Coverage for src/cvxmarkowitz/cvxerror.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"""Custom exceptions used by the Markowitz package.""" 

15 

16 

17class CvxError(Exception): 

18 """Base error for the package. 

19 

20 Every error raised by cvxmarkowitz derives from this, so 

21 ``except CvxError`` continues to catch all of them. Prefer catching one 

22 of the subclasses below when the handling differs by failure mode. 

23 """ 

24 

25 

26class CvxDataError(CvxError): 

27 """Input data is missing, or its shape disagrees with the model. 

28 

29 Raised when required keyword data is absent, or when arrays that must 

30 agree in length or shape do not. Recoverable by supplying corrected 

31 input and retrying. 

32 """ 

33 

34 

35class CvxSolverError(CvxError): 

36 """The solver returned a non-optimal status. 

37 

38 Raised when a problem is infeasible, unbounded, or otherwise did not 

39 solve to optimality. Retrying with the same input will not help; 

40 another solver or a relaxed formulation might. 

41 """ 

42 

43 

44class CvxBuildError(CvxError): 

45 """The assembled problem does not satisfy the package's construction rules. 

46 

47 Raised by :meth:`Builder.build` when the problem it assembled is not 

48 :abbr:`DPP (disciplined parametrized programming)`-compliant. The whole 

49 point of building a parametrized problem here is that cvxpy caches the 

50 canonicalization and reuses it on later solves, and only DPP-compliant 

51 problems get that treatment -- so a non-DPP problem is a formulation bug, 

52 not a data problem. Retrying will not help; the objective or the 

53 constraints have to change. 

54 """