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Modularize LearningSolver into components; implement branch-priority
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@@ -12,11 +12,11 @@ from scipy.stats import uniform, randint
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def test_stab():
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graph = nx.cycle_graph(5)
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weights = [1., 2., 3., 4., 5.]
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weights = [1., 1., 1., 1., 1.]
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instance = MaxWeightStableSetInstance(graph, weights)
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solver = LearningSolver()
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solver.solve(instance)
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assert instance.model.OBJ() == 8.
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assert instance.model.OBJ() == 2.
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def test_stab_generator_fixed_graph():
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