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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// 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
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// Author: richie.stebbing@gmail.com (Richard Stebbing)
#include "ceres/dynamic_compressed_row_sparse_matrix.h"
#include <memory>
#include "ceres/casts.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/linear_least_squares_problems.h"
#include "ceres/triplet_sparse_matrix.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
using std::copy;
using std::vector;
class DynamicCompressedRowSparseMatrixTest : public ::testing::Test {
protected:
void SetUp() final {
num_rows = 7;
num_cols = 4;
// The number of additional elements reserved when `Finalize` is called
// should have no effect on the number of rows, columns or nonzeros.
// Set this to some nonzero value to be sure.
num_additional_elements = 13;
expected_num_nonzeros = num_rows * num_cols - std::min(num_rows, num_cols);
InitialiseDenseReference();
InitialiseSparseMatrixReferences();
dcrsm.reset(new DynamicCompressedRowSparseMatrix(num_rows,
num_cols,
0));
}
void Finalize() {
dcrsm->Finalize(num_additional_elements);
}
void InitialiseDenseReference() {
dense.resize(num_rows, num_cols);
dense.setZero();
int num_nonzeros = 0;
for (int i = 0; i < (num_rows * num_cols); ++i) {
const int r = i / num_cols, c = i % num_cols;
if (r != c) {
dense(r, c) = i + 1;
++num_nonzeros;
}
}
ASSERT_EQ(num_nonzeros, expected_num_nonzeros);
}
void InitialiseSparseMatrixReferences() {
vector<int> rows, cols;
vector<double> values;
for (int i = 0; i < (num_rows * num_cols); ++i) {
const int r = i / num_cols, c = i % num_cols;
if (r != c) {
rows.push_back(r);
cols.push_back(c);
values.push_back(i + 1);
}
}
ASSERT_EQ(values.size(), expected_num_nonzeros);
tsm.reset(new TripletSparseMatrix(num_rows,
num_cols,
expected_num_nonzeros));
copy(rows.begin(), rows.end(), tsm->mutable_rows());
copy(cols.begin(), cols.end(), tsm->mutable_cols());
copy(values.begin(), values.end(), tsm->mutable_values());
tsm->set_num_nonzeros(values.size());
Matrix dense_from_tsm;
tsm->ToDenseMatrix(&dense_from_tsm);
ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all());
crsm.reset(CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm));
Matrix dense_from_crsm;
crsm->ToDenseMatrix(&dense_from_crsm);
ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all());
}
void InsertNonZeroEntriesFromDenseReference() {
for (int r = 0; r < num_rows; ++r) {
for (int c = 0; c < num_cols; ++c) {
const double& v = dense(r, c);
if (v != 0.0) {
dcrsm->InsertEntry(r, c, v);
}
}
}
}
void ExpectEmpty() {
EXPECT_EQ(dcrsm->num_rows(), num_rows);
EXPECT_EQ(dcrsm->num_cols(), num_cols);
EXPECT_EQ(dcrsm->num_nonzeros(), 0);
Matrix dense_from_dcrsm;
dcrsm->ToDenseMatrix(&dense_from_dcrsm);
EXPECT_EQ(dense_from_dcrsm.rows(), num_rows);
EXPECT_EQ(dense_from_dcrsm.cols(), num_cols);
EXPECT_TRUE((dense_from_dcrsm.array() == 0.0).all());
}
void ExpectEqualToDenseReference() {
Matrix dense_from_dcrsm;
dcrsm->ToDenseMatrix(&dense_from_dcrsm);
EXPECT_TRUE((dense.array() == dense_from_dcrsm.array()).all());
}
void ExpectEqualToCompressedRowSparseMatrixReference() {
typedef Eigen::Map<const Eigen::VectorXi> ConstIntVectorRef;
ConstIntVectorRef crsm_rows(crsm->rows(), crsm->num_rows() + 1);
ConstIntVectorRef dcrsm_rows(dcrsm->rows(), dcrsm->num_rows() + 1);
EXPECT_TRUE((crsm_rows.array() == dcrsm_rows.array()).all());
ConstIntVectorRef crsm_cols(crsm->cols(), crsm->num_nonzeros());
ConstIntVectorRef dcrsm_cols(dcrsm->cols(), dcrsm->num_nonzeros());
EXPECT_TRUE((crsm_cols.array() == dcrsm_cols.array()).all());
ConstVectorRef crsm_values(crsm->values(), crsm->num_nonzeros());
ConstVectorRef dcrsm_values(dcrsm->values(), dcrsm->num_nonzeros());
EXPECT_TRUE((crsm_values.array() == dcrsm_values.array()).all());
}
int num_rows;
int num_cols;
int num_additional_elements;
int expected_num_nonzeros;
Matrix dense;
std::unique_ptr<TripletSparseMatrix> tsm;
std::unique_ptr<CompressedRowSparseMatrix> crsm;
std::unique_ptr<DynamicCompressedRowSparseMatrix> dcrsm;
};
TEST_F(DynamicCompressedRowSparseMatrixTest, Initialization) {
ExpectEmpty();
Finalize();
ExpectEmpty();
}
TEST_F(DynamicCompressedRowSparseMatrixTest, InsertEntryAndFinalize) {
InsertNonZeroEntriesFromDenseReference();
ExpectEmpty();
Finalize();
ExpectEqualToDenseReference();
ExpectEqualToCompressedRowSparseMatrixReference();
}
TEST_F(DynamicCompressedRowSparseMatrixTest, ClearRows) {
InsertNonZeroEntriesFromDenseReference();
Finalize();
ExpectEqualToDenseReference();
ExpectEqualToCompressedRowSparseMatrixReference();
dcrsm->ClearRows(0, 0);
Finalize();
ExpectEqualToDenseReference();
ExpectEqualToCompressedRowSparseMatrixReference();
dcrsm->ClearRows(0, num_rows);
ExpectEqualToCompressedRowSparseMatrixReference();
Finalize();
ExpectEmpty();
InsertNonZeroEntriesFromDenseReference();
dcrsm->ClearRows(1, 2);
Finalize();
dense.block(1, 0, 2, num_cols).setZero();
ExpectEqualToDenseReference();
InitialiseDenseReference();
}
} // namespace internal
} // namespace ceres