182 lines
7.3 KiB
C++
182 lines
7.3 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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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: sameeragarwal@google.com (Sameer Agarwal)
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#ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
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#define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
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#include <vector>
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#include "ceres/internal/macros.h"
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#include "ceres/internal/port.h"
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#include "ceres/sparse_matrix.h"
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#include "ceres/types.h"
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#include "glog/logging.h"
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namespace ceres {
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struct CRSMatrix;
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namespace internal {
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class TripletSparseMatrix;
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class CompressedRowSparseMatrix : public SparseMatrix {
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public:
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// Build a matrix with the same content as the TripletSparseMatrix
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// m. TripletSparseMatrix objects are easier to construct
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// incrementally, so we use them to initialize SparseMatrix
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// objects.
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//
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// We assume that m does not have any repeated entries.
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explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m);
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// Use this constructor only if you know what you are doing. This
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// creates a "blank" matrix with the appropriate amount of memory
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// allocated. However, the object itself is in an inconsistent state
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// as the rows and cols matrices do not match the values of
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// num_rows, num_cols and max_num_nonzeros.
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//
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// The use case for this constructor is that when the user knows the
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// size of the matrix to begin with and wants to update the layout
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// manually, instead of going via the indirect route of first
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// constructing a TripletSparseMatrix, which leads to more than
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// double the peak memory usage.
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CompressedRowSparseMatrix(int num_rows,
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int num_cols,
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int max_num_nonzeros);
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// Build a square sparse diagonal matrix with num_rows rows and
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// columns. The diagonal m(i,i) = diagonal(i);
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CompressedRowSparseMatrix(const double* diagonal, int num_rows);
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virtual ~CompressedRowSparseMatrix();
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// SparseMatrix interface.
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virtual void SetZero();
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virtual void RightMultiply(const double* x, double* y) const;
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virtual void LeftMultiply(const double* x, double* y) const;
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virtual void SquaredColumnNorm(double* x) const;
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virtual void ScaleColumns(const double* scale);
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virtual void ToDenseMatrix(Matrix* dense_matrix) const;
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virtual void ToTextFile(FILE* file) const;
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virtual int num_rows() const { return num_rows_; }
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virtual int num_cols() const { return num_cols_; }
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virtual int num_nonzeros() const { return rows_[num_rows_]; }
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virtual const double* values() const { return &values_[0]; }
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virtual double* mutable_values() { return &values_[0]; }
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// Delete the bottom delta_rows.
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// num_rows -= delta_rows
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void DeleteRows(int delta_rows);
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// Append the contents of m to the bottom of this matrix. m must
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// have the same number of columns as this matrix.
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void AppendRows(const CompressedRowSparseMatrix& m);
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void ToCRSMatrix(CRSMatrix* matrix) const;
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// Low level access methods that expose the structure of the matrix.
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const int* cols() const { return &cols_[0]; }
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int* mutable_cols() { return &cols_[0]; }
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const int* rows() const { return &rows_[0]; }
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int* mutable_rows() { return &rows_[0]; }
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const std::vector<int>& row_blocks() const { return row_blocks_; }
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std::vector<int>* mutable_row_blocks() { return &row_blocks_; }
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const std::vector<int>& col_blocks() const { return col_blocks_; }
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std::vector<int>* mutable_col_blocks() { return &col_blocks_; }
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// Destructive array resizing method.
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void SetMaxNumNonZeros(int num_nonzeros);
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// Non-destructive array resizing method.
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void set_num_rows(const int num_rows) { num_rows_ = num_rows; }
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void set_num_cols(const int num_cols) { num_cols_ = num_cols; }
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void SolveLowerTriangularInPlace(double* solution) const;
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void SolveLowerTriangularTransposeInPlace(double* solution) const;
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CompressedRowSparseMatrix* Transpose() const;
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static CompressedRowSparseMatrix* CreateBlockDiagonalMatrix(
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const double* diagonal,
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const std::vector<int>& blocks);
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// Compute the sparsity structure of the product m.transpose() * m
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// and create a CompressedRowSparseMatrix corresponding to it.
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//
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// Also compute a "program" vector, which for every term in the
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// outer product points to the entry in the values array of the
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// result matrix where it should be accumulated.
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//
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// This program is used by the ComputeOuterProduct function below to
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// compute the outer product.
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//
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// Since the entries of the program are the same for rows with the
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// same sparsity structure, the program only stores the result for
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// one row per row block. The ComputeOuterProduct function reuses
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// this information for each row in the row block.
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static CompressedRowSparseMatrix* CreateOuterProductMatrixAndProgram(
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const CompressedRowSparseMatrix& m,
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std::vector<int>* program);
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// Compute the values array for the expression m.transpose() * m,
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// where the matrix used to store the result and a program have been
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// created using the CreateOuterProductMatrixAndProgram function
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// above.
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static void ComputeOuterProduct(const CompressedRowSparseMatrix& m,
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const std::vector<int>& program,
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CompressedRowSparseMatrix* result);
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private:
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int num_rows_;
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int num_cols_;
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std::vector<int> rows_;
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std::vector<int> cols_;
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std::vector<double> values_;
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// If the matrix has an underlying block structure, then it can also
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// carry with it row and column block sizes. This is auxilliary and
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// optional information for use by algorithms operating on the
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// matrix. The class itself does not make use of this information in
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// any way.
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std::vector<int> row_blocks_;
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std::vector<int> col_blocks_;
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CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix);
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
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