saving

app/services/graph_generator.py

@@ -1310,15 +1310,19 @@ class GraphGenerator:
         self,
         data: list[list],
         columns: list[str],
+        vo2_max_value: float = None,
+        category: str = None,
         cell_colors: list[list[str]] = None,
         save_as_base64: bool = True,
     ) -> str:
         """
-        Generate VO2 Max table as an image with optimized sizing.
+        Generate VO2 Max table as an image with optimized sizing, highlighting the patient's category.
 
         Args:
             data: List of rows (each row is a list of values)
             columns: List of column headers
+            vo2_max_value: Patient's VO2 max value (for title and arrow)
+            category: Category that the patient falls into (e.g., 'Good', 'Excellent')
             cell_colors: Optional matrix of cell colors
             save_as_base64: If True, return base64 string
 
@@ -1327,12 +1331,11 @@ class GraphGenerator:
         """
         import io
 
-        # Fixed optimal sizing for VO2 Max table (8 columns, 1 data row)
-        fig, ax = plt.subplots(figsize=(16, 2.5))
-        ax.axis("off")
+        from matplotlib.patches import FancyArrowPatch, RegularPolygon
 
-        # Even column widths for VO2 Max table
-        col_widths = [1.0 / len(columns)] * len(columns)
+        # Fixed optimal sizing for VO2 Max table (7 columns, 1 data row)
+        fig, ax = plt.subplots(figsize=(14, 3))
+        ax.axis("off")
 
         # Create table
         table = ax.table(
@@ -1340,33 +1343,87 @@ class GraphGenerator:
             colLabels=columns,
             cellLoc="center",
             loc="center",
-            colColours=["#4dd0e1"] * len(columns),
-            colWidths=col_widths,
+            bbox=[0, 0, 1, 1],
         )
 
         # Style the table
         table.auto_set_font_size(False)
         table.set_fontsize(11)
-        table.scale(1, 3.0)
+        table.scale(1, 2.5)
 
-        # Apply cell colors
-        if cell_colors:
-            for i, row_colors in enumerate(cell_colors):
-                for j, color in enumerate(row_colors):
-                    if color and j < len(columns):
-                        cell = table[(i + 1, j)]
-                        cell.set_facecolor(color)
+        # Header row styling (cyan background)
+        for i in range(len(columns)):
+            cell = table[(0, i)]
+            cell.set_facecolor("#7dd3fc")  # cyan-300 equivalent
+            cell.set_text_props(weight="bold", color="black", fontsize=12)
+            cell.set_edgecolor("#9ca3af")  # gray-400
+            cell.set_linewidth(1)
 
-        # Style all cells
-        for (row, col), cell in table.get_celld().items():
-            if row == 0:
-                cell.set_text_props(weight="bold", fontsize=12)
-                cell.set_edgecolor("#333333")
-                cell.set_linewidth(1.5)
+        # Find the column index for the category (if provided)
+        category_index = None
+        if category and category in columns:
+            category_index = columns.index(category)
+
+        # Data row styling
+        for i in range(len(data[0])):
+            cell = table[(1, i)]
+            if i == 0:  # Age column
+                cell.set_facecolor("#a5f3fc")  # cyan-200
+                cell.set_text_props(weight="semibold", color="black", fontsize=11)
             else:
-                cell.set_edgecolor("#666666")
-                cell.set_linewidth(1.0)
-                cell.set_text_props(fontsize=10)
+                cell.set_facecolor("#f3f4f6")  # gray-100
+                cell.set_text_props(color="black", fontsize=10)
+                # Bold the cell that corresponds to the patient's category
+                if category_index is not None and i == category_index:
+                    cell.set_text_props(weight="bold", color="black", fontsize=11)
+            cell.set_edgecolor("#9ca3af")  # gray-400
+            cell.set_linewidth(1)
+
+        # Add arrow indicator below the category column
+        if category_index is not None:
+            # Calculate position
+            cell_width = 1.0 / len(columns)
+            arrow_x = (category_index + 0.5) * cell_width
+
+            # Draw arrow pointing up
+            arrow = FancyArrowPatch(
+                (arrow_x, -0.15),
+                (arrow_x, -0.05),
+                arrowstyle="->",
+                mutation_scale=20,
+                linewidth=2,
+                color="black",
+                transform=ax.transAxes,
+            )
+            ax.add_patch(arrow)
+
+            # Add triangle at the top
+            triangle = RegularPolygon(
+                (arrow_x, -0.05),
+                3,
+                radius=0.02,
+                orientation=np.pi / 2,
+                color="black",
+                transform=ax.transAxes,
+            )
+            ax.add_patch(triangle)
+
+        # Set title - calculate approximate percentile
+        if vo2_max_value is not None:
+            if category == "Superior":
+                percentile = "100th percentile"
+            else:
+                percentile_map = {
+                    "Very Poor": "1st-10th percentile",
+                    "Poor": "10th-20th percentile",
+                    "Fair": "20th-40th percentile",
+                    "Good": "40th-60th percentile",
+                    "Excellent": "60th-80th percentile",
+                }
+                percentile = percentile_map.get(category, "N/A")
+
+            title = f"VO2 Max - {vo2_max_value:.1f} ({percentile})"
+            ax.set_title(title, fontsize=14, fontweight="bold", pad=20)
 
         if save_as_base64:
             buf = io.BytesIO()