Navigation: Up, Table of Contents, Bibliography, Index, Title Page

## LinearAlgebraTraits_d

### Definition

The data type LinearAlgebraTraits_d encapsulates two classes Matrix, Vector and many functions of basic linear algebra. An instance of data type Matrix is a matrix of variables of type NT. Accordingly, Vector implements vectors of variables of type NT. Most functions of linear algebra are checkable, i.e., the programs can be asked for a proof that their output is correct. For example, if the linear system solver declares a linear system A x = b unsolvable it also returns a vector c such that cT A = 0 and cT b 0.

### Types

LinearAlgebraTraits_d::NT
| the number type of the components.
LinearAlgebraTraits_d::Vector
| the vector type.
LinearAlgebraTraits_d::Matrix
| the matrix type.

### Operations

static Matrix | LA.transpose ( Matrix M)
|  | returns MT (a M.column_dimension() × M.column_dimension() - matrix).
static bool | LA.inverse ( Matrix M, Matrix& I, NT& D, Vector& c)
|  | determines whether M has an inverse. It also computes either the inverse as (1/D) · I or when no inverse exists, a vector c such that cT · M = 0 . Precondition: M is square.
static Matrix | LA.inverse ( Matrix M, NT& D)
|  | returns the inverse matrix of M. More precisely, 1/D times the matrix returned is the inverse of M. Precondition: determinant(M) != 0. Precondition: M is square.
static NT |
LA.determinant ( | Matrix M, Matrix& L, Matrix& U, std::vector<int>& q, Vector& c)
|  | returns the determinant D of M and sufficient information to verify that the value of the determinant is correct. If the determinant is zero then c is a vector such that cT · M = 0. If the determinant is non-zero then L and U are lower and upper diagonal matrices respectively and q encodes a permutation matrix Q with Q(i,j) = 1 iff i = q(j) such that L · M · Q = U, L(0,0) = 1, L(i,i) = U(i - 1,i - 1) for all i, 1 i < n, and D = s · U(n - 1,n - 1) where s is the determinant of Q. Precondition: M is square.
static bool |
LA.verify_determinant ( | Matrix M, NT D, Matrix& L, Matrix& U, std::vector<int> q, Vector& c)
|  | verifies the conditions stated above.
static NT | LA.determinant ( Matrix M)
|  | returns the determinant of M. Precondition: M is square.
static int | LA.sign_of_determinant ( Matrix M)
|  | returns the sign of the determinant of M. Precondition: M is square.
static bool |
LA.linear_solver ( | Matrix M, Vector b, Vector& x, NT& D, Matrix& spanning_vectors, Vector& c)
|  | determines the complete solution space of the linear system M · x = b. If the system is unsolvable then cT · M = 0 and cT · b 0. If the system is solvable then (1/D) x is a solution, and the columns of spanning_vectors are a maximal set of linearly independent solutions to the corresponding homogeneous system. Precondition: M.row_dimension() = b.dimension().
static bool |
LA.linear_solver ( | Matrix M, Vector b, Vector& x, NT& D, Vector& c)
|  | determines whether the linear system M · x = b is solvable. If yes, then (1/D) x is a solution, if not then cT · M = 0 and cT · b 0. Precondition: M.row_dimension() = b.dimension().
static bool |
LA.linear_solver ( | Matrix M, Vector b, Vector& x, NT& D)
|  | as above, but without the witness c Precondition: M.row_dimension() = b.dimension().
static bool | LA.is_solvable ( Matrix M, Vector b)
|  | determines whether the system M · x = b is solvable Precondition: M.row_dimension() = b.dimension().
static bool | LA.homogeneous_linear_solver ( Matrix M, Vector& x)
|  | determines whether the homogeneous linear system M · x = 0 has a non - trivial solution. If yes, then x is such a solution.
static int |
LA.homogeneous_linear_solver ( | Matrix M, Matrix& spanning_vecs)
|  | determines the solution space of the homogeneous linear system M · x = 0. It returns the dimension of the solution space. Moreover the columns of spanning_vecs span the solution space.
static int |
LA.independent_columns ( | Matrix M, std::vector<int>& columns)
|  | returns the indices of a maximal subset of independent columns of M.
static int | LA.rank ( Matrix M)
|  | returns the rank of matrix M

### Has Models

CGAL::Linear_algebraHd<RT>
CGAL::Linear_algebraCd<FT>

Next: Vector

Navigation: Table of Contents, Bibliography, Index, Title Page

The CGAL Project . Tue, December 21, 2004 .