436 lines
14 KiB
C++
436 lines
14 KiB
C++
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/program.h"
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#include <limits>
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#include <cmath>
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#include <vector>
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#include "ceres/sized_cost_function.h"
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#include "ceres/problem_impl.h"
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#include "ceres/residual_block.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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using std::string;
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using std::vector;
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// A cost function that simply returns its argument.
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class UnaryIdentityCostFunction : public SizedCostFunction<1, 1> {
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public:
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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residuals[0] = parameters[0][0];
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if (jacobians != NULL && jacobians[0] != NULL) {
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jacobians[0][0] = 1.0;
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}
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return true;
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}
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};
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// Templated base class for the CostFunction signatures.
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template <int kNumResiduals, int N0, int N1, int N2>
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class MockCostFunctionBase : public
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SizedCostFunction<kNumResiduals, N0, N1, N2> {
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public:
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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for (int i = 0; i < kNumResiduals; ++i) {
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residuals[i] = kNumResiduals + N0 + N1 + N2;
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}
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return true;
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}
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};
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class UnaryCostFunction : public MockCostFunctionBase<2, 1, 0, 0> {};
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class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1, 0> {};
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class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {};
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TEST(Program, RemoveFixedBlocksNothingConstant) {
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ProblemImpl problem;
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double x;
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double y;
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double z;
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problem.AddParameterBlock(&x, 1);
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problem.AddParameterBlock(&y, 1);
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problem.AddParameterBlock(&z, 1);
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problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);
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problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);
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problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 3);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 3);
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EXPECT_EQ(removed_parameter_blocks.size(), 0);
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EXPECT_EQ(fixed_cost, 0.0);
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}
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TEST(Program, RemoveFixedBlocksAllParameterBlocksConstant) {
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ProblemImpl problem;
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double x = 1.0;
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problem.AddParameterBlock(&x, 1);
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problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);
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problem.SetParameterBlockConstant(&x);
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 0);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 0);
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EXPECT_EQ(removed_parameter_blocks.size(), 1);
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EXPECT_EQ(removed_parameter_blocks[0], &x);
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EXPECT_EQ(fixed_cost, 9.0);
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}
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TEST(Program, RemoveFixedBlocksNoResidualBlocks) {
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ProblemImpl problem;
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double x;
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double y;
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double z;
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problem.AddParameterBlock(&x, 1);
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problem.AddParameterBlock(&y, 1);
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problem.AddParameterBlock(&z, 1);
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 0);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 0);
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EXPECT_EQ(removed_parameter_blocks.size(), 3);
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EXPECT_EQ(fixed_cost, 0.0);
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}
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TEST(Program, RemoveFixedBlocksOneParameterBlockConstant) {
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ProblemImpl problem;
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double x;
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double y;
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double z;
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problem.AddParameterBlock(&x, 1);
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problem.AddParameterBlock(&y, 1);
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problem.AddParameterBlock(&z, 1);
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problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);
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problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);
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problem.SetParameterBlockConstant(&x);
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 1);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 1);
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}
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TEST(Program, RemoveFixedBlocksNumEliminateBlocks) {
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ProblemImpl problem;
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double x;
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double y;
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double z;
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problem.AddParameterBlock(&x, 1);
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problem.AddParameterBlock(&y, 1);
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problem.AddParameterBlock(&z, 1);
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problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);
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problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);
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problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);
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problem.SetParameterBlockConstant(&x);
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 2);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 2);
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}
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TEST(Program, RemoveFixedBlocksFixedCost) {
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ProblemImpl problem;
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double x = 1.23;
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double y = 4.56;
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double z = 7.89;
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problem.AddParameterBlock(&x, 1);
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problem.AddParameterBlock(&y, 1);
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problem.AddParameterBlock(&z, 1);
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problem.AddResidualBlock(new UnaryIdentityCostFunction(), NULL, &x);
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problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);
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problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);
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problem.SetParameterBlockConstant(&x);
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ResidualBlock *expected_removed_block =
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problem.program().residual_blocks()[0];
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scoped_array<double> scratch(
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new double[expected_removed_block->NumScratchDoublesForEvaluate()]);
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double expected_fixed_cost;
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expected_removed_block->Evaluate(true,
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&expected_fixed_cost,
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NULL,
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NULL,
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scratch.get());
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vector<double*> removed_parameter_blocks;
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double fixed_cost = 0.0;
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string message;
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scoped_ptr<Program> reduced_program(
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CHECK_NOTNULL(problem
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.program()
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.CreateReducedProgram(&removed_parameter_blocks,
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&fixed_cost,
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&message)));
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EXPECT_EQ(reduced_program->NumParameterBlocks(), 2);
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EXPECT_EQ(reduced_program->NumResidualBlocks(), 2);
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EXPECT_DOUBLE_EQ(fixed_cost, expected_fixed_cost);
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}
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TEST(Program, CreateJacobianBlockSparsityTranspose) {
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ProblemImpl problem;
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double x[2];
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double y[3];
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double z;
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problem.AddParameterBlock(x, 2);
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problem.AddParameterBlock(y, 3);
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problem.AddParameterBlock(&z, 1);
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problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 0, 0>(), NULL, x);
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problem.AddResidualBlock(new MockCostFunctionBase<3, 1, 2, 0>(), NULL, &z, x);
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problem.AddResidualBlock(new MockCostFunctionBase<4, 1, 3, 0>(), NULL, &z, y);
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problem.AddResidualBlock(new MockCostFunctionBase<5, 1, 3, 0>(), NULL, &z, y);
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problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 1, 0>(), NULL, x, &z);
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problem.AddResidualBlock(new MockCostFunctionBase<2, 1, 3, 0>(), NULL, &z, y);
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problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 1, 0>(), NULL, x, &z);
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problem.AddResidualBlock(new MockCostFunctionBase<1, 3, 0, 0>(), NULL, y);
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TripletSparseMatrix expected_block_sparse_jacobian(3, 8, 14);
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{
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int* rows = expected_block_sparse_jacobian.mutable_rows();
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int* cols = expected_block_sparse_jacobian.mutable_cols();
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double* values = expected_block_sparse_jacobian.mutable_values();
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rows[0] = 0;
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cols[0] = 0;
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rows[1] = 2;
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cols[1] = 1;
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rows[2] = 0;
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cols[2] = 1;
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rows[3] = 2;
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cols[3] = 2;
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rows[4] = 1;
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cols[4] = 2;
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rows[5] = 2;
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cols[5] = 3;
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rows[6] = 1;
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cols[6] = 3;
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rows[7] = 0;
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cols[7] = 4;
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rows[8] = 2;
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cols[8] = 4;
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rows[9] = 2;
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cols[9] = 5;
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rows[10] = 1;
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cols[10] = 5;
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rows[11] = 0;
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cols[11] = 6;
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rows[12] = 2;
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cols[12] = 6;
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rows[13] = 1;
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cols[13] = 7;
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std::fill(values, values + 14, 1.0);
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expected_block_sparse_jacobian.set_num_nonzeros(14);
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}
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Program* program = problem.mutable_program();
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program->SetParameterOffsetsAndIndex();
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scoped_ptr<TripletSparseMatrix> actual_block_sparse_jacobian(
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program->CreateJacobianBlockSparsityTranspose());
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Matrix expected_dense_jacobian;
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expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian);
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Matrix actual_dense_jacobian;
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actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian);
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EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0);
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}
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template <int kNumResiduals, int kNumParameterBlocks>
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class NumParameterBlocksCostFunction : public CostFunction {
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public:
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NumParameterBlocksCostFunction() {
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set_num_residuals(kNumResiduals);
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for (int i = 0; i < kNumParameterBlocks; ++i) {
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mutable_parameter_block_sizes()->push_back(1);
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}
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}
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virtual ~NumParameterBlocksCostFunction() {
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}
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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return true;
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}
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};
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TEST(Program, ReallocationInCreateJacobianBlockSparsityTranspose) {
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// CreateJacobianBlockSparsityTranspose starts with a conservative
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// estimate of the size of the sparsity pattern. This test ensures
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// that when those estimates are violated, the reallocation/resizing
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// logic works correctly.
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ProblemImpl problem;
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double x[20];
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vector<double*> parameter_blocks;
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for (int i = 0; i < 20; ++i) {
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problem.AddParameterBlock(x + i, 1);
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parameter_blocks.push_back(x + i);
|
||
|
|
}
|
||
|
|
|
||
|
|
problem.AddResidualBlock(new NumParameterBlocksCostFunction<1, 20>(),
|
||
|
|
NULL,
|
||
|
|
parameter_blocks);
|
||
|
|
|
||
|
|
TripletSparseMatrix expected_block_sparse_jacobian(20, 1, 20);
|
||
|
|
{
|
||
|
|
int* rows = expected_block_sparse_jacobian.mutable_rows();
|
||
|
|
int* cols = expected_block_sparse_jacobian.mutable_cols();
|
||
|
|
for (int i = 0; i < 20; ++i) {
|
||
|
|
rows[i] = i;
|
||
|
|
cols[i] = 0;
|
||
|
|
}
|
||
|
|
|
||
|
|
double* values = expected_block_sparse_jacobian.mutable_values();
|
||
|
|
std::fill(values, values + 20, 1.0);
|
||
|
|
expected_block_sparse_jacobian.set_num_nonzeros(20);
|
||
|
|
}
|
||
|
|
|
||
|
|
Program* program = problem.mutable_program();
|
||
|
|
program->SetParameterOffsetsAndIndex();
|
||
|
|
|
||
|
|
scoped_ptr<TripletSparseMatrix> actual_block_sparse_jacobian(
|
||
|
|
program->CreateJacobianBlockSparsityTranspose());
|
||
|
|
|
||
|
|
Matrix expected_dense_jacobian;
|
||
|
|
expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian);
|
||
|
|
|
||
|
|
Matrix actual_dense_jacobian;
|
||
|
|
actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian);
|
||
|
|
EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Program, ProblemHasNanParameterBlocks) {
|
||
|
|
ProblemImpl problem;
|
||
|
|
double x[2];
|
||
|
|
x[0] = 1.0;
|
||
|
|
x[1] = std::numeric_limits<double>::quiet_NaN();
|
||
|
|
problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);
|
||
|
|
string error;
|
||
|
|
EXPECT_FALSE(problem.program().ParameterBlocksAreFinite(&error));
|
||
|
|
EXPECT_NE(error.find("has at least one invalid value"),
|
||
|
|
string::npos) << error;
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Program, InfeasibleParameterBlock) {
|
||
|
|
ProblemImpl problem;
|
||
|
|
double x[] = {0.0, 0.0};
|
||
|
|
problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);
|
||
|
|
problem.SetParameterLowerBound(x, 0, 2.0);
|
||
|
|
problem.SetParameterUpperBound(x, 0, 1.0);
|
||
|
|
string error;
|
||
|
|
EXPECT_FALSE(problem.program().IsFeasible(&error));
|
||
|
|
EXPECT_NE(error.find("infeasible bound"), string::npos) << error;
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Program, InfeasibleConstantParameterBlock) {
|
||
|
|
ProblemImpl problem;
|
||
|
|
double x[] = {0.0, 0.0};
|
||
|
|
problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);
|
||
|
|
problem.SetParameterLowerBound(x, 0, 1.0);
|
||
|
|
problem.SetParameterUpperBound(x, 0, 2.0);
|
||
|
|
problem.SetParameterBlockConstant(x);
|
||
|
|
string error;
|
||
|
|
EXPECT_FALSE(problem.program().IsFeasible(&error));
|
||
|
|
EXPECT_NE(error.find("infeasible value"), string::npos) << error;
|
||
|
|
}
|
||
|
|
|
||
|
|
} // namespace internal
|
||
|
|
} // namespace ceres
|