Block return_period and exceedance_freq_curve

Author: luseverin

climada/engine/impact_forecast.py

@@ -119,3 +119,35 @@ def local_exceedance_impact(
         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 climada.engine.impact.Impact for details.
+        Returns
+        -------
+        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 climada.engine.impact.Impact for details.
+        Returns
+        -------
+        NotImplementedError
+        """
+
+        LOGGER.error("calc_freq_curve is not defined for ImpactForecast")
+        raise NotImplementedError("calc_freq_curve is not defined for ImpactForecast")

climada/engine/test/test_impact_forecast.py

@@ -105,7 +105,13 @@ def test_impact_forecast_concat(impact_forecast, member):
     npt.assert_array_equal(impact_fc.member, np.concatenate([member, member]))
 
 
-def test_impact_forecast_exceedance_freq_curve_error(impact_forecast):
+def test_impact_forecast_blocked_methods(impact_forecast):
     """Check if ImpactForecast.exceedance_freq_curve raises NotImplementedError"""
     with pytest.raises(NotImplementedError):
         impact_forecast.local_exceedance_impact(np.array([10, 50, 100]))
+
+    with pytest.raises(NotImplementedError):
+        impact_forecast.local_return_period(np.array([10, 50, 100]))
+
+    with pytest.raises(NotImplementedError):
+        impact_forecast.calc_freq_curve(np.array([10, 50, 100]))