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>
* Add GitHub Actions
* Add Windows Check
* Fix wrong os selection
* Add XCode version
* Upgrade GCC Version
* Make GCC match Ubuntu name
* Do not fail everyone when one failed
* More checks on ccache
* Do not expose GenericValue on Windows
* Fix BetweenFactor for Windows
* Update
* Add Python CI
* Typo
* Add note about GENERICVALUE_VISIBILITY
* Fix Windows Boost
* Change substitution scheme to PowerShell
* Fix the spurious error of the Point3 default constructor
* Separate builds to allow easier restarts
* Fix uninitialized variable usage
* Change of policy, only build python stuff, mac and win on PRs
* Further separate the Python tests
- Added python-install target variable for easy updating.
- Fixed/Added all dependencies so that everything is built automatically.
- Removed unnecessary install commands
Build everything inside the build/cython{BuildType} directory directly, so we can bypass the `make install` step and introduce the `make python-install` step which allows cmake to handle all dependencies.
* add deadsnakes ppa to install python3.6 on Ubuntu Xenial
* updated travis distro to Ubuntu 18.04 bionic
* Revert "updated travis distro to Ubuntu 18.04 bionic"
This reverts commit 323264a924e8554da49c27a374e9a6278c5a659e.
* restrict numpy version to be less than 1.19.0
* use ubuntu packaged numpy as baseline version to test against
* downgrade minimum required version of numpy to version supported by Ubuntu Xenial
* undo explicit pip install
Frank Dellaert
Frank Dellaert
Fan Jiang
mawallace
Varun Agrawal
Fan Jiang