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https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-06 01:18:52 -06:00
Use np in Constraints.lazy; replace some get_vector
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@@ -39,7 +39,7 @@ def test_learning_solver(
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sample = instance.get_samples()[0]
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assert_equals(
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sample.get_vector("mip_var_values"), [1.0, 0.0, 1.0, 1.0, 61.0]
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sample.get_array("mip_var_values"), [1.0, 0.0, 1.0, 1.0, 61.0]
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)
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assert sample.get_scalar("mip_lower_bound") == 1183.0
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assert sample.get_scalar("mip_upper_bound") == 1183.0
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@@ -48,7 +48,7 @@ def test_learning_solver(
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assert len(mip_log) > 100
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assert_equals(
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sample.get_vector("lp_var_values"), [1.0, 0.923077, 1.0, 0.0, 67.0]
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sample.get_array("lp_var_values"), [1.0, 0.923077, 1.0, 0.0, 67.0]
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)
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assert_equals(sample.get_scalar("lp_value"), 1287.923077)
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lp_log = sample.get_scalar("lp_log")
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