{
 "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": 2,
   "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": 3,
   "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",
       "      <th>catalog_attribute_1</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",
       "      <td>1</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",
       "      <td>2</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   \n",
       "\n",
       "   catalog_attribute_1  \n",
       "0                    1  \n",
       "1                    2  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_categorical_catalog['catalog_attribute_1'] = [1, 2]\n",
    "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": 4,
   "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",
       "      <th>catalog_attribute_2</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",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>./benchmark_categorical_1.tif</td>\n",
       "      <td>compare2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          map_id compare_id  catalog_attribute_2\n",
       "0  ./benchmark_categorical_0.tif   compare1                    3\n",
       "1  ./benchmark_categorical_1.tif   compare2                    4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "benchmark_categorical_catalog['catalog_attribute_2'] = [3, 4]\n",
    "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": 5,
   "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>catalog_attribute_1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</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>catalog_attribute_2</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</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",
       "catalog_attribute_1                                    1   \n",
       "map_id_benchmark           ./benchmark_categorical_0.tif   \n",
       "catalog_attribute_2                                    3   \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",
       "catalog_attribute_1                                    2   \n",
       "map_id_benchmark           ./benchmark_categorical_1.tif   \n",
       "catalog_attribute_2                                    4   \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",
       "catalog_attribute_1                                    2  \n",
       "map_id_benchmark           ./benchmark_categorical_1.tif  \n",
       "catalog_attribute_2                                    4  \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": 5,
     "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": 6,
   "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(\n",
    "        title=f'Agreement Map {int(ag_map.split(\"_\")[-1][0]) + 1}'\n",
    "    )"
   ]
  },
  {
   "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": 7,
   "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",
       "      <th>catalog_attribute_1</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",
       "      <td>1</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",
       "      <td>2</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   \n",
       "\n",
       "   catalog_attribute_1  \n",
       "0                    1  \n",
       "1                    2  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_continuous_catalog['catalog_attribute_1'] = [1, 2]\n",
    "candidate_continuous_catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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",
       "      <th>catalog_attribute_2</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",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>./benchmark_continuous_1.tif</td>\n",
       "      <td>compare2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         map_id compare_id  catalog_attribute_2\n",
       "0  ./benchmark_continuous_0.tif   compare1                    3\n",
       "1  ./benchmark_continuous_1.tif   compare2                    4"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "benchmark_continuous_catalog['catalog_attribute_2'] = [3, 4]\n",
    "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": 9,
   "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",
       "      <th>2</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",
       "      <td>./candidate_continuous_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_continuous_0.tif</td>\n",
       "      <td>./agreement_continuous_1.tif</td>\n",
       "      <td>./agreement_continuous_1.tif</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>catalog_attribute_1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</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",
       "      <td>./benchmark_continuous_1.tif</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>catalog_attribute_2</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</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>coefficient_of_determination</th>\n",
       "      <td>-0.06616</td>\n",
       "      <td>-2.829421</td>\n",
       "      <td>0.10903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_absolute_error</th>\n",
       "      <td>0.317389</td>\n",
       "      <td>0.485031</td>\n",
       "      <td>0.485031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_absolute_percentage_error</th>\n",
       "      <td>0.159568</td>\n",
       "      <td>0.202235</td>\n",
       "      <td>0.153235</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",
       "catalog_attribute_1                                        1   \n",
       "map_id_benchmark                ./benchmark_continuous_0.tif   \n",
       "catalog_attribute_2                                        3   \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",
       "catalog_attribute_1                                        2   \n",
       "map_id_benchmark                ./benchmark_continuous_1.tif   \n",
       "catalog_attribute_2                                        4   \n",
       "band                                                       1   \n",
       "coefficient_of_determination                       -2.829421   \n",
       "mean_absolute_error                                 0.485031   \n",
       "mean_absolute_percentage_error                      0.202235   \n",
       "\n",
       "                                                           2  \n",
       "map_id_candidate                ./candidate_continuous_1.tif  \n",
       "compare_id                                          compare2  \n",
       "agreement_maps                  ./agreement_continuous_1.tif  \n",
       "catalog_attribute_1                                        2  \n",
       "map_id_benchmark                ./benchmark_continuous_1.tif  \n",
       "catalog_attribute_2                                        4  \n",
       "band                                                       2  \n",
       "coefficient_of_determination                         0.10903  \n",
       "mean_absolute_error                                 0.485031  \n",
       "mean_absolute_percentage_error                      0.153235  "
      ]
     },
     "execution_count": 9,
     "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": 10,
   "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(\n",
    "        title=f'Agreement Map {int(ag_map.split(\"_\")[-1][0]) + 1}'\n",
    "    )"
   ]
  }
 ],
 "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": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}