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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
// 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: keir@google.com (Keir Mierle)
#ifndef CERES_INTERNAL_PARAMETER_BLOCK_H_
#define CERES_INTERNAL_PARAMETER_BLOCK_H_
#include <algorithm>
#include <cstdlib>
#include <limits>
#include <string>
#include "ceres/array_utils.h"
#include "ceres/collections_port.h"
#include "ceres/integral_types.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/local_parameterization.h"
#include "ceres/stringprintf.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
class ProblemImpl;
class ResidualBlock;
// The parameter block encodes the location of the user's original value, and
// also the "current state" of the parameter. The evaluator uses whatever is in
// the current state of the parameter when evaluating. This is inlined since the
// methods are performance sensitive.
//
// The class is not thread-safe, unless only const methods are called. The
// parameter block may also hold a pointer to a local parameterization; the
// parameter block does not take ownership of this pointer, so the user is
// responsible for the proper disposal of the local parameterization.
class ParameterBlock {
public:
// TODO(keir): Decide what data structure is best here. Should this be a set?
// Probably not, because sets are memory inefficient. However, if it's a
// vector, you can get into pathological linear performance when removing a
// residual block from a problem where all the residual blocks depend on one
// parameter; for example, shared focal length in a bundle adjustment
// problem. It might be worth making a custom structure that is just an array
// when it is small, but transitions to a hash set when it has more elements.
//
// For now, use a hash set.
typedef HashSet<ResidualBlock*> ResidualBlockSet;
// Create a parameter block with the user state, size, and index specified.
// The size is the size of the parameter block and the index is the position
// of the parameter block inside a Program (if any).
ParameterBlock(double* user_state, int size, int index) {
Init(user_state, size, index, NULL);
}
ParameterBlock(double* user_state,
int size,
int index,
LocalParameterization* local_parameterization) {
Init(user_state, size, index, local_parameterization);
}
// The size of the parameter block.
int Size() const { return size_; }
// Manipulate the parameter state.
bool SetState(const double* x) {
CHECK(x != NULL)
<< "Tried to set the state of constant parameter "
<< "with user location " << user_state_;
CHECK(!is_constant_)
<< "Tried to set the state of constant parameter "
<< "with user location " << user_state_;
state_ = x;
return UpdateLocalParameterizationJacobian();
}
// Copy the current parameter state out to x. This is "GetState()" rather than
// simply "state()" since it is actively copying the data into the passed
// pointer.
void GetState(double *x) const {
if (x != state_) {
memcpy(x, state_, sizeof(*state_) * size_);
}
}
// Direct pointers to the current state.
const double* state() const { return state_; }
const double* user_state() const { return user_state_; }
double* mutable_user_state() { return user_state_; }
LocalParameterization* local_parameterization() const {
return local_parameterization_;
}
LocalParameterization* mutable_local_parameterization() {
return local_parameterization_;
}
// Set this parameter block to vary or not.
void SetConstant() { is_constant_ = true; }
void SetVarying() { is_constant_ = false; }
bool IsConstant() const { return is_constant_; }
// This parameter block's index in an array.
int index() const { return index_; }
void set_index(int index) { index_ = index; }
// This parameter offset inside a larger state vector.
int state_offset() const { return state_offset_; }
void set_state_offset(int state_offset) { state_offset_ = state_offset; }
// This parameter offset inside a larger delta vector.
int delta_offset() const { return delta_offset_; }
void set_delta_offset(int delta_offset) { delta_offset_ = delta_offset; }
// Methods relating to the parameter block's parameterization.
// The local to global jacobian. Returns NULL if there is no local
// parameterization for this parameter block. The returned matrix is row-major
// and has Size() rows and LocalSize() columns.
const double* LocalParameterizationJacobian() const {
return local_parameterization_jacobian_.get();
}
int LocalSize() const {
return (local_parameterization_ == NULL)
? size_
: local_parameterization_->LocalSize();
}
// Set the parameterization. The parameterization can be set exactly once;
// multiple calls to set the parameterization to different values will crash.
// It is an error to pass NULL for the parameterization. The parameter block
// does not take ownership of the parameterization.
void SetParameterization(LocalParameterization* new_parameterization) {
CHECK(new_parameterization != NULL) << "NULL parameterization invalid.";
CHECK(new_parameterization->GlobalSize() == size_)
<< "Invalid parameterization for parameter block. The parameter block "
<< "has size " << size_ << " while the parameterization has a global "
<< "size of " << new_parameterization->GlobalSize() << ". Did you "
<< "accidentally use the wrong parameter block or parameterization?";
if (new_parameterization != local_parameterization_) {
CHECK(local_parameterization_ == NULL)
<< "Can't re-set the local parameterization; it leads to "
<< "ambiguous ownership.";
local_parameterization_ = new_parameterization;
local_parameterization_jacobian_.reset(
new double[local_parameterization_->GlobalSize() *
local_parameterization_->LocalSize()]);
CHECK(UpdateLocalParameterizationJacobian())
<< "Local parameterization Jacobian computation failed for x: "
<< ConstVectorRef(state_, Size()).transpose();
} else {
// Ignore the case that the parameterizations match.
}
}
void SetUpperBound(int index, double upper_bound) {
CHECK_LT(index, size_);
if (upper_bounds_.get() == NULL) {
upper_bounds_.reset(new double[size_]);
std::fill(upper_bounds_.get(),
upper_bounds_.get() + size_,
std::numeric_limits<double>::max());
}
upper_bounds_[index] = upper_bound;
}
void SetLowerBound(int index, double lower_bound) {
CHECK_LT(index, size_);
if (lower_bounds_.get() == NULL) {
lower_bounds_.reset(new double[size_]);
std::fill(lower_bounds_.get(),
lower_bounds_.get() + size_,
-std::numeric_limits<double>::max());
}
lower_bounds_[index] = lower_bound;
}
// Generalization of the addition operation. This is the same as
// LocalParameterization::Plus() followed by projection onto the
// hyper cube implied by the bounds constraints.
bool Plus(const double *x, const double* delta, double* x_plus_delta) {
if (local_parameterization_ != NULL) {
if (!local_parameterization_->Plus(x, delta, x_plus_delta)) {
return false;
}
} else {
VectorRef(x_plus_delta, size_) = ConstVectorRef(x, size_) +
ConstVectorRef(delta, size_);
}
// Project onto the box constraints.
if (lower_bounds_.get() != NULL) {
for (int i = 0; i < size_; ++i) {
x_plus_delta[i] = std::max(x_plus_delta[i], lower_bounds_[i]);
}
}
if (upper_bounds_.get() != NULL) {
for (int i = 0; i < size_; ++i) {
x_plus_delta[i] = std::min(x_plus_delta[i], upper_bounds_[i]);
}
}
return true;
}
std::string ToString() const {
return StringPrintf("{ this=%p, user_state=%p, state=%p, size=%d, "
"constant=%d, index=%d, state_offset=%d, "
"delta_offset=%d }",
this,
user_state_,
state_,
size_,
is_constant_,
index_,
state_offset_,
delta_offset_);
}
void EnableResidualBlockDependencies() {
CHECK(residual_blocks_.get() == NULL)
<< "Ceres bug: There is already a residual block collection "
<< "for parameter block: " << ToString();
residual_blocks_.reset(new ResidualBlockSet);
}
void AddResidualBlock(ResidualBlock* residual_block) {
CHECK(residual_blocks_.get() != NULL)
<< "Ceres bug: The residual block collection is null for parameter "
<< "block: " << ToString();
residual_blocks_->insert(residual_block);
}
void RemoveResidualBlock(ResidualBlock* residual_block) {
CHECK(residual_blocks_.get() != NULL)
<< "Ceres bug: The residual block collection is null for parameter "
<< "block: " << ToString();
CHECK(residual_blocks_->find(residual_block) != residual_blocks_->end())
<< "Ceres bug: Missing residual for parameter block: " << ToString();
residual_blocks_->erase(residual_block);
}
// This is only intended for iterating; perhaps this should only expose
// .begin() and .end().
ResidualBlockSet* mutable_residual_blocks() {
return residual_blocks_.get();
}
double LowerBoundForParameter(int index) const {
if (lower_bounds_.get() == NULL) {
return -std::numeric_limits<double>::max();
} else {
return lower_bounds_[index];
}
}
double UpperBoundForParameter(int index) const {
if (upper_bounds_.get() == NULL) {
return std::numeric_limits<double>::max();
} else {
return upper_bounds_[index];
}
}
private:
void Init(double* user_state,
int size,
int index,
LocalParameterization* local_parameterization) {
user_state_ = user_state;
size_ = size;
index_ = index;
is_constant_ = false;
state_ = user_state_;
local_parameterization_ = NULL;
if (local_parameterization != NULL) {
SetParameterization(local_parameterization);
}
state_offset_ = -1;
delta_offset_ = -1;
}
bool UpdateLocalParameterizationJacobian() {
if (local_parameterization_ == NULL) {
return true;
}
// Update the local to global Jacobian. In some cases this is
// wasted effort; if this is a bottleneck, we will find a solution
// at that time.
const int jacobian_size = Size() * LocalSize();
InvalidateArray(jacobian_size,
local_parameterization_jacobian_.get());
if (!local_parameterization_->ComputeJacobian(
state_,
local_parameterization_jacobian_.get())) {
LOG(WARNING) << "Local parameterization Jacobian computation failed"
"for x: " << ConstVectorRef(state_, Size()).transpose();
return false;
}
if (!IsArrayValid(jacobian_size, local_parameterization_jacobian_.get())) {
LOG(WARNING) << "Local parameterization Jacobian computation returned"
<< "an invalid matrix for x: "
<< ConstVectorRef(state_, Size()).transpose()
<< "\n Jacobian matrix : "
<< ConstMatrixRef(local_parameterization_jacobian_.get(),
Size(),
LocalSize());
return false;
}
return true;
}
double* user_state_;
int size_;
bool is_constant_;
LocalParameterization* local_parameterization_;
// The "state" of the parameter. These fields are only needed while the
// solver is running. While at first glance using mutable is a bad idea, this
// ends up simplifying the internals of Ceres enough to justify the potential
// pitfalls of using "mutable."
mutable const double* state_;
mutable scoped_array<double> local_parameterization_jacobian_;
// The index of the parameter. This is used by various other parts of Ceres to
// permit switching from a ParameterBlock* to an index in another array.
int32 index_;
// The offset of this parameter block inside a larger state vector.
int32 state_offset_;
// The offset of this parameter block inside a larger delta vector.
int32 delta_offset_;
// If non-null, contains the residual blocks this parameter block is in.
scoped_ptr<ResidualBlockSet> residual_blocks_;
// Upper and lower bounds for the parameter block. SetUpperBound
// and SetLowerBound lazily initialize the upper_bounds_ and
// lower_bounds_ arrays. If they are never called, then memory for
// these arrays is never allocated. Thus for problems where there
// are no bounds, or only one sided bounds we do not pay the cost of
// allocating memory for the inactive bounds constraints.
//
// Upon initialization these arrays are initialized to
// std::numeric_limits<double>::max() and
// -std::numeric_limits<double>::max() respectively which correspond
// to the parameter block being unconstrained.
scoped_array<double> upper_bounds_;
scoped_array<double> lower_bounds_;
// Necessary so ProblemImpl can clean up the parameterizations.
friend class ProblemImpl;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PARAMETER_BLOCK_H_
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