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adding smart flags for several static noise model creation function

release/4.3a0
Duy-Nguyen Ta 2012-06-19 06:04:31 +00:00
parent 06f4de3981
commit 0a3d9975f3
2 changed files with 13 additions and 7 deletions
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6
gtsam/linear/NoiseModel.cpp
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@ -422,6 +422,12 @@ SharedDiagonal Constrained::QR(Matrix& Ab) const {
/* ************************************************************************* */
// Isotropic
/* ************************************************************************* */
Isotropic::shared_ptr Isotropic::Sigma(size_t dim, double sigma, bool smart) {
if (smart && fabs(sigma-1.0)<1e-9) return Unit::Create(dim);
return shared_ptr(new Isotropic(dim, sigma));
}
/* ************************************************************************* */
Isotropic::shared_ptr Isotropic::Variance(size_t dim, double variance, bool smart) {
if (smart && fabs(variance-1.0)<1e-9) return Unit::Create(dim);

14
gtsam/linear/NoiseModel.h
View File

@ -112,6 +112,8 @@ namespace gtsam {
* as indeed
* |y|^2 = y'*y = x'*R'*R*x
* Various derived classes are available that are more efficient.
* The named constructors return a shared_ptr because, when the smart flag is true,
* the underlying object might be a derived class such as Diagonal.
*/
class Gaussian: public Base {
@ -274,8 +276,8 @@ namespace gtsam {
* A diagonal noise model created by specifying a Vector of precisions, i.e.
* i.e. the diagonal of the information matrix, i.e., weights
*/
static shared_ptr Precisions(const Vector& precisions) {
return Variances(reciprocal(precisions));
static shared_ptr Precisions(const Vector& precisions, bool smart = false) {
return Variances(reciprocal(precisions), smart);
}
virtual void print(const std::string& name) const;
@ -496,9 +498,7 @@ namespace gtsam {
/**
* An isotropic noise model created by specifying a standard devation sigma
*/
static shared_ptr Sigma(size_t dim, double sigma) {
return shared_ptr(new Isotropic(dim, sigma));
}
static shared_ptr Sigma(size_t dim, double sigma, bool smart = false);
/**
* An isotropic noise model created by specifying a variance = sigma^2.
@ -509,8 +509,8 @@ namespace gtsam {
/**
* An isotropic noise model created by specifying a precision
*/
static shared_ptr Precision(size_t dim, double precision) {
return Variance(dim, 1.0/precision);
static shared_ptr Precision(size_t dim, double precision, bool smart = false) {
return Variance(dim, 1.0/precision, smart);
}
virtual void print(const std::string& name) const;