Initial commit of Ceres Solver.
diff --git a/internal/ceres/compressed_row_sparse_matrix_test.cc b/internal/ceres/compressed_row_sparse_matrix_test.cc
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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/compressed_row_sparse_matrix.h"
+
+#include "gtest/gtest.h"
+#include "ceres/casts.h"
+#include "ceres/linear_least_squares_problems.h"
+#include "ceres/matrix_proto.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
+
+namespace ceres {
+namespace internal {
+
+void CompareMatrices(const SparseMatrix* a, const SparseMatrix* b) {
+ EXPECT_EQ(a->num_rows(), b->num_rows());
+ EXPECT_EQ(a->num_cols(), b->num_cols());
+
+ int num_rows = a->num_rows();
+ int num_cols = a->num_cols();
+
+ for (int i = 0; i < num_cols; ++i) {
+ Vector x = Vector::Zero(num_cols);
+ x(i) = 1.0;
+
+ Vector y_a = Vector::Zero(num_rows);
+ Vector y_b = Vector::Zero(num_rows);
+
+ a->RightMultiply(x.data(), y_a.data());
+ b->RightMultiply(x.data(), y_b.data());
+
+ EXPECT_EQ((y_a - y_b).norm(), 0);
+ }
+}
+
+class CompressedRowSparseMatrixTest : public ::testing::Test {
+ protected :
+ virtual void SetUp() {
+ scoped_ptr<LinearLeastSquaresProblem> problem(
+ CreateLinearLeastSquaresProblemFromId(1));
+
+ CHECK_NOTNULL(problem.get());
+
+ tsm.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
+ crsm.reset(new CompressedRowSparseMatrix(*tsm));
+
+ num_rows = tsm->num_rows();
+ num_cols = tsm->num_cols();
+ }
+
+ int num_rows;
+ int num_cols;
+
+ scoped_ptr<TripletSparseMatrix> tsm;
+ scoped_ptr<CompressedRowSparseMatrix> crsm;
+};
+
+TEST_F(CompressedRowSparseMatrixTest, RightMultiply) {
+ CompareMatrices(tsm.get(), crsm.get());
+}
+
+TEST_F(CompressedRowSparseMatrixTest, LeftMultiply) {
+ for (int i = 0; i < num_rows; ++i) {
+ Vector a = Vector::Zero(num_rows);
+ a(i) = 1.0;
+
+ Vector b1 = Vector::Zero(num_cols);
+ Vector b2 = Vector::Zero(num_cols);
+
+ tsm->LeftMultiply(a.data(), b1.data());
+ crsm->LeftMultiply(a.data(), b2.data());
+
+ EXPECT_EQ((b1 - b2).norm(), 0);
+ }
+}
+
+TEST_F(CompressedRowSparseMatrixTest, ColumnNorm) {
+ Vector b1 = Vector::Zero(num_cols);
+ Vector b2 = Vector::Zero(num_cols);
+
+ tsm->SquaredColumnNorm(b1.data());
+ crsm->SquaredColumnNorm(b2.data());
+
+ EXPECT_EQ((b1 - b2).norm(), 0);
+}
+
+TEST_F(CompressedRowSparseMatrixTest, Scale) {
+ Vector scale(num_cols);
+ for (int i = 0; i < num_cols; ++i) {
+ scale(i) = i + 1;
+ }
+
+ tsm->ScaleColumns(scale.data());
+ crsm->ScaleColumns(scale.data());
+ CompareMatrices(tsm.get(), crsm.get());
+}
+
+TEST_F(CompressedRowSparseMatrixTest, DeleteRows) {
+ for (int i = 0; i < num_rows; ++i) {
+ tsm->Resize(num_rows - i, num_cols);
+ crsm->DeleteRows(crsm->num_rows() - tsm->num_rows());
+ CompareMatrices(tsm.get(), crsm.get());
+ }
+}
+
+TEST_F(CompressedRowSparseMatrixTest, AppendRows) {
+ for (int i = 0; i < num_rows; ++i) {
+ TripletSparseMatrix tsm_appendage(*tsm);
+ tsm_appendage.Resize(i, num_cols);
+
+ tsm->AppendRows(tsm_appendage);
+ CompressedRowSparseMatrix crsm_appendage(tsm_appendage);
+ crsm->AppendRows(crsm_appendage);
+
+ CompareMatrices(tsm.get(), crsm.get());
+ }
+}
+
+#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+TEST_F(CompressedRowSparseMatrixTest, Serialization) {
+ SparseMatrixProto proto;
+ crsm->ToProto(&proto);
+
+ CompressedRowSparseMatrix n(proto);
+ ASSERT_EQ(n.num_rows(), crsm->num_rows());
+ ASSERT_EQ(n.num_cols(), crsm->num_cols());
+ ASSERT_EQ(n.num_nonzeros(), crsm->num_nonzeros());
+
+ for (int i = 0; i < n.num_rows() + 1; ++i) {
+ ASSERT_EQ(crsm->rows()[i], proto.compressed_row_matrix().rows(i));
+ ASSERT_EQ(crsm->rows()[i], n.rows()[i]);
+ }
+
+ for (int i = 0; i < crsm->num_nonzeros(); ++i) {
+ ASSERT_EQ(crsm->cols()[i], proto.compressed_row_matrix().cols(i));
+ ASSERT_EQ(crsm->cols()[i], n.cols()[i]);
+ ASSERT_EQ(crsm->values()[i], proto.compressed_row_matrix().values(i));
+ ASSERT_EQ(crsm->values()[i], n.values()[i]);
+ }
+}
+#endif
+
+TEST_F(CompressedRowSparseMatrixTest, ToDenseMatrix) {
+ Matrix tsm_dense;
+ Matrix crsm_dense;
+
+ tsm->ToDenseMatrix(&tsm_dense);
+ crsm->ToDenseMatrix(&crsm_dense);
+
+ EXPECT_EQ((tsm_dense - crsm_dense).norm(), 0.0);
+}
+
+} // namespace internal
+} // namespace ceres
