|  | // Ceres Solver - A fast non-linear least squares minimizer | 
|  | // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. | 
|  | // http://code.google.com/p/ceres-solver/ | 
|  | // | 
|  | // 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: wjr@google.com (William Rucklidge) | 
|  | // | 
|  | // Tests for the conditioned cost function. | 
|  |  | 
|  | #include "ceres/conditioned_cost_function.h" | 
|  |  | 
|  | #include "gtest/gtest.h" | 
|  | #include "ceres/internal/eigen.h" | 
|  | #include "ceres/normal_prior.h" | 
|  | #include "ceres/types.h" | 
|  |  | 
|  | namespace ceres { | 
|  | namespace internal { | 
|  |  | 
|  | // The size of the cost functions we build. | 
|  | static const int kTestCostFunctionSize = 3; | 
|  |  | 
|  | // A simple cost function: return ax + b. | 
|  | class LinearCostFunction : public CostFunction { | 
|  | public: | 
|  | LinearCostFunction(double a, double b) : a_(a), b_(b) { | 
|  | set_num_residuals(1); | 
|  | mutable_parameter_block_sizes()->push_back(1); | 
|  | } | 
|  |  | 
|  | virtual bool Evaluate(double const* const* parameters, | 
|  | double* residuals, | 
|  | double** jacobians) const { | 
|  | *residuals = **parameters * a_ + b_; | 
|  | if (jacobians && *jacobians) { | 
|  | **jacobians = a_; | 
|  | } | 
|  |  | 
|  | return true; | 
|  | } | 
|  |  | 
|  | private: | 
|  | const double a_, b_; | 
|  | }; | 
|  |  | 
|  | // Tests that ConditionedCostFunction does what it's supposed to. | 
|  | TEST(CostFunctionTest, ConditionedCostFunction) { | 
|  | double v1[kTestCostFunctionSize], v2[kTestCostFunctionSize], | 
|  | jac[kTestCostFunctionSize * kTestCostFunctionSize], | 
|  | result[kTestCostFunctionSize]; | 
|  |  | 
|  | for (int i = 0; i < kTestCostFunctionSize; i++) { | 
|  | v1[i] = i; | 
|  | v2[i] = i * 10; | 
|  | // Seed a few garbage values in the Jacobian matrix, to make sure that | 
|  | // they're overwritten. | 
|  | jac[i * 2] = i * i; | 
|  | result[i] = i * i * i; | 
|  | } | 
|  |  | 
|  | // Make a cost function that computes x - v2 | 
|  | VectorRef v2_vector(v2, kTestCostFunctionSize, 1); | 
|  | Matrix identity(kTestCostFunctionSize, kTestCostFunctionSize); | 
|  | identity.setIdentity(); | 
|  | NormalPrior* difference_cost_function = new NormalPrior(identity, v2_vector); | 
|  |  | 
|  | vector<CostFunction*> conditioners; | 
|  | for (int i = 0; i < kTestCostFunctionSize; i++) { | 
|  | conditioners.push_back(new LinearCostFunction(i + 2, i * 7)); | 
|  | } | 
|  |  | 
|  | ConditionedCostFunction conditioned_cost_function(difference_cost_function, | 
|  | conditioners, | 
|  | TAKE_OWNERSHIP); | 
|  | EXPECT_EQ(difference_cost_function->num_residuals(), | 
|  | conditioned_cost_function.num_residuals()); | 
|  | EXPECT_EQ(difference_cost_function->parameter_block_sizes(), | 
|  | conditioned_cost_function.parameter_block_sizes()); | 
|  |  | 
|  | double *parameters[1]; | 
|  | parameters[0] = v1; | 
|  | double *jacs[1]; | 
|  | jacs[0] = jac; | 
|  |  | 
|  | conditioned_cost_function.Evaluate(parameters, result, jacs); | 
|  | for (int i = 0; i < kTestCostFunctionSize; i++) { | 
|  | EXPECT_DOUBLE_EQ((i + 2) * (v1[i] - v2[i]) + i * 7, result[i]); | 
|  | } | 
|  |  | 
|  | for (int i = 0; i < kTestCostFunctionSize; i++) { | 
|  | for (int j = 0; j < kTestCostFunctionSize; j++) { | 
|  | double actual = jac[i * kTestCostFunctionSize + j]; | 
|  | if (i != j) { | 
|  | EXPECT_DOUBLE_EQ(0, actual); | 
|  | } else { | 
|  | EXPECT_DOUBLE_EQ(i + 2, actual); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | }  // namespace internal | 
|  | }  // namespace ceres |