diff --git a/docs/compile_readme_and_arrange_docs.py b/docs/compile_readme_and_arrange_docs.py
index 12e56da5..3713d46b 100755
--- a/docs/compile_readme_and_arrange_docs.py
+++ b/docs/compile_readme_and_arrange_docs.py
@@ -106,6 +106,16 @@ def compile_readme():
         f"{abs_path}/sphinx/SphinxMulticatTutorial.ipynb",
     )
 
+    shutil.copy(
+        f"{abs_path}/../notebooks/Subsampling Tutorial.ipynb",
+        f"{abs_path}/sphinx/SphinxSubsamplingTutorial.ipynb",
+    )
+
+    shutil.copy(
+        f"{abs_path}/../notebooks/Catalog Tutorial.ipynb",
+        f"{abs_path}/sphinx/SphinxCatalogTutorial.ipynb",
+    )
+
     shutil.copy(
         f"{abs_path}/../CONTRIBUTING.MD",
         f"{abs_path}/sphinx/SPHINX_CONTRIBUTING.MD",
diff --git a/docs/sphinx/SphinxCatalogTutorial.ipynb b/docs/sphinx/SphinxCatalogTutorial.ipynb
new file mode 100644
index 00000000..e192e984
--- /dev/null
+++ b/docs/sphinx/SphinxCatalogTutorial.ipynb
@@ -0,0 +1,809 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9a3cec9a",
+   "metadata": {},
+   "source": [
+    "<img src=\"https://github.com/NOAA-OWP/gval/raw/main/docs/images/gval_light_mode.png\" style=\"float:left\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3075cb24-8ac3-4c1d-a47c-1499a7c46821",
+   "metadata": {},
+   "source": [
+    "# Catalog Comparisons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a11bac2a-a058-41c2-b8ff-a0920c0ed7df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import rioxarray as rxr\n",
+    "\n",
+    "from gval.catalogs.catalogs import catalog_compare"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "837f6d52-5395-4ee8-b929-557e37b7bf74",
+   "metadata": {},
+   "source": [
+    "## Initializing Catalogs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e52648d3-09b4-4db2-9399-56f9eeb941c6",
+   "metadata": {},
+   "source": [
+    "The cataloging functionality was designed to easily facilitate batch comparisons of maps residing locally, in a service, or in the cloud.  The format of such catalogs are as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "b66eca6a-007f-42d2-a476-054b70c2395c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "TEST_DATA_DIR = './'\n",
+    "\n",
+    "candidate_continuous_catalog = pd.read_csv(f'{TEST_DATA_DIR}candidate_catalog_0.csv')\n",
+    "benchmark_continuous_catalog = pd.read_csv(f'{TEST_DATA_DIR}benchmark_catalog_0.csv')\n",
+    "candidate_categorical_catalog = pd.read_csv(f'{TEST_DATA_DIR}candidate_catalog_1.csv')\n",
+    "benchmark_categorical_catalog = pd.read_csv(f'{TEST_DATA_DIR}benchmark_catalog_1.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2eddef14",
+   "metadata": {},
+   "source": [
+    "### Candidate Catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "972505a1",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "      <th>agreement_maps</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./candidate_categorical_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "      <td>agreement_categorical_0.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          map_id compare_id               agreement_maps\n",
+       "0  ./candidate_categorical_0.tif   compare1  agreement_categorical_0.tif\n",
+       "1  ./candidate_categorical_1.tif   compare2  agreement_categorical_1.tif"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "candidate_categorical_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8529ce2",
+   "metadata": {},
+   "source": [
+    "The catalog should have columns representing: \n",
+    "1. An identifier of a candidate map, (in this case `compare_id`) <br />\n",
+    "2. The location of the candidate map, (in this case `map_id`) <br />\n",
+    "3. The name of the agreement map to be created named `agreement_maps`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0d408d2c",
+   "metadata": {},
+   "source": [
+    "### Benchmark Catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "f09a9c91-8bc4-41bc-b11a-733412ba091d",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./benchmark_categorical_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          map_id compare_id\n",
+       "0  ./benchmark_categorical_0.tif   compare1\n",
+       "1  ./benchmark_categorical_1.tif   compare2"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "benchmark_categorical_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5acb15d0",
+   "metadata": {},
+   "source": [
+    "Similar to the previous catalog, the benchmark catalog should have columns representing: \n",
+    "1. An identifier of a candidate map, (in this case `compare_id`) <br />\n",
+    "2. The location of the candidate map, (in this case `map_id`)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "40e2fa0d",
+   "metadata": {},
+   "source": [
+    "## Categorical Catalog Comparison"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8fa314fa",
+   "metadata": {},
+   "source": [
+    "When `compare_type` is set to 'categorical' the catalog will be run as categorical comparisons.  See arguments and output below for the comparison metrics:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "d6034a81",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>map_id_candidate</th>\n",
+       "      <td>./candidate_categorical_0.tif</td>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>compare_id</th>\n",
+       "      <td>compare1</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>agreement_maps</th>\n",
+       "      <td>agreement_categorical_0.tif</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>map_id_benchmark</th>\n",
+       "      <td>./benchmark_categorical_0.tif</td>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>5939.0</td>\n",
+       "      <td>5939.0</td>\n",
+       "      <td>5939.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>1977.0</td>\n",
+       "      <td>1977.0</td>\n",
+       "      <td>1977.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.539427</td>\n",
+       "      <td>0.539427</td>\n",
+       "      <td>0.539427</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                       0  \\\n",
+       "map_id_candidate           ./candidate_categorical_0.tif   \n",
+       "compare_id                                      compare1   \n",
+       "agreement_maps               agreement_categorical_0.tif   \n",
+       "map_id_benchmark           ./benchmark_categorical_0.tif   \n",
+       "band                                                   1   \n",
+       "fn                                                 844.0   \n",
+       "fp                                                 844.0   \n",
+       "tn                                                5939.0   \n",
+       "tp                                                1977.0   \n",
+       "critical_success_index                          0.539427   \n",
+       "true_positive_rate                              0.700815   \n",
+       "positive_predictive_value                       0.700815   \n",
+       "\n",
+       "                                                       1  \\\n",
+       "map_id_candidate           ./candidate_categorical_1.tif   \n",
+       "compare_id                                      compare2   \n",
+       "agreement_maps               agreement_categorical_1.tif   \n",
+       "map_id_benchmark           ./benchmark_categorical_1.tif   \n",
+       "band                                                   1   \n",
+       "fn                                                 844.0   \n",
+       "fp                                                 844.0   \n",
+       "tn                                                5939.0   \n",
+       "tp                                                1977.0   \n",
+       "critical_success_index                          0.539427   \n",
+       "true_positive_rate                              0.700815   \n",
+       "positive_predictive_value                       0.700815   \n",
+       "\n",
+       "                                                       2  \n",
+       "map_id_candidate           ./candidate_categorical_1.tif  \n",
+       "compare_id                                      compare2  \n",
+       "agreement_maps               agreement_categorical_1.tif  \n",
+       "map_id_benchmark           ./benchmark_categorical_1.tif  \n",
+       "band                                                   2  \n",
+       "fn                                                 844.0  \n",
+       "fp                                                 844.0  \n",
+       "tn                                                5939.0  \n",
+       "tp                                                1977.0  \n",
+       "critical_success_index                          0.539427  \n",
+       "true_positive_rate                              0.700815  \n",
+       "positive_predictive_value                       0.700815  "
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arguments = {\n",
+    "    \"candidate_catalog\": candidate_categorical_catalog,\n",
+    "    \"benchmark_catalog\": benchmark_categorical_catalog,\n",
+    "    \"on\": \"compare_id\",\n",
+    "    \"map_ids\": \"map_id\",\n",
+    "    \"how\": \"inner\",\n",
+    "    \"compare_type\": \"categorical\",\n",
+    "    \"compare_kwargs\": {\n",
+    "        \"metrics\": (\n",
+    "            \"critical_success_index\",\n",
+    "            \"true_positive_rate\",\n",
+    "            \"positive_predictive_value\",\n",
+    "        ),\n",
+    "        \"encode_nodata\": True,\n",
+    "        \"nodata\": -9999,\n",
+    "        \"positive_categories\": 2,\n",
+    "        \"negative_categories\": 1\n",
+    "    },\n",
+    "    \"open_kwargs\": {\n",
+    "        \"mask_and_scale\": True, \n",
+    "        \"masked\": True\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "agreement_categorical_catalog = catalog_compare(**arguments)\n",
+    "agreement_categorical_catalog.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0aa97373",
+   "metadata": {},
+   "source": [
+    "We can see the agreement maps below (and why the metrics are similar as the datasets were essentially equivalent):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "18b0df29",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for ag_map in agreement_categorical_catalog['agreement_maps'].unique():\n",
+    "    rxr.open_rasterio(ag_map, mask_and_scale=True).gval.cat_plot(title=ag_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff002dea",
+   "metadata": {},
+   "source": [
+    "## Continuous Catalog Compare"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f17d903",
+   "metadata": {},
+   "source": [
+    "The continuous catalogs are as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "a86f7eca",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "      <th>agreement_maps</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./candidate_continuous_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "      <td>./agreement_continuous_0.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./candidate_continuous_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>./agreement_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         map_id compare_id                agreement_maps\n",
+       "0  ./candidate_continuous_0.tif   compare1  ./agreement_continuous_0.tif\n",
+       "1  ./candidate_continuous_1.tif   compare2  ./agreement_continuous_1.tif"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "candidate_continuous_catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "1b94b2cc",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./benchmark_continuous_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./benchmark_continuous_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         map_id compare_id\n",
+       "0  ./benchmark_continuous_0.tif   compare1\n",
+       "1  ./benchmark_continuous_1.tif   compare2"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "benchmark_continuous_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a8a1c9c",
+   "metadata": {},
+   "source": [
+    "Just like before, `compare_type` is set to 'continuous' and the catalog will be run as continuous comparisons:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "6dad7a6d",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>map_id_candidate</th>\n",
+       "      <td>./candidate_continuous_0.tif</td>\n",
+       "      <td>./candidate_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>compare_id</th>\n",
+       "      <td>compare1</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>agreement_maps</th>\n",
+       "      <td>./agreement_continuous_0.tif</td>\n",
+       "      <td>./agreement_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>map_id_benchmark</th>\n",
+       "      <td>./benchmark_continuous_0.tif</td>\n",
+       "      <td>./benchmark_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>coefficient_of_determination</th>\n",
+       "      <td>-0.06616</td>\n",
+       "      <td>-0.329965</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean_absolute_error</th>\n",
+       "      <td>0.317389</td>\n",
+       "      <td>0.485031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean_absolute_percentage_error</th>\n",
+       "      <td>0.159568</td>\n",
+       "      <td>0.177735</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                           0  \\\n",
+       "map_id_candidate                ./candidate_continuous_0.tif   \n",
+       "compare_id                                          compare1   \n",
+       "agreement_maps                  ./agreement_continuous_0.tif   \n",
+       "map_id_benchmark                ./benchmark_continuous_0.tif   \n",
+       "band                                                       1   \n",
+       "coefficient_of_determination                        -0.06616   \n",
+       "mean_absolute_error                                 0.317389   \n",
+       "mean_absolute_percentage_error                      0.159568   \n",
+       "\n",
+       "                                                           1  \n",
+       "map_id_candidate                ./candidate_continuous_1.tif  \n",
+       "compare_id                                          compare2  \n",
+       "agreement_maps                  ./agreement_continuous_1.tif  \n",
+       "map_id_benchmark                ./benchmark_continuous_1.tif  \n",
+       "band                                                       1  \n",
+       "coefficient_of_determination                       -0.329965  \n",
+       "mean_absolute_error                                 0.485031  \n",
+       "mean_absolute_percentage_error                      0.177735  "
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arguments = {\n",
+    "    \"candidate_catalog\": candidate_continuous_catalog,\n",
+    "    \"benchmark_catalog\": benchmark_continuous_catalog,\n",
+    "    \"on\": \"compare_id\",\n",
+    "    \"map_ids\": \"map_id\",\n",
+    "    \"how\": \"inner\",\n",
+    "    \"compare_type\": \"continuous\",\n",
+    "    \"compare_kwargs\": {\n",
+    "        \"metrics\": (\n",
+    "            \"coefficient_of_determination\",\n",
+    "            \"mean_absolute_error\",\n",
+    "            \"mean_absolute_percentage_error\",\n",
+    "        ),\n",
+    "        \"encode_nodata\": True,\n",
+    "        \"nodata\": -9999,\n",
+    "    },\n",
+    "    \"open_kwargs\": {\n",
+    "        \"mask_and_scale\": True, \n",
+    "        \"masked\": True\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "agreement_continuous_catalog = catalog_compare(**arguments)\n",
+    "agreement_continuous_catalog.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "056dde35",
+   "metadata": {},
+   "source": [
+    "We can see the continuous agreement maps below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "c97ea173",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for ag_map in agreement_continuous_catalog['agreement_maps'].unique():\n",
+    "    rxr.open_rasterio(ag_map, mask_and_scale=True).gval.cont_plot(title=ag_map)"
+   ]
+  }
+ ],
+ "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": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/sphinx/SphinxSubsamplingTutorial.ipynb b/docs/sphinx/SphinxSubsamplingTutorial.ipynb
new file mode 100644
index 00000000..96cab560
--- /dev/null
+++ b/docs/sphinx/SphinxSubsamplingTutorial.ipynb
@@ -0,0 +1,2277 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a032a578",
+   "metadata": {},
+   "source": [
+    "<img src=\"https://github.com/NOAA-OWP/gval/raw/main/docs/images/gval_light_mode.png\" style=\"float:left\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "02838b30",
+   "metadata": {},
+   "source": [
+    "# Subsampling Comparisons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f194294a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import rioxarray as rxr\n",
+    "import geopandas as gpd\n",
+    "from shapely import unary_union\n",
+    "\n",
+    "from gval import CatStats"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e88210f",
+   "metadata": {},
+   "source": [
+    "## Create Subsampling DataFrame"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d96f2912",
+   "metadata": {},
+   "source": [
+    "Let's open up a geopackage with polygons to use for subsampling:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "65bee66c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_path = './'\n",
+    "polygons_continuous = gpd.read_file(f'{data_path}/subsample_continuous_polygons.gpkg')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72ce0153",
+   "metadata": {},
+   "source": [
+    "To use this DataFrame as a subsampling DataFrame let's use `create_subsampling_df`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "ce38ccc5",
+   "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",
+       "      <th>subsample_type</th>\n",
+       "      <th>subsample_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>POLYGON ((-97.72375 29.56328, -97.72304 29.558...</td>\n",
+       "      <td>include</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>POLYGON ((-97.71604 29.55635, -97.71587 29.551...</td>\n",
+       "      <td>include</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                            geometry subsample_type  \\\n",
+       "0  POLYGON ((-97.72375 29.56328, -97.72304 29.558...        include   \n",
+       "1  POLYGON ((-97.71604 29.55635, -97.71587 29.551...        include   \n",
+       "\n",
+       "   subsample_id  \n",
+       "0             1  \n",
+       "1             2  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "polygons_continuous.gval.create_subsampling_df(subsampling_type=[\"include\", \"include\"], inplace=True)\n",
+    "polygons_continuous"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f73f0a71",
+   "metadata": {},
+   "source": [
+    "The DataFrame above has a geometry column, a subsample type with the value of \"include\" (calculating data within the geometry) or \"exclude\" (remove all data contained within the geometry), and subsample_id.\n",
+    "\n",
+    "There is also the ability to add subsampling_weights:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6e330044",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    \n",
+       "        &lt;script&gt;\n",
+       "            L_NO_TOUCH = false;\n",
+       "            L_DISABLE_3D = false;\n",
+       "        &lt;/script&gt;\n",
+       "    \n",
+       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
+       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_fae377627d9b5a9583e577b12fcf8d5a {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "        \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
+       "                        .foliumtooltip {\n",
+       "                            \n",
+       "                        }\n",
+       "                       .foliumtooltip table{\n",
+       "                            margin: auto;\n",
+       "                        }\n",
+       "                        .foliumtooltip tr{\n",
+       "                            text-align: left;\n",
+       "                        }\n",
+       "                        .foliumtooltip th{\n",
+       "                            padding: 2px; padding-right: 8px;\n",
+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_fae377627d9b5a9583e577b12fcf8d5a&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_fae377627d9b5a9583e577b12fcf8d5a = L.map(\n",
+       "                &quot;map_fae377627d9b5a9583e577b12fcf8d5a&quot;,\n",
+       "                {\n",
+       "                    center: [29.558023998293017, -97.71753025470662],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    zoom: 10,\n",
+       "                    zoomControl: true,\n",
+       "                    preferCanvas: false,\n",
+       "                }\n",
+       "            );\n",
+       "            L.control.scale().addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_a5dcad47f74f579e058588c60d39abd0 = L.tileLayer(\n",
+       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            ).addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
+       "        \n",
+       "    \n",
+       "            map_fae377627d9b5a9583e577b12fcf8d5a.fitBounds(\n",
+       "                [[29.551956909232516, -97.72374664573506], [29.56409108735352, -97.71131386367819]],\n",
+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_ca4e4a81d59de75107d8373f4a4ab3f7.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_ca4e4a81d59de75107d8373f4a4ab3f7 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler,\n",
+       "                pointToLayer: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_pointToLayer\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_add (data) {\n",
+       "            geo_json_ca4e4a81d59de75107d8373f4a4ab3f7\n",
+       "                .addData(data)\n",
+       "                .addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
+       "        }\n",
+       "            geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_add({&quot;bbox&quot;: [-97.72374664573506, 29.551956909232516, -97.71131386367819, 29.56409108735352], &quot;features&quot;: [{&quot;bbox&quot;: [-97.72374664573506, 29.558580487446218, -97.71573863109144, 29.56409108735352], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.72374664573506, 29.563276712982983], [-97.72304085461393, 29.558580487446218], [-97.71573863109144, 29.558743362320325], [-97.72038056500351, 29.56409108735352], [-97.72374664573506, 29.563276712982983]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 1, &quot;subsample_type&quot;: &quot;exclude&quot;, &quot;weights&quot;: 2}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-97.7160372350273, 29.551956909232516, -97.71131386367819, 29.556354530833417], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.7160372350273, 29.556354530833417], [-97.7158743601532, 29.551956909232516], [-97.71131386367819, 29.55277128360305], [-97.7118024883005, 29.55518726090231], [-97.71267115429575, 29.556191655959307], [-97.7160372350273, 29.556354530833417]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 2, &quot;subsample_type&quot;: &quot;exclude&quot;, &quot;weights&quot;: 1}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_ca4e4a81d59de75107d8373f4a4ab3f7.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;subsample_type&quot;, &quot;weights&quot;, &quot;subsample_id&quot;];\n",
+       "    let aliases = [&quot;subsample_type&quot;, &quot;weights&quot;, &quot;subsample_id&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x7fa3ab00e500>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "polygons_continuous = polygons_continuous.gval.create_subsampling_df(subsampling_type=[\"exclude\", \"exclude\"], subsampling_weights=[2, 1])\n",
+    "polygons_continuous.explore()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14562a37",
+   "metadata": {},
+   "source": [
+    "## Continuous Compare Subsampling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "13ba505a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cds = rxr.open_rasterio(f'{data_path}/candidate_continuous_1.tif', band_as_variable=True, mask_and_scale=True)\n",
+    "bds = rxr.open_rasterio(f'{data_path}/benchmark_continuous_1.tif', band_as_variable=True, mask_and_scale=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1bb8f787-d1b0-4ca1-8e10-af5195918284",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aac9af50>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cds.gval.cont_plot(title=\"Candidate Map\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0e2c3739-2879-48a1-95f5-398aeae7c7c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aaa6d180>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bds.gval.cont_plot(title=\"Benchmark Map\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0459cab",
+   "metadata": {},
+   "source": [
+    "Let's use this newly created subsampling dataframe on a continuous comparison.  For each subsample an agreement map is created and then used to calculate continuous statistics. There are four subsampling-average types:\n",
+    "\n",
+    "1. <b>full-detail</b>: reports all metrics calculated on separate bands and subsamples.\n",
+    "2. <b>band</b>: reports all metrics on subsamples with band values averaged.\n",
+    "3. <b>subsample</b>: reports all metrics on bands with subsample values averaged.\n",
+    "4. <b>weighted</b>: reports all metrics on bands with subsample values averaged and scaled by weights."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c6586a4",
+   "metadata": {},
+   "source": [
+    "#### Full-Detail"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "8153c36a",
+   "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>subsample</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.125928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.111844</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.167116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.143187</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample band  mean_percentage_error\n",
+       "0         1    1               0.125928\n",
+       "1         1    2              -0.111844\n",
+       "2         2    1               0.167116\n",
+       "3         2    2              -0.143187"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                      subsampling_df=polygons_continuous,\n",
+    "                                      subsampling_average=\"full-detail\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d31b4b76-4300-46ee-9350-a4d5e94fb2cf",
+   "metadata": {},
+   "source": [
+    "The agreement maps for each subsample will look as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "cb0f69d3-8d88-4945-a2f1-55cee672d427",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa732590>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cont_plot(title=\"Agreement Map 1st Exclusion\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a14bedab-6669-4d14-8f6c-cc4d49bf219b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa6e5cc0>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[1].gval.cont_plot(title=\"Agreement Map 2nd Exclusion\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "100a159d",
+   "metadata": {},
+   "source": [
+    "#### Band"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "740f2f48",
+   "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>subsample</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>averaged</td>\n",
+       "      <td>0.007042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>averaged</td>\n",
+       "      <td>0.011964</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample      band  mean_percentage_error\n",
+       "0         1  averaged               0.007042\n",
+       "1         2  averaged               0.011964"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                     subsampling_df=polygons_continuous,\n",
+    "                                     subsampling_average=\"band\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f50fc6b",
+   "metadata": {},
+   "source": [
+    "#### Subsample"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ca0131f3",
+   "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>subsample</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.146522</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.127515</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample band  mean_percentage_error\n",
+       "0  averaged    1               0.146522\n",
+       "1  averaged    2              -0.127515"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                     subsampling_df=polygons_continuous,\n",
+    "                                     subsampling_average=\"subsample\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01e1c7ed",
+   "metadata": {},
+   "source": [
+    "#### Weighted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "b30d4794",
+   "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>subsample</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.083952</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.037281</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample band  mean_percentage_error\n",
+       "0  averaged    1               0.083952\n",
+       "1  averaged    2              -0.037281"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                      subsampling_df=polygons_continuous,\n",
+    "                                      subsampling_average=\"weighted\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37019088-5a21-444e-81f4-4face46dff38",
+   "metadata": {},
+   "source": [
+    "If one desires to have only one subsample with all of the exclusions combined use Shapely's `unary_union`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "bbd026aa-6a33-4fee-ab2c-c5d852bbc33d",
+   "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>subsample</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.133122</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.117482</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample band  mean_percentage_error\n",
+       "0         1    1               0.133122\n",
+       "1         1    2              -0.117482"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "combined_df = gpd.GeoDataFrame(geometry=[unary_union(polygons_continuous['geometry'])], \n",
+    "                               crs=polygons_continuous.crs)\n",
+    "combined_df.gval.create_subsampling_df(subsampling_type=[\"exclude\"], inplace=True)\n",
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                      subsampling_df=combined_df,\n",
+    "                                      subsampling_average=\"full-detail\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "db842a2f-e30d-4ea7-800c-838bb8842b1f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa4e0820>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cont_plot(title=\"Agreement Map Exclusion\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e17ce32e",
+   "metadata": {},
+   "source": [
+    "## Categorical"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "13730e57",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    \n",
+       "        &lt;script&gt;\n",
+       "            L_NO_TOUCH = false;\n",
+       "            L_DISABLE_3D = false;\n",
+       "        &lt;/script&gt;\n",
+       "    \n",
+       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
+       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_7a482419a882361faafe71791ce249e6 {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "        \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
+       "                        .foliumtooltip {\n",
+       "                            \n",
+       "                        }\n",
+       "                       .foliumtooltip table{\n",
+       "                            margin: auto;\n",
+       "                        }\n",
+       "                        .foliumtooltip tr{\n",
+       "                            text-align: left;\n",
+       "                        }\n",
+       "                        .foliumtooltip th{\n",
+       "                            padding: 2px; padding-right: 8px;\n",
+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_7a482419a882361faafe71791ce249e6&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_7a482419a882361faafe71791ce249e6 = L.map(\n",
+       "                &quot;map_7a482419a882361faafe71791ce249e6&quot;,\n",
+       "                {\n",
+       "                    center: [30.00813899359811, -97.33918187936801],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    zoom: 10,\n",
+       "                    zoomControl: true,\n",
+       "                    preferCanvas: false,\n",
+       "                }\n",
+       "            );\n",
+       "            L.control.scale().addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_c35eec0dfcda0a07ce9d98360ffc13c2 = L.tileLayer(\n",
+       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            ).addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "        \n",
+       "    \n",
+       "            map_7a482419a882361faafe71791ce249e6.fitBounds(\n",
+       "                [[29.938469924981753, -97.56735097529567], [30.077808062214462, -97.11101278344036]],\n",
+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_42f502bfad8fb4b20ee4ac133ef66803.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_42f502bfad8fb4b20ee4ac133ef66803_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_42f502bfad8fb4b20ee4ac133ef66803 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_42f502bfad8fb4b20ee4ac133ef66803_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler,\n",
+       "                pointToLayer: geo_json_42f502bfad8fb4b20ee4ac133ef66803_pointToLayer\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_add (data) {\n",
+       "            geo_json_42f502bfad8fb4b20ee4ac133ef66803\n",
+       "                .addData(data)\n",
+       "                .addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "        }\n",
+       "            geo_json_42f502bfad8fb4b20ee4ac133ef66803_add({&quot;bbox&quot;: [-97.56735097529567, 29.938469924981753, -97.11101278344036, 30.077808062214462], &quot;features&quot;: [{&quot;bbox&quot;: [-97.56735097529567, 29.96872487790609, -97.29513995428285, 30.07450190965067], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.56735097529567, 30.07450190965067], [-97.5180015379423, 29.96872487790609], [-97.29513995428285, 29.97237224487936], [-97.36734101708505, 30.04412406749238], [-97.44813361508811, 30.06807403338502], [-97.56735097529567, 30.07450190965067]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 1, &quot;subsample_type&quot;: &quot;include&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-97.2165793929137, 29.938469924981753, -97.11101278344036, 30.077808062214462], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.2165793929137, 30.070110147912505], [-97.20986142764495, 29.95981101477043], [-97.11101278344036, 29.938469924981753], [-97.1296905666604, 30.077808062214462], [-97.2165793929137, 30.070110147912505]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 2, &quot;subsample_type&quot;: &quot;include&quot;}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_42f502bfad8fb4b20ee4ac133ef66803.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;subsample_type&quot;, &quot;subsample_id&quot;];\n",
+       "    let aliases = [&quot;subsample_type&quot;, &quot;subsample_id&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x7fa3aa3847c0>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Subsampling DF\n",
+    "polygons_categorical = gpd.read_file(f'{data_path}/subsample_two-class_polygons.gpkg')\n",
+    "polygons_categorical.gval.create_subsampling_df(subsampling_type=[\"include\", \"include\"], inplace=True)\n",
+    "polygons_categorical.explore()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "29db6c85-8072-430e-8b59-d87a602ae849",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Candidate and Benchmark\n",
+    "cda = rxr.open_rasterio(f'{data_path}/candidate_map_multiband_two_class_categorical.tif', mask_and_scale=True)\n",
+    "bda = rxr.open_rasterio(f'{data_path}/benchmark_map_multiband_two_class_categorical.tif', mask_and_scale=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "cf163d20-ce17-448a-af75-d04eb675075e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa399f6e290>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cda.gval.cat_plot(\"Candidate Map\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "8881be72-af9f-4579-b21f-dd8b08a72a0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa38a781ba0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bda.gval.cat_plot(\"Benchmark Map\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d3e01d77",
+   "metadata": {},
+   "source": [
+    "Just as done earlier in continuous comparison, the following performs subsampling on categorical comparisons..  For each subsample an agreement map, a cross-tabulation table, and a metric table is created. There are three subsampling-average types:\n",
+    "\n",
+    "1. <b>full-detail</b>: reports all metrics calculated on separate bands and subsamples.\n",
+    "2. <b>band</b>: reports all metrics on subsamples with band values averaged.\n",
+    "3. <b>subsample</b>: reports all metrics on bands with subsample values averaged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df0c50d5",
+   "metadata": {},
+   "source": [
+    "#### Full-detail"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "910e7d59",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>201953.0</td>\n",
+       "      <td>182389.0</td>\n",
+       "      <td>68239.0</td>\n",
+       "      <td>58638.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>761242.0</td>\n",
+       "      <td>397531.0</td>\n",
+       "      <td>43646.0</td>\n",
+       "      <td>65967.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>762262.0</td>\n",
+       "      <td>398338.0</td>\n",
+       "      <td>1479858.0</td>\n",
+       "      <td>729902.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>201936.0</td>\n",
+       "      <td>181301.0</td>\n",
+       "      <td>335650.0</td>\n",
+       "      <td>305052.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.50026</td>\n",
+       "      <td>0.499879</td>\n",
+       "      <td>0.94195</td>\n",
+       "      <td>0.892541</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.500157</td>\n",
+       "      <td>0.499506</td>\n",
+       "      <td>0.901198</td>\n",
+       "      <td>0.877941</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.173316</td>\n",
+       "      <td>0.238171</td>\n",
+       "      <td>0.749997</td>\n",
+       "      <td>0.70999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>0.000104</td>\n",
+       "      <td>-0.000426</td>\n",
+       "      <td>0.696008</td>\n",
+       "      <td>0.602268</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.29543</td>\n",
+       "      <td>0.384715</td>\n",
+       "      <td>0.857141</td>\n",
+       "      <td>0.830402</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.790344</td>\n",
+       "      <td>0.686781</td>\n",
+       "      <td>0.115071</td>\n",
+       "      <td>0.1778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.500021</td>\n",
+       "      <td>0.501496</td>\n",
+       "      <td>0.168955</td>\n",
+       "      <td>0.161231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.209448</td>\n",
+       "      <td>0.31407</td>\n",
+       "      <td>0.044079</td>\n",
+       "      <td>0.074363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.499665</td>\n",
+       "      <td>0.499493</td>\n",
+       "      <td>0.028648</td>\n",
+       "      <td>0.082887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.323765</td>\n",
+       "      <td>0.395147</td>\n",
+       "      <td>0.857564</td>\n",
+       "      <td>0.830444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>0.000255</td>\n",
+       "      <td>-0.000918</td>\n",
+       "      <td>0.821398</td>\n",
+       "      <td>0.751849</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>0.999373</td>\n",
+       "      <td>1.001976</td>\n",
+       "      <td>0.173938</td>\n",
+       "      <td>0.175802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.790552</td>\n",
+       "      <td>0.68593</td>\n",
+       "      <td>0.955921</td>\n",
+       "      <td>0.925637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>2.384759</td>\n",
+       "      <td>1.591553</td>\n",
+       "      <td>0.93911</td>\n",
+       "      <td>1.020152</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>1.000628</td>\n",
+       "      <td>0.99802</td>\n",
+       "      <td>29.0084</td>\n",
+       "      <td>10.119461</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.209656</td>\n",
+       "      <td>0.313219</td>\n",
+       "      <td>0.884929</td>\n",
+       "      <td>0.8222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.499922</td>\n",
+       "      <td>0.500248</td>\n",
+       "      <td>0.156594</td>\n",
+       "      <td>0.239171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500335</td>\n",
+       "      <td>0.500507</td>\n",
+       "      <td>0.971352</td>\n",
+       "      <td>0.917113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.499979</td>\n",
+       "      <td>0.498504</td>\n",
+       "      <td>0.831045</td>\n",
+       "      <td>0.838769</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         0         1          2          3\n",
+       "band                                     1         1          2          2\n",
+       "subsample                                1         2          1          2\n",
+       "fn                                201953.0  182389.0    68239.0    58638.0\n",
+       "fp                                761242.0  397531.0    43646.0    65967.0\n",
+       "tn                                762262.0  398338.0  1479858.0   729902.0\n",
+       "tp                                201936.0  181301.0   335650.0   305052.0\n",
+       "accuracy                           0.50026  0.499879    0.94195   0.892541\n",
+       "balanced_accuracy                 0.500157  0.499506   0.901198   0.877941\n",
+       "critical_success_index            0.173316  0.238171   0.749997    0.70999\n",
+       "equitable_threat_score            0.000104 -0.000426   0.696008   0.602268\n",
+       "f_score                            0.29543  0.384715   0.857141   0.830402\n",
+       "false_discovery_rate              0.790344  0.686781   0.115071     0.1778\n",
+       "false_negative_rate               0.500021  0.501496   0.168955   0.161231\n",
+       "false_omission_rate               0.209448   0.31407   0.044079   0.074363\n",
+       "false_positive_rate               0.499665  0.499493   0.028648   0.082887\n",
+       "fowlkes_mallows_index             0.323765  0.395147   0.857564   0.830444\n",
+       "matthews_correlation_coefficient  0.000255 -0.000918   0.821398   0.751849\n",
+       "negative_likelihood_ratio         0.999373  1.001976   0.173938   0.175802\n",
+       "negative_predictive_value         0.790552   0.68593   0.955921   0.925637\n",
+       "overall_bias                      2.384759  1.591553    0.93911   1.020152\n",
+       "positive_likelihood_ratio         1.000628   0.99802    29.0084  10.119461\n",
+       "positive_predictive_value         0.209656  0.313219   0.884929     0.8222\n",
+       "prevalence                        0.209552  0.313645   0.209552   0.313645\n",
+       "prevalence_threshold              0.499922  0.500248   0.156594   0.239171\n",
+       "true_negative_rate                0.500335  0.500507   0.971352   0.917113\n",
+       "true_positive_rate                0.499979  0.498504   0.831045   0.838769"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
+    "                                             metrics=\"all\",\n",
+    "                                             positive_categories=[2],\n",
+    "                                             negative_categories=[0, 1],\n",
+    "                                             subsampling_df=polygons_categorical,\n",
+    "                                             subsampling_average=\"full-detail\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08429c79-4f1b-4e47-b5c7-1061e1f2ff82",
+   "metadata": {},
+   "source": [
+    "The agreement map will look as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "5268a23d-761a-44d5-b8e2-97714a2618b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa39a335600>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cat_plot(title=\"Agreement Map 1st Inclusion\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b335f4dc-b7ac-4004-bf71-6fca84124fa8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3a6fa5d80>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[1].gval.cat_plot(title=\"Agreement Map 2nd Inclusion\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8a6dd94",
+   "metadata": {},
+   "source": [
+    "#### Band"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "da3aee47",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>averaged</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>270192.0</td>\n",
+       "      <td>241027.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>804888.0</td>\n",
+       "      <td>463498.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>2242120.0</td>\n",
+       "      <td>1128240.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>537586.0</td>\n",
+       "      <td>486353.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.721105</td>\n",
+       "      <td>0.69621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.700678</td>\n",
+       "      <td>0.688723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.333352</td>\n",
+       "      <td>0.408399</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>0.192488</td>\n",
+       "      <td>0.211025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.500021</td>\n",
+       "      <td>0.579948</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.599556</td>\n",
+       "      <td>0.487969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.334488</td>\n",
+       "      <td>0.331363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.107547</td>\n",
+       "      <td>0.176026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.264157</td>\n",
+       "      <td>0.29119</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.516237</td>\n",
+       "      <td>0.585118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>0.342864</td>\n",
+       "      <td>0.356123</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>0.454564</td>\n",
+       "      <td>0.467492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.892453</td>\n",
+       "      <td>0.823974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>1.661934</td>\n",
+       "      <td>1.305853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>2.519382</td>\n",
+       "      <td>2.296222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.400444</td>\n",
+       "      <td>0.512031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.38651</td>\n",
+       "      <td>0.397562</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.735843</td>\n",
+       "      <td>0.70881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.665512</td>\n",
+       "      <td>0.668637</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                          0          1\n",
+       "subsample                                 1          2\n",
+       "band                               averaged   averaged\n",
+       "fn                                 270192.0   241027.0\n",
+       "fp                                 804888.0   463498.0\n",
+       "tn                                2242120.0  1128240.0\n",
+       "tp                                 537586.0   486353.0\n",
+       "accuracy                           0.721105    0.69621\n",
+       "balanced_accuracy                  0.700678   0.688723\n",
+       "critical_success_index             0.333352   0.408399\n",
+       "equitable_threat_score             0.192488   0.211025\n",
+       "f_score                            0.500021   0.579948\n",
+       "false_discovery_rate               0.599556   0.487969\n",
+       "false_negative_rate                0.334488   0.331363\n",
+       "false_omission_rate                0.107547   0.176026\n",
+       "false_positive_rate                0.264157    0.29119\n",
+       "fowlkes_mallows_index              0.516237   0.585118\n",
+       "matthews_correlation_coefficient   0.342864   0.356123\n",
+       "negative_likelihood_ratio          0.454564   0.467492\n",
+       "negative_predictive_value          0.892453   0.823974\n",
+       "overall_bias                       1.661934   1.305853\n",
+       "positive_likelihood_ratio          2.519382   2.296222\n",
+       "positive_predictive_value          0.400444   0.512031\n",
+       "prevalence                         0.209552   0.313645\n",
+       "prevalence_threshold                0.38651   0.397562\n",
+       "true_negative_rate                 0.735843    0.70881\n",
+       "true_positive_rate                 0.665512   0.668637"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
+    "                                             metrics=\"all\",\n",
+    "                                             positive_categories=[2],\n",
+    "                                             negative_categories=[0, 1],\n",
+    "                                             subsampling_df=polygons_categorical,\n",
+    "                                             subsampling_average=\"band\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff5a26ef",
+   "metadata": {},
+   "source": [
+    "#### Subsample"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "a9e533c6",
+   "metadata": {
+    "scrolled": false
+   },
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>averaged</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>384342.0</td>\n",
+       "      <td>126877.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>1158773.0</td>\n",
+       "      <td>109613.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>1160600.0</td>\n",
+       "      <td>2209760.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>383237.0</td>\n",
+       "      <td>640702.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.500117</td>\n",
+       "      <td>0.92339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.499837</td>\n",
+       "      <td>0.893723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.198944</td>\n",
+       "      <td>0.730401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>-0.000122</td>\n",
+       "      <td>0.657571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.331866</td>\n",
+       "      <td>0.844199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.751469</td>\n",
+       "      <td>0.146089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.50072</td>\n",
+       "      <td>0.165295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.248774</td>\n",
+       "      <td>0.054299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.499606</td>\n",
+       "      <td>0.04726</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.352259</td>\n",
+       "      <td>0.844253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>-0.000282</td>\n",
+       "      <td>0.793505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>1.000651</td>\n",
+       "      <td>0.173494</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.751226</td>\n",
+       "      <td>0.945701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>2.008927</td>\n",
+       "      <td>0.977509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>0.999348</td>\n",
+       "      <td>17.662067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.248531</td>\n",
+       "      <td>0.853911</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.248653</td>\n",
+       "      <td>0.248653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.500082</td>\n",
+       "      <td>0.192211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500394</td>\n",
+       "      <td>0.95274</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.49928</td>\n",
+       "      <td>0.834705</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                          0          1\n",
+       "subsample                          averaged   averaged\n",
+       "band                                      1          2\n",
+       "fn                                 384342.0   126877.0\n",
+       "fp                                1158773.0   109613.0\n",
+       "tn                                1160600.0  2209760.0\n",
+       "tp                                 383237.0   640702.0\n",
+       "accuracy                           0.500117    0.92339\n",
+       "balanced_accuracy                  0.499837   0.893723\n",
+       "critical_success_index             0.198944   0.730401\n",
+       "equitable_threat_score            -0.000122   0.657571\n",
+       "f_score                            0.331866   0.844199\n",
+       "false_discovery_rate               0.751469   0.146089\n",
+       "false_negative_rate                 0.50072   0.165295\n",
+       "false_omission_rate                0.248774   0.054299\n",
+       "false_positive_rate                0.499606    0.04726\n",
+       "fowlkes_mallows_index              0.352259   0.844253\n",
+       "matthews_correlation_coefficient  -0.000282   0.793505\n",
+       "negative_likelihood_ratio          1.000651   0.173494\n",
+       "negative_predictive_value          0.751226   0.945701\n",
+       "overall_bias                       2.008927   0.977509\n",
+       "positive_likelihood_ratio          0.999348  17.662067\n",
+       "positive_predictive_value          0.248531   0.853911\n",
+       "prevalence                         0.248653   0.248653\n",
+       "prevalence_threshold               0.500082   0.192211\n",
+       "true_negative_rate                 0.500394    0.95274\n",
+       "true_positive_rate                  0.49928   0.834705"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
+    "                                             metrics=\"all\",\n",
+    "                                             positive_categories=[2],\n",
+    "                                             negative_categories=[0, 1],\n",
+    "                                             subsampling_df=polygons_categorical,\n",
+    "                                             subsampling_average=\"subsample\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "453186df-60f5-4343-beeb-6e995d5bfefc",
+   "metadata": {},
+   "source": [
+    "As done earlier, if one wants to combine the inclusion of multiple polygons use `unary_union`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "2380f1c8-945d-4a61-87b8-c35eebc928e0",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>384342.0</td>\n",
+       "      <td>126877.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>1158773.0</td>\n",
+       "      <td>109613.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>1160600.0</td>\n",
+       "      <td>2209760.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>383237.0</td>\n",
+       "      <td>640702.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.500117</td>\n",
+       "      <td>0.92339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.499837</td>\n",
+       "      <td>0.893723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.198944</td>\n",
+       "      <td>0.730401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>-0.000122</td>\n",
+       "      <td>0.657571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.331866</td>\n",
+       "      <td>0.844199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.751469</td>\n",
+       "      <td>0.146089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.50072</td>\n",
+       "      <td>0.165295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.248774</td>\n",
+       "      <td>0.054299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.499606</td>\n",
+       "      <td>0.04726</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.352259</td>\n",
+       "      <td>0.844253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>-0.000282</td>\n",
+       "      <td>0.793505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>1.000651</td>\n",
+       "      <td>0.173494</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.751226</td>\n",
+       "      <td>0.945701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>2.008927</td>\n",
+       "      <td>0.977509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>0.999348</td>\n",
+       "      <td>17.662067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.248531</td>\n",
+       "      <td>0.853911</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.248653</td>\n",
+       "      <td>0.248653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.500082</td>\n",
+       "      <td>0.192211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500394</td>\n",
+       "      <td>0.95274</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.49928</td>\n",
+       "      <td>0.834705</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                          0          1\n",
+       "band                                      1          2\n",
+       "subsample                                 1          1\n",
+       "fn                                 384342.0   126877.0\n",
+       "fp                                1158773.0   109613.0\n",
+       "tn                                1160600.0  2209760.0\n",
+       "tp                                 383237.0   640702.0\n",
+       "accuracy                           0.500117    0.92339\n",
+       "balanced_accuracy                  0.499837   0.893723\n",
+       "critical_success_index             0.198944   0.730401\n",
+       "equitable_threat_score            -0.000122   0.657571\n",
+       "f_score                            0.331866   0.844199\n",
+       "false_discovery_rate               0.751469   0.146089\n",
+       "false_negative_rate                 0.50072   0.165295\n",
+       "false_omission_rate                0.248774   0.054299\n",
+       "false_positive_rate                0.499606    0.04726\n",
+       "fowlkes_mallows_index              0.352259   0.844253\n",
+       "matthews_correlation_coefficient  -0.000282   0.793505\n",
+       "negative_likelihood_ratio          1.000651   0.173494\n",
+       "negative_predictive_value          0.751226   0.945701\n",
+       "overall_bias                       2.008927   0.977509\n",
+       "positive_likelihood_ratio          0.999348  17.662067\n",
+       "positive_predictive_value          0.248531   0.853911\n",
+       "prevalence                         0.248653   0.248653\n",
+       "prevalence_threshold               0.500082   0.192211\n",
+       "true_negative_rate                 0.500394    0.95274\n",
+       "true_positive_rate                  0.49928   0.834705"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "combined_df = gpd.GeoDataFrame(geometry=[unary_union(polygons_categorical['geometry'])], \n",
+    "                               crs=polygons_continuous.crs)\n",
+    "combined_df.gval.create_subsampling_df(subsampling_type=[\"include\"], inplace=True)\n",
+    "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
+    "                                             metrics=\"all\",\n",
+    "                                             positive_categories=[2],\n",
+    "                                             negative_categories=[0, 1],\n",
+    "                                             subsampling_df=combined_df,\n",
+    "                                             subsampling_average=\"full-detail\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "6b02adf2-f144-477e-88d9-397418c4ba9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3a1331e40>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cat_plot(title=\"Agreement Map Inclusion\")"
+   ]
+  }
+ ],
+ "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": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/sphinx/api.rst b/docs/sphinx/api.rst
index b3de48a1..327c10fd 100644
--- a/docs/sphinx/api.rst
+++ b/docs/sphinx/api.rst
@@ -7,5 +7,7 @@ GVAL API
 
    extension
    comparison
+   subsampling
+   catalog
    statistics
    utils
diff --git a/docs/sphinx/catalog.rst b/docs/sphinx/catalog.rst
new file mode 100644
index 00000000..50a7e58c
--- /dev/null
+++ b/docs/sphinx/catalog.rst
@@ -0,0 +1,7 @@
+Catalogs
+########
+
+:doc:`Return to Homepage <../index>`
+
+.. automodule:: gval.catalogs.catalogs
+    :members:
diff --git a/docs/sphinx/index.rst b/docs/sphinx/index.rst
index 01e883ba..9010a5b1 100644
--- a/docs/sphinx/index.rst
+++ b/docs/sphinx/index.rst
@@ -19,6 +19,8 @@ ___________________________________
    SphinxTutorial
    SphinxMulticatTutorial
    SphinxContinuousTutorial
+   SphinxSubsamplingTutorial
+   SphinxCatalogTutorial
    api
    contributing
 
diff --git a/docs/sphinx/subsampling.rst b/docs/sphinx/subsampling.rst
new file mode 100644
index 00000000..a95699a7
--- /dev/null
+++ b/docs/sphinx/subsampling.rst
@@ -0,0 +1,7 @@
+Subsampling
+###########
+
+:doc:`Return to Homepage <../index>`
+
+.. automodule:: gval.subsampling.subsampling
+    :members:
diff --git a/notebooks/Catalog Tutorial.ipynb b/notebooks/Catalog Tutorial.ipynb
new file mode 100644
index 00000000..e192e984
--- /dev/null
+++ b/notebooks/Catalog Tutorial.ipynb	
@@ -0,0 +1,809 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9a3cec9a",
+   "metadata": {},
+   "source": [
+    "<img src=\"https://github.com/NOAA-OWP/gval/raw/main/docs/images/gval_light_mode.png\" style=\"float:left\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3075cb24-8ac3-4c1d-a47c-1499a7c46821",
+   "metadata": {},
+   "source": [
+    "# Catalog Comparisons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a11bac2a-a058-41c2-b8ff-a0920c0ed7df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import rioxarray as rxr\n",
+    "\n",
+    "from gval.catalogs.catalogs import catalog_compare"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "837f6d52-5395-4ee8-b929-557e37b7bf74",
+   "metadata": {},
+   "source": [
+    "## Initializing Catalogs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e52648d3-09b4-4db2-9399-56f9eeb941c6",
+   "metadata": {},
+   "source": [
+    "The cataloging functionality was designed to easily facilitate batch comparisons of maps residing locally, in a service, or in the cloud.  The format of such catalogs are as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "b66eca6a-007f-42d2-a476-054b70c2395c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "TEST_DATA_DIR = './'\n",
+    "\n",
+    "candidate_continuous_catalog = pd.read_csv(f'{TEST_DATA_DIR}candidate_catalog_0.csv')\n",
+    "benchmark_continuous_catalog = pd.read_csv(f'{TEST_DATA_DIR}benchmark_catalog_0.csv')\n",
+    "candidate_categorical_catalog = pd.read_csv(f'{TEST_DATA_DIR}candidate_catalog_1.csv')\n",
+    "benchmark_categorical_catalog = pd.read_csv(f'{TEST_DATA_DIR}benchmark_catalog_1.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2eddef14",
+   "metadata": {},
+   "source": [
+    "### Candidate Catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "972505a1",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "      <th>agreement_maps</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./candidate_categorical_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "      <td>agreement_categorical_0.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          map_id compare_id               agreement_maps\n",
+       "0  ./candidate_categorical_0.tif   compare1  agreement_categorical_0.tif\n",
+       "1  ./candidate_categorical_1.tif   compare2  agreement_categorical_1.tif"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "candidate_categorical_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8529ce2",
+   "metadata": {},
+   "source": [
+    "The catalog should have columns representing: \n",
+    "1. An identifier of a candidate map, (in this case `compare_id`) <br />\n",
+    "2. The location of the candidate map, (in this case `map_id`) <br />\n",
+    "3. The name of the agreement map to be created named `agreement_maps`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0d408d2c",
+   "metadata": {},
+   "source": [
+    "### Benchmark Catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "f09a9c91-8bc4-41bc-b11a-733412ba091d",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./benchmark_categorical_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          map_id compare_id\n",
+       "0  ./benchmark_categorical_0.tif   compare1\n",
+       "1  ./benchmark_categorical_1.tif   compare2"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "benchmark_categorical_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5acb15d0",
+   "metadata": {},
+   "source": [
+    "Similar to the previous catalog, the benchmark catalog should have columns representing: \n",
+    "1. An identifier of a candidate map, (in this case `compare_id`) <br />\n",
+    "2. The location of the candidate map, (in this case `map_id`)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "40e2fa0d",
+   "metadata": {},
+   "source": [
+    "## Categorical Catalog Comparison"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8fa314fa",
+   "metadata": {},
+   "source": [
+    "When `compare_type` is set to 'categorical' the catalog will be run as categorical comparisons.  See arguments and output below for the comparison metrics:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "d6034a81",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>map_id_candidate</th>\n",
+       "      <td>./candidate_categorical_0.tif</td>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "      <td>./candidate_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>compare_id</th>\n",
+       "      <td>compare1</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>agreement_maps</th>\n",
+       "      <td>agreement_categorical_0.tif</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "      <td>agreement_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>map_id_benchmark</th>\n",
+       "      <td>./benchmark_categorical_0.tif</td>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "      <td>./benchmark_categorical_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "      <td>844.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>5939.0</td>\n",
+       "      <td>5939.0</td>\n",
+       "      <td>5939.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>1977.0</td>\n",
+       "      <td>1977.0</td>\n",
+       "      <td>1977.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.539427</td>\n",
+       "      <td>0.539427</td>\n",
+       "      <td>0.539427</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "      <td>0.700815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                       0  \\\n",
+       "map_id_candidate           ./candidate_categorical_0.tif   \n",
+       "compare_id                                      compare1   \n",
+       "agreement_maps               agreement_categorical_0.tif   \n",
+       "map_id_benchmark           ./benchmark_categorical_0.tif   \n",
+       "band                                                   1   \n",
+       "fn                                                 844.0   \n",
+       "fp                                                 844.0   \n",
+       "tn                                                5939.0   \n",
+       "tp                                                1977.0   \n",
+       "critical_success_index                          0.539427   \n",
+       "true_positive_rate                              0.700815   \n",
+       "positive_predictive_value                       0.700815   \n",
+       "\n",
+       "                                                       1  \\\n",
+       "map_id_candidate           ./candidate_categorical_1.tif   \n",
+       "compare_id                                      compare2   \n",
+       "agreement_maps               agreement_categorical_1.tif   \n",
+       "map_id_benchmark           ./benchmark_categorical_1.tif   \n",
+       "band                                                   1   \n",
+       "fn                                                 844.0   \n",
+       "fp                                                 844.0   \n",
+       "tn                                                5939.0   \n",
+       "tp                                                1977.0   \n",
+       "critical_success_index                          0.539427   \n",
+       "true_positive_rate                              0.700815   \n",
+       "positive_predictive_value                       0.700815   \n",
+       "\n",
+       "                                                       2  \n",
+       "map_id_candidate           ./candidate_categorical_1.tif  \n",
+       "compare_id                                      compare2  \n",
+       "agreement_maps               agreement_categorical_1.tif  \n",
+       "map_id_benchmark           ./benchmark_categorical_1.tif  \n",
+       "band                                                   2  \n",
+       "fn                                                 844.0  \n",
+       "fp                                                 844.0  \n",
+       "tn                                                5939.0  \n",
+       "tp                                                1977.0  \n",
+       "critical_success_index                          0.539427  \n",
+       "true_positive_rate                              0.700815  \n",
+       "positive_predictive_value                       0.700815  "
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arguments = {\n",
+    "    \"candidate_catalog\": candidate_categorical_catalog,\n",
+    "    \"benchmark_catalog\": benchmark_categorical_catalog,\n",
+    "    \"on\": \"compare_id\",\n",
+    "    \"map_ids\": \"map_id\",\n",
+    "    \"how\": \"inner\",\n",
+    "    \"compare_type\": \"categorical\",\n",
+    "    \"compare_kwargs\": {\n",
+    "        \"metrics\": (\n",
+    "            \"critical_success_index\",\n",
+    "            \"true_positive_rate\",\n",
+    "            \"positive_predictive_value\",\n",
+    "        ),\n",
+    "        \"encode_nodata\": True,\n",
+    "        \"nodata\": -9999,\n",
+    "        \"positive_categories\": 2,\n",
+    "        \"negative_categories\": 1\n",
+    "    },\n",
+    "    \"open_kwargs\": {\n",
+    "        \"mask_and_scale\": True, \n",
+    "        \"masked\": True\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "agreement_categorical_catalog = catalog_compare(**arguments)\n",
+    "agreement_categorical_catalog.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0aa97373",
+   "metadata": {},
+   "source": [
+    "We can see the agreement maps below (and why the metrics are similar as the datasets were essentially equivalent):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "18b0df29",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for ag_map in agreement_categorical_catalog['agreement_maps'].unique():\n",
+    "    rxr.open_rasterio(ag_map, mask_and_scale=True).gval.cat_plot(title=ag_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff002dea",
+   "metadata": {},
+   "source": [
+    "## Continuous Catalog Compare"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f17d903",
+   "metadata": {},
+   "source": [
+    "The continuous catalogs are as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "a86f7eca",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "      <th>agreement_maps</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./candidate_continuous_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "      <td>./agreement_continuous_0.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./candidate_continuous_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "      <td>./agreement_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         map_id compare_id                agreement_maps\n",
+       "0  ./candidate_continuous_0.tif   compare1  ./agreement_continuous_0.tif\n",
+       "1  ./candidate_continuous_1.tif   compare2  ./agreement_continuous_1.tif"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "candidate_continuous_catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "1b94b2cc",
+   "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>map_id</th>\n",
+       "      <th>compare_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>./benchmark_continuous_0.tif</td>\n",
+       "      <td>compare1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>./benchmark_continuous_1.tif</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         map_id compare_id\n",
+       "0  ./benchmark_continuous_0.tif   compare1\n",
+       "1  ./benchmark_continuous_1.tif   compare2"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "benchmark_continuous_catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a8a1c9c",
+   "metadata": {},
+   "source": [
+    "Just like before, `compare_type` is set to 'continuous' and the catalog will be run as continuous comparisons:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "6dad7a6d",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>map_id_candidate</th>\n",
+       "      <td>./candidate_continuous_0.tif</td>\n",
+       "      <td>./candidate_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>compare_id</th>\n",
+       "      <td>compare1</td>\n",
+       "      <td>compare2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>agreement_maps</th>\n",
+       "      <td>./agreement_continuous_0.tif</td>\n",
+       "      <td>./agreement_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>map_id_benchmark</th>\n",
+       "      <td>./benchmark_continuous_0.tif</td>\n",
+       "      <td>./benchmark_continuous_1.tif</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>coefficient_of_determination</th>\n",
+       "      <td>-0.06616</td>\n",
+       "      <td>-0.329965</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean_absolute_error</th>\n",
+       "      <td>0.317389</td>\n",
+       "      <td>0.485031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean_absolute_percentage_error</th>\n",
+       "      <td>0.159568</td>\n",
+       "      <td>0.177735</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                           0  \\\n",
+       "map_id_candidate                ./candidate_continuous_0.tif   \n",
+       "compare_id                                          compare1   \n",
+       "agreement_maps                  ./agreement_continuous_0.tif   \n",
+       "map_id_benchmark                ./benchmark_continuous_0.tif   \n",
+       "band                                                       1   \n",
+       "coefficient_of_determination                        -0.06616   \n",
+       "mean_absolute_error                                 0.317389   \n",
+       "mean_absolute_percentage_error                      0.159568   \n",
+       "\n",
+       "                                                           1  \n",
+       "map_id_candidate                ./candidate_continuous_1.tif  \n",
+       "compare_id                                          compare2  \n",
+       "agreement_maps                  ./agreement_continuous_1.tif  \n",
+       "map_id_benchmark                ./benchmark_continuous_1.tif  \n",
+       "band                                                       1  \n",
+       "coefficient_of_determination                       -0.329965  \n",
+       "mean_absolute_error                                 0.485031  \n",
+       "mean_absolute_percentage_error                      0.177735  "
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arguments = {\n",
+    "    \"candidate_catalog\": candidate_continuous_catalog,\n",
+    "    \"benchmark_catalog\": benchmark_continuous_catalog,\n",
+    "    \"on\": \"compare_id\",\n",
+    "    \"map_ids\": \"map_id\",\n",
+    "    \"how\": \"inner\",\n",
+    "    \"compare_type\": \"continuous\",\n",
+    "    \"compare_kwargs\": {\n",
+    "        \"metrics\": (\n",
+    "            \"coefficient_of_determination\",\n",
+    "            \"mean_absolute_error\",\n",
+    "            \"mean_absolute_percentage_error\",\n",
+    "        ),\n",
+    "        \"encode_nodata\": True,\n",
+    "        \"nodata\": -9999,\n",
+    "    },\n",
+    "    \"open_kwargs\": {\n",
+    "        \"mask_and_scale\": True, \n",
+    "        \"masked\": True\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "agreement_continuous_catalog = catalog_compare(**arguments)\n",
+    "agreement_continuous_catalog.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "056dde35",
+   "metadata": {},
+   "source": [
+    "We can see the continuous agreement maps below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "c97ea173",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for ag_map in agreement_continuous_catalog['agreement_maps'].unique():\n",
+    "    rxr.open_rasterio(ag_map, mask_and_scale=True).gval.cont_plot(title=ag_map)"
+   ]
+  }
+ ],
+ "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": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/Subsampling Tutorial.ipynb b/notebooks/Subsampling Tutorial.ipynb
index e7be7c8a..96cab560 100644
--- a/notebooks/Subsampling Tutorial.ipynb	
+++ b/notebooks/Subsampling Tutorial.ipynb	
@@ -1,5 +1,13 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a032a578",
+   "metadata": {},
+   "source": [
+    "<img src=\"https://github.com/NOAA-OWP/gval/raw/main/docs/images/gval_light_mode.png\" style=\"float:left\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "02838b30",
@@ -10,35 +18,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 1,
    "id": "f194294a",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "time.struct_time(tm_year=2023, tm_mon=9, tm_mday=20, tm_hour=12, tm_min=5, tm_sec=8, tm_wday=2, tm_yday=263, tm_isdst=1)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "import xarray as xr\n",
     "import rioxarray as rxr\n",
-    "import gval\n",
-    "from gval import CatStats\n",
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import dask\n",
     "import geopandas as gpd\n",
-    "from gval.utils.schemas import SubsamplingDf, Sample_identifiers, Subsample_identifiers\n",
-    "from geocube.api.core import make_geocube\n",
-    "import flox\n",
-    "from flox.xarray import xarray_reduce\n",
-    "from shapely.geometry import Point\n",
-    "from typing import Union\n",
-    "from gval.comparison.pairing_functions import difference\n",
-    "import dask as da"
+    "from shapely import unary_union\n",
+    "\n",
+    "from gval import CatStats"
    ]
   },
   {
@@ -59,62 +48,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 2,
    "id": "65bee66c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\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 ((-97.72375 29.56328, -97.72304 29.558...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>POLYGON ((-97.71604 29.55635, -97.71587 29.551...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                            geometry\n",
-       "0  POLYGON ((-97.72375 29.56328, -97.72304 29.558...\n",
-       "1  POLYGON ((-97.71604 29.55635, -97.71587 29.551..."
-      ]
-     },
-     "execution_count": 80,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "data_path = '../data/data'\n",
-    "polygons_continuous = gpd.read_file(f'{data_path}/subsample_continuous_polygons.gpkg')\n",
-    "polygons_continuous"
+    "data_path = './'\n",
+    "polygons_continuous = gpd.read_file(f'{data_path}/subsample_continuous_polygons.gpkg')"
    ]
   },
   {
@@ -127,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 3,
    "id": "ce38ccc5",
    "metadata": {},
    "outputs": [
@@ -184,7 +124,7 @@
        "1             2  "
       ]
      },
-     "execution_count": 81,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -206,74 +146,194 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 4,
    "id": "6e330044",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
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-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    \n",
+       "        &lt;script&gt;\n",
+       "            L_NO_TOUCH = false;\n",
+       "            L_DISABLE_3D = false;\n",
+       "        &lt;/script&gt;\n",
+       "    \n",
+       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
+       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_fae377627d9b5a9583e577b12fcf8d5a {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "        \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
+       "                        .foliumtooltip {\n",
+       "                            \n",
+       "                        }\n",
+       "                       .foliumtooltip table{\n",
+       "                            margin: auto;\n",
+       "                        }\n",
+       "                        .foliumtooltip tr{\n",
+       "                            text-align: left;\n",
+       "                        }\n",
+       "                        .foliumtooltip th{\n",
+       "                            padding: 2px; padding-right: 8px;\n",
+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_fae377627d9b5a9583e577b12fcf8d5a&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_fae377627d9b5a9583e577b12fcf8d5a = L.map(\n",
+       "                &quot;map_fae377627d9b5a9583e577b12fcf8d5a&quot;,\n",
+       "                {\n",
+       "                    center: [29.558023998293017, -97.71753025470662],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    zoom: 10,\n",
+       "                    zoomControl: true,\n",
+       "                    preferCanvas: false,\n",
+       "                }\n",
+       "            );\n",
+       "            L.control.scale().addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
        "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
+       "            \n",
        "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_a5dcad47f74f579e058588c60d39abd0 = L.tileLayer(\n",
+       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            ).addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
+       "        \n",
+       "    \n",
+       "            map_fae377627d9b5a9583e577b12fcf8d5a.fitBounds(\n",
+       "                [[29.551956909232516, -97.72374664573506], [29.56409108735352, -97.71131386367819]],\n",
+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_ca4e4a81d59de75107d8373f4a4ab3f7.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_ca4e4a81d59de75107d8373f4a4ab3f7 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_styler,\n",
+       "                pointToLayer: geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_pointToLayer\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_add (data) {\n",
+       "            geo_json_ca4e4a81d59de75107d8373f4a4ab3f7\n",
+       "                .addData(data)\n",
+       "                .addTo(map_fae377627d9b5a9583e577b12fcf8d5a);\n",
+       "        }\n",
+       "            geo_json_ca4e4a81d59de75107d8373f4a4ab3f7_add({&quot;bbox&quot;: [-97.72374664573506, 29.551956909232516, -97.71131386367819, 29.56409108735352], &quot;features&quot;: [{&quot;bbox&quot;: [-97.72374664573506, 29.558580487446218, -97.71573863109144, 29.56409108735352], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.72374664573506, 29.563276712982983], [-97.72304085461393, 29.558580487446218], [-97.71573863109144, 29.558743362320325], [-97.72038056500351, 29.56409108735352], [-97.72374664573506, 29.563276712982983]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 1, &quot;subsample_type&quot;: &quot;exclude&quot;, &quot;weights&quot;: 2}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-97.7160372350273, 29.551956909232516, -97.71131386367819, 29.556354530833417], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.7160372350273, 29.556354530833417], [-97.7158743601532, 29.551956909232516], [-97.71131386367819, 29.55277128360305], [-97.7118024883005, 29.55518726090231], [-97.71267115429575, 29.556191655959307], [-97.7160372350273, 29.556354530833417]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 2, &quot;subsample_type&quot;: &quot;exclude&quot;, &quot;weights&quot;: 1}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_ca4e4a81d59de75107d8373f4a4ab3f7.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;subsample_type&quot;, &quot;weights&quot;, &quot;subsample_id&quot;];\n",
+       "    let aliases = [&quot;subsample_type&quot;, &quot;weights&quot;, &quot;subsample_id&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\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",
-       "      <th>subsample_type</th>\n",
-       "      <th>weights</th>\n",
-       "      <th>subsample_id</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>POLYGON ((-97.72375 29.56328, -97.72304 29.558...</td>\n",
-       "      <td>exclude</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>POLYGON ((-97.71604 29.55635, -97.71587 29.551...</td>\n",
-       "      <td>exclude</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
       ],
       "text/plain": [
-       "                                            geometry subsample_type  weights  \\\n",
-       "0  POLYGON ((-97.72375 29.56328, -97.72304 29.558...        exclude        2   \n",
-       "1  POLYGON ((-97.71604 29.55635, -97.71587 29.551...        exclude        1   \n",
-       "\n",
-       "   subsample_id  \n",
-       "0             1  \n",
-       "1             2  "
+       "<folium.folium.Map at 0x7fa3ab00e500>"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "polygons_continuous = polygons_continuous.gval.create_subsampling_df(subsampling_type=[\"exclude\", \"exclude\"], subsampling_weights=[2, 1])\n",
-    "polygons_continuous"
+    "polygons_continuous.explore()"
    ]
   },
   {
@@ -295,12 +355,74 @@
     "bds = rxr.open_rasterio(f'{data_path}/benchmark_continuous_1.tif', band_as_variable=True, mask_and_scale=True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1bb8f787-d1b0-4ca1-8e10-af5195918284",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aac9af50>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cds.gval.cont_plot(title=\"Candidate Map\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0e2c3739-2879-48a1-95f5-398aeae7c7c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aaa6d180>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bds.gval.cont_plot(title=\"Benchmark Map\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c0459cab",
    "metadata": {},
    "source": [
-    "Let's use this newly created subsampling df on a continuous comparison.  For each subsample an agreement map is created and then used to calculate continuous statistics. There are four subsampling-average types:\n",
+    "Let's use this newly created subsampling dataframe on a continuous comparison.  For each subsample an agreement map is created and then used to calculate continuous statistics. There are four subsampling-average types:\n",
     "\n",
     "1. <b>full-detail</b>: reports all metrics calculated on separate bands and subsamples.\n",
     "2. <b>band</b>: reports all metrics on subsamples with band values averaged.\n",
@@ -318,7 +440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 8,
    "id": "8153c36a",
    "metadata": {},
    "outputs": [
@@ -385,7 +507,7 @@
        "3         2    2              -0.143187"
       ]
      },
-     "execution_count": 83,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -393,11 +515,81 @@
    "source": [
     "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
     "                                      metrics=[\"mean_percentage_error\"],\n",
-    "                                     subsampling_df=polygons_continuous,\n",
-    "                                     subsampling_average=\"full-detail\")\n",
+    "                                      subsampling_df=polygons_continuous,\n",
+    "                                      subsampling_average=\"full-detail\")\n",
     "met"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d31b4b76-4300-46ee-9350-a4d5e94fb2cf",
+   "metadata": {},
+   "source": [
+    "The agreement maps for each subsample will look as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "cb0f69d3-8d88-4945-a2f1-55cee672d427",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa732590>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cont_plot(title=\"Agreement Map 1st Exclusion\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a14bedab-6669-4d14-8f6c-cc4d49bf219b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa6e5cc0>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[1].gval.cont_plot(title=\"Agreement Map 2nd Exclusion\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "100a159d",
@@ -408,7 +600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 11,
    "id": "740f2f48",
    "metadata": {},
    "outputs": [
@@ -461,7 +653,7 @@
        "1         2  averaged               0.011964"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -484,7 +676,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 12,
    "id": "ca0131f3",
    "metadata": {},
    "outputs": [
@@ -537,7 +729,7 @@
        "1  averaged    2              -0.127515"
       ]
      },
-     "execution_count": 85,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -560,7 +752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 13,
    "id": "b30d4794",
    "metadata": {},
    "outputs": [
@@ -613,7 +805,7 @@
        "1  averaged    2              -0.037281"
       ]
      },
-     "execution_count": 86,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -628,52 +820,16 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e17ce32e",
-   "metadata": {},
-   "source": [
-    "## Categorical"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "id": "13730e57",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Subsampling DF\n",
-    "polygons_categorical = gpd.read_file(f'{data_path}/subsample_two-class_polygons.gpkg')\n",
-    "polygons_categorical.gval.create_subsampling_df(subsampling_type=[\"exclude\", \"exclude\"], inplace=True)\n",
-    "\n",
-    "# Candidate and Benchmark\n",
-    "cda = rxr.open_rasterio(f'{data_path}/candidate_map_multiband_two_class_categorical.tif', mask_and_scale=True)\n",
-    "bda = rxr.open_rasterio(f'{data_path}/benchmark_map_multiband_two_class_categorical.tif', mask_and_scale=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d3e01d77",
-   "metadata": {},
-   "source": [
-    "Just as done earlier in continuous comparison, the following performs subsampling on categorical comparisons..  For each subsample an agreement map, a cross-tabulation table, and a metric table is created. There are three subsampling-average types:\n",
-    "\n",
-    "1. <b>full-detail</b>: reports all metrics calculated on separate bands and subsamples.\n",
-    "2. <b>band</b>: reports all metrics on subsamples with band values averaged.\n",
-    "3. <b>subsample</b>: reports all metrics on bands with subsample values averaged."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "df0c50d5",
+   "id": "37019088-5a21-444e-81f4-4face46dff38",
    "metadata": {},
    "source": [
-    "#### Full-detail"
+    "If one desires to have only one subsample with all of the exclusions combined use Shapely's `unary_union`:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
-   "id": "910e7d59",
+   "execution_count": 14,
+   "id": "bbd026aa-6a33-4fee-ab2c-c5d852bbc33d",
    "metadata": {},
    "outputs": [
     {
@@ -697,206 +853,917 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>band</th>\n",
        "      <th>subsample</th>\n",
-       "      <th>fn</th>\n",
-       "      <th>fp</th>\n",
-       "      <th>tn</th>\n",
-       "      <th>tp</th>\n",
-       "      <th>accuracy</th>\n",
-       "      <th>balanced_accuracy</th>\n",
-       "      <th>critical_success_index</th>\n",
-       "      <th>equitable_threat_score</th>\n",
-       "      <th>f_score</th>\n",
-       "      <th>false_discovery_rate</th>\n",
-       "      <th>false_negative_rate</th>\n",
-       "      <th>false_omission_rate</th>\n",
-       "      <th>false_positive_rate</th>\n",
-       "      <th>fowlkes_mallows_index</th>\n",
-       "      <th>matthews_correlation_coefficient</th>\n",
-       "      <th>negative_likelihood_ratio</th>\n",
-       "      <th>negative_predictive_value</th>\n",
-       "      <th>overall_bias</th>\n",
-       "      <th>positive_likelihood_ratio</th>\n",
+       "      <th>band</th>\n",
+       "      <th>mean_percentage_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.133122</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>-0.117482</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  subsample band  mean_percentage_error\n",
+       "0         1    1               0.133122\n",
+       "1         1    2              -0.117482"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "combined_df = gpd.GeoDataFrame(geometry=[unary_union(polygons_continuous['geometry'])], \n",
+    "                               crs=polygons_continuous.crs)\n",
+    "combined_df.gval.create_subsampling_df(subsampling_type=[\"exclude\"], inplace=True)\n",
+    "ag, met = cds.gval.continuous_compare(benchmark_map=bds,\n",
+    "                                      metrics=[\"mean_percentage_error\"],\n",
+    "                                      subsampling_df=combined_df,\n",
+    "                                      subsampling_average=\"full-detail\")\n",
+    "met"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "db842a2f-e30d-4ea7-800c-838bb8842b1f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3aa4e0820>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cont_plot(title=\"Agreement Map Exclusion\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e17ce32e",
+   "metadata": {},
+   "source": [
+    "## Categorical"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "13730e57",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
+       "&lt;html&gt;\n",
+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    \n",
+       "        &lt;script&gt;\n",
+       "            L_NO_TOUCH = false;\n",
+       "            L_DISABLE_3D = false;\n",
+       "        &lt;/script&gt;\n",
+       "    \n",
+       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
+       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
+       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
+       "    \n",
+       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_7a482419a882361faafe71791ce249e6 {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
+       "                    left: 0.0%;\n",
+       "                    top: 0.0%;\n",
+       "                }\n",
+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "        \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
+       "                        .foliumtooltip {\n",
+       "                            \n",
+       "                        }\n",
+       "                       .foliumtooltip table{\n",
+       "                            margin: auto;\n",
+       "                        }\n",
+       "                        .foliumtooltip tr{\n",
+       "                            text-align: left;\n",
+       "                        }\n",
+       "                        .foliumtooltip th{\n",
+       "                            padding: 2px; padding-right: 8px;\n",
+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_7a482419a882361faafe71791ce249e6&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_7a482419a882361faafe71791ce249e6 = L.map(\n",
+       "                &quot;map_7a482419a882361faafe71791ce249e6&quot;,\n",
+       "                {\n",
+       "                    center: [30.00813899359811, -97.33918187936801],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    zoom: 10,\n",
+       "                    zoomControl: true,\n",
+       "                    preferCanvas: false,\n",
+       "                }\n",
+       "            );\n",
+       "            L.control.scale().addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_c35eec0dfcda0a07ce9d98360ffc13c2 = L.tileLayer(\n",
+       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            ).addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "        \n",
+       "    \n",
+       "            map_7a482419a882361faafe71791ce249e6.fitBounds(\n",
+       "                [[29.938469924981753, -97.56735097529567], [30.077808062214462, -97.11101278344036]],\n",
+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_42f502bfad8fb4b20ee4ac133ef66803.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_42f502bfad8fb4b20ee4ac133ef66803_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_42f502bfad8fb4b20ee4ac133ef66803 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_42f502bfad8fb4b20ee4ac133ef66803_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_42f502bfad8fb4b20ee4ac133ef66803_styler,\n",
+       "                pointToLayer: geo_json_42f502bfad8fb4b20ee4ac133ef66803_pointToLayer\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_42f502bfad8fb4b20ee4ac133ef66803_add (data) {\n",
+       "            geo_json_42f502bfad8fb4b20ee4ac133ef66803\n",
+       "                .addData(data)\n",
+       "                .addTo(map_7a482419a882361faafe71791ce249e6);\n",
+       "        }\n",
+       "            geo_json_42f502bfad8fb4b20ee4ac133ef66803_add({&quot;bbox&quot;: [-97.56735097529567, 29.938469924981753, -97.11101278344036, 30.077808062214462], &quot;features&quot;: [{&quot;bbox&quot;: [-97.56735097529567, 29.96872487790609, -97.29513995428285, 30.07450190965067], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.56735097529567, 30.07450190965067], [-97.5180015379423, 29.96872487790609], [-97.29513995428285, 29.97237224487936], [-97.36734101708505, 30.04412406749238], [-97.44813361508811, 30.06807403338502], [-97.56735097529567, 30.07450190965067]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 1, &quot;subsample_type&quot;: &quot;include&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-97.2165793929137, 29.938469924981753, -97.11101278344036, 30.077808062214462], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[-97.2165793929137, 30.070110147912505], [-97.20986142764495, 29.95981101477043], [-97.11101278344036, 29.938469924981753], [-97.1296905666604, 30.077808062214462], [-97.2165793929137, 30.070110147912505]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;subsample_id&quot;: 2, &quot;subsample_type&quot;: &quot;include&quot;}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_42f502bfad8fb4b20ee4ac133ef66803.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;subsample_type&quot;, &quot;subsample_id&quot;];\n",
+       "    let aliases = [&quot;subsample_type&quot;, &quot;subsample_id&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x7fa3aa3847c0>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Subsampling DF\n",
+    "polygons_categorical = gpd.read_file(f'{data_path}/subsample_two-class_polygons.gpkg')\n",
+    "polygons_categorical.gval.create_subsampling_df(subsampling_type=[\"include\", \"include\"], inplace=True)\n",
+    "polygons_categorical.explore()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "29db6c85-8072-430e-8b59-d87a602ae849",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Candidate and Benchmark\n",
+    "cda = rxr.open_rasterio(f'{data_path}/candidate_map_multiband_two_class_categorical.tif', mask_and_scale=True)\n",
+    "bda = rxr.open_rasterio(f'{data_path}/benchmark_map_multiband_two_class_categorical.tif', mask_and_scale=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "cf163d20-ce17-448a-af75-d04eb675075e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa399f6e290>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cda.gval.cat_plot(\"Candidate Map\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "8881be72-af9f-4579-b21f-dd8b08a72a0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa38a781ba0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bda.gval.cat_plot(\"Benchmark Map\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d3e01d77",
+   "metadata": {},
+   "source": [
+    "Just as done earlier in continuous comparison, the following performs subsampling on categorical comparisons..  For each subsample an agreement map, a cross-tabulation table, and a metric table is created. There are three subsampling-average types:\n",
+    "\n",
+    "1. <b>full-detail</b>: reports all metrics calculated on separate bands and subsamples.\n",
+    "2. <b>band</b>: reports all metrics on subsamples with band values averaged.\n",
+    "3. <b>subsample</b>: reports all metrics on bands with subsample values averaged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df0c50d5",
+   "metadata": {},
+   "source": [
+    "#### Full-detail"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "910e7d59",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>201953.0</td>\n",
+       "      <td>182389.0</td>\n",
+       "      <td>68239.0</td>\n",
+       "      <td>58638.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>761242.0</td>\n",
+       "      <td>397531.0</td>\n",
+       "      <td>43646.0</td>\n",
+       "      <td>65967.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>762262.0</td>\n",
+       "      <td>398338.0</td>\n",
+       "      <td>1479858.0</td>\n",
+       "      <td>729902.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>201936.0</td>\n",
+       "      <td>181301.0</td>\n",
+       "      <td>335650.0</td>\n",
+       "      <td>305052.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.50026</td>\n",
+       "      <td>0.499879</td>\n",
+       "      <td>0.94195</td>\n",
+       "      <td>0.892541</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.500157</td>\n",
+       "      <td>0.499506</td>\n",
+       "      <td>0.901198</td>\n",
+       "      <td>0.877941</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.173316</td>\n",
+       "      <td>0.238171</td>\n",
+       "      <td>0.749997</td>\n",
+       "      <td>0.70999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>0.000104</td>\n",
+       "      <td>-0.000426</td>\n",
+       "      <td>0.696008</td>\n",
+       "      <td>0.602268</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.29543</td>\n",
+       "      <td>0.384715</td>\n",
+       "      <td>0.857141</td>\n",
+       "      <td>0.830402</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.790344</td>\n",
+       "      <td>0.686781</td>\n",
+       "      <td>0.115071</td>\n",
+       "      <td>0.1778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.500021</td>\n",
+       "      <td>0.501496</td>\n",
+       "      <td>0.168955</td>\n",
+       "      <td>0.161231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.209448</td>\n",
+       "      <td>0.31407</td>\n",
+       "      <td>0.044079</td>\n",
+       "      <td>0.074363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.499665</td>\n",
+       "      <td>0.499493</td>\n",
+       "      <td>0.028648</td>\n",
+       "      <td>0.082887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.323765</td>\n",
+       "      <td>0.395147</td>\n",
+       "      <td>0.857564</td>\n",
+       "      <td>0.830444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>0.000255</td>\n",
+       "      <td>-0.000918</td>\n",
+       "      <td>0.821398</td>\n",
+       "      <td>0.751849</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>0.999373</td>\n",
+       "      <td>1.001976</td>\n",
+       "      <td>0.173938</td>\n",
+       "      <td>0.175802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.790552</td>\n",
+       "      <td>0.68593</td>\n",
+       "      <td>0.955921</td>\n",
+       "      <td>0.925637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>2.384759</td>\n",
+       "      <td>1.591553</td>\n",
+       "      <td>0.93911</td>\n",
+       "      <td>1.020152</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>1.000628</td>\n",
+       "      <td>0.99802</td>\n",
+       "      <td>29.0084</td>\n",
+       "      <td>10.119461</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_predictive_value</th>\n",
+       "      <td>0.209656</td>\n",
+       "      <td>0.313219</td>\n",
+       "      <td>0.884929</td>\n",
+       "      <td>0.8222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.499922</td>\n",
+       "      <td>0.500248</td>\n",
+       "      <td>0.156594</td>\n",
+       "      <td>0.239171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500335</td>\n",
+       "      <td>0.500507</td>\n",
+       "      <td>0.971352</td>\n",
+       "      <td>0.917113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.499979</td>\n",
+       "      <td>0.498504</td>\n",
+       "      <td>0.831045</td>\n",
+       "      <td>0.838769</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         0         1          2          3\n",
+       "band                                     1         1          2          2\n",
+       "subsample                                1         2          1          2\n",
+       "fn                                201953.0  182389.0    68239.0    58638.0\n",
+       "fp                                761242.0  397531.0    43646.0    65967.0\n",
+       "tn                                762262.0  398338.0  1479858.0   729902.0\n",
+       "tp                                201936.0  181301.0   335650.0   305052.0\n",
+       "accuracy                           0.50026  0.499879    0.94195   0.892541\n",
+       "balanced_accuracy                 0.500157  0.499506   0.901198   0.877941\n",
+       "critical_success_index            0.173316  0.238171   0.749997    0.70999\n",
+       "equitable_threat_score            0.000104 -0.000426   0.696008   0.602268\n",
+       "f_score                            0.29543  0.384715   0.857141   0.830402\n",
+       "false_discovery_rate              0.790344  0.686781   0.115071     0.1778\n",
+       "false_negative_rate               0.500021  0.501496   0.168955   0.161231\n",
+       "false_omission_rate               0.209448   0.31407   0.044079   0.074363\n",
+       "false_positive_rate               0.499665  0.499493   0.028648   0.082887\n",
+       "fowlkes_mallows_index             0.323765  0.395147   0.857564   0.830444\n",
+       "matthews_correlation_coefficient  0.000255 -0.000918   0.821398   0.751849\n",
+       "negative_likelihood_ratio         0.999373  1.001976   0.173938   0.175802\n",
+       "negative_predictive_value         0.790552   0.68593   0.955921   0.925637\n",
+       "overall_bias                      2.384759  1.591553    0.93911   1.020152\n",
+       "positive_likelihood_ratio         1.000628   0.99802    29.0084  10.119461\n",
+       "positive_predictive_value         0.209656  0.313219   0.884929     0.8222\n",
+       "prevalence                        0.209552  0.313645   0.209552   0.313645\n",
+       "prevalence_threshold              0.499922  0.500248   0.156594   0.239171\n",
+       "true_negative_rate                0.500335  0.500507   0.971352   0.917113\n",
+       "true_positive_rate                0.499979  0.498504   0.831045   0.838769"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
+    "                                             metrics=\"all\",\n",
+    "                                             positive_categories=[2],\n",
+    "                                             negative_categories=[0, 1],\n",
+    "                                             subsampling_df=polygons_categorical,\n",
+    "                                             subsampling_average=\"full-detail\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08429c79-4f1b-4e47-b5c7-1061e1f2ff82",
+   "metadata": {},
+   "source": [
+    "The agreement map will look as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "5268a23d-761a-44d5-b8e2-97714a2618b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa39a335600>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cat_plot(title=\"Agreement Map 1st Inclusion\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b335f4dc-b7ac-4004-bf71-6fca84124fa8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3a6fa5d80>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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mLNu9ezex2WwkLi7O8BZR3nvvPQKAZGdnE6/XG9QeNfayG7fTTz9d2A/qcdm0aVPQOp/PR/Ly8ojFYjFuxt1uN+nfvz9JTEwUeokaGxtJeno66dOnT0A/6fnedtttQfvMnTuXACCHHnpo0FPijRs3Cm9AIu03OxYib8OXX34pPE6shBQhhJx33nlE13Xyv//9jxDiL+IAgLz99tuEELmQMuOggw4i/fr1C1jGCql33303aJ/ly5cTAAFPv6OBtpOamipMfKd9eO+994LW0Rt7dlzXrVtn/A48Hk/QPscdd1zMhVS4ffv8888JADJw4MCgZH0RsRRS8fHxpE+fPiGPSYhYSO3bt4/Ex8cTXdeFntTHH3+cACCTJ08OWE7H7plnngnaZ/HixULBJqOmpoYAIFlZWdJt6PHM/livHyFiIbV9+3ayePFiYrfbhQLokUceIYmJiUFtH3LIIeT+++8n+/fvD9h+xIgRBABZu3atsN9//OMfA7zVs2bNIh9//HHANq+//joZPnw4+cMf/hC0/xtvvCEcy3CE1AsvvBBwDhaLhSxatIg0NTWZ7sdy/vnnE8DvweY9jH/+858JAGK1WklqaipZtWoV+f3338nmzZvJzJkzCQDidDqNaxrPX/7yFwKAPPLII2H3R6FQxB6VI6XoVWzbtg0fffQRUlNTceaZZxrL+/XrhylTpqCpqQmvvfZawD6ffvopAH9pYF0P/idx/vnnmx7zrLPOClq2c+dObNy4EdnZ2TjiiCOC1muahnHjxsHr9aK0tBQA8NVXX2H37t0YO3Ys0tLSgvaJj4+Hy+XCnj17UFFREbT+lFNOCVp26KGHAvDnUdH4fn5ddXV1u/odqg/Dhg0LOk6smTlzJnw+n1GW+KWXXsLAgQOF/eH57bffsGLFCtxwww24/PLLcemll+LSSy+F2+3Gb7/9ht9//z1on759++Lkk08OWk5zVD777LOoc6U+/vhjXHfdddA0DX//+9+Fie+AP19j4sSJQctF4/3xxx8DAGbMmAGLxSLtd6yIpG/vv/++0Qc+Wb+jof+eLr/88qjKapeWlhplq0UFFv7whz8A8F9jRL+HWPx72blzJwCElfszffp0zJo1S/iXk5Mj3GfixIlG/uJBBx2EG2+8EW63G7feemtQKfO5c+di27Zt+Nvf/oaLLroI2dnZAPy5hQsWLMDEiROxf//+sM4LgFH2nP376aefArY555xz8MMPP+Af//hHwPK9e/dizpw5GDZsWFj5VzwzZ84EIQTNzc3YvHkzbrnlFixcuBDjx48Pa0qFBx54AK+++ir69u2Ll156yciJo9Dfg8fjwdNPP40LL7wQffr0wbBhw/DCCy/gmGOOQV1dHZ588klh+3379gXQlpumUCi6BjWPlKJX8dJLL4EQghkzZsDhcASsmzlzJv7973/jxRdfxJ/+9CdjOb1hGTx4sLBNvqJaOOvpJKUVFRVBBpRn9+7dAfu89957Ye0zfPjwgGUHHXRQ0HZ0zhizdWzyfzT9Zhk0aFDQMnpzLCsyEAtOPfVU9OvXDy+99BImT56M7777Dtdcc4100k3Kyy+/jCuvvBL79u2TbrN3717jpoVy8MEHC7d1Op1ITU1FbW0t9uzZg379+kV0Ht9++y3OPvtstLS04PHHH8c555wj3TY9PV0oikTjTRPdZf0WFWFoD5H0jRYsOOyww2Lah3BYtmwZpk6dir///e/4+9//jrS0NIwfPx7Tpk2Tik4WOq6y8UtNTYXT6URdXZ3w9xCLfy+0yEo4InTx4sURf9d0HilN0xAfH4+hQ4firLPOwtChQ4Xb9+3bF1dccQWuuOIKAP7JapctW4ZHHnkEJSUleOSRR/CXv/wFAIzxEF1LAL/IoFx11VV4+umnw+73rbfeiv/97394//33g2xBJNjtdgwbNgyLFi1C3759ccMNN+COO+7A0qVLpfu8+OKLWLBgARITE/H2228bD61Y6PU3KSkJ5557btD6yy67DF988QU2bNggPAatbhhpYRKFQhFblJBS9CpoifP169fj+OOPD1hHq9d99NFH+OWXX6Q3lZESFxcXtIw+bUxPT0dBQYHp/rQfdJ+hQ4di3LhxpvuIbtBF3rRw1rFE0+9ojhNrbDYbzjvvPCxfvhy33norAJhW6wP8N3i0EuOjjz6K008/HQcddBDi4+MBAGPHjkVxcTEIIR3ad0plZSVOOeUU7NmzB3fddReuueYa0+27aqzDobv1TeYdHDVqFMrLy7F27VoUFhZi/fr1+Oc//4l//vOfyM/Px/r16yOq0CbC7IFELMbJ6XQC8Av+juCWW27BhAkTot7/4IMPxoMPPgiPx4MlS5bg7bffNoRUbm4uPv30U3z99dfCiXrbw3/+8x/ExcXhnnvuwT333BO03uv1Guf16KOPIi8vL2Sbf/jDH3DDDTfg3//+t1RIvfXWW7jssstgs9nw+uuvY8yYMcLt6PVzyJAhwt8IFbzU48hDBXRqamrIfisUio5DCSlFr6G0tBTff/89AOCnn34KCgGhEELw0ksvGTfcGRkZAAJL+bLIlptBnzT3798fK1eujGifESNGhL1PrImm392FmTNnYvny5Vi7di2GDRuGY4891nT7wsJCtLS04MYbb8R1110XtP7nn3+W7rtt2zbh8vr6etTW1iI+Pj6iG5zq6mqcfPLJqK6uxnXXXYc777wz7H3Dgf7Gf/nlF+F62fLOgHqCt2zZ0q52qOAReRfN/g3HxcVh6tSpmDp1KgB/ifiLLroIxcXFePbZZ425g0TQsEvZ+NXV1Rm/h/aU3TZj4MCBACAMQe1OTJo0CUuWLAnwPp122ml48skn8dprr+GBBx4I6QGMlKamJqlHB4CxLlyvTt++faHrujScbsOGDTj33HNBCMGqVatMQ4tpCXlZmCD9PqnniofuF0m5eYVCEXu612NDhaId0LmjbrzxRhB/IZWgPzrHDN0WgOH9WbNmjdD78M9//jPivgwaNAgjRoxAeXl5WHPgAMAxxxwDp9OJDRs2dNlNUTT9jhZ648uG77SHsWPHIjc3F/369TMmwTSD3oiIwqs++ugj1NTUSPf97bff8MEHHwQtp/MG5efnh31TuGfPHhQUFGDLli247LLLsGTJkrD2i4QTTjgBgH/SVJF3RjbfUWcwefJkAP4wS7MQy1BQsSj63b733ntht3P44Ydj9uzZAPyhlma4XC7Ex8ejtLRUmLdIrzPjxo3rMC/dwIEDkZ6ejl9//VU4z1xnEcpzSx9ssWHGU6ZMwciRI7Ft2zbcf//9Me3P1q1bpXYAACwWi/E5XI/bxx9/DJ/PJwxD/eqrr3DWWWehubkZzz77LKZPn27a1tixY9GvXz/s2LEDmzdvDlpPRZ5sgmX60DAcT5pCoeg4lJBS9Aq8Xq8xc7xZ4vwJJ5yAgw46CN9//71RLGHSpEnIzs7G5s2b8eCDDwZsv3LlSiNRP1Juv/12+Hw+TJ8+HWVlZUHrf/vtt4AJFR0OB+bPn4+9e/di2rRpQo/I9u3bjfDFjiLSfkcLfZovuomIlrKyMuzevRs333xzyG1pUv+LL76IhoYGY/n27dtx1VVXhdz/xhtvDJicuLKyEgsXLgQA40Y8FI2NjTj99NOxadMmnHfeeXjmmWdC5qZFw4QJEzBixAhs2bIFixYtClj39NNPo7i4OObHDJdjjz0WEydOxM6dO3HllVcGfBeA/4Z406ZNIdsZP348AGD58uUB30tZWRnuuOOOoO0bGxvx+OOPB3kjfD6fMUmxLG+SkpiYiD/+8Y/w+XyYPXt2QN9//PFHY6yvvfbakP1vDyeccAK8Xi++/vrrDj2OGWeddRYef/xx4UOgzz//3AivmzFjhrFc13W88MILcDgcuP322zF//vygibUB/zVHdp1Ys2YNRowYgUsuuSQm5/HQQw8JvURffPGFkfd12WWXBazbvHkzTj31VNTX1+Oxxx4LmrxdhNVqxbx580AIwezZs1FfX2+se//9940JoP/85z8L9//vf/8Lu90uDR1UKBSdgwrtU/QK3n33XdTU1GDYsGE46qijpNvpuo7zzz8fjzzyCF544QW4XC7ouo7nn38ekydPxi233IKXX34ZOTk52LJlC7744gvMnj0by5YtizhX4qKLLsJ3332H++67Dy6XC3l5eTjssMNACMGWLVvwzTffICkpyTDOgD8f4YcffsALL7yAkSNHYvTo0cjKykJLSws2b96M8vJyjBo1yqgG1hFE0+9oOOWUUxAXF4clS5bg22+/RWZmJjRNw0033RRUSKMjOOuss3D44Yfjyy+/NPLSmpqa8OGHHyIvLw9jx47FZ599Jtx3zJgxaGlpwdChQzFp0iS43W588MEHaGxsxMyZMzFt2rSw+vCXv/wFxcXFsFgssFqtuPzyy4XbtTfMUtd1rFy5EieddBLuvPNOrF69GkcccQR++uknfPnll7j66qul1cE6gxdeeAEnnXQSXn75ZRQVFeH444+Hw+HAli1bUFZWhocffhhHHnmkaRsTJ07E+PHjsWHDBuTk5GDcuHHYvXs3Pv/8c1x77bVYvHhxwPYtLS247rrrcOONN8LlcuGQQw5BS0sLvvjiC/z666845JBDcOWVV4bs+/3334+SkhK89957OPTQQzF+/Hg0NDRg3bp1aGpqwrXXXhtQQbQjOP300/Haa69h/fr1pvmVN954ozRULCEhoV2/gV9//RXXXXcdbrjhBuTl5SErKws+n8/4DgHgzDPPDBIGLpcL77//Ps4991w89NBDePzxx3HcccchMzMTTU1N+N///oeNGzfC7XZjxIgROProowP2r6urw+bNm5Genh5131nmz5+P2267DaNHjzZ+Ez///DM2btwIADjvvPOCQoEvuOAC7Nq1CwMGDEBpaalQSI0YMQK33HJLwLKbbroJH374Id5//30MGzYMY8aMwe7du1FSUgKv14t7771XGKK8ZcsW/O9//8Opp55q5HQqFIouovMqrSsUHceFF14Y9twrX3zxhTFvjdvtNpaXlZWRM844g6SkpJDExEQybtw48s4775AXX3yRACC33HJLQDuh5q2hbNiwgZx77rkkMzOT2Gw20q9fPzJq1CgyZ84csmHDBuE+//73v8npp59OBg4cSGw2Gxk4cCBxuVxk/vz5pLS0NGBbOt+LaLJN2SSiFAjm1omm39HM4UMIIUVFRWTcuHEkKSnJmK8lnLme+HmkQiGbR+r3338n//d//0cOOeQQ4nA4yKGHHkpuvvlm0tDQIBxXOo/U+PHjSW1tLbn66qtJZmYmsdvtZPjw4WTx4sXCeZpCnUeoPx6z783sO//mm2/ImWeeSZxOJ0lMTCT5+fnkrbfeks7NZIbZPFLR9K2+vp4sXLiQjBo1isTHx5OkpCQyYsQIMmfOnICJoc36WltbS6666iqSlpZGHA4HOfzww8ny5cuF/XK73WTZsmVk2rRp5LDDDiMJCQkkNTWVjBo1itx9993kt99+C7vv+/btI3fffTfJyckhDoeDJCcnk+OPP56sWrXKdOxERPNdNDY2EqfTSXJyckyPZ/bndDoD9jGbkFdERUUFefzxx8mZZ55Jhg0bRpKSkojNZiMZGRnk9NNPJ6tWrQqaS4mloaGBPPbYY+Skk04iaWlpxGazkaSkJDJ8+HBy8cUXkzVr1gRcrymhJuQVAZN5pJYuXUqmTZtGDj30UJKYmEjsdjs56KCDyNlnny2daDuc8ZX1r6WlhTzwwAPk8MMPJ3FxcSQlJYVMmjQpaBJnloULFxIIJvlVKBSdj0ZIJ5WkUih6KLTs7iuvvBJyTilF72br1q3IysrC+PHjjXw7haI7MHfuXDz66KP48ssv4XK5uro7ig6CEIKRI0di37592Lp1a8gpHhQKRceicqQUCvgrJNE5lFheffVVPPvss0hNTcUZZ5zR+R1TKBSKMFiwYAGSkpJiXrRB0b144403sHnzZixcuFCJKIWiG6D+FSoU8CeG5+fnY9SoUcbkid9//z02b94Mi8WCp59+GomJiV3cS4VCoRAzcOBA3HTTTbjrrruwadOmkDllip4HIQQLFy7EEUccEVZBC4VC0fGo0D6FAv5JDxcuXIh169ahqqoKDQ0N6N+/P8aOHYsbb7wR+fn5Xd1FRTdAhfYpFAqFQqGgKCGlUCgUCoVCoVAoFBGicqQUCoVCoVAoFAqFIkKUkFIoFAqFQqFQKBSKCFFCSqFQKBQKhUKhUCgiRAkphUKhUCgUCoVCoYgQJaQUCoVCoVAoFAqFIkKUkFIoFAqFQqFQKBSKCFFCSqFQKBQKhUKhUCgiRAkphUKhUCgUCoVCoYgQJaQUCoVCoVAoFAqFIkKUkFIcMNx1113QNK2ru6FQKBQKRY9D2VCFIhglpBQxZ+XKldA0LeBv4MCBmDhxIt55552u7l5INm/ejLlz52Ls2LGIi4uDpmnYunVrV3dLoVAoFAcAPd2Gvv766zj//PNx6KGHIiEhAcOHD8cNN9yA2traru6aQhFzrF3dAUXvZeHChcjKygIhBDU1NVi5ciWmTJmC//znPzjjjDO6untSiouL8fjjjyMnJwcjR45EWVlZV3dJoVAoFAcYPdWGXnnllcjMzMTMmTMxZMgQbNq0CU888QQKCwvx1VdfIT4+vqu7qFDEDCWkFB3GaaedhqOPPtr4fPnllyMtLQ0vv/xytzYCZ511Fmpra5GcnIzFixcrIaVQKBSKTqen2tDVq1djwoQJActcLhdmzZqFl156CX/605+6pmMKRQegQvsUnUZqairi4+NhtQbq98WLF2Ps2LHo168f4uPj4XK5sHr16qD9NU3DnDlz8MYbb+CII46Aw+HA4YcfjrVr1wZt+8knn+CYY45BXFwcDjvsMDz99NNh97Nv375ITk6O/AQVCoVCoeggeooN5UUUAJxzzjkAgO+//z7sdhSKnoDySCk6jLq6OuzevRuEEOzcuRNLly7Fvn37MHPmzIDtHnvsMZx11lm4+OKL0dLSgldeeQXnnnsu3nrrLZx++ukB237yySd4/fXXcfXVVyM5ORmPP/44pk+fjm3btqFfv34AgE2bNuGUU07BgAEDcNddd8Hj8eDOO+9EWlpap527QqFQKBTtoTfZ0B07dgAA+vfvH3UbCkW3hCgUMWbFihUEQNCfw+EgK1euDNq+sbEx4HNLSws54ogjyKRJkwKWAyB2u5389NNPxrKNGzcSAGTp0qXGsqlTp5K4uDjyyy+/GMvKy8uJxWIhkf7kH3roIQKAVFZWRrSfQqFQKBTR0JtsKOXyyy8nFouF/Pjjj1Htr1B0V5RHStFhLFu2DMOGDQMA1NTU4MUXX8Sf/vQnJCcnY9q0acZ2bOLpnj174PV6ccIJJ+Dll18OanPy5Mk47LDDjM+jRo1CSkoKfv75ZwCA1+tFUVERpk6diiFDhhjbjRw5EgUFBSgsLIz5eSoUCoVCEWt6iw1dtWoVnnvuOcyfPx/Z2dkR769QdGeUkFJ0GMcee2xAouyFF16I0aNHY86cOTjjjDNgt9sBAG+99RYWLVqEsrIyNDc3G9uL5qtgL+yUPn36YM+ePQCAXbt2Yf/+/cKL9fDhw5WQUigUCkWPoDfY0I8//hiXX345CgoKcO+990a0r0LRE1DFJhSdhq7rmDhxIqqrq1FRUQHAf5E966yzEBcXhyeffBKFhYV47733cNFFF4EQEtSGxWIRti3aVqFQKBSK3kJPs6EbN27EWWedhSOOOAKrV68OKpKhUPQG1K9a0al4PB4AwL59+wAA//rXvxAXF4eioiI4HA5juxUrVkTV/oABAxAfH28YGZbNmzdH1aZCoVAoFN2BnmJDt2zZglNPPRUDBw5EYWEhkpKSouqPQtHdUR4pRafhdrvx7rvvwm63Y+TIkQD8T8c0TYPX6zW227p1K954442ojmGxWFBQUIA33ngD27ZtM5Z///33KCoqalf/FQqFQqHoKnqKDd2xYwdOOeUU6LqOoqIiDBgwIKq+KBQ9AeWRUnQY77zzDn744QcAwM6dO7Fq1SpUVFTglltuQUpKCgDg9NNPxyOPPIJTTz0VF110EXbu3Illy5Zh6NCh+Oabb6I67t133421a9fihBNOwNVXXw2Px4OlS5fi8MMPD6vNuro6LF26FADw6aefAgCeeOIJpKamIjU1FXPmzImqXwqFQqFQhEtPtaGnnnoqfv75Z8yfPx+ffPIJPvnkE2NdWloaTj755Kj6pVB0S7q2aKCiNyIq3RoXF0fy8vLI8uXLic/nC9j+ueeeI9nZ2cThcJARI0aQFStWkDvvvDOozCoAMnv27KDjHXzwwWTWrFkByzZs2EBcLhex2+3k0EMPJU899ZSwTRGVlZXC0rMAyMEHHxzxeCgUCoVCES493YbK7CcAMn78+IjHQ6HozmiEqCx9hUKhUCgUCoVCoYgElSOlUCgUCoVCoVAoFBGihJRCoVAoFAqFQqFQRIgSUgqFQqFQKBQKhUIRIUpIKRQKhUKhUCgUCkWEKCGlUCgUCoVCoVAoFBGihJRCoVAoFAqFQqFQRIiakDdKfD4fqqqqkJycDE3Turo7CkWXQwjB3r17kZmZCV1Xz2gUCoUcZUMVikCUDe2ZKCEVJVVVVRg8eHBXd0Oh6Hb8+uuvGDRoUFd3Q6FQdGOUDVUoxCgb2rNQQipKkpOTAQDff/u18T5cCCHwEgKvF7BYAIumBT2RI4SgqbkFNnsCWpobYLNZoes6PF7A5/NC13RYrPwTCzq3suzpXtvcy/w0zBYNET0BcWsebNN3oZ+7LxrRiASrDU5vYmu7/sY1wXkF9YgQYx+6LX11e7wANFgtoduJBYQQeL3NsFgcQcdz+wjq3T64PV4k2yyIt2rQdd3/PfkI9rkJ+jl0Y+TD7e/Mg28AAAz/KPif4uYTPUHLhn9kxeYTPQHbT0u60N//sI4YSLO3GU2eRrh9bhAQxMfZkBzvwP5mN1rcXri9Xvh8bS1bLToS4+xIjLfDarMYywkhqK9rwFlHXRnxvweFQnHgoWyosqGxtKHtYcFXf/D3P4p9lQ1VKCEVJfQfeXJyMlJSIv/RE0Lg8frg9WmwWQCLRQ9a72h2w2KLgyfOijiHDQDg9vhAYIHP54GuaYD//wEX39YeGi8aNBBCILs4+3w+WC0aLBYLwsULL+odLfA2+pChpaNJb0QKkqFJDZBgDIz/sT1ubYEALR4fNA2wccYukmPI8Pjc8Pg8iLPGG8t8Xg+aGhoRLwg18fg8sLj3QvfFI94WF2CYUghBXEsd9rnrAACXfPsv5KdVGvuWu4IFUU6pFeUuD0Z9FS/djl1H128Z719Ot80ptWJERo7fgPl8/t8ENOg6P0b0M2n9LcDYzkt8aHQ3oL6lFi3Yj/3u/SAWAouuA14dXq8XmuY3ehaLBR5oIFYLEpPihcZOhekoFIpQKBuqbKjMhg6zXoiCzNyw+mHVbO0+F2VDFe1BCakuxGrR4fF64SMa+Muvpmmw2Sxwez0g0EAIjAtii9sDi64FXRzNMfmHGcHFn21Ph45mixua1/9UKdJrMwHBLls9mnS3YQB0aLAQDbpHh8MXh/22/dAt/rUOYkOKJyFqE0AIQaOnAc3eZuiajhZvMxyWOP+RWy9cjvhU4b5Nnv2Y/vXzyE+rDBAx5S4Pckr9/4yWZJRiTNkMlOStNoxATqnV2I7dh+4nEll0Owp7DPqZ3ebyzDtwdenpaHG7AeJ/KuqIc8B/Spwx83jQ0twCTfMb/YT4BMRbE5BsS0Gqoy/irHH+J4Se/djr3os9Db9jn3cvmtxN0C0EKQ4n7BYHGpvr4E0g0DTSelOhLv4KhaJzUTa059lQ55QKaftFVRuj7Fn7UDZU0R6UkOpCPF4CTdMR9OAD/guW2+OFbnXA5/UY/8iMJyGcC7+z0aDBTixw+7yARtCsu+EjxLQMJPvkDAB8mg9NlhY06M2B1yoCJHji0WJtxN64BmPxQLezXc/RWnwtqKj9AQQE9wxfiaKqjZi71SXclhc4dYXZAcupiKFiqKhqI8aUzQAAFGTmCkUSu49oObu9SDzx+7HLPPCgxdvif6zqBTSbOMzEBx+8mhcWiwVezYNGdyP2exrxe9Nu6JoOm25HnCUeSfZkJNtS0L/fQBBCsN/diH0te9EnoS92N+1EXYsPe/buh9frg8WiI95hhcfjFY6lQqFQdATKhnadDf3XvhexJKMUBf3C8xxRGyqDFVHheqNiibKhimhRQqoL8Mc0E3i9PsPdy6/3en2AZoXP64XdxrnlNQ2ABV6fFxY92BDQ9vl46ViiAbASCyweHV6bD/stLajRa7mtCHwafUfggw9Eg2EKCAhadIFHhgB2rxX7bc0grXHfdp8VyZ744G05bqu8Turt4QULFT7OKRVBXiPR/iV5q1GAtgs8PQ4rcOjTNrNjizxUfDt0vcxjxW+n6zrsdht0XYfPR6TfuaZpcDjszOe2dT7iQ7O3Cc3eJtS17IEGDVbdBofuQJI9GSlxTjgdfZBsT0G/uAGoa96Dvd567G/ej6bm/fC53aZ9VSgUiligbGjH2dBpfWeHfxJVfgHUXuHD2r6uEFGAsqGK6FFCqpPxX+C9cHsIdIs/ttfr9cJi0Y2nZV6vD26PD1Z7HDwt+2Gx2QL+UWsa4PF6QDQCix4cUuCPHQcsOhHE+cYOnehwWz2wwYqU5iR44YNP88Gte+CxeOCz+ECo/SLwx5qH6A8hBDaPFTqx4KaUhabb8uKEXc4KED6cri0UbzUAYG6pK6A9fr+cUquxbVHVRsytdgWsp94oKqLY/fh+8JgJK9G5mAkrq9W/jy64MaBEckNAQOD2tcDta8E+z17saf4NyXYn+jj6IsmWjAHxA7G3pR5e4kWTtxH1+3eH3XY4eL1euJVhiRibzRZRroZC0ZNQNjR2NrQrqCvMDgrvW5JRCqDrRBRF2VAFELkNVUKqEyGEwEcIWjwEVqsdHk8LbDYH3B4vPF53qxEANN0K3WqBp6UJDrs16B+upmnQNcBmlf+D9hEExYwHrPf5AERWZYjHTqzwJnixo2kn4rV4WGCBHXYk+6zQfTqIm6ARjSAA7MSOFr0FDZZGvLDlQWkBBtFnszA3s3A4kXAJ2KcqcD8+bI++L3d5MLfUZVzsZX1mBRt7HLM+mfWRF1X89uy6jgpP0TUdSbZk9IsbgCRbMpx2p7Guwd2ALXU/wmG3YUCKE3ZPbG7eCSHYsWMHamtrY9LegUhqairS09NVzL2iV6FsqN+GLki9L+pjxgqZ7ZLhnFIRMryvK1E2VMESiQ1VQqqTaW52w2qPh9fdhDi7FW53MzTNAl13gBACq80Kr7sFGvEgziH7ejQQ+ADoJl8yAYG85Km7tZqPPUojoEGDhejQdR3NCW6s/O6vwpt/kWeIf08/s4jC7ERti4o3iPZhj0FfCzJz/U/HUCHsA3sMAEYhCVFfSvJWB3mq+DEwKzohOh4/FqJxo+/HlwV1vd3EWeIxJDkLfeL6IsmW1PpAVIOXeLCzsQbbG37FXnc9iM2OfcSDBuyPyXGpARg4cCASEhKUGIgAQggaGxuxc+dOAEBGRkYX90ihiC291YbOj1sUVTtdhdkDRoUfZUN7HtHYUCWkOglCiL9SkM0Bj7sZDru1NSZXg8/ng9fbAg2Au8XbWso1+CkaQJ+a+OD387f6+oUHDNGfECmnNNeorjAbJXmrjdA1meeGfpblBgHyMuDsej6kTXQsMzHFHscsLC6n1Nqa3LoRYwpnAKgMao895pKMUoypyWoVS8ECiCUSjxldX1eYbVQElI2vaD+z7WJBXfMe7G7aiWRbCpq9TbDpNjR4GrCvpR4tvhYACJgjo714vV7DAPTr1y9m7R5IxMf78yB27tyJgQMHqjA/Ra+gp9lQmmvU1UUUOhIqosLJk6LeKDasj7VdY8pmGA81o0EUMtgdUDa05xGpDVVCqp34fOycAn5EF2//HAWARSOwWrTWuQpglNC0WCzw+nwgXoQug2lMwCffRvTPkk0ileXliG7ijZLeCLxQmokJup4nVOgdL2Rkwobdn++zTGTw282t9j9No0KxJG+1Iar4YxVk5qKkyu91ov0prsnyj09NljFvFC/wROGJwhyoQnEoIN+mTIyVoxD/VzbFWM7/JoHIQxeavPvRtN//hOz3JnnsdlOLG26P15/c3U5oPHdCQkK72zqQoePndruVkFJ0a3qqDY2U9gqF7khBZq4hFOkrmy/M4pxS4RdczH0E683qahG0PE/ZUEUbkdhQJaTaidvrQ4uHgBD/PwCLBthswcPq9XphsznQ0rwfCfF2iaHwv4b6t0paN5rRf46xTCaCQuUNyUQLW2RhTNmMACMg8vTIiiOIjiVbHjKnSdB/dhnftiikjxcjtFR5flol5la7UJLnLyrBi8ecUivGlM0IEExLMlYHlDoXnYesT/z2xTXm4yryvPHjl2rvg73uvfAS/3qPxwOPxwsNgMVigdUmfkIbDv4nvl4jH0DX20JiPF4fdtc2oHFfbMISADWfRntR46foKXQXG9rRiB5G9gZ4T1RJ1Woj/5hdz4fWA3LR1VUoG6qgRDJ+Ski1E6tFh0UDiKYDIMZTMhY6A7vV4p8FW/a0DQDu+d9cAOLwMPq5uCYr6OIjEij8TbtZWB4fFme8r0LQdvwFUSTcROJHlg9klicUjrii24USNOw2Mg8RFUbOKRUYUzgDJVWrjTLpQNuku/lplYa4DOU1kwkfdsxLqvwCDlUwcq1k7cjGxO1zw+lIxX5PI/Z79oMQwOf1GqV8rYKbE7oOxF+61WKxCH+fXq8X7hY3CPxVrhxxjoD1LW4vWtwH5hwYW7duRVZWFr7++mvk5eVh/fr1mDhxIvbs2YPU1NSu7p5C0a2JtQ29MO0a0+P5H4KVCq+zivbDCquiqo1Bk+xSL1RHjL8ofDASlA3tGnq6DVVCqp1YdA1Wk9nRaanWe6vnhxW2Fk54V35pJYpbc5fYpz1mOUKiUDNR26JjA/6naexNvigckN3XLByN35btn+iz6HxEQpA9PzPPm6ifbBv0GFQsBYT+tYqqJRmlKDDxooWTt8T2ifV2ybxavAjkz6fBsw/N3iYk2pLhcMShHnUgPh/QOmu6DHeL2//UTddgsxLY7LagbSwWC9xw+xNlfd6AOVY6k0svvRTPP/980PKCggKsXbu20/sjYuzYsaiurobT6Qy9sUJxgBOuDb04c15MjlfuYookVHVu3hKdPkMWtdHboOHzIqgNjSXt9W4pG6psaDQoIdVOZh58A0Z9FS8VRewymYhit5UJBPqe4pxSYXiL+NA1XnDwxyiuyUJ+aaX0ppxd5s8Zagt1K2bygVhEnheR0JKdDz8GfAibSKCZebr48RB9FoX+8f2hniJWROWnVRrGN5T3TBZuyZ4XzbXiz1U0RvxydozHlwEe4kFdyx7EWeKRGtcHcdY47Pc0wkd80ou21+sFQEB8BLpFfEOj6zrsDjt0XQcxmaywMzj11FOxYsWKgGUOh0Oydedjt9uRnp7e1d1QKHoEMw++AVYt+MazIwkQU1HQnsIGSzJKe2WIXyTEWrzGsqy6sqFdT0+zodFPgKAwCDdHKNR+7PJQbVAvBu/54duVeYPYdvhtZGFqov5JQwJDtC0TjnxbshBEkXeGFy2idXwbZn2vK8w2xBMVks4pFUH9EwlCdr1MuNF+leStNsqqs8tDfSdm33GTdz9qm/fAqluR6ugDu0V+kbQ77IiLizMu8jKsVn+VLItVHLrQWTgcDqSnpwf89enTB4A/rvnZZ5/FOeecg4SEBGRnZ+PNN98M2P+7777DGWecgZSUFCQnJ+OEE07Ali1bAPjj2BcuXIhBgwbB4XAgLy8v6Cndf//7X4wePRpxcXE4+uij8fXXXwesX79+PTRNM+bwWLlyJVJTU1FUVISRI0ciKSkJp556Kqqrq419PB4Prr32WqSmpqJfv364+eabMWvWLEydOtXYZvXq1TjyyCMRHx+Pfv36YfLkyWhoaIjVsCoUBxQHileoKxEJ1Z5SuVDZUGVDw0UJqQ7CTGiEwuxmWebNMfOKsCzJKJWKAfaPtuOcUhFQgIE/Fv/HtxfKwyYSVLLwOzOxxh+DXSdqn91GNMblLk/AubP7mnmwePjvn+0TGz/OVgOU9d1sLEUQ4kOTpwkN7gYk2pKQZEuGzv2TpxWvdItuzOre07n77rtx3nnn4ZtvvsGUKVNw8cUX4/fffwcAbN++HSeeeCIcDgfWrVuH0tJS/PGPf4TH4x/3xx57DA8//DAWL16Mb775BgUFBTjrrLNQUeF/+rxv3z6cccYZyMnJQWlpKe666y7ceOONIfvU2NiIxYsX44UXXsBHH32Ebdu2Bez3wAMP4KWXXsKKFSvw6aefor6+Hm+88Yaxvrq6GhdeeCH++Mc/4vvvv8f69esxbdo0YWUphULRcUTqjeopwqEj6Og8tLrC7HbnRZmhbKiyoeGghFQHIhIZgLj4A++NYJex+5ktD+VJAgIv6qFC3GTir7gmSxh+JvOI8W3Jwt1kYXsi0cPCLxOJOhEyzx/7/RRk5hreKHru4X5XIs9UcU0W6gqz/eEdmblG+7RtkVgSear43w8AbPC+KzxPt68F9S21IITA6UiFXQ98sqZpWsBftHTWTf1bb72FpKSkgL/77rvPWH/ppZfiwgsvxNChQ3Hfffdh3759+O9//wsAWLZsGZxOJ1555RUcffTRGDZsGC677DIMHz4cALB48WLcfPPNuOCCCzB8+HA88MADyMvLw6OPPgoAWLVqFXw+H5577jkcfvjhOOOMM3DTTTeF7LPb7cZTTz2Fo48+GkcddRTmzJmDDz74wFi/dOlSLFiwAOeccw5GjBiBJ554IiDJtrq6Gh6PB9OmTcMhhxyCI488EldffTWSkpJiMKIKhSJcYnHDHstQtO5MucsTJKb44hORQsUTFbTs99HecV2eVyhcrmyosqFmKCEVA8xu5AF5qJdsf7N22Vd6c28mfETeF/ZCFioHh0LDz3gPDRs+Z7a/6LxlIkQmfkTihN0/lDdOJPRk27DvRV4p0WeR50h0Ls4pFUZ1QPq53OUxJuQVtSMSl2bnTS/IVt0Ki2aBj/jQ4NmHve69iLfGI9GWDF0z/+dPqxGxf6bb+9o/B0Y4TJw4EWVlZQF/V111lbF+1KhRxvvExESkpKQYs5SXlZXhhBNOgM0WnJNRX1+PqqoqjBs3LmD5uHHj8P333wMAvv/+e4waNQpxcXHG+vz8/JB9TkhIwGGHHWZ8zsjIMPpUV1eHmpoaHHvsscZ6i8UCl6vtBiQ3NxcnnXQSjjzySJx77rl45plnsGfPnpDHVSgUsedAEUKxoCNCKHkBRd/H0iulbKgfZUNDo4RUOxn+kXhuH1leDr+Ov9EWhceJbqLZ/B3R/qI+ADAKG5iFAvI386zXBICRz8OKKF48yDwronBAmRDkPXf8ezNRFeqc+H6Gc7Hn57wwC7tjj0sp5ibu5fsk+42I2hJ9z+UuDxwW/8XJ5/WhpbkFzS3NaHY3Gxdwj8+NupZaeH0eJNlSjO2DIIAGDe5mN5qbm9HU1BTaCHRSlFliYiKGDh0a8Ne3b19jPX+B1zQNvlYDRWcs72xEfYrk6aPFYsF7772Hd955Bzk5OVi6dCmGDx+Oysrgwi8KhSI00XpGohFRB3J4H097wv3aU+QjXJQNVTY0UpSQaiebTxTnLvE3/ZRwvCGi/BhRPhHrkRJ5d0Q3+bRkusgLJHrPemXYwguhQhNFwofvH39esvGTeb3Y8eTHTubtksGLK9oub2xFQpfvD79tXWG2MfeX7HuSeRPZV7PltN997P3Qx9EPfeP6Y0BiGuyaA26PO6htL/HA6/MgzhKHFLsTFi1w5m6rbsfgxGwMTs5GWtwgOG394NDiYYEFIJp/RksCOOxW9E9NxMA+yUjvnxp0nO7GqFGj8PHHHxuzv7OkpKQgMzMTn376acDyTz/9FDk5OQCAkSNH4ptvvkFTU5OxvqSkpF19cjqdSEtLwxdffGEs83q9+OqrrwK20zQN48aNw913342vv/4adrsda9asadexFYoDGfYBYSS092aej3LozbQ3lA9AQChfR6NsqDnKhgbTOzLjuhDqkeI9JSLPiewzYF46m64PuHEvhDEfhUwEidoRzTsl2p9vlxVRLCKRKBNOoULxzMIhZWMo8uiIRE4448ufd3FNljHPRVHVRpTkrQ6YAySUJ42+FteE1wezMRGJVpGAz/z1ECTHJRghB7/WbkV9Sy0smgWJtiT44IPb68bQ1GFIsTuxo7EaNY3VSLIlw+1raZ2EkCDJlgIdOn5vrkGCLQlOW1/E2eKhQ4eXeNDk249mbyNsNoLEOCugEbibm4POryNobm7Gjh07ApZZrVb0798/5L5z5szB0qVLccEFF2DBggVwOp0oKSnBsccei+HDh+Omm27CnXfeicMOOwx5eXlYsWIFysrK8NJLLwEALrroIvzlL3/BFVdcgQULFmDr1q1YvHhxu8/pmmuuwf3334+hQ4dixIgRWLp0Kfbs2WPE23/++ef44IMPcMopp2DgwIH4/PPPsWvXLowcObLdx1YoDlSiuTHvjJv53kJdYTYKMv3vqaDqiFC/WJKZoGyoGcqGBqOEVAyQ3eibCRzRjbvIG0Phb96La4Jzfvjt+Xb4CQjNxA7fDhDolZJ51vjz58+TP99QXifRuPGCyWw7mddM1H5wvyqMZXOrXSiuyfKLqVJXkCdN1vdylwcobDW+gvHivwPR+Yi+S9E6ALBYbLDACouugxCC9ORMWG02aJqGfnH94SVe7G2pR/+4AWhw74PH50GTZz+IxYchyYeirmUPfm/6DQmWFNS796BF248Wz34AgO62wKrZYNfjkGBLQFpyGhwWB3SfBrevBbUNnROXsHbtWmRkZAQsGz58OH744YeQ+/br1w/r1q3DTTfdhPHjx8NisSAvL8+I6b722mtRV1eHG264ATt37kROTg7efPNNZGf7w3mSkpLwn//8B1dddRVGjx6NnJwcPPDAA5g+fXq7zunmm2/Gjh07cMkll8BiseDKK69EQUEBLBb/U86UlBR89NFHePTRR1FfX4+DDz4YDz/8ME477bR2HVeh6GqGf2TFlvGde0xZVEgoOrJCXG+EHSc6OW+0nqXOGnNlQ81RNjQYjaj6uVFRX18Pp9OJP380HVvGa9IbfPqZRyREZPuzbdDl7MVIFjrIH0M0ma7I8yMSgux8EGPKZgS0Y+aBCiV6RN4d0fFloW9m+/PbhmorFHQMRF49vg91hdnGGIX7XYvEn6zvsmXXDrgTfeOdsOi6NIaYgKC+pQ6/7d+FXY01qGuphUW3IMGWCB06+sb1R6LeB9v2VmBv8y7AYgU0vbUiERBntyEhzg6HzQqLboHHraFxnw8tjV5MOXoG6urqkJKSEnI8RTQ1NaGyshJZWVkByagHGj6fDyNHjsR5552He+65J+L91TgqujvUhk7A2cak9p1JUdXGiHOX2hNexoa48fm2BwI5pVbDhtI8KbPvvLNC+Xie2naPsqG9gM60ocoj1U42n+gxZmUPJ1SNvVleklEaMlRMdlNtFi7G72sWUhaOaCl3eYCq4LA+mTeIXcZ7nOh+oUIa+X6FEkKicw4lOsxCL4WipnUMSqr8njnWY0XPsahqI8YUzjC8d/lpldLvgfeGhfLGyTx47HZ1LXuQGpcKGq2taRp8Xg+am+qwH254dX9sdvW+7aiur0Kzxx+nHBcfhwb3Pv9ORMPAPkOQnpQBj3svmrz7QXQriKZBt1iRnOiAzWrB7j0NsOgaNF1Dg7sF+5uboIiOX375Be+++y7Gjx+P5uZmPPHEE6isrMRFF13U1V1TKDoc2QOwUHTVzbaifRgPJREsZNliHl3x/Sob2jPpShuqik20k/rVh6GoaqMxv5DIEPChWfTGN5QwMRNJ9OLCHpO/0ebFS35apVG1j4Xdhz8u9a6YnZOoPdH5sPux6/nzl8H30Wx72ffA7isSqaKxpPDfVyQx3+GcMz+e7Dq+X7I+Pl/3OPTWaSwIIfB5W0CIDxarA3s9DSj/7RtU1P2A3U270ORpgs/nM/78OwEWzQabbsOQlCwcmTkGac4sWHUbQAh8LU1oaWiEx+OFx+uF10fg8/mf2Nnt6rlMtOi6jpUrV+KYY47BuHHjsGnTJrz//vsqB0rR66lffZhRkKcziaZ6nHNKRVRV+2JRcCEcZDa5u9Idy8jfPPQRZUN7IF1pQ9W31k4+GPUGxpSdDwBGOFe4YopW0APknht2XYDnofVJjSjHR+aVofk6SzJKMbfUJe0X2/+iqo0YU+a/2NFKQ3OrXUa+j5n3h20zkvA0XpDKPDUy0cGfA+/ZChU+KPP6UC8gnaCXhme0eQmzAGxEflol5la7/FX6JH0SCUEzD5xZuB8vrDS0lQb1+bzQdSusVgf62fvgf5oV+1r2AgDsNjvibHGAD7DZbbBqVuxz70WSzQmrrkPXdDjtfTCiTxJqHP3wv31bsa+5Hnv3t8ADK2w+Ai8At9sD4vPBaol+IsIDncGDBwdVOlIoDjQ60wOxJKNU6BEJh0j6yYuojgzrk4WadwfKXR4jWkNGd8lBUza059GVNlQJqXZy0jdT8cW4tiIMxTVZbcUFGEKFd8lC32Thc/lplVjSGuMtuukOx2Mj8pLx24wp9Iensd4YNjeLFyYyj1EoEWG2nF3P9p09lpmXiT2+2bmaiZVylwdOVBhGkR0PGtIHJlTTzFPHny8v8sIZC77v7Huyy/9e0zRYbfH+iQB9HvjcTSDeFiTpcUhxpCLOnoyBCemwalZ4iRcaNGyt/xlOe19Y9DZntQ4rBsYNRqLFiarGX7Br/w7sa2qGBsDq9cLSsh82RxwcDgsUCoWiPXTWzXRBZm5UeVLRQAstdCYyO9SVOKdUAFXidd1FRAH+yuSAsqGK8FChfTGCf8rCuqzNPCjsBLn8DbHIY8H+FWTmoq4wWypSqMBglzmnVBjzQLH94MkpbZtDiRqAkrzVphc51vMkC+EL58LOtlNck2WMJQ2fZMfTLMwtVMiiqK98W3x7ovA+2j92fi4zQcb+sctE48Ceh9l4se/55FhN06DpVvgccbDbk5Ez0IWc/qNxqDMbybYUJNgSkWxPQaItCcNSc5Dq6AtNg1E21Ov1t5doTUZW8ggMSz0CKY4+gKbDDR/cNjuavB7UxWiWcIVCoQg37Ks94WFzq10R7x/JjT5tmxVRnSkU6EM+asu7WyhdSd7qABvaHUQUAGVDFRHRpUJq+fLlGDVqFFJSUpCSkoL8/Hy88847xvqmpibMnj0b/fr1Q1JSEqZPn46amhrTNgkhuOOOO5CRkYH4+HhMnjwZFRXB/zjffvttHHfccYiPj0efPn0wderUdp9PSd5qQ1CV5K02RBJ/08ze+LK5TqL17DpWGAFtF0X6yoejyfYtyVuNJRmlUu8VbV80d5RZDg97fJGnK5RYFJ27c0oF8tMqUVS10Qij48fTbH+Z90l0fH57dszocvZCz37XY8pmBBgE/pxFoox/5QWfLGwylAAToWkaEqxJGN4nByl2J3TdAr21ihC7jUWz+KsVBezc+h9Ng0WzoX9cJkY4czEkKQtx1nhougVeAuxzq+cyCkVn0ttsKE84N/7tufleklFq3MxHSjSiJNoJgNtDQWau4X3rDkLFLDeNTrzbHVE2VCGjS/2+gwYNwl//+ldkZ2eDEILnn38eZ599Nr7++mscfvjhmDt3Lt5++2289tprcDqdmDNnDqZNm2YaB/nggw/i8ccfx/PPP4+srCzcfvvtKCgoQHl5uVHC8F//+heuuOIK3HfffZg0aRI8Hg++/fbbqM9DdHFk82jySysDbnpp+B+dqA4ILnRAl4mg6/PTKgMq/8k8LEH7trrW/ResSmN+KdG5sJ42ui6/NLCEuiy8jz+XUOcn8qZRZGEYIqHBH0sWJiny+MnWsW3yApMKaOM7bw2HFHnDzEILZe9FwkrWv3KXB9gZ1DwAwG6xw26xi1cy0IdxhBC4PT4AGkC88LXOxE5A4LAkYkjSUPR19MfvTb9hr7cONS07zJpVKBQxprfYUDNE+Uix8mDQkLtow/to32h/2LkWQ+3T2XRmKGN76a7VGJUNVYjoUiF15plnBny+9957sXz5cpSUlGDQoEF47rnnsGrVKkyaNAkAsGLFCowcORIlJSUYM2ZMUHuEEDz66KO47bbbcPbZZwMA/vGPfyAtLQ1vvPEGLrjgAng8Hlx33XV46KGHcPnllxv75uTkRH0eVGzQG2kKK6ZKqtjl/ouuWR6NyNPA3lSzT9CKa7LgREXQfiKhIOs3u4w9D/6cSvJWB80BIcvJEuUtibxS4ZwzDauj58nva3aefH/M+kk/m+1PBazMYNIiE+x5mXnO+HEKN++MF1ixiocnhIBAM141+PyvGqDpGjyEoMnrhZto2PJrA6p/+gWHHzEESbbGmBxfoVCER2+xoaHoCC8Fa0PbIzD87bS1FY6YOpApd3kwt9Q8Z6w7iqhIUDb0wKLb+BG9Xi9eeeUVNDQ0ID8/H6WlpXC73Zg8ebKxzYgRIzBkyBAUFxcL26isrMSOHTsC9nE6nTjuuOOMfb766its374duq5j9OjRyMjIwGmnnRbyaVpzczPq6+sD/kTwokS0nnowaHidLFSNwofs5ZRaMbfaZbjsnVPaiiCIRAkveMaUzTD++L6KvC3stmPKZhj9FvWPPQ7fZ9l6FlneE73osucpEj5m42e2n2wfURgdewzeaPLFP0Tnxp87P050WzMhbJY3dfev8+DztKClaS9amupBiE96nmYQQlr//Mm3u1p8+HGvG9/VubFxjxub9rSgLr4f9vc5CB98/C0afm2J6jgKhaL99BYbGgntEVgFmbmYW+0y/oqqNkb8MEpWgc6sMh3QNblKfCpAd4EXnd1BRJ0/8FplQxVh0+VCatOmTUhKSoLD4cBVV12FNWvWICcnBzt27IDdbkdqamrA9mlpadixQ+z+pMvT0tKk+/z8888AgLvuugu33XYb3nrrLfTp0wcTJkzA77//Lu3n/fffD6fTafwNHjwYgL/8OYXNkRJ5eVgPFUWUk0Pf8zlHou3ZV5G3gsJ7RUT95M9DFOZH96MXY17EmHmf2D6KvDKikDz6mXrB2KeGZvlBvICThfvJBInIwyMzsqzR5I/D9oEXYmbhfLzw43O1RLDizwcNFosNFosdCIzWDgM20VbzP1kDgcdHkGDRkGLTYdf94Qu6xYL+Q7Jw0NEnoPzXhgiPo1Ao2ktPt6FdSaiojfYSTqnvzoIKlO4gVGI9zh2BsqGKcOny2pjDhw9HWVkZ6urqsHr1asyaNQsbNmzosOPRSdP+8pe/YPr06QD84Q6DBg3Ca6+9hj//+c/C/RYsWIB58+YZn+vr6zF48ODW8uf/Cdo+IGeG8e6wr4A8LI8iEybsDTUNM6O5S2YCq9zlL+ONquCLvCgsUbSc4p9jqu24Zp41UTidaB3fd1ZQ0vLjVFSFGhuRyDPrj8xDxu9DvWL5aZXGmFCRObfaZeotYtsM18MkE6iivtJtfNBhs1oDEmHDRWsNSaDJsSA+aNCQ7vAn1moacFC8BTuaPNjW4IXbpyEuKRkH5x0X8bEiYee2XajbvbdDj8Hi7J+MgUMGRLTP9u3bcfPNN+Odd95BY2Mjhg4dihUrVuDoo4+W7rN+/XrMmzcP3333HQYPHozbbrsNl156aTt7rzhQ6Ok2tL20N5+m3OUxbBkbOs7C2wE2CkQGb19FDy07u1pdd8iTyim1GhEm1JZ3x3BIZUPbz4FiQ7tcSNntdgwdOhQA4HK58MUXX+Cxxx7D+eefj5aWFtTW1gY8UaupqUF6erqwLbq8pqYGGRkZAfvk5eUBgLGcjed2OBw49NBDsW3bNmk/HQ4HHA6HdD0fCsfnFYm2NbZnihPwN9myEDAeehPPzw5fkrcaqIJRKj0/rRLFNVkYU5YtvXjxxRNE50g/sxPTUkTiw8yTIsul4tcDMM6Rn4xYNDaifCO2bVmuEr8Nu56N62bLwrPjwYb3ibxQ4Xi6+D6KJlHmYftOfBqI7r+GR4Km+Z+lebwaCPFB0ywgRIeP+GDRAV0DfITAYbHioHjA7QO2NXihaxoyk+X/PtrLzm27cOmI6+BucnfYMXhscTas/OGxsA3Bnj17MG7cOEycOBHvvPMOBgwYgIqKCvTp00e6T2VlJU4//XRcddVVeOmll/DBBx/gT3/6EzIyMlBQUBCrU1H0YnqLDW0PsShOUJK3GgXw20mRJ4kWpgiV3xMNnVlcwV/yPavLPFO8DR3D3bN01FhE2q6yoe3nQLGhXR7ax+Pz+dDc3AyXywWbzYYPPvjAWLd582Zs27YN+fn5wn2zsrKQnp4esE99fT0+//xzYx+XywWHw4HNmzcb27jdbmzduhUHH3xwxP1985irA8SIqGS46DMvVoprsoJu5M08DkDbjTNtm5ZyZY0AfeJDjQMrtPiqc3xoIvW4sH2WIQo9C5WvxH6WnRvfPj8W4cS0i8IhZX3j18vC6djvmc0h4wtxiPogOq7ZcupxlHn8RB5ITSMRGwCgdb4M+KsM2ewOWKxWAATE50NLiwctbi8AHYQAFk1DP7uOBIsGh0VDZnzHTSZYt3tvpxoAAHA3uSN6evfAAw9g8ODBWLFiBY499lhkZWXhlFNOwWGHHSbd56mnnkJWVhYefvhhjBw5EnPmzMGMGTOwZMmSWJyC4gCkJ9rQaDCbuzFS6DW8qGpjULv0mk4FQCQiiu7bnbwtXRlWF4697igRFSnKhrafA8WGdqmQWrBgAT766CNs3boVmzZtwoIFC7B+/XpcfPHFcDqduPzyyzFv3jx8+OGHKC0txWWXXYb8/PyAakMjRozAmjVrAPh/wNdffz0WLVqEN998E5s2bcIll1yCzMxMY46LlJQUXHXVVbjzzjvx7rvvYvPmzfi///s/AMC5554b9bnIRIZIZIn240WO6KZZJDRySq3GhYf3dJXkrQ7Yh/co0fe8KABgeK74c+G9WHQZW4BCVtxBljsl8rKx+7DtUm+UzJsUKjfMrH1RG/w6s/LwdHtZTlQoMSgaFxpyIuo72zZ/nlZrdP+0NU2DrusAfGhpboK7uREgPlitNsQnJMJud8BitcHjaYHH40aKVcMhSRZkJliQEOUxewtvvvkmjj76aJx77rkYOHAgRo8ejWeeecZ0n+Li4oDEfgAoKCiQFgNQKFh6kw01g39AyC5niVZMdcTNO/VghSuiOitnqrvMJ0URpRDEkmjHVdnQzqen2tAuDe3buXMnLrnkElRXV8PpdGLUqFEoKirCySefDABYsmQJdF3H9OnT0dzcjIKCAjz55JMBbWzevBl1dXXG5/nz56OhoQFXXnklamtrcfzxx2Pt2rXG/BcA8NBDD8FqteIPf/gD9u/fj+OOOw7r1q0zdR+GQlRcQrTObN+SvNVG+JYsJ0bmNeHD8HjMQvTMziWghDsnuvjzrCvMRrlLHHLHwnugQoWqsdsU1wSWqhWF75mFCLKEE4LItkkvyLzXMWA+r6CzCD4XUaimKCcMgDG/FzV8sid6/DlrQFSx3UBrKAMBAA02m78tt9cLd7MbFqsD7uZmWCxWaJoO3WJBH+9+eOBBiy+6yka9hZ9//hnLly/HvHnzcOutt+KLL77AtddeC7vdjlmzZgn32bFjhzCxv76+Hvv370d8fHxndF3RQ+lNNtQMNg+Vx6xwUiyOGe2+AILC1kLRWSF+XTVPk8yb1xkTBkfatrKhnU9PtaFdKqSee+450/VxcXFYtmwZli1bJt2GEBLwWdM0LFy4EAsXLpTuY7PZsHjxYixevDiyDkuQXdzNPDii0uPsjN+yYgjsOlnImVnZdf6YZv2h63nxRN+z21DoJL8y75nonCIJz6PhhiIBImpb5GES5UiZecnY/WVji4xSYR6TWX4Wj+j4dMz5dkVjF844Roa/bKuP6NBAAN0Cn88NTSPweDzweDzQLVa/QfASeDwHthHw+Xw4+uijcd999wEARo8ejW+//RZPPfWU1AgoFO2ht9jQcAjnYWF7iyh0hxC8jhY5BZm5KKny54N1Jmb2iRbu6OpCGLFH2dBI6Kk29MD2I8aYULlSvAjhc5LYeaVEOUeAuJod4BcYBZm5AZXkgLbKeqIS7CKBJDoXM2+WSJzJhJMszI5dJxOLsn0jycMSiTt2Xahj5adVBs2/xY8B3xYrePjvTCSO+UkiAQR538zOm75O7zcnaH00kNZZ2HVdg26xAPCHLVgtOiwW3R+uEB8Pq9WC/U1NMTlmTyUjIyNoUtKRI0eaJuCnp6ejpqYmYFlNTQ1SUlKUN0qhYAjHO9Se8DjnlArjjzKmbEZrcaauF1g9nXKXJ+BhsYhYjDP7G2hPVURlQzufnmpDlZDqAMyq9slKibNEIkDYG+u6wmwjr0k2nxVfjl20TCawRJ4qs2qFovORFaOoK8yWVtPj96Wik92H3YYVoPx7/rj8NiLY8WfHS5RbZiZ+WUElGg+AVlTKbitpzxT8EI0Pfy7hevjCpjW0QdcAEAJNo7O1+w0E4H+i/dNPPxllkQ9Uxo0bF5CADwA//vijaQJ+fn5+QGI/ALz33nvSYgAKxYFIuCF27c2zqSvMDrgRj6a9rhJdkYrIoqqNnT6XVWcUunBOqQj4Hrs8H0zZ0LDpqTZUCakYIPLu8DHdvCBhhQ4vQFgviSi3hkV0YZJ5TMwu8PSGnXWri7xUsvLubNt86JmsgAP7mRa3EIkM/ryp9w3wz8Ml8mTxr3ybbD8pS1rD86gniBdh7BM1vuoifV9ck2X0iT0/PsSP7RstKlFUtdGovMg+uQvKm0KwKDMrmBEpbGy4pmnQdAs8PrSWctWgaXrrn38+DE3TkJiYhIbGA3sywblz56KkpAT33XcffvrpJ6xatQp/+9vfMHv2bGObBQsW4JJLLjE+X3XVVfj5558xf/58/PDDD3jyySfxz3/+E3Pnzu2KU1AouiWdIU5ySq0B9lr03oy51a6gqUA6EyogwqEgM9cf4pe3OuR8WJFABYxZPwoyc6XfJ+1PNH3ij92VAkrZ0OjoqTZUCakYUZK3GvlplXBOqcDcahecUyqMixULL7h4QUW9LDIRwS7jvVHshT9UGB9/3OKaLJTkrQ46nqwwhSjvi25DQxRFeUf8Kyu6aJVBXnSJKtOx29ALZ6icKf49K1bZ8A1aBlcmZKkhEIVvAm0XcD5MkxeWOaXWgGqHFPqboXOLic6H9o8m74b6zUSC/4kZAE0HIZr/KVrr3Ow+n7f1AZsPuq7D4/GgpbkZBx2UgbS0fu06bk/nmGOOwZo1a/Dyyy/jiCOOwD333INHH30UF198sbFNdXV1QJhCVlYW3n77bbz33nvIzc3Fww8/jGeffVbNIaU4IGHD60ShduEQrTDg5wWMdv9Y0Nmeolgcj2/DrE3nlAphmDwlkjwp0XHob8bst0P364ixVjY0OnqqDdUIn2mqCIv6+no4nU7875efkGE/LWgS1pxSK4prsoyKbrJCDaKiD2zxCVEYF1+8oNzlCciFoogq7skEEe9VYvvGb8/3WdQeKwJEfWbHid2OzQsKx6tlzEjfOkFvqKIOIpFBDaCo8iLfLm1DtA8LPweXSJDxhpf/LthKfew40HMWHYPddlHWY8K+hYIQAq+XgEAD/DYAPp8Pum5pTUyn8Qg+eH0EHm8L3J6t8JJ9GJp1Furq6pCSkhLVsZuamlBZWYmsrKyAKmE9YTLB7oRsHBWK7gJrQ88pf05400sLL0QrjiK5IY+FZyaWnrNoPSqReGSoLWuvJy2UaJLtYyZaw/nuRNODhHtss/WU13+XF2kxQ9lQPweKDe3Sqn29BX8YljgEj3/KJfpHbyZ0wg3dEnmIaHEE2TH4in0igRRuCVj+vMw8UaJzocvmVrv8c0UhUETw+7H5Umzb/D78MpHQohXxqOgtyMxFAXKRX1qJcohDEVElDqGky6iI5kPwWAFGS+PyIRkFmblAYeDx+HMKJaLaA4F/5nVCiBF2oLfO1k6ID7rmD/v2EQ3QmqFZfkFKUhN+291xz2QGDhmAlT88FtHkfu3F2T+5RxoAhaKnEdpzELvwMxGyayadC6onEUmIXyyPSYlV1UFZBT9e8NJqjew5hzMGHRn6p2yonwPFhiohFQNE+Tg5pa0T5VaFV7ZVJGpouN2YshlAYeDNsyjkS+h9YowA9WJQbw+9AOWXVhrzOMytdgkFF20/lKgS5UuZiSr+XMpdHuSXVgKt66moYi+erDeG9oeek0hQ8XlOMm8V0CaK+XbYyYnZ8E2Zd4qOQ36pPDyPLddLn7rSuah4bxSlrjAbY8qyA0Qaj7H970GrwoIQAh/RQXweaLoOn9cLQgCb3Qavz+23ABrg9dWDaNsQF+9FS1MC7JaODUsYOGTAAXFRVigUftrjjQKCb7pFN+ZmD55EIorNX6XzB7J0hZDhEQkbvk/sNiV5sSuHHsoLRLdxTqkwjin7jsMph05tNj3HUGF9nfHdKBt6YKFypGIALw78E9P6b2b5PBq++IQoB4kXMiV5q+GcUiGs3kdvpmnMMdsmCx8KVu7yBJTVBtqMDBVTIsw8anQfdq4nFpEHSrQdm7uUn1aJnFIr5la7MLfahYLMXDinVBi5RexFli/QwYsmkfDgRRXbP3YZzX8Dgi/EosqIFFpdsKhqY0AeFis4qQCk58LnjrGIxKzsvG6rvA7RorU+MiOE+Eu1Wq2tsd0aCIDmlt2AXon4BAvczQMRZxsKi6ZCyBQKRfvpiJvd8G7IzaHh9rJ9wsnNCYdYekvYPrF/dIzDOe9Y9cPMhspC9GjxCVkRCvb7iLWXaVrf2aE3kqBs6IGDypGKEja++9JDbgm6kaXeJBZZ4Qa6LlSeEhVDIk+K4c3g8qV4zxLr6eAR5WDRtkNVAuSPIcrjErUtWy8SV6LQQD6+O1RulFnOFB8eJxpnoC22mzfMonE3Gzc6TiLY75Hd1yx3SnROdw9+ELrFHtEM7T6fD26Pvzxra8VWEE2DRdfg83rgJbXQbf+DrvvQvL8/HLaDYLdasHfvPgw6eGiHxHcrIkONo6K7w9tQnlhWk2OReaVY75JZOB8rpkR2SkSkwrAzK87x8xV2BrIcJbo83IIfofosysOKNB/stZ2PKBt6ABLJOCqPVAdB/6HKvESiJzDhhNDREDNRFTrq/aCCixqFMWUzjFKn7AWdr4YnExtzq13IT6sMqvYHwPDU0PNhK9bRvonEiyi0jz8fmWcpIL+p1XtGjYHsWKL8KJm3iq+sx1fEo7lnovVmxT3YCorU0yb6LmgJdlnxEPZc+d8Bb9h9Pi+MxNYw0TQNNpsOu1WH1arBatVgswAWzQOPbzusju3QNcDXkgGHNROADo/XnzSrUCgU7YVGIXQEZgKNToEBwIiCoLAiSxYxIMOs+iC/rrPLdlMxUlS1sd35teES6hzDKdph9vugUSCi+yj+PigUyoYqQqGEVAxgb9T5anKAuEoff4PMwpfW5venYWLssWlJbueUCiO/aklGqSF02Cc9dL4iWREIuoy9MafHoIKM97bw4o81NLxgEBkfmbAS5Z/xgmhM2YyAi2qoyn388fjzFIVP8v0oyVttGFyzEuYUXlDxbYvGSrYPEFjynZ6DaIystnhoWmT/zP2JsRp0XYNF12HRNegaQZP7f7DH/wafl4B4BiHOng6b1QINBIRo8HoP7MkEFQpFbKAPlDoKPkyMPpQDAgUT9VLxRSfoOpHtNyOacu6dRWeF+LGYlSDvyP5EIqaUDVWEQhWbiCG0KMGSDPkNMCCv9iYLBZN5rmg4HyU/zV+koSAzFyVVTOGKqtUA2ralYYdsZTn2HCiy8AV2UloARsLomLIZKKlaHZR7FSpsT1YUIlR/2H2WZJRiTKH/fNmQOT70TRYyKDKCrFeKPT4dAzqOc6tdyCltE0+04iDvFaRjxocW8McXhYCKCpa0GQJxuCeAiMIRxPhLte5v+R9scb/D47HA4jsYdltqa9sENqv/GDarei6jUCjaR0eF9MmOxdorvy3zV3JlH5RR+NC/JRmlmFvqCktEsbC5QnyVu1hVvYsUGiaPws7xitEHvLICEeVAyGIUZpEtoSjJWw1U+d/T71XUhrKhilAoIRUD+HwWUd4Qj8gjxd9s8zfOIsElu5CzJbTpPmzluYLMXDhRgSVVGzGmMDj3SpaTxK6nZcPrCrNQkAnjeKGEEP/ebDu2L3yIHoCAyobG/FulwRfFUO2z2/DiykzA0TA9KuT4anrlLg9QGDxJMjUQdYXZWJLR9nlJRinGsNUaIZ5rjMLmaon6114IAZpadsLq2A232w3i7g+b3QqPtx6t87dDgxW6bkOk4Q8KhUIBBM7N19nIKsOJSp9LRVVVdDlGrKDqqmp/rEgRPbjtLCKZ/4qFfiesTe1OKBva+1FCKgbw+Sz8nE6A+c0wu54l3Pmc6E18uasiQHBQzwwVUAH7V7UdgxVRZmKHLuNv2PPTKlHcmtQpK4ZAP7OYeZtY0STzYAEwSqiyHjiRmOHznmQeKrN+8n1hJ1umc0IV12S1egD9htbvNQw+BjVeY8oCQxvo51Dim35mnyAKQxqjLIEO+Eu4trj3QLPuQEKCHY2NHsD6GzRLLXRdh9frhdfrBWCFz6OjyRPZE0GFQqEAzIs7dAZ8wQV6LS1ArlTk8aIqpzRyrwilK0umszlSnQ3rlaKI5oOaWx38HfCf2f3CLVbBtuX/DuXpANGgbOiBgfIjxgjRTS59jUREsTlRIq8E2w59T9fT3Cc+lI6fvJXdD/Df/NcVZgeIGL5wAV8hjs8pYp8iiYohyIQa21czL4ooF4jtL5u7xbcvCxk0SxZmz1UUmlhckxVQzhwIFMtjymYIQ0Poehn0HNg/fj/Rb40m1/L9j7Z8KyEEHm8DPPgfEhKtADTYbA6AWNDSZIWnxQmvuw98Hie8Hh26hUC37IvqWAqFQtEdEJXYZvOnZLBFKqKFD+/rbKigilSERAsvoGTbAOEL7XDmupQh+w6VDVWEQnmkYkBD3Cc4qeRR4Tp+Pij6KvNghRJafIiYrKobH+7F5vSIjmP0qdWbwu9PkVW3o8eg7YvivEXhfHyonpnXSgTbB3r+NNyRHlOUB8XnP7H9EwlI/jxoHpToKZ5IOIu+Q/b7C3XxZ8M/+WIf9JVOTGg2nuFB4PU1o9mzFUkpBG63B037rdDJQFgtTtiscf7kWwsAC2mdfNANnbTD/RUGO/bXoraloUOPwZJqT0R6fGpE+3z00Ud46KGHUFpaiurqaqxZswZTp0411u/btw+33HIL3njjDfz222/IysrCtddei6uuusq03ddeew233347tm7diuzsbDzwwAOYMmVKFGelUHQ/GuI+QWLT8V3dDQM+3I/mT4Xy2rDr+TmnwoH1THVVrlRnHVs2pxRLOBE54awPl9gVuFA2FDhwbKgSUjFGdIMr80CIxJCoPbYN9iaa93CxN+j+i5PfE0Uv5vmllcK4b2Gxi0IEebJEIW68mAq40W8NN+T3NSvwwLbJ9p3fXiTwnKgAqoLnyxIdR3Yuoj6ItmXFm2gs+fei9eF6KPl9QwnvIHEY4tpMCGlNh/W7qH3Eg2b3L0hIcmN/ow540xFn6wdds8Kfd8sm32rQNECHBTZLsvmB2sGO/bWY8fEjaPF1XuiDXbdi9QnzIjIEDQ0NyM3NxR//+EdMmzYtaP28efOwbt06vPjiizjkkEPw7rvv4uqrr0ZmZibOOussYZufffYZLrzwQtx///0444wzsGrVKkydOhVfffUVjjjiiGhPT6FQmMDOzUgpyJSH+vFEW4iCpbPFVEFmrlE2nOYcxZpww+fMqtaabdteovm+lA0Vc6DYUBXaFyNkXgj+YiDyQJgJLfZV6kWSeLZEc04BgUmxvIhi+7UkoxTFNVkBokYU1sd+puKLtiUqK86HEPJ9FOVFyQoo8EKIrWgoy82ifeHPSxR+KLros8ek40XPmw8xlF3gWUHMtyHajv0ses/3i+0vIW1/ItwE2FLvQXWjFz7ixf6WbbDH70PTfgusOBRx9jRYdFtrhaH2VjCKjtqWhk41AADQ4vNE/PTutNNOw6JFi3DOOecI13/22WeYNWsWJkyYgEMOOQRXXnklcnNz8d///lfa5mOPPYZTTz0VN910E0aOHIl77rkHRx11FJ544omI+qZQKCKDnSaEUu7yhF1Ygs7tGAndpTx6rMMLQ4Xvs5X7oi160VEl05UNjY4DxYYqIRUjROFb7HLZDbBovihRKGCofWUhe/TJGV+8YW61y5hIl22LPw4VQ6EKNfBeKfb4sgsoL15kF1neU8SfC32l50rHQOTV4tvi34v6Y1aYgq2eCLBFI2YEfKcio8B7pGg5en5f/ljsOdL3Mu9hXWE2CAgaPD4QWUUgAsRbNaTYvKiu+RZE2wV3iwVWHAyrJSkG5V8VlLFjx+LNN9/E9u3bQQjBhx9+iB9//BGnnHKKdJ/i4mJMnjw5YFlBQQGKi4s7ursKxQGPzPtE51UMBftAMRo6M1+qPQUbzAjn/NmQxmhD9WjRiGiQ7adsaPeiO9pQFdoXQ2ShWnQdxcxLwb4PtY+o6IDMY0VDEngvEq1wJ4r9ZqvgAfIcIva13OUx8qxoG+xNPi/K6D4iT4roSSC/nN2Xzp9FkZW1lRWR4M+Dtl3HVCRkz6Xc5UF+aWVAWXl6zjTWXeQ1FHkBWUHGlz+XiXS6Dmh7msefB+2vRZM/B7NZgAH2JlTvKMcPP25Cnz6pyD1iAmy2FGUAYszSpUtx5ZVXYtCgQbBardB1Hc888wxOPPFE6T47duxAWlpawLK0tDTs2LGjo7urUHR7ZEV4YonMlgDBc0vJMAtn7y44p1QYFX2B9ocWUjskKhtPx4O1lSw0zDBSYl0B0jmlAvhN2dDuQne0ocojFWP4XCa6jK3CVpCZi7nVriAvgsh7wbcjOp7Im8Ued0zZDBRVbURxTZbwyRCteid7IsNW9eNFCB8WR9ti+8t6xSjhChn6nq8kyH7mPW38OLLb8MUt2Pbpe7YfvEgSeazY75GOv8x7xQsrM4Ek8jKKPFUAjKp9RVUbUVeYHRCSqWsa4q268IJOiA/NLbWo/OVzbK+uQGJiMnKGHw+HrY8yAB3A0qVLUVJSgjfffBOlpaV4+OGHMXv2bLz//vtd3TWFosdAvUGiaq0dBV/Rj38YOLfaJbWhtCJcuJ4pXrx0plcqmvmwRIhElGyb7hDOSL8jakPZMVc2tPvQHW2oElIxgr3plXmGgLZkVVo+2yznRRbGxy5jBZqoEAH/SoWBqLw37R9/HLovLa3Oh/ixsMucUyqMUDV2vUzMsfuLQu34PCX+ePQ9X0Y2VG6WKJeKikceakj5saMGXTQOMiMviwHnt+dFlSwHTxbqR4i/KhALaa0qVN+wDZt/+hReXwMyMw5G3pETkJQwwF9RSBFT9u/fj1tvvRWPPPIIzjzzTIwaNQpz5szB+eefj8WLF0v3S09PR01NTcCympoapKend3SXFYpuxZiyGYaNoje70eTStAd2eg8W+tkstCwSMQX4bVlXiAy2FHo0XiEaah9q/i0WftzaEw7ZXkryVgeMu7Kh3YPuakPVNx1jzPJi6IRvSzJKjZtgWjKcz3lh2wqVZ8Uv40UV/8oLBD53iCZ7io5BhQlvRERepaKqjQEFKNjtRGLMrLoeu6+o0h4viPLTKo3+8/Nalbs8QZ4m2fFlYoXvH5sfRidCFu0ji/02e6LKe6RE27O/Gb5s7/R+c1o/+Y2B1+dGU/PvqPj5M/y2ZzPiE3TE2fticGYekhKVAego3G433G43dD1wfC0WC3w+n3S//Px8fPDBBwHL3nvvPeTn53dIPxWK7oqoZHZXCA22mBELtU+hxFS40PPsSjEFiKf5iKWXjB/LjioaES7s5LwAlA3tJnRXG6pypGJIqJth6o1iS6rWFWYBXJEEdh+zyn2iHBt2W5agG/CqtouFKPfI6GNh8HmxYoh95dsYU+afl4rPLQIgFFP8xVQmtELlVgGtCaucx88sRr3t+8hGcU2wGGVFKi0Ly/ejIDMX+aWVKBe0zwso0WcZoXLvgsIEqwLnASt3ebC/6XfU1u+Ernuxv6kW1Tu2Y9++vUhN7Yvh2UcjwTEAVkscuqqiUG9h3759+Omnn4zPlZWVKCsrQ9++fTFkyBCMHz8eN910E+Lj43HwwQdjw4YN+Mc//oFHHnnE2OeSSy7BQQcdhPvvvx8AcN1112H8+PF4+OGHcfrpp+OVV17Bl19+ib/97W+dfn4KRXdANAF8Z8MWNuBtYbnLY8xl2N6cna4SU9GOa3u+j64WUBT63bL3DMqGdg490YYq2Rxj+PA69j1/403na+C3A0J7nES5NqL3fFts/3jvDg+/nB6PGgbeM8Ruz5dYl8HnScm8UnyOFN9v3jPElmEH2owRbUNklNiEVz5sUtRvXuRRDxw9F1HuFNsnkceRD9Wk+/LvRev43xo7Jrv3lKHkv+/j+81f4n/bt0EjNowcfhxGDhsPhyMTusUBZQDaz5dffonRo0dj9OjRAPxzXowePRp33HEHAOCVV17BMcccg4svvhg5OTn461//invvvTdgMsFt27ahurra+Dx27FisWrUKf/vb35Cbm4vVq1fjjTfeUHNIKQ4oRNEAXSWiRIgKL8ke3IXT767OG+Jzpfg+8/2L9vtg7TgvOruLsAKgbGgn0RNtqPJIxQj2ZlhUEIBeEOiFtbjG74kShXqFCuGT5ceIClyY5dLUFWYbVfsovKDJL60MqjoHAE5UCD087EWR7uP3xJnnR4VTuU+Wk8UasCUZpW1Vh5iLMvUIis6zzQBsNLZlBU6QaClsq3bI9sn/Hbd9pt+xDJFHUfbdh/qN8OKdrbSYU2qF3Z6EY48eh7i4FFgsyUhOTIVFtwMAmt0++HyArpFumxybak+EXbd2+mSCqfbEiPaZMGFCUCw9S3p6OlasWGHaxvr164OWnXvuuTj33HMj6otC0Ztgb9yNa30XIyu3zRehaG9fO1NUycTQmLIZ/knvBUT6fcjGjV/WHb5jirKhkXOg2NAuFVLLly/H8uXLsXXrVgDA4YcfjjvuuAOnnXYaAKCpqQk33HADXnnlFTQ3N6OgoABPPvlkUBlDFkII7rzzTjzzzDOora3FuHHjsHz5cmRnB8fzNjc347jjjsPGjRvx9ddfIy8vL+pzkYXcAW15M0DbBWdMWbaxLUVU1U3mqQqVYCuqCsdC9y+uyRJeHEWCKOD4hTMAVErD5WgII02uDScUUBTuJxNqrAiir0tahSnbV/az6DxpKB+YfWUFHCiynC+2f/7+BIfjycQZ/73KPov24dunsP0a2Pco6LoVPh/Q4iHQAGiaBq/XB03T0E2v/Qbp8alYfcK8iCf3aw+p9sSIZmRXKDqb3mRDzeBv4rvTDXaouYvKXZ6AkuIUs5LqFFoavKMJp8IeG9bOEo0Xqjt5msxg7z+UDY2cA8WGdqmQGjRoEP76178iOzsbhBA8//zzOPvss/H111/j8MMPx9y5c/H222/jtddeg9PpxJw5czBt2jR8+umn0jYffPBBPP7443j++eeRlZWF22+/HQUFBSgvL0dcXFzAtvPnz0dmZiY2bow+PMBDPCCEBNwg86FW+WlteTOslyLcqm0yz0Wo/CiznJyAY1QFesx4z9DcUpdRnIHvM+9l4oWSX3D5PVtAcCw5Dyum+PZEHit2/dxSV4Bg5ccQVW3emnKXJ2CeJ35MZDlJtEAIfw6ic6Ix8mYiSPQdij5TRIUr2PbY+cJYdN0GANIJBalR6M6kx6ceEBdlhSJcepMNlcE+iAS6LifKDJGY4qvhtqff7Z3PKRRG9VmIw/mojSmq2hjwfXT0dxELb140xwSCH+IqG6qQ0aU5UmeeeSamTJmC7OxsDBs2DPfeey+SkpJQUlKCuro6PPfcc3jkkUcwadIkuFwurFixAp999hlKSkqE7RFC8Oijj+K2227D2WefjVGjRuEf//gHqqqq8MYbbwRs+8477+Ddd981LZkYDj/sL0dVy/aAZeyNr8wAiMQSe3MtumEuyMwNqEYnEkayXByZMKDraTl2OgfRkoxSY+4omu/DH48tpc6+AoFCxjmlwjT/SfQqQlaUghcz9D0dL3YsaF9kx+HzlvjloUq0sufB50mJBC//vfF5bjLPlMzTyHv7yl2eQEPEl3HVAJN7GIVC0Y3prTaUJVYiilY0jdU8STy03Df94+ciEh03nPMpyVvdZflS7FxdFNnDynCJ1BvVHbxXAd+TsqEKjm5TbMLr9eKVV15BQ0MD8vPzUVpaCrfbjcmTJxvbjBgxAkOGDEFxcbGwjcrKSuzYsSNgH6fTieOOOy5gn5qaGlxxxRV44YUXkJCQ0K5+72rZhR8avw9aTm+C2VLgFPammC8sQJez2zmnVAQ8JaET/9GLXH5apfFelnMlE1Whti+uyTKKKLBzS1D4gg+yHCh+W9kcHPyrTDTxxSdEUCEhCoekc3jJQuRCiVTaF7Py7bRv9Pvi9+eLTpitM/NgUQoycwPGh04uOKZsBhKbjg/cuPXBmc8HaBqg6d37SZpCoTCnt9lQnvaIqILM3AAxQq/Jor9YQW07neCVHpclVIh+dyYWniJqQ2VFOSix/m7MjkP7BQROwqxsqEJGlwupTZs2ISkpCQ6HA1dddRXWrFmDnJwc7NixA3a7HampqQHbp6WlYceOHcK26HI+/pvdhxCCSy+9FFdddRWOPvrosPvZ3NyM+vr6gD+Kl/hwc/YIYTU26hEQ3RCzr2biJlQ1IPbmOT+tMuimnW3PLGyQ9YDwr6wxYNuUCSC2v2aTEPKCSRb6ZzYGvKji39O+Uu8QPQ+RqGTHhD9Xuow/Lt8vfhyMcrit4pcv/sGOM49sO15Y0ZA+wP9diebJMtCCawspE6BQ9Ex6iw1d03CbdN/ODOfriJt2Kqh48SG77vN0Rp5UONCHqR3xfYQSU0DHCioask8r8Jqeo7KhCoYuF1LDhw9HWVkZPv/8c/zf//0fZs2ahfJy0Uw8sWHp0qXYu3cvFixYENF+999/P5xOp/E3ePBgYx19GsHfIJfkrQ6YeV2WoyTzSND2imuyAooryMLJgLabdvoETiSiRF4YUW4X+15WAIMXWCKvEw0dZJfRbXmPlihMj/1sdrGVebkoVNCJRKOZ10dk7GT9Fh1fJLhE+U0iASf6zIpyKpxzSq2G95Dfnm9X1zTQy76u+W+MfD4Vm6BQ9ER6kw0VEQsRwbcRjickVjftIvvOwttQEfReoqvp6D6EI6ZiDf2ewxJQrSgbqmDpciFlt9sxdOhQuFwu3H///cjNzcVjjz2G9PR0tLS0oLa2NmD7mpoapKenC9uiy2tqaqT7rFu3DsXFxXA4HLBarRg6dCgA4Oijj8asWbOk/VywYAHq6uqMv19//dVY5/9HFDyrsqyAAFuUgr2pF21D34sEClvhTpZjlJ9WKRRIPCIvCV0OtIUXigQgvcjTPKslGaVGvlV+WmVQlTsZMqFI9zM7T7YNti3adzZUke27KB+Krhd5g0T5VWaeMX4bAMY4skZaVETELI+OeqHozcCSjNKA3xXdht0XgPHYjCbMahpAANNkb4VC0X3pzTYUCN9rY4ZZG6FEVXvFFL1um+VnUY+V6K8gM1cYGt6Z0DHoDEEXrshlX6OFDeUL28umbKiCo0ur9onw+Xxobm6Gy+WCzWbDBx98gOnTpwMANm/ejG3btiE/P1+4b1ZWFtLT0/HBBx8YZVjr6+uNJ3UA8Pjjj2PRokXGPlVVVSgoKMCrr76K4447Ttovh8MBh8MhXOcvfRn8NE2Wg8N6CUIVggiFWQEHup6fC4r2ge0n2y+236xQ4st5i7w2/HnQXCS0VjXiQ/nMQgP5in0iYSIKDeTHx99GBQqQi/xSvwfHOaVtHiyzeTPY82L34TEr8S7CX8WpNKDsughRsYk2EWZ+HJE30fiVBuTKaoCmjIBC0RvoTTa0s5EVIopF9Ti2Ah4QvkDsLlUKqeigOdnsOIU7NqzwCeV9ClXMor3fiaw6XyiUDVXwdKmQWrBgAU477TQMGTIEe/fuxapVq7B+/XoUFRXB6XTi8ssvx7x589C3b1+kpKTgmmuuQX5+PsaMGWO0MWLECNx///0455xzoGkarr/+eixatAjZ2dlG6dbMzExMnToVADBkyJCAPiQlJQEADjvsMAwaNCiq86BuXV6IhBJRZhdSXmBFchPPw4opCnuDbiaGRGFnovf05p6GmrHzX/AXLF4cicSV6Fx4ocK2KSv0IBobPryQLRleUiUWm4DfoNEwOv58RPDnw+8jCuuTFaRgtwGC57IyKxoSsFzTALRVHfJHI5DWUAWFQtGT6G02tDsgqz4bq1LcshB7+rCOhYqojqo0GC68wORtHiuQzMYo1Jxb/DFFx4olUYUSKhuq4OhSIbVz505ccsklqK6uhtPpxKhRo1BUVISTTz4ZALBkyRLouo7p06cHTCbIsnnzZtTV1Rmf58+fj4aGBlx55ZWora3F8ccfj7Vr1wbNfxFLNE2DxeL/R2SW88Iuk11MZZ4dUV6UmdDgoWKKvcjJhJVZP/g+88KQnWMJ8M/XxEbrizxHvODgRZBsX1EelUxQyQxBcU0WUAj/pLyFALAxSBDT8WC9UvzYyo4jOg8eWa4U3wd2Hd+eSJSbeaTYWxaNifdWKBQ9h95oQ7sT/M18LOc1Ej74KgwUU10toFhk3rruNDlyJESbj6VsqIKnS4XUc889Z7o+Li4Oy5Ytw7Jly6Tb8HGpmqZh4cKFWLhwYVh9OOSQQ9od20qYeQXMwudkSaeyQg4soQQFj8wbMqbQvJBCqHAD2fYBYqB1gt/imixjIl6+n+F4ndjzkI2BaD++sp+oiAV9pZ4dGuInGn/2nEWeJdF7vl8iA8R6lUSICoUY+3HtifKq+EIVH7Q+hCaEBFzzCQE8Xh90nwZN58yBpgV87srwm99bdqPBs7fTjpdoTUZfe/+wt7///vvx+uuv44cffkB8fDzGjh2LBx54AMOHDze2aWpqwg033IBXXnkl4MaWr5LGQgjBnXfeiWeeeQa1tbUYN24cli9fjuzsrk8+V3QtvdGGHshQ+0kf2nX0RLyRIhJT4XqjYnlM9tjRHJOGxkeLsqHhcaDY0G6XI9UTofHdIs8CIPfq0G1kBQLY/WjhBorI82LmkWnbpgJzS13C8ENR6B7fJ7qdLLwvYFlr8QmjjSpwHqtgISLre6hqfaJQPlkogujCTJN6/V6ptvNkz5dHFi5oVsGPPyZ/HIosb47P1TL6UCj2MIogBPD5/MndFl2DBgIf0eAlALwExEdgpH23ZtJadQ2aBuh6WwhDZxqE31t2497yefAQd6cd06rZ8JecR8I2BBs2bMDs2bNxzDHHwOPx4NZbb8Upp5yC8vJyJCYmAgDmzp2Lt99+G6+99hqcTifmzJmDadOm4dNPP5W2++CDD+Lxxx/H888/b4RaFRQUoLy8vEO9BApFZ9EZOVKxEiVUOHSkJ4baS2CjIawoXSWsQoXY0bC9WI5LOMfsCpQNDY8DxYYqIRUDiL9ki6mIkgkl2XJZO6FilUVeKpGnhoopGXwOlWzbcMIX+fMqgD9cYUlGaUDSqkxQybxTZh4gfhteaFEPFD3+mLIZcKIiKMyS//7YPsuelIlCDs3OUSS4RSKOXc8KOL8g2xi0PX8OJ5U8ivePuw66rsHr0+Bt8cJq0WC1WkB8QIvPh0YPwV63D40eH9w+wEcIQACHBXDaLOjjsMBhASy6/6+zDEGDZ2+nGgAA8BA3Gjx7wzYCa9euDfi8cuVKDBw4EKWlpTjxxBNRV1eH5557DqtWrcKkSZMAACtWrMDIkSNRUlISkLdCIYTg0UcfxW233Yazzz4bAPCPf/wDaWlpeOONN3DBBRe08ywViq6H2tCOhLU9sSDWosGMgPsDJvyvqz1WkeQ88fuECnnvSPjjhlvQI7HpeOxzfKxsaJgcKDa0y8uf9wY0DdA13TSsTySg2OX8Dbuosh+LKDeIFQlsKW5ZSByNvzbzZPB9DJUDJuo729aYshlGqXTaH1nYInsuIkJ5nug2os98eCStTCiDHxeZJyqc/lJ44SQSq6Lvg7ZRV5gd0gDwQn13kw/VjR5sb/SgYp8Xm+s9+HZPC8p+b8Y3e1pQUe9GTZMX+zxAiw/wEA0tAOo8wNZGD76tbcGvDW7sa/GhxeOD1+dTITkSaN5J3759AQClpaVwu92YPHmysc2IESMwZMgQFBcXC9uorKzEjh07AvZxOp047rjjpPsoFD0NakO7K6JoD6D95bejoSRvddjzHcWKcAs+RCos2fuUriCacVQ2tPPoKTZUeaTaiVWzoK+1L/pbB0qr3bHLZDk4ZqF9fI6O2VMcXoCYVcSjFevY8uiiSkKivpptKwr1MxNrsnwnWf6RqGCFKKRRlkNmtFXFlGcX9Is9F/Y9m/clbBfBHjPeKxYJ/DgvySg1wj7MCoaI2FzXgnir/wmYVdMQb9MRZ9Hg0DXYdMCma/4QBLRGJLRe330gaPYS7GryoWa/BzubfBicYEE/hwU2C4HV0n1vgroCn8+H66+/HuPGjcMRRxwBANixYwfsdjtSU1MDtk1LS8OOHTuE7dDlfPy32T4KRU+CtaEdTXu9IEIxVdrxoX4yYu1li4ZYnXeoCJNYMaZsBlAY/fxkyoZ2Dj3Jhqpvrp0Mjx+BEXFHYKBlkLFM5mViEeVGmYUBUngvjEx00HXsfnwb7Gc64a5Zf/n3ocL/ZCW52fXUM2VWcZDvPz3HUMUnZG2UuzyG90nUZ1lREMqSjFJp+7K8Kf5zucsTUviY5dzJxlz2PdFjHJZiQ25fB3L7OnBEXzsOS7bioAQrBsRbkOqwINGmw2HRYLdosOn+V7tFQ5xFR4pNx6HJVhzZx4EEm46fG7z4tdGDJg/g8ainaiyzZ8/Gt99+i1deeaWru6JQdGtENrSj6IhQMvrgcm61q0s8VB3tmZIJmfYIKNm+HemdEkUCRYOyoZ1DT7KhSki1k1R9AHRiQ73v96AwON4zIxJNsn/QoW7mKaIiE7zYEl2cRGFoVFDxIYWyvC72POl7M3ixSPdbklEq9TKJzkEmGPlt2TFZklGKoqqNqCvMRk6pVShKaB/5dey5seGJInhxJwo7pNuws8WLBJAo3FO2Dd9fFvZ7TIu3wNr6xMzSmuAdboi2pmnQNQ3JNg0jU+04OMmK31p8qNznRqPHX7VIAcyZMwdvvfUWPvzww4B5ddLT09HS0oLa2tqA7WtqapCeni5siy6vqakJex+FoifB2tCeDCuoOptIxZSZWGHD7djtlmSUGn+xwKydcAtNhTvW4dxLhYuyoR1PT7OhSki1E00Dar278XNTYMJnqDA+szAyetNL/8aUzUBBZq7QayMSQ/Q1VCU5FlHulKian1m+lOj8ROF+lEgvbqKcKNFYsMuKa7JQV5gdJFxlokQWnin7PulxWTEnEnKycxCJNVnBCJEQlYWQyr6HWEwaqGkaHBYNBydZMSLVjgYfULG3BfXuA/tpGiEEc+bMwZo1a7Bu3TpkZWUFrHe5XLDZbPjggw+MZZs3b8a2bduQn58vbDMrKwvp6ekB+9TX1+Pzzz+X7qNQ9CRkNjTWdKbA6QoxFQ6iB3uhvECxFE+R0BGeqfZ4oijKhnYcPdWGKiHVTvaSWlS6f0ID2SfMJ+LFEV0eqkiDiHAqwfEXSlHVOn4d2x79o5WAzMLO2H7z60QV6EReF4pZiJ+sap9oDNj1svA9nlDFNkSiUZTnJQrrE+V4scvZtuiYh5NXx/eb/Y2Z/Q5jiaZp6GPXMdxpgxsaKhs6tyJQd2P27Nl48cUXsWrVKiQnJ2PHjh3YsWMH9u/fD8Cf4Hr55Zdj3rx5+PDDD1FaWorLLrsM+fn5AdWGRowYgTVr1gDwj/H111+PRYsW4c0338SmTZtwySWXIDMzE1OnTu2K01QoYgprQ3sy/I1/Z4sps2JJQHD1XrqMf89HcnQlMvsuQzbm7Q3n6yiUDQ2kp9pQJaTayZb9P2GfZx+8Xi8A8+p77HIW9kad3U4WqsULJJHA4i9AZh4qfns29Ex0AZJ51WRCSRQaKPK6sBdtWc4TX5VQVKGQ7pufVgnnlAoUZObCOaXCGEsq2vi+sX1kX0XhjUBbrlSoAh+037zRKnd5DO8fNQB0rjCZuBMJcpGXUBZymdh0fND5tgdqCHL72uG0W2Ladk9j+fLlqKurw4QJE5CRkWH8vfrqq8Y2S5YswRlnnIHp06fjxBNPRHp6Ol5//fWAdjZv3mxUKwKA+fPn45prrsGVV16JY445Bvv27cPatWvVHFKKXgFvQzuKjsiP4ulKMVWSJ688a5a7y2/HbkPzvvj8r84I7wsX2i/+VUQsHiYqG9px9FQb2jFZfQcQDb4GxGtx0Cx+d6/oJlckqmRPR0T7sROwAsElwmUucFkxBtl72QWWv6mX5Q3x58G+iraXFdfgvTiiPDC2//x58pUJ26jE3GoX8tMqsSSjVCjm2P7xuWxCcVLob5f/DvjviJ6XmQAWIfqtmOVMyfY3+821F03TEG8BspJsHdI+4J8h3arZOn0ywURrctjbh5MoHBcXh2XLlmHZsmVht6NpGhYuXIiFCxeG3ReFoqfA29COwH9z3XFCqqMKJERKSZ64il8k1fDMzqWjxFRnCc7u6JUClA2l9FQb2j3+9fdgCCHGH4UPszK7yQWChQi7fX5aJSDwZIhu0Ol6uoz9zCMXG4FtFCAXJVWhw8JEN/vh5IMFfS5sE46y/puJJZGoEp0XqsRV7fjvjnqIqHdOdt5zq11CgSQ6tvipZfBykUA1C6MM9Tujrx8Ez1nXbjRNg0XvuBuhvvb++EvOI2jw7O2wY/AkWpPDnkhQoVBEh8iGxhJ6be5IzIRJZ07cC3T9JL084Yiv9oqp7pqTFgnKhvZclJCKAXRm6luGjwQgz3GRhcix6/hcHPYCIRNPFFFoGV1G50tib/hFHpLimiwsyfD3y4mK1kIN2WEVj5Cdm6zQgyzPqqhqY4DxkyXIisSUzEMlGjOz3K2CzFw4UYFy5pgysct7p0RGQZYrxZ8fFXm0XbOwUJHHjKcjcqNkdPT87H3t/Q+Ii7JCcaBBbegb+2/H1Ph7Ytp2rEQUDZsTiRT2Gs6Khc4WUUCrbapqKxrVVUQqbug40THrDeIoUpQN7ZmoHKkOQpQLJMqFMltHK/UBwblB7DIWPn+I7xNbapxCt+Vzh4qqNhremYLMXGl+F9t/dhmLmUtdNBas8TETISJE8eCy2HU+BHFM2YwAA8TuR8fCrNAGbzT5HC6zvtIS7fxvhj+uyNtpls8lCrNUKBSK3k5H3IzzeUgyEcV/7mxhEKokensFptn5tOdcRcIz3NDJrqowqDiwUUKqnWjQAAL/H8wn0+VvhmXbs5Pjiqq9iUL56HtRlZtylydIpNCy4PQ976nhBVJR1UZjjin2fHj4kD72pt/MEyXycFGDxZ6X6PzYHKpQ48NuzxagAPzCNT+tUngsmlPFj4uoGAcdY1EFQhF0fqtQ+ViinC5Z/prM+6nElEKh6E7wNjQW0OIIHRXSV1eYjbrCbBRVbQz75r0rvCzhzi8V7Tjx52M2KXGkAoduH46IUgJK0ZUoIdVOLJoFiVoKdK2t2ko4RQDY9fwNuiy3h/3Me6pEFXlYT4jMyyHqo0gssV4yUZ9F+UbseIQT1shuS1/Zp38yD5zonNnlIqFFl+en+QtQFGTmCisd8n028+6I1rGijhd5dYXZKK7JChgvUfieqPiF6Ni8R5Bvl25zUsmjwjYUCoWisxHZ0FjQ0XlR0T6U6ioxJcuFbi+iqn6dRVcJqFhX7lP0bFSOVDtxkAT0t6Tjl5YfAYs4b4W9ATcTWUbstSAMzLwaXeB27Cs1JmzBCFFfZH1il88tbSsvKhJCobxVomOGyiejYYWycEXROITyBLHCSpRnZoZI0Air+QHIL60U9rXc5Z/jihdIojw5WV6UyLPJh4nKtu+snCmFQqEIBW9D2wO9me+MUuf8A8JIbui7IneKEq4d7e4oD5Siu6A8Uu2kj7U/6snvhgGQeQNkooMuZ0PKKLwHhcJ7XHhvC++hoWFjNDSPz90KdVNOX9kcKjo3E49IaIiOIwrvk40d9UrxRSNk4yUSk2bVC1lEbfJhdzyiMeXblhW8iFTghFt4wiyMVKFQKLoLvA2Nlo4UUbJCE5FeU/mcqc7y4hRVbewUcSlDiR5Fb0YJqXZihRX1nlr4vD4A4jA1XjiY5bIAwYKAwgsodjn/nt2GlvAWCYJQN/Js/0vyVhuudCpkzMLyRCFrMs+cLKeKbZ+vbicK1RMhy5MSwReHoNuJQuf4EEf2fOgx2O+SvlKjIirQITqGyNMny58S5XHJvGcKhULR1fA2tDtCBRQVVCK7Hi7dJZ+Hv5foSqEVKd1h/BQKSs/z53YzPPDAp/ugM5pUJiLY9eyNsHNKBSAoW07fA3IvDF0nIkBMlVYaJdBFgknkQZIJK9aLxoYohCp+IFvH90FknIprsgLml2LPTxaeJ/JIyYpUmBFOnht/DlS88t+laCJgs3GR5baJBLEsjyqUcFcoFIquQmRDI6WjPDuBtqUypjfwtPhEZ4X5FVVtDKgETOmuAipWRSsUio5GeaTaSaIlCQkkCT6vv+SQKD+Fwt/E0nWsl0SUA8WH8IkwC2OjbeanVYaV4yO66eZDxah3ii+WYJYLJrrpZxHd5LPigRdDfGEJM4MgEqIiUcW3x56fLP+NPV9ZaB+FNw5mvw/+mPyY8G2IvIsiT6gK8VMoFN0F3oZGSzgPxUIhikZgibVg6y7eKUpHiKpYn9+BOL+UonujPFLtpK7JgUOShmOfbw8avPtQktc2mWCom2S2uAQgnwNK5E2h8DlBMi+NUfIbFQETvoqINF+HvpcJRfa9mVgS7cd+zk+rDPIuicQnLyb5KofsOurpovDjviRDLPZCefVElf/osVlPnig0UtSezLsn2of3WvHiuSRvNRpwfVD/uzvEWwX49nTeAfU+0CyZYW9+//334/XXX8cPP/yA+Ph4jB07Fg888ACGDx8etC0hBFOmTMHatWuxZs0aTJ06VdouIQR33nknnnnmGdTW1mLcuHFYvnw5srOzpfsoFD0F3oZGQmfdVLN2oysLRXRHuqKsOz1eV3wP1I5+MKbTD91ulA3tGBuqhFQ72dFkRXyzA5mJfZHgiw/KbZGF+NFJX83C+GRFJug27DJR7g+fm8MaAlaUlLs8KECuEf5XkJkbUOWP9t3M+2ImvMzCHGk7Ik+P6JiRhPHx4yDaJz+tEsWF2Sh3VQS1L7tI8/lIou+atiUSvzS8D1yYnyj/KVSYqKxfocRUT4N4q0B2nQKgpROPagcGvBu2IdiwYQNmz56NY445Bh6PB7feeitOOeUUlJeXIzExMWDbRx99FJoW3jz2Dz74IB5//HE8//zzyMrKwu23346CggKUl5cjLi4u4rNSKLoTvA0Nl464eQ8V1UApQK5wGxq+fSCJLXquou+jo8agM8a2p9pKGcqGdpwNVUKqnQx06NjdpKGvIxkZCU4AoUPXaDlvUayyTBCI8qcoZuJJ5BERhbnR9/lplUCp1V+VDxXGHBR8EQT6XiZ42HOWbScqqGCWN0XFJ+1vqHmfROcsGq/8Ur+YonlN/PnJPouKYhjrqdevkBEwhUBxDTCmtfqhaEzDyWETbRduiCB97XFP03x70LkGAP7j+fYAYRqBtWvXBnxeuXIlBg4ciNLSUpx44onG8rKyMjz88MP48ssvkZGRYdomIQSPPvoobrvtNpx99tkAgH/84x9IS0vDG2+8gQsuuCDCc1IouhdBNrQ59D6dWeY8XNgHlexrTxJU0ZZBNxNT0dJV4xaOgOqRUR3KhnaYDVU5Uu3kkHg3+mmN+GWvG1v3eqUiiv7j5C80fJU4MzEgE1/sq0xE8W3x+8ug4kV2Xuy6cMP3RMJB5Mnj2+HHiY2J58dIJCD5c2ZfnVMqUFyTheKarID9ZefFL+O9VDLPG/+Zr/5kNsai44mW8/3ml5fkrVaT8nYCdXV1AIC+ffsayxobG3HRRRdh2bJlSE9PD9lGZWUlduzYgcmTJxvLnE4njjvuOBQXF8e+0wpFJ8Pb0FB0RxElgtqRnpDTI8sJiwQqpnqScGQJJ3+YtblqUt6Op6fYUCWk2kmCIwHDUu04NNmKPc3eoBtZ9qZ4brVLeuNPCSffiUVUnEK2Df9eVPqUL+TAlkyn8EUNeI+MrNABHRdePPBtydoRjR0LW2qcRyau2PHmS9zyfef7L/Oe8f2XrZctC+cz3ydeWLHbyESYouPw+Xy4/vrrMW7cOBxxxBHG8rlz52Ls2LHGk7FQ7NixAwCQlpYWsDwtLc1Yp1D0ZHgbagZ9sNddRZSo8FF3FRahpgKJhp7ohVMFmLonPcmGqtC+duIjXligIT3Bin5xVmBL8DYleauNC4wsx4fHLESPIhNF7P58WyLRRrcRCav80rZwt3C8JmaeGkq4uT+82MgvrRT2UWQIeEEqMxbB4+HPE/OHNG6UCkWZEOS3kY0Hf86yvCaz8eGPJwpFFNFjw/t6ELNnz8a3336LTz75xFj25ptvYt26dfj666+7sGcKRfciyIa6xdv1BBEFBIff01D+7iguYimiKD3FMxWpeFIPHzuXnmRDu9QjtXz5cowaNQopKSlISUlBfn4+3nnnHWN9U1MTZs+ejX79+iEpKQnTp09HTU2NaZuEENxxxx3IyMhAfHw8Jk+ejIqKtqpsW7duxeWXX46srCzEx8fjsMMOw5133omWluhiR3XNCltcCgDAbglMfGNzokRCx8wgyPJ6Qr3S97L8IZknh9+HF1n8LOxzq10hvTMiT5YsF4quF+3L7sdX6ZMJ03CNrciQ8LlSfL9k5ysL5+Q/m4ULijx2zikVcE6pQH5apfEqElkyQcUexyxEUxEb5syZg7feegsffvghBg0aZCxft24dtmzZgtTUVFitVlit/t/e9OnTMWHCBGFbNHSBv+7V1NSEFdag6N30dhsK+K9vbH5sd8YspF5kQ3sr3enc6O+H/1N0X3qaDe1SITVo0CD89a9/RWlpKb788ktMmjQJZ599Nr777jsAfhfef/7zH7z22mvYsGEDqqqqMG3aNNM2aXWOp556Cp9//jkSExNRUFCApqYmAMAPP/wAn8+Hp59+Gt999x2WLFmCp556CrfeemtU56DpOjRNM6qHfDDm+gBxIfJEyYpFyC7AonVmn9nwAlZoiYpPiNoXhRvSz2zFP15wAIGih35mX/nl/D6siBB5ZmThiDJhynvjRNux41/u8hhP0kTH55fL8pDYcwyVP8aPAeAX33OrXUa4YVCBDIHYk4krUd9UKEPsIYRgzpw5WLNmDdatW4esrKyA9bfccgu++eYblJWVGX8AsGTJEqxYsULYZlZWFtLT0/HBBx8Yy+rr6/H5558jPz+/w85F0TPojTa0Ie6TgPXs9BQ9gVDRD6yg6mzBweYZdyTdwRtFBZPs9yNbzucu87ZZ0XH0VBsa9b+mLVu2YMWKFdiyZQsee+wxDBw4EO+88w6GDBmCww8/PKw2zjzzzIDP9957L5YvX46SkhIMGjQIzz33HFatWoVJkyYBAFasWIGRI0eipKQEY8YExyWFU53j1FNPxamnnmrsc+ihh2Lz5s1Yvnw5Fi9eHO1wgBACAi88nv24rdW17ZxSYcwRRYlFOJqsmh/9bCbM+P1ksOKDF2Hs8Qsyc1FXmB1WqJ8olI39TLdjYT1ArHjgz1EmVHlPnawIBduOWS6TyKMjyyETfRbty7c5t9qFHMYOsb+HutbqgsWtlf9EuWVs22aevx5XdaibM3v2bKxatQr//ve/kZycbMRfO51OxMfHIz09XfgEbMiQIQEGY8SIEbj//vtxzjnnQNM0XH/99Vi0aBGys7ON0q2ZmZmm82Youj/KhgYfm9rQaZm5KKra2GM8B+EKE9FDvAOpVHpnYfa7qSvMhnNKhZELLXvYqMRT59NTbWhUHqkNGzbgyCOPxOeff47XX38d+/btAwBs3LgRd955Z1Qd8Xq9eOWVV9DQ0ID8/HyUlpbC7XYHVNoYMWIEhgwZIq20EW11jrq6uoCqIJHQ1LIbTc070dj8K2p2b0TZt+8C8P9jpP9QZaIkVAU+UVge/SwqrMDnU4kEmUgQiXKp2OUi+LbNxIQoFE60jLYjC5sT5XqJxlMU2sj3V2TQ6gqzjUlyw30KZZa7JAsD5M+LvvJPz/g8Odo33uiaefFE4ZTKG9UxLF++HHV1dZgwYQIyMjKMv1dffTWidjZv3mxUKwKA+fPn45prrsGVV16JY445Bvv27cPatWvVHFI9GGVD2xDZUHqdptNvdHfMoiJkdLRXqCvo6tyoudWukCKKvoqiZ5T3qWvpqTY0qn/Jt9xyCxYtWoR58+YhOTnZWD5p0iQ88cQTEbW1adMm5Ofno6mpCUlJSVizZg1ycnJQVlYGu92O1NTUgO3NKm1EU53jp59+wtKlS0M+SWtubkZzc9sEF/X19QCAX6t+QFJSEupqm7Br1x4kJWtAalueTXFNFpxTKoQ3+/xnILwQPjNvjKgtkZgIdcEXFavgYZfJxJKZkOA9Mfy2vDBwoiKkGJL1n13Pnr8xOS7XH1lRCApfcELmaeLb5S/SNHxvbqnfC2UWasnOSWXmKRMJOJEn7aSSR/HBmOuDzq1bovcBYEenTyao9wl7a0JIxEcQ7cMv0zQNCxcuxMKFCyNuX9E9UTbU3IaWn+SfJD6n1IqiqtIe45kCws/PNYs66Ul0tTct8LcR3tiHEkvhiqnEpuODQlG7LcqGdpgNjepf8aZNm7Bq1aqg5QMHDsTu3bsjamv48OEoKytDXV0dVq9ejVmzZmHDhg3RdCtitm/fjlNPPRXnnnsurrjiCtNt77//ftx9991Byz1NA2BN6o/0ATYMOciKPqkJeK+q7R9Wfpp/stfiGqCkanVQTLRI1Ii8SoC5h4r/LBNX7Pah+iESXUIxVuh/CaeQgSgUTSQ6+GVzq11GmKSZx012bnSdMcFwIRVo5qXO2WWykD/+vUiMiYSPc0oFypl+m1VZpBUFRX3ji2CI8tLMwip7ApolExjwbuukgp2E3ifsGdkVikhQNrQNkQ19DOuN9XOrXSiqartZ70miKhSdKaZilY/V1cKJJdLfgnNKRdhezp5oJ81QNrTjiOpfcGpqKqqrq4MSwb7++mscdNBBEbVlt9sxdOhQAIDL5cIXX3yBxx57DOeffz5aWlpQW1sb8ETNrNIGW52Dne24pqYGeXl5AdtWVVVh4sSJGDt2LP72t7+F7OeCBQswb94843N9fT0GDx6MEcOHwelMCdiWvzhSjxS9meULCJiF48nC7cxCAylmnieRQJOJKVE/+Bt8GufN50WxhKocJxIB9DXcsEPRcqN4ROGMAOEk8t6IKhGKijjIzsksjI/dns2DCvUdsedNvVK0TTNvmaif/LKelCelWTLDniFdoejOKBtqbkMp9LpXAP8Nc1HVxh6VOxUO5S4P5pZ27/mXumO/Ovo3IHr42dNRNrRjiCpH6oILLsDNN9+MHTt2QNM0+Hw+fPrpp7jxxhtxySWXtKtDPp8Pzc3NcLlcsNlsAZU2Nm/ejG3btkkrbYRbnWP79u2YMGECXC4XVqxYAV0PPQwOh8MoMUv/ABiVhkJBK63lp1UGTPgq8y6JBIMsv4l/H26hiHA+y7YR5WvR+GTZTTwvVtj1onXsMnbMeG8N+764Jsv4W5JR2uaBkjxdyk+rNHKTRH3nEeUc8e9lIgxoq8bHw4omkYjmKy2FUxCD3dZM5CkUis5F2dDIbSjQVomtp+ROhQu1X3yJ9FgSrhiieU7snxm0zx3Zd/54nSmkQ6UoKBRReaTuu+8+zJ49G4MHD4bX60VOTg68Xi8uuugi3HbbbWG3s2DBApx22mkYMmQI9u7di1WrVmH9+vUoKiqC0+nE5Zdfjnnz5qFv375ISUnBNddcg/z8/IBqQ5FW56AG4OCDD8bixYuxa9cuo62OmJdFFB5Xkrcac0td0jwes/A0maeKPR67HbsslDfHLMyA947wN/bs/uzFVOThYZeL3rOvFGN94QwU1wAoFD8hGlOTJQ134yvj+S/G/nA/UX/MQuP492biia04WA7xOIf6zuk+vMdPdnyZuOL7qCblVSg6H2VD2wfNme1NsDagAB0jFmPpWWLtfGd4rOZWu1rHKPyCHrGkN3ikFB1DVELKbrfjmWeewe23345vv/0W+/btw+jRo5GdnR16Z4adO3fikksuQXV1NZxOJ0aNGoWioiKcfPLJAPy14XVdx/Tp09Hc3IyCggI8+eSTAW2IqnM0NDTgyiuvRG1tLY4//viA6hzvvfcefvrpJ/z0008BE30B0SW6yZDdLOeUWlufqJUGiSm6DWA+txTvZWK359/Tz6GKTPBeLL4/bLsiUcUvpwUUgPDyc3jxIgqVM8tZosv5tgsyc1FS1SYyaLl2AEZu15iybOETJ5FLX1aEQtQXukw03xaLSLyG+r5EuVeikD+z/C2FQtE1KBvaPmj56p42x1QkFGTmGtVauxK+PDv93Jn96k4T/LKMKZuhHkYqoJHOuvL1Murr6+F0OvG/X35CSkpywLrbKq+TenfYG2PqCaET3ALm8yGZFZnghY3Mw2X22SwE0OxYMmhxB5nIMLuxl+Vaybwx7Dr+GKL9zIpFyI7Dts0fT7bO8ESFGHOZmObHmlYZlMVvmwko/vwLMnPx+u/Lgs4hWurr92LQwUNRV1dnhO1ESlNTEyorK3HIIYcgPj4+Zn070Ni/fz+2bt2KrKwsVSZd0S0xs6HT+s4Oqw36UKw3C6reFsYYKbEO45PNexkpY8pmwDmlQtnQXkokNjRsjxSbJBqKRx55JOxteyOhhAZdR0tfFxdmhx2mYOal4I8v6osonFDUvigXi/dYmd380/cFmbnILw2eQJb3PFFEYXkUXiSEysUKJaJExzdD5JmSCS7DsAvGnB13s/BO2e8o1Hmavaf4n/B5cFvldViU9VhY598Z2Gw2AEBjY6MyAu2gsbERQNt4KroeZUNjD73O9mbvVHfxTHU2baF8sScWFfno721a39kxFVPtRdnQ2BCJDQ1bSH399dcBn7/66it4PB4MHz4cAPDjjz/CYrHA5eqeLtjORJa7xIbksa/FNeFNiit6zxddYI8vKlQhWxfOObDLQoX88fuw4XUy8WTmhZJV/JN5tKinj1YSpMvY9bQ92QWVF1zs8UQhiPQ9P29YOB4oWTgmO76A37hQURru+IjOhYZKlLs8wO/C0+8SLBYLUlNTsXPnTgBAQkJCRMnoBzqEEDQ2NmLnzp1ITU2FxWLp6i4pWlE2VBEt5S4PUNX5x+XD+jrzuB0FDQsNV0yJtuvOOXrKhraPaGxo2ELqww8/NN4/8sgjSE5OxvPPP48+ffyTbe3ZsweXXXYZTjjhhCi63rswKxzAC5FylwcoDF26XCRcZE9rZPk1opt3mbiSeU3MbvjNQtQKMnOZnCT5hLEUWYgai8yzJSsSYZabZdY+u17UH3ZZflqlMd8VO15mwkqWSydaRn8v/HHZMZCNGf0cSyNFI4MJAbw+X0zapAnr1BAoIic1NbXTEv8V4aFsqKI9dEW1wt4monhCiSlZtEosvZ/KhnZPIrGhURWbePjhh/Huu+8aBgAA+vTpg0WLFuGUU07BDTfcEE2zvQbeWyQrysDCx3rL9qPr+M+8KDLLkWJf2eWs14w/jixcUCTmeO9bWxsVxjxIZrlOLLLiDux6uq+ocp2ZQAslnvh9RP1h23FOqTBC+fixEI0zL0BDjTtdVlwjHyvRe55QuW0i2FRKQvyfSet7HyEANHhjYwOgaRoyMjIwcOBAuN3u2DR6AGGz2ZQnqpujbGjsORDypXpj6XcWXkSFk8rQXkIVwBItj8YbpWxozyFSGxqVkKqvrw8oeUrZtWsX9u7dG02TvQpZqBZ9DfbctMV50/359th2zUQMfzz2vcjDJQs7Ewkn2bnxx5C16d/GP3lvfpo/b4q/4WfjoouqNgrzoPhqfmaV6XhRJBNuMkFllgtFKxM6p1SgALkhQ/j48TPzCLLjyq9zTqkwwjzMxKXoPOhEwDKvJYV9SkZAWi/2AFov+jRUQAOBRdegAbBGNSudHIvFogSBoleibGhsYXOleju0+IIsb4otztDdRVc43qeOEFM0vI8iEk0yT1W4Ql3Z0AOHqKr2XXLJJfj444/x8MMP49hjjwUAfP7557jppptwwgkn4Pnnn495R7sbZhWHgLbKfUCwyKDwn4tb50CiyaWy7cy8TWYheiJBJRJNsm1lx2D7KDoefw6ycZD1g44Lj1llPRZZlUCzan1A4AXTbGxl3h1ZvpvZfmailhWYsn6bedr46pD0/b9+ewJA6xMyAhAAPh8BQWtcNSGA5n/KpWuABv97GnZNDUIsKg4pFAcCyoaGtqHhVu5jORC8UpEiE1ydgUwohbKdZvvEAl5wh1t4QlZBUNnQA5uoPFJPPfUUbrzxRlx00UWG29BqteLyyy/HQw89FNMO9mTCEUPsciqi2PWydkU357KcKr4PZjfwfL/5Y8pu7mU3/uGGsMn6Uu7yIL+0MrA4Atq8VeGWSGfhw/9YaKEIAAG5Tvw5ivorOmf+/GRhkaKnbjLRRr12dFx4oSkaF+eUCpQLjpNTaoXHS+Dz+UML/Piflll0QNMADTrYXFWVuKpQtA9lQzsOJaICKXd5jDkdWTpKXInEk+ghKb+8Mwk1t6MIszLsyoYe2LRrHqmGhgZs2bIFAHDYYYchMTExZh3r7tCnab9urYDTGfzkQPQ0zSxUrtzln3OJ/ccqEkwsZh6PUMImnLZFmLXH7xtuiGC4XjP2M1+5DgidN0S3CbfoQijvHEuo0Eez5ez+7Lay71V07uz5UdgQRLaffF/uGPQI9NbQAk0LvMhHcsFXT9MUishQNjQyGxqK3lwGvT2IbE8shJRMNMn6EK5XKZJ7kkiJxkMXqhT7KzWPKxt6ANOuRwGJiYkYNWpUrPrSI/F4fSBMvCtFFnbHI/NE8MtCPdEJ5yaf3VcU4hXKk8L3h98uVMigTHTxXjXqtRL1FWg1AMzEtDRsjb3Y0f2dqAhoa26pK2hbvr+yPoYSSLIxMvNgidbz48rvm1/qL+tOz4GGKcg8dKKbC/ZcL8C13WoeDIXiQEHZULkNVcQO3qaJhEQ4oij4nkC+PlRbZohsp9n9SLjQNmhZd3rOoYTVkoxSFEDukbogTdnQA5mohNTEiRNNL3rr1q2LukM9DQINbg+BzSp/8sDfMItC5CjUK2WWW0OXmYXjido3E3ey9vj1ZsItlNdLJlDMhIpIkBUg15idnM394cMGZecn2pZfJztP/hxkx5ONq4xwBSxrCNr6EjjhMYV9P7c0WGTyx1IoFJ2DsqFthGNDI0F5pULDzw/Fhs6b2fdQxMprxLfXEXaKFY7hzJcViUdNcWAR1a8zLy8v4LPb7UZZWRm+/fZbzJo1Kxb96jFYdMAH/1M1q0U3DIHsxhqQC5gxha2hWILSmqIbbTNPh0jAmF0czfrHrw/laRGJklAXIDPBxb8vd3kC5nBiL4ihvGCi8+DbFo2X2Xia9ZVvmyccsUapK8zGkoy24hJ0kuOSvNUYw4T7iSoNFtdkBfyuROOsUCg6B2VD25DZUEXnE+oBLaWzBYXoniCaPrQnnDGUV0px4BLVXdSSJUuEy++66y7s27evXR3qaeiaBqsOeLwaNI20Jhe2iSmK7MaVvRmnN8kFyJV6IkTeLJHXiff0yG6aRX2k4WL8nFZ8f/l1shA30fYy75MZS1rD+fJL2xJFx5TNEIatse8j6Z9ouVl4g6g9s+OLhJ7sOPz3WFzTto6vzicqrMFX9Cuq2sh5srou2VehOJBRNrQNMxvak+mOnjEqJNoz6W1XeWXaK6ZiYef4PHaFAgBiWrV+5syZ+Pvf/x7LJrs9/sosGiw6gdcbOOmazAsiuyCMKZsRMEcELzjM3NwiLxB/vHC8SnRZSd7qVg9Iqek+MnFiJkz47fltZaKCCgd2/im2+g4vTPixk/U/lEeJ/S74focSVSIBLNo+lHdL9CRNNmkwv5wVVEsySk29dAqFoutQNjTQhkZDdxEvJXmrUVS1sVvObSUK6wPMHwp2B6Ltj/9BdWyqFHb3ubkUnU9MH0UXFxcjLi4ulk32CPyGQIfP54PHC9i0QEMg8giJvBbFNfLKeyJEYszMwxHqaU5xTRZQCBTXAAUuf6EGOtGsGWahgzIvi8gjIgqZY7enHhlWGPBlTMMZN9F4mIlNvi+ytkRiSDYmMi+V2bFEEw+L4D1V7CvfD76/CoWi61A2VGxDewrsTTbNde4Owi6ca7xMpHS3h27doQ8KBUtUd1DTpk0L+EwIQXV1Nb788kvcfvvtMelYT0PTAItFg8cLeL0+YS4NC39honMBseLAzLsh8mzIPDuisDz+PX1qZggTZnlxTWvoWGFgYQe+X6K26XHNcozM9qOvtH+sSOBFlGxMZOfNj7EsJE+0XPTK98FsHEL1l/+uRdX4zMq98x4qfs6soL7/HtSUQqHoIJQNDYa3oZFCbURXhdRREcWGfpW7/NOasNffrgoNM6vUF0qcKPGiUMiJKrQvJSUFTqfT+Ovbty8mTJiAwsJC3HnnnbHuY4+AhidoGoGH6MIbZnojzV+U6AV4brULJXmrA27AzbxYLLLt6I2ybPvimqyg2eDZbfPTKpGfVomCzFwjrK6oaiOWZJRiSUapNGSOPVeR50fWZ749dhvWI8MbI5GINFsnGhN2PbuNqL98+KRMFPHHkoUIioRZKOPFe6REEwzTSZ6pmKLhfbwAjGbOFoVCER3KhgbD29BI4G1YZ5FTakVR1UahiKIUZObCOaXCWEe37+qwv1BzIyna4HPKROF9yoYeuETlkVq5cmWMu9F70DUdmm4x9USxN8n0aZVzSgVQam39Bxuc7xRKGJh9li3zHzs7wAvF9pE/dkFmLvJLKw2DUFeYjZKq1UGlU/njhQp5E3mMWNhS5yyyeO5QIoc/R7O2+HZloszsXNnPMu+YWZ/LXR6gUFxgAmgTUKJ5pMaUzQAKgTFl2QFiKr+0UhlRhaKLUDZUDrWh4cKLqM4UU7QAUrjHZHOgy10elFStBqo61kuVUyrPD1Jh3eERq/wqRe8kKo/UoYceit9++y1oeW1tLQ499NB2d6on4wPg9bXFd4tulunFi4qo/LRK0xtvM88N/8duJ/tM39MnZaJtQoUmAn6DNaZsBoprsoJElGgfkZeKjgv/me0rLxDY8TILMRSNp8irJArB4/vFngO/P7sP3044XkSR90k25qwYYuGXifKn2GW06IQypApF56NsqBzehprREZ4o9tof6m9utSuqY9PrO+ul6ghk1/f2VO37//bOPDyq6vzj33tnJivJQCCEIFuUXTSUiCZq0SqC4AZI1WpVrJbaHy5E60K1VYuUuhWXWrXV4tJaW3HXVFxZxKA0FlBBDBgUSAjIkn2ZmXt+f0zOzZkz59yZyb68n+fJk5k755577pnkvvd73+UQQbpiERGic2jRXdTOnTsRCATCtjc0NGDPnj2tHlR3hQGwAhYsFnC8Oefb5YuZzpsh4uTxEd/H4sHShd9FCkEDgqF/yzKLgNLgxbmwPAvemcVaD4zq3FQCQ2wnFlfgT/9U41P1pzuu6pjRiBknYakSnrLnySmcUNcngDAxKQsn2WMXTVl03TkSBNG+kA1VI9rQaPDOLG6XG1r5Gq77rC2YPjjbDvPj59ORXjWyAS1j/cQVtK4UASBGIfX666/br1euXAmv12u/DwQCeP/99zFixIg2G1x3w0AwYZZZzNHbIb4XcRI8TmFfToJHxskromun845xuCFYllkEZBYht2AutuQUa/uXRaU8bnGOxLA+vvjulij6UM2DPPfy55HeqwSmSlzKnirVnDq11f0diALKqWofoF6UV/6cC1Ld90oQRNtCNtQZ0YZ2FtGEjLc10wdn22F+wCbkFkQfLqiDX9PlsDT5AW57nhdB9AZiunuaNWsWgGBSqLz6usfjwYgRI/DAAw+02eC6A5ZlwbIsewFB0wDiPHFhN+C6m2ReDED+TNVeJ74i3QirPpdv/HX7qML9xH34e564agufJkOgEzxyyKO8jceecwHgnVlsVw3Uib9IokY+djTzIPevO678uc7rpxJ2qj7DPitt/kyVIyV+pvJA6QRVyDGoch9BtCtkQ8PR2dCuRnuLDTHMb/3E1uVOcRsqkl+Wo8z16QihSBA9mZiElGUFS5JmZWVhw4YNGDBgQLsMqjvhDwCNfhYs3WoEjUAAltYL4iSQZHEhe6F0XhAnAaETZ05eEKfPZHElH6uwvKlKEYrD9lWdr8qjJl/sczfOxfrSFcjd2BzCEY1Q0gkeuZ3uM6fwSXkfnVBy+q4i9cVfB0NXmmPo5RA/3W9VKXT+fv3EFcgvylHOP0EQ7QPZ0HB0NrS3IhavaOm1WSWYnEQUR/ewsLvTXsUiyHYSQAtzpEpKSiI36iW4XYDHbcCyGPyWAdNgAJgyREwFLzbhlI+j8prEEran2xbNRVN14+8kOuRwhGWZRWEeNyeBxz1RvJKgKu+HV6LjHi9xnKpzi+TBUp2H2F4nNuXvRiei5M902+U5Fc9bWY0Pag+UKuRPbsdfc8FLEETHQTa0GZ0N7a3IBaBWlm6KyTMlLqcSSVDxHJ9IDw0JNcsyiyhPioheSD388MOYP38+EhIS8PDDDzu2ve6661o9sO6CaZpwmSZMg8FiFixmwjAMrPj+EcwdcK3dTr5QFZZn2Ws0yWIgmjwd8XWksDEZJ2Gk8lBE6tvJy5JfloOVpUExFSkEsbA8C2i6yC/LLEJueRYAvedFNjAqT5dKxKq8aqrz0AktpzmKJgxSPqZIJDEsljoXiWahXlVBivyi5nj520uux91ZD4XtSxBE6yEbqiZaGyrDizJ0xuK7HYloQyMhRi9E44Xhc9jTxZNqjcW2QrT1c9IW4OWDj7bLcYiuS9RCatmyZbjkkkuQkJCAZcuWadsZhtGrjICIx2XAsoAAYwgIBSc44k06F1Cqm3bdzbp8I68LD9OF+YlEc5Mv960LG9SFyNnbS0NXfVeFCvKwQFWRBF34mnw+ujHK44xGCOpC8pzCCJ3ElTwOnXdOHhefMxQ0b5fFkCpXSjV/4j7880jiliCItoFsaGRkG+pETxdQMiFrTjoQKR+2N+KdWRySZ0wQbUnUd1BiKAKFJYRjGEbTDwMCwRCFSF4h/tspfE7lpXLaz8lLIqLz1Ih9OLn7nW6+xTFVFIwKWQzWi2LlzXthk/eJo8rzEQ0D355XFPlvURfyx99HE4YZKYRQ1b/sEdOJz0ieqpWlm5Bf5kZheZZSZHLkBXp1a0vJcxkiMKngBEG0C2RDnVHZUCLUs+RUclssA08iqhmeMsCrCxNEW9OiBXl/97vfoba2Nmx7XV0dfve737V6UN0ZwzDgcvE4b3WhBn6DzT8TL5TyDXYkr5JKLEUKXZP3lfuUx83fi8JA/FHtz/uXvSUVBaOwsnQTCsuz7N+80h/HKcdHFBHrJ66wBZhKbDp5pcRzVIXliecabfy4bj5UAljlURSPzVkmhDryJ5EqI6kqja7zVqnyqnTjIQii7SEbqke2odHQmxZHXVm6SfnDr/exiqiePnfchsaaa0YQ0dIiIXXXXXehuro6bHttbS3uuuuuqPt57LHHcOyxxyI1NRWpqanIy8vDf/7zH/vz+vp6LFiwAP3790efPn1w/vnno7y83LFPxhh++9vfIjMzE4mJiZg6dSqKi0Nd4QcPHsQll1yC1NRU9O3bF1deeaXyfFqDx22GCRdA78EQ26hu6sW2ujAxFZE8LSoPi66tasw6McCxixrMLLYv8roQPfnGX5cHJO/DL5TRzLf4mTzP8udin/L3IPch9+Pk8ZOPrRsfEIyPF0Woam5UYXs6saV6TQKKIDoWsqGR8bhbdHvSY+HrPzmtHxgtcrRCTxZT4rpZPDyyrSEb2rtp0ZWKMWav+SCyadMmpKWlRd3PkCFD8Ic//AFFRUX473//i9NOOw3nnXcevvzySwBAfn4+3njjDbz44otYvXo1SktLMWfOHMc+7733Xjz88MN4/PHH8cknnyA5ORnTp09HfX293eaSSy7Bl19+iXfffRdvvvkm1qxZg/nz50c9bhHGGBgLfXImzo3uplu8kc4vy3EMEeOI++hu0p3yfGRUeVLyDb7uZl8+ji7sEGi+ac8vy0F+WU5wTSihMp8qDE3lVeGoSnurxqMSTLpz0M2P3IechyV/bypR5SSaZHEsexm5x00X2ii/1wlQWWDxOVT9nREE0b6QDW0mkg2Nht6QL7Ulx4/pg7ORl1Fii4Ppg7PD7GEkodAeQqIrIxfdoLBHoq0xmHwFc6Bfv34wDAMVFRVITU0NudgFAgFUV1fj6quvxqOPtrxqSVpaGu677z7MnTsX6enpeP755zF3bvAf/6uvvsK4ceNQWFiI3NzcsH0ZYxg8eDBuvPFG/OpXvwIAVFRUICMjA08//TQuuugibN26FePHj8eGDRtw3HHHAQDefvttzJw5E7t378bgwYOjGmdlZSW8Xi++2bENfb2pcJlG2MV/TtoCALEVaogl90klXsS2kZ6SRApbC+bm5DgeWyUaeBv+lEtcdFjsh7fnT4m4sBIvfHy7mB8kC4r1E1eEjVOF6ntQfa7y9unOOVIfHCdvoE7M8Nhup4pDupA9lXBSzRsv/sHH0ZqqfZWVVRgyfKR9fSAIIhSyoc3EYkO7K7wqXksRc3qcwtK4reXHknOB5FLoKjHVU8Voe+dFcVHL7XdrqvaRDe2exOSPfPDBB8EYw89+9jPcdddd8Hq99mdxcXEYMWIE8vLyWjSQQCCAF198ETU1NcjLy0NRURF8Ph+mTp1qtxk7diyGDRumNQIlJSXYu3dvyD5erxcnnHACCgsLcdFFF6GwsBB9+/a1DQAATJ06FaZp4pNPPsHs2bOV42toaEBDQ4P9vrKyEkDwyZk/AIBZcLlMexug9g6JRLq5VnlAVMgepEgFDlTeK/G96CkrLM8CCqBd60oeR+i4i0NCBuT+m8XWJlsMAeEXebEUOkf2VhWWZyGvqCRMxKjmUJVPJY5RDOWLFCKoEqJOnkCnflSCSi4WoRJDsncu0hM3VbEJfmwq30oQ7QfZ0NhsaHfHO7M4TOTEQjQFEuSwPJWN0Xll5PC+niqmdLRHWXSyob2PmITU5ZdfDiC4KvuJJ54Ij8fT6gF8/vnnyMvLQ319Pfr06YNXXnkF48ePx8aNGxEXF4e+ffuGtM/IyMDevXuVffHtGRkZ2n327t2LgQMHhnzudruRlpam7RcAli5dqoxddxkGAIYATFh+C6ZpwDQAw1CXK4/2Bl71GRBdCJYsolQCzsnrIh6fe4n4OJZlFtlrD6k8M7wPLsAAHroY3n/QE9Wc9yOG+nHEAgriNv5bV33OyTPk5LmLRpRG8hiqju/0HegE25YcP9aXhho88ZydFupVfa4KBxQX5NX9bUZLDM5tguiVkA2NzYb2BGRxEq1gEYsw6bxRseY26fJre1u4H8cppzhWdCkUsUA2tHvSohypU045xTYA9fX1qKysDPmJhTFjxmDjxo345JNP8Mtf/hKXX345tmzZ0pJhtSuLFi1CRUWF/bNr1y4AAIMFGAYMZgEAAhbgCzA0+oL/EJHCwwD1wq+qtk776LxM4ufij9yfzlsmb+cX9GWZRVhZukkrWOTCEHJ/PN5bJYRUoiF341zbY6XKm8rLKAkTgbL3SXW+Oo+Sah5U34fKuxXJE6XyOIpjV32XqkIb4lzIgkmXQyW/jyTwY4OMAEFEA9nQ6G1oT4OLqIqCUY5CKJqb+1g9SDw/WWUjeqI3Khqb1hYiit8HtJ6e+Tff02mRkKqtrcU111yDgQMHIjk5Gf369Qv5iYW4uDiMHDkSOTk5WLp0KbKzs/HQQw9h0KBBaGxsxOHDh0Pal5eXY9CgQcq++Ha5KpG4z6BBg7Bv376Qz/1+Pw4ePKjtFwDi4+Ptykj8J0jwsZlpBqsMxbkNeFyAyxX8NFJImPxb98+o81TJ/apyluTf4s1/tMcXj7klx28XjlCJOb5NVxmOH5vnRslPhEQvGO+HlzoXn9DxdqK4i0Z0RuOp0uU+RROOqevL6aIufi8c1cr0ohFUiaNIa0yJr0WR21IRxRPFfX4fyqrCyzkTBBEO2dDobWhPxTuzOCrx4uQtUgkxbp9ViGGC3pnFtu0UxV1PQmVD25q28EKRDe3etEhI3XTTTfjggw/w2GOPIT4+Hk8++STuuusuDB48GM8++2yrBmRZFhoaGpCTkwOPx4P333/f/mzbtm347rvvtDHkWVlZGDRoUMg+lZWV+OSTT+x98vLycPjwYRQVNf+DffDBB7AsCyeccELM4zUNAwYYAk2LBxqGAdM04TIN5c237qZVJWxUeT1ie3GbzqPE95c9JtGKC11/8pgLy7OwLLPIfsrGb+rFREx5HHKek3gRzy/LsYWSKA7yy3JCwhxyN86116Pir+X5E+dRJR5FnMIudfOpwmk+daGasndIVZ1Q5ZkSV7uXPVRiG/k1n8eWhSQ0Xfwb63Cw6jC2VTTi62p6mkYQ0UA2tBknG9qbWFm6ybaf4kPGWDxFFQWjbLvDH3bKqASc6B3raWIqGsR7lVgQ95HvLyJDNrSnEFPVPs6wYcPw7LPP4tRTT0Vqaio+++wzjBw5Es899xz++c9/oqCgIKp+Fi1ahBkzZmDYsGGoqqrC888/j3vuuQcrV67EGWecgV/+8pcoKCjA008/jdTUVFx77bUAgI8//tjuY+zYsVi6dKmd4HrPPffgD3/4A5555hlkZWXhN7/5DTZv3owtW7YgISEBADBjxgyUl5fj8ccfh8/nwxVXXIHjjjsOzz//fNRzwCsO7dpZjMSkZDAYcLuCRgEIGoM5aQu0oglQe5Q4sljR/RbbqPqP1sOkyhtyyvGR+7fzoprgxSnkMavOu7A8K6yYher4PLZc/EysaicLLnlunc5JJVx1IW+6EMBovmunY6r2KZSKbPDzk8MevTOLbREpiyiVd0r0Jsrj0FXuEy8VVsCPOr8fpTU+7K610Gh4UFtdjXl5x1LFIYKIANnQ6G1obyLaKn0yqrwrld1StRNzsTixCriujOr8VERT2IMj5nSr7tvIhvYuWuSROnjwII488kgAQGpqKg4ePAgAOPnkk7FmzZqo+9m3bx8uu+wyjBkzBqeffjo2bNhgGwAAWLZsGc4++2ycf/75mDJlCgYNGoSXX345pI9t27ahoqLCfn/zzTfj2muvxfz58zF58mRUV1fj7bfftg0AAPzjH//A2LFjcfrpp2PmzJk4+eST8Ze//KUlUwEAMA00uWYZfH7L3q7LqYmUgyOiaiu/d/KiRPLCqASZ7BVT5QDJIkMMu/POLFYKEV24Id/f6WnO+CI31k9cgYqCUXZ+FvdCiV4asYqfam5l0SCfr5M4cgoXdPqeVCJVbieHAPL+nXKj5Nfi4r3idtmbxUWmSoirBHMw9MACswKorzmAurpKlNcHsPGQHzvr3Gg04gAYiO9lT5AJoqWQDQ1FZ0N7E+KC67GIKHn/aNqJni8V3Nb2BGLJgYp23vk9juqejGxo76NFHqljjz0WjzzyCE455RRMnToVEydOxP3334+HH34Y99xzD/bs2dMeY+1S8Kdp35V8jaQ+fRAIsKaQBAMeV3A9jNtLrtfePOs8TnKbaDxQIrH0p9sm4+Sq5vvwC7LoCdJ5dWQBwuOYxVAzVR9AqLFQCQVVFTvRi+V0zk6eKJ1XTefVkc9TbqM6pngc/lpciV11fvwcRS+TyjiKbeTjiOfIx8SfqPHLQ2NDNfb5PKjxWai1TBxutNDYdL/jNoABCS54rTpkjx5DT9MIIgJkQ6Ozob3JI8Wv9S3xBEVTYp3bmmg9NECzbe3O3qlY1pHi6yrqcqti+X54CXSyoT2fFnmkrrjiCmzaFPzjvPXWW/Hoo48iISEB+fn5uPnmm9t0gF2dAAP8fga3y4TH3WwAgKB7V/QucJw8M3Ib+eZeJQBkz4vcXuxHbCceS+d1EvtRjXdl6SbbAEwfnB12THmMMny7WEWOF43gF31+UeMXRFEkyXlW4mve58rSTTGNSTU+1ZyrhJmqX1mwqDxvqidZvI1cpVBVsjZ341zbq8ffy9UP+fcjn4/u7wQAGLPga6gC3EkorQN21gL76psNQLLbwBhvHI7uF4e0uBZdTgii10E2tBknG9ob1uMRbWhbCRbxgaOY/7SydJMyjE+HKn+5O+H0EFhFRcEox/uClnw/ZEN7Pi0q1ZWfn2+/njp1Kr766isUFRVhwIAB+Pvf/95mg+sOGAZgmiYsxmA2VR8SnXxyuJy8TRdaF8mTpfJoie9FnPpzEnGRPF8VBaOAzKJgBb2iEmwR9teFwcnnGyxM0ZzkWlgO5DYtrsvDBXM3zsX60hVhwkDOE+KoPDfcEGzJab4QqubFae5U+8jiVvW9qASu/Deh84apzlVEzg/bkuPHdGTb60+J85FX1BzTHY1HjTGGgK8OFmM40MBQ5QsNuUnxGBjfNw7eODOYMN5TFn4hiHaGbGgzkWxoT4Y/HJw+ODtkTb9YkEWT6rPWlPi29y3tHrlTYQ9LS6Pfd/3EFZiO7JjypZwgG9o7aBP5O3z4cMyZMwderxdPPfVUW3TZbXAZBjxuAE1P1SzLgi/AEAgEDYHqRlznXVIJKnEflQiSb7yd+uDbxc9Uni/VMeS24pOtSKGHTuOTPUlijpOMnC+kywESvVRymXDR0KiEq87zJu4jnrOIzlMov1Z5CzmF5Vl2/teyzCJ73Q95DlTCSjRw0wdnK0ukq85NNW7GGPy+Wrjc8ag2+qC40ge/cG8TbxrI6uNB3ziTLv4E0UrIhkJrQ3sq7e3liVZExSKyukPuFLedPJc6lmp8Yo6UnC8V66LFZEN7Dy3ySBHNGIYBl2kCLgv+poUEGWOwDMDlMrRP/3UeJf65KmxMF0qm2k9EtY0LlfUTVyC/qLn4gC4EUTxmYXkWcsuzQirFqfZRjUE+H9l7whFFkKqcNxAuoMR95c/FfsR8LqcwvFi+E104gOo7UX3nAH86uSn0nAtC50OcC9lblVsQmg/Gc6J4KXnddyuOk78P+Othujzww4XdNT7UCzc18S4D47wepCe6ABggE0AQREuJZEO7KqKgiNVLw/OUpg/ODlbSa6E3ih9bJ27aYrFZZZ9d1DulmodY1pJaWbopbHkVfo6xfkdkQ3sPFJDZRvAEWY/LgGkw+19DDt+S0YkXlTeJI9+8qzwc8o2/3Id3ZjHyMkowfXA2CsuzQqrcyd4r+ZjrJ66wS3+KYsTJiyXDw/pUJbtVoWziIr2q3CixD52HShYiheVZ9hgieaVUglhEPF+V4NKF8fH+uLCVz0E8N90iu+IciMJWLCyhE9i6v7+ArwGm6cG+egv76wP256YBDE12Iz3RBZdhgB6kEQTRFuhsaFeFr8fEHyjGGgomL4bbEsT8J44c3cFpyTpJTqyfuMI+767gpWqLMEYgfNHilkI2tPdAHqk2wmj6h7AsBgYTLpPBYupqb06eDcC5FHqkfBudZ0Q+trgNCHorRE+NKkyPr9k0fTAAqD0xKuGhulkP9jUq5OKuywMCQkP9VMmyuoVoeXunBWp5/9wzNh3qhWp1XiiVaBVDKMXz5tt4PhgAoMC5vDkfr0ogqs5PF2ap+rvShfrFJXpR5WPYXeMHf5BmAMhIcGFospuewBAE0abobGh3gIsiMedJRVsWlZAr9UWqxheLZyZWuJcK6DhPVfj5tj6nqa0gG9q7iElIzZkzx/Hzw4cPt2Ys3RLLskITYw0DYAH4/Ra4w0/29OhurlU5M7owMNX+4j5iPzphJvfJS3+qcq/EcL5oxi33L4uxXEEYbcnxw4vQBWV1+VAyqsV4Za+OriiF3D9vxw3UsszmsEcVOrEiz4W4LViFcAVyhXW35HGphJIqpE81fvk7VL0Wx6/62ygsz0LjMGBntQ8Vjc3JsalxJo5K9SDOBMV0E0QLIBsaTjQ2tLsgL+EhXm+DdmVTq0WGzvvjnVkcU2GF9kIM/QPavnR6s4BqH+HUkjW8RPiD4oMW2dDeQkxCyuv1Rvz8sssua9WAuhv+QHARQYbg0wbTBAzTQMAPGEZ4wQmVyOG/VUJEFxqn6kvuV3eDr3otvuf7BEuBNgmczKKg90jhpZGPqxKK/LPcgmbBwMP1eBtdHpRTuVZZSKhEhriP7L3RhcyJ4X9hazY1VRBclhlaUZDnKQX3E/oStukEoaqke6Q5kAVk87HU1flUHkLxc3HNqjTfD1FW+w747Y3HBLL6uJHspspCBNFSyIaGE40N7W7w6y0vdhD0Bm1q9U26jCxSdHnDnYFY7a9taVsBJdv+ioJRMYs/8UExh2xo7yEmIbV8+fL2Gke3xeUyYDY9NGMsGJZgwIDLZYbFeOtya3TFCGQRpbsB1gkj8ZhOn8mf8+Pzi4ns5dCdi26M4mfiTf4WoY0YYijup6tSpxIaKjElEk31Ir6vd2Yxcgvmhh3fqQ+VKNNt0+0bCbFNflmOHZ+fu3Eu8jJK7KISPGnWKXRUnGt5jS4AtgEwAByR5MaABFfTO4IgWgLZ0HBisaHdDR663pYCyukm37bZyI5p4d22hof3deYYooGXnedePrEMvVx4QodKRHHIhvYOKEeqlbhME25X0AoEwxOC/yQ+vxn2NE3lhZK3RxOipyoisSXHHwybK5hre3qiKTCgCzMsLM+CF8X26y05xY55W6rcrUheNn3OVrMB4rlRPGwhUkGJSBX75G1iW3HhWvGYHKe1nFRtInmSdAUlOKpwRDlheHyR267KBzR/58F2fvuJqC4UM2StLknw3TQk+Dst3sSwPm64DFBiLEEQbUosNrS9kfOOWgoP7+LX65Z4OVqLd2YxpiM7JC+rLdZGckIO55MfSHYFVOJI9d2IeW9OFX6jyT0jG9qz6V4ByF0co2lBNcYYGAu+jya5X/QqyUKDo3stChZxUVbeLto+5DGJFxZ+EZQ9WJHGKW9zKoQhw9vy6oK8D1WlPt02/lo+D7GdHBonX2TF99GGGKpQ5WKp+pVF2fTB2UGD2PRb/lsR3wPhFRvFyn38JoEbeVlEqcbfL87EaG8cEl0UjkAQRPuisqHdFX7zHYvdaw+47egoxDxq8X1HIj98nD442/6JFTGyg1f45TY0GhFFNrTnQx6pdoAB4BHfunA4VUEJGVUuklN4XV5GSfAfu9Q56dUpR4pTUTCquT/pcydh5BRK6JQX5lRUg38mPiHSeZo4ujWXOGJInNiXyjvIxUh+WY5j9UBdeXIRVbELeR/bI4ZQg+Q0X6r5Cxe4Jc2CSvhedXPYL87EuL5xSPHoDYCYJG51lxJbBEF0aUQb2pHwcLS28CAtyyyyQ+y6CnJ1wZYgep0inZtoQ7mHTrynaKucLvnhKffGBWkbIbslJ7ju5fii6Csgkg3tHZCQakP4P4RlBZ+kmZp/HF14HqD3SIk4VYbLL8oJLeWtyG8S24vjsUP6ZhZjfWnwhr75YuQcFij25YQuL0vVh0pg8lA2QB22x+Hb8jJKQsSPOCc8JI7HRecX5SjnaXyRu/kiLfXFiRSWp/KaiW1FscYv/KpCIfIcRRLp4jnwz7bkNBmZgvCxiGMqM68LMwD8b5w1vWYM9o8/YIX1QxAEES3R2tD2hAuESKXMdfBQsNyNc+FFcZdbtBaIXlDJuU6q0D0Zp3sALkAirZMYjbCS+5AfQLYXzYLKHVFQqUQU2dCeBwmpNsYfsBCwDLhdzbGwuop5IpE8OTovkEqIeGcWhwgqeV0ooDmRUj5eXkYJlvHiBUWheTeRCk44CTZVLpbqfJ3Eoyywpg/ORl5RUAhxUcDPfzqCn23J8dvnwYszRCsAedEGJ+S8K25YeK6aauFi/rSzomCU4DkMH4tOVEcSxWIbVZEJGbliIH/93gnBP+DgxT54wbf4Rb9puwF+wxNMGicIgmgNKhva0Yj5RbqiA/J2fm2dPjgbK0uLgCaPVFdGHL/oXbKFEpoF03Rkt0ik6MSTjCjSuCdPJ0JFG9oVhSonxUM2tDdAQqqNYIzBH7BgNRkAl2mE5EipBJAsPJxEhVPhBpW42ZLjt8VFSC5MKS90MCpkAVqxbznXShyLTgTJxQycxJ/Yn6qghthG7EvuVxwzF4+68cjtdWPhTxM5YkgCPw7vUxRr+UVNBR/svoqF1/6wsYp9iW10fxccncdMNc+62PzmJ2mbHD1pfRp+iIPm6qZPDAAMhhG86AeTZs2QGx2XSSmXBEG0DJ0N7SzE66zqgRq3pwCUxQi6G20hSLhtEW3o9MHOoqgl43HyiHUE0XijAJAN7SXQt9ZGMMZgWcEyrqIBcMojchIY4s1xpPwXGTEsQZcjlJdRYhczUI2J5wvpBJE4TjlXRzxP+caft9WFJ8rH1PWjO54suuTj8nb8IlhYnmUnjTYvxFsUYjh5sql8/nKfunwlea6A4HekE3m6PuX5kD/TiUx5fyC8+p/4dyKGWZimAZfLgMcNxHlMeNzBH5fLhNn0d85/CIIgWorOhnY044uCRQV0N8qi54Tb0O4uoloCt5c8p0ycM25T+by0h+DpzNyzLTn+MBuqg2xoz4eEVBthNblqXdKK1S8ffDTsBlv+AdTeHZ1IkG+W+W9RAPBKPXkZJWHxxqqnOfyYvJCDfJFwEjIqwSD+FtuL23XiQyda5H6chI0OMfwCgJ0jBYQWXcjdOFcpXmP1Euq8RHJlI1kMOc2lPA5xf6fzH18UzIELlrP3axf1FXG7DLhdJkzTpIs9QRDthpMN7ShEMaCr9MYLAo0vcoddx3kffP+ejHgfwUPYO+P4HQ0P94xWPJMN7flQaF8b0FyqlcEwwrWpymOjCz0TBRO/oIthA7oQsC05fnvNIzlkjMc25xflNB2neRw8iTQY170pLJlUJ4bk9zrxoBurk+jRiaZIoXnytkj9cyoKRgVDHSc2F+jgeVWq/qLtWzcfvKBHNOPVhe7JbXWCTnzNQzwB2Gt75JflhC1kzNt4ZxbDOEgXfYIg2pdINrQlyDaUE82122kZDLkfWzg15VQBsAtN9BZk7117i8jOyo0SI1VEwazLpZ4+OBsvkw3t8ZCQagOCq7EDuvBWpxtkVWiXXWVOcJPnFszFsswVyC2YC744Lt+Xf85zXmQRoDpu8012UGBVFGQBCF4MnCrxRLqx14ko3VyohJVKsKmEhlOYoKqdqr+VpZuAzKIQAakLCRSP4RQ26LTvsswi5JZnaUMadX8ruv5U34fqvZgnJ1JYnhVSCl2eB8YYPUEjCKJdiWRDoyXkui4QcqNfGrq+nii4WoKqAl5XLoDQFoi2SJ7rjhBRnYFOLDmJKABkQ3sBBhOL2BNRU1lZCa/Xi107i5Hcpw/8AYY4twFTYQluL7kegLNXBWgWULqLsHxDLJfTlkP1ONG4oCN5jnRCRiaSx03XRh6nTsDotuk8Qao2y5qEkzyPqrW3nMYWKXRRnhfd+YtE8uxFOnfVcWXDo1tYmK8bJhrCv26/G2n9+kZlCCorqzBk+EhUVFQgNTU1YnuCIHovsdjQOWkLIvani+IQPwec1wBqCxEQTYh5d8ZJePbUcMZo193i3inx749saM+HPFJtQDAkQb8Ku3yzW1ieZccUi091pvMbaOhDyfIySuwy3rxEaF5GiVJE6QSLbozi/k7iRDyGjC5UUScKIokWub18bFXIpOw1kkWUjLgYb7RCTd4eyTskz5dujCoRqBuDzosl7h80AKHV+eTXQLO4CpbKb+5r7Yer8cNTT0FaWnSGgCAIIlYi2VAZ8WZVvLY338DqPfu8JLl6v9bTk0UUEP1itD2FWBYvbl5Wpnkb2dCeDwmpNoAx5/XX5dAvL4qxjMdSN+WqqNZ0Uu0bjbdDFjIqEaQLVxNLl8phgJGOK7eThYbuvJwEG98mtlOJJt1YeNuQ/CBBSPC55/ljcv86YaMTfapz5J5EUew6ec10oY269zrvnxy2x89dfK1b+NAeQ9GHGFp8BNioo9A/rR+A6G92CIIgoiGSDZXhy1LwvGCAe0OiFzH2Na60bcVPV1/bqKU4CYqO8ER1xrwGozmiF1I8N078e3r25+9iaAHZ0J4MVe1rI6L9x+ClQqcPzkZ+WY7tYdKJByexwb1RunYcnZdIJTymD85uztGCugS3U5ifzqMj9iG+l48vvlcJM9Vc6I7Pt8ursnPxxM9XJep0gkZ33nIbWdyIVY1UIkg+tiiCxfNyEqyymJKLSMj5UbKI4k9l5XMcVLUXX/y3CDt3fguKBCYIoj2IxoZyLzt/4KerrBctusV2WwNfKLYnoRJRog3tCDpDnOoeNOrQjZFsaM+GhFQrsZpWrHZCDLNaP3EF8jJKtIJHfK0SO1ty/HbpzbyMEm2InC6UTHVMJ6+SfA6qkDTxt3xsJwEnt9OF0MljlEWFTpyJvznc6I4vctsCVhyffL66OZM9f/JvVdiffM5ifyrhpPM6yfMgz4XqvDlySB9/7bTq/BCPhaG1+/HJqlXYvv0bBAKWti1BEEQsRGND+TVSLE3eGi8SFzo9NaenPRGFK81fM2RDey8kpFpJwArGdrsizOSWHL99AVLd7KpuzFXiQu7TaXs0hkYUIbL3xEk0OXmnIh1f9qDI4kvVJ9+uCq9Tva4oGBWyyC6AEAHrNEZR2Iht5O2y+JHHEen7UbXRhfCp/g50nkF+/k6he6owR7kPji9zBEb2S8bJ/RNQvmM7du/eg0AgoOyXIAgiFqKxofw61xrvU0fSXUP7xOs+Xy9JXpy+txBLbpSTiALIhvZ0KEeqlbhNAx530AI4hSZEyoNRtRG38adx+UU5TTlMkYtH6G68dR4SlbhQCQd5vKpxyCJAhTwelSdH3F/28MjbuWhalrnCLmkuVuTjCaBO5+T0/ejmRHeOuvOR+1B57cTxiOjmVd5nfWmoUJIv9GKYo13xUeMBde0bD5/LjaF7diDF14Di7V+juqoKo8eMgtvtpnhvgiBaTLQ2tDUeKA7Ps+muQqe9kfPORPh9B6HGadkY11CyoT2ZTvVILV26FJMnT0ZKSgoGDhyIWbNmYdu2bSFtduzYgdmzZyM9PR2pqam44IILUF5e7thvVVUVFi5ciOHDhyMxMREnnngiNmzYENKmuroa11xzDYYMGYLExESMHz8ejz/+eAvOIhiSEOkfQZU7I34WaV8gPIdFlz+j86gA+gp+qptynVhQheTJ58gpFNZM0gkKeZt8TF04G2+3LLPILiah8rSIIXwqb5A4Bt3YdGJR/l51HiadiNKFFjqJZLGNysPGBSUXS3JlPrlsvlyxUBZ/htsDV9ZY+IaNQV+PiVH+w/j600L8d0MRGht9FPNNEJ1Eb7KhbUF3FFAdkW8le55k2rKqYXcgFm+UE/yegGxoz6ZThdTq1auxYMECrF+/Hu+++y58Ph+mTZuGmpoaAEBNTQ2mTZsGwzDwwQcfYN26dWhsbMQ555wDy9LHmF511VV499138dxzz+Hzzz/HtGnTMHXqVOzZs8duc8MNN+Dtt9/G3//+d2zduhULFy7ENddcg9dffz2mcwhYDNH8C6iEi5PnxcmToeuP/1Z5WFT9y+113hVdaJsq9EwWBvym3SmcUXU8cRsXY/xiL77nMfPcs8ITkEURJaKav0hhfjqBpBIyOpEpbxPnUvyt8xY6hfWJY+CFNfic8N8q8cR/cjfOVYp7ceyGywXXsJHwZY2DNzEepw1OReXOHdix/Rs0NjaSISCITqA32VCi5XBhIIbriTZVJL8sJ8RutjYfrbvRViJKhmxoz6VLLci7f/9+DBw4EKtXr8aUKVPwzjvvYMaMGTh06JC9OFlFRQX69euHd955B1OnTg3ro66uDikpKXjttddw1lln2dtzcnIwY8YM3H333QCACRMm4MILL8RvfvMbbRsn+GKC32zfhtTUFHjcpvaJmryYoC7ETucpUoVbqTwYTh6NSKF2ToJA7kMlKnRijF+UdNXx5L5EIaCqMqdaSFdcUNYpjFA+B6c5ErdF05/c3in8zkncRvpeVW3FNitLN4XlPYnzqJrb9RNXhJW8F4/58sFH7dfMshAo+w7ub7agvrER240+QHomjhp5JBobfRg6YhQtJkgQnURvsaG9CdGGAnrbLLdvCb0pB0pHrPPHbamTt5NsaM+mS+VIVVRUAADS0tIAAA0NDTAMA/Hx8XabhIQEmKaJjz76SGkE/H4/AoEAEhISQrYnJibio48+st+feOKJeP311/Gzn/0MgwcPxqpVq/D1119j2bJlMY3Z5TJgMQP+gAW3S28IdKF8sQgneV/VMVSha7rjqkLSVDfuqv51N/OyJ40LqJWlTQlKpcELz7LMFfZ7fvEOigDnIgkAQsrGA4KAkjw6uvNxCu+ThZFTiJ1KeOk8dvJ73RxH+n51iCXe5fBGnTCN5nxkDNOEK3MYAm4P4rd/jtEN1Sjcsgm7d+9G9sRjHfclCKJ96ck2tLcSZkMV5BcFQ++cRIAc7q6m93ieZNrLEyVDNrTn0WWElGVZWLhwIU466SRMmDABAJCbm4vk5GTccsst+P3vfw/GGG699VYEAgGUlZUp+0lJSUFeXh4WL16McePGISMjA//85z9RWFiIkSNH2u0eeeQRzJ8/H0OGDIHb7YZpmvjrX/+KKVOmKPttaGhAQ0OD/b6yshIAYBoG3C4gYBkIBBhcrvBYb6ebZ5UHQHfDrcsj0m2LJMhU+TkqcRQp3EznNVmWWYTcgrkASsI8SSEekVK+3lFoLLh3ZnHIePOLcuyiCE5CRD4fcbtuDiN9N05zEUl8RQrbi4TOWxgynoLQfaItMsG3ietcyce4veR63J31kP2ZYRgwBw6G5fbA/fUm5KYF8FHpbmwsoipEBNFZ9GQb2hvhNhRwEj5BVEUi7CJCTXhRjOngHqfeK5g6gzlpC0K8UmRDexZdpvz5ggUL8MUXX+CFF16wt6Wnp+PFF1/EG2+8gT59+sDr9eLw4cOYNGkSTFM/9Oeeew6MMRxxxBGIj4/Hww8/jJ/85Cch+zzyyCNYv349Xn/9dRQVFeGBBx7AggUL8N577yn7XLp0Kbxer/0zdOhQAMF/CJdpwDQY/BaDZYWviSF7fJxu6PlrndAR+xT7loWYKj9HHotTiF804WryMcYXBctuF5Zn2Yv6rp+4Assyi+wb97yMEkwfnI28jJIQr5OYz8PbyGOUjyXOYyRRKc+LauxO6LxMfF/VdyB/f7I3Tzf/TgJXbic/hZQ9eao5lhG3RzUvhhE0BGnpYOMmwZPaF6cOSUO6r0bZP0EQ7U9PtqG9CZ63xEUUgJDXPA/YSVzll+V0y8IanUVHeaNsyIb2KLpEjtQ111yD1157DWvWrEFWVpayzffffw+3242+ffti0KBBuPHGG3HTTTc59ltTU4PKykpkZmbiwgsvRHV1Nd566y3U1dXB6/XilVdeCYkBv+qqq7B79268/fbbYX2pnqYNHToUu7/djtTUFDDG4PNbYDDgkZ6o/WbnQm2ujLxNt13lyXDapjsOELxo6Krw6HKEdPk9/AIkV4bjiB4RHoInH4NX3HOKARfHEylvSNdWl5cUaX/dOMRjy/06ofveInm/dCGLuqpOqpwy+XuS88t0cyt6pEQYY2DVFWDbNqFqbymGXbqQ4rsJooPp6Tb0/P7XxDol7Qovo94WxHITL+YwqXJjSTy1jNYIqWhypIDQPCkRsqHdn04N7WOM4dprr8Urr7yCVatWaQ0AAAwYMAAA8MEHH2Dfvn0499xzI/afnJyM5ORkHDp0CCtXrsS9994LAPD5fPD5fGFP5Fwul7aSUXx8fEicuYxhGHC7Tfj8FnwBwOMKViOyrGadqvJMAOqqcarwNI7OsxEppEx1M67qV3dDLcP3l2/SRZHmRXHIcVRj4B4onVhTzVOkMLloQiJ1YZVyPyqBozpWtCJMNdZIYZvyMQrLs4ACLpbUBTp04X1hoZVNIlb27kV7DiwpFf7RE+GvbYzqfAmCaBt6mw3taeiur9EUfRBt1fTB2fCie4uoaO452hL+ANIpH7ujIBvavelUIbVgwQI8//zzeO2115CSkoK9e/cCALxeLxITEwEAy5cvx7hx45Ceno7CwkJcf/31yM/Px5gxY+x+Tj/9dMyePRvXXBN8arVy5UowxjBmzBhs374dN910E8aOHYsrrrgCAJCamopTTjkFN910ExITEzF8+HCsXr0azz77LP74xz/GdA6MBcMQLMYABhgALAvwAWDMgNsEFo94EOfjmqhDu1ReEqebWqewNpUQEYVOJCER6QYfaK76xgtAOF0M5fE4eYfkfSIJQd3nOq+a0/w6zYmq/4qCUViW2ez54cm/4rgihWiqxsi3LWtaYLiwvOnC3/ReXiuKowrpk8WTmHysmgNxG3dcM8ZgWRYsBlgWg8UA03TBSPTCGOccx08QRNvSW2zoSwf+1KW8Uu3h+QmNyOh9OUw8zytaD0+shAuntgnnUz2sVEE2tOfSqULqscceAwCceuqpIduXL1+OefPmAQC2bduGRYsW4eDBgxgxYgRuu+025Ofnh7TfsWMHvv/+e/t9RUUFFi1ahN27dyMtLQ3nn38+lixZAo/HY7d54YUXsGjRIlxyySU4ePAghg8fjiVLluDqq6+O6Rx8fgsNPssOQzBgwDCD/xiWZQWfqLHgEzqdZ0b3JEZ1ky9u093sO3lcxO1AU1hdaXMlH51o0Hlm8styUFieZRcrKCzPQl5RifL4OuGjyyWKdD5OnrPxRe7mkEE0P91blllkv3eal0ghlbx/AE3zF1p2vLA8K8wbpztnsV/eJwqAwvLgb1GgyehEEt+m2kcVhsnnRf5++euGMj8YDAAGTNMNGIBhAi5mwWIBgAUAV9ihCIJoR3qbDe2KiKHVsd78b8kJFlESc6C47egK8HMTz6u9wxpt+1XQslBFcQmVUNo+D0q0u5HmpaGRbGhPpUvkSHVH+BoYO0u+hjclBUEbYICHdTc/fQACjOGigdcB0IumSOFU0ebvOHlWnESZ6PWQq+XJokIcL7/xl6u+6cIXdXOgC2UTP+fCSFVlThZV/ALNhR4/J36OQHNVQNWxnOZNhBtAVe6R6ph8rpz+BoDmvDHely7fSc570nmdnHLYxHayt1Kc3+f3PgIwCwCDYQCmacBlBssVG4aBysoqDBk+kuK7CYKISEttaFdGJTyc4PYB6Jg1nGIRfeK5iHnVovhpizE75SeFLo3SbKuimd/2LiCh80I5jY1saM+kUz1SPQG3acLlCq9+JCbKmoyFeFtUXhrRAyCiy8nRhaXpRID4nvchw6sAyR4JkRBP1sQVyC1vjsnXedBknMbnNFbvzKbyrQVNHhRhkV87tK6g2QsTvAj7bc+QKGjWTwy23ZITftGLVugWlmcBmUV2WOOWHH9ICVp+8c8VBKA9NoQX1uDH5QZMFj/ybxG5f76/uI+cPyW/FgWqSjzGuQHDCD4yo/LEBEG0BdHa0O4AFx1iFISODq8Uh+ab/IqCUWEeFFXRIv550NaGj3ll6aZWiSl5sWFxm/w6xP6VOos4cT+nsHcnIq1n2RLIhvZMSEi1E8EKRAF43C77HyZSzk6kfCGnUEAeXqcLd9Pl3sh922F+TTk+utBAvvYTgLCbb7FdrHlI8hypw+2KkV+UA8Bvr1XF87O8M4tDxg6Eeo2414W3FcMAdAUv5LGKc8DnnnufuAdM5SkSf4vH5U/6REMWKe5aFD9O3iqxvbhd178YViKHojqVSyYIgmhLVDa0PWnLkLVY+uqMansqAeU0BllA6YRPS0WVOF/TB2dHJTJVx+UPL3kYn8rGtZVA0tlQp++ebGjPhL7VdiKYPGsgoKg4pBJUOi+I7KGRvUWF5Vn2BWVZZpEyv0U8Fn8t972ydBMqCkbZFwad52xZZpF9PHn9IXGMkVCdl5PnTfwRhRX3Bqn63JLjDxNR8oXeO7PY3sbXwJLHwI8pru8hh0iI3ymvQsgFC183S54zXixC7k8uFCF7j2RPk/iZvF1uz7fJ+/L36yeuwMrSTSG5arq8OYIgiPbCyYa2Jdw7w1+3FG4fAL3XQ7QjnPUTV0RlM9sL78xi7Y0/Hy8nd+PcMBsqrmnF7yN08HOX50A+/vTB2SHHkd/r+hVtXTQFIJxwEls6G8ppzd8R0f2gHKkWwuO7+RoYIsGqLAz+AINpAh63C7eXXK/1uujC4FQ5Uar8FTGfJlLVPLlv7gkRY49VN/VOFyjd+lBOhRrkNvKYnHLGdCGEco6USkDwC7bsKePbuJAS2wEIEViiuIkmz0p8HekCq3rKJeZa8fOQ9+Hbo8mT0u0nzhP33HG25Pi162BwKL6bIIhoidWGzklb0G5jaU3BCKDZO8JtTKxhe9Ha7Y5CtDciOu+ZaKPFXGsR3ZzE4sVyGpeTgBJDGoG2L3kebb4U2dCeCYX2tRP+QDCZUBX7LecfRSrEEOkCy8PaxCpy/CbYKayOv+c3zc2ioDhEXImhYPwCJN7cyxdClThSnb/8uUp4qUSnHJooe+qC87DJzqnin+UVlQAasWfnWDXNoXz+aDpPnnSrEo+qeQ5/XRImyoDQUD0+v3K//FzEfcUS6E5FJcR9VKETOjElhjsSBEF0FE42tK2Rc4fEbZHg10dxLaf8shzlDb8Iv7by0PCuhK4AhlM1QfF8eR6TDLc9LQ0B5HZQFK4c1QNIGXubYmyxIH+/LQnzI3oOFNrXSvgaGCJ8AUGXy4AY2R2e6+MP264TUdHkGHlnFoeU3xZD/XgbeZ/mmOJm5ItUflmOMjytsDwr5IIoix1dzpRq7Lr3KpEptxfhIkV1oZbnQQ4n5OfIL3xcjPLzVyH2pRNRsucrL6PEFqf8uOsnrrCPLeacyX0BkT1J/LWujfj9RhJenZEQTRBE7yEWG9reyLlD0YRoqQSTHCLOQ9NkO9LVRJQYyidGJERiS47fDvvjP7kb59p9iOfe2pA71dj4HPIwxfaeU/n7dYLC/Ho+9Ki5lfgDDAGLgT80Yyz4HgZgNpW05OhC1pw8UrpwPvG92BcPERCLQaBA/XSGXzC9M4uxRRhjflGOPgSuNHiM8UXBog/yOER04YiiIFKdl7i/6rdOcPILVl5G0POkCgsU504MA8wvc4d4q7jHyYvg3IjzK/ejei2ev7xNNFS8Da+Yp/PgRUL0Tuk8U7IA0xWnEPe3PVNRVKEiCIKIlVhsaEcgeqdEz4p4veZoPTe8wqyE6L0Sj9VVCD2f6EMNVZ4Xfl8hz0NbnDMfZ2fNX7RrOnLIM9WzISHVWoxgHHcg0LQke9OCa7poBFUomspDJXtNoinmILaZPjgbeUUlzXk1Bc35T8syV9griAe9H+qwP5XQUeUZifvI45D316ESC055UCoxpZoH1RzL4ocbjZaMM9rcKFG0AeHrTOVH6C9kbpsMe6Sy6KrqRKrqfarPZTGFAud54TkNBEEQMRGjDe0ouBgSiznJi+cCHbP+U0fQmhDujhQJwaJYTeGXaBa9bTWG1lb1cwrzc4JsaPeFhFQrcZsmPG4DPDLBaHqKFnwd7o1ShbEBUN7s63KNVKJFJXrEvJq8jBIUCv/Icp6P7pjydvFiJec6qYSNShjIfcvjjhV+DLvgRlFOyHbVeOUx6YSc2I+TR0yVKyX3wcMoeQgfbyev4O4Uvsk/013o5Qu4rsCEUxEKWWTZ7dYDK4+7FoZhwDSbnxQzxsAshsoDVcoxEQRB6IjWhnYWYp6oKKJaKqB6ivDqDGLNX+ssdGLq9PUPkg3tgVCOVCsxjODK1G5X8EdcpVrESRjpcMpv4tvEfCRdqCCH38BPH5wd1p8qx0d3HBVO56bKDdMJS1V/qv7FsVYUjApb2E8lVnX9qDxwKsHrdF5O4XdiyXhVkQouWETvo1O4Jw/hixRrLof16Sr6if2qyrOLNPqB2nqf/eSMG4BD5RUI+AKO4yEIgpCJ1oZ2FnIebaRS3N0RvqwH0DWFXkuKgLSGtsjj0j3sJBva8yCPVAeiExK6kDjxtXyD7RR+J7fXhZvpxJ3q+CrvU0tD7lTHltup+tPlG+VuHCU8NQwXZtGOV3eslnjLgmtSNVdEbD5u6DkCzU88dWGI4pjExX5Vi/5ynDxN8uto1qLiJCQmoa62FhazYDIDzGKoqahDXEIc+iZ5Y54ngiCI3kI0+a4djfwQsqsQS0n6WMRVsF/nIkptVR5dZYfJhvY8yCPVQcjhYaptstDSeUR0QkcltOQbdF1YoDwW3RicvDaqc3GaD9X56EIMVd420csjCw7xR9Wn6nzF48lz4iQ+xf55tcS8jBJ7Yd5IQk3uS3yvQhfDrVtgV95HFlziNqd+7c+aHhT7fQEc2lsBl9uFPn2T7HAcgiCInkBrQs67OuOLWlahr73h3qf2qsDX1mtItQiyoT0KElIdxMsHH3UMD5Pfq7xU8v6ix0kUG7K4kts6HVd8H6tXRt5HJYZkgePUl9iHPH4gVBBEEnCqY+nmWu5HNZ+6fcTQSXG7anxOoZTyOfF2uspAohCSPUzifro2qn7lEMLcjXODZYoZ4Kv342DpIcQlepDYJx6G2XVCcQiC6HlEWsy0rVFFQPRUutK5dUT5cid0+U2t6U+0t2RDex4kpDoBXRie/F6VM6O64Km8K7JIUN348+1yGGC0Y41WFDl5tXTCK1Jf44vc9gVPNW6VR00nDFViVDdPqvHK35GTAdaFUqrmRNzO+9dV2+PIC/uqPlctYqgqnS7vt37iCjQ2NqChvgHVh2uR3DcZffolwzDp4k8QRPdGvO6qHlgSvYf28FrxPsmG9jxISHUgkQQHoPesqDxEOu+S2EZ1XF2Ymvy57r24Xdev6rdOUOjGpBI+/PeyzCKhfHtoG5UI0h3XSRyp9lEJIVGIqcYrhxiKfanmwWn+vTOLw9Z4UhWSUKEKCYwmRFDc1lBdDTT60HdACpK9ifQEjSCIbo/OlvZUATW+yN2li0u0J9Geb1t6pTjrJ64gG9oDISHVSviq7PKPZVlh21S5OoBzfo68Tef9cArbE/uRP4/FmyTvoxMI4r5O3ha5ndyXTsCIq4rL7VXeJae2kc5ZlSclH0v+3EkwiueumrNoPIJAuOdJ56mSF97l2ziq/eRwQDHs74ikGUjsEw93nAuMhf/9EwRBxEIsNrS9cYr86GpEE26vQ14LiwjHySsVTdVcHWRDex49N5Oyg2j0BdDQKJSs5OtfAGBQ/1NEcwMtosqTiuTdcQrJc/LYyO9VIs5JNImvoz0nJ4+Z2N+WHH/QADR5o1RrWulCB53C75zmNBoxpvKi6cRyJNGq2t9p3oHIa0fpcqCA0HhwnZiS93HFxcMfAPhfOL/4+wNkBAiCiI2W2NC2RvfwrKvSGhHFC0wAvc8bxYl20V0n29kayIb2LEhItRK324THbQIw7EosAADGbIPA0QkQ1Wtxm9PNtdhvpLA01We697rcIqd2kUIGxX235PibypCGhubpBBF/zS9mfEFb1XxEGqf8uU7YigZVJWJ134FqXE5hh5HCGuXje2cWh5SGFcWOU+EIEb6Pro0uvC9341y8e3zwPX94xmA0rfsStgtBEIQjsdjQ3o5sq1aWbkJ+WU7Uok/cv7eKKKCpXHppdG1VAqq1OVRuV/A32dCeAQmpVuIyTbhcqgjJ8P8IJ68CEPkpUzQiRxYUqht5p5wg3Y2+7iZf5TXSbV9ZugkobbowFQT35+si5RflKIWLSEXBKKyfuCJkpflI86P7XCciVU8jdR4h3VyqxKDOwyUfQ3c8eXxcSPIwRzl8T/Va/B3pSZtuPan1E1egxlzY1Cr0b9yt/D8gCILQE4sN7a1wW6AKyVuWWQSUImS9Ql0fvTUvSgWfA9FD11GYdnEJsqE9AfrWOhAnAcO3iT/y5+J+4mexhIupvFcq8aXy1EQ6nkqErCzdhMLyLFQUjELuxrnIL8ux11jKyyixb9KXZRaFhOHx91wscA+MvN6FPF9OYlUnGmWPj04w6USm0/yL5yS213nPZDGn8nCJ78ViG4A6JM8pR0pEtb01seAEQRBEZFQ2l79fWboJyzKLbBGUX5YT8sPhn4v7yX3w/YlmnERltMWYiN4NeaQ6kEieIr5dbqsTT06haaq+dF4leUx8H1EERHMslTjILQjNZYLUbjpCnwqtLN0UvHlv8lTJnhNZ9IjHdvLUqcao8+aJ/YrnEskL5jR/fJtuvE77qISaeCzuzfOiOeSP55DlF+Uon2KKc+tU8U9efyp341y8n6tsSomyBEEQrURlZ0LD90LtQX5RUBjx67x4vaeiEtEhiil+DwI0rWmF0FD69oRsaPfEYPTNtYjKykp4vV7s/nY7UlNTotpnTtqCkPeqm/BIXisZnRiL5LmKFOont1N9rhJPTv1HOh9d36LrXRcPHmksujkWxxgp9FJurxq7U6ijfBynMErd+MS28nFVxxQrHALqin1ybpRuO9/n/dyFynmpqKjE0BGjUFFRgdTUVGUbgiAIoG1saE9CZXucoh2i2Z8jCioK64sNlYiSH/LGSk3CR+pjkQ3tllBoXwcjenXk0C2dZ0UOmYvkeZG9R3IYn9xOFdYn960bl9zWyZOi+0wWIWLfYkggF1G6Y8phdNEINpVXSA4V1PWhCsEUv1PVviqxoxNlcl/y/Ij7y5/zkEqnhXtlbxPfLm4Tt/N9Tl//oLJPeiRDEATRMkSbEilk3Gl/+b2YF0UiKnoqCkZpPVGtEVEAkFx/snI72dDuCQmpTkTnKVKJJ/6ZeGMdjViR++OobvZ1AkfsR7zpd/ICOY3HaV9ZVIgXK6c5cRJHOlTeHPHHKZxPJTZVIlXn+XOaF7l9JC+g2HZZZhEKy7Mc140SUXmfxM9UpdF1BqSjShUTBEEQalT3BZTnGj1OAgoIfcDY1pAN7Z6QkOpA5Jt+3c0yb6vyVqhu4EWcwgMjCQ5dn7Jwi0YERfIG6cSD+NmypvWieEEFp3A6nShUzZ+Tt0jcV34tt5XFkM67JY5d9ibp2uq+Z9X3yedKrODHcSpprvM+iZ+pqgCqYIzBIhtAEATRZeD5PiF5yoSSSAIKaN9CE2RDuy8kpDoY+SY50g29uE0ntlQ38E7HjuRF0Ykxpz5lIRBNCJvcvzgvPBxBrEqn8ozJ3hr5nMQ2KhGnGosuZFA+b51Yi2Ysunaq0EJefYm3U4XwqUL1dCLKSVxxQaV66hbxqSbFJRAE0Y7orttEODwsnkSUOs9J/CzaYhLt7tkjG9ot6VQhtXTpUkyePBkpKSkYOHAgZs2ahW3btoW02bFjB2bPno309HSkpqbiggsuQHl5uWO/VVVVWLhwIYYPH47ExESceOKJ2LBhQ1i7rVu34txzz4XX60VycjImT56M7777rk3PUYR7DHReHZ1XgxPJ6yLfZOvCBHVekkiiLJqQN3kfXR/y+fLfYplX3XlG8vw4edp03kCV8NEJWSdvl9yH3JdK/PL3K0s3hRTW4NtyN87FssyiEJG1Jcdve+wihRrwED3Vorzi56rXYttIK7zT0zSC6Fh6mw0Vl8kg1MQiDHoaqnPn71Vz0pJ50tnTtoBsaPekU4XU6tWrsWDBAqxfvx7vvvsufD4fpk2bhpqaGgBATU0Npk2bBsMw8MEHH2DdunVobGzEOeecA8uytP1eddVVePfdd/Hcc8/h888/x7Rp0zB16lTs2bPHbrNjxw6cfPLJGDt2LFatWoXNmzfjN7/5DRISEtrlXHlxRG4IInmNVK/5b5VwiEaUqbwjujaRtqs+dwr3k0UIv+BVFIyyBQT3rADBxFi+3oUsPnT5SfL5qOZK7E/Vt7ivU6ij6rVKXIleNJ0o5vPBL87i3IieJnG++GcyoghyymuSF+YV86lUbeX+ZRhjME2X8jOCINqH3mpDCYTYCfGH451Z3Ku8UeK5q+ZD3t4WYrMtxRTZ0O5Llyp/vn//fgwcOBCrV6/GlClT8M4772DGjBk4dOiQXQqyoqIC/fr1wzvvvIOpU6eG9VFXV4eUlBS89tprOOuss+ztOTk5mDFjBu6++24AwEUXXQSPx4PnnnuuRWONpXQrYwyHDldgaOLZIa521c01J1aBI+8ne5l0uTl8H/lzp/A+XZ+6NtzwiYUNRO9GXkZJRBGm8/I4ecicvFg6L5yuP9V5OrUVty3LLApZdV4cE/c4yblIkcLyVO1Vv8U2KlSlz+X+Vcgl0AMBC4cqqnHkUVS6lSA6i95gQ4HeV8I70k1/TxdMFQWjtOfYVbxvseZPySXQyYZ2X7pUjlRFRQUAIC0tDQDQ0NAAwzAQHx9vt0lISIBpmvjoo4+Uffj9fgQCgbCnYomJifY+lmXhrbfewujRozF9+nQMHDgQJ5xwAl599dU2PyfGGCqrqrDz250hN7QqYaPynnCcvCqqNjqB5pRbJO7r5M3RCTNdOCH3LuVllNgGkJdi9c4sVuY+iei8YfJxogmN1J2/fGw5jE41r5FElNxW7KOwPCvEq8S9Q96ZxZg+ONvODXNaz0kngsTtsqCSjyd6olQV/cT+tdX6GIPFGMD0T7gJgmh/eroN5fS28D7uXRK9TPL73obOq9Te86Kzha3xTpEN7d50GSFlWRYWLlyIk046CRMmTAAA5ObmIjk5Gbfccgtqa2tRU1ODX/3qVwgEAigrK1P2k5KSgry8PCxevBilpaUIBAL4+9//jsLCQnufffv2obq6Gn/4wx9w5pln4p133sHs2bMxZ84crF69WtlvQ0MDKisrQ34iwRjD4YpKFH32GRKTK+1/Pp4Ho7upj3TzL4sc3f6qsDNVro8OXdiaTsDphJfch1yFT5VrJItL+VzlPCWVEHJCJZpU+6nEoW5f/plKePHQRS6g5NLk6yeugHdmccixuPDk86UqRy6G6PH3/EcWVE6ocq2cRJa8DoZlAYbheAiCINqR3mBDOb09V6o3iqdowvLkeWmtqJKLL8n20ak4UyTIhvYcuoyQWrBgAb744gu88MIL9rb09HS8+OKLeOONN9CnTx94vV4cPnwYkyZNgmnqh/7cc8+BMYYjjjgC8fHxePjhh/GTn/zE3ofHhp933nnIz8/HxIkTceutt+Lss8/G448/ruxz6dKl8Hq99s/QoUMdz4cxhqqqaqxeuxam5wAyBnlR4XkX1fFrAQQLT0QSAk6hbSrPj+4zuU8nkcO3i0JFJzJ06DxGqmOpPlOhOn/xtc5rJPapOycnL5VqPE7zqDsPlVARKxJOH5yt9byJuWNyPpP4WzyW3FZ8r8uLUq0ZJfanE2bB6GADhklWgCA6i95mQ3u7mCJChZNOLI0vcocUcYqG9lwrSgXZ0O5Nl7gKXXPNNXjzzTexZs0aDBkyJOSzadOmYceOHfj+++/hdrvRt29fDBo0CEceeaS2v6OOOgqrV69GTU0NKisrkZmZiQsvvNDeZ8CAAXC73Rg/fnzIfuPGjdOGOyxatAg33HCD/b6yslJrCBhjqKurx/ZvvkF6BjBmTBZSEkfCZSbAMAzUJHyE93MBHAy2n4MFANQCQ3XD7pQnpQrZcxJlsnhS9Smi8srI4X46D5rqt2rs0YQT6vKi5HlRhU+q5kyeH13/cjvVvIoeJ5Q2iw6eJ8U9TeOLggLKi+KQsYnHKizPcvQu6RbT5e3Ez/nxvTOLgdLQvnRV+XS5WABQg4UAgpWGgmaAIIjOoDfaUAC4OwvAQWBO2oKIc0R0H6L1OOm2ccYXNedot4Uw4jYUaNuiJ2RDuzedKqQYY7j22mvxyiuvYNWqVcjKytK2HTBgAADggw8+wL59+3DuuedG7D85ORnJyck4dOgQVq5ciXvvvRcAEBcXh8mTJ4eVif36668xfPhwZV/x8fEhceZO51RXV4+vtxcjLqEKw7MGIyV5NNyuJBgav+3LBx8NvmgSVjgI3F5yfZPXqlh5068rYKDyAqmEk4guV0vn9RGPqWqrC3XTiROdKNF5xHQeJJFoxFe0njCd1wpoLiRRUTAKyzJDhQYgFdPQCEiViLUv0kKJc46cDxWp9Ll4jvzY+WU5WJZZhLyMkpB1qJzWmJKP/X5ucyUtgGn/vgmCaB/IhgaxbajAnLQFEYsU9MYQua4G/x6cikbE+j2F2NA2RLwH4TaU/24pZEO7P50qpBYsWIDnn38er732GlJSUrB3714AgNfrRWJiIgBg+fLlGDduHNLT01FYWIjrr78e+fn5GDNmjN3P6aefjtmzZ+Oaa64BAKxcuRKMMYwZMwbbt2/HTTfdhLFjx+KKK66w97nppptw4YUXYsqUKfjRj36Et99+G2+88QZWrVrV4vNhjKG+oQHrCtfDdFcge+IQpCSNhMeVHPM/yN1ZDwFNT9s44lM38clIRcGoMMGly2NShatFCmET95f3cQo/lMeiynOSBZRq7Kp+VOenE5Oq7dEKL91nQFPIXdPaYFxg5GWUIL8sx27vnVmMLcLxdF4y+bi5BXO1gklVoU9GtWbUdGSHnFduQbC4hRfNfzuRFuFVeaQCFoNp0NM0guhoyIbqCXtAiVAbynNSt+T4SVR1Eqo1nrrD9yDfg/D7sZYKKrKh3ZtOLX+uuzAuX74c8+bNAwDceuutePrpp3Hw4EGMGDECV199NfLz80P2HTFiBObNm4c777wTAPDvf/8bixYtwu7du5GWlobzzz8fS5YsgdfrDTnO3/72NyxduhS7d+/GmDFjcNddd+G8886Lauy8dOu3JV8jJaUPTMOEz+fD5i++RPn+bThu8nD0SxmHOI+3XZ8y8IRFnmPj5LURt3NUAkoV2hbpvdhXJMGjO47TMXT7RQrx03nHxG3isZzywHhb8WLJxVM0qI6hOncxnE/2bulKmjuJKn7DII9hZemmENHHbyg4cqifLLJqEj4CYwyNfgYDDHV1tRg6fCSVbiWIDoJsaOsRbSjRMcjep7YUT+3hjRKjf+TjiA+1gdjEFNnQnkGXWkeqO8GNQMk325CcnAK/z4/vdn+HhsZyDD7CDW+f0Yj39OtwV+3tJdc7igX+Xhc+J34u7y/j1J/qc1XfOnRjUgmPaASY+HlheVbYWl6quVCJQHHdJ1GEqMahG4vqPOXxAfrS5xyn9ae4uHMKpxSFlDwWee0v8Zic9064HpbF4AsAHldw8c8hZAQIgoiCrmpDKd8qMq3x4LW396mthJRKPKmOI9tQTjRjqI5fSza0B9Alik10Z9ymCWb5sXHTRjCjEqPHpMCbPLJTDADQFBJ4MHTbnLQFdggdz2kC9MUdRHQeGzFUTcYpdM1JXIntdeJIJQzkvsR2qjGsL11hF1sAgiFuW3KaCz6oPDW8b77WU35R81Mo1fzpBIzcRg5B3JLjBwqaxhXForyymBK9T6rxqc5FHhcQfDorPzWUj9Wn4Yc4aK6BaQAmVRsiCKIFdDUbqsu3IkJx8ipFElpdOXwvkoCSEduJdj+a3CmyoT0DElKtxB/w46vPt6N079fIzRuO1OSjEB/Xv0slDYYYBl4psElcqTxS0eYqiW3Fz5y8U+L+orhyyhcSxZF8HNU45THJokYuNb6+dIWdkwQIgqFJbE1Htu2JyssowRapT51g0p2Dzgu1LDN8HIC6Mp+4Taz8F2kc4njFvCl53oJP25xD+3I3zkXBJMDt0ocYEQRBONHtbGgTvVlcyUJItbaT7Hni77uiF0oOz4tWRKkI2bdU306EbGj3hkL7WggPS1i96n1UVZdj2AgXMgaMQ0LcwG75D8GFFaDPK4qUMyXi5E3S/ZZxCpWLFL6oGrtO9Mnj5Rdk/kSJCysxDy2SR81pjOI4ZQMgixZV2XE5L8sp90qeE05FwSht+J+cRyUij+egazXi3CYMw0BlZRWFJRAEERU90YYSQUTR1BGFJGJdJwqI3fOkOqYY1qciGoFHNrT7Q0KqhXAj8Oqrf8eYccnol5qFxPgMGEaXWeO41YheKxknkRIpT8jJmyQTzTF0fUbKT4r2nJyOJe8baV5U+3Mj4FQwAkCYmJPHBgQ9W6riF7GOW9xHNgTiOP+Tcy08ZAQIgoiR3mJDifYlVm9UpKIibVnBkdtSp/Edcq0mG9rNodC+VjJgoA99U0f0OAMAqMvHnr7+wZAbepFIOU2F5VlYXxos0qC6qY9WmK0s3RT18VWf6zxdch9O4Ya6cUYSLDLBp3VBIRVpwUCVRyxsLAXORT5kYRkp90zlLSMIgmgreoUNFTh9/YMAWuadaavwuJ5U7r0tRVR70B7rWRFdCxJSrWRg/yORFD+oxxkAHe/nLkQNFuJlKdcK0Ht9eIhYbtPCr4DeEDiJExHRlT8d2RHD7FR5YCpRwftQvde11/UnnoPu/FSV+VQlznM3ztXmZInvVcUjInn9ZOT5VuVI8bEdNq6PqW+CIAiR3mhDAYTkK0eDGCLXFkKou63dpCJW2xYNHT0XveXvvidDQqqVJPQiA6BC5bWSS7Bz0aPKyXHKtdIJB/5UyS4A7ZcojgAAOMtJREFUUVSCZZlFYU+bdMJOl08l76vyQsn7R8pFcsoB494o3eK6onDxziwGFMd18ro5nY/Oeyefb35RTti4xEWC3/yBBcMADBgIWFbYORIEQThBNjRyIYu2LtTA+2lrcdbRdHVvFBC5ep8/QDa0u0NCqpUY6L0GQMfiEQ/Ct7MM7gP/he+zRACbwhI7deJCF/Kn8gpNH5xtiyggaAiWZTZX2+MV8MQLqErYRCpUIXu7dJ4rVf9OhRw4upA5cXteUUnUHjBd8YloQidV4Yn8u+NiTxR4B4zr4A8wGAYQCChPgyAIQgvZ0HBeOvAn+KqabKiRiJl7v2wXkSMLKrnyntyuKxGLNyp341xtZduOwElMGYZBNrSbQ0KqlXTH6kLtDgvAqvoWJrPAUoaiOn4t7s5qmichnEEXUqfy8ugKOWzJ8dslvNeXrrDXRhILOPB1mYL9FDuKNV1YHj9WJA+UODb5XGQhZo9PeC17p/jCv5HQiVLdOCMJVjm3TUQM9etvTUFV3BoABgyD6tYQBBEbZEMVSDb0vROmwjgYOk9tWchCFlRytb3uHgbYWWPWFWwSIRva/SEhRbQ5/rrD8DQeQKORAHfKEQAAuTjkSwf+FLbfb3YujFgcwUkw5Jfl2BdM/loUDHytC774rrhvNGFvOk+OTmDJ3h25H1UulEizNy3yIsTyscVx6dqKOHnj+JM8Lk7lUD/TDD5RdrvoyTJBEERraakNPb//Na06rig4VOKD29DuJKY6K6RPhD8M1QkqsqHdGxJSPRzLYmBgMA2jQ578MWYhULUL8aaJhsThMI1EBHwWYBgAGMAANMUDo2k8jDEwZuH2Ix4A9gabud0GLsB1ANTFHQD92lAiopCxPVWlzV4VvugsEAwFFLeJi9XKfYnb5NdO1QFFMSWH9OkWvpWPIwsyp8p7Kg9eNOJRPl+n8b6fGzZcgiCIHkF3sqHP732oqZMmG5p+XZuOjXuqdCGAqvZthcreR7sf0LpFdltDpIeYRPeH1pFqIXwNjN3fbkdqakpnD0eLzx9AIGAhPs7dIUbAX18JVvYxTAMIZOTBFRdcC6H5j6zZEIRuYjCEdi7ThGmGj5eHM+hyflQ5PvJ2HeJ+FQWjtPlVMqo+5WPzJ1GyGFEVmBAFFT9+NMZAd+7yOHVeNV1buY287lVNwkcAgIqKSgwdMYrWwCAIIiJkQ9V0lA1tb3gxqNaKKW5/WlpGvCt4pIDQ+wT5XMiGdm9ISLWQ7mIE/P4AApYBj8eA2c5GgDGGhu+3IKF6O+rjMxE/6DgYpongX1jwz6w9DJFYgl3EKUxQF3Yn7mdXBcwo0Qo1Xd+F5VnKanyqHCgAWjGlqnSoOkdOtIJLnp9IqHKm+Ni5EaDFBAmCiBayoeF0pg1tD1oiplornGS6ipAC9OdGNrR7Q77GHgxjDE11NZtftyOWrxZm9S5YcMGVOhxGU9xv8LDtd2y5fOztJeFrGzmFBahymICmC3BBaDtOJPHFRYYYpqcK2ZPzo+SS51sU4xUFkCo8L1IIpCp3Su7fKTxRFn8U2kcQRE+kt9rQthJW0RRKApy9Na0/fueE9BG9BxJSPRgGIGABBhjMdl6ngzEGX9UeJKAB9Z4BiEtMa9fjOXF3VlOceFOFQJ/fwoUDr40pVrq52s4Ke60qVRsReV0oGVWFPhFxP3lhXTG/Sa7+F23IYSQhqPKyyflUcq7U+okrUIOFYccmCILo7vRWGyoLK25DY2VLjj9YTbcg3CulioRoaxHVWXlROiKlFxDdEwrtayHdISzB5wvAYgY87mA4QHvGdwd8dfCXrkOcVYfGtB8gLvWILlPWNhjjDsTHmfaYdOGAQHjI27LMIuWTNTncTRRGuoV15RA/EbHKoFM+k3z8aMIWI4UxRptXFVJWXhj3ywcfpbAEgiCihmxoKN3RhkbLytJNYcJGtmdtIaKmD87u9OISToj50iLTB2eTDe3GkDTuoTDGYDHANBkMw2zXCzJjDP6qMsRZtWhweRHXZ2CXMQDNhD4vUK0mf3vJ9cq8Ibn4g1iQgnusZLEk50CJiJ9NH5xthwMC6vLlctVCeZsudE9XdENsE6nynxzyKC/Km1+Wgy0ALMbCyvMSBEF0V8iGykS2oSpxFZIXVBoa7tdW4ok/4AO6poBygudwkQ3tvpCQ6qEwBsAwguHd7Z0ga/nAqncBjMFIHQHD9LTr8VpEFHNwd9ZDdjgg5/aS621PEYcbBGCTUkTx33KRCRH+fnyRG/llOcGiEg4CSSWo+HYRVc6UygOl2sfpM37eueVZIeeWl1GC8UVu+PwMATICBEH0EMiGSkQxBzpxlV8Uuo5SW4bwjS9yd6mCEk44nTfZ0O4LCakeC6+P2r7/mIwx+GsPIC5QiUYzGZ4+g7rgk7SWG0JRXNUAqCh4ELkbR4UJI1XRCDknSkasCKha20mHLsRP/lxX/t3pt9if6LUqLM9C7sbQtUPWT1xhh2sY+wwEAo7DJgiC6EaQDRVp6ZhEcVUDYFnmyW00oiDdwQOlC+kTMQyyod0VElI9FMMwgiagnR9wMBaAVVECExZYnyEwXHHte8AW0lbz8H7uQgCwCyy8nwvkrg9+JnuhOGKVu7yMkpDQhsLyLHgRuTSsrpS76nOOXKhC3K4K5dOJOF7uXDwXgMejB/fzuACPK+JpEARBdAvIhobSVvPAS32LJNdHL67EtRWXZRZhZemmLu+RUokouSw82dDuS/uWoSE6FQarXWNuGWMI1B2Cp/EAGo0keFKHttuxWgtjVrv1/d4J1+M/OdehYNK1qI5fa4stUUBNH5xtrwnFkd8DasEk/ojtollY16lKkK6ohfyZWMqdi8T8spwQ4UWx3QRB9DTIhjbTnja0On4tDrnW4KC5GtXxa5ViK78sJ0Qwbcnxd3kB5YRcxZBsaPeFPFI9FMMwgo+QTBOMsXYKFWDwV+xEomHBlzgIHk9ilwxJ6AhcLsDnN+APMLhdzU/d3s8NXiB/U7QQQHi4XV5GCbZAvbaTykMktomU+6TLt1KJJhm52IYsouTiFv5ywBcgQ0AQRM+AbGjHorOhQNCGbsm5RrmfWACqu6ASgP4A2dDuCgmpNsJoWmMimqc2hukCs9o/GNY0TVgWA1xtf2FmjMFfXwFPwz74EQd36lC054KBrUU0TuKTH8b4QouwV62P1ZAZhgETgMu0ELAMmAaDaQa3M8ZgWQw3JN4FK2Ch//dp4MuRLNuzBI1WA4ADyvLlIrLnSCW4nNaniCSqVIUpgPCy7nxbXlFJyBh/tzsf+X3vimq+CIIgZMiGkg11sqFPblkStKGZzTZ0wXG/Q111PYLZV10PXW6UKhzxooxr8dcdSzpqaEQbQkKqDYhLSEZ8QjIAoKG+Bo31NfDEJcAdlwCXywOAIRDwI+D3IS4+EYYRfMJVU/m90p1rmC7ExSfC7YmHaboQCPjha6yDr6EesSW+Rr8Su2m6EZeQBJfbA9N0wQr4EQj40NhQB5fLA8M04fc1wArwm2eGQOUuJMKPuoQhiE9Ijfni6XLHweX2wAr44fc1wOWOQ3xCEmAYYJaF+tpKMMYQF58EtyceMICA34eGuuqYjgMEL8iWxQAES9pajAGsKZ3YHjeDaQSfPJoxVmsyXW4kJcQjELDQUF9nx8wyi6FifyWYxTBkVBY8cfH2083f9n0IjDE0VFehrrYGd+66QftkjQugEzcPxOS0H2Lvw37sHbQag96qdgzRc/Ja6dag4vDcKLGQBv8txqnzfa3irnsTQBBE14VsKNnQltjQZ7f/KWhD66pQt68GFwy8LuJx0of0x9RLp8AKWHj32dU4uPdwzHMRDdEUmJCxLLKh3RESUq3E7fEgPiEZv//97zFt2jT8YGI23H3iwGBg5cqVWLVqFdxuN0466STMnDkTgIH58+dj6dKlSOnTBw11VSH9udxxSOrTF3v37sVzzz2HsrIyTJo0CT/+8Y+RlJKIuurDMcQqB/8pWQRbYLrcSE5Jw1dffYWXXnoJ33//PYYNG4azzjoLo0ePRl1dHQ4dOoxBgzJQXfE9ACDQWANXXRn8MOFKHYZYn6SZpgtJffri22+/xZAhQwAwxCX0wYYN/8Wnn36KCy+8EP36psDXWI/4xD745z//iZqaGlx11VXwNzYgEPA59s+Nq2UFn2YZpgt+y7LtomkYMMzgawMGGBgCAQaLGQAD/MyC2wRcrujWD0lK7osDBw8iISEBickpqK+thMEs1FbVIz4xDkkpifDExeOWW27B2WefjR/+8Ie46667kJubi9NP+xFcrjrcOfSPweOXAwzBsBIGhrv33AAgKFb+uPoaHDE4A+atJvIWHY2F/X6v9WY5rRmlQhRWyzKLgCYjwEP68jJKMH1wNioKRtkFMsS+emlECkEQrYBsKNlQoG1s6L/3PRw8PkJt6MWDmgXWon9cjyOOzoBpmjjmh+Nx+zlLY5r3aFCJKLG4hLjulQjZ0O6JwSjDrUXwVdmrqyqwb/8BzJkzB0VFRTAMA4cPH8bpp5+O/v3746KLLgIAvPHGGzjhhBOwaNEiPPXUU9iyZQseeOABVFd833xRNwz0SemPN996Cz/72c/wi1/8AhMmTMBrr72GDRs2YM2aNcjIGAjLCsDjiQfQtGggf9rWWA8YBuLik+DxxAcvfD4ffI21YMxCfEJy8KkUguETViCAxoY6eOITsGFDEc455xzcfPPNGD58OLZu3YrExETccssteO+997B06VK8//77YJYFwzQR8NXD5UmAFfABhomAP3hRdnviggm0/kY01NWAMQsudxzi4hPhcseBWQH4fY0wXW64PXEYMGAAtm7divT0dADAHXfcgXvvvRe/+c1vsGjRIvga63Hg4GGMHj0aycnJ2Lt3Lxob6mCaJlzu4FobAb8fjQ21sAJ+xCf2gScuwZ6bgN+PhoY6NNTXwDQNGDDsi5XpciM+IRkud1yw9Kjfh8aGWgQCgaa58gQNgr8RjfU1cHvi4IlLtI9rWRasgA9+XwMSklJx2WWX4fTTT8fll1+OgD8oMFxutz0WwzDwz3/+E5MmTcKYMWNwySWXYMaMGfjpT38KZlnw+xvRUF8Dl8sNT1wiGLNQV1sN03QhITEZhmnC5XJj0aJFSElJwa9//Wtsr96Kj79/DylvHIXjpk1E2lEp2FmzHe+VvwY/82NKyVxMPnMiAKC2qg6BhEZ8t2Evhk0ehBSPFyWff4dtAzbg4awVGFUIe6FhTsjCuw4CDAAWpt6FI0eOoVXZCYKICNlQsqFdwYZuXrMFbz7xLsbljsJx0ybCOyAFW9cX44V7XoGvwY/L77owxIY21DWidPteDB45CP0GBm3oulc/xfNLXoKv0a/1REVTGOMvxUvIhnZDSEi1kMrKSmRkZKC2tha//vWv0bdvX9xyyy1gjOGmm27Ctm3b8Prrr4NZATAwuFwe7N+/H+np6aiqqsLo0aOxY8cOmEYAvoY6AGgKZUjC4MGD8cQTT2D27NkI+H1wuT2YN28eTNPE3/72N+zatQubNm1C37598fbbb+OYY47BBRdcAF9jHVzuONTW1uGf//wndu3ahSlTpuCMM84AAHz11VfYu3cvLMvC+++/j5ycHMyePRuGYWDhwoXweDy47777ws514cKFePvtt5Gfn4/09HTMmTMHy5cvx+mnn44XXngBWVlZ+PGPf4wtW7bgxRdfRFJSEi666CIMGTIEvoY6xCUkYd26dSgoKMCgQYNw2WWXwev14r333sN5552Hu+66CykpKbjooovwxz/+EVu3bsXnn3+OLVu2wDAM3Hfffdi4cSPef/997N27FwCwatUqrFmzBpZl4Uc/+hFOOeUUWAE/Dh46jFWrVuHII4/EK6+8gpEjR+KnP/1pk1FqfnLJn1pu2bIFL730EhoaGnDaaafhtNNOAwBs3rwZb7zxBpKSknDhhRciMzMThmHgP//5D0aOHIkPP/wQpaWlmDNnDo499lh8/fXXuOyyyzB27Fjk5eXhpJNOQkpKCrZs2YLU1FQUFBTgyiuvxNdff42xY8dixIgRuOSSSzB16lQ0NjZi7969mD17No499lgAwHvvvYcRI0Zg+LAhcLk9KCxcj9TUVKSlpeHKK69EQkICZsyYgYkTJ+KEE07AwYMH8Y9//AOHDh3C9OnTccIJJwAAtm7din379qGhoQEffvghbrjhBlRVVeFf//oXKioqcNRRR+Hyyy/HirK/4cGt3wFA2ALDfK0rINzLJW6/sd/vMDxrNBkBgiAiQjaUbGhPs6EXxf9R+bcebXXBp775PdnQbkinlj9funQpJk+ejJSUFAwcOBCzZs3Ctm3bQtrs2LEDs2fPRnp6OlJTU3HBBRegvLzcsd+qqiosXLgQw4cPR2JiIk488URs2LBB2/7qq6+GYRh48MEHYxr/5MmTYRgG3nrrLfzoRz8CYxYMw8C///1v/N///R+sgB81VQdRW3UItdWH0debgvraKqSkpGDUqFFYt24d3O7mNSNcnnisWbMGpmli1qxZqK+tRG31Ifh9Dbj66qvx8ssvw+/3Y+vWrbjyyivx6KOPYsKECXj88cdx2223IS4+CQ0NjTjhhBOwc+dOHH300Vi8eDEeeeQRAMDHH3+MSy+9FC+99BJGjx6N2267Dc899xwAYNiwYSgoKMDq1avR0NAQcp5xcXEwTRMJCQmIiwuO94YbbsBll11mX5gKCgowe/ZsDBkyBAkJCZgyZQrKysoQl5CEZcuW4Ve/+hXGjx+PQ4cO4aSTTkJDQwPi4oJPseLj45GQkGC7/4844giMGDEChYWFYIzh2WefxaWXXhoypoKCAowcORJHHXUUrr32WrzwwgswXW7s2rUL8+fPx+LFizFhwgSsWLECV199NeLiE2G6miNZE5JS8NZbb2HatGlIS0vDhAkT8OmnnwIAPvzwQ5x11llIT09HbW0tJk+ejLKyMgDAn//8Z5x//vmorq6G1+vFqaeeir1798LlcsHlcsHj8SAhIQEulwubN2/Gz372M/zpT3/CqFGj4HK58Oc//xmbN2+2x7F48WJUV1dj0KBBOPPMM7Fx40YAwJNPPon//ve/MAzT/pv64IMPYJom3G433G43EhIS4Ha7UVlZieOOOw5lZWUYNmwYLr74YqxYERRDH330ES655BK8+OKLGDNmDKqrq3HKKafA6/UiLy8PpaWlqK2txUVplWF/3zwUwamQhRgySE9kCKJjIRtKNpRsaNe1oUD0Igpo76WfiXaDdSLTp09ny5cvZ1988QXbuHEjmzlzJhs2bBirrq5mjDFWXV3NjjzySDZ79my2efNmtnnzZnbeeeexyZMns0AgoO33ggsuYOPHj2erV69mxcXF7I477mCpqals9+7dYW1ffvlllp2dzQYPHsyWLVsW9dgrKirY5ZdfzizLYh6Phx04cIAF/H7m8/kYAPbll1+yhvoaVnmoPOyHMcbmzZvHHnroIeb3++ztfl8je/LJJ9nkyZOD5195gFUeKmf1ddWstLSUAWDff/89W7lyJUtPT2cNDQ2MMcb27t3LkpKSWENDA/vzn//MLrvsMnucu3btYsOGDWOMMfbUU0+xE0880f7s6aefZhdffDFjjLH6+nq2aNEiNmTIEBYXF8dmzpzJtmzZwhhj7N1332WnnXZayPn37duXffjhh/b7H/zgB2zt2rX2+9/+9rds8eLFrLGxkaWmprJ9+/bZn82dO5e99NJLjDHG+vfvz/bt28cCAb+938KFC9kLL7zA5s+fzz755BM2depU9uWXX7KMjIyQMRw6dIht3bqV/eUvf2HnnHMOY4yxzz77jCUkJLDDhw8zxhirqqqyj19fW8UqD5WzmsqD9pjffPNNZlkW8/ka7H753yXnF7/4BfvNb37DGGPs7LPPZvfee6/92axZs9iLL77IGGPs0ksvZU8//bT9t/n666+z4cOHM7/fzyzLYowxds4557DXXnuNMcbYxRdfzK677jq7r/vvv5/NmzePMcbYhRdeyP75z38yX2MDs6wAu+6669iDDz7IGGPs1ltvZUuWLLH7/NOf/sTmzJlj9/PWW2+xiRMnMsYY+8tf/sImT55st92+fTsbMmQIKy8vD5nLC9c+yCb/ZxG77rOL2FRjLpv8n0Uh76cac9l1n10U9p6/nmrMZTu2b2MAWEVFBSMIov0hG0o2lGxo17Chgf0zWaBslG0bA2Wj7PfR/pAN7Z50arGJt99+O+T9008/jYEDB6KoqAhTpkzBunXrsHPnTvzvf/+z3ZzPPPMM+vXrhw8++ABTp04N67Ourg4vvfQSXnvtNUyZMgUAcOedd+KNN97AY489hrvvvttuu2fPHlx77bVYuXIlzjrrrJjHHx8fD8uy4PP54PF4grHMLjdSUlLw/fffY9TIo+y2hmHC7YmD39cYrKITF4eGhoaQ9FLGGNLS0nDgwAF7H/77wIEDcLvdSE4OVjYaM2YM4uLiUF9XhYyMDKSkpGDPnj344osvsGrVKuTl5dnJoi6XC4FAsFTsqFHB/BdfYwP69++Pw4cPB9uYBpYsWYIlS5Zg586dWLJkCc455xwUF4cuGld9cDf6pA0BAIwfPx5WwA/DdOHLL7/EDTfcANM07e9hxowZ+Pbbb1FXV4dzzz3XHk9VVRUOHjwY0q+voQ6e+ET7/XnnnYdbb70VjY2NmDdvXmhbnw8XX3wxvvvuO4waNQoVFRV2uAIADB8+HF6vF/V1VejTJwXDhg1DSUkJJmYfE5xPM7h8+FdffYXjjjsOjQ21aKyvsUMVtm/fjuzs7GC1Jbcb2dnZWLt2rd3/6NGj4fc1wO2JD5lDjhXww+cLxuyPHTsWLpcLNVUHkZySBpljjjkGAb8PlhWwY/nDUWegWlYApmFix44dOPbYY2FZwRCX7OxsbN++3W43fvx4GIaB2urDOPLII3HllVfi2GOPxfDhw/HTn/4U11xzDZ4/Zi9yC5uPs37iiuCTNIeqf7KnytMOJYIJgtBDNpRsKIdsaOfaUHiOBfxCEabS2LxRANnQ7kqXqtpXUVEBAEhLC/6zNDQ02G5rTkJCAkzTxEcffaQ0An6/H4FAAAkJCSHbExMT8dFHzQu8WZaFSy+9FDfddBOOPvroiGNraGgIcddXVlba7ujBgwdj7969GDF8KFxuD84991y8+uqrmDJlCiyrDxhjiE9IAmMMnrhg6MLevXtxyimnIGBZaPQFL9CuxgacfvrpKC0txaZNmzBhwtHwNTYgLj4Rr776Ks444wz7vPbu3WuXNa2vr8fhw4cxYMAApKenY9asWXjooYeU58Fd/5ZlhVTScXviEAgEwJiFrKws3HHHHXjqqadQV1fXVPY0eFFL7ndE8z5uNxhjMA0DAwYMwN/+9jdMmDAh5HgHDhyAx+PBBx98gMTERMjwvj3xSbYBAWDHL//jH//Ao48+ip07d9qfrV69GuXl5Vi/fj0Mw8DLL7+MpUubK+/s378fgUAAcfHJsCwL+/btw4ABA+yEZP47IyMDe/bswYABxwKMIS4hCQCQnp6OsrIyZGdnwzAMlJWV2Ym84hyqXluWBbcnzv7HcjclykKTirh3795guVzmQnl5OQYMGGCff11dHVxuDwzDwIEDB3DkkUeGHMfVFGaRnp6Ob7/9Fqbpgic+EWVlX4WM120n6wa/8zvvvBO//e1v8dlnn+GnP/0psrKyMG3anfhPzkH8bnewBHt+WQ6A0MWDObqS6Ut2LVKeI0EQHQPZULKhHLKhHW9DqxqvAxCsEBiriAKAy7JuinkfovPp1BwpEcuysHDhQpx00kn2hSQ3NxfJycm45ZZbUFtbi5qaGvzqV79CIBCw421lUlJSkJeXh8WLF6O0tBSBQAB///vfUVhYGLLPPffcA7fbjeuui7zuABCMRfd6vfbP0KFD7XjgKVOmYMOGDTAMF3yNjVi0aBGeffZZLFmyBHtK96Js7z48/PDDWLZsGVxNF07+xNDvay5BWl9fi9TUVNx888245JJLsGrValRUVuMvf/kLli1bhttvv91uu3PnTjzxxBOoqKjEnXfeialTpyIlJQWXXnopnn/+ebzxxhuoqqrCzp078fLLL4edj2GGPvn461//ihUrVqC8fB927tyJP/zhD8jJyUFSUhKGDh2K4uJibNiwASUlJSH7+f2NAIBf/OIXuPbaa7Ft2zbU1NTg448/xmeffYb+/fvjnHPOwdVXX409e/agoqICb7/9Nr799lsAwbjyN998E1u3bkVjY2NI3/feey+2bduGpKSksO949+7d2L17N7Zv345777035PPKykr84Q9/QEVFBe6//36MGDECWVlZwepIAAIBHxhj+PnPf478/HyUlOxEXYMfa9cGbxIuueQSLF68GHv27MFnn32GJ598EhdffHHIMVTX9GHDhmHNmjX4/PPPw54W6vjb3/6Gzz//HN9++x3uv/9+/OQnPwEA/OAHP8ALL7yA8vJyrFy5Em+99VbIcdavX4/NmzejvLwcP/7xj7FixQqsWbMG+/btx+23345LLrkk7FieuETs3LkTK1euRG1tLYYMGYLk5OSgkWg6obuzHrJ/Xj74KACElU3XlVjfNqX7rCxPED0NsqFkQ8mGdr4NffngoyE/RM+ny3ikFixYgC+++CLkiVd6ejpefPFF/PKXv8TDDz8M0zTxk5/8BJMmTQp58iLz3HPP4Wc/+xmOOOIIuFwuTJo0CT/5yU9QVBQsSVlUVISHHnoIn332WdSLxS1atAg33HCD/b6yshJDhw5FQ30d5s2bh8cffxwXX3wxaqsrMH78OHz66af485//jAsuuAButxsnn3wybrzxRgDAunXrMH78eAwZMgQ1lQfhcTefS31dNe68805kZ2fjj3/8I0pLSzFp0iSsWrUKEyZMgNUUXsATUc844wwce+yxeOaZZ2BZARx11FEoKCiwjUZ6ejouuOACAMCIESNQV1cXLCMKYNCgQTjppJMABMMc/vrXv+K+++5DXFwcJk2aZLvIR48ejbvuugsPPfQQjjjiCNxzzz0499xz7VCMhvoa3HbbbUhPT8f8+fNRWVmJcePG4de//jWA4IXuj3/8I+bMmQPLsjBx4kQsXrwYQND4PP744/jPf/6DRx55BOPHj0dtbS0AwO1i6OftA7+vESkpKTj77LMBACeccAKuvvpqnH/++Rg4cCBuueUWrF+/3p7D8ePHIyEhAdOmTcOoUaPwyiuvNC3IGHw6C8bQWF+DW265BcnJybjsssvg9/sxa9YsTJkyBf/3f/8Hv9+PuXPnol+/fnjiiSfsCj4nnngiMjMzwZgFZjFMmjQJI0aMABCszHTPPfdg8eLFmDdvHjIzM+355TaD7w8Axx9/PM4880zccccd2Lt3L+bPn4+5c+fCCvgxf/58bN++HWeffTZOOukkLFmyBMOHDwcAXHrppSgrK7NDR37605/ihRdewNKlS1FRUYGzzjoLN998MwAgKysLfr+/KSSEweVy4ZlnnsGiRYuQnJyMefPmYfr06aiuqlD+3d+d1fRUVrJpc7AgJNRvfJEbDdUMq6YouyEIop0hGxqEbCjZ0K5kQ3Viak7aAuV2ovvRJcqfX3PNNXjttdewZs0aZGVlKdt8//33cLvd6Nu3LwYNGoQbb7wRN93k7AatqalBZWUlMjMzceGFF6K6uhpvvfUWHnzwwZBYZAAIBAIwTRNDhw4NcYHrqKioQN++fbH7uxIMHjIcp556Kv76179iyBGZqKw4iFRvGpKSU0L28TU2wBMXj9mzZ+Pmm29GTs4k7N+7O6zvxKQ+SPH2g8fTXI2ovq4GlYcPok9qP3y07mPcd999ePfdd+3P62qrcejAfrg9Hnj79kd8QnMIAGMMfl+j7eKuqapAfX0d0gYMbFr1PYBAwI+4uPiQcdTWVKPi0PdISExCqrefvfYDx+/34fvyUgQCfvRJ8SLF2w9mU+w0ADQ2NqDi4H4kJPVBSmrfkH3r62pRXVWBFG8/xMeHhpAwxlBVeQhVFYcAAB5PHPoPzITL5UZjYwPqaqvh7dtf+b3873//wxVXXGFX7gnOTQ32798LEyzE6PdJ7YtUbz87jh4AqqsOIxAIINWbZrcNBPw4dGA/kpL7ICk5BZYVwM5tO5Ca1hf9B6aDMYbKwwcQF58Q9p0DQE11JQ4f3I9+aQOR1Ce4v2VZcEvzCQCHD+5HTXUl+qalI7lPaPlTxhgOHtgPjycOqd7m+Wyor4PpcoX8vVRWHETA74e33wAYhoHqqgrUVleiX/+BiJPm+/DB/cEYdYPB43IhVhgDLh1xI7L+w7B8xus4fPgwvF5vzP0QBNEyyIaGQjaUbGh3tKF++PARCsiGdjfau5qFE5ZlsQULFrDBgwezr7/+Oqp93n//fWYYBvvqq6+iPs7BgweZ1+tlTzzxBGOMse+//559/vnnIT+DBw9mt9xyS9T97tq1iwFghmGwTZs2sUOHDrHDhw+zN998M/jYAmApKSls4sSJ7JhjjmEJCQns1FNPZZZlsZ07dzLGGDv11FPttqqfo446iuXk5LD09HR72wsvvMDeeecdNm3aNMYYY+eddx7r379/2L6ZmZnsuOOOYyNHjmSGYTAALD4+niUnJ9ttPB4P69Onj/3e6/WyH/zgB2z8+PEh7fhPYmIiS0lJsduaphnyuWmabPz48SwnJydsTPHx8Sw7O5tNnDjR7oP/uFwu5vV6mcvlYomJiSwpKSns2LwNf5+UlMSys7NZVlYWc7vdLCUlhT3yyCPss88+Y5MmTWKMMXbllVeyjIwMxzn2eDzsmGOOYdnZ2SHH5eMdMWKEPX8AWJ8+fVhcXFzIOOLj40P6TE1NZfHx8SwuLi5kfuX9k5OTWVxcHBs2bBg75phjmMfjCWnbr18/9oMf/ID179+fJSUlsYSEhJDPU1JSWGJiov1+1KhRbMKECSHji4+PD5vPtLQ0NmnSJDZ27NiwY7bFz65du6L+3yQIouWQDSUbSjaUbCjRuXSqR+r//u//8Pzzz+O1117DmDFj7O1er9dOqly+fDnGjRuH9PR0FBYW4vrrr8e8efPwwAMP2O1PP/10zJ49O1g5BcDKlSvBGMOYMWOwfft23HTTTUhISMDatWvh8YQ/wQCCLvuFCxdi4cKFUY3dsiyUlpYiJSUFpmna/fp8PjhNqdvttisA+f2x55TExcXZybJ+v9924ROAx+Ox/24YY6iqqoqwR/TwMJRdu3bRQnka+JwPHjzYMWyIIIi2gWwo2dC2hGxo50I2tHvSqTlSjz32GADg1FNPDdm+fPlyu1zntm3bsGjRIhw8eBAjRozAbbfdhvz8/JD2O3bswPfff2+/r6iowKJFi7B7926kpaXh/PPPx5IlS7QGoCWYpokhQ4aEbZcrHbUHNTU1+MUvfoHHHnuMLkgaDMNol7lJTU2lOXeAwhEIouMgG9oyyIZGhmxo50A2tPvRJXKkiNiorKyE1+tFRUUFXZA6CJpzgiCIngFdzzsemnOip0K+Q4IgCIIgCIIgiBghIdUNiY+Pxx133BGyyCLRvtCcEwRB9Azoet7x0JwTPRUK7SMIgiAIgiAIgogR8kgRBEEQBEEQBEHECAkpgiAIgiAIgiCIGCEhRRAEQRAEQRAEESMkpAiCIAiCIAiCIGKEhBRBEARBEARBEESMkJAiCAD79+9HIBDo7GEQBEEQRLeDbCjRWyEh1YXYt28fnnnmGaxZswYVFRWdPZxewd69ezFlyhT8/Oc/x+HDhzt7OARBEEQLIRva8ZANJXo7JKS6CA888ACGDRuGJ554AjNnzsTFF1+M//73vwAAWuqrffj1r3+NoUOHIjU1FY888gj69+/f2UMiCIIgWgDZ0I6HbChBkJDqEuzatQvPPPMMnnjiCXz88cd48cUX4fF4cOGFF6Kurg6GYXT2EHsUdXV1GDZsGB5++GH85z//wZtvvomhQ4fC5/N19tAIgiCIGCEb2rGQDSWIZgxGj2o6HMZYyIX96aefxo033og9e/YgISEBAFBSUoIf/vCHOP/88/HQQw911lB7HJZlwTRNXHXVVfjkk09QVFSEr776Co888gjcbjdGjhyJs846C2PHjrXbEgRBEF0HsqGdB9lQggiFhFQH09jYiMbGRvTp08fe9t577+GCCy7Axo0bMWzYMPvi8+yzz+LnP/85tmzZgqOOOqoTR9294fPp9/thmiZM04TP50O/fv0wbNgwVFVV4ZRTTkFjYyM2b94My7Lwv//9D8nJyWEGmyAIgug8yIZ2PGRDCUIPPSroQJYuXYopU6bg3HPPxY033ohdu3YBANxuN8aOHYt//etfAGA/wTn//PMxduxY3H///QCCFzMiNu677z5MmzYNQHCeuTHweDx48MEHUV9fj+effx7PPvss/v3vf+Oll16CaZq4/vrrAVBsPUEQRFeBbGjHQzaUIJwhIdUBfPnllzj55JPx97//Hddddx0mTZqENWvWYMGCBQCAH/7whxg2bBhWr16Nzz//HEDwgp+cnIxZs2bhq6++Qm1tLbnIY+Cbb77BRRddhPvuuw8ffPABHn30UQBAIBCA2+0GAFx11VV46qmncMIJJ9hPzI4++mjMmzcPa9euxeHDh2nOCYIgOhmyoR0P2VCCiA76C29n/H4/Xn31VaSnp2PVqlW4+OKLcf/99+P666/Hnj17UFxcDJfLhSuuuAL79u3D8uXLATQ/UduxYwfi4+ORlJRET3Zi4IsvvgAAPPHEE7jppptw9913o6amBi6XK+Sp5I9+9CPExcXBMAx7++bNm5GRkYH4+PhOGTtBEAQRhGxo50A2lCCiw93ZA+jpMMYwbtw4HH/88UhPT7djjePi4rBv3z4MGDAAADB9+nQUFRXhmWeeQXx8PH75y1+irq4OJSUlmD17NgBQnHEU8HjsM844AxkZGTjhhBMwcuRIvPXWW7j55pvtp2oqTNPExo0bsWfPHlx22WVITEzswJETBEEQMmRDOxayoQQRG1RsogMQky25EXjyySfxt7/9DatWrYLL5YLL5UJFRQVef/11XHPNNRg+fDhKSkpw5plnYvny5SGJtURs1NXV4cknn8Rtt92GwsJCHH300QgEAnC5XACA7777Dp9++ik+/PBDPPfcc/jxj3+MRx55BElJSZ08coIgCIJsaOdCNpQg9JCQaiM++ugjDBkyBCNGjHCsUsONwBVXXIGkpCQ8+uijYSVCd+3ahV27diE1NRUTJkzoqFPodkQz53z7N998g/nz58M0TbzzzjshbTZu3IjHHnsMO3bswN13343c3NyOOgWCIAgCZEM7A7KhBNEGMKJV7Ny5k5133nnMMAz2y1/+Mqp9LMtiI0aMYP/+97/tbd988w1jjLFAINAu4+xJtGTOA4EAW7FiBevbty979dVXGWOMrV69mu3fv58xxlh5eXm7jZcgCIJQQza04yEbShBtBxWbaAXXXXcdjjzySLhcLpx22mkIBAJoaGiIuF9hYSEaGxtxxhlnoKysDBdffDGOOuoo7N69myrcRKClc26apr0448KFC3HOOefg1FNPxdatWwEAAwcObO+hEwRBEAJkQzsesqEE0bbQFacFfPrpp0hISMDHH3+MdevW4aWXXsK4ceNQVFSE+Pj4iJWBtm7diiOPPBKPPvooRo4ciQMHDmDHjh0YMmRIB51B96O1c87Zv38/vv32W3g8HnzzzTf44Q9/2M4jJwiCIETIhnY8ZEMJon2gqn1RwoT4YbfbjVdffRVnnnmm/fnkyZPx0ksvYffu3REv5m+++SbWrVuHQ4cOYcWKFZgxY0a7jr270pZzvmPHDlx22WXYvXs3PvzwQ5xyyintOnaCIAiiGbKhHQ/ZUIJof8gjFQXV1dU4dOiQ/X7ixIn2xYg/xfF4PIiPj8fhw4fD9q+trcXLL78MAPD5fJgxYwaefvppfPHFF2QANLTlnAPAsGHDsHjxYnz77bdkAAiCIDoQsqEdD9lQgugYSEhF4Pbbb0d2djZmzZqFiy66CF9//bUdgy26wk899VTs2bMH5eXlABCyYN26deswd+5cvPPOO/B4PJg/fz4uu+yyjj2RbkRbzvl7770HIGgwTjvttA48C4IgCIJsaMdDNpQgOg4SUhoaGxtx6aWXoqCgAE888QSuuuoqVFVV4cwzz0RRURGA4OJ+3G3OGEN2djY++ugjAAhJeD3++OOxePFiKsMagfaY8/Hjx3f8iRAEQfRyyIZ2PGRDCaIT6Ngigd2Hzz//nB199NHsww8/tLfV1dWx1NRUduGFF7Li4mLGWHOpVb/fz4455hi2aNGikO1E9NCcEwRB9Azoet7x0JwTRMdDHikNFRUV2LZtG7Kzs+1t5eXlSEtLw0cffYT33nsPjDGYpgm/3w+Xy4WTTjoJH3zwAQBQCdYWQHNOEATRM6DrecdDc04QHQ/912hITU3FMcccg9tvv93e9sQTT+DMM8/EsGHD8Oqrr4IxBsYY3O5g8UN+ceLxxkRs0JwTBEH0DOh63vHQnBNEx2MwFuXiAb2M+vp6vPDCC5g/fz4mTZqE7du3Iz4+Hh9//DG++eYbTJs2DYcOHUKfPn1gWRZM08TatWuRkZGB0aNHd/bwuyU05wRBED0Dup53PDTnBNHx0DpSEn6/H263GwkJCZg3bx6OPvpo/O9//0O/fv3w4x//GACwYcMGjBw50r4gcXc4LUzXMmjOCYIgegZ0Pe94aM4JovMgIdUEvxC53W74fD7ceuut+OUvf4nJkydj8uTJIW3Xrl2L0aNHY+jQoZ002p4BzTlBEETPgK7nHQ/NOUF0Pr0+RyoQCITECz/44IMYMGAAXnvtNbtEKAB88803+Oabb3DzzTdjxYoVuOKKKwCErslARAfNOUEQRM+ArucdD805QXQderVHKhAIwOVyAQDef/99/OIXv0B1dTX++Mc/4vLLL7cvUgCwfv16LF26FIZh4N///jdOOukkAAi5aBGRoTknCILoGdD1vOOhOSeIrkWvLzaxa9cuzJ8/H++//z6uv/56LFq0CGlpafbnjDEYhoHa2lps2rQJeXl5nTjangHNOUEQRM+ArucdD805QXQdenVo34oVK3DkkUfC5XJh8+bNuO+++0IuRkDzk5ukpCS6GLUBNOcEQRA9A7qedzw05wTRtejVHqlvvvkG5eXldKHpQGjOCYIgegZ0Pe94aM4JomvRq4UUQRAEQRAEQRBES+jVoX0EQRAEQRAEQRAtgYQUQRAEQRAEQRBEjJCQIgiCIAiCIAiCiBESUgRBEARBEARBEDFCQoogCIIgCIIgCCJGSEgRBEEQBEEQBEHECAkpgiAIgiAIgiCIGCEhRRAEQRAEQRAEESMkpAiCIAiCIAiCIGKEhBRBEARBEARBEESMkJAiujU7d+6EYRjYuHFju/RvGAZeffXVdumbIAiCIDoTsqEE0TpISBGtYt68eZg1a1anHX/o0KEoKyvDhAkTAACrVq2CYRg4fPhwp42JIAiCIKKBbChBdG/cnT0AgmgNLpcLgwYN6uxhEARBEES3g2woQbQO8kgR7cbq1atx/PHHIz4+HpmZmbj11lvh9/vtz0899VRcd911uPnmm5GWloZBgwbhzjvvDOnjq6++wsknn4yEhASMHz8e7733XkiogBiWsHPnTvzoRz8CAPTr1w+GYWDevHkAgBEjRuDBBx8M6XvixIkhxysuLsaUKVPsY7377rth57Rr1y5ccMEF6Nu3L9LS0nDeeedh586drZ0qgiAIggiBbChBdH1ISBHtwp49ezBz5kxMnjwZmzZtwmOPPYannnoKd999d0i7Z555BsnJyfjkk09w77334ne/+5198Q0EApg1axaSkpLwySef4C9/+Qtuu+027TGHDh2Kl156CQCwbds2lJWV4aGHHopqvJZlYc6cOYiLi8Mnn3yCxx9/HLfccktIG5/Ph+nTpyMlJQVr167FunXr0KdPH5x55plobGyMZXoIgiAIQgvZUILoHlBoH9Eu/PnPf8bQoUPxpz/9CYZhYOzYsSgtLcUtt9yC3/72tzDNoIY/9thjcccddwAARo0ahT/96U94//33ccYZZ+Ddd9/Fjh07sGrVKjv0YMmSJTjjjDOUx3S5XEhLSwMADBw4EH379o16vO+99x6++uorrFy5EoMHDwYA/P73v8eMGTPsNv/6179gWRaefPJJGIYBAFi+fDn69u2LVatWYdq0abFNEkEQBEEoIBtKEN0DElJEu7B161bk5eXZF0sAOOmkk1BdXY3du3dj2LBhAIJGQCQzMxP79u0DEHwiNnTo0JD47eOPP77dxjt06FDbAABAXl5eSJtNmzZh+/btSElJCdleX1+PHTt2tMu4CIIgiN4H2VCC6B6QkCI6FY/HE/LeMAxYltXmxzFNE4yxkG0+ny+mPqqrq5GTk4N//OMfYZ+lp6e3anwEQRAEEStkQwmicyEhRbQL48aNw0svvQTGmP1Ebd26dUhJScGQIUOi6mPMmDHYtWsXysvLkZGRAQDYsGGD4z5xcXEAgrHhIunp6SgrK7PfV1ZWoqSkJGS8u3btQllZGTIzMwEA69evD+lj0qRJ+Ne//oWBAwciNTU1qnMgCIIgiFghG0oQ3QMqNkG0moqKCmzcuDHkZ/78+di1axeuvfZafPXVV3jttddwxx134IYbbrBjuyNxxhln4KijjsLll1+OzZs3Y926dbj99tsBICTcQWT48OEwDANvvvkm9u/fj+rqagDAaaedhueeew5r167F559/jssvvxwul8veb+rUqRg9ejQuv/xybNq0CWvXrg1Lyr3kkkswYMAAnHfeeVi7di1KSkqwatUqXHfdddi9e3dLpo4gCILo5ZANJRtKdF9ISBGtZtWqVfjBD34Q8rN48WIUFBTg008/RXZ2Nq6++mpceeWV9kU8GlwuF1599VVUV1dj8uTJuOqqq+wLc0JCgnKfI444AnfddRduvfVWZGRk4JprrgEALFq0CKeccgrOPvtsnHXWWZg1axaOOuooez/TNPHKK6+grq4Oxx9/PK666iosWbIkpO+kpCSsWbMGw4YNw5w5czBu3DhceeWVqK+vp6drBEEQRIsgG0o2lOi+GEwOeiWILsy6detw8sknY/v27SEXcYIgCIIgnCEbShBtCwkpokvzyiuvoE+fPhg1ahS2b9+O66+/Hv369cNHH33U2UMjCIIgiC4N2VCCaF+o2ATRpamqqsItt9yC7777DgMGDMDUqVPxwAMPdPawCIIgCKLLQzaUINoX8kgRBEEQBEEQBEHECBWbIAiCIAiCIAiCiBESUgRBEARBEARBEDFCQoogCIIgCIIgCCJGSEgRBEEQBEEQBEHECAkpgiAIgiAIgiCIGCEhRRAEQRAEQRAEESMkpAiCIAiCIAiCIGKEhBRBEARBEARBEESMkJAiCIIgCIIgCIKIkf8Hfup7c3eAHOwAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[1].gval.cat_plot(title=\"Agreement Map 2nd Inclusion\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8a6dd94",
+   "metadata": {},
+   "source": [
+    "#### Band"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "da3aee47",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>band</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>averaged</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fn</th>\n",
+       "      <td>270192.0</td>\n",
+       "      <td>241027.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fp</th>\n",
+       "      <td>804888.0</td>\n",
+       "      <td>463498.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tn</th>\n",
+       "      <td>2242120.0</td>\n",
+       "      <td>1128240.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tp</th>\n",
+       "      <td>537586.0</td>\n",
+       "      <td>486353.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.721105</td>\n",
+       "      <td>0.69621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>balanced_accuracy</th>\n",
+       "      <td>0.700678</td>\n",
+       "      <td>0.688723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>critical_success_index</th>\n",
+       "      <td>0.333352</td>\n",
+       "      <td>0.408399</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equitable_threat_score</th>\n",
+       "      <td>0.192488</td>\n",
+       "      <td>0.211025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f_score</th>\n",
+       "      <td>0.500021</td>\n",
+       "      <td>0.579948</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_discovery_rate</th>\n",
+       "      <td>0.599556</td>\n",
+       "      <td>0.487969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_negative_rate</th>\n",
+       "      <td>0.334488</td>\n",
+       "      <td>0.331363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_omission_rate</th>\n",
+       "      <td>0.107547</td>\n",
+       "      <td>0.176026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>false_positive_rate</th>\n",
+       "      <td>0.264157</td>\n",
+       "      <td>0.29119</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.516237</td>\n",
+       "      <td>0.585118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>0.342864</td>\n",
+       "      <td>0.356123</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>0.454564</td>\n",
+       "      <td>0.467492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>negative_predictive_value</th>\n",
+       "      <td>0.892453</td>\n",
+       "      <td>0.823974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>overall_bias</th>\n",
+       "      <td>1.661934</td>\n",
+       "      <td>1.305853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>2.519382</td>\n",
+       "      <td>2.296222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>positive_predictive_value</th>\n",
-       "      <th>prevalence</th>\n",
-       "      <th>prevalence_threshold</th>\n",
-       "      <th>true_negative_rate</th>\n",
-       "      <th>true_positive_rate</th>\n",
+       "      <td>0.400444</td>\n",
+       "      <td>0.512031</td>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1353554.0</td>\n",
-       "      <td>4665316.0</td>\n",
-       "      <td>4669177.0</td>\n",
-       "      <td>1355189.0</td>\n",
-       "      <td>0.500228</td>\n",
-       "      <td>0.500254</td>\n",
-       "      <td>0.183778</td>\n",
-       "      <td>0.000177</td>\n",
-       "      <td>0.310494</td>\n",
-       "      <td>0.774904</td>\n",
-       "      <td>0.499698</td>\n",
-       "      <td>0.224741</td>\n",
-       "      <td>0.499793</td>\n",
-       "      <td>0.335583</td>\n",
-       "      <td>0.000425</td>\n",
-       "      <td>0.998983</td>\n",
-       "      <td>0.775259</td>\n",
-       "      <td>2.222619</td>\n",
-       "      <td>1.001018</td>\n",
-       "      <td>0.225096</td>\n",
-       "      <td>0.224918</td>\n",
-       "      <td>0.499873</td>\n",
-       "      <td>0.500207</td>\n",
-       "      <td>0.500302</td>\n",
+       "      <th>prevalence</th>\n",
+       "      <td>0.209552</td>\n",
+       "      <td>0.313645</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1373118.0</td>\n",
-       "      <td>5029027.0</td>\n",
-       "      <td>5033101.0</td>\n",
-       "      <td>1375824.0</td>\n",
-       "      <td>0.500265</td>\n",
-       "      <td>0.500347</td>\n",
-       "      <td>0.176887</td>\n",
-       "      <td>0.000234</td>\n",
-       "      <td>0.300602</td>\n",
-       "      <td>0.785190</td>\n",
-       "      <td>0.499508</td>\n",
-       "      <td>0.214341</td>\n",
-       "      <td>0.499798</td>\n",
-       "      <td>0.327888</td>\n",
-       "      <td>0.000570</td>\n",
-       "      <td>0.998611</td>\n",
-       "      <td>0.785659</td>\n",
-       "      <td>2.329933</td>\n",
-       "      <td>1.001390</td>\n",
-       "      <td>0.214810</td>\n",
-       "      <td>0.214576</td>\n",
-       "      <td>0.499826</td>\n",
-       "      <td>0.500202</td>\n",
-       "      <td>0.500492</td>\n",
+       "      <th>prevalence_threshold</th>\n",
+       "      <td>0.38651</td>\n",
+       "      <td>0.397562</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2</td>\n",
-       "      <td>1</td>\n",
-       "      <td>570988.0</td>\n",
-       "      <td>468631.0</td>\n",
-       "      <td>8865862.0</td>\n",
-       "      <td>2137755.0</td>\n",
-       "      <td>0.913676</td>\n",
-       "      <td>0.869501</td>\n",
-       "      <td>0.672806</td>\n",
-       "      <td>0.598781</td>\n",
-       "      <td>0.804404</td>\n",
-       "      <td>0.179801</td>\n",
-       "      <td>0.210794</td>\n",
-       "      <td>0.060506</td>\n",
-       "      <td>0.050204</td>\n",
-       "      <td>0.804553</td>\n",
-       "      <td>0.749276</td>\n",
-       "      <td>0.221937</td>\n",
-       "      <td>0.939494</td>\n",
-       "      <td>0.962212</td>\n",
-       "      <td>15.719903</td>\n",
-       "      <td>0.820199</td>\n",
-       "      <td>0.224918</td>\n",
-       "      <td>0.201417</td>\n",
-       "      <td>0.949796</td>\n",
-       "      <td>0.789206</td>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.735843</td>\n",
+       "      <td>0.70881</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2</td>\n",
-       "      <td>580589.0</td>\n",
-       "      <td>446310.0</td>\n",
-       "      <td>9615818.0</td>\n",
-       "      <td>2168353.0</td>\n",
-       "      <td>0.919843</td>\n",
-       "      <td>0.872220</td>\n",
-       "      <td>0.678617</td>\n",
-       "      <td>0.610168</td>\n",
-       "      <td>0.808543</td>\n",
-       "      <td>0.170695</td>\n",
-       "      <td>0.211205</td>\n",
-       "      <td>0.056941</td>\n",
-       "      <td>0.044355</td>\n",
-       "      <td>0.808797</td>\n",
-       "      <td>0.758274</td>\n",
-       "      <td>0.221007</td>\n",
-       "      <td>0.943059</td>\n",
-       "      <td>0.951152</td>\n",
-       "      <td>17.783516</td>\n",
-       "      <td>0.829305</td>\n",
-       "      <td>0.214576</td>\n",
-       "      <td>0.191679</td>\n",
-       "      <td>0.955645</td>\n",
-       "      <td>0.788795</td>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.665512</td>\n",
+       "      <td>0.668637</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "  band subsample         fn         fp         tn         tp  accuracy  \\\n",
-       "0    1         1  1353554.0  4665316.0  4669177.0  1355189.0  0.500228   \n",
-       "1    1         2  1373118.0  5029027.0  5033101.0  1375824.0  0.500265   \n",
-       "2    2         1   570988.0   468631.0  8865862.0  2137755.0  0.913676   \n",
-       "3    2         2   580589.0   446310.0  9615818.0  2168353.0  0.919843   \n",
-       "\n",
-       "   balanced_accuracy  critical_success_index  equitable_threat_score  \\\n",
-       "0           0.500254                0.183778                0.000177   \n",
-       "1           0.500347                0.176887                0.000234   \n",
-       "2           0.869501                0.672806                0.598781   \n",
-       "3           0.872220                0.678617                0.610168   \n",
-       "\n",
-       "    f_score  false_discovery_rate  false_negative_rate  false_omission_rate  \\\n",
-       "0  0.310494              0.774904             0.499698             0.224741   \n",
-       "1  0.300602              0.785190             0.499508             0.214341   \n",
-       "2  0.804404              0.179801             0.210794             0.060506   \n",
-       "3  0.808543              0.170695             0.211205             0.056941   \n",
-       "\n",
-       "   false_positive_rate  fowlkes_mallows_index  \\\n",
-       "0             0.499793               0.335583   \n",
-       "1             0.499798               0.327888   \n",
-       "2             0.050204               0.804553   \n",
-       "3             0.044355               0.808797   \n",
-       "\n",
-       "   matthews_correlation_coefficient  negative_likelihood_ratio  \\\n",
-       "0                          0.000425                   0.998983   \n",
-       "1                          0.000570                   0.998611   \n",
-       "2                          0.749276                   0.221937   \n",
-       "3                          0.758274                   0.221007   \n",
-       "\n",
-       "   negative_predictive_value  overall_bias  positive_likelihood_ratio  \\\n",
-       "0                   0.775259      2.222619                   1.001018   \n",
-       "1                   0.785659      2.329933                   1.001390   \n",
-       "2                   0.939494      0.962212                  15.719903   \n",
-       "3                   0.943059      0.951152                  17.783516   \n",
-       "\n",
-       "   positive_predictive_value  prevalence  prevalence_threshold  \\\n",
-       "0                   0.225096    0.224918              0.499873   \n",
-       "1                   0.214810    0.214576              0.499826   \n",
-       "2                   0.820199    0.224918              0.201417   \n",
-       "3                   0.829305    0.214576              0.191679   \n",
-       "\n",
-       "   true_negative_rate  true_positive_rate  \n",
-       "0            0.500207            0.500302  \n",
-       "1            0.500202            0.500492  \n",
-       "2            0.949796            0.789206  \n",
-       "3            0.955645            0.788795  "
+       "                                          0          1\n",
+       "subsample                                 1          2\n",
+       "band                               averaged   averaged\n",
+       "fn                                 270192.0   241027.0\n",
+       "fp                                 804888.0   463498.0\n",
+       "tn                                2242120.0  1128240.0\n",
+       "tp                                 537586.0   486353.0\n",
+       "accuracy                           0.721105    0.69621\n",
+       "balanced_accuracy                  0.700678   0.688723\n",
+       "critical_success_index             0.333352   0.408399\n",
+       "equitable_threat_score             0.192488   0.211025\n",
+       "f_score                            0.500021   0.579948\n",
+       "false_discovery_rate               0.599556   0.487969\n",
+       "false_negative_rate                0.334488   0.331363\n",
+       "false_omission_rate                0.107547   0.176026\n",
+       "false_positive_rate                0.264157    0.29119\n",
+       "fowlkes_mallows_index              0.516237   0.585118\n",
+       "matthews_correlation_coefficient   0.342864   0.356123\n",
+       "negative_likelihood_ratio          0.454564   0.467492\n",
+       "negative_predictive_value          0.892453   0.823974\n",
+       "overall_bias                       1.661934   1.305853\n",
+       "positive_likelihood_ratio          2.519382   2.296222\n",
+       "positive_predictive_value          0.400444   0.512031\n",
+       "prevalence                         0.209552   0.313645\n",
+       "prevalence_threshold                0.38651   0.397562\n",
+       "true_negative_rate                 0.735843    0.70881\n",
+       "true_positive_rate                 0.665512   0.668637"
       ]
      },
-     "execution_count": 88,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -907,23 +1774,25 @@
     "                                             positive_categories=[2],\n",
     "                                             negative_categories=[0, 1],\n",
     "                                             subsampling_df=polygons_categorical,\n",
-    "                                             subsampling_average=\"full-detail\")\n",
-    "met"
+    "                                             subsampling_average=\"band\")\n",
+    "met.transpose()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "f8a6dd94",
+   "id": "ff5a26ef",
    "metadata": {},
    "source": [
-    "#### Band"
+    "#### Subsample"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
-   "id": "da3aee47",
-   "metadata": {},
+   "execution_count": 25,
+   "id": "a9e533c6",
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [
     {
      "data": {
@@ -946,132 +1815,176 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
        "      <th>subsample</th>\n",
+       "      <td>averaged</td>\n",
+       "      <td>averaged</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fn</th>\n",
+       "      <td>384342.0</td>\n",
+       "      <td>126877.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fp</th>\n",
+       "      <td>1158773.0</td>\n",
+       "      <td>109613.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>tn</th>\n",
+       "      <td>1160600.0</td>\n",
+       "      <td>2209760.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>tp</th>\n",
+       "      <td>383237.0</td>\n",
+       "      <td>640702.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>accuracy</th>\n",
+       "      <td>0.500117</td>\n",
+       "      <td>0.92339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>balanced_accuracy</th>\n",
+       "      <td>0.499837</td>\n",
+       "      <td>0.893723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>critical_success_index</th>\n",
+       "      <td>0.198944</td>\n",
+       "      <td>0.730401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>equitable_threat_score</th>\n",
+       "      <td>-0.000122</td>\n",
+       "      <td>0.657571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>f_score</th>\n",
+       "      <td>0.331866</td>\n",
+       "      <td>0.844199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_discovery_rate</th>\n",
+       "      <td>0.751469</td>\n",
+       "      <td>0.146089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_negative_rate</th>\n",
+       "      <td>0.50072</td>\n",
+       "      <td>0.165295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_omission_rate</th>\n",
+       "      <td>0.248774</td>\n",
+       "      <td>0.054299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_positive_rate</th>\n",
+       "      <td>0.499606</td>\n",
+       "      <td>0.04726</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.352259</td>\n",
+       "      <td>0.844253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>-0.000282</td>\n",
+       "      <td>0.793505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>1.000651</td>\n",
+       "      <td>0.173494</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>negative_predictive_value</th>\n",
+       "      <td>0.751226</td>\n",
+       "      <td>0.945701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>overall_bias</th>\n",
+       "      <td>2.008927</td>\n",
+       "      <td>0.977509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>0.999348</td>\n",
+       "      <td>17.662067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>positive_predictive_value</th>\n",
+       "      <td>0.248531</td>\n",
+       "      <td>0.853911</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>prevalence</th>\n",
+       "      <td>0.248653</td>\n",
+       "      <td>0.248653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>prevalence_threshold</th>\n",
-       "      <th>true_negative_rate</th>\n",
-       "      <th>true_positive_rate</th>\n",
+       "      <td>0.500082</td>\n",
+       "      <td>0.192211</td>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>averaged</td>\n",
-       "      <td>1924542.0</td>\n",
-       "      <td>5133947.0</td>\n",
-       "      <td>13535039.0</td>\n",
-       "      <td>3492944.0</td>\n",
-       "      <td>0.706952</td>\n",
-       "      <td>0.684877</td>\n",
-       "      <td>0.331040</td>\n",
-       "      <td>0.180302</td>\n",
-       "      <td>0.497415</td>\n",
-       "      <td>0.595110</td>\n",
-       "      <td>0.355246</td>\n",
-       "      <td>0.124489</td>\n",
-       "      <td>0.274999</td>\n",
-       "      <td>0.510935</td>\n",
-       "      <td>0.321994</td>\n",
-       "      <td>0.489994</td>\n",
-       "      <td>0.875511</td>\n",
-       "      <td>1.592416</td>\n",
-       "      <td>2.344570</td>\n",
-       "      <td>0.404890</td>\n",
-       "      <td>0.224918</td>\n",
-       "      <td>0.395070</td>\n",
-       "      <td>0.725001</td>\n",
-       "      <td>0.644754</td>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500394</td>\n",
+       "      <td>0.95274</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>averaged</td>\n",
-       "      <td>1953707.0</td>\n",
-       "      <td>5475337.0</td>\n",
-       "      <td>14648919.0</td>\n",
-       "      <td>3544177.0</td>\n",
-       "      <td>0.710054</td>\n",
-       "      <td>0.686284</td>\n",
-       "      <td>0.322984</td>\n",
-       "      <td>0.178008</td>\n",
-       "      <td>0.488266</td>\n",
-       "      <td>0.607055</td>\n",
-       "      <td>0.355356</td>\n",
-       "      <td>0.117675</td>\n",
-       "      <td>0.272076</td>\n",
-       "      <td>0.503299</td>\n",
-       "      <td>0.320245</td>\n",
-       "      <td>0.488178</td>\n",
-       "      <td>0.882325</td>\n",
-       "      <td>1.640543</td>\n",
-       "      <td>2.369348</td>\n",
-       "      <td>0.392945</td>\n",
-       "      <td>0.214576</td>\n",
-       "      <td>0.393814</td>\n",
-       "      <td>0.727924</td>\n",
-       "      <td>0.644644</td>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.49928</td>\n",
+       "      <td>0.834705</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "  subsample      band         fn         fp          tn         tp  accuracy  \\\n",
-       "0         1  averaged  1924542.0  5133947.0  13535039.0  3492944.0  0.706952   \n",
-       "1         2  averaged  1953707.0  5475337.0  14648919.0  3544177.0  0.710054   \n",
-       "\n",
-       "   balanced_accuracy  critical_success_index  equitable_threat_score  \\\n",
-       "0           0.684877                0.331040                0.180302   \n",
-       "1           0.686284                0.322984                0.178008   \n",
-       "\n",
-       "    f_score  false_discovery_rate  false_negative_rate  false_omission_rate  \\\n",
-       "0  0.497415              0.595110             0.355246             0.124489   \n",
-       "1  0.488266              0.607055             0.355356             0.117675   \n",
-       "\n",
-       "   false_positive_rate  fowlkes_mallows_index  \\\n",
-       "0             0.274999               0.510935   \n",
-       "1             0.272076               0.503299   \n",
-       "\n",
-       "   matthews_correlation_coefficient  negative_likelihood_ratio  \\\n",
-       "0                          0.321994                   0.489994   \n",
-       "1                          0.320245                   0.488178   \n",
-       "\n",
-       "   negative_predictive_value  overall_bias  positive_likelihood_ratio  \\\n",
-       "0                   0.875511      1.592416                   2.344570   \n",
-       "1                   0.882325      1.640543                   2.369348   \n",
-       "\n",
-       "   positive_predictive_value  prevalence  prevalence_threshold  \\\n",
-       "0                   0.404890    0.224918              0.395070   \n",
-       "1                   0.392945    0.214576              0.393814   \n",
-       "\n",
-       "   true_negative_rate  true_positive_rate  \n",
-       "0            0.725001            0.644754  \n",
-       "1            0.727924            0.644644  "
+       "                                          0          1\n",
+       "subsample                          averaged   averaged\n",
+       "band                                      1          2\n",
+       "fn                                 384342.0   126877.0\n",
+       "fp                                1158773.0   109613.0\n",
+       "tn                                1160600.0  2209760.0\n",
+       "tp                                 383237.0   640702.0\n",
+       "accuracy                           0.500117    0.92339\n",
+       "balanced_accuracy                  0.499837   0.893723\n",
+       "critical_success_index             0.198944   0.730401\n",
+       "equitable_threat_score            -0.000122   0.657571\n",
+       "f_score                            0.331866   0.844199\n",
+       "false_discovery_rate               0.751469   0.146089\n",
+       "false_negative_rate                 0.50072   0.165295\n",
+       "false_omission_rate                0.248774   0.054299\n",
+       "false_positive_rate                0.499606    0.04726\n",
+       "fowlkes_mallows_index              0.352259   0.844253\n",
+       "matthews_correlation_coefficient  -0.000282   0.793505\n",
+       "negative_likelihood_ratio          1.000651   0.173494\n",
+       "negative_predictive_value          0.751226   0.945701\n",
+       "overall_bias                       2.008927   0.977509\n",
+       "positive_likelihood_ratio          0.999348  17.662067\n",
+       "positive_predictive_value          0.248531   0.853911\n",
+       "prevalence                         0.248653   0.248653\n",
+       "prevalence_threshold               0.500082   0.192211\n",
+       "true_negative_rate                 0.500394    0.95274\n",
+       "true_positive_rate                  0.49928   0.834705"
       ]
      },
-     "execution_count": 89,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1082,22 +1995,22 @@
     "                                             positive_categories=[2],\n",
     "                                             negative_categories=[0, 1],\n",
     "                                             subsampling_df=polygons_categorical,\n",
-    "                                             subsampling_average=\"band\")\n",
-    "met"
+    "                                             subsampling_average=\"subsample\")\n",
+    "met.transpose()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ff5a26ef",
+   "id": "453186df-60f5-4343-beeb-6e995d5bfefc",
    "metadata": {},
    "source": [
-    "#### Subsample"
+    "As done earlier, if one wants to combine the inclusion of multiple polygons use `unary_union`:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
-   "id": "a9e533c6",
+   "execution_count": 26,
+   "id": "2380f1c8-945d-4a61-87b8-c35eebc928e0",
    "metadata": {},
    "outputs": [
     {
@@ -1121,144 +2034,222 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>subsample</th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
        "      <th>band</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>subsample</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fn</th>\n",
+       "      <td>384342.0</td>\n",
+       "      <td>126877.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fp</th>\n",
+       "      <td>1158773.0</td>\n",
+       "      <td>109613.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>tn</th>\n",
+       "      <td>1160600.0</td>\n",
+       "      <td>2209760.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>tp</th>\n",
+       "      <td>383237.0</td>\n",
+       "      <td>640702.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>accuracy</th>\n",
+       "      <td>0.500117</td>\n",
+       "      <td>0.92339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>balanced_accuracy</th>\n",
+       "      <td>0.499837</td>\n",
+       "      <td>0.893723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>critical_success_index</th>\n",
+       "      <td>0.198944</td>\n",
+       "      <td>0.730401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>equitable_threat_score</th>\n",
+       "      <td>-0.000122</td>\n",
+       "      <td>0.657571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>f_score</th>\n",
+       "      <td>0.331866</td>\n",
+       "      <td>0.844199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_discovery_rate</th>\n",
+       "      <td>0.751469</td>\n",
+       "      <td>0.146089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_negative_rate</th>\n",
+       "      <td>0.50072</td>\n",
+       "      <td>0.165295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_omission_rate</th>\n",
+       "      <td>0.248774</td>\n",
+       "      <td>0.054299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>false_positive_rate</th>\n",
+       "      <td>0.499606</td>\n",
+       "      <td>0.04726</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>fowlkes_mallows_index</th>\n",
+       "      <td>0.352259</td>\n",
+       "      <td>0.844253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>matthews_correlation_coefficient</th>\n",
+       "      <td>-0.000282</td>\n",
+       "      <td>0.793505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>negative_likelihood_ratio</th>\n",
+       "      <td>1.000651</td>\n",
+       "      <td>0.173494</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>negative_predictive_value</th>\n",
+       "      <td>0.751226</td>\n",
+       "      <td>0.945701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>overall_bias</th>\n",
+       "      <td>2.008927</td>\n",
+       "      <td>0.977509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>positive_likelihood_ratio</th>\n",
+       "      <td>0.999348</td>\n",
+       "      <td>17.662067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>positive_predictive_value</th>\n",
+       "      <td>0.248531</td>\n",
+       "      <td>0.853911</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>prevalence</th>\n",
+       "      <td>0.248653</td>\n",
+       "      <td>0.248653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>prevalence_threshold</th>\n",
-       "      <th>true_negative_rate</th>\n",
-       "      <th>true_positive_rate</th>\n",
+       "      <td>0.500082</td>\n",
+       "      <td>0.192211</td>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>averaged</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2726672.0</td>\n",
-       "      <td>9694343.0</td>\n",
-       "      <td>9702278.0</td>\n",
-       "      <td>2731013.0</td>\n",
-       "      <td>0.500247</td>\n",
-       "      <td>0.500301</td>\n",
-       "      <td>0.180241</td>\n",
-       "      <td>0.000206</td>\n",
-       "      <td>0.305430</td>\n",
-       "      <td>0.780206</td>\n",
-       "      <td>0.499602</td>\n",
-       "      <td>0.219381</td>\n",
-       "      <td>0.499795</td>\n",
-       "      <td>0.331639</td>\n",
-       "      <td>0.000499</td>\n",
-       "      <td>0.998796</td>\n",
-       "      <td>0.780619</td>\n",
-       "      <td>2.276672</td>\n",
-       "      <td>1.001205</td>\n",
-       "      <td>0.219794</td>\n",
-       "      <td>0.219587</td>\n",
-       "      <td>0.499849</td>\n",
-       "      <td>0.500205</td>\n",
-       "      <td>0.500398</td>\n",
+       "      <th>true_negative_rate</th>\n",
+       "      <td>0.500394</td>\n",
+       "      <td>0.95274</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>averaged</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1151577.0</td>\n",
-       "      <td>914941.0</td>\n",
-       "      <td>18481680.0</td>\n",
-       "      <td>4306108.0</td>\n",
-       "      <td>0.916855</td>\n",
-       "      <td>0.870914</td>\n",
-       "      <td>0.675720</td>\n",
-       "      <td>0.604581</td>\n",
-       "      <td>0.806483</td>\n",
-       "      <td>0.175241</td>\n",
-       "      <td>0.211001</td>\n",
-       "      <td>0.058654</td>\n",
-       "      <td>0.047170</td>\n",
-       "      <td>0.806681</td>\n",
-       "      <td>0.753869</td>\n",
-       "      <td>0.221447</td>\n",
-       "      <td>0.941346</td>\n",
-       "      <td>0.956642</td>\n",
-       "      <td>16.726668</td>\n",
-       "      <td>0.824759</td>\n",
-       "      <td>0.219587</td>\n",
-       "      <td>0.196470</td>\n",
-       "      <td>0.952830</td>\n",
-       "      <td>0.788999</td>\n",
+       "      <th>true_positive_rate</th>\n",
+       "      <td>0.49928</td>\n",
+       "      <td>0.834705</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "  subsample band         fn         fp          tn         tp  accuracy  \\\n",
-       "0  averaged    1  2726672.0  9694343.0   9702278.0  2731013.0  0.500247   \n",
-       "1  averaged    2  1151577.0   914941.0  18481680.0  4306108.0  0.916855   \n",
-       "\n",
-       "   balanced_accuracy  critical_success_index  equitable_threat_score  \\\n",
-       "0           0.500301                0.180241                0.000206   \n",
-       "1           0.870914                0.675720                0.604581   \n",
-       "\n",
-       "    f_score  false_discovery_rate  false_negative_rate  false_omission_rate  \\\n",
-       "0  0.305430              0.780206             0.499602             0.219381   \n",
-       "1  0.806483              0.175241             0.211001             0.058654   \n",
-       "\n",
-       "   false_positive_rate  fowlkes_mallows_index  \\\n",
-       "0             0.499795               0.331639   \n",
-       "1             0.047170               0.806681   \n",
-       "\n",
-       "   matthews_correlation_coefficient  negative_likelihood_ratio  \\\n",
-       "0                          0.000499                   0.998796   \n",
-       "1                          0.753869                   0.221447   \n",
-       "\n",
-       "   negative_predictive_value  overall_bias  positive_likelihood_ratio  \\\n",
-       "0                   0.780619      2.276672                   1.001205   \n",
-       "1                   0.941346      0.956642                  16.726668   \n",
-       "\n",
-       "   positive_predictive_value  prevalence  prevalence_threshold  \\\n",
-       "0                   0.219794    0.219587              0.499849   \n",
-       "1                   0.824759    0.219587              0.196470   \n",
-       "\n",
-       "   true_negative_rate  true_positive_rate  \n",
-       "0            0.500205            0.500398  \n",
-       "1            0.952830            0.788999  "
+       "                                          0          1\n",
+       "band                                      1          2\n",
+       "subsample                                 1          1\n",
+       "fn                                 384342.0   126877.0\n",
+       "fp                                1158773.0   109613.0\n",
+       "tn                                1160600.0  2209760.0\n",
+       "tp                                 383237.0   640702.0\n",
+       "accuracy                           0.500117    0.92339\n",
+       "balanced_accuracy                  0.499837   0.893723\n",
+       "critical_success_index             0.198944   0.730401\n",
+       "equitable_threat_score            -0.000122   0.657571\n",
+       "f_score                            0.331866   0.844199\n",
+       "false_discovery_rate               0.751469   0.146089\n",
+       "false_negative_rate                 0.50072   0.165295\n",
+       "false_omission_rate                0.248774   0.054299\n",
+       "false_positive_rate                0.499606    0.04726\n",
+       "fowlkes_mallows_index              0.352259   0.844253\n",
+       "matthews_correlation_coefficient  -0.000282   0.793505\n",
+       "negative_likelihood_ratio          1.000651   0.173494\n",
+       "negative_predictive_value          0.751226   0.945701\n",
+       "overall_bias                       2.008927   0.977509\n",
+       "positive_likelihood_ratio          0.999348  17.662067\n",
+       "positive_predictive_value          0.248531   0.853911\n",
+       "prevalence                         0.248653   0.248653\n",
+       "prevalence_threshold               0.500082   0.192211\n",
+       "true_negative_rate                 0.500394    0.95274\n",
+       "true_positive_rate                  0.49928   0.834705"
       ]
      },
-     "execution_count": 90,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+    "combined_df = gpd.GeoDataFrame(geometry=[unary_union(polygons_categorical['geometry'])], \n",
+    "                               crs=polygons_continuous.crs)\n",
+    "combined_df.gval.create_subsampling_df(subsampling_type=[\"include\"], inplace=True)\n",
     "ag, ctab, met = cda.gval.categorical_compare(benchmark_map=bda,\n",
     "                                             metrics=\"all\",\n",
     "                                             positive_categories=[2],\n",
     "                                             negative_categories=[0, 1],\n",
-    "                                             subsampling_df=polygons_categorical,\n",
-    "                                             subsampling_average=\"subsample\")\n",
-    "met"
+    "                                             subsampling_df=combined_df,\n",
+    "                                             subsampling_average=\"full-detail\")\n",
+    "met.transpose()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "6b02adf2-f144-477e-88d9-397418c4ba9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa3a1331e40>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ag[0].gval.cat_plot(title=\"Agreement Map Inclusion\")"
    ]
   }
  ],
diff --git a/notebooks/benchmark_catalog_0.csv b/notebooks/benchmark_catalog_0.csv
new file mode 100644
index 00000000..f0a287f4
--- /dev/null
+++ b/notebooks/benchmark_catalog_0.csv
@@ -0,0 +1,3 @@
+map_id,compare_id
+./benchmark_continuous_0.tif,compare1
+./benchmark_continuous_1.tif,compare2
diff --git a/notebooks/benchmark_catalog_1.csv b/notebooks/benchmark_catalog_1.csv
new file mode 100644
index 00000000..b77b55dd
--- /dev/null
+++ b/notebooks/benchmark_catalog_1.csv
@@ -0,0 +1,3 @@
+map_id,compare_id
+./benchmark_categorical_0.tif,compare1
+./benchmark_categorical_1.tif,compare2
diff --git a/notebooks/benchmark_categorical_0.tif b/notebooks/benchmark_categorical_0.tif
new file mode 100644
index 00000000..38013ec4
Binary files /dev/null and b/notebooks/benchmark_categorical_0.tif differ
diff --git a/notebooks/benchmark_categorical_1.tif b/notebooks/benchmark_categorical_1.tif
new file mode 100644
index 00000000..d23950d5
Binary files /dev/null and b/notebooks/benchmark_categorical_1.tif differ
diff --git a/notebooks/benchmark_continuous_0.tif b/notebooks/benchmark_continuous_0.tif
new file mode 100644
index 00000000..6a1b0a2d
Binary files /dev/null and b/notebooks/benchmark_continuous_0.tif differ
diff --git a/notebooks/benchmark_continuous_1.tif b/notebooks/benchmark_continuous_1.tif
new file mode 100644
index 00000000..622a9e75
Binary files /dev/null and b/notebooks/benchmark_continuous_1.tif differ
diff --git a/notebooks/benchmark_map_multiband_two_class_categorical.tif b/notebooks/benchmark_map_multiband_two_class_categorical.tif
new file mode 100644
index 00000000..78849fca
Binary files /dev/null and b/notebooks/benchmark_map_multiband_two_class_categorical.tif differ
diff --git a/notebooks/candidate_catalog_0.csv b/notebooks/candidate_catalog_0.csv
new file mode 100644
index 00000000..b55929d3
--- /dev/null
+++ b/notebooks/candidate_catalog_0.csv
@@ -0,0 +1,3 @@
+map_id,compare_id,agreement_maps
+./candidate_continuous_0.tif,compare1,./agreement_continuous_0.tif
+./candidate_continuous_1.tif,compare2,./agreement_continuous_1.tif
diff --git a/notebooks/candidate_catalog_1.csv b/notebooks/candidate_catalog_1.csv
new file mode 100644
index 00000000..32450d68
--- /dev/null
+++ b/notebooks/candidate_catalog_1.csv
@@ -0,0 +1,3 @@
+map_id,compare_id,agreement_maps
+./candidate_categorical_0.tif,compare1,agreement_categorical_0.tif
+./candidate_categorical_1.tif,compare2,agreement_categorical_1.tif
diff --git a/notebooks/candidate_categorical_0.tif b/notebooks/candidate_categorical_0.tif
new file mode 100644
index 00000000..78457972
Binary files /dev/null and b/notebooks/candidate_categorical_0.tif differ
diff --git a/notebooks/candidate_categorical_1.tif b/notebooks/candidate_categorical_1.tif
new file mode 100644
index 00000000..9ea06cbd
Binary files /dev/null and b/notebooks/candidate_categorical_1.tif differ
diff --git a/notebooks/candidate_continuous_0.tif b/notebooks/candidate_continuous_0.tif
new file mode 100644
index 00000000..a0f46463
Binary files /dev/null and b/notebooks/candidate_continuous_0.tif differ
diff --git a/notebooks/candidate_continuous_1.tif b/notebooks/candidate_continuous_1.tif
new file mode 100644
index 00000000..6831004e
Binary files /dev/null and b/notebooks/candidate_continuous_1.tif differ
diff --git a/notebooks/candidate_map_multiband_two_class_categorical.tif b/notebooks/candidate_map_multiband_two_class_categorical.tif
new file mode 100644
index 00000000..fbb0f858
Binary files /dev/null and b/notebooks/candidate_map_multiband_two_class_categorical.tif differ
diff --git a/notebooks/subsample_continuous_polygons.gpkg b/notebooks/subsample_continuous_polygons.gpkg
new file mode 100644
index 00000000..1a73e36c
Binary files /dev/null and b/notebooks/subsample_continuous_polygons.gpkg differ
diff --git a/notebooks/subsample_two-class_polygons.gpkg b/notebooks/subsample_two-class_polygons.gpkg
new file mode 100644
index 00000000..9ca21ca3
Binary files /dev/null and b/notebooks/subsample_two-class_polygons.gpkg differ
diff --git a/pyproject.toml b/pyproject.toml
index f6a07cd5..a6838128 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,7 +12,7 @@ authors = [
 requires-python = ">=3.8"
 keywords = ["geospatial", "evaluations"]
 license = {text = "MIT"}
-version = "0.2.3"
+version = "0.2.3.1"
 dynamic = ["readme", "dependencies"]
 
 
diff --git a/src/gval/accessors/gval_dataframe.py b/src/gval/accessors/gval_dataframe.py
index 09ae9a9a..e59a6364 100644
--- a/src/gval/accessors/gval_dataframe.py
+++ b/src/gval/accessors/gval_dataframe.py
@@ -182,11 +182,12 @@ def create_subsampling_df(
                 )  # pragma: no cover
 
             if "geometry" not in geo_df.columns:
-                geo_df["geometry"] = (
-                    geometries if geometries is not None else self._obj["geometry"]
+                geo_df.set_geometry(
+                    geometries if geometries is not None else self._obj["geometry"],
+                    inplace=True
                 )
                 geo_df.crs = crs
-
+                
         if subsampling_type:
             geo_df["subsample_type"] = subsampling_type