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

from logging import warning
import xarray as xr

from ....domains.gridded_NetCDF.utils import find_coord
from .....utils.hdf5 import _hdf5_lock




def read(self, name, varnames, dates, files, interpol_flx=False, comp_type=None, **kwargs):
    """Read a gridded NetCDF initial-condition field into a pyCIF DataArray.

    Opens the inicond NetCDF file, renames its latitude/longitude/level
    coordinates to ``lat``/``lon``/``lev`` (using
    ``self.vertical_dim_name`` for the vertical coordinate and
    :func:`~pycif.plugins.domains.gridded_NetCDF.utils.find_coord` for the
    horizontal ones), optionally sorts latitude/longitude in ascending
    order, and adds a singleton ``time`` dimension set to the simulation
    start date.

    Args:
        self: The field/tracer Plugin (``vertical_dim_name``, ``sort_lat``,
            ``sort_lon`` attributes are used).
        name: Name of the component; used as the variable name if
            ``varnames`` is not given.
        varnames: Name of the variable to read in the NetCDF file.
        dates: List of date entries matching ``files``; only the first
            date is used as the initial date.
        files: List of files matching ``dates``; only the first file is
            read (a warning is issued if more than one is given).
        interpol_flx: Unused.
        comp_type: Unused.
        **kwargs: Unused.

    Returns:
        xarray.DataArray: A 4-dimensional ``(time, lev, lat, lon)`` array.
    """

    if len(files) > 1:
        warning("multiple inicond files to read, "
                "reading the first one and ignoring all others")

    inicond_file = files[0]
    initial_date = dates[0][0]

    # Getting inicond dataarray
    varnames = varnames if varnames else name
    with _hdf5_lock:
        xmod = xr.open_dataset(inicond_file)[varnames]

        # Getting coordinates names
        lev_coord_name = self.vertical_dim_name
        lat_coord_name = find_coord(xmod, 'latitude', 'lat')
        lon_coord_name = find_coord(xmod, 'longitude', 'lon')

        # Renaming spatial coordinates to 'lev', 'lat' and 'lon'
        xmod = xmod.rename({lat_coord_name: 'lat',
                            lon_coord_name: 'lon',
                            lev_coord_name: 'lev'})

        # TODO: need to also rename the dimensions associated with lat, lon and time
        # if they have a different name than the coordinates.

        # Sorting latitudes and longitudes in ascending order
        dims_to_sort = []
        if self.sort_lat:
            dims_to_sort.append('lat')
        if self.sort_lon:
            dims_to_sort.append('lon')
        if dims_to_sort:
            xmod = xmod.sortby(dims_to_sort)

        # Adding 'time' dimension and coordinate
        if 'time' in xmod.dims:
            xmod = xmod.isel(time=0)

        xmod = xmod.expand_dims(['time'])
        xmod['time'] = (['time'], [initial_date])

        # Reordering dimensions
        xmod = xmod.transpose('time', 'lev', 'lat', 'lon')

    return xmod