Source code for pycif.plugins.datastreams.backgrounds.tm5_background.read

import xarray as xr
import numpy as np
from netCDF4 import Dataset
import datetime
import pandas as pd
from .....utils.datastores.empty import init_empty




def read(
    self,
    name,
    varnames,
    dates,
    files,
    interpol_flx=False,
    tracer=None,
    model=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

    """
    
    trcr_bc = []
    out_dates = []
    ref_file = ""
    
    for dd, ff in zip(dates, files):
        if ff != ref_file:
            ref_file = ff
            with Dataset(ff) as bkg:
                # Station ids
                ids = [''.join([c.decode().lower() for c in name])
                       for name in bkg[tracer.id_varname][:]]
                ids = pd.Series(ids).str.split("_", expand=True)
                stations = ids[0].values
                network = ids[1].values
                agl = ids[2].values
                # Time steps
                ts = np.array([
                    datetime.datetime(*t) for t in bkg[tracer.time_varname][:]
                ])
                # Simulations from TM5
                data = bkg.variables[self.varname][:]
                mesh_stat, mesh_ts = np.meshgrid(stations, ts)
                mesh_network, mesh_ts = np.meshgrid(network, ts)
                mesh_agl, mesh_ts = np.meshgrid(agl, ts)
                ds = init_empty()
                ds[("metadata", "date")] = mesh_ts.flatten()
                ds[("metadata", "station")] = mesh_stat.flatten()
                ds[("metadata", "network")] = mesh_network.flatten()
                ds[("metadata", "parameter")] = name
                ds[("metadata", "duration")] = 1
                ds[("maindata", "obserror")] = 0
                ds[("maindata", "spec")] = \
                    data.flatten() * getattr(tracer, "numscale", 1)
    
    return ds