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add gtsam namespace

release/4.3a0
Varun Agrawal 2022-07-19 14:09:39 -04:00
parent 3d3703441c
commit 31d174d640
2 changed files with 6 additions and 39 deletions
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2
gtsam/nonlinear/CustomFactor.h
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@ -19,8 +19,6 @@
#include <gtsam/nonlinear/NonlinearFactor.h>
using namespace gtsam;
namespace gtsam {
using JacobianVector = std::vector<Matrix>;

43
gtsam/nonlinear/nonlinear.i
View File

@ -99,11 +99,11 @@ class NonlinearFactorGraph {
string dot(
const gtsam::Values& values,
const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
const GraphvizFormatting& writer = GraphvizFormatting());
const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting());
void saveGraph(
const string& s, const gtsam::Values& values,
const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
const GraphvizFormatting& writer = GraphvizFormatting()) const;
const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting()) const;
// enabling serialization functionality
void serialize() const;
@ -135,37 +135,6 @@ virtual class NoiseModelFactor : gtsam::NonlinearFactor {
Vector whitenedError(const gtsam::Values& x) const;
};
#include <gtsam/nonlinear/CustomFactor.h>
virtual class CustomFactor : gtsam::NoiseModelFactor {
/*
* Note CustomFactor will not be wrapped for MATLAB, as there is no supporting
* machinery there. This is achieved by adding `gtsam::CustomFactor` to the
* ignore list in `matlab/CMakeLists.txt`.
*/
CustomFactor();
/*
* Example:
* ```
* def error_func(this: CustomFactor, v: gtsam.Values, H: List[np.ndarray]):
* <calculated error>
* if not H is None:
* <calculate the Jacobian>
* H[0] = J1 # 2-d numpy array for a Jacobian block
* H[1] = J2
* ...
* return error # 1-d numpy array
*
* cf = CustomFactor(noise_model, keys, error_func)
* ```
*/
CustomFactor(const gtsam::SharedNoiseModel& noiseModel,
const gtsam::KeyVector& keys,
const gtsam::CustomErrorFunction& errorFunction);
void print(string s = "",
gtsam::KeyFormatter keyFormatter = gtsam::DefaultKeyFormatter);
};
#include <gtsam/nonlinear/Values.h>
class Values {
Values();
@ -554,7 +523,7 @@ virtual class GncParams {
GncParams(const PARAMS& baseOptimizerParams);
GncParams();
BaseOptimizerParameters baseOptimizerParams;
GncLossType lossType;
gtsam::GncLossType lossType;
size_t maxIterations;
double muStep;
double relativeCostTol;
@ -563,12 +532,12 @@ virtual class GncParams {
std::vector<size_t> knownInliers;
std::vector<size_t> knownOutliers;
void setLossType(const GncLossType type);
void setLossType(const gtsam::GncLossType type);
void setMaxIterations(const size_t maxIter);
void setMuStep(const double step);
void setRelativeCostTol(double value);
void setWeightsTol(double value);
void setVerbosityGNC(const This::Verbosity value);
void setVerbosityGNC(const gtsam::This::Verbosity value);
void setKnownInliers(const std::vector<size_t>& knownIn);
void setKnownOutliers(const std::vector<size_t>& knownOut);
void print(const string& str = "GncParams: ") const;
@ -900,7 +869,7 @@ template <T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias}>
virtual class NonlinearEquality2 : gtsam::NoiseModelFactor {
NonlinearEquality2(Key key1, Key key2, double mu = 1e4);
NonlinearEquality2(gtsam::Key key1, gtsam::Key key2, double mu = 1e4);
gtsam::Vector evaluateError(const T& x1, const T& x2);
};