| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111 | // Ceres Solver - A fast non-linear least squares minimizer// Copyright 2015 Google Inc. All rights reserved.// http://ceres-solver.org///// Redistribution and use in source and binary forms, with or without// modification, are permitted provided that the following conditions are met://// * Redistributions of source code must retain the above copyright notice,//   this list of conditions and the following disclaimer.// * Redistributions in binary form must reproduce the above copyright notice,//   this list of conditions and the following disclaimer in the documentation//   and/or other materials provided with the distribution.// * Neither the name of Google Inc. nor the names of its contributors may be//   used to endorse or promote products derived from this software without//   specific prior written permission.//// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE// POSSIBILITY OF SUCH DAMAGE.//// Author: strandmark@google.com (Petter Strandmark)#include "ceres/gradient_problem.h"#include "gtest/gtest.h"namespace ceres {namespace internal {class QuadraticTestFunction : public ceres::FirstOrderFunction { public:  explicit QuadraticTestFunction(bool* flag_to_set_on_destruction = NULL)      : flag_to_set_on_destruction_(flag_to_set_on_destruction) {}  virtual ~QuadraticTestFunction() {    if (flag_to_set_on_destruction_) {      *flag_to_set_on_destruction_ = true;    }  }  virtual bool Evaluate(const double* parameters,                        double* cost,                        double* gradient) const {    const double x = parameters[0];    cost[0] = x * x;    if (gradient != NULL) {      gradient[0] = 2.0 * x;    }    return true;  }  virtual int NumParameters() const { return 1; } private:  bool* flag_to_set_on_destruction_;};TEST(GradientProblem, TakesOwnershipOfFirstOrderFunction) {  bool is_destructed = false;  {    ceres::GradientProblem problem(new QuadraticTestFunction(&is_destructed));  }  EXPECT_TRUE(is_destructed);}TEST(GradientProblem, EvaluationWithoutParameterizationOrGradient) {  ceres::GradientProblem problem(new QuadraticTestFunction());  double x = 7.0;  double cost = 0;  problem.Evaluate(&x, &cost, NULL);  EXPECT_EQ(x * x, cost);}TEST(GradientProblem, EvalutaionWithParameterizationAndNoGradient) {  ceres::GradientProblem problem(new QuadraticTestFunction(),                                 new IdentityParameterization(1));  double x = 7.0;  double cost = 0;  problem.Evaluate(&x, &cost, NULL);  EXPECT_EQ(x * x, cost);}TEST(GradientProblem, EvaluationWithoutParameterizationAndWithGradient) {  ceres::GradientProblem problem(new QuadraticTestFunction());  double x = 7.0;  double cost = 0;  double gradient = 0;  problem.Evaluate(&x, &cost, &gradient);  EXPECT_EQ(2.0 * x, gradient);}TEST(GradientProblem, EvaluationWithParameterizationAndWithGradient) {  ceres::GradientProblem problem(new QuadraticTestFunction(),                                 new IdentityParameterization(1));  double x = 7.0;  double cost = 0;  double gradient = 0;  problem.Evaluate(&x, &cost, &gradient);  EXPECT_EQ(2.0 * x, gradient);}}  // namespace internal}  // namespace ceres
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