Merge pull request #1 from varunagrawal/custom-factor-separate
Wrap custom factor in a separate filerelease/4.3a0
Amado Antonini
GitHub
commit
74678fbb8f
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@ -19,8 +19,6 @@
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#include <gtsam/nonlinear/NonlinearFactor.h>
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using namespace gtsam;
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namespace gtsam {
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using JacobianVector = std::vector<Matrix>;
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@ -0,0 +1,38 @@
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//*************************************************************************
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// Custom Factor wrapping
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//*************************************************************************
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namespace gtsam {
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#include <gtsam/nonlinear/CustomFactor.h>
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virtual class CustomFactor : gtsam::NoiseModelFactor {
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/*
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* Note CustomFactor will not be wrapped for MATLAB, as there is no supporting
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* machinery there. This is achieved by adding `gtsam::CustomFactor` to the
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* ignore list in `matlab/CMakeLists.txt`.
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*/
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CustomFactor();
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/*
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* Example:
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* ```
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* def error_func(this: CustomFactor, v: gtsam.Values, H: List[np.ndarray]):
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* <calculated error>
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* if not H is None:
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* <calculate the Jacobian>
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* H[0] = J1 # 2-d numpy array for a Jacobian block
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* H[1] = J2
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* ...
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* return error # 1-d numpy array
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*
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* cf = CustomFactor(noise_model, keys, error_func)
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* ```
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*/
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CustomFactor(const gtsam::SharedNoiseModel& noiseModel,
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const gtsam::KeyVector& keys,
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const gtsam::CustomErrorFunction& errorFunction);
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void print(string s = "",
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gtsam::KeyFormatter keyFormatter = gtsam::DefaultKeyFormatter);
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};
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}
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@ -99,11 +99,11 @@ class NonlinearFactorGraph {
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string dot(
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const gtsam::Values& values,
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const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
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const GraphvizFormatting& writer = GraphvizFormatting());
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const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting());
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void saveGraph(
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const string& s, const gtsam::Values& values,
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const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
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const GraphvizFormatting& writer = GraphvizFormatting()) const;
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const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting()) const;
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// enabling serialization functionality
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void serialize() const;
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@ -135,37 +135,6 @@ virtual class NoiseModelFactor : gtsam::NonlinearFactor {
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Vector whitenedError(const gtsam::Values& x) const;
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};
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#include <gtsam/nonlinear/CustomFactor.h>
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virtual class CustomFactor : gtsam::NoiseModelFactor {
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/*
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* Note CustomFactor will not be wrapped for MATLAB, as there is no supporting
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* machinery there. This is achieved by adding `gtsam::CustomFactor` to the
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* ignore list in `matlab/CMakeLists.txt`.
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*/
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CustomFactor();
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/*
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* Example:
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* ```
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* def error_func(this: CustomFactor, v: gtsam.Values, H: List[np.ndarray]):
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* <calculated error>
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* if not H is None:
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* <calculate the Jacobian>
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* H[0] = J1 # 2-d numpy array for a Jacobian block
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* H[1] = J2
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* ...
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* return error # 1-d numpy array
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*
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* cf = CustomFactor(noise_model, keys, error_func)
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* ```
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*/
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CustomFactor(const gtsam::SharedNoiseModel& noiseModel,
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const gtsam::KeyVector& keys,
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const gtsam::CustomErrorFunction& errorFunction);
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void print(string s = "",
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gtsam::KeyFormatter keyFormatter = gtsam::DefaultKeyFormatter);
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};
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#include <gtsam/nonlinear/Values.h>
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class Values {
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Values();
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@ -554,7 +523,7 @@ virtual class GncParams {
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GncParams(const PARAMS& baseOptimizerParams);
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GncParams();
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BaseOptimizerParameters baseOptimizerParams;
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GncLossType lossType;
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gtsam::GncLossType lossType;
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size_t maxIterations;
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double muStep;
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double relativeCostTol;
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@ -563,12 +532,12 @@ virtual class GncParams {
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std::vector<size_t> knownInliers;
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std::vector<size_t> knownOutliers;
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void setLossType(const GncLossType type);
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void setLossType(const gtsam::GncLossType type);
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void setMaxIterations(const size_t maxIter);
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void setMuStep(const double step);
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void setRelativeCostTol(double value);
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void setWeightsTol(double value);
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void setVerbosityGNC(const This::Verbosity value);
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void setVerbosityGNC(const gtsam::This::Verbosity value);
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void setKnownInliers(const std::vector<size_t>& knownIn);
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void setKnownOutliers(const std::vector<size_t>& knownOut);
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void print(const string& str = "GncParams: ") const;
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@ -900,7 +869,7 @@ template <T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2,
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gtsam::PinholeCamera<gtsam::Cal3Unified>,
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gtsam::imuBias::ConstantBias}>
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virtual class NonlinearEquality2 : gtsam::NoiseModelFactor {
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NonlinearEquality2(Key key1, Key key2, double mu = 1e4);
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NonlinearEquality2(gtsam::Key key1, gtsam::Key key2, double mu = 1e4);
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gtsam::Vector evaluateError(const T& x1, const T& x2);
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};
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@ -73,6 +73,7 @@ set(interface_files
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${GTSAM_SOURCE_DIR}/gtsam/geometry/geometry.i
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${GTSAM_SOURCE_DIR}/gtsam/linear/linear.i
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${GTSAM_SOURCE_DIR}/gtsam/nonlinear/nonlinear.i
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${GTSAM_SOURCE_DIR}/gtsam/nonlinear/custom.i
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${GTSAM_SOURCE_DIR}/gtsam/symbolic/symbolic.i
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${GTSAM_SOURCE_DIR}/gtsam/sam/sam.i
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${GTSAM_SOURCE_DIR}/gtsam/slam/slam.i
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@ -61,6 +61,7 @@ set(interface_headers
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${PROJECT_SOURCE_DIR}/gtsam/geometry/geometry.i
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${PROJECT_SOURCE_DIR}/gtsam/linear/linear.i
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${PROJECT_SOURCE_DIR}/gtsam/nonlinear/nonlinear.i
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${PROJECT_SOURCE_DIR}/gtsam/nonlinear/custom.i
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${PROJECT_SOURCE_DIR}/gtsam/symbolic/symbolic.i
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${PROJECT_SOURCE_DIR}/gtsam/sam/sam.i
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${PROJECT_SOURCE_DIR}/gtsam/slam/slam.i
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@ -0,0 +1,12 @@
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/* Please refer to:
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* https://pybind11.readthedocs.io/en/stable/advanced/cast/stl.html
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* These are required to save one copy operation on Python calls.
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*
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* NOTES
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* =================
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*
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* `PYBIND11_MAKE_OPAQUE` will mark the type as "opaque" for the pybind11
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* automatic STL binding, such that the raw objects can be accessed in Python.
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* Without this they will be automatically converted to a Python object, and all
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* mutations on Python side will not be reflected on C++.
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*/
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@ -10,3 +10,4 @@
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* Without this they will be automatically converted to a Python object, and all
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* mutations on Python side will not be reflected on C++.
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*/
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#include <pybind11/stl.h>
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@ -0,0 +1,12 @@
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/* Please refer to:
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* https://pybind11.readthedocs.io/en/stable/advanced/cast/stl.html
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* These are required to save one copy operation on Python calls.
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*
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* NOTES
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* =================
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*
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* `py::bind_vector` and similar machinery gives the std container a Python-like
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* interface, but without the `<pybind11/stl.h>` copying mechanism. Combined
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* with `PYBIND11_MAKE_OPAQUE` this allows the types to be modified with Python,
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* and saves one copy operation.
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*/
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