// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2013 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)
// mierle@gmail.com (Keir Mierle)
#include "ceres/problem_impl.h"
#include <algorithm>
#include <cstddef>
#include <iterator>
#include <set>
#include <string>
#include <utility>
#include <vector>
#include "ceres/casts.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/cost_function.h"
#include "ceres/crs_matrix.h"
#include "ceres/evaluator.h"
#include "ceres/loss_function.h"
#include "ceres/map_util.h"
#include "ceres/parameter_block.h"
#include "ceres/program.h"
#include "ceres/residual_block.h"
#include "ceres/stl_util.h"
#include "ceres/stringprintf.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
typedef map<double*, internal::ParameterBlock*> ParameterMap;
namespace {
internal::ParameterBlock* FindParameterBlockOrDie(
const ParameterMap& parameter_map,
double* parameter_block) {
ParameterMap::const_iterator it = parameter_map.find(parameter_block);
CHECK(it != parameter_map.end())
<< "Parameter block not found: " << parameter_block;
return it->second;
}
// Returns true if two regions of memory, a and b, with sizes size_a and size_b
// respectively, overlap.
bool RegionsAlias(const double* a, int size_a,
const double* b, int size_b) {
return (a < b) ? b < (a + size_a)
: a < (b + size_b);
}
void CheckForNoAliasing(double* existing_block,
int existing_block_size,
double* new_block,
int new_block_size) {
CHECK(!RegionsAlias(existing_block, existing_block_size,
new_block, new_block_size))
<< "Aliasing detected between existing parameter block at memory "
<< "location " << existing_block
<< " and has size " << existing_block_size << " with new parameter "
<< "block that has memory address " << new_block << " and would have "
<< "size " << new_block_size << ".";
}
} // namespace
ParameterBlock* ProblemImpl::InternalAddParameterBlock(double* values,
int size) {
CHECK(values != NULL) << "Null pointer passed to AddParameterBlock "
<< "for a parameter with size " << size;
// Ignore the request if there is a block for the given pointer already.
ParameterMap::iterator it = parameter_block_map_.find(values);
if (it != parameter_block_map_.end()) {
if (!options_.disable_all_safety_checks) {
int existing_size = it->second->Size();
CHECK(size == existing_size)
<< "Tried adding a parameter block with the same double pointer, "
<< values << ", twice, but with different block sizes. Original "
<< "size was " << existing_size << " but new size is "
<< size;
}
return it->second;
}
if (!options_.disable_all_safety_checks) {
// Before adding the parameter block, also check that it doesn't alias any
// other parameter blocks.
if (!parameter_block_map_.empty()) {
ParameterMap::iterator lb = parameter_block_map_.lower_bound(values);
// If lb is not the first block, check the previous block for aliasing.
if (lb != parameter_block_map_.begin()) {
ParameterMap::iterator previous = lb;
--previous;
CheckForNoAliasing(previous->first,
previous->second->Size(),
values,
size);
}
// If lb is not off the end, check lb for aliasing.
if (lb != parameter_block_map_.end()) {
CheckForNoAliasing(lb->first,
lb->second->Size(),
values,
size);
}
}
}
// Pass the index of the new parameter block as well to keep the index in
// sync with the position of the parameter in the program's parameter vector.
ParameterBlock* new_parameter_block =
new ParameterBlock(values, size, program_->parameter_blocks_.size());
// For dynamic problems, add the list of dependent residual blocks, which is
// empty to start.
if (options_.enable_fast_removal) {
new_parameter_block->EnableResidualBlockDependencies();
}
parameter_block_map_[values] = new_parameter_block;
program_->parameter_blocks_.push_back(new_parameter_block);
return new_parameter_block;
}
void ProblemImpl::InternalRemoveResidualBlock(ResidualBlock* residual_block) {
CHECK_NOTNULL(residual_block);
// Perform no check on the validity of residual_block, that is handled in
// the public method: RemoveResidualBlock().
// If needed, remove the parameter dependencies on this residual block.
if (options_.enable_fast_removal) {
const int num_parameter_blocks_for_residual =
residual_block->NumParameterBlocks();
for (int i = 0; i < num_parameter_blocks_for_residual; ++i) {
residual_block->parameter_blocks()[i]
->RemoveResidualBlock(residual_block);
}
ResidualBlockSet::iterator it = residual_block_set_.find(residual_block);
residual_block_set_.erase(it);
}
DeleteBlockInVector(program_->mutable_residual_blocks(), residual_block);
}
// Deletes the residual block in question, assuming there are no other
// references to it inside the problem (e.g. by another parameter). Referenced
// cost and loss functions are tucked away for future deletion, since it is not
// possible to know whether other parts of the problem depend on them without
// doing a full scan.
void ProblemImpl::DeleteBlock(ResidualBlock* residual_block) {
// The const casts here are legit, since ResidualBlock holds these
// pointers as const pointers but we have ownership of them and
// have the right to destroy them when the destructor is called.
if (options_.cost_function_ownership == TAKE_OWNERSHIP &&
residual_block->cost_function() != NULL) {
cost_functions_to_delete_.push_back(
const_cast<CostFunction*>(residual_block->cost_function()));
}
if (options_.loss_function_ownership == TAKE_OWNERSHIP &&
residual_block->loss_function() != NULL) {
loss_functions_to_delete_.push_back(
const_cast<LossFunction*>(residual_block->loss_function()));
}
delete residual_block;
}
// Deletes the parameter block in question, assuming there are no other
// references to it inside the problem (e.g. by any residual blocks).
// Referenced parameterizations are tucked away for future deletion, since it
// is not possible to know whether other parts of the problem depend on them
// without doing a full scan.
void ProblemImpl::DeleteBlock(ParameterBlock* parameter_block) {
if (options_.local_parameterization_ownership == TAKE_OWNERSHIP &&
parameter_block->local_parameterization() != NULL) {
local_parameterizations_to_delete_.push_back(
parameter_block->mutable_local_parameterization());
}
parameter_block_map_.erase(parameter_block->mutable_user_state());
delete parameter_block;
}
ProblemImpl::ProblemImpl() : program_(new internal::Program) {}
ProblemImpl::ProblemImpl(const Problem::Options& options)
: options_(options),
program_(new internal::Program) {}
ProblemImpl::~ProblemImpl() {
// Collect the unique cost/loss functions and delete the residuals.
const int num_residual_blocks = program_->residual_blocks_.size();
cost_functions_to_delete_.reserve(num_residual_blocks);
loss_functions_to_delete_.reserve(num_residual_blocks);
for (int i = 0; i < program_->residual_blocks_.size(); ++i) {
DeleteBlock(program_->residual_blocks_[i]);
}
// Collect the unique parameterizations and delete the parameters.
for (int i = 0; i < program_->parameter_blocks_.size(); ++i) {
DeleteBlock(program_->parameter_blocks_[i]);
}
// Delete the owned cost/loss functions and parameterizations.
STLDeleteUniqueContainerPointers(local_parameterizations_to_delete_.begin(),
local_parameterizations_to_delete_.end());
STLDeleteUniqueContainerPointers(cost_functions_to_delete_.begin(),
cost_functions_to_delete_.end());
STLDeleteUniqueContainerPointers(loss_functions_to_delete_.begin(),
loss_functions_to_delete_.end());
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
const vector<double*>& parameter_blocks) {
CHECK_NOTNULL(cost_function);
CHECK_EQ(parameter_blocks.size(),
cost_function->parameter_block_sizes().size());
// Check the sizes match.
const vector<int32>& parameter_block_sizes =
cost_function->parameter_block_sizes();
if (!options_.disable_all_safety_checks) {
CHECK_EQ(parameter_block_sizes.size(), parameter_blocks.size())
<< "Number of blocks input is different than the number of blocks "
<< "that the cost function expects.";
// Check for duplicate parameter blocks.
vector<double*> sorted_parameter_blocks(parameter_blocks);
sort(sorted_parameter_blocks.begin(), sorted_parameter_blocks.end());
vector<double*>::const_iterator duplicate_items =
unique(sorted_parameter_blocks.begin(),
sorted_parameter_blocks.end());
if (duplicate_items != sorted_parameter_blocks.end()) {
string blocks;
for (int i = 0; i < parameter_blocks.size(); ++i) {
blocks += StringPrintf(" %p ", parameter_blocks[i]);
}
LOG(FATAL) << "Duplicate parameter blocks in a residual parameter "
<< "are not allowed. Parameter block pointers: ["
<< blocks << "]";
}
}
// Add parameter blocks and convert the double*'s to parameter blocks.
vector<ParameterBlock*> parameter_block_ptrs(parameter_blocks.size());
for (int i = 0; i < parameter_blocks.size(); ++i) {
parameter_block_ptrs[i] =
InternalAddParameterBlock(parameter_blocks[i],
parameter_block_sizes[i]);
}
if (!options_.disable_all_safety_checks) {
// Check that the block sizes match the block sizes expected by the
// cost_function.
for (int i = 0; i < parameter_block_ptrs.size(); ++i) {
CHECK_EQ(cost_function->parameter_block_sizes()[i],
parameter_block_ptrs[i]->Size())
<< "The cost function expects parameter block " << i
<< " of size " << cost_function->parameter_block_sizes()[i]
<< " but was given a block of size "
<< parameter_block_ptrs[i]->Size();
}
}
ResidualBlock* new_residual_block =
new ResidualBlock(cost_function,
loss_function,
parameter_block_ptrs,
program_->residual_blocks_.size());
// Add dependencies on the residual to the parameter blocks.
if (options_.enable_fast_removal) {
for (int i = 0; i < parameter_blocks.size(); ++i) {
parameter_block_ptrs[i]->AddResidualBlock(new_residual_block);
}
}
program_->residual_blocks_.push_back(new_residual_block);
if (options_.enable_fast_removal) {
residual_block_set_.insert(new_residual_block);
}
return new_residual_block;
}
// Unfortunately, macros don't help much to reduce this code, and var args don't
// work because of the ambiguous case that there is no loss function.
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4, double* x5) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
residual_parameters.push_back(x5);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4, double* x5,
double* x6) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
residual_parameters.push_back(x5);
residual_parameters.push_back(x6);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4, double* x5,
double* x6, double* x7) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
residual_parameters.push_back(x5);
residual_parameters.push_back(x6);
residual_parameters.push_back(x7);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4, double* x5,
double* x6, double* x7, double* x8) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
residual_parameters.push_back(x5);
residual_parameters.push_back(x6);
residual_parameters.push_back(x7);
residual_parameters.push_back(x8);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
ResidualBlock* ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* x0, double* x1, double* x2, double* x3, double* x4, double* x5,
double* x6, double* x7, double* x8, double* x9) {
vector<double*> residual_parameters;
residual_parameters.push_back(x0);
residual_parameters.push_back(x1);
residual_parameters.push_back(x2);
residual_parameters.push_back(x3);
residual_parameters.push_back(x4);
residual_parameters.push_back(x5);
residual_parameters.push_back(x6);
residual_parameters.push_back(x7);
residual_parameters.push_back(x8);
residual_parameters.push_back(x9);
return AddResidualBlock(cost_function, loss_function, residual_parameters);
}
void ProblemImpl::AddParameterBlock(double* values, int size) {
InternalAddParameterBlock(values, size);
}
void ProblemImpl::AddParameterBlock(
double* values,
int size,
LocalParameterization* local_parameterization) {
ParameterBlock* parameter_block =
InternalAddParameterBlock(values, size);
if (local_parameterization != NULL) {
parameter_block->SetParameterization(local_parameterization);
}
}
// Delete a block from a vector of blocks, maintaining the indexing invariant.
// This is done in constant time by moving an element from the end of the
// vector over the element to remove, then popping the last element. It
// destroys the ordering in the interest of speed.
template<typename Block>
void ProblemImpl::DeleteBlockInVector(vector<Block*>* mutable_blocks,
Block* block_to_remove) {
CHECK_EQ((*mutable_blocks)[block_to_remove->index()], block_to_remove)
<< "You found a Ceres bug! \n"
<< "Block requested: "
<< block_to_remove->ToString() << "\n"
<< "Block present: "
<< (*mutable_blocks)[block_to_remove->index()]->ToString();
// Prepare the to-be-moved block for the new, lower-in-index position by
// setting the index to the blocks final location.
Block* tmp = mutable_blocks->back();
tmp->set_index(block_to_remove->index());
// Overwrite the to-be-deleted residual block with the one at the end.
(*mutable_blocks)[block_to_remove->index()] = tmp;
DeleteBlock(block_to_remove);
// The block is gone so shrink the vector of blocks accordingly.
mutable_blocks->pop_back();
}
void ProblemImpl::RemoveResidualBlock(ResidualBlock* residual_block) {
CHECK_NOTNULL(residual_block);
// Verify that residual_block identifies a residual in the current problem.
const string residual_not_found_message =
StringPrintf("Residual block to remove: %p not found. This usually means "
"one of three things have happened:\n"
" 1) residual_block is uninitialised and points to a random "
"area in memory.\n"
" 2) residual_block represented a residual that was added to"
" the problem, but referred to a parameter block which has "
"since been removed, which removes all residuals which "
"depend on that parameter block, and was thus removed.\n"
" 3) residual_block referred to a residual that has already "
"been removed from the problem (by the user).",
residual_block);
if (options_.enable_fast_removal) {
CHECK(residual_block_set_.find(residual_block) !=
residual_block_set_.end())
<< residual_not_found_message;
} else {
// Perform a full search over all current residuals.
CHECK(std::find(program_->residual_blocks().begin(),
program_->residual_blocks().end(),
residual_block) != program_->residual_blocks().end())
<< residual_not_found_message;
}
InternalRemoveResidualBlock(residual_block);
}
void ProblemImpl::RemoveParameterBlock(double* values) {
ParameterBlock* parameter_block =
FindParameterBlockOrDie(parameter_block_map_, values);
if (options_.enable_fast_removal) {
// Copy the dependent residuals from the parameter block because the set of
// dependents will change after each call to RemoveResidualBlock().
vector<ResidualBlock*> residual_blocks_to_remove(
parameter_block->mutable_residual_blocks()->begin(),
parameter_block->mutable_residual_blocks()->end());
for (int i = 0; i < residual_blocks_to_remove.size(); ++i) {
InternalRemoveResidualBlock(residual_blocks_to_remove[i]);
}
} else {
// Scan all the residual blocks to remove ones that depend on the parameter
// block. Do the scan backwards since the vector changes while iterating.
const int num_residual_blocks = NumResidualBlocks();
for (int i = num_residual_blocks - 1; i >= 0; --i) {
ResidualBlock* residual_block =
(*(program_->mutable_residual_blocks()))[i];
const int num_parameter_blocks = residual_block->NumParameterBlocks();
for (int j = 0; j < num_parameter_blocks; ++j) {
if (residual_block->parameter_blocks()[j] == parameter_block) {
InternalRemoveResidualBlock(residual_block);
// The parameter blocks are guaranteed unique.
break;
}
}
}
}
DeleteBlockInVector(program_->mutable_parameter_blocks(), parameter_block);
}
void ProblemImpl::SetParameterBlockConstant(double* values) {
FindParameterBlockOrDie(parameter_block_map_, values)->SetConstant();
}
void ProblemImpl::SetParameterBlockVariable(double* values) {
FindParameterBlockOrDie(parameter_block_map_, values)->SetVarying();
}
void ProblemImpl::SetParameterization(
double* values,
LocalParameterization* local_parameterization) {
FindParameterBlockOrDie(parameter_block_map_, values)
->SetParameterization(local_parameterization);
}
const LocalParameterization* ProblemImpl::GetParameterization(
double* values) const {
return FindParameterBlockOrDie(parameter_block_map_, values)
->local_parameterization();
}
void ProblemImpl::SetParameterLowerBound(double* values,
int index,
double lower_bound) {
FindParameterBlockOrDie(parameter_block_map_, values)
->SetLowerBound(index, lower_bound);
}
void ProblemImpl::SetParameterUpperBound(double* values,
int index,
double upper_bound) {
FindParameterBlockOrDie(parameter_block_map_, values)
->SetUpperBound(index, upper_bound);
}
bool ProblemImpl::Evaluate(const Problem::EvaluateOptions& evaluate_options,
double* cost,
vector<double>* residuals,
vector<double>* gradient,
CRSMatrix* jacobian) {
if (cost == NULL &&
residuals == NULL &&
gradient == NULL &&
jacobian == NULL) {
LOG(INFO) << "Nothing to do.";
return true;
}
// If the user supplied residual blocks, then use them, otherwise
// take the residual blocks from the underlying program.
Program program;
*program.mutable_residual_blocks() =
((evaluate_options.residual_blocks.size() > 0)
? evaluate_options.residual_blocks : program_->residual_blocks());
const vector<double*>& parameter_block_ptrs =
evaluate_options.parameter_blocks;
vector<ParameterBlock*> variable_parameter_blocks;
vector<ParameterBlock*>& parameter_blocks =
*program.mutable_parameter_blocks();
if (parameter_block_ptrs.size() == 0) {
// The user did not provide any parameter blocks, so default to
// using all the parameter blocks in the order that they are in
// the underlying program object.
parameter_blocks = program_->parameter_blocks();
} else {
// The user supplied a vector of parameter blocks. Using this list
// requires a number of steps.
// 1. Convert double* into ParameterBlock*
parameter_blocks.resize(parameter_block_ptrs.size());
for (int i = 0; i < parameter_block_ptrs.size(); ++i) {
parameter_blocks[i] =
FindParameterBlockOrDie(parameter_block_map_,
parameter_block_ptrs[i]);
}
// 2. The user may have only supplied a subset of parameter
// blocks, so identify the ones that are not supplied by the user
// and are NOT constant. These parameter blocks are stored in
// variable_parameter_blocks.
//
// To ensure that the parameter blocks are not included in the
// columns of the jacobian, we need to make sure that they are
// constant during evaluation and then make them variable again
// after we are done.
vector<ParameterBlock*> all_parameter_blocks(program_->parameter_blocks());
vector<ParameterBlock*> included_parameter_blocks(
program.parameter_blocks());
vector<ParameterBlock*> excluded_parameter_blocks;
sort(all_parameter_blocks.begin(), all_parameter_blocks.end());
sort(included_parameter_blocks.begin(), included_parameter_blocks.end());
set_difference(all_parameter_blocks.begin(),
all_parameter_blocks.end(),
included_parameter_blocks.begin(),
included_parameter_blocks.end(),
back_inserter(excluded_parameter_blocks));
variable_parameter_blocks.reserve(excluded_parameter_blocks.size());
for (int i = 0; i < excluded_parameter_blocks.size(); ++i) {
ParameterBlock* parameter_block = excluded_parameter_blocks[i];
if (!parameter_block->IsConstant()) {
variable_parameter_blocks.push_back(parameter_block);
parameter_block->SetConstant();
}
}
}
// Setup the Parameter indices and offsets before an evaluator can
// be constructed and used.
program.SetParameterOffsetsAndIndex();
Evaluator::Options evaluator_options;
// Even though using SPARSE_NORMAL_CHOLESKY requires SuiteSparse or
// CXSparse, here it just being used for telling the evaluator to
// use a SparseRowCompressedMatrix for the jacobian. This is because
// the Evaluator decides the storage for the Jacobian based on the
// type of linear solver being used.
evaluator_options.linear_solver_type = SPARSE_NORMAL_CHOLESKY;
evaluator_options.num_threads = evaluate_options.num_threads;
string error;
scoped_ptr<Evaluator> evaluator(
Evaluator::Create(evaluator_options, &program, &error));
if (evaluator.get() == NULL) {
LOG(ERROR) << "Unable to create an Evaluator object. "
<< "Error: " << error
<< "This is a Ceres bug; please contact the developers!";
// Make the parameter blocks that were temporarily marked
// constant, variable again.
for (int i = 0; i < variable_parameter_blocks.size(); ++i) {
variable_parameter_blocks[i]->SetVarying();
}
program_->SetParameterBlockStatePtrsToUserStatePtrs();
program_->SetParameterOffsetsAndIndex();
return false;
}
if (residuals !=NULL) {
residuals->resize(evaluator->NumResiduals());
}
if (gradient != NULL) {
gradient->resize(evaluator->NumEffectiveParameters());
}
scoped_ptr<CompressedRowSparseMatrix> tmp_jacobian;
if (jacobian != NULL) {
tmp_jacobian.reset(
down_cast<CompressedRowSparseMatrix*>(evaluator->CreateJacobian()));
}
// Point the state pointers to the user state pointers. This is
// needed so that we can extract a parameter vector which is then
// passed to Evaluator::Evaluate.
program.SetParameterBlockStatePtrsToUserStatePtrs();
// Copy the value of the parameter blocks into a vector, since the
// Evaluate::Evaluate method needs its input as such. The previous
// call to SetParameterBlockStatePtrsToUserStatePtrs ensures that
// these values are the ones corresponding to the actual state of
// the parameter blocks, rather than the temporary state pointer
// used for evaluation.
Vector parameters(program.NumParameters());
program.ParameterBlocksToStateVector(parameters.data());
double tmp_cost = 0;
Evaluator::EvaluateOptions evaluator_evaluate_options;
evaluator_evaluate_options.apply_loss_function =
evaluate_options.apply_loss_function;
bool status = evaluator->Evaluate(evaluator_evaluate_options,
parameters.data(),
&tmp_cost,
residuals != NULL ? &(*residuals)[0] : NULL,
gradient != NULL ? &(*gradient)[0] : NULL,
tmp_jacobian.get());
// Make the parameter blocks that were temporarily marked constant,
// variable again.
for (int i = 0; i < variable_parameter_blocks.size(); ++i) {
variable_parameter_blocks[i]->SetVarying();
}
if (status) {
if (cost != NULL) {
*cost = tmp_cost;
}
if (jacobian != NULL) {
tmp_jacobian->ToCRSMatrix(jacobian);
}
}
program_->SetParameterBlockStatePtrsToUserStatePtrs();
program_->SetParameterOffsetsAndIndex();
return status;
}
int ProblemImpl::NumParameterBlocks() const {
return program_->NumParameterBlocks();
}
int ProblemImpl::NumParameters() const {
return program_->NumParameters();
}
int ProblemImpl::NumResidualBlocks() const {
return program_->NumResidualBlocks();
}
int ProblemImpl::NumResiduals() const {
return program_->NumResiduals();
}
int ProblemImpl::ParameterBlockSize(const double* parameter_block) const {
return FindParameterBlockOrDie(parameter_block_map_,
const_cast<double*>(parameter_block))->Size();
};
int ProblemImpl::ParameterBlockLocalSize(const double* parameter_block) const {
return FindParameterBlockOrDie(
parameter_block_map_, const_cast<double*>(parameter_block))->LocalSize();
};
bool ProblemImpl::HasParameterBlock(const double* parameter_block) const {
return (parameter_block_map_.find(const_cast<double*>(parameter_block)) !=
parameter_block_map_.end());
}
void ProblemImpl::GetParameterBlocks(vector<double*>* parameter_blocks) const {
CHECK_NOTNULL(parameter_blocks);
parameter_blocks->resize(0);
for (ParameterMap::const_iterator it = parameter_block_map_.begin();
it != parameter_block_map_.end();
++it) {
parameter_blocks->push_back(it->first);
}
}
void ProblemImpl::GetResidualBlocks(
vector<ResidualBlockId>* residual_blocks) const {
CHECK_NOTNULL(residual_blocks);
*residual_blocks = program().residual_blocks();
}
void ProblemImpl::GetParameterBlocksForResidualBlock(
const ResidualBlockId residual_block,
vector<double*>* parameter_blocks) const {
int num_parameter_blocks = residual_block->NumParameterBlocks();
CHECK_NOTNULL(parameter_blocks)->resize(num_parameter_blocks);
for (int i = 0; i < num_parameter_blocks; ++i) {
(*parameter_blocks)[i] =
residual_block->parameter_blocks()[i]->mutable_user_state();
}
}
void ProblemImpl::GetResidualBlocksForParameterBlock(
const double* values,
vector<ResidualBlockId>* residual_blocks) const {
ParameterBlock* parameter_block =
FindParameterBlockOrDie(parameter_block_map_,
const_cast<double*>(values));
if (options_.enable_fast_removal) {
// In this case the residual blocks that depend on the parameter block are
// stored in the parameter block already, so just copy them out.
CHECK_NOTNULL(residual_blocks)->resize(
parameter_block->mutable_residual_blocks()->size());
std::copy(parameter_block->mutable_residual_blocks()->begin(),
parameter_block->mutable_residual_blocks()->end(),
residual_blocks->begin());
return;
}
// Find residual blocks that depend on the parameter block.
CHECK_NOTNULL(residual_blocks)->clear();
const int num_residual_blocks = NumResidualBlocks();
for (int i = 0; i < num_residual_blocks; ++i) {
ResidualBlock* residual_block =
(*(program_->mutable_residual_blocks()))[i];
const int num_parameter_blocks = residual_block->NumParameterBlocks();
for (int j = 0; j < num_parameter_blocks; ++j) {
if (residual_block->parameter_blocks()[j] == parameter_block) {
residual_blocks->push_back(residual_block);
// The parameter blocks are guaranteed unique.
break;
}
}
}
}
} // namespace internal
} // namespace ceres