def convert_fits_to_hdf(args=None):
""" Convert a FITS file to HDF5 in HDFITS format
An input and output directory must be specified, and all files with a matching
extension will be converted. Command line options set the compression algorithm
and other run-time settings.
"""
# Parse options and arguments
parser = argparse.ArgumentParser(description='Convert FITS files to HDF5 files in HDFITS format.')
parser.add_argument('-c', '--compression', dest='comp', type=str,
help='Data compression. Defaults to None, also lzf, bitshuffle, gzip')
parser.add_argument('-x', '--extension', dest='ext', type=str, default='fits',
help='File extension of FITS files. Defaults to .fits')
parser.add_argument('-v', '--verbosity', dest='verbosity', type=int, default=4,
help='verbosity level (default 0, up to 5)')
parser.add_argument('-s', '--scaleoffset', dest='scale_offset', default=None,
help='Add scale offset')
parser.add_argument('-S', '--shuffle', dest='shuffle', action='store_true', default=None,
help='Apply byte shuffle filter')
parser.add_argument('-t', '--pytables', dest='table_type', action='store_true', default=None,
help='Set output tables to be PyTables TABLE class, instead of HDFITES DATA_GROUP')
parser.add_argument('-C', '--checksum', dest='checksum', action='store_true', default=None,
help='Compute fletcher32 checksum on datasets.')
parser.add_argument('dir_in', help='input directory')
parser.add_argument('dir_out', help='output_directory')
args = parser.parse_args()
dir_in = args.dir_in
dir_out = args.dir_out
if not os.path.exists(dir_out):
print("Creating directory %s" % dir_out)
os.mkdir(dir_out)
# Form a list of keyword arguments to pass to HDF5 export
kwargs = {}
if args.comp is not None:
kwargs['compression'] = args.comp
if args.scale_offset is not None:
kwargs['scaleoffset'] = int(args.scale_offset)
if args.shuffle is not None:
kwargs['shuffle'] = args.shuffle
if args.checksum is not None:
kwargs['fletcher32'] = args.checksum
if args.table_type is not None:
kwargs['table_type'] = 'TABLE'
else:
kwargs['table_type'] = 'DATA_GROUP'
pp = PrintLog(verbosity=args.verbosity)
if args.verbosity == 0:
warnings.simplefilter("ignore")
pp.h1("FITS2HDF")
pp.pa("Input directory: %s" % dir_in)
pp.pa("Output directory: %s" % dir_out)
pp.pa("Dataset creation arguments:")
for key, val in kwargs.items():
pp.pa("%16s: %s" % (key, val))
# Create list of files to process
filelist = os.listdir(dir_in)
filelist = [fn for fn in filelist if fn.endswith(args.ext)]
t_start = time.time()
file_count = 0
for filename in filelist:
file_in = os.path.join(dir_in, filename)
file_out = os.path.join(dir_out, filename.split('.' + args.ext)[0] + '.h5')
a = IdiHdulist()
try:
pp.pp("\nReading %s" % file_in)
a = read_fits(file_in)
pp.pp("Creating %s" % file_out)
t1 = time.time()
export_hdf(a, file_out, **kwargs)
t2 = time.time()
pp.pp("Input filesize: %sB" % os.path.getsize(file_in))
pp.pp("Output filesize: %sB" % os.path.getsize(file_out))
compfact = float(os.path.getsize(file_in)) / float(os.path.getsize(file_out))
pp.pp("Compression: %2.2fx" % compfact)
pp.pp("Comp/write time: %2.2fs" % (t2 - t1))
file_count += 1
except IOError:
pp.err("ERROR: Cannot load %s" % file_in)
pp.h1("\nSUMMARY")
pp.pa("Files created: %i" % file_count)
pp.pa("Time taken: %2.2fs" % (time.time() - t_start))
def convert_hdf_to_fits(args=None):
""" Convert a HDF5 (in HDFITS format) to a FITS file
An input and output directory must be specified, and all files with a matching
extension will be converted. Command line options set the run-time settings.
"""
# Parse options and arguments
parser = argparse.ArgumentParser(description='Convert HDF5 in HDFITS format FITS files.')
parser.add_argument('-x', '--extension', dest='ext', type=str, default='h5',
help='File extension of HDFITS files. Defaults to .h5')
parser.add_argument('-v', '--verbosity', dest='verbosity', type=int, default=4,
help='verbosity level (default 0, up to 5)')
parser.add_argument('dir_in', help='input directory')
parser.add_argument('dir_out', help='output_directory')
args = parser.parse_args()
dir_in = args.dir_in
dir_out = args.dir_out
if not os.path.exists(dir_out):
print("Creating directory %s" % dir_out)
os.mkdir(dir_out)
# Form a list of keyword arguments to pass to HDF5 export
kwargs = {}
pp = PrintLog(verbosity=args.verbosity)
if args.verbosity == 0:
warnings.simplefilter("ignore")
pp.h1("HDF2FITS")
pp.pa("Input directory: %s" % dir_in)
pp.pa("Output directory: %s" % dir_out)
pp.pa("Dataset creation arguments:")
for key, val in kwargs.items():
pp.pa("%16s: %s" % (key, val))
# Create list of files to process
filelist = os.listdir(dir_in)
filelist = [fn for fn in filelist if fn.endswith(args.ext)]
t_start = time.time()
file_count = 0
for filename in filelist:
file_in = os.path.join(dir_in, filename)
file_out = os.path.join(dir_out, filename.split('.' + args.ext)[0] + '.fits')
a = IdiHdulist()
try:
pp.pp("\nReading %s" % file_in)
a = read_hdf(file_in)
pp.pp("Creating %s" % file_out)
t1 = time.time()
export_fits(a, file_out, **kwargs)
t2 = time.time()
pp.pp("Input filesize: %sB" % os.path.getsize(file_in))
pp.pp("Output filesize: %sB" % os.path.getsize(file_out))
compfact = float(os.path.getsize(file_in)) / float(os.path.getsize(file_out))
pp.pp("Compression: %2.2fx" % compfact)
pp.pp("Comp/write time: %2.2fs" % (t2 - t1))
file_count += 1
except IOError:
pp.err("ERROR: Cannot load %s" % file_in)
pp.h1("\nSUMMARY")
pp.pa("Files created: %i" % file_count)
pp.pa("Time taken: %2.2fs" % (time.time() - t_start))