Upload climate_data.py

data/climate_data.py

@@ -40,7 +40,52 @@ class ClimateLocation:
     summer_daily_range: float  # Mean daily temperature range in summer (°C)
     monthly_temps: Dict[str, float]  # Average monthly temperatures (°C)
     monthly_humidity: Dict[str, float]  # Average monthly relative humidity (%)
+    wind_speed: float  # Mean wind speed (m/s)
+    pressure: float  # Atmospheric pressure (Pa)
     
+    def __init__(self, epw_file=None, manual_data=None, **kwargs):
+        """Initialize ClimateLocation with EPW file or manual data."""
+        if epw_file:
+            # 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))
+            # Populate other fields from EPW processing
+            self.id = kwargs.get("id")
+            self.country = kwargs.get("country")
+            self.state_province = kwargs.get("state_province")
+            self.city = kwargs.get("city")
+            self.latitude = kwargs.get("latitude")
+            self.longitude = kwargs.get("longitude")
+            self.elevation = kwargs.get("elevation")
+            self.climate_zone = kwargs.get("climate_zone")
+            self.heating_degree_days = kwargs.get("heating_degree_days")
+            self.cooling_degree_days = kwargs.get("cooling_degree_days")
+            self.summer_design_temp_db = kwargs.get("summer_design_temp_db")
+            self.summer_design_temp_wb = kwargs.get("summer_design_temp_wb")
+            self.summer_daily_range = kwargs.get("summer_daily_range")
+            self.monthly_temps = kwargs.get("monthly_temps")
+            self.monthly_humidity = kwargs.get("monthly_humidity")
+        elif manual_data:
+            self.winter_design_temp = manual_data.get("winter_temp", -10.0)
+            self.wind_speed = manual_data.get("wind_speed", 5.0)
+            self.pressure = manual_data.get("pressure", 101325.0)
+            # Populate other fields from manual data
+            for key, value in kwargs.items():
+                setattr(self, key, value)
+        else:
+            # Default initialization with kwargs
+            for key, value in kwargs.items():
+                setattr(self, key, value)
+            self.winter_design_temp = kwargs.get("winter_design_temp", -10.0)
+            self.wind_speed = kwargs.get("wind_speed", 5.0)
+            self.pressure = self.adjust_pressure_for_altitude(kwargs.get("elevation", 0.0))
+
+    def adjust_pressure_for_altitude(self, elevation: float) -> float:
+        """Calculate atmospheric pressure based on elevation."""
+        return 101325 * (1 - 2.25577e-5 * elevation)**5.25588
+
     def to_dict(self) -> Dict[str, Any]:
         """Convert the climate location to a dictionary."""
         return {
@@ -59,7 +104,9 @@ class ClimateLocation:
             "summer_design_temp_wb": self.summer_design_temp_wb,
             "summer_daily_range": self.summer_daily_range,
             "monthly_temps": self.monthly_temps,
-            "monthly_humidity": self.monthly_humidity
+            "monthly_humidity": self.monthly_humidity,
+            "wind_speed": self.wind_speed,
+            "pressure": self.pressure
         }
 
 class ClimateData:
@@ -106,7 +153,8 @@ class ClimateData:
             "id", "country", "city", "latitude", "longitude", "elevation",
             "climate_zone", "heating_degree_days", "cooling_degree_days",
             "winter_design_temp", "summer_design_temp_db", "summer_design_temp_wb",
-            "summer_daily_range", "monthly_temps", "monthly_humidity"
+            "summer_daily_range", "monthly_temps", "monthly_humidity",
+            "wind_speed", "pressure"
         ]
         month_names = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
         
@@ -128,6 +176,10 @@ class ClimateData:
             return False
         if data["summer_daily_range"] < 0:
             return False
+        if not (0 <= data["wind_speed"] <= 20):
+            return False
+        if not (50000 <= data["pressure"] <= 120000):
+            return False
         
         for month in month_names:
             if month not in data["monthly_temps"] or month not in data["monthly_humidity"]:
@@ -159,7 +211,7 @@ class ClimateData:
         return wet_bulb
 
     def display_climate_input(self, session_state: Dict[str, Any]):
-        """Display form for manual input or EPW upload in Streamlit."""
+        """Display form for EPW upload or manual input in Streamlit."""
         st.title("Climate Data")
         
         if not session_state.building_info.get("country") or not session_state.building_info.get("city"):
@@ -168,10 +220,94 @@ class ClimateData:
             return
         
         st.subheader(f"Location: {session_state.building_info['country']}, {session_state.building_info['city']}")
-        tab1, tab2 = st.tabs(["Manual Input", "Upload EPW File"])
+        tab1, tab2 = st.tabs(["Upload EPW File", "Manual Input"])
         
-        # Manual Input Tab
+        # EPW Upload Tab
         with tab1:
+            uploaded_file = st.file_uploader("Upload EPW File", type=["epw"])
+            if uploaded_file:
+                try:
+                    epw_content = uploaded_file.read().decode("utf-8")
+                    epw_lines = epw_content.splitlines()
+                    header = next(line for line in epw_lines if line.startswith("LOCATION"))
+                    header_parts = header.split(",")
+                    latitude = float(header_parts[6])
+                    longitude = float(header_parts[7])
+                    elevation = float(header_parts[8])
+                    
+                    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)
+                    if len(epw_data) != 8760:
+                        raise ValueError(f"EPW file has {len(epw_data)} records, expected 8760.")
+                    
+                    for col in epw_data.columns:
+                        epw_data[col] = pd.to_numeric(epw_data[col], errors='coerce')
+                    
+                    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)
+                    
+                    wet_bulb = self.calculate_wet_bulb(dry_bulb, humidity)
+                    
+                    if np.all(np.isnan(dry_bulb)) or np.all(np.isnan(humidity)) or np.all(np.isnan(wet_bulb)):
+                        raise ValueError("Dry bulb, humidity, or calculated wet bulb data is entirely NaN.")
+                    
+                    daily_temps = np.nanmean(dry_bulb.reshape(-1, 24), axis=1)
+                    hdd = round(np.nansum(np.maximum(18 - daily_temps, 0)))
+                    cdd = round(np.nansum(np.maximum(daily_temps - 18, 0)))
+                    
+                    winter_design_temp = round(np.nanpercentile(dry_bulb, 0.4), 1)
+                    summer_design_temp_db = round(np.nanpercentile(dry_bulb, 99.6), 1)
+                    summer_design_temp_wb = round(np.nanpercentile(wet_bulb, 99.6), 1)
+                    summer_mask = (months >= 6) & (months <= 8)
+                    summer_temps = dry_bulb[summer_mask].reshape(-1, 24)
+                    summer_daily_range = round(np.nanmean(np.nanmax(summer_temps, axis=1) - np.nanmin(summer_temps, axis=1)), 1)
+                    
+                    monthly_temps = {}
+                    monthly_humidity = {}
+                    month_names = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
+                    for i in range(1, 13):
+                        month_mask = (months == i)
+                        monthly_temps[month_names[i-1]] = round(np.nanmean(dry_bulb[month_mask]), 1)
+                        monthly_humidity[month_names[i-1]] = round(np.nanmean(humidity[month_mask]), 1)
+                    
+                    avg_humidity = np.nanmean(humidity)
+                    climate_zone = self.assign_climate_zone(hdd, cdd, avg_humidity)
+                    
+                    location = ClimateLocation(
+                        epw_file=epw_data,
+                        id=f"{session_state.building_info['country'][:2].upper()}-{session_state.building_info['city'][:3].upper()}",
+                        country=session_state.building_info["country"],
+                        state_province="N/A",
+                        city=session_state.building_info["city"],
+                        latitude=latitude,
+                        longitude=longitude,
+                        elevation=elevation,
+                        climate_zone=climate_zone,
+                        heating_degree_days=hdd,
+                        cooling_degree_days=cdd,
+                        summer_design_temp_db=summer_design_temp_db,
+                        summer_design_temp_wb=summer_design_temp_wb,
+                        summer_daily_range=summer_daily_range,
+                        monthly_temps=monthly_temps,
+                        monthly_humidity=monthly_humidity
+                    )
+                    self.add_location(location)
+                    climate_data_dict = location.to_dict()
+                    if not self.validate_climate_data(climate_data_dict):
+                        raise ValueError("Invalid climate data extracted from EPW file.")
+                    session_state["climate_data"] = climate_data_dict  # Save to session state
+                    st.success("Climate data extracted from EPW file with calculated Wet Bulb Temperature!")
+                    st.write(f"Debug: Saved climate data for {location.city} (ID: {location.id}): {climate_data_dict}")  # Debug
+                    self.display_design_conditions(location)
+                    self.visualize_data(location, epw_data=epw_data)
+                except Exception as e:
+                    st.error(f"Error processing EPW file: {str(e)}. Ensure it has 8760 hourly records and correct format.")
+
+        # Manual Input Tab
+        with tab2:
             with st.form("manual_climate_form"):
                 col1, col2 = st.columns(2)
                 with col1:
@@ -222,10 +358,7 @@ class ClimateData:
                     winter_design_temp = st.number_input(
                         "Winter Design Temp (99.6%) (°C)",
                         min_value=-50.0,
-                        max_value=20.0,
-                        value=0.0,
-                        step=0.5,
-                        help="Enter the 99.6% winter design temperature in °C (extreme cold condition)"
+                        max
                     )
                     summer_design_temp_db = st.number_input(
                         "Summer Design Temp DB (0.4%) (°C)",
@@ -250,6 +383,14 @@ class ClimateData:
                         step=0.5,
                         help="Enter the average daily temperature range in summer in °C"
                     )
+                    wind_speed = st.number_input(
+                        "Wind Speed (m/s)",
+                        min_value=0.0,
+                        max_value=20.0,
+                        value=5.0,
+                        step=0.1,
+                        help="Enter the average wind speed in meters per second"
+                    )
                 
                 # Monthly Data with clear titles (no help added here)
                 monthly_temps = {}
@@ -278,7 +419,13 @@ class ClimateData:
                     try:
                         # Generate ID internally using country and city from session_state
                         generated_id = f"{session_state.building_info['country'][:2].upper()}-{session_state.building_info['city'][:3].upper()}"
+                        manual_data = {
+                            "winter_temp": winter_design_temp,
+                            "wind_speed": wind_speed,
+                            "pressure": ClimateLocation.adjust_pressure_for_altitude(None, elevation)
+                        }
                         location = ClimateLocation(
+                            manual_data=manual_data,
                             id=generated_id,
                             country=session_state.building_info["country"],
                             state_province="N/A",  # Default since input removed
@@ -289,7 +436,6 @@ class ClimateData:
                             climate_zone=climate_zone,
                             heating_degree_days=hdd,
                             cooling_degree_days=cdd,
-                            winter_design_temp=winter_design_temp,
                             summer_design_temp_db=summer_design_temp_db,
                             summer_design_temp_wb=summer_design_temp_wb,
                             summer_daily_range=summer_daily_range,
@@ -308,89 +454,6 @@ class ClimateData:
                     except Exception as e:
                         st.error(f"Error saving climate data: {str(e)}. Please check inputs and try again.")
 
-        # EPW Upload Tab
-        with tab2:
-            uploaded_file = st.file_uploader("Upload EPW File", type=["epw"])
-            if uploaded_file:
-                try:
-                    epw_content = uploaded_file.read().decode("utf-8")
-                    epw_lines = epw_content.splitlines()
-                    header = next(line for line in epw_lines if line.startswith("LOCATION"))
-                    header_parts = header.split(",")
-                    latitude = float(header_parts[6])
-                    longitude = float(header_parts[7])
-                    elevation = float(header_parts[8])
-                    
-                    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)
-                    if len(epw_data) != 8760:
-                        raise ValueError(f"EPW file has {len(epw_data)} records, expected 8760.")
-                    
-                    for col in epw_data.columns:
-                        epw_data[col] = pd.to_numeric(epw_data[col], errors='coerce')
-                    
-                    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)
-                    
-                    wet_bulb = self.calculate_wet_bulb(dry_bulb, humidity)
-                    
-                    if np.all(np.isnan(dry_bulb)) or np.all(np.isnan(humidity)) or np.all(np.isnan(wet_bulb)):
-                        raise ValueError("Dry bulb, humidity, or calculated wet bulb data is entirely NaN.")
-                    
-                    daily_temps = np.nanmean(dry_bulb.reshape(-1, 24), axis=1)
-                    hdd = round(np.nansum(np.maximum(18 - daily_temps, 0)))
-                    cdd = round(np.nansum(np.maximum(daily_temps - 18, 0)))
-                    
-                    winter_design_temp = round(np.nanpercentile(dry_bulb, 0.4), 1)
-                    summer_design_temp_db = round(np.nanpercentile(dry_bulb, 99.6), 1)
-                    summer_design_temp_wb = round(np.nanpercentile(wet_bulb, 99.6), 1)
-                    summer_mask = (months >= 6) & (months <= 8)
-                    summer_temps = dry_bulb[summer_mask].reshape(-1, 24)
-                    summer_daily_range = round(np.nanmean(np.nanmax(summer_temps, axis=1) - np.nanmin(summer_temps, axis=1)), 1)
-                    
-                    monthly_temps = {}
-                    monthly_humidity = {}
-                    month_names = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
-                    for i in range(1, 13):
-                        month_mask = (months == i)
-                        monthly_temps[month_names[i-1]] = round(np.nanmean(dry_bulb[month_mask]), 1)
-                        monthly_humidity[month_names[i-1]] = round(np.nanmean(humidity[month_mask]), 1)
-                    
-                    avg_humidity = np.nanmean(humidity)
-                    climate_zone = self.assign_climate_zone(hdd, cdd, avg_humidity)
-                    
-                    location = ClimateLocation(
-                        id=f"{session_state.building_info['country'][:2].upper()}-{session_state.building_info['city'][:3].upper()}",
-                        country=session_state.building_info["country"],
-                        state_province="N/A",
-                        city=session_state.building_info["city"],
-                        latitude=latitude,
-                        longitude=longitude,
-                        elevation=elevation,
-                        climate_zone=climate_zone,
-                        heating_degree_days=hdd,
-                        cooling_degree_days=cdd,
-                        winter_design_temp=winter_design_temp,
-                        summer_design_temp_db=summer_design_temp_db,
-                        summer_design_temp_wb=summer_design_temp_wb,
-                        summer_daily_range=summer_daily_range,
-                        monthly_temps=monthly_temps,
-                        monthly_humidity=monthly_humidity
-                    )
-                    self.add_location(location)
-                    climate_data_dict = location.to_dict()
-                    if not self.validate_climate_data(climate_data_dict):
-                        raise ValueError("Invalid climate data extracted from EPW file.")
-                    session_state["climate_data"] = climate_data_dict  # Save to session state
-                    st.success("Climate data extracted from EPW file with calculated Wet Bulb Temperature!")
-                    st.write(f"Debug: Saved climate data for {location.city} (ID: {location.id}): {climate_data_dict}")  # Debug
-                    self.display_design_conditions(location)
-                    self.visualize_data(location, epw_data=epw_data)
-                except Exception as e:
-                    st.error(f"Error processing EPW file: {str(e)}. Ensure it has 8760 hourly records and correct format.")
-
         col1, col2 = st.columns(2)
         with col1:
             st.button("Back to Building Information", on_click=lambda: setattr(session_state, "page", "Building Information"))
@@ -420,7 +483,9 @@ class ClimateData:
                 "Winter Design Temperature (99.6%)",
                 "Summer Design Dry-Bulb Temp (0.4%)",
                 "Summer Design Wet-Bulb Temp (0.4%)",
-                "Summer Daily Temperature Range"
+                "Summer Daily Temperature Range",
+                "Wind Speed (m/s)",
+                "Atmospheric Pressure (Pa)"
             ],
             "Value": [
                 f"{location.latitude}°",
@@ -432,7 +497,9 @@ class ClimateData:
                 f"{location.winter_design_temp} °C",
                 f"{location.summer_design_temp_db} °C",
                 f"{location.summer_design_temp_wb} °C",
-                f"{location.summer_daily_range} °C"
+                f"{location.summer_daily_range} °C",
+                f"{location.wind_speed} m/s",
+                f"{location.pressure} Pa"
             ]
         })