fdfd_tools/README.md

# meanas README

**meanas** is a python package for electromagnetic simulations

** UNSTABLE / WORK IN PROGRESS **

Formerly known as [fdfd_tools](https://mpxd.net/code/jan/fdfd_tools).

This package is intended for building simulation inputs, analyzing
simulation outputs, and running short simulations on unspecialized hardware.
It is designed to provide tooling and a baseline for other, high-performance
purpose- and hardware-specific solvers.


**Contents**
- Finite difference frequency domain (FDFD)
    * Library of sparse matrices for representing the electromagnetic wave
    equation in 3D, as well as auxiliary matrices for conversion between fields
    * Waveguide mode operators
    * Waveguide mode eigensolver
    * Stretched-coordinate PML boundaries (SCPML)
    * Functional versions of most operators
    * Anisotropic media (limited to diagonal elements eps_xx, eps_yy, eps_zz, mu_xx, ...)
    * Arbitrary distributions of perfect electric and magnetic conductors (PEC / PMC)
- Finite difference time domain (FDTD)
    * Basic Maxwell time-steps
    * Poynting vector and energy calculation
    * Convolutional PMLs

This package does *not* provide a fast matrix solver, though by default
`meanas.fdfd.solvers.generic(...)` will call
`scipy.sparse.linalg.qmr(...)` to perform a solve.
For 2D FDFD problems this should be fine; likewise, the waveguide mode
solver uses scipy's eigenvalue solver, with reasonable results.

For solving large (or 3D) FDFD problems, I recommend a GPU-based iterative
solver, such as [opencl_fdfd](https://mpxd.net/code/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.

- [WORKING Source repository](https://mpxd.net/code/jan/fdfd_tools/src/branch/ongoing)
- *TODO* [Source repository](https://mpxd.net/code/jan/meanas)
- PyPI *TBD*


## Installation

**Requirements:**
* python 3 (tests require 3.7)
* numpy
* scipy


Install from PyPI with pip:
```bash
pip3 install 'meanas[test,examples]'
```

### Development install
Install python3.7 and virtualenv:
```bash
# This is for Debian/Ubuntu/other-apt-based systems; you may need an alternative command
sudo apt install python3.7 virtualenv build-essential python3.7-dev
```

If python 3.7 is not your default python3 version, create a virtualenv:
```bash
# Check python3 version:
python3 --version
# output: Python 3.7.5rc1

# Create a virtual environment using python3.7 and place it in the directory `venv/`
virtualenv -p python3.7 venv
```

In-place development install:
```bash
# Download using git
git clone --branch ongoing https://mpxd.net/code/jan/fdfd_tools.git meanas/

# NOTE: In the future this will become
#git clone https://mpxd.net/code/jan/meanas.git

# If you are using a virtualenv, activate it
source venv/bin/activate

# Install in-place (-e, editable) from ./meanas, including testing and example dependencies ([test, examples])
pip3 install --user -e './meanas[test,examples]'

# Run tests
python3 -m pytest
```


## Use

See `examples/` for some simple examples; you may need additional
packages such as [gridlock](https://mpxd.net/code/jan/gridlock)
to run the examples.