Update data/climate_data.py

data/climate_data.py

@@ -45,12 +45,12 @@ class ClimateLocation:
     
     def __init__(self, epw_file=None, manual_data=None, **kwargs):
         """Initialize ClimateLocation with EPW file or manual data."""
-        if epw_file:
+        if epw_file is not None and isinstance(epw_file, pd.DataFrame):
             # Extract from EPW (epw_data[6] for dry-bulb temperature)
             temps = np.array(epw_file[6], dtype=float)
             self.winter_design_temp = np.percentile(temps[~np.isnan(temps)], 0.4)  # 99.6% percentile
-            self.wind_speed = round(np.nanmean(epw_file[13]), 1)  # m/s
-            self.pressure = self.adjust_pressure_for_altitude(kwargs.get("elevation", 0.0))
+            self.wind_speed = round(np.nanmean(epw_file[21]), 1)  # Wind speed (m/s, index 21)
+            self.pressure = round(np.nanmean(epw_file[9]), 1)  # Atmospheric pressure (Pa, index 9)
             # Populate other fields from EPW processing
             self.id = kwargs.get("id")
             self.country = kwargs.get("country")
@@ -237,17 +237,24 @@ class ClimateData:
                     
                     data_start_idx = next(i for i, line in enumerate(epw_lines) if line.startswith("DATA PERIODS")) + 1
                     epw_data = pd.read_csv(StringIO("\n".join(epw_lines[data_start_idx:])), header=None, dtype=str)
+                    
+                    # Validate row and column counts
                     if len(epw_data) != 8760:
                         raise ValueError(f"EPW file has {len(epw_data)} records, expected 8760.")
+                    if len(epw_data.columns) != 35:
+                        raise ValueError(f"EPW file has {len(epw_data.columns)} columns, expected 35.")
                     
-                    for col in epw_data.columns:
+                    # Convert relevant columns to numeric
+                    for col in [1, 6, 8, 9, 21]:
                         epw_data[col] = pd.to_numeric(epw_data[col], errors='coerce')
+                        if epw_data[col].isna().all():
+                            raise ValueError(f"Column {col} (e.g., {'wind speed' if col == 21 else 'pressure' if col == 9 else 'other'}) contains only non-numeric or missing data.")
                     
                     months = epw_data[1].values  # Month
                     dry_bulb = epw_data[6].values  # Dry-bulb temperature (°C)
                     humidity = epw_data[8].values  # Relative humidity (%)
                     pressure = epw_data[9].values  # Atmospheric pressure (Pa)
-                    wind_speed = epw_data[13].values  # Wind speed (m/s)
+                    wind_speed = epw_data[21].values  # Wind speed (m/s)
                     
                     wet_bulb = self.calculate_wet_bulb(dry_bulb, humidity)
                     
@@ -665,5 +672,5 @@ class ClimateData:
 
 if __name__ == "__main__":
     climate_data = ClimateData()
-    session_state = {"building_info": {"country": "Iceland", "city": "Reyugalvik"}, "page": "Climate Data"}
+    session_state = {"building_info": {"country": "Iceland", "city": "Reykjavik"}, "page": "Climate Data"}
     climate_data.display_climate_input(session_state)