Reading FITS Files
Introduction
Most of the numerical SDSS-III data is stored in the form of FITS files. These files can contain both images and binary data tables in a well-defined format. FITS files can be read and written with many programming languages, but the most common ones used by SDSS-III are IDL and Python.
IDL
The Goddard utilities contain
tools for reading and writing FITS files. The most commonly used functions are
mrdfits
and mwrfits
.
The Goddard utilities are included in the idlutils package,
which also contains additional programs for manipulating FITS files.
Python
The PyFITS package handles the reading and writing of FITS files in Python. Version 2.4.0 or later is strongly recommended, since this version now correctly reads and writes FITS checksum headers.
Another package is fitsio
, developed by
Erin Sheldon, which is a Python wrapper on the
CFITSIO library.
It allows direct access to the columns of a FITS binary table
which can be useful for reading large fits files, as detailed
below. This package
is available for download
here.
Large FITS Files
FITS files larger than about 2 GB can be more challenging to read.
One such file is the
spAll
file. The simplest method for reading
large FITS files is to download the fitsio
Python
module described above. The module can read only selected columns from the
FITS file:
import fitsio columns = ['PLATE', 'MJD', 'FIBERID', 'Z', 'ZWARNING', 'Z_ERR'] d = fitsio.read('spAll-v5_5_12.fits', columns=columns)
The PyFITS module has more stringent hardware requirements as it must read
the whole file in order to use it. On a 64-bit machine with > 4 GB
of memory, it is possible to use the memmap
option:
import pyfits fx = pyfits.open('spAll-v5_5_12.fits', memmap=True) d = fx[1].data
In IDL, the routine
hogg_mrdfits
is available as part of the idlutils package.
This routine is similar to fitsio
, in that one can specify a
subset of columns to read. It avoids memory overload by reading only a subset of the rows
of a FITS file, extracting the columns, then moving on to the next subset of
rows.