Apply suggestions from code review Chahan

Co-authored-by: Chahan M. Kropf <[email protected]>

Author: ValentinGebhart

climada/engine/impact.py

@@ -1180,6 +1180,7 @@ def plot_rp_imp(
         return_periods=(25, 50, 100, 250),
         log10_scale=True,
         axis=None,
+        kwargs_local_exceedance_impact={},
         **kwargs,
     ):
         """
@@ -1204,7 +1205,10 @@ def plot_rp_imp(
         axis : matplotlib.axes.Axes
         imp_stats : np.array
             return_periods.size x num_centroids
-
+        See Also
+        --------
+        engine.impact.local_exceedance_impact :
+            inter- and extrapolation method
         Notes
         -----
         For handling large data, and for more flexible options in the exceedance
@@ -1221,6 +1225,7 @@ def plot_rp_imp(
 
         impacts_stats, title, column_labels = self.local_exceedance_impact(
             return_periods
+        **kwargs_local_exceedance_impact
         )
 
         impacts_stats_vals = impacts_stats.values[:, 1:].T.astype(float)

climada/hazard/plot.py

@@ -41,6 +41,7 @@ def plot_rp_intensity(
         self,
         return_periods=(25, 50, 100, 250),
         axis=None,
+        kwargs_local_exceedance_intensity={},
         **kwargs,
     ):
         """
@@ -54,13 +55,18 @@ def plot_rp_intensity(
             return periods to consider
         axis: matplotlib.axes._subplots.AxesSubplot, optional
             axis to use
+            kwargs_local_exceedance_intensity: dict
+                 Dictionary of keyword arguments for the method hazard.local_exceedance_intensity
         kwargs: optional
             arguments for pcolormesh matplotlib function used in event plots
 
         Returns
         -------
         axis, inten_stats:  matplotlib.axes._subplots.AxesSubplot, np.ndarray
             intenstats is return_periods.size x num_centroids
+       See Also
+       ---------
+       hazard.local_exceedance_intensity: method to calculate local exceedance frequencies.
 
         Notes
         -----
@@ -76,7 +82,7 @@ def plot_rp_intensity(
         )
 
         inten_stats, title, column_labels = self.local_exceedance_intensity(
-            return_periods
+            return_periods, **kwargs_local_exceedance_intensity
         )
 
         axis = u_plot.plot_from_gdf(