gauss_seidel_stochastic, a Python code which uses a stochastic version of the Gauss-Seidel iteration to solve a linear system with a symmetric positive definite (SPD) matrix.
The main interest of this code is that it is an understandable analogue to the stochastic gradient descent method used for optimization in various machine learning applications.
The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.
gauss_seidel is available in a MATLAB version and a Python version.
cg_rc, a Python code which implements the conjugate gradient method for solving a positive definite sparse linear system A*x=b, using reverse communication.
jacobi, a Python code which implements the Jacobi iteration for linear systems.
test_mat, a Python code which defines test matrices.