black formatting

Author: tyrneh

examples/appl_example.py

@@ -58,8 +58,8 @@
 
 
 # plot fitted IV smile as 2D plot
-# est_appl.plot_iv(observations="range", x_axis="strike")
-# plt.show()
+est_appl.plot_iv(observations="range", x_axis="strike")
+plt.show()
 
 
 # return SVI parameters
@@ -154,7 +154,7 @@
 print("\nTesting Plotting...")
 try:
     import matplotlib.pyplot as plt
-    
+
     # 1. VolCurve Plot
     # Pick the first available expiry
     expiry_to_plot = appl_surface.expiries[0]
@@ -168,7 +168,7 @@
     fig_pdf = dist.plot(kind="pdf", title="Implied PDF (100 days)")
     # plt.show() # Uncomment to see plot
     print("Distribution.plot() successful")
-    
+
 except ImportError:
     print("Matplotlib not installed, skipping plotting tests")
 except Exception as e:

oipd/interface/volatility.py

@@ -173,7 +173,7 @@ def iv_smile(
 
         Returns:
             DataFrame containing:
-            
+
             - ``strike``: Strike levels.
             - ``fitted_iv``: Fitted implied volatility from the calibrated model.
             - ``market_iv``: *(if include_observed=True)* Mid-price implied volatility
@@ -203,31 +203,32 @@ def iv_smile(
 
     def plot(self, **kwargs) -> Any:
         """Plot the fitted implied volatility smile.
-        
+
         Args:
             **kwargs: Arguments forwarded to ``oipd.presentation.iv_plotting.plot_iv_smile``.
-        
+
         Returns:
             matplotlib.figure.Figure: The plot figure.
-        """        
+        """
         smile_df = self.iv_smile()
-        
+
         # Map our column names to what plot_iv_smile expects
-        plot_df = smile_df.rename(columns={
-            "market_bid_iv": "bid_iv",
-            "market_ask_iv": "ask_iv",
-            "market_last_iv": "last_iv"
-        })
+        plot_df = smile_df.rename(
+            columns={
+                "market_bid_iv": "bid_iv",
+                "market_ask_iv": "ask_iv",
+                "market_last_iv": "last_iv",
+            }
+        )
 
         # Extract reference price (forward) for log-moneyness plotting
         reference = None
         forward_price = self._metadata.get("forward_price")
         if forward_price is not None:
             reference = ReferenceAnnotation(
-                value=float(forward_price),
-                label=f"Forward: {float(forward_price):.2f}"
+                value=float(forward_price), label=f"Forward: {float(forward_price):.2f}"
             )
-        
+
         # If no reference price is available, default to strike axis to avoid errors
         if reference is None and "axis_mode" not in kwargs:
             kwargs["axis_mode"] = "strike"