This commit includes the following:
- Changes to CMake to make it safer to see which compiler flags are supported,
so this way we do not need to worry about version checks in CMake.
- Unix platforms (which includes both Linux and Apple as far as i can tell)
will now enable -Wmissing-declarations warning for the whole Ceres.
- Changes in all sources to solve missing declaration warning. In most cases
it was either matter of using static qualifier or moving functions to an
anonymous namespace.
In one case the function got removed, since it seems to be unused.
Additionally, in slam examples there was a non-inlined function implementation
in a header, which is a direct way to cause linking errors if other .cc file
will include that helper header.
- All third party sources (which is currently only gmock) has this extra
paranoid warning disabled.
This warning is important in the following cases:
- Detect helper functions which are not needed anymore.
- Avoid unnoticed pollution of namespace.
- Avoid bad level calls.
- Avoid missing updates in header files after changes in implementation file.
- Helps integrating Ceres into software where paranoid warnings are important.
Change-Id: I9b1044aced3910d8c6b2356cfe2bf57f3c8c58db
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
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
The standard sparse normal Cholesky solver assumes a fixed
sparsity pattern which is useful for a large number of problems
presented to Ceres. However, some problems are symbolically dense
but numerically sparse i.e. each residual is a function of a
large number of parameters but at any given state the residual
only depends on a sparse subset of them. For these class of
problems it is faster to re-analyse the sparsity pattern of the
jacobian at each iteration of the non-linear optimisation instead
of including all of the zero entries in the step computation.
The proposed solution adds the dynamic_sparsity option which can
be used with SPARSE_NORMAL_CHOLESKY. A
DynamicCompressedRowSparseMatrix type (which extends
CompressedRowSparseMatrix) has been introduced which allows
dynamic addition and removal of elements. A Finalize method is
provided which then consolidates the matrix so that it can be
used in place of a regular CompressedRowSparseMatrix. An
associated jacobian writer has also been provided.
Changes that were required to make this extension were adding the
SetMaxNumNonZeros method to CompressedRowSparseMatrix and adding
a JacobianFinalizer template parameter to the ProgramEvaluator.
Change-Id: Ia5a8a9523fdae8d5b027bc35e70b4611ec2a8d01
Sergey Sharybin