Update app.py

app.py

@@ -56,20 +56,23 @@ def main():
                 plot_prediction_graphs(all_data)
 
 def plot_prediction_graphs(data):
-    # Function to plot graphs for predictions
+    # Function to plot graphs for predictions, divided by prediction value
     for model_name in models.keys():
-        plt.figure(figsize=(10, 4))
-        predictions = {seq: values[model_name][1] for seq, values in data.items()}  # Using confidence for ordering
-        # Sorting sequences based on confidence, descending
-        sorted_sequences = sorted(predictions.items(), key=lambda x: x[1], reverse=True)
-        sequences = [x[0] for x in sorted_sequences]
-        conf_values = [x[1] for x in sorted_sequences]
-        sns.barplot(x=sequences, y=conf_values, palette="viridis")
-        plt.title(f'Confidence Scores for {model_name.capitalize()} Model')
-        plt.xlabel('Sequences')
-        plt.ylabel('Confidence')
-        plt.xticks(rotation=45)  # Rotate x labels for better visibility
-        st.pyplot(plt)  # Display each plot below the results table
+        fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6), sharey=True)
+        for prediction_val in [0, 1]:
+            ax = ax1 if prediction_val == 0 else ax2
+            filtered_data = {seq: values[model_name] for seq, values in data.items() if values[model_name][0] == prediction_val}
+            # Sorting sequences based on confidence, descending
+            sorted_sequences = sorted(filtered_data.items(), key=lambda x: x[1][1], reverse=True)
+            sequences = [x[0] for x in sorted_sequences]
+            conf_values = [x[1][1] for x in sorted_sequences]
+            sns.barplot(x=sequences, y=conf_values, palette="coolwarm" if prediction_val == 0 else "cubehelix", ax=ax)
+            ax.set_title(f'Confidence Scores for {model_name.capitalize()} (Prediction {prediction_val})')
+            ax.set_xlabel('Sequences')
+            ax.set_ylabel('Confidence')
+            ax.tick_params(axis='x', rotation=45)  # Rotate x labels for better visibility
+
+        st.pyplot(fig)  # Display the plot with two subplots below the results table
 
 if __name__ == "__main__":
     main()