TOMOMAK is an easy-to-use cross-platform framework for the multidimensional limited data tomography. The main features of the TOMOMAK framework are:
- Arbitrary number of dimensions.
- Support of different coordinate systems.
- Limited data treating: regularization or model restrictions.
- Possibility to combine different algorithms.
- Arbitrary detector geometry support.
- Algorithms for the synthetic data generation.
- Calculation of the reconstruction quality criteria.
- Hardware acceleration using GPU.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Usage of Anaconda is recommended. Use the following command in order to install required packages:
pip install <package name>
or if you use Anaconda:
conda install <package name>
Required packages:
- SciPy
- NumPy
- Matplotlib
- decorator
- Shapely (for 2D geometry).
- CuPy (for GPU acceleration).
- Mayavi (for 3D visualization).
- Trimesh (for 3D geometry, note that you should also have OpenSCAD or Blender installed)
- pyglet (for Trimesh visualization)
- Rtree (for ray casting in 3D geometry)
Copy repository to your computer.
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The best way to understand the framework is to use it. Start with the basic functionality example.
As soon as you are done switch to the other examples and documentation.
To generate API-doumentation in your terminal or Anaconda Prompt, go to doc folder in the downloaded tomomak archive and use pdoc:
pdoc --html --force ../tomomak
- Nikolai Bakharev - PhD, Researcher at Ioffe Institute, St.-Petersburg, Russian Federation
This project is licensed under the Revised BSD License - see the LICENSE.txt file for details
If you have any questions, proposals or you simply don't know, is it possible to use this framework in your study - don't hesitate to contact the author.
