Source code for pycif.plugins.datastreams.fluxes.edgar_v5.read

import datetime
import glob
import os
from netCDF4 import Dataset, num2date

import numpy as np
import xarray as xr

from logging import info




def read(
    self,
    name,
    varnames,
    dates,
    files,
    interpol_flx=False,
    tracer=None,
    model=None,
    **kwargs
):

    # Reading fluxes for periods within the simulation window
    trcr_flx = []
    trcr_dates = []
    for dd, file_flx in zip(dates, files):
        
        # Check if "time" is in variables
        # Do not do it with open_dataset which is slow with big files...
        with Dataset(file_flx, "r") as f:
            available_time = "time" in f.variables

        if available_time:
            with Dataset(file_flx, "r") as f:
                times = f.variables["time"]
                times = num2date(times[:], times.units,
                                 only_use_python_datetimes=True,
                                 only_use_cftime_datetimes=False)
            
            ind_data = np.where(times == dd[1])[0][0]
            
            # Now read the data at the correct index
            with Dataset(file_flx, "r") as f:
                data = f.variables[varnames][ind_data].data

        else:
            nc = xr.open_dataset(file_flx)
            data = nc[varnames].values

        trcr_flx.append(
            np.concatenate([data[:, :1800], data[:, 1800:]], axis=1))

        trcr_dates.append(dd[0])
    
    return xr.DataArray(
        np.array(trcr_flx)[:, np.newaxis, ...],
        coords={"time": trcr_dates},
        dims=("time", "lev", "lat", "lon"),
    )