Keir Mierle | 8ebb073 | 2012-04-30 23:09:08 -0700 | [diff] [blame] | 1 | // Ceres Solver - A fast non-linear least squares minimizer |
| 2 | // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. |
| 3 | // http://code.google.com/p/ceres-solver/ |
| 4 | // |
| 5 | // Redistribution and use in source and binary forms, with or without |
| 6 | // modification, are permitted provided that the following conditions are met: |
| 7 | // |
| 8 | // * Redistributions of source code must retain the above copyright notice, |
| 9 | // this list of conditions and the following disclaimer. |
| 10 | // * Redistributions in binary form must reproduce the above copyright notice, |
| 11 | // this list of conditions and the following disclaimer in the documentation |
| 12 | // and/or other materials provided with the distribution. |
| 13 | // * Neither the name of Google Inc. nor the names of its contributors may be |
| 14 | // used to endorse or promote products derived from this software without |
| 15 | // specific prior written permission. |
| 16 | // |
| 17 | // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| 18 | // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| 19 | // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| 20 | // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| 21 | // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| 22 | // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| 23 | // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| 24 | // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| 25 | // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| 26 | // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| 27 | // POSSIBILITY OF SUCH DAMAGE. |
| 28 | // |
| 29 | // Author: wjr@google.com (William Rucklidge) |
| 30 | // |
| 31 | // Tests for the conditioned cost function. |
| 32 | |
| 33 | #include "ceres/conditioned_cost_function.h" |
| 34 | |
Keir Mierle | 8ebb073 | 2012-04-30 23:09:08 -0700 | [diff] [blame] | 35 | #include "ceres/internal/eigen.h" |
| 36 | #include "ceres/normal_prior.h" |
| 37 | #include "ceres/types.h" |
Sameer Agarwal | 0beab86 | 2012-08-13 15:12:01 -0700 | [diff] [blame] | 38 | #include "gtest/gtest.h" |
Keir Mierle | 8ebb073 | 2012-04-30 23:09:08 -0700 | [diff] [blame] | 39 | |
| 40 | namespace ceres { |
| 41 | namespace internal { |
| 42 | |
| 43 | // The size of the cost functions we build. |
| 44 | static const int kTestCostFunctionSize = 3; |
| 45 | |
| 46 | // A simple cost function: return ax + b. |
| 47 | class LinearCostFunction : public CostFunction { |
| 48 | public: |
| 49 | LinearCostFunction(double a, double b) : a_(a), b_(b) { |
| 50 | set_num_residuals(1); |
| 51 | mutable_parameter_block_sizes()->push_back(1); |
| 52 | } |
| 53 | |
| 54 | virtual bool Evaluate(double const* const* parameters, |
| 55 | double* residuals, |
| 56 | double** jacobians) const { |
| 57 | *residuals = **parameters * a_ + b_; |
| 58 | if (jacobians && *jacobians) { |
| 59 | **jacobians = a_; |
| 60 | } |
| 61 | |
| 62 | return true; |
| 63 | } |
| 64 | |
| 65 | private: |
| 66 | const double a_, b_; |
| 67 | }; |
| 68 | |
| 69 | // Tests that ConditionedCostFunction does what it's supposed to. |
| 70 | TEST(CostFunctionTest, ConditionedCostFunction) { |
| 71 | double v1[kTestCostFunctionSize], v2[kTestCostFunctionSize], |
| 72 | jac[kTestCostFunctionSize * kTestCostFunctionSize], |
| 73 | result[kTestCostFunctionSize]; |
| 74 | |
| 75 | for (int i = 0; i < kTestCostFunctionSize; i++) { |
| 76 | v1[i] = i; |
| 77 | v2[i] = i * 10; |
| 78 | // Seed a few garbage values in the Jacobian matrix, to make sure that |
| 79 | // they're overwritten. |
| 80 | jac[i * 2] = i * i; |
| 81 | result[i] = i * i * i; |
| 82 | } |
| 83 | |
| 84 | // Make a cost function that computes x - v2 |
| 85 | VectorRef v2_vector(v2, kTestCostFunctionSize, 1); |
| 86 | Matrix identity(kTestCostFunctionSize, kTestCostFunctionSize); |
| 87 | identity.setIdentity(); |
| 88 | NormalPrior* difference_cost_function = new NormalPrior(identity, v2_vector); |
| 89 | |
| 90 | vector<CostFunction*> conditioners; |
| 91 | for (int i = 0; i < kTestCostFunctionSize; i++) { |
| 92 | conditioners.push_back(new LinearCostFunction(i + 2, i * 7)); |
| 93 | } |
| 94 | |
| 95 | ConditionedCostFunction conditioned_cost_function(difference_cost_function, |
| 96 | conditioners, |
| 97 | TAKE_OWNERSHIP); |
| 98 | EXPECT_EQ(difference_cost_function->num_residuals(), |
| 99 | conditioned_cost_function.num_residuals()); |
| 100 | EXPECT_EQ(difference_cost_function->parameter_block_sizes(), |
| 101 | conditioned_cost_function.parameter_block_sizes()); |
| 102 | |
| 103 | double *parameters[1]; |
| 104 | parameters[0] = v1; |
| 105 | double *jacs[1]; |
| 106 | jacs[0] = jac; |
| 107 | |
| 108 | conditioned_cost_function.Evaluate(parameters, result, jacs); |
| 109 | for (int i = 0; i < kTestCostFunctionSize; i++) { |
| 110 | EXPECT_DOUBLE_EQ((i + 2) * (v1[i] - v2[i]) + i * 7, result[i]); |
| 111 | } |
| 112 | |
| 113 | for (int i = 0; i < kTestCostFunctionSize; i++) { |
| 114 | for (int j = 0; j < kTestCostFunctionSize; j++) { |
| 115 | double actual = jac[i * kTestCostFunctionSize + j]; |
| 116 | if (i != j) { |
| 117 | EXPECT_DOUBLE_EQ(0, actual); |
| 118 | } else { |
| 119 | EXPECT_DOUBLE_EQ(i + 2, actual); |
| 120 | } |
| 121 | } |
| 122 | } |
| 123 | } |
| 124 | |
| 125 | } // namespace internal |
| 126 | } // namespace ceres |