def fits_osiris_allclose(a, b):
"""Assert that two OSIRIS fits files are close."""
a = fits.open(a)
b = fits.open(b)
try:
del a[0].header['COMMENT']
del b[0].header['COMMENT']
report = StringIO()
diff = FITSDiff(
a, b,
ignore_keywords=["COMMENT"],
ignore_comments=["SIMPLE"],
ignore_fields=[],
ignore_blanks=True,
ignore_blank_cards=True,
tolerance=1e-5)
diff.report(fileobj=report)
assert diff.identical, report.getvalue()
finally:
a.close()
b.close()
def test_partially_identical_files3(self):
"""
Test files that have some identical HDUs but a different extension
name.
"""
phdu = PrimaryHDU()
ehdu = ImageHDU(name='FOO')
hdula = HDUList([phdu, ehdu])
ehdu = BinTableHDU(name='BAR')
ehdu.header['EXTVER'] = 2
ehdu.header['EXTLEVEL'] = 3
hdulb = HDUList([phdu, ehdu])
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdus[0][0] == 1
hdu_diff = diff.diff_hdus[0][1]
assert hdu_diff.diff_extension_types == ('IMAGE', 'BINTABLE')
assert hdu_diff.diff_extnames == ('FOO', 'BAR')
assert hdu_diff.diff_extvers == (1, 2)
assert hdu_diff.diff_extlevels == (1, 3)
report = diff.report()
assert 'Extension types differ' in report
assert 'a: IMAGE\n b: BINTABLE' in report
assert 'Extension names differ' in report
assert 'a: FOO\n b: BAR' in report
assert 'Extension versions differ' in report
assert 'a: 1\n b: 2' in report
assert 'Extension levels differ' in report
assert 'a: 1\n b: 2' in report
def pruebas_varias():
# from subprocess import Popen, PIPE
# resultado = Popen(["fitsdiff", "-k", "filename,filtnam1,NUM-BS,NUM-OVPE,NUM-TRIM", "-n 1", "-d 1.e-1", "arc_rss.fits", "cArcCalibrationRecipe_arc_rss.fits" ], stdout=PIPE, stderr=PIPE)
# if "Data contains differences" in resultado.stdout.read():
# print "Hay Diferencias"
# else:
# print "Son iguales"
# print "*" * 40
# ejemplo = FITSDiff( "arc_rss.fits", "cArcCalibrationRecipe_arc_rss.fits",["filename","filtnam1","NUM-BS","NUM-OVPE","NUM-TRIM"])
ejemplo = FITSDiff( "arc_rss.fits", "cArcCalibrationRecipe_arc_rss.fits",["NUM-BS","NUM-OVPE"])
print ejemplo.report()
if "Data contains differences" in ejemplo.report():
print "Hay Diferencias"
else:
print "Son iguales"
print "*" * 40
# hd = HeaderDiff.fromdiff(ejemplo, "arc_rss.fits", "cArcCalibrationRecipe_arc_rss.fits")
hd = HeaderDiff.fromdiff(ejemplo, "arc_image.fits", "cArcCalibrationRecipe_arc_rss.fits")
print "Cabeceras identicas: ", hd.identical
def compare(cls, reference_file, test_file, atol=None, rtol=None):
import astropy
from astropy.io.fits.diff import FITSDiff
from astropy.utils.introspection import minversion
if minversion(astropy, '2.0'):
diff = FITSDiff(reference_file, test_file, rtol=rtol)
else:
diff = FITSDiff(reference_file, test_file, tolerance=rtol)
return diff.identical, diff.report()
def test_partially_identical_files2(self):
"""
Test files that have some identical HDUs but one different HDU.
"""
a = np.arange(100).reshape(10, 10)
phdu = PrimaryHDU(data=a)
ehdu = ImageHDU(data=a)
ehdu2 = ImageHDU(data=(a + 1))
hdula = HDUList([phdu, ehdu, ehdu])
hdulb = HDUList([phdu, ehdu2, ehdu])
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdu_count == ()
assert len(diff.diff_hdus) == 1
assert diff.diff_hdus[0][0] == 1
hdudiff = diff.diff_hdus[0][1]
assert not hdudiff.identical
assert hdudiff.diff_extnames == ()
assert hdudiff.diff_extvers == ()
assert hdudiff.diff_extension_types == ()
assert hdudiff.diff_headers.identical
assert hdudiff.diff_data is not None
datadiff = hdudiff.diff_data
assert isinstance(datadiff, ImageDataDiff)
assert not datadiff.identical
assert datadiff.diff_dimensions == ()
assert (datadiff.diff_pixels ==
[((0, y), (y, y + 1)) for y in range(10)])
assert datadiff.diff_ratio == 1.0
assert datadiff.diff_total == 100
report = diff.report()
# Primary HDU and 2nd extension HDU should have no differences
assert 'Primary HDU' not in report
assert 'Extension HDU 2' not in report
assert 'Extension HDU 1' in report
assert 'Headers contain differences' not in report
assert 'Data contains differences' in report
for y in range(10):
assert 'Data differs at [{}, 1]'.format(y + 1) in report
assert '100 different pixels found (100.00% different).' in report
def test_identical_files_basic(self):
"""Test identicality of two simple, extensionless files."""
a = np.arange(100).reshape(10, 10)
hdu = PrimaryHDU(data=a)
hdu.writeto(self.temp('testa.fits'))
hdu.writeto(self.temp('testb.fits'))
diff = FITSDiff(self.temp('testa.fits'), self.temp('testb.fits'))
assert diff.identical
report = diff.report()
# Primary HDUs should contain no differences
assert 'Primary HDU' not in report
assert 'Extension HDU' not in report
assert 'No differences found.' in report
a = np.arange(10)
ehdu = ImageHDU(data=a)
diff = HDUDiff(ehdu, ehdu)
assert diff.identical
report = diff.report()
assert 'No differences found.' in report
def test_partially_identical_files1(self):
"""
Test files that have some identical HDUs but a different extension
count.
"""
a = np.arange(100).reshape(10, 10)
phdu = PrimaryHDU(data=a)
ehdu = ImageHDU(data=a)
hdula = HDUList([phdu, ehdu])
hdulb = HDUList([phdu, ehdu, ehdu])
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdu_count == (2, 3)
# diff_hdus should be empty, since the third extension in hdulb
# has nothing to compare against
assert diff.diff_hdus == []
report = diff.report()
assert 'Files contain different numbers of HDUs' in report
assert 'a: 2\n b: 3' in report
assert 'No differences found between common HDUs' in report
def test_nircam_setpointing(_jail, rtdata, fitsdiff_default_kwargs):
"""
Regression test of the set_telescope_pointing script on a level-1b NIRCam file.
"""
# Get SIAF PRD database file
siaf_path = rtdata.get_data("common/prd.db")
rtdata.get_data(
"nircam/tsgrism/jw00721012001_03103_00001-seg001_nrcalong_uncal.fits")
# The add_wcs function overwrites its input
rtdata.output = rtdata.input
# Call the WCS routine, using the ENGDB_Service
add_wcs(rtdata.input,
siaf_path=siaf_path,
engdb_url=engdb_tools.ENGDB_BASE_URL)
rtdata.get_truth(
"truth/test_nircam_setpointing/jw00721012001_03103_00001-seg001_nrcalong_uncal.fits"
)
fitsdiff_default_kwargs['rtol'] = 1e-6
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_partially_identical_files1(self):
"""
Test files that have some identical HDUs but a different extension
count.
"""
a = np.arange(100).reshape(10, 10)
phdu = PrimaryHDU(data=a)
ehdu = ImageHDU(data=a)
hdula = HDUList([phdu, ehdu])
hdulb = HDUList([phdu, ehdu, ehdu])
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdu_count == (2, 3)
# diff_hdus should be empty, since the third extension in hdulb
# has nothing to compare against
assert diff.diff_hdus == []
report = diff.report()
assert 'Files contain different numbers of HDUs' in report
assert 'a: 2\n b: 3' in report
assert 'No differences found between common HDUs' in report
def test_nirspec_ifu_mbkg_user(rtdata, fitsdiff_default_kwargs):
"""Test NIRSpec IFU data with a user-supplied background file."""
# Get user-supplied background
user_background = "prism_bkg_x1d.fits"
rtdata.get_data(f"nirspec/ifu/{user_background}")
# Get input data
rtdata.get_data("nirspec/ifu/prism_sci_bkg_cal.fits")
MasterBackgroundStep.call(rtdata.input,
user_background=user_background,
save_results=True,
suffix='master_background')
output = "prism_sci_bkg_master_background.fits"
rtdata.output = output
# Get the truth file
rtdata.get_truth(f"truth/test_nirspec_ifu_mbkg_user/{output}")
# Compare the results
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_identical(orig_fits, current_fits):
error = False
for cfits in current_fits:
# find corresponding original file
try:
ofits = next(ofits for ofits in orig_fits
if ofits.name == cfits.name)
except StopIteration:
error = True
warnings.warn(
f"no corresponding file found for {cfits} in the original fits files"
)
continue
diff = FITSDiff(
ofits,
cfits,
ignore_keywords=['CHECKSUM', 'DATASUM', 'DATE', 'VERS_SW'])
if not diff.identical:
error = True
warnings.warn(diff.report())
if error:
raise ValueError(
"one or many errors\nthere are differentses in FITS files")
def fitsdiff(input1, input2, comment_excl_list='', value_excl_list='',
field_excl_list='', maxdiff=10, delta=0.0, neglect_blanks=True,
output=None):
if isinstance(comment_excl_list, string_types):
comment_excl_list = list_parse(comment_excl_list)
if isinstance(value_excl_list, string_types):
value_excl_list = list_parse(value_excl_list)
if isinstance(field_excl_list, string_types):
field_excl_list = list_parse(field_excl_list)
diff = FITSDiff(input1, input2, ignore_keywords=value_excl_list,
ignore_comments=comment_excl_list,
ignore_fields=field_excl_list, numdiffs=maxdiff,
tolerance=delta, ignore_blanks=neglect_blanks)
if output is None:
output = sys.stdout
diff.report(output)
return diff.identical
def test_nirspec_fs_mbkg_user(rtdata, fitsdiff_default_kwargs):
"""Run a test for NIRSpec FS data with a user-supplied background file."""
# Get user-supplied background
user_background = "v2_nrs_bkg_user_clean_x1d.fits"
rtdata.get_data(f"nirspec/fs/{user_background}")
# Get input data
rtdata.get_data("nirspec/fs/nrs_sci+bkg_cal.fits")
MasterBackgroundStep.call(rtdata.input,
save_results=True,
suffix='master_background',
user_background=user_background)
output = "nrs_sci+bkg_master_background.fits"
rtdata.output = output
# Get the truth file
rtdata.get_truth(f"truth/test_nirspec_fs_mbkg_user/{output}")
# Compare the results
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nirspec_fs_mbkg_user(rtdata, fitsdiff_default_kwargs):
"""Run a test for NIRSpec FS data with a user-supplied background file."""
# Get user-supplied background
user_background = "v2_nrs_bkg_user_clean_x1d.fits"
rtdata.get_data(f"nirspec/fs/{user_background}")
# Get input data
rtdata.get_data("nirspec/fs/nrs_sci+bkg_cal.fits")
collect_pipeline_cfgs("config")
args = ["config/master_background.cfg", rtdata.input,
"--user_background", user_background]
Step.from_cmdline(args)
output = "nrs_sci+bkg_master_background.fits"
rtdata.output = output
# Get the truth file
rtdata.get_truth(f"truth/test_nirspec_fs_mbkg_user/{output}")
# Compare the results
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_diff_empty_tables(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/178
Ensure that diffing tables containing empty data doesn't crash.
"""
c1 = Column('D', format='J')
c2 = Column('E', format='J')
thdu = BinTableHDU.from_columns([c1, c2], nrows=0)
hdula = fits.HDUList([thdu])
hdulb = fits.HDUList([thdu])
diff = FITSDiff(hdula, hdulb)
assert diff.identical
def test_identical_comp_image_hdus(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/189
For this test we mostly just care that comparing to compressed images
does not crash, and returns the correct results. Two compressed images
will be considered identical if the decompressed data is the same.
Obviously we test whether or not the same compression was used by
looking for (or ignoring) header differences.
"""
data = np.arange(100.0).reshape(10, 10)
hdu = fits.CompImageHDU(data=data)
hdu.writeto(self.temp('test.fits'))
hdula = fits.open(self.temp('test.fits'))
hdulb = fits.open(self.temp('test.fits'))
diff = FITSDiff(hdula, hdulb)
assert diff.identical
def test_ignore_hdus(self):
a = np.arange(100).reshape(10, 10)
b = a.copy()
ha = Header([('A', 1), ('B', 2), ('C', 3)])
xa = np.array([(1.0, 1), (3.0, 4)], dtype=[('x', float), ('y', int)])
xb = np.array([(1.0, 2), (3.0, 5)], dtype=[('x', float), ('y', int)])
phdu = PrimaryHDU(header=ha)
ihdua = ImageHDU(data=a, name='SCI')
ihdub = ImageHDU(data=b, name='SCI')
bhdu1 = BinTableHDU(data=xa, name='ASDF')
bhdu2 = BinTableHDU(data=xb, name='ASDF')
hdula = HDUList([phdu, ihdua, bhdu1])
hdulb = HDUList([phdu, ihdub, bhdu2])
# ASDF extension should be different
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdus[0][0] == 2
# ASDF extension should be ignored
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASDF'])
assert diff.identical, diff.report()
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASD*'])
assert diff.identical, diff.report()
# SCI extension should be different
hdulb['SCI'].data += 1
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASDF'])
assert not diff.identical
# SCI and ASDF extensions should be ignored
diff = FITSDiff(hdula, hdulb, ignore_hdus=['SCI', 'ASDF'])
assert diff.identical, diff.report()
# All EXTVER of SCI should be ignored
ihduc = ImageHDU(data=a, name='SCI', ver=2)
hdulb.append(ihduc)
diff = FITSDiff(hdula, hdulb, ignore_hdus=['SCI', 'ASDF'])
assert not any(diff.diff_hdus), diff.report()
assert any(diff.diff_hdu_count), diff.report()
def compare(cls, reference_file, test_file, atol=None, rtol=None):
from astropy.io.fits.diff import FITSDiff
diff = FITSDiff(reference_file, test_file, tolerance=rtol)
return diff.identical, diff.report()
def test_ignore_hdus(self):
a = np.arange(100).reshape(10, 10)
b = a.copy()
ha = Header([('A', 1), ('B', 2), ('C', 3)])
xa = np.array([(1.0, 1), (3.0, 4)], dtype=[('x', float), ('y', int)])
xb = np.array([(1.0, 2), (3.0, 5)], dtype=[('x', float), ('y', int)])
phdu = PrimaryHDU(header=ha)
ihdua = ImageHDU(data=a, name='SCI')
ihdub = ImageHDU(data=b, name='SCI')
bhdu1 = BinTableHDU(data=xa, name='ASDF')
bhdu2 = BinTableHDU(data=xb, name='ASDF')
hdula = HDUList([phdu, ihdua, bhdu1])
hdulb = HDUList([phdu, ihdub, bhdu2])
# ASDF extension should be different
diff = FITSDiff(hdula, hdulb)
assert not diff.identical
assert diff.diff_hdus[0][0] == 2
# ASDF extension should be ignored
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASDF'])
assert diff.identical, diff.report()
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASD*'])
assert diff.identical, diff.report()
# SCI extension should be different
hdulb['SCI'].data += 1
diff = FITSDiff(hdula, hdulb, ignore_hdus=['ASDF'])
assert not diff.identical
# SCI and ASDF extensions should be ignored
diff = FITSDiff(hdula, hdulb, ignore_hdus=['SCI', 'ASDF'])
assert diff.identical, diff.report()
# All EXTVER of SCI should be ignored
ihduc = ImageHDU(data=a, name='SCI', ver=2)
hdulb.append(ihduc)
diff = FITSDiff(hdula, hdulb, ignore_hdus=['SCI', 'ASDF'])
assert not any(diff.diff_hdus), diff.report()
assert any(diff.diff_hdu_count), diff.report()
