Software package for processing astronomical photometric and spectroscopic Hierarchical Semi-Sparse data within HDF5. Can be extended to any kind of multidimensional data combination and information retrieval.
The whole framework and its usage are described in detail in the Astronomy&Computing article, while the parallel version is described in this IEEE Xplore article.
- Installing dependencies
apt-get update
apt-get install -y python3-pip libbz2-dev libsm6 libfontconfig1 libxrender1 libopenmpi-dev ffmpeg libsm6 libxext6
- Download h5py and hdf5 into ext_lib folder within the SDSSCube git folder.
mkdir h5py && cd h5py && git clone https://github.com/h5py/h5py.git .
- Latest tar release of HDF5 from here: https://www.hdfgroup.org/downloads/hdf5/source-code/.
- Build & Install HDF5 parallel
./configure --enable-build-mode=debug --enable-parallel --enable-codestack
make -j8
make install
- Build & Install h5py
export CC=mpicc
export HDF5_MPI="ON"
export HDF5_DIR=~/SDSSCube/ext_lib/hdf5-1.12.1/
export LD_LIBRARY_PATH=~/SDSSCube/ext_lib/hdf5-1.12.1/hdf5/lib:$LD_LIBRARY_PATH
python setup_configure.py --mpi
pip uninstall h5py
python setup.py install
- Download code
mkdir SDSSCube
cd SDSSCube
git clone https://github.com/nadvornikjiri/HiSS-Cube.git .
4.Create virtual environment
pip3 install virtualenv
python3 -m virtualenv venv
source venv/bin/activate
pip3 install -r requirements.txt
Download the "data.tar.gz" from Zenodo HiSS Cube and extract the contentse ìnside the git repository. The "data" folder should afterwards contain "galaxy_small", "images", "spectra", etc. All of the tests in the scripts/tests folder will pass afterwards and the Ipython notebook pre-set paths will work as well.
- Run the IPython notebook
jupyterlab
- Open the SDSS Cube.ipynb file.
- Run all of the cells.
- The output HiSS-Cube file is produced in the last cell at the specified output path, default is results/SDSS_Cube.h5.
More information about the notebooks is documented in the notebooks/Readme file.