Risk Trajectory Split 3 : Impact Computation Strategies

climada/trajectories/__init__.py

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+"""
+This file is part of CLIMADA.
+
+Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.
+
+CLIMADA is free software: you can redistribute it and/or modify it under the
+terms of the GNU General Public License as published by the Free
+Software Foundation, version 3.
+
+CLIMADA is distributed in the hope that it will be useful, but WITHOUT ANY
+WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with CLIMADA. If not, see <https://www.gnu.org/licenses/>.
+
+---
+
+This module implements risk trajectory objects which enable computation and
+possibly interpolation of risk metric over multiple dates.
+
+"""
+
+from .snapshot import Snapshot
+
+__all__ = [
+    "Snapshot",
+]

climada/trajectories/impact_calc_strat.py

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+"""
+This file is part of CLIMADA.
+
+Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.
+
+CLIMADA is free software: you can redistribute it and/or modify it under the
+terms of the GNU General Public License as published by the Free
+Software Foundation, version 3.
+
+CLIMADA is distributed in the hope that it will be useful, but WITHOUT ANY
+WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with CLIMADA. If not, see <https://www.gnu.org/licenses/>.
+
+---
+
+This modules implements the impact computation strategy objects for risk
+trajectories.
+
+"""
+
+from abc import ABC, abstractmethod
+
+from climada.engine.impact import Impact
+from climada.engine.impact_calc import ImpactCalc
+from climada.entity.exposures.base import Exposures
+from climada.entity.impact_funcs.impact_func_set import ImpactFuncSet
+from climada.hazard.base import Hazard
+
+__all__ = ["ImpactCalcComputation"]
+
+
+# The following is acceptable.
+# We design a pattern, and currently it requires only to
+# define the compute_impacts method.
+# pylint: disable=too-few-public-methods
+class ImpactComputationStrategy(ABC):
+    """
+    Interface for impact computation strategies.
+
+    This abstract class defines the contract for all concrete strategies
+    responsible for calculating and optionally modifying with a risk transfer,
+    the impact computation, based on a set of inputs (exposure, hazard, vulnerability).
+
+    It revolves around a `compute_impacts()` method that takes as arguments
+    the three dimensions of risk (exposure, hazard, vulnerability) and return an
+    Impact object.
+    """
+
+    @abstractmethod
+    def compute_impacts(
+        self,
+        exp: Exposures,
+        haz: Hazard,
+        vul: ImpactFuncSet,
+    ) -> Impact:
+        """
+        Calculates the total impact, including optional risk transfer application.
+
+        Parameters
+        ----------
+        exp : Exposures
+            The exposure data.
+        haz : Hazard
+            The hazard data (e.g., event intensity).
+        vul : ImpactFuncSet
+            The set of vulnerability functions.
+
+        Returns
+        -------
+        Impact
+            An object containing the computed total impact matrix and metrics.
+
+        See Also
+        --------
+        ImpactCalcComputation : The default implementation of this interface.
+        """
+
+
+class ImpactCalcComputation(ImpactComputationStrategy):
+    r"""
+    Default impact computation strategy using the core engine of climada.
+
+    This strategy first calculates the raw impact using the standard
+    :class:`ImpactCalc` logic.
+
+    """
+
+    def compute_impacts(
+        self,
+        exp: Exposures,
+        haz: Hazard,
+        vul: ImpactFuncSet,
+    ) -> Impact:
+        """
+        Calculates the impact.
+
+        Parameters
+        ----------
+        exp : Exposures
+            The exposure data.
+        haz : Hazard
+            The hazard data.
+        vul : ImpactFuncSet
+            The set of vulnerability functions.
+
+        Returns
+        -------
+        Impact
+            The final impact object.
+        """
+        return ImpactCalc(exposures=exp, impfset=vul, hazard=haz).impact()

climada/trajectories/snapshot.py

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+"""
+This file is part of CLIMADA.
+
+Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.
+
+CLIMADA is free software: you can redistribute it and/or modify it under the
+terms of the GNU General Public License as published by the Free
+Software Foundation, version 3.
+
+CLIMADA is distributed in the hope that it will be useful, but WITHOUT ANY
+WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License along
+with CLIMADA. If not, see <https://www.gnu.org/licenses/>.
+
+---
+
+This modules implements the Snapshot class.
+
+Snapshot are used to store a snapshot of Exposure, Hazard and Vulnerability
+at a specific date.
+
+"""
+
+import copy
+import datetime
+import logging
+
+from climada.entity.exposures import Exposures
+from climada.entity.impact_funcs import ImpactFuncSet
+from climada.entity.measures.base import Measure
+from climada.hazard import Hazard
+
+LOGGER = logging.getLogger(__name__)
+
+__all__ = ["Snapshot"]
+
+
+class Snapshot:
+    """
+    A snapshot of exposure, hazard, and impact function at a specific date.
+
+    Parameters
+    ----------
+    exposure : Exposures
+    hazard : Hazard
+    impfset : ImpactFuncSet
+    date : int | datetime.date | str
+        The date of the Snapshot, it can be an integer representing a year,
+        a datetime object or a string representation of a datetime object
+        with format "YYYY-MM-DD".
+    ref_only : bool, default False
+        Should the `Snapshot` contain deep copies of the Exposures, Hazard and Impfset (False)
+        or references only (True).
+
+    Attributes
+    ----------
+    date : datetime
+        Date of the snapshot.
+    measure: Measure | None
+        The possible measure applied to the snapshot.
+
+    Notes
+    -----
+
+    The object creates deep copies of the exposure hazard and impact function set.
+
+    Also note that exposure, hazard and impfset are read-only properties.
+    Consider snapshot as immutable objects.
+
+    To create a snapshot with a measure, create a snapshot `snap` without
+    the measure and call `snap.apply_measure(measure)`, which returns a new Snapshot object
+    with the measure applied to its risk dimensions.
+    """
+
+    def __init__(
+        self,
+        *,
+        exposure: Exposures,
+        hazard: Hazard,
+        impfset: ImpactFuncSet,
+        measure: Measure | None,
+        date: int | datetime.date | str,
+        ref_only: bool = False,
+    ) -> None:
+        self._exposure = exposure if ref_only else copy.deepcopy(exposure)
+        self._hazard = hazard if ref_only else copy.deepcopy(hazard)
+        self._impfset = impfset if ref_only else copy.deepcopy(impfset)
+        self._measure = measure if ref_only else copy.deepcopy(impfset)
+        self._date = self._convert_to_date(date)
+
+    @classmethod
+    def from_triplet(
+        cls,
+        *,
+        exposure: Exposures,
+        hazard: Hazard,
+        impfset: ImpactFuncSet,
+        date: int | datetime.date | str,
+        ref_only: bool = False,
+    ) -> "Snapshot":
+        """Create a Snapshot from exposure, hazard and impact functions set
+
+        This method is the main point of entry for the creation of Snapshot. It
+        creates a new Snapshot object for the given date with copies of the
+        hazard, exposure and impact function set given in argument (or
+        references if ref_only is True)
+
+        Parameters
+        ----------
+        exposure : Exposures
+        hazard : Hazard
+        impfset : ImpactFuncSet
+        date : int | datetime.date | str
+        ref_only : bool
+            If true, uses references to the exposure, hazard and impact
+            function objects. Note that modifying the original objects after
+            computations using the Snapshot might lead to inconsistencies in
+            results.
+
+        Returns
+        -------
+        Snapshot
+
+        Notes
+        -----
+
+        To create a Snapshot with a measure, first create the Snapshot without
+        the measure using this method, and use `apply_measure(measure)` afterward.
+
+        """
+        return cls(
+            exposure=exposure,
+            hazard=hazard,
+            impfset=impfset,
+            measure=None,
+            date=date,
+            ref_only=ref_only,
+        )
+
+    @property
+    def exposure(self) -> Exposures:
+        """Exposure data for the snapshot."""
+        return self._exposure
+
+    @property
+    def hazard(self) -> Hazard:
+        """Hazard data for the snapshot."""
+        return self._hazard
+
+    @property
+    def impfset(self) -> ImpactFuncSet:
+        """Impact function set data for the snapshot."""
+        return self._impfset
+
+    @property
+    def measure(self) -> Measure | None:
+        """(Adaptation) Measure data for the snapshot."""
+        return self._measure
+
+    @property
+    def date(self) -> datetime.date:
+        """Date of the snapshot."""
+        return self._date
+
+    @property
+    def impact_calc_data(self) -> dict:
+        """Convenience function for ImpactCalc class."""
+        return {
+            "exposures": self.exposure,
+            "hazard": self.hazard,
+            "impfset": self.impfset,
+        }
+
+    @staticmethod
+    def _convert_to_date(date_arg) -> datetime.date:
+        """Convert date argument of type int or str to a datetime.date object."""
+        if isinstance(date_arg, int):
+            # Assume the integer represents a year
+            return datetime.date(date_arg, 1, 1)
+        if isinstance(date_arg, str):
+            # Try to parse the string as a date
+            try:
+                return datetime.datetime.strptime(date_arg, "%Y-%m-%d").date()
+            except ValueError as exc:
+                raise ValueError("String must be in the format 'YYYY-MM-DD'") from exc
+        if isinstance(date_arg, datetime.date):
+            # Already a date object
+            return date_arg
+
+        raise TypeError("date_arg must be an int, str, or datetime.date")
+
+    def apply_measure(self, measure: Measure, ref_only: bool = False) -> "Snapshot":
+        """Create a new snapshot by applying a Measure object.
+
+        This method creates a new `Snapshot` object by applying a measure on
+        the current one.
+
+        Parameters
+        ----------
+        measure : Measure
+            The measure to be applied to the snapshot.
+
+        Returns
+        -------
+            The Snapshot with the measure applied.
+
+        """
+
+        LOGGER.debug("Applying measure %s on snapshot %s", measure.name, id(self))
+        exp, impfset, haz = measure.apply(self.exposure, self.impfset, self.hazard)
+        snap = Snapshot(
+            exposure=exp,
+            hazard=haz,
+            impfset=impfset,
+            date=self.date,
+            measure=measure,
+            ref_only=ref_only,
+        )
+        return snap