|
1 | | -import numpy as np |
2 | | - |
3 | | -mean_electric_output: float = None |
4 | | - |
5 | | -annual_electric_output: float = None |
6 | | - |
7 | | -maintenance: float = None |
8 | | - |
9 | | -total_costs: float = None |
| 1 | +from dataclasses import dataclass, field |
10 | 2 |
|
11 | | -s_label: list[str] = None |
12 | | - |
13 | | -s_kref: list[float] = None |
14 | | - |
15 | | -s_k: list[float] = None |
16 | | - |
17 | | -s_cref: list[float] = None |
| 3 | +import numpy as np |
18 | 4 |
|
19 | | -s_cost: list[float] = None |
20 | 5 |
|
21 | | -s_cost_factor: list[float] = None |
| 6 | +@dataclass |
| 7 | +class Cost2015Data: |
| 8 | + mean_electric_output: float = 0.0 |
22 | 9 |
|
| 10 | + annual_electric_output: float = 0.0 |
23 | 11 |
|
24 | | -def init_cost_2015_variables(): |
25 | | - global mean_electric_output |
26 | | - mean_electric_output = 0.0 |
| 12 | + maintenance: float = 0.0 |
27 | 13 |
|
28 | | - global annual_electric_output |
29 | | - annual_electric_output = 0.0 |
| 14 | + total_costs: float = 0.0 |
30 | 15 |
|
31 | | - global maintenance |
32 | | - maintenance = 0.0 |
| 16 | + s_label: list[str] = field( |
| 17 | + default_factory=lambda: np.array(["not used"] * 100, dtype=object) |
| 18 | + ) |
33 | 19 |
|
34 | | - global total_costs |
35 | | - total_costs = 0.0 |
| 20 | + s_kref: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64)) |
36 | 21 |
|
37 | | - global s_label |
38 | | - s_label = np.array(["not used"] * 100, dtype=object) |
| 22 | + s_k: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64)) |
39 | 23 |
|
40 | | - global s_kref |
41 | | - s_kref = np.zeros(100, dtype=np.float64) |
| 24 | + s_cref: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64)) |
42 | 25 |
|
43 | | - global s_k |
44 | | - s_k = np.zeros(100, dtype=np.float64) |
| 26 | + s_cost: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64)) |
45 | 27 |
|
46 | | - global s_cref |
47 | | - s_cref = np.zeros(100, dtype=np.float64) |
| 28 | + s_cost_factor: list[float] = field( |
| 29 | + default_factory=lambda: np.zeros(100, dtype=np.float64) |
| 30 | + ) |
48 | 31 |
|
49 | | - global s_cost |
50 | | - s_cost = np.zeros(100, dtype=np.float64) |
51 | 32 |
|
52 | | - global s_cost_factor |
53 | | - s_cost_factor = np.zeros(100, dtype=np.float64) |
| 33 | +CREATE_DICTS_FROM_DATACLASS = Cost2015Data |
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