continents_spatial_partitions.geojson

dask-geopandas-sjoin.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dask-GeoPandas spatial join test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import geopandas\n",
    "import dask_geopandas\n",
    "import dask.dataframe as dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import faulthandler\n",
    "faulthandler.enable()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Dataset**\n",
    "\n",
    "Here, we are using the NaturalEarth states polygons data (but a higher resolution version including provinces, compared to the dummy small countries dataset included in GeoPandas, downloaded from https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-1-states-provinces/):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = geopandas.read_file(\"ne_10m_admin_1_states_provinces.zip\")\n",
    "\n",
    "# for purposes of the demo, take a subset of the columns\n",
    "gdf = gdf[[\"name\", \"adm0_a3\", \"type_en\", \"geometry\"]]\n",
    "# and drop Antartica\n",
    "gdf = gdf[gdf[\"adm0_a3\"] != \"ATA\"]\n",
    "# and convert to Mercator (don't do this at home for global area calculation!)\n",
    "gdf = gdf.to_crs(\"EPSG:3857\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4592"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(gdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now create a `dask_geopandas.GeoDataFrame` from our GeoPandas GeoDataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf = dask_geopandas.from_geopandas(gdf, npartitions=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=4</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>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>geometry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1148</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2297</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3446</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4593</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, 4 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 4 tasks | 4 npartitions>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Created this way, we don't have spatial partitioning information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf.spatial_partitions is None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the spatial extents for the current dask partitions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf.calculate_spatial_partitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    POLYGON ((-6070339.975 -4137670.314, -6527608....\n",
       "1    POLYGON ((-7527629.083 -7542209.228, -7547774....\n",
       "2    POLYGON ((-3040371.644 -8283275.878, -19616607...\n",
       "3    POLYGON ((-7056384.457 -4768442.571, -7066339....\n",
       "dtype: geometry"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf.spatial_partitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ddf.spatial_partitions.plot(alpha=0.5, cmap=\"Set1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a another dataframe of points:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "minx, miny, maxx, maxy = ddf.total_bounds.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 1_000_000\n",
    "df_points = geopandas.GeoDataFrame(\n",
    "    {\"id\": np.arange(N)},\n",
    "    geometry=geopandas.points_from_xy(minx + maxx * np.random.random(N), miny + maxy * np.random.random(N)),\n",
    "    crs=ddf.crs\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Basic spatial join implementation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask_geopandas import from_geopandas\n",
    "\n",
    "from dask.highlevelgraph import HighLevelGraph\n",
    "from dask.dataframe.core import new_dd_object\n",
    "from dask.base import tokenize\n",
    "\n",
    "def sjoin(left, right, how='inner', op='intersects', buffer=0.01):\n",
    "    if isinstance(left, geopandas.GeoDataFrame):\n",
    "        left = from_geopandas(left, npartitions=1)\n",
    "    if isinstance(right, geopandas.GeoDataFrame):\n",
    "        right = from_geopandas(right, npartitions=1)\n",
    "\n",
    "    name = 'sjoin2-' + tokenize(left, right, how, op)\n",
    "    meta = geopandas.sjoin(left._meta, right._meta, how=how, op=op)\n",
    "\n",
    "    if left.spatial_partitions is not None and right.spatial_partitions is not None:\n",
    "        # Spatial partitions are known -> use them to trim down the list of\n",
    "        # partitions that need to be joined\n",
    "        parts = geopandas.sjoin(\n",
    "            left.spatial_partitions.to_frame(\"geometry\"),\n",
    "            right.spatial_partitions.to_frame(\"geometry\"),\n",
    "            how=\"inner\",\n",
    "            op=\"intersects\",\n",
    "        )\n",
    "        parts_left = np.asarray(parts.index)\n",
    "        parts_right = np.asarray(parts[\"index_right\"].values)\n",
    "    else:\n",
    "        # Unknown spatial partitions -> full cartesian (cross) product of all\n",
    "        # combinations of the partitions of the left and right dataframe\n",
    "        n_left = left.npartitions\n",
    "        n_right = right.npartitions\n",
    "        parts_left = np.repeat(np.arange(n_left), n_right)\n",
    "        parts_right = np.tile(np.arange(n_right), n_left)\n",
    "\n",
    "    dsk = {}\n",
    "    # regions = []\n",
    "    for i, (l, r) in enumerate(zip(parts_left, parts_right)):\n",
    "        dsk[(name, i)] = (geopandas.sjoin, (left._name, l), (right._name, r), how, op)\n",
    "        # TODO preserve spatial partitions of the output\n",
    "        # lr = left.spatial_partitions.iloc[l]\n",
    "        # rr = right.spatial_partitions.iloc[r]\n",
    "        # extent = lr.intersection(rr).buffer(buffer).intersection(lr.union(rr))\n",
    "        # regions.append(region)\n",
    "    \n",
    "    divisions = [None] * (len(dsk) + 1)\n",
    "    graph = HighLevelGraph.from_collections(name, dsk, dependencies=[left, right])\n",
    "    return dask_geopandas.GeoDataFrame(graph, name, meta, divisions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Case 1: geopandas.GeoDataFrame + dask_geopandas.GeoDataFrame\n",
    "\n",
    "The geopandas.GeoDataFrame gets converted to a partitioned GeoDataFrame with a single partition.\n",
    "It has no spatial information, so is combined with each of the 4 partitions of the right polygons dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_joined = sjoin(df_points, ddf, op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>index_right</th>\n",
       "      <th>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=4</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></th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: sjoin2, 9 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 9 tasks | 4 npartitions>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check equivalence with normal geopandas sjoin:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "res1 = ddf_joined.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "res0 = geopandas.sjoin(df_points, gdf, op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas.testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "geopandas.testing.assert_geodataframe_equal(res0.sort_values(\"id\"), res1.sort_values(\"id\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing speed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "935 ms ± 35.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%timeit ddf_joined.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.21 s ± 25.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%timeit geopandas.sjoin(df_points, gdf, op=\"within\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Case 2: dask_geopandas.GeoDataFrame + dask_geopandas.GeoDataFrame _without_ spatial partitions\n",
    "\n",
    "Convert the left points dataframe upfront to a dask_geopandas.GeoDataFrame with multiple partitions. There is still no spatial partitioning information, so each partition of the left dataframe is combined with each partition of the right dataframe, which results in 16 output partitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points = dask_geopandas.from_geopandas(df_points, npartitions=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_joined2 = sjoin(ddf_points, ddf, op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>index_right</th>\n",
       "      <th>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=16</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></th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: sjoin2, 24 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 24 tasks | 16 npartitions>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined2.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res2 = ddf_joined2.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "geopandas.testing.assert_geodataframe_equal(res1.sort_values(\"id\"), res3.sort_values(\"id\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculating the spatial partitions doesn't help in this case (it still gives 16 output partitions, no sjoin operations are skipped based on the spatial partitions), because are points are randomly distributed and not efficiently spatially partitioned:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points.calculate_spatial_partitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>index_right</th>\n",
       "      <th>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=16</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></th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: sjoin2, 24 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 24 tasks | 16 npartitions>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sjoin(ddf_points, ddf, op=\"within\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating spatial partitions\n",
    "\n",
    "Let's now try to repartition our dataframes to get useful spatial partitions.\n",
    "\n",
    "For the point dataframe, we can try to use geohashing:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geohash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_points4326 = df_points.to_crs(4326)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 49.8 s, sys: 320 ms, total: 50.1 s\n",
      "Wall time: 50.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_points[\"geohash\"] = df_points4326.geometry.map(lambda geom: geohash.encode(geom.y, geom.x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_points[\"geohash1\"] = df_points[\"geohash\"].str.get(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>geohash</th>\n",
       "      <th>geohash1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>POINT (-5269393.721 7216926.466)</td>\n",
       "      <td>fcwkdg5phsu2</td>\n",
       "      <td>f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>POINT (-11037485.480 3073856.648)</td>\n",
       "      <td>9u9rrfb0umxm</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>POINT (-19159211.757 8105534.817)</td>\n",
       "      <td>b4mtet30r3g7</td>\n",
       "      <td>b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>POINT (-11131770.158 4584255.310)</td>\n",
       "      <td>9ybbk7zmhsfh</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>POINT (-14193620.710 10045869.157)</td>\n",
       "      <td>c5v6fw4b1znp</td>\n",
       "      <td>c</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                            geometry       geohash geohash1\n",
       "0   0    POINT (-5269393.721 7216926.466)  fcwkdg5phsu2        f\n",
       "1   1   POINT (-11037485.480 3073856.648)  9u9rrfb0umxm        9\n",
       "2   2   POINT (-19159211.757 8105534.817)  b4mtet30r3g7        b\n",
       "3   3   POINT (-11131770.158 4584255.310)  9ybbk7zmhsfh        9\n",
       "4   4  POINT (-14193620.710 10045869.157)  c5v6fw4b1znp        c"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_points.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RkpOPnMCaY+mmQFVTGhNbUmBnrK9PUSLtJoocm5qUdWedqz0As7Un3SJMCmFD53hXc7rFmHAkkbiZLbWLLGP9AJwO6ZOegmMgmiqYXjb60pzpZc6E44Hu+thHufLCCzh88CDLZs/igd/+pr9QY6JYzgkto1VIrYaUkoARZkfzsXSLMuFE/Ajgs2d+NsSBdBtGf5XSVNEX5zM0DkhRSDoO6Be/+/2wbQHDxKUlHrNlOQVktnuJWfoywzGl5De7XyJoWHex7eoTB9i4cDXSIpkRnYpIWfDhQGoqXFSVOlMSCW0kOWEwIQporOqmQoh/BD484JgLgVIpZbsQ4jjQQ8QK10eqoBgvZnO3pWZR+lCEwKcnlkw8E/DbHLR68hEyasVaYCi2zGlP24SspooJnWofCXu6h2DxVDeVUn4f+H60/TXAl6WUAyPpLpJStiYrCwCqOnbR6wxECEG+3U1XKLNXicdCVxRenr+KuqLoyn4LKB+A2c7JVwDpRBEiqRkwmBgn9Hirm94K/HECjhsTdVqBZX7AQ1lYPH3sRhmGz2anrqCUnHAA1TQtde0q7VpK4n/ShSklXt1IKtn+RCig8VQ3dQNXAI8O2CyBF4QQ24QQdyUrjJLjQF1clWw3U5IqT6GlEtFLIpHPM9ub2HBoFzdveQln2BrDTIcAp4VCCkZiaF368TIRPqC4q5sC1wBvDhl+bZBS1gshyoAXhRD7o7XmBx8kopzuAqipqRldIgsuxZBIZhVUUuTMpSPQm3E14kdCi07V2E2DhhwPimGABdaiOoXoT0afDkSgG/uBJ1F6mzA95YTmX4t05k34cSSRmTBHgssxJkJFj6e66S0MGX5JKeuj/zYDjxMZ0g1jPKWZjWMT406aSggEmqJw+5JLuGD6EnJsTlxaZk9bD7w96wpKeHHR2fic7rTJM5F0mZKDgSDhNEyIuN76IUV3LyX32S+T8/r3yH32yxTdvRTXWz9Mqt/Tp05x/fsuZ/2KZZy7agU//+lPop+kdwi2hWh1UyGEnYiSGVaxXgiRD1wAPDFgW44QIrfvNXA5sCdpiSwYB9SHqiicXTmXL6z6Oz638irL5IR+p3YxumqtqJA/tXUjUqyAXG/9kJzXvosID56sEGEfOa99NyklpGoa3/ref/DWjl089+rr/Prn93Jg376kZsKSVkAjVTcdUhkV4AbgBSmld8C2cuANIcROYDPwtJTyuWRlsupi1KGYUqJZJGam0+1JtwgTzgKXAxMx6RVR+xCBbtxv//eobdxv/zcimNhKgYrKSpavXAmAJzeXeQsW0FB/OqmZsImqjDqsuqmU8t4h738L/HbItqPA8omQYRD5LujM7LIu8dDo7aAz6B27YQaQG/DR7slPtxgTynUFnpSW5rEfeHKY5TMUEfZh3/8kweUfHrXdWJw8cZzdO3Zy1pqzCZsSLUFTxpJuesVt7fgLAN0weGj/6+kWY0KQQEFvj+UCSL0pdgUovU3xtfPG124kent7uf3WW/jO939Abl5eti7YUKTFCxMapsnjhzalJMXnZCOB48UVHCurslQMkFMIipJYI5UIpie+NDRmTuLpasLhMLffejMfuPkWrr7+eoCkpuEtqYBEghn6MwEpJS+f3MWRrsZ0izIhdDvcvDJvhaXScADYopUwUklo/rVI2+iziNLmJrTg2oT6l1LypU9/innzF/CZL36pf3sy68GsddWjSAvPggX0kGX8PgBPL1tP0G6NmbyB9JgmvSnOTy6defjWfXHUNr51X0Q6Eqsl985bb/HwHx7kjVdf4cJz1nDhOWt48blnE+qrD2uaChYdgkkpsas2VlfM4UR3C7oFaoLNaGtkt3tOusWYFB7t6OZjxQXYBClbkuFf/w9AdLZrgENa2tz41n2x//NEWLthAy3+4ZHqiQYhgkUVkMh1IXutEdLfh4zWXVKFYHvTUUsoH4CzTh5gz7Ray6TgGMiRYJj/aW7nPI+L1TmulOUF8q//BwJnfRL7/idRvE2YOeWEFlybsOUzGooQ5GTzAQ1Gm11KqLHTUiviBz5BrTQEc+phinu6aM0rtJQTuo823eDprkhJnrWe1EV5S0du0lPtYyGAwiQX3FrSB4QiLKV8hjIjrzSlWfYmm66cXEsqnz7CErosWK9OU0TSuf8sqYDC751OtwiTytmV87CpNksEfEsgbLFKqEOxC5jpsN45hk1JV0hPezqOKYXR1otss84QJRYem5OPLboQl5b5AZcCcAesl2StDw2otGnMddhTtiQjlUgp056OY0qhH21JtwiThpQSCbT7e3j4wBuWSdG69theXpm3ElO1liNaA871uLgoLyfleZx6Qz28WvcS7f5WilwlXFB9CR77xDuhJcnFAVlOARE4k7Rd18OEwkFczhxLZKYTQhA2dH61+8V0izKhzGuuQ0jJO7WL6HW6IksyJmpWLFZ+aSlRCWOICUxnEuM4OmCS+rxAD+y9jwf3/YaAfmY95E+3/4APL7ydjyy6M+F+A4EA1156CaFQEF3XueaG9/NP3/hmUv5IyykgpdhDsKuXV9/+Xw4d3QVInE4PF6y7jtrpCxPuV0pJWA/R09tOYX4ZSpI3SN+0+njRFAWHqhEcWENdQq50okqFTsU3/mwAEmYZZVyoL0bHYJdykuNaCz6ChJQYtdollMt8Ks1CfAQ5qDYMPqZk3DLMbTnN3JaI7+6X517NhAcZDFIQEhthrpRP8zTXIkWMaznexPhCIKSBjRAhcab0TYVNHeGriP9LEhjEO6vywN77uG/3z4ZtD+j+/u0DlZBKGAMbIBFIJGJEuRwOB4899zwej4dwOMzVF1/EJZe/j/edf25cssXCcj4gbVYpL77+MIeO7cIwdQzTwOvr4rm/PkhD8wkgYhntPbiFZ19+gNc2PUFbR2RxnpQSXQ/HHKs3t57i/oe/i8Pujql8Bu4Ta/9QKEBndyuGodPYfILW9vqEfAJSMkj51OglfDx4AR8Mref94XOYbZSjyCGzgBIKTU/s37CEGWYp5+uLUFCwY+MscxY3hs7hQ6FzuSS0FCHP/CCFhEvDy7gitIJV+izW6fP5YHAdLmkHSeTYSaALhXFrr9G+x1hKRCgEcLGb5VzHY/HvNwZOAvwz3+IOeU+/TAvsPSOcTfz9x/sr6Q318OC+34za5sF9v8Eb7u1/36d87PhR0dEIM9IiElWY5HkiyjUcDhPWwwghMJJwbVnOAvIFejlx+gCGMfjJbZoGf3nxt3zsA1/jsWfvpbu3HT36Be49uJWVS88nx53H6fojXLTh/WiaHSW6PknXwzzz8gOERslXLKWko6sZXdfJzyvGFt3fMA1ee/sJDhzdjiIi/eV5CmnrbOazH//3cZ1bWA/R1NvR/77UzOMSfSlq9DkiEFyoL2aOWcG76jFa1G6QMM+oxImNDrV3WJ/nhxYyV1YiBtwQfa81VGrMYv4uuBIXDtzY8YogHulAi/50FFRsuLk5uB6AJtHFC/adGCNM0FYZhcw3pmFD5YjayFGlGSnO/IJNRWHgLeeQAT7Eb7mAl9Ew8OPiWa7haa7BQENBMoOjHGIhQppIceaZqsowEoEptOEKRSjUyRq+zPf4X26K5+sf0yoy0Mill4vZSC8eXlY/yFxbG3XEyuAZrwUkyacZiD1ctBFAwSCMk1frXho07IpFQPfz9qmnuWLWDejRPu0EsBNEEvl9CyCImzCRSQ4VHSe9gMQwDNavv5yjR45zx6c+zeqzz44uik7swWM5BdTT2oKq2TDCwwv4hcIBHnjs+wRDQaSMGPlSSgyps3Xny/TV82nrbOSSc2+itLgKCbx3cAs+fySJ08GjO1i2cD3agKlj0zRpaTvNI09HTNwcdz5/d8nHKMwv5Y3NT3Pg6HYMQ+8fVrR1NgMSf8CL2zVyIi7TNNANHZtmxx/wsm3XX9l3YjfUzAMhWKHPRBly4QWC6WYJlWYhD4hX0YTGWfps9ml1MasVzZLlg5TPUFRUyinob1MgY/9kVBQEgipZyAyjhJNqK7qIKqHo7/Os8CyWGNPRUBEIKs0C5opKnrfvwBTgt9l5ceFqDEXptyD+ke8wn/0oUcnd+Hk/D/M+nuYtzmMe+ymmhYflh8illy3yHFopRSCppJ5b+D3fk/86ouLIpQchdaSInJdNhpjBMbzk0CCqzzSUEjshTAkKkhCOQX0qUqeaU1TQAMBV/IV62xUUy5OcFkuQQ241gRkd7ow2CJGUcQQ7ISK5+4Z/rmBgI4iNEJ3++NJstAeaceIljE4IJ3YCEJWmDwc+DDQkAhc99P1yNFVh8zsb6ejs5qabP8ne995jw6oVcR03FpZTQIVV1Rj6yNVDA8HRpnwjX3JHVwuPPP0zbJodU5qDrKmtO19metUc8vNKsGk2wuEwhqnz4usP97fx+rp4+Kmf4HJ68AeGWx19x3lj81+47PybB/mC+oZluh6m19fFo8/cSzDo799HAjafD+HwkC/dIyoPFYVl4VqWyOnY0Vip11Ju5LNTO0Gj2tnfzsBEY3R/1mgKamgbgeAifQnHzeaIbwiYbZRzWG1kmTGj31oDsKFRLvOZbkYUljvs433BFzhKFQoGS9jJXA70K58zxwIPXi7nueg5KHyMX6Nh8AEe4hQ1+HExn/0EcJJLF36Zgy7OPDRUqbOEnaiYuPETknbO4S1u41dIBDbCdMs8fsjXOEEtHnr4Lz6PicJ+lnCQeWyUV6KiY6AyjTq+wnf7+9fQaTUdOPGxkDc5wHr6NLHAYD6bOMC66E0e+f4VdEwUQEFgoBJmHlvxkU8opgICjb7fuqTCFd8sV4mzmIgfLIhksMV5Bomb7n4raCiFBfmcd/4GXn/pRc47a2Vcx42FyMTYhNWrV8utW7eO+PlTP/4eB99+Y9KOL4SgpmoeRUUV1NUfpqWtnkRCrxVFZf6slWw4+++w2xxIadLYfJLW9gZONx3j2Mm9yBjVLzxaIdNz5jOnYA0u4YrbmS37lZjERNIoOsmRDgrIiUvJJIOPIE5sKDGe+PuV0+yrfIHaWdtwOnvH5X7p+9ZH2sWHi1/yafawAr1/2GhSQAf/l29SSCc9eNjOKtbxFjbOPGz6+t7LImo4SS6DHyYBnBynljy6qWJw8KuOysf5I49XvUWJGkai0E0JAkkerQghCUgX9cyjnWnYCFLBYboox0cuebQwnX3YRETB9PguZPq8JQz8nTnxonFm4XVvyMtVT92CXw+M+H25NCfPXPsQHltO1O2soMTp8m9pacVms1FQkI/f7+fqq2/hq1/9Etdff0v/b3Dfvn0sXDh4skcIsW2kisepKs18IZFk9Meimx6TUv6/ePZNhM7GhmS7GBUpJSdOH+DE6QNJ9WOaBvsOb2Xf4ZGVaSx69Q4OdG2hNVjPRRW3ROcuxmelKMA0WYSIzn1MNu4RnqQmJvnlB1m46NWEVmOMtYuTACvYzo38mV48HGUOVZxmKTtQo+edSy/nM6wSVH/fi9k77LO+vhewb9h2Gf37Dl/jaHMxJZVnowiTAprPtJHgFH5msZNZ7OzfXs6JmMdSCZNDZ9RvI6PO4sEPJ489h9sW3sI9u3874vdx28Jb8NhyoucnozNs8dHY2MwnP/lFDMPANE1uvPFarrzyIgzDh6blxN3PQFJSmjnK61LKqxPcd1y0HD+azO4ZgYlBe7Ce7lAb+Y6ShPoYqJDShUBA3kkc3ipCnpGqOSWOguQCXul/v4D9E36MoQjAhkEtxxBGHVKuRgyZ6k9M2ZrYGNm6AbhjUWQB6m/3PTTIEnJpTm5beEv/54mwdOkiNm0aHoOm673pU0AMKM0MIIToK80cjxJJZt+/eQyp47ZNfHRrqqk48FGkCBPyNHJq1X9hOrrTLVJCKIoL0xw8CyWljtd3gFzPopTJcceiD/PBudfz8qnXaQ20UeIs5uLp5/VbPhNPeiOhY5VmPidGu3XR8jv1wFellO+NY99xIWPO91gP0T+YylxENPBNSAeOnmqmbf8ip9Z+O91iJYRpDg7TcNgryM8/G5stMQs1GTy2HK6ddUVKjjXUuhsPE/Hrjac087vADCnlcuAnwP+OY99IQyHuEkJsFUJsbWkZfb1X3hiVU62CjP5nFQQqzt5qCGfqItszPhmHo4qysmtxuaajaS5LLkTtQ4jEV/qnpDSzlLJbStkbff0MYBNClMSz74A+4i7NrFqswuZICBRUYa1zlcLA4a1KtxhJEww20tP7Xv97K6xFHIl0JyQbszSzEKJCRKUUQpwdPW5bPPsmQnerdVfED8ShuNLqQJ5oQu5GvMXvEcw9NXbjKY9JZ+fbdHVv7w96tSqKkrjFmvTjU0qpCyH6SjOrwK/7SjNHP78X+ADwGSGEDviBW2TEJo25bzLynNi1AyNszaT0fczKXc78vDXYVdfYjTMAU4Q5vfLH+AsPIoUJilVuWJPOzrfo6tpCRfmN2O3FKTtyyAxxInACn+nHrbiY4ZyBXZnA1f9RhFDSq4Bg7NLMUsqfAj+Nd99k2LkxuTIhU50VhRcxO28F2iT8mNJF04Lf4yvcD6pVFM9gpNTp6HiTsrKrEWLyJw129e5mt3cPujwTVLm5ZytLc5awzLM0qb4Nw2DDhiuoqqrgsccewGYrSvsQbEoRCli3JrxdcTInb5WllI9EIkzVssongiQQPE2iCzbHw67e3Wzv3TFI+QDoUmd77w529e5Oqv+f/vSXzJ8/FwCbLR9FSc6GsZwCWrDuPITFMuv1kW8vwZAx8vNkMAJBfsN56RYjJUy2Izpkhtjt3TNqm93ePYTMxFwUdXX1PPfcS9x++4eAiGWXLJZTQAvPu5CiysyfRYmFV+9GSSLmYqoiDOslbB+Ky1U76cc4ETgxzPIZii51TgROJtT/P/7jN/n3f/+//WlqDMMfc63ieLCcAlI1Gx/57n+nZKydanx6Ny2BU5gWm1UJO9ssHTeqKC6KiybfyvOZ8bkf/HG2G8gzz7xIWVkJq1Yt798mpYmu94y7r4FY7y4FNLs9FcPttPBW8xMEdGtV/chpX4gwJ94KEkLF7apFkE4LS6Gq8hZUdbKWQZzBrcQ3K+qKs91A3n57M3/5ywvMn7+Gj33s07zyyhvcfvtnMYxAtixPLKSZwYXglNGTVDm01FXYTAVC2ik6ct2EW0FSGvj8x5CMnB9qssnLXYmqpuZ6zXDOQBsjMFUTGjOcNePu+9vf/heOHHmXAwe28Lvf3cuFF57Lb35zN8leNEsqoFN7k/P0pxNF1SCG8lSFhipsnFv+fstFPwOYit+SVqvTOT1lgYh2xc7SnCWjtlmas2TC44GkTFzBW+6X3NnUyKP//o10i5EwphHbiVjlmsOq4stwWsz66UNqoYSqaUx1Wtueo7TkahyO0pT4JfvifIbGAWlCm5A4IIDzz1/P+eev739vGAGUBJWa5RTQ9uefwtCtNVUNcNp3iJmeJeTJYnK0/NSuLUpBcoGyg7dQeOoSTq35T3Rn++QeLIUUFKxLmfLpY5lnKQvc8zkROInf9ONSXMxw1kxKJHSEbCBiP50NE5/UaipgYvBmy+PY1fhTsE4Yk3y4SFoRFc1fStWOz03uwVJIXu4qctxz0zIja1fszHXPYZlnKXPdcyZR+ZCUj8tyCqh64ehj4Eym3DkzPdPVKfLnK6g4eqejBYpSc8BJJjd3GYpi5RgngaZ5kirSaTkFNGvVmnSLMGlY0fk8DGGi6JmaD2gwifpFMgOB3V6Epo1cVioeLKeA3AWFY0xjZy5NgeP9xQ2tQKxkaqYaJJTTmAZpJp5g8HTSkcJTF0k43Jl0ojXr/JqjuDy5VC9IXf7dVBI2g2xv24huhi0RDS2VEDJalUGiY4ogDUt+Fan/bAHaO95ESj0tSsjs6aXn8afp+OXv6Xn8acyeWPXpkkNKA8NIbvG3JW36S+74DPd/dfKcmZrdjh5KT86ho727aA3WMyt3GXPyVqFm8Now3d6JFijhzPy7QvGRawjmHcewJxfiPxXQ9U7qG/5IUeF5uN2zUnbczl8+QOevH0T6z1TFaPvPn1Jwx4cp+ORHkup7/vw15OZ6UFUVTVN5++2XgawTehBHtm2e1P433PyxSe1/LLrDrRzp3kGmL6CyBcpQomWaBSqKtOHqrqVqxxfSLdqEYRhefP7jKTte5y8foOPu+wYpHwDpD9Bx9310/vKBpI/x3HOP8M47G3nzzeezQ7BY1B+c3Ko+u15+flL7j4devTPuihgVX1+DyJt6DtFY6WSFtOHsnonmT30liSGSTFg/uZ7FE9TX6Jg9vXT++sFR23T++kHM3olbSyilkVSktyUVkN01uQv/Ok6nL2exgkKurYhy1wyMeELgNUHv5kYwMscZKoWOFkp3vbNkrUuFvNyVVFXegt1eNiESjYV346vDLJ+hSH8A78ZXEz6GEIJrrrmF9esv5777fg+AnsTi6FSVZv4w8LXo217gM1LKndHPjgM9gAHoI9WQjpdwIMDhLW8n08WUpdazlBVFF0fy8Ao1Zp31YeiS3pcyK8m7QCHoOT12wylMWdk1OOzlKY0D0lvjiyA3WhKPNH/55SepqqqgubmVq6++mfnz53DeeYmnGknaAhpQXvlKYBFwqxBi6DTUMeACKeUy4NvAL4Z8fpGUckWyygfg+M53LVUpoo8yZw2rii/FrjqxKXZUoVqm1MvA6XhTCdI892GkmrmFBRyOShz2spQHIWol8QVwqqWJB3pWVVUAUFZWwrXXXsmWLTuSivSeiCFYf3llKWUI6Cuv3I+U8i0pZUf07SYi9b8mBcPQCadphmoyWZi/1lK5oAcjCebU0Vu8i9Mrf0xXzcvpFigpHPbypKqFJkrOpRcgXM5R2wiXk5xLL0iof6/XR090Ot/r9bFx46ssXjw/qVxHqSzN3MedwMDSFRJ4QQghgZ9LKYdaR+Ni5rJVYMHgr2O9u8mxFSKQ2BUXdnX0H1omIVAIeE7RuOznllgNrxtepDRSroSUXA8Fd3yYjrvvG7FNwR0fRvEkpjCam1u4+eY7ANB1nZtvvoHLL78kKQtoIhTQeMorX0REAZ07YPMGKWW9EKIMeFEIsV9K+VqMfe8C7gKoqRk5oZLT40EoSmYnJIvBSe8+Tnr3oQoNKSXT3HM4u/Qqy1hFdn85SAVE5l83v/8oUp6HlGbKF6L2xfkMjQMSLmfScUC1tTPYvPmlGJ8k7rCfCAUUV3llIcQy4FfAlVLKtr7tUsr66L/NQojHiQzphimgqGX0C4DVq1ePesbVC5dy6r2d4z+TDKCvKsZp/2E2tfyFDWU3WMIXZDi6EKYNqQTTLUrSSGnQ2PQ4pSWXY7MVASKl16jgkx8h79Yb8G58FaOlHbW0iJxLL0jY8hkdiUhijWKqSjPXAI8BH5VSHhywPUcIkdv3GrgcGL2uSBxc8ZkvotqsvAoZTGnQ4D9KwMjs/NB9Dmh7dzVSsU4eJ13voKHxT4RCrWl5QCieHHKvv4qCT36E3OuvmiTlAyAwzcSvW9IKSEaKA/WVV94HPNxXmrmvPDPwTaAY+JkQYocQYmt0eznwhhBiJ7AZeFpK+VyyMnmKiimosGZpnoEoqARNX7rFSAqBQGKihQooOHURQrfGkLIPw/RaeEEqRIZfiZ9fqkozfwL4RIz9jgLLh25PliPb3qE9jcGCqUJi4tEK0y3GqCgeG2bv6AGTAgUhFcoOfBhX1xw6al4gkHci42vEu1y1OJ3TsYRnfRQMI4Ca4KSIJSOhj27fajkndCyEFFP76SoYU/kMbi7Ia1xLzeZ/pvjoNZMo2OQjhEpJ8aUoQrOEj240zAQrrYJFFZA7Lz/dIqQEnTD7uyZ34W1SJDw5IkBm7ip/AIejinQuFg75DQ5s6mD7Cy0c2NRByD+Z1mR6Z8GmHEsuuowtTz76N2EFHe/dw9IUVN1MJVLR6S3fOnbDqUySq8STYccLLezc2IoeOiPDpscaWX5pCSsuL02q787OLj7zma+wd+9+hBDce++PWLdutLC/0bGkBVRYUcWVn/8KWCh74EiYU3kIlgASk47pGwnmnUi3KEkRCNYnnaoiEXa80MK2Z1oGKR8APSTZ9kwLO15oSar/r371G1x++UXs3PkGmze/xIIFc1GUxINiLXuHLtxwAfM3nJ9uMSad2tzk6zxNJULOFlrn/TndYkwAJs0tz2CaesoUUchvsHNj66htdm5sJRRIbDjW3d3DG29s4rbbPgSA3W6noCAfLYladZZVQKf37+XAG6+kW4xJRRM2lhSeO3bDDEEiMe29CNManoFQqAGv91DKnNDHdnYPs3yGoockx3d0J9b/sROUlBRz111fYu3ay/jMZ76C368nteTEsgrozT/9Pt0iTCouJY9rpn/GMknqJZLmeQ9xas33kBZYjtFHT8+OlFlAvu74AgLjbTcUXdfZsWM3n/zkx9m06UXcbhf/+Z8/TOr8rPHrjUHT8aPpFmFSWVl8EXbVlW4xJgx/4QG6pv8VqYZBsY4CCutdGCmKVnfnxWc5xttuKNOmVTFtWiVnn70KgBtuuJodO3Zlp+GH0tFwmpAvs5cojIUjiWqUU5GuqjeQivXSqIBBa9sLhMMdYzdNktrleWj20Yd7ml0wc0VeQv1XVJRRXV3FwYOHAXjllTdYsGAeyUzDW1IBbbzvnnSLMKlowk6Jc1q6xZhQws7kZmemMsFgAw2NjySVujQe7C6V5ZeOnkt7+aUl2J2J+2x++MN/5/bbP8eaNRezc+ce/s//+fukfEDW8PYN4eQea66E70OXIY737KU2d4klomwlEjWUZ+kVC1Lq9PTsorBw3aQepy/OZ2gckGYXExIHtHz5Et58c3BRhmRWw1tOAUkpJy0IrLBqGh31UyNX8Za2Z+jV21laeH7GKyGBQPUXnykPZklMgqHmlBxpxeWlLDq/iOM7uvF167jzNGauyEvK8hkZEc17lFjfllNAdfuSzuYRG0VhzdU38vJv701bUcKh7O/aTKG9nOmeBekWJWFM1U/dyh/hzz+WblEmGQW7vThlR7M7VeatTc1C5WSef5ZTQL7Ozsnp2DR54Rf/Mzl9J8j8/DVU58xPtxhJ0bTwAQL5R0G1Ti6gWAihkpe7LN1iTDACRdGyPqCBzFx5VrpFSAkChcX5GzJ6+CUx6SnbjLSs8lEAE7u9jKKiC9C0xGafpjJqkrOxlpsFc7jcrPq768ZumOFITDpCTekWI0kE03Z8EczMXvkeCyE0qqfdSc30z1BZcROOFBUnTC2ScLgbw/An3IPlFBDARR/7JJd9yjr1xUfilHdfukVICoHA1TmPvIbJnRlKBw5HNULIlCel78MIm7TWBWk44qe1LogRnqzgTomu9yQcDW25IVgf5bVz0BwO9GDmJzkfCSOJmtxTBcW0k1+/ge6KTaDqCMOGVMIWmA1L37VpOOKn6Zgfc4AIdfuhvNZF5ezEo+cPHjzMRz/66f73x46d4Bvf+Ee+8IVPEUnLOn5LNlWlmUX086sAH3CblPLdePZNlKLKaTGn4x2KTpmzF59uoy2USKJuiUPRWV9ynFdbZmPKsZ9wqjAwpUAOMTgVTFYUnmZxQQs7OyrY3VkxrM1ICBRKndVIKfv9QBI5qCpsrPeRfQXNWjs/L/8zWz3voUqNi7vWcGfzDbjk+FIrhESY/zv9p7y//RLW9kacrK/kbeUPJc/QpnUyOzCdO5tvYH5g5oh9OLtmU3TiCoKeUzi7ZuEr3Ie/ZP8ZuWVUajH4ekpToAfz0Bw9iCHLN6QceXYm1md9P5WxXGrx9hsIjByuMVYfeiAPPZCL5vCiuTqHtzFVpFRQ1OHZJhuO+Gk4PHxIZBr0b+9TQtJUkaaKUHXEKOvvpKlihN3MnrGCTW+9ilDDGIbB7NkrufbaK0kmfiJpBTSgNPNlREr0bBFCPCml3Dug2ZXA3OjfOcA9wDlx7psQNqeTc95/M289/ADVzg66Qg7m57ewruQUhhSoQtIedPHYqcX4DMd4zphcW5AVRY0gFF5rnomUAhOBgsREwamEWV7YQE1OJz1hO17dxluttRhD9KGJwrHeYi6qOM4F5ceoyenk2dPzsKmSHC1Ee9A1QCEJzoS8C1yah+k5Z6bfw+hsdb3H2f4lqKjDlE9kL4GOTkjR+WLtf9Cl9iKFBHReKHibI846fnjiqxA9khLHjypEmJAI851pv2BGsIpCPZfdOYcJKZGbY3fOIb4248d8/8Q/MDdQg08J8GzBG7zj2U2Rns917RexMFCL2Pd+jgVMvKbE4TmLgjW/wV1yhGB3OaHuSjzTdgw7tpQqxzf+M1J3UrL4CYrmjV1RVZoKvpY52D0t2HLOLI+Ix5cvZWR/iUAII/KNKjKyzbDRtPMDlK98CEU1AJOWlucoLb2KSOmaPutgZCtBSjDDTjqOnd2/TXP0kj9jy6B2QjEQMRLBG2GTpmOj+2Oajvkpm+FE1RSMkBtQQJcgTDRHb8x9hGKCVJCAEXahSIW/vvI8tbUzmTFjesx94mUiLKD+0swAQoi+0swDlch1wO9kZKC4SQhRIISoBGbGsW/CrL1oPasOfAN8bXSFbOTbg9gUk76CPSVOLzfWvMdDx5YSZmgZnzM3+0AUTGrcXSgCVhXVU+tpZ39XKVLCrNwO3m2v5LLKw6hCoojIj6o77ODt1pkxZew7il0xmeXp4OYZuyhz+TBMhfuPraQ7HHlaTXfPoy14lLApqM6Zz7KiC1GVyOXb7zzGd6p/SbvWiU3aOK97FR9ou5SZoeHLNcJC58+FL+JXglHlE92u6Bx3nma/6xgL/LU8XPQc13dcjFOOrpy9ip+DrhNIITnqqov5MAyKEPeXPsnXT9/JF2q/R5vWGVFQEl7L28q83jmcffDD5BiRmuXBnnJ6Xv0y0zb8lMattzHj4u/FVBDSsGFzdRJon0XL7vejOnrJnxFJUWsatqjFJFFUAykF0lRo2X09HYcvxl1yhJoLf3imr1GskjONVOpe/wKm7sTQnRTNfQlnwSkCHTNpP3A5YW8J3SfWUnnOfXQdOxfdX8ipin1UrzyK3a2ghS/H8M6lYMa7wwowSglIha5TK0GeuS31YC7epgUMqz0gwdBdSMNGRBHqdDR1DBp2xcI0oO20pKjcAwMfbqNZ8nLgFyMwdQd//vMTfPCD15/ZP0FSVZo5Vptpce4LxF8ZtZ99T8Hjn8Ie8oICpc7hU72qgFKHlzUldbzVOhMQTHN1cUnFYUocPt5sqWFbezV6ND+xQGJTDFYX1/X3UWgPsK40cgpSwpVVh6Ly0v9vvj1Ini1Ie8jFwIulCYPFBWeiY1VhUub0ogpQVQMtqiDm5zVzacV2HIoPiYtufRq9RmSoVG9r5usz/ptAdCFnSIR5OX8zB5zHufv4P2OXgxVrSNF5qOTZmNMPEjjsOMUjBRvZlLeL2lA1y7zzcEgbSowdJJJHil8cpMhi/hYFHHGe4tGijTTZ2jD7bj4ROeYBz2GOLv8Pbtr1f8gLRoL1pOGgadtHMEJujFAOmqtzmIIQapiwt6S/fevea8ifsRnTVDBDHk6+8mUKZr2B3dOMt3kB3cc3YOqR783XMg9Tt6FoYUxDjQ7hRnekSlMh3FtO2FcCSJq2fWx4G8NJ/Vufpc+GDHZX0nlsAwvOA7ttDgDd9YvIq3oPGb2xhZAEusvpbVyIHGqNS5VAVxWewsHll4xQDlIq/V+4NDWCvvhu53BAMPwHIDANO4o6NMg2sn0goVCIp59+gf/3//4ZECjCnrCzPVWlmUdqE3dZ5/FURuW1H8Br3wc9MGoziCiI+bmtbGqdQZHDx401e7BF/QkbSk9S7PCzta0an2Gjxt3BhrKT5NpiR0KP9gR9//Td/OH4CsKmRlgq2IRBicPHWUVnfAUCUAZcx2UFDZz25/G+ykP9Mgm85Gl/whAh/uyp4c/FLxAQg+WRQlLnaGK/8zjzAjU4pQMdA10Y/LjygchvL8a3r2Pw+9K/0KN5QcK/Vd/DAn8t13Scz7ndq7APsRJ1DJ4pfGPU77ePsnAxjxZvPKN8BiIgrAbZVv08Fx35UP/msLcMoYboOHQxFasH53cydRs9daswgmdia3R/AdJU8bfMoWHzHej+Ilp23RRbIKnQ27gIm6uL3oalFC94DqGNXMHDNBWC3VVR5TMWgv4v17Rhhm20HMlhWnTEHOyaRpvfg93djam7CHmLx2GBnPEBDb2ANnt8t7PNHnsYaIadCGEiBpRDMg0NUx+sFF/Y+AIrViylvLws6ovKjeu4sUhVaeaR2tjj2Hd8BLriVj59FDkDnF1yimK7D3XADSIELMxvYWF+8iu18+0hPj13M0d7C2kK5FLl6mZGzvCn+kBWFtUzO9zWr3z6UEQQl+1hflNWiy+GIzIiPPzf6T/h7zrP4yzvIppsbTxZ9ConHQ39nw9SQhIMxaBH8Z75HNjvPsYB13EUFNb2LEOTGoYwMJH86/SfYcaRu8du2ljuncthx8mRGwnJ6byDQzciDTtdx86jYM4rOAuilqZho/PIBTTvvnFQa6nbOPj4fw+3ImIfkPq3Pt//Ltg5naq1v4x8oujR85dIw4aUCkYgn9NvfnbQ/vEiTehuCTJtQd+NKjBDBQRC+f3vR9kbm7sdOHNOcoSKIfmlOdQfbsM0R34+K4ogv3SkyReBEcoBYSKEiTQVYpnKjzzyZz5w4wcxQm6kqeFMYo3ZRCig/tLMwGkipZk/NKTNk8Dnoz6ec4AuKWWDEKIljn3HR9N7oNpHVEAjjfU3lJ5EN0GZxOlfIWB2bgezc+PLDaMIKLDHDiPQpImNAKM5NcOqzv8W/5X/Lf7rCAIN6dNQ0NXhCkUKyX9M+w3z/DNY7p1Pr+rl9bx36VXjC0BTpcIu96ExlZU7HCtSOCLkiRf/hcK5fyW/9g166xfT+t77Y5TuUZFGYjdDb/1Kjjz9PXKnb0XRgngblmKEcnAUHkP3lhDsSq7AoM0Zy8KJpz9B2FeI3Qz1O4KlqcbcV9UUSmsKaDo+8u+rtKYAVRtjuCSVqIU1HJ/Px8uvvMx//+gnSFPD4bYlFY2ftAKSUupCiL7SzCrw677SzNHP7yVSNfUq4DCRafjbR9s3KYE85WCMbEqP9l2NdV0mm/FcR5+i0KNMoMCCmMpnIAddJzjoGn+1Cr8a5ID7+KhtFEPl/CM3x5y9i6DScehSOg5dOu7jx4sRzKPz8MWDtun+5Bd0KiqUzUymNruKNGzowbGHOuUzCgBoOdk5yBJSFEFpTUH/54nidrs5eTTiA3V57KhaclHsqSrNLIHPxbtvUhTPhsrlcGrThHU51fALwU8K8zEzeB3YQAp9lVxy6CMU+6tGUD6Zi1Cgcl4ueaXjCfVIjvIZBZRMy6OrxUs4ZGCzq+SX5oxt+YyTcMiYGgpoynHRP8Pvrk23FBNK37OsVVH4QVEBz+R60irPRJHnL+GG3V/CZjosp3xKZ7iomJuLZku9aa1qCkWViTuH40EPGZBkZmBrKiCLFeuDMyN+j5TsdqbuaTrZrDx9KZpps5zyAXDm2lA1653XRGLJxahMW5VuCSYNTUqu67FOwv2y3hkoCawhygTa6nxjN/obx5oK6MgIsz4WwAbkWajmfaerCTPGsgI5RlBgJuDr1NGDZlpKNKeKcCi5XE7WHIJt/Ld0SzBp6MBeuw3VNDGESC4f5hRg+7SN1HQuRjHPRNtKJCYGaob/PBVVoNqUtCSNC/q9HNu2CV9XJ+78AmrPWovDlcxM3AjH8YVRVQVFTV8k9NSjc/xTxZmCAOaHwmzXDRo0lVCGK6BWTx3Pz/8V5x39IJ5QIRKDA6VbmN+yJplyU1MCzaFErZ/UXqN3n3mU7c89PigVzZsP/4aVV9zAqqtuHGXPsfnpz37C/b//LQLB4kWLuefun2NzaDhcWQUUwTRBc0LYmuPv7xQX8hdPDoG+GKC4VlFObeoKDvDHld/GZjgwRJiLjnwETdrH3nGKEw6kPifQu888ypYnHhq2XQ8G+7cnqoTq609z789/xpZN7+JyufjY7R/hkcf+zO233ZawvNbzAe36ExhTo2rFRNOoqjzp8ZxRPpDxyqef6HqwFfWXMqfNGpMI0gRDlynzAQX9XrY/9/iobbY/9zghf+IPZ13X8Qf86LqOz+ejsqIS1Zb4JIL1FNCWX4JpzSTn+xx27FYMMZCCme1LuPDIrdR2LEUgLOGEduVpqJpImQ/o2LZNY2YA1YNBjr6bWJBuVdU0/v4LX2LR0vnMWTCL/Lx8Lrn40qQCHK2ngMKJJ8ie6lTqesTxbCEUU+Hv9n6Wiw99lAUtayn2VltC+QAEenVaT/pSZgH5ujrjbJdYnfqOzg6efuYv7N6xl0P7juD1eXnk8YeTUrDWU0ALrk63BJPGglCY2nAYzULTunPazqK8dwZ2M5KnR0FBRP+bUNKgt6UJDYd7aT6Wmrgtd35BnO0SW9/2yit/ZcaMGZSWlGKz2bj2mut4Z3NyS56sp4DKFmDF0+rj3sYWVvsDqJNYgjqVzGldhc1MQWR3mr4qaUDjES9ylBQZE0XtWWvRHKN/l5rDwaxVaxPqv7q6mi1bt+DzRay6V159hYULFybUVx/Wu1Md+WBPcoHKFKVdUfheUSHvuJyWiAEC0JWRMxdYBdOQGPrkKyCHK4eVV9wwapuVV9yA3ZXY/bFm9dlcf+31nHvhes5ZvwZpmtxx250J9dWH9abha8+L5D+wGDrw0apyTmsa0gKKp4+95W8xvXNBaqygNCEEKVsT1jfFPjQOSHM4JiQO6F++/g3+5evfONNvdjX8EDQHXPMT+PPwfL2ZzOtuF02qajkndF3+fvZUvM6y+osG5Z220uJUzaEgJjPT3RBWXXUjSy66kqPvbsLX1YE7v5BZq9YmbPmMRrIzfNZTQAC+1nRLMOEcsdkIWkz5ACCg3dWAVAyEBUs0A4T9Jo1HeqmYnboUKnaXmwUbLh67YZIYujmoNt14sZ4PCKBhZ7olmHCqdGvGNgGsrrsCzcz8yOfRaDzcS1dz/HnKMwXTMNHDiUd8W1MBWXAZxqVen4UGJYNxh/PHbpThSBOajlonjcpA9GCaFJAQokgI8aIQ4lD032EBBkKI6UKIvwoh9gkh3hNCfHHAZ/8mhDgthNgR/bsqGXn6KVscyYVpIezAd1tacRuZXw9+KG3ukcsYWwk9aL0o9mRJ9i79J+AlKeVc4KXo+6HowFeklAuBtcDnhBCLBnz+IynliujfxOSGrj3XEjEyQ7nK6+fVU6dZHAha6vw2zXiSsGLN9Xv9CMgtSd0wUwZ0gjtbCLxZT3BnCzIweUN4JY1LMa4D7o++vh+4fmgDKWWDlPLd6OseYB+RiqiTQzgAf7yVjM/lEAMBOCXc05R8nbKpRGPeUf6y6G7q8g4SUH2WWYrRT3QaPlVO6MBb9XTdvQv/sycIvF6P/9kTdN29i8BbyZXcA/jZvXdz9rrVrFl3Fnff81MAjDT6gMqllA0QUTRA2WiNhRAzgZXAOwM2f14IsUsI8etYQ7gB+94lhNgqhNja0jLKDbj/afAnttYlU3BJk/lBa1kMTZ7j/GXR3bw47zeWU0CaXTBvXRG2JAr4xUvgrXoCr9VDeMhwL2wSeK0+KSW0d+97/Pb+3/DKS6/x9uvv8Nzzz3L4yOFRCyGOxZgKSAixUQixJ8bfdeM5kBDCAzwKfElK2R3dfA8wG1gBNAD/NdL+UspfSClXSylXl5aWjnygg89adjV8HwYCVWCdYZiEQm8FV+39NFfv+2zMOvSZjB6MTFNP9nIMGdAJvN04apvA243IBJ3GBw4eYM2aNbjdbjRN49wN5/LUX56c3MWoUspLpZRLYvw9ATQJISoBov82x+pDCGEjonwelFI+NqDvJimlIaU0gV8CZyd8Jn007Eq6i6lOWAj22+2WWIoBgIAOTyMb591Pj619XLs63CqafXIVlpgAw+Xwlg7Ck+yEDh3oGG75DCVsEtqf2Ahh4cJFvPnWm7S1t+Hz+Xj+xec5fboOuzPxcMJkr9yTwMejrz8OPDG0gYiox/uAfVLKHw75rHLA2xuAPUnKY8mSPAORwP9noaKEAwlpfh5a8f/RbW+Le5+gz0APTe41lxMw8RgOGhj6JMvZG9+6OulNbPi+YP4CvvzFf+C6G67mhg9cx9LFS7Hbbdgc6VNA3wMuE0IcAi6LvkcIUSWE6JvR2gB8FLg4xnT7fwohdgshdgEXAV9OUh5YaN10HH18tbOL5YHRE09lJAJQJA15R9ItyYSSV+agal4uTs/kLjwQHlt87XISn437+Edv441X3+b5Z16ktLyEBYsWJNwXJLkUQ0rZBlwSY3s9kVrwSCnfYIRsLFLKjyZz/Jic82l440cT3u1UQQBlhsnPG5u5rrqSJlW1zlAMMBWDbdXPM781+dH4VMDhVqmYnYM7Pz7lkAz2+YX4N54afRhmU7AvSLzefUtLM6WlZZw6dYrHH3uct95+O+G+wIqR0CfeJC3Zp1KMJiU3dvdaSvn04XV0pluECSPoMziytQPTSHy9VLwIp4ZzXcWobZzrKhCOxJ1aH/7Yh1i9dhUfvPUD/Nf3f4RDdSU1tLTeYtT6nVgxBmgoDuAcv5+fUZBuUSacAn95ukWYUKQp6WwIUDx98vNUOddXAZHZrkGWkE3Bua6i//NEeeHZjcO2BX0h3HnOhPqzngLKn7wYx6nGopD1knmpho21J65NtxgTimlAKJC6yRHn+iocZ5UT2t+B9IYQOXbsCwqTsnxGwzQlpilREkg5Yj0F5Bk1FtJS2AGXaeJXMnwkLUFIhYJAGeuPvZ/p3fPTLdGEoqgCd35qbzXhUHEsL0nd8RLcz3oKSLV2WoeB/Ck3B3+G+4A03cHak5GZyxkdS8gNFaVZoolFKODIUckrtXLGR5FwwjXrKaCademWICW843Twg6LCzHZCmwIpTDbV/AWE5O2ZT3D2yatZ3nBRuiVLGpszYpUWVbkon52TlvrwqUKzJz60s54CcheB3QOh3nRLMuH0udZ9QnBffl7G14UXAowhSek3T3+a6q55FPsy25c366xC3HmTP/We6WS482AEpidWdmSqc7RoOj8szOfrpcW87XJmtvUDIIfLbyo6B0u2pkGYiaX+QA+GbgwqSpiqAoUA6AaiqRtR145o6gZ98vJI6SEj4XOzngUEcP5X4cjw6cJMZ7vew/3F+ZYJMpBi+MyQRA6zijKRntYQuza2gAR3vo3pi/NSEowIIOraUU53IAYsfpXHBea0QmR14j62EydPcNPNN7L57cEPCCllxDxP4HloTQtItYGWWFzCVMUAGhWT67p7cJsWWe8W4wermXZq25enXpbJIHr/+7rCHHqnnZB/8rNZirp21FPtg5QPgDBlZHvd+Bb7xn/gxHazpgIK+yNKyEJI4FOd3fxTeycbT55mUdBCa8Fk5E8xVUp6q6nqnpNuiSYc05Q0H5/knNC6gXJ69JXuyukOSCJyWTd07vrMJ1m74Ww+8vEP4fP5sDm0bFWMQVSvAatYCUTuTw2wATlSkislP25qtUY+IAlIgU13srzuEq7d+wVL1QTrR4K/Z3LzVIk27zDLZ1gbUyLaE5+gOXToILd//A42vbmZ3NxcfnnfL1CTSMlqTR+QzQlnfxLe/HG6JZkQYt2O+aZJha7TaMtgS0/C2mPXMbftLNx6njUVTxQhwJ03ybdbOE4FF0pcEVZPq2bd2kioyy0fvJV7fv4zQgEdzZbYVLw1LSCAknmgWssPNBAJdKmZX8jv3eoXcekeSysfAKEKSmfmTO5BbHEqOHviinDoUEsIgZnEaMPaCsiwXiG4PnoVJeOjoAFKvdUIC/8MEZBbbGf+umLsk5wTWhbnIMeISJaKQBYlnhz/VN0p3tkcSen+50cfZt3a9ShJLAWy5pUPB+BPH0q3FBNK1E+LTmRG7JvFFliyIGBR07mWtn6EAlXzPZOejAwATcWcNnquH3NaISThs5k/fwF/+OMDrN1wNh0dHXzijk8mlZLVmj6gfU+BvyvdUkw4ElCJ+IT+o6WVz5SXssfpyOiARJc+ycOSNCMNJj1n9aDjVRdhwPA4ICX5OKAZNTPYuundYdsT9f+AVRVQ6wEwLDRNTUTpDFQzBVJyf2MzPyrM54GCzC1tfKD0HSp7ZllyGObK08grdRDw6thdqbvVZHURRkVBZLYrpINdiwy7krB8RiPRVByQpAISQhQBfwJmAseBD0ophwUiCCGOAz1ERg+6lHL1ePYfN2ULQXODbr0a8QBHbRoH7Xamh3Xe3+vNaAUkhSSo+rAbLhQy36nex7SFuZRMdyNEmtLjaQqyLC9FB0swDJrkLaC+0szfE0L8U/T910Zoe5GUsjWJ/eNnwTWgfHHsdhlGGPiHshLedjnRiGjzTK8UX593mAdWfZvqrrlM65qHK5zLrPblGV0bLKfQRnG1C0WN3JSZO0COD9OQJOqHTlYBXQdcGH19P/AK41Mgye4fG18b6P6ku5lq/KIgj7ddToKKQv8AM8ODEXsdnSAkx4t3c7x4N5phw3+yi6WNF6ZbtIQprHT2K5+BSDn5eaHTQTiYvjigeEszS+AFIcQ2IcRdCewff2lmgG2/sWRa6EdyPQSHPmoy/QctBl8oXQ1zrHB3moSZIPqmLIdulmAa1onQ72NSk9ILITYCsVLt/8s4jrNBSlkvhCgDXhRC7JdSvjaO/ZFS/gL4BcDq1atHVy/N+0FarzyzfZJL+04VKnsyey1Ye0OAomoX6lDHrITOpiBFVa5JlyEYDHLw0H56vV48OTnMm7sAh2PqZWUcUwFJKS8d6TMhRJMQolJK2TBaaeZonTCklM1CiMeJlGB+jWhp57H2HzfT18C+J7GaGfSttnbuqihDZrrVMxoScgOZHePk6wzTcsJHWTTyWSIRCE7s7qRiduJBgPGyafNbvLNlE+HwmbQmL7/6EuesWcvas9dP+PEUNX2BiPGUZs4RQuT2vQYu50wJ5jH3T4ja80lE+UgJx8wKHtQvQZexv5pUuFxGOsaaQDByVv0NJkYRTbVAQFPRIS+EWN6CWNQG9vG42uO5QJLh46Shr0f4K/SDag5oL6PDyMHHbTjYy/43W2k42EP9/h7ee6UFza4kFZAYz42+afNbvPHW64OUD0A4HOaNt15n0+a3Ej7+SDiSCDFI1gn9PeBhIcSdwEngJoiUZgZ+JaW8CigHHo863zTgD1LK50bbP2kMHRQNzPENw/5Hv4GfGdchERjAB9TXcYvBdbTjNT6kHJ97JiBtKJiclOXMFI1oDB9X61Kj5/A/4Sx/ihmlBlXOuWzveh6DkRN4ldhrmOlaRsDoJV8r44B3E63hkwDUuBZzS+W/8mTTjzni20ZYpj92SpN2bLN9qOv39K+U54qTmI/NRh6PY1rZZkYURGDoIt2+qeKBikIMeS1BkbC2ARwmQlcQM7pBF5iPzUUsb0E5vx7ZY8PcXA5Nbij3o6xpQuQFMZ+chTx0JhI56DVo9p4JBamY7YnthA74wRkZlom2RnC6kDlnQitUTWBzarhzHXi7/CM+oILBIO9s2TTq1/POlk2sXH7WyMOxUWbU//DQg/zPT/4bIQRLFi/hlz+/D4jMgqkJapJUlGY+CsTMMDXS/klTvmjcymePOYN7jGsJEqmq8U39DvbKmXxSfYZa0Ygixmf6dJKDWwZxiNHl2G9O52vhT7JH1qIgsRPiHtuPWa/sRRuQMVCXCo8b54JeSGXgLm6vXoBQwuzofmHEh/515f/AsrxLkNEGNuHgcj7Jts5nOOrfzo0VX0NVbNw67Vu80/kEzzXfi0mfvINvVpeSz5Lc87Epdo74ttMUPDqu7yNepGowc40HYRtgYQDK+49g/GQZhNWIgpnWA6fyhqd1lQLlQwcxf78g0rYfMeDfka6lALuBdn7j4C5NoMSHcn49wiYRRSGUK04N21t5/1HkrmLM52YMkkuISH1424h1uST2rX8ltGwd7id/je3gdgLrryJ4zW2UTC9g9vJKDhw8gGnKUS3wg4f2D7N8hhIOhzl4+ABLFy8bePjI/4yopamo0Oe/CgVBUdl36CDf/6//5MXnXqKkuIT2jjOJzZJxrFszEtrmAs0BevxP9L8Y6wgN+joEDxmX8KSxgW9q93OL9uq4RGiRBWw353Cd+hY6ghxCwyyiVpnHB0L/Si9OQMEAwqj8n/CneNTxb+RLLw7CvG4u5Sf69eyQcxDA+hkV2FUVITTeX/E1nmj8IUE5ONnVktwLWZp3ETZl+JPurIKrWJF/OaoSsRKEEKzOv4oqx1ze7XqWc4tuISi9PNt0D6cCe5nlXsWHp/0/VGHDkGEuxmRPzyv8b+MPot+UQsTTMfLdoWFHJzTi5wCqonLR3LU4nTFKK0kQs7qRB/JRPngISv2Yv1sAPXYwokMTm4FY2I4oDaB+5ADGbxYS+3E+ihLKjSGjAGVVS1SpjHyOQoBY3oaUIP9aDaYAU2CbGWDG7JHr1amNJ3E9/Vu0w7ux798GgPONv+Da9jKm3caphQsxPvdZAseOQ1HFiBZKrze+hGde74B8QFJCOITi7UZ4e0CAzMnDdOWCqaO2NyPtDl599RWuv/Z6SopLQEqKCor690+0JA9YVQEBLLsZuf0PiAGzYbGGRX3bDBRiXVkT6JWuQfuONbzySTt/NC7mN8aV/My4jlXiELdrz7GIE4Osmj/pFxJGZbArTtBIMRcEf8QlyruEpcYrcgVmtI0AHtl1khlFHko9Thbnnk+5o5Z7TnwagcCUJgZh1hXcgF0ZebZFU2xD3tupcS+m2rUQgUAIwSdm/Hj4fiKiHBbnXsDB3nc45N2CU82hSKviRCD29LmKjQ1FN1HjWsIjDf8ffrNnWJscu4sPrLySXOcITlpFgl2HZa2ISi/CLhG37cfcVI48UAg2E+WsZsSytkj0cXEA5nTC4REWZ3pCENBAH2CVaAbKhoZhTYUAWRKI262oLG+DpW3Q5QC3jrRB12mNoo6aiEVhH/BQCAVxP/t7hK8Xx/YzDzkB4Pdh+sG3aRPmRz+CyBndge3JiW9dXY4rB8yo38o0UdsaI24LIptEbxdq75m1lCLoh55OhK5DKIQIR6wi6XKDlGhJpPfI3HDTMQhe/C2OyQp6pZOwVOmRTsKohIeY7BLBYaOCIrpRGT5cCuDg342PsCH4Pzypr8Uv7ZwwSwlIG0GpYcrItQxLBb/U8Ek7b5pLuN+4DIATsoLHzfP4ZOgrNMgieqWToNSQEg7JaQSJPRbX0XjePJuX5ap+5RORF0K6yXP76oGI9VLqqOHrcx7nC7W/5n1ld6IKG+XO2SN+N6MFwylCiStYzqG4uKjk4/xd+ef5Yu39fHz6f7DYc0Gso3FV2We4pPR25uSs5qKSj2ETg/M02YSDS+adN7LyAdAkYmkb6pWnIDo8E04D9cJ6tE+9h3bHPpTlbf0PBqFJlHMah8UZRQ5ooLzvJGJ5K2gmaAY4dMTFdSgLOmN/LxX+iH8pDoQAoYIoCiKcBlI1aC09BqEgzuceRGk8CQEf6on9eO77Ntrx/fFNA5gGhIMjKsJ5s+dj00ZXBjZVZUFRHkp3G0p7M2rjyTPKZxQuWnMWjz/xGJ0Hd6N0tNDe2gThMGp7Y8LrwABESkuFTBCrV6+WW7eOXLqluSfAp363lZ2nOjhf2ckCcYqjspJd5izutv8Pi8VxdFQMFP45fCdPmwPL+Iz8ZQpMKmingRIqaONa9S3yhZfXjaXkCh/lopN3jTnspZYzv5Iz/akYXKDspEY0YZNhcgjyc/Ma/Iw/cVqe08a3rojlWpM0B09RYp+GIlK/tupA7yb+0vQ/dOutuNV87pz+I0oc1Wekk5JtXc/yStvv6NHbKbZVcXnZp5hWoeH37JswOWTfxFRAxXhkDtTnRBSIBHF+PerZkYgPGRbg18ATRozwOB7vhEIsbO1+Vn5jK1pvALXp1LjnHcN3/5S55eWAwCipBMcQ61YPoXS18fb2bbz+3nsj9nPe4sWsX7hw3PIDPPDEE/z4t79FVRSWL1zEL/79O2jFxdgqzoQJ7tu3j4VD+hdCbOtb/zkUyymgoG5w8Q9epaHLz0hxe1W0kid8HJZV6FNiFDr+xXzV+W6+ctGiyREnDYS0FjpLnp2UvqUEujXw2qEkgLCnNhrZfbSd6X/cTtnrJxIOeDijgAYgRMyYjbf27WPT/v2EjTPhCzZVZe2CBQkrn2EIgZKTg72mBjEgOn+8Cmgq3H0TyvPvNdHpC42ofADqKaF+Sund8f0s7arCJfNiBadnJhIJUkHRczC1ia8cIQSQr0f+UogS0Fn0by9S8F4TImxOfLTVCMbD+oULOWvOHA7U1dEbCOBxOplfXY1jAvOHC1XDNm3aIOWTCJZTQIebevCGMn2NeGwcqoIE3regihXTMjtaeCiqkUdu9xp8OfsI25syfwm5lMz9nzco2NWIkoYlNA6bjWW1tZPWv9TDhA4fxjFvHiKJ3OSWU0CzyzzYFEHYguumPrF2DjVFHuxJhL5PTSTdha8QtrWAoltjBY2E0teOp0X5pAppGIROnMQxK3FFZ7VfMu9bXG5J5QNwutOX8YZBLAKuo2eUD2S+9UO0/pYFV74PxfT7MEOjx3eNhuUUkBwaGWshnthbR08ghGExBRtwHjmjfCyC1BR6ZxenW4zJRwjkGNHXo2E5BeS0KbhTmAQ8lSgIGnsCw9M8ZDzWvF6H/n4DulPD1FJ/vXTTS5P/RU55H6bJ/yK6OUlloaVESSLNh+WuvBCCdbNK0i3GpGBKSV2X9fJcu3zzwLScO5LeeSVsu/cG6q9ZRLAgdUUy67wPs7XtDo70/JRT3gc50vNTtrbdQZ334Qk7xnd+9jN+/Nv70YqKEGMEP46G5RQQwKKqVCXjTj2WM34AR7AGZ2AGSNUaDugBBCtyOfGRlbScN3kzUgOp8z7MSe+DmHJwUU5TBjjpfXBClZCw29AqkgsHsd5jB6gqcKEIRo0FykQk8OrhJi6cXYEWnQmzQp5hgSCvewNu32K6Cv6KoQ1fK5ZxGCbVj+5h2hN7sbenxmrVTS91vkdHbVPne5QK19Voinvc/f/HL37BH556iuryckqKili5ZEnSvz1LWkDvW1xhSUsBIGxKdjd09r+3ko7V9AJyu9ZFLKFJIlXVNub/1+vMeHA7jjYfQsZekjbRtAXfGmb5DMWUAdqC409K9u577/HIs8/y9sMP88cf/5hte/aAaWIGkit/bkkFVJRjpyo/dWPuVBLSTVp6A4R0I2L9pFugCcYersDdu3TS+jcxJ78IopRIRaAGUxsQGzLjK6kXNtvHbjSEt959l2suuQS3y0Wex8PfXXhh5JjHjiGNxM/TkgqoOxDmVEdymnmqIoG3T0SqggghMn74NRRThDFsydemHA0ZI9vkhCIEh7+wDtOW2tvLroxeF74Pm5JYFH2s35o0TYyuxMugJ/UNCSGKhBAvCiEORf8d9g0IIeYLIXYM+OsWQnwp+tm/CSFOD/jsqmTk6aPbn3hcQibgtqkYGbiIeCQkElOEkOj43PsIOk6kW6SkMe0ancsrU3rMYsd6FDG65a8IJ8WO8Sem33DWWTz10kv4AwF6vF6eeTWau0hKZCjx+23SK6NKKQ8AKwCEECpwGnh8QJMfSSl/kKQcg6jKd2HXFIJJ1CuaymiKMuUSySeDoXjp9Wwl7GhEqolH1U41OpdVULT1dP/7xAsYx4em5FDtvpGT3gdHbFPtvjEhB/TKRYu48YorWHvTTdRUVrJ+1arIB4qC4krc3ZHqyqiXAEeklJP6iDvW5sU0ral8AE53+TGlCRaopW4SpqP4aaQSPHN3TvadmiI6llcRyt2N5gvjn5ZHz5wSKl4+MqnHrM75IBCZ7RrokFaEk2r3jf2fJ8LX7rqLr91116BtQtNQcnMT7jNZBTSosmm08OBo3AL8cci2zwshPgZsBb4ipUzaAfA/Gw9hWGeEMoiSHAdfOG8+qqLQl8spk/1AAg1HYAaBnIMDN2Y+QuCdX8qmhz+MEtAxXTZE2KD85SOTfnrVOR+kwnU1bcG3CJvt2JQiih3rE7J8xkKGdWQohHAmZgWlqjIqQgg7cC3w9QGb7wG+TeSZ923gv4A7Rtj/LuAugJqamlGPte1kh+VigPr4+JpZeOy2pNJgTiUEgtye1ej2NnRbW7rFmXiEwHRF8vDYOvykKkBNU9yUu0asKTpxSBO9qQn7jBkJ7Z6SyqhRrgTelVI2Dei7/7UQ4pfAX0aRI+7SzCUeO3Ud/tGaZCR5ThvluS7LKJ8zKCh6LlhRAQ1g+sM7rRcdC5i+xO+1Sa+MOoBbGTL8iiqtPm7gTMXUpNjfaIFI2hioQlgq8LAPU/URcg6vs2UppCTnSIclRpdDEbb0rQX7HnCZEOIQcFn0PUKIKiHEM/0CCuGOfv7YkP3/UwixWwixC7gI+HKS8vDYu3UEwtZ0QHf4Q2w50YppoSl4gKDjlLVCukeg9fzUrAdLNVppaeL7JnPgeCqjRt/7gGHJUaSUH03m+LH49RvHJrrLKcWju07S7A1w/ZLpGe18HoxVzmMUhMBbG1+g4ERgEsavNmEQQsWOyyhHYeJyQvchVBU1P3/shiNgucWo3QFrByFKsFx8kyNQQ2/utnSLMamIsIHncGp8XD3qUXq0Y0hxZolEl3aAXL2WXGPWhB5LLUwuN7nllmJctsg61SJGorXXWstMVNNNbtc5kUWoZubHNg1DSpSwwbQn9k76oXrUo3TbDg9SPgBSGHTbDtOjHp24gykKWlniwy+woAL6zIWz8Tgs+CMewIkOr+VcJq7AHIparkXTC9ItysQjYenXn8PZMklZCaOYhOnRRndB9GjHMGNUAI6HPz71FOfdeivnfOADfP5b30KbMSPpsjyWU0AlHgev/uNFuO1TWwnF6/WI1U43Je3e4ESKk1Yia8EC+HL2oNtTPxWvok5qmg5hSnKOd05IX2phEWpe7IR7frVpmOUzFCkM/GrTqG1isf/oUR55/nle/t3veOeRR7Dl5PDHR0fPPRQPlvMBARR7HPzgpuV85eGd+MODL4gqIn4USeR/HqeGL6hPeOT0+xaXc/GCMu5++TAnh8QkOTWFr1+1kPJcJ8++18Cpdh/v1XcR1OWwdp88fxa/e/sEwbCBbkokcO7MUopzxpeH164JHDaFuZVujjX56fCO/RRUBWN+L4LkJ7DsqiC/JIDTpdMSchI0J26IqaAwwzUHn9ELwMLc5TgUJ+90vkZ3uIMcLZc1BefiUt281PIXDKmjSz1SLHECEIYk70ArNmcO+TddQ8FNH8D7zju0/NcPkboO40hlITQNW0U5ZiCA0dMzrDChQXzr6EwlBOPMoPHXTZvYvncv5956KwIISEnFzJnj6yQGlivNPJA/bTnJfz53gO5AGIem8olzZ3Ldiml4nDaKc+zopowsWg0bfPlPO3h2TyNCgKYIrltRxcGmHvY39pLn1LhtQy23nj2dT9y/lXdPdvYfQ4H+5A4i+r+7zqvla1cs7A8YfONQKz/eeJCT7T4WV+Xxlcvns2Ta4JmDNw+38on7t2JKSVA3cdtVVtUU8pvb12CYklcOtNDtD7NudjFVBS4O1fdy4LSvP65NEVCQY8MXCBPQz8gmFDhrdj7Tis+EyuuGydsHOunoDSNl7Ni4whyNWRVuKgsdnG4PUNcaQFMj59PUGUJRBKYpKcmzU5ijcbTJT9iQ5DgVakpclBc46PSG2H/aRyBk4rILHDaVzgGKTwhYNSuPmtLBdc6llEgk+3p28mb7S8OUQd9C3FhKQqBgEzbKHJVUOWuYnTOfPFvB8BOMgSlN2kORVCeb2l+lMXQaFQVdGhRoRUxz1dAV7uBkYGQ/ioqKIhR0qaMJGzbFzvWVHyJXG3y9w01NtP/6N3g3b8bo7ERvbBymUFxnnYVaVITR0Y73S19i0apViOgSnHB9fSQNxoA1jz6tng5t7FC6srLLyc1ZiAwGIZrPOVxfj+n1Rss9A3LwRMc9Dz5IQ0sL3/6Hf8A+Zw6K3R6z77/52vBDMU1Jb0gnx66NWU3CG9Rp94aoyHdiG6X436GmHv605RRt3hCXLyqnMt/J5uPtFLjtXLmkglxnYtOdLT1BnthxmrbeEBvmlLB+dvGoUc+9AZ1TrQF0Q1JZ6KA414YQgrBu0twVeRqWFdhHPJdun05vQMfjVKhvD9HYEcRpV5ld4aY0P/YPDCAYNunx67jsKjnOM0PdeNLDtveEaeyMVPaoLnYN2j+mjOFO9nRvpyPcSrG9jKV5q3CrHgKmn169h51dm2kLt1BsK2VVwVqK7Mk5RQfSEWqjM9xOga2IQvuZKBKv3suh3r14jV6CZoCGwCmEEMzzLGF57moagqdpDzeTq+Uz0z0HVYw90DCDQYLHjtP16KOYPi8FN96Ia+XK/u9z6I0tpcT0+TC7ukBRUAsKkDbB8eO/QMqRZ4KFsFFbexeKMtyCNkMhTK8XoaooOTmYvb2YoRAyEGTvvr3c9OlP88Ybb1BeVUV7ezs9PT3MGLIEI6uAsmSxILFu7Fi0t79De/ubI35eVLSBoqJzEpLhT3/6E9/97ncxTRObzcbdd9/N2rVrx5RzNAVkSR9Qlix/q/Qpl46OzYMsISFsFBaenbDyAbj55pu5+eabk5ZxIFkFlCWLxSgqOoeCghX09h5C171oWg4ez9yYw650k1VAWbJYEEVxkJe3JN1ijInl4oCyZMmSOWQVUJYsWdJGRg7Btm3b1iqEiDevdAnQOpnypAkrnpcVzwkm4LxefPHFpYZhJLaGYpIwDENTVXWQTI2NjdqiRYt2D2k6YrrEjFRAUsq4gz2EEFtHmgLMZKx4XlY8J5iY89q5c+fxJUuWxK3EOsK6+nBje2FTULeVO7TwByuKOgpt2oRWStyzZ8/CJUuW7Bu4zTCMkvGca0YqoCxZsozMt4/UV9xX11IZMGW/i+W7Rxum31ld2vCN2VWNifb7ne98p+zXv/516ZIlS3xPPvnkhCTeyiqgLFksxLeP1FfcfbJ52tDtAVMqfdsTVUL33Xdf6bPPPntowYIFE1a87W/BCf2LdAswSVjxvKx4TpCi8+oI6+p9dS2jlmO9r66lsjOsj/u+/9CHPlRTV1fnuPbaa+d861vfKgMoKSlpSVTWPixvAUWraVgOK56XFc8JUndeDze2Fw4cdsUiYErl4cb2wruml40r78kf/vCHk6+++mr+q6++erCyslIHqKioSHrC4G/BAsqS5W+CpqAe1yroplB87VJBVgFlyWIRyh1aXAnRy+3xtUsFllNAQojvCyH2CyF2CSEeF0IUjNDuCiHEASHEYSHEP6VYzHEjhLhJCPGeEMIUQow4zSmEOB4tdbRDCDGlUwaM45wy7VoVCSFeFEIciv4bsxzGRF+rD1YUdTgVMWrFAqcizA9WFMVd/ry9vT1v165dS3bt2rVESjksd4qUkmPHjk3ftWvXkt27dy8Kh8Mj53GJgeUUEPAisERKuQw4yOBS0AAIIVTgbiLVWhcBtwohFqVUyvGzB3g/8FocbS+SUq7IgJiaMc8pQ6/VPwEvSSnnAi9F34/EhF2rQptm3Fld2jBamzurSxsKbFpcZVWklNTV1dXMnTv34JIlS94DFL/fP2hFa0dHR34wGHQuXbp0z4wZM050dXUNK781GpZTQFLKF6SUfdGZm4DqGM3OBg5LKY9KKUPAQ8B1qZIxEaSU+6SUB9Itx0QS5zll3LUiIt/90df3A9en6sDfmF3V+LmastNDLSGnIszP1ZSdHs8UfE9PT47dbg+6XK6Qoihy8+bN9Xa7PXdgm87OzoLi4uI2IQR5eXle0zSVIRWPR8Xqs2B3AH+KsX0aMLAWcB2QeKKUqYUEXhBCSODnFphZysRrVS6lbACQUjYIIcpGaDcp1+obs6sav1BT1vxwY3thU0i3ldsjkdDxWj59hEIhu81m64/5sdvtIa/X6xnYJhwO2+x2e3+b6NKMacCollgfGamAhBAbgVgFwP5FSvlEtM2/ADrwYKwuYmxLe2rIeM4rDjZIKeujP/oXhRD7pZTxDNsmhQk4p4y7VuPoZtKuVYFNM8c71R4n8Xz3cV+fjFRAUspLR/tcCPFx4GrgEhk752wdMH3A+2qgfuIkTIyxzivOPuqj/zYLIR4nMoRJmwKagHPKuGslhGgSQlRGrZ9KoHmEPqbUtRqK3W4PDXQqRy2iQTNoNpstHAqF+tsYhqExjutjOR+QEOIK4GvAtdGa9LHYAswVQtQKIezALcCTqZJxshBC5AghcvteA5cTcfRmMpl4rZ4EPh59/XFgmKWXCdfK4/F4g8Gg0+/3203TFJ2dnUWFhYWdA9sUFBR0trW1FUsp6e7uzlEUxewbfsaD5RQQ8FMgl4hJu0MIcS+AEKJKCPEMQNRJ/XngeWAf8LCU8r10CRwPQogbhBB1wDrgaSHE89Ht/ecFlANvCCF2ApuBp6WUz6VH4rGJ55wy8VoB3wMuE0IcAi6Lvs+4a6UoCtOnTz956NCheXv27FlcUFDQnpOTE2hsbCxtbGwsBSgsLOxyOBzB3bt3Lzlx4sSMvLy89vEcIyOrYmTJ8rfGzp07jy9fvjzupQ8Bw1SPdPsKfbphc2tqeHaeu8OpKhOajiMWO3fuLFm+fPnMeNtnpA8oS5YsI7OltbtiX2dvpSHPjHC2tXVPX1jgaVhTkpdwOo7JIKuAsmSxEFtauyv2dPQOS8dhSJS+7VNJCVnRB5Qly98kAcNU93X2jhoEuK+ztzJomAnd9//4j/9YWVtbu3j9+vVzr7nmmtpvfvOb5YlJeoasAsqSxSIc6fYVDhx2xcKQKIe7fTHXpo3Ga6+95n7qqacKd+/evffpp58+smvXrpzEJT1DdgiWJYtF8OlGXGk2fIYZdzqOI0eOzOzu7s5/6qmn5JVXXtnq8XgkIC+77LLOoW2PHz8+vaWlpVAIsQNwA2VSyoLR+s8qoCxZLIJbU+NKs+FWlbjTcZSUlLSWlZU1SynnjNV25syZp7q6uvxSyhVCiC8AK8faJzsEy5LFIszOc3eoglHXe6kCc06eO+50HPn5+b02m01ftWqV+fzzz+f7fD7R1NTk2rhxY2lvb2/Z3r175/t8PmeMXW8F/jhW/1kFlCWLRXCqirGwwDNqFPLCAk+DQ1XGtSgVYOnSpfKKK67oWrRo0eLrr79+/tKlS3umTZvWUF1dXXfixImagW2FEDOAWuDlsfrNKqAsWSzEmpK8xiWFntNDLSFVYC4p9JxOZgr+X//1XxsPHz689/vf/75y5MiR3Orq6vKTJ0/O0PVhKV5vAR6RUo4Z+Jj1AWXJYjHWlOQ1Liv0NB/u9hX6DNPmVpXwnDx3RyKWz0A+8pGPzDh06JArEAiIW2+9tf7mm28eSZndAnwunj6zCihLFgviUBVzcaFnQtNxPPXUU8cA9u7du6CsrCwIkayJXq/X5fF4/ABRa6gQeDuePrMKKEuWLCNy6NChWq/Xm2sYhrZjx45llZWV9bW1tUdPnDgxo7GxsVJKKQoKCtr7FJDf788B7h0hDc4wsgooS5bMwDRNUyiKktLV43Pnzo1ZgnnBggWHhm4zTVPk5ua2SynjLhyQdUJnyZIZ7Glpack3TTNWhsi0Y5qmaGlpyWecOY2yFlCWLBmAruufaGxs/FVjY+MSpqbhYAJ7dF3/xHh2yuYDypIlS9qYipo0S5YsfyNkFVCWLFnSRlYBZcmSJW1kFVCWLFnSRlYBZcmSJW38//LMNJgWqD8uAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_points.sample(frac=0.01).plot(column=\"geohash1\", legend=True, cmap=\"tab20\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_points_sorted = df_points.sort_values(\"geohash1\").reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>geohash</th>\n",
       "      <th>geohash1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>490128</td>\n",
       "      <td>POINT (-16130619.118 -6196904.196)</td>\n",
       "      <td>0z2gyeu706fv</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>793121</td>\n",
       "      <td>POINT (-16479737.886 -6670448.776)</td>\n",
       "      <td>0wysr3293zup</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>847862</td>\n",
       "      <td>POINT (-17681913.223 -6758307.957)</td>\n",
       "      <td>0qz13xbsz3ev</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>130846</td>\n",
       "      <td>POINT (-18316129.543 -7387634.866)</td>\n",
       "      <td>0q4yrgkjedcm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>482462</td>\n",
       "      <td>POINT (-18822901.995 -7680644.055)</td>\n",
       "      <td>0jzvbq95ute4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                            geometry       geohash geohash1\n",
       "0  490128  POINT (-16130619.118 -6196904.196)  0z2gyeu706fv        0\n",
       "1  793121  POINT (-16479737.886 -6670448.776)  0wysr3293zup        0\n",
       "2  847862  POINT (-17681913.223 -6758307.957)  0qz13xbsz3ev        0\n",
       "3  130846  POINT (-18316129.543 -7387634.866)  0q4yrgkjedcm        0\n",
       "4  482462  POINT (-18822901.995 -7680644.055)  0jzvbq95ute4        0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_points_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points_sorted = dask_geopandas.from_geopandas(df_points_sorted.set_index(\"geohash1\"), npartitions=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0', '2', '3', '4', '5', '7', '8', '9', 'b', 'c', 'd', 'e', 'f', 'g', 'g')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_points_sorted.divisions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points_sorted = ddf_points_sorted.repartition(\n",
    "    divisions=('0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'b', 'c', 'd', 'e', 'f', 'g', 'g')).persist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points_sorted.calculate_spatial_partitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ddf_points_sorted.spatial_partitions.plot(cmap=\"tab20\", alpha=0.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Repartitioning the polygons data given known regions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def repartition_pandas(gdf, partitions):\n",
    "    partitions = geopandas.GeoDataFrame({'geometry': partitions.geometry},\n",
    "                                  crs=partitions.crs)\n",
    "    joined = geopandas.sjoin(partitions, gdf, how='inner', op='intersects').index_right\n",
    "    name = 'from-geopandas-' + tokenize(gdf, partitions)\n",
    "    dsk = {}\n",
    "    new_partitions = []\n",
    "    \n",
    "    # TODO warn if certain rows are dropped (not intersecting with any of the partitions)\n",
    "\n",
    "    j = 0\n",
    "    for i, partition in enumerate(partitions.geometry):\n",
    "        try:\n",
    "            ind = joined.loc[i]\n",
    "        except KeyError:\n",
    "            continue\n",
    "        else:\n",
    "            if not isinstance(ind, pd.Series):\n",
    "                ind = pd.Series([ind])\n",
    "            subset = gdf.loc[ind]\n",
    "        subset2 = subset[subset.geometry.representative_point().intersects(partition)]\n",
    "        dsk[name, j] = subset2\n",
    "        j += 1\n",
    "        if (subset2.geometry.type == 'Point').all():\n",
    "            new_partitions.append(partition)\n",
    "        else:\n",
    "            new_partitions.append(subset2.geometry.convex_hull.unary_union.convex_hull)\n",
    "\n",
    "    divisions= tuple([None]*(j+1))\n",
    "    result = dask_geopandas.GeoDataFrame(dsk, name, gdf.head(0), divisions, new_partitions)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-11858134.820 3717897.056, -10674278...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((-17611091.317 3267835.833, -18878111...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((4598451.622 19430904.086, 4481044.34...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((3796168.573 3884224.029, 3849980.241...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((15047699.136 2661231.577, 13286590.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>POLYGON ((19704854.396 -9568692.949, 11055851....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry\n",
       "0  POLYGON ((-11858134.820 3717897.056, -10674278...\n",
       "1  POLYGON ((-17611091.317 3267835.833, -18878111...\n",
       "2  POLYGON ((4598451.622 19430904.086, 4481044.34...\n",
       "3  POLYGON ((3796168.573 3884224.029, 3849980.241...\n",
       "4  POLYGON ((15047699.136 2661231.577, 13286590.0...\n",
       "5  POLYGON ((19704854.396 -9568692.949, 11055851...."
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "continents = geopandas.read_file(\"continents_spatial_partitions.geojson\")\n",
    "# without clipping first, the reprojection goes awry\n",
    "from shapely.geometry import box\n",
    "continents = geopandas.clip(continents, box(-180, -85, 180, 85)).to_crs(\"EPSG:3857\")\n",
    "continents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=6</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>geometry</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>...</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></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-geopandas, 6 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 6 tasks | 6 npartitions>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_sorted = repartition_pandas(gdf, continents)\n",
    "ddf_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4539"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ddf_sorted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4592"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(gdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ddf_sorted.spatial_partitions.plot(cmap=\"Set1\", alpha=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With this dataset, this gives a few problems because of a part of Russia / N-America crossing the anti-meridian (so a part of the a MultiPolygon lies on the other side of the \"map\"). Let's ignore this problem for now."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Case 3: dask_geopandas.GeoDataFrame + dask_geopandas.GeoDataFrame _with_ spatial partitions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we join the two frames with the spatial partitions we determined above, the `sjoin` will make use of those partitions, and only create a task / output partition when input partitions intersect. For this specific case, this results in 32 output partitions, instead of the max of 96 (16 x 6)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_joined3 = sjoin(ddf_points_sorted, ddf_sorted, op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>geohash</th>\n",
       "      <th>index_right</th>\n",
       "      <th>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=32</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></th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>object</td>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: sjoin2, 54 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 54 tasks | 32 npartitions>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined3.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "res3 = ddf_joined3.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# re-calculate expected result because spatial re-partitioning dropped a few rows\n",
    "res0b = geopandas.sjoin(ddf_points_sorted.compute(), ddf_sorted.compute(), op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "geopandas.testing.assert_geodataframe_equal(res0b.sort_values(\"id\"), res3.sort_values(\"id\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking performance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.91 s ± 86.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%timeit ddf_joined3.compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case, this is slower, because we created many small tasks (and the overhead of dask + the overhead of geopandas.sjoin on small frames adds up).\n",
    "\n",
    "But if we compare to the same operation without using the spatial partitioning information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_points_sorted.spatial_partitions = None\n",
    "ddf_sorted.spatial_partitions = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_joined4 = sjoin(ddf_points_sorted, ddf_sorted, op=\"within\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>id</th>\n",
       "      <th>geometry</th>\n",
       "      <th>geohash</th>\n",
       "      <th>index_right</th>\n",
       "      <th>name</th>\n",
       "      <th>adm0_a3</th>\n",
       "      <th>type_en</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=96</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></th>\n",
       "      <td>int64</td>\n",
       "      <td>geometry</td>\n",
       "      <td>object</td>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: sjoin2, 118 tasks</div>"
      ],
      "text/plain": [
       "<dask_geopandas.GeoDataFrame | 118 tasks | 96 npartitions>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_joined4  # this now has the max of 96 output partitions (16 x 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%timeit ddf_joined4.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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