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ceres-solver/internal/ceres/linear_least_squares_problems.cc
T
Sameer Agarwal c4a329155c Enable support for dumping trust region minimizer problems. 
This support was broken due to the TrustRegionMinimizer refactoring.
It is now enabled again, with the responsibilty for dumping the
problem shifted to the individual TrustRegionStrategy.

There is however one wrinkle, which is perhaps an indication of
poor design to start with. The LinearLeastSquaresProblemProto
carries in it num_eliminate_blocks, something which does not
exist anymore. More importantly, the TrustRegionStrategy does not
have access to this quantity anymore.

Dealing with this will be the subject of a future change.

Change-Id: I358adf6a2e386f4940b617bf950d6c7e87d2635d
2013-06-13 22:00:48 -07:00

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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/linear_least_squares_problems.h"
#include <cstdio>
#include <string>
#include <vector>
#include "ceres/block_sparse_matrix.h"
#include "ceres/block_structure.h"
#include "ceres/casts.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/file.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/matrix_proto.h"
#include "ceres/stringprintf.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromId(int id) {
switch (id) {
case 0:
return LinearLeastSquaresProblem0();
case 1:
return LinearLeastSquaresProblem1();
case 2:
return LinearLeastSquaresProblem2();
case 3:
return LinearLeastSquaresProblem3();
default:
LOG(FATAL) << "Unknown problem id requested " << id;
}
return NULL;
}
#ifndef CERES_NO_PROTOCOL_BUFFERS
LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
const string& filename) {
LinearLeastSquaresProblemProto problem_proto;
{
string serialized_proto;
ReadFileToStringOrDie(filename, &serialized_proto);
CHECK(problem_proto.ParseFromString(serialized_proto));
}
LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
const SparseMatrixProto& A = problem_proto.a();
if (A.has_block_matrix()) {
problem->A.reset(new BlockSparseMatrix(A));
} else if (A.has_triplet_matrix()) {
problem->A.reset(new TripletSparseMatrix(A));
} else {
problem->A.reset(new CompressedRowSparseMatrix(A));
}
if (problem_proto.b_size() > 0) {
problem->b.reset(new double[problem_proto.b_size()]);
for (int i = 0; i < problem_proto.b_size(); ++i) {
problem->b[i] = problem_proto.b(i);
}
}
if (problem_proto.d_size() > 0) {
problem->D.reset(new double[problem_proto.d_size()]);
for (int i = 0; i < problem_proto.d_size(); ++i) {
problem->D[i] = problem_proto.d(i);
}
}
if (problem_proto.d_size() > 0) {
if (problem_proto.x_size() > 0) {
problem->x_D.reset(new double[problem_proto.x_size()]);
for (int i = 0; i < problem_proto.x_size(); ++i) {
problem->x_D[i] = problem_proto.x(i);
}
}
} else {
if (problem_proto.x_size() > 0) {
problem->x.reset(new double[problem_proto.x_size()]);
for (int i = 0; i < problem_proto.x_size(); ++i) {
problem->x[i] = problem_proto.x(i);
}
}
}
problem->num_eliminate_blocks = 0;
if (problem_proto.has_num_eliminate_blocks()) {
problem->num_eliminate_blocks = problem_proto.num_eliminate_blocks();
}
return problem;
}
#else
LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
const string& filename) {
LOG(FATAL)
<< "Loading a least squares problem from disk requires "
<< "Ceres to be built with Protocol Buffers support.";
return NULL;
}
#endif // CERES_NO_PROTOCOL_BUFFERS
/*
A = [1 2]
[3 4]
[6 -10]
b = [ 8
18
-18]
x = [2
3]
D = [1
2]
x_D = [1.78448275;
2.82327586;]
*/
LinearLeastSquaresProblem* LinearLeastSquaresProblem0() {
LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
TripletSparseMatrix* A = new TripletSparseMatrix(3, 2, 6);
problem->b.reset(new double[3]);
problem->D.reset(new double[2]);
problem->x.reset(new double[2]);
problem->x_D.reset(new double[2]);
int* Ai = A->mutable_rows();
int* Aj = A->mutable_cols();
double* Ax = A->mutable_values();
int counter = 0;
for (int i = 0; i < 3; ++i) {
for (int j = 0; j< 2; ++j) {
Ai[counter]=i;
Aj[counter]=j;
++counter;
}
};
Ax[0] = 1.;
Ax[1] = 2.;
Ax[2] = 3.;
Ax[3] = 4.;
Ax[4] = 6;
Ax[5] = -10;
A->set_num_nonzeros(6);
problem->A.reset(A);
problem->b[0] = 8;
problem->b[1] = 18;
problem->b[2] = -18;
problem->x[0] = 2.0;
problem->x[1] = 3.0;
problem->D[0] = 1;
problem->D[1] = 2;
problem->x_D[0] = 1.78448275;
problem->x_D[1] = 2.82327586;
return problem;
}
/*
A = [1 0 | 2 0 0
3 0 | 0 4 0
0 5 | 0 0 6
0 7 | 8 0 0
0 9 | 1 0 0
0 0 | 1 1 1]
b = [0
1
2
3
4
5]
c = A'* b = [ 3
67
33
9
17]
A'A = [10 0 2 12 0
0 155 65 0 30
2 65 70 1 1
12 0 1 17 1
0 30 1 1 37]
S = [ 42.3419 -1.4000 -11.5806
-1.4000 2.6000 1.0000
11.5806 1.0000 31.1935]
r = [ 4.3032
5.4000
5.0323]
S\r = [ 0.2102
2.1367
0.1388]
A\b = [-2.3061
0.3172
0.2102
2.1367
0.1388]
*/
// The following two functions create a TripletSparseMatrix and a
// BlockSparseMatrix version of this problem.
// TripletSparseMatrix version.
LinearLeastSquaresProblem* LinearLeastSquaresProblem1() {
int num_rows = 6;
int num_cols = 5;
LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
TripletSparseMatrix* A = new TripletSparseMatrix(num_rows,
num_cols,
num_rows * num_cols);
problem->b.reset(new double[num_rows]);
problem->D.reset(new double[num_cols]);
problem->num_eliminate_blocks = 2;
int* rows = A->mutable_rows();
int* cols = A->mutable_cols();
double* values = A->mutable_values();
int nnz = 0;
// Row 1
{
rows[nnz] = 0;
cols[nnz] = 0;
values[nnz++] = 1;
rows[nnz] = 0;
cols[nnz] = 2;
values[nnz++] = 2;
}
// Row 2
{
rows[nnz] = 1;
cols[nnz] = 0;
values[nnz++] = 3;
rows[nnz] = 1;
cols[nnz] = 3;
values[nnz++] = 4;
}
// Row 3
{
rows[nnz] = 2;
cols[nnz] = 1;
values[nnz++] = 5;
rows[nnz] = 2;
cols[nnz] = 4;
values[nnz++] = 6;
}
// Row 4
{
rows[nnz] = 3;
cols[nnz] = 1;
values[nnz++] = 7;
rows[nnz] = 3;
cols[nnz] = 2;
values[nnz++] = 8;
}
// Row 5
{
rows[nnz] = 4;
cols[nnz] = 1;
values[nnz++] = 9;
rows[nnz] = 4;
cols[nnz] = 2;
values[nnz++] = 1;
}
// Row 6
{
rows[nnz] = 5;
cols[nnz] = 2;
values[nnz++] = 1;
rows[nnz] = 5;
cols[nnz] = 3;
values[nnz++] = 1;
rows[nnz] = 5;
cols[nnz] = 4;
values[nnz++] = 1;
}
A->set_num_nonzeros(nnz);
CHECK(A->IsValid());
problem->A.reset(A);
for (int i = 0; i < num_cols; ++i) {
problem->D.get()[i] = 1;
}
for (int i = 0; i < num_rows; ++i) {
problem->b.get()[i] = i;
}
return problem;
}
// BlockSparseMatrix version
LinearLeastSquaresProblem* LinearLeastSquaresProblem2() {
int num_rows = 6;
int num_cols = 5;
LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
problem->b.reset(new double[num_rows]);
problem->D.reset(new double[num_cols]);
problem->num_eliminate_blocks = 2;
CompressedRowBlockStructure* bs = new CompressedRowBlockStructure;
scoped_array<double> values(new double[num_rows * num_cols]);
for (int c = 0; c < num_cols; ++c) {
bs->cols.push_back(Block());
bs->cols.back().size = 1;
bs->cols.back().position = c;
}
int nnz = 0;
// Row 1
{
values[nnz++] = 1;
values[nnz++] = 2;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 0;
row.cells.push_back(Cell(0, 0));
row.cells.push_back(Cell(2, 1));
}
// Row 2
{
values[nnz++] = 3;
values[nnz++] = 4;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 1;
row.cells.push_back(Cell(0, 2));
row.cells.push_back(Cell(3, 3));
}
// Row 3
{
values[nnz++] = 5;
values[nnz++] = 6;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 2;
row.cells.push_back(Cell(1, 4));
row.cells.push_back(Cell(4, 5));
}
// Row 4
{
values[nnz++] = 7;
values[nnz++] = 8;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 3;
row.cells.push_back(Cell(1, 6));
row.cells.push_back(Cell(2, 7));
}
// Row 5
{
values[nnz++] = 9;
values[nnz++] = 1;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 4;
row.cells.push_back(Cell(1, 8));
row.cells.push_back(Cell(2, 9));
}
// Row 6
{
values[nnz++] = 1;
values[nnz++] = 1;
values[nnz++] = 1;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 5;
row.cells.push_back(Cell(2, 10));
row.cells.push_back(Cell(3, 11));
row.cells.push_back(Cell(4, 12));
}
BlockSparseMatrix* A = new BlockSparseMatrix(bs);
memcpy(A->mutable_values(), values.get(), nnz * sizeof(*A->values()));
for (int i = 0; i < num_cols; ++i) {
problem->D.get()[i] = 1;
}
for (int i = 0; i < num_rows; ++i) {
problem->b.get()[i] = i;
}
problem->A.reset(A);
return problem;
}
/*
A = [1 0
3 0
0 5
0 7
0 9
0 0]
b = [0
1
2
3
4
5]
*/
// BlockSparseMatrix version
LinearLeastSquaresProblem* LinearLeastSquaresProblem3() {
int num_rows = 5;
int num_cols = 2;
LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem;
problem->b.reset(new double[num_rows]);
problem->D.reset(new double[num_cols]);
problem->num_eliminate_blocks = 2;
CompressedRowBlockStructure* bs = new CompressedRowBlockStructure;
scoped_array<double> values(new double[num_rows * num_cols]);
for (int c = 0; c < num_cols; ++c) {
bs->cols.push_back(Block());
bs->cols.back().size = 1;
bs->cols.back().position = c;
}
int nnz = 0;
// Row 1
{
values[nnz++] = 1;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 0;
row.cells.push_back(Cell(0, 0));
}
// Row 2
{
values[nnz++] = 3;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 1;
row.cells.push_back(Cell(0, 1));
}
// Row 3
{
values[nnz++] = 5;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 2;
row.cells.push_back(Cell(1, 2));
}
// Row 4
{
values[nnz++] = 7;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 3;
row.cells.push_back(Cell(1, 3));
}
// Row 5
{
values[nnz++] = 9;
bs->rows.push_back(CompressedRow());
CompressedRow& row = bs->rows.back();
row.block.size = 1;
row.block.position = 4;
row.cells.push_back(Cell(1, 4));
}
BlockSparseMatrix* A = new BlockSparseMatrix(bs);
memcpy(A->mutable_values(), values.get(), nnz * sizeof(*A->values()));
for (int i = 0; i < num_cols; ++i) {
problem->D.get()[i] = 1;
}
for (int i = 0; i < num_rows; ++i) {
problem->b.get()[i] = i;
}
problem->A.reset(A);
return problem;
}
namespace {
bool DumpLinearLeastSquaresProblemToConsole(const SparseMatrix* A,
const double* D,
const double* b,
const double* x,
int num_eliminate_blocks) {
CHECK_NOTNULL(A);
Matrix AA;
A->ToDenseMatrix(&AA);
LOG(INFO) << "A^T: \n" << AA.transpose();
if (D != NULL) {
LOG(INFO) << "A's appended diagonal:\n"
<< ConstVectorRef(D, A->num_cols());
}
if (b != NULL) {
LOG(INFO) << "b: \n" << ConstVectorRef(b, A->num_rows());
}
if (x != NULL) {
LOG(INFO) << "x: \n" << ConstVectorRef(x, A->num_cols());
}
return true;
};
#ifndef CERES_NO_PROTOCOL_BUFFERS
bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& filename_base,
const SparseMatrix* A,
const double* D,
const double* b,
const double* x,
int num_eliminate_blocks) {
CHECK_NOTNULL(A);
LinearLeastSquaresProblemProto lsqp;
A->ToProto(lsqp.mutable_a());
if (D != NULL) {
for (int i = 0; i < A->num_cols(); ++i) {
lsqp.add_d(D[i]);
}
}
if (b != NULL) {
for (int i = 0; i < A->num_rows(); ++i) {
lsqp.add_b(b[i]);
}
}
if (x != NULL) {
for (int i = 0; i < A->num_cols(); ++i) {
lsqp.add_x(x[i]);
}
}
lsqp.set_num_eliminate_blocks(num_eliminate_blocks);
const string filename = filename_base + ".bin";
LOG(INFO) << "Dumping least squares problem to disk. File: " << filename;
WriteStringToFileOrDie(lsqp.SerializeAsString(), filename);
return true;
}
#else
bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& filename_base,
const SparseMatrix* A,
const double* D,
const double* b,
const double* x,
int num_eliminate_blocks) {
LOG(ERROR) << "Dumping least squares problems is only "
<< "supported when Ceres is compiled with "
<< "protocol buffer support.";
return false;
}
#endif
void WriteArrayToFileOrDie(const string& filename,
const double* x,
const int size) {
CHECK_NOTNULL(x);
VLOG(2) << "Writing array to: " << filename;
FILE* fptr = fopen(filename.c_str(), "w");
CHECK_NOTNULL(fptr);
for (int i = 0; i < size; ++i) {
fprintf(fptr, "%17f\n", x[i]);
}
fclose(fptr);
}
bool DumpLinearLeastSquaresProblemToTextFile(const string& filename_base,
const SparseMatrix* A,
const double* D,
const double* b,
const double* x,
int num_eliminate_blocks) {
CHECK_NOTNULL(A);
LOG(INFO) << "writing to: " << filename_base << "*";
string matlab_script;
StringAppendF(&matlab_script,
"function lsqp = load_trust_region_problem()\n");
StringAppendF(&matlab_script,
"lsqp.num_rows = %d;\n", A->num_rows());
StringAppendF(&matlab_script,
"lsqp.num_cols = %d;\n", A->num_cols());
{
string filename = filename_base + "_A.txt";
FILE* fptr = fopen(filename.c_str(), "w");
CHECK_NOTNULL(fptr);
A->ToTextFile(fptr);
fclose(fptr);
StringAppendF(&matlab_script,
"tmp = load('%s', '-ascii');\n", filename.c_str());
StringAppendF(
&matlab_script,
"lsqp.A = sparse(tmp(:, 1) + 1, tmp(:, 2) + 1, tmp(:, 3), %d, %d);\n",
A->num_rows(),
A->num_cols());
}
if (D != NULL) {
string filename = filename_base + "_D.txt";
WriteArrayToFileOrDie(filename, D, A->num_cols());
StringAppendF(&matlab_script,
"lsqp.D = load('%s', '-ascii');\n", filename.c_str());
}
if (b != NULL) {
string filename = filename_base + "_b.txt";
WriteArrayToFileOrDie(filename, b, A->num_rows());
StringAppendF(&matlab_script,
"lsqp.b = load('%s', '-ascii');\n", filename.c_str());
}
if (x != NULL) {
string filename = filename_base + "_x.txt";
WriteArrayToFileOrDie(filename, x, A->num_cols());
StringAppendF(&matlab_script,
"lsqp.x = load('%s', '-ascii');\n", filename.c_str());
}
string matlab_filename = filename_base + ".m";
WriteStringToFileOrDie(matlab_script, matlab_filename);
return true;
}
} // namespace
bool DumpLinearLeastSquaresProblem(const string& filename_base,
DumpFormatType dump_format_type,
const SparseMatrix* A,
const double* D,
const double* b,
const double* x,
int num_eliminate_blocks) {
switch (dump_format_type) {
case CONSOLE:
return DumpLinearLeastSquaresProblemToConsole(A, D, b, x,
num_eliminate_blocks);
case PROTOBUF:
return DumpLinearLeastSquaresProblemToProtocolBuffer(
filename_base,
A, D, b, x,
num_eliminate_blocks);
case TEXTFILE:
return DumpLinearLeastSquaresProblemToTextFile(filename_base,
A, D, b, x,
num_eliminate_blocks);
default:
LOG(FATAL) << "Unknown DumpFormatType " << dump_format_type;
};
return true;
}
} // namespace internal
} // namespace ceres
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