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Diffstat (limited to 'internal/ceres/compressed_row_sparse_matrix.h')
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diff --git a/internal/ceres/compressed_row_sparse_matrix.h b/internal/ceres/compressed_row_sparse_matrix.h new file mode 100644 index 0000000..10f96c0 --- /dev/null +++ b/internal/ceres/compressed_row_sparse_matrix.h @@ -0,0 +1,149 @@ +// Ceres Solver - A fast non-linear least squares minimizer +// Copyright 2010, 2011, 2012 Google Inc. All rights reserved. +// http://code.google.com/p/ceres-solver/ +// +// 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: sameeragarwal@google.com (Sameer Agarwal) + +#ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ +#define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ + +#include <vector> +#include <glog/logging.h> +#include "ceres/sparse_matrix.h" +#include "ceres/triplet_sparse_matrix.h" +#include "ceres/internal/eigen.h" +#include "ceres/internal/macros.h" +#include "ceres/internal/port.h" +#include "ceres/types.h" + +namespace ceres { + +struct CRSMatrix; + +namespace internal { + +class SparseMatrixProto; + +class CompressedRowSparseMatrix : public SparseMatrix { + public: + // Build a matrix with the same content as the TripletSparseMatrix + // m. TripletSparseMatrix objects are easier to construct + // incrementally, so we use them to initialize SparseMatrix + // objects. + // + // We assume that m does not have any repeated entries. + explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m); +#ifndef CERES_NO_PROTOCOL_BUFFERS + explicit CompressedRowSparseMatrix(const SparseMatrixProto& proto); +#endif + + // Use this constructor only if you know what you are doing. This + // creates a "blank" matrix with the appropriate amount of memory + // allocated. However, the object itself is in an inconsistent state + // as the rows and cols matrices do not match the values of + // num_rows, num_cols and max_num_nonzeros. + // + // The use case for this constructor is that when the user knows the + // size of the matrix to begin with and wants to update the layout + // manually, instead of going via the indirect route of first + // constructing a TripletSparseMatrix, which leads to more than + // double the peak memory usage. + CompressedRowSparseMatrix(int num_rows, + int num_cols, + int max_num_nonzeros); + + // Build a square sparse diagonal matrix with num_rows rows and + // columns. The diagonal m(i,i) = diagonal(i); + CompressedRowSparseMatrix(const double* diagonal, int num_rows); + + virtual ~CompressedRowSparseMatrix(); + + // SparseMatrix interface. + virtual void SetZero(); + virtual void RightMultiply(const double* x, double* y) const; + virtual void LeftMultiply(const double* x, double* y) const; + virtual void SquaredColumnNorm(double* x) const; + virtual void ScaleColumns(const double* scale); + + virtual void ToDenseMatrix(Matrix* dense_matrix) const; +#ifndef CERES_NO_PROTOCOL_BUFFERS + virtual void ToProto(SparseMatrixProto* proto) const; +#endif + virtual void ToTextFile(FILE* file) const; + virtual int num_rows() const { return num_rows_; } + virtual int num_cols() const { return num_cols_; } + virtual int num_nonzeros() const { return rows_[num_rows_]; } + virtual const double* values() const { return values_.get(); } + virtual double* mutable_values() { return values_.get(); } + + // Delete the bottom delta_rows. + // num_rows -= delta_rows + void DeleteRows(int delta_rows); + + // Append the contents of m to the bottom of this matrix. m must + // have the same number of columns as this matrix. + void AppendRows(const CompressedRowSparseMatrix& m); + + void ToCRSMatrix(CRSMatrix* matrix) const; + + // Low level access methods that expose the structure of the matrix. + const int* cols() const { return cols_.get(); } + int* mutable_cols() { return cols_.get(); } + + const int* rows() const { return rows_.get(); } + int* mutable_rows() { return rows_.get(); } + + const vector<int>& row_blocks() const { return row_blocks_; } + vector<int>* mutable_row_blocks() { return &row_blocks_; } + + const vector<int>& col_blocks() const { return col_blocks_; } + vector<int>* mutable_col_blocks() { return &col_blocks_; } + + private: + scoped_array<int> cols_; + scoped_array<int> rows_; + scoped_array<double> values_; + + int num_rows_; + int num_cols_; + int max_num_nonzeros_; + + // If the matrix has an underlying block structure, then it can also + // carry with it row and column block sizes. This is auxilliary and + // optional information for use by algorithms operating on the + // matrix. The class itself does not make use of this information in + // any way. + vector<int> row_blocks_; + vector<int> col_blocks_; + + CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix); +}; + +} // namespace internal +} // namespace ceres + +#endif // CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ |