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lect05, Wed 01/23
Solving Ax = b by Jacobi and conjugate gradients
Reading assignment
For next Wednesday, read sections 5.1, 5.2, and 5.5 of the NCM book.
References for today’s lecture
The sections on the Jacobi method and the conjugate gradient method (CG) from the Templates book.
If you’re interested in learning more about how CG works, there’s a great paper called An introduction to the conjugate gradient method without the agonizing pain by Jonathan Shewchuk at Berkeley. Reading it is optional for CS 111, but it’s fun if you like the math.
Outline
Interesting matrices:
- Manipulating sparse matrices in scipy
Iterative methods for Ax = b:
- Jacobi iteration
- Conjugate gradients
- Lecture codes:
- Jsolve()
- CGsolve()
- numpy/scipy routines:
- spla.cg()