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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2014 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: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/reorder_program.h"
#include "ceres/parameter_block.h"
#include "ceres/problem_impl.h"
#include "ceres/program.h"
#include "ceres/sized_cost_function.h"
#include "ceres/solver.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
// Templated base class for the CostFunction signatures.
template <int kNumResiduals, int N0, int N1, int N2>
class MockCostFunctionBase : public
SizedCostFunction<kNumResiduals, N0, N1, N2> {
public:
virtual bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const {
// Do nothing. This is never called.
return true;
}
};
class UnaryCostFunction : public MockCostFunctionBase<2, 1, 0, 0> {};
class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1, 0> {};
class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {};
TEST(_, ReorderResidualBlockNormalFunction) {
ProblemImpl problem;
double x;
double y;
double z;
problem.AddParameterBlock(&x, 1);
problem.AddParameterBlock(&y, 1);
problem.AddParameterBlock(&z, 1);
problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);
problem.AddResidualBlock(new BinaryCostFunction(), NULL, &z, &x);
problem.AddResidualBlock(new BinaryCostFunction(), NULL, &z, &y);
problem.AddResidualBlock(new UnaryCostFunction(), NULL, &z);
problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);
problem.AddResidualBlock(new UnaryCostFunction(), NULL, &y);
ParameterBlockOrdering* linear_solver_ordering = new ParameterBlockOrdering;
linear_solver_ordering->AddElementToGroup(&x, 0);
linear_solver_ordering->AddElementToGroup(&y, 0);
linear_solver_ordering->AddElementToGroup(&z, 1);
Solver::Options options;
options.linear_solver_type = DENSE_SCHUR;
options.linear_solver_ordering.reset(linear_solver_ordering);
const vector<ResidualBlock*>& residual_blocks =
problem.program().residual_blocks();
vector<ResidualBlock*> expected_residual_blocks;
// This is a bit fragile, but it serves the purpose. We know the
// bucketing algorithm that the reordering function uses, so we
// expect the order for residual blocks for each e_block to be
// filled in reverse.
expected_residual_blocks.push_back(residual_blocks[4]);
expected_residual_blocks.push_back(residual_blocks[1]);
expected_residual_blocks.push_back(residual_blocks[0]);
expected_residual_blocks.push_back(residual_blocks[5]);
expected_residual_blocks.push_back(residual_blocks[2]);
expected_residual_blocks.push_back(residual_blocks[3]);
Program* program = problem.mutable_program();
program->SetParameterOffsetsAndIndex();
string message;
EXPECT_TRUE(LexicographicallyOrderResidualBlocks(
2,
problem.mutable_program(),
&message));
EXPECT_EQ(residual_blocks.size(), expected_residual_blocks.size());
for (int i = 0; i < expected_residual_blocks.size(); ++i) {
EXPECT_EQ(residual_blocks[i], expected_residual_blocks[i]);
}
}
TEST(_, ApplyOrderingOrderingTooSmall) {
ProblemImpl problem;
double x;
double y;
double z;
problem.AddParameterBlock(&x, 1);
problem.AddParameterBlock(&y, 1);
problem.AddParameterBlock(&z, 1);
ParameterBlockOrdering linear_solver_ordering;
linear_solver_ordering.AddElementToGroup(&x, 0);
linear_solver_ordering.AddElementToGroup(&y, 1);
Program program(problem.program());
string message;
EXPECT_FALSE(ApplyOrdering(problem.parameter_map(),
linear_solver_ordering,
&program,
&message));
}
TEST(_, ApplyOrderingNormal) {
ProblemImpl problem;
double x;
double y;
double z;
problem.AddParameterBlock(&x, 1);
problem.AddParameterBlock(&y, 1);
problem.AddParameterBlock(&z, 1);
ParameterBlockOrdering linear_solver_ordering;
linear_solver_ordering.AddElementToGroup(&x, 0);
linear_solver_ordering.AddElementToGroup(&y, 2);
linear_solver_ordering.AddElementToGroup(&z, 1);
Program* program = problem.mutable_program();
string message;
EXPECT_TRUE(ApplyOrdering(problem.parameter_map(),
linear_solver_ordering,
program,
&message));
const vector<ParameterBlock*>& parameter_blocks = program->parameter_blocks();
EXPECT_EQ(parameter_blocks.size(), 3);
EXPECT_EQ(parameter_blocks[0]->user_state(), &x);
EXPECT_EQ(parameter_blocks[1]->user_state(), &z);
EXPECT_EQ(parameter_blocks[2]->user_state(), &y);
}
} // namespace internal
} // namespace ceres