Lines Matching full:matrix
18 i.e either row major or column major. The default is column major. Most arithmetic operations on sparse matrices will assert that they have the same storage order. Moreover, when interacting with external libraries that are not yet supported by Eigen, it is important to know how to send the required matrix pointers.
24 SparseMatrix<double> sm1(1000,1000); // 1000x1000 compressed sparse matrix of double.
25 SparseMatrix<std::complex<double>,RowMajor> sm2; // Compressed row major matrix of complex double.
30 // Eventually fill the matrix sm1 ...
38 sm1.resize(m,n); //Change sm to a mxn matrix.
41 Note that when calling reserve(), it is not required that nnz is the exact number of nonzero elements in the final matrix. However, an exact estimation will avoid multiple reallocations during the insertion phase.
43 Insertions of values in the sparse matrix can be done directly by looping over nonzero elements and use the insert() function
46 sm1.insert(i, j) = v_ij; // It is assumed that v_ij does not already exist in the matrix.
64 The following functions can be used to set constant or random values in the matrix.
66 sm1.setZero(); // Reset the matrix with zero elements
70 \section SparseBasicInfos Matrix properties
71 Beyond the functions rows() and cols() that are used to get the number of rows and columns, there are some useful functions that are available to easily get some informations from the matrix.
80 sm1.norm(); // (Euclidian ??) norm of the matrix
82 sm1.isVector(); // Check if sm1 is a sparse vector or a sparse matrix
89 It is easy to perform arithmetic operations on sparse matrices provided that the dimensions are adequate and that the matrices have the same storage order. Note that the evaluation can always be done in a matrix with a different storage order.
157 There are a set of low-levels functions to get the standard compressed storage pointers. The matrix should be in compressed mode which can be checked by calling isCompressed(); makeCompressed() should do the job otherwise.
159 // Scalar pointer to the values of the matrix, size nnz
161 // Index pointer to get the row indices (resp. column indices) for column major (resp. row major) matrix, size nnz
166 These pointers can therefore be easily used to send the matrix to some external libraries/solvers that are not yet supported by Eigen.
169 In many cases, it is necessary to reorder the rows and/or the columns of the sparse matrix for several purposes : fill-in reducing during matrix decomposition, better data locality for sparse matrix-vector products... The class PermutationMatrix is available to this end.
180 The following functions are useful to extract a block of rows (resp. columns) from a row-major (resp. column major) sparse matrix. Note that because of the particular storage, it is not ?? efficient ?? to extract a submatrix comprising a certain number of subrows and subcolumns.
182 sm1.innerVector(outer); // Returns the outer -th column (resp. row) of the matrix if sm is col-major (resp. row-major)
183 sm1.innerVectors(outer); // Returns the outer -th column (resp. row) of the matrix if mat is col-major (resp. row-major)
191 sm2 = sm1.triangularview<Lower>(); // Get the lower triangular part of the matrix.
193 sm2 = sm1.selfadjointview<Lower>(); // Build a selfadjoint matrix from the lower part of sm1.
