Create CAT bond module

climada_petals/engine/cat_bonds/pay_dam_subarea.py

@@ -0,0 +1,49 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+import subarea_calculations
+
+class Pay_dam_subarea:
+    def __init__(self, subareas, index_stat, exhaustion_point, attachment_point):
+        self.subareas_class = subareas
+        self.index_stat = index_stat
+        self.exhaustion_point = exhaustion_point
+        self.attachment = attachment_point
+        self._get_pay_vs_dam()
+
+    def _get_pay_vs_dam(self):
+        calculation_class = subarea_calculations.Subarea_Calculations(self.subareas_class, self.index_stat, self.exhaustion_point, self.attachment)
+        self.pay_vs_dam, self.principal = calculation_class.create_pay_vs_dam()
+
+    def plot_pay_vs_dam(self, calculation_class):
+        tot_exp = calculation_class.exposure.gdf['value'].sum()
+
+        fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 4))
+
+        ax1.scatter(self.pay_vs_dam/tot_exp, payout_flt/tot_exp, marker='o', color='blue', label='Events')
+        ax1.plot([0, nominal/tot_exp], [0, nominal/tot_exp], color='black', linestyle='--', label='Trendline')
+        ax1.axhline(y = nominal/tot_exp, color = 'r', linestyle = '-', label='Principal') 
+        ax1.axhline(y = 0.05, color = 'r', linestyle = '-', label='Attachment Point') 
+        ax1.axvline(x = 0.05, color = 'r', linestyle = '--', label='Min. Damage') 
+        ax1.set_xlabel("Damage [share of GDP]", fontsize=12)
+        ax1.set_ylabel("Payout [share of GDP]", fontsize=12)
+        ax1.legend(loc='lower right', borderpad=2.0)
+
+        ax2.scatter(damages/tot_exp, pay_dam_df['pay']/tot_exp, marker='o', color='blue', label='Events')
+        ax2.axhline(y = nominal/tot_exp, color = 'r', linestyle = '-', label='Principal') 
+        ax2.axhline(y = 0.05, color = 'r', linestyle = '-', label='Attachment Point') 
+        ax2.axvline(x = 0.05, color = 'black', linestyle = '--', label='Min. Damage') 
+        ax2.set_xscale('log')
+        ax2.set_xlabel("Damage [share of GDP]", fontsize=12)
+        ax2.set_ylabel("Payout [share of GDP]", fontsize=12)
+
+        panel_labels = ["a)", "b)"]
+        for i, ax in enumerate([ax1, ax2]):
+            ax.annotate(panel_labels[i], 
+                xy=(-0.1, 1),  
+                xycoords="axes fraction", 
+                fontsize=14, 
+                fontweight="bold")
+
+        plt.tight_layout()
+        plt.show()