// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2023 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: sameeragarwal@google.com (Sameer Agarwal) #include "ceres/parameter_block_ordering.h" #include #include #include #include #include "ceres/cost_function.h" #include "ceres/graph.h" #include "ceres/problem_impl.h" #include "ceres/program.h" #include "ceres/sized_cost_function.h" #include "ceres/stl_util.h" #include "gtest/gtest.h" namespace ceres::internal { using VertexSet = std::unordered_set; template class DummyCostFunction : public SizedCostFunction { bool Evaluate(double const* const* parameters, double* residuals, double** jacobians) const final { return true; } }; class SchurOrderingTest : public ::testing::Test { protected: void SetUp() final { // The explicit calls to AddParameterBlock are necessary because // the below tests depend on the specific numbering of the // parameter blocks. problem_.AddParameterBlock(x_, 3); problem_.AddParameterBlock(y_, 4); problem_.AddParameterBlock(z_, 5); problem_.AddParameterBlock(w_, 6); problem_.AddResidualBlock(new DummyCostFunction<2, 3>, nullptr, x_); problem_.AddResidualBlock(new DummyCostFunction<6, 5, 4>, nullptr, z_, y_); problem_.AddResidualBlock(new DummyCostFunction<3, 3, 5>, nullptr, x_, z_); problem_.AddResidualBlock(new DummyCostFunction<7, 5, 3>, nullptr, z_, x_); problem_.AddResidualBlock( new DummyCostFunction<1, 5, 3, 6>, nullptr, z_, x_, w_); } ProblemImpl problem_; double x_[3], y_[4], z_[5], w_[6]; }; TEST_F(SchurOrderingTest, NoFixed) { const Program& program = problem_.program(); const std::vector& parameter_blocks = program.parameter_blocks(); auto graph = CreateHessianGraph(program); const VertexSet& vertices = graph->vertices(); EXPECT_EQ(vertices.size(), 4); for (int i = 0; i < 4; ++i) { EXPECT_TRUE(vertices.find(parameter_blocks[i]) != vertices.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[0]); EXPECT_EQ(neighbors.size(), 2); EXPECT_TRUE(neighbors.find(parameter_blocks[2]) != neighbors.end()); EXPECT_TRUE(neighbors.find(parameter_blocks[3]) != neighbors.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[1]); EXPECT_EQ(neighbors.size(), 1); EXPECT_TRUE(neighbors.find(parameter_blocks[2]) != neighbors.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[2]); EXPECT_EQ(neighbors.size(), 3); EXPECT_TRUE(neighbors.find(parameter_blocks[0]) != neighbors.end()); EXPECT_TRUE(neighbors.find(parameter_blocks[1]) != neighbors.end()); EXPECT_TRUE(neighbors.find(parameter_blocks[3]) != neighbors.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[3]); EXPECT_EQ(neighbors.size(), 2); EXPECT_TRUE(neighbors.find(parameter_blocks[0]) != neighbors.end()); EXPECT_TRUE(neighbors.find(parameter_blocks[2]) != neighbors.end()); } } TEST_F(SchurOrderingTest, AllFixed) { problem_.SetParameterBlockConstant(x_); problem_.SetParameterBlockConstant(y_); problem_.SetParameterBlockConstant(z_); problem_.SetParameterBlockConstant(w_); const Program& program = problem_.program(); auto graph = CreateHessianGraph(program); EXPECT_EQ(graph->vertices().size(), 0); } TEST_F(SchurOrderingTest, OneFixed) { problem_.SetParameterBlockConstant(x_); const Program& program = problem_.program(); const std::vector& parameter_blocks = program.parameter_blocks(); auto graph = CreateHessianGraph(program); const VertexSet& vertices = graph->vertices(); EXPECT_EQ(vertices.size(), 3); EXPECT_TRUE(vertices.find(parameter_blocks[0]) == vertices.end()); for (int i = 1; i < 3; ++i) { EXPECT_TRUE(vertices.find(parameter_blocks[i]) != vertices.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[1]); EXPECT_EQ(neighbors.size(), 1); EXPECT_TRUE(neighbors.find(parameter_blocks[2]) != neighbors.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[2]); EXPECT_EQ(neighbors.size(), 2); EXPECT_TRUE(neighbors.find(parameter_blocks[1]) != neighbors.end()); EXPECT_TRUE(neighbors.find(parameter_blocks[3]) != neighbors.end()); } { const VertexSet& neighbors = graph->Neighbors(parameter_blocks[3]); EXPECT_EQ(neighbors.size(), 1); EXPECT_TRUE(neighbors.find(parameter_blocks[2]) != neighbors.end()); } // The constant parameter block is at the end. std::vector ordering; ComputeSchurOrdering(program, &ordering); EXPECT_EQ(ordering.back(), parameter_blocks[0]); } } // namespace ceres::internal