109 lines
3.6 KiB
Markdown
109 lines
3.6 KiB
Markdown
# meanas README
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**meanas** is a python package for electromagnetic simulations
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** UNSTABLE / WORK IN PROGRESS **
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Formerly known as [fdfd_tools](https://mpxd.net/code/jan/fdfd_tools).
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This package is intended for building simulation inputs, analyzing
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simulation outputs, and running short simulations on unspecialized hardware.
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It is designed to provide tooling and a baseline for other, high-performance
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purpose- and hardware-specific solvers.
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**Contents**
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- Finite difference frequency domain (FDFD)
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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 operators
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* Waveguide mode eigensolver
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* Stretched-coordinate PML boundaries (SCPML)
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* Functional versions of most operators
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* Anisotropic media (limited to diagonal elements 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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- Finite difference time domain (FDTD)
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* Basic Maxwell time-steps
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* Poynting vector and energy calculation
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* Convolutional PMLs
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This package does *not* provide a fast matrix solver, though by default
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`meanas.fdfd.solvers.generic(...)` will call
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`scipy.sparse.linalg.qmr(...)` to perform a solve.
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For 2D FDFD 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) FDFD problems, I recommend a GPU-based iterative
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solver, such as [opencl_fdfd](https://mpxd.net/code/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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- [WORKING Source repository](https://mpxd.net/code/jan/fdfd_tools/src/branch/wip)
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- *TODO* [Source repository](https://mpxd.net/code/jan/meanas)
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- PyPI *TBD*
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## Installation
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**Requirements:**
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* python 3 (tests require 3.7)
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* numpy
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* scipy
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Install from PyPI with pip:
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```bash
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pip3 install 'meanas[test,examples]'
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```
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### Development install
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Install python3.7, virtualenv, and git:
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```bash
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# This is for Debian/Ubuntu/other-apt-based systems; you may need an alternative command
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sudo apt install python3.7 virtualenv build-essential python3.7-dev git
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```
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If python 3.7 is not your default python3 version, create a virtualenv:
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```bash
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# Check python3 version:
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python3 --version
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# output on my system: Python 3.7.5rc1
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# If this indicates a version >= 3.7, you can skip all
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# the steps involving virtualenv or referencing the venv/ directory
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# Create a virtual environment using python3.7 and place it in the directory `venv/`
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virtualenv -p python3.7 venv
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```
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In-place development install:
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```bash
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# Download using git
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git clone --branch wip https://mpxd.net/code/jan/fdfd_tools.git meanas/
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# NOTE: In the future this will become
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#git clone https://mpxd.net/code/jan/meanas.git
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# If you are using a virtualenv, activate it
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source venv/bin/activate
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# Install in-place (-e, editable) from ./meanas, including testing and example dependencies ([test, examples])
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pip3 install --user -e './meanas[test,examples]'
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# Run tests
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python3 -m pytest -rsxX | tee test_results.txt
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```
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#### See also:
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- [git book](https://git-scm.com/book/en/v2)
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- [virtualenv documentation](https://virtualenv.pypa.io/en/stable/userguide/)
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- [python language reference](https://docs.python.org/3/reference/index.html)
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- [python standard library](https://docs.python.org/3/library/index.html)
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## Use
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See `examples/` for some simple examples; you may need additional
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packages such as [gridlock](https://mpxd.net/code/jan/gridlock)
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to run the examples.
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