modules/visuals.py

import streamlit as st
import matplotlib.pyplot as plt

def display_dashboard(df):
    """
    Display system-wide summary metrics on the dashboard.
    
    :param df: DataFrame containing the pole data.
    """
    st.subheader("📊 System Summary")

    # Columns to display different metrics
    col1, col2, col3 = st.columns(3)

    # Total Poles
    col1.metric("Total Poles", df.shape[0])

    # Red Alerts
    col2.metric("🚨 Red Alerts", df[df['Alert Level'] == "Red"].shape[0])

    # Power Insufficiency Issues
    col3.metric("⚡ Power Issues", df[df['Power Sufficient'] == "No"].shape[0])

def display_charts(df):
    """
    Display charts for energy generation and tilt vs vibration.
    
    :param df: DataFrame containing the pole data.
    """
    st.subheader("⚙️ Energy Generation Trends")

    # Plot bar chart for Solar and Wind Generation
    fig, ax = plt.subplots(figsize=(10, 6))
    df.set_index("Pole ID")[["Solar Gen (kWh)", "Wind Gen (kWh)"]].plot(kind="bar", ax=ax)
    ax.set_ylabel("Energy Generation (kWh)")
    ax.set_xlabel("Pole ID")
    st.pyplot(fig)

    st.subheader("📉 Tilt vs Vibration")

    # Plot scatter chart for Tilt vs Vibration
    fig, ax = plt.subplots(figsize=(10, 6))
    ax.scatter(df["Tilt (°)"], df["Vibration (g)"], color='blue')
    ax.set_xlabel("Tilt (°)")
    ax.set_ylabel("Vibration (g)")
    st.pyplot(fig)