| // Ceres Solver - A fast non-linear least squares minimizer | 
 | // Copyright 2015 Google Inc. All rights reserved. | 
 | // http://ceres-solver.org/ | 
 | // | 
 | // Redistribution and use in source and binary forms, with or without | 
 | // modification, are permitted provided that the following conditions are met: | 
 | // | 
 | // * Redistributions of source code must retain the above copyright notice, | 
 | //   this list of conditions and the following disclaimer. | 
 | // * Redistributions in binary form must reproduce the above copyright notice, | 
 | //   this list of conditions and the following disclaimer in the documentation | 
 | //   and/or other materials provided with the distribution. | 
 | // * Neither the name of Google Inc. nor the names of its contributors may be | 
 | //   used to endorse or promote products derived from this software without | 
 | //   specific prior written permission. | 
 | // | 
 | // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | 
 | // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | 
 | // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | 
 | // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE | 
 | // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR | 
 | // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | 
 | // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | 
 | // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | 
 | // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | 
 | // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | 
 | // POSSIBILITY OF SUCH DAMAGE. | 
 | // | 
 | // Author: strandmark@google.com (Petter Strandmark) | 
 |  | 
 | #ifndef CERES_INTERNAL_CXSPARSE_H_ | 
 | #define CERES_INTERNAL_CXSPARSE_H_ | 
 |  | 
 | // This include must come before any #ifndef check on Ceres compile options. | 
 | #include "ceres/internal/config.h" | 
 |  | 
 | #ifndef CERES_NO_CXSPARSE | 
 |  | 
 | #include <memory> | 
 | #include <string> | 
 | #include <vector> | 
 |  | 
 | #include "ceres/internal/disable_warnings.h" | 
 | #include "ceres/linear_solver.h" | 
 | #include "ceres/sparse_cholesky.h" | 
 | #include "cs.h" | 
 |  | 
 | namespace ceres { | 
 | namespace internal { | 
 |  | 
 | class CompressedRowSparseMatrix; | 
 | class TripletSparseMatrix; | 
 |  | 
 | // This object provides access to solving linear systems using Cholesky | 
 | // factorization with a known symbolic factorization. This features does not | 
 | // explicitly exist in CXSparse. The methods in the class are nonstatic because | 
 | // the class manages internal scratch space. | 
 | class CERES_NO_EXPORT CXSparse { | 
 |  public: | 
 |   CXSparse(); | 
 |   ~CXSparse(); | 
 |  | 
 |   // Solve the system lhs * solution = rhs in place by using an | 
 |   // approximate minimum degree fill reducing ordering. | 
 |   bool SolveCholesky(cs_di* lhs, double* rhs_and_solution); | 
 |  | 
 |   // Solves a linear system given its symbolic and numeric factorization. | 
 |   void Solve(cs_dis* symbolic_factor, | 
 |              csn* numeric_factor, | 
 |              double* rhs_and_solution); | 
 |  | 
 |   // Compute the numeric Cholesky factorization of A, given its | 
 |   // symbolic factorization. | 
 |   // | 
 |   // Caller owns the result. | 
 |   csn* Cholesky(cs_di* A, cs_dis* symbolic_factor); | 
 |  | 
 |   // Creates a sparse matrix from a compressed-column form. No memory is | 
 |   // allocated or copied; the structure A is filled out with info from the | 
 |   // argument. | 
 |   cs_di CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A); | 
 |  | 
 |   // Creates a new matrix from a triplet form. Deallocate the returned matrix | 
 |   // with Free. May return nullptr if the compression or allocation fails. | 
 |   cs_di* CreateSparseMatrix(TripletSparseMatrix* A); | 
 |  | 
 |   // B = A' | 
 |   // | 
 |   // The returned matrix should be deallocated with Free when not used | 
 |   // anymore. | 
 |   cs_di* TransposeMatrix(cs_di* A); | 
 |  | 
 |   // C = A * B | 
 |   // | 
 |   // The returned matrix should be deallocated with Free when not used | 
 |   // anymore. | 
 |   cs_di* MatrixMatrixMultiply(cs_di* A, cs_di* B); | 
 |  | 
 |   // Computes a symbolic factorization of A that can be used in SolveCholesky. | 
 |   // | 
 |   // The returned matrix should be deallocated with Free when not used anymore. | 
 |   cs_dis* AnalyzeCholesky(cs_di* A); | 
 |  | 
 |   // Computes a symbolic factorization of A that can be used in | 
 |   // SolveCholesky, but does not compute a fill-reducing ordering. | 
 |   // | 
 |   // The returned matrix should be deallocated with Free when not used anymore. | 
 |   cs_dis* AnalyzeCholeskyWithNaturalOrdering(cs_di* A); | 
 |  | 
 |   // Computes a symbolic factorization of A that can be used in | 
 |   // SolveCholesky. The difference from AnalyzeCholesky is that this | 
 |   // function first detects the block sparsity of the matrix using | 
 |   // information about the row and column blocks and uses this block | 
 |   // sparse matrix to find a fill-reducing ordering. This ordering is | 
 |   // then used to find a symbolic factorization. This can result in a | 
 |   // significant performance improvement AnalyzeCholesky on block | 
 |   // sparse matrices. | 
 |   // | 
 |   // The returned matrix should be deallocated with Free when not used | 
 |   // anymore. | 
 |   cs_dis* BlockAnalyzeCholesky(cs_di* A, | 
 |                                const std::vector<int>& row_blocks, | 
 |                                const std::vector<int>& col_blocks); | 
 |  | 
 |   // Compute an fill-reducing approximate minimum degree ordering of | 
 |   // the matrix A. ordering should be non-nullptr and should point to | 
 |   // enough memory to hold the ordering for the rows of A. | 
 |   void ApproximateMinimumDegreeOrdering(cs_di* A, int* ordering); | 
 |  | 
 |   void Free(cs_di* sparse_matrix); | 
 |   void Free(cs_dis* symbolic_factorization); | 
 |   void Free(csn* numeric_factorization); | 
 |  | 
 |  private: | 
 |   // Cached scratch space | 
 |   CS_ENTRY* scratch_; | 
 |   int scratch_size_; | 
 | }; | 
 |  | 
 | // An implementation of SparseCholesky interface using the CXSparse | 
 | // library. | 
 | class CERES_NO_EXPORT CXSparseCholesky final : public SparseCholesky { | 
 |  public: | 
 |   // Factory | 
 |   static std::unique_ptr<SparseCholesky> Create(OrderingType ordering_type); | 
 |  | 
 |   // SparseCholesky interface. | 
 |   ~CXSparseCholesky() override; | 
 |   CompressedRowSparseMatrix::StorageType StorageType() const final; | 
 |   LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs, | 
 |                                         std::string* message) final; | 
 |   LinearSolverTerminationType Solve(const double* rhs, | 
 |                                     double* solution, | 
 |                                     std::string* message) final; | 
 |  | 
 |  private: | 
 |   explicit CXSparseCholesky(const OrderingType ordering_type); | 
 |   void FreeSymbolicFactorization(); | 
 |   void FreeNumericFactorization(); | 
 |  | 
 |   const OrderingType ordering_type_; | 
 |   CXSparse cs_; | 
 |   cs_dis* symbolic_factor_; | 
 |   csn* numeric_factor_; | 
 | }; | 
 |  | 
 | }  // namespace internal | 
 | }  // namespace ceres | 
 |  | 
 | #include "ceres/internal/reenable_warnings.h" | 
 |  | 
 | #else | 
 |  | 
 | typedef void cs_dis; | 
 |  | 
 | class CXSparse { | 
 |  public: | 
 |   void Free(void* arg) {} | 
 | }; | 
 | #endif  // CERES_NO_CXSPARSE | 
 |  | 
 | #endif  // CERES_INTERNAL_CXSPARSE_H_ |