The installation is done in two steps. The first involves installing all the python scripts, which is done with the command:
pip install mwa-vcstoolsOr git clone into the repo and run
python setup.py installor
python3 setup.py install --prefix="<install_dir>" --single-version-externally-managed --record=record.txtThe second step is to compile the beamformer which is much more difficult. All of the beamformer's dependancies must be taken into account as seen in this example cmake command:
cmake -DCMAKE_C_COMPILER=$CC -DCMAKE_CXX_COMPILER=$CXX -DCMAKE_CUDA_COMPILER=$CUDA_COMPILER \
-DCMAKE_INSTALL_PREFIX=${CMAKE_INSTALL_PREFIX} \
-DCMAKE_CUDA_FLAGS=${CUDA_FLAGS} \
-DCFITSIO_ROOT_DIR=${MAALI_CFITSIO_HOME} \
-DFFTW3_ROOT_DIR=${FFTW3_ROOT_DIR} \
-DFFTW3_INCLUDE_DIR=${FFTW_INCLUDE_DIR} \
-DPAL_ROOT_DIR=${PAL_ROOT} \
-DPSRFITS_UTILS_ROOT_DIR=${PSRFITS_UTILS_ROOT} \
..For this reason, we have created a docker image which is much easier to install and can be found here
You will have to make your own entry in vcstools/config.py for your supercomputer which we are happy to help with.
Documentation on how to process MWA VCS data can be found here
You can reference this repository using:
If you use the MWA beamformer, please give credit by citing: Ord et al. (2019)
If you used polarimetry, please give credit by citing: Xue et al. (2019)
If you used the inverse PFB, please give credit by citing: McSweeney et al. (2020)