00mjk / vcstools-1

A suite of tools for processing MWA-VCS data

VCStools software tools

Installation

The installation is done in two steps. The first involves installing all the python scripts, which is done with the command:

pip install mwa-vcstools

Or git clone into the repo and run

python setup.py install

or

python3 setup.py install --prefix="<install_dir>" --single-version-externally-managed --record=record.txt

The 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.

Help

Documentation on how to process MWA VCS data can be found here and the developer documentation can be found here

Credit

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)