Source code for pycif.plugins.datastreams.fields.iconart_icbc.read

import pandas as pd
import numpy as np
import xarray as xr



def read(
        self,
        name,
        varnames,
        dates,
        files,
        interpol_flx=False,
        comp_type=None,
        ddi=None,
        **kwargs
):
    """Get fluxes from pre-computed fluxes and load them into a pyCIF
    variables

    Args:
        self: the fluxes Plugin
        name: the name of the component
        tracdir, tracfile: flux directory and file format
        dates: list of dates to extract
        interpol_flx (bool): if True, interpolates fluxes at time t from
        values of surrounding available files

    """

    var2extract = varnames if varnames != "" else name

    # Check the type of limit condition to check
    if comp_type is None:
        raise Exception(
            "Trying to read limit conditions for ICON-ART, "
            "but did not specify the type"
        )

    # Read initial conditions
    if comp_type == "inicond":

        ic_file = files[0]
        ds = xr.open_dataset(ic_file)
        data = ds[var2extract][:]
        
        # -- Add fake lat dimensions at the end
        data = data.values[:, :, np.newaxis, :]
        
        xmod = xr.DataArray(
            data,
            coords={"time": [np.min(dates)]},
            dims=("time", "lev", "lat", "lon"),
        )

    # Read Lateral boundary conditions
    elif comp_type in ["lbc", "background"]:
     
        trcr_lbc = []
        out_dates = []
        for dd, ff in zip(dates, files):

            # Getting the data
            ds = xr.open_dataset(ff)
            da = ds[var2extract]

            if dd[0] in pd.to_datetime(da.time):
                data = da.sel(time=dd[0])
            else:
                raise KeyError("Could not find the correct data in the lbc file")

            # Appending
            trcr_lbc.append(data)
            out_dates.append(dd[0])

        xout = np.array(trcr_lbc)[:, :, np.newaxis, :]

        # Putting the data into an xarray
        xmod = xr.DataArray(
            xout, coords={"time": out_dates}, dims=("time", "lev", "lat", "lon")
        )

            

    else:
        raise Exception(
            "Could not recognize the type of file "
            "to read in ICONART: {}".format(comp_type)
        )
    
    return xmod