Skip to content

Commit

Permalink
Moved the location of second figure in paper.md
Browse files Browse the repository at this point in the history
  • Loading branch information
ankushaggarwal committed Sep 23, 2024
1 parent 2d0c85c commit f0b2060
Showing 1 changed file with 2 additions and 2 deletions.
4 changes: 2 additions & 2 deletions joss-paper/paper.md
Original file line number Diff line number Diff line change
Expand Up @@ -70,6 +70,8 @@ While several finite element analysis packages are available for performing biom

# Structure

![Structure of `pyMechT` \label{fig:overview}](drawing-1.svg){height="1 inch"}

The package is implemented in Python using an object-oriented structure. The package builds upon widely-used Python libraries: NumPy, SciPy, Pandas, Matplotlib, and PyTorch. `pyMechT` consists of four main modules (see Figure \ref{fig:overview}): 1) `MatModel` for defining constitutive models for materials, 2) `SampleExperiment` for simulating ex-vivo uniaxial/biaxial/inflation-extension experiments, 3) `ParamFitter` for performing parameter estimation based on experimental data, and 4) `MCMC`/`RandomParameters` for performing Bayesian inference using Monte Carlo (MC) or Markov Chain Monte Carlo (MCMC) simulations. Currently, there are eighteen material models implemented in `MatModel`, including fourteen analytical hyperelastic models, two data-based hyperelastic models, and one structural model. In addition, an arbitrary hyperelastic model is also implemented, where a user-defined form of the free energy functional is automatically implemented based on symbolic differentiation. Below is the list of the material models available to-date:

- ‘NH’: Neo-Hookean model
Expand All @@ -91,8 +93,6 @@ The package is implemented in Python using an object-oriented structure. The pac
- ‘StructModel’: A structural model with fiber distribution
- ‘ARB’: Arbitrary model with user-defined strain energy density function

![Structure of `pyMechT` \label{fig:overview}](drawing-1.svg){height="1 inch"}

A particular focus is on parameters, for which a custom dictionary has been implemented named `ParamDict`. This dictionary facilitates handling large numbers of parameters via string-based identifiers ("Keys"), and stores lower/upper bounds, fixed/variable flags, in addition to the current parameter values. The dictionary can also be saved/read as csv files. An example set of parameters is shown in Table \ref{table:params} below.


Expand Down

0 comments on commit f0b2060

Please sign in to comment.