forked from jan/fdfd_tools
47 lines
1.6 KiB
Markdown
47 lines
1.6 KiB
Markdown
# fdfd_tools
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**fdfd_tools** is a python package containing utilities for
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creating and analyzing 2D and 3D finite-difference frequency-domain (FDFD)
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electromagnetic simulations.
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**Contents**
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* Library of sparse matrices for representing the electromagnetic wave
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equation in 3D, as well as auxiliary matrices for conversion between fields
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* Waveguide mode solver and waveguide mode operators
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* Stretched-coordinate PML boundaries (SCPML)
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* Functional versions of most operators
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* Anisotropic media (eps_xx, eps_yy, eps_zz, mu_xx, ...)
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* Arbitrary distributions of perfect electric and magnetic conductors (PEC / PMC)
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This package does *not* provide a fast matrix solver, though by default
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```fdfd_tools.solvers.generic(...)``` will call
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```scipy.sparse.linalg.qmr(...)``` to perform a solve.
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For 2D problems this should be fine; likewise, the waveguide mode
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solver uses scipy's eigenvalue solver, with reasonable results.
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For solving large (or 3D) problems, I recommend a GPU-based iterative
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solver, such as [opencl_fdfd](https://mpxd.net/gogs/jan/opencl_fdfd) or
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those included in [MAGMA](http://icl.cs.utk.edu/magma/index.html)). Your
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solver will need the ability to solve complex symmetric (non-Hermitian)
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linear systems, ideally with double precision.
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## Installation
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**Requirements:**
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* python 3 (written and tested with 3.5)
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* numpy
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* scipy
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Install with pip, via git:
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```bash
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pip install git+https://mpxd.net/gogs/jan/fdfd_tools.git@release
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```
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## Use
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See examples/test.py for some simple examples; you may need additional
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packages such as [gridlock](https://mpxd.net/gogs/jan/gridlock)
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to run the examples.
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