Source code for pycif.plugins.datastreams.fluxes.becker_ocean.read

import numpy as np
import xarray as xr
from logging import debug
import warnings
import xarray as xr
from xarray import SerializationWarning




def read(
        self,
        name,
        varnames,
        dates,
        files,
        interpol_flx=False,
        tracer=None,
        model=None,
        ddi=None,
        **kwargs
):
    """Get fluxes from raw files and load them into a pyCIF
    variables.


    Args:
        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

    Return:
        xr.DataArray: the actual data with dimension:
            time, levels, latitudes, longitudes

    """

    var2extract = varnames if varnames != "" else name

    # Loop over dates/files and import data
    data = []
    out_dates = []
    for dd, ff in zip(dates, files):
        debug(
            "Reading the file {} for the date interval {}".format(
                ff, dd
            )
        )

        # Read and ignore warnings
        with warnings.catch_warnings():
            warnings.simplefilter('ignore', category=SerializationWarning)
            times = xr.open_dataset(ff)["time"].values

            ind_time = np.where(times == np.datetime64(dd[0]))[0][0]

            data.append(xr.open_dataset(ff)[var2extract][ind_time].values)
            out_dates.append(dd[0])

    # if only one level for emissions, create the axis
    if data != []:
        data = np.array(data)[:, np.newaxis]
        data[np.isnan(data)] = 0
    xmod = xr.DataArray(
        data,
        coords={"time": out_dates},
        dims=("time", "lev", "lat", "lon"),
    )

    return xmod