Test use case for https://github.com/Open-EO/openeo-geopyspark-driver/issues/367

issue367.ipynb

{
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   "cell_type": "markdown",
   "id": "63f07a15-6a73-4de4-8f1e-5e131743d1d6",
   "metadata": {},
   "source": [
    "https://github.com/Open-EO/openeo-geopyspark-driver/issues/367"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e78e5357-55af-4433-b5ff-98bb1ae47d06",
   "metadata": {},
   "outputs": [],
   "source": [
    "import openeo\n",
    "import openeo.processes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c5459c7e-c067-496f-844c-e357ce945f93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'biopar': '1.2.2',\n",
       " 'cropsar': '1.4.11.dev20220902+8',\n",
       " 'cropsar_px': '0.0.10',\n",
       " 'geopyspark': '0.4.7+openeo',\n",
       " 'geotrellis-backend-assembly-static': '0.4.6-openeo',\n",
       " 'geotrellis-extensions-static': '2.3.0_2.12-SNAPSHOT 66bf1a0',\n",
       " 'nextland_services': '0.1.0.dev20230215+150',\n",
       " 'openeo': '0.15.0',\n",
       " 'openeo-geopyspark': '0.9.3a1.dev20230310+1086',\n",
       " 'openeo_driver': '0.37.2a1.dev20230308+444',\n",
       " 'openeo_r_udf': '0.5.0',\n",
       " 'openeo_udf': '1.0.0rc3'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "connection = openeo.connect(\n",
    "    # \"openeo.vito.be\"\n",
    "    \"openeo-dev.vito.be\"\n",
    ")\n",
    "connection.capabilities().capabilities[\"processing:software\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4f9d3949-4521-4796-9cad-1fcf1be8d571",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Authenticated using refresh token.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Connection to 'https://openeo-dev.vito.be/openeo/1.1/' with OidcBearerAuth>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "connection.authenticate_oidc()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9c6c2a06-cc34-4268-a441-73e323e78556",
   "metadata": {},
   "outputs": [],
   "source": [
    "collection_id = \"TERRASCOPE_S2_NDVI_V2\"\n",
    "# connection.describe_collection(collection_id)\n",
    "bands = [\"NDVI_10M\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dc7b64aa-1f9d-4555-aefe-8abcd5781138",
   "metadata": {},
   "outputs": [],
   "source": [
    "cube = connection.load_collection(\n",
    "    collection_id,\n",
    "    temporal_extent=[\"2022-09-01\", \"2022-09-30\"],\n",
    "    bands=bands\n",
    ")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c81f6e3b-8306-4ec6-97df-bb3b6c5a8c00",
   "metadata": {},
   "outputs": [],
   "source": [
    "geometries = {\n",
    "    \"type\": \"FeatureCollection\",\n",
    "    \"properties\": {},\n",
    "    \"features\": [\n",
    "        {\n",
    "            \"type\": \"Feature\",\n",
    "            \"properties\": {},\n",
    "            \"geometry\": {\n",
    "                \"type\": \"Polygon\",\n",
    "                \"coordinates\": [((3.001, 51.000), (3.001, 51.001), (3.000, 51.001), (3.000, 51.000), (3.001, 51.000))],\n",
    "            }\n",
    "        },\n",
    "        {\n",
    "            \"type\": \"Feature\",\n",
    "            \"properties\": {},\n",
    "            \"geometry\": {\n",
    "                \"type\": \"Polygon\",\n",
    "                \"coordinates\": [((3.011, 51.000), (3.011, 51.001), (3.010, 51.001), (3.010, 51.000), (3.011, 51.000))],\n",
    "            }\n",
    "        }\n",
    "    ]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8ed7b230-d6b6-415b-bf09-6715c878eb99",
   "metadata": {},
   "outputs": [],
   "source": [
    "aggregated = cube.aggregate_spatial(geometries=geometries, reducer=\"mean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ce6ac100-971b-47de-bcb5-4325832348ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "udf = \"\"\"\n",
    "def udf_apply_feature_dataframe(df: pd.DataFrame) -> pd.Series:\n",
    "    # Sum along index (time dimension)\n",
    "    return df.sum(axis=0)\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "aa81a5d0-bf1b-4227-aa60-c108d58bf88d",
   "metadata": {},
   "outputs": [],
   "source": [
    "post_processed = aggregated.process(\n",
    "    \"run_udf\",\n",
    "    data=aggregated,\n",
    "    udf=udf,\n",
    "    runtime=\"Python\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6a84702c-dc47-4049-8cee-5a990ea4da55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'columns': ['feature_index', 'avg(band_0)'],\n",
       " 'data': [[1, 519.5059523809524], [0, 611.348901098901]],\n",
       " 'index': [0, 1]}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_processed.execute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52fdd14b-d964-44d6-8c17-e7357cd41149",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d8489d1-ffcc-40d6-a917-04299cb639b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bd78079-b8be-43b4-972d-762d3964d5d3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60946f5c-6325-43ec-b76e-47269a779959",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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