Source code for pycif.plugins.models.satwetch4.ini_periods

import datetime

import numpy as np
import pandas as pd
import xarray as xr
from netCDF4 import Dataset

from logging import info, debug

from ....utils.dates import date_range
from ....utils.netcdf import readnc




def ini_periods(self, **kwargs):
    """
    The function :bash:`ini_periods` is optional but very recommended.
    It is used to define the temporal variables ``subsimu_dates``, ``input_dates``,
    ``tstep_dates`` and ``tstep_all``.
    The function is automatically called at the initialization
    of the :bash:`model` class if available.
    If not available, the temporal variables should be defined manually
    in the :bash:`ini_data` function (not recommended).

    :bash:`ini_periods` is a class method that applies to the :bash:`model` plugin itself.
    Therefore, the only expected argument is :bash:`self`.

    .. code-block:: python

        def ini_periods(self, **kwargs):

            self.subsimu_dates = XXXX
            self.tstep_dates = XXXXX
            self.input_dates = XXXXX
            self.tstep_all = XXXXX

    """

    datei = self.datei
    datef = self.datef

    # List of sub-simulation windows
    #self.subsimu_dates = [datei, datef]
    self.subsimu_dates = date_range(datei, datef, period=self.periods)

    # Fixed time step (in hours): list of time steps for each sub-simulation
    self.tstep_dates = {
        ddi: date_range(ddi, ddf, period=self.timestep)
        for ddi, ddf in zip(self.subsimu_dates[:-1], self.subsimu_dates[1:])
    }

    # Fixed time step (in hours): list of required input time steps
    self.input_dates = {
        ddi: date_range(ddi, ddf, period=self.timestep)
        for ddi, ddf in zip(self.subsimu_dates[:-1], self.subsimu_dates[1:])
    }

    # # Merged list of time steps
    # self.tstep_all = date_range(
    #     datei, datef, period=self.timestep)


    # # # Merged list of time steps
    if self.timestep == '1MS':  
        self.tstep_all = date_range(
        datei, datef, period=self.timestep
        )