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
[email protected]

Xiaodong Zhuge, Researcher
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
[email protected]

Willem Jan Palenstijn, Researcher
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
[email protected]

Joost Batenburg, Professor
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
Leiden University, Leiden, The Netherlands
[email protected]

Ozan Öktem, Associate Professor
KTH, Royal Institute of Technology
[email protected]