# Copyright (c) 2018-2024 by xcube team and contributors
# Permissions are hereby granted under the terms of the MIT License:
# https://opensource.org/licenses/MIT.
from typing import Sequence, Any, Dict, Callable, Optional
import xarray as xr
from .abc import MultiLevelDataset
from .lazy import LazyMultiLevelDataset
[docs]
class CombinedMultiLevelDataset(LazyMultiLevelDataset):
"""A multi-level dataset that is a combination of other
multi-level datasets.
Args:
ml_datasets: The multi-level datasets to be combined. At least
two must be provided.
ds_id: Optional dataset identifier.
combiner_function: An optional function used to combine the
datasets, for example ``xarray.merge``. If given, it
receives a list of datasets (``xarray.Dataset`` instances)
and *combiner_params* as keyword arguments. If not given or
``None`` is passed, a copy of the first dataset is made,
which is then subsequently updated by the remaining datasets
using ``xarray.Dataset.update()``.
combiner_params: Parameters to the *combiner_function* passed as
keyword arguments.
"""
def __init__(
self,
ml_datasets: Sequence[MultiLevelDataset],
ds_id: Optional[str] = None,
combiner_function: Optional[Callable] = None,
combiner_params: Optional[Dict[str, Any]] = None,
):
if not ml_datasets or len(ml_datasets) < 2:
raise ValueError("ml_datasets must have at least two elements")
super().__init__(ds_id=ds_id, parameters=combiner_params)
self._ml_datasets = ml_datasets
self._combiner_function = combiner_function
def _get_num_levels_lazily(self) -> int:
return self._ml_datasets[0].num_levels
def _get_dataset_lazily(
self, index: int, combiner_params: Dict[str, Any]
) -> xr.Dataset:
datasets = [ml_dataset.get_dataset(index) for ml_dataset in self._ml_datasets]
if self._combiner_function is None:
combined_dataset = datasets[0].copy()
for dataset in datasets[1:]:
combined_dataset.update(dataset)
return combined_dataset
else:
return self._combiner_function(datasets, **combiner_params)
[docs]
def close(self):
for ml_dataset in self._ml_datasets:
ml_dataset.close()