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

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

Configuration reference: point_sources plugin

pycif.plugins.datastreams.fluxes.point_sources.fetch.fetch(ref_dir, ref_file, input_interval, target_dir, tracer=None, component=None, **kwargs)[source]#
pycif.plugins.datastreams.fluxes.point_sources.get_domain.get_domain(ref_dir, ref_file, input_interval, target_dir, tracer=None)[source]#
pycif.plugins.datastreams.fluxes.point_sources.read.read(self, name, varnames, dates, files, interpol_flx=False, tracer=None, model=None, ddi=None, **kwargs)[source]#

Get fluxes from raw files and load them into a pyCIF variables.

The list of date intervals and corresponding files is directly provided, coming from what is returned by the fetch function. One should loop on dates and files and extract the corresponding temporal slice of data

Warning

Make sure to optimize the opening of files. There is high chances that the same file has to be open and closed over and over again to loop on the dates. If this is the case, make sure not to close it between each date.

Parameters:

  • name (str) – name of the component

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

  • dates (list) – list of the date intervals to extract

  • files (list) – list of the files matching dates

Returns:

the actual data with dimension:

time, levels, latitudes, longitudes

Return type:

xr.DataArray

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