Update app.py

app.py

@@ -1,128 +1,32 @@
-import random
-import pandas as pd
-import streamlit as st
-import pydeck as pdk
-from datetime import datetime, timedelta
-
-# ---- Constants ----
-POLES_PER_SITE = 12
-SITES = {
-    "Hyderabad": [17.385044, 78.486671],
-    "Gadwal": [16.2351, 77.8052],
-    "Kurnool": [15.8281, 78.0373],
-    "Ballari": [12.9716, 77.5946]
-}
-
-# ---- Helper Functions ----
-def generate_location(base_lat, base_lon):
-    return [
-        base_lat + random.uniform(-0.02, 0.02),
-        base_lon + random.uniform(-0.02, 0.02)
-    ]
-
-def simulate_pole(pole_id, site_name):
-    lat, lon = generate_location(*SITES[site_name])
-    solar_kwh = round(random.uniform(3.0, 7.5), 2)
-    wind_kwh = round(random.uniform(0.5, 2.0), 2)
-    power_required = round(random.uniform(4.0, 8.0), 2)
-    total_power = solar_kwh + wind_kwh
-    power_status = 'Sufficient' if total_power >= power_required else 'Insufficient'
-
-    tilt_angle = round(random.uniform(0, 45), 2)
-    vibration = round(random.uniform(0, 5), 2)
-    camera_status = random.choice(['Online', 'Offline'])
-
-    alert_level = 'Green'
-    anomaly_details = []
-    if tilt_angle > 30 or vibration > 3:
-        alert_level = 'Yellow'
-        anomaly_details.append("Tilt or Vibration threshold exceeded.")
-    if tilt_angle > 40 or vibration > 4.5:
-        alert_level = 'Red'
-        anomaly_details.append("Critical tilt or vibration detected.")
-
-    health_score = max(0, 100 - (tilt_angle + vibration * 10))
-    timestamp = datetime.now() - timedelta(hours=random.randint(0, 6))
-
-    return {
-        'Pole ID': f'{site_name[:3].upper()}-{pole_id:03}',
-        'Site': site_name,
-        'Latitude': lat,
-        'Longitude': lon,
-        'Solar (kWh)': solar_kwh,
-        'Wind (kWh)': wind_kwh,
-        'Power Required (kWh)': power_required,
-        'Total Power (kWh)': total_power,
-        'Power Status': power_status,
-        'Tilt Angle (°)': tilt_angle,
-        'Vibration (g)': vibration,
-        'Camera Status': camera_status,
-        'Health Score': round(health_score, 2),
-        'Alert Level': alert_level,
-        'Anomalies': "; ".join(anomaly_details),
-        'Last Checked': timestamp.strftime('%Y-%m-%d %H:%M:%S')
-    }
-
-# ---- Streamlit UI ----
-st.set_page_config(page_title="Smart Pole Monitoring", layout="wide")
-st.title("🌍 Smart Renewable Pole Monitoring - Multi-Site")
-
-selected_site = st.text_input("Enter site to view (Hyderabad, Gadwal, Kurnool, Ballari):", "Hyderabad")
-
-if selected_site in SITES:
-    with st.spinner(f"Simulating poles at {selected_site}..."):
-        poles_data = [simulate_pole(i + 1, site) for site in SITES for i in range(POLES_PER_SITE)]
-        df = pd.DataFrame(poles_data)
-        site_df = df[df['Site'] == selected_site]
-
-    # Summary Metrics
-    col1, col2, col3 = st.columns(3)
-    col1.metric("Total Poles", site_df.shape[0])
-    col2.metric("Red Alerts", site_df[site_df['Alert Level'] == 'Red'].shape[0])
-    col3.metric("Power Insufficiencies", site_df[site_df['Power Status'] == 'Insufficient'].shape[0])
-
-    # Table View
-    st.subheader(f"📋 Pole Data Table for {selected_site}")
-    with st.expander("Filter Options"):
-        alert_filter = st.multiselect("Alert Level", options=site_df['Alert Level'].unique(), default=site_df['Alert Level'].unique())
-        camera_filter = st.multiselect("Camera Status", options=site_df['Camera Status'].unique(), default=site_df['Camera Status'].unique())
-
-    filtered_df = site_df[(site_df['Alert Level'].isin(alert_filter)) & (site_df['Camera Status'].isin(camera_filter))]
-    st.dataframe(filtered_df, use_container_width=True)
-
-    # Charts
-    st.subheader("📊 Energy Generation Comparison")
-    st.bar_chart(site_df[['Solar (kWh)', 'Wind (kWh)']].mean())
-
-    st.subheader("📈 Tilt vs. Vibration")
-    st.scatter_chart(site_df[['Tilt Angle (°)', 'Vibration (g)']])
-
-    # Map with Red Alerts
-    st.subheader("📍 Red Alert Pole Locations")
-    red_df = site_df[site_df['Alert Level'] == 'Red']
-    if not red_df.empty:
-        st.pydeck_chart(pdk.Deck(
-            initial_view_state=pdk.ViewState(
-                latitude=SITES[selected_site][0],
-                longitude=SITES[selected_site][1],
-                zoom=12,
-                pitch=50
-            ),
-            layers=[
-                pdk.Layer(
-                    'ScatterplotLayer',
-                    data=red_df,
-                    get_position='[Longitude, Latitude]',
-                    get_color='[255, 0, 0, 160]',
-                    get_radius=100,
-                )
-            ]
-        ))
-        st.markdown("<h3 style='text-align: center;'>Red Alert Poles are Blinking</h3>", unsafe_allow_html=True)
+# Map with Alert Level Color Coding
+st.subheader("📍 Pole Alert Levels (Green, Yellow, Red)")
+
+def alert_level_to_color(level):
+    if level == 'Red':
+        return [255, 0, 0, 160]      # Red
+    elif level == 'Yellow':
+        return [255, 255, 0, 160]    # Yellow
     else:
-        st.info("No red alerts at this time.")
-
-else:
-    st.warning("Invalid site. Please enter one of: Hyderabad, Gadwal, Kurnool, Ballari")
-
-
+        return [0, 255, 0, 160]      # Green
+
+# Apply color mapping
+site_df['Color'] = site_df['Alert Level'].apply(alert_level_to_color)
+
+st.pydeck_chart(pdk.Deck(
+    initial_view_state=pdk.ViewState(
+        latitude=SITES[selected_site][0],
+        longitude=SITES[selected_site][1],
+        zoom=12,
+        pitch=50
+    ),
+    layers=[
+        pdk.Layer(
+            'ScatterplotLayer',
+            data=site_df,
+            get_position='[Longitude, Latitude]',
+            get_color='Color',
+            get_radius=100,
+        )
+    ]
+))
+st.markdown("<h3 style='text-align: center;'>Poles Color-coded by Alert Level</h3>", unsafe_allow_html=True)