Skip to main content

Scientific computing utilities combining FEM, ANN and tooling

Project description

Davout

Repository to store my workhorses and research-themed park. Github link to the repository and source files: https://github.com/Matheus-Janczkowski/Davout

  1. Link to the booklet on installation of a miscelaneous of software: https://www.overleaf.com/read/wbxhncmtnmkm#0eb73b

  2. Link to the booklet on python programming: https://www.overleaf.com/read/hcmfzzsrhndj#00fdb1

  3. Link to the booklet on writing in LaTeX: https://www.overleaf.com/read/sdrvfrpdjhft#66d6f9

  4. Link for the presentation template: https://www.overleaf.com/read/sbgxdphxswmm#6d7d64

Citation

https://doi.org/10.5281/zenodo.18806245

What does Davout do?

Workhorse for a research project that encompasses finite element analy- sis, machine learning, and multiscale analysis. Additionally, a set of tools is provided.

This package contains extensive implementation of hyperelastic problems in large strains using FEniCS and GMSH for mesh generation. A consistent and general purpose implementation of ANN models using tensorflow is al- so available. 

This suite performs:

  1. Geometry and mesh generation
  2. Finite element analysis
  3. ANN models definition and training
  4. Post-processing automation using ParaView
  5. Generation of figures, collages, and slides using own graphical tools
  6. LaTeX writing and formating using an ensemble of commands

Installation using pip

pip install Davout

Philosophy and aims

Davout aims to be a unified software to accompany researchers in compu- tational mechanics. Davout sits on a profound love for python and open software.

Davout stands on the shoulders of other massively mighty python packages, such as FEniCS, TensorFlow, GMSH, ParaView, and matplotlib.

Installation using installer file

Download the zip file, unzip it and move it to a suitable directory. Open the Davout folder, where setup.py is located. Open this path in terminal (using a virtual environment) and run the following command

python davout_installer.py

Installation using command

Download the repository, unzip the file, put it in a suitable place for you. Activate a python virtual environment (follow instruction in the booklet 1. to create a virtual environment if you don't have one), go into the directory where the files are located through the virtual environment terminal. Then, type in terminal (instead of python you might need to explicitely type in the version, like python3):

python setup.py bdist_wheel sdist

pip install .

To test the installation:

python

import Davout

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

davout-0.1.0.dev115.tar.gz (752.5 kB view details)

Uploaded Source

Built Distribution

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

davout-0.1.0.dev115-py3-none-any.whl (889.3 kB view details)

Uploaded Python 3

File details

Details for the file davout-0.1.0.dev115.tar.gz.

File metadata

  • Download URL: davout-0.1.0.dev115.tar.gz
  • Upload date:
  • Size: 752.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for davout-0.1.0.dev115.tar.gz
Algorithm Hash digest
SHA256 b855e2fedec9374b65a91822eabea2c336591765c2671fa8c28d1d3677ac7f1c
MD5 10c45bc06b110f0686e83b59cdc17a7f
BLAKE2b-256 f6bcb282564ba7f0574760277760592c5be6a621ddeb1537334af3c91fa37e2c

See more details on using hashes here.

File details

Details for the file davout-0.1.0.dev115-py3-none-any.whl.

File metadata

  • Download URL: davout-0.1.0.dev115-py3-none-any.whl
  • Upload date:
  • Size: 889.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for davout-0.1.0.dev115-py3-none-any.whl
Algorithm Hash digest
SHA256 8e1654ec5e1edb1d419fa88fe770482c88a513fb2d0c3f1b42e9056905b40a80
MD5 f8113b9eba3dd8495d2fa839e97dbc53
BLAKE2b-256 6e878a0ea6fcd0fbdd03c722c05ee54a270a3f50b87401f5407c47f8206349e8

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