1nSdyM10bqfb0pS2bHul5ztyCvVE7ATndmP/YMVHJtVlRABAA1Dj4nrr1q2aPXu2JOnll1/W0qVL1bhxYz322GMU1/AouTkZ6n9d7WbhWLuZPsKe5kRupopvb+PcDlGbKs4+qbj049cdqoNUAICGpsbFdWFhoXx9fXXkyBHZbDZdccUVkqRjx47VWTgAAADAk9S4uO7QoYMWLVqk33//XT179pQkHTlyREFBQXWVDQAAAPAoVS/3VsqMGTO0d+9e5efna8KECZKkr7/+Wv369aurbAAAAIBHqXHL9TnnnKN58+a57OvTp4/69Onj9lAAAACAJ6pxy7XD4dCKFSt07733Olurd+7cqXfffbfOwgEAAACepMYt188884y++OIL3XvvvYqLi5MktWzZUrNmzdKtt95aZwEBAAAkadbMGcrNyavyHJvNpheXx9fqebJzbIqNmV7pcf8AP0VGRdfqOdBw1bi4XrNmjdasWaMmTZooPj5ektS6dWsdOsT0VAAAoO7l5uTp9htijI6hdR8nGx0BJlbj4tputyswMFDSyWXPJSk7O1sBAQF1kwwAAMADzZmRrLzs/CrPybDZNPeN+NN+jhO5NiVEVd66Lkl+gY00Ldr4i5EzTY2L6+uuu06zZs1SVFSUpJN9sJ955hldf/31dRYOAADA0+Rl52vMFZFGx9CC/8wyOsIZqcbFdWRkpKZOnaorrrhCRUVFuuyyy3TNNddozpw5dZkPAADUg+SZycrKrby1Nd2Wrn+/UbvuEPk5NkVMr7y1Nci/kWKiaGmFZ6txcR0UFKT58+fr+PHj+v3339WqVSs1b968LrMBAIB6kpWbrwtunmZohr3v02AHz1fjqfhKCwsLU15eng4dOsSARgAAAOB/atxy/emnnyo6OlpHjx512W+xWPTjjz+6PRgAAADgaWpcXCcmJurRRx/VHXfcIT8/v7rMZKiUmQkqyMmRzZauuDdec+635WRrRsw0+QYEaEpUnIEJAQAAYFY1Lq5PnDihO++80zkNX0NVkJOjuJtur/R4wgfr6jENAAAAPEmNi+tBgwZp1apVGjx4cF3mAQCgQYmfmaiMKlYVTLely7LihVo9hyMnUxNjoio9HhLgp/io2Fo9B4CaqXFx/e233+q1117T4sWL1axZM5djy5cvd3swAAAagoycPOXddH+lx/3d9DxVLgr+wVI3PQuA6tS4uB4yZIiGDBlSl1kAAAAAj1bj4rpdu3a69NJLy+3ftWuXWwMBAAAAnqrG81zff3/Ft7Qeeught4UBAAAAPFm1LdfFxcVyOBwu/5U4ePCgrFZrnQYEgIYibmasMnKzqjwnPT1devPD03+SnHxNmP5ElaeE+AcpISrx9J8DAFCpaovrjh07Oqff69ixo8sxLy8vjR49um6SAUADk5GbJdtNnao8xx2TndqqO+EDuvMBQF2ptrjetGmTHA6H7r77bi1btsy532KxqEmTJg16QRkAAADgVFRbXJ999tmSpI0bN8rLy0s+Pj7OY4WFhSooKJCvr2/dJQQAAAA8RI1nC3nggQc0ZcoUde7c2bnv+++/17x58/Taa69V/kAAAACYTmZ2lj7e95nRMZSZXfVYFE9T4+L6p59+KjcVX6dOnbRnzx63hwLOBDNmRCg7J6PS4+m243p/naPS4zWRl2dRVPSYSo8HBoQoOnp2rZ4DAOCZggODdEP7a42Ooe35u42O4FY1Lq4bN26sY8eOqXnz5s59x44dk7+/u9aWQmXmzpiugpxMl30Z6elK2vBFpY/JyC1UcvQE57ZvQLCmRifVVUSchuycDHW59mgdP4tDUuXP8aXxDRYAADQoNS6ub7rpJk2aNEkxMTFq06aNDh48qNmzZ+uWW26py3yQVJCTqair25bZW3a7ajO/OOC+QAAatLiZccrIya70eLotXXrr7do9SU6uJsRMrvKUkIBAJUQlVHo8bma8TuTkVno8zZYuy1vLKj1eE46cHE2MmVbp8cYB/kqIiq/VcwBoWGpcXE+cOFGzZ8/WkCFDVFBQoEaNGmngwIF64omq51MFAHiWjJxsZfTuUenxGq8+Vt3zVHfCh59WefhETq4ye/er9LhPpUdOTWZVBz9c76ZnAdBQ1Li4btSokeLi4hQbG6v09HSFhYU5578G0HAlzoxUVo6t0uPptuM68VbtnqMoV5oaU3nf8KCAUMVGzardkwAAUA9qXFyXyM7Odv5Xok2bNm4NBcA8snJsCu99rNLj4W57psqfI7UWCxYCAFCfalxc//zzz5o8ebL27Nkji8Uih8PhbLn+8ccf6ywgAAAA4Clq3HUuISFBV111lXbs2KGgoCDt3LlTw4YN0+zZTOMFAAAASKdQXO/Zs0eTJ09W48aN5XA4FBwcrKlTp+qZZ56py3wAAACAxzilAY1FRUXy8fFRWFiY/vjjDzVu3Fg2m60O48FMZs+IVF62rdLjtvQ0LXy/ds+RmSfFR1U+sM0vMFQR0VUPbJs5I1K5VQzAs6Uf14r3TjfhSTl50vQqFmfxDwhVVDU5AQBAw1Pj4vqKK67Qe++9p4EDB+rmm2/WqFGj5Ovrq65du9ZlPphIXrZN93WpavIsq5ueqfLnePnL6h+dm2PTLV2PuylLVSp/jve21cPTAwAA06lxcV26+8cTTzyhv/3tb8rJydGAAQPqIhcA1FjczBhl5J6o8pw0W5q0wnb6T5JbpAnTx1V5Soh/YyVEJZ/+cwAAPN4pT8XncDhks9nUv39/5rkGYAoZuSeU3qdJledYVPXxmkiv7oSNabV+DgCAZ6vxgMYTJ05oypQp6tSpk66++mp16tRJU6ZMoc81AAAA8D81Lq4jIyOVn5+vt99+W19//bXefvttFRQUKCoqqi7zAQAAAB6jxt1Ctm/fri1btsjPz0+S1L59e82ePVvXXnttnYUDAAAAPEmNW67btm2r33//3WXfH3/8obZt27o9FAAAAOCJatxy3a1bNz3wwAPq37+/WrZsqT///FPr1q1T//799dZbbznPGzx4cJ0EBQAAAMyuxsX1119/rXPOOUdff/21c1+bNm301Vdf6auvvpIkWSwWimsAAACcsWpcXL/22mt1mcMwKTPiVZCT49y22dKVsPbNSs+35eVqRvRU57ZvQICmRMfXZUQAAAB4iFOe5zorK0vZ2dku+1q0aOG2QPWtICdH07v3Pu3HJ2350I1pAAAA4MlqXFx//vnnio2NLTeo0WKx6Mcff3R7MAAAAMDT1Li4jomJ0aOPPqpbb73VOR0fAAAAgL/UuLjOz8/XwIEDZbVa6zIPAAAA4LFqPM/1fffdpyVLlsjhcNRlHgAAAMBj1bjl+qabbtKDDz6oRYsWKSwszOXYpk2b3B4MAAAA8DQ1Lq7HjRunLl26qE+fPvS5BgAAACpQ4+L6t99+09tvvy0vrxr3JAEAAADOKDWulG+88UZt27atLrMAAAAAHq3GLdcFBQUaM2aMunTpoqZNm7ocmzt3rtuDAQAAAJ6mxsX1+eefr/PPP78uswAAAAAercbF9eOPP16XOQAAAACPV+PiWpK2bdumtWvXKjU1VeHh4br99tvVrVu3usoGAAAAeJQaD2hcuXKlJk6cqObNm6t3794KDw/X5MmTtWLFirrMBwAAAHiMGrdcL1myREuXLtVFF13k3HfLLbdo3LhxGjp0aJ2EAwAAADxJjVuubTab2rdv77KvXbt2ysjIcHsoAAAAwBPVuLi+/PLLNXv2bOXm5kqScnJyNHfuXF122WV1Fg4AAADwJDXuFpKQkKAnnnhCXbp0UUhIiDIyMnTZZZdp3rx5dZkPAAAA8Bg1Lq7Dw8O1bNky/fnnn87ZQlq2bFmX2QAAAACPUuPiesuWLTr77LPVtm1bZ1G9f/9+HT58WNdcc02dBQQAAAA8RY2L68TERC1btsxlX2BgoBITE/X++++7PRgAAACQmZ2lTf/90vAMNVXj4vr48eMKDw932RceHq6jR4/WPBkqNDc5RgU5mZUet6WnacaHtZuVJSO/SMlR46s8xzcgWFNjkmv1PAAAAO4UHBikG8/vYmiGbTm/1PjcGhfXbdq00datW11WZNy+fbtat259SuFQXkFOpiIua17FGVUdc5/ZX3OhBAAAUBs1Lq4ff/xxjR07VoMHD1abNm106NAhrV69WjNnzqzLfAAAAJKkrOxMfbX7I6NjKCu78rvNQI2L6169eumll17SW2+9pc2bN6tly5ZasmSJOnXqVJf5AAAAJElBgcG6/JJeRsfQb0e3GR0BJlbj4lqSOnXqVGUx/fDDD+uf//xnrUMBAAAAnuiUiuvqfPmlsSM5AcDMcrOzlbnrv0bHUKPsbKMjwISyszO1/9uPDc8AeDq3FtcAgMr5BwYquNP5RseQ/5+5RkeACQUGBqvdpTcYmmHvnzsNfX7AHbyMDgAAAAA0FLRcAwBQh3Kzs5Sxa6uhGUJOYQEMALXj1uLa4XC488cBAODx/AODZOnUrfoT65Dfn3sMfX7gTFKjbiF2u13Tpk1TQUFBleeNHj3aLaEAAAAAT1Sj4tpqterzzz+XxWKp8rxHHnnELaEAAAAAT1TjbiH33nuvnnvuOY0dO1Y+Pj51mQk4I2Rn5+qn742dEi07O8jQ5wcAoKGpcXG9bNkyHTt2TEuXLlWTJk1cWrE/+eSTusgGNGiBgf668O+BhmbITPM39PkBAGhoalxcp6Sk1GUOACaVk52r33YZO9NAUbaxFyEAcCqysjO15adNRsdQFovyGKLGxfWVV15ZlzkAmFRAoL/COxnbfST1CC3sADxHUGCwul94o9ExtDtrh9ERzkinNBXfjz/+qC+//FLp6eku0+6NHz/e7cEAAAAAT1PjFRrffPNNDR8+XNu2bdPixYu1d+9eLV26VAcPHqzLfAAAAIDHqHHL9ZIlS7RkyRJ16dJF//jHP/TCCy9o8+bNevfdd+syHwCgnuVmZytz1/dGx5BvdtWz6eRmZ+nErq/qKU3FvFn5EEAZNS6ujx8/ri5dukiSvLy8VFxcrOuuu05Tpkyps3C1lZIcp/ycqj+cM9LTlfjB2tN+joy8XCVHTa7ynEYBgZoSk3DazwEA9ck/MFDBnf5udAz5Hzle9fHAIDXudHk9pakkw5HfDX1+AOZT4+K6ZcuW+u2339S6dWudd9552rRpk8LCwkw953V+TrZiLr/W6BhK/uozoyMAAACgHtS4uH7ooYe0b98+tW7dWo8++qjGjx+vwsJCRUdH12U+AAAAwGPUuLgeOHCg89/XXXedduzYocLCQgUGMv8sAAAAIFVTXBcXF1f+QG9veXt7q7i4WF5eNZ50BAAAAGiwqiyuO3bs6LLMeVkOh0MWi0U//vij24MBAAAAnqbK4nrTJuOX7oR5ZGXnattPxi6lmpXta+jzAwAAVKXK4vrss8+urxzwAEGB/up6YbChGfZksgw2AAAwrxoPaJwyZUqlXUTmzp3rtkAAAACAp6pxcX3uuee6bB89elTvv/+++vXr5/ZQQG1kZ+fqmx+NXTUtOzvA0OcHAADGqHFx/fjjj5fbN3jwYL3wwgtuDQTUVmCgvzp3CDI0w+EMuq8AAHAmqnFxXZEOHTpox44d7soCAKclNztHWd/mGR1DftmVT18KADgz1Li43rp1q8t2Xl6e3nnnHf3tb3+r0eMPHDigiIgI2Ww2hYaGas6cOTrvvPMqPHf//v264447NGLECE2bNq2mEQGcofwDAxR0aROjY8j/cJrREQAABqtxcV12mfOAgABddNFFmjdvXo0eHxcXpxEjRqh///5au3atYmNj9eqrr5Y7z263Ky4uTr169appNAAAAMAUalxcf/zxx6f9JMePH9cPP/ygpUuXSpL69u2rpKQkpaWlqUkT19amf/7zn+rZs6dycnKUk5Nz2s8JAAAA1Lcar1u+ZcsWHThwwGXf/v379fnnn1f72MOHD6tFixayWq2SJKvVqvDwcB0+fNjlvD179mjLli267777ahoLAAAAMI0at1wnJiZq2bJlLvsCAwOVmJio999/v9ZBCgsLNX36dM2aNctZhJ+Opk3/miXC6lXja4c6ZfXyUvPmlS++4uVV+RLz9cnLy1JlTqvV+N+n1Vr171Iyx+te3WsuSVar8a+71Vr1ay5JXibI6VVNTjO85lL1r7vH5DTBe12q/v3uCX+bkue8160m+C6yVvM95GWSv02vav42PeW9bob3kFSDz3gT5KzJe6hEjYvr48ePKzw83GVfeHi4jh49Wu1jW7VqpSNHjshut8tqtcputys1NVWtWrVynnP06FEdPHhQDz/8sCTpxIkTcjgcysrKUlJSUk1j6vjxLBUXOyRJ9mJzjNy3Fxfr6NHKlw0vyWu04mJHlTntduN/n3Z71b9LyRyve3WvuSTZ7ca/7nZ71a+5JBWbIGdxNTnN8JpL1b/uHpPTBO91qfr3uyf8bUqe8163m+C7yF7N91CxSf42i6v52/SU97oZ3kNSDT7jTZCz7HvIy8vi0qBbWo2L6zZt2mjr1q3q1q2bc9/27dvVunXrah/btGlTdejQQRs2bFD//v21YcMGdejQwaW/9VlnnaXt27c7t5977jnl5OQwWwgAAAA8xiktIjN27FgNHjxYbdq00aFDh7R69WrNnDmzRo+Pj49XRESE5s+fr8aNG2vOnDmSpFGjRmncuHG65JJLTu//AQAAAGASNS6ue/XqpZdeeklvvfWWNm/erJYtW2rJkiXq1KlTjR7fvn17rVy5stz+xYsXV3j+2LFjaxoNAAAAMIUaFdd2u10333yz3n33XSUmJtZ1JgAAAMAj1Wg4q9VqldVqVX5+fl3nAQAAADxWjbuF3HPPPZowYYIeeeQRtWzZUhbLX9OitGnTpk7CAQAAAJ6kxsV1yXR4ZReNsVgs+vHHH92bCgAAAPBANS6u9+zZU5c5AAAAAI9njiWEAAAAgAagypbrBx98UC+++KIkacSIES79rEtbvny5+5MBAAAAHqbK4nrAgAHOfw8ZMqSuswAAAAAercriul+/fs5/f//997r11lt1+eWXO/d99dVXeu+993THHXfUXUIAAADAQ9S4z/WGDRt08cUXu+y7+OKLtWHDBreHAgAAADxRjYtri8Wi4uJil312u73cPgAAAOBMVePiukuXLnrmmWecxXRxcbGee+45denSpc7CAQAAAJ6kxvNcR0dH65FHHlH37t111lln6fDhw2revLkWLlxYl/kAAAAAj1Hj4rply5Zas2aNdu3apcOHD6tVq1bq1KmTvLyYKhsAAACQTqG4liQvLy917txZnTt3rqM4AAAAgOei2RkAAABwE4prAAAAwE0orgEAAAA3obgGAAAA3ITiGgAAAHCTU5otBHUjMztHH+/9zegYysy2Gx0BAADAo1Fcm0BwYIBuuKC50TG0I/uo0RGABi3EP0j6YFeV56Snp0sBjU7/SXLyFRYWVn0OAECdoLgGgHqSEJVY7TmTYifL2r/baT+Hfe1WzUt88rQfDwCoHfpcAwAAAG5CyzUAAFCQfyPtfX9OpcfTbelqFBBaq+fIz7EpLLTybktB/rXoEgWYBMU1AAB1KCTAT/pgaaXH023psgQE1+o5HDmZVRatIQF+1f6MmKiYKo9HxU7XP+6IPuVspe1cM0MzE5Nq9TMAs6O4BgwSGBCiLz+r/Hi67bj8/By1eo68PIvCQptWmaE6QQGhSv2w8uPptuPy9j+ddH8pylWVOYNq2VoGGCk+KrbK45NjoxRw+yO1eo6cdYv0ZOLMWv0MT+Af4Kd1HydXeY7NZlNgLT8zsnNsCg2t/Gf41+BiBWcuimvAINHRs6s+HvOYru1dUKvn+OxDX81IfqFWPyM2alaVx6dNf0zt+hbW6jn2b/DRnKTa5QTQ8EVGVd9yHh8bq5GD4mr1PMtWJSg+sfoByEBFGNAIAAAAuAnFNQAAAOAmFNcAAACAm1BcAwAAAG5CcQ0AAAC4CcU1AAAA4CZMxQcAcBESECh9+Gmlx9Nt6VJALSc3z8mtctETZw4A8DAU1wAAFwlRCVUenzR9qiz9bqrVczjWf6B5SXNr9TMAwIzoFgIAAAC4SYNuuc7Mztamn743OoYys7ONjgAAAIB60KCL6+DAQN144d+NjqGt2WlGRwCABqdxgL/04fpKj6fZ0mUJCKjVczhyctSkir7hjWvb9xwwkG+Qn2b9MN/oGPIN8jM6gls16OIaANBwJUTFV3l80vQIefcbXKvnKFr/luYlza7VzwDMamrMdKMjNEj0uQYAAADchOIaAAAAcBOKawAAAMBNKK4BAAAAN2FAI2rMLzBUL39Z+XFbepqCazngNzNPCg1rUmUGAAAAs6K4Ro1FRM+q8nhC9ON66FpHrZ5jyWcWxc14vlY/AwAAwCh0CwEAAADchOIaAAAAcBOKawAAAMBNKK4BAAAAN2FAIxoc/4BQvbet8uO29OMKqOWsJjl5UmhY0yozAACAMw/FNRqcqGpmNYmNeUz9ryuo1XOs3eyrxOQXavUz4D4h/o2ljWlVnpNmS5P8a/GRl1ukJqGVTxPpzAEAOKNRXAPweAlRydWe80TsBBXf3ua0n8Nr3SE9lfh/p/14AMCZgT7XAAAAgJtQXAMAAABuQnENAAAAuAl9rgHARBr7B+rE2q3O7XRburwCK5/epjg7T2GhYS6PBwAYh+IaAEwkLjLBZXtq3FSF39m70vNT3/hQcxPm1nUsADCMb6C/Znz7luEZaoriGgAAAKY1NSbO6AinhOIaQK0EBYRo/4YM57bNliafAEul5xfmOBRaZr7ooICQOssHAEB9orgGUCvTI2e6bEfGjtUlgwIqPX/3qhzNSnyurmMBAGAIZgsBAAAA3ISWa8CkAgJC9NmHpbtbHJeff9XXw3m5xQoNberyMwAA9csvsJEW/GdWledk2Gxq7B962s9xItemkNCqH+8X2Oi0fz5OH8U1YFLRUa7dLWKmj1XvvpV3t5CkDzfkKDmJLheAJwn291fmukXO7XSbTdaA4CofY8/JVFipwirYv+YzGaDuTYuOqfacpNhYTep3+gP15q1P0PTExNN+POoOxTUAAAaKi5zusj0tLlqthz1e5WN+e/N5zUmYUZexAJwm+lwDAAAAbkLLNQAAqFagfyPtXPNXa7nNZpNfYGiVj8nLtim0VPeVQH/6AKPho7gGAADVio507UccEx+rXndNr+Tskz5anqTkePoF48xCcQ0AABoMP/9GWrYqwblty7ApOCi00vMzs2wKDXE97kcLO2qB4hoAADQYEZHRLtuJCXEa80BSpecveGm6YuMSKj0OnCoGNAIAAABuQnENAAAAuAndQgAApyQ4IECZ6z9w2ZdmS5c1sPKFTOzZuWoSGubyMwCgIaK4BgCckvjI+HL7psRNU5PBt1f6mLS31iklYU4dpgIAc6BbCAAAAOAmFNcAAACAm1BcAwAAAG5CcQ0AAAC4CcU1AAAA4CYU1wAAAICbMBUfAKBBahzgrxPr33Jup9vS5RUYWOVjirOzFVZqPu7GAZXP3Q0AFaG4NgHfgGDN/vpopcdt6WkKaVS7lyojv0ihYU2qzQEADUVcZJzL9pS4SDUffFeVjzn61nKlJMyqy1gAGjiKaxOYGpNc5fHk6AmKurptrZ5j5hcHFDPj/2r1MwAAAFA1+lwDAAAAbkJxDQAAALgJxTUAAADgJhTXAAAAgJswoBHwEAEBjfXhhhOy2dIUEGh17s/Jtis0tInzHKMF+jfW7lUnlG5LU6NSOfOz7QoLbaJAf+MzAgBQVyiu4TZ+AY215LMTLvtstuMK9qv8BklmXrFCQ5u6/AxULCpyhiQpNna8+g1u5dy//q3DSkx8xqhY5cT8L2d03Hh1HXGWc/+21//QjATz5AQAoC5QXMNtpkXPLLcvIWacxvSufP7sBR9mKi752bqMBQAAUG/ocw0AAAC4CcU1AAAA4CZ0C8EZxz8gRGs3Zzi3benHFeBvqfIxObkOhYb91TfcPyCkzvKhbjT2D9aJdYec2+m2NFkCfCo935FTqLD/DRQtebwRgvwDlPrGh0q3pcsnKMC5vzArR2GhYQryD6ji0QCA+kZxjTNOZJRr3/C46WM1+Ga/Kh/z1vt5Skh6ri5joY7FRya5bE+Om6jgIR0qPT9z5Y96MuHpuo5VrdiIeElSRPw0dbz/Duf+H5au0ez4OQalAgBUhm4hAAAAgJvQcg0AgIkE+fvptzefV7rNJt8g1+lJC7JOKCw0VEH+Vd9tA2CcBl1cNwoIVPJXn1V5TkZ6ukL8/E/7OTLychUSFlZtDgAAamJ6xHRJUmR8jC69b6LLsW9fflqz4pONiAWghhp0cT0lJqHac2ZET9X07r1P+zmStnyo6BlzT/vxAAAAaDjocw0AAAC4CcU1AAAA4CYNulsIAACoGwF+jfTR8iTZbOkKCAp17s/Jsik0NMx5DnCmobgGANRasF+A0t5ap3RburwD/xrEXZSdrbDQMAX7sdhNQxMVES1Jik2I1aCH/xrjtOqfcUqMSzQqFmA4imsAQK3FRsZJkiLiI9R+5DDn/n3L3tTs+NlGxQKAekefawAAAMBNKK4BAAAAN6G4BgAAANyE4hoAAABwEwY0AgAA1LNG/o00b/1fs6xk2GwKCQ6t9PyMTJtCQv863sifaQ7NiuIaAACgnk2NjHbZnpEQp+mPJFd6ftKiGEXHJVR6HOZBtxAAAADATWi5BjyMv3+wXnvxewUE+ijzRL5an93W6EgVCvAP1nvzv5d/kI+yT+SpjUlzAgDgTrRcAx4mMjJZYWHNdPf9XeXlZVVkZOW3EY0UHZGsJmFN1e/hq+TlZVV0hDlzAgDgTrRcAwDOCMF+/jr61nJJks2WLu/AIOexouwshYaGKdjP36h4ABoIimsAwBkhNjLW+e+I+CidP/J+5/Z/ly3V7PiZRsQC0MDQLQQAAABwE4prAAAAwE3oFgIAHiDIL0Bbnloi/5DGys/MUusWZxsdCQBQAVquAcADxETEycfqrVvGPqimYU0VExFndCQAQAVouQYAAA1Wo0a+WvDSdNls6QppHObcn3EiXaGhYWrUyNfAdGiI6q24PnDggCIiImSz2RQaGqo5c+bovPPOcznnhRde0Lvvviur1Spvb29NnDhR1157bX1FBAAADcy0iJPLjCcnxWnapFnO/XPmRSpmOsuJw/3qrbiOi4vTiBEj1L9/f61du1axsbF69dVXXc7p1KmTHnjgAfn7+2vPnj0aOXKktmzZIj8/v/qKCQAAAJy2eimujx8/rh9++EFLly6VJPXt21dJSUlKS0tTkyZNnOeVbqW+8MIL5XA4ZLPZ1LJly/qIaVq+AcGa+cUBl30Z6ekK8fep9DEZuYUKCfvr9pdvQHCd5auKX0CwFnyYqQxbmoIDrM79mTl2hYQ2kZ9BuQAAAOpCvRTXhw8fVosWLWS1niyurFarwsPDdfjwYZfiurS3335b55xzzhlfWEvS1OikcvuSY57Q9BsvrvQxSZu+U0zyU3UZq0amRc2QJCXGTtDYfm2c+59bf0ixif9nUCpXfv6N9db7J2SzpSnQ33WMb3ZusUJDm8jPv7FB6VBXGvsF68TKH5VuS5d34F99LouyCxQWGqbGflz4AQBOnSkHNO7YsUPPPPOMXnrppVN+bNOmQdWfVIqX1XLKz1H28c2b1/+XsNVa9UQvVquXIbkqY/WylNs2S76nnn5WkjT2sQd1Z99mLsfe2HBMz73wohGxquTl9dfrb5bfY0VK/52aLedzTz0tSXpo7GidNeIK5/4/Xv+Pljy30KhYNWKm909Zpf82S7bNmNWrzGeSlwl/p9YKvp+sBn3nVKXs95HZvn9KeJXJ6WWynNXVI0bVGzh19VJct2rVSkeOHJHdbpfVapXdbldqaqpatWpV7tyvv/5aU6ZM0fz589WuXbtTfq7jx7NUXOyo8fnF9pqfW9njjx7NrNXPOB12e3G1x43IVRl7mdfEXmzM760qZTOW7DNbTkkqLv7r9TdjvhKl/07NmrP077Jk26xZS5j171LynN9n2e+JYhP+Tu0VfD/ZDfrOqUrZ7yOzff+UKC6Ts9hkOaurR4yqN1AxLy9LpQ269TLPddOmTdWhQwdt2LBBkrRhwwZ16NChXJeQXbt2aeLEiXr22Wf197//vT6iAQAAAG5Tb4vIxMfHa9myZbr55pu1bNkyJSScnP5m1KhR2r17tyQpISFBeXl5io2NVf/+/dW/f3/99NNP9RURAAAAqJV663Pdvn17rVy5stz+xYsXO/+9atWq+ooDAAAAuB3LnwMeyN8vWAuf26LCQrvRUQAAQCmmnC0EQNUiIhI1bvx98vXl+hjmEujnrx3Pzpdf48YqyMpS65ZnGR3JYwX6+Wnz/8XJL/jkVKB5mSd0NtPTAqbHNzOAOhPgF6wV87aoqLDq2W3QcEyPiJOP1VvXj3lYTcOaaHpEnNGRPFZMRIyahoWp79hI9R0bqaZhYYqJiDE6FoBqUFwDqDNREYmyWLzk59fI6CgAANQLimsAAADATehzDQAATpu/XyO9OHe8ghuHKsOWprPPKr9AHHAmoeUaAACctshp0WoSFqZHJiXL6nVyGziT0XINADjjBPn5aduzT8q/cYjyszLVpiWtrQDc44wvrn0DApS05UPnts2WrlA//0rPt+XlKjQ0zOXxAADPEhMRq9HjR+uGMWO1Y8lCxUTEGh0JQANxxhfXU6LjXbZnxExT3E23V3p+wgfrFJ08p45TAQAAwBPR5xoAAABwE4prAAAAwE0orgEAAAA3obgGAAAA3ITiGgAAAHATimsAAADATc74qfgAnNmC/AK1+/kP5BPkp/wTOTr3rHOMjgQA8GC0XAM4o02PSFTTsKbq9sht8rZ6a3pEotGRAAAejJZr4H/8/YO1fN1RpR0/qpDgRsrKKVLLVucaHatShYV2WYwOAQAAXNByDfxPRGSyEhKfkcXLqlEjr1BoWDNFRCYbHatSvr4+8vPzMzoG6lFxkV1rZzyjgEb+RkcBAFSC4hpAnSoqKJK9qNjoGA1C8+bN5SUpelqs0VEAAJWguAZQp7x9fNSsWXOjYwAAUC8orgEAAAA3obgGALhVcVGR3p87T4F+9A0HcOZhthDUi0b+wUp4+WuFBfvpRE6Bwk08CweA2mnWPFzHjqXSNxzAGYmWa9SLaZFJsnh5adLdVys0rJmmRSYZHQkAAMDtaLn2UI0CgpS06Ttl2NIV6u/r3G/LLVBIaJgaBQQZmA4AAODMRHHtoaZEnVxFbsb0yYrte5Vzf+KG7YpOetKoWAAANwrwa6RVM6dJklq3OsvgNABqgm4hAACYVNS0GFktFlktFkVNizE6DoAaoOUaAADAYL5+vkpaFCNbhk1hoWHO/em2dIWGhMrXz7eKR8NMKK4BD1VYUCSHt8XoGAAAN5gyLVqSNHNGvOYkzHXunxY3VVHR8QalwumgWwjgoXx8fdWsOSsfAqfLXliojXNnKNDPz+goABoQimsAwBnJz89PXhaLoqdNNzqKx/Pz89W8uEdVWFhgdBTAcBTXAACgViKmRsvb2yp/f1blBCiuAQAAADehuAYAAADchNlCyvANCFDCB+tks6UrLCDQuT89J1uhoWHyDQgwMB2AuhDYKFCfprwli4PZVwAAtUNxXcaUqDhJ0ozYCCUMGOrcH/v2CkUnzjYqFupRYaFd8xZt11lnnWd0lAahIK9A/n7mviiNiYjXw2PvZ/YVAECtUVwDZfj6+kiSIiKTDE7SMOTnFSpiarzRMRoE/0b+Kswz/2wMAY38VJiXb3QMADAExTUAeIjIqdM1atQ9RseoVtS06brnnqHVnwjUI99GvoqMHaOw0DCl29IVHh5udCQ0UAxoBAAADd7UqdFqEhamGclz1SQsTFOnRhsdCQ0UxTUAAADgJhTXAAAAgJtQXAMAAABuQnENeKj8vAL5NWKpYQAAzITiGvBQdrs0dWqc0TEAAEApFNcAAACAm1BcAwAAAG5CcY16U1hYrOkLP1Ej/yCjowAAANQJimvUGz+/RpLFS1MjEo2OAgAAUCcorgEAAAA38TY6AGrHNyBQE159R02CA2XLzlX4WW2MjgQAAHDGouXaw02JTJDV21vxd/VTaJOmmhKZYHQk1JOQkFCjIwAezV5UpKKCfKNjAGhgKK4BDxUaGmp0BMCjNW8eLl9fX6NjAGhg6BYClFFYaDc6AuDxrFa+XgCcmfj0A8rw9fUxOgLg8by9+XoBcGaiWwgAAADgJjQtVMLX319jX1qgJsGNlZZ5Qi3Obm10JMAj0T0AAHAmoeW6ElMi4+Tl7a2k+0bJy9tbUyLjjI4EeCRP6R5QlF+ggEb+RscAAHg4imvAQ/Xocb3RERqUgpx8RU+LNzoGAMDDUVwDHoriGgAA8/GM+7UAAABnAF9fX02Lm+qyDc9CcQ0AgIkVFhYYHQH1aPKUKKMjoJYorgEAMLEAfwbaAp6EPtcAAACAm1BcAwAAAG5CcQ0AAAC4CX2uUW8K7cUqKrQbHaNahYV2OYwOAQAAPBIt16g3zZs1l4+P+a/n/Pz81MjXx+gYgEcLCQk1OgIAGILiugEotBdr3KI35esXaHQUAJAkhYaGGh0BAAxBcd0ANGvWXMUOaUpkvNFRAI9lsViMjgAAaAAorgFAFNcAAPcwfwdYAABgekWsJAlIorgGAABuEN483OgIgCnQLQQAcEbyb9RIBXn5RscA0MBQXAMAzkgRU2PksJt/7n0AnoXiugqF9iLFvvaiCu1FRkcBAACAB6C4rkLzZs2VPHqsmjdrbnQUAAAAeAAGNAJlFBXZVVTE3QoAAHDqaLkGymjePFw+LH8O1EqPHtcbHQEADEFxDQBwO4prAGcqimsAAADATSiuAcCDhISEGh0BAFAFiusGwNcvQLkFhUbHAFAPQkNDjY4AAKgCxXUDMCUiTlm5eUbHqJavX4Dy8rkIAAAADRfFNerN1GnxyskrMDoGAABAnaG4roJPI389PCdJPo38jY4CAAAAD0BxXYUpEdN1PCNDUyKmGx0FACQxxR0AmB3FNVCGbyN/5efRNxzmRHENAOZGcQ2UMXVqrIrsDqNjNBhMHQcAOJNQXAOoU0wdBwA4k1BcA6hTdGMAAJxJKK4B1ClPKa6tVm+jIwAAGgC+TRoIi8VidATAo3l783EIcyoqZIA14En4NmkgPKW49pTWQQbhAWcGT3ivhzcPNzoCgFNAt5BqeEox6Ck8pXWQQXhnHk8osuB+vNcBuBvFdTU8pRgEUDsUWQAAd6C4BgAAANyE4hoAAABwE4prAAAAwE0orhsIBl4CAAAYj4qsgfCUgZfMyAAAp8bX19foCDXi69vI6AiAKXhGRYYGgxkZAODUTJ0SbXSEGpkyJcroCIAp0C0EAAAAcBOK62rQjQEAAAA1RXFdDU/pxsBFAFA7PXpcb3QEAEADQHHdQHjKRQBgVhTXZyZedwDuRnENADhjUVwDcDeKa6ACfOECAIDTQXENVIDiGgAAnA6K62pQZLkXv08AANCQUVxXg2LQvfh9AgCAhoziGgAAAHATiusGghZhAAAA41FcNxAU1wAAAMajuAYAAADchOIaAACcEXx8fRUzfap8fH2NjoIGzOJwOBxGh3Cn48ezVFzcoP4vAQAAwES8vCxq2jSo4mP1nAUAAABosOqtuD5w4ICGDRumm2++WcOGDdMvv/xS7hy73a6EhAT16tVLvXv31sqVK+srHgAAAFBr9VZcx8XFacSIEXr//fc1YsQIxcbGljtn/fr1OnjwoD744AO9+eabeu655/Tbb7/VV0QAAACgVuqluD5+/Lh++OEH9e3bV5LUt29f/fDDD0pLS3M5791339WQIUPk5eWlJk2aqFevXtq4cWN9RAQAAABqrV6K68OHD6tFixayWq2SJKvVqvDwcB0+fLjceWeddZZzu1WrVvrzzz/rIyIAAABQa95GB3C3ykZuAgAAAHWtXorrVq1a6ciRI7Lb7bJarbLb7UpNTVWrVq3KnffHH3+oU6dOksq3ZNcEU/EBAACgLhk+FV/Tpk3VoUMHbdiwQZK0YcMGdejQQU2aNHE5r0+fPlq5cqWKi4uVlpamjz76SDfffHN9RAQAAABqrd4Wkdm3b58iIiJ04sQJNW7cWHPmzFG7du00atQojRs3TpdcconsdrsSExP1+eefS5JGjRqlYcOGndLz0HINAACAulRVyzUrNAIAAACnwPBuIQAAAMCZgOIaAAAAcBOKawAAAMBNKK4BAAAAN6G4BgAAANyE4hoAAABwE4prAAAAwE0orgEAAAA3obgGAAAA3ITiGgAAAHATimsAAADATSiuAQAAADehuAYAAADchOIaAAAAcBOKawAAAMBNKK4BAAAAN6G4BgAAANzE2+gA7ublZTE6AgAAABqwqupNi8PhcNRjFgAAAKDBolsIAAAA4CYU1wAAAICbUFwDAAAAbkJxDQAAALgJxTUAAADgJhTXAAAAgJtQXAMAAABuQnENAAAAuAnFNQAAAOAmFNeoM8XFxdq8ebPRMQAAAOqNt9EBzCY3N1cLFy7Ub7/9pnnz5mnfvn06cOCAevXqZXS0crZu3ap9+/Zp5MiROnbsmDIzM9W2bVujYzl5eXlpwYIFuu6664yOUqmff/65yuN/+9vf6ikJ6svy5curPH7XXXfVU5Kaeffdd9WjRw8FBQXpmWee0a5duzRx4kRdfPHFRkdzsXPnTnXs2FGBgYFauXKldu/erVGjRqlNmzZGR0Md6dOnj0aOHKkBAwYoKCjI6DiVys/PV6NGjYyOUa1vvvlGnTt3NjpGtWJjYzVy5EhdcMEFRkepkpGvOy3XZcTHx8tut2vPnj2SpJYtW+r55583OFV5//znP/X888/r1VdflSQVFRUpKirK4FTlXXzxxdq1a5fRMSr18MMPV/rfI488YnQ8F3v27NGwYcN06aWXqkOHDs7/zGjLli1avHixnn/+eed/ZvHdd9/pu+++02effaZ58+bpiy++0BdffKF58+Zp+/btRscrZ8GCBQoKCtKuXbu0ZcsWDRgwQMnJyUbHKicxMVEBAQH673//q6VLl+qss85SdHS00bHKmT17tjIzM1VUVKQRI0aoc+fOWrt2rdGxylm6dKkyMzMlSVOmTFGfPn20ZcsWg1O5euqpp/Tjjz/qpptuUlxcnH766SejI1Xohhtu0OzZs/Xrr78aHaVKcXFxGjhwoN566y3l5+cbHadSbdu21dixY3XXXXfp3XffVVFRkdGRKmTo6+6AiwEDBjgcDoejf//+zn39+vUzKE3l+vXr5ygoKHDJ2bdvX+MCVaJ///6Ojh07Om655RbHoEGDnP/h1A0bNszxxRdfOPr16+c4cuSI46mnnnIsWrTI6FjlpKSkOO655x7H1Vdf7Zg+fbrj6quvdkyaNMnoWOU8+uijjoMHDzq3Dx486JgwYYKBiSpW8pk0f/58x5tvvumyz0xKMi1ZssTx6quvOhwO189Rsyj5PP/3v//tmDBhguPPP/903H777QanKq/k83zr1q2OBx54wPGf//zHcccddxicqmIZGRmOl156ydGjRw/HiBEjHO+//77RkVwcO3bM8cILLzh69uzpePDBBx0ff/yxo7i42OhYFdq5c6dj4sSJjmuuucYxe/Zsl88os9m8ebPjkUcecVx77bWOZ555xvHnn38aHcmFka87Lddl+Pj4uGzn5+fL4XAYlKZyfn5+5bJaLBaD0lQuKipKS5cuVXx8vKZOner8z2yefvppbd++XQUFBUZHqVRBQYG6desmh8Oh8PBwTZw4UZ999pnRscrZvHmzXnzxRTVt2lSJiYlavXq1cnJyjI5Vzu+//+7SZaFNmzY6cOCAgYkqZrFYtG7dOr3zzjvq1q2bJKmwsNDgVOUVFRXpP//5j95//3117dpVkmS32w1OVbmdO3eqd+/eatGihSk/O61WqyRp+/bt6tevny6//HJTfhdJ0rfffqvt27fLz89P1157rd544w1NmDDB6FhOTZs21aOPPqqPPvpIQ4cOVUJCgm688Ua99NJLpmsh7tKli5566iktXrxY7733nm6++WaNHj1a+/btMzpaOZ07d9ZVV10lLy8vffPNNxoyZIhefvllo2M5Gfm60+e6jC5dumjhwoUqKCjQ9u3btXTpUt1www1GxyqnZcuW+vLLL2WxWFRcXKyFCxfq/PPPNzpWOVdeeaUkKS0tTU2aNDE4TeWCg4P1z3/+U9999506dOigbt26qWvXrrr00kuNjuZU8mUbEhKiPXv2qEWLFvr9998NTlWer6+vvL29ZbFYVFhYqBYtWujPP/80OlY5oaGheuGFFzRkyBBJ0qpVqxQaGmpsqApMnz5dixcv1pAhQ9SmTRv98ssvuuqqq4yOVc748eOVmJiorl276vzzz9eBAwd07rnnGh2rnKZNmyomJkaff/65Hn74YRUVFZnyIsDPz08LFizQ+vXr9a9//UsOh8N0F1UvvfSS3njjDbVp00Z33323rrvuOlksFo0ePVq9e/c2Op6L3NxcrV27Vq+//rrOOeccDRkyRNu3b9eoUaOc3SvN4Msvv9Ty5cv17bffavDgwRoyZIi2bdumRx99VO+//77R8SSd7Fq3fPlyff755+rbt6+WLVum1q1bKysrS3379tV9991ndEQnw173emkf9yAFBQWO+fPnOwYPHuwYNGiQ44UXXnAUFhYaHauc1NRUx/333+/4+9//7rj44osd9913n+PYsWNGxyrnm2++cfTs2dPRo0cPh8PhcOzatcsRExNjcKrKFRQUOFavXu24/vrrHRdddJHRcVy89NJLjrS0NMfmzZsdnTt3dnTq1MmxZMkSo2OVc/fddztycnIccXFxjieeeMIxa9Ysx+DBg42OVc6ff/7pGDt2rOPKK690XHnllY5x48aZ7rZmUVGR45lnnjE6RoNy/Phxx9KlSx1ff/21w+FwOA4dOuRYtWqVsaEqsH//fkdycrKzi8Wvv/7qWLhwocGpXMXHxzt+/vnnCo/t3r27ntNULjEx0XHNNdc4pk+f7ti7d6/LsZtvvtmgVOX17dvXMWzYMMf69evL1R0PPPCAQanK69u3r+ONN95w5Obmljv2r3/9y4BEFTPydbc4HCa9z4RK2e12vfXWWxo2bJhyc3NVXFyswMBAo2NV6M4771RycrImT56st99+W5J022236Z133jE2WBnvv/++tm7dqq+++kpNmzZ1tlx36tTJ6GgVKiwsVH5+vilH6B87dkyNGzeW3W53Dsq6++67ddZZZxkdzSPdfffdeu2114yOUam5c+dWedyM3cDgHosXL9aoUaOq3We0JUuWaOjQoWrcuHG5Y6mpqQoPDzcgVXm7d+/WJZdcYnSMam3dutXZRa2qfUYz8nWnW8j/eNIXhNVq1dq1azVs2DD5+/sbHadKhYWF5aazK9tX3AzGjx+vyy67TFOnTlXXrl3l7W2et8ahQ4fUpk2bSqcNNNt0gc2aNXP++9FHHzUwSfW2bt2qgwcPuox2N9tUfD179tSLL76oAQMGKCAgwLnfLO/9kkwHDx509mOWpI8++kjdu3c3MpqLrl27Vtm3euvWrfWYpnKDBg2qMudbb71Vj2mq9u6775YrpCvaZ7QjR46UK7BmzJih6Oho0xTWkjRz5kz961//ctk3fPjwcvuMNnfuXK1Zs8ZlX0pKilavXm1QoooZ+bqbp4IwmKd8QZS4+uqrtXHjRvXp08foKFXy9fVVdna288vi559/NuV8o59//rm2bdum9957T3PmzFHLli119dVX6/777zc6mpKTk7Vo0SI9/PDD5Y5ZLBZt2rTJgFTlpaSkaMqUKRo3blyFxcEzzzxjQKrKRURE6LvvvlPHjh2d/dnNKCUlxfm/FotFDodDFotFP/74o8HJTnr88cclSaNGjdLq1asVFhYmSRozZowiIiKMjOZi1apVkk4WpzabTcOGDZPD4dCqVavUokULg9P9Zdq0aZKkTz75RPv379fgwYMlSatXr1bHjh2NjOb0+eefa8uWLUpNTXVpmMrKyjIwVeW+/PLLcvt27txpQJKq5eXluWwXFxcrIyPDoDTl/frrr/rll1+UlZXlskBcZmamcnNzDUxWMSNfd4rr//GUL4gSy5Ytk81mk5+fn/z9/Z1fuGZpfSkxevRoPfjgg0pNTVVERIQ+++wzZ7FgJk2bNlWfPn3UsmVLtWrVSqtXr9Z//vMfUxTXixYtkiR9/PHHBiep2hVXXCFJuv766w1OUjNff/21NmzYYMo7KaWVzLlvdocPH3Z+bkpSWFiYqQbcnn322ZJOfrkuW7bMuT8mJkYjR440TWtrySDw5557Tq+++qrzQvX666/Xfffd5/yuMpKPj48CAwNlsVhc7qaEh4dX2AhglPfee0/vvfeefv/9d40fP965PysrS35+fgYmc7VkyRItWbJEWVlZLl0r8vLy1K9fPwOTufrqq6+0evVqHTt2TEuWLHHuDwoKcl4UmoEZXneK6zLM/gVRoqQVxqxycnIUEBCg6667Tu3atdNnn30mh8OhMWPGmHIGgUceeUTffvutzj//fHXt2lUpKSmmmimkxN69e7Vjxw5ZLBZdddVVpuoSUjKrzh133GFwkppp2bKl0RFq7MCBA9q3b5969eql7OxsFRYWmm5mk3bt2ik6OtqlpbVdu3YGpyovNTXVZfaitLQ0HT161OBU5R05ckT5+fnOYqCgoECpqakGpzrpyiuv1JVXXqmbbrrJ1Kv0tW3bVj179tTu3bvVs2dP5/6goCBT9Q8eNmyY+vTpo6SkJMXGxjr3BwUFKSQkxMBkru644w7dcccdWr16tQYOHGh0nEqZ4XVnQGMZ48aNU3BwsMsXREZGhp599lmDk3mWgQMHavXq1ZoyZYopW6rL2rJli7p06WKq1oyyli9froULF6pnz55yOBz69NNPNXr0aI0YMcLoaC5SU1OVnJys7du3Oy8CzNa3UTq5GtrPP/+sXr16ydfX17nfbH2uV69erX/+858qLCzUpk2btH//fiUmJppqPlnpZKvQ888/rx07dsjhcKhr16567LHHTDfodvny5Vq0aJHzS3fz5s165JFHTPc+evrpp/XJJ5/o1ltvlXSyNa5nz56mmD/6vffe0y233KLly5dXeNxs7yGbzWa6i1FP5Gnjf4x83Wm5LmPmzJl64YUXlJSU5PyCMNPtjhKVDc4xS7eQ3Nxcfffdd/r++++1b9++cosfmO1NWNKv/vjx4y6Ty5tphotXX31Vb7/9tpo2bSrpZIvb8OHDTVcUTJ06VV26dHEufb1q1SpNnTrVdMVgQUGBzjnnHO3du9foKFV69dVXtWrVKmfB0q5dOx07dszgVOUFBQWZsgtdWXfddZeuuOIK7dy5Uw6HQ3fddZcuvPBCo2OVM3HiRF166aXOi5UJEya4tMIZ6b///a9uueUWfffdd0ZHqdIrr7yie++9V//85z8rPG6WiQpKGqEqG8xqlkGsnjL+xwyvO8V1GWbrO1SZ0t1C8vPztX79elPNcHH33Xdr6tSpOnjwYLm+jGZ6E5bYunWrIiIidPz4cXl5eTlvu5vlYkWSmjdv7iysJalJkyYuM3OYRXp6uku/UDMtflDarFmzjI5QIyX9W0sz4wDM3NxczZ8/X1988YUsFouuueYajR492jSzmpT2t7/9TVarVRaLReedd57RcSp1ww03OFe7LN232Wjjxo2TZP73UMngeTP97ipy7733SpLpaw9PGf9jhtfdPNWYwTztNlfJ4JwS48eP1z333KPHHnvMoESuBgwYoBEjRmjixIl6+umnjY5TrZSUFL388suaOHGi1qxZo5UrV+qPP/4wOpYkOW/BXX755S59WtesWWPKmWzOPfdc/frrr86+9QcPHjTl6qGStH//fu3Zs8dl2fsBAwYYF6gCoaGhOnDggLNFa+3atabsL56UlCS73a6oqChJJ1vbEhMTTVeA7d69W+PGjZOvr68cDoeKior03HPP6e9//7vR0VwcPHhQkydPdg5o7dixo1JSUtSmTRuDk7ky83SWd955pySZYhBoVS6++GJJfw1m9QS5ubn6888/XVY3NcsdaTO87hTX/+Mpt7kqc+jQIVMNvBw5cqRWr15tqtb06rRt21ZFRUWyWCwaOnSoab4gyt6CK92abrFYNGbMmPqOVKGSKfiysrLUv39/5+whX331lf7xj38YnK68V199VW+++aaOHj2qSy65RF9++aX+8Y9/mK64joyM1KRJk3TgwAHdcMMN8vPz08KFC42OVc7u3bu1fv165/bll1+u22+/3cBEFZsxY4ZmzpzpHNi0bds2JSUl6Y033jA4mau4uDgNHTpUgwYNknSy731sbKyWLl1qcLK/TJs2Td9//73pp7PMz8/XunXrdOjQIZeLALN0Cymxf/9+LViwoFxOs3QLKbF8+XI9+eSTCgkJkZeXlyRz3pE28nX3nMqnjnnKba4SpftcFxcXq6ioyNliZAae1ue65CKgRYsW+vjjj3X22Wfrzz//NDjVSSW34E6cOFHhSlNmUXoKvtLTR/Xt29eIONVasWKFVq5cqeHDh+vFF1/U3r17nbc9zaRdu3ZauXKlfvnlFzkcDrVt29a0hUzJLEGSTDnvrXQyV+kZA7p27WrKrGlpac67VNLJxWVeffVVAxOV980333jEdJbjx49XYWGhOnXq5DJ42WyeeOIJ9enTRwMHDjTte1ySXnrpJW3YsKHcHXSzMfJ1p7gu491331WPHj0UFBSkZ555Rrt27dITTzxhuluGpftce3t7q1mzZqZ6M3pan+t77rlHGRkZGj9+vCZNmqTMzExTXaw4HA6NHDlS69atMzpKpe644w7Z7Xa98MILzotVM/P19VVAQICKi4vlcDh0wQUX6ODBg0bHKmf8+PF65pln1L59+3L7zKRfv34aNmyYbrvtNlksFr3zzjvq37+/0bHK8ff317Zt25x9mXfs2GHKfuFeXl7av3+/czrDAwcOmOozXvKc6Sx//fVXvffee0bHqFZxcbFGjx5tdIxqNW/e3PSFtWTs605xXcaCBQt06623ateuXdqyZYvuueceU94yfPnll52zMZQoWdbTDEaMGOExfa6Li4sVHByskJAQderUSR9++KHRkcqxWCxq06aNMjIyTDXvaVlWq9WUK59VxN/fX4WFhbrooouUkpKiVq1alVshzQwqKvj3799vQJKqPfzww7rwwgu1bds2ORwOTZ48WT169DA6VjlRUVEaP368syWrsLDQlFOtTpw4UXfddZc6dOgg6eRiQqVXQzSD8847T/fdd5/pp7Ns06aNsrKyTDctZFmdO3fWnj17dNFFFxkdpUpXX3215s6dq9tuu81lxWWz3ZE28nWnuC6jpHvA559/riFDhqhfv3566aWXDE5Vnqcs52r2wlo62UK0YMECXXfddUZHqVJAQIDuuOMO9ejRw2UUtNn6Dfbs2VMvvviiBgwY4JLTbK2DcXFxKiwsVEREhJ566in99ttvpipeVqxYoTfffFO//PKLS/eAzMxMtW3b1sBklbvuuuuc/evNOkNDp06d9MEHH+jAgQNyOBxq166dKbs19OjRQ++8846+/fZbORwOde7c2bnwjVl4ynSWwcHBGjRokK699lqXiwCzfXbu2rVLq1evVtu2bV2KVrP1uX777bclSRs3bnTuM+MdaSNfd4rrMiwWi9atW6d33nlHCxYskHSyZcMszLCs56kw+3zcJS6++GLt2rVLnTp1MjpKpc4991xTrm5ZVsmiQSkpKbJYLHI4HLJYLPrxxx8NTuaqZGW5gIAAzZgxw+A05V1zzTU699xzlZSU5PJlEBQUZMp5mT1ldgvp5O3iksYIb29vly43ZmKxWGSxWOTl5VXh56jRPGWMUtu2bU17QVqamboiVsXsU/GVMPJ1Z4XGMr766istWbJEV111le6991798ssveu211zR9+nSjo0k6eWvwhx9+0HPPPefSr7VkWU+z3fYqPYNJ6fm4zTJlYIkBAwbov//9r84991yXFjeztRig9qprnTZTa5bdbldcXJySk5ONjlKt+++/X7fddpvL7BYbNmww1ewW0slWtyeffNK5IMunn36qyZMnm25mk88++0xTpkxRx44d5XA49NNPPyklJUXXXHON0dFceMJ0lqgbZl50zWgU12UcOXJELVq0MDpGtTx5Odd77rnHdKPed+zYUeF+M807WllRaKZiUKp8lgizdAt5/vnnqzxutjlxzfh+qUj//v21du3aavcZ7fbbb9eLL76o5s2bS5KOHj2qBx980HSDhQcOHKiUlBRnq/q+ffs0ZcoUrV692uBkf6lsOsslS5YYHa2cLVu26Mcff3QpBs32Xs/MzNTixYvL5TTb+98TFl0rYdTrTreQMgYNGqTLLrtMd911l3M0uZl4UqtbRcw2H3eJkiI6OztbksqtiGcGpVvU8/Pz9cknnzgXHzCTyy67zKU7SAmzdAsx2xdqdbp27arExMRyfdjNNnjIE2a3KFFSWJf9t5kUFRW5dFdp3769y1y9ZuAp01k++eST2r17t37++WfdeOON2rRpk8t0jGYRFRWl9u3b65dfftH48eO1atUq081UJpl70bXSjHzdKa7L+Pjjj/Xuu+/q6aefVmZmpu666y7179/fNN0tzDpIqDIVzcdtlhlNStu3b5+mTp2qvXv3ymKx6IILLtCcOXNM1RezbFH4yCOPaMqUKQalqVxJn1vpr65A6enpBibybCVdkz755BPnPjMOHvKE2S0k6ZxzztGzzz6rYcOGyWKxaMWKFabsF96kSROtXr1aAwcOlHRyRVazDWj0lOksN2/erDVr1mjgwIFKTEzUY489poSEBKNjlfPrr7/queee06ZNm9S3b1/ddNNN5RYRMwuzLrpWmpGvO8V1Gb6+vhowYIAGDBigr776Sk888YTmzZunO+64Q48++qiaNm1qaD5Pa3Uz+3zcJSIjI3X33Xc75+Vdt26dIiMjtWLFCoOTVS4wMNCUX2SlNWrUSIMHD9bIkSPLzXeOmvGUwUM9evTQhg0btGvXLtPObiFJCQkJSk5Odvaxvuaaa5SYmGhwqvISExM1efJkxcXFyWKxqEOHDs7BwmbhKdNZ+vr6ytvbWxaLRYWFhWrRooVpFgkrrWRGCx8fH9lsNoWEhJgyp5kXXSvNyNed4roCv//+u9544w1t2LBB3bp105AhQ7Rt2zY9+OCDzilojOYp/W/PPvtspaWl6dtvv5XFYtGll16qsLAwo2OVU1RU5DIIp3///nrllVeMC1SB0q+5w+HQd999Z8oR8KX7XBcXF2v37t1KTU01MFHD4AmDh5o2baprrrlGdrtd0sm/BbP0tS/RtGlTj5gi9JxzztGKFSuUnZ0th8NhmrunpZl9OssSgYGBys3N1WWXXaaIiAg1b97clI085513nmw2m3NBpuDgYOedIDMx+6JrJYx83RnQWMbo0aO1d+9e3XnnnRoyZIhLIdi3b19t2LDBwHR/KT0oq3T/W7NNjfTBBx9o+vTpuvjii1VcXKw9e/YoKSlJvXr1Mjqai8jISA0aNEhdunSRJP3nP//RO++8o9jYWIOT/aX0a261WnXOOefopptuMt0cvRdddJGzz3VJzoiICNPNI75x40b16dPHZd/8+fP16KOPGpSoYp4yeOiDDz5QcnKyjh49KkmmnYJROvk7PXjwoEsfZjPe1j548KAOHjzovFiRZLr3kSc4duyYGjduLLvdrqVLlyozM1N33323KS9QS3z55ZfKzMxUjx49THkh4AmMfN0prst49913dfPNN3vcH3NWVpamTJninJvbLG655RbNnz/f2cL6yy+/aMyYMaZbirZ///7au3evzjnnHEknv9Q6dOggLy8vSUzJ1xANGjRIUVFRuuKKKyRJS5cu1b///W/TjcwfOHCg5s2bV27w0IQJE4yO5qJ3796aM2eOOnfu7HzfmFFERIS+++47dezY0eVz3mwNE/PmzdPKlSvVvn175+/TYrGY6u8zNTVVycnJ2r59uywWi6666ipFR0crPDzc6GgVMvOA9RKl7/R26tTJlF2rioqK9Oabb2r79u2STo6tGjp0qLO7iNkY8bqb8zdhEIfDoYULF+rWW281OsopM2v/25CQEJeuC+edd54ppxA04yDLsjzpi2zv3r3asWOHM6fZZraQTt4JePjhh/XMM89o+/btev/99025GqvkGYOHQkJCdPnllxsdo1pff/21NmzYYLo7PmVt3LhRH330kSm7g5SYOnWqunTp4vz8XLVqlaZOnaqXX37Z2GBleMKAdclz7vQmJibq999/14ABA+RwOLRu3Trt2bPHdGMXjHzdKa5LsVgsatOmjTIyMhQSEmJ0nCqZvf9tSb/b7t27a8GCBRo8eLAcDodWr16t3r17G5yuvNLzWRcUFCgjI8N0U3R5yhfZ8uXLtXDhQvXs2VMOh0OLFi3S6NGjNWLECKOjuWjVqpVSUlI0evRohYSEaOnSpaacjcfsg4dK3uu9e/fW66+/rltvvdVl6Waz9blu2bKl0RFqpHnz5qYurCUpPT3dZZD9o48+qvfff9/ARBXzlAHrTz/9tN54441yd3rNVlzv3LlT77zzjvOOyq233qp+/foZnKo8I193iusyAgICdMcdd6hHjx4uX7RmGyhYOpvVatWdd96pm266ycBErkrPdSxJzzzzjPOYxWLRAw88YFS0Ck2cOFGJiYny8fFR//79lZ6erkceeUQPPvig0dGcPOWL7NVXX9Xbb7/tnFknLS1Nw4cPN01xPW7cOJf5ty0WiwICApwXLaX/Vs2gosFDkZGRRsdyKvteT0xMNOWy98uXL5d08u7Zfffdp169ejlnZ5DM0+d68+bNkqTOnTvriSeeUJ8+fVwuVszU5/rcc8/Vr7/+qnPPPVfSye50559/vsGpyvOEAeuS59zpbdmypQoKCuTn5yfp5O+3VatWBqcqz8jXneK6jHPPPdf5QWFmZp+Sr/Rcx57gwIEDCg4O1saNG3XVVVcpMjJSQ4cONVVx7SlfZM2bN3eZsrJJkyZq1qyZgYlcXX/99S7bJctgm1Xfvn0lSZ06ddKHH35ocJry9uzZo+LiYu3du1cXXXSR0XEq9d133zn/fc4552jv3r0Gpqlc2dUNX3vtNee/LRaLKYrrkgvUrKws9e/f3zlu4auvvtI//vEPg9OVd+GFF+rLL790GbDeuXNnY0OV4il3eksuUFu3bq1hw4Y5u9Bu3LjR+bs1EyNfd4rrMm655ZZy/XH27dtnUJrKjR07VklJSc6r2vT0dMXHx5uu1c1TlMwasHPnTl133XXy9/c3zaAsT/ki+/nnnyVJl19+uaKjozV48GBJJxe/6N69u5HRXNxxxx2y2+164YUXNG7cOKPjVKvkC60ss7S0SidXZ4yOjnaZ195sZs2a5RGv+2uvvSa73a633npLw4YNMzpOhUpfoJbuDlByIWgWgwYNcs5xvGbNGmfDxK+//qqOHTsanO4vnnKnt/QFaseOHfXLL79IOjlDVFZWlkGpyjPD605xXcbkyZO1Zs2aavcZ7dChQy63i8LCwkw5oNFTtG/fXg888ID279+vSZMmmWohBE/5Iiu7kljpqeIsFovGjBlT35EqZbVatXPnTqNj1EjpL7T8/Hxt375dl156qamKa+nke+i3335T69atjY5SKU953a1Wq9atW2fa4tpTLlCnTZtmdIQa8ZQ7vbNmzVJxcbE+++wzU9xBqYwZXneK6/9JS0tTWlqa8vPztW/fPucVZGZmpnJycgxOV57dbpfdbndOJVVYWKiCggKDU3muOXPmaMuWLbrwwgsVEBCgI0eOaNKkSUbHknTyi8wTeMpKgiV69uypF198UQMGDHAZw2C2AXhlp4hLTU3VzJkzDUpTubS0NN1+++264oorXH6fZrub5imve7du3Sqci90sPOFC5corr5TdbldcXJySk5ONjlMlu92uoUOHmvruj3TyLtWCBQtMXVyb4XWnuP6f9evX65VXXlFqaqrLMs3BwcF66KGHDExWse7du2vixIm65557JJ0cRHbttdcanMpz+fn5uYzIbtGihVq0aGFgovLKDsQrYbbipaR7SFlmm46vZCnplJQUUw7Aq0x4eLjzdqyZ3HbbbbrtttuMjlEtT3ndly1bJpvNJj8/P/n7+ztzmmnxIE+4ULFarR5xV9dqtSosLEz5+fkuA1jN6OKLL9auXbvUqVMno6NUyujXnUVkyli4cKFGjx5tdIxqFRYWatGiRfrkk0/kcDh0/fXX6+GHH3YZ/W4G+fn5WrdunQ4dOuSyGprZZl/xBKW7JuXn5+v9999X+/btFRMTY2Cq8m644QbnvwsKCnTs2DGdddZZHteybRal+1w7HA7t3r1bhw8fNtViInC/33//vcL9Z599dj0nqVzpAaxmvlCZP3++jh07Vu4iwGwX/MnJyfrmm2908803u+Q0WxewAQMG6L///a/OPfdcl5xmW2zNyNed4roCubm5+vPPP12WnDXbm9BTjB49WoWFherUqZPLamhmn+3EExQUFGjMmDF68cUXjY5Spa1bt+rTTz81RT84T1R62r2S5eSHDh1quim6POXOSsnMDGWZqbUV7lX6gr+ExWLRpk2bDEhTucqm2DTb6qE7duyocH/p9SLMwMjXneK6jOXLl+vJJ59USEiIy5KzZnkTvvfee7rllls8YgYB6eTsK2Zb6ryhKCwsVN++fU0513VZd955p9544w2jY7jYs2eP4uLitGfPHpfxCmZrdfMUnnJn5aKLLnJpZS1htte9a9euFV6smKlbCBcqQMXoc13GSy+9pA0bNpjq1ltp//3vf3XLLbe4zCBgZm3atFFWVpbpVxrzhO4rpVsGHQ6HfvrpJ3Xr1s3gVOWV7nNdXFys3bt3KzMz08BEFYuPj9eECRM0a9YsLVmyRMuXL1dgYKDRscopvRprRczyN1p24O3AgQNNNUNMidIzM+Tn52v9+vVKT083MFHFSg9sK8lZslqnWZSeQs7MFyqeMg7EUxrNSqa6K8ts3UKMfN3N9U41gebNm5u2sJZOFljFxcXq06ePqUfrlggODtagQYN07bXXuvQHN0tBUGL8+PHO7itm67deovSUfFarVQ888ICpFkIoUXpKPm9vb51zzjmaPXu2gYkqVlBQoG7dusnhcCg8PFwTJ07U3XffXW5KQaMdO3ZMO3fudC4m8dFHH6l79+4KDw83OFnVLBaLfvvtN6NjVKlRo0YaPHiwRo4c6TKQ3QzKfg+NHz9e99xzjx577DGDEpXnKRcqpd/TZh4H4inTbpbu4pefn6933nnHlJ9HRr7uFNdlXH311Zo7d65uu+02lxG7ZrrC9YSpcEq0bdvWZTlXs/r1119N332ldMtgQUGBMjIyDExTObN9YVWmpNtXSEiI9uzZoxYtWlQ6iMxI6enpWr16tcLCwiRJY8aMUUREhBITEw1O5spT7qyU7spQcmclNTXVwEQ1c+jQIVP+fZYw84VK2c+kknEgZuMp026W7VvdvXt30yx0U5qRrzvFdRlvv/22pJPLeZYwU5/rEp4wFY7kOQMXPaH7ysSJE5WYmCgfHx/1799f6enpeuSRR0y1RLt0cpXLjh07KjAwUCtXrtTu3bs1atQotWnTxuhoLm677Talp6fr4Ycf1vDhw1VcXGzKBTEOHz7sLKylkwtGmbHI8pQ7K6W7MpQMEI2OjjY6Vjml+1wXFxerqKjIdDk99UKlW7duphtoWxGzTrtZVlZWlg4dOmR0jGrV5+tOcV2Gp7S6ffnll/rXv/5l+qlwJGnLli368ccflZ+f79xntqLbE7qvHDhwQMHBwdq4caOuuuoqRUZGaujQoaYrrhMTE7Vu3Tr997//1dKlS3X77bcrOjraVFPH/fTTTzrrrLOUkZGhHj16aMeOHcrPzzflxVW7du1clpNfvXq12rVrZ3Cq8krurJQsulX6c8lMPGU1vNJ9rr29vdWsWTOXGZfMwFMuVDxlHEhF0242btzYwEQVK93nuri4WL/99pvuv/9+g1OVZ+TrTnFdhqcMfIiKijI6Qo08+eST2r17t37++WfdeOON2rRpkylvFXtC95WSgZY7d+7UddddJ39/f2fXBjPx9vaWxWLRp59+quHDh+vuu+92uRNktFdffVXPPvus2rZtqwMHDigxMVG33nqrfHx8jI5WoZkzZ+qFF15QUlKSHA6HunbtasppDQ8dOqRJkyY5i9eOHTsqJSXFdHcspJOf89u3b5d0soW4ffv2Bicq7+yzz1Z6erq+/fZbWSwWXXrppaabftFTLlQ8ZRxI6T7XVqtV7du3r3R6PiOV/vyxWq1q3bq16RZdk4x93ZmKrwwWwHCvfv36ac2aNRo4cKDWrVunI0eOKCEhQfPnzzc6mscZP368MjMztX//fr377rvy8vLSsGHDtHbtWqOjuejXr5/i4+M1Z84czZgxQ+eff7769eun9evXGx1NknTrrbfqpZdeUsuWLfXzzz8rJibGdNMEeqL7779ft912mwYNGiTpZAv7hg0btHTpUoOTuXr77bf15JNPqmfPnpKkTz/9VJMnT9btt99ubLAyPvvsM02ZMkUdO3Z09mFPSUnRNddcY3Q0ANWg5boMTxn4UNFUOMHBwercubMeeugh00wp5uvr62zJLCwsVIsWLfTnn38aHauc48ePa9asWTp8+LCWL1+uPXv26Ouvv9bw4cONjuY0Z84cbdmyRRdeeKECAgJ05MgRTZo0yehY5YwfP16JiYnq1q2bzj//fB04cEDnnnuu0bGcfH191bJlS0kn70iV7q6E05eWlubsuiKd/IwyU1egEi+99JLWrFmj5s2bS5KOHj2qBx980HTF9dNPP63ly5c7W9X37dunKVOmUFwDHoDiuhpmHfjQrVs3/frrrxowYIAkae3atTr33HN15MgRxcfHKyUlxdiA/xMYGKjc3FxddtllioiIUPPmzU3Xb1CSYmJi1KNHD73++uuSTvZznTJliqmKaz8/P/Xq1cu53aJFC1PeiuvVq5dLzrZt2+r55583MJGrrKwsbd68udJtT5iFx4y8vLy0f/9+Z3/wAwcOmPK9LslZWJf9t5kUFRW5dFdp3769yxz8AMyL4roMTxn4sHPnTr355pvO7euvv1733XefXnnlFd16660GJnP11FNPyWq1atq0aVq6dKkyMzNNebFy5MgRDR8+3Pk79fX1NWV/ZtReq1attGTJEud2y5YtndsWi4Xi+jRNnDhRd911lzp06CDpZH/c6hbAMcI555yjZ599VsOGDZPFYtGKFStM2S+8SZMmWr16tQYOHCjp5AqYTZo0MTgVgJqguC7DUwY+pKenKz8/3zkXd0FBgY4cOSKLxSI/Pz+D0/2lWbNmkqTs7Gzde++9pumuUlbZlc9OnDghhiM0TK+99prRERqkHj166J133tG3334rh8Ohzp07m7IYTEhIUHJysrMbyDXXXGO6OcOlk7PuTJ48WXFxcbJYLOrQoYOefPJJo2NJ8pxVQz1VQUGB7Ha7c9ssy8lXtoJkCbMtdmMkiusyPGXg4i233KJhw4bplltukcVi0caNG3XzzTcrOzvbVCtM7tu3T1OnTtXevXtlsVh0wQUXaM6cOaYbnX/TTTcpNjZW2dnZWr16tV5//XXnwCw0LL1791bXrl1144036uqrrzbtipyl5zkurWSp6a1btxqQqmbMfNenadOmevrpp42OUa1zzjlHK1asUHZ2thwOh6mmiTTrNItllV7YqCJmu4v64YcfKikpSUePHpX013vdLMvJl8xmkp6erh07djhn/tq6dau6d+9umuK6suXZS9THlMXMFlKBzz77TF988YUsFouuueYa0w4g+fjjj7Vjxw45HA5dddVVLjOdmMXQoUM1YsQI9e/fX5K0bt06LV++XCtWrDA4WXnr1q3Txx9/LIfDoRtuuMGZ2Wie2Ep04MAB7du3T7169VJ2drYKCwtNM41YQUGBvvjiC23atElbt25Vhw4ddOONN6pnz56mySip2oVizHQRLUkffPCBpk+frosvvljFxcXas2ePkpKSXPrfm0FRUZHefPNNl6n4hg4dWu7ulRls3rxZ27Ztk3QyJ12WTs2aNWuqPF561Vsz6N27t+bMmaPOnTub+gL1scceU0REhLM71aFDh/TUU0+Z5qJ1x44dkqRPPvlE+/fvd1kjoGPHjvWyzgbFdRmLFy/W2rVrddttt0mS3n33XQ0YMMB0C3V4ioEDB2r16tXV7kPlSgYDHjx4UDt37lTv3r0lSR999JG6d+9uulvaa9as0aJFi1RYWKhNmzZp//79SkxM1Msvv2x0tHIcDoe++eYbffTRR/rkk0/UpEkT3XjjjbrvvvuMjuZxbrnlFs2fP985X/wvv/yiMWPG6L333jM4mavY2Fj9/vvvGjBggBwOh9atW6ezzjrLdO+jp59+Wh9//LFuu+02ORwObdy4Uddff70mTJhgdDQXnrBImKcYPHiwKReCK2vAgAHO1ayr2me0u+++W6+++qqzFdtut+u+++6rl66B5rtUN9i6dev0xhtvOG/B3X333Ro+fLjpiuvMzEwtXry43Iea2aa+uvDCC/Xll1+qS5cukqT//Oc/plwSOTU1VcnJydq+fbssFouuuuoqRUdHKzw83Ohozi+qUaNGafXq1c6lsMeMGaOIiAgjo1XolVde0apVq5y3CNu1a6djx44ZnKpiFotFl112mS677DJNmTJF+/bt06ZNm4yO5eLw4cNKSUnRnj17XN7rZssZEhLishDTeeedZ6o7ASV27typd955x9kyeOutt6pfv34Gpypv48aNWrNmjbMLxr333qs77rjDVMW1pywSVlRUpFWrVpX7vpw1a5aBqcrr3bu3Xn/9dd16663O8VSSefpclwgNDdULL7ygIUOGSDq5mqgZ3+tHjhxRfn6+cxxaQUGBUlNT6+W5zXvfwUCl+7aZqZ9baVFRUfLy8tIvv/yioUOHymq1qlOnTkbHcho0aJAGDx6sH374QSNHjtTNN9+sm2++WXfddZe++eYbo+OVM3XqVF1wwQVat26d1q5dqwsvvNB03S0OHz7sLKwlKSwsrNquA0bw8fEpN3DVjFOy5ebm6umnn3bOFb5v3z4dOHDAZVCzGURFRalbt25yOBx68skndcUVV5jqdnZubq5yc3PVvXt3LViwQEePHlVqaqoWLlzovMtiJi1btlRBQYFzu6ioSK1atTIwUcXCw8NdiqpGjRqZ4mK/tM2bN+vFF19U06ZNlZiYqNWrVysnJ8foWOXExsbqq6++0ieffKLzzjtP3333nakG/pd4+umnlZiYqK5du+ryyy/XZZddpssvv9zoWOXMmTNHP/30k/r166d+/fppz549mjNnjtGxyikZm7Zo0SItWrRIw4cP1y233FIvz03LdRkXX3yxIiMjNWTIEFksFq1cuVIXX3yx0bHK+fXXX/Xcc89p06ZN6tu3r2666SZTFQVmXJ65Kunp6S63Mh999FG9//77BiYqr127doqOjnbpP1Yyp7CZhIaG6sCBA85bcWvXrnUu2mIm8fHxat68uXMJ55YtW2rSpEmm6yOcnp6uIUOG6NVXX9Vll12mSy+91FTdVi677DJZLBbn7DqlB4lZLBY98MADRkVzUTLTQevWrTVs2DDnlKUbN2503lkzg5I51zt06KCHHnrIeSG1du1a0xVanrJI2O7du7V+/Xr169dPjzzyiEaMGGGqOwAlPGU5+RYtWujZZ581Oka1Jk6cqEsvvdQ5Nm3ChAnOlVnrGsV1GdOnT9f8+fOVnJwsSbr66qv16KOPGpyqvJIZDnx8fGSz2RQSEmKqD7Urr7xSdrtdcXFxzt+lmZ177rn69ddfnSsJHjx4UOeff77BqVzNnDlTzz//vJKSkuRwONS1a1dTXsRERUVp0qRJOnDggG644Qb5+flp4cKFRscqZ+/evc5VL6WTCx4VFxcbnKo8Hx8fSSdnaPjjjz/UrFkz/fHHHwan+ounFAQlMx1IUseOHfXLL79Iki666CJlZWUZlKq80nOwS3JZz+Drr7+u7zhV8pRFwkq6WFitVuXm5io4OLjeugc0RLm5uVq0aJEOHTqkefPmOe/6ma1hQpJuuOEGQ6YFpbguIyAgQJMnTzY6RrXOO+882Ww29evXT8OGDVNwcLBz8QazsFqtOnjwoNExaiQrK0v9+/fXFVdcIUn66quv9I9//EPjx4+XZI4pm4KCgkzZx7qstm3bauXKlfrll1/kcDjUtm1bU37hlhStJfLz8005t3mXLl1ks9k0fPhwDRw4UL6+vurTp4/RsSpl1jl6zda/tjKeNA+7pywSFhISooyMDF177bUaNWqUwsLCnGswmMmePXsUFxenPXv2uHRdMstUfCU85a7ft99+qwkTJqi4uFibN2/W7t27tWLFCiUlJdX5czNbSBnJycl6/PHHnZ3z09PTNX/+fEVHRxsbrApffvmlMjMz1aNHD9MVMfPnz9exY8c0YMAAl7lR//a3vxmYqjxPmLLp+PHjmjVrlg4fPqzly5drz549+vrrr02zRHtubm6Vx81SZJWYO3euGjdurHXr1ikuLk5Lly7VhRdeqIkTJxodrVJ//PGHsrKydMEFFxgdpZwPPvhAycnJSk1NdXYTMdMcvaVt3bpVBw8edFlO3Cxz9JZ28OBBHTx40OVihen4Tp3dbpfValVxcbHWrVunrKwsDRgwwHRjqu68806NHz9es2bN0pIlS7R8+XIFBgaaqsundPL7cM2aNS4zhNx+++1at26dscHKuPPOO5WcnKzJkyc7c952221655136vy5abku48svv3QZ9RoWFqadO3caF6gGzNRfsKySaYU++eQT5z6LxWK6mQ7MUDxXJyYmRj169NDrr78u6WQf7ClTppimuC7b97Y0MxZZEydO1JIlSxQYGKiUlBTdcMMNpvoSKygokK+vr8tFS1hYmMLCwpSbm2u6i5WUlBT93//9n+nn6J02bZq+//57dezY0XSNEaXNmzdPK1euVPv27Z2/T4vFYqrievjw4Vq4cKFCQkIkSTabTY899li1K/nVt5LX2cvLSwMGDDA2TBUKCgqcg5fDw8M1ceJE3X333ab6XJI8565fYWFhuYa8stnrCsV1GaVbCEqUbt3AqfGEFS+//PJLPf/88/rpp58knZw+8PHHHzfdRcuRI0c0fPhwZx9MX19fUxUxntL3toSPj4/GjBmjMWPGGB2lQsOGDdOaNWtcLlrM3CIcEhJiugF3Ffnmm2+0YcOGevuSPV0bN27URx99ZLrW1dJycnKchbV0cjCzmfqvl/jqq6+UkpKiQ4cOuXzHm22V05KLgJCQEO3Zs0ctWrQw5YxQXbp00cKFC1VQUKDt27dr6dKlplzEztfXV9nZ2c7B9T///LPLFId1ieK6jEsuuUTJyckaNWqUHA6HlixZoksuucToWB6n7IAri8WiJk2a1Nsfdk199NFHSkpK0ujRo52DA7/++mtNmjRJ06dPN1UfsrIryJ04ccKUrQWSlJaWpm+//VYWi0WXXnqpyxSCZrF06VINHjxYwcHBmjp1qnbt2qWYmBh1797d6GiS/uqqZPaLlpKWdU+Zo9eMM9dUpHnz5qYurCWpuLhYOTk5zi5/2dnZFTZQGS06OlqPPvqo6e+q3HrrrUpPT9fDDz+s4cOHq7i4WGPHjjU6VjkV3fV75JFHjI5VzujRo/Xggw8qNTVVERER+uyzz5SSklIvz02f6zKysrI0Y8YMffLJJ7JYLOrZs6ciIyMVHBxsdDSP0rVr13JdBLKystS5c2fNnTtXZ511loHp/jJw4EDNmTOn3Mwge/fu1bRp06rti12flixZooMHD2rr1q0aM2aMXn/9dfXr10/33nuv0dFclCyD/fe//10Oh8O0y2D369dP69ev17Zt27R48WI99thjSk5ONt3qoTNmzCg35qOifUa56KKLyr3XzdjCXtJVYe/evfr555/Vq1cv56xLknn6XJdMxbd9+3b9+eef6tOnj8vFipm6hSxatEj//ve/nV3T/vWvf5mue5X0Vx9hT1JYWKj8/HxTXmDt27dP7du3r3afGRw6dEifffaZHA6Hunfv7pwRrK7Rcl1GUFCQR4wqN/vgtm3btpXbZ7fb9cYbbygpKUkLFiwwIFV5eXl5FU65d8EFF7is5GUGDz30kNatW6cTJ05o8+bNuvvuu9W/f3+jY5Xz9NNP64033ii3DLbZiuuSW7Dbt29Xv379dPnll5vyTsCXX35Zbp+ZxoGYvWW9ROmp+M455xzt3bvXwDSVKzsVX+nZQ8zW5/qRRx5ReHi4Pv74YzkcDt15552m7NPco0cPbd682VS/u4oMHz5c//rXvySd7Lbm4+Pjss8sJk+eXO5ipaJ9Rlu8eLFGjRqlESNGlNtX1yiuPZTZB7dVxGq16q677nIOcjSDwsJCFRYWlut/WVBQ4DIVkhls3bpVt99+u26//XaXfWZbbthTlsH28/PTggULtH79ev3rX/+Sw+FQYWGh0bGc3nvvPb333nv6/fffnVNCSifvAJlxdbmKZosxU5cQT2g0kTxrKj7pZKuw2QeEv/nmm1q0aJECAwPl6+vrvKtitj7XeXl5Ltt2u10ZGRkGpSkvLS1NaWlpys/P1759+5yNEZmZmaZcmfPdd98tV0hXtK8uUFx7KLMPbquKmfrk3XjjjZo2bZoSEhKcXX9OnDih+Ph43XjjjQanczV37txyLQMpKSmm6cZQUlyVLIM9ePBgORwOrV692pTLYM+aNUuvv/66pk6dqubNm+vgwYPq16+f0bGc2rZtq549e2r37t0uq4oFBQWZ7oJK+mu2mNK8vb3VqVMnJSUlmWY10YpmsggODlanTp103nnn1X+gSpR0DyktKChIF1xwgWm6KaalpSkpKUlbt26VxWLR1Vdfrejo6HpfsKM6q1atMjpClZYsWaIlS5YoKyvL5b2dl5dnqs+k9evX65VXXlFqaqpLgRocHKyHHnrIwGSuPv/8c23ZskWpqamaO3euc399Dralz7WHGjp0qFasWOGcZ/LEiRMaOXKkaeaZrKgVy2az6Y033tBvv/2mefPmGZCqvIKCAsXHx2vjxo3Ovli//vqr+vTpo/j4eJc+mUb59ddf9csvvyg5OVkxMTHO/ZmZmXrhhRf03nvvGZjuLxX1vS1hpr63nsZms5my5b+sRYsWqVGjRi4XVfn5+WrWrJnWrFljmhbZ0aNHa+fOnc4iZtu2bbriiiv0008/6fHHH9fgwYMNTnjSsGHDtHv3bl144YWSTvYVv+iii/Tnn38qOTlZ119/vcEJpbFjx+pvf/ub7rzzTjkcDq1YsUJ79+7V888/b3S0coqKinTgwAFZLBadd9555QaIGykzM1MZGRlKSkpSbGysc39QUJDLbCxmsXDhQo0ePdroGJXasWOHduzYoTfeeEN33nmnc39QUJB69eql1q1b13kGimsPZfbBbWULrZLZQq6++mpFRkaarmXjjz/+0N69e+VwOHTBBRfo7LPPNjqS05o1a7R69Wp99913uvjii537g4KCNGzYMJdWTdTcoEGDyrW0SjJVtyXp5PiK1157TYcOHXKZFtRsK+ENHDiw3F2UESNGOD+b1q9fb1AyV2PGjNH06dOdg6oPHz6slJQURUZG6v7779eGDRsMTnjSlClTdO+99zrf899//73efPNN3XvvvXriiSe0du1agxNK/fv3L5ejon1G2717t8aNG+fsElJUVKTnnntOf//7342O5tGOHz/uMjbJLBMVlNi7d69hC26Z59LNYCWzW1TGbH2zzD64zVMGOZU466yzTPfBUKKkT+Pq1as1cOBAo+M0GCVTL0onF0F45513FB4ebmCiio0dO1bt27dXt27dTL3oSW5urg4dOqQ2bdpIOjlKPz09XZJMlfu3335zea+3atVK+/fvV/PmzU2Vc8+ePS4X03//+9/1/fffq3379qYZeFtcXKzjx4+radOmkk4WW8XFxQanKm/GjBmaOXOmy92KpKQkvfHGGwYnO2nKlClKSUnxmAv+bdu2adq0aTp+/Li8vLxUWFio0NBQ09VJF1xwgbZs2aIff/zR5SLg8ccfr/Pnprj+n5I+WW+99ZZsNpuGDRsmh8OhVatWqUWLFganq1jZwW1o2Ly8vJSRkeGyGtqnn35qmr+Be++9V6+88kq5C1WzDh668sorXba7d++uBx54wKA0lTtx4oSSkpKMjlGtCRMmaPDgwS4trQkJCcrOzlafPn0MTveXpk2bauHChRo4cKAsFotWr16tkJAQ2e32KhtY6pu/v782bNigvn37SpI2bNjgLP7NkvPBBx/UgAED1LNnT1ksFm3evFlPPPGE0bHKyc3NdenL3LVr1wq7Lhql5I5z6Qt+M5s7d65efvllTZw4UWvWrNHKlSvLrW1hBk8++aR2796tn3/+WTfeeKM2bdpUb+NV6BZSxsiRI7Vs2bJq9xll3LhxVX6wmu1WMdzn9ttvL9envqTPvRmkpqYqPDy80hXFzNTVpiKZmZm644479NFHHxkdxcXEiRMVERFh2ov80o4fP65vv/1WDodDnTt3drZomsmRI0c0Y8YMbd++XZJ01VVXKSoqSmFhYfrll1+cfZyNtm/fPk2ZMkX/396dBkRZvW0AvwYEUVzIIil3USsTBERxIUrCDWR1AdywEtJ/lhoqiAumBCJopaXghku4s4pWLhRpIYua4MKLbAKmoOICSMzAzPuB5olx0FRgzhm6f1+CZ6jnygLuOc997pOTkwORSARDQ0MEBweja9euOH/+PEaMGME6IgDg2rVrSElJgUwmw7Bhw9C5c2duNlzKubm5Yf78+Rg6dCiAup7c9evXc7NyrW7kLWDjx48X2qimTp3K3bH39vb2iImJgYuLC+Lj41FSUoIvvvgCmzZtavZ708r1Y0pLS1FWVib0BJeVleH27duMU/1DvoklIyMDGRkZwqplQkKC0kocafl4mrwib6moX0TfvXsXRUVFMDExYZTqyeo/gpVKpSguLsYHH3zAOJWyhw8fwsHBAaampgqHifD4Rvrll1/m8hjk+jp37owNGzY0+BovhTUAGBoaIjo6WphwUP8wEV4KawDo27evwlkB7733Hn755Rd2gRrg5+eHefPmCRvUJRLJE/8fYEHdFs3km0E7d+6MxMREdOnSBbdu3WKcSpm2tjZatWoFkUgEiUSCzp07qywnFdeP8fDwEB5zAXXjkHg61lM+TzQuLg6RkZHCvFtXV1fMmTOHZTTSzPT19XH8+HGMHj0aAPDTTz9xuTI4ZcoUhIeHQyaTwcnJCR06dICVlRV3jzzr59HU1ETXrl25XB0eP3680BrAI3VpBzp37hwGDRrU4Ig7gJ+TD+V96zk5OQ2+3qdPHxUnej48Pgw3NjbG8ePHkZ+fD5lMht69eyudbcASD5NfnseMGTPw4MEDzJs3D97e3igvL4efnx/rWEp0dXVRVVUFU1NT+Pr6qnRfBbWFNCArKwtpaWmQyWSwsLDgajVDbuzYsTh27Jgw27q2thZ2dnb48ccfGScjzSU3Nxf/+9//hA1Dmpqa2LRpEzfzg+XkrSpxcXH4v//7PyxcuBCOjo7cTIuoj+fxXOpCXdqBli1bhoCAAEyfPl3pNZFIhN27dzNIpezjjz9GeHh4g08ARCIRTp06xSDVs+Np5VosFkNbW/uJ/dU8HXKkLqRSKU6fPs3Nm9GnuXPnDjp06IDa2lpERESgvLwc06dPV8nwAiqu1dSKFStw48YNhZXs1157DatWrWKcjDSn2tpahdUXnqYbyNna2uLYsWPw8/ODra0tLC0tueoNl1OX8VwFBQVYsmQJSkpKkJiYiMuXLyMxMRGffvop62hKKioqcP36de7+DEnTetKqOgDMnDkTZ86cUWGaJ3N2dkZMTIzCaNj6f+Vt9r66HMrj5ubGfb96bW0t/P39ERAQwOT+VFz/7UkjcOR4G4UjkUiwf/9+pKamChtJJk+ezNWjLtL0kpOTkZubi2nTpuHu3bt4+PChwlHjPFi5ciWSk5Mhk8mQkJCAv/76CzNnzuTmJEk5Nzc3zJs3T2E819dff83dL42ZM2fiww8/xLp16xAXFwepVAp7e3scPXqUdTQFSUlJWLFiBTQ1NZGYmIjMzEx89913CAsLYx1NgUwmw+HDh3H9+nUsXLgQxcXFKC0thZmZGetoSnj9fn9aX706rK7zSl0O5QkICICDgwOMjY1ZR3mqGTNmMHsiRc9A/8ZbP+i/0dLSwvTp0xt8xElapi1btiApKQm3b9/GtGnTIJFI4Ofnh3379rGOpsDf3x9ZWVno1q0btLW1UVlZyWz14Gl4H88lV15eDisrK6xfvx5A3UhGHt9Eb9iwAYcPHxaORTYyMkJhYSHjVMqCgoJw9+5dXL58GQsXLoSuri4CAwO5W0Dh+fs9MTGRdYTn0tD3NY8tIYWFhdi4caPw+WeffcbV+RVy6enp2LdvH3r06IG2bdsK13n7Hho6dChWrVoFJycnhZyq2LdAxfXf1GXSxq5du+Dh4YHg4OAGV9oXL17MIBVRhYSEBERFRWHSpEkAAAMDA2GSAE8KCgrQu3dvtG7dGqdPn8bVq1fh6urKOpaSNm3a4OzZswrjuXj8haupqQmJRCJ8v5eUlAh7LXijr6+v8Ll8OgNPUlJSEBsbK7TUvfTSSwoHTPBCXb7f1YGpqanS78tWrVrB2NgYq1ev5mbfirocysPj5sWGyIv9+nsAVPVkhYrrv4WEhGDRokVPHInDyygc+SguXV1dxkmIquno6CitWPJymER98+fPx+HDh1FUVAR/f3+MGDECPj4+3LUH8D6eS27KlCmYO3cu7t27h40bNyI2NhYLFixgHUuJrq4u7ty5I/w/mZKSwt28Y6DuZ2j97xseixdAfb7f1cGCBQvQunVrTJw4ETKZDNHR0aiursYrr7wCf39/7Nmzh3VEAOpzKM/NmzeVVtR5O/IeYPuEhYrrvw0aNAgA/yNx3NzcAKjm+E7CFwMDA6Snp0MkEkEqlSIsLExhviwv5G0LSUlJcHd3h6enJ5ePNnkfzyXn5OSErl274ueff0ZVVRWCg4Nhbm7OOpaShQsXwtPTE8XFxZg+fToKCgqwefNm1rGU9OvXD/Hx8ZDJZCguLsaWLVuEn/88UZfvd3Xw008/Kez58PDwwJQpU7B3715EREQwTKbIyckJ/fv3F/ZSzZgxg8vRizt37lT6md7QNdbmzZuntDDa0LXmQMX13+7du4fi4mLhUSHvIiIiMHHiRLRv3x6LFi1CZmYmli1bBktLS9bRSDNZvnw5fHx8cO3aNQwcOBDm5uYIDQ1lHUtJdXW1MNlCvsLK677pmpoaaGlpoba2FtevXwfA5xxhc3NzLgvq+oyNjbF7926cP38eQN2j+A4dOjBOpczX1xdr1qzB7du3MXnyZFhbW3O550Zdvt/VQVVVlTA/HKibJX7v3j0A4G7iknzDqnw8KE8yMzORkZGBe/fuKZzGWFFRAYlEwjBZwxra85GXl6eSe1Nx/bcTJ05gzZo1aN++PSwsLDBkyBBYWFioZB7ii4iOjsYHH3yAs2fPoqysDIGBgQgICKDiugXT19fHjh07UFVVBalUym1rkIeHB+zs7DBs2DAYGRmhqKiIy/aAyMhIhIaGQk9PT3jcztOkA3WbYAQA7du3x7Bhw4STQ6uqqrjrY2/Xrh2XG2wfpy7f7+pg/vz5mDhxIgYMGAAAuHz5Mr744gtUVlZi7NixjNP9Iz09Hd7e3tDR0YFMJoNYLMb69eu5mWRTUlKCS5cuoaqqCpcuXRKu6+rqIigoiGEyRQcPHsSBAwdQUFCAiRMnCtfLy8tVNm2HRvHVI5VKcfnyZaSlpSE1NRXnz58Xiu3AwEDW8RTI5wZ/88036NGjB5ycnISZnqTlKiwsRGFhocKx57wP86+trUVtbS13m9vef/997N69m5tDTh6XmpoKoG4zTl5envBLIjo6Gv379+euNez48eMICAjA7du3AYDbWcJA3Yi7wsJC1NTUCNemTp3KMFHD1PH7nVdlZWX4448/IJPJYGJiwuXptg4ODli+fDkGDx4MoK7YXrVqFeLj4xknU3TmzBmuF/Ju3LiB4uJirF69GitWrBCut2vXDm+88YZKnlbQynU9GhoaMDIygpGREaysrHD27Fns2bMHP/zwA3fFtY6ODjZv3owjR45g3759kMlkXD6WIU1n3bp1OHToEAwNDYVpESKRiLtftlVVVQgPD0dRURHWrVuHgoIC5Ofnw8bGhnU0Bfr6+twW1sA/E4w2btyI3bt3C6vYI0eOxMyZM7krrkNCQvD111/DxMSE22kmQF1byKVLl9C/f3/uWgLqU5fvd3Xx4MEDSKVS2NjYoLKyEvfv34eenh7rWApat24tFNZAXTuYjo4Ow0QNs7S05PoNapcuXdClSxckJCQwy0DF9d9yc3ORkpKClJQUZGVloWfPnjA3N8eaNWtgZGTEOp6SoKAg7N27F4sXL4a+vj4KCwthb2/POhZpRj/++CNOnjyJdu3asY7yVCtXroS+vj6ysrIA1G3M8vb25qa4lp8uN3z4cKxduxZ2dnbCFB6Av57rkpISVFdXC79kxWIxSktLGadS1rFjR24eXz/NhQsXkJCQwOXm1frU5ftdHcTExCA8PBwSiQQ2NjYoKSnBqlWrsHPnTtbRFJibmyM+Ph4ODg4AgCNHjsDKyopxKmXq8gY1Ly8PmzdvRlFRkcKbAFW01FFx/Tc7OzuYmJhgzpw5sLKy4n7k0YMHD7B06VLh8+7du+Pjjz9mmIg0N319fbX4RZudnY3g4GDhCGRdXV2uxp15eXkpfP7jjz8KH/PUcy03btw4uLq6wtbWFgDwww8/YNy4cYxTKRs1ahT27t0LW1tbhTcrvPVcGxgYsI7wTNTl+10d7Nq1C1FRUcLKau/evXHnzh3GqZTFxMQgIiICy5YtA1D3RlpPTw/ff/89RCIRkpOTGSesoy5vUD///HOMHTsWLi4uKn8TQMX13zZv3oy0tDR8++23CA0NhZmZGYYMGYIhQ4YoHYzAA39/f2hqamLq1KkYP368wi8z0jKZmJgIPyzq//fm7THx4z9wq6uruZoWom6nyy1YsAADBw4UxnPNnz8f7733HutYSr766isAwKpVqyASibjtue7ZsydmzpwJGxsbhX0AvDzSllOX73d1oKWlpbQhlMcV16ioKNYRnom6vEGVSqWYPXs2k3tTcf23kSNHCjOuKysrce7cOaSlpWHDhg0QiUQKq1s8iIuLQ3p6Ovbu3YuvvvoK9vb2mDJlijBqiLQ8mZmZAKBw4AGPPZjm5uYICwuDWCxGSkoKIiIiYG1tzTpWg5KTk5Gbm4tp06bh7t27ePjwocp2kz8Pa2trbv8M5eRtQLwTi8Xo3r07srOzWUd5KnX5flcHenp6yM/PF55Ix8XFcVkgdunSBTU1NULWnj17olUr/so0dXqDmpWVhTfffFPl96ZpIY8pKytDSkoKUlNTkZKSghs3bsDY2JibE5wacvXqVcyZMwelpaWwsrLCokWLYGhoyDoW+Y+SSCTYtm0bEhMTIZPJYG1tDS8vL+5+SWzZsgVJSUm4ffs2jh8/jlu3bmHBggXYt28f62gA1OfUWEJ4l5+fD29vb+Tl5aFTp07Q0dFBWFgYunfvzjqagszMTHz22WfQ1taGTCZDTU0NNm7ciLfffpt1NAVLlixp8DpP4/iAuqlqOTk56NWrl8LTH1X0XFNx/beVK1ciLS0NxcXFMDIyElpCzMzMuBshJpeeno7IyEhcvHgRLi4umDRpEs6ePYtNmzbhp59+Yh2PNAMazdV0HBwcEBUVhUmTJiE2NhYAYG9vjyNHjrAN9rfExERYW1s/cbymuhx4RQgPamtrUVBQAJlMhl69euH+/fvcjeNzc3PDvHnzMGzYMADA2bNn8fXXX2P//v2Mk6kn+TjTx8knMTUnvpaSGNLT08OyZctgZmamFv3L9vb20NXVxbRp0xASEiKsCjo6OnI3E5M0DXUZzRUQEIC5c+cKY67u3buHTZs2KWzA5YGOjo5SfzhPG5nlbSBURBPy4m7fvo2SkhK8+eabMDQ0RFlZGdauXYvo6GikpaWxjqegqqpKKKwBYOjQoaiqqmKYqGGPj1vNzc3lctyqvIguKytDp06dVHpvKq7/Nn/+fNYRnplUKkVgYOATRwRu375dxYmIKqjLaK709HSF+bEvvfQSd7/EgLpNOenp6RCJRJBKpQgLC0Pfvn1Zx1KyZs0afPLJJ2jTpg1mzJiBK1eu4IsvvoCjoyPraIRw7dChQ/jiiy/QsWNHdOrUCd7e3li4cCEsLS253DzYpk0bnD17FkOHDgVQt/LK27QdgP9xq3IXL17E/PnzIZVKkZSUhMzMTBw8eBCrV69u9ntTca2GNDQ0sHLlSi5/OJDmoy6jueq3rMjVnzHKi+XLl8PHxwfXrl3DwIEDYW5ujtDQUNaxlPz+++/w9fXFL7/8gs6dO+Orr76Cl5cXN8V1ZGTkU1/nbZMT+e/YuXMnYmJi0LdvX5w7dw4eHh4IDQ3l6sjz+pYuXSr0XAN1+1c2bNjAOJUy3setygUFBWHr1q1YuHAhAMDIyAi+vr4quTcV12rK0NAQxcXF6Nq1K+soREXUZTSXkZERAgIC4OnpCZlMhm3btnF3EFNtbS0SExOxY8cOVFVVQSqVKo3q4k1aWhpGjRqFzp07c9W+cunSJdYRnsmECROe+uemik1Oz4PlARgtRatWrYSnUYMGDULXrl25LaylUinKyspw/Phx5OfnQyaToXfv3lzOkuZ93KqcRCJROhRMVX+eVFyrqbKyMjg4OGDQoEFo27atcJ0mCLRc6jKay8/PD19++SWcnJwgEonw3nvvwc/Pj3UsBZqamoiLi4OrqyuXj13re/nll7Fs2TL89ttv8PLyQk1NTYNPB1jhbULAk/j4+LCO8FxYHoDRUkgkEuTm5gqFn4aGhsLnPJ3GqqGhgc2bN+Pdd99Fv379WMd5KnUZt6qtrY3KykrhTXVOTo7K9tTRtBA1RRMECGmcb7/9Fn369OF2JUuurKwM8fHxMDExgYmJCYqLi5GamgoXFxfW0ZTk5eUhKysLYrFYuObk5MQukBpzcHCgzemN9LSCj8fTWAMCAuDg4ABjY2PWUZ5KXcatJiUlCU9/3nnnHZw+fRohISEYPnx4s9+bims1lZycrLCr+EnXSMty+vRp/P777xCJRBgxYgRGjBjBOpKSLVu2YPLkyQrTQqKiojBr1iy2wR4zdOhQ3L9/Hzo6OmjTpo1woiAvRwzXV1FRgevXr3M377a+3bt348CBA7h9+zaMjIyQnp6OwYMHY9u2bayjKSgvL8fWrVtx9epVVFdXC9d3797NMJWyFStWYMqUKUwOwCBsODk54dq1a+jRo4fCE2lqBXpxRUVFOH36NGQyGSwtLdGjRw+V3JeKazXl7OystHrt4uKC6OhoRolIc9u6dSvi4uJgZ2cHADh27BicnJzw0UcfMU6myNHREXFxcQrXnJychFnSvLhx40aD17t06aLiJE+XlJSEFStWQFNTE4mJicjMzMR3332HsLAw1tEUjB8/HgcPHoS7uzvi4uKQnZ2N8PBwrFu3jnU0BZ9++ikMDQ1x9OhRzJs3D1FRUXj77beFTU+8YHkABmGD5Vzm56Eu41bLysrQrl07hQ2i5eXlKhnLx9caPvlX169fR0FBASoqKpCUlCRcLy8v53IeJmk68fHx2L9/vzAxZPr06XB3d+euuG7o/TpPPcJyvBXRT7JhwwYcPnwYnp6eAOo2jBYWFjJOpUxbWxtt27aFVCqFTCZDv379uMx5/fp1bNy4EadOncL48eMxevRoeHl5sY6lhLd9CqT53bx5U2kK0OMLFTxQl3GrH3/8scITKYlEgtmzZ+PgwYPNfm8qrtXM+fPnER0djTt37ig8bm3Xrp3abdghz6/+KD5ex/L17NkTERERmDlzJmQyGXbu3MndMcNA3S+ykJAQZGVlKbQH8NaHCdSNYayPx1Nj27RpA4lEgjfffBMhISF47bXX8Ndff7GOpUT+Z6elpYX79++jY8eOuHXrFuNUynhbrSTNb+fOnUrFdUPXWFOXcatisVhhw3rbtm0VftY3Jyqu1YyzszOcnZ0RHR3N5YYm0nwGDBiAJUuWYNKkSRCJRDh06BAGDBjAOpaSpUuXYtGiRVi/fj1EIhFMTU0REhLCOpYSPz8/2Nra4urVqwgNDcW+ffu4fBOgq6uLO3fuCDveU1JS0L59e8aplPn7+0MikcDX1xfr169HcXEx1q5dyzqWkp49e+L+/fuwt7eHq6sr2rdvj7feeot1LCXq0htOGi8zMxMZGRm4d++ewtz4iooKSCQShskapg7jVuXqn8549+5dlc3jpp5rNVZYWIjCwkKFd5G8jWUjTefRo0fYtGkTfv/9dwDA8OHD8b///U9h4wtPHj16BKButSA9PR3m5uaMEymS94Hb29vjyJEjkEqlmDlzJnfFS0ZGBvz9/VFcXIw333wTBQUF2Lx5M5dvrNRNeno6ysvLYWVlxd24O3XpDSeNd/LkSZw6dQqJiYkKE050dXXh6OjIXeFaUVGBL7/8Er/88oswbnXJkiXcvek/fPgwtm7dKqz8x8XFwcvLCxMmTGj2e1NxrabWr1+PgwcPwtDQEBoaGgDqRgvxVhiQ/67S0lLExsYiKioKMpkMx48fZx1JwaRJk3Do0CG4urriq6++wiuvvAJbW1ucPHmSdTSBVCpFdnY2unTpgvPnzwMATE1N0aFDB8bJ/rFr1y54eHggODi4wUNaFi9ezCCV+pOP4pO/+ROLxfDy8sLOnTtZRyPN5MyZM7C0tGQdo0VJSUlBUlKSMDJw8ODBKrkvtYWoqR9++AEnT57ktu+WND112KFdU1ODxMREHD58GBcvXkRNTQ22b98OExMT1tGUmJub4/79+3B3d4eLiwu0tbW5m3mtoaGBpUuXIioqitunUvJJFryfcOnh4YFdu3Zh6NChCm8CeB3BqC694aTpDBo0CF9//TWKioqwbt065ObmIj8/HzY2NqyjKUlOTkZhYaFCr/XUqVMZJmqYhYUFLCwsVH5fKq7VlL6+PhXW/zG879AOCgrC0aNH0a9fPzg7O2PDhg2wtbXlrrCOioqChYWFsAHYyckJQ4YMQUVFBZcnoxkaGqK4uBhdu3ZlHaVBbm5uAIBx48bB0NBQ4bXc3FwWkRok7/uPiopinOTZqEtvOGk6K1euhL6+PrKysgAABgYG8Pb25q649vX1xaVLl9C/f3/u2qnqy8vLEw6Rqf8mQBXjLKm4VlMmJibC8bj1Z6DyurpFGo/3Hdr79u2DqakpvLy8MHToUABosE2AtRMnTmDNmjVo3749LCwsMGTIEFhYWHBZWAN1G3IcHBwwaNAghf76b775hmEqZQsXLlSavd/QNVZeffVVAHXz4eVjDeW2bt2qdI210NBQAMAHH3wAIyMjoTectFzZ2dkIDg7GmTNnANQ9DVLVBrznceHCBSQkJEBLS4t1lKeS10guLi4qfxNAxbWayszMBADs2bNHuCYSiai4bsF436F95swZHDlyBGvXrsWDBw/g5OTE5XzrsLAwSKVSXL58GWlpafjpp58QFBQkFNuBgYGsIyqws7MTDg7iUVlZGcrKylBdXY3c3Fxhznl5ebmwqZUnDRXXDV3jQVlZGS5evAiRSISBAwdyvUpIGu/xYrW6urrBcwNYMzAwYB3hmUilUsyePZvJvWlDIyFq4vEd2u+++y78/Py426ENAFlZWTh8+DASEhJgaGgIe3t7oX2ANzk5OTh79iz27NmD0tJSXLhwgXUktbJr1y7s2rULpaWlwuowALRv3x7Tpk3DpEmTGKb7x2+//YYzZ84gPj5eYW5wRUUFMjMzuVlhlzt+/DiWL1+OAQMGQCqVIisrC6tXr+auRYA0nbVr16JDhw6Ij4+Hv78/IiIi8MYbb2DBggWsoynw9/dHTk4ObGxsFGbu89ZzvWLFCkyZMgVvvvmmyu9NxbWaqn86Y320ck14IpFIcOLECcTExGDr1q2s4wCo6wNOSUlBSkoKsrKy0LNnT5ibm8Pc3BxGRkZo1Yoe6L2IsLAwZqtEzyI1NRWpqanYv3+/whu9du3awcbGhrue9nHjxmHTpk3o1asXAKCgoABz5szBDz/8wDgZaS4SiQTbtm1DYmKiMN3Cy8uLu59JS5YsafB6UFCQipM8nZOTE3JyctCrVy+F9llV9FxTca2mpk+fLnwsFotx9epV9O/fH/v372eYijSnY8eOwcrKCu3atcM333yDjIwMLFiwgOYdP6c333wTJiYmmDNnDqysrLjsC1dXVVVVuHXrlkI7UJ8+fRgmUpadnc1tf319bm5uSj/P3d3dsW/fPkaJCFEvqampDV5XxemnVFy3EDk5OYiIiMCXX37JOgppJvJ5txkZGVi9ejVmzJiByMhIekP1nH7++WekpaUhLS0Nf/31F8zMzDBkyBAMGTJE6Zhx8uwiIyMRGhqKjh07Ksze5+04+erqasTHxytNEOBlHndVVRUAYPv27dDU1MTEiRMhk8kQHR0NbW1tfPjhh4wTkqZW/1TGhvDWbiGTyXDgwAH8/vvvEIlEGDFihHByMI/qH2imKnw9ayAvrE+fPvi///s/1jFIM5I/Gvztt98wadIk2NvbY8eOHYxTqZ+RI0di5MiRAIDKykqcO3cOaWlp2LBhA0QiEX788UfGCevk5OQ89XXeVoR37NiBhIQEdOnShXWUp5o3bx4kEgmMjY0V+kV5YWpqCpFIJGxkqz8VRiQSUXHdAq1evRoDBgxA3759WUd5JmvXrsXVq1fh4uICAIiNjUVBQQE3b1DlioqK4O3tjatXr0IkEqF///4ICQlBt27dmv3eVFyrqfo911KpFJmZmVyO7CFNRyQSIT4+HkePHsXmzZsB1PXokRdTVlaGlJQUpKamIiUlBbdu3YKxsTHrWAIvLy+hyLp586Yw176iogKvvfYaEhMTGSdUpK+vz31hDQDXr1/num9ZPuOY/Hd8+eWXiI2NRU5ODpycnDB+/Hh07NiRdawnOnPmDGJiYoQFn3HjxsHFxYW74nrFihWYPHmycNx5dHQ0VqxYgYiIiGa/NxXXamrbtm3Cx61atUK3bt24m3tLmtayZcuwbds2TJo0Cd26dUNBQQGTk6fU3cqVK5GWlobi4mIYGRlhyJAhWLFiBczMzLhayZQXzwEBARg0aBDGjRsHAPjxxx9x5coVltEaNHz4cKxduxZ2dnYKm4d4W2Hv1q0bKioquD6Eq7a2FpMnT1abA29I40yYMAETJkxAcXExYmJi4O7ujn79+mHOnDl44403WMdrUP0WEF7bQcrKyjBx4kTh8wkTJmD37t0quTcV12qq/nxr8t9gZmaGTZs2CZ/37NkTy5cvZ5hIPenp6WHZsmUwMzNTKAJ5lZGRgWXLlgmfjx07lst2oNjYWABQaKvhsee6ffv2mDBhAt555x2FN1M8rbppamripZdeQnV1tVr8P0qaRteuXTFz5ky88sor2LBhA0aMGMFlcW1paQlPT084OztDJBIhJiYGlpaWrGMp0dDQQF5eHnr37g0AyM/PV9mseCqu1ZS6bSggL27Xrl3w8PDA2rVrG3ydp6JAHcyfP591hOdSVVWF9PR0mJubAwDS09OFTW884a1N5Ul69eoljLfjWc+ePTF16lSMGTNGYSMWb5vbSOPJZDKcPn0a0dHRyM7Oxrhx43Dw4EGV9Aa/iEWLFuHAgQM4ceIEZDIZbGxs4OrqyjqWkgULFmDq1Kl46623IBKJcPXq1Sf+Hm1qVFyrKXXZUEAaT75ypcqdzoQf/v7++Pzzz9GmTRsAddMu1q1bxzhVw5KTk5Gbm4tp06bh7t27ePjwIXeF7Ny5c1lHeCaVlZXo27cv8vLyWEchzczKygr6+vpwcXHBJ598ApFIhOrqamFTMy+tVbW1tRCLxWjTpg3c3d3h7u4OoG4BgMfBc1ZWVjh69CguXrwImUwGExMTdOrUSSX3plF8asre3l5hQ4FEIoGLiwuOHDnCOBkhpKmJxWLk5+dDJpOhd+/eXPWGy23ZsgVJSUm4ffs2jh8/jlu3bmHBggXczWW+e/cugoKCcPPmTURGRiIrKwsXLlwQCgVCVM3a2lr4uP6kGPnnvLRWBQcHo3fv3kqnru7evRu3bt3ibnEvOzsbXbt2FRamKisr8eeff6pkKgutXKsxddhQQJpGRkYGduzYIaxk9O3bFx988AFX0y1I8zl37hz3K8IJCQmIiooSfvEaGBigoqKCcSply5Ytg5WVFfbu3QsA6N27NxYtWsRdcf2k2cfUFtLyqEtL1a+//oqFCxcqXZ86dSocHR25K659fX1x4MAB4XMtLS34+PggOjq62e9NxbWaUpcNBaTxLly4AC8vL7i5uWH8+PGQyWTIyMjArFmzsHXrVgwcOJB1RNKM6q8IT5s2DRKJBH5+ftytCOvo6EBLS0vhGo9v+ktKSuDu7i780tXW1hYOveHJpUuXhI+rq6uRkpKCgQMHUnFNmNHQ0GhwQ6CmpiaX3+u1tbUKP5O0tbUVTo9tTlRcqyl12VBAGm/btm0IDAzEqFGjhGujRo3CwIEDER4erjBBhLQ86rIibGBggPT0dIhEIkilUoSFhXF5KIa8lU7u4cOHXPaLBgUFKXxeWlqKwMBARmkIqWtPq6qqEvZ/yFVWVkIsFjNK9WStWrVCUVGRsDG0sLCQpoWQhqnbhgLSeDk5OQqFtZyNjQ1CQkIYJCKqpC4rwsuXL4ePjw+uXbuGgQMHwtzcHKGhoaxjKRk9ejRWrFiByspKREdHY+/evcIhEzx79dVXUVBQwDoG+Q+ztbWFj48PAgMDhTnx5eXlWLFiBcaOHcs4nbK5c+fC3d0d7777LoC6w/cCAgJUcm8qrtVMaGhogxsKDh06xOWGAtJ4Ojo6L/QaaRnUZUVYX18fO3bsQFVVFaRSKXR1dVlHatCsWbMQHx+Phw8fIikpCdOnT4ejoyPrWErq91zLZDJkZmaiQ4cODBOR/7pPPvkEvr6+eOedd9CzZ08AQEFBAaytrfHpp5+yDdeAkSNH4vvvv8dvv/0GoO7U2x49eqjk3jQtRM3Y2dkhPj5e6dFGbW0tHB0dkZCQwCgZaS62trbYuHFjg08mPvvsMxw7doxBKqIqt2/fho+PD1JTUyESiYQV4Zdffpl1NAB1q0FPI181Is9nyZIlwseampro3r07Jk+eDD09PXahCAFw/fp1XLlyBTKZDG+//bbKClZ1QivXakbdNhSQxvvrr7/g6enZ4Gv037zl431FeNu2bQDq+jEzMzPRr18/AHVjsExMTLgprj/77LOnfr988803Kkzz7x7vuSaEFz169KCC+l9Qca1m1G1DAWk8dRnTRJqWuqwI79mzB0DdJms/Pz9hek1GRgYOHz7MMpqCkSNHAqjLlZGRAQcHBwB1G0aHDBnCMhohpIWh4lrNqNuGAkLIi1GXFWG53NxchbGQxsbGWLlyJbtAj3F2dgYAxMXFITIyUtiv4Orqijlz5rCMRghpYlKpFKdPn2b2c5K/4Z7kqT755BNoa2vjnXfegbOzM5ydnWFlZQUNDQ0uNxQQQl7Mnj17sGfPHnTv3h379u1DbGwsYmNjsX//fm6OQ66vVatWiIuLEz6Pj49XGnvHg1u3bimccKmlpYWbN28yTEQIaWoaGhrYvHkzs/vz95OPPFWrVq0QGhpKGwoI+Y/gfUVYLigoCIsWLcLy5cshEonQt29fBAcHs46lZMiQIcIBXEDdSjavbSH5+fnIzc2FjY0NKisrIZFIaEMjIc9owIAByMjIYHKSMU0LIYQQjk2ePFk4XhioWxH+/vvvcfDgQcbJGiY/4EbetsYbiUSC/fv3IzU1FTKZDMOGDcPkyZOVZomzFhMTg/DwcEgkEpw6dQp5eXlYtWoVdu7cyToaIWrByckJ165dQ48ePdC2bVvhuir2glBxTQghHMvJycHixYtx7do1aGhoCCvChoaGrKMBgHACWk5OToOv89jCog6cnJwQGRmJqVOnIjY2FgAwfvx4GrdKyDNKTU1t8LoqnlRRWwghhHCsT58+iI6O5nZFOCAgAOHh4fDy8lJ6TSQS4dSpUwxSKdu1axc8PDwQHBzc4Eg+3g7g0tLSUhq7qKqjmwlpCeRFdFlZGTp16qTSe1NxTQghHFKXUXzh4eEA+B8Z2bp1awDgbk74k+jp6SE/P194IxAXFwcDAwPGqQhRHxcvXsT8+fMhlUqRlJSEzMxMHDx4EKtXr272e1NbCCGEcGj69OkAnjyKb+/evSzjKcnPz8frr7+O1q1b4/Tp07h69SpcXV3RsWNH1tHUUn5+Pry9vZGXl4dOnTpBR0cHYWFh6N69O+tohKgFNzc3BAQEYOHChUJrlZ2dHY4ePdrs96ZRfIQQwiF1G8U3f/58aGhooKioCP7+/igqKoKPjw/rWEoiIiJQXl4OoO7gm7Fjx+LMmTOMUynr1asXDh06hKioKGzZsgVHjhyhwpqQ5yCRSJR+Vqpq4zIV14QQwrGGRvFdunSJYaKGaWhoQEtLC0lJSXB3d8fq1au5nB8dHR2N9u3b4+zZsygrK0NgYCDWr1/POpaS/Px81NTUwNDQEDdv3sT27dvx4MED1rEIURva2tqorKwUWqtycnKE9rDmRsU1IYRwTF0OZ6murkZJSQkSExMxdOhQAACPXYfyTYEpKSmwt7eHmZkZlznV5UkAIbyaPXs2PvroI5SWlsLX1xceHh6YN2+eSu7N309oQgghAnU5nMXDwwN2dnYYNmwYjIyMUFRUhPbt27OOpURHRwebN2/GkSNHsG/fPshkMkgkEtaxlDz+JMDT01OYdU4I+XfvvvsuevfujdOnT0Mmk2HOnDkqO3CPNjQSQoga4HUU35PU1taitrZW4ahxHuTn52Pv3r0YPHgwRo8ejcLCQvzwww/4+OOPWUdTYGtri4iICCxZsgQLFiyAkZERHBwcEB8fzzoaIWpDIpEIU3d69eqlsqd+tHJNCCEcUrfDWaqqqhAeHo6ioiKsW7cOBQUFyM/Ph42NDetoCnr16oWlS5eirKwMANC9e3fuCmtAfZ4EEMKr9PR0eHt7Q0dHBzKZDGKxGOvXr4eZmVmz35tWrgkhhEMff/wxwsPDYW1trfQaT4ezyPn4+EBfXx8///wzjh49isrKSoXTBXnBcvZtY0ilUtTU1HD3JIAQXjk4OGD58uUYPHgwgLpie9WqVSp5+kMr14QQwiH54SyxsbHo0KED4zT/Ljs7G8HBwcJYO11dXUilUsaplAUFBWHr1q1YuHAhAMDIyAi+vr6MUzUsOTkZhYWFqKmpEa5NnTqVYSJC1Efr1q2FwhoAzM3NoaOjo5J7U3FNCCGckslkmDZtmlr02T4+P7a6uprLKRwsZ98+Dx8fH1y+fBn9+/enY88JeQHm5uaIj4+Hg4MDAODIkSOwsrJSyb2puCaEEE6JRCJ069YNDx484P6kQ3Nzc4SFhUEsFiMlJQURERENtrSwxnL27fP4448/kJCQwGXhT4g6iImJQUREBJYtWwag7rRbPT09fP/99xCJREhOTm62e1NxTQghHGvbti2cnZ1hZWWFtm3bCtcXL17MMJWyBQsWYNu2bdDV1UVISAisra3h5eXFOpaSx2ffnj59GiEhIaxjKTEwMGAdgRC1FhUVxezetKGREEI49u233zZ4fe7cuSpO8mS1tbXw9/dHQEAA6yj/qry8HPfv3xdm31paWqps9u3z8Pf3R05ODmxsbBQ2MVLPNSHP5ujRoxgzZgyTQ7do5ZoQQjjGUxH9JJqamigsLGQd41/JZDJMnToV8fHxmDJlCus4TyUWi9G9e3dkZ2ezjkKIWkpISEBwcDAmTJgANzc3dO7cWWX3ppVrQgjhUG5uLvLy8jBq1CgAQGBgIMrLywEAM2bMwFtvvcUynpJNmzbhzp07cHJyUmhf4W0e9yeffILAwEDue9gJIY1348YN7Nu3D7GxsTAzM8OUKVMwdOjQZr8vFdeEEMKhefPmwdbWFmPGjAEAjBkzBjNmzMCjR49w5coVfPXVV4wTKlKXedyLFi3CuXPnuO9hf/xQntzcXC4P5SFEHZw/fx6ff/45Hjx4gK5du8Lf3x/m5ubNdj9qCyGEEA4VFhYKhTUAtGnTRui35bHvNjExkXWEZ9KjRw8ue6wft3LlSujr6yMrKwtA3QZHb29vKq4JeUZisRjHjh3Dvn37UFtbi/nz58PW1hYZGRlYvHhxs/7MouKaEEI4VP/gEABYt26d8PHDhw9VHafFUIcedkB9DuUhhFfW1tawsLCAr68vTE1Nhevm5uYYNmxYs96bimtCCOGQRCJBRUUF2rVrBwAwNDQEAFRUVEAsFrOMRlRAXQ7lIYRX0dHRePXVVxt87csvv2zWe1NxTQghHLKzs4Ofnx8CAwOFAruiogLLli2Dra0t43SkuanLoTyE8CYtLU34+Pr160qv1z8SvbnQhkZCCOFQTU0NfH19cerUKfTs2RMAUFBQgPfffx9r1qxhMruVqI5EIsG2bduQmJgImUwmHMpD/90JeboJEyYIH+fl5aF3797C5yKRCIcPH272DFRcE0IIx65fv44rV64AAPr378/dZrzPPvtMOEq8Id98840K0zyb/Px85ObmwsbGBpWVlZBIJNDT02MdixDSxJycnBAbG6vy+9JbYEII4Rjv0y1GjhwJAMjIyEBGRgYcHBwA1B3gMGTIEJbRGhQTE4Pw8HBIJBLY2NigpKQEq1atws6dO1lHE2RkZGDHjh3IyckBAPTt2xcffPABjI2NGScjRL087Y1/c6LimhBCyAtzdnYGAMTFxSEyMhI6OjoAAFdXV8yZM4dltAbt2rULUVFRwjjD3r17486dO4xT/ePChQvw8vKCm5sbxo8fD5lMhoyMDMyaNQtbt27FwIEDWUckhPwLKq4JIYQ02q1bt6CtrS18rqWlhZs3bzJM1DAtLS3o6uoqXNPU1GSURtm2bdsQGBgonMwJAKNGjcLAgQMRHh6OTZs2MUxHCP/kT3yAuik7ubm5CpN2VHFqLBXXhBBCGm3IkCHw9PRUWMnmsS1ET08P+fn5wuPiuLg4GBgYME71j5ycHIXCWs7GxgYhISEMEhGiXry8vBQ+9/T0FD5W1amxtKGREEJIo0kkEuzfvx+pqamQyWQYNmwYJk+erDSvmbX8/Hx4e3sjLy8PnTp1go6ODsLCwtC9e3fW0QAAjo6OiIuLe+7XCCH8oJVrQgghjaalpYXp06dj+vTprKM8Va9evXDo0CEUFBRAJpOhV69eXLWFSCQSpcfY9V8jhPCPVq4JIYQ0Wn5+Pvz8/FBSUoLExERcvnwZiYmJ+PTTT1lHU5Cfn4/XX38drVu3xunTp3H16lW4urqiY8eOrKMBwFMPilHVI21CSONQcU0IIaTRZs6ciQ8//BDr1q1DXFwcpFIp7O3tcfToUdbRFDg6OuLw4cO4desWPDw8MGLECNy+fRthYWGsoxFCWggN1gEIIYSov/LyclhZWQkbBTU0NLjrtwb+yZWUlAR3d3esXr2ay6kmhBD1RcU1IYSQRtPU1IREIhGK65KSEmho8Pcrprq6WmhdGTp0KAA02N9MCCEvir+ffIQQQtTOlClTMHfuXNy7dw8bN27ElClT8OGHH7KOpcTDwwN2dnbQ1dWFkZERioqK0L59e9axCCEtCPVcE0IIaRLp6en4+eefIZPJYG1tDXNzc9aR/pVUKkVNTY3CATiEENIYVFwTQghptLi4ODg6Ov7rNR4kJyejsLAQNTU1wjX5ceiEENJYNOeaEEJIo+3cuVOpkG7oGms+Pj64fPky+vfvz9V8a0JIy0HFNSGEkBeWmZmJjIwM3Lt3D5GRkcL1iooKLg89+eOPP5CQkMDlJBNCSMtAxTUhhJAXVlJSgkuXLqGqqgqXLl0Sruvq6iIoKIhhsoYZGBiwjkAIaeGo55oQQkijnTlzBpaWlqxj/Ct/f3/k5OTAxsZGYRMj9VwTQpoKrVwTQghptCtXrmDAgAHQ09MDANy7dw9RUVGYNWsW22CPEYvF6N69O7Kzs1lHIYS0ULRyTQghpNEcHR0RFxencM3JyQmxsbFsAhFCCCN0iAwhhJBGa2idpra2lkGSp6uqqsLXX38Nb29vAEBubi5OnjzJOBUhpCWh4poQQkij9ezZExEREZDJZJBKpdixYwe6d+/OOpaSlStXoqamBllZWQDqNjh+++23jFMRQloSKq4JIYQ02tKlS/Hzzz/D2NgYJiYmSEpKwooVK1jHUpKdnY2FCxcKo/h0dXUhlUoZpyKEtCS0oZEQQkijde7cGbt378ajR48AAG3btmWcqGGPz7eurq5usKWFEEJeFK1cE0IIaTSZTIZDhw5h06ZNaNu2LYqLi3H+/HnWsZSYm5sjLCwMYrEYKSkpmDdvHqytrVnHIoS0IFRcE0IIabSgoCCcPXtW2Byoq6uLwMBAxqmULViwADKZDLq6uggJCYGxsTE+/fRT1rEIIS0ItYUQQghptJSUFMTGxsLZ2RkA8NJLL6G6uppxKmVaWlqYM2cO5syZwzoKIaSFouKaEEJIo7Vu3RoikUj4nMdNghkZGdixYwdycnIAAH379sUHH3wAY2NjxskIIS0JtYUQQghptH79+iE+Ph4ymQzFxcVYuXIlBg0axDqW4MKFC/joo4/QrVs3zJ8/H/PmzUPXrl0xa9YsXLx4kXU8QkgLQic0EkIIabSKigqsWbMGiYmJAABra2ssWbIEurq6jJPV+eSTT+Dk5IRRo0YpXD958iSio6OxadMmRskIIS0NFdeEEEJavDFjxuCnn3567tcIIeR5Uc81IYSQJpGcnIzCwkLU1NQI16ZOncow0T90dHRe6DVCCHleVFwTQghpNF9fX1y6dAn9+/eHpqYm6zhKJBIJcnNzGzwwRiKRMEhECGmpqLgmhBDSaBcuXEBCQoLSCYi8+Ouvv+Dp6dnga/WnnBBCSGNRcU0IIaTRDAwMWEd4KvlGS0IIaW5UXBNCCGm0nj17YubMmbCxsYG2trZwnZeea0IIURUqrgkhhDSaWCxG9+7dkZ2dzToKIYQwRaP4CCGEEEIIaSK0ck0IIaRJ8DyKjxBCVIWKa0IIIY3m4+ODy5cvczuKjxBCVIWKa0IIIY32xx9/cD2KjxBCVEWDdQBCCCHqj/dRfIQQoiq0ck0IIaTRaBQfIYTUoeKaEEJIo9EoPkIIqUOj+AghhBBCCGkitHJNCCGk0WQyGQ4cOIDff/8dIpEII0aMwKRJkyASiVhHI4QQlaLimhBCSKOtXbsWV69ehYuLCwAgNjYWBQUFWLx4MeNkhBCiWtQWQgghpNHs7e0RExODVq3q1mwkEglcXFxw5MgRxskIIUS1aBQfIYSQJlG/BYTaQQgh/1XUFkIIIaTRLC0t4enpCWdnZ4hEIsTExMDS0pJ1LEIIUTlqCyGEENJoUqkUBw4cQHJyMmQyGYYPHw5XV1doaNADUkLIfwsV14QQQl5YbW0txGIx2rRpo3C9qqoK2tra0NTUZJSMEELYoCUFQgghLyw0NBQJCQlK1w8dOoR169YxSEQIIWxRcU0IIeSF/frrr8L4vfqmTp2KX3/9lUEiQghhi4prQgghL0xDQ6PB1g9NTU2aGEII+U+i4poQQsgLE4vFqKqqUrpeWVkJsVjMIBEhhLBFxTUhhJAXZmtrCx8fH1RUVAjXysvLsWzZMowdO5ZhMkIIYYOmhRBCCHlhNTU18PX1xalTp9CzZ08AQEFBAaytrREcHCyc2EgIIf8VVFwTQghptOvXr+PKlSuQyWR4++230aNHD9aRCCGECSquCSGEEEIIaSLUc00IIYQQQkgToeKaEEIIIYSQJkLFNSGEqEhYWBiWLl3KOgYhhJBmRD3XhBDSwkRHR+PQoUPYt2+fyu9tbW2NgIAADB8+XOX3JoQQHtDKNSGEEAU1NTWsIxBCiNqi4poQQprBli1b8M4778DU1BRjxoxBcnIyNm7ciIULFwpfExsbi5EjR8LCwgLfffcdrK2t8fvvvwMANm7ciHnz5mHx4sUwNTWFnZ0dMjMzFf75NjY2MDU1ha2tLU6cOAEAyM3Nhb+/P/744w+YmprC3NwcADB9+nQcOnRI+Pujo6Ph7u4ufP7GG28gMjISo0ePxujRowEAP//8MxwdHWFubg43NzdkZWU99d950aJF+PPPPzF79myYmppi69at8PLywp49exS+zt7eHidPnhTuu3v3brz//vuwsLBAcHAwpFKp8LWHDx/GuHHjMHjwYHz00Ue4cePGs/9HIIQQBqi4JoSQJpaXl4fIyEgcPnwYFy5cwPbt29GlSxeFr8nJycEXX3yBkJAQnD59GhUVFSgpKVH4msTERNjZ2SE9PR3W1tZYvXq18Fq3bt0QGRmJc+fOYe7cuVi0aBFKS0thaGiIL774AiYmJrhw4QLS09OfOffJkydx8OBBHDt2DJcvX4afnx9WrVqFlJQUuLq64n//+99TjzQPCQnB66+/jrCwMFy4cAGenp5wcnJCfHy88DVZWVkoLS2FlZWVcO3EiROIiopCTEwMEhMTERUVJeQJDw/Ht99+i+TkZAwaNAje3t7P/O9DCCEsUHFNCCFNTFNTE2KxGLm5uZBIJOjatSu6d++u8DU//vgjRo4cCXNzc2hra+Ozzz6DSCRS+JpBgwbh3XffhaamJhwdHRVWjseNG4fOnTtDQ0MDtra26NGjBzIyMhqV28vLC3p6etDR0cHBgwfh6uqKgQMHQlNTE87OztDS0sIff/zxXP9MGxsbXL9+HQUFBQCAuLg4jBs3Dtra2sLXeHp6Qk9PD6+//jpmzJiBhIQEAMD+/fvh5eUFQ0NDtGrVCrNnz8bVq1dp9ZoQwjU6l5YQQppYjx494Ofnh40bNyInJweWlpbw9fVV+JrS0lIYGBgIn7dp0wZ6enoKX/PKK68IH+vo6KC6uho1NTVo1aoVYmNjERERIRSajx49wr179xqV+7XXXhM+/vPPPxEbG4vvv/9euCaRSFBaWvpc/0xtbW2MHTsW8fHxmDt3LhISErBhw4Yn3rdLly7CPf78808EBgYiODhYeF0mk6GkpETpSQAhhPCCimtCCGkG9vb2sLe3R0VFBVasWIHQ0FCF1etXX30V+fn5wud//fUX7t+//0z/7Bs3bmDZsmXYuXMnTE1NhZVtucdXwIG64r2qqkr4/M6dO0pfU//ve+211zB79mzMmTPnmTI9jbOzMxYvXoxBgwahTZs2MDU1VXj95s2b6Nu3L4C6gvrVV19VyODg4NDoDIQQoirUFkIIIU0sLy8PycnJEIvF0NbWRuvWraGpqanwNWPGjEFiYiLOnz8PsViMDRs24Fkno1ZVVUEkEqFTp04AgKioKFy7dk14/eWXX0ZJSYlCf/Rbb72FEydOoKqqCtevX8fhw4efeo9JkyZh//79uHjxImQyGR49eoRffvkFFRUVT/37XnnlFRQVFSlcMzU1hYaGBtasWdNgobx9+3Y8ePAAN2/exO7du2FrawsAcHNzw5YtW4R/t/Lycvzwww9PvT8hhLBGxTUhhDQxsViMdevWwcLCApaWligrK8OCBQsUvqZv375Yvnw5Pv/8c7zzzjvQ1dVFp06dFHqRn6RPnz748MMP4ebmhuHDhyM7OxtmZmbC60OHDkWfPn1gaWkJCwsLAICHhwe0tLQwfPhw+Pj4wN7e/qn3MDIywurVq7Fq1SoMHjwYo0ePRnR09L9m8/LywubNm2Fubo7t27cL1x0dHZGdna2wwi73/vvvw8XFBU5OTnjvvfcwceJEAMCoUaMwa9YsfP755zAzM8P48ePx66+//msGQghhiQ6RIYQQDlRWVmLw4MH46aef0K1bN9ZxmlxsbCwOHDigdLDNG2+8gePHj6NHjx6MkhFCSNOilWtCCGEkMTERVVVVePToEYKDg9GvXz907dqVdawmV1VVhb1798LV1ZV1FEIIaXa0oZEQQhg5deoUFi9eDJlMhgEDBmD9+vUNbkbkyZ9//gk7O7sGXzt69Chef/11hWunT5/Gp59+imHDhmH8+PGqiEgIIUxRWwghhBBCCCFNhNpCCCGEEEIIaSJUXBNCCCGEENJEqLgmhBBCCCGkiVBxTQghhBBCSBOh4poQQgghhJAmQsU1IYQQQgghTeT/AQHT9sSOjhjPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='circular_compactness', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "secure-catholic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"circular_compactness\"].reset_index(),\n",
    "                 x_vars=grouped[\"circular_compactness\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "atmospheric-notebook",
   "metadata": {},
   "source": [
    "### Donut index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "exciting-telephone",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='donut_index', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "transparent-hours",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"donut_index\"].reset_index(),\n",
    "                 x_vars=grouped[\"donut_index\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hearing-congo",
   "metadata": {},
   "source": [
    "### Fractality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "korean-mitchell",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='fractality', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "decimal-lithuania",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"fractality\"].reset_index(),\n",
    "                 x_vars=grouped[\"fractality\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "valued-index",
   "metadata": {},
   "source": [
    "### Convexity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "incorporated-cinema",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='convexity', hue='signature_type', dodge=False, data=signatures, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "conservative-reward",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(grouped[\"convexity\"].reset_index(),\n",
    "                 x_vars=grouped[\"convexity\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "intellectual-cincinnati",
   "metadata": {},
   "source": [
    "## Using only 50% largest signatures per each type\n",
    "\n",
    "The rationale is that it eliminates the \"noise\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "western-basis",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = pandas.Series(numpy.zeros(len(signatures), dtype=bool), index=signatures.index)\n",
    "\n",
    "for cl in signatures.signature_type.unique():\n",
    "    sub = signatures[signatures.signature_type == cl]\n",
    "    mean = sub.area.mean()\n",
    "    above = sub.area > mean\n",
    "    mask[above[above].index] = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "relevant-nudist",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6915"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fitting-cambridge",
   "metadata": {},
   "outputs": [],
   "source": [
    "significant = signatures[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "complicated-australian",
   "metadata": {},
   "outputs": [],
   "source": [
    "significant_grouped = significant.groupby(\"signature_type\").describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "popular-solid",
   "metadata": {},
   "source": [
    "### Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "tamil-clinic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='area', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.set_yscale(\"log\")\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "constitutional-semester",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"area\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"area\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "western-extreme",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"area\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"area\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "g.set(xscale='log')\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "saved-catalog",
   "metadata": {},
   "source": [
    "### Perimeter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "suspected-infection",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='perimeter', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.set_yscale(\"log\")\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "novel-experiment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"perimeter\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"perimeter\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "virtual-friendly",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"perimeter\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"perimeter\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "g.set(xscale='log')\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "necessary-craps",
   "metadata": {},
   "source": [
    "### ERI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "german-relationship",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='eri', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "national-eight",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"eri\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"eri\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "linear-excuse",
   "metadata": {},
   "source": [
    "### Circlular compactness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "different-greeting",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='circular_compactness', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "accompanied-suite",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"circular_compactness\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"circular_compactness\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "compound-approach",
   "metadata": {},
   "source": [
    "### Donut index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "generous-patio",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='donut_index', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "continuous-spencer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"donut_index\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"donut_index\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "played-airline",
   "metadata": {},
   "source": [
    "### Fractality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "elegant-produce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='fractality', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "colonial-woman",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"fractality\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"fractality\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "running-costa",
   "metadata": {},
   "source": [
    "### Convexity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "loose-chicken",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15]),\n",
       " [Text(0, 0, 'Wild countryside'),\n",
       "  Text(1, 0, 'Countryside agriculture'),\n",
       "  Text(2, 0, 'Urban buffer'),\n",
       "  Text(3, 0, 'Open sprawl'),\n",
       "  Text(4, 0, 'Disconnected suburbia'),\n",
       "  Text(5, 0, 'Accessible suburbia'),\n",
       "  Text(6, 0, 'Warehouse/Park land'),\n",
       "  Text(7, 0, 'Gridded residential quarters'),\n",
       "  Text(8, 0, 'Connected residential neighbourhoods'),\n",
       "  Text(9, 0, 'Dense residential neighbourhoods'),\n",
       "  Text(10, 0, 'Dense urban neighbourhoods'),\n",
       "  Text(11, 0, 'Local urbanity'),\n",
       "  Text(12, 0, 'Regional urbanity'),\n",
       "  Text(13, 0, 'Metropolitan urbanity'),\n",
       "  Text(14, 0, 'Concentrated urbanity'),\n",
       "  Text(15, 0, 'Hyper concentrated urbanity')])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "seaborn.boxenplot(x=\"signature_type\", y='convexity', hue='signature_type', dodge=False, data=significant, ax=ax, showfliers=False, linewidth=.75)\n",
    "ax.legend_.remove()\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "designed-waters",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1260x720 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = seaborn.PairGrid(significant_grouped[\"convexity\"].reset_index(),\n",
    "                 x_vars=significant_grouped[\"convexity\"].columns[1:], y_vars=[\"signature_type\"],\n",
    "                 height=10, aspect=.25)\n",
    "g.map(seaborn.stripplot, size=10, orient=\"h\", jitter=False,\n",
    "      linewidth=1, edgecolor=\"w\")\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "chubby-somewhere",
   "metadata": {},
   "source": [
    "## Notes\n",
    "\n",
    "### Area\n",
    "\n",
    "*Wild countryside*, *Countryside agriculture* and *Urban buffer* much larger than the rest. The difference between more urban signatures is small, with an exception of *Warehouse/Park land* that tends to be a bit larger and *Disconnected suburbia* that tends to be smaller.\n",
    "\n",
    "### Perimeter\n",
    "\n",
    "Very similar as area, we could almost say the same.\n",
    "\n",
    "### Equivalent rectangular index\n",
    "\n",
    "*(higher the value is, less complex the shape is)*\n",
    "\n",
    "There's an intereseting tendency shown - more urban signatures tend to be less complex in shape than rural ones and there is almost a gradient of increasing complexity as we lose urbanity. In other words, more urban singatures have much simpler shapes.\n",
    "\n",
    "However, this clear tendency is lost when we take into account only 50% largest polygons.\n",
    "\n",
    "### Circular compactness\n",
    "\n",
    "*(higher value means more compact, circle-like shape)*\n",
    "\n",
    "Nothing super interesting comes up. Countryside tends to have less compact shapes but the rest doesn't tell much.\n",
    "\n",
    "### Donut index\n",
    "\n",
    "*(higher values means more holes)*\n",
    "\n",
    "This is interesting. We have two groups of signatures showing donut-like tendency. \n",
    "\n",
    "- Countryside right next to the city - *urban buffer* and *open sprawl* have a tendency to encircle more urban development\n",
    "- Dense central areas - *dense urban neighbourhoods* and the *urbanity* singatures tend to form concentric rings, therefore having a donut shape.\n",
    "\n",
    "### Fractality\n",
    "\n",
    "*(higher means more fractal-like)*\n",
    "\n",
    "There is some variation, especially looking only at top 50% but I am not sure if there is any specific tendency apart from a relative randomness.\n",
    "\n",
    "### Convexity\n",
    "\n",
    "*(1 means convex, 0 complex)*\n",
    "\n",
    "Again, not sure if it shows anything meaningful.\n",
    "\n",
    "## By area and cell count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "virtual-isaac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>signature_type</th>\n",
       "      <th>area</th>\n",
       "      <th>perimeter</th>\n",
       "      <th>eri</th>\n",
       "      <th>circular_compactness</th>\n",
       "      <th>donut_index</th>\n",
       "      <th>fractality</th>\n",
       "      <th>convexity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.826984e+07</td>\n",
       "      <td>29577.575163</td>\n",
       "      <td>0.601828</td>\n",
       "      <td>0.439852</td>\n",
       "      <td>7.105984e-05</td>\n",
       "      <td>1.065559</td>\n",
       "      <td>0.788857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.235908e+04</td>\n",
       "      <td>555.207264</td>\n",
       "      <td>0.892662</td>\n",
       "      <td>0.254347</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.047118</td>\n",
       "      <td>0.983245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>7.234542e+05</td>\n",
       "      <td>5746.792461</td>\n",
       "      <td>0.602136</td>\n",
       "      <td>0.339522</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.077707</td>\n",
       "      <td>0.629428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>1.229467e+06</td>\n",
       "      <td>6161.670240</td>\n",
       "      <td>0.731125</td>\n",
       "      <td>0.306803</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.046892</td>\n",
       "      <td>0.799648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Countryside agriculture</td>\n",
       "      <td>7.604014e+06</td>\n",
       "      <td>22500.262066</td>\n",
       "      <td>0.539593</td>\n",
       "      <td>0.252670</td>\n",
       "      <td>2.808737e-04</td>\n",
       "      <td>1.089988</td>\n",
       "      <td>0.641429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96687</th>\n",
       "      <td>Hyper concentrated urbanity</td>\n",
       "      <td>1.797907e+03</td>\n",
       "      <td>187.424114</td>\n",
       "      <td>0.981508</td>\n",
       "      <td>0.369170</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.026657</td>\n",
       "      <td>0.996822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96688</th>\n",
       "      <td>Hyper concentrated urbanity</td>\n",
       "      <td>1.271663e+06</td>\n",
       "      <td>10882.240090</td>\n",
       "      <td>0.415598</td>\n",
       "      <td>0.541253</td>\n",
       "      <td>1.464732e-14</td>\n",
       "      <td>1.125311</td>\n",
       "      <td>0.827377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96689</th>\n",
       "      <td>Hyper concentrated urbanity</td>\n",
       "      <td>1.872188e+03</td>\n",
       "      <td>175.432872</td>\n",
       "      <td>0.986566</td>\n",
       "      <td>0.621376</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.003591</td>\n",
       "      <td>0.980982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96690</th>\n",
       "      <td>Hyper concentrated urbanity</td>\n",
       "      <td>2.767724e+03</td>\n",
       "      <td>213.469395</td>\n",
       "      <td>0.995107</td>\n",
       "      <td>0.614557</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.003611</td>\n",
       "      <td>0.965406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96691</th>\n",
       "      <td>Hyper concentrated urbanity</td>\n",
       "      <td>9.875395e+05</td>\n",
       "      <td>5945.760474</td>\n",
       "      <td>0.771656</td>\n",
       "      <td>0.216829</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.058343</td>\n",
       "      <td>0.824101</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96689 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    signature_type          area     perimeter       eri  \\\n",
       "0          Countryside agriculture  1.826984e+07  29577.575163  0.601828   \n",
       "1          Countryside agriculture  1.235908e+04    555.207264  0.892662   \n",
       "2          Countryside agriculture  7.234542e+05   5746.792461  0.602136   \n",
       "3          Countryside agriculture  1.229467e+06   6161.670240  0.731125   \n",
       "4          Countryside agriculture  7.604014e+06  22500.262066  0.539593   \n",
       "...                            ...           ...           ...       ...   \n",
       "96687  Hyper concentrated urbanity  1.797907e+03    187.424114  0.981508   \n",
       "96688  Hyper concentrated urbanity  1.271663e+06  10882.240090  0.415598   \n",
       "96689  Hyper concentrated urbanity  1.872188e+03    175.432872  0.986566   \n",
       "96690  Hyper concentrated urbanity  2.767724e+03    213.469395  0.995107   \n",
       "96691  Hyper concentrated urbanity  9.875395e+05   5945.760474  0.771656   \n",
       "\n",
       "       circular_compactness   donut_index  fractality  convexity  \n",
       "0                  0.439852  7.105984e-05    1.065559   0.788857  \n",
       "1                  0.254347  0.000000e+00    1.047118   0.983245  \n",
       "2                  0.339522  0.000000e+00    1.077707   0.629428  \n",
       "3                  0.306803  0.000000e+00    1.046892   0.799648  \n",
       "4                  0.252670  2.808737e-04    1.089988   0.641429  \n",
       "...                     ...           ...         ...        ...  \n",
       "96687              0.369170  0.000000e+00    1.026657   0.996822  \n",
       "96688              0.541253  1.464732e-14    1.125311   0.827377  \n",
       "96689              0.621376  0.000000e+00    1.003591   0.980982  \n",
       "96690              0.614557  0.000000e+00    1.003611   0.965406  \n",
       "96691              0.216829  0.000000e+00    1.058343   0.824101  \n",
       "\n",
       "[96689 rows x 8 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "signatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "lightweight-scheduling",
   "metadata": {},
   "outputs": [],
   "source": [
    "joined = dask.dataframe.read_parquet(\"../../urbangrammar_samba/spatial_signatures/signatures/hindex_to_type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "prepared-butler",
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = joined.groupby('id').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "shaped-pointer",
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = counts.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "democratic-product",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>hindex</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>2461180</td>\n",
       "      <td>2461180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2797</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2801</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95069</th>\n",
       "      <td>313</td>\n",
       "      <td>313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95071</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95072</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95075</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95077</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96704 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        hindex     type\n",
       "id                     \n",
       "459    2461180  2461180\n",
       "2797         2        2\n",
       "2801         1        1\n",
       "2817         2        2\n",
       "2818         1        1\n",
       "...        ...      ...\n",
       "95069      313      313\n",
       "95071        1        1\n",
       "95072        1        1\n",
       "95075        2        2\n",
       "95077        1        1\n",
       "\n",
       "[96704 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "manufactured-future",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-12-a85cca808231>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  signatures[\"cell_count\"] = counts.type\n"
     ]
    }
   ],
   "source": [
    "signatures[\"cell_count\"] = counts.type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "blond-balance",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py:1676: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_column(ilocs[0], value, pi)\n"
     ]
    }
   ],
   "source": [
    "for cat in signatures.signature_type.cat.categories:\n",
    "    mask = signatures.signature_type == cat\n",
    "    desc = signatures[mask].cell_count.describe()\n",
    "    signatures.loc[mask, \"count_quartile\"] = pandas.cut(signatures[mask].cell_count, bins=[0, desc[\"25%\"]+.1, desc[\"50%\"]+.2, desc[\"75%\"]+.3, desc['max']], labels=[\"q1\", \"q2\", \"q3\", \"q4\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "generic-cheese",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_by_count_quartile(variable, log=False):\n",
    "    plot_data = pandas.DataFrame(index=signatures.signature_type.cat.categories, columns=[\"q1\", \"q2\", \"q3\", \"q4\"])\n",
    "    plot_data.index.name = \"types\"\n",
    "    for cat, q in product(signatures.signature_type.cat.categories, [\"q1\", \"q2\", \"q3\", \"q4\"]):\n",
    "        plot_data.loc[cat, q] = signatures[(signatures.signature_type == cat) & (signatures.count_quartile == q)][variable].mean()\n",
    "\n",
    "    fig, axs = plt.subplots(1, 4, figsize=(20, 10), sharey=True)\n",
    "    axs = axs.flatten()\n",
    "    for i, col in enumerate(plot_data):\n",
    "        seaborn.scatterplot(data=plot_data, x=col, y=\"types\", ax=axs[i])\n",
    "        if log:\n",
    "            axs[i].set_xscale('log')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cordless-homework",
   "metadata": {},
   "source": [
    "### Area by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "occupied-spoke",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"area\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "pursuant-protest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"area\", log=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "finished-offering",
   "metadata": {},
   "source": [
    "### Perimeter by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "later-steal",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"perimeter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "upset-steps",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"perimeter\", log=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "crude-israeli",
   "metadata": {},
   "source": [
    "### ERI by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "enormous-orientation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"eri\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "universal-pride",
   "metadata": {},
   "source": [
    "### Circlular compactness by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "regulated-store",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"circular_compactness\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ultimate-dividend",
   "metadata": {},
   "source": [
    "### Donut index by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "loaded-qualification",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"donut_index\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "introductory-finnish",
   "metadata": {},
   "source": [
    "### Fractality by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "pleasant-ticket",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"fractality\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amazing-wesley",
   "metadata": {},
   "source": [
    "### Convexity by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "posted-annual",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_count_quartile(\"convexity\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "material-software",
   "metadata": {},
   "source": [
    "## Area quartiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "automatic-spouse",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py:1599: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[key] = infer_fill_value(value)\n",
      "/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py:1676: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_column(ilocs[0], value, pi)\n"
     ]
    }
   ],
   "source": [
    "for cat in signatures.signature_type.cat.categories:\n",
    "    mask = signatures.signature_type == cat\n",
    "    desc = signatures[mask][\"area\"].describe()\n",
    "    signatures.loc[mask, \"area_quartile\"] = pandas.cut(signatures[mask].cell_count, bins=[0, desc[\"25%\"], desc[\"50%\"], desc[\"75%\"], desc['max']], labels=[\"q1\", \"q2\", \"q3\", \"q4\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "alert-chair",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_by_area_quartile(variable, log=False):\n",
    "    plot_data = pandas.DataFrame(index=signatures.signature_type.cat.categories, columns=[\"q1\", \"q2\", \"q3\", \"q4\"])\n",
    "    plot_data.index.name = \"types\"\n",
    "    for cat, q in product(signatures.signature_type.cat.categories, [\"q1\", \"q2\", \"q3\", \"q4\"]):\n",
    "        plot_data.loc[cat, q] = signatures[(signatures.signature_type == cat) & (signatures.area_quartile == q)][variable].mean()\n",
    "\n",
    "    fig, axs = plt.subplots(1, 4, figsize=(20, 10), sharey=True)\n",
    "    axs = axs.flatten()\n",
    "    for i, col in enumerate(plot_data):\n",
    "        seaborn.scatterplot(data=plot_data, x=col, y=\"types\", ax=axs[i])\n",
    "        if log:\n",
    "            axs[i].set_xscale('log')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "intensive-graph",
   "metadata": {},
   "source": [
    "### Area by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "living-jones",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"area\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "difficult-buffer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"area\", log=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "senior-trouble",
   "metadata": {},
   "source": [
    "### Perimeter by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "final-compound",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"perimeter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "upper-orchestra",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"perimeter\", log=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "brief-fight",
   "metadata": {},
   "source": [
    "### ERI by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "ordinary-freeze",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"eri\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sufficient-sector",
   "metadata": {},
   "source": [
    "### Circlular compactness by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "intermediate-think",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"circular_compactness\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "earlier-cookie",
   "metadata": {},
   "source": [
    "### Donut index by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "apparent-julian",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"donut_index\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pointed-today",
   "metadata": {},
   "source": [
    "### Fractality by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "casual-cardiff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"fractality\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precise-flavor",
   "metadata": {},
   "source": [
    "### Convexity by area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ordinary-evolution",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_by_area_quartile(\"convexity\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "armed-damage",
   "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": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}