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
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
1. Add the ability to evaluate the problem without loss function.
2. Remove static Evaluator::Evaluate
3. Refactor the common code from problem_test.cc and
evaluator_test.cc into evaluator_test_utils.cc
Change-Id: I1aa841580afe91d288fbb65288b0ffdd1e43e827
1. Added CRSMatrix object which will store the initial
and final jacobians if requested by the user.
2. Conversion routine and test for converting a
CompressedRowSparseMatrix to CRSMatrix.
3. New Evaluator::Evaluate function to do the actual evaluation.
4. Changes to Program::StateVectorToParmeterBlocks and
Program::SetParameterBlockStatePtrstoUserStatePtrs so that
they do not try to set the state of constant parameter blocks.
5. Tests for Evaluator::Evaluate.
6. Minor cleanups in SolverImpl.
7. Minor cpplint cleanups triggered by this CL.
Change-Id: I3ac446484692f943c28f2723b719676f8c83ca3d
This extends the Evaluator interface to support evaluating the
gradient in addition to the residuals and jacobian, if requested.
bool Evaluate(const double* state,
double* cost,
double* residuals,
double* gradient, <----------- NEW
SparseMatrix* jacobian) = 0;
The ProgramEvaluator is extended to support the new gradient
evaluation. This required some gymnastics around the block
evaluate preparer, which now contains a scratch evaluate preparer
for the case that no jacobian is requested but the gradient is.
Gradient evaluation is a prerequisite for the planned suite of
first order methods, including nonlinear conjugate gradient,
CG_DESCENT, L-BFGS, trust region with line search, and more.
This also considerably refactors the evaluator_test to make it
shorter and check the results for all combinations of the optional
parameters [residuals, gradient, jacobian].
Change-Id: Ic7d0fec028dc5ffebc08ee079ad04eeaf6e02582
Keir Mierle