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# Laplace-Dirichlet Rule-Based (LDRB) algorithm for assigning myocardial fiber orientations
A software for assigning myocardial fiber orientations based on the Laplace Dirichlet Ruled-Based algorithm.
> Bayer, J.D., Blake, R.C., Plank, G. and Trayanova, N.A., 2012.
> A novel rule-based algorithm for assigning myocardial fiber orientation
>to computational heart models. Annals of biomedical engineering, 40(10),
pp.2243-2254.(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518842/)
```python
# Generate an example geometry using https://github.com/ComputationalPhysiology/cardiac_geometries
import cardiac_geometries # pip install cardiac-geometries
import ldrb
geo = cardiac_geometries.mesh.create_biv_ellipsoid(char_length=0.2)
# Decide on the angles you want to use
angles = dict(
alpha_endo_lv=30, # Fiber angle on the LV endocardium
alpha_epi_lv=-30, # Fiber angle on the LV epicardium
beta_endo_lv=0, # Sheet angle on the LV endocardium
beta_epi_lv=0, # Sheet angle on the LV epicardium
alpha_endo_sept=60, # Fiber angle on the Septum endocardium
alpha_epi_sept=-60, # Fiber angle on the Septum epicardium
beta_endo_sept=0, # Sheet angle on the Septum endocardium
beta_epi_sept=0, # Sheet angle on the Septum epicardium
alpha_endo_rv=80, # Fiber angle on the RV endocardium
alpha_epi_rv=-80, # Fiber angle on the RV epicardium
beta_endo_rv=0, # Sheet angle on the RV endocardium
beta_epi_rv=0, # Sheet angle on the RV epicardium
)
# Convert markers to correct format
markers = {
"base": geo.markers["BASE"][0],
"lv": geo.markers["ENDO_LV"][0],
"rv": geo.markers["ENDO_RV"][0],
"epi": geo.markers["EPI"][0],
}
# Choose space for the fiber fields
# This is a string on the form {family}_{degree}
fiber_space = "P_2"
# Compute the microstructure
fiber, sheet, sheet_normal = ldrb.dolfin_ldrb(
mesh=geo.mesh, fiber_space=fiber_space, ffun=geo.ffun, markers=markers, **angles
)
# Store files using a built in xdmf viewer that also works for functions
# defined in quadrature spaces
ldrb.fiber_to_xdmf(fiber, "fiber")
# And visualize it in Paraview
```
# Installation
## pip
In order to install the software you need to have
installed [FEniCS](https://fenicsproject.org) (versions older than 2016
are not supported)
The package can be installed with pip.
```
python -m pip install ldrb
```
or if you need the most recent version you can install the source
```
python -m pip install git+https://github.com/finsberg/ldrb.git
```
## Conda
`ldrb` is also available on `conda`
```
conda install -c conda-forge ldrb
```
## Docker
If you don't already have FEniCS installed you can use one of the provided [docker images](https://github.com/finsberg/ldrb/pkgs/container/ldrb), e.g
```
docker pull ghcr.io/finsberg/ldrb:latest
```
to pull the image and use the following command to start a container and sharing your current directory
```
docker run --rm -v $PWD:/home/shared -w /home/shared -it ghcr.io/finsberg/ldrb:latest
```
# Documentation
Documentation is hosted at http://finsberg.github.io/ldrb
# Getting started
Check out the [demos](http://finsberg.github.io/ldrb/demo_lv.html)
# License
`ldrb` is licensed under the GNU LGPL, version 3 or (at your option) any later version.
`ldrb` is Copyright (2011-2019) by the authors and Simula Research Laboratory.
# Contributors
Henrik Finsberg (henriknf@simula.no)
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