Merge pull request #762 from borglab/feature/wrapper-interface-updates
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@ -10,11 +10,11 @@
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namespace gtsam {
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namespace gtsam {
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// Actually a FastList<Key>
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#include <gtsam/inference/Key.h>
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#include <gtsam/inference/Key.h>
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const KeyFormatter DefaultKeyFormatter;
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const KeyFormatter DefaultKeyFormatter;
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// Actually a FastList<Key>
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class KeyList {
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class KeyList {
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KeyList();
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KeyList();
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KeyList(const gtsam::KeyList& other);
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KeyList(const gtsam::KeyList& other);
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@ -1284,31 +1284,26 @@ class SymbolicBayesTree {
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gtsam::SymbolicBayesNet* jointBayesNet(size_t key1, size_t key2) const;
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gtsam::SymbolicBayesNet* jointBayesNet(size_t key1, size_t key2) const;
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};
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};
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// class SymbolicBayesTreeClique {
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class SymbolicBayesTreeClique {
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// SymbolicBayesTreeClique();
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SymbolicBayesTreeClique();
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// SymbolicBayesTreeClique(CONDITIONAL* conditional);
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// SymbolicBayesTreeClique(gtsam::sharedConditional* conditional);
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// SymbolicBayesTreeClique(const pair<typename ConditionalType::shared_ptr, typename ConditionalType::FactorType::shared_ptr>& result) : Base(result) {}
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//
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bool equals(const gtsam::SymbolicBayesTreeClique& other, double tol) const;
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// bool equals(const This& other, double tol) const;
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void print(string s = "",
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// void print(string s = "",
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const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter) const;
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// const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter) const;
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size_t numCachedSeparatorMarginals() const;
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// void printTree() const; // Default indent of ""
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// gtsam::sharedConditional* conditional() const;
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// void printTree(string indent) const;
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bool isRoot() const;
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// size_t numCachedSeparatorMarginals() const;
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size_t treeSize() const;
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//
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gtsam::SymbolicBayesTreeClique* parent() const;
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// CONDITIONAL* conditional() const;
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// bool isRoot() const;
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// size_t treeSize() const;
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// const std::list<derived_ptr>& children() const { return children_; }
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// derived_ptr parent() const { return parent_.lock(); }
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//
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// // TODO: need wrapped versions graphs, BayesNet
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// // TODO: need wrapped versions graphs, BayesNet
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// BayesNet<ConditionalType> shortcut(derived_ptr root, Eliminate function) const;
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// BayesNet<ConditionalType> shortcut(derived_ptr root, Eliminate function) const;
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// FactorGraph<FactorType> marginal(derived_ptr root, Eliminate function) const;
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// FactorGraph<FactorType> marginal(derived_ptr root, Eliminate function) const;
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// FactorGraph<FactorType> joint(derived_ptr C2, derived_ptr root, Eliminate function) const;
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// FactorGraph<FactorType> joint(derived_ptr C2, derived_ptr root, Eliminate function) const;
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//
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//
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// void deleteCachedShortcuts();
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void deleteCachedShortcuts();
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// };
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};
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#include <gtsam/inference/VariableIndex.h>
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#include <gtsam/inference/VariableIndex.h>
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class VariableIndex {
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class VariableIndex {
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@ -1554,7 +1549,7 @@ class Sampler {
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#include <gtsam/linear/VectorValues.h>
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#include <gtsam/linear/VectorValues.h>
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class VectorValues {
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class VectorValues {
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//Constructors
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//Constructors
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VectorValues();
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VectorValues();
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VectorValues(const gtsam::VectorValues& other);
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VectorValues(const gtsam::VectorValues& other);
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@ -2160,7 +2155,7 @@ virtual class NonlinearFactor {
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bool active(const gtsam::Values& c) const;
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bool active(const gtsam::Values& c) const;
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gtsam::GaussianFactor* linearize(const gtsam::Values& c) const;
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gtsam::GaussianFactor* linearize(const gtsam::Values& c) const;
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gtsam::NonlinearFactor* clone() const;
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gtsam::NonlinearFactor* clone() const;
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// gtsam::NonlinearFactor* rekey(const gtsam::KeyVector& newKeys) const; //TODO: Conversion from KeyVector to std::vector does not happen
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gtsam::NonlinearFactor* rekey(const gtsam::KeyVector& newKeys) const;
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};
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};
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/nonlinear/NonlinearFactor.h>
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@ -2778,11 +2773,17 @@ virtual class GeneralSFMFactor2 : gtsam::NoiseModelFactor {
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};
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};
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#include <gtsam/slam/SmartProjectionFactor.h>
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#include <gtsam/slam/SmartProjectionFactor.h>
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/// Linearization mode: what factor to linearize to
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enum LinearizationMode { HESSIAN, IMPLICIT_SCHUR, JACOBIAN_Q, JACOBIAN_SVD };
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/// How to manage degeneracy
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enum DegeneracyMode { IGNORE_DEGENERACY, ZERO_ON_DEGENERACY, HANDLE_INFINITY };
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class SmartProjectionParams {
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class SmartProjectionParams {
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SmartProjectionParams();
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SmartProjectionParams();
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// TODO(frank): make these work:
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void setLinearizationMode(gtsam::LinearizationMode linMode);
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// void setLinearizationMode(LinearizationMode linMode);
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void setDegeneracyMode(gtsam::DegeneracyMode degMode);
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// void setDegeneracyMode(DegeneracyMode degMode);
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void setRankTolerance(double rankTol);
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void setRankTolerance(double rankTol);
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void setEnableEPI(bool enableEPI);
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void setEnableEPI(bool enableEPI);
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void setLandmarkDistanceThreshold(bool landmarkDistanceThreshold);
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void setLandmarkDistanceThreshold(bool landmarkDistanceThreshold);
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@ -13,6 +13,7 @@
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#include <pybind11/eigen.h>
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#include <pybind11/eigen.h>
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#include <pybind11/stl_bind.h>
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#include <pybind11/stl_bind.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/operators.h>
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#include <pybind11/functional.h>
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#include <pybind11/functional.h>
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#include <pybind11/iostream.h>
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#include <pybind11/iostream.h>
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#include "gtsam/config.h"
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#include "gtsam/config.h"
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