feat: Enhance context generation with new table images for VO2 Max and Heart Rate Zones

- Added functionality to generate VO2 Max and Heart Rate Zones tables in the context_generator.py.
- Integrated graph_generator to create table images with specified data and styles.
- Updated report_generator.py to pass graph_generator to context generation.
- Introduced a new method in graph_generator.py to generate table images with customizable options.
- Created test scripts for Page 5 (RMR and NEAT calculations) and Page 6 (Meal Plan calculations) using actual patient data.
- Updated Jupyter notebook metadata for better environment identification.

app/services/graph_generator.py

@@ -1305,3 +1305,86 @@ class GraphGenerator:
         plt.close()
 
         return self._image_to_base64(chart_path) if save_as_base64 else str(chart_path)
+
+    def generate_table_image(
+        self,
+        data: list[list],
+        columns: list[str],
+        title: str = None,
+        col_widths: list[float] = None,
+        cell_colors: list[list[str]] = None,
+        header_color: str = "#4dd0e1",
+        save_as_base64: bool = True,
+    ) -> str:
+        """
+        Generate a table as an image.
+
+        Args:
+            data: List of rows (each row is a list of values)
+            columns: List of column headers
+            title: Optional title for the table
+            col_widths: Optional list of column widths
+            cell_colors: Optional matrix of cell colors (same shape as data)
+            header_color: Color for the header row
+            save_as_base64: If True, return base64 string
+
+        Returns:
+            Base64 string or file path
+        """
+        # Calculate figure size based on rows and columns
+        # Approximate height: header + rows
+        height = (len(data) + 1) * 0.5 + (0.5 if title else 0)
+        width = len(columns) * 2.5 if not col_widths else sum(col_widths) * 10
+
+        fig, ax = plt.subplots(figsize=(width, height))
+        ax.axis("off")
+
+        if title:
+            plt.title(title, pad=20, fontsize=14, fontweight="bold")
+
+        # Create table
+        table = ax.table(
+            cellText=data,
+            colLabels=columns,
+            cellLoc="center",
+            loc="center",
+            colColours=[header_color] * len(columns),
+        )
+
+        # Style the table
+        table.auto_set_font_size(False)
+        table.set_fontsize(10)
+        table.scale(1, 1.5)  # Increase row height
+
+        # Apply cell colors if provided
+        if cell_colors:
+            for i, row_colors in enumerate(cell_colors):
+                for j, color in enumerate(row_colors):
+                    if color:
+                        # (row_idx, col_idx) - row_idx starts at 1 for data (0 is header)
+                        cell = table[(i + 1, j)]
+                        cell.set_facecolor(color)
+
+        # Bold headers
+        for (row, col), cell in table.get_celld().items():
+            if row == 0:
+                cell.set_text_props(weight="bold")
+                cell.set_height(0.1)
+
+        plt.tight_layout()
+
+        if save_as_base64:
+            import io
+
+            buf = io.BytesIO()
+            plt.savefig(buf, format="png", bbox_inches="tight", dpi=300)
+            plt.close(fig)
+            buf.seek(0)
+            return base64.b64encode(buf.read()).decode("utf-8")
+        else:
+            output_path = (
+                self.charts_dir / f"table_{pd.Timestamp.now().timestamp()}.png"
+            )
+            plt.savefig(output_path, bbox_inches="tight", dpi=300)
+            plt.close(fig)
+            return str(output_path)