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": [15.1394, 76.9214]
}

# ---- Set Page Config (Must be first Streamlit command) ----
st.set_page_config(page_title="Smart Pole Monitoring", layout="wide")

# ---- Custom CSS for Advanced UI ----
st.markdown("""
    <style>
    .stApp {
        background-color: #f5f7fa;
    }
    .metric-card {
        background-color: white;
        padding: 15px;
        border-radius: 10px;
        box-shadow: 0 4px 8px rgba(0,0,0,0.1);
        text-align: center;
    }
    .red-alert {
        background-color: #ffe6e6;
        color: #d32f2f;
        padding: 10px;
        border-radius: 5px;
        font-weight: bold;
    }
    .sidebar .sidebar-content {
        background-color: #ffffff;
        border-right: 1px solid #e0e0e0;
    }
    h1, h2, h3 {
        color: #1a237e;
    }
    </style>
""", unsafe_allow_html=True)

# ---- 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'])

    # Anomaly detection
    anomalies = []
    if solar_kwh < 4.0:
        anomalies.append("Low Solar Output")
    if wind_kwh < 0.7:
        anomalies.append("Low Wind Output")
    if tilt_angle > 30:
        anomalies.append("Pole Tilt Risk")
    if vibration > 3:
        anomalies.append("Vibration Alert")
    if camera_status == 'Offline':
        anomalies.append("Camera Offline")
    if power_status == 'Insufficient':
        anomalies.append("Power Insufficient")

    # Alert level logic
    alert_level = 'Green'
    if anomalies:
        if tilt_angle > 40 or vibration > 4.5 or len(anomalies) > 1:
            alert_level = 'Red'
        else:
            alert_level = 'Yellow'

    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(anomalies) if anomalies else 'None',
        'Last Checked': timestamp.strftime('%Y-%m-%d %H:%M:%S')
    }

# ---- Streamlit UI ----
st.title("🌍 Smart Renewable Pole Monitoring - Multi-Site")

# Sidebar with enhanced controls
with st.sidebar:
    st.header("🛠️ Control Panel")
    with st.expander("Site Selection", expanded=True):
        selected_site = st.selectbox(
            "Select Site",
            options=list(SITES.keys()),
            index=0,
            help="Choose a site to monitor poles."
        )
    with st.expander("Simulation Settings"):
        num_poles = st.slider("Number of Poles per Site", 5, 50, POLES_PER_SITE)
        simulate_faults = st.checkbox("Simulate Faults", value=True)
    with st.expander("Filters"):
        alert_filter = st.multiselect(
            "Alert Level",
            options=['Green', 'Yellow', 'Red'],
            default=['Green', 'Yellow', 'Red']
        )
        camera_filter = st.multiselect(
            "Camera Status",
            options=['Online', 'Offline'],
            default=['Online', 'Offline']
        )

# Simulate data
if selected_site in SITES:
    with st.spinner(f"Simulating {num_poles} poles at {selected_site}..."):
        poles_data = [simulate_pole(i + 1, site) for site in SITES for i in range(num_poles)]
        df = pd.DataFrame(poles_data)
        site_df = df[df['Site'] == selected_site]

    # Tabs for different views
    tab1, tab2, tab3, tab4 = st.tabs(["📊 Dashboard", "📋 Data Table", "📈 Charts", "📍 Map"])

    with tab1:
        # Dashboard with metrics
        st.subheader("System Overview")
        red_alerts_count = site_df[site_df['Alert Level'] == 'Red'].shape[0]
        if red_alerts_count > 0:
            st.markdown(f"<div class='red-alert'>🚨 {red_alerts_count} Red Alerts Detected! Immediate Action Required!</div>", unsafe_allow_html=True)
        else:
            st.success("✅ No Red Alerts Detected")

        col1, col2, col3, col4 = st.columns(4)
        with col1:
            st.markdown("<div class='metric-card'>", unsafe_allow_html=True)
            st.metric("Total Poles", site_df.shape[0])
            st.markdown("</div>", unsafe_allow_html=True)
        with col2:
            st.markdown("<div class='metric-card'>", unsafe_allow_html=True)
            st.metric("Red Alerts", red_alerts_count, delta_color="inverse")
            st.markdown("</div>", unsafe_allow_html=True)
        with col3:
            st.markdown("<div class='metric-card'>", unsafe_allow_html=True)
            st.metric("Power Insufficiencies", site_df[site_df['Power Status'] == 'Insufficient'].shape[0])
            st.markdown("</div>", unsafe_allow_html=True)
        with col4:
            st.markdown("<div class='metric-card'>", unsafe_allow_html=True)
            st.metric("Average Health Score", round(site_df['Health Score'].mean(), 2))
            st.markdown("</div>", unsafe_allow_html=True)

        # Red Alerts Summary
        red_df = site_df[site_df['Alert Level'] == 'Red']
        if not red_df.empty:
            st.subheader("🚨 Critical Red Alerts")
            st.dataframe(
                red_df[['Pole ID', 'Anomalies', 'Tilt Angle (°)', 'Vibration (g)', 'Power Status', 'Camera Status', 'Health Score', 'Last Checked']],
                use_container_width=True
            )
            csv = red_df.to_csv(index=False)
            st.download_button(
                label="Download Red Alerts CSV",
                data=csv,
                file_name=f"{selected_site}_red_alerts.csv",
                mime="text/csv"
            )

    with tab2:
        # Filtered Data Table
        st.subheader(f"Pole Data for {selected_site}")
        filtered_df = site_df[
            (site_df['Alert Level'].isin(alert_filter)) &
            (site_df['Camera Status'].isin(camera_filter))
        ]
        
        # Conditional formatting for red alerts
        def highlight_red_alerts(row):
            return ['background-color: #ffe6e6' if row['Alert Level'] == 'Red' else '' for _ in row]
        
        st.dataframe(
            filtered_df[['Pole ID', 'Anomalies', 'Solar (kWh)', 'Wind (kWh)', 'Power Status', 'Tilt Angle (°)', 'Vibration (g)', 'Camera Status', 'Health Score', 'Alert Level', 'Last Checked']].style.apply(highlight_red_alerts, axis=1),
            use_container_width=True
        )

    with tab3:
        # Charts
        st.subheader("Energy Generation Comparison")
        st.bar_chart(site_df[['Solar (kWh)', 'Wind (kWh)']].mean())

        st.subheader("Tilt vs. Vibration")
        scatter_data = site_df[['Tilt Angle (°)', 'Vibration (g)', 'Alert Level']].copy()
        scatter_data['color'] = scatter_data['Alert Level'].map({
            'Green': '[0, 255, 0, 160]',
            'Yellow': '[255, 255, 0, 160]',
            'Red': '[255, 0, 0, 160]'
        })
        st.scatter_chart(scatter_data[['Tilt Angle (°)', 'Vibration (g)']])

    with tab4:
        # Map with Red Alerts
        st.subheader("Red Alert Pole Locations")
        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,
                        pickable=True,
                        auto_highlight=True
                    )
                ],
                tooltip={
                    "html": "<b>Pole ID:</b> {Pole ID}<br><b>Anomalies:</b> {Anomalies}<br><b>Tilt:</b> {Tilt Angle (°)}°<br><b>Vibration:</b> {Vibration (g)}g<br><b>Health Score:</b> {Health Score}",
                    "style": {"backgroundColor": "white", "color": "#333"}
                }
            ))
        else:
            st.info("No red alerts at this time.")

else:
    st.error("Invalid site. Please enter one of: Hyderabad, Gadwal, Kurnool, Ballari")