# AsymmetricMatrixBasedSolver¶

class probnum.linalg.AsymmetricMatrixBasedSolver(A, b, x0)[source]

Asymmetric matrix-based probabilistic linear solver.

Parameters: A (array-like or LinearOperator or RandomVariable, shape=(n,n)) – The square matrix or linear operator of the linear system. b (array_like, shape=(n,) or (n, nrhs)) – Right-hand side vector or matrix in $$A x = b$$.

Methods Summary

 has_converged(iter, maxiter, **kwargs) Check convergence of a linear solver. solve([callback, maxiter, atol]) Solve the linear system $$Ax=b$$.

Methods Documentation

has_converged(iter, maxiter, **kwargs)[source]

Check convergence of a linear solver.

Evaluates a set of convergence criteria based on its input arguments to decide whether the iteration has converged.

Parameters: iter (int) – Current iteration of solver. maxiter (int) – Maximum number of iterations has_converged (bool) – True if the method has converged. convergence_criterion (str) – Convergence criterion which caused termination.
solve(callback=None, maxiter=None, atol=None)[source]

Solve the linear system $$Ax=b$$.

Parameters: callback (function, optional) – User-supplied function called after each iteration of the linear solver. It is called as callback(xk, Ak, Ainvk, sk, yk, alphak, resid, **kwargs) and can be used to return quantities from the iteration. Note that depending on the function supplied, this can slow down the solver. kwargs – Key-word arguments adjusting the behaviour of the solve iteration. These are usually convergence criteria. x (RandomVariable, shape=(n,) or (n, nrhs)) – Approximate solution $$x$$ to the linear system. Shape of the return matches the shape of b. A (RandomVariable, shape=(n,n)) – Posterior belief over the linear operator. Ainv (RandomVariable, shape=(n,n)) – Posterior belief over the linear operator inverse $$H=A^{-1}$$. info (dict) – Information on convergence of the solver.