Coverage for src / cvx / core / variable.py: 100%

1# Copyright 2023 Stanford University Convex Optimization Group 

2# 

3# Licensed under the Apache License, Version 2.0 (the "License"); 

4# you may not use this file except in compliance with the License. 

5# You may obtain a copy of the License at 

6# 

7# http://www.apache.org/licenses/LICENSE-2.0 

8# 

9# Unless required by applicable law or agreed to in writing, software 

10# distributed under the License is distributed on an "AS IS" BASIS, 

11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

12# See the License for the specific language governing permissions and 

13# limitations under the License. 

14"""Decision variable class for portfolio optimization. 

15 

16This module provides the Variable class, which acts as a placeholder for 

17decision variables in portfolio optimization problems. After calling 

18:func:`~cvx.risk.portfolio.min_risk.minrisk_problem` and solving, the 

19``value`` attribute is populated with the optimal solution. 

20 

21Example: 

22 Create a variable and use it in an optimization problem: 

23 

24 >>> import numpy as np 

25 >>> from cvx.core.variable import Variable 

26 >>> w = Variable(3) 

27 >>> w.n 

28 3 

29 >>> w.value is None 

30 True 

31 

32""" 

33 

34from __future__ import annotations 

35 

36from dataclasses import dataclass, field 

37 

38import numpy as np 

39 

40 

41@dataclass 

42class Variable: 

43 """A decision variable for portfolio optimization. 

44 

45 Acts as a placeholder whose ``value`` attribute is populated with 

46 the optimal solution once the problem has been solved. 

47 

48 Attributes: 

49 n: Dimension of the variable (number of assets or factors). 

50 value: Optimal solution populated by the solver, or ``None`` before 

51 the problem has been solved. 

52 

53 Example: 

54 >>> from cvx.core.variable import Variable 

55 >>> w = Variable(4) 

56 >>> w.n 

57 4 

58 >>> w.value is None 

59 True 

60 

61 """ 

62 

63 n: int 

64 """Dimension of the variable.""" 

65 

66 value: np.ndarray | None = field(default=None, init=False) 

67 """Optimal value set after solving, or ``None`` before solving."""