fdfd_tools/README.md
2016-08-04 23:05:11 -07:00

47 lines
1.6 KiB
Markdown

# fdfd_tools
**fdfd_tools** is a python package containing utilities for
creating and analyzing 2D and 3D finite-difference frequency-domain (FDFD)
electromagnetic simulations.
**Contents**
* Library of sparse matrices for representing the electromagnetic wave
equation in 3D, as well as auxiliary matrices for conversion between fields
* Waveguide mode solver and waveguide mode operators
* Stretched-coordinate PML boundaries (SCPML)
* Functional versions of most operators
* Anisotropic media (eps_xx, eps_yy, eps_zz, mu_xx, ...)
* Arbitrary distributions of perfect electric and magnetic conductors (PEC / PMC)
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
**Requirements:**
* python 3 (written and tested with 3.5)
* numpy
* scipy
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.