added f1 score

results/score_board.py

@@ -1,16 +1,12 @@
 import matplotlib.pyplot as plt
 
 
-def create_score_board(weeks=None, scores=None, save_path=None, show=False):
+def create_score_board(save_path=None, show=False):
     """
-    Create a score board plot for R^2 scores over weeks.
+    Create a score board plot for R^2 and F1 scores over assignments.
 
     Parameters
     ----------
-    weeks : list, optional
-        List of week numbers. Default is [0, 1, 2].
-    scores : list, optional
-        List of R^2 scores. Default is [0, 0.51, 0.59].
     save_path : str, optional
         Path to save the plot. If None, the plot is not saved.
     show : bool, optional
@@ -21,60 +17,95 @@ def create_score_board(weeks=None, scores=None, save_path=None, show=False):
     fig : matplotlib.figure.Figure
         The generated figure object.
     """
-    if weeks is None:
-        weeks = [0, 1, 2, 3, 4, 5]
-    if scores is None:
-        # Week 0: Start, Week 1: A2 baseline, Week 2: A2 outlier removal
-        # Week 3: A4 Random Forest, Week 4: A5 Weighted Ensemble, Week 5: A5b (champion retained)
-        scores = [0, 0.52, 0.59, 0.65, 0.7204, 0.7204]
-
-    # Create figure and axis
-    fig, ax = plt.subplots(figsize=(8, 6))
-
-    # Plot the data
-    ax.plot(
-        weeks,
-        scores,
+    # Assignment progression
+    assignments = ['Start', 'A2', 'A3', 'A4', 'A5', 'A5b/A6']
+    
+    # R² Score progression (Regression)
+    # Start=0, A2 baseline=0.52, A2 outliers=0.59, A4 RF=0.65, A5 Ensemble=0.7204, A5b retained
+    r2_scores = [0, 0.52, 0.59, 0.65, 0.7204, 0.7204]
+    
+    # F1 Score progression (Classification)
+    # Start=0, A2=N/A(0), A3 LDA=0.57, A4 RF=0.6110, A5 Ensemble=0.6484, A6 retained
+    f1_scores = [0, 0, 0.57, 0.6110, 0.6484, 0.6484]
+
+    # Create figure with 2 subplots
+    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 6))
+    
+    x_pos = range(len(assignments))
+
+    # Plot R² scores
+    ax1.plot(
+        x_pos,
+        r2_scores,
         marker='o',
         linestyle='-',
-        color='b',
+        color='#4361ee',
         linewidth=2,
-        markersize=8
+        markersize=10
     )
-
-    # Set labels and title
-    ax.set_xlabel('Week', fontsize=12)
-    ax.set_ylabel('R^2 Score', fontsize=12)
-    ax.set_title(
-        'R^2 Score Progression Over Weeks',
+    ax1.set_xlabel('Assignment', fontsize=12)
+    ax1.set_ylabel('R² Score', fontsize=12)
+    ax1.set_title(
+        'Regression: R² Score Progression',
         fontsize=14,
         fontweight='bold'
     )
+    ax1.set_xticks(x_pos)
+    ax1.set_xticklabels(assignments)
+    ax1.set_ylim(0, 0.85)
+    ax1.grid(True, linestyle='--', alpha=0.7)
+    ax1.axhline(y=0.7204, color='green', linestyle=':', alpha=0.5, label='Champion')
+    
+    for i, (x, y) in enumerate(zip(x_pos, r2_scores)):
+        ax1.annotate(
+            f'{y:.2f}' if y > 0 else '',
+            (x, y),
+            textcoords="offset points",
+            xytext=(0, 10),
+            ha='center',
+            fontweight='bold'
+        )
 
-    # Set x-axis ticks to be exactly the weeks
-    ax.set_xticks(weeks)
-    ax.set_xticklabels([f'Week {w}' for w in weeks])
-
-    # Add grid for better readability
-    ax.grid(True, linestyle='--', alpha=0.7)
-
-    # Annotate each point with its score
-    for i, (x, y) in enumerate(zip(weeks, scores)):
-        ax.annotate(
-            f'{y:.2f}',
+    # Plot F1 scores
+    ax2.plot(
+        x_pos,
+        f1_scores,
+        marker='s',
+        linestyle='-',
+        color='#06d6a0',
+        linewidth=2,
+        markersize=10
+    )
+    ax2.set_xlabel('Assignment', fontsize=12)
+    ax2.set_ylabel('F1 Score (weighted)', fontsize=12)
+    ax2.set_title(
+        'Classification: F1 Score Progression',
+        fontsize=14,
+        fontweight='bold'
+    )
+    ax2.set_xticks(x_pos)
+    ax2.set_xticklabels(assignments)
+    ax2.set_ylim(0, 0.85)
+    ax2.grid(True, linestyle='--', alpha=0.7)
+    ax2.axhline(y=0.6484, color='green', linestyle=':', alpha=0.5, label='Champion')
+    
+    for i, (x, y) in enumerate(zip(x_pos, f1_scores)):
+        ax2.annotate(
+            f'{y:.2f}' if y > 0 else '',
             (x, y),
             textcoords="offset points",
             xytext=(0, 10),
-            ha='center'
+            ha='center',
+            fontweight='bold'
         )
 
-    # Adjust layout to prevent clipping
+    # Adjust layout
+    fig.suptitle('Model Performance Progression', fontsize=16, fontweight='bold', y=1.02)
     fig.tight_layout()
 
     # Save the plot if save_path is provided
     if save_path is not None:
-        # we save it into the main directory
-        fig.savefig(save_path, dpi=300)
+        fig.savefig(save_path, dpi=300, bbox_inches='tight')
         print(f"Plot saved to {save_path}")
 
     # Show the plot if requested
@@ -85,5 +116,5 @@ def create_score_board(weeks=None, scores=None, save_path=None, show=False):
 
 
 if __name__ == "__main__":
-    # Example usage with default data
+    # Generate the score board
     fig = create_score_board(save_path='score_board.png', show=True)