Installation instructions¶
Windows, binary¶
Add the mex and tools subdirectories to your MATLAB path and/or the Python module to your Python path.
Linux, from source¶
Requirements: g++, boost, CUDA (driver+toolkit), Matlab and/or Python (2.7 or 3.x)
cd build/linux
./autogen.sh # when building a git version
./configure --with-cuda=/usr/local/cuda \
--with-matlab=/usr/local/MATLAB/R2012a \
--with-python
--prefix=/usr/local/astra
make
make install
Add /usr/local/astra/lib to your LD_LIBRARY_PATH. Add /usr/local/astra/matlab and its subdirectories (tools, mex) to your matlab path. Add /usr/local/astra/python to your PYTHONPATH.
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).
Linux, using conda for python¶
Requirements: conda python environment
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
Windows, from source using Visual Studio 2008¶
Requirements: Visual Studio 2008, boost, CUDA (driver+toolkit), matlab. Note that a .zip with all required (and precompiled) boost files is available from our website.
Set the environment variable MATLAB_ROOT to your matlab install location. Open astra_vc08.sln in Visual Studio. Select the appropriate solution configuration. (typically Release_CUDA|win32 or Release_CUDA|x64) Build the solution. Install by copying AstraCuda32.dll or AstraCuda64.dll from bin/ and all .mexw32 or .mexw64 files from bin/Release_CUDA or bin/Debug_CUDA and the entire matlab/tools directory to a directory to be added to your matlab path.
Linux, building conda packages¶
To build your own conda packages for the ASTRA toolbox, perform the following steps inside the conda environment:
cd python/conda/libastra
CUDA_ROOT=/path/to/cuda conda-build ./ # Build C++ library
cd ../
CUDA_ROOT=/path/to/cuda conda-build ./ # Build Python interface
The final step includes a test to check whether the build was successful. To be able to perform this test, conda should be able to find the ASTRA C++ library package of the second step. One way of accomplishing this is to temporarily add the conda build directory as a custom channel. To do this, the following steps can be used:
cd python/conda/libastra
CUDA_ROOT=/path/to/cuda conda-build ./ # Build C++ library
cd ../
CUDA_ROOT=/path/to/cuda conda-build \
-c file://[/path/to/conda_env]/conda-bld/ \
-c defaults --override-channels ./ # Build Python interface