From 068e0c7c935af2dc72eaf64a9a788be603c2ec17 Mon Sep 17 00:00:00 2001 From: jan Date: Thu, 4 Aug 2016 22:55:24 -0700 Subject: [PATCH] Update README with solver and example information. --- README.md | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index ea4de31..1399887 100644 --- a/README.md +++ b/README.md @@ -13,11 +13,17 @@ electromagnetic simulations. * Functional versions of most operators * Anisotropic media (eps_xx, eps_yy, eps_zz, mu_xx, ...) -This package does *not* provide a matrix solver. The waveguide mode solver -uses scipy's eigenvalue solver; I recommend a GPU-based iterative solver (eg. -those included in [MAGMA](http://icl.cs.utk.edu/magma/index.html)). You will -need the ability to solve complex symmetric (non-Hermitian) linear systems, -ideally with double precision. +This package does *not* provide a fast matrix solver, though by default +```fdfd_tools.solvers.generic(...)``` will call +```scipy.sparse.linalg.qmr(...)``` to perform a solve. +For 2D problems this should be fine; likewise, the waveguide mode +solver uses scipy's eigenvalue solver, with reasonable results. + +For solving large (or 3D) problems, I recommend a GPU-based iterative +solver, such as [opencl_fdfd](https://mpxd.net/gogs/jan/opencl_fdfd) or +those included in [MAGMA](http://icl.cs.utk.edu/magma/index.html)). Your +solver will need the ability to solve complex symmetric (non-Hermitian) +linear systems, ideally with double precision. ## Installation @@ -31,3 +37,9 @@ Install with pip, via git: ```bash pip install git+https://mpxd.net/gogs/jan/fdfd_tools.git@release ``` + +## Use + +See examples/test.py for some simple examples; you may need additional +packages such as [gridlock](https://mpxd.net/gogs/jan/gridlock) +to run the examples.