Create visuals.py

modules/visuals.py

@@ -0,0 +1,49 @@
+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)