pycontrails.datalib.ecmwf.IFS¶

class pycontrails.datalib.ecmwf.IFS(time, variables, pressure_levels=-1, paths=None, grid=None, forecast_path=None, forecast_date=None)¶

Bases: MetDataSource

ECMWF Integrated Forecasting System (IFS) data source.

Warning

This data source is not fully implemented.

Parameters:

time (datalib.TimeInput | None) – The time range for data retrieval, either a single datetime or (start, end) datetime range. Input must be a single datetime-like or tuple of datetime-like (datetime, pandas.Timestamp, numpy.datetime64) specifying the (start, end) of the date range, inclusive. If None, all time coordinates will be loaded.
variables (datalib.VariableInput) – Variable name (i.e. “air_temperature”, [“air_temperature, relative_humidity”]) See pressure_level_variables for the list of available variables.
pressure_levels (datalib.PressureLevelInput, optional) – Pressure level bounds for data (min, max), in hPa (mbar) Set to -1 for to download surface level parameters. Defaults to -1.
paths (str | list[str] | pathlib.Path | list[pathlib.Path] | None, optional) – UNSUPPORTED FOR IFS
forecast_path (str | pathlib.Path | None, optional) – Path to local forecast files. Defaults to None
forecast_date (DatetimeLike, optional) – Forecast date to load specific netcdf files. Defaults to None

Notes

This takes an average pressure of the model level to create pressure level dimensions.

__init__(time, variables, pressure_levels=-1, paths=None, grid=None, forecast_path=None, forecast_date=None)¶

Methods

`__init__`(time, variables[, pressure_levels, ...])
`cache_dataset`(dataset)	Cache data from data source.
`create_cachepath`(t)	Return cachepath to local data file based on datetime.
`download`(**xr_kwargs)	Confirm all data files are downloaded and available locally in the `cachestore`.
`download_dataset`(times)	Download data from data source for input times.
`is_datafile_cached`(t, **xr_kwargs)	Check datafile defined by datetime for variables and pressure levels in class.
`list_timesteps_cached`(**xr_kwargs)	Get a list of data files available locally in the `cachestore`.
`list_timesteps_not_cached`(**xr_kwargs)	Get a list of data files not available locally in the `cachestore`.
`open_dataset`(disk_paths, **xr_kwargs)	Open multi-file dataset in xarray.
`open_metdataset`([dataset, xr_kwargs])	Open MetDataset from data source.
`set_metadata`(ds)	Set met source metadata on `ds.attrs`.

Attributes

`forecast_date`	Forecast datetime of IFS forecast
`forecast_path`	Root path of IFS data
`grid`	Lat / Lon grid spacing
`hash`	Generate a unique hash for this datasource.
`is_single_level`	Return True if the datasource is single level data.
`paths`	Path to local source files to load.
`pressure_level_variables`	Parameters available from data source.
`pressure_levels`	List of pressure levels.
`single_level_variables`	Parameters available from data source.
`supported_pressure_levels`	IFS does not provide constant pressure levels and instead uses model levels.
`supported_variables`	IFS parameters available.
`timesteps`	List of individual timesteps from data source derived from `time` Use `parse_time()` to handle `TimeInput`.
`variable_shortnames`	Return a list of variable short names.
`variable_standardnames`	Return a list of variable standard names.
`variables`	Variables requested from data source Use `parse_variables()` to handle `VariableInput`.
`cachestore`	Cache store for intermediates while processing data source If None, cache is turned off.

cache_dataset(dataset)¶

Cache data from data source.

Parameters:: dataset (xarray.Dataset) – Dataset loaded from remote API or local files. The dataset must have the same format as the original data source API or files.

create_cachepath(t)¶

Return cachepath to local data file based on datetime.

Parameters:: t (datetime) – Datetime of datafile
Returns:: str – Path to cached data file

download_dataset(times)¶

Download data from data source for input times.

Parameters:: times (list[datetime]) – List of datetimes to download a store in cache

forecast_date¶: Forecast datetime of IFS forecast

forecast_path¶: Root path of IFS data

open_metdataset(dataset=None, xr_kwargs=None, **kwargs)¶

Open MetDataset from data source.

This method should download / load any required datafiles and returns a MetDataset of the multi-file dataset opened by xarray.

Parameters:

dataset (xr.Dataset | None, optional) – Input xr.Dataset loaded manually. The dataset must have the same format as the original data source API or files.
xr_kwargs (dict[str, Any] | None, optional) – Dictionary of keyword arguments passed into xarray.open_mfdataset() when opening files. Examples include “chunks”, “engine”, “parallel”, etc. Ignored if dataset is input.
**kwargs (Any) – Keyword arguments passed through directly into MetDataset constructor.

Returns:

MetDataset – Meteorology dataset