pycif.plugins.datastreams.fluxes.iconart — API reference

pycif.plugins.datastreams.fluxes.iconart — API reference#

Configuration reference: iconart plugin

pycif.plugins.datastreams.fluxes.iconart.fetch.fetch(ref_dir, ref_file, input_interval, target_dir, tracer=None, **kwargs)[source]#

Fetch ICON-ART flux files and build the hourly date intervals they cover.

Splits the simulation interval into sub-periods using tracer.model.periods (default '10D'), links the file matching the start of each sub-period (if it exists) into target_dir, and expands each sub-period into hourly [start, end] intervals at tracer.model.input_resolution.

Parameters:

  • ref_dir (str) – Directory containing the reference input files.

  • ref_file (str) – Filename pattern of the input files (a strftime format string).

  • input_interval (list[datetime.datetime]) – [date_i, date_f] simulation interval to cover.

  • target_dir (str) – Directory where the resolved files are linked.

  • tracer – The flux tracer plugin, providing access to model (for periods and input_resolution).

Returns:

(list_files, list_dates), each keyed by the start date of a sub-period, mapping to the list of file paths and the list of hourly [start, end] date-interval pairs within that sub-period.

Return type:

tuple[dict, dict]

pycif.plugins.datastreams.fluxes.iconart.read.read(self, name, varnames, dates, files, interpol_flx=False, tracer=None, model=None, ddi=None, **kwargs)[source]#

Get ICON-ART fluxes and load them into a pyCIF variable, applying temporal scaling if configured.

Opens the base emission field from the first file only. Then, depending on which tfactors_* input arguments are set on self:

  • if tfactors_hoy_file is set, computes an hour-of-year scaling factor per country and per requested date;

  • else if tfactors_hod_file, tfactors_dow_file and tfactors_moy_file are all set, computes the combined month-of-year x day-of-week x hour-of-day scaling factor per country and per requested date;

  • otherwise, reads all requested hourly time steps directly from the base field with no scaling.

When scaling is applied, per-country factors are broadcast to grid cells via the file’s country_ids mask (or directly, if the number of countries already matches the number of cells).

Parameters:

  • self – the fluxes Plugin, providing the tfactors_*/ vfactors_* input arguments.

  • name – the name of the component

  • varnames (list[str]) – original names of variables to read; use name if varnames is empty

  • dates – list of [start, end] date intervals to extract; only the start of each interval is used.

  • files – list of files matching dates; only the first file is actually opened.

  • interpol_flx (bool) – Unused, kept for interface consistency with other flux plugins.

  • tracer – Unused directly, kept for interface consistency.

  • model – Unused directly, kept for interface consistency.

  • ddi – Unused directly, kept for interface consistency.

Returns:

the flux data with dimensions

(time, lev, lat, lon).

Return type:

xr.DataArray

Raises:

CifKeyError – If no temporal-scaling arguments are set and either the base field has no time dimension, or some requested hours are missing from it.

pycif.plugins.datastreams.fluxes.iconart.write.write(self, name, flx_file, flx, mode='a', **kwargs)[source]#

No-op stub; writing ICON-ART fluxes is not implemented.

Parameters:

  • self (Fluxes) – the Fluxes plugin

  • name (str) – name of the flux variable

  • flx_file (str) – the file where fluxes would be written

  • flx (xarray.DataArray) – fluxes data that would be written

  • mode (str) – ‘w’ to overwrite, ‘a’ to append