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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 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/block_sparse_matrix.h"
#include <string>
#include "ceres/casts.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/linear_least_squares_problems.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
class BlockSparseMatrixTest : public ::testing::Test {
protected :
virtual void SetUp() {
scoped_ptr<LinearLeastSquaresProblem> problem(
CreateLinearLeastSquaresProblemFromId(2));
CHECK_NOTNULL(problem.get());
A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
problem.reset(CreateLinearLeastSquaresProblemFromId(1));
CHECK_NOTNULL(problem.get());
B_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
CHECK_EQ(A_->num_rows(), B_->num_rows());
CHECK_EQ(A_->num_cols(), B_->num_cols());
CHECK_EQ(A_->num_nonzeros(), B_->num_nonzeros());
}
scoped_ptr<BlockSparseMatrix> A_;
scoped_ptr<TripletSparseMatrix> B_;
};
TEST_F(BlockSparseMatrixTest, SetZeroTest) {
A_->SetZero();
EXPECT_EQ(13, A_->num_nonzeros());
}
TEST_F(BlockSparseMatrixTest, RightMultiplyTest) {
Vector y_a = Vector::Zero(A_->num_rows());
Vector y_b = Vector::Zero(A_->num_rows());
for (int i = 0; i < A_->num_cols(); ++i) {
Vector x = Vector::Zero(A_->num_cols());
x[i] = 1.0;
A_->RightMultiply(x.data(), y_a.data());
B_->RightMultiply(x.data(), y_b.data());
EXPECT_LT((y_a - y_b).norm(), 1e-12);
}
}
TEST_F(BlockSparseMatrixTest, LeftMultiplyTest) {
Vector y_a = Vector::Zero(A_->num_cols());
Vector y_b = Vector::Zero(A_->num_cols());
for (int i = 0; i < A_->num_rows(); ++i) {
Vector x = Vector::Zero(A_->num_rows());
x[i] = 1.0;
A_->LeftMultiply(x.data(), y_a.data());
B_->LeftMultiply(x.data(), y_b.data());
EXPECT_LT((y_a - y_b).norm(), 1e-12);
}
}
TEST_F(BlockSparseMatrixTest, SquaredColumnNormTest) {
Vector y_a = Vector::Zero(A_->num_cols());
Vector y_b = Vector::Zero(A_->num_cols());
A_->SquaredColumnNorm(y_a.data());
B_->SquaredColumnNorm(y_b.data());
EXPECT_LT((y_a - y_b).norm(), 1e-12);
}
TEST_F(BlockSparseMatrixTest, ToDenseMatrixTest) {
Matrix m_a;
Matrix m_b;
A_->ToDenseMatrix(&m_a);
B_->ToDenseMatrix(&m_b);
EXPECT_LT((m_a - m_b).norm(), 1e-12);
}
} // namespace internal
} // namespace ceres
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