polish
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@@ -44,7 +44,7 @@ code_sample_py(name = "assignment_mb")
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code_sample_py(name = "bin_packing_mb")
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code_sample_py(name = "copy_model_mb")
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code_sample_py(name = "clone_model_mb")
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code_sample_py(name = "simple_lp_program_mb")
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@@ -13,7 +13,7 @@
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# limitations under the License.
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# [START program]
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"""Integer programming examples that show how to use the APIs."""
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"""Integer programming examples that show how to clone a model."""
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# [START import]
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import math
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@@ -35,7 +35,7 @@ def main():
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# [START constraints]
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# x + 7 * y <= 17.5.
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c1 = model.add(x + 7 * y <= 17.5)
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unused_c1 = model.add(x + 7 * y <= 17.5)
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# x <= 3.5.
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c2 = model.add(x <= 3.5)
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@@ -56,14 +56,12 @@ def main():
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# Add new constraint.
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model_copy.add(x_copy >= 1)
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print("Number of constraints in original model =", model.num_constraints)
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print("Number of constraints in cloned model =", model_copy.num_constraints)
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print(f"Number of constraints in original model ={model.num_constraints}")
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print(f"Number of constraints in cloned model = {model_copy.num_constraints}")
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# Modify a constraint.
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c2_copy.add_term(z_copy, 2.0)
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print(model_copy.export_to_lp_string())
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# [START solve]
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# Create the solver with the SCIP backend, and solve the model.
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solver = model_builder.ModelSolver("scip")
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@@ -73,17 +71,17 @@ def main():
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# [START print_solution]
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if status == model_builder.SolveStatus.OPTIMAL:
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print("Solution:")
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print("Objective value =", solver.objective_value)
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print("x =", solver.value(x_copy))
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print("y =", solver.value(y_copy))
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print("z =", solver.value(z_copy))
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print(f"Objective value = {solver.objective_value}")
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print(f"x = {solver.value(x_copy)}")
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print(f"y = {solver.value(y_copy)}")
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print(f"z = {solver.value(z_copy)}")
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else:
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print("The problem does not have an optimal solution.")
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# [END print_solution]
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# [START advanced]
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print("\nAdvanced usage:")
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print("Problem solved in %f seconds" % solver.wall_time)
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print(f"Problem solved in {solver.wall_time} seconds")
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# [END advanced]
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