Replace ceres::String* with their more modern and performant
absl strings library equivalent and delete our string
manipulation library.
Change-Id: Iecbdba9864e0abf329778f81fdc0708f78f7594f
1. Add abseil-cpp as a submodule. We are tracking the latest LTS
release, which is lts_2024_01_16.
2. Replace glog/gflags with absl::log and absl::flags.
3. Remove miniglog
4. Also take a whack at making the bazel build work with
abseil-cpp and gtest.
There are a number of TODOs in this CL that still need to be resolved.
Change-Id: I39355ed7d61375be4ebcbc8596d9cc70acc1c678
1. Add a version history
2. Update copyright years across the code base
3. Run format_all.sh
4. Update version strings from 2.1.0 to 2.2.0 in the docs and
elsewhere.
Change-Id: I46d8d479d54bd6002d532785e67342106e73c9ac
Currently, the logic for exporting symbols is rather complicated: when
tests are enabled internal symbols are exported in addition to the
public symbols. Such logic causes several problems. (1) Test binaries
link against a Ceres build that is different from the final release
since fewer optimizations are applied if more symbols are exported. (2)
Also, some toolchains hide symbols by default breaking the existing
logic eventually causing linker errors.
Since internal symbols are not intended to be used outside of the
project, we can compile them into object files and use exactly the same
binary code both for the final build and the tests without relying on
conditionals.
By default, all symbols are now hidden unless annotated as public.
Internal symbols are explicitly marked as not being exported in case
users chose not to hide symbols by default.
Change-Id: I589dd10be2f6f438508783cf99d141af0120057b
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
Local parameterizations with zero tangent/local size will cause the
corresponding parameter block to be treated as constant.
https://github.com/ceres-solver/ceres-solver/issues/347
Change-Id: I554a2acc420f5dd9d0cc7f97b691877eb057b2c0
Introduce IsSetConstantByUser method which indicates whether
the user set the parameter block constant or not.
Changed the definition of IsConstant() to indicate if the
parameter block is effectively constant or not, which is
now the uniion of two conditions - the user set it to be constant
or the local tangent space is of size zero. Currently
this change has no effect as we do not allow local parameterizations
with zero tangent space size, but thats an inconsistency we are
working on fixing.
A variety of code cleans up to parameter_block.h
1. Remove an old TODO comment which is not really actionable.
2. Remove Init() method.
3. NULL -> nullptr
4. memcpy -> std::copy
Change-Id: I12973ee0f053fa22f09908cf36e9aa57d9d8dd74
This header defined integral types in the pre-C++11 days, and can
be replaced with <cstdint> and the types defined therein.
Also remove a shallow (and incorrect) typedef in include/ceres/types.h
https://github.com/ceres-solver/ceres-solver/issues/409
Change-Id: I398c652f74d24bbeea459672508bf28f591b100f
When Solver::Options::check_gradients is true, Ceres internally
creates a new ProblemImpl object which wraps each CostFunction
in the user's problem with a GradientCheckingCostFunction.
Doing this also requires creating new ParameterBlock objects,
and when support for upper and lower bounds was added to Ceres,
CreateGradientCheckingProblemImpl should also have been updated
to create a problem with the same parameter bounds. As a result,
if check_gradients is enabled for a bounded problem, it constructs
an unconstrained problem and solves it.
This CL fixes this, by introducing Problem::GetParameterLowerBound,
and Problem::GetParameterUpperBound and using them to create a bounded
problem when checking gradients.
Thanks to @pbeeson for not only reporting this problem, but also
providing a small standalone reproduction which made debugging this
possible.
https://github.com/ceres-solver/ceres-solver/issues/379
Change-Id: Id18eb858a7009bf4fa452a21b925922d13f3249f
1. Replace HashMap and HashSet with std::unordered_map and
std::unordered_set respectively.
2. Extract the pair hasher into a struct pair_hash.
3. Delete collections_port.h
4. Convert explicit iterator based loops to auto based
loops where sensible.
Change-Id: Ib88bcd13a7463d18435639d3b771abaa52080efb
1. SubsetParameterization can now be constructed such that all
parameters are constant. This is required for it be used as part
of a ProductParameterization to hold a part of parameter block
constant. For example, a parameter block consisting of a rotation
as a quaternion and a translation vector can now have a local
parameterization where the translation part is constant and the
quaternion part has a QuaternionParameterization associated with it.
2. The check for the tangent space of a parameterization being
positive dimensional. We were not doing this check up till now
and the user could accidentally create parameterizations like this
and create a problem for themselves. This will ensure that even
though one can construct a SubsetParameterization where all
parameters are constant, you cannot actually use it as a local
parameterization for an entire parameter block. Which is how
it was before, but the check was inside the SubsetParameterization
constructor.
3. Added more tests and refactored existing tests to be more
granular.
Change-Id: Ic0184a1f30e3bd8a416b02341781a9d98e855ff7
When the user provides an ordering which starts at a non-zero group id,
or has gaps in the groups, then CAMD, the algorithm used to reorder
the program can crash or return garbage results.
The solution is to map the ordering into grouping constraints, and then
to re-number the groups to be contiguous using a call to
MapValuesToContiguousRange. This was already done for CAMD based
ordering for Schur type solvers, but was not done for SPARSE_NORMAL_CHOLESKY.
Thanks to Bernhard Zeisl for not only reporting the bug but also
providing a reproduction.
Change-Id: I5cfae222d701dfdb8e1bda7f0b4670a30417aa89
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
For historical reasons we had a "using namespace std;" in port.h. This
is generally a bad idea. So removing it and along the way doing a bunch
of cpplint cleanup.
Change-Id: Ia125601a55ae62695e247fb0250df4c6f86c46c6
Problems that do not use bounds do not have to pay the
price of storing bounds constraints.
Also replace the raw pointer access to the upper and
lower bounds arrays with accessors which hides the
lazy initialization from the user.
Change-Id: I0325a35de9c29f853559f891e32e7c777686e537
Add setters and getters for lower and upper bounds.
Generalize the Plus operation to include projection onto the
hypercube implied by the bounds.
Change-Id: I1e4028a9886c4064f31bbc5b7c22b0341a56c15d
Not entirely sure how and why this was compiling up till now.
Thanks to Carlos Hernandez for reporting this.
Change-Id: Ieadbb8cb0a3769afe9dcef927ff0287342e44f1f
This adds support for removing parameter and residual blocks.
There are two modes of operation: in the first, removals of
paremeter blocks are expensive, since each remove requires
scanning all residual blocks to find ones that depend on the
removed parameter. In the other, extra memory is sacrificed to
maintain a list of the residuals a parameter block depends on,
removing the need to scan. In both cases, removing residual blocks
is fast.
As a caveat, any removals destroys the ordering of the parameters,
so the residuals or jacobian returned from Solver::Solve() is
meaningless. There is some debate on the best way to handle this;
the details remain for a future change.
This also adds some overhead, even in the case that fast removals
are not requested:
- 1 int32 to each residual, to track its position in the program.
- 1 pointer to each parameter, to store the dependent residuals.
Change-Id: I71dcac8656679329a15ee7fc12c0df07030c12af
A non-linear generalization of Ruhe & Wedin's algorithm
for separable non-linear least squares problem. It is implemented
as coordinate descent on an independent subset of the parameter
blocks at the end of every successful Newton step. The resulting
algorithm has much improved convergence at the cost of some
execution time.
Change-Id: I8fdc5edbd0ba1e702c9658b98041b2c2ae705402
more than just the residual block evaluation routines now.
Check the step computed by the linear solver for finiteness, and terminate early
if it is not. This will prevent bugs where the solver continues to run after
encountering an nan.
Sameer Agarwal