/*========================================================================= * * Copyright NumFOCUS * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0.txt * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * *=========================================================================*/ #include #include "itkLBFGS2Optimizerv4.h" #include "itkMath.h" #include "itkTestingMacros.h" #include /** * \class itkLBFGSOptimizerv4TestMetric * * The objectif function is the quadratic form: * * 1/2 x^T A x - b^T x * * Where A is represented as an itkMatrix and * b is represented as a itkVector * * The system in this example is: * * | 3 2 ||x| | 2| |0| * | 2 6 ||y| + |-8| = |0| * * * the solution is the vector | 2 -2 | * */ class itkLBFGS2Optimizerv4TestMetric : public itk::ObjectToObjectMetricBase { public: using Self = itkLBFGS2Optimizerv4TestMetric; using Superclass = itk::ObjectToObjectMetricBase; using Pointer = itk::SmartPointer; using ConstPointer = itk::SmartPointer; itkNewMacro(Self); itkTypeMacro(itkLBFGS2Optimizerv4TestMetric, ObjectToObjectMetricBase); enum { SpaceDimension = 2 }; using ParametersType = Superclass::ParametersType; using DerivativeType = Superclass::DerivativeType; using MeasureType = Superclass::MeasureType; itkLBFGS2Optimizerv4TestMetric() { m_HasLocalSupport = false; } MeasureType GetValue() const override { double x = this->m_Parameters[0]; double y = this->m_Parameters[1]; std::cout << "GetValue ( " << x << " , " << y << ") = "; double val = 0.5 * (3 * x * x + 4 * x * y + 6 * y * y) - 2 * x + 8 * y; std::cout << val << std::endl; return val; } void GetDerivative(DerivativeType & derivative) const override { double x = this->m_Parameters[0]; double y = this->m_Parameters[1]; std::cout << "GetDerivative ( " << x << " , " << y << ") = "; derivative = DerivativeType(SpaceDimension); derivative[0] = -(3 * x + 2 * y - 2); derivative[1] = -(2 * x + 6 * y + 8); std::cout << "(" << derivative[0] << " , " << derivative[1] << ")" << std::endl; } void GetValueAndDerivative(MeasureType & value, DerivativeType & derivative) const override { value = GetValue(); GetDerivative(derivative); } void Initialize() override { m_Parameters.SetSize(SpaceDimension); } Superclass::NumberOfParametersType GetNumberOfLocalParameters() const override { return SpaceDimension; } Superclass::NumberOfParametersType GetNumberOfParameters() const override { return SpaceDimension; } void SetParameters(ParametersType & params) override { this->m_Parameters = params; } const ParametersType & GetParameters() const override { return this->m_Parameters; } bool HasLocalSupport() const override { return m_HasLocalSupport; } void SetHasLocalSupport(bool hls) { m_HasLocalSupport = hls; } void UpdateTransformParameters(const DerivativeType &, ParametersValueType) override {} private: ParametersType m_Parameters; bool m_HasLocalSupport; }; int itkLBFGS2Optimizerv4Test(int, char *[]) { std::cout << "LBFGS2 Optimizerv4 Test \n \n"; using OptimizerType = itk::LBFGS2Optimizerv4; // Declaration of a itkOptimizer OptimizerType::Pointer itkOptimizer = OptimizerType::New(); // Declaration of the metric itkLBFGS2Optimizerv4TestMetric::Pointer metric = itkLBFGS2Optimizerv4TestMetric::New(); // Set some optimizer parameters itkOptimizer->SetHessianApproximationAccuracy(5); itkOptimizer->SetSolutionAccuracy(1e-5); itkOptimizer->SetDeltaConvergenceDistance(0); itkOptimizer->SetDeltaConvergenceTolerance(0); itkOptimizer->SetMaximumIterations(0); itkOptimizer->SetLineSearch(OptimizerType::LineSearchMethodEnum::LINESEARCH_DEFAULT); itkOptimizer->SetMaximumLineSearchEvaluations(20); itkOptimizer->SetMinimumLineSearchStep(1e-20); itkOptimizer->SetMaximumLineSearchStep(1e+20); itkOptimizer->SetLineSearchAccuracy(1e-4); itkOptimizer->SetWolfeCoefficient(0); itkOptimizer->SetLineSearchGradientAccuracy(0.9); // itkOptimizer->SetMachinePrecisionTolerance(): itkOptimizer->SetOrthantwiseCoefficient(0); itkOptimizer->SetOrthantwiseStart(0); itkOptimizer->SetOrthantwiseEnd(1); std::cout << "GetValue() before optimizer starts: " << itkOptimizer->GetValue() << std::endl; std::cout << "SetMetric." << std::endl; itkOptimizer->SetMetric(metric); constexpr unsigned int SpaceDimension = 2; OptimizerType::ParametersType initialValue(SpaceDimension); // We start not so far from | 2 -2 | initialValue[0] = 100; initialValue[1] = -100; // Set the initial position by setting the metric // parameters. std::cout << "Set metric parameters." << std::endl; metric->SetParameters(initialValue); itkOptimizer->Print(std::cout); std::cout << "Stop description = " << itkOptimizer->GetStopConditionDescription() << std::endl; std::cout << "Start optimization." << std::endl; try { itkOptimizer->StartOptimization(); } catch (const itk::ExceptionObject & e) { std::cerr << "Exception thrown ! " << std::endl; std::cerr << "An error occurred during Optimization" << std::endl; std::cerr << "Location = " << e.GetLocation() << std::endl; std::cerr << "Description = " << e.GetDescription() << std::endl; return EXIT_FAILURE; } OptimizerType::ParametersType finalPosition; finalPosition = itkOptimizer->GetCurrentPosition(); std::cout << "Solution = (" << finalPosition[0] << "," << finalPosition[1] << ")" << std::endl; std::cout << "End condition = " << itkOptimizer->GetStopConditionDescription() << std::endl; std::cout << "LineSearchAccuracy = " << itkOptimizer->GetLineSearchAccuracy() << std::endl; std::cout << "SolutionAccuracy = " << itkOptimizer->GetSolutionAccuracy() << std::endl; std::cout << "NumberOfIterations = " << itkOptimizer->GetCurrentIteration() << std::endl; // // check results to see if it is within range // bool pass = true; double trueParameters[2] = { 2, -2 }; for (unsigned int j = 0; j < 2; ++j) { if (itk::Math::FloatAlmostEqual(finalPosition[j], trueParameters[j])) { pass = false; } } if (!pass) { std::cout << "Test failed." << std::endl; return EXIT_FAILURE; } // Get the final value of the optimizer std::cout << "Testing GetValue() : "; OptimizerType::MeasureType finalValue = itkOptimizer->GetValue(); if (std::fabs(finalValue + 10.0) > 0.01) { std::cout << "[FAILURE]" << std::endl; return EXIT_FAILURE; } else { std::cout << "[SUCCESS]" << std::endl; } // // Test stopping when number of iterations reached // itkOptimizer->SetMaximumIterations(5); metric->SetParameters(initialValue); try { itkOptimizer->StartOptimization(); } catch (const itk::ExceptionObject & e) { std::cerr << "Exception thrown ! " << std::endl; std::cerr << "An error occurred during Optimization" << std::endl; std::cerr << e << std::endl; return EXIT_FAILURE; } std::cout << "Solution = (" << finalPosition[0] << "," << finalPosition[1] << ")" << std::endl; std::cout << "NumberOfIterations = " << itkOptimizer->GetCurrentIteration() << std::endl; if (itkOptimizer->GetCurrentIteration() != 5) { std::cout << "Not expected number of iterations!" << std::endl; std::cout << "[FAILURE]" << std::endl; return EXIT_FAILURE; } // Test with local-support transform. Should FAIL. // Such transforms are not yet supported. metric->SetHasLocalSupport(true); ITK_TRY_EXPECT_EXCEPTION(itkOptimizer->StartOptimization()); // Test streaming enumeration for LBFGS2Optimizerv4Enums::LineSearchMethod elements const std::set allLineSearchMethod{ itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_DEFAULT, itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_MORETHUENTE, itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_BACKTRACKING_ARMIJO, itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_BACKTRACKING, itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_BACKTRACKING_WOLFE, itk::LBFGS2Optimizerv4Enums::LineSearchMethod::LINESEARCH_BACKTRACKING_STRONG_WOLFE }; for (const auto & ee : allLineSearchMethod) { std::cout << "STREAMED ENUM VALUE LBFGS2Optimizerv4Enums::LineSearchMethod: " << ee << std::endl; } std::cout << "Test passed." << std::endl; return EXIT_SUCCESS; }