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

from ....utils.dates import date_range




def ini_periods(self, **kwargs):
    """Compute temporal discretisation for the LMDZ-ACC model.

    Splits the full simulation window into sub-simulation periods and builds
    time-step arrays at the resolution dictated by the LMDZ domain's
    dynamical (``dsplit``) and physical (``psplit``) sub-steps and the
    meteorological offset time step (``meteo.offtstep``).

    Sets on *self*:

    * ``subsimu_dates`` — period boundary dates.
    * ``tstep_dates`` — per-period time-step arrays.
    * ``input_dates`` — per-period initial/end-concentration date arrays.
    * ``flx_input_dates`` — per-period flux/meteo input date arrays.
    * ``tstep_all`` — sorted unique merge of all time steps.
    * ``iniobs``, ``reset_obs`` — per-period observation bookkeeping flags.
    * ``chain`` — per-period flag indicating whether the period is chained
      from the previous one.

    Args:
        self: LMDZ-ACC model plugin instance with ``datei``, ``datef``,
            ``periods``, ``domain``, and ``meteo`` set.
        **kwargs: unused.
    """
    datei = self.datei
    datef = self.datef

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

    # Dynamical and physical time step for LMDZ
    dstep = self.domain.dsplit
    pstep = self.domain.psplit

    # Initializes offtstep from meteo
    if not hasattr(self.meteo, "offtstep"):
        self.meteo.read("", "", self.subsimu_dates, self.meteo.dir, "")

    offtstep = self.meteo.offtstep

    # Time steps per day
    freq = f"{offtstep // min([dstep, pstep]):.0f}s"

    # List of time steps
    self.tstep_dates = {
        ddi: date_range(ddi, ddf, period=freq)
        for ddi, ddf in zip(self.subsimu_dates[:-1], self.subsimu_dates[1:])
    }

    # List of input dates
    # TODO: make the date inputs flexible (daily so far)
    self.input_dates = {
        ddi: date_range(ddi, ddf, period="1D")
        for ddi, ddf in zip(self.subsimu_dates[:-1], self.subsimu_dates[1:])
    }
    self.flx_input_dates = {
        ddi: date_range(ddi, ddf, period=self.flx_tresol)
        for ddi, ddf in zip(self.subsimu_dates[:-1], self.subsimu_dates[1:])
    }
    self.meteo_dates = {
        ddi: date_range(ddi, ddf, period="3h")
        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.periods, subperiod=freq)

    # Initializes dictionary to keep in memory whether observations were
    # already dumped for a given period
    self.iniobs = {ddi: False for ddi in self.subsimu_dates}
    self.reset_obs = {ddi: True for ddi in self.subsimu_dates}
    self.nbobs_prior = {ddi: 0 for ddi in self.subsimu_dates}
    self.nbdatatot_prior = {ddi: 0 for ddi in self.subsimu_dates}

    # Run model or approximation with fake_end
    self.runsimu = {ddi: True for ddi in self.subsimu_dates}

    # Keep in memory whether a given period has a successor period
    # The info is used by the adjoint to fetch or not the restart file
    self.chain = {ddi: True for ddi in self.subsimu_dates[:-1]}
    self.chain[self.subsimu_dates[-2]] = False