def primal(self):
if self.problem is not None:
if self.problem._glpk_is_mip():
primal_from_solver = glp_mip_row_val(self.problem.problem, self._index)
else:
primal_from_solver = glp_get_row_prim(self.problem.problem, self._index)
# return self._round_primal_to_bounds(primal_from_solver) # Test assertions fail
return primal_from_solver
else:
return None
def constraint_values(self):
dual_values = collections.OrderedDict()
is_mip = self._glpk_is_mip()
for index, constraint in enumerate(self.constraints):
if is_mip:
value = glp_mip_row_val(self.problem, index + 1)
else:
value = glp_get_row_prim(self.problem, index + 1)
dual_values[constraint.name] = value
return dual_values
def primal(self):
if self.problem is not None:
if self.problem._glpk_is_mip():
primal_from_solver = glp_mip_row_val(self.problem.problem, self._index)
else:
primal_from_solver = glp_get_row_prim(self.problem.problem, self._index)
# return self._round_primal_to_bounds(primal_from_solver) # Test assertions fail
return primal_from_solver
else:
return None
def get_rates(problem: SwigPyObject) -> Iterable[Tuple[str, float]]:
for i in range(1, 1 + lp.glp_get_num_rows(problem)):
yield (
lp.glp_get_row_name(problem, i),
lp.glp_mip_row_val(problem, i) / 100,
)
