Update data/climate_data.py

data/climate_data.py

@@ -223,94 +223,126 @@ class ClimateData:
         return wet_bulb
 
     def display_climate_input(self, session_state: Dict[str, Any]):
-        """Display Streamlit interface for EPW upload and visualizations."""
-        st.title("Climate Data Analysis")
-        
-        if not session_state.building_info.get("country") or not session_state.building_info.get("city"):
-            st.warning("Please enter country and city in Building Information first.")
-            st.button("Go to Building Information", on_click=lambda: setattr(session_state, "page", "Building Information"))
-            return
-        
-        st.subheader(f"Location: {session_state.building_info['country']}, {session_state.building_info['city']}")
-        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(",")
-                city = header_parts[1].strip()
-                state_province = header_parts[2].strip() or "N/A"
-                country = header_parts[3].strip()
-                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.")
-                if len(epw_data.columns) != 35:
-                    raise ValueError(f"EPW file has {len(epw_data.columns)} columns, expected 35.")
-                
-                for col in [1, 6, 8, 9, 13, 20, 21]:
-                    epw_data[col] = pd.to_numeric(epw_data[col], errors='coerce')
-                    if epw_data[col].isna().all():
-                        raise ValueError(f"Column {col} contains only non-numeric or missing data.")
-                
-                location = ClimateLocation(
-                    epw_file=epw_data,
-                    id=f"{country[:1].upper()}{city[:3].upper()}",
-                    country=country,
-                    state_province=state_province,
-                    city=city,
-                    latitude=latitude,
-                    longitude=longitude,
-                    elevation=elevation
-                )
-                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
-                st.success("Climate data extracted from EPW file!")
-                
-                tab1, tab2, tab3, tab4, tab5 = st.tabs([
-                    "General Information",
-                    "Psychrometric Chart",
-                    "Sun Shading Chart",
-                    "Temperature Range",
-                    "Wind Rose"
-                ])
-                
-                with tab1:
-                    self.display_design_conditions(location)
-                
-                with tab2:
-                    self.plot_psychrometric_chart(location, epw_data)
-                
-                with tab3:
-                    self.plot_sun_shading_chart(location)
-                
-                with tab4:
-                    self.plot_temperature_range(location, epw_data)
-                
-                with tab5:
-                    self.plot_wind_rose(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"))
-        with col2:
-            if self.locations:
-                st.button("Continue to Building Components", on_click=lambda: setattr(session_state, "page", "Building Components"))
-            else:
-                st.button("Continue to Building Components", disabled=True)
+    """Display Streamlit interface for EPW upload and visualizations."""
+    st.title("Climate Data Analysis")
+    
+    if not session_state.building_info.get("country") or not session_state.building_info.get("city"):
+        st.warning("Please enter country and city in Building Information first.")
+        st.button("Go to Building Information", on_click=lambda: setattr(session_state, "page", "Building Information"))
+        return
+    
+    st.subheader(f"Location: {session_state.building_info['country']}, {session_state.building_info['city']}")
+    uploaded_file = st.file_uploader("Upload EPW File", type=["epw"])
+    
+    # Initialize location and epw_data for display
+    location = None
+    epw_data = None
+    
+    if uploaded_file:
+        try:
+            # Process new EPW file (existing code)
+            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(",")
+            city = header_parts[1].strip()
+            state_province = header_parts[2].strip() or "N/A"
+            country = header_parts[3].strip()
+            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.")
+            if len(epw_data.columns) != 35:
+                raise ValueError(f"EPW file has {len(epw_data.columns)} columns, expected 35.")
+            
+            for col in [1, 6, 8, 9, 13, 20, 21]:
+                epw_data[col] = pd.to_numeric(epw_data[col], errors='coerce')
+                if epw_data[col].isna().all():
+                    raise ValueError(f"Column {col} contains only non-numeric or missing data.")
+            
+            location = ClimateLocation(
+                epw_file=epw_data,
+                id=f"{country[:1].upper()}{city[:3].upper()}",
+                country=country,
+                state_province=state_province,
+                city=city,
+                latitude=latitude,
+                longitude=longitude,
+                elevation=elevation
+            )
+            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
+            st.success("Climate data extracted from EPW file!")
+        
+        except Exception as e:
+            st.error(f"Error processing EPW file: {str(e)}. Ensure it has 8760 hourly records and correct format.")
+    
+    # Check for existing data in session_state
+    elif "climate_data" in session_state and self.validate_climate_data(session_state["climate_data"]):
+        # Reconstruct location and epw_data from session_state
+        climate_data_dict = session_state["climate_data"]
+        location = ClimateLocation(
+            epw_file=pd.DataFrame(),  # Empty DataFrame since hourly_data is in climate_data_dict
+            **{k: v for k, v in climate_data_dict.items() if k != "hourly_data"}
+        )
+        location.hourly_data = climate_data_dict["hourly_data"]
+        self.add_location(location)
+        
+        # Reconstruct epw_data for plotting
+        hourly_data = climate_data_dict["hourly_data"]
+        epw_data = pd.DataFrame({
+            1: [d["month"] for d in hourly_data],  # Month
+            6: [d["dry_bulb"] for d in hourly_data],  # Dry-bulb temperature
+            8: [d["relative_humidity"] for d in hourly_data],  # Relative humidity
+            13: [d["global_horizontal_radiation"] for d in hourly_data],  # Global horizontal radiation
+            20: [d["wind_direction"] for d in hourly_data],  # Wind direction
+            21: [d["wind_speed"] for d in hourly_data],  # Wind speed
+            9: [climate_data_dict["pressure"]] * len(hourly_data)  # Pressure (mean value)
+        })
+        st.info("Displaying previously extracted climate data.")
+    
+    # Display tabs if location and epw_data are available
+    if location and epw_data is not None:
+        tab1, tab2, tab3, tab4, tab5 = st.tabs([
+            "General Information",
+            "Psychrometric Chart",
+            "Sun Shading Chart",
+            "Temperature Range",
+            "Wind Rose"
+        ])
+        
+        with tab1:
+            self.display_design_conditions(location)
+        
+        with tab2:
+            self.plot_psychrometric_chart(location, epw_data)
+        
+        with tab3:
+            self.plot_sun_shading_chart(location)
+        
+        with tab4:
+            self.plot_temperature_range(location, epw_data)
+        
+        with tab5:
+            self.plot_wind_rose(epw_data)
+    
+    # Navigation buttons
+    col1, col2 = st.columns(2)
+    with col1:
+        st.button("Back to Building Information", on_click=lambda: setattr(session_state, "page", "Building Information"))
+    with col2:
+        if self.locations:
+            st.button("Continue to Building Components", on_click=lambda: setattr(session_state, "page", "Building Components"))
+        else:
+            st.button("Continue to Building Components", disabled=True)
 
     def display_design_conditions(self, location: ClimateLocation):
         """Display design conditions for HVAC calculations using Markdown."""