Source code for pycif.plugins.datastreams.fields.lmdz_chemfield.fetch

import os

import numpy as np
import pandas as pd

from .....utils import path




def fetch(ref_dir, ref_file, input_interval, target_dir, tracer=None, **kwargs):
    """Link monthly LMDz chemical field files and build daily sub-intervals.

    Builds the list of monthly file dates spanning ``input_interval`` at
    ``tracer.file_freq``, links each existing file into ``target_dir``, and
    for each linked file generates one daily ``[start, end]`` sub-interval
    per day of that month.

    Args:
        ref_dir: Directory where the original files are found.
        ref_file: Date-format pattern for the original file names.
        input_interval: List of two dates, the beginning and end of the
            period to fetch.
        target_dir: Directory where links to the original files are
            created.
        tracer: Tracer/component configuration; ``tracer.file_freq`` gives
            the frequency at which files are available.
        **kwargs: Unused.

    Returns:
        A tuple ``(list_files, list_dates)`` of dictionaries keyed by
        monthly file date. ``list_dates`` maps each key to one
        ``[day_start, day_end]`` interval per day of the month; ``list_files``
        maps each key to the (repeated) path of that month's file.
    """

    # Reshape input interval to include full months
    date_i, date_f = input_interval

    # Getting file dates
    file_dates = pd.date_range(
        date_i, date_f, freq=tracer.file_freq, inclusive='left')

    if file_dates.empty:
        file_dates = pd.to_datetime([date_i])

    if file_dates[0] > date_i:
        file_dates = pd.to_datetime([date_i] + file_dates.to_list())

    # Getting files paths
    file_paths = np.array([os.path.join(ref_dir, date.strftime(ref_file))
                           for date in file_dates])

    list_dates = {}
    list_files = {}

    for date, source_path in zip(file_dates, file_paths):
        if not os.path.isfile(source_path):
            continue

        # Fetching
        target_path = os.path.join(target_dir, os.path.basename(source_path))
        path.link(source_path, target_path)

        # Time stamps
        period_start = pd.date_range(
            date, periods=date.days_in_month, freq="1D")
        period_end = period_start + pd.offsets.Hour(24)

        date = date.to_pydatetime()
        period_start = period_start.to_pydatetime()
        period_end = period_end.to_pydatetime()

        list_dates[date] = [[di, df]
                            for di, df in zip(period_start, period_end)]

        list_files[date] = (len(period_start) * [target_path])

    return list_files, list_dates