def ComputeExactConditionNumber(self) -> "double":
r"""
Advanced usage: computes the exact condition number of the current scaled
basis: L1norm(B) * L1norm(inverse(B)), where B is the scaled basis.
This method requires that a basis exists: it should be called after Solve.
It is only available for continuous problems. It is implemented for GLPK
but not CLP because CLP does not provide the API for doing it.
The condition number measures how well the constraint matrix is conditioned
and can be used to predict whether numerical issues will arise during the
solve: the model is declared infeasible whereas it is feasible (or
vice-versa), the solution obtained is not optimal or violates some
constraints, the resolution is slow because of repeated singularities.
The rule of thumb to interpret the condition number kappa is:
- o kappa <= 1e7: virtually no chance of numerical issues
- o 1e7 < kappa <= 1e10: small chance of numerical issues
- o 1e10 < kappa <= 1e13: medium chance of numerical issues
- o kappa > 1e13: high chance of numerical issues
The computation of the condition number depends on the quality of the LU
decomposition, so it is not very accurate when the matrix is ill
conditioned.
"""
return _pywraplp.Solver_ComputeExactConditionNumber(self)
def ComputeExactConditionNumber(self) -> "double":
return _pywraplp.Solver_ComputeExactConditionNumber(self)