Source code for minizinc.helpers

import sys
from dataclasses import asdict, is_dataclass
from datetime import timedelta
from typing import Any, Dict, Optional, Sequence, Union

import minizinc

if sys.version_info >= (3, 8):
    from typing import Protocol

    class DataClass(Protocol):
        # Checking for this attribute is currently the most reliable way to
        # ascertain that something is a dataclass
        __dataclass_fields__: Dict


else:
    DataClass = Any


[docs]def check_result( model: minizinc.Model, result: minizinc.Result, solver: minizinc.Solver, solution_nrs: Optional[Sequence[int]] = None, ) -> bool: """Checks a result object for a model using the given solver. Check the correctness of the solving process using a (different) solver configuration. The solver configuration is now used to confirm is assignment of the variables is correct. By default only the last solution will be checked. A sequence of solution numbers can be provided to check multiple solutions. Args: model (Model): To model for which the solution was provided result (Result): The solution to be checked solver (Solver): The solver configuration used to check the solutions. solution_nrs: The index set of solutions to be checked. (default: ``-1``) Returns: bool: True if the given result object is correctly verified. """ if solution_nrs is None: solution_nrs = [-1] solutions = ( result.solution if isinstance(result.solution, list) else [result.solution] ) for i in solution_nrs: sol = solutions[i] if not check_solution(model, sol, result.status, solver): return False return True
[docs]def check_solution( model: minizinc.Model, solution: Union[DataClass, Dict[str, Any]], status: minizinc.Status, solver: minizinc.Solver, ) -> bool: """Checks a solution for a model using the given solver. Check the correctness of the solving process using a (different) solver configuration. A new model instance is created and will be assigned all available values from the given solution. The Instance.solve() method is then used to ensure that the same solution with the same expected status is reached. Note that this method will not check the optimality of a solution. Args: model (Model): To model for which the solution was provided solution (Union[DataClass, Dict[str, Any]]): The solution to be checked status (Status): The expected (compatible) MiniZinc status solver (Solver): The solver configuration used to check the solution. Returns: bool: True if the given solution are correctly verified. """ instance = minizinc.Instance(solver, model) if is_dataclass(solution): solution = asdict(solution) for k, v in solution.items(): if k not in ("objective", "__output_item"): instance[k] = v try: check = instance.solve(timeout=timedelta(seconds=5)) if status == check.status: return True elif check.status in [ minizinc.Status.SATISFIED, minizinc.Status.OPTIMAL_SOLUTION, ] and status in [ minizinc.Status.SATISFIED, minizinc.Status.OPTIMAL_SOLUTION, minizinc.Status.ALL_SOLUTIONS, ]: return True else: return False except minizinc.MiniZincError: if status == minizinc.Status.ERROR: return True return False