feat: Implement dose calculation fix and enhance legend feature

- Fixed dose calculation logic in `_calculate_daily_dose` to correctly parse timestamps with multiple colons.
- Added comprehensive test cases for various dose formats and edge cases in `test_dose_calculation.py`.
- Enhanced graph legend to display individual medicines with average dosages and track medicines without dose data.
- Updated legend styling and positioning for better readability and organization.
- Created new tests for enhanced legend functionality, including handling of medicines with and without data.
- Improved mocking for matplotlib components in tests to prevent TypeErrors.

src/graph_manager.py

@@ -163,6 +163,10 @@ class GraphManager:
                 "quetiapine",
             ]
 
+            # Track medicines with and without data for legend
+            medicines_with_data = []
+            medicines_without_data = []
+
             for medicine in medicines:
                 dose_column = f"{medicine}_doses"
                 if self.toggle_vars[medicine].get() and dose_column in df.columns:
@@ -174,23 +178,66 @@ class GraphManager:
 
                     # Only plot if there are non-zero doses
                     if any(dose > 0 for dose in daily_doses):
+                        medicines_with_data.append(medicine)
                         # Scale doses for better visibility
                         # (divide by 10 to fit with 0-10 scale)
                         scaled_doses = [dose / 10 for dose in daily_doses]
+
+                        # Calculate total dosage for this medicine across all days
+                        total_medicine_dose = sum(daily_doses)
+                        non_zero_doses = [d for d in daily_doses if d > 0]
+                        avg_dose = total_medicine_dose / len(non_zero_doses)
+
+                        # Create more informative label
+                        label = f"{medicine.capitalize()} (avg: {avg_dose:.1f}mg)"
+
                         self.ax.bar(
                             df.index,
                             scaled_doses,
                             alpha=0.6,
                             color=medicine_colors.get(medicine, "#DDA0DD"),
-                            label=f"{medicine.capitalize()} (mg/10)",
+                            label=label,
                             width=0.6,
                             bottom=-max(scaled_doses) * 1.1 if scaled_doses else -1,
                         )
                         has_plotted_series = True
+                    else:
+                        # Medicine is toggled on but has no dose data
+                        if self.toggle_vars[medicine].get():
+                            medicines_without_data.append(medicine)
 
             # Configure graph appearance
             if has_plotted_series:
-                self.ax.legend()
+                # Get current legend handles and labels
+                handles, labels = self.ax.get_legend_handles_labels()
+
+                # Add information about medicines without data if any are toggled on
+                if medicines_without_data:
+                    # Add a text note about medicines without dose data
+                    med_list = ", ".join(medicines_without_data)
+                    info_text = f"Tracked (no doses): {med_list}"
+                    labels.append(info_text)
+                    # Create a dummy handle for the info text (invisible)
+                    from matplotlib.patches import Rectangle
+
+                    dummy_handle = Rectangle(
+                        (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0
+                    )
+                    handles.append(dummy_handle)
+
+                # Create an expanded legend with better formatting
+                self.ax.legend(
+                    handles,
+                    labels,
+                    loc="upper left",
+                    bbox_to_anchor=(0, 1),
+                    ncol=2,  # Display in 2 columns for better space usage
+                    fontsize="small",
+                    frameon=True,
+                    fancybox=True,
+                    shadow=True,
+                    framealpha=0.9,
+                )
             self.ax.set_title("Medication Effects Over Time")
             self.ax.set_xlabel("Date")
             self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
@@ -239,12 +286,8 @@ class GraphManager:
                 continue
 
             try:
-                if ":" in entry:
-                    # Extract dose part after the timestamp
-                    _, dose_part = entry.split(":", 1)
-                else:
-                    # Handle cases where there's no timestamp
-                    dose_part = entry
+                # Extract dose part after the last colon (timestamp:dose format)
+                dose_part = entry.split(":")[-1] if ":" in entry else entry
 
                 # Extract numeric part from dose (e.g., "150mg" -> 150)
                 dose_value = ""