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# The ASTRA Toolbox
The ASTRA Toolbox is a MATLAB and Python toolbox of high-performance GPU primitives for 2D and 3D tomography.
We support 2D parallel and fan beam geometries, and 3D parallel and cone beam. All of them have highly flexible source/detector positioning.
A large number of 2D and 3D algorithms are available, including FBP, SIRT, SART, CGLS.
The basic forward and backward projection operations are GPU-accelerated, and directly callable from MATLAB and Python to enable building new algorithms.
## Documentation / samples
See the MATLAB and Python code samples in samples/ and on http://www.astra-toolbox.com/ .
## Installation instructions
### Windows, binary
Add the mex and tools subdirectories to your MATLAB path, or copy the Python
astra module to your Python site-packages directory. We require the Microsoft
Visual Studio 2015 redistributable package. If this is not already installed on
your system, it is included as vc_redist.x64.exe in the ASTRA zip file.
### Linux/Windows, using conda for python
Requirements: [conda](http://conda.pydata.org/) python environment, with 64 bit Python 2.7, 3.5 or 3.6.
There are packages available for the ASTRA Toolbox in the astra-toolbox
channel for the conda package manager. To use these, run the following
inside a conda environment.
```
conda install -c astra-toolbox astra-toolbox
```
### Linux, from source
#### For Matlab
Requirements: g++, boost, CUDA (5.5 or higher), Matlab (R2012a or higher)
```
cd build/linux
./autogen.sh # when building a git version
./configure --with-cuda=/usr/local/cuda \
--with-matlab=/usr/local/MATLAB/R2012a \
--prefix=$HOME/astra \
--with-install-type=module
make
make install
```
Add $HOME/astra/matlab and its subdirectories (tools, mex) to your matlab path.
If you want to build the Octave interface instead of the Matlab interface,
specify --enable-octave instead of --with-matlab=... . The Octave files
will be installed into $HOME/astra/octave .
NB: Each matlab version only supports a specific range of g++ versions.
Despite this, if you have a newer g++ and if you get errors related to missing
GLIBCXX_3.4.xx symbols, it is often possible to work around this requirement
by deleting the version of libstdc++ supplied by matlab in
MATLAB_PATH/bin/glnx86 or MATLAB_PATH/bin/glnxa64 (at your own risk),
or setting LD_PRELOAD=/usr/lib64/libstdc++.so.6 (or similar) when starting
matlab.
#### For Python
Requirements: g++, boost, CUDA (5.5 or higher), Python (2.7 or 3.x)
```
cd build/linux
./autogen.sh # when building a git version
./configure --with-cuda=/usr/local/cuda \
--with-python \
--with-install-type=module
make
make install
```
This will install Astra into your current Python environment.
### macOS, from source
Use the Homebrew package manager to install boost, libtool, autoconf, automake.
```
cd build/linux
./autogen.sh
CPPFLAGS="-I/usr/local/include" NVCCFLAGS="-I/usr/local/include" ./configure \
--with-cuda=/usr/local/cuda \
--with-matlab=/Applications/MATLAB_R2016b.app \
--prefix=$HOME/astra \
--with-install-type=module
make
make install
```
### Windows, from source using Visual Studio 2015
Requirements: Visual Studio 2015 (full or community), boost (recent), CUDA 8.0,
Matlab (R2012a or higher) and/or WinPython 2.7/3.x.
Using the Visual Studio IDE:
Set the environment variable MATLAB_ROOT to your matlab install location.
Copy boost headers to lib\include\boost, and boost libraries to lib\x64.
Open astra_vc14.sln in Visual Studio.
Select the appropriate solution configuration (typically Release_CUDA|x64).
Build the solution.
Install by copying AstraCuda64.dll and all .mexw64 files from
bin\x64\Release_CUDA and the entire matlab/tools directory to a directory
to be added to your matlab path.
Using .bat scripts in build\msvc:
Edit build_env.bat and set up the correct directories.
Run build_setup.bat to automatically copy the boost headers and libraries.
For matlab: Run build_matlab.bat. The .dll and .mexw64 files will be in bin\x64\Release_Cuda.
For python 2.7/3.5: Run build_python27.bat or build_python35.bat. Astra will be directly installed into site-packages.
## Testing your installation
To perform a (very) basic test of your ASTRA installation in Python, you can
run the following Python command.
```
import astra
astra.test()
```
To test your ASTRA installation in Matlab, the equivalent command is:
```
astra_test
```
## References
If you use the ASTRA Toolbox for your research, we would appreciate it if you would refer to the following papers:
W. van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, K. J. Batenburg, and J. Sijbers, “Fast and Flexible X-ray Tomography Using the ASTRA Toolbox”, Optics Express, 24(22), 25129-25147, (2016), http://dx.doi.org/10.1364/OE.24.025129
W. van Aarle, W. J. Palenstijn, J. De Beenhouwer, T. Altantzis, S. Bals, K. J. Batenburg, and J. Sijbers, “The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography”, Ultramicroscopy, 157, 35–47, (2015), http://dx.doi.org/10.1016/j.ultramic.2015.05.002
Additionally, if you use parallel beam GPU code, we would appreciate it if you would refer to the following paper:
W. J. Palenstijn, K J. Batenburg, and J. Sijbers, "Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)", Journal of Structural Biology, vol. 176, issue 2, pp. 250-253, 2011, http://dx.doi.org/10.1016/j.jsb.2011.07.017
## License
The ASTRA Toolbox is open source under the GPLv3 license.
## Contact
email: astra@astra-toolbox.com
website: http://www.astra-toolbox.com/
Copyright: 2010-2018, iMinds-Vision Lab, University of Antwerp
2014-2018, CWI, Amsterdam
http://visielab.uantwerpen.be/ and http://www.cwi.nl/
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