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+// 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: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
+#define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
+
+#include <vector>
+#include "ceres/internal/port.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+
+namespace ceres {
+
+struct CRSMatrix;
+
+namespace internal {
+
+class TripletSparseMatrix;
+
+class CompressedRowSparseMatrix : public SparseMatrix {
+ public:
+ enum StorageType {
+ UNSYMMETRIC,
+ // Matrix is assumed to be symmetric but only the lower triangular
+ // part of the matrix is stored.
+ LOWER_TRIANGULAR,
+ // Matrix is assumed to be symmetric but only the upper triangular
+ // part of the matrix is stored.
+ UPPER_TRIANGULAR
+ };
+
+ // Create a matrix with the same content as the TripletSparseMatrix
+ // input. We assume that input does not have any repeated
+ // entries.
+ //
+ // The storage type of the matrix is set to UNSYMMETRIC.
+ //
+ // Caller owns the result.
+ static CompressedRowSparseMatrix* FromTripletSparseMatrix(
+ const TripletSparseMatrix& input);
+
+ // Create a matrix with the same content as the TripletSparseMatrix
+ // input transposed. We assume that input does not have any repeated
+ // entries.
+ //
+ // The storage type of the matrix is set to UNSYMMETRIC.
+ //
+ // Caller owns the result.
+ static CompressedRowSparseMatrix* FromTripletSparseMatrixTransposed(
+ const TripletSparseMatrix& input);
+
+ // 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.
+ //
+ // The storage type is set to UNSYMMETRIC.
+ 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);
+ //
+ // The storage type is set to UNSYMMETRIC
+ CompressedRowSparseMatrix(const double* diagonal, int num_rows);
+
+ // SparseMatrix interface.
+ virtual ~CompressedRowSparseMatrix();
+ 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;
+ 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_[0]; }
+ virtual double* mutable_values() { return &values_[0]; }
+
+ // 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;
+
+ CompressedRowSparseMatrix* Transpose() const;
+
+ // Destructive array resizing method.
+ void SetMaxNumNonZeros(int num_nonzeros);
+
+ // Non-destructive array resizing method.
+ void set_num_rows(const int num_rows) { num_rows_ = num_rows; }
+ void set_num_cols(const int num_cols) { num_cols_ = num_cols; }
+
+ // Low level access methods that expose the structure of the matrix.
+ const int* cols() const { return &cols_[0]; }
+ int* mutable_cols() { return &cols_[0]; }
+
+ const int* rows() const { return &rows_[0]; }
+ int* mutable_rows() { return &rows_[0]; }
+
+ const StorageType storage_type() const { return storage_type_; }
+ void set_storage_type(const StorageType storage_type) {
+ storage_type_ = storage_type;
+ }
+
+ const std::vector<int>& row_blocks() const { return row_blocks_; }
+ std::vector<int>* mutable_row_blocks() { return &row_blocks_; }
+
+ const std::vector<int>& col_blocks() const { return col_blocks_; }
+ std::vector<int>* mutable_col_blocks() { return &col_blocks_; }
+
+ // Create a block diagonal CompressedRowSparseMatrix with the given
+ // block structure. The individual blocks are assumed to be laid out
+ // contiguously in the diagonal array, one block at a time.
+ //
+ // Caller owns the result.
+ static CompressedRowSparseMatrix* CreateBlockDiagonalMatrix(
+ const double* diagonal, const std::vector<int>& blocks);
+
+ // Options struct to control the generation of random block sparse
+ // matrices in compressed row sparse format.
+ //
+ // The random matrix generation proceeds as follows.
+ //
+ // First the row and column block structure is determined by
+ // generating random row and column block sizes that lie within the
+ // given bounds.
+ //
+ // Then we walk the block structure of the resulting matrix, and with
+ // probability block_density detemine whether they are structurally
+ // zero or not. If the answer is no, then we generate entries for the
+ // block which are distributed normally.
+ struct RandomMatrixOptions {
+ // Type of matrix to create.
+ //
+ // If storage_type is UPPER_TRIANGULAR (LOWER_TRIANGULAR), then
+ // create a square symmetric matrix with just the upper triangular
+ // (lower triangular) part. In this case, num_col_blocks,
+ // min_col_block_size and max_col_block_size will be ignored and
+ // assumed to be equal to the corresponding row settings.
+ StorageType storage_type = UNSYMMETRIC;
+
+ int num_row_blocks = 0;
+ int min_row_block_size = 0;
+ int max_row_block_size = 0;
+ int num_col_blocks = 0;
+ int min_col_block_size = 0;
+ int max_col_block_size = 0;
+
+ // 0 < block_density <= 1 is the probability of a block being
+ // present in the matrix. A given random matrix will not have
+ // precisely this density.
+ double block_density = 0.0;
+ };
+
+ // Create a random CompressedRowSparseMatrix whose entries are
+ // normally distributed and whose structure is determined by
+ // RandomMatrixOptions.
+ //
+ // Caller owns the result.
+ static CompressedRowSparseMatrix* CreateRandomMatrix(
+ RandomMatrixOptions options);
+
+ private:
+ static CompressedRowSparseMatrix* FromTripletSparseMatrix(
+ const TripletSparseMatrix& input, bool transpose);
+
+ int num_rows_;
+ int num_cols_;
+ std::vector<int> rows_;
+ std::vector<int> cols_;
+ std::vector<double> values_;
+ StorageType storage_type_;
+
+ // 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.
+ std::vector<int> row_blocks_;
+ std::vector<int> col_blocks_;
+};
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_