sigmaepsilon 0.0.25b0

High-Performance Computational Mechanics in Python.

SigmaEpsilon - High-Performance Computational Solid Mechanics in Python

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 (http://www.gnu.org/licenses/gpl.txt) 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.