Source code for

from pathlib import Path
from typing import DefaultDict, Dict, Optional, Union
import logging
from import BaseStore
from xarray import Dataset

logger = logging.getLogger("")
logger.setLevel(logging.DEBUG)  # Have to set level for logger as well as handler

__all__ = ["EulerianModel"]

# TODO: Currently built around these keys but will probably need more unique distiguishers for different setups
# model name
# species
# date (start_date)
# ...
# setup (included as option for now)

[docs]class EulerianModel(BaseStore): """This class is used to process Eulerian model data""" _root = "EulerianModel" _uuid = "63ff2365-3ba2-452a-a53d-110140805d06" _metakey = f"{_root}/uuid/{_uuid}/metastore"
[docs] @staticmethod def read_file( filepath: Union[str, Path], model: str, species: str, start_date: Optional[str] = None, end_date: Optional[str] = None, setup: Optional[str] = None, overwrite: bool = False, ) -> Dict: """Read Eulerian model output Args: filepath: Path of Eulerian model species output model: Eulerian model name species: Species name start_date: Start date (inclusive) associated with model run end_date: End date (exclusive) associated with model run setup: Additional setup details for run overwrite: Should this data overwrite currently stored data. """ # TODO: As written, this currently includes some light assumptions that we're dealing with GEOSChem SpeciesConc format. # May need to split out into multiple modules (like with ObsSurface) or into separate retrieve functions as needed. from collections import defaultdict from import assign_data, datasource_lookup, load_metastore from openghg.util import clean_string, hash_file, timestamp_now, timestamp_tzaware from pandas import Timestamp as pd_Timestamp from xarray import open_dataset model = clean_string(model) species = clean_string(species) start_date = clean_string(start_date) end_date = clean_string(end_date) setup = clean_string(setup) filepath = Path(filepath) em_store = EulerianModel.load() metastore = load_metastore(key=em_store._metakey) file_hash = hash_file(filepath=filepath) if file_hash in em_store._file_hashes and not overwrite: raise ValueError( f"This file has been uploaded previously with the filename : {em_store._file_hashes[file_hash]}." ) em_data = open_dataset(filepath) # Check necessary 4D coordinates are present and rename if necessary (for consistency) check_coords = { "time": ["time"], "lat": ["lat", "latitude"], "lon": ["lon", "longitude"], "lev": ["lev", "level", "layer", "sigma_level"], } for name, coord_options in check_coords.items(): for coord in coord_options: if coord in em_data.coords: break else: raise ValueError(f"Input data must contain one of '{coord_options}' co-ordinate") if name != coord:"Renaming co-ordinate '{coord}' to '{name}'") em_data = em_data.rename({coord: name}) attrs = em_data.attrs # author_name = "OpenGHG Cloud" # em_data.attrs["author"] = author_name metadata = {} metadata.update(attrs) metadata["model"] = model metadata["species"] = species metadata["processed"] = str(timestamp_now()) metadata["data_type"] = "eulerian_model" if start_date is None: if len(em_data["time"]) > 1: start_date = str(timestamp_tzaware(em_data.time[0].values)) else: try: start_date = attrs["simulation_start_date_and_time"] except KeyError: raise Exception("Unable to derive start_date from data, please provide as an input.") else: start_date = timestamp_tzaware(start_date) start_date = str(start_date) if end_date is None: if len(em_data["time"]) > 1: end_date = str(timestamp_tzaware(em_data.time[-1].values)) else: try: end_date = attrs["simulation_end_date_and_time"] except KeyError: raise Exception("Unable to derive `end_date` from data, please provide as an input.") else: end_date = timestamp_tzaware(end_date) end_date = str(end_date) date = str(pd_Timestamp(start_date).date()) metadata["date"] = date metadata["start_date"] = start_date metadata["end_date"] = end_date metadata["max_longitude"] = round(float(em_data["lon"].max()), 5) metadata["min_longitude"] = round(float(em_data["lon"].min()), 5) metadata["max_latitude"] = round(float(em_data["lat"].max()), 5) metadata["min_latitude"] = round(float(em_data["lat"].min()), 5) history = metadata.get("history") if history is None: history = "" metadata["history"] = history + f" {str(timestamp_now())} Processed onto OpenGHG cloud" key = "_".join((model, species, date)) model_data: DefaultDict[str, Dict[str, Union[Dict, Dataset]]] = defaultdict(dict) model_data[key]["data"] = em_data model_data[key]["metadata"] = metadata required = ("model", "species", "date") lookup_results = datasource_lookup(metastore=metastore, data=model_data, required_keys=required) data_type = "eulerian_model" datasource_uuids = assign_data( data_dict=model_data, lookup_results=lookup_results, overwrite=overwrite, data_type=data_type, ) em_store.add_datasources(uuids=datasource_uuids, data=model_data, metastore=metastore) # Record the file hash in case we see this file again em_store._file_hashes[file_hash] = metastore.close() return datasource_uuids