Source code for pycif.plugins.datastreams.fields.tm5_ic.read

import xarray as xr
from netCDF4 import Dataset
from .....utils.hdf5 import _hdf5_lock




def read(
    self,
    name,
    tracdir,
    tracfile,
    varnames,
    dates,
    interpol_flx=False,
    comp_type=None,
    model=None,
    tracer=None,
    **kwargs
):
    """Get the TM5 initial condition and load it into a pyCIF variable.

    Reads ``q{restart_id:02d}`` (using ``tracer.restart_id`` if set,
    otherwise the ``restart_id`` of the species in the chemical scheme)
    from the single file matching the earliest requested date.

    Args:
        self: the IC Plugin
        name: the name of the component
        tracdir, tracfile: restart file directory and file format
        varnames: unused, accepted for interface compatibility
        dates: list of dates to extract; only the earliest date is used
        interpol_flx (bool): unused, accepted for interface compatibility
        comp_type: unused, accepted for interface compatibility
        model: the model Plugin, used to resolve the species'
            ``restart_id`` via ``model.chemistry.acspecies`` when
            ``tracer.restart_id`` is not set
        tracer: may carry an explicit ``restart_id``, taking precedence
            over the chemical scheme's

    Returns:
        xarray.DataArray with dims ``(time, lev, lat, lon)``.

    """

    ic_file = min(dates).strftime(f"{tracdir}/{tracfile}")
    with _hdf5_lock:
        with Dataset(ic_file, "r") as f:
            if hasattr(tracer, "restart_id"):
                spec_id = f"q{tracer.restart_id:02d}"
            else:
                spec_id = f"q{getattr(model.chemistry.acspecies, name).restart_id:02d}"

            data = f.variables[spec_id][:]

    xmod = xr.DataArray(
        data, coords={"time": [min(dates)]}, dims=("time", "lev", "lat", "lon")
    )

    return xmod