Refactor exercise progress

db.py

@@ -462,16 +462,13 @@ class DataBase():
         exercises = self.execute(
             'SELECT exercise_id, name FROM exercise')
         return exercises
-
+    
     def get_exercise_progress_for_user(self, person_id, exercise_id):
+        # Execute SQL query to fetch topset data for a specific person and exercise
         topsets = self.execute("""
             SELECT 
-                T.topset_id, 
-                E.name AS exercise_name,
-                W.person_id,
-                T.workout_id,
-                T.repetitions,
-                T.weight,
+                T.topset_id, E.name AS exercise_name, W.person_id, T.workout_id,
+                T.repetitions, T.weight,
                 ROUND((100 * T.weight::NUMERIC::INTEGER) / (101.3 - 2.67123 * T.repetitions), 0)::NUMERIC::INTEGER AS estimated_1rm,
                 W.start_date
             FROM 
@@ -481,15 +478,41 @@ class DataBase():
             JOIN 
                 workout W ON T.workout_id = W.workout_id
             WHERE
-                W.person_id = %s AND
-                E.exercise_id = %s
+                W.person_id = %s AND E.exercise_id = %s
             ORDER BY 
-                W.start_date;""", [person_id, exercise_id])
-        # Get a list of all estimated_1rm values
-        estimated_1rm = [t['estimated_1rm'] for t in topsets]
-        # Get a list of all start_dates
-        start_dates = [t['start_date'] for t in topsets]
-        # Create a list of messages with the structure 'estimated_1rm kg on start_date' with start_date formatted as 'dd/mm/yyyy'
-        messages = [f'{t["repetitions"]} x {t["weight"]}kg ({t["estimated_1rm"]}kg E1RM) on {t["start_date"].strftime("%d/%m/%Y")}' for t in topsets]
+                W.start_date;
+        """, [person_id, exercise_id])
 
-        return (estimated_1rm, start_dates, messages)
+        # Return None if no topsets found
+        if not topsets:
+            return None
+
+        # Extracting values and calculating value ranges for SVG dimensions
+        estimated_1rm = [t['estimated_1rm'] for t in topsets]
+        start_dates = [t['start_date'] for t in topsets]
+        min_date, max_date = min(start_dates), max(start_dates)
+        min_value, max_value = min(estimated_1rm), max(estimated_1rm)
+        
+        # Calculate viewBox dimensions
+        date_range = max_date - min_date
+        value_range = max_value - min_value
+        vb_width, vb_height = date_range.days, value_range
+        vb_width *= 200 / vb_width  # Scale to 200px width
+        vb_height *= 75 / vb_height  # Scale to 75px height
+
+        # Scale estimated_1rm values for SVG plotting
+        estimated_1rm_scaled = [((value - min_value) / value_range) * vb_height for value in estimated_1rm]
+        total_span = date_range.days or 1
+        relative_positions = [(date - min_date).days / total_span for date in start_dates]
+
+        # Create messages and zip data for SVG plotting
+        messages = [f'{t["repetitions"]} x {t["weight"]}kg ({t["estimated_1rm"]}kg E1RM) on {t["start_date"].strftime("%d %b %y")}' for t in topsets]
+        data_points = zip(estimated_1rm_scaled, relative_positions, messages)
+
+        # Return exercise data with SVG dimensions and data points
+        return {
+            'exercise_name': topsets[0]['exercise_name'],
+            'vb_width': vb_width,
+            'vb_height': vb_height,
+            'data_points': list(data_points)
+        }