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Remove raw memory access codes

release/4.3a0
Sungtae An 2014-11-12 04:21:06 -05:00
parent 102974588a
commit 84f6018481
2 changed files with 0 additions and 85 deletions
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76
gtsam/linear/HessianFactor.cpp
View File

@ -358,23 +358,6 @@ VectorValues HessianFactor::hessianDiagonal() const {
return d; return d;
} }
/* ************************************************************************* */
// TODO: currently assumes all variables of the same size 9 and keys arranged from 0 to n
void HessianFactor::hessianDiagonal(double* d) const {
// Use eigen magic to access raw memory
typedef Eigen::Matrix<double, 9, 1> DVector;
typedef Eigen::Map<DVector> DMap;
// Loop over all variables in the factor
for (DenseIndex pos = 0; pos < (DenseIndex)size(); ++pos) {
Key j = keys_[pos];
// Get the diagonal block, and insert its diagonal
const Matrix& B = info_(pos, pos).selfadjointView();
DMap(d + 9 * j) += B.diagonal();
}
}
/* ************************************************************************* */ /* ************************************************************************* */
map<Key,Matrix> HessianFactor::hessianBlockDiagonal() const { map<Key,Matrix> HessianFactor::hessianBlockDiagonal() const {
map<Key,Matrix> blocks; map<Key,Matrix> blocks;
@ -548,48 +531,6 @@ void HessianFactor::multiplyHessianAdd(double alpha, const VectorValues& x,
} }
} }
/* ************************************************************************* */
void HessianFactor::multiplyHessianAdd(double alpha, const double* x,
double* yvalues, vector<size_t> offsets) const {
// Use eigen magic to access raw memory
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> DVector;
typedef Eigen::Map<DVector> DMap;
typedef Eigen::Map<const DVector> ConstDMap;
// Create a vector of temporary y values, corresponding to rows i
vector<Vector> y;
y.reserve(size());
for (const_iterator it = begin(); it != end(); it++)
y.push_back(zero(getDim(it)));
// Accessing the VectorValues one by one is expensive
// So we will loop over columns to access x only once per column
// And fill the above temporary y values, to be added into yvalues after
for (DenseIndex j = 0; j < (DenseIndex) size(); ++j) {
DenseIndex i = 0;
for (; i < j; ++i)
y[i] += info_(i, j).knownOffDiagonal()
* ConstDMap(x + offsets[keys_[j]],
offsets[keys_[j] + 1] - offsets[keys_[j]]);
// blocks on the diagonal are only half
y[i] += info_(j, j).selfadjointView()
* ConstDMap(x + offsets[keys_[j]],
offsets[keys_[j] + 1] - offsets[keys_[j]]);
// for below diagonal, we take transpose block from upper triangular part
for (i = j + 1; i < (DenseIndex) size(); ++i)
y[i] += info_(i, j).knownOffDiagonal()
* ConstDMap(x + offsets[keys_[j]],
offsets[keys_[j] + 1] - offsets[keys_[j]]);
}
// copy to yvalues
for (DenseIndex i = 0; i < (DenseIndex) size(); ++i)
DMap(yvalues + offsets[keys_[i]], offsets[keys_[i] + 1] - offsets[keys_[i]]) +=
alpha * y[i];
}
/* ************************************************************************* */ /* ************************************************************************* */
VectorValues HessianFactor::gradientAtZero() const { VectorValues HessianFactor::gradientAtZero() const {
VectorValues g; VectorValues g;
@ -599,23 +540,6 @@ VectorValues HessianFactor::gradientAtZero() const {
return g; return g;
} }
/* ************************************************************************* */
// TODO: currently assumes all variables of the same size 9 and keys arranged from 0 to n
void HessianFactor::gradientAtZero(double* d) const {
// Use eigen magic to access raw memory
typedef Eigen::Matrix<double, 9, 1> DVector;
typedef Eigen::Map<DVector> DMap;
// Loop over all variables in the factor
for (DenseIndex pos = 0; pos < (DenseIndex)size(); ++pos) {
Key j = keys_[pos];
// Get the diagonal block, and insert its diagonal
DVector dj = -info_(pos,size()).knownOffDiagonal();
DMap(d + 9 * j) += dj;
}
}
/* ************************************************************************* */ /* ************************************************************************* */
std::pair<boost::shared_ptr<GaussianConditional>, boost::shared_ptr<HessianFactor> > std::pair<boost::shared_ptr<GaussianConditional>, boost::shared_ptr<HessianFactor> >
EliminateCholesky(const GaussianFactorGraph& factors, const Ordering& keys) EliminateCholesky(const GaussianFactorGraph& factors, const Ordering& keys)

9
gtsam/linear/HessianFactor.h
View File

@ -340,9 +340,6 @@ namespace gtsam {
/// Return the diagonal of the Hessian for this factor /// Return the diagonal of the Hessian for this factor
virtual VectorValues hessianDiagonal() const; virtual VectorValues hessianDiagonal() const;
/* ************************************************************************* */
virtual void hessianDiagonal(double* d) const;
/// Return the block diagonal of the Hessian for this factor /// Return the block diagonal of the Hessian for this factor
virtual std::map<Key,Matrix> hessianBlockDiagonal() const; virtual std::map<Key,Matrix> hessianBlockDiagonal() const;
@ -380,15 +377,9 @@ namespace gtsam {
/** y += alpha * A'*A*x */ /** y += alpha * A'*A*x */
void multiplyHessianAdd(double alpha, const VectorValues& x, VectorValues& y) const; void multiplyHessianAdd(double alpha, const VectorValues& x, VectorValues& y) const;
void multiplyHessianAdd(double alpha, const double* x, double* y, std::vector<size_t> keys) const;
void multiplyHessianAdd(double alpha, const double* x, double* y) const {};
/// eta for Hessian /// eta for Hessian
VectorValues gradientAtZero() const; VectorValues gradientAtZero() const;
virtual void gradientAtZero(double* d) const;
/** /**
* Densely partially eliminate with Cholesky factorization. JacobianFactors are * Densely partially eliminate with Cholesky factorization. JacobianFactors are
* left-multiplied with their transpose to form the Hessian using the conversion constructor * left-multiplied with their transpose to form the Hessian using the conversion constructor