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{
"cells": [
{
"cell_type": "code",
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime as dt\n",
"from collections import namedtuple\n",
"from pathlib import Path\n",
"\n",
"from toargridding.toar_rest_client import AnalysisServiceDownload, Connection\n",
"from toargridding.grids import RegularGrid\n",
"from toargridding.gridding import get_gridded_toar_data\n",
"from toargridding.metadata import TimeSample"
]
},
{
"cell_type": "code",
"Config = namedtuple(\"Config\", [\"grid\", \"time\", \"variables\", \"stats\",\"moreOptions\"])\n",
"\n",
"#moreOptions is implemented as a dict to add additional arguments to the query to the REST API\n",
"#For example the field toar1_category with its possible values Urban, RuralLowElevation, RuralHighElevation and Unclassified can be added.\n",
"#see page 18 in https://toar-data.fz-juelich.de/sphinx/TOAR_UG_Vol03_Database/build/latex/toardatabase--userguide.pdf\n",
"#or type_of_area with urban, suburban and rural on page 20 can be used\n",
"\n",
"details4Query ={\n",
" #\"toar1_category\" : \"Urban\" #uncomment if wished:-)\n",
" #\"toar1_category\" : \"RuralLowElevation\" #uncomment if wished:-)\n",
" #\"toar1_category\" : \"RuralHighElevation\" #uncomment if wished:-)\n",
" #\"type_of_area\" : \"Urban\" #also test Rural, Suburban,\n",
" \"type_of_area\" : \"Rural\" #also test Rural, Suburban,\n",
" #\"type_of_area\" : \"Suburban\" #also test Rural, Suburban,\n",
"}\n",
"grid = RegularGrid( lat_resolution=1.9, lon_resolution=2.5, )\n",
"configs = dict()\n",
" valid_data = Config(\n",
" grid,\n",
" TimeSample( start=dt(2000+year,1,1), end=dt(2000+year,12,31), sampling=\"daily\"),#possibly adopt range:-)\n",
" [\"mole_fraction_of_ozone_in_air\"],#variable name\n",
" #[ \"mean\", \"dma8epax\"],# will start one request after another other...\n",
" [ \"dma8epa_strict\" ],\n",
" details4Query\n",
" )\n",
" \n",
" configs[f\"test_ta{year}\"] = valid_data\n",
"#config = configs[\"test_ta2\"]\n",
"#config.grid"
]
},
{
"cell_type": "code",
"#CAVE: this cell runs about 45minutes per requested year. therefore we increase the waiting duration to 1h per request.\n",
"#the processing is done on the server of the TOAR database.\n",
"#a restart of the cell continues the request to the REST API if the requested data are ready for download\n",
"# The download can also take a few minutes\n",
"\n",
"stats_endpoint = \"https://toar-data.fz-juelich.de/api/v2/analysis/statistics/\"\n",
"cache_basepath = Path(\"cache\")\n",
"result_basepath = Path(\"results\")\n",
"cache_basepath.mkdir(exist_ok=True)\n",
"analysis_service = AnalysisServiceDownload(stats_endpoint=stats_endpoint, cache_dir=cache_basepath, sample_dir=result_basepath, use_downloaded=True)\n",
"minutes = 5\n",
"analysis_service.connection.wait_seconds = [minutes * 60 for i in range(5,61,minutes) ]\n",
"for person, config in configs.items():\n",
" print(f\"\\nProcessing {person}:\")\n",
" print(f\"--------------------\")\n",
" datasets, metadatas = get_gridded_toar_data(\n",
" analysis_service=analysis_service,\n",
" grid=config.grid,\n",
" time=config.time,\n",
" variables=config.variables,\n",
" stats=config.stats,\n",
" **config.moreOptions\n",
" )\n",
"\n",
" for dataset, metadata in zip(datasets, metadatas):\n",
" dataset.to_netcdf(result_basepath / f\"{metadata.get_id()}_{config.grid.get_id()}.nc\")\n",
]
}
],
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