Skip to main content

High-Performance Computational Mechanics in Python.

Project description

SigmaEpsilon - High-Performance Computational Solid Mechanics in Python

Binder CircleCI Documentation Status License PyPI Code style: black

Warning This package is under active development and in an alpha stage. Come back later, or star the repo to make sure you don’t miss the first stable release!

Highlights

Head over to the Quick Examples page in the docs to explore our gallery of examples showcasing what SigmaEpsilon can do! Want to test-drive SigmaEpsilon? All of the examples from the gallery are live on MyBinder for you to test drive without installing anything locally: Launch on Binder.

Overview

  • A solid submodule to analyze and optimize solid structures of all kinds with the Finite Element Method. The implementations so far only cover linear behaviour, but with practically no limits on the complexity of the shape and topology of the domain under investigation.

Installation

This is optional, but we suggest you to create a dedicated virtual enviroment at all times to avoid conflicts with your other projects. Create a folder, open a command shell in that folder and use the following command

>>> python -m venv venv_name

Once the enviroment is created, activate it via typing

>>> .\venv_name\Scripts\activate

sigmaepsilon can be installed (either in a virtual enviroment or globally) from PyPI using pip on Python >= 3.6:

>>> pip install sigmaepsilon

Documentation

Refer to the docs for further details on installation and usage.

Testing

To run all tests, open up a console in the root directory of the project and type the following

>>> python -m unittest

Dependencies

We use Numba's JIT compiler to speed up heavy computations, and it relies on the C++ redistributable package. It is likely already installed on your system, but if it is not, you can download it from Microsoft's website under "Other Tools, Frameworks, and Redistributables".

must have

  • Numba, NumPy, SciPy, SymPy, awkward

strongly suggested

  • PyVista, Plotly, matplotlib, sectionproperties

optional

  • networkx

License

SigmaEpsilon is Copyright(C) 2022: Bence Balogh

All rights reserved.

This program is dual-licensed as follows:

(1) You may use SigmaEpsilon as free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.

In this case the program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License at http://www.gnu.org/licenses/gpl.txt or in the LICENSE file of this repository for more details.

(2) You may use SigmaEpsilon as part of a commercial software. In this case a proper agreement must be reached with the Authors based on a proper licensing contract.

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

sigmaepsilon-0.0.29.tar.gz (124.8 kB view details)

Uploaded Source

Built Distribution

sigmaepsilon-0.0.29-py3-none-any.whl (160.1 kB view details)

Uploaded Python 3

File details

Details for the file sigmaepsilon-0.0.29.tar.gz.

File metadata

  • Download URL: sigmaepsilon-0.0.29.tar.gz
  • Upload date:
  • Size: 124.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.10

File hashes

Hashes for sigmaepsilon-0.0.29.tar.gz
Algorithm Hash digest
SHA256 084a2e785ed656700340aa5c326da3261c755bcbbd570fefb1e45f1eece00b1f
MD5 477e1b5bde8eb163ceb60968aa8f7ffe
BLAKE2b-256 8989f3eeaa4be9d88f25a6f06cd15e2287123515a54d6fc4d4f9d8a77f3b68f4

See more details on using hashes here.

Provenance

File details

Details for the file sigmaepsilon-0.0.29-py3-none-any.whl.

File metadata

File hashes

Hashes for sigmaepsilon-0.0.29-py3-none-any.whl
Algorithm Hash digest
SHA256 98e255721547ffb7363de91e78b7293e8a566e8c5c1a4bfc04e7ce0ab99b3a17
MD5 b672b63a972d19fc495ef42222d5a1df
BLAKE2b-256 2d6cabaafbf2b1df31b508d319c624fdb0518aceaf89fab1e0f7732f5f8b69a3

See more details on using hashes here.

Provenance

Supported by

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