/usr/lib/python3/dist-packages/pyfits/py3compat.py is in python3-pyfits 1:3.2-1build2.
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if sys.version_info[0] >= 3: # pragma: py3
# Stuff to do if Python 3
import builtins
import io
# Bring back the cmp() function
builtins.cmp = lambda a, b: (a > b) - (a < b)
# Make the decode_ascii utility function actually work
import pyfits.util
import numpy
def encode_ascii(s):
if isinstance(s, str):
return s.encode('ascii')
elif isinstance(s, numpy.ndarray) and \
issubclass(s.dtype.type, numpy.str_):
ns = numpy.char.encode(s, 'ascii').view(type(s))
if ns.dtype.itemsize != s.dtype.itemsize / 4:
ns = ns.astype((numpy.bytes_, s.dtype.itemsize / 4))
return ns
return s
pyfits.util.encode_ascii = encode_ascii
def decode_ascii(s):
if isinstance(s, bytes):
return s.decode('ascii')
elif (isinstance(s, numpy.ndarray) and
issubclass(s.dtype.type, numpy.bytes_)):
# np.char.encode/decode annoyingly don't preserve the type of the
# array, hence the view() call
# It also doesn't necessarily preserve widths of the strings,
# hence the astype()
if s.size == 0:
# Numpy apparently also has a bug that if a string array is
# empty calling np.char.decode on it returns an empty float64
# array wth
dt = s.dtype.str.replace('S', 'U')
ns = numpy.array([], dtype=dt).view(type(s))
else:
ns = numpy.char.decode(s, 'ascii').view(type(s))
if ns.dtype.itemsize / 4 != s.dtype.itemsize:
ns = ns.astype((numpy.str_, s.dtype.itemsize))
return ns
return s
pyfits.util.decode_ascii = decode_ascii
# See the docstring for pyfits.util.fileobj_open for why we need to replace
# this function
def fileobj_open(filename, mode):
return open(filename, mode, buffering=0)
pyfits.util.fileobj_open = fileobj_open
# Support the io.IOBase.readable/writable methods
from pyfits.util import isreadable as _isreadable
def isreadable(f):
if hasattr(f, 'readable'):
return f.readable()
return _isreadable(f)
pyfits.util.isreadable = isreadable
from pyfits.util import iswritable as _iswritable
def iswritable(f):
if hasattr(f, 'writable'):
return f.writable()
return _iswritable(f)
pyfits.util.iswritable = iswritable
# isfile needs to support the higher-level wrappers around FileIO
def isfile(f):
if isinstance(f, io.FileIO):
return True
elif hasattr(f, 'buffer'):
return isfile(f.buffer)
elif hasattr(f, 'raw'):
return isfile(f.raw)
return False
pyfits.util.isfile = isfile
# Here we monkey patch (yes, I know) numpy to fix a few numpy Python 3
# bugs. The only behavior that's modified is that bugs are fixed, so that
# should be OK.
# Fix chararrays; this is necessary in numpy 1.5.1 and below--hopefully
# should not be necessary later. See
# http://projects.scipy.org/numpy/ticket/1817
# TODO: Maybe do a version check on numpy for this? (Note: the fix for
# this hasn't been accepted in Numpy yet, so a version number check would
# not be helpful yet...)
import pyfits.file
_chararray = numpy.char.chararray
class chararray(_chararray):
def __getitem__(self, obj):
val = numpy.ndarray.__getitem__(self, obj)
if isinstance(val, numpy.character):
temp = val.rstrip()
if numpy.char._len(temp) == 0:
val = ''
else:
val = temp
return val
for m in [numpy.char, numpy.core.defchararray, numpy.core.records]:
m.chararray = chararray
# Fix recarrays with sub-array fields. See
# http://projects.scipy.org/numpy/ticket/1766
# TODO: Same as above, though the fix to this problem hasn't made it into
# any Numpy release yet either, so we'll have to hold off on a version
# check
def _fix_dtype(dtype):
"""
Numpy has a bug (in Python3 only) that causes a segfault when
accessing the data of arrays containing nested arrays. Specifically,
this happens if the shape of the subarray is not given as a tuple.
See http://projects.scipy.org/numpy/ticket/1766.
"""
if not hasattr(dtype, 'fields') or dtype.fields is None:
return dtype
formats = []
offsets = []
titles = []
for name in dtype.names:
field = dtype.fields[name]
shape = field[0].shape
if not isinstance(shape, tuple):
shape = (shape,)
formats.append((field[0].base, shape))
offsets.append(field[1])
# There seems to be no obvious way to extract the titles from
# a dtype, so this just searches for duplicate fields
title = None
for key, dup in list(dtype.fields.items()):
if key != name and dup == field:
title = key
break
titles.append(title)
return numpy.dtype({'names': dtype.names, 'formats': formats,
'offsets': offsets, 'titles': titles})
_recarray = numpy.recarray
class recarray(_recarray):
def __new__(subtype, shape, dtype=None, buf=None, offset=0,
strides=None, formats=None, names=None, titles=None,
byteorder=None, aligned=False, order='C'):
if dtype is not None:
dtype = _fix_dtype(dtype)
if 'order' in _recarray.__new__.__code__.co_varnames:
return _recarray.__new__(
subtype, shape, dtype, buf, offset, strides, formats,
names, titles, byteorder, aligned, order)
else:
return _recarray.__new__(
subtype, shape, dtype, buf, offset, strides, formats,
names, titles, byteorder, aligned)
numpy.recarray = numpy.core.records.recarray = recarray
# We also need to patch pyfits.file._File which can also be affected by the
# #1766 bug
old_File = pyfits.file._File
class _File(old_File):
def readarray(self, size=None, offset=0, dtype=numpy.uint8,
shape=None):
if isinstance(dtype, numpy.dtype):
dtype = _fix_dtype(dtype)
return old_File.readarray(self, size, offset, dtype, shape)
readarray.__doc__ = old_File.readarray.__doc__
pyfits.file._File = _File
# Replace pyfits.util.maketrans and translate with versions that work
# with Python 3 unicode strings
pyfits.util.maketrans = str.maketrans
def translate(s, table, deletechars):
if deletechars:
table = table.copy()
for c in deletechars:
table[ord(c)] = None
return s.translate(table)
pyfits.util.translate = translate
else:
# Stuff to do if not Python 3
# We want a bytes stand-in so we can do stuff like isinstance(..., bytes)
# and have it work correctly
import builtins
if not hasattr(__builtin__, 'bytes'):
builtins.bytes = str
import string
import pyfits.util
pyfits.util.maketrans = string.maketrans
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