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wrap sampling methods

release/4.3a0
Frank Dellaert 2022-02-06 20:21:04 -05:00
parent 539bf70829
commit a25378abe7
1 changed files with 24 additions and 13 deletions
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37
gtsam/linear/linear.i
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@ -482,15 +482,19 @@ virtual class GaussianConditional : gtsam::JacobianFactor {
gtsam::Key parent2,
const Vector& b,
double sigma);
// Standard Interface
// Testable
void print(string s = "GaussianConditional",
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::GaussianConditional& cg, double tol) const;
// Standard Interface
gtsam::Key firstFrontalKey() const;
gtsam::VectorValues solve(const gtsam::VectorValues& parents) const;
gtsam::VectorValues sample(const gtsam::VectorValues& parents) const;
gtsam::VectorValues sample() const;
// Advanced Interface
gtsam::VectorValues solve(const gtsam::VectorValues& parents) const;
gtsam::VectorValues solveOtherRHS(const gtsam::VectorValues& parents,
const gtsam::VectorValues& rhs) const;
void solveTransposeInPlace(gtsam::VectorValues& gy) const;
@ -512,11 +516,13 @@ virtual class GaussianDensity : gtsam::GaussianConditional {
const Vector& mean,
double sigma);
// Standard Interface
// Testable
void print(string s = "GaussianDensity",
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::GaussianDensity& cg, double tol) const;
// Standard Interface
Vector mean() const;
Matrix covariance() const;
};
@ -533,6 +539,21 @@ virtual class GaussianBayesNet {
bool equals(const gtsam::GaussianBayesNet& other, double tol) const;
size_t size() const;
// Standard interface
void push_back(gtsam::GaussianConditional* conditional);
void push_back(const gtsam::GaussianBayesNet& bayesNet);
gtsam::GaussianConditional* front() const;
gtsam::GaussianConditional* back() const;
gtsam::VectorValues optimize() const;
gtsam::VectorValues optimize(gtsam::VectorValues given) const;
gtsam::VectorValues optimizeGradientSearch() const;
gtsam::VectorValues sample(gtsam::VectorValues given) const;
gtsam::VectorValues sample() const;
gtsam::VectorValues backSubstitute(const gtsam::VectorValues& gx) const;
gtsam::VectorValues backSubstituteTranspose(const gtsam::VectorValues& gx) const;
// FactorGraph derived interface
gtsam::GaussianConditional* at(size_t idx) const;
gtsam::KeySet keys() const;
@ -541,22 +562,12 @@ virtual class GaussianBayesNet {
void saveGraph(const string& s) const;
gtsam::GaussianConditional* front() const;
gtsam::GaussianConditional* back() const;
void push_back(gtsam::GaussianConditional* conditional);
void push_back(const gtsam::GaussianBayesNet& bayesNet);
gtsam::VectorValues optimize() const;
gtsam::VectorValues optimize(gtsam::VectorValues& solutionForMissing) const;
std::pair<Matrix, Vector> matrix() const;
gtsam::VectorValues optimizeGradientSearch() const;
gtsam::VectorValues gradient(const gtsam::VectorValues& x0) const;
gtsam::VectorValues gradientAtZero() const;
double error(const gtsam::VectorValues& x) const;
double determinant() const;
double logDeterminant() const;
gtsam::VectorValues backSubstitute(const gtsam::VectorValues& gx) const;
gtsam::VectorValues backSubstituteTranspose(const gtsam::VectorValues& gx) const;
string dot(
const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,