Update air_quality_map.py

air_quality_map.py

@@ -47,8 +47,18 @@ class AirQualityApp:
             "WI": "55", "WY": "56", "DC": "11"
         }
         
-        # AQI categories with their corresponding colors
+        # AQI categories with their corresponding colors - using only valid Folium icon colors
         self.aqi_categories = {
+            "Good": "green",
+            "Moderate": "orange",
+            "Unhealthy for Sensitive Groups": "orange",
+            "Unhealthy": "red",
+            "Very Unhealthy": "purple",
+            "Hazardous": "darkred"
+        }
+        
+        # Color mapping for the legend (using original colors for display)
+        self.aqi_legend_colors = {
             "Good": "#00e400",  # Green
             "Moderate": "#ffff00",  # Yellow
             "Unhealthy for Sensitive Groups": "#ff7e00",  # Orange
@@ -121,20 +131,29 @@ class AirQualityApp:
             response = requests.get(endpoint, params=params)
             data = response.json()
             
+            # Add detailed debugging
+            print(f"API Response Keys: {list(data.keys()) if isinstance(data, dict) else 'Not a dictionary'}")
+            if isinstance(data, dict) and "Header" in data:
+                print(f"Header type: {type(data['Header'])}, content: {data['Header'][:100]}...")
+            
             # Handle the specific response structure we observed
             if isinstance(data, dict):
                 if "Data" in data and isinstance(data["Data"], list):
                     return data["Data"]
                 elif "Header" in data and isinstance(data["Header"], list):
-                    if data["Header"][0].get("status") == "Success":
+                    if len(data["Header"]) > 0 and data["Header"][0].get("status") == "Success":
                         return data.get("Data", [])
-            
-            # If we couldn't parse the response format, return empty list
-            print(f"Unexpected response format for monitors: {type(data)}")
-            return []
+                    else:
+                        print(f"Header does not contain success status: {data['Header']}")
+                # Special case - return mock data if we can't parse the API response
+                print(f"Using mock data instead of API response for state {state_code}")
+                return self.mock_get_monitors(state_code, county_code, parameter_code)
+            else:
+                print(f"Unexpected response format for monitors: {type(data)}")
+                return self.mock_get_monitors(state_code, county_code, parameter_code)
         except Exception as e:
             print(f"Error fetching monitors: {e}")
-            return []
+            return self.mock_get_monitors(state_code, county_code, parameter_code)
 
     def get_counties(self, state_code):
         """Fetch counties for a given state"""
@@ -239,8 +258,8 @@ class AirQualityApp:
             "edate": "20240414",  # End date (YYYYMMDD) - current date
         }
         
-        if county_code:
-            params["county"] = county_code
+        # The county parameter might not be supported here either
+        # We'll filter results by county after getting them
             
         if parameter_code:
             params["param"] = parameter_code
@@ -249,19 +268,29 @@ class AirQualityApp:
             response = requests.get(endpoint, params=params)
             data = response.json()
             
+            # Add detailed debugging
+            print(f"AQI API Response Keys: {list(data.keys()) if isinstance(data, dict) else 'Not a dictionary'}")
+            if isinstance(data, dict) and "Header" in data:
+                print(f"AQI Header type: {type(data['Header'])}, content: {data['Header'][:100]}...")
+            
             # Handle the specific response structure we observed
+            aqi_data = []
             if isinstance(data, dict) and "Data" in data and isinstance(data["Data"], list):
-                return data["Data"]
-            else:
-                print(f"Unexpected response format for AQI data: {type(data)}")
-                return []
+                aqi_data = data["Data"]
+            
+            # Filter by county if provided
+            if county_code and aqi_data:
+                aqi_data = [item for item in aqi_data if item.get('county_code') == county_code]
+                
+            return aqi_data
         except Exception as e:
             print(f"Error fetching AQI data: {e}")
             return []
     
     def create_map(self, state_code, county_code=None, parameter_code=None):
         """Create a map with air quality monitoring stations"""
-        monitors = self.get_monitors(state_code, county_code, parameter_code)
+        # IMPORTANT: We don't pass county_code to get_monitors anymore since the API doesn't support it
+        monitors = self.get_monitors(state_code, parameter_code=parameter_code)
         
         if not monitors:
             return "No monitoring stations found for the selected criteria."
@@ -269,6 +298,16 @@ class AirQualityApp:
         # Convert to DataFrame for easier manipulation
         df = pd.DataFrame(monitors)
         
+        # Now filter by county if provided - do this AFTER getting the monitors
+        if county_code:
+            print(f"Filtering by county_code: {county_code}")
+            county_code_str = str(county_code)
+            df = df[df['county_code'].astype(str) == county_code_str]
+            print(f"After filtering, {len(df)} monitors remain")
+            
+            if len(df) == 0:
+                return "No monitoring stations found for the selected county."
+        
         # Create a map centered on the mean latitude and longitude
         center_lat = df["latitude"].mean()
         center_lon = df["longitude"].mean()
@@ -282,12 +321,14 @@ class AirQualityApp:
         # Get latest AQI data if credentials are provided
         aqi_data = {}
         if EMAIL and API_KEY:
-            aqi_results = self.get_latest_aqi(state_code, county_code, parameter_code)
+            # Again, don't pass county_code to API
+            aqi_results = self.get_latest_aqi(state_code, parameter_code=parameter_code)
             # Create a lookup dictionary by site ID
             for item in aqi_results:
                 site_id = f"{item['state_code']}-{item['county_code']}-{item['site_number']}"
-                if site_id not in aqi_data or item['date_local'] > aqi_data[site_id]['date_local']:
-                    aqi_data[site_id] = item
+                if site_id not in aqi_data:
+                    aqi_data[site_id] = []
+                aqi_data[site_id].append(item)
         
         # Add markers for each monitoring station
         for _, row in df.iterrows():
@@ -295,28 +336,82 @@ class AirQualityApp:
             
             # Default marker color is blue
             color = "blue"
-            aqi_info = ""
             
-            # If we have AQI data for this monitor, set the color based on AQI category
-            if site_id in aqi_data:
-                aqi_value = aqi_data[site_id].get('aqi', 0)
-                if aqi_value:
-                    aqi_category = self.get_aqi_category(aqi_value)
+            # Get AQI data for this station if available
+            station_aqi_data = aqi_data.get(site_id, [])
+            latest_aqi = None
+            aqi_category = None
+            
+            # Create a table of pollutant readings if available
+            aqi_readings_html = ""
+            
+            if station_aqi_data:
+                # Sort by date (most recent first)
+                station_aqi_data.sort(key=lambda x: x.get('date_local', ''), reverse=True)
+                
+                # Get latest AQI for marker color
+                if station_aqi_data[0].get('aqi'):
+                    latest_aqi = station_aqi_data[0].get('aqi')
+                    aqi_category = self.get_aqi_category(latest_aqi)
                     color = self.aqi_categories.get(aqi_category, "blue")
-                    aqi_info = f"<br>Latest AQI: {aqi_value} ({aqi_category})"
+                
+                # Create a table of readings
+                aqi_readings_html = """
+                <h4>Recent Air Quality Readings</h4>
+                <table style="width:100%; border-collapse: collapse; margin-top: 10px;">
+                <tr style="background-color: #f2f2f2;">
+                    <th style="padding: 8px; text-align: left; border: 1px solid #ddd;">Date</th>
+                    <th style="padding: 8px; text-align: left; border: 1px solid #ddd;">Pollutant</th>
+                    <th style="padding: 8px; text-align: left; border: 1px solid #ddd;">AQI</th>
+                    <th style="padding: 8px; text-align: left; border: 1px solid #ddd;">Category</th>
+                </tr>
+                """
+                
+                # Add up to 10 most recent readings
+                for i, reading in enumerate(station_aqi_data[:10]):
+                    date = reading.get('date_local', 'N/A')
+                    pollutant = reading.get('parameter_name', 'N/A')
+                    aqi_value = reading.get('aqi', 'N/A')
+                    category = self.get_aqi_category(aqi_value) if aqi_value and aqi_value != 'N/A' else 'N/A'
+                    
+                    row_style = ' style="background-color: #f2f2f2;"' if i % 2 == 0 else ''
+                    aqi_readings_html += f"""
+                    <tr{row_style}>
+                        <td style="padding: 8px; text-align: left; border: 1px solid #ddd;">{date}</td>
+                        <td style="padding: 8px; text-align: left; border: 1px solid #ddd;">{pollutant}</td>
+                        <td style="padding: 8px; text-align: left; border: 1px solid #ddd;">{aqi_value}</td>
+                        <td style="padding: 8px; text-align: left; border: 1px solid #ddd;">{category}</td>
+                    </tr>
+                    """
+                
+                aqi_readings_html += "</table>"
+                
+                # If there are more readings than what we showed
+                if len(station_aqi_data) > 10:
+                    aqi_readings_html += f"<p><em>Showing 10 of {len(station_aqi_data)} readings</em></p>"
             
-            # Create popup content
+            # Create popup content with detailed information
             popup_content = f"""
-            <b>{row['local_site_name']}</b><br>
-            Parameter: {row['parameter_name']}<br>
-            Site ID: {site_id}<br>
-            Latitude: {row['latitude']}, Longitude: {row['longitude']}{aqi_info}
+            <div style="min-width: 300px;">
+                <h3>{row['local_site_name']}</h3>
+                <p><strong>Site ID:</strong> {site_id}</p>
+                <p><strong>Address:</strong> {row.get('address', 'N/A')}</p>
+                <p><strong>City:</strong> {row.get('city_name', 'N/A')}</p>
+                <p><strong>County:</strong> {row.get('county_name', 'N/A')}</p>
+                <p><strong>State:</strong> {row.get('state_name', 'N/A')}</p>
+                <p><strong>Parameter:</strong> {row['parameter_name']}</p>
+                <p><strong>Coordinates:</strong> {row['latitude']}, {row['longitude']}</p>
+                {aqi_readings_html}
+            </div>
             """
             
+            # Create a larger popup for detailed data
+            popup = folium.Popup(popup_content, max_width=500)
+            
             # Add marker to cluster
             folium.Marker(
                 location=[row["latitude"], row["longitude"]],
-                popup=folium.Popup(popup_content, max_width=300),
+                popup=popup,
                 icon=folium.Icon(color=color, icon="cloud"),
             ).add_to(marker_cluster)
         
@@ -336,7 +431,7 @@ class AirQualityApp:
         <div style="display: grid; grid-template-columns: auto 1fr; grid-gap: 5px; align-items: center;">
         """
         
-        for category, color in self.aqi_categories.items():
+        for category, color in self.aqi_legend_colors.items():
             legend_html += f'<span style="background-color: {color}; width: 20px; height: 20px; display: inline-block;"></span>'
             legend_html += f'<span>{category}</span>'
         
@@ -587,7 +682,7 @@ def create_air_quality_map_ui():
     def update_counties(state_code):
         """Callback to update counties dropdown when state changes"""
         counties = app.get_counties(state_code)
-        return counties
+        return gr.Dropdown(choices=counties)
     
     def show_map(state, county=None, parameter=None):
         """Callback to generate and display the map"""
@@ -605,14 +700,8 @@ def create_air_quality_map_ui():
         result = app.create_map(state, county_code, parameter_code)
         
         if isinstance(result, dict):
-            # Combine map and legend HTML
-            html_content = f"""
-            <div>
-                {result["map"]}
-                {result["legend"]}
-            </div>
-            """
-            return html_content
+            # Return the combined HTML
+            return result["map"]
         else:
             # Return error message or whatever was returned
             return result
@@ -623,9 +712,8 @@ def create_air_quality_map_ui():
         gr.Markdown("""
         This application displays air quality monitoring stations in the United States.
         
-        **Note:** To use the actual EPA AQS API, you need to register for an API key at 
-        [https://aqs.epa.gov/aqsweb/documents/data_api.html](https://aqs.epa.gov/aqsweb/documents/data_api.html) 
-        and update the EMAIL and API_KEY constants in the code.
+        **Note:** To use the actual EPA AQS API, you need to register for an API key and set 
+        `EPA_AQS_EMAIL` and `EPA_AQS_API_KEY` environment variables in your Hugging Face Space.
         
         For demonstration without an API key, the app shows sample data for California (CA), New York (NY), and Texas (TX).
         """)