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https://github.com/ceres-solver/ceres-solver.git
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Lint cleanup from William Rucklidge
Change-Id: Id8b99a2f557efe3744e95a3947f26cdc0c9c269e
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@@ -372,7 +372,7 @@ class Solver {
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// In some rare cases, it is worth using a more complicated
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// reordering algorithm which has slightly better runtime
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// performance at the expense of an extra copy of the Jacobian
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// // matrix. Setting use_postordering to true enables this tradeoff.
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// matrix. Setting use_postordering to true enables this tradeoff.
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bool use_postordering;
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// Some non-linear least squares problems have additional
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@@ -1357,8 +1357,8 @@ void SolverImpl::AlternateLinearSolverForSchurTypeLinearSolver(
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// CGNR currently only supports the JACOBI preconditioner.
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options->preconditioner_type = JACOBI;
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} else {
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msg += StringPrintf("ITERATIVE_SCHUR with IDENTITY preconditioner "
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"to CGNR with IDENTITY preconditioner.");
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msg += "ITERATIVE_SCHUR with IDENTITY preconditioner"
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"to CGNR with IDENTITY preconditioner.";
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}
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}
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LOG(WARNING) << msg;
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@@ -1371,8 +1371,8 @@ bool SolverImpl::ReorderProgramForSchurTypeLinearSolver(
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string* error) {
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// At this point one of two things is true.
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//
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// 1. The user did not specify an ordering - ordering has one
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// group containined all the parameter blocks.
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// 1. The user did not specify an ordering - ordering has one group
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// containing all the parameter blocks.
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// 2. The user specified an ordering, and the first group has
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// non-zero elements.
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@@ -1425,7 +1425,7 @@ bool SolverImpl::ReorderProgramForSchurTypeLinearSolver(
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TripletSparseMatrix* SolverImpl::CreateJacobianBlockSparsityTranspose(
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const Program* program) {
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// Matrix to store the block sparsity structure of
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// Matrix to store the block sparsity structure of the Jacobian.
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TripletSparseMatrix* tsm =
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new TripletSparseMatrix(program->NumParameterBlocks(),
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program->NumResidualBlocks(),
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@@ -167,7 +167,7 @@ class SolverImpl {
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// by the Schur eliminator occur before others and the residuals be
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// sorted in lexicographic order of their parameter blocks.
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//
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// If ordering has atleast two groups, then apply the ordering,
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// If ordering has at least two groups, then apply the ordering,
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// otherwise compute a new ordering using a Maximal Independent Set
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// algorithm and apply it.
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//
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@@ -172,7 +172,8 @@ cholmod_factor* SuiteSparse::AnalyzeCholeskyWithUserOrdering(
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return factor;
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}
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cholmod_factor* SuiteSparse::AnalyzeCholeskyWithNaturalOrdering(cholmod_sparse* A) {
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cholmod_factor* SuiteSparse::AnalyzeCholeskyWithNaturalOrdering(
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cholmod_sparse* A) {
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cc_.nmethods = 1;
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cc_.method[0].ordering = CHOLMOD_NATURAL;
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cc_.postorder = 0;
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