Update the minimum required version of Eigen to 3.3.
Change-Id: I6e6bd745311b7d4f1d5b749ec70d314f9e765438
diff --git a/docs/source/installation.rst b/docs/source/installation.rst
index b3dfb50..c6ddfff 100644
--- a/docs/source/installation.rst
+++ b/docs/source/installation.rst
@@ -32,7 +32,7 @@
:ref:`section-customizing` .
- `Eigen <http://eigen.tuxfamily.org/index.php?title=Main_Page>`_
- 3.2.2 or later **strongly** recommended, 3.1.0 or later **required**.
+ 3.3 or later **required**.
.. NOTE ::
@@ -409,8 +409,8 @@
#. Get dependencies; unpack them as subdirectories in ``ceres/``
(``ceres/eigen``, ``ceres/glog``, etc)
- #. ``Eigen`` 3.1 (needed on Windows; 3.0.x will not work). There is
- no need to build anything; just unpack the source tarball.
+ #. ``Eigen`` 3.3 . There is no need to build anything; just unpack
+ the source tarball.
#. ``google-glog`` Open up the Visual Studio solution and build it.
#. ``gflags`` Open up the Visual Studio solution and build it.
@@ -431,7 +431,7 @@
#. Unpack the Ceres tarball into ``ceres``. For the tarball, you
should get a directory inside ``ceres`` similar to
- ``ceres-solver-1.3.0``. Alternately, checkout Ceres via ``git`` to
+ ``ceres-solver-1.14.0``. Alternately, checkout Ceres via ``git`` to
get ``ceres-solver.git`` inside ``ceres``.
#. Install ``CMake``,
@@ -693,15 +693,6 @@
#. ``EIGENSPARSE [Default: ON]``: By default, Ceres will not use
Eigen's sparse Cholesky factorization.
- .. NOTE::
-
- For good performance, use Eigen version 3.2.2 or later.
-
- .. NOTE::
-
- Unlike the rest of Eigen (>= 3.1.1 MPL2, < 3.1.1 LGPL), Eigen's sparse
- Cholesky factorization is (still) licensed under the LGPL.
-
#. ``GFLAGS [Default: ON]``: Turn this ``OFF`` to build Ceres without
``gflags``. This will also prevent some of the example code from
building.
diff --git a/include/ceres/jet.h b/include/ceres/jet.h
index 00ecdca..1879ea1 100644
--- a/include/ceres/jet.h
+++ b/include/ceres/jet.h
@@ -941,7 +941,6 @@
static inline Real lowest() { return Real(-std::numeric_limits<T>::max()); }
};
-#if EIGEN_VERSION_AT_LEAST(3, 3, 0)
// Specifying the return type of binary operations between Jets and scalar types
// allows you to perform matrix/array operations with Eigen matrices and arrays
// such as addition, subtraction, multiplication, and division where one Eigen
@@ -956,7 +955,6 @@
struct ScalarBinaryOpTraits<T, ceres::Jet<T, N>, BinaryOp> {
typedef ceres::Jet<T, N> ReturnType;
};
-#endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)
} // namespace Eigen
diff --git a/internal/ceres/eigensparse.cc b/internal/ceres/eigensparse.cc
index 76dba31..22ed2c4 100644
--- a/internal/ceres/eigensparse.cc
+++ b/internal/ceres/eigensparse.cc
@@ -143,10 +143,6 @@
const OrderingType ordering_type) {
std::unique_ptr<SparseCholesky> sparse_cholesky;
- // The preprocessor gymnastics here are dealing with the fact that
- // before version 3.2.2, Eigen did not support a third template
- // parameter to specify the ordering and it always defaults to AMD.
-#if EIGEN_VERSION_AT_LEAST(3, 2, 2)
typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>,
Eigen::Upper,
Eigen::AMDOrdering<int>>
@@ -161,11 +157,6 @@
sparse_cholesky.reset(
new EigenSparseCholeskyTemplate<WithNaturalOrdering>());
}
-#else
- typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper>
- WithAMDOrdering;
- sparse_cholesky.reset(new EigenSparseCholeskyTemplate<WithAMDOrdering>());
-#endif
return sparse_cholesky;
}
@@ -174,10 +165,6 @@
std::unique_ptr<SparseCholesky> FloatEigenSparseCholesky::Create(
const OrderingType ordering_type) {
std::unique_ptr<SparseCholesky> sparse_cholesky;
- // The preprocessor gymnastics here are dealing with the fact that
- // before version 3.2.2, Eigen did not support a third template
- // parameter to specify the ordering and it always defaults to AMD.
-#if EIGEN_VERSION_AT_LEAST(3, 2, 2)
typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<float>,
Eigen::Upper,
Eigen::AMDOrdering<int>>
@@ -192,11 +179,6 @@
sparse_cholesky.reset(
new EigenSparseCholeskyTemplate<WithNaturalOrdering>());
}
-#else
- typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<float>, Eigen::Upper>
- WithAMDOrdering;
- sparse_cholesky.reset(new EigenSparseCholeskyTemplate<WithAMDOrdering>());
-#endif
return sparse_cholesky;
}
diff --git a/internal/ceres/jet_test.cc b/internal/ceres/jet_test.cc
index 3f2b7d3..dff660b 100644
--- a/internal/ceres/jet_test.cc
+++ b/internal/ceres/jet_test.cc
@@ -765,8 +765,6 @@
EXPECT_FALSE(IsNaN(a));
}
-#if EIGEN_VERSION_AT_LEAST(3, 3, 0)
-
// The following test ensures that Jets have all the appropriate Eigen
// related traits so that they can be used as part of matrix
// decompositions.
@@ -900,7 +898,6 @@
ExpectJetsClose(r3(0), r3(0));
ExpectJetsClose(r4(1), r4(1));
}
-#endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)
} // namespace internal
} // namespace ceres
diff --git a/internal/ceres/reorder_program.cc b/internal/ceres/reorder_program.cc
index 45dbbc4..aa6032a 100644
--- a/internal/ceres/reorder_program.cc
+++ b/internal/ceres/reorder_program.cc
@@ -85,7 +85,7 @@
return min_parameter_block_position;
}
-#if EIGEN_VERSION_AT_LEAST(3, 2, 2) && defined(CERES_USE_EIGEN_SPARSE)
+#if defined(CERES_USE_EIGEN_SPARSE)
Eigen::SparseMatrix<int> CreateBlockJacobian(
const TripletSparseMatrix& block_jacobian_transpose) {
typedef Eigen::SparseMatrix<int> SparseMatrix;
@@ -179,7 +179,6 @@
}
-#if EIGEN_VERSION_AT_LEAST(3, 2, 2)
void OrderingForSparseNormalCholeskyUsingEigenSparse(
const TripletSparseMatrix& tsm_block_jacobian_transpose,
int* ordering) {
@@ -212,7 +211,6 @@
}
#endif // CERES_USE_EIGEN_SPARSE
}
-#endif
} // namespace
@@ -385,10 +383,7 @@
const int size_of_first_elimination_group,
const ProblemImpl::ParameterMap& parameter_map,
Program* program) {
-#if !EIGEN_VERSION_AT_LEAST(3, 2, 2) || !defined(CERES_USE_EIGEN_SPARSE)
- return;
-#else
-
+#if defined(CERES_USE_EIGEN_SPARSE)
std::unique_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose(
program->CreateJacobianBlockSparsityTranspose());
@@ -574,18 +569,9 @@
return true;
} else if (sparse_linear_algebra_library_type == EIGEN_SPARSE) {
-#if EIGEN_VERSION_AT_LEAST(3, 2, 2)
- OrderingForSparseNormalCholeskyUsingEigenSparse(
+ OrderingForSparseNormalCholeskyUsingEigenSparse(
*tsm_block_jacobian_transpose,
&ordering[0]);
-#else
- // For Eigen versions less than 3.2.2, there is nothing to do as
- // older versions of Eigen do not expose a method for doing
- // symbolic analysis on pre-ordered matrices, so a block
- // pre-ordering is a bit pointless.
-
- return true;
-#endif
}
// Apply ordering.
