Functional blocks

FHD is designed around a set of mathematical building blocks. These blocks can then be combined together in different ways to perform many different tasks, from simulating visibilities, to calibrating data, to deconvolving sources, to cosmology precision uvf and image-frequency cubes (12 sets). In the current implementation all of the blocks are implemented in FHD (IDL) and the most important for cosmology applications have been ported to pyFHD (python). All of them can be used in cluster and cloud computing environments (thought python is easier), and the IDL can be freely called from python to enable mixing of IDL and python operational blocks. In this section we will concentrate on high level descriptions of the major functional blocks. Please see the GitHub pages for full documentation and tutorials, including many smaller functional blocks not detailed here.