Add support to set degree of line of best fit for exercise progress graphs in custom view

db.py

@@ -481,7 +481,7 @@ class DataBase():
             'SELECT exercise_id, name FROM exercise')
         return exercises
     
-    def get_exercise_progress_for_user(self, person_id, exercise_id, min_date=None, max_date=None, epoch='all'):
+    def get_exercise_progress_for_user(self, person_id, exercise_id, min_date=None, max_date=None, epoch='all', degree=1):
         today = datetime.now()
         if epoch == '1M':
             min_date = today - relativedelta(months=1)
@@ -489,6 +489,7 @@ class DataBase():
             min_date = today - relativedelta(months=3)
         elif epoch == '6M':
             min_date = today - relativedelta(months=6)
+        
         # Execute SQL query to fetch topset data for a specific person and exercise
         topsets = self.execute("""
             SELECT 
@@ -516,13 +517,26 @@ class DataBase():
             return None
 
         # Extracting values and calculating value ranges for SVG dimensions
+        exercise_name = topsets[0]['exercise_name']
         estimated_1rm = [t['estimated_1rm'] for t in topsets]
         repetitions = [t['repetitions'] for t in topsets]
         weight = [t['weight'] for t in topsets]
         start_dates = [t['start_date'] for t in topsets]
         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]
 
-        exercise_progress = get_exercise_graph_model(topsets[0]['exercise_name'], estimated_1rm, repetitions, weight, start_dates, messages, epoch, person_id, exercise_id, min_date, max_date)
+        exercise_progress = get_exercise_graph_model(
+            exercise_name, 
+            estimated_1rm, 
+            repetitions, 
+            weight, 
+            start_dates, 
+            messages, 
+            epoch, 
+            person_id, 
+            exercise_id, 
+            min_date, 
+            max_date, 
+            degree)
 
         return exercise_progress