Update visualization.py

visualization.py

@@ -200,22 +200,24 @@ def plot_posture(df, posture_scores, color='blue', anomaly_threshold=3):
     plt.close()
     return fig
 
-def create_kdeplot(df, mse_embeddings, mse_posture):
+def create_kdeplot(df):
     plt.figure(figsize=(10, 6), dpi=300)
-    df['MSE_Embeddings'] = mse_embeddings
-    df['MSE_Posture'] = mse_posture
-    sns.kdeplot(data=df, x='MSE_Embeddings', y='MSE_Posture', cmap="YlOrRd", shade=True, cbar=True)
-    plt.xlabel('Facial Features MSE')
-    plt.ylabel('Body Posture MSE')
-    plt.title('KDE Plot of Facial Features vs Body Posture MSE')
+    scatter = plt.scatter(df['Timecode_Seconds'], df['Timecode_Seconds'], 
+                          c=df['MSE_Combined'], cmap='YlOrRd', alpha=0.5)
+    plt.colorbar(scatter, label='Combined MSE')
+    plt.xlabel('Facial Features Timecode')
+    plt.ylabel('Body Posture Timecode')
+    plt.title('Scatter Plot of Facial Features vs Body Posture Timecodes (Color: Combined MSE)')
     plt.close()
     return plt.gcf()
 
-def create_jointplot(df, mse_embeddings, mse_posture):
+def create_jointplot(df):
     plt.figure(figsize=(10, 6), dpi=300)
-    df['MSE_Embeddings'] = mse_embeddings
-    df['MSE_Posture'] = mse_posture
-    joint_plot = sns.jointplot(data=df, x='MSE_Embeddings', y='MSE_Posture', kind='hex', cmap="YlOrRd")
-    joint_plot.fig.suptitle('Joint Plot of Facial Features vs Body Posture MSE', y=1.02)
+    joint_plot = sns.jointplot(data=df, x='Timecode_Seconds', y='Timecode_Seconds', 
+                               kind='scatter', hue='MSE_Combined', palette='YlOrRd', 
+                               joint_kws={'alpha': 0.5})
+    joint_plot.fig.suptitle('Joint Plot of Facial Features vs Body Posture Timecodes (Color: Combined MSE)', y=1.02)
+    plt.xlabel('Facial Features Timecode')
+    plt.ylabel('Body Posture Timecode')
     plt.close()
     return joint_plot.fig