class TMatrixTSym<double>: public TMatrixTBase<double>

 delete data pointer m, if it was assigned on the heap

 return data pointer . if requested size <= kSizeMax, assign pointer
 to the stack space

 copy copySize doubles from *oldp to *newp . However take care of the
 situation where both pointers are assigned to the same stack space

 Allocate new matrix. Arguments are number of rows, columns, row
 lowerbound (0 default) and column lowerbound (0 default).

 Symmetric matrix summation. Create a matrix C such that C = A + B.

 Symmetric matrix summation. Create a matrix C such that C = A + B.

 Create a matrix C such that C = A' * A. In other words,
 c[i,j] = SUM{ a[k,i] * a[k,j] }.

 Matrix multiplication, with A symmetric
 Create a matrix C such that C = A' * A = A * A = A * A'

 Get submatrix [row_lwb..row_upb][row_lwb..row_upb]; The indexing range of the
 returned matrix depends on the argument option:

 option == "S" : return [0..row_upb-row_lwb+1][0..row_upb-row_lwb+1] (default)
 else          : return [row_lwb..row_upb][row_lwb..row_upb]

 Get submatrix [row_lwb..row_upb][col_lwb..col_upb]; The indexing range of the
 returned matrix depends on the argument option:

 option == "S" : return [0..row_upb-row_lwb+1][0..col_upb-col_lwb+1] (default)
 else          : return [row_lwb..row_upb][col_lwb..col_upb]

 Insert matrix source starting at [row_lwb][row_lwb], thereby overwriting the part
 [row_lwb..row_lwb+nrows_source][row_lwb..row_lwb+nrows_source];

 Insert matrix source starting at [row_lwb][col_lwb] in a symmetric fashion, thereby overwriting the part
 [row_lwb..row_lwb+nrows_source][row_lwb..row_lwb+nrows_source];

 Set size of the matrix to nrows x ncols
 New dynamic elements are created, the overlapping part of the old ones are
 copied to the new structures, then the old elements are deleted.

 Set size of the matrix to [row_lwb:row_upb] x [col_lwb:col_upb]
 New dynamic elemenst are created, the overlapping part of the old ones are
 copied to the new structures, then the old elements are deleted.

 Invert the matrix and calculate its determinant
 Notice that the LU decomposition is used instead of Bunch-Kaufman
 Bunch-Kaufman guarantees a symmetric inverted matrix but is slower than LU .
 The user can access Bunch-Kaufman through the TDecompBK class .

 Invert the matrix and calculate its determinant

 Transpose a matrix.

 Perform a rank 1 operation on the matrix:
     A += alpha * v * v^T

 Calculate B * (*this) * B^T , final matrix will be (nrowsb x nrowsb)
 This is a similarity transform when B is orthogonal . It is more
 efficient than applying the actual multiplication because this
 routine realizes that  the final matrix is symmetric .

 Calculate B * (*this) * B^T , final matrix will be (nrowsb x nrowsb)
 This is a similarity transform when B is orthogonal . It is more
 efficient than applying the actual multiplication because this
 routine realizes that  the final matrix is symmetric .

 Calculate scalar v * (*this) * v^T

 Calculate B^T * (*this) * B , final matrix will be (ncolsb x ncolsb)
 It is more efficient than applying the actual multiplication because this
 routine realizes that  the final matrix is symmetric .

 Assign val to every element of the matrix.

 Add val to every element of the matrix.

 Subtract val from every element of the matrix.

 Multiply every element of the matrix with val.

 Add the source matrix.

 Subtract the source matrix.

 Apply action to each element of the matrix. To action the location
 of the current element is passed.

 randomize matrix element values but keep matrix symmetric

 randomize matrix element values but keep matrix symmetric positive definite

 Return a matrix containing the eigen-vectors ordered by descending eigen-values.
 For full functionality use TMatrixDSymEigen .

 Stream an object of class TMatrixTSym.

 or as a[i][j]