Source code for foxes.algorithms.downwind.models.set_amb_point_results

import foxes.variables as FV
from foxes.core import PointDataModel



[docs]
class SetAmbPointResults(PointDataModel):
    """
    This model copies point results to ambient results.

    Attributes
    ----------
    pvars: list of str
        The point variables to be treated
    vars: list of str
        The variables to be copied to output

    :group: algorithms.downwind.models

    """


[docs]
    def __init__(self):
        """
        Constructor.
        """
        super().__init__()
        self.pvars = None
        self.vars = None



[docs]
    def initialize(self, algo, verbosity=0, force=False):
        """
        Initializes the model.

        Parameters
        ----------
        algo: foxes.core.Algorithm
            The calculation algorithm
        verbosity: int
            The verbosity level, 0 = silent
        force: bool
            Overwrite existing data

        """
        self.pvars = algo.states.output_point_vars(algo)
        self.vars = [v for v in self.pvars if v in FV.var2amb]
        super().initialize(algo, verbosity, force)



[docs]
    def output_point_vars(self, algo):
        """
        The variables which are being modified by the model.

        Parameters
        ----------
        algo: foxes.core.Algorithm
            The calculation algorithm

        Returns
        -------
        output_vars: list of str
            The output variable names

        """
        return [FV.var2amb[v] for v in self.vars]



[docs]
    def calculate(self, algo, mdata, fdata, pdata):
        """
        The main model calculation.

        This function is executed on a single chunk of data,
        all computations should be based on numpy arrays.

        Parameters
        ----------
        algo: foxes.core.Algorithm
            The calculation algorithm
        mdata: foxes.core.Data
            The model data
        fdata: foxes.core.Data
            The farm data
        pdata: foxes.core.Data
            The point data

        Returns
        -------
        results: dict
            The resulting data, keys: output variable str.
            Values: numpy.ndarray with shape (n_states, n_points)

        """
        for v in self.vars:
            pdata[FV.var2amb[v]] = pdata[v].copy()
        return {v: pdata[v] for v in self.output_point_vars(algo)}