- Use the same logic as per gflags & glog whereby we perform (up to)
two find_package() calls such that installed packages are preferred
to exported build directories across all platforms.
Change-Id: Ifb9a7ba322ee43ed18c5774633e4bb527ce7cd75
SchurComplementSolver implements a variant of ITERATIVE_SCHUR
when explicit_schur_complement is set to true. In this case
the SparseCholesky object should not be instantiated. Even
though there is no CPU cost, it can be the case that ITERATIVE_SCHUR
is being used when there are not sparse linear algebra libraries
are available, and this can result in a crash.
Change-Id: I349d5f79201782689b3ab0ccc2c5001804b44c7b
- Previously we were only adding the OpenMP flags when compiling for C++
which could cause linker issues when compiling the C examples.
Change-Id: Ie7d8192b9da6fb17b8f554e6d164ec0a65403c99
Parametric tests in gunit use tuple, which can be in the std::tr1
or the std namespaces depending on the version of STL one is using.
This change adds conditions the choice of namespace on whether
CXX11 mode is enabled or not.
It is entirely possible that we will have to come back and add
detection for this along the lines of shared_ptr.
Change-Id: I7fc85a32cf9f3f3bf30f86d9ba972ac67c6635fb
The code for creating and updating preconditioners has been pulled
out in into its own function for better readability.
Change-Id: I5335de3b158a8485cf6d052ee37d0d8fd57145e9
The addition of crsb_rows and crsb_cols to CompressedRowSparseMatrix
broke the build for problems with dynamic sparsity.
The fix is to remove unnecessarily filling of row_blocks and col_blocks,
which was triggering a check inside CompressedRowSparseMatrix around
block handling, since block structure makes no sense for matrices with
dynamic sparsity anyways.
Also added a test "dynamic_sparsity_test" based on i
examples/ellipse_approximation.cc
Thanks to Richard Stebbing for reporting this.
Change-Id: Ic1d49e97690ac17e0ea2949772271bd915277d68
SparseCholesky is an interface to sparse cholesky factorization
routines across sparse linear algebra libraries. Each sparse
linear algebra library is responsible for implementing its own
instance of this interface.
As a result the various places - SparseNormalCholeskySolver,
SparseSchurComplementSolver and VisibilityBasedPreconditioner
are significantly simplified.
Change-Id: I8b465705eae83bba9e1adfffcc741a05c70faf2e
1. Convert a CompressedRowSparseMatrix constructor which
takes a TripletSparseMatrix as input into a factory method
which allows the input to be transposed.
2. Move the random matrix creation routine for CompressedRowSparseMatrix
from being a standalone function to a static method.
3. Add a corresponding random matrix generation static method to
TripletSparseMatrix.
4. Add a new constructor to TripletSparseMatrix, which takes as input
the row, col and values arrays.
Change-Id: Iec7b184646818f432a5e6822bea3b2f3128a82aa
- Use target_compile_features() to specify the C++11 dependency for
Ceres if the CXX11 option is enabled and the current CMake version
supports it (>= 3.1). Otherwise fall back onto our existing
target_compile_options() solution if available.
- We prefer the use of target_compile_features() if available as it more
gracefully handles ‘upgrading’ of the C++ standard in client projects
that depend upon Ceres, e.g. if the client requires C++14. The
current solution may fail to produce the expected result in this case
as raised in
https://github.com/ceres-solver/ceres-solver/issues/273.
Change-Id: Ib3cff8d4b9fe93fa6d6b376b4dd53923bb1c4ecc
Now that there is a single piece of code doing the outer product
computation for all three sparse linear algebra backends, move
this code one level up the call stack and there by make the actual
per-library solver code shorter and simpler.
Also fix a minor omission in the outer product computation code
where row/column blocks were not being copied over to the
outer product matrix.
Change-Id: I22a7967bdc659385b741901afefa7af312e676e5
SchurEliminator::Init now takes a bool that tells it whether
it can assume that the diagonal blocks it is inverting can
be assumed to be full rank or not.
This information is then passed onto InvertPSDMatrix.
Change-Id: I26037b6233f2aad5584fed245f631c3959928afe
- Updates FindEigen.cmake to default to an installed Eigen CMake
Configuration if available, otherwise falls back to previous behaviour
of searching for Eigen components.
- This mimics the behaviour of FindGflags.cmake & FindGlog.cmake.
Change-Id: Ifce948d554a0135ce1a0c443267c0230e516f14b
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
SolveLowerTriangularInPlace
SolveLowerTriangularTransposeInPlace
were unused functions which can be removed.
Change-Id: I0fd29c1efae2a0a74666f6e3541473bebc22ae82
This code was currently buried under a bool inside SparseNormalCholeskySolver.
Pulling this out in its own solver makes the code simpler more readable
and more performant in the case of SuiteSparse.
Change-Id: I72379ca9ca162abbb83c12f7ee8ff92bc71e772c
By adding an enum to CompressedRowSparseMatrix, which indicates
whether the matrix is unsymmetric, upper or lower triangular
we are able to improve the readability and fix some minor
bugs in the way some matrix manipulation code was being
called.
Thank to William Rucklidge for this suggestion.
Change-Id: I355c90d11cd5d31f5a25741b0bda4fc4583e9095
Move it to compressed_row_sparse_matrix.h/cc for upcoming re-use.
Also clean up the tests for ComputeOuterProduct so that they do
not depend on CXSparse anymore and use Eigen instead. This also
makes the test simpler and shorter.
Change-Id: I06bbeb3b0c6a07fb1f3da354ef0abd17d246be9a
1. Add stype to the outerproduct computation to control the output
matrix in upper or lower triangular matrix. For SuiteSparse,
upper triangular matrix is generated. SuiteSparse can directly use
this matrix format for cholesky without matrix transpose overhead.
2. Change the outerproduct computation to block multiplication. This
reduces the computation complexity for the sort in preprocessing, also
allows formulation of the block outerproduct computation as dense Eigen
block matrix multiplication.
3. Solve 32 Tango problems on Qualcomm MSM8994 Cortex-A53 (1.55GHz)
before change: 140 seconds
after change: 131 seconds
Change-Id: I8054114cef911de6a303310a448821ca296e4744
- 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
Alex Stewart