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Format all .Net using Microsoft style

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This commit is contained in:
Corentin Le Molgat
2020-11-03 10:04:19 +01:00
parent eefa058d24
commit a9385fc3d2
196 changed files with 26140 additions and 23301 deletions
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examples/dotnet/cslinearprogramming.cs
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@@ -14,146 +14,155 @@
using System;
using Google.OrTools.LinearSolver;
public class CsLinearProgramming {
private static void RunLinearProgrammingExample(String solverType) {
Console.WriteLine($"---- Linear programming example with {solverType} ----");
public class CsLinearProgramming
{
private static void RunLinearProgrammingExample(String solverType)
{
Console.WriteLine($"---- Linear programming example with {solverType} ----");
Solver solver = Solver.CreateSolver(solverType);
if (solver == null) {
Console.WriteLine("Could not create solver " + solverType);
return;
}
// x1, x2 and x3 are continuous non-negative variables.
Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");
Solver solver = Solver.CreateSolver(solverType);
if (solver == null)
{
Console.WriteLine("Could not create solver " + solverType);
return;
}
// x1, x2 and x3 are continuous non-negative variables.
Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");
// Maximize 10 * x1 + 6 * x2 + 4 * x3.
Objective objective = solver.Objective();
objective.SetCoefficient(x1, 10);
objective.SetCoefficient(x2, 6);
objective.SetCoefficient(x3, 4);
objective.SetMaximization();
// Maximize 10 * x1 + 6 * x2 + 4 * x3.
Objective objective = solver.Objective();
objective.SetCoefficient(x1, 10);
objective.SetCoefficient(x2, 6);
objective.SetCoefficient(x3, 4);
objective.SetMaximization();
// x1 + x2 + x3 <= 100.
Constraint c0 = solver.MakeConstraint(double.NegativeInfinity, 100.0);
c0.SetCoefficient(x1, 1);
c0.SetCoefficient(x2, 1);
c0.SetCoefficient(x3, 1);
// x1 + x2 + x3 <= 100.
Constraint c0 = solver.MakeConstraint(double.NegativeInfinity, 100.0);
c0.SetCoefficient(x1, 1);
c0.SetCoefficient(x2, 1);
c0.SetCoefficient(x3, 1);
// 10 * x1 + 4 * x2 + 5 * x3 <= 600.
Constraint c1 = solver.MakeConstraint(double.NegativeInfinity, 600.0);
c1.SetCoefficient(x1, 10);
c1.SetCoefficient(x2, 4);
c1.SetCoefficient(x3, 5);
// 10 * x1 + 4 * x2 + 5 * x3 <= 600.
Constraint c1 = solver.MakeConstraint(double.NegativeInfinity, 600.0);
c1.SetCoefficient(x1, 10);
c1.SetCoefficient(x2, 4);
c1.SetCoefficient(x3, 5);
// 2 * x1 + 2 * x2 + 6 * x3 <= 300.
Constraint c2 = solver.MakeConstraint(double.NegativeInfinity, 300.0);
c2.SetCoefficient(x1, 2);
c2.SetCoefficient(x2, 2);
c2.SetCoefficient(x3, 6);
// 2 * x1 + 2 * x2 + 6 * x3 <= 300.
Constraint c2 = solver.MakeConstraint(double.NegativeInfinity, 300.0);
c2.SetCoefficient(x1, 2);
c2.SetCoefficient(x2, 2);
c2.SetCoefficient(x3, 6);
Console.WriteLine("Number of variables = " + solver.NumVariables());
Console.WriteLine("Number of constraints = " + solver.NumConstraints());
Console.WriteLine("Number of variables = " + solver.NumVariables());
Console.WriteLine("Number of constraints = " + solver.NumConstraints());
Solver.ResultStatus resultStatus = solver.Solve();
Solver.ResultStatus resultStatus = solver.Solve();
// Check that the problem has an optimal solution.
if (resultStatus != Solver.ResultStatus.OPTIMAL) {
Console.WriteLine("The problem does not have an optimal solution!");
return;
// Check that the problem has an optimal solution.
if (resultStatus != Solver.ResultStatus.OPTIMAL)
{
Console.WriteLine("The problem does not have an optimal solution!");
return;
}
Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");
// The objective value of the solution.
Console.WriteLine("Optimal objective value = " + solver.Objective().Value());
// The value of each variable in the solution.
Console.WriteLine("x1 = " + x1.SolutionValue());
Console.WriteLine("x2 = " + x2.SolutionValue());
Console.WriteLine("x3 = " + x3.SolutionValue());
Console.WriteLine("Advanced usage:");
double[] activities = solver.ComputeConstraintActivities();
Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
Console.WriteLine("c0: dual value = " + c0.DualValue());
Console.WriteLine(" activity = " + activities[c0.Index()]);
Console.WriteLine("c1: dual value = " + c1.DualValue());
Console.WriteLine(" activity = " + activities[c1.Index()]);
Console.WriteLine("c2: dual value = " + c2.DualValue());
Console.WriteLine(" activity = " + activities[c2.Index()]);
}
Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");
private static void RunLinearProgrammingExampleNaturalApi(String solverType, bool printModel)
{
Console.WriteLine($"---- Linear programming example (Natural API) with {solverType} ----");
// The objective value of the solution.
Console.WriteLine("Optimal objective value = " + solver.Objective().Value());
Solver solver = Solver.CreateSolver(solverType);
if (solver == null)
{
Console.WriteLine("Could not create solver " + solverType);
return;
}
// x1, x2 and x3 are continuous non-negative variables.
Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");
// The value of each variable in the solution.
Console.WriteLine("x1 = " + x1.SolutionValue());
Console.WriteLine("x2 = " + x2.SolutionValue());
Console.WriteLine("x3 = " + x3.SolutionValue());
solver.Maximize(10 * x1 + 6 * x2 + 4 * x3);
Constraint c0 = solver.Add(x1 + x2 + x3 <= 100);
Constraint c1 = solver.Add(10 * x1 + x2 * 4 + 5 * x3 <= 600);
Constraint c2 = solver.Add(2 * x1 + 2 * x2 + 6 * x3 <= 300);
Console.WriteLine("Advanced usage:");
double[] activities = solver.ComputeConstraintActivities();
Console.WriteLine("Number of variables = " + solver.NumVariables());
Console.WriteLine("Number of constraints = " + solver.NumConstraints());
Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
Console.WriteLine("c0: dual value = " + c0.DualValue());
Console.WriteLine(" activity = " + activities[c0.Index()]);
Console.WriteLine("c1: dual value = " + c1.DualValue());
Console.WriteLine(" activity = " + activities[c1.Index()]);
Console.WriteLine("c2: dual value = " + c2.DualValue());
Console.WriteLine(" activity = " + activities[c2.Index()]);
}
if (printModel)
{
string model = solver.ExportModelAsLpFormat(false);
Console.WriteLine(model);
}
private static void RunLinearProgrammingExampleNaturalApi(String solverType, bool printModel) {
Console.WriteLine($"---- Linear programming example (Natural API) with {solverType} ----");
Solver.ResultStatus resultStatus = solver.Solve();
Solver solver = Solver.CreateSolver(solverType);
if (solver == null) {
Console.WriteLine("Could not create solver " + solverType);
return;
}
// x1, x2 and x3 are continuous non-negative variables.
Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");
// Check that the problem has an optimal solution.
if (resultStatus != Solver.ResultStatus.OPTIMAL)
{
Console.WriteLine("The problem does not have an optimal solution!");
return;
}
solver.Maximize(10 * x1 + 6 * x2 + 4 * x3);
Constraint c0 = solver.Add(x1 + x2 + x3 <= 100);
Constraint c1 = solver.Add(10 * x1 + x2 * 4 + 5 * x3 <= 600);
Constraint c2 = solver.Add(2 * x1 + 2 * x2 + 6 * x3 <= 300);
Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");
Console.WriteLine("Number of variables = " + solver.NumVariables());
Console.WriteLine("Number of constraints = " + solver.NumConstraints());
// The objective value of the solution.
Console.WriteLine("Optimal objective value = " + solver.Objective().Value());
if (printModel) {
string model = solver.ExportModelAsLpFormat(false);
Console.WriteLine(model);
// The value of each variable in the solution.
Console.WriteLine("x1 = " + x1.SolutionValue());
Console.WriteLine("x2 = " + x2.SolutionValue());
Console.WriteLine("x3 = " + x3.SolutionValue());
Console.WriteLine("Advanced usage:");
double[] activities = solver.ComputeConstraintActivities();
Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
Console.WriteLine("c0: dual value = " + c0.DualValue());
Console.WriteLine(" activity = " + activities[c0.Index()]);
Console.WriteLine("c1: dual value = " + c1.DualValue());
Console.WriteLine(" activity = " + activities[c1.Index()]);
Console.WriteLine("c2: dual value = " + c2.DualValue());
Console.WriteLine(" activity = " + activities[c2.Index()]);
}
Solver.ResultStatus resultStatus = solver.Solve();
static void Main()
{
RunLinearProgrammingExample("GLOP");
RunLinearProgrammingExample("GLPK_LP");
RunLinearProgrammingExample("CLP");
// Check that the problem has an optimal solution.
if (resultStatus != Solver.ResultStatus.OPTIMAL) {
Console.WriteLine("The problem does not have an optimal solution!");
return;
RunLinearProgrammingExampleNaturalApi("GLOP", true);
RunLinearProgrammingExampleNaturalApi("GLPK_LP", false);
RunLinearProgrammingExampleNaturalApi("CLP", false);
}
Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");
// The objective value of the solution.
Console.WriteLine("Optimal objective value = " + solver.Objective().Value());
// The value of each variable in the solution.
Console.WriteLine("x1 = " + x1.SolutionValue());
Console.WriteLine("x2 = " + x2.SolutionValue());
Console.WriteLine("x3 = " + x3.SolutionValue());
Console.WriteLine("Advanced usage:");
double[] activities = solver.ComputeConstraintActivities();
Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
Console.WriteLine("c0: dual value = " + c0.DualValue());
Console.WriteLine(" activity = " + activities[c0.Index()]);
Console.WriteLine("c1: dual value = " + c1.DualValue());
Console.WriteLine(" activity = " + activities[c1.Index()]);
Console.WriteLine("c2: dual value = " + c2.DualValue());
Console.WriteLine(" activity = " + activities[c2.Index()]);
}
static void Main() {
RunLinearProgrammingExample("GLOP");
RunLinearProgrammingExample("GLPK_LP");
RunLinearProgrammingExample("CLP");
RunLinearProgrammingExampleNaturalApi("GLOP", true);
RunLinearProgrammingExampleNaturalApi("GLPK_LP", false);
RunLinearProgrammingExampleNaturalApi("CLP", false);
}
}