toasty tile-healpix
¶
The tile-healpix
command transforms all-sky FITS images in the HEALPix
format into WWT’s FITS TOAST format.
Usage¶
toasty tile-healpix
[--galactic]
[--outdir DIR]
[--parallelism FACTOR] [-j FACTOR]
{FITS-PATH}
{TOAST-DEPTH}
The FITS-PATH
argument gives the filename of the input image, which should
be a single FITS file storing data in the HEALPix format.
The TOAST-DEPTH
argument specifies the resolution level of the TOAST
pixelization that will be generated. A depth of 0 means that the input will be
sampled onto a single 256×256 tile, a depth of 1 means that the input will be
sampled onto four tiles for a total resolution of 512×512, and so on. When
converting from HEALPix, the appropriate TOAST depth can be derived from the
HEALPix N_side
parameter as approximately:
depth = log2(N_side) - 6.2
One should typically round up to the next larger integer to err on the side of higher resolution, although the best policy will depend on the sampling of the input HEALPix map.
The --outdir DIR
option specifies where the output data should be written.
If unspecified, the data root will be the current directory.
The --galactic
option forces the tiling to assume that the input map is in
Galactic coordinates, even if the FITS headers do not specify that. This has
been observed in some data sets in the wild.
The --parallelism FACTOR
argument (or -j FACTOR
) specifies the level of
parallism to use. On operating systems that support parallel processing, the
default is to use all CPUs. To disable parallel processing, explicitly specify a
factor of 1.
Notes¶
This command requires that the healpy Python module is installed.
This command will create FITS files for the highest-resolution tile layer,
corresponding to the DEPTH
argument, and emit an index_rel.wtml
file
containing projection information and template metadata.
The WWT rendering engine can also display datasets in the hierarchical HiPS FITS format, which addresses about the same use case as TOAST. If a HiPS FITS dataset already exists, it is probably a wiser choice to use it rather than creating a new TOAST pyramid. However, TOAST provides noticeably better performance for the initial data display and avoiding positional shifts as the user zooms in.
Currently, parallel processing is only supported on the Linux operating system,
because fork()
-based multiprocessing is required. MacOS should support this,
but there is currently (as of Python 3.8) a bug preventing that.