- Change formatting standard to Cpp11. Main difference is not having
the space between two closing >> for nested templates. We don't
choose c++14, because older versions of clang-format (version 9
and earlier) don't know this value yet, and it doesn't make a
difference in the formatting.
- Apply clang-format to all (non generated) internal source files.
- Manually fix some code sections (clang-format on/off) and c-strings
- Exclude some embedded external files with very different formatting
(gtest/gmock)
- Add script to format all source files
Change-Id: Ic6cea41575ad6e37c9e136dbce176b0d505dc44d
This CL changes the implementation of AddResidualBlock() in
ceres::Problem using variadic templates. Also one new overload for
AddResidualBlock() is added using a double** and the number of
parameter blocks.
Change-Id: I007a82a06897335a117213a0d12fedb4a77076a0
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
A Ceres Context holds common global state that can be re-used within
Ceres. The Context current contains a thread pool if compiling with
C++11 threading support. Threads are expensive to create and destroy so
it is good to maintain across multiple Ceres solves.
Tested by compiling with and without TBB support and ran unit tests. Ran
bazel as well.
Change-Id: I82f598dfae642aa0e81a6039dc174608a5e8dbfb
This is a follow-up on c/7470. GradientCheckingCostFunction calls
callback_->SetGradientErrorDetected() in its Evaluate method,
which will run in multiple threads simultaneously when enabling
this option in the solver. Thus, the string append operation
inside that method has to be protected by a mutex.
Change-Id: I314ef1df2be52595370d9af05851bf6da39bb45e
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
This method numerically computes function derivatives in different
scales, extrapolating between intermediate results to conserve function
evaluations. Adaptive differentiation is essential to produce accurate
results for functions with noisy derivatives.
Full changelist:
-Created a new type of NumericDiffMethod (RIDDERS).
-Implemented EvaluateRiddersJacobianColumn in NumericDiff.
-Created unit tests with f(x) = x^2 + [random noise] and
f(x) = exp(x).
Change-Id: I2d6e924d7ff686650272f29a8c981351e6f72091
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
Ensure that when a new problem object is constructed for validing
gradients, the parameter blocks have their data pointers point to
the user's parameter blocks.
We used to do this inside solver_impl.cc, but doing this at
construction is the right thing to do.
Change-Id: I3bfdc89bb0027c8d67cde937e8f2fa385d89c30c
CostFunction now uses int32 instead of int16
to store the size of its parameter blocks.
This is an API breaking change.
Change-Id: I032ea583bc7ea4b3009be25d23a3be143749c73e
Move the GradientCheckingCostFunction to DynamicNumericDiffCostFunction.
Also fix a const correctness issue with DynamicNumericDiffCostFunction.
Change-Id: Id446810f43374e7b7db7fe4dd01a891e3c54abb9
Nikolaus Demmel