mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Richard Stebbing
32530788d0
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
87 lines
3.7 KiB
C++
87 lines
3.7 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#include <vector>
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#include "ceres/block_evaluate_preparer.h"
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#include "ceres/block_jacobian_writer.h"
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#include "ceres/compressed_row_jacobian_writer.h"
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#include "ceres/compressed_row_sparse_matrix.h"
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#include "ceres/crs_matrix.h"
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#include "ceres/dense_jacobian_writer.h"
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#include "ceres/dynamic_compressed_row_finalizer.h"
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#include "ceres/dynamic_compressed_row_jacobian_writer.h"
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#include "ceres/evaluator.h"
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#include "ceres/internal/port.h"
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#include "ceres/program_evaluator.h"
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#include "ceres/scratch_evaluate_preparer.h"
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#include "glog/logging.h"
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namespace ceres {
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namespace internal {
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Evaluator::~Evaluator() {}
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Evaluator* Evaluator::Create(const Evaluator::Options& options,
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Program* program,
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string* error) {
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switch (options.linear_solver_type) {
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case DENSE_QR:
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case DENSE_NORMAL_CHOLESKY:
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return new ProgramEvaluator<ScratchEvaluatePreparer,
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DenseJacobianWriter>(options,
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program);
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case DENSE_SCHUR:
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case SPARSE_SCHUR:
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case ITERATIVE_SCHUR:
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case CGNR:
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return new ProgramEvaluator<BlockEvaluatePreparer,
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BlockJacobianWriter>(options,
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program);
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case SPARSE_NORMAL_CHOLESKY:
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if (options.dynamic_sparsity) {
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return new ProgramEvaluator<ScratchEvaluatePreparer,
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DynamicCompressedRowJacobianWriter,
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DynamicCompressedRowJacobianFinalizer>(
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options, program);
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} else {
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return new ProgramEvaluator<ScratchEvaluatePreparer,
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CompressedRowJacobianWriter>(options,
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program);
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}
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default:
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*error = "Invalid Linear Solver Type. Unable to create evaluator.";
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return NULL;
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}
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}
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} // namespace internal
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} // namespace ceres
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