pyMechT is a Python package for simulating the mechanical response of soft biological tissues. The focus is on flexibility of defining models (referred to as MatModels). The ethos of pyMechT is to create simplified virtual experimental setups. That is, a sample is created of which there are the following options:
- Uniaxial extension;
- Biaxial extension; and
- Inflation-extension.
The MatModel is applied to the sample, such that the parameters encompass both the material parameters and those which define the corresponding sample setup (an example being the dimensions of the specimen). Finally, the samples can be simulated in either displacement-controlled or force-controlled loading to allow the use of Bayesian inference methods.
Required dependencies are:
- matplotlib
- numpy
- pandas
- pyDOE
- scipy
- torch
- sympy
- tqdm
To create an environment in Anaconda, execute:
conda create -n pymecht
To activate this virtual environment, execute:
conda activate pymecht
This is an option, but recommended step. There are other options for create and managing environments (such as venv or virtualenv)
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.To fork a branch, head to the Github repository and click the fork button in the top right-hand corner.
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.
To install a developer version of pyMechT, navigate to the locally cloned repo and execute:
python setup.py develop
An editable version of pyMechT is now installed. All local changes to the cloned source code files will be reflected when pyMechT is imported.
Ensure that pyMechT has been installed by executing:
pip list
The package and version should be visible in the resulting list.
Find the full documentation at https://pymecht.readthedocs.io/en/latest/.
To contribute to the pyMechT framework, install pyMechT using the developer options. All changes should be made to your forked repo. If there is a new feature or bug fix, raise a pull request. In the case that an additional feature is added, a corresponding example and test should be written in the respective python scripts.