Source code for pycif.plugins.models.iconart.io.outputs2native

from logging import warning

from .outputs.read_sim import read_sim
from .outputs.endconcs import fetch_end



def outputs2native(
        self, data2dump, input_type, di, df, runsubdir, mode="fwd",
        onlyinit=False, check_transforms=False, **kwargs
):
    """Reads outputs to pyCIF objects.

    Args:
        self: the model itself
        data2dump (dict): a dictionary with output data structure to be filled
            with correct data for every component/tracer
        input_type (str): the type of model outputs to be processed;
            this information is redundant with the components of
            the data2dump dictionary
        di (datetime.datetime): starting date of the present sub-simulation
        df (datetime.datetime): ending date of the present sub-simulation
        runsubdir (str): path to the present sub-simulation work directory
        mode (str): running mode; one of "fwd", "tl" and "adj"
        onlyinit (bool): if ``True``,  means that the function is called during
            the initialization process of the observation vector
        do_simu (bool): if ``False``, means that the observation vector
            is retrieving information from a previous existing run;
            in that case, it may not be necessary to dump files

    Return:
        dict: a dictionary with structure the components/tracers to be extracted

    Note:

        The input data ``data2dump`` has a dictionary structure with two levels:
        component/tracer and date.
        This reads as:

        .. code-block:: python

            data2dump = {
                (comp1, tracer1): {
                    dd0: pd.DataFrame
                    dd1: pd.DataFrame
                    [...]
                }
            }

        In the output, the date level should be removed and only the outputs
        corresponding to the present simulation (``di``) should be included

    """

    ddi = min(di, df)
    ddf = max(di, df)
    
    # If no data to extract, pass
    if data2dump == {}:
        return data2dump
    
    # If the model is not run, pass
    if self.dont_run:
        warning(f"Skipping iconart.outputs2native because self.dont_run = {self.dont_run}")
        return {}
    
    # Read simulations if input_type is in outcomp
    outcomp = ["concs", "pressure", "dpressure", "airm", "hlay"]
    if input_type in outcomp and not onlyinit:
        return read_sim(self, data2dump, runsubdir, mode, ddi, ddf)
    
    # Fetch end concentrations if input_type is "endconcs"
    elif input_type == "endconcs":
        return fetch_end(self, data2dump, runsubdir, mode, ddi, ddf)
    
    else:
        return data2dump