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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2172d92",
+   "metadata": {},
+   "source": [
+    "# Intercomparison\n",
+    "\n",
+    "**Author:** Hannah Kerner\n",
+    "\n",
+    "**Last updated:** October 19, 2023\n",
+    "\n",
+    "**Description:** Runs intercomparison for Rwanda 2019\n",
+    "\n",
+    "## 1. Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8da37404",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#earthengine authenticate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ca87e195",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ee\n",
+    "import geemap\n",
+    "import sys\n",
+    "import pandas as pd\n",
+    "import geopandas as gpd\n",
+    "\n",
+    "ee.Initialize()\n",
+    "\n",
+    "sys.path.append(\"../..\")\n",
+    "\n",
+    "from src.compare_covermaps import TARGETS, filter_by_bounds, generate_report, CLASS_COL, COUNTRY_COL\n",
+    "from src.compare_covermaps import TEST_COUNTRIES, TEST_CODE"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9965e7c4",
+   "metadata": {},
+   "source": [
+    "## 2. Read in evaluation set"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0fe592eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "country = \"Rwanda\"\n",
+    "country_code = TEST_CODE[country]\n",
+    "dataset_path = \"../\" + TEST_COUNTRIES[country]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "27cd956c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/hkerner/anaconda3/envs/landcover-mapping/lib/python3.8/site-packages/geopandas/array.py:275: ShapelyDeprecationWarning: The array interface is deprecated and will no longer work in Shapely 2.0. Convert the '.coords' to a numpy array instead.\n",
+      "  return GeometryArray(vectorized.points_from_xy(x, y, z), crs=crs)\n"
+     ]
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(dataset_path)[[\"lat\", \"lon\", \"class_probability\", \"subset\"]]\n",
+    "df = df[(df[\"class_probability\"] != 0.5)].copy()\n",
+    "df = df[(df[\"subset\"] == \"validation\") | (df[\"subset\"] == \"testing\")].copy()\n",
+    "df[CLASS_COL] = (df[\"class_probability\"] > 0.5).astype(int)\n",
+    "df[COUNTRY_COL] = country\n",
+    "\n",
+    "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.lon, df.lat), crs=\"epsg:4326\")\n",
+    "gdf = filter_by_bounds(country_code=country_code, gdf=gdf)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25c025d0",
+   "metadata": {},
+   "source": [
+    "## 3. Run intercomparison"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b2e82752",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "TARGETS = {k:v for k,v in TARGETS.items()}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "acd098c3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[Rwanda] sampling copernicus...\n",
+      "[Rwanda] sampling worldcover-v100...\n",
+      "[Rwanda] sampling worldcover-v200...\n",
+      "[Rwanda] sampling worldcereal-v100...\n",
+      "[Rwanda] sampling glad...\n",
+      "[Rwanda] sampling asap...\n",
+      "[Rwanda] sampling dynamicworld...\n",
+      "[Rwanda] sampling gfsad-gcep...\n",
+      "[Rwanda] sampling gfsad-lgrip...\n",
+      "[Rwanda] sampling digital-earth-africa...\n",
+      "Warning: length of sampled dataset (566) != test points (376)\n",
+      "[Rwanda] sampling esa-cci-africa...\n",
+      "[Rwanda] sampling globcover-v23...\n",
+      "[Rwanda] sampling globcover-v22...\n",
+      "[Rwanda] sampling esri-lulc...\n",
+      "[Rwanda] sampling nabil-etal-2021...\n",
+      "[Rwanda] sampling harvest-dev...\n",
+      "Warning: length of sampled dataset (972) != test points (475)\n"
+     ]
+    }
+   ],
+   "source": [
+    "for cropmap in TARGETS.values():\n",
+    "    if country not in cropmap.countries:\n",
+    "        continue\n",
+    "    print(f\"[{country}] sampling \" + cropmap.title + \"...\")\n",
+    "    map_sampled = cropmap.extract_test(gdf).copy()\n",
+    "    gdf = pd.merge(gdf, map_sampled, on=[\"lat\", \"lon\"], how=\"left\")\n",
+    "    gdf.drop_duplicates(inplace=True)  # TODO find why points get duplicated"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3b1fd718",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ensemble maps: ['glad', 'worldcover-v200', 'esri-lulc']\n"
+     ]
+    },
+    {
+     "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>country</th>\n",
+       "      <th>crop_f1</th>\n",
+       "      <th>std_crop_f1</th>\n",
+       "      <th>accuracy</th>\n",
+       "      <th>std_acc</th>\n",
+       "      <th>crop_recall_pa</th>\n",
+       "      <th>std_crop_pa</th>\n",
+       "      <th>noncrop_recall_pa</th>\n",
+       "      <th>std_noncrop_pa</th>\n",
+       "      <th>crop_precision_ua</th>\n",
+       "      <th>std_crop_ua</th>\n",
+       "      <th>noncrop_precision_ua</th>\n",
+       "      <th>std_noncrop_ua</th>\n",
+       "      <th>crop_support</th>\n",
+       "      <th>noncrop_support</th>\n",
+       "      <th>tn</th>\n",
+       "      <th>fp</th>\n",
+       "      <th>fn</th>\n",
+       "      <th>tp</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dataset</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>copernicus</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>173</td>\n",
+       "      <td>138</td>\n",
+       "      <td>103</td>\n",
+       "      <td>329</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>worldcover-v100</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.84</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.58</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>262</td>\n",
+       "      <td>49</td>\n",
+       "      <td>189</td>\n",
+       "      <td>243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>worldcover-v200</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>270</td>\n",
+       "      <td>41</td>\n",
+       "      <td>184</td>\n",
+       "      <td>248</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>worldcereal-v100</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.55</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.90</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>299</td>\n",
+       "      <td>12</td>\n",
+       "      <td>321</td>\n",
+       "      <td>111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>glad</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>228</td>\n",
+       "      <td>83</td>\n",
+       "      <td>172</td>\n",
+       "      <td>260</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>asap</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>252</td>\n",
+       "      <td>59</td>\n",
+       "      <td>343</td>\n",
+       "      <td>89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dynamicworld</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.94</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>292</td>\n",
+       "      <td>19</td>\n",
+       "      <td>353</td>\n",
+       "      <td>79</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gfsad-gcep</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.74</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.49</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.58</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>151</td>\n",
+       "      <td>160</td>\n",
+       "      <td>111</td>\n",
+       "      <td>321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gfsad-lgrip</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.62</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>144</td>\n",
+       "      <td>167</td>\n",
+       "      <td>115</td>\n",
+       "      <td>317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>digital-earth-africa</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.74</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>231</td>\n",
+       "      <td>80</td>\n",
+       "      <td>178</td>\n",
+       "      <td>254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>esa-cci-africa</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.62</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.58</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.54</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>181</td>\n",
+       "      <td>130</td>\n",
+       "      <td>156</td>\n",
+       "      <td>276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>globcover-v23</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>161</td>\n",
+       "      <td>150</td>\n",
+       "      <td>149</td>\n",
+       "      <td>283</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>globcover-v22</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>178</td>\n",
+       "      <td>133</td>\n",
+       "      <td>175</td>\n",
+       "      <td>257</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>esri-lulc</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.84</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.79</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.51</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>262</td>\n",
+       "      <td>49</td>\n",
+       "      <td>247</td>\n",
+       "      <td>185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>nabil-etal-2021</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.71</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.74</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.51</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>158</td>\n",
+       "      <td>153</td>\n",
+       "      <td>111</td>\n",
+       "      <td>321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>harvest-dev</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.49</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>227</td>\n",
+       "      <td>84</td>\n",
+       "      <td>233</td>\n",
+       "      <td>199</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ensemble-subset</th>\n",
+       "      <td>Rwanda</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.88</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>432</td>\n",
+       "      <td>311</td>\n",
+       "      <td>273</td>\n",
+       "      <td>38</td>\n",
+       "      <td>187</td>\n",
+       "      <td>245</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     country  crop_f1  std_crop_f1  accuracy  std_acc  \\\n",
+       "dataset                                                                 \n",
+       "copernicus            Rwanda     0.73         0.05      0.68     0.02   \n",
+       "worldcover-v100       Rwanda     0.67         0.05      0.68     0.02   \n",
+       "worldcover-v200       Rwanda     0.69         0.05      0.70     0.02   \n",
+       "worldcereal-v100      Rwanda     0.40         0.04      0.55     0.02   \n",
+       "glad                  Rwanda     0.67         0.06      0.66     0.02   \n",
+       "asap                  Rwanda     0.31         0.06      0.46     0.02   \n",
+       "dynamicworld          Rwanda     0.30         0.04      0.50     0.02   \n",
+       "gfsad-gcep            Rwanda     0.70         0.06      0.64     0.02   \n",
+       "gfsad-lgrip           Rwanda     0.69         0.06      0.62     0.02   \n",
+       "digital-earth-africa  Rwanda     0.66         0.06      0.65     0.02   \n",
+       "esa-cci-africa        Rwanda     0.66         0.06      0.62     0.02   \n",
+       "globcover-v23         Rwanda     0.65         0.06      0.60     0.02   \n",
+       "globcover-v22         Rwanda     0.63         0.06      0.59     0.02   \n",
+       "esri-lulc             Rwanda     0.56         0.06      0.60     0.02   \n",
+       "nabil-etal-2021       Rwanda     0.71         0.06      0.64     0.02   \n",
+       "harvest-dev           Rwanda     0.56         0.06      0.57     0.02   \n",
+       "ensemble-subset       Rwanda     0.69         0.05      0.70     0.02   \n",
+       "\n",
+       "                      crop_recall_pa  std_crop_pa  noncrop_recall_pa  \\\n",
+       "dataset                                                                \n",
+       "copernicus                      0.76         0.02               0.56   \n",
+       "worldcover-v100                 0.56         0.02               0.84   \n",
+       "worldcover-v200                 0.57         0.02               0.87   \n",
+       "worldcereal-v100                0.26         0.01               0.96   \n",
+       "glad                            0.60         0.02               0.73   \n",
+       "asap                            0.21         0.01               0.81   \n",
+       "dynamicworld                    0.18         0.01               0.94   \n",
+       "gfsad-gcep                      0.74         0.02               0.49   \n",
+       "gfsad-lgrip                     0.73         0.02               0.46   \n",
+       "digital-earth-africa            0.59         0.02               0.74   \n",
+       "esa-cci-africa                  0.64         0.02               0.58   \n",
+       "globcover-v23                   0.66         0.02               0.52   \n",
+       "globcover-v22                   0.59         0.02               0.57   \n",
+       "esri-lulc                       0.43         0.01               0.84   \n",
+       "nabil-etal-2021                 0.74         0.02               0.51   \n",
+       "harvest-dev                     0.46         0.01               0.73   \n",
+       "ensemble-subset                 0.57         0.01               0.88   \n",
+       "\n",
+       "                      std_noncrop_pa  crop_precision_ua  std_crop_ua  \\\n",
+       "dataset                                                                \n",
+       "copernicus                      0.02               0.70         0.02   \n",
+       "worldcover-v100                 0.02               0.83         0.02   \n",
+       "worldcover-v200                 0.02               0.86         0.02   \n",
+       "worldcereal-v100                0.01               0.90         0.03   \n",
+       "glad                            0.02               0.76         0.02   \n",
+       "asap                            0.02               0.60         0.04   \n",
+       "dynamicworld                    0.01               0.81         0.04   \n",
+       "gfsad-gcep                      0.02               0.67         0.02   \n",
+       "gfsad-lgrip                     0.02               0.65         0.02   \n",
+       "digital-earth-africa            0.02               0.76         0.02   \n",
+       "esa-cci-africa                  0.02               0.68         0.02   \n",
+       "globcover-v23                   0.02               0.65         0.02   \n",
+       "globcover-v22                   0.02               0.66         0.02   \n",
+       "esri-lulc                       0.02               0.79         0.03   \n",
+       "nabil-etal-2021                 0.02               0.68         0.02   \n",
+       "harvest-dev                     0.02               0.70         0.03   \n",
+       "ensemble-subset                 0.02               0.87         0.02   \n",
+       "\n",
+       "                      noncrop_precision_ua  std_noncrop_ua  crop_support  \\\n",
+       "dataset                                                                    \n",
+       "copernicus                            0.63            0.03           432   \n",
+       "worldcover-v100                       0.58            0.02           432   \n",
+       "worldcover-v200                       0.59            0.02           432   \n",
+       "worldcereal-v100                      0.48            0.02           432   \n",
+       "glad                                  0.57            0.02           432   \n",
+       "asap                                  0.42            0.02           432   \n",
+       "dynamicworld                          0.45            0.02           432   \n",
+       "gfsad-gcep                            0.58            0.03           432   \n",
+       "gfsad-lgrip                           0.56            0.03           432   \n",
+       "digital-earth-africa                  0.56            0.02           432   \n",
+       "esa-cci-africa                        0.54            0.03           432   \n",
+       "globcover-v23                         0.52            0.03           432   \n",
+       "globcover-v22                         0.50            0.03           432   \n",
+       "esri-lulc                             0.51            0.02           432   \n",
+       "nabil-etal-2021                       0.59            0.03           432   \n",
+       "harvest-dev                           0.49            0.02           432   \n",
+       "ensemble-subset                       0.59            0.02           432   \n",
+       "\n",
+       "                      noncrop_support   tn   fp   fn   tp  \n",
+       "dataset                                                    \n",
+       "copernicus                        311  173  138  103  329  \n",
+       "worldcover-v100                   311  262   49  189  243  \n",
+       "worldcover-v200                   311  270   41  184  248  \n",
+       "worldcereal-v100                  311  299   12  321  111  \n",
+       "glad                              311  228   83  172  260  \n",
+       "asap                              311  252   59  343   89  \n",
+       "dynamicworld                      311  292   19  353   79  \n",
+       "gfsad-gcep                        311  151  160  111  321  \n",
+       "gfsad-lgrip                       311  144  167  115  317  \n",
+       "digital-earth-africa              311  231   80  178  254  \n",
+       "esa-cci-africa                    311  181  130  156  276  \n",
+       "globcover-v23                     311  161  150  149  283  \n",
+       "globcover-v22                     311  178  133  175  257  \n",
+       "esri-lulc                         311  262   49  247  185  \n",
+       "nabil-etal-2021                   311  158  153  111  321  \n",
+       "harvest-dev                       311  227   84  233  199  \n",
+       "ensemble-subset                   311  273   38  187  245  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "comparisons = []\n",
+    "for cropmap in TARGETS.keys():\n",
+    "    if cropmap not in gdf.columns:\n",
+    "        continue\n",
+    "    temp = gdf[[CLASS_COL, cropmap]].dropna()\n",
+    "    comparison = generate_report(cropmap, country, temp[CLASS_COL], temp[cropmap])\n",
+    "    comparisons.append(comparison)\n",
+    "\n",
+    "results = pd.concat(comparisons).set_index([\"dataset\"])\n",
+    "\n",
+    "# Add ensemble\n",
+    "ensemble_maps = [\"glad\", \"worldcover-v200\", \"esri-lulc\"] # Should be odd number\n",
+    "print(f\"Ensemble maps: {ensemble_maps}\")\n",
+    "ensemble = gdf[ensemble_maps].mode(axis='columns')\n",
+    "comparison = generate_report(\"ensemble-subset\", country, gdf[CLASS_COL], ensemble)\n",
+    "comparisons.append(comparison)\n",
+    "\n",
+    "results = pd.concat(comparisons).set_index([\"dataset\"])\n",
+    "results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "514c2c46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x1400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "crop_proportion = round(gdf[CLASS_COL].value_counts(normalize=True)[1], 4) * 100\n",
+    "ax = results.sort_values(\"crop_f1\").plot(\n",
+    "    y=[\"accuracy\", \"crop_recall_pa\", \"crop_precision_ua\", \"crop_f1\"], \n",
+    "    xerr=\"std_crop_f1\",\n",
+    "    kind=\"barh\", \n",
+    "    figsize=(6, 14),\n",
+    "    width=0.8,\n",
+    "    title=f\"{country}: {len(gdf)} points (crop proportion: {crop_proportion}%)\",\n",
+    ");\n",
+    "\n",
+    "for c in ax.containers[1::2]:\n",
+    "    ax.bar_label(c)\n",
+    "\n",
+    "for border in [\"top\", \"right\", \"bottom\", \"left\"]:\n",
+    "    ax.spines[border].set_visible(False)\n",
+    "\n",
+    "ax.legend(bbox_to_anchor=(1, 1), reverse=True);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc597c5f",
+   "metadata": {},
+   "source": [
+    "## 4. Visualize best available map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "b72ee430",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "To view and export map copy and paste the text below the dashed line into GEE\n",
+      "----------------------------------------------------------------------------------------------------\n",
+      "\n",
+      "var palettes = require('users/gena/packages:palettes');\n",
+      "var classVis = {palette: palettes.cmocean.Speed[7].slice(0,-2)}\n",
+      "var aoi = ee.FeatureCollection(\"FAO/GAUL/2015/level0\")\n",
+      "    .filter(ee.Filter.eq('ADM0_NAME', 'Rwanda'));\n",
+      "Map.centerObject(aoi, 7);\n",
+      "\n",
+      "var copernicus = ee.ImageCollection(\"COPERNICUS/Landcover/100m/Proba-V-C3/Global\")\n",
+      "        .select(\"discrete_classification\")\n",
+      "        .filterDate(\"2019-01-01\", \"2019-12-31\").filterBounds(aoi).mosaic().clip(aoi);\n",
+      "copernicus = copernicus.eq(40).rename('crop')\n",
+      "Map.addLayer(copernicus, classVis, 'Cropland from copernicus');\n",
+      "Export.image.toCloudStorage({\n",
+      "    image: copernicus,\n",
+      "    description: \"Rwanda_copernicus\",\n",
+      "    bucket: 'crop-mask-preds-merged',\n",
+      "    fileNamePrefix: 'Rwanda_copernicus',\n",
+      "    region: aoi,\n",
+      "    scale: 10,\n",
+      "    crs: \"EPSG:4326\",\n",
+      "    maxPixels: 1e10,\n",
+      "    skipEmptyTiles: true\n",
+      "});\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Run this cell to view and export map\n",
+    "print(\"To view and export map copy and paste the text below the dashed line into GEE\\n\" + \"-\"*100)\n",
+    "best_dataset = results[\"crop_f1\"].idxmax()\n",
+    "if best_dataset in TARGETS:\n",
+    "    print(TARGETS[best_dataset].ee_script(country))\n",
+    "else:\n",
+    "    image_var_names = [TARGETS[d].title_safe for d in ensemble_maps]\n",
+    "    for i, dataset in enumerate(ensemble_maps):\n",
+    "        print(TARGETS[dataset].ee_script(country, include_prefix=(i == 0), include_export=False))\n",
+    "        print(\"\\n\")\n",
+    "    print(f\"var ensemble = ee.ImageCollection.fromImages([{', '.join(image_var_names)}]).mode()\")\n",
+    "    print(f\"Map.addLayer(ensemble, classVis, 'Cropland from ensemble');\")\n",
+    "    print(f\"\"\"\n",
+    "Export.image.toCloudStorage({{\n",
+    "    image: ensemble,\n",
+    "    description: \"{country}_ensemble_{'_'.join(image_var_names)}\",\n",
+    "    bucket: 'crop-mask-preds-merged',\n",
+    "    fileNamePrefix: \"{country}_ensemble_{'_'.join(image_var_names)}\",\n",
+    "    region: aoi,\n",
+    "    scale: 10,\n",
+    "    crs: \"EPSG:4326\",\n",
+    "    maxPixels: 1e10,\n",
+    "    skipEmptyTiles: true\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": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/compare_covermaps.py b/src/compare_covermaps.py
index 99f2ec58..734db05d 100644
--- a/src/compare_covermaps.py
+++ b/src/compare_covermaps.py
@@ -636,6 +636,11 @@ def generate_report(dataset_name: str, country: str, true, pred) -> pd.DataFrame
                 ee.Image("users/adadebay/Tanzania_cropland_2019"),
                 ee.Image("users/eutzschn/Ethiopia_Bure_Jimma_2020_v1"),
                 ee.Image("users/izvonkov/Ethiopia_Bure_Jimma_2019_v1"),
+                ee.Image(
+                    "users/izvonkov/Rwanda_2019_skip_era5_min_lat--3"
+                    "-035_min_lon-28-43_max_lat--0-76_max_lon-31-013"
+                    "_dates-2019-02-01_202"
+                )
             ]
         )""",
         resolution=10,
@@ -653,6 +658,7 @@ def generate_report(dataset_name: str, country: str, true, pred) -> pd.DataFrame
             "BureJimma2020",
             "Tigray2021",
             "Tigray2020",
+            "Rwanda"
         ],
     ),
 }