Source code for pycif.plugins.datastreams.fluxes.dummy_txt.fetch

import os
import pandas as pd
from .....utils import path
from .make import make




def fetch(ref_dir, ref_file, input_interval, target_dir, tracer=None, **kwargs):
    """Fetch (or synthesize) dummy_txt flux files covering the interval.

    Extends the requested interval to full ``tracer.period`` blocks. For
    each period, links the existing file into ``target_dir`` if present;
    otherwise generates the flux field on the fly via ``tracer.make(tracer)``
    and writes it with ``tracer.write(...)`` so a file is always available.
    Each period is then subdivided into ``tracer.freq`` sub-intervals for the
    returned dates/files.

    Args:
        ref_dir (str): directory where the original files are found.
        ref_file (str): (template) name of the original files.
        input_interval (list): simulation interval, as a list of the two
            bounding dates.
        target_dir (str): directory where links to the original (or
            generated) files are created.
        tracer: the tracer Plugin, giving access to ``period`` and ``freq``.
        **kwargs: unused, kept for interface compatibility.

    Returns:
        (dict, dict): ``list_files`` and ``list_dates``.

        list_files: for each date that begins a period, a list containing
            the name of the file used for the dates within this period.
        list_dates: for each date that begins a period, a list containing
            the date intervals matching the files listed in ``list_files``.
    """

    # Extend simulation interval if end date does not include a full period
    # of fluxes
    datei = input_interval[0]
    datef = input_interval[1]
    tmp_dates = pd.date_range(datei, datef, freq=tracer.period)

    # Fetching or creating if necessary
    list_files = {}
    list_dates = {}
    for di in tmp_dates:
        f = datei.strftime(f"{ref_dir}/{ref_file}")
        target_file = f"{target_dir}/{os.path.basename(f)}"
        if os.path.isfile(f):
            path.link(f, target_file)

        else:
            flx = tracer.make(tracer)
            tracer.write("", target_file, flx[0, 0])

        df = di + pd.to_timedelta(tracer.period)
        drange = pd.date_range(di, df, freq=tracer.freq)

        list_files[di] = (len(drange) - 1) * [target_file]
        list_dates[di] = [[d0, d1] for d0, d1 in zip(drange[:-1], drange[1:])]

    return list_files, list_dates