Could someone point me to more details on the jacobi preconditioner in PySparse? For a linear system A*x = b, the usual formulation of damped jacobi is
x_1 = x_0 + \omega*D^{-1} (b - A*x)
When I run
>>>omega=1
>>>ns=100
>>>preconA = jacobi(A,omega,ns)
>>>preconA.precon(b,x)
I get a different answer than with a simple implementation of Jacobi iteration. Does precon just repeatedly multiply by D^{-1}?
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Hi,
Could someone point me to more details on the jacobi preconditioner in PySparse? For a linear system A*x = b, the usual formulation of damped jacobi is
x_1 = x_0 + \omega*D^{-1} (b - A*x)
When I run
>>>omega=1
>>>ns=100
>>>preconA = jacobi(A,omega,ns)
>>>preconA.precon(b,x)
I get a different answer than with a simple implementation of Jacobi iteration. Does precon just repeatedly multiply by D^{-1}?