Skip to main content

An open source EM FEM simulator in Python

Project description

Introduction

Hello everybody. Thanks for showing interest in this repository.

Feel free to download your version of EMerge and start playing around with it! If you have suggestions/changes/questions either use the Github issue system or join the Discord using the following link:

https://discord.gg/7PF4WcS6uA

How to install

Clone this repository or download the files. While in the EMerge path containing the src/emerge folder, install the module using:

pip install .

If you want to install the library with PyPardiso on Intel machines, you can install the optional dependency with EMerge using:

pip install ".[pypardiso]"

Compatibility

As far as I know, the library should work on all systems. PyPARDISO is not supported on ARM but the current SuperLU and UMFPACK solvers work on ARM as well. Both SuperLU and UMFPACK can run on multi-processing implementations as long as you do entry-point protection:

import emerge as em

def main():
    # setup simulation

    model.mw.frequency_domain(True, ..., multi_processing=True)

if __name__ == "__main__":
    main()

Otherwise, the parallel solver will default to SuperLU which is significantly slower on larger problems.

Required libraries

To run this FEM library you need the following libraries

  • numpy
  • scipy
  • pypardiso
  • gmsh
  • loguru
  • numba
  • matplotlib (for the matplotlib base display)
  • pyvista (for the PyVista base display)
  • numba-progress
  • scikit-umfpack

NOTICE

First time runs will be very slow because Numba needs to generate local C-compiled functions of the assembler and other mathematical functions. These compilations are chached so this should only take time once.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

emerge-0.4.6.tar.gz (167.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

emerge-0.4.6-py3-none-any.whl (2.1 kB view details)

Uploaded Python 3

File details

Details for the file emerge-0.4.6.tar.gz.

File metadata

  • Download URL: emerge-0.4.6.tar.gz
  • Upload date:
  • Size: 167.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for emerge-0.4.6.tar.gz
Algorithm Hash digest
SHA256 eec0e6e93a05f6a7cc1a00c5d94efe7e392ac89a8c970386a652a3e99bc770ed
MD5 aab6877cdd2ca69628bc3917a8938158
BLAKE2b-256 350c809223a16ac1d2a11369c95ba5fc97759ede216db9278f68805b3c957467

See more details on using hashes here.

File details

Details for the file emerge-0.4.6-py3-none-any.whl.

File metadata

  • Download URL: emerge-0.4.6-py3-none-any.whl
  • Upload date:
  • Size: 2.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for emerge-0.4.6-py3-none-any.whl
Algorithm Hash digest
SHA256 7adbf2a3f741c79715948d2605cf0a3337d39393fd7c3c0c3033a947fa30ffd2
MD5 2d5cd424824f3281f1da05edc05834b8
BLAKE2b-256 e257ab84d787f95bdc92610f44dc62cd56c2d6567422287c8341974c943a9678

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page