Update app.py

app.py

@@ -46,84 +46,33 @@ shap_values = explainer(df[columns])
 
 # Define functions for Gradio
 
-def get_shap_summary():
-    """Generates SHAP summary plot."""
-    plt.figure()
-    shap.summary_plot(shap_values, df[columns], feature_names=columns, show=False)
-    plt.savefig("shap_summary.png")
-    return "shap_summary.png"
-
-def get_shap_waterfall(index):
-    """Generates SHAP waterfall plot for a specific data point."""
-    specific_index = int(index)
-    plt.figure()
-    shap.waterfall_plot(
-        shap.Explanation(
-            values=shap_values.values[specific_index],
-            base_values=shap_values.base_values[specific_index],
-            data=df.iloc[specific_index],
-            feature_names=columns
-        )
-    )
-    plt.savefig("shap_waterfall.png")
-    return "shap_waterfall.png"
-
-def get_scatter_plot(feature1, feature2):
-    """Generates scatter plot for two features."""
-    plt.figure(figsize=(8, 6))
-    plt.scatter(
-        df[feature1],
-        df[feature2],
-        c=(df["Anomaly_Label"] == "Anomaly"),
-        cmap="coolwarm",
-        edgecolor="k",
-        alpha=0.7
-    )
-    plt.title(f"Isolation Forest - {feature1} vs {feature2}")
-    plt.xlabel(feature1)
-    plt.ylabel(feature2)
-    plt.savefig("scatter_plot.png")
-    return "scatter_plot.png"
-
 def get_anomaly_samples():
     """Returns formatted top, middle, and bottom 10 records based on anomaly score."""
     sorted_df = df.sort_values("Anomaly_Score", ascending=False)
-    top_10 = sorted_df.head(10)
-    middle_10 = sorted_df.iloc[len(sorted_df) // 2 - 5: len(sorted_df) // 2 + 5]
-    bottom_10 = sorted_df.tail(10)
+    # Top 10 anomalies
+    top_10 = sorted_df[sorted_df["Anomaly_Label"] == "Anomaly"].head(10)
+    # Middle 10 (mixed records)
+    mid_start = len(sorted_df) // 2 - 5
+    middle_10 = sorted_df.iloc[mid_start: mid_start + 10]
+    # Bottom 10 normal records
+    bottom_10 = sorted_df[sorted_df["Anomaly_Label"] == "Normal"].tail(10)
     return top_10, middle_10, bottom_10
 
 # Create Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Isolation Forest Anomaly Detection")
     
-    with gr.Tab("SHAP Summary"):
-        gr.Markdown("### Global Explainability: SHAP Summary Plot")
-        shap_button = gr.Button("Generate SHAP Summary Plot")
-        shap_image = gr.Image()
-        shap_button.click(get_shap_summary, outputs=shap_image)
-    
-    with gr.Tab("SHAP Waterfall"):
-        gr.Markdown("### Local Explainability: SHAP Waterfall Plot")
-        index_input = gr.Number(label="Data Point Index", value=0)
-        shap_waterfall_button = gr.Button("Generate SHAP Waterfall Plot")
-        shap_waterfall_image = gr.Image()
-        shap_waterfall_button.click(get_shap_waterfall, inputs=index_input, outputs=shap_waterfall_image)
-    
-    with gr.Tab("Feature Scatter Plot"):
-        gr.Markdown("### Feature Interaction: Scatter Plot")
-        feature1_dropdown = gr.Dropdown(choices=columns, label="Feature 1")
-        feature2_dropdown = gr.Dropdown(choices=columns, label="Feature 2")
-        scatter_button = gr.Button("Generate Scatter Plot")
-        scatter_image = gr.Image()
-        scatter_button.click(get_scatter_plot, inputs=[feature1_dropdown, feature2_dropdown], outputs=scatter_image)
-
     with gr.Tab("Anomaly Samples"):
-        gr.Markdown("### Anomaly Samples")
-        anomaly_samples_button = gr.Button("Show Anomaly Samples")
+        gr.Markdown("<h3 style='text-align: center; font-size: 18px; font-weight: bold;'>Top 10 Records (Anomalies)</h3>", unsafe_allow_html=True)
         top_table = gr.Dataframe(label="Top 10 Records")
+        
+        gr.Markdown("<h3 style='text-align: center; font-size: 18px; font-weight: bold;'>Middle 10 Records (Mixed)</h3>", unsafe_allow_html=True)
         middle_table = gr.Dataframe(label="Middle 10 Records")
+        
+        gr.Markdown("<h3 style='text-align: center; font-size: 18px; font-weight: bold;'>Bottom 10 Records (Normal)</h3>", unsafe_allow_html=True)
         bottom_table = gr.Dataframe(label="Bottom 10 Records")
+        
+        anomaly_samples_button = gr.Button("Show Anomaly Samples")
         anomaly_samples_button.click(
             get_anomaly_samples, 
             outputs=[top_table, middle_table, bottom_table]