- Previously the LAPACK option meant would Ceres link against LAPACK,
whether directly or indirectly via SuiteSparse (if SUITESPARSE=ON),
as such if LAPACK=OFF, the use of SuiteSparse was disabled, even if
it was found.
- To support the use-case of using a limited LAPACK implementation that
satisfies SuiteSparse’s requirements, but potentially not Ceres’ we
now adopt the more conventional terminology whereby the LAPACK option
refers only to whether Ceres itself will directly call LAPACK
routines, not whether it or any of its dependencies will.
- This means that the LAPACK and SUITESPARSE options are now
independent.
- Also unnecessary calls to find_package(BLAS), as find_package(LAPACK)
already searches for BLAS, and appends the resulting libraries to
LAPACK_LIBRARIES if they are found.
Change-Id: I9cf5fa5e4cb621812f6f0526db8d16a7a39c9c8f
Skip the test in dynamic_sparsity_test when there are no sparse
linear algebra libraries available.
Also fix a minor typo in version_history.rst
Change-Id: Ie7cc14e655c58b6bd9625ce9f9025f94d0624d2d
Update the version history in preparation for 1.13.0RC1 and
also reformat older parts of the version history file.
Change-Id: I133e5966629e8277631ec5d407165ad188efa1e1
1. Fix a bug which was causing the cost and gradient evaluation
time to not be reported.
2. Add the number of times cost and gradients are evaluated to
the Summary object and to the output of FullReport.
Change-Id: Id0703cd2dafbf437f3e537fbdc30ae81d5f4f540
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This has been replaced by two enums now.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
- Using Ceres_[SOURCE/BINARY]_DIR (which are defined by CMake when
project(Ceres) is called, in favour of CMAKE_[SOURCE/BINARY]_DIR
enables Ceres to be nested within (and built by) a larger CMake
project (which also contains other projects).
- CMAKE_[SOURCE/BINARY]_DIR always refers to the top-level source
and binary directories (i.e. the first encountered), as a result if
Ceres is a nested project within a larger project, these would not
correctly identify the source/binary directories for Ceres (as they
would refer to the root project in which Ceres is nested).
- Using Ceres_[SOURCE/BINARY]_DIR should ensure that Ceres always uses
the correct source/binary directories, irrespective of whether Ceres
is nested or not.
Change-Id: I62226ea3f6552b1d7e2bdac1aef02f1f489ae55e
Doing this also necessitated some re-organization of the derivatives
article into chapters and some minor edits.
Change-Id: Ic08e83af138817173caa80a52a9e72707cd57512
Remove the "Guide" and expose the modeling and solving non-linear
least squares in the left hand side navigation bar.
Change-Id: Ibbb4f0f580a5981165a0945570fc0f4c4ea559e9
1. Refactor the python code that generates the template specializations
to remove code duplication.
2. Improved the logic for template specialization selection where
Eigen::Dynamic now serves as a wildcard.
3. Added schur_templates.h/cc which allows querying the set of available
template specializations without instantiating a linear solver.
4. Added Solver::Summary::schur_structre_given and
Solver::Summary::schur_structure_used and expose them in
Solver::Summary::FullReport for better performance debugging.
5. Updated the templates with newer dates and some minor comments cleanup
which lead to the the template specializations to be re-generated.
Change-Id: Iaf3c6f714353597899916c300465da01f151c3de
Binary operations between Jets and doubles are well defined
and should not require an explicit conversion to Jets to work.
This was an oversight earlier and lead to overzealous conversions
all over our in our example code.
Change-Id: I1799770818e136edfc0a5802d86037ce9aec4923
1. Section title changes.
2. Moving the glog discussion into installation.rst
3. Re-working the faqs into two separate chapters.
Change-Id: I95dd25bace50f0f9077ef114504999190686963e
Solver::Options::numeric_derivative_relative_step_size to
Solver::Options::gradient_check_numeric_derivative_relative_step_size
Change-Id: Ib89ae3f87e588d4aba2a75361770d2cec26f07aa
Change the Ceres gradient checking API to make is useful for
unit testing, clean up code duplication and fix interaction between
gradient checking and local parameterizations.
There were two gradient checking implementations, one being used
when using the check_gradients flag in the Solver, the other
being a standalone class. The standalone version was restricted
to cost functions with fixed parameter sizes at compile time, which
is being lifted here. This enables it to be used inside the
GradientCheckingCostFunction as well.
In addition, this installs new hooks in the Solver to ensure
that Solve will fail if any incorrect gradients are detected. This
way, you can set the check_gradient flags to true and detect
errors in an automated way, instead of just printing error information
to the log. The error log is now also returned in the Solver summary
instead of being printed directly. The user can then decide what to
do with it. The existing hooks for user callbacks are used for
this purpose to keep the internal API changes minimal and non-invasive.
The last and biggest change is the way the the interaction between
local parameterizations and the gradient checker works. Before,
local parameterizations would be ignored by the checker. However,
if a cost function does not compute its Jacobian along the null
space of the local parameterization, this wil not have any effect
on the solver, but would result in a gradient checker error.
With this change, the Jacobians are multiplied by the Jacobians
of the respective local parameterization and thus being compared
in the tangent space only.
The typical use case for this are quaternion parameters, where
a cost function will typically assume that the quaternion is
always normalized, skipping the correct computation of the Jacobian
along the normal to save computation cost.
Change-Id: I5e1bb97b8a899436cea25101efe5011b0bb13282
- Users can now specify particular components from Ceres, such as
SuiteSparse support) that must be present in a detected version of
Ceres in order for it to be reported as found by find_package().
- This allows users to specify for example that they require a version
of Ceres with SuiteSparse support at configure time, rather than
finding out only at run time that Ceres was not compiled with the
options they require.
- The list of available components are built directly from the Ceres
compile options.
- The meta-module SparseLinearAlgebraLibrary is present if at least
one sparse linear algebra backend is available.
Change-Id: I65f1ddfd7697e6dd25bb4ac7e54f5097d3ca6266
Alex Stewart