def _get_fname_ftype_from_inputs(fileobj, **keywords):
"""
Get filename, file type, and file system
"""
fs='local'
try:
fname = fileobj.name
fobj = fileobj
except AttributeError:
if is_in_hdfs(fileobj):
fs='hdfs'
# make sure we expand all ~username and other variables
fname=ostools.expand_filename(fileobj)
fobj = fname
ftype=None
if 'type' in keywords:
ftype=keywords['type']
elif 'typ' in keywords:
ftype = keywords['typ']
if ftype is None:
ftype=get_ftype(fname)
ftype = ftype.lower()
return fname, fobj, ftype, fs
def _get_fname_ftype_from_inputs(fileobj, **keywords):
"""
Get filename, file type, and file system
"""
fs='local'
if isinstance(fileobj, file):
fname = fileobj.name
fobj = fileobj
elif isinstance(fileobj, (str,unicode)):
if is_in_hdfs(fileobj):
fs='hdfs'
# make sure we expand all ~username and other variables
fname=ostools.expand_filename(fileobj)
fobj = fname
else:
raise ValueError("Input must be a string or file object, or a "
"list thereof")
ftype=None
if 'type' in keywords:
ftype=keywords['type']
elif 'typ' in keywords:
ftype = keywords['typ']
if ftype is None:
ftype=get_ftype(fname)
ftype = ftype.lower()
return fname, fobj, ftype, fs
def _get_fname_ftype_from_inputs(fileobj, **keywords):
"""
Get filename, file type, and file system
"""
fs = 'local'
try:
fname = fileobj.name
fobj = fileobj
except AttributeError:
if is_in_hdfs(fileobj):
fs = 'hdfs'
# make sure we expand all ~username and other variables
fname = ostools.expand_filename(fileobj)
fobj = fname
ftype = None
if 'type' in keywords:
ftype = keywords['type']
elif 'typ' in keywords:
ftype = keywords['typ']
if ftype is None:
ftype = get_ftype(fname)
ftype = ftype.lower()
return fname, fobj, ftype, fs
def read_fits_pyfits(fileobj, **keywords):
import numpy
import pyfits
header = keywords.get('header', False)
rows=None
fields=None
columns=None
if 'verbose' in keywords:
del keywords['verbose']
if 'rows' in keywords:
rows=keywords['rows']
del keywords['rows']
if 'fields' in keywords:
fields=keywords['fields']
del keywords['fields']
if 'columns' in keywords:
columns=keywords['columns']
del keywords['columns']
if fields is None:
if columns is not None:
# allow columns to be synonymous with fields
fields=columns
if isinstance(fileobj,(str,unicode)):
fileobj=ostools.expand_filename(fileobj)
if 'ignore_missing_end' not in keywords:
# the ignore_missing_end=True is for the multitude
# of malformed FITS files out there
keywords['ignore_missing_end'] = True
if header == 'only':
return pyfits.getheader(fileobj, **keywords)
if header:
d,h = pyfits.getdata(fileobj, **keywords)
else:
d = pyfits.getdata(fileobj, **keywords)
view = keywords.get('view',numpy.ndarray)
if view is not None:
d = d.view(view)
# extract subsets of the data
if rows is not None:
d = d[rows]
if fields is not None:
d = numpy_util.extract_fields(d.view(numpy.ndarray), fields)
if header:
return d,h
else:
return d
