Coverage for backend/core/auxiliary/methods/export_scenario_data.py: 66%
40 statements
« prev ^ index » next coverage.py v7.10.7, created at 2025-11-06 23:27 +0000
« prev ^ index » next coverage.py v7.10.7, created at 2025-11-06 23:27 +0000
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.PropertyInfo import (
5 PropertyInfo,
6)
7from core.auxiliary.models.Solution import Solution
8from core.auxiliary.models.SolveState import SolveState, SolveValue
9from core.auxiliary.models.Solution import Solution
12def values_per_index(scenario: Scenario):
13 if not scenario.enable_dynamics: 13 ↛ 16line 13 didn't jump to line 16 because the condition on line 13 was always true
14 return 1
15 else :
16 return scenario.num_time_steps
18# Tested in test_mss.py
19def export_scenario_data(flowsheet: Flowsheet, scenario: Scenario):
20 # Create a column for each property value
21 solutions = Solution.objects.filter(scenario=scenario).order_by("solve_index")
22 property_values = PropertyValue.objects.filter(flowsheet=flowsheet, solutions__in=solutions).distinct()
24 # Create a list of blanks to fill in missing data
25 blanks = [None for _ in range(values_per_index(scenario))]
27 columns = {}
28 data = {}
30 for uo_name, prop_key, prop_id in property_values.values_list(
31 "property__set__simulationObject__componentName", # Link to PropertyInfo -> PropertySet -> SimulationObject Name
32 "property__key", # PropertyInfo key
33 "id"
34 ):
35 column_name = f"{uo_name} - {prop_key} ({prop_id})"
36 columns[prop_id] = column_name
37 data[column_name] = []
39 # Populate the columns
40 current_solve_index = 0
42 for solution in solutions:
43 if solution.solve_index > current_solve_index:
44 # Fill in blanks for missing solve indices
45 for _ in range(solution.solve_index - current_solve_index - 1): 45 ↛ 46line 45 didn't jump to line 46 because the loop on line 45 never started
46 for column_name in data.keys():
47 data[column_name].extend(blanks)
48 current_solve_index = solution.solve_index
50 column_name = columns[solution.property_id]
51 # Because the values are an array, we flatten them into the data column
52 data[column_name].extend(solution.values)
54 return data
56def collate(data: dict[str,list]):
57 """
58 Collate the data into rows for CSV export
59 """
60 # Collate the data into rows
61 # Each row is a dict with keys as column names
62 rows = []
63 max_length = max((len(v) for v in data.values()),default=0)
64 for i in range(max_length):
65 row = {}
66 for key, values in data.items():
67 row[key] = values[i] if i < len(values) else None
68 rows.append(row)
69 return rows