def test_different_keyword_values(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['C'] = 4
diff = HeaderDiff(ha, hb)
assert not diff.identical
assert diff.diff_keyword_values == {'C': [(3, 4)]}
def test_ignore_blank_cards(self):
"""Test for #152--ignore blank cards."""
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = Header([('A', 1), ('', ''), ('B', 2), ('', ''), ('C', 3)])
hc = ha.copy()
hc.append()
hc.append()
# We now have a header with interleaved blanks, and a header with end
# blanks, both of which should ignore the blanks
assert_true(HeaderDiff(ha, hb).identical)
assert_true(HeaderDiff(ha, hc).identical)
assert_true(HeaderDiff(hb, hc).identical)
assert_false(HeaderDiff(ha, hb, ignore_blank_cards=False).identical)
assert_false(HeaderDiff(ha, hc, ignore_blank_cards=False).identical)
# Both hb and hc have the same number of blank cards; since order is
# currently ignored, these should still be identical even if blank
# cards are not ignored
assert_true(HeaderDiff(hb, hc, ignore_blank_cards=False).identical)
hc.append()
# But now there are different numbers of blanks, so they should not be
# ignored:
assert_false(HeaderDiff(hb, hc, ignore_blank_cards=False).identical)
def test_different_keyword_values(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['C'] = 4
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'C': [(3, 4)]})
def test_different_keyword_comments(self):
ha = Header([('A', 1), ('B', 2), ('C', 3, 'comment 1')])
hb = ha.copy()
hb.comments['C'] = 'comment 2'
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_comments,
{'C': [('comment 1', 'comment 2')]})
def test_different_keyword_values_with_duplicate(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
ha.append(('C', 4))
hb.append(('C', 5))
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'C': [None, (4, 5)]})
def test_different_keywords(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['C'] = 4
hb['D'] = (5, 'Comment')
ha['E'] = (6, 'Comment')
ha['F'] = (7, 'Comment')
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keywords, (['E', 'F'], ['D']))
def test_different_keyword_count(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
del hb['B']
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_count, (3, 2))
# But make sure the common keywords are at least correct
assert_equal(diff.common_keywords, ['A', 'C'])
def test_different_keyword_count(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
del hb['B']
diff = HeaderDiff(ha, hb)
assert not diff.identical
assert diff.diff_keyword_count == (3, 2)
# But make sure the common keywords are at least correct
assert diff.common_keywords == ['A', 'C']
def test_floating_point_tolerance(self):
ha = Header([('A', 1), ('B', 2.00001), ('C', 3.000001)])
hb = ha.copy()
hb['B'] = 2.00002
hb['C'] = 3.000002
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values,
{'B': [(2.00001, 2.00002)], 'C': [(3.000001, 3.000002)]})
diff = HeaderDiff(ha, hb, tolerance=1e-6)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'B': [(2.00001, 2.00002)]})
def test_asymmetric_duplicate_keywords(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
ha.append(('A', 2, 'comment 1'))
ha.append(('A', 3, 'comment 2'))
hb.append(('B', 4, 'comment 3'))
hb.append(('C', 5, 'comment 4'))
diff = HeaderDiff(ha, hb)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {})
assert_equal(diff.diff_duplicate_keywords,
{'A': (3, 1), 'B': (1, 2), 'C': (1, 2)})
def test_ignore_keyword_values(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['B'] = 4
hb['C'] = 5
diff = HeaderDiff(ha, hb, ignore_keywords=['*'])
assert diff.identical
diff = HeaderDiff(ha, hb, ignore_keywords=['B'])
assert not diff.identical
assert diff.diff_keyword_values == {'C': [(3, 5)]}
report = diff.report()
assert 'Keyword B has different values' not in report
assert 'Keyword C has different values' in report
# Test case-insensitivity
diff = HeaderDiff(ha, hb, ignore_keywords=['b'])
assert not diff.identical
assert diff.diff_keyword_values == {'C': [(3, 5)]}
def test_ignore_keyword_values(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['B'] = 4
hb['C'] = 5
diff = HeaderDiff(ha, hb, ignore_keywords=['*'])
assert_true(diff.identical)
diff = HeaderDiff(ha, hb, ignore_keywords=['B'])
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'C': [(3, 5)]})
report = diff.report()
assert_true('Keyword B has different values' not in report)
assert_true('Keyword C has different values' in report)
# Test case-insensitivity
diff = HeaderDiff(ha, hb, ignore_keywords=['b'])
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'C': [(3, 5)]})
def test_ignore_blanks(self):
pyfits.STRIP_HEADER_WHITESPACE = False
try:
ha = Header([('A', 1), ('B', 2), ('C', 'A ')])
hb = ha.copy()
hb['C'] = 'A'
assert_not_equal(ha['C'], hb['C'])
diff = HeaderDiff(ha, hb)
# Trailing blanks are ignored by default
assert_true(diff.identical)
assert_equal(diff.diff_keyword_values, {})
# Don't ignore blanks
diff = HeaderDiff(ha, hb, ignore_blanks=False)
assert_false(diff.identical)
assert_equal(diff.diff_keyword_values, {'C': [('A ', 'A')]})
finally:
pyfits.STRIP_HEADER_WHITESPACE = True
def test_ignore_keyword_comments(self):
ha = Header([('A', 1, 'A'), ('B', 2, 'B'), ('C', 3, 'C')])
hb = ha.copy()
hb.comments['B'] = 'D'
hb.comments['C'] = 'E'
diff = HeaderDiff(ha, hb, ignore_comments=['*'])
assert diff.identical
diff = HeaderDiff(ha, hb, ignore_comments=['B'])
assert not diff.identical
assert diff.diff_keyword_comments == {'C': [('C', 'E')]}
report = diff.report()
assert 'Keyword B has different comments' not in report
assert 'Keyword C has different comments' in report
# Test case-insensitivity
diff = HeaderDiff(ha, hb, ignore_comments=['b'])
assert not diff.identical
assert diff.diff_keyword_comments == {'C': [('C', 'E')]}
def test_ignore_keyword_comments(self):
ha = Header([('A', 1, 'A'), ('B', 2, 'B'), ('C', 3, 'C')])
hb = ha.copy()
hb.comments['B'] = 'D'
hb.comments['C'] = 'E'
diff = HeaderDiff(ha, hb, ignore_comments=['*'])
assert_true(diff.identical)
diff = HeaderDiff(ha, hb, ignore_comments=['B'])
assert_false(diff.identical)
assert_equal(diff.diff_keyword_comments, {'C': [('C', 'E')]})
report = diff.report()
assert_true('Keyword B has different comments' not in report)
assert_true('Keyword C has different comments' in report)
# Test case-insensitivity
diff = HeaderDiff(ha, hb, ignore_comments=['b'])
assert_false(diff.identical)
assert_equal(diff.diff_keyword_comments, {'C': [('C', 'E')]})
def test_ignore_blanks(self):
fits.STRIP_HEADER_WHITESPACE = False
try:
ha = Header([('A', 1), ('B', 2), ('C', 'A ')])
hb = ha.copy()
hb['C'] = 'A'
assert ha['C'] != hb['C']
diff = HeaderDiff(ha, hb)
# Trailing blanks are ignored by default
assert diff.identical
assert diff.diff_keyword_values == {}
# Don't ignore blanks
diff = HeaderDiff(ha, hb, ignore_blanks=False)
assert not diff.identical
assert diff.diff_keyword_values == {'C': [('A ', 'A')]}
finally:
fits.STRIP_HEADER_WHITESPACE = True
def test_identical_headers(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
assert_true(HeaderDiff(ha, hb).identical)
def load(cls, datafile, cdfile=None, hfile=None, replace=False,
header=None):
"""
Create a table from the input ASCII files. The input is from up to
three separate files, one containing column definitions, one containing
header parameters, and one containing column data.
The column definition and header parameters files are not required.
When absent the column definitions and/or header parameters are taken
from the header object given in the header argument; otherwise sensible
defaults are inferred (though this mode is not recommended).
Parameters
----------
datafile : file path, file object or file-like object
Input data file containing the table data in ASCII format.
cdfile : file path, file object, file-like object, optional
Input column definition file containing the names,
formats, display formats, physical units, multidimensional
array dimensions, undefined values, scale factors, and
offsets associated with the columns in the table. If
`None`, the column definitions are taken from the current
values in this object.
hfile : file path, file object, file-like object, optional
Input parameter definition file containing the header
parameter definitions to be associated with the table. If
`None`, the header parameter definitions are taken from
the current values in this objects header.
replace : bool
When `True`, indicates that the entire header should be
replaced with the contents of the ASCII file instead of
just updating the current header.
header : Header object
When the cdfile and hfile are missing, use this Header object in
the creation of the new table and HDU. Otherwise this Header
supercedes the keywords from hfile, which is only used to update
values not present in this Header, unless replace=True in which
this Header's values are completely replaced with the values from
hfile.
Notes
-----
The primary use for the `load` method is to allow the input of ASCII
data that was edited in a standard text editor of the table data and
parameters. The `dump` method can be used to create the initial ASCII
files.
"""
# Process the parameter file
if header is None:
header = Header()
if hfile:
if replace:
header = Header.fromtextfile(hfile)
else:
header.extend(Header.fromtextfile(hfile), update=True,
update_first=True)
coldefs = None
# Process the column definitions file
if cdfile:
coldefs = cls._load_coldefs(cdfile)
# Process the data file
data = cls._load_data(datafile, coldefs)
if coldefs is None:
coldefs = ColDefs(data)
# Create a new HDU using the supplied header and data
hdu = cls(data=data, header=header)
hdu.columns = coldefs
return hdu
def __init__(self, a, b, ignore_keywords=[], ignore_comments=[],
tolerance=0.0, ignore_blanks=True, ignore_blank_cards=True):
"""
See `FITSDiff` for explanations of the initialization parameters.
"""
self.ignore_keywords = set(k.upper() for k in ignore_keywords)
self.ignore_comments = set(k.upper() for k in ignore_comments)
self.tolerance = tolerance
self.ignore_blanks = ignore_blanks
self.ignore_blank_cards = ignore_blank_cards
self.ignore_keyword_patterns = set()
self.ignore_comment_patterns = set()
for keyword in list(self.ignore_keywords):
keyword = keyword.upper()
if keyword != '*' and glob.has_magic(keyword):
self.ignore_keywords.remove(keyword)
self.ignore_keyword_patterns.add(keyword)
for keyword in list(self.ignore_comments):
keyword = keyword.upper()
if keyword != '*' and glob.has_magic(keyword):
self.ignore_comments.remove(keyword)
self.ignore_comment_patterns.add(keyword)
# Keywords appearing in each header
self.common_keywords = []
# Set to the number of keywords in each header if the counts differ
self.diff_keyword_count = ()
# Set if the keywords common to each header (excluding ignore_keywords)
# appear in different positions within the header
# TODO: Implement this
self.diff_keyword_positions = ()
# Keywords unique to each header (excluding keywords in
# ignore_keywords)
self.diff_keywords = ()
# Keywords that have different numbers of duplicates in each header
# (excluding keywords in ignore_keywords)
self.diff_duplicate_keywords = {}
# Keywords common to each header but having different values (excluding
# keywords in ignore_keywords)
self.diff_keyword_values = defaultdict(lambda: [])
# Keywords common to each header but having different comments
# (excluding keywords in ignore_keywords or in ignore_comments)
self.diff_keyword_comments = defaultdict(lambda: [])
if isinstance(a, basestring):
a = Header.fromstring(a)
if isinstance(b, basestring):
b = Header.fromstring(b)
if not (isinstance(a, Header) and isinstance(b, Header)):
raise TypeError('HeaderDiff can only diff pyfits.Header objects '
'or strings containing FITS headers.')
super(HeaderDiff, self).__init__(a, b)
def test_slightly_different_headers(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['C'] = 4
assert_false(HeaderDiff(ha, hb).identical)
def __init__(self, data=None, header=None, do_not_scale_image_data=False,
uint=False, scale_back=False, **kwargs):
from pyfits.hdu.groups import GroupsHDU
super(_ImageBaseHDU, self).__init__(data=data, header=header)
if header is not None:
if not isinstance(header, Header):
# TODO: Instead maybe try initializing a new Header object from
# whatever is passed in as the header--there are various types
# of objects that could work for this...
raise ValueError('header must be a Header object')
if data is DELAYED:
# Presumably if data is DELAYED then this HDU is coming from an
# open file, and was not created in memory
if header is None:
# this should never happen
raise ValueError('No header to setup HDU.')
# if the file is read the first time, no need to copy, and keep it
# unchanged
else:
self._header = header
else:
# TODO: Some of this card manipulation should go into the
# PrimaryHDU and GroupsHDU subclasses
# construct a list of cards of minimal header
if isinstance(self, ExtensionHDU):
c0 = ('XTENSION', 'IMAGE',
self.standard_keyword_comments['XTENSION'])
else:
c0 = ('SIMPLE', True, self.standard_keyword_comments['SIMPLE'])
cards = [
c0,
('BITPIX', 8, self.standard_keyword_comments['BITPIX']),
('NAXIS', 0, self.standard_keyword_comments['NAXIS'])]
if isinstance(self, GroupsHDU):
cards.append(('GROUPS', True,
self.standard_keyword_comments['GROUPS']))
if isinstance(self, (ExtensionHDU, GroupsHDU)):
cards.append(('PCOUNT', 0,
self.standard_keyword_comments['PCOUNT']))
cards.append(('GCOUNT', 1,
self.standard_keyword_comments['GCOUNT']))
if header is not None:
orig = header.copy()
header = Header(cards)
header.extend(orig, strip=True, update=True, end=True)
else:
header = Header(cards)
self._header = header
self._do_not_scale_image_data = do_not_scale_image_data
self._uint = uint
self._scale_back = scale_back
if do_not_scale_image_data:
self._bzero = 0
self._bscale = 1
else:
self._bzero = self._header.get('BZERO', 0)
self._bscale = self._header.get('BSCALE', 1)
# Save off other important values from the header needed to interpret
# the image data
self._axes = [self._header.get('NAXIS' + str(axis + 1), 0)
for axis in xrange(self._header.get('NAXIS', 0))]
self._bitpix = self._header.get('BITPIX', 8)
self._gcount = self._header.get('GCOUNT', 1)
self._pcount = self._header.get('PCOUNT', 0)
self._blank = self._header.get('BLANK')
self._orig_bitpix = self._bitpix
self._orig_bzero = self._bzero
self._orig_bscale = self._bscale
# Set the name attribute if it was provided (if this is an ImageHDU
# this will result in setting the EXTNAME keyword of the header as
# well)
if 'name' in kwargs and kwargs['name']:
self.name = kwargs['name']
# Set to True if the data or header is replaced, indicating that
# update_header should be called
self._modified = False
if data is DELAYED:
return
else:
self.data = data
self.update_header()
def test_common_keywords(self):
ha = Header([('A', 1), ('B', 2), ('C', 3)])
hb = ha.copy()
hb['C'] = 4
hb['D'] = (5, 'Comment')
assert_equal(HeaderDiff(ha, hb).common_keywords, ['A', 'B', 'C'])