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