This repository contains the code for the article "High-level algorithm prototyping: an example extending the TVR-DART algorithm" by A. Ringh, X. Zhuge, W. J. Palenstijn, K. J. Batenburg, and O. Öktem.
The code contains the following
- Files containing the implementation of the relevant operators and functionals.
- A script running the TVR-DART algorithm. All figures in the article is from this script.
- Code from odl which contains minor modifications compared to commit 32842320a (which is essentially release 0.6.0, when it comes to changes in these parts of the code). These are default_functionals.py, steplen.py, and tensor_ops.py. The modifications are marked in the code
- A script running the DART algorithm.
- A test phantom.
Clone the repository. Then, using miniconda run the following commands to set up a new environment (essentially follow the odl installation instructions)
- $ conda create -c odlgroup -n my_env python=3.5 odl=0.6.0 matplotlib pytest scikit-image spyder
- $ source activate my_env
- $ conda install -c astra-toolbox astra-toolbox
After this, the scripts can be run using, e.g., spyder.
Axel Ringh, PhD student
KTH Royal Institute of Technology, Stockholm, Sweden
aringh@kth.se
Xiaodong Zhuge, Researcher
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
x.zhuge@cwi.nl
Willem Jan Palenstijn, Researcher
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
willem.jan.palenstijn@cwi.nl
Joost Batenburg, Professor
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
Leiden University, Leiden, The Netherlands
joost.batenburg@cwi.nl
Ozan Öktem, Associate Professor
KTH, Royal Institute of Technology
ozan@kth.se