updated readme

Author: bbartling

open_fdd/air_handling_unit/faults/__init__.py

@@ -2072,7 +2072,6 @@ def apply(self, df: pd.DataFrame) -> pd.DataFrame:
             raise e
 
 
-
 class FaultConditionSixteen(FaultCondition):
     """Class provides the definitions for Fault Condition 16.
     ERV Ineffective Process based on outdoor air temperature ranges.
@@ -2181,10 +2180,10 @@ def calculate_erv_efficiency(self, df: pd.DataFrame) -> pd.DataFrame:
         # Calculate the temperature differences
         delta_temp_oa = df[self.erv_oat_leaving_col] - df[self.erv_oat_enter_col]
         delta_temp_ea = df[self.erv_eat_enter_col] - df[self.erv_oat_enter_col]
-        
+
         # Use the absolute value to handle both heating and cooling applications
         df["erv_efficiency_oa"] = np.abs(delta_temp_oa) / np.abs(delta_temp_ea)
-        
+
         return df
 
     def apply(self, df: pd.DataFrame) -> pd.DataFrame:

open_fdd/air_handling_unit/reports/__init__.py

@@ -919,7 +919,7 @@ def create_plot(self, df: pd.DataFrame):
         print("summary statistics ")
         print(df["erv_efficiency_oa"].describe())
         print("=" * 50)
-        
+
         sys.stdout.flush()
 
         # Create the plot with four subplots
@@ -934,16 +934,19 @@ def create_plot(self, df: pd.DataFrame):
 
         # Plot ERV Exhaust Air Side Temps
         ax2.plot(df.index, df[self.erv_eat_enter_col], label="Enter", color="red")
-        ax2.plot(df.index, df[self.erv_eat_leaving_col], label="Leaving", color="purple")
+        ax2.plot(
+            df.index, df[self.erv_eat_leaving_col], label="Leaving", color="purple"
+        )
         ax2.legend(loc="best")
         ax2.set_ylabel("ERV Exhaust Air Side Temps °F")
 
-
         # Plot ERV Efficiency
-        ax3.plot(df.index, df["erv_efficiency_oa"], label="ERV Efficiency OA", color="b")
+        ax3.plot(
+            df.index, df["erv_efficiency_oa"], label="ERV Efficiency OA", color="b"
+        )
         ax3.legend(loc="best")
         ax3.set_ylabel("ERV Efficiency OA")
-        
+
         # Plot Fault Flags
         ax4.plot(df.index, df[self.fault_col], label="Fault", color="k")
         ax4.set_xlabel("Date")
@@ -970,14 +973,12 @@ def summarize_fault_times(self, df: pd.DataFrame) -> dict:
             "flag_true_erv_oat_leave_temp": round(
                 df[self.erv_oat_leaving_col].where(df[self.fault_col] == 1).mean(), 2
             ),
-
             "flag_true_erv_eat_enter_temp": round(
                 df[self.erv_eat_enter_col].where(df[self.fault_col] == 1).mean(), 2
             ),
             "flag_true_erv_eat_leave_temp": round(
                 df[self.erv_eat_leaving_col].where(df[self.fault_col] == 1).mean(), 2
             ),
-
             "hours_motor_runtime": round(
                 (delta * df[self.supply_vfd_speed_col].gt(0.01).astype(int)).sum()
                 / pd.Timedelta(hours=1),