| // 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: keir@google.com (Keir Mierle) |
| |
| #include "ceres/residual_block.h" |
| |
| #include <cstdint> |
| |
| #include "ceres/internal/eigen.h" |
| #include "ceres/manifold.h" |
| #include "ceres/parameter_block.h" |
| #include "ceres/sized_cost_function.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres::internal { |
| |
| using std::vector; |
| |
| // Trivial cost function that accepts three arguments. |
| class TernaryCostFunction : public CostFunction { |
| public: |
| TernaryCostFunction(int num_residuals, |
| int32_t parameter_block1_size, |
| int32_t parameter_block2_size, |
| int32_t parameter_block3_size) { |
| set_num_residuals(num_residuals); |
| mutable_parameter_block_sizes()->push_back(parameter_block1_size); |
| mutable_parameter_block_sizes()->push_back(parameter_block2_size); |
| mutable_parameter_block_sizes()->push_back(parameter_block3_size); |
| } |
| |
| bool Evaluate(double const* const* parameters, |
| double* residuals, |
| double** jacobians) const final { |
| for (int i = 0; i < num_residuals(); ++i) { |
| residuals[i] = i; |
| } |
| if (jacobians) { |
| for (int k = 0; k < 3; ++k) { |
| if (jacobians[k] != nullptr) { |
| MatrixRef jacobian( |
| jacobians[k], num_residuals(), parameter_block_sizes()[k]); |
| jacobian.setConstant(k); |
| } |
| } |
| } |
| return true; |
| } |
| }; |
| |
| TEST(ResidualBlock, EvaluateWithNoLossFunctionOrManifolds) { |
| double scratch[64]; |
| |
| // Prepare the parameter blocks. |
| double values_x[2]; |
| ParameterBlock x(values_x, 2, -1); |
| |
| double values_y[3]; |
| ParameterBlock y(values_y, 3, -1); |
| |
| double values_z[4]; |
| ParameterBlock z(values_z, 4, -1); |
| |
| vector<ParameterBlock*> parameters; |
| parameters.push_back(&x); |
| parameters.push_back(&y); |
| parameters.push_back(&z); |
| |
| TernaryCostFunction cost_function(3, 2, 3, 4); |
| |
| // Create the object under tests. |
| ResidualBlock residual_block(&cost_function, nullptr, parameters, -1); |
| |
| // Verify getters. |
| EXPECT_EQ(&cost_function, residual_block.cost_function()); |
| EXPECT_EQ(nullptr, residual_block.loss_function()); |
| EXPECT_EQ(parameters[0], residual_block.parameter_blocks()[0]); |
| EXPECT_EQ(parameters[1], residual_block.parameter_blocks()[1]); |
| EXPECT_EQ(parameters[2], residual_block.parameter_blocks()[2]); |
| EXPECT_EQ(3, residual_block.NumScratchDoublesForEvaluate()); |
| |
| // Verify cost-only evaluation. |
| double cost; |
| residual_block.Evaluate(true, &cost, nullptr, nullptr, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| |
| // Verify cost and residual evaluation. |
| double residuals[3]; |
| residual_block.Evaluate(true, &cost, residuals, nullptr, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| // Verify cost, residual, and jacobian evaluation. |
| cost = 0.0; |
| VectorRef(residuals, 3).setConstant(0.0); |
| |
| Matrix jacobian_rx(3, 2); |
| Matrix jacobian_ry(3, 3); |
| Matrix jacobian_rz(3, 4); |
| |
| jacobian_rx.setConstant(-1.0); |
| jacobian_ry.setConstant(-1.0); |
| jacobian_rz.setConstant(-1.0); |
| |
| double* jacobian_ptrs[3] = { |
| jacobian_rx.data(), jacobian_ry.data(), jacobian_rz.data()}; |
| |
| residual_block.Evaluate(true, &cost, residuals, jacobian_ptrs, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| EXPECT_TRUE((jacobian_rx.array() == 0.0).all()) << "\n" << jacobian_rx; |
| EXPECT_TRUE((jacobian_ry.array() == 1.0).all()) << "\n" << jacobian_ry; |
| EXPECT_TRUE((jacobian_rz.array() == 2.0).all()) << "\n" << jacobian_rz; |
| |
| // Verify cost, residual, and partial jacobian evaluation. |
| cost = 0.0; |
| VectorRef(residuals, 3).setConstant(0.0); |
| jacobian_rx.setConstant(-1.0); |
| jacobian_ry.setConstant(-1.0); |
| jacobian_rz.setConstant(-1.0); |
| |
| jacobian_ptrs[1] = nullptr; // Don't compute the jacobian for y. |
| |
| residual_block.Evaluate(true, &cost, residuals, jacobian_ptrs, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| // clang-format off |
| EXPECT_TRUE((jacobian_rx.array() == 0.0).all()) << "\n" << jacobian_rx; |
| EXPECT_TRUE((jacobian_ry.array() == -1.0).all()) << "\n" << jacobian_ry; |
| EXPECT_TRUE((jacobian_rz.array() == 2.0).all()) << "\n" << jacobian_rz; |
| // clang-format on |
| } |
| |
| // Trivial cost function that accepts three arguments. |
| class LocallyParameterizedCostFunction : public SizedCostFunction<3, 2, 3, 4> { |
| public: |
| bool Evaluate(double const* const* parameters, |
| double* residuals, |
| double** jacobians) const final { |
| for (int i = 0; i < num_residuals(); ++i) { |
| residuals[i] = i; |
| } |
| if (jacobians) { |
| for (int k = 0; k < 3; ++k) { |
| // The jacobians here are full sized, but they are transformed in the |
| // evaluator into the "local" jacobian. In the tests, the |
| // "SubsetManifold" is used, which should pick out columns from these |
| // jacobians. Put values in the jacobian that make this obvious; in |
| // particular, make the jacobians like this: |
| // |
| // 0 1 2 3 4 ... |
| // 0 1 2 3 4 ... |
| // 0 1 2 3 4 ... |
| // |
| if (jacobians[k] != nullptr) { |
| MatrixRef jacobian( |
| jacobians[k], num_residuals(), parameter_block_sizes()[k]); |
| for (int j = 0; j < k + 2; ++j) { |
| jacobian.col(j).setConstant(j); |
| } |
| } |
| } |
| } |
| return true; |
| } |
| }; |
| |
| TEST(ResidualBlock, EvaluateWithManifolds) { |
| double scratch[64]; |
| |
| // Prepare the parameter blocks. |
| double values_x[2]; |
| ParameterBlock x(values_x, 2, -1); |
| |
| double values_y[3]; |
| ParameterBlock y(values_y, 3, -1); |
| |
| double values_z[4]; |
| ParameterBlock z(values_z, 4, -1); |
| |
| vector<ParameterBlock*> parameters; |
| parameters.push_back(&x); |
| parameters.push_back(&y); |
| parameters.push_back(&z); |
| |
| // Make x have the first component fixed. |
| vector<int> x_fixed; |
| x_fixed.push_back(0); |
| SubsetManifold x_manifold(2, x_fixed); |
| x.SetManifold(&x_manifold); |
| |
| // Make z have the last and last component fixed. |
| vector<int> z_fixed; |
| z_fixed.push_back(2); |
| SubsetManifold z_manifold(4, z_fixed); |
| z.SetManifold(&z_manifold); |
| |
| LocallyParameterizedCostFunction cost_function; |
| |
| // Create the object under tests. |
| ResidualBlock residual_block(&cost_function, nullptr, parameters, -1); |
| |
| // Verify getters. |
| EXPECT_EQ(&cost_function, residual_block.cost_function()); |
| EXPECT_EQ(nullptr, residual_block.loss_function()); |
| EXPECT_EQ(parameters[0], residual_block.parameter_blocks()[0]); |
| EXPECT_EQ(parameters[1], residual_block.parameter_blocks()[1]); |
| EXPECT_EQ(parameters[2], residual_block.parameter_blocks()[2]); |
| EXPECT_EQ(3 * (2 + 4) + 3, residual_block.NumScratchDoublesForEvaluate()); |
| |
| // Verify cost-only evaluation. |
| double cost; |
| residual_block.Evaluate(true, &cost, nullptr, nullptr, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| |
| // Verify cost and residual evaluation. |
| double residuals[3]; |
| residual_block.Evaluate(true, &cost, residuals, nullptr, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| // Verify cost, residual, and jacobian evaluation. |
| cost = 0.0; |
| VectorRef(residuals, 3).setConstant(0.0); |
| |
| Matrix jacobian_rx(3, 1); // Since the first element is fixed. |
| Matrix jacobian_ry(3, 3); |
| Matrix jacobian_rz(3, 3); // Since the third element is fixed. |
| |
| jacobian_rx.setConstant(-1.0); |
| jacobian_ry.setConstant(-1.0); |
| jacobian_rz.setConstant(-1.0); |
| |
| double* jacobian_ptrs[3] = { |
| jacobian_rx.data(), jacobian_ry.data(), jacobian_rz.data()}; |
| |
| residual_block.Evaluate(true, &cost, residuals, jacobian_ptrs, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| // clang-format off |
| |
| Matrix expected_jacobian_rx(3, 1); |
| expected_jacobian_rx << 1.0, 1.0, 1.0; |
| |
| Matrix expected_jacobian_ry(3, 3); |
| expected_jacobian_ry << 0.0, 1.0, 2.0, |
| 0.0, 1.0, 2.0, |
| 0.0, 1.0, 2.0; |
| |
| Matrix expected_jacobian_rz(3, 3); |
| expected_jacobian_rz << 0.0, 1.0, /* 2.0, */ 3.0, // 3rd parameter constant. |
| 0.0, 1.0, /* 2.0, */ 3.0, |
| 0.0, 1.0, /* 2.0, */ 3.0; |
| |
| EXPECT_EQ(expected_jacobian_rx, jacobian_rx) |
| << "\nExpected:\n" << expected_jacobian_rx |
| << "\nActual:\n" << jacobian_rx; |
| EXPECT_EQ(expected_jacobian_ry, jacobian_ry) |
| << "\nExpected:\n" << expected_jacobian_ry |
| << "\nActual:\n" << jacobian_ry; |
| EXPECT_EQ(expected_jacobian_rz, jacobian_rz) |
| << "\nExpected:\n " << expected_jacobian_rz |
| << "\nActual:\n" << jacobian_rz; |
| |
| // clang-format on |
| |
| // Verify cost, residual, and partial jacobian evaluation. |
| cost = 0.0; |
| VectorRef(residuals, 3).setConstant(0.0); |
| jacobian_rx.setConstant(-1.0); |
| jacobian_ry.setConstant(-1.0); |
| jacobian_rz.setConstant(-1.0); |
| |
| jacobian_ptrs[1] = nullptr; // Don't compute the jacobian for y. |
| |
| residual_block.Evaluate(true, &cost, residuals, jacobian_ptrs, scratch); |
| EXPECT_EQ(0.5 * (0 * 0 + 1 * 1 + 2 * 2), cost); |
| EXPECT_EQ(0.0, residuals[0]); |
| EXPECT_EQ(1.0, residuals[1]); |
| EXPECT_EQ(2.0, residuals[2]); |
| |
| EXPECT_EQ(expected_jacobian_rx, jacobian_rx); |
| EXPECT_TRUE((jacobian_ry.array() == -1.0).all()) << "\n" << jacobian_ry; |
| EXPECT_EQ(expected_jacobian_rz, jacobian_rz); |
| } |
| |
| } // namespace ceres::internal |