Skip to main content

This is PYthon-based repository is for MECHanics of Tissue mechanics. The focus is on flexibility of adding new constitutive models and varying their parameters.

Project description

PyPI - Version Build Status Documentation Status Python versions GitHub

pyMechT

pyMechT is a Python package for simulating the mechanical response of soft biological tissues. The ethos of pyMechT is to create simplified virtual experimental setups, rather than finite element analyses. Thus, varying parameters and running simulations is much faster, making it feasible to perform Bayesian inference and Markov Chain Monte Carlo analyses. A short overview is provided in the video below.

pyMechT overview

Documentation

Find the full documentation at https://pymecht.readthedocs.io/en/latest/.

Structure

pyMechT is a collection of modules for:

  • MatModel: defining material models
  • SampleExperiment: simulating experiments, such as uniaxial extension, biaxial extension, and inflation-extension. Simulations can be either disp_controlled or force_controlled
  • ParamDict: a custom dictionary class of a datastructure called Param, which facilitates storing/varying/fitting parameters
  • ParamFitter: fitting parameters to experimental data
  • RandomParameters and MCMC: Bayesian inference by running Monte Carlo (MC) and Markov chain Monte Carlo (MCMC) simulations

Structure of pyMechT{{caption=Structure of pyMechT}

This package is developed and maintained by the Computational Biomechanics Research Group at the University of Glasgow.

Required dependencies are:

  • matplotlib
  • numpy
  • pandas
  • pyDOE
  • scipy
  • torch
  • sympy
  • tqdm

Installation

Step 1 (optional): Create a virtual environment

To create an environment in Anaconda, execute:

conda create -n pymecht python=3.9 ipykernel

Python3.9 is suggested, although any of the currently-supported versions of Python will also work.

To activate this virtual environment, execute:

conda activate pymecht

This is an optional, but recommended, step. There are other options for creating and managing environments (such as venv or virtualenv)

Step 2: Install via pip

User

pyMechT can be installed directly from PyPI via pip by using:

pip install pymecht
Developer To install as a devloper, it is recommended to fork from the repo and clone this fork locally.

Step 2.1 Fork from ankushaggarwal/pymecht

To fork a branch, head to the Github repository and click the fork button in the top right-hand corner.

Step 2.2 Clone the forked repo

To clone this repo locally, use the

git clone <repo-address>

where <repo-address> can be replaced by either the https or ssh addresses of the forked repo.

Step 2.3 Install developer version of pyMechT

To install a developer version of pyMechT, navigate to the locally cloned repo and execute:

pip install -e .

An editable version of pyMechT is now installed. All local changes to the cloned source code files will be reflected when pyMechT is imported.

Step 3: Check installation

Ensure that pyMechT has been installed by executing:

pip list

The package and version should be visible in the resulting list.

Contributing to pyMechT

See the contributing guidelines CONTRIBUTING.md for information on submitting issues and pull requests.

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

pymecht-1.1.3.tar.gz (512.4 kB view details)

Uploaded Source

Built Distribution

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

pymecht-1.1.3-py3-none-any.whl (30.7 kB view details)

Uploaded Python 3

File details

Details for the file pymecht-1.1.3.tar.gz.

File metadata

  • Download URL: pymecht-1.1.3.tar.gz
  • Upload date:
  • Size: 512.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for pymecht-1.1.3.tar.gz
Algorithm Hash digest
SHA256 66a6a8b2ffcef4719190cf6f3f3295f38f10970441b6acfe02eb46e007b1343b
MD5 e4f72e0d5901328cfc3b7b3072eb966e
BLAKE2b-256 fb9c723290c6f20d61c773cd42f35abdee5b60458c3f64ffc7bc13256aac1851

See more details on using hashes here.

File details

Details for the file pymecht-1.1.3-py3-none-any.whl.

File metadata

  • Download URL: pymecht-1.1.3-py3-none-any.whl
  • Upload date:
  • Size: 30.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for pymecht-1.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 843e02e0fe9b2886f846589ceeee463e2fdb35740c1b6c98f441a7ca8ec3bc22
MD5 e3102f270c40776467dfa8e35e4b61f4
BLAKE2b-256 0deea4b85ee482909633342a7ef55db8c044d3161912fc68c7be02afed64167c

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