import streamlit as st
import plotly.express as px
import pandas as pd

def display_dashboard(df):
    st.subheader("📊 System Summary")
    col1, col2, col3, col4 = st.columns(4)
    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])
    col4.metric("📍 Sites", len(df['Site'].unique()))

def display_charts(df):
    st.subheader("⚙️ Energy Generation Trends")
    st.bar_chart(df.groupby("Site")[["SolarGen(kWh)", "WindGen(kWh)"]].mean())
    st.subheader("📉 Tilt vs Vibration")
    st.scatter_chart(df.rename(columns={"Tilt(°)": "Tilt", "Vibration(g)": "Vibration"}).set_index("PoleID")[["Tilt", "Vibration"]])

def display_heatmap(df):
    st.subheader("🌡️ Alert Heatmap by Site")
    # Map AlertLevel to numeric values for heatmap intensity
    alert_map = {"Green": 1, "Yellow": 2, "Red": 3}
    df["AlertValue"] = df["AlertLevel"].map(alert_map)
    
    # Create heatmap using Plotly
    fig = px.density_heatmap(
        df,
        x="XCoord",
        y="YCoord",
        z="AlertValue",
        color_continuous_scale=["green", "yellow", "red"],
        title="Alert Intensity Heatmap Across Sites",
        labels={"XCoord": "Site Zone X", "YCoord": "Site Zone Y", "AlertValue": "Alert Intensity"},
        nbinsx=20,
        nbinsy=20
    )
    
    # Add site boundaries for zoning
    site_boundaries = {
        "Hyderabad": (0, 10),
        "Ballari": (10, 20),
        "Kurnool": (20, 30),
        "Gadwal": (30, 40)
    }
    for site, (x_min, x_max) in site_boundaries.items():
        fig.add_vline(x=x_min, line_dash="dash", line_color="white")
        fig.add_annotation(x=(x_min + x_max) / 2, y=10, text=site, showarrow=False, font=dict(color="white"))
    
    st.plotly_chart(fig, use_container_width=True)