Update modules/visuals.py

modules/visuals.py

@@ -1,105 +1,38 @@
+import folium
+from folium.plugins import HeatMap
 import streamlit as st
-import plotly.express as px
-import plotly.graph_object as go
-import pandas as pd
 
-def display_dashboard(df, location):
-    st.subheader(f"📊 System Summary - {location}")
-    col1, col2, col3 = st.columns(3)
-    col1.metric("Total Poles", df.shape[0])
-    col2.metric("🚨 Red Alerts", df[df['AlertLevel'] == "Red"].shape[0])
-    col3.metric("⚡ Power Issues", df[df['PowerSufficient'] == "No"].shape[0])
+def display_heatmap(df):
+    # Initialize the base map at a central location (around Hyderabad)
+    center_lat = 17.385044  # Example latitude for Hyderabad
+    center_lon = 78.486671  # Example longitude for Hyderabad
+    map = folium.Map(location=[center_lat, center_lon], zoom_start=6)
 
-def display_charts(df):
-    st.subheader("⚙️ Energy Generation Trends")
-    st.bar_chart(df.groupby("Zone")[["SolarGen(kWh)", "WindGen(kWh)"]].sum())
-    st.subheader("📉 Tilt vs Vibration")
-    st.scatter_chart(df.rename(columns={"Tilt(°)": "Tilt", "Vibration(g)": "Vibration"}).set_index("PoleID")[["Tilt", "Vibration"]])
+    # Add heatmap layer
+    heat_data = []
+    for index, row in df.iterrows():
+        lat = row["Latitude"]
+        lon = row["Longitude"]
+        alert = row["Alert Level"]
+        
+        # Color mapping for heatmap intensity based on alert level
+        if alert == "Green":
+            color = [0, 255, 0]  # Green
+        elif alert == "Yellow":
+            color = [255, 255, 0]  # Yellow
+        elif alert == "Red":
+            color = [255, 0, 0]  # Red
+        
+        # Add data to the heatmap layer (latitude, longitude, intensity)
+        heat_data.append([lat, lon, 1 if alert == "Red" else 0.5 if alert == "Yellow" else 0.1])
 
-def display_map_heatmap(df, location):
-    if df.empty:
-        st.warning("No data available for this location.")
-        return
+    # Create HeatMap with data
+    HeatMap(heat_data).add_to(map)
 
-# Example DataFrame with location data
-df = pd.DataFrame({
-    'latitude': [17.385044, 17.444418],
-    'longitude': [78.486671, 78.348397],
-    'alert_level': ['red', 'yellow'],
-    'location': ['Location A', 'Location B']
-})
-    
-    # Debug: Print DataFrame to verify coordinates
-    st.write("Debug: Sample Data", df[["Latitude", "Longitude", "AlertLevel"]].head())  # Temporary debug
-    
-    # Map AlertLevel to sizes, colors, and styles with dark theme preference
-    df = df.copy()
-    df["MarkerColor"] = df["AlertLevel"].map({"Green": "green", "Yellow": "yellow", "Red": "red"})
-    df["MarkerSize"] = df["AlertLevel"].map({"Green": 20, "Yellow": 25, "Red": 35})
-    df["MarkerSymbol"] = df["AlertLevel"].map({"Green": "circle", "Yellow": "circle", "Red": "star"})
-    df["MarkerOpacity"] = df["AlertLevel"].map({"Green": 0.6, "Yellow": 0.8, "Red": 1.0})  # Higher opacity for red
-    
-    # Create scatter map with dark theme
-    fig = px.scatter_mapbox(
-        df,
-        lat="Latitude",
-        lon="Longitude",
-        color="AlertLevel",
-        color_discrete_map={"Green": "green", "Yellow": "yellow", "Red": "red"},
-        size="MarkerSize",
-        size_max=35,
-        zoom=15 if location == "Hyderabad" else 11,
-        hover_data={
-            "PoleID": True,
-            "RFID": True,
-            "Timestamp": True,
-            "AlertLevel": True,
-            "Anomalies": True,
-            "Zone": True,
-            "Latitude": False,
-            "Longitude": False
-        },
-        title=f"Pole Alert Map - {location}",
-        height=600
-    )
-    fig.update_traces(
-        marker=dict(
-            color=df["MarkerColor"],  # Explicitly set marker color
-            symbol=df["MarkerSymbol"],
-            opacity=df["MarkerOpacity"],
-            size=df["MarkerSize"]
-        )
-    )
-    fig.update_layout(
-        mapbox_style="dark",  # Changed to dark theme
-        margin={"r": 0, "t": 50, "l": 0, "b": 0},
-        showlegend=True,
-        legend=dict(
-            itemsizing="constant",
-            bgcolor="rgba(0, 0, 0, 0.7)",
-            font=dict(color="white"),
-            traceorder="normal"
-        )
-    )
-fig.update_layout(
-    mapbox=dict(
-        style="open-street-map",  # Base style
-        center=dict(lat=17.385044, lon=78.486671),
-        zoom=12  # Zoom to an appropriate level
-    )
-)
+    # Display the map in Streamlit
+    folium_static(map)
 
-fig.show()
-fig = go.Figure(go.Scattermapbox(
-    lat=df['latitude'],
-    lon=df['longitude'],
-    mode='markers',
-    marker=go.scattermapbox.Marker(
-        size=14,  # Increased size
-        color=df['alert_level'],  # Colors based on alert level
-        colorscale='YlOrRd',  # Set a color scale
-        opacity=0.9  # Increased opacity for visibility
-    ),
-    text=df['location'],
-))
-    st.plotly_chart(fig, use_container_width=True)
+def folium_static(map):
+    # This is a helper function to render Folium maps in Streamlit
+    from streamlit.components.v1 import html
+    html(map._repr_html_(), width=725, height=500)