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Fixed VectorValues, added linearize and denseJacobian/denseHessian

release/4.3a0
Frank Dellaert 2011-10-28 16:25:15 +00:00
parent e1c984f2b4
commit 980ed4d590
2 changed files with 14 additions and 3 deletions
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6
examples/matlab/PlanarSLAMExample_easy.m
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@ -73,3 +73,9 @@ initialEstimate.print('initial estimate');
%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
result = graph.optimize_(initialEstimate);
result.print('final result');
%% Print out the corresponding dense matrix
ord = graph.orderingCOLAMD(result);
gfg = graph.linearize(result,ord);
A_b = gfg.denseJacobian;
AtA_Atb = gfg.denseHessian;

11
gtsam.h
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@ -55,8 +55,7 @@ class VectorValues {
void print(string s) const;
bool equals(const VectorValues& expected, double tol) const;
size_t size() const;
void reserve(size_t nVars, size_t totalDims);
size_t push_back_preallocated(Vector vector);
void insert(size_t j, const Vector& value);
};
class GaussianConditional {
@ -109,6 +108,8 @@ class GaussianFactorGraph {
double error(const VectorValues& c) const;
double probPrime(const VectorValues& c) const;
void combine(const GaussianFactorGraph& lfg);
Matrix denseJacobian() const;
Matrix denseHessian() const;
};
class Landmark2 {
@ -133,9 +134,13 @@ class PlanarSLAMValues {
class PlanarSLAMGraph {
PlanarSLAMGraph();
void print(string s) const;
double error(const PlanarSLAMValues& c) const;
Ordering* orderingCOLAMD(const PlanarSLAMValues& config) const;
void print(string s) const;
GaussianFactorGraph* linearize(const PlanarSLAMValues& config, const Ordering& ordering) const;
void addPrior(size_t i, const Pose2& p, const SharedNoiseModel& model);
void addPoseConstraint(size_t i, const Pose2& p);
void addOdometry(size_t i, size_t j, const Pose2& z,