Coverage for backend/django/core/auxiliary/methods/export_scenario_data.py: 75%

1from core.auxiliary.models.Scenario import Scenario 

2from core.auxiliary.models.Flowsheet import Flowsheet 

3from core.auxiliary.models.PropertyValue import PropertyValue 

4from core.auxiliary.models.Solution import Solution 

5 

6 

7def values_per_index(scenario: Scenario): 

8 if not scenario.enable_dynamics: 8 ↛ 11line 8 didn't jump to line 11 because the condition on line 8 was always true

9 return 1 

10 else : 

11 return scenario.num_time_steps 

12 

13# Tested in test_mss.py 

14def export_scenario_data(flowsheet: Flowsheet, scenario: Scenario, properties: list[int] | None = None): 

15 # Create a column for each property value 

16 if properties: 

17 solutions = Solution.objects.filter(scenario=scenario, property__property_id__in=properties).order_by("solve_index") 

18 else: 

19 solutions = Solution.objects.filter(scenario=scenario).order_by("solve_index") 

20 property_values = PropertyValue.objects.filter(flowsheet=flowsheet, solutions__in=solutions).distinct() 

21 

22 # Create a list of blanks to fill in missing data 

23 blanks = [None for _ in range(values_per_index(scenario))] 

24 

25 columns = {} 

26 data = {} 

27 

28 for uo_name, prop_key, prop_id in property_values.values_list( 

29 "property__set__simulationObject__componentName", # Link to PropertyInfo -> PropertySet -> SimulationObject Name 

30 "property__key", # PropertyInfo key 

31 "id" 

32 ): 

33 column_name = f"{uo_name} - {prop_key}" 

34 columns[prop_id] = column_name 

35 data[column_name] = [] 

36 

37 # Populate the columns 

38 current_solve_index = 0 

39 

40 for solution in solutions: 

41 if solution.solve_index > current_solve_index: 

42 # Fill in blanks for missing solve indices 

43 for _ in range(solution.solve_index - current_solve_index - 1): 43 ↛ 44line 43 didn't jump to line 44 because the loop on line 43 never started

44 for column_name in data.keys(): 

45 data[column_name].extend(blanks) 

46 current_solve_index = solution.solve_index 

47 

48 column_name = columns[solution.property_id] 

49 # Because the values are an array, we flatten them into the data column 

50 data[column_name].extend(solution.values) 

51 

52 return data 

53 

54def collate(data: dict[str,list]): 

55 """ 

56 Collate the data into rows for CSV export 

57 """ 

58 # Collate the data into rows 

59 # Each row is a dict with keys as column names 

60 rows = [] 

61 max_length = max((len(v) for v in data.values()),default=0) 

62 for i in range(max_length): 62 ↛ 63line 62 didn't jump to line 63 because the loop on line 62 never started

63 row = {} 

64 for key, values in data.items(): 

65 row[key] = values[i] if i < len(values) else None 

66 rows.append(row) 

67 return rows 

68 

69