Metadata-Version: 2.1
Name: gratopy
Version: 0.1.0
Summary: Gratopy - Graz accelerated tomographic projections for Python
Home-page: https://github.com/kbredies/gratopy
Author: Kristian Bredies, Richard Huber
Author-email: kristian.bredies@uni-graz.at
License: GPLv3
Project-URL: Documentation, https://gratopy.readthedocs.io/
Keywords: Radon transform,fanbeam transform,pixel-driven projection methods,computed tomography,image reconstruction,pyopencl
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Environment :: GPU
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE


[![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.5221442.svg)](https://doi.org/10.5281/zenodo.5221442)
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The gratopy (**Gr**az **a**ccelerated **to**mographic projections for **Py**thon) toolbox is a Python3 software package for the efficient and high-quality computation of Radon transforms, fanbeam transforms as well as the associated backprojections. The included operators are based on pixel-driven projection methods which were shown to possess [favorable approximation properties](https://epubs.siam.org/doi/abs/10.1137/20M1326635). The toolbox offers a powerful parallel OpenCL/GPU implementation which admits high execution speed and allows for seamless integration into [PyOpenCL](https://documen.tician.de/pyopencl/). Gratopy can efficiently be combined with other PyOpenCL code and is well-suited for the development of iterative tomographic reconstruction approaches, in particular, for those involving optimization algorithms.

## Highlights
* Easy-to-use tomographic projection toolbox.
* High-quality 2D projection operators.
* Fast projection due to custom OpenCL/GPU implementation.
* Seamless integration into PyOpenCL.
* Basic iterative reconstruction schemes included (Landweber, CG, total variation).
* Comprehensive documentation, tests and example code.

See the [documentation](https://gratopy.readthedocs.io/) and the project's [GitHub page](https://github.com/kbredies/gratopy) for installation, usage, updates and further information.


