forked from lijiext/lammps
1067 lines
37 KiB
C++
1067 lines
37 KiB
C++
#ifndef SPARSEMATRIX_INL_H
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#define SPARSEMATRIX_INL_H
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#include "mpi.h"
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#include "DenseVector.h"
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namespace ATC_matrix {
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template <typename T>
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TRI_COORD<T>::TRI_COORD(INDEX row, INDEX col) : i(row), j(col) {}
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template <typename T>
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TRI_COORD<T>::TRI_COORD(INDEX row, INDEX col, T val, bool add_to)
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: i(row), j(col), v(val), add(add_to) {}
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//-----------------------------------------------------------------------------
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// default constructor - creates an empty sparsematrix with specified size
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T>::SparseMatrix(INDEX rows, INDEX cols)
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: _val(NULL), _ia(NULL), _ja(NULL), _size(0), _nRowsCRS(0), hasTemplate_(false),
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_nRows(rows),_nCols(cols) {}
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//-----------------------------------------------------------------------------
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// copy constructor
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T>::SparseMatrix(const SparseMatrix<T>& C)
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: _val(NULL), _ia(NULL), _ja(NULL), hasTemplate_(false)
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{
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_copy(C);
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}
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//-----------------------------------------------------------------------------
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// copy constructor - converts from DenseMatrix
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T>::SparseMatrix(const DenseMatrix<T>& C)
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: _val(NULL), _ia(NULL), _ja(NULL), hasTemplate_(false)
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{
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reset(C);
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}
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//-----------------------------------------------------------------------------
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// constructor - creates a sparse matrix given an array of row indeces,
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// an array of col indeces, and an array of nonzero values.
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T>::SparseMatrix(INDEX* rows, INDEX* cols, T* vals,
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INDEX size, INDEX nRows, INDEX nCols, INDEX nRowsCRS)
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: hasTemplate_(true)
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{
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_val = vals;
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_ia = rows;
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_ja = cols;
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_size = size;
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_nRows = nRows;
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_nCols = nCols;
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_nRowsCRS = nRowsCRS;
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}
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//-----------------------------------------------------------------------------
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// assigns internal storage for CRS
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::_create(INDEX size, INDEX nrows)
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{
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_size = size;
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_nRowsCRS = nrows;
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// assign memory to hold matrix
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try
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{
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_val = (_size*nrows) ? new T [_size] : NULL;
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_ia = (_size*nrows) ? new INDEX [_nRowsCRS+1] : NULL;
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_ja = (_size*nrows) ? new INDEX [_size] : NULL;
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}
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catch (std::exception &e)
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{
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cout << "Could not allocate SparseMatrix of "<< _size << " nonzeros.\n";
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ERROR_FOR_BACKTRACE
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exit(EXIT_FAILURE);
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}
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if (!_ia) return;
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// automatically handle the ends of rowpointer
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*_ia = 0; // first non-zero is the zero index
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_ia[_nRowsCRS] = _size; // last row pointer is the size
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}
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//-----------------------------------------------------------------------------
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// cleans up internal storage, but retains nRows & nCols
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::_delete()
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{
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vector<TRI_COORD<T> >().swap(_tri); // completely deletes _tri
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if (_val) delete [] _val;
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if (_ia) delete [] _ia;
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if (_ja) delete [] _ja;
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_size = _nRowsCRS = 0;
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_val = NULL;
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_ia = _ja = NULL;
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}
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//-----------------------------------------------------------------------------
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// full memory copy of C into this
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::_copy(const SparseMatrix<T> &C)
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{
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compress(C);
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_delete();
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_create(C.size(), C._nRowsCRS);
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if (_size) {
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std::copy(C._val, C._val+_size, _val);
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std::copy(C._ja, C._ja+_size, _ja);
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}
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if (_nRowsCRS) {
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std::copy(C._ia, C._ia+_nRowsCRS+1, _ia);
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}
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_nCols = C._nCols;
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_nRows = C._nRows;
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if (_nCols > 0 && _nRows > 0) hasTemplate_ = true; // needs if since map seems to call the copy instead of the default constructor
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}
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// this version is accessible to derived classes
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template<typename T>
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void SparseMatrix<T>::copy(const SparseMatrix<T> &C)
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{
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_copy(C);
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}
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//----------------------------------------------------------------------------
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// general sparse matrix assignment
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//----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::_set_equal(const Matrix<T> &r)
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{
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this->resize(r.nRows(), r.nCols());
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const Matrix<T> *ptr_r = &r;
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const SparseMatrix<T> *s_ptr = dynamic_cast<const SparseMatrix<T>*>(ptr_r);
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if (s_ptr) this->reset(*s_ptr);
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else if (dynamic_cast<const DiagonalMatrix<T>*>(ptr_r))
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for (INDEX i=0; i<r.size(); i++) set(i,i,r[i]);
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else if (dynamic_cast<const DenseMatrix<T>*>(ptr_r)) this->reset(r);
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else
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{
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cout <<"Error in general sparse matrix assignment\n";
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exit(1);
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}
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}
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// General flat index by value operator (by nth nonzero)
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template <typename T> inline T SparseMatrix<T>::operator[](INDEX i) const
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{
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VICK(i); return _val[i];
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}
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// General flat index by reference operator (by nth nonzero)
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template <typename T> inline T& SparseMatrix<T>::operator[](INDEX i)
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{
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VICK(i); return _val[i];
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}
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template<typename T>
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T SparseMatrix<T>::_zero = T(0);
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//-----------------------------------------------------------------------------
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// triplet comparison operator returns true if x < y
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//-----------------------------------------------------------------------------
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template <typename T>
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bool triplet_comparision(const TRI_COORD<T> &x, const TRI_COORD<T> &y)
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{
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const bool row_less = (x.i) < (y.i);
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const bool row_equal = (x.i) == (y.i);
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const bool col_less = (x.j) < (y.j);
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return (row_less || (row_equal && col_less));
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}
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//-----------------------------------------------------------------------------
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// triplet comparison operator returns true if x == y
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//-----------------------------------------------------------------------------
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template <typename T>
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bool triplets_equal(const TRI_COORD<T> &x, const TRI_COORD<T> &y)
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{
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return x.i==y.i && x.j==y.j;
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}
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//-----------------------------------------------------------------------------
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// multiply sparse matrix by a vector
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//-----------------------------------------------------------------------------
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template<typename T>
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DenseVector<T> operator*(const SparseMatrix<T> &A, const Vector<T>& x)
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{
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DenseVector<T> y(A.nRows(), true);
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A.MultMv(x, y);
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return y;
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}
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//-----------------------------------------------------------------------------
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// multiply a vector by a sparse matrix
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//-----------------------------------------------------------------------------
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template<typename T>
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DenseVector<T> operator*(const Vector<T>& x, const SparseMatrix<T> &A)
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{
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return A.transMat(x);
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}
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//-----------------------------------------------------------------------------
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// multiply sparse matrix by dense matrix
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//-----------------------------------------------------------------------------
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template<typename T>
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DenseMatrix<T> operator*(const SparseMatrix<T> &A, const Matrix<T>& D)
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{
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DenseMatrix<T> C(A.nRows(), D.nCols(), true); // initialized to zero
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A.MultAB(D, C);
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return C;
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}
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//-----------------------------------------------------------------------------
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// multiply sparse matrix by a diagonal matrix - scales each column
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T> operator*(const SparseMatrix<T> &A, const DiagonalMatrix<T>& D)
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{
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GCK(A, D, A.nCols()!=D.nRows(),"SparseMatrix * DiagonalMatrix")
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SparseMatrix<T> C(A); // C has same sparcity as A
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// C(i,j) = A(i,k) * D(k, j) * j==k
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INDEX i, ij;
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for (i=0; i<A._nRowsCRS; i++)
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for (ij=A._ia[i]; ij<A._ia[i+1]; ij++)
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C[ij] = A._val[ij]*D(A._ja[ij],A._ja[ij]);
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return C;
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}
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//-----------------------------------------------------------------------------
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// multiplies two sparse matrices - assumes their output is sparse
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//-----------------------------------------------------------------------------
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template<typename T>
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SparseMatrix<T> operator*(const SparseMatrix<T> &A, const SparseMatrix<T> &B)
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{
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SparseMatrix<T> At(A.transpose());
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SparseMatrix<T>::compress(B);
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GCK(A, B, A.nCols()!=B.nRows(), "SparseMatrix * SparseMatrix");
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SparseMatrix<T> C(A.nRows(), B.nCols());
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if (At.empty() || B.empty()) return C;
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INDEX k, ki, kj;
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INDEX K = std::min(At._nRowsCRS, B._nRowsCRS);
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for (k=0; k<K; k++) // loop over rows of A or B (smallest)
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for (ki=At._ia[k]; ki<At._ia[k+1]; ki++) // loop over row nonzeros of A
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for (kj=B._ia[k]; kj<B._ia[k+1]; kj++) // loop over row nonzeros of B
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C.add(At._ja[ki], B._ja[kj], At[ki]*B[kj]); // C(i,j) = At(k,i)*B(k, j)
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C.compress();
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return C;
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}
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//-----------------------------------------------------------------------------
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// returns the first row number with a nonzero entry or -1 if no rows
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//-----------------------------------------------------------------------------
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template<typename T>
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int SparseMatrix<T>::_first_nonzero_row_crs() const
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{
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if (!_nRowsCRS) return -1;
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INDEX r;
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for (r=0; r<_nRowsCRS; r++)
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if (_ia[r+1]>0) return r;
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return -1;
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}
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//-----------------------------------------------------------------------------
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// converts T to CRS
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::compress(const SparseMatrix<T> &C)
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{
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const_cast<SparseMatrix<T>*>(&C)->compress();
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}
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//-----------------------------------------------------------------------------
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// merges all the _tri triples with CRS storage
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::compress()
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{
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if (_tri.empty()) return;
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// Sort and find the number of unique triplets.
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// Triplet values will all be not present in existing CRS structure.
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const INDEX nUnique = CountUniqueTriplets();
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// Max number of rows in new CRS structure.
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const INDEX nRows = std::max((INDEX)_tri.back().i+1, _nRowsCRS);
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// make a new CRS structure
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INDEX *ia = new INDEX [nRows+1];
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INDEX *ja = new INDEX [nUnique];
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T *val = new T [nUnique];
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// Set first and last row ptr to 0 and nnz respectively.
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// Set all else to a flagvalue MAX_UNSIGNED (~0).
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ia[0] = 0;
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INDEX i;
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for (i=1; i<nRows; i++) ia[i]=~0; // ~0 is max(INDEX)
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ia[nRows] = nUnique;
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INDEX crs_pt, crs_row;
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unsigned tri_ct; // must be unsigned to interface with std::vector without warnings
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// Get the first CRS and triplet coordinates (if they exist).
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TRI_COORD<T> nextCRS, nextTRI(_tri[0]), next;
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int first_row = _first_nonzero_row_crs();
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if (first_row != -1) nextCRS = TRI_COORD<T>(first_row, _ja[0], _val[0]);
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// merge sorted triplets into a new CRS structure
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crs_pt = crs_row = tri_ct = 0; // initialize counters
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for (i=0; i<nUnique; i++)
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{
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// is the next non-zero in the new triplet vector
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if (tri_ct < _tri.size()
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&& (triplet_comparision(nextTRI, nextCRS) || crs_pt>=_size)) {
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next = nextTRI;
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// advance the triplet counter, and skip voided TRIPLET entries
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do tri_ct++;
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while ( tri_ct<_tri.size() && _tri[tri_ct].j == ~0 );
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// if not at the end of the vector, set the next triplet
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if (tri_ct<_tri.size()) nextTRI = _tri[tri_ct];
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}
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// is the next nonzero in the old CRS data
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else if (crs_pt < _size) {
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next = nextCRS;
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// Advance the CRS counter, don't set next if we are at the end.
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if (++crs_pt < _size) {
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// advance to the row corresponding to this value
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while (crs_pt >= _ia[crs_row+1]) {
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crs_row++;
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}
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nextCRS = TRI_COORD<T>(crs_row, _ja[crs_pt], _val[crs_pt]);
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}
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}
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else cout << "SparseMatrix - Error in compressing CRS\n";
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// Add next to the new CRS structure.
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// Is this a new row (is j>0 and is ja[j] == 0)?
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if (ia[next.i]==~0) ia[next.i] = i;
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ja[i] = next.j;
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val[i] = next.v;
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}
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// sweep backwards through row pointers and check for skipped rows
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for (i=nRows-1; i>0; i--) ia[i] = (ia[i]==~0) ? ia[i+1] : ia[i];
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_delete();
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_val = val;
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_ia = ia;
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_ja = ja;
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_size = nUnique;
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_nRowsCRS = nRows;
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hasTemplate_=true;
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}
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//-----------------------------------------------------------------------------
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// Sorts the triplets, condenses duplicates, and returns the # of unique values
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//-----------------------------------------------------------------------------
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template<typename T>
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INDEX SparseMatrix<T>::CountUniqueTriplets()
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{
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if (_tri.empty()) return _size;
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std::sort(_tri.begin(), _tri.end(), triplet_comparision<T>);
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INDEX nUnique=1 + _size;
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typename vector<TRI_COORD<T> >::reverse_iterator t;
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// Loop backwards over all new triplets.
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for (t = _tri.rbegin(); t+1!=_tri.rend(); ++t) {
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// If this triplet is the same as the preceding one.
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if (triplets_equal(*(t+1), *t)) {
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if (t->add) (t+1)->v += t->v; // Add to previous
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else (t+1)->v = t->v; // Replace previous -- DOES THIS WORK?
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t->j = ~0; // Void this entry's column pointer
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}
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else nUnique++;
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}
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return nUnique;
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}
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//-----------------------------------------------------------------------------
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// Checks if a value has been set
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//-----------------------------------------------------------------------------
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template<typename T>
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bool SparseMatrix<T>::has_entry(INDEX i, INDEX j) const
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{
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if (has_entry_compressed(i,j)) return true;
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if (has_entry_uncompressed(i,j)) return true;
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return false;
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}
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template<typename T>
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bool SparseMatrix<T>::has_entry_uncompressed(INDEX i, INDEX j) const
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{
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for (unsigned k=0; k<_tri.size() ; k++) {
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if (_tri[k].i == i && _tri[k].j == j) return true;
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}
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return false;
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}
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template<typename T>
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bool SparseMatrix<T>::has_entry_compressed(INDEX i, INDEX j) const
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{
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if (_size == 0) return false;
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if (i >= _nRowsCRS) return false;
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if (_ia[i] < _ia[i+1]) {
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return -1 < ATC_Utility::search_sorted(_ja, j, _ia[i], _ia[i+1]);
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}
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return false;
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}
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//-----------------------------------------------------------------------------
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// check if the matrix has been compressed at least once
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//-----------------------------------------------------------------------------
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template<typename T>
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bool SparseMatrix<T>::has_template(void) const
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{
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return hasTemplate_;
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}
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//-----------------------------------------------------------------------------
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// Index by copy operator - return zero if not found
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//-----------------------------------------------------------------------------
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template<typename T>
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T SparseMatrix<T>::operator()(INDEX i, INDEX j) const
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{
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MICK(i,j); // Matrix Index ChecKing
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compress(*this);
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if (i>=_nRowsCRS || _ia[i+1]==_ia[i]) return 0.0;
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INDEX f = std::lower_bound(_ja+_ia[i], _ja+_ia[i+1]-1, j) - _ja;
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if (f>=_ia[i] && f<_ia[i+1] && _ja[f] == j) return _val[f];
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return 0.0;
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}
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//-----------------------------------------------------------------------------
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// Index by reference operator - add to _tri if not found
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//-----------------------------------------------------------------------------
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template<typename T>
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T& SparseMatrix<T>::operator()(INDEX i, INDEX j)
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{
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MICK(i,j); // Matrix Index ChecKing
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compress(*this);
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if (i < _nRowsCRS && _ia[i+1]>_ia[i]) {
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INDEX f = std::lower_bound(_ja+_ia[i], _ja+_ia[i+1]-1, j) - _ja;
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if (f>=_ia[i] && f<_ia[i+1] && _ja[f] == j) return _val[f];
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}
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// NEVER use index operator as LHS to modify values not already in the
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// sparcity pattern - the crude check below will only catch this on the
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// second infraction.
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if (_zero != T(0)) cout << "Use add or set for SparseMatrix\n";
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return _zero;
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}
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//-----------------------------------------------------------------------------
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// Sets (i,j) to value
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::set(INDEX i, INDEX j, T v)
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{
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MICK(i,j); // Matrix Index ChecKing
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if (i < _nRowsCRS)
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{
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const int loc = ATC_Utility::search_sorted(_ja, j, _ia[i], _ia[i+1]);
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if (loc >=0 )
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{
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_val[loc] = v;
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return;
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}
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}
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_tri.push_back(TRI_COORD<T>(i,j,v,false));
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}
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//-----------------------------------------------------------------------------
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// Adds (i,j) to value
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::add(INDEX i, INDEX j, T v)
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{
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MICK(i,j); // Matrix Index ChecKing
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if (i < _nRowsCRS)
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{
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const int loc = ATC_Utility::search_sorted(_ja, j, _ia[i], _ia[i+1]);
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if (loc >=0 )
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{
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_val[loc] += v;
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return;
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}
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}
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_tri.push_back(TRI_COORD<T>(i,j,v,true));
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}
|
|
//-----------------------------------------------------------------------------
|
|
// returns a triplet value of the ith nonzero
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
TRIPLET<T> SparseMatrix<T>::triplet(INDEX i) const
|
|
{
|
|
compress(*this);
|
|
if (i >= _ia[_nRowsCRS]) {
|
|
gerror("ERROR: tried indexing triplet of sparse matrix beyond range");
|
|
}
|
|
|
|
INDEX row(std::lower_bound(_ia, _ia+_nRowsCRS, i)-_ia);
|
|
row -= _ia[row] != i;
|
|
return TRIPLET<T>(row, _ja[i], _val[i]);
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// full reset - completely wipes out all SparseMatrix data, zero is ignored
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::reset(INDEX rows, INDEX cols, bool zero)
|
|
{
|
|
_delete();
|
|
_nRows = rows;
|
|
_nCols = cols;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// resize - changes the _nRows and _nCols without changing anything else if
|
|
// the matrix is being enlarged, other wise wipes it
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::resize(INDEX rows, INDEX cols, bool copy)
|
|
{
|
|
//if (copy) throw;
|
|
if (_nRowsCRS>rows) {
|
|
_delete();
|
|
}
|
|
if (copy)
|
|
_nRows = rows;
|
|
_nCols = cols; // a check on this would be expensive
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// get sparsity from DenseMatrix, if TOL < 0, then only zero values are added
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::reset(const DenseMatrix<T>& D, double TOL)
|
|
{
|
|
_delete(); // clears all values
|
|
// if TOL is specified then TOL = TOL^2 * max(abs(D))^2
|
|
if (TOL > 0.0)
|
|
{
|
|
TOL *= D.maxabs();
|
|
TOL *= TOL;
|
|
}
|
|
_nRows = D.nRows();
|
|
_nCols = D.nCols();
|
|
for (INDEX i=0; i<D.nRows(); i++)
|
|
for (INDEX j=0; j<D.nCols(); j++)
|
|
if (D(i,j)*D(i,j) >= TOL) // if TOL wasn't specified then TOL < 0
|
|
set(i, j, D(i,j));
|
|
|
|
compress();
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// copy - dangerous: ignores rows & columns
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::copy(const T * ptr, INDEX rows, INDEX cols)
|
|
{
|
|
cout << "SparseMatrix<T>::copy() has no effect.\n";
|
|
throw;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// dense_copy - copy to dense matrix
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::dense_copy(DenseMatrix <T> & D ) const
|
|
{
|
|
SparseMatrix<T>::compress(*this);
|
|
D.reset(nRows(),nCols());
|
|
for (INDEX i=0; i<_nRowsCRS; i++)
|
|
for (INDEX j=_ia[i]; j<_ia[i+1]; j++)
|
|
D(i, _ja[j]) = _val[j];
|
|
}
|
|
template<typename T>
|
|
DenseMatrix <T> SparseMatrix<T>::dense_copy(void) const
|
|
{
|
|
DenseMatrix<T> D;
|
|
dense_copy(D);
|
|
return D;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns true if the matrix has no non-zero elements
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
bool SparseMatrix<T>::empty() const
|
|
{
|
|
return _size==0 && _tri.empty();
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the number of rows specified by the user
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
inline INDEX SparseMatrix<T>::nRows() const
|
|
{
|
|
return _nRows;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns ??????????????????????
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
inline INDEX SparseMatrix<T>::nRowsCRS() const
|
|
{
|
|
return _nRowsCRS;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the number of columns specified by the user
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
inline INDEX SparseMatrix<T>::nCols() const
|
|
{
|
|
return _nCols;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the number of non-zeros in the matrix
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
INDEX SparseMatrix<T>::size() const
|
|
{
|
|
compress(*this);
|
|
return _size;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the number of nonzero elements in a row
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
INDEX SparseMatrix<T>::RowSize(INDEX r) const
|
|
{
|
|
compress(*this);
|
|
GCHK(r>=_nRows, "Rowsize: invalid row");
|
|
if (r >= _nRowsCRS) return 0;
|
|
return _ia[r+1]-_ia[r];
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns a pointer to the data, causes a compress
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
T* SparseMatrix<T>::ptr() const
|
|
{
|
|
compress(*this);
|
|
return _val;
|
|
}
|
|
template<typename T>
|
|
INDEX* SparseMatrix<T>::rows() const
|
|
{
|
|
compress(*this);
|
|
return _ia;
|
|
}
|
|
template<typename T>
|
|
INDEX* SparseMatrix<T>::cols() const
|
|
{
|
|
compress(*this);
|
|
return _ja;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns true if (i,j) falls in the user specified range
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
bool SparseMatrix<T>::in_range(INDEX i, INDEX j) const
|
|
{
|
|
return i < nRows() && j < nCols();
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// assigns this sparsematrix from another one - full memory copy
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::operator=(const SparseMatrix<T> &C)
|
|
{
|
|
_delete();
|
|
_copy(C);
|
|
return *this;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// assigns existing sparsematrix to a value, preserving structure
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::operator=(const T v)
|
|
{
|
|
this->set_all_elements_to(v);
|
|
return *this;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// scales this sparse matrix by a constant
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::set_all_elements_to(const T &a)
|
|
{
|
|
compress(*this);
|
|
for (INDEX i=0; i<size(); i++) _val[i] = a;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// scales this sparse matrix by a constant
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::operator*=(const T &a)
|
|
{
|
|
compress(*this);
|
|
for (INDEX i=0; i<size(); i++) _val[i] *= a;
|
|
return *this;
|
|
}
|
|
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::operator*=(const SparseMatrix<T> &a)
|
|
{
|
|
compress(*this);
|
|
Matrix<T>::operator*=(a);
|
|
return *this;
|
|
}
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// Adds two sparse matrices together.
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::operator+=(const SparseMatrix & R)
|
|
{
|
|
|
|
compress(R);
|
|
|
|
int *Ria = R.rows();
|
|
int *Rja = R.cols();
|
|
T *Rval = R.ptr();
|
|
|
|
int nRowsCRS = R.nRowsCRS();
|
|
|
|
int rowR, colR;
|
|
T valR;
|
|
for (rowR = 0; rowR < nRowsCRS; ++rowR) {
|
|
|
|
for (int j = Ria[rowR]; j < Ria[rowR+1]; ++j) {
|
|
colR = Rja[j];
|
|
valR = Rval[j];
|
|
|
|
// Because we simply want to add the value, we call add and let compress
|
|
// take care of the rest--we don't have to worry about extant entries.
|
|
add(rowR, colR, valR);
|
|
}
|
|
}
|
|
return *this;
|
|
}
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// Return matrix transpose
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T> SparseMatrix<T>::transpose() const
|
|
{
|
|
compress(*this);
|
|
SparseMatrix<T> At(nCols(), nRows());
|
|
|
|
for (INDEX i=0; i<_nRowsCRS; i++)
|
|
for (INDEX ij=_ia[i]; ij<_ia[i+1]; ij++)
|
|
At.set(_ja[ij], i, _val[ij]);
|
|
compress(At);
|
|
return At;
|
|
}
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// multiplies each row by the corresponding element in Vector scale
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::row_scale(const Vector<T> &v)
|
|
{
|
|
compress(*this);
|
|
INDEX i,ij;
|
|
GCK(*this, v, v.size()!=nRows(), "Incompatible Vector length in row_scale.");
|
|
for(i=0; i<_nRowsCRS; i++)
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++) _val[ij] *= v[i];
|
|
return *this;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// multiples each column by the corresponding element in Vector scale
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
SparseMatrix<T>& SparseMatrix<T>::col_scale(const Vector<T> &v)
|
|
{
|
|
compress(*this);
|
|
INDEX i,ij;
|
|
GCK(*this, v, v.size()!=nCols(), "Incompatible Vector length in col_scale.");
|
|
for(i=0; i<_nRowsCRS; i++)
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++) _val[ij] *= v[_ja[ij]];
|
|
return *this;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Returns a vector of the sums of each column
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
DenseVector<T> SparseMatrix<T>::col_sum() const
|
|
{
|
|
compress(*this);
|
|
INDEX i,ij;
|
|
GCHK(!nRows(), "SparseMatrix::Matrix not initialized in col_sum.")
|
|
DenseVector<T> csum(nCols());
|
|
for(i=0; i<_nRowsCRS; i++)
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++) csum(_ja[ij]) += _val[ij];
|
|
return(csum);
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Returns a vector with the number of nonzeros in each column
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
DenseVector<INDEX> SparseMatrix<T>::column_count() const
|
|
{
|
|
compress(*this);
|
|
INDEX i,j;
|
|
DenseVector<INDEX> counts(nCols());
|
|
|
|
for (i=0; i<_nRowsCRS; i++)
|
|
for(j=_ia[i]; j<_ia[i+1]; j++) counts(_ja[j])++;
|
|
return(counts);
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Writes a the nonzeros of a row to a vector
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::row(INDEX i, DenseVector<T>& row, DenseVector<INDEX>& indx) const
|
|
{
|
|
compress(*this);
|
|
GCHK(i>=nRows(), "get_row() - invalid row number");
|
|
if (i >= _nRowsCRS) {
|
|
row.resize(0);
|
|
indx.resize(0);
|
|
return;
|
|
}
|
|
row.resize(RowSize(i));
|
|
indx.resize(row.size());
|
|
INDEX idx=0, ij;
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++)
|
|
{
|
|
row(idx) = _val[ij];
|
|
indx(idx++) = _ja[ij];
|
|
}
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Computes the product of N'DN
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::
|
|
weighted_least_squares(const SparseMatrix<T> &N, const DiagonalMatrix<T> &D)
|
|
{
|
|
compress(N);
|
|
GCK(N,D,N.nRows()!=D.nRows(),"SparseMatrix::WeightedLeastSquares()");
|
|
INDEX k, ki, kj;
|
|
|
|
resize(N.nCols(), N.nCols()); // set size of this matrix
|
|
for (k=0; k<_size; k++) _val[k] = 0.0;
|
|
// compute R(i,j) = N(k,i) D(k,q) N(i,j) = N(k,i)*D(k,k)*N(k,j) (sum on k)
|
|
for (k=0; k<N._nRowsCRS; k++)
|
|
for (ki=N._ia[k]; ki<N._ia[k+1]; ki++)
|
|
for (kj=N._ia[k]; kj<N._ia[k+1]; kj++)
|
|
add(N._ja[ki],N._ja[kj], D[k]*N[kj]*N[ki]);
|
|
compress();
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Return a diagonal matrix containing the diagonal entries of this matrix
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
DiagonalMatrix<T> SparseMatrix<T>::diag() const
|
|
{
|
|
compress(*this);
|
|
DiagonalMatrix<T> D(nRows(), true); // initialized to zero
|
|
INDEX i, ij;
|
|
for (i=0; i<_nRowsCRS; i++)
|
|
{
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++)
|
|
{
|
|
if (_ja[ij]>=i) // have we reached or passed the diagonal?
|
|
{
|
|
if (_ja[ij]==i) D[i]=_val[ij]; // this this the diagonal?
|
|
break; // D[i] is already zero if there is no diagonal
|
|
}
|
|
}
|
|
}
|
|
return D;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Return a diagonal matrix containing row-sum lumped entries of the matrix
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
DiagonalMatrix<T> SparseMatrix<T>::row_sum_lump() const
|
|
{
|
|
compress(*this);
|
|
DiagonalMatrix<T> D(nRows(), true); // initialized to zero
|
|
INDEX i, ij;
|
|
for (i=0; i<_nRowsCRS; i++)
|
|
{
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++)
|
|
{
|
|
D(i,i) += _val[ij];
|
|
}
|
|
}
|
|
return D;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// output function - builds a string with each nonzero triplet value
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
string SparseMatrix<T>::to_string() const
|
|
{
|
|
compress(*this);
|
|
string out;
|
|
INDEX i, ij;
|
|
for(i=0; i<_nRowsCRS; i++)
|
|
{
|
|
for(ij=_ia[i]; ij<_ia[i+1]; ij++)
|
|
{
|
|
if (ij) out += "\n"; // append newline if not first nonzero
|
|
out += "(" + ATC_Utility::to_string(i) + ", "; // append "(i,"
|
|
out += ATC_Utility::to_string(_ja[ij]) + ") = "; // append "j) = "
|
|
out += ATC_Utility::to_string(_val[ij]); // append "value"
|
|
}
|
|
}
|
|
return out; // return the completed string
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the maximum value in the row
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
T SparseMatrix<T>::row_max(INDEX row) const
|
|
{
|
|
compress(*this);
|
|
if (!RowSize(row)) return (T)0; // if there are no nonzeros in the row
|
|
INDEX ij;
|
|
T max = _val[_ia[row]];
|
|
for(ij=_ia[row]+1; ij<_ia[row+1]; ij++) max = std::max(max,_val[ij]);
|
|
return max;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// returns the minimum value in the row
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
T SparseMatrix<T>::row_min(INDEX row) const
|
|
{
|
|
compress(*this);
|
|
if (!RowSize(row)) return (T)0; // if there are no nonzeros in the row
|
|
INDEX ij;
|
|
T min = _val[_ia[row]];
|
|
for(ij=_ia[row]+1; ij<_ia[row+1]; ij++) min = std::min(min,_val[ij]);
|
|
return min;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// prints a histogram of the values of a row to the screen
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::print_row_histogram(const string &name, INDEX nbins) const
|
|
{
|
|
compress(*this);
|
|
cout << "Begin histogram " << name << "\n";
|
|
cout << "# rows: " << _nRows << " columns: " << _nCols
|
|
<< " size: " << _size << "\n";
|
|
for(INDEX i=0; i<_nRows; i++)
|
|
{
|
|
print_row_histogram(i, nbins);
|
|
cout << "\n";
|
|
}
|
|
cout << "End histogram " << name << "\n";
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// prints a histogram of the values of a row to the screen
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::print_row_histogram(INDEX row, INDEX nbins) const
|
|
{
|
|
compress(*this);
|
|
if (!nbins) nbins++;
|
|
vector<INDEX> counts(nbins, 0);
|
|
const T min = row_min(row);
|
|
const T max = row_max(row);
|
|
const T range = max-min;
|
|
const double bin_size = range/double(nbins);
|
|
if (range<=0.0) counts[nbins-1]=RowSize(row);
|
|
else
|
|
{
|
|
for(INDEX ij=_ia[row]; ij<_ia[row+1]; ij++)
|
|
{
|
|
INDEX bin = INDEX((_val[ij]-min)/bin_size);
|
|
counts[bin-(bin==nbins)]++;
|
|
}
|
|
}
|
|
cout<<showbase<<scientific;
|
|
cout<<"# Histogram: row "<<row<<" min "<<min<<" max "<<max<<" cnt " <<RowSize(row)<<"\n";
|
|
T bin_start = min;
|
|
for(INDEX i=0; i<nbins; i++)
|
|
{
|
|
cout << "(" << bin_start << ",";
|
|
bin_start += bin_size;
|
|
cout << bin_start << ") " << counts[i] << "\n";
|
|
}
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// prints the triplets the screen
|
|
//-----------------------------------------------------------------------------
|
|
template<typename T>
|
|
void SparseMatrix<T>::print_triplets() const
|
|
{
|
|
typename vector<TRI_COORD<T> >::const_iterator t;
|
|
string out;
|
|
out += "==================BEGIN TRIPLETS=======================\n";
|
|
// Loop backwards over all new triplets.
|
|
for (t = _tri.begin(); t!=_tri.end(); ++t) {
|
|
out += "(" + ATC_Utility::to_string(t->i) + ", "; // append "(i,"
|
|
out += ATC_Utility::to_string(t->j) + ") = "; // append "j) = "
|
|
out += ATC_Utility::to_string(t->v); // append "value"
|
|
out += "\n";
|
|
}
|
|
out += "===================END TRIPLETS========================\n";
|
|
cout << out;
|
|
}
|
|
//-----------------------------------------------------------------------------
|
|
// Outputs a string to a sparse Matlab type
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::matlab(ostream &o, const string &s) const
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{
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compress(*this);
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INDEX i, ij;
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o << s <<" = sparse(" << nRows() << "," << nCols() << ");\n";
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o << showbase << scientific;
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for(i=0; i<_nRowsCRS; i++)
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for(ij=_ia[i]; ij<_ia[i+1]; ij++)
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o<<s<<"("<<i+1<<","<<_ja[ij]+1<<")="<<_val[ij]<<";\n";
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}
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//-----------------------------------------------------------------------------
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// Writes the matrix to a binary file (after a compress).
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::binary_write(std::fstream& f) const
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{
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compress(*this);
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f.write((char*)&_size, sizeof(INDEX)); // writes number of nonzeros
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f.write((char*)&_nRowsCRS, sizeof(INDEX)); // writes number of rows in crs
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f.write((char*)&_nRows, sizeof(INDEX)); // write matrix rows
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f.write((char*)&_nCols, sizeof(INDEX)); // write number of columns
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if (!_size) return;
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f.write((char*)_val, sizeof(T) *_size);
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f.write((char*)_ja, sizeof(INDEX)*_size);
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f.write((char*)_ia, sizeof(INDEX)*(_nRowsCRS+1));
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}
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//-----------------------------------------------------------------------------
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// Reads a SparseMatrix from a binary file. (wipes out any original data)
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::binary_read(std::fstream& f)
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{
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_delete();
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f.read((char*)&_size, sizeof(INDEX));
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f.read((char*)&_nRowsCRS, sizeof(INDEX));
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f.read((char*)&_nRows, sizeof(INDEX));
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f.read((char*)&_nCols, sizeof(INDEX));
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if (!_size) return;
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_create(_size,_nRowsCRS);
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f.read((char*)_val, sizeof(T)*_size);
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f.read((char*)_ja, sizeof(INDEX)*_size);
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f.read((char*)_ia, sizeof(INDEX)*(_nRowsCRS+1));
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}
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//-----------------------------------------------------------------------------
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// Writes the sparse matrix to a file in a binary format
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//-----------------------------------------------------------------------------
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template<typename T>
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void SparseMatrix<T>::write_restart(FILE *f) const
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{
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compress(*this);
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fwrite(&_size, sizeof(INDEX), 1 ,f); // write number of nonzeros
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fwrite(&_nRowsCRS, sizeof(INDEX), 1 ,f); // write number of rows
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fwrite(&_nRows, sizeof(INDEX), 1 ,f); // write number of columns
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fwrite(&_nCols, sizeof(INDEX), 1 ,f); // write number of columns
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if (!_size) return;
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fwrite(_val, sizeof(T), _size ,f);
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fwrite(_ja, sizeof(T), _size ,f);
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fwrite(_ia, sizeof(INDEX), _nRowsCRS+1 ,f);
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}
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} // end namespace
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#endif
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