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Merge pull request #3 from GregorCH/dev-robust-gap

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Make gap computation robust against missing upper/lower bounds
This commit is contained in:
Alinson S. Xavier
2021-01-15 08:01:55 -06:00
committed by GitHub
parent 28e2ba7c01 601bfa261a
commit 3efc92742d
1 changed files with 10 additions and 1 deletions
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11
miplearn/benchmark.py
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@@ -74,6 +74,14 @@ class BenchmarkRunner:
for (solver_name, solver) in self.solvers.items(): for (solver_name, solver) in self.solvers.items():
solver.fit(training_instances) solver.fit(training_instances)
def computeGap(self, ub, lb):
# solver did not find a solution and/or bound, use maximum gap possible
if lb is None or ub is None or lb * ub < 0:
return 1.0
else:
# divide by max(abs(ub),abs(lb)) to ensure gap <= 1
return (ub - lb) / max(abs(ub), abs(lb))
def _push_result(self, result, solver, solver_name, instance): def _push_result(self, result, solver, solver_name, instance):
if self.results is None: if self.results is None:
self.results = pd.DataFrame( self.results = pd.DataFrame(
@@ -93,7 +101,8 @@ class BenchmarkRunner:
) )
lb = result["Lower bound"] lb = result["Lower bound"]
ub = result["Upper bound"] ub = result["Upper bound"]
gap = (ub - lb) / lb gap = self.computeGap(ub, lb)
if "Predicted LB" not in result: if "Predicted LB" not in result:
result["Predicted LB"] = float("nan") result["Predicted LB"] = float("nan")
result["Predicted UB"] = float("nan") result["Predicted UB"] = float("nan")