JacobiSolver constructor

JacobiSolver({ required RealMatrix matrix, required List<double> knownValues, required List<double> x0, int maxSteps = 30, double precision = 1.0e-10, })

Given an equation in the form Ax = b, A is a square matrix containing n equations in n unknowns and b is the vector of the known values.

• matrix is the matrix containing the equations;
• knownValues is the vector with the known values;
• x0 is the initial guess (which is a vector);
• precision tells how accurate the algorithm has to be;
• maxSteps the maximum number of iterations the algorithm.

The matrix A must be strictly diagonally dominant.

Implementation

factory JacobiSolver({
  required RealMatrix matrix,
  required List<double> knownValues,
  required List<double> x0,
  int maxSteps = 30,
  double precision = 1.0e-10,
}) {
  // The initial vector with the guesses MUST have the same size as the matrix
  // of course
  if (x0.length != knownValues.length) {
    throw const SystemSolverException(
      'The length of the guesses vector '
      'must match the size of the square matrix.',
    );
  }

  return JacobiSolver._(
    matrix: matrix,
    knownValues: knownValues,
    x0: x0,
    maxSteps: maxSteps,
    precision: precision,
  );
}