Manifolds are now part of the public API and co-exist
with LocalParameterizations.
1. Add Manifolds to the Problem API.
a. AddParameterBlock(double*, int, Manifold*)
b. SetParameterization(double*, Manifold*)
b. GetManifold(const double*)
c. HasManifold(const double*)
2. Internally Ceres now only uses Manifolds. When the user uses
a LocalParameterization, it is wrapped in a ManifoldAdapter.
3. To preserve the API semantics while keeping the internals clean
we need a new map in ProblemImpl which stores the association
between parameter blocks and local parameterizations. This
is temporary, it will go away once this transition is complete.
4. There are NO algorithmic changes, as in we are not using
any of the expanded interface of the Manifold objects yet.
That will come later.
5. All tests that use LocalParameterization have been duplicated
to use Manifolds, and when this transition is complete the
LocalParameterization based tests will be deleted.
6. Public documentation for the API has been updated. Deprecation
notices to the documentation as well as C++ annotations will come
later.
7. Similar changes have been made to GradientProblem.
Change-Id: I8e03c8ced6e141876ef3eca5740c113afa788f0c
- ensure all public headers files adhere to clang-format
- preserve one-per-line for enums by adding trailing comma
- preserve include order for en/disable_warning.h
Change-Id: I78dbd0527a294ab2ec5f074fb426e48b20c393e6
Due to the large amount of changes made as part of
the C++11 migration, it makes sense to have a
large version bump.
Change-Id: I2d81828e2d8e23f0829070726e7b3ec31d7f1724
THIS IS AN API BREAKING CHANGE.
Decouple the algorithm from the sparse linear algebra
library being used to perform the computation.
Before this change
Covariance::AlgorithmType had values
DENSE_SVD
EIGEN_SPARSE_QR
SUITE_SPARSE_QR
This has been replaced by two enums now.
Covariance::Options::sparse_linear_algebra_library_type
which can take values EIGEN_SPARSE, SUITE_SPARSE or CX_SPARSE.
The last one is currently not supported.
And Covariance::Options::algorithm_type takes values
DENSE_SVD
SPARSE_QR
This sets the stage for future extensions of the covariance
computation algorithm.
Also as part of this change, the covariance computation chapter
has been made a top level chapter on its own instead of being
buried deep inside the Solving Non-linear Least Squares problem.
Change-Id: Ibfbf60902d8d17694d9ff585047a5a57d329ab22
Accumulate the number of steps of the line search algorithm
and report it as part of Summary::FullReport.
Change-Id: I1de12784009a3e08f2a2c2aff5085d57a3c73828
Since Ceres is moving to using GitHub for issues, and the Google
Code URL in the current copyright header will soon become invalid,
update all the headers.
Change-Id: I1fce70375d1bcf098591f07b4d8f01a5c1e0789c
This replaces the broken CERES_VERSION and CERES_ABI_VERSION
defines with a different set, including integer versions for
MAJOR/MINOR/etc.
This also adds the Ceres version to Solver::FullReport().
Example report from powell:
Ceres Solver v1.10.0 Solve Report
----------------------------------
Original Reduced
Parameter blocks 4 4
Parameters 4 4
Residual blocks 4 4
Residual 4 4
Minimizer TRUST_REGION
Dense linear algebra library EIGEN
Trust region strategy LEVENBERG_MARQUARDT
Given Used
Linear solver DENSE_QR DENSE_QR
Threads 1 1
Linear solver threads 1 1
Cost:
Initial 1.075000e+02
Final 1.791438e-14
Change 1.075000e+02
Minimizer iterations 14
Successful steps 14
Unsuccessful steps 0
Time (in seconds):
Preprocessor 0.001
Residual evaluation 0.000
Jacobian evaluation 0.000
Linear solver 0.000
Minimizer 0.001
Postprocessor 0.000
Total 0.003
Change-Id: I5bf0e8023693e9195276b1f1e881b13121ba1196
Termination: CONVERGENCE (Gradient tolerance reached. Gradient max norm: 3.642190e-11 <= 1.000000e-10)
Sameer Agarwal