Update app.py

app.py

@@ -39,26 +39,32 @@ def forecast_plot(hours):
 
     # Plot forecasted energy load
     plt.figure(figsize=(12,6))
-    plt.plot(forecast['ds_local'], forecast['yhat'], label='Forecast', color='orange')
-    plt.fill_between(forecast['ds_local'], forecast['yhat_lower'], forecast['yhat_upper'], alpha=0.3, color='orange', label='Confidence Interval')
-    plt.xlabel("Local Time (Europe/Berlin)")
-    plt.ylabel("Energy Load (MW)")
-    plt.title("⚡ German Energy Load Forecast (Zoomed into Future)")
+    plt.plot(forecast['ds_local'], forecast['yhat'], label='Forecast', color='#FF6347', linewidth=2)  # Orange-ish color
+    plt.fill_between(forecast['ds_local'], forecast['yhat_lower'], forecast['yhat_upper'], alpha=0.3, color='#FF6347')
+    plt.xlabel("Local Time (Europe/Berlin)", fontsize=12, fontweight='bold')
+    plt.ylabel("Energy Load (MW)", fontsize=12, fontweight='bold')
+    plt.title("⚡ German Energy Load Forecast (Zoomed into Future)", fontsize=16, fontweight='bold')
     plt.legend()
-    plt.grid(True)
+    plt.grid(True, linestyle='--', alpha=0.6)
+    plt.xticks(rotation=45)
     plt.tight_layout()
     plt.show()  # Show plot immediately
 
-    # Prepare the explanation text to highlight graph trends
-    explanation = (
-        f"**Forecast Highlights**:\n"
-        f"- **Peak Energy Demand**: {peak_demand:.2f} MW at {peak_time.strftime('%Y-%m-%d %H:%M:%S')}.\n"
-        f"- **Confidence Interval**: The forecasted energy load is expected to be between "
-        f"{lower_bound:.2f} MW and {upper_bound:.2f} MW.\n"
-        f"- The trend shows that the energy demand is expected to [increase/decrease], "
-        f"with a potential peak at the specified time.\n"
-    )
-    
+    # Prepare the explanation text with Markdown style formatting
+    explanation = f"""
+    ## 📊 **Forecast Highlights**
+    - **Peak Energy Demand**: {peak_demand:.2f} MW at **{peak_time.strftime('%Y-%m-%d %H:%M:%S')}**.
+    - **Confidence Interval**: The forecasted energy load is expected to be between 
+      **{lower_bound:.2f} MW** and **{upper_bound:.2f} MW**.
+    - The trend shows that the energy demand is expected to [increase/decrease], 
+      with a potential peak at the specified time.
+    \n\n
+    ## 🔍 **Key Observations**:
+    - The forecast suggests that **energy demand** will **reach its highest point** at **{peak_time.strftime('%H:%M')}**.
+    - This peak could be a critical time for grid management to prevent overloading.
+    - **Confidence interval** gives us a range, helping to understand the possible **fluctuations in demand**.
+    """
+
     # Return both the plot and explanation
     return plt, explanation
 
@@ -68,5 +74,6 @@ gr.Interface(
     inputs=gr.Slider(24, 168, step=24, label="Forecast Hours (1 to 7 days)"),
     outputs=[gr.Plot(), gr.Textbox()],
     title="⚡ Smart Energy Load Forecasting (Germany)",
-    description="Predict the energy demand using Facebook Prophet. Select the number of hours to forecast (1-7 days)."
-).launch()
+    description="Predict the energy demand using Facebook Prophet. Select the number of hours to forecast (1-7 days).",
+    theme="huggingface",  # You can add more themes if desired
+).launch()