MatrixBlockSparseCols.h

Go to the documentation of this file.

/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */
 
#ifndef _mrpt_math_MatrixBlockSparseCols_H
#define _mrpt_math_MatrixBlockSparseCols_H
 
#include <mrpt/containers/map_as_vector.h>
#include <mrpt/math/CMatrixTemplateNumeric.h>  // For mrpt::math::CMatrixDouble
 
namespace mrpt
{
namespace math
{
/** A templated column-indexed efficient storage of block-sparse Jacobian or
 * Hessian matrices, together with other arbitrary information.
  *  Columns are stored in a non-associative container, but the contents of each
 * column are kept within an std::map<> indexed by row.
  *  All submatrix blocks have the same size, which allows dense storage of them
 * in fixed-size matrices, avoiding costly memory allocations.
  *
  * \tparam NROWS Rows in each elementary matrix.
  * \tparam NCOLS Cols in each elementary matrix.
  * \tparam INFO  Type of the extra data fields within each block
  * \tparam HAS_REMAP Is true, an inverse mapping between column indices and
 * "user IDs" is kept.
  * \tparam INDEX_REMAP_MAP_IMPL Ignore if HAS_REMAP=false. Defaults to
 * "mrpt::utils::map_as_vector<size_t,size_t>" for amortized O(1). Can be set to
 * "std::map<size_t,size_t>" in very sparse systems to save memory at the cost
 * of a O(log N) access time when using the remap indices.
  *
  * \ingroup mrpt_math_grp
  */
template <typename Scalar, int NROWS, int NCOLS, typename INFO, bool HAS_REMAP,
                  typename INDEX_REMAP_MAP_IMPL =
                          mrpt::utils::map_as_vector<size_t, size_t>>
struct MatrixBlockSparseCols
{
        using matrix_t = Eigen::Matrix<Scalar, NROWS, NCOLS>;
        using symbolic_t = INFO;
 
        struct TEntry
        {
                /** Numeric matrix */
                matrix_t num;
                /** Extra symbolic info */
                symbolic_t sym;
        };
 
        /** Each compressed sparse column */
        using col_t = mrpt::aligned_std_map<size_t, TEntry>;
 
   private:
        /** -> cols[i]: i'th column.
          * -> Each column is a map [row] -> TEntry
          */
        std::deque<col_t> cols;
        /** "remapped index" is the index of some global variable, interpreted by
         * the external user of this class. */
        // map<size_t,size_t> col_inverse_remapped_indices;
        mrpt::utils::map_as_vector<size_t, size_t> col_inverse_remapped_indices;
        std::vector<size_t> col_remapped_indices;
 
   public:
        inline MatrixBlockSparseCols() : cols(0) {}
        inline col_t& getCol(const size_t idx) { return cols[idx]; }
        inline const col_t& getCol(const size_t idx) const { return cols[idx]; }
        inline const mrpt::utils::map_as_vector<size_t, size_t>&
                getColInverseRemappedIndices() const
        {
                if (!HAS_REMAP) assert(false);
                return col_inverse_remapped_indices;
        }
        inline const std::vector<size_t>& getColRemappedIndices() const
        {
                if (!HAS_REMAP) assert(false);
                return col_remapped_indices;
        }
 
        /** Append one column, returning a ref to the new col_t data */
        inline col_t& appendCol(const size_t remapIndex)
        {
                const size_t idx = cols.size();
                cols.push_back(col_t());
 
                if (HAS_REMAP)
                {
                        col_remapped_indices.resize(idx + 1);
                        col_remapped_indices[idx] = remapIndex;
 
                        col_inverse_remapped_indices[remapIndex] = idx;
                }
 
                return *cols.rbegin();
        }
 
        /** Change the number of columns (keep old contents) */
        inline void setColCount(const size_t nCols) { cols.resize(nCols); }
        /** Get current number of cols. \sa findCurrentNumberOfRows */
        inline size_t cols() const { return cols.size(); }
        /** Clear all the entries in each column (do not change the number of
         * columns, though!) \sa getColCount */
        inline void clearColEntries()
        {
                for (size_t i = 0; i < cols.size(); i++) cols[i].clear();
        }
 
        /** Clear all the entries in each column (do not change the number of
         * columns, though!) \sa getColCount */
        inline void clearAll()
        {
                cols.clear();
                if (HAS_REMAP)
                {
                        col_remapped_indices.clear();
                        col_inverse_remapped_indices.clear();
                }
        }
 
        /** Builds a dense representation of the matrix and saves to a text file. */
        void saveToTextFileAsDense(
                const std::string& filename, const bool force_symmetry = false,
                const bool is_col_compressed = true) const
        {
                mrpt::math::CMatrixDouble D;
                getAsDense(D, force_symmetry, is_col_compressed);
                return D.saveToTextFile(filename);
        }
 
        /** Builds a dense representation of the matrix and saves to a text file.
          * \param is_col_compressed true: interpret this object as compressed by
         * cols; false: compressed by rows
          */
        void getAsDense(
                mrpt::math::CMatrixDouble& D, const bool force_symmetry = false,
                const bool is_col_compressed = true) const
        {
                const size_t nCols = cols.size();
                const size_t nRows = findCurrentNumberOfRows();
 
                if (is_col_compressed)
                        D.setSize(nRows * NROWS, nCols * NCOLS);
                else
                        D.setSize(nCols * NROWS, nRows * NCOLS);
 
                for (size_t j = 0; j < nCols; j++)
                {
                        for (typename col_t::const_iterator itRow = cols[j].begin();
                                 itRow != cols[j].end(); ++itRow)
                        {
                                const size_t row = itRow->first;
                                const size_t row_idx =
                                        is_col_compressed ? row * NROWS : j * NROWS;
                                const size_t col_idx =
                                        is_col_compressed ? j * NCOLS : row * NCOLS;
                                D.block(row_idx, col_idx, NROWS, NCOLS) = itRow->second.num;
                                if (force_symmetry && row_idx != col_idx)
                                        D.block(col_idx, row_idx, NCOLS, NROWS) =
                                                itRow->second.num.transpose();
                        }
                }
        }
 
        /** Goes over all the columns and keep the largest column length. \sa
         * cols() */
        size_t findCurrentNumberOfRows() const
        {
                size_t nRows = 0;
                const size_t nCols = cols.size();
                for (size_t j = 0; j < nCols; j++)
                        for (typename col_t::const_iterator itRow = cols[j].begin();
                                 itRow != cols[j].end(); ++itRow)
                                mrpt::keep_max(nRows, itRow->first);
                return nRows +
                           1;  // nRows was the max. row index, now it's the row count.
        }
 
        /** Builds a binary matrix with 1s where an elementary matrix is stored, 0s
         * elsewhere. */
        template <class MATRIX>
        void getBinaryBlocksRepresentation(MATRIX& out) const
        {
                const size_t nCols = cols.size();
                const size_t nRows = findCurrentNumberOfRows();
                out.zeros(nRows, nCols);
                for (size_t j = 0; j < nCols; j++)
                        for (typename col_t::const_iterator itRow = cols[j].begin();
                                 itRow != cols[j].end(); ++itRow)
                        {
                                const size_t row = itRow->first;
                                out(row, j) = 1;
                        }
        }
 
        /** Clear the current contents of this objects and replicates the sparse
         * structure and numerical values of \a o */
        void copyNumericalValuesFrom(
                const MatrixBlockSparseCols<Scalar, NROWS, NCOLS, INFO, HAS_REMAP>& o)
        {
                const size_t nC = o.cols.size();
                if (cols.size() != nC)
                {
                        // Just create an empty structure with the numerical matrices:
                        cols.resize(nC);
                        for (size_t i = 0; i < nC; i++)
                        {
                                cols[i].clear();
                                for (typename col_t::const_iterator it = o.cols[i].begin();
                                         it != o.cols[i].end(); ++it)
                                        cols[i][it->first].num = it->second.num;
                        }
                }
                else
                {
                        // It might be that we're overwriting an existing data structure:
                        for (size_t i = 0; i < nC; i++)
                        {
                                // ASSERTMSG_(cols[i].size()>=o.cols[i].size(),
                                // "copyNumericalValuesFrom() invoked on dissimilar structures")
                                typename col_t::iterator it_dst = cols[i].begin();
                                typename col_t::const_iterator it_src = o.cols[i].begin();
                                while (it_src != o.cols[i].end())
                                {
                                        if (it_dst->first < it_src->first)
                                        {
                                                it_dst->second.num.setZero();
                                                it_dst++;
                                        }
                                        else if (it_dst->first > it_src->first)
                                        {
                                                cols[i][it_src->first].num = it_src->second.num;
                                                it_src++;
                                        }
                                        else
                                        {
                                                it_dst->second.num = it_src->second.num;
                                                ++it_dst;
                                                ++it_src;
                                        }
                                }
                        }
                }
        }  // end copyNumericalValuesFrom()
 
};  // end of MatrixBlockSparseCols
 
}  // end NS
}  // end NS
 
#endif  //_mrpt_math_MatrixBlockSparseCols_H