https://github.com/BYUCamachoLab/emepy
https://github.com/BYUCamachoLab/emepy
Last synced: 6 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/BYUCamachoLab/emepy
- Owner: BYUCamachoLab
- License: mit
- Created: 2020-11-25T20:40:10.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-10-03T21:36:48.000Z (over 2 years ago)
- Last Synced: 2024-11-07T06:12:16.439Z (6 months ago)
- Language: Python
- Homepage: https://emepy.rtfd.io
- Size: 42.1 MB
- Stars: 34
- Watchers: 1
- Forks: 8
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome_photonics - emepy
README
# EMEPy 1.2.3 Eigenmode Expansion Tool for Python
### An open source tool for simulating EM fields in python using the Eigenmode Expansion Method (EME). Employs neural networks as a means for accelerating the cross sectional field profile generation process.
## Installation
Clone the repo
git clone [email protected]:BYUCamachoLab/emepy.git
Install the development version of emepy using pip:
pip install -e .
Or collect the most recent publication to pip
pip install emepy
## Docs
Read the docs [here](https://emepy.readthedocs.io/en/latest/).
## ANN Models
Optionally, the user can download and use our neural networks for fundamental TE generation.
The neural network models can be found [here](https://byu.box.com/s/xtpp2h8vfwp4l07wdl5559j3vnip5cqj). Simply download the three folders (Hy_chunks, Hx_chunks, neff_pickle) and place them under path/to/repo/emepy/models/
This will look like:
.../emepy/emepy/models/Hy_chunks/
.../emepy/emepy/models/Hx_chunks/
.../emepy/emepy/models/neff_pickle/
## BibTeX citation
```
@article{emepy,
author = {Ian M. Hammond and Alec M. Hammond and Ryan M. Camacho},
journal = {Opt. Lett.},
number = {6},
pages = {1383--1386},
publisher = {OSA},
title = {Deep learning-enhanced, open-source eigenmode expansion},
volume = {47},
month = {Mar},
year = {2022},
doi = {10.1364/OL.443664},
}
```