# 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@uantwerpen.be
website: http://www.astra-toolbox.com/

Copyright: 2010-2016, iMinds-Vision Lab, University of Antwerp
           2014-2016, CWI, Amsterdam
           http://visielab.uantwerpen.be/ and http://www.cwi.nl/