2019-04-17 12:05:53 +08:00
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/*
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* @file KarcherMeanFactor.cpp
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* @author Frank Dellaert
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* @date March 2019
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*/
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#pragma once
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#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/slam/KarcherMeanFactor.h>
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2023-01-12 05:33:25 +08:00
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#include <optional>
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2019-04-17 12:05:53 +08:00
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using namespace std;
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namespace gtsam {
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2019-12-11 01:19:38 +08:00
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template <class T, class ALLOC>
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T FindKarcherMeanImpl(const vector<T, ALLOC>& rotations) {
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2019-04-17 12:05:53 +08:00
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// Cost function C(R) = \sum PriorFactor(R_i)::error(R)
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// No closed form solution.
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NonlinearFactorGraph graph;
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static const Key kKey(0);
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for (const auto& R : rotations) {
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2020-04-12 08:09:54 +08:00
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graph.addPrior<T>(kKey, R);
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2019-04-17 12:05:53 +08:00
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}
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Values initial;
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initial.insert<T>(kKey, T());
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auto result = GaussNewtonOptimizer(graph, initial).optimize();
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return result.at<T>(kKey);
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}
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2022-02-07 01:14:30 +08:00
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template <class T>
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2019-12-11 04:10:32 +08:00
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T FindKarcherMean(const std::vector<T>& rotations) {
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return FindKarcherMeanImpl(rotations);
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}
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template <class T>
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T FindKarcherMean(const std::vector<T, Eigen::aligned_allocator<T>>& rotations) {
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2019-12-11 01:19:38 +08:00
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return FindKarcherMeanImpl(rotations);
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}
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template <class T>
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T FindKarcherMean(std::initializer_list<T>&& rotations) {
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return FindKarcherMeanImpl(std::vector<T, Eigen::aligned_allocator<T> >(rotations));
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}
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2019-04-17 12:05:53 +08:00
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template <class T>
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template <typename CONTAINER>
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Feature/shonan averaging (#473)
Shonan Rotation Averaging.
199 commit messages below, many are obsolete as design has changed quite a bit over time, especially from the earlier period where I thought we only needed SO(4).
* prototyping weighted sampler
* Moved WeightedSampler into its own header
* Random now uses std header <random>.
* Removed boost/random usage from linear and discrete directories
* Made into class
* Now using new WeightedSampler class
* Inlined random direction generation
* eradicated last vestiges of boost/random in gtsam_unstable
* Added 3D example g2o file
* Added Frobenius norm factors
* Shonan averaging algorithm, using SOn class
* Wrapping Frobenius and Shonan
* Fixed issues with <<
* Use Builder parameters
* Refactored Shonan interface
* Fixed << issues as well as MATLAB segfault, using eval(), as discussed in issue #451
* ShonanAveragingParameters
* New factor FrobeniusWormholeFactorP computes |Rj*P - Ri*P*Rij|
* Fixed broken GetDimension for Lie groups with variable dimension.
* Removed all but Shonan averaging factor and made everything work with new SOn
* Just a single WormholeFactor, wrapped noise model
* Use std <random>
* comments/todos
* added timing script
* add script to process ShonanAveraging timing results
* Now producing a CSV file
* Parse csv file and make combined plot
* Fixed range
* change p value and set two flags on
* input file path, all the csv files proceeses at the same time
* add check convergence rate part
* csv file have name according to input data name
* correct one mistake in initialization
* generate the convergence rate for each p value
* add yticks for the bar plot
* add noises to the measurements
* test add noise
* Basic structure for checkOptimalityAt
* change optimizer method to cholesky
* buildQ now working. Tests should be better but visually inspected.
* multiple test with cholesky
* back
* computeLambda now works
* make combined plots while make bar plot
* Calculate minimum eigenvalue - the very expensive version
* Exposed computeMinEigenValue
* make plots and bar togenter
* method change to jacobi
* add time for check optimality, min_eigen_value, sub_bound
* updated plot min_eigen value and subounds
* Adding Spectra headers
* David's min eigenvalue code inserted and made to compile.
* Made it work
* Made "run" method work.
* add rim.g2o name
* Fixed bug in shifting eigenvalues
* roundSolution which replaces projectFrom
* removed extra arguments
* Added to wrapper
* Add SOn to template lists
* roundSolution delete the extra arguement p
* only calculate p=5 and change to the correct way computing f_R
* Fixed conflict and made Google-style name changes
* prototype descent code and unit test for initializeWithDescent
* add averaging cost/time part in processing data
* initializewithDescent success in test
* Formatting and find example rather than hardcode
* Removed accidentally checked in cmake files
* give value to xi by block
* correct gradient descent
* correct xi
* }
* Fix wrapper
* Make Hat/Vee have alternating signs
* MakeATangentVector helpder function
* Fixed cmake files
* changed sign
* add line search
* unit test for line search
* test real data with line search
* correct comment
* Fix boost::uniform_real
* add save .dat file
* correct test case
* add explanation
* delete redundant cout
* add name to .dat output file
* correct checkR
* add get poses_ in shonan
* add Vector Point type for savig data
* Remove cmake file which magically re-appeared??
* Switched to std random library.
* Prepare Klaus test
* Add klaus3.g2o data.
* fix comment
* Fix derivatives
* Fixed broken GetDimension for Lie groups with variable dimension.
* Fix SOn tests to report correct dimension
* Added tests for Klaus3 data
* Add runWithRandomKlaus test for shonan.
* Finish runWithRandomKlaus unittest.
* Correct datafile.
* Correct the format.
* Added measured and keys methods
* Shonan works on Klaus data
* Create dense versions for wrappers, for testing
* Now store D, Q, and L
* Remove another cmake file incorrectly checked in.
* Found and fixed the bug in ComputeLambda !
* Now using Q in Lambdas calculation, so Lambdas agree with Eriksson18cvpr.
* Make FrobeniusFactor not use deprecated methods
* FrobeniusWormholeFactor takes Rot3 as argument
* Wrapped some more methods.
* Wrapped more methods
* Allow creating and populating BetweenFactorPose3s in python
* New constructors for ShonanAveraging
* add function of get measurements number
* Remove option not to use noise model
* wrap Use nrMeasurements
* Made Logmap a bit more tolerant of slightly degenerate rotations (with trace < -1)
* Allow for Anchor index
* Fix anchor bug
* Change outside view to Rot3 rather than SO3
* Add Lift in SOn class
* Make comet working
* Small fixes
* Delete extra function
* Add SOn::Lift
* Removed hardcoded flag
* Moved Frobenius factor to gtsam from unstable
* Added new tests and made an old regression pass again
* Cleaned up formatting and some comments, added EXPORT directives
* Throw exception if wrongly dimensioned values are given
* static_cast and other throw
* Fixed run-time dimension
* Added gauge-constraining factor
* LM parameters now passed in, added Gauge fixing
* 2D test scaffold
* Comments
* Pre-allocated generators
* Document API
* Add optional weight
* New prior weeights infrastructure
* Made d a template parameter
* Recursive Hat and RetractJacobian test
* Added Spectra 0.9.0 to 3rdparty
* Enabling 2D averaging
* Templatized Wormhole factor
* ignore xcode folder
* Fixed vec and VectorizedGenerators templates for fixed N!=3 or 4
* Simplifying constructors
Moved file loading to tests (for now)
All unit tests pass for d==3!
* Templated some methods internally
* Very generic parseToVector
* refactored load2d
* Very much improved FrobeniusWormholeFactor (Shonan) Jacobians
* SO(2) averaging works !
* Templated parse methods
* Switched to new Dataset paradigm
* Moved Shonan to gtsam
* Checked noise model is correctly gotten from file
* Fixed covariance bug
* Making Shonan wrapper work
* Renamed FrobeniusWormholeFactor to ShonanFactor and moved into its own compilation unit in gtsam/sfm
* Fixed wrong include
* Simplified interface (removed irrelevant random inits) and fixed eigenvector test
* Removed stray boost::none
* Added citation as suggested by Jose
* Made descent test deterministic
* Fixed some comments, commented out flaky test
Co-authored-by: Jing Wu <jingwu@gatech.edu>
Co-authored-by: jingwuOUO <wujing2951@gmail.com>
Co-authored-by: swang <swang736@gatech.edu>
Co-authored-by: ss <ss>
Co-authored-by: Fan Jiang <prof.fan@foxmail.com>
2020-08-17 19:43:10 +08:00
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KarcherMeanFactor<T>::KarcherMeanFactor(const CONTAINER &keys, int d,
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2023-01-12 05:33:25 +08:00
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std::optional<double> beta)
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Feature/shonan averaging (#473)
Shonan Rotation Averaging.
199 commit messages below, many are obsolete as design has changed quite a bit over time, especially from the earlier period where I thought we only needed SO(4).
* prototyping weighted sampler
* Moved WeightedSampler into its own header
* Random now uses std header <random>.
* Removed boost/random usage from linear and discrete directories
* Made into class
* Now using new WeightedSampler class
* Inlined random direction generation
* eradicated last vestiges of boost/random in gtsam_unstable
* Added 3D example g2o file
* Added Frobenius norm factors
* Shonan averaging algorithm, using SOn class
* Wrapping Frobenius and Shonan
* Fixed issues with <<
* Use Builder parameters
* Refactored Shonan interface
* Fixed << issues as well as MATLAB segfault, using eval(), as discussed in issue #451
* ShonanAveragingParameters
* New factor FrobeniusWormholeFactorP computes |Rj*P - Ri*P*Rij|
* Fixed broken GetDimension for Lie groups with variable dimension.
* Removed all but Shonan averaging factor and made everything work with new SOn
* Just a single WormholeFactor, wrapped noise model
* Use std <random>
* comments/todos
* added timing script
* add script to process ShonanAveraging timing results
* Now producing a CSV file
* Parse csv file and make combined plot
* Fixed range
* change p value and set two flags on
* input file path, all the csv files proceeses at the same time
* add check convergence rate part
* csv file have name according to input data name
* correct one mistake in initialization
* generate the convergence rate for each p value
* add yticks for the bar plot
* add noises to the measurements
* test add noise
* Basic structure for checkOptimalityAt
* change optimizer method to cholesky
* buildQ now working. Tests should be better but visually inspected.
* multiple test with cholesky
* back
* computeLambda now works
* make combined plots while make bar plot
* Calculate minimum eigenvalue - the very expensive version
* Exposed computeMinEigenValue
* make plots and bar togenter
* method change to jacobi
* add time for check optimality, min_eigen_value, sub_bound
* updated plot min_eigen value and subounds
* Adding Spectra headers
* David's min eigenvalue code inserted and made to compile.
* Made it work
* Made "run" method work.
* add rim.g2o name
* Fixed bug in shifting eigenvalues
* roundSolution which replaces projectFrom
* removed extra arguments
* Added to wrapper
* Add SOn to template lists
* roundSolution delete the extra arguement p
* only calculate p=5 and change to the correct way computing f_R
* Fixed conflict and made Google-style name changes
* prototype descent code and unit test for initializeWithDescent
* add averaging cost/time part in processing data
* initializewithDescent success in test
* Formatting and find example rather than hardcode
* Removed accidentally checked in cmake files
* give value to xi by block
* correct gradient descent
* correct xi
* }
* Fix wrapper
* Make Hat/Vee have alternating signs
* MakeATangentVector helpder function
* Fixed cmake files
* changed sign
* add line search
* unit test for line search
* test real data with line search
* correct comment
* Fix boost::uniform_real
* add save .dat file
* correct test case
* add explanation
* delete redundant cout
* add name to .dat output file
* correct checkR
* add get poses_ in shonan
* add Vector Point type for savig data
* Remove cmake file which magically re-appeared??
* Switched to std random library.
* Prepare Klaus test
* Add klaus3.g2o data.
* fix comment
* Fix derivatives
* Fixed broken GetDimension for Lie groups with variable dimension.
* Fix SOn tests to report correct dimension
* Added tests for Klaus3 data
* Add runWithRandomKlaus test for shonan.
* Finish runWithRandomKlaus unittest.
* Correct datafile.
* Correct the format.
* Added measured and keys methods
* Shonan works on Klaus data
* Create dense versions for wrappers, for testing
* Now store D, Q, and L
* Remove another cmake file incorrectly checked in.
* Found and fixed the bug in ComputeLambda !
* Now using Q in Lambdas calculation, so Lambdas agree with Eriksson18cvpr.
* Make FrobeniusFactor not use deprecated methods
* FrobeniusWormholeFactor takes Rot3 as argument
* Wrapped some more methods.
* Wrapped more methods
* Allow creating and populating BetweenFactorPose3s in python
* New constructors for ShonanAveraging
* add function of get measurements number
* Remove option not to use noise model
* wrap Use nrMeasurements
* Made Logmap a bit more tolerant of slightly degenerate rotations (with trace < -1)
* Allow for Anchor index
* Fix anchor bug
* Change outside view to Rot3 rather than SO3
* Add Lift in SOn class
* Make comet working
* Small fixes
* Delete extra function
* Add SOn::Lift
* Removed hardcoded flag
* Moved Frobenius factor to gtsam from unstable
* Added new tests and made an old regression pass again
* Cleaned up formatting and some comments, added EXPORT directives
* Throw exception if wrongly dimensioned values are given
* static_cast and other throw
* Fixed run-time dimension
* Added gauge-constraining factor
* LM parameters now passed in, added Gauge fixing
* 2D test scaffold
* Comments
* Pre-allocated generators
* Document API
* Add optional weight
* New prior weeights infrastructure
* Made d a template parameter
* Recursive Hat and RetractJacobian test
* Added Spectra 0.9.0 to 3rdparty
* Enabling 2D averaging
* Templatized Wormhole factor
* ignore xcode folder
* Fixed vec and VectorizedGenerators templates for fixed N!=3 or 4
* Simplifying constructors
Moved file loading to tests (for now)
All unit tests pass for d==3!
* Templated some methods internally
* Very generic parseToVector
* refactored load2d
* Very much improved FrobeniusWormholeFactor (Shonan) Jacobians
* SO(2) averaging works !
* Templated parse methods
* Switched to new Dataset paradigm
* Moved Shonan to gtsam
* Checked noise model is correctly gotten from file
* Fixed covariance bug
* Making Shonan wrapper work
* Renamed FrobeniusWormholeFactor to ShonanFactor and moved into its own compilation unit in gtsam/sfm
* Fixed wrong include
* Simplified interface (removed irrelevant random inits) and fixed eigenvector test
* Removed stray boost::none
* Added citation as suggested by Jose
* Made descent test deterministic
* Fixed some comments, commented out flaky test
Co-authored-by: Jing Wu <jingwu@gatech.edu>
Co-authored-by: jingwuOUO <wujing2951@gmail.com>
Co-authored-by: swang <swang736@gatech.edu>
Co-authored-by: ss <ss>
Co-authored-by: Fan Jiang <prof.fan@foxmail.com>
2020-08-17 19:43:10 +08:00
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: NonlinearFactor(keys), d_(static_cast<size_t>(d)) {
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2019-04-17 12:05:53 +08:00
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if (d <= 0) {
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throw std::invalid_argument(
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"KarcherMeanFactor needs dimension for dynamic types.");
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}
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Feature/shonan averaging (#473)
Shonan Rotation Averaging.
199 commit messages below, many are obsolete as design has changed quite a bit over time, especially from the earlier period where I thought we only needed SO(4).
* prototyping weighted sampler
* Moved WeightedSampler into its own header
* Random now uses std header <random>.
* Removed boost/random usage from linear and discrete directories
* Made into class
* Now using new WeightedSampler class
* Inlined random direction generation
* eradicated last vestiges of boost/random in gtsam_unstable
* Added 3D example g2o file
* Added Frobenius norm factors
* Shonan averaging algorithm, using SOn class
* Wrapping Frobenius and Shonan
* Fixed issues with <<
* Use Builder parameters
* Refactored Shonan interface
* Fixed << issues as well as MATLAB segfault, using eval(), as discussed in issue #451
* ShonanAveragingParameters
* New factor FrobeniusWormholeFactorP computes |Rj*P - Ri*P*Rij|
* Fixed broken GetDimension for Lie groups with variable dimension.
* Removed all but Shonan averaging factor and made everything work with new SOn
* Just a single WormholeFactor, wrapped noise model
* Use std <random>
* comments/todos
* added timing script
* add script to process ShonanAveraging timing results
* Now producing a CSV file
* Parse csv file and make combined plot
* Fixed range
* change p value and set two flags on
* input file path, all the csv files proceeses at the same time
* add check convergence rate part
* csv file have name according to input data name
* correct one mistake in initialization
* generate the convergence rate for each p value
* add yticks for the bar plot
* add noises to the measurements
* test add noise
* Basic structure for checkOptimalityAt
* change optimizer method to cholesky
* buildQ now working. Tests should be better but visually inspected.
* multiple test with cholesky
* back
* computeLambda now works
* make combined plots while make bar plot
* Calculate minimum eigenvalue - the very expensive version
* Exposed computeMinEigenValue
* make plots and bar togenter
* method change to jacobi
* add time for check optimality, min_eigen_value, sub_bound
* updated plot min_eigen value and subounds
* Adding Spectra headers
* David's min eigenvalue code inserted and made to compile.
* Made it work
* Made "run" method work.
* add rim.g2o name
* Fixed bug in shifting eigenvalues
* roundSolution which replaces projectFrom
* removed extra arguments
* Added to wrapper
* Add SOn to template lists
* roundSolution delete the extra arguement p
* only calculate p=5 and change to the correct way computing f_R
* Fixed conflict and made Google-style name changes
* prototype descent code and unit test for initializeWithDescent
* add averaging cost/time part in processing data
* initializewithDescent success in test
* Formatting and find example rather than hardcode
* Removed accidentally checked in cmake files
* give value to xi by block
* correct gradient descent
* correct xi
* }
* Fix wrapper
* Make Hat/Vee have alternating signs
* MakeATangentVector helpder function
* Fixed cmake files
* changed sign
* add line search
* unit test for line search
* test real data with line search
* correct comment
* Fix boost::uniform_real
* add save .dat file
* correct test case
* add explanation
* delete redundant cout
* add name to .dat output file
* correct checkR
* add get poses_ in shonan
* add Vector Point type for savig data
* Remove cmake file which magically re-appeared??
* Switched to std random library.
* Prepare Klaus test
* Add klaus3.g2o data.
* fix comment
* Fix derivatives
* Fixed broken GetDimension for Lie groups with variable dimension.
* Fix SOn tests to report correct dimension
* Added tests for Klaus3 data
* Add runWithRandomKlaus test for shonan.
* Finish runWithRandomKlaus unittest.
* Correct datafile.
* Correct the format.
* Added measured and keys methods
* Shonan works on Klaus data
* Create dense versions for wrappers, for testing
* Now store D, Q, and L
* Remove another cmake file incorrectly checked in.
* Found and fixed the bug in ComputeLambda !
* Now using Q in Lambdas calculation, so Lambdas agree with Eriksson18cvpr.
* Make FrobeniusFactor not use deprecated methods
* FrobeniusWormholeFactor takes Rot3 as argument
* Wrapped some more methods.
* Wrapped more methods
* Allow creating and populating BetweenFactorPose3s in python
* New constructors for ShonanAveraging
* add function of get measurements number
* Remove option not to use noise model
* wrap Use nrMeasurements
* Made Logmap a bit more tolerant of slightly degenerate rotations (with trace < -1)
* Allow for Anchor index
* Fix anchor bug
* Change outside view to Rot3 rather than SO3
* Add Lift in SOn class
* Make comet working
* Small fixes
* Delete extra function
* Add SOn::Lift
* Removed hardcoded flag
* Moved Frobenius factor to gtsam from unstable
* Added new tests and made an old regression pass again
* Cleaned up formatting and some comments, added EXPORT directives
* Throw exception if wrongly dimensioned values are given
* static_cast and other throw
* Fixed run-time dimension
* Added gauge-constraining factor
* LM parameters now passed in, added Gauge fixing
* 2D test scaffold
* Comments
* Pre-allocated generators
* Document API
* Add optional weight
* New prior weeights infrastructure
* Made d a template parameter
* Recursive Hat and RetractJacobian test
* Added Spectra 0.9.0 to 3rdparty
* Enabling 2D averaging
* Templatized Wormhole factor
* ignore xcode folder
* Fixed vec and VectorizedGenerators templates for fixed N!=3 or 4
* Simplifying constructors
Moved file loading to tests (for now)
All unit tests pass for d==3!
* Templated some methods internally
* Very generic parseToVector
* refactored load2d
* Very much improved FrobeniusWormholeFactor (Shonan) Jacobians
* SO(2) averaging works !
* Templated parse methods
* Switched to new Dataset paradigm
* Moved Shonan to gtsam
* Checked noise model is correctly gotten from file
* Fixed covariance bug
* Making Shonan wrapper work
* Renamed FrobeniusWormholeFactor to ShonanFactor and moved into its own compilation unit in gtsam/sfm
* Fixed wrong include
* Simplified interface (removed irrelevant random inits) and fixed eigenvector test
* Removed stray boost::none
* Added citation as suggested by Jose
* Made descent test deterministic
* Fixed some comments, commented out flaky test
Co-authored-by: Jing Wu <jingwu@gatech.edu>
Co-authored-by: jingwuOUO <wujing2951@gmail.com>
Co-authored-by: swang <swang736@gatech.edu>
Co-authored-by: ss <ss>
Co-authored-by: Fan Jiang <prof.fan@foxmail.com>
2020-08-17 19:43:10 +08:00
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// Create the constant Jacobian made of d*d identity matrices,
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// where d is the dimensionality of the manifold.
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Matrix A = Matrix::Identity(d, d);
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if (beta) A *= std::sqrt(*beta);
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2019-04-17 12:05:53 +08:00
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std::map<Key, Matrix> terms;
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for (Key j : keys) {
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Feature/shonan averaging (#473)
Shonan Rotation Averaging.
199 commit messages below, many are obsolete as design has changed quite a bit over time, especially from the earlier period where I thought we only needed SO(4).
* prototyping weighted sampler
* Moved WeightedSampler into its own header
* Random now uses std header <random>.
* Removed boost/random usage from linear and discrete directories
* Made into class
* Now using new WeightedSampler class
* Inlined random direction generation
* eradicated last vestiges of boost/random in gtsam_unstable
* Added 3D example g2o file
* Added Frobenius norm factors
* Shonan averaging algorithm, using SOn class
* Wrapping Frobenius and Shonan
* Fixed issues with <<
* Use Builder parameters
* Refactored Shonan interface
* Fixed << issues as well as MATLAB segfault, using eval(), as discussed in issue #451
* ShonanAveragingParameters
* New factor FrobeniusWormholeFactorP computes |Rj*P - Ri*P*Rij|
* Fixed broken GetDimension for Lie groups with variable dimension.
* Removed all but Shonan averaging factor and made everything work with new SOn
* Just a single WormholeFactor, wrapped noise model
* Use std <random>
* comments/todos
* added timing script
* add script to process ShonanAveraging timing results
* Now producing a CSV file
* Parse csv file and make combined plot
* Fixed range
* change p value and set two flags on
* input file path, all the csv files proceeses at the same time
* add check convergence rate part
* csv file have name according to input data name
* correct one mistake in initialization
* generate the convergence rate for each p value
* add yticks for the bar plot
* add noises to the measurements
* test add noise
* Basic structure for checkOptimalityAt
* change optimizer method to cholesky
* buildQ now working. Tests should be better but visually inspected.
* multiple test with cholesky
* back
* computeLambda now works
* make combined plots while make bar plot
* Calculate minimum eigenvalue - the very expensive version
* Exposed computeMinEigenValue
* make plots and bar togenter
* method change to jacobi
* add time for check optimality, min_eigen_value, sub_bound
* updated plot min_eigen value and subounds
* Adding Spectra headers
* David's min eigenvalue code inserted and made to compile.
* Made it work
* Made "run" method work.
* add rim.g2o name
* Fixed bug in shifting eigenvalues
* roundSolution which replaces projectFrom
* removed extra arguments
* Added to wrapper
* Add SOn to template lists
* roundSolution delete the extra arguement p
* only calculate p=5 and change to the correct way computing f_R
* Fixed conflict and made Google-style name changes
* prototype descent code and unit test for initializeWithDescent
* add averaging cost/time part in processing data
* initializewithDescent success in test
* Formatting and find example rather than hardcode
* Removed accidentally checked in cmake files
* give value to xi by block
* correct gradient descent
* correct xi
* }
* Fix wrapper
* Make Hat/Vee have alternating signs
* MakeATangentVector helpder function
* Fixed cmake files
* changed sign
* add line search
* unit test for line search
* test real data with line search
* correct comment
* Fix boost::uniform_real
* add save .dat file
* correct test case
* add explanation
* delete redundant cout
* add name to .dat output file
* correct checkR
* add get poses_ in shonan
* add Vector Point type for savig data
* Remove cmake file which magically re-appeared??
* Switched to std random library.
* Prepare Klaus test
* Add klaus3.g2o data.
* fix comment
* Fix derivatives
* Fixed broken GetDimension for Lie groups with variable dimension.
* Fix SOn tests to report correct dimension
* Added tests for Klaus3 data
* Add runWithRandomKlaus test for shonan.
* Finish runWithRandomKlaus unittest.
* Correct datafile.
* Correct the format.
* Added measured and keys methods
* Shonan works on Klaus data
* Create dense versions for wrappers, for testing
* Now store D, Q, and L
* Remove another cmake file incorrectly checked in.
* Found and fixed the bug in ComputeLambda !
* Now using Q in Lambdas calculation, so Lambdas agree with Eriksson18cvpr.
* Make FrobeniusFactor not use deprecated methods
* FrobeniusWormholeFactor takes Rot3 as argument
* Wrapped some more methods.
* Wrapped more methods
* Allow creating and populating BetweenFactorPose3s in python
* New constructors for ShonanAveraging
* add function of get measurements number
* Remove option not to use noise model
* wrap Use nrMeasurements
* Made Logmap a bit more tolerant of slightly degenerate rotations (with trace < -1)
* Allow for Anchor index
* Fix anchor bug
* Change outside view to Rot3 rather than SO3
* Add Lift in SOn class
* Make comet working
* Small fixes
* Delete extra function
* Add SOn::Lift
* Removed hardcoded flag
* Moved Frobenius factor to gtsam from unstable
* Added new tests and made an old regression pass again
* Cleaned up formatting and some comments, added EXPORT directives
* Throw exception if wrongly dimensioned values are given
* static_cast and other throw
* Fixed run-time dimension
* Added gauge-constraining factor
* LM parameters now passed in, added Gauge fixing
* 2D test scaffold
* Comments
* Pre-allocated generators
* Document API
* Add optional weight
* New prior weeights infrastructure
* Made d a template parameter
* Recursive Hat and RetractJacobian test
* Added Spectra 0.9.0 to 3rdparty
* Enabling 2D averaging
* Templatized Wormhole factor
* ignore xcode folder
* Fixed vec and VectorizedGenerators templates for fixed N!=3 or 4
* Simplifying constructors
Moved file loading to tests (for now)
All unit tests pass for d==3!
* Templated some methods internally
* Very generic parseToVector
* refactored load2d
* Very much improved FrobeniusWormholeFactor (Shonan) Jacobians
* SO(2) averaging works !
* Templated parse methods
* Switched to new Dataset paradigm
* Moved Shonan to gtsam
* Checked noise model is correctly gotten from file
* Fixed covariance bug
* Making Shonan wrapper work
* Renamed FrobeniusWormholeFactor to ShonanFactor and moved into its own compilation unit in gtsam/sfm
* Fixed wrong include
* Simplified interface (removed irrelevant random inits) and fixed eigenvector test
* Removed stray boost::none
* Added citation as suggested by Jose
* Made descent test deterministic
* Fixed some comments, commented out flaky test
Co-authored-by: Jing Wu <jingwu@gatech.edu>
Co-authored-by: jingwuOUO <wujing2951@gmail.com>
Co-authored-by: swang <swang736@gatech.edu>
Co-authored-by: ss <ss>
Co-authored-by: Fan Jiang <prof.fan@foxmail.com>
2020-08-17 19:43:10 +08:00
|
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terms[j] = A;
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2019-04-17 12:05:53 +08:00
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}
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Feature/shonan averaging (#473)
Shonan Rotation Averaging.
199 commit messages below, many are obsolete as design has changed quite a bit over time, especially from the earlier period where I thought we only needed SO(4).
* prototyping weighted sampler
* Moved WeightedSampler into its own header
* Random now uses std header <random>.
* Removed boost/random usage from linear and discrete directories
* Made into class
* Now using new WeightedSampler class
* Inlined random direction generation
* eradicated last vestiges of boost/random in gtsam_unstable
* Added 3D example g2o file
* Added Frobenius norm factors
* Shonan averaging algorithm, using SOn class
* Wrapping Frobenius and Shonan
* Fixed issues with <<
* Use Builder parameters
* Refactored Shonan interface
* Fixed << issues as well as MATLAB segfault, using eval(), as discussed in issue #451
* ShonanAveragingParameters
* New factor FrobeniusWormholeFactorP computes |Rj*P - Ri*P*Rij|
* Fixed broken GetDimension for Lie groups with variable dimension.
* Removed all but Shonan averaging factor and made everything work with new SOn
* Just a single WormholeFactor, wrapped noise model
* Use std <random>
* comments/todos
* added timing script
* add script to process ShonanAveraging timing results
* Now producing a CSV file
* Parse csv file and make combined plot
* Fixed range
* change p value and set two flags on
* input file path, all the csv files proceeses at the same time
* add check convergence rate part
* csv file have name according to input data name
* correct one mistake in initialization
* generate the convergence rate for each p value
* add yticks for the bar plot
* add noises to the measurements
* test add noise
* Basic structure for checkOptimalityAt
* change optimizer method to cholesky
* buildQ now working. Tests should be better but visually inspected.
* multiple test with cholesky
* back
* computeLambda now works
* make combined plots while make bar plot
* Calculate minimum eigenvalue - the very expensive version
* Exposed computeMinEigenValue
* make plots and bar togenter
* method change to jacobi
* add time for check optimality, min_eigen_value, sub_bound
* updated plot min_eigen value and subounds
* Adding Spectra headers
* David's min eigenvalue code inserted and made to compile.
* Made it work
* Made "run" method work.
* add rim.g2o name
* Fixed bug in shifting eigenvalues
* roundSolution which replaces projectFrom
* removed extra arguments
* Added to wrapper
* Add SOn to template lists
* roundSolution delete the extra arguement p
* only calculate p=5 and change to the correct way computing f_R
* Fixed conflict and made Google-style name changes
* prototype descent code and unit test for initializeWithDescent
* add averaging cost/time part in processing data
* initializewithDescent success in test
* Formatting and find example rather than hardcode
* Removed accidentally checked in cmake files
* give value to xi by block
* correct gradient descent
* correct xi
* }
* Fix wrapper
* Make Hat/Vee have alternating signs
* MakeATangentVector helpder function
* Fixed cmake files
* changed sign
* add line search
* unit test for line search
* test real data with line search
* correct comment
* Fix boost::uniform_real
* add save .dat file
* correct test case
* add explanation
* delete redundant cout
* add name to .dat output file
* correct checkR
* add get poses_ in shonan
* add Vector Point type for savig data
* Remove cmake file which magically re-appeared??
* Switched to std random library.
* Prepare Klaus test
* Add klaus3.g2o data.
* fix comment
* Fix derivatives
* Fixed broken GetDimension for Lie groups with variable dimension.
* Fix SOn tests to report correct dimension
* Added tests for Klaus3 data
* Add runWithRandomKlaus test for shonan.
* Finish runWithRandomKlaus unittest.
* Correct datafile.
* Correct the format.
* Added measured and keys methods
* Shonan works on Klaus data
* Create dense versions for wrappers, for testing
* Now store D, Q, and L
* Remove another cmake file incorrectly checked in.
* Found and fixed the bug in ComputeLambda !
* Now using Q in Lambdas calculation, so Lambdas agree with Eriksson18cvpr.
* Make FrobeniusFactor not use deprecated methods
* FrobeniusWormholeFactor takes Rot3 as argument
* Wrapped some more methods.
* Wrapped more methods
* Allow creating and populating BetweenFactorPose3s in python
* New constructors for ShonanAveraging
* add function of get measurements number
* Remove option not to use noise model
* wrap Use nrMeasurements
* Made Logmap a bit more tolerant of slightly degenerate rotations (with trace < -1)
* Allow for Anchor index
* Fix anchor bug
* Change outside view to Rot3 rather than SO3
* Add Lift in SOn class
* Make comet working
* Small fixes
* Delete extra function
* Add SOn::Lift
* Removed hardcoded flag
* Moved Frobenius factor to gtsam from unstable
* Added new tests and made an old regression pass again
* Cleaned up formatting and some comments, added EXPORT directives
* Throw exception if wrongly dimensioned values are given
* static_cast and other throw
* Fixed run-time dimension
* Added gauge-constraining factor
* LM parameters now passed in, added Gauge fixing
* 2D test scaffold
* Comments
* Pre-allocated generators
* Document API
* Add optional weight
* New prior weeights infrastructure
* Made d a template parameter
* Recursive Hat and RetractJacobian test
* Added Spectra 0.9.0 to 3rdparty
* Enabling 2D averaging
* Templatized Wormhole factor
* ignore xcode folder
* Fixed vec and VectorizedGenerators templates for fixed N!=3 or 4
* Simplifying constructors
Moved file loading to tests (for now)
All unit tests pass for d==3!
* Templated some methods internally
* Very generic parseToVector
* refactored load2d
* Very much improved FrobeniusWormholeFactor (Shonan) Jacobians
* SO(2) averaging works !
* Templated parse methods
* Switched to new Dataset paradigm
* Moved Shonan to gtsam
* Checked noise model is correctly gotten from file
* Fixed covariance bug
* Making Shonan wrapper work
* Renamed FrobeniusWormholeFactor to ShonanFactor and moved into its own compilation unit in gtsam/sfm
* Fixed wrong include
* Simplified interface (removed irrelevant random inits) and fixed eigenvector test
* Removed stray boost::none
* Added citation as suggested by Jose
* Made descent test deterministic
* Fixed some comments, commented out flaky test
Co-authored-by: Jing Wu <jingwu@gatech.edu>
Co-authored-by: jingwuOUO <wujing2951@gmail.com>
Co-authored-by: swang <swang736@gatech.edu>
Co-authored-by: ss <ss>
Co-authored-by: Fan Jiang <prof.fan@foxmail.com>
2020-08-17 19:43:10 +08:00
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whitenedJacobian_ =
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2023-01-18 06:05:12 +08:00
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std::make_shared<JacobianFactor>(terms, Vector::Zero(d));
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2019-04-17 12:05:53 +08:00
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}
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2023-01-12 05:33:25 +08:00
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} // namespace gtsam
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