Impact calc return impact forecast #1179

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Merged

peanutfun merged 24 commits into forecast-class from impactCalc_return_impactForecast

Dec 9, 2025

+279 −18

climada/engine/impact_calc.py

-Original file line number
+Diff line change
@@ Expand Up / @@ -29,6 +29,8 @@ @@
     from climada import CONFIG
     from climada.engine.impact import Impact
+    from climada.engine.impact_forecast import ImpactForecast
+    from climada.hazard.forecast import HazardForecast
     LOGGER = logging.getLogger(__name__)
@@ Expand Down Expand Up / @@ -217,7 +219,7 @@ def _return_impact(self, imp_mat_gen, save_mat): @@
             Returns
             -------
-            Impact
+            Impact or ImpactForecast
                 Impact Object initialize from the impact matrix
             See Also
@@ Expand All / @@ -230,12 +232,31 @@ def _return_impact(self, imp_mat_gen, save_mat): @@
                 at_event, eai_exp, aai_agg = self.risk_metrics(
                     imp_mat, self.hazard.frequency
                 )
+                if isinstance(self.hazard, HazardForecast):
+                    eai_exp = np.full_like(eai_exp, np.nan, dtype=eai_exp.dtype)
+                    aai_agg = np.full_like(aai_agg, np.nan, dtype=aai_agg.dtype)
+                    LOGGER.warning(
+                        "eai_exp and aai_agg are undefined with forecasts. "
+                        "Setting them to NaN arrays."
+                    )
             else:
+                if isinstance(self.hazard, HazardForecast):
+                    raise ValueError(
+                        "Saving impact matrix is required when using HazardForecast."
+                        "Please set save_mat=True."
+                    )
                 imp_mat = None
                 at_event, eai_exp, aai_agg = self.stitch_risk_metrics(imp_mat_gen)
-            return Impact.from_eih(
+            impact = Impact.from_eih(
                 self.exposures, self.hazard, at_event, eai_exp, aai_agg, imp_mat
             )
+            if isinstance(self.hazard, HazardForecast):
+                return ImpactForecast.from_impact(
+                    impact, self.hazard.lead_time, self.hazard.member
+                )
+            return impact
         def _return_empty(self, save_mat):
             """
@@ Expand All / @@ -248,21 +269,37 @@ def _return_empty(self, save_mat): @@
             Returns
             -------
-            Impact
+            Impact or ImpactForecast
                 Empty impact object with correct array sizes.
             """
             at_event = np.zeros(self.n_events)
-            eai_exp = np.zeros(self.n_exp_pnt)
-            aai_agg = 0.0
+            if isinstance(self.hazard, HazardForecast):
+                eai_exp = np.full(self.n_exp_pnt, np.nan)
+                aai_agg = np.nan
+            else:
+                eai_exp = np.zeros(self.n_exp_pnt)
+                aai_agg = 0.0
             if save_mat:
                 imp_mat = sparse.csr_matrix(
                     (self.n_events, self.n_exp_pnt), dtype=np.float64
                 )
             else:
+                if isinstance(self.hazard, HazardForecast):
+                    raise ValueError(
+                        "Saving impact matrix is required when using HazardForecast. "
+                        "Please set save_mat=True."
+                    )
                 imp_mat = None
-            return Impact.from_eih(
+            impact = Impact.from_eih(
                 self.exposures, self.hazard, at_event, eai_exp, aai_agg, imp_mat
             )
+            if isinstance(self.hazard, HazardForecast):
+                return ImpactForecast.from_impact(
+                    impact, self.hazard.lead_time, self.hazard.member
+                )
+            return impact
         def minimal_exp_gdf(
             self, impf_col, assign_centroids, ignore_cover, ignore_deductible
@@ Expand Down @@

climada/engine/impact_forecast.py

-Original file line number
+Diff line change
@@ Expand Up / @@ -90,6 +90,88 @@ def from_impact( @@
                     haz_type=impact.haz_type,
                 )
+        @property
+        def at_event(self):
+            """Get the total impact for each member/lead_time combination."""
+            LOGGER.warning(
+                "at_event gives the total impact for one specific combination of member and "
+                "lead_time."
+            )
+            return self._at_event
+        @at_event.setter
+        def at_event(self, value):
+            """Set the total impact for each member/lead_time combination."""
+            self._at_event = value
+        def local_exceedance_impact(
+            self,
+            return_periods=(25, 50, 100, 250),
+            method="interpolate",
+            min_impact=0,
+            log_frequency=True,
+            log_impact=True,
+            bin_decimals=None,
+        ):
+            """Compution of local exceedance impact for given return periods is not
+            implemented for ImpactForecast.
+            See Also
+            --------
+            See :py:meth:`~climada.engine.impact.Impact.local_exceedance_impact`
+            Raises
+            ------
+            NotImplementedError
+            """
+            LOGGER.error("local_exceedance_impact is not defined for ImpactForecast")
+            raise NotImplementedError(
+                "local_exceedance_impact is not defined for ImpactForecast"
+            )
+        def local_return_period(
+            self,
+            threshold_impact=(1000.0, 10000.0),
+            method="interpolate",
+            min_impact=0,
+            log_frequency=True,
+            log_impact=True,
+            bin_decimals=None,
+        ):
+            """Compution of local return period for given impact thresholds is not
+            implemented for ImpactForecast.
+            See Also
+            --------
+            See :py:meth:`~climada.engine.impact.Impact.local_return_period`
+            Raises
+            -------
+            NotImplementedError
+            """
+            LOGGER.error("local_return_period is not defined for ImpactForecast")
+            raise NotImplementedError(
+                "local_return_period is not defined for ImpactForecast"
+            )
+        def calc_freq_curve(self, return_per=None):
+            """Computation of the impact exceedance frequency curve is not
+            implemented for ImpactForecast.
+            See Also
+            --------
+            See :py:meth:`~climada.engine.impact.Impact.calc_freq_curve`
+            Raises
+            ------
+            NotImplementedError
+            """
+            LOGGER.error("calc_freq_curve is not defined for ImpactForecast")
+            raise NotImplementedError("calc_freq_curve is not defined for ImpactForecast")
         def _check_sizes(self):
             """Check sizes of forecast data vs. impact data.
@@ Expand Down @@

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