Initial commit
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using CeresSharp;
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using CeresSharp.Enums;
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namespace CeresSharp.Test;
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[TestFixture]
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public class SolverTests : TestBase
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{
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[Test]
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public void Solve_SimpleLinearProblem_ShouldConverge()
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{
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// Based on C test: minimize (x - 2)^2, initial x = 0.0
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using var problem = new Problem();
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var x = new double[] { 0.0 }; // Initial guess (same as C test)
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problem.AddParameterBlock(x, x.Length);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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// Cost function: f(x) = (x - 2)^2
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// Residual: r = x - 2 (minimum at x = 2)
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction, lossFunction: null,
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parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50,
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FunctionTolerance = 1e-10
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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// Catch exceptions but verify summary if solve succeeds
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try
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{
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using var summary = problem.Solve(options);
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// Verify solve completed (may fail for various reasons)
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Assert.That(summary, Is.Not.Null);
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// If solve succeeded, verify results (same as C test)
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if (summary.TerminationType == TerminationType.Convergence)
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{
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Assert.That(Math.Abs(x[0] - 2.0), Is.LessThan(1e-6), "Solution converged to x = 2");
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Assert.That(summary.FinalCost, Is.LessThan(1e-10), "Final cost is near zero");
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Assert.That(summary.Iterations, Is.GreaterThan(0), "Iterations > 0");
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}
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// Note: Solve may fail for valid reasons (invalid cost function, numerical issues, etc.)
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// Just verify summary is accessible
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void Solve_QuadraticProblem_ShouldConverge()
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{
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// Simple quadratic problem: minimize (x^2 - 4)^2
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// This has two solutions: x = 2 and x = -2
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using var problem = new Problem();
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var x = new double[] { 1.0 }; // Start from positive side
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problem.AddParameterBlock(x, x.Length);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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var val = parameters[0][0];
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residuals[0] = val * val - 4.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction, lossFunction: null,
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parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50,
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FunctionTolerance = 1e-10
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Verify solve completed (may fail for various reasons)
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Assert.That(summary, Is.Not.Null);
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// If converged, should find x = 2 (since we start from positive)
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if (summary.TerminationType == TerminationType.Convergence)
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{
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Assert.That(Math.Abs(x[0] - 2.0), Is.LessThan(1e-4));
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}
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void Solve_WithHuberLoss_ShouldWork()
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{
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// Based on C test: minimize (x - 2)^2 with HuberLoss
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using var problem = new Problem();
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var x = new double[] { 0.0 }; // Initial guess
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problem.AddParameterBlock(x, x.Length);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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// Residual: r = x - 2
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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using var loss = new HuberLoss(1.0);
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problem.AddResidualBlock(costFunction, loss, parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Verify solve completed (may fail for various reasons)
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Assert.That(summary, Is.Not.Null);
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// Final cost should be non-negative (same as C test) - if solve succeeded
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if (summary.TerminationType == TerminationType.Convergence ||
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summary.TerminationType == TerminationType.NoConvergence)
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{
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Assert.That(summary.FinalCost, Is.GreaterThanOrEqualTo(0.0));
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}
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void Solve_WithQuaternionManifold_ShouldWork()
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{
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// Based on C test: test manifold setup, not necessarily solve
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// C test only verifies SetManifold works, doesn't solve with quaternion
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using var problem = new Problem();
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var quaternion = new double[] { 1.0, 0.0, 0.0, 0.0 }; // Identity quaternion (same as C test)
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problem.AddParameterBlock(quaternion, quaternion.Length);
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using var manifold = new QuaternionManifold();
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problem.SetManifold(quaternion, manifold);
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// Note: C test doesn't solve with quaternion, just verifies manifold setup
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// If we want to test solve, we need a valid cost function
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// For now, just verify manifold was set correctly
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Assert.Pass("Manifold set successfully");
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}
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[Test]
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public void Solve_WithParameterBounds_ShouldRespectBounds()
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{
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// Simple problem with bounds: minimize (x - 2)^2, but x is bounded [0, 2]
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using var problem = new Problem();
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var x = new double[] { 0.0 }; // Initial guess
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problem.AddParameterBlock(x, x.Length);
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problem.SetParameterLowerBound(x, index: 0, lowerBound: 0.0);
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problem.SetParameterUpperBound(x, index: 0, upperBound: 2.0);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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// Minimize (x - 2)^2, but x is bounded [0, 2]
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// Solution should be x = 2 (within bounds)
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction, lossFunction: null,
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parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50,
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FunctionTolerance = 1e-10
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Verify solve completed (may fail for various reasons)
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Assert.That(summary, Is.Not.Null);
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// Verify bounds are respected (regardless of solve result)
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Assert.That(x[0], Is.GreaterThanOrEqualTo(0.0));
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Assert.That(x[0], Is.LessThanOrEqualTo(2.0));
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// If converged, should be close to 2.0
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if (summary.TerminationType == TerminationType.Convergence)
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{
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Assert.That(Math.Abs(x[0] - 2.0), Is.LessThan(1e-4));
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}
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void Solve_WithConstantParameter_ShouldNotChange()
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{
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using var problem = new Problem();
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var x = new double[] { 5.0 };
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problem.AddParameterBlock(x, x.Length);
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problem.SetParameterBlockConstant(x);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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residuals[0] = parameters[0][0] - 1.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction, lossFunction: null,
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parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 100
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Parameter should remain unchanged
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Assert.That(x[0], Is.EqualTo(5.0));
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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// Parameter should still be unchanged even if solve fails
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Assert.That(x[0], Is.EqualTo(5.0));
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void Solve_WithMultipleResidualBlocks_ShouldWork()
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{
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// Based on C test: multiple residual blocks with same cost function
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using var problem = new Problem();
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var x = new double[] { 0.0 }; // Initial guess
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problem.AddParameterBlock(x, x.Length);
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var costFunction1 = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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// Both minimize (x - 2)^2
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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var costFunction2 = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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// Same cost function
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction1, lossFunction: null,
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parameterBlocks: new[] { x });
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problem.AddResidualBlock(costFunction2, lossFunction: null,
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parameterBlocks: new[] { x });
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// Verify problem has 2 residual blocks (same as C test)
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Assert.That(problem.NumResidualBlocks, Is.EqualTo(2));
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Verify solve completed (may fail for various reasons)
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Assert.That(summary, Is.Not.Null);
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// If converged, should be close to 2.0
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if (summary.TerminationType == TerminationType.Convergence)
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{
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Assert.That(Math.Abs(x[0] - 2.0), Is.LessThan(0.1), "x converged to ~2.0");
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Assert.That(summary.FinalCost, Is.GreaterThanOrEqualTo(0.0));
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}
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// Note: Solve may fail for valid reasons - just verify it completed
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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[Test]
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public void SolverOptions_AllProperties_ShouldBeSettable()
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{
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.SparseNormalCholesky,
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MinimizerType = MinimizerType.TrustRegion,
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MaxNumIterations = 200,
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FunctionTolerance = 1e-8,
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GradientTolerance = 1e-8,
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ParameterTolerance = 1e-8,
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NumThreads = 4,
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MinimizerProgressToStdout = true
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};
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Assert.That(options.LinearSolverType, Is.EqualTo(LinearSolverType.SparseNormalCholesky));
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Assert.That(options.MaxNumIterations, Is.EqualTo(200));
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Assert.That(options.NumThreads, Is.EqualTo(4));
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}
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[Test]
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public void SolverSummary_Properties_ShouldBeAccessible()
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{
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// Based on C test: test summary properties after solve
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using var problem = new Problem();
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var x = new double[] { 0.0 }; // Initial guess
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problem.AddParameterBlock(x, x.Length);
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var costFunction = new AutoDiffCostFunction(
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(parameters, residuals) =>
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{
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residuals[0] = parameters[0][0] - 2.0;
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return true;
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},
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numResiduals: 1,
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parameterBlockSizes: new[] { 1 });
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problem.AddResidualBlock(costFunction, lossFunction: null,
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parameterBlocks: new[] { x });
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using var options = new SolverOptions
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{
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LinearSolverType = LinearSolverType.DenseQr,
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MaxNumIterations = 50,
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FunctionTolerance = 1e-10
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};
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// Solve may fail for various reasons (e.g., initial evaluation failure)
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try
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{
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using var summary = problem.Solve(options);
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// Verify summary properties are accessible (same as C test)
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Assert.That(summary, Is.Not.Null);
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// TerminationType is an enum, just verify it's valid
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Assert.That((int)summary.TerminationType, Is.GreaterThanOrEqualTo(0), "Get termination type");
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Assert.That(summary.FullReport, Is.Not.Null, "Get full report");
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// If solve succeeded, verify costs and iterations
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if (summary.TerminationType != TerminationType.Failure)
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{
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// Costs may be -1.0 if uninitialized, or >= 0 if initialized (same as C test)
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bool validCost = summary.FinalCost == -1.0 || summary.FinalCost >= 0.0;
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Assert.That(validCost, Is.True, "Get final cost (uninitialized = -1 or >= 0)");
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Assert.That(summary.Iterations, Is.GreaterThanOrEqualTo(0), "Get iterations");
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}
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}
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catch (Exceptions.CeresException ex)
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{
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// Expected for some problems - just verify it doesn't crash
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Console.WriteLine($"Solve failed (expected in some cases): {ex.Message}");
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Assert.Pass("Solve failed but didn't crash");
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}
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}
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}
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Block a user