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

def show_fault_map(df):
    # Filter valid location rows
    df_map = df.dropna(subset=["Location_Latitude__c", "Location_Longitude__c"]).copy()

    # Define color mapping for alert levels
    alert_color_map = {
        "High": "red",
        "Medium": "yellow",
        "Low": "green",
        "Normal": "green",
        "City": "blue"
    }

    # Apply color mapping
    df_map["Color"] = df_map["Alert_Level__c"].map(alert_color_map).fillna("gray")

    # Add fixed city markers
    fixed_cities = pd.DataFrame([
        {"Name": "Hyderabad", "Location_Latitude__c": 17.3850, "Location_Longitude__c": 78.4867, "Alert_Level__c": "City", "Color": "blue"},
        {"Name": "Ballari",   "Location_Latitude__c": 15.1394, "Location_Longitude__c": 76.9214, "Alert_Level__c": "City", "Color": "blue"},
        {"Name": "Gadwal",    "Location_Latitude__c": 16.2333, "Location_Longitude__c": 77.8000, "Alert_Level__c": "City", "Color": "blue"},
        {"Name": "Warangal",  "Location_Latitude__c": 17.9784, "Location_Longitude__c": 79.5941, "Alert_Level__c": "City", "Color": "blue"},
    ])

    df_map_combined = pd.concat([df_map, fixed_cities], ignore_index=True)

    # Define map center (around Telangana/Karnataka)
    map_center = {"lat": 16.5, "lon": 78.0}

    # Plot map
    fig = px.scatter_mapbox(
        df_map_combined,
        lat="Location_Latitude__c",
        lon="Location_Longitude__c",
        hover_name="Name",
        color="Color",
        color_discrete_map="identity",
        zoom=7,
        center=map_center,
        mapbox_style="open-street-map"
    )

    st.subheader("🗺️ Pole Locations with Fault Levels")
    st.plotly_chart(fig, use_container_width=True)

    # Optional: Add legend explanation
    with st.expander("🟢 Legend"):
        st.markdown("""
        - 🔴 **Red** = High Alert  
        - 🟡 **Yellow** = Medium Alert  
        - 🟢 **Green** = Low/Normal  
        - 🔵 **Blue** = Fixed Cities  
        - ⚪ **Gray** = Unknown
        """)