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

import os
import datetime
import pandas as pd
import numpy as np
from netCDF4 import Dataset
from .....utils import path




def fetch(ref_dir, ref_file, date_interval, target_dir, tracer=None, **kwargs):
    
    # Reshape input interval to include full years
    datei, datef = date_interval
    datei = datetime.datetime(year=datei.year, month=1, day=1)
    datef = datetime.datetime(year=datef.year + 1, month=1, day=1)
    
    list_dates_files = pd.date_range(datei, datef, freq="1YS")
    
    list_dates = {}
    list_files = {}
    for dd in list_dates_files:
        file = dd.strftime("{}/{}".format(ref_dir, ref_file))
        if os.path.isfile(file):
            # Fetching
            target_file = "{}/{}".format(target_dir, os.path.basename(file))
            path.link(file, target_file)

            # Time stamps
            with Dataset(file) as bkg:
                ts = np.array([
                    datetime.datetime(*t) for t in bkg[tracer.time_varname][:]
                ])
                
            list_dates[dd] = [
                [hh0, hh0 + datetime.timedelta(hours=1)]
                for hh0 in ts]

            list_files[dd] = (len(list_dates[dd]) * [target_file])
    
    return list_files, list_dates