Commit Graph

5 Commits

Author SHA1 Message Date
Sergiu Deitsch f90833f5fa Simplify symbol export
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
2022-02-14 20:19:08 +01:00
Sergiu Deitsch c14f360e63 Drop trivial special members
Do not define trivial constructors or destructors unless necessary
(e.g., for implementing pimpl) following the rule of zero. Define
virtual base class destructors out-of-line to avoid emitting vtables in
every translation unit.

Change-Id: Iea2d8978e62a8ee5a97b86cbb4e858d56e0fb274
2022-02-09 21:30:14 +01:00
Sergiu Deitsch a35bd1bf90 Use = default for trivial special members
Applied changes correspond to clang-tidy fixes
stemming from the modernize-use-equals-default check.

Change-Id: I254b0908a76d464131564b637cd0e42a6b03fb5a
2022-02-09 18:38:52 +01:00
Sameer Agarwal 4362a21699 Run clang-format on the public headers.
Also update copyright year.

Change-Id: I8508d4fd4564c646ec2281a1b3b2c36136b54b46
2019-12-03 14:50:37 -08:00
Sameer Agarwal 056ba9bb1d Add AutoDiffFirstOrderFunction
This is to FirstOrderFunction, what AutoDiffCostFunction is to CostFunction.
This allows users of GradientSolver to be able to define objective functions
without requiring them to define the derivatives.

The implementation uses the same Jet objects for computing the gradient as
is used by AutoDiffCostFunction.

Change-Id: Ide6e60532a3adab9be9899ba9b368dc267fd2dbb
2019-03-03 06:50:56 +00:00