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 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 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 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_level_1(out_dir):
l0 = test_data.products.L0_LightCurve_fits
l1 = Level1(out_dir / 'LB', out_dir)
res = sorted(l1.process_fits_files(files=l0))
assert len(res) == 2
# test for https://github.com/i4Ds/STIXCore/issues/180
# TODO remove when solved
lc1 = Product(res[0])
lc2 = Product(res[1])
t = np.hstack((np.array(lc1.data['time']), (np.array(lc2.data['time']))))
td = np.hstack(
(np.array(lc1.data['timedel']), (np.array(lc2.data['timedel']))))
range(len(lc1.data['time']) - 3, len(lc1.data['time']) + 3)
assert np.all((t[1:] - t[0:-1]) == td[0:-1])
# end test for https://github.com/i4Ds/STIXCore/issues/180
for fits in res:
diff = FITSDiff(
test_data.products.DIR / fits.name,
fits,
ignore_keywords=['CHECKSUM', 'DATASUM', 'DATE', 'VERS_SW'])
if not diff.identical:
print(diff.report())
assert diff.identical
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 test_image3_closedfile(run_image3_closedfile, rtdata, fitsdiff_default_kwargs):
"""Ensure production of Image3Pipeline output with data having closed file issues"""
rtdata.output = 'jw00617-o082_t001_nircam_clear-f090w-sub320_i2d.fits'
rtdata.get_truth('truth/test_nircam_image/jw00617-o082_t001_nircam_clear-f090w-sub320_i2d.fits')
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
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 test_miri_setpointing(_jail, rtdata, fitsdiff_default_kwargs):
"""
Regression test of the set_telescope_pointing script on a level-1b MIRI image.
"""
# Get SIAF PRD database file
siaf_path = rtdata.get_data("common/prd.db")
# Get the input level-1b file
rtdata.get_data("miri/image/jw80600010001_02101_00001_mirimage_uncal.fits")
# The add_wcs function overwrites its input, so output = input
rtdata.output = rtdata.input
# Call the WCS routine, using the ENGDB_Service
# Note that there aren't any quaternion mnemonics in the ENGDB for the time
# range of this exposure, so we set "allow_default" to tell add_wcs to use
# default values for the pointing-related keywords. Keyword values retrieved
# from the SIAF will be good.
add_wcs(rtdata.input, allow_default=True, siaf_path=siaf_path)
# Compare the results
rtdata.get_truth(
"truth/test_miri_setpointing/jw80600010001_02101_00001_mirimage_uncal.fits"
)
fitsdiff_default_kwargs['rtol'] = 1e-6
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_miri_lrs_slitless_tso3(
run_spec3_pipeline,
generate_tso3_asn,
rtdata_module,
fitsdiff_default_kwargs,
step_suffix,
filename_extension,
is_product,
diff_astropy_tables,
):
"""Compare the output of a MIRI LRS slitless calwebb_tso3 step."""
rtdata = rtdata_module
_, asn_id = generate_tso3_asn
if is_product:
output_filename = f"{PRODUCT_NAME}_{step_suffix}.{filename_extension}"
else:
output_filename = f"{DATASET_ID}_{asn_id}_{step_suffix}.{filename_extension}"
rtdata.output = output_filename
rtdata.get_truth(f"truth/test_miri_lrs_slitless_tso3/{output_filename}")
if filename_extension == "fits":
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
else:
diff = diff_astropy_tables(rtdata.output, rtdata.truth)
assert len(diff) == 0, "\n".join(diff)
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")
collect_pipeline_cfgs("config")
args = [
"config/master_background.cfg", rtdata.input, "--user_background",
user_background
]
Step.from_cmdline(args)
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_nircam_setpointing_tsimg(_jail, rtdata, fitsdiff_default_kwargs):
"""
Regression test of the set_telescope_pointing script on a level-1b
NIRCam TSO imaging file.
"""
# Get SIAF PRD database file
siaf_path = rtdata.get_data("common/prd.db")
rtdata.get_data(
"nircam/tsimg/jw00312006001_02102_00001-seg001_nrcb1_uncal.fits")
# The add_wcs function overwrites its input, so output = input
rtdata.output = rtdata.input
# Call the WCS routine, using the ENGDB_Service
try:
add_wcs(rtdata.input, siaf_path=siaf_path)
except ValueError:
pytest.skip('Engineering Database not available.')
rtdata.get_truth(
"truth/test_nircam_setpointing/jw00312006001_02102_00001-seg001_nrcb1_uncal.fits"
)
fitsdiff_default_kwargs['rtol'] = 1e-6
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
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_miri_image2(run_pipeline, fitsdiff_default_kwargs, output):
"""Regression test of calwebb_image2 pipeline performed on MIRI data."""
rtdata = run_pipeline
rtdata.output = output
rtdata.get_truth(os.path.join("truth/test_miri_image2_cal", output))
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_miri_image3_i2d(run_image3, rtdata_module, fitsdiff_default_kwargs):
rtdata = rtdata_module
rtdata.input = "det_dithered_5stars_image3_asn.json"
rtdata.output = "det_dithered_5stars_f770w_i2d.fits"
rtdata.get_truth("truth/test_miri_image_stages/det_dithered_5stars_f770w_i2d.fits")
fitsdiff_default_kwargs["rtol"] = 1e-4
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
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_miri_lrs_extract1d_from_cal(run_pipeline, rtdata_module, fitsdiff_default_kwargs):
rtdata = rtdata_module
rtdata.input = "jw00623032001_03102_00001_mirimage_cal.fits"
Extract1dStep.call(rtdata.input, save_results=True)
output = "jw00623032001_03102_00001_mirimage_extract1dstep.fits"
rtdata.output = output
rtdata.get_truth(f"truth/test_miri_lrs_slit_spec2/{output}")
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_image_stages12(run_pipelines, fitsdiff_default_kwargs, suffix):
"""Regression test of detector1 and image2 pipelines performed on NIRCam data."""
rtdata = run_pipelines
rtdata.input = "jw42424001001_01101_00001_nrca5_uncal.fits"
output = "jw42424001001_01101_00001_nrca5_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_nircam_image_stages/" + output)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nirspec_detector1(run_pipeline, fitsdiff_default_kwargs, output):
"""
Regression test of calwebb_detector1 pipeline performed on NIRSpec data.
"""
rtdata = run_pipeline
rtdata.output = output
rtdata.get_truth(os.path.join("truth/test_nirspec_subarray", output))
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_spec3(run_spec3, fitsdiff_default_kwargs, output):
"""Regression test matching output files"""
rtdata = run_spec3
rtdata.output = output
rtdata.get_truth(os.path.join(TRUTH_PATH, rtdata.output))
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_image_stage3_segm(run_image3pipeline, rtdata_module, fitsdiff_default_kwargs):
"""Test that segmentation map looks good for NIRCam imaging"""
rtdata = rtdata_module
rtdata.input = "jw42424-o002_20191220t214154_image3_001_asn.json"
output = "jw42424-o002_t001_nircam_clear-f444w_segm.fits"
rtdata.output = output
rtdata.get_truth(f"truth/test_nircam_image_stages/{output}")
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_niriss_soss_stage3_x1dints(run_pipelines, fitsdiff_default_kwargs):
rtdata = run_pipelines
rtdata.input = "jw00625-o023_20191210t204036_tso3_001_asn.json"
rtdata.output = "jw00625-o023_t001_niriss_clear-gr700xd-substrip256_x1dints.fits"
rtdata.get_truth(
"truth/test_niriss_soss_stages/jw00625-o023_t001_niriss_clear-gr700xd-substrip256_x1dints.fits"
)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_tsgrism_stage3_x1dints(run_pipelines, fitsdiff_default_kwargs):
rtdata = run_pipelines
rtdata.input = "jw00721-o012_20191119t043909_tso3_001_asn.json"
rtdata.output = "jw00721-o012_t004_nircam_f444w-grismr-subgrism256_x1dints.fits"
rtdata.get_truth(
"truth/test_nircam_tsgrism_stages/jw00721-o012_t004_nircam_f444w-grismr-subgrism256_x1dints.fits"
)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_spec2(rtdata_module, run_spec2, fitsdiff_default_kwargs, suffix):
"""Test ensuring the calwebb_tso-spec2 is operating appropriately for MIRI MRS TSO data"""
rtdata = rtdata_module
output = f"jw80600018001_02101_00003_mirifushort_{suffix}.fits"
rtdata.output = output
rtdata.get_truth(f"{TRUTH_PATH}/{output}")
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_coron3_exp(run_pipeline, suffix, exposure, fitsdiff_default_kwargs):
"""Check intermediate results of calwebb_coron3"""
rtdata = run_pipeline
output = "jw9999947001_02102_" + exposure + "_nrcb3_a3001_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_nircam_coron3/" + output)
fitsdiff_default_kwargs["atol"] = 1e-5
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_tsgrism_stage2(run_pipelines, fitsdiff_default_kwargs, suffix):
"""Regression test of tso-spec2 pipeline performed on NIRCam TSO grism data."""
rtdata = run_pipelines
rtdata.input = "jw00721012001_03103_00001-seg001_nrcalong_rateints.fits"
output = "jw00721012001_03103_00001-seg001_nrcalong_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_nircam_tsgrism_stages/" + output)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_niriss_soss_stage2(run_pipelines, fitsdiff_default_kwargs, suffix):
"""Regression test of tso-spec2 pipeline performed on NIRISS SOSS data."""
rtdata = run_pipelines
rtdata.input = "jw00625023001_03101_00001-seg001_nis_rateints.fits"
output = "jw00625023001_03101_00001-seg001_nis_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_niriss_soss_stages/" + output)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_miri_image_stage3_i2d(run_pipelines, fitsdiff_default_kwargs):
rtdata = run_pipelines
rtdata.input = "det_dithered_5stars_image3_asn.json"
rtdata.output = "det_dithered_5stars_f770w_i2d.fits"
rtdata.get_truth(
"truth/test_miri_image_stages/det_dithered_5stars_f770w_i2d.fits")
fitsdiff_default_kwargs['ignore_fields'] = ['date', 'filename']
fitsdiff_default_kwargs['ignore_keywords'] += ['naxis1', 'tform*']
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_coron3_product(run_pipeline, suffix, fitsdiff_default_kwargs):
"""Check final products of calwebb_coron3"""
rtdata = run_pipeline
output = "jw99999-a3001_t1_nircam_f140m-maskbar_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_nircam_coron3/" + output)
fitsdiff_default_kwargs['atol'] = 1e-5
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_image_moving_target_i2d(rtdata, fitsdiff_default_kwargs):
"""Test resampled i2d of moving target exposures for NIRCam imaging"""
rtdata.get_asn("nircam/image/mt_asn.json")
rtdata.output = "mt_assoc_i2d.fits"
args = ["calwebb_image3", rtdata.input]
Step.from_cmdline(args)
rtdata.get_truth("truth/test_nircam_mtimage/mt_assoc_i2d.fits")
fitsdiff_default_kwargs["atol"] = 1e-5
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_miri_lrs_slitless_spec2(run_spec2_pipeline, rtdata_module,
fitsdiff_default_kwargs, step_suffix):
"""Compare the output of a MIRI LRS slitless calwebb_tso-spec2 step."""
rtdata = rtdata_module
output_filename = f"{DATASET_ID}_{step_suffix}.fits"
rtdata.output = output_filename
rtdata.get_truth(f"truth/test_miri_lrs_slitless_spec2/{output_filename}")
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_nircam_tsimg_stage2(run_pipelines, fitsdiff_default_kwargs, suffix):
"""Regression test of tso-image2 pipeline performed on NIRCam TSIMG data."""
rtdata = run_pipelines
rtdata.input = "jw00312006001_02102_00001-seg001_nrcb1_rateints.fits"
output = "jw00312006001_02102_00001-seg001_nrcb1_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_nircam_tsimg_stage23/" + output)
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_niriss_ami3_product(run_pipeline, suffix, fitsdiff_default_kwargs):
"""Check final products of calwebb_ami3"""
rtdata = run_pipeline
output = "jw00793-c1014_t005_niriss_f480m-nrm-sub80_" + suffix + ".fits"
rtdata.output = output
rtdata.get_truth("truth/test_niriss_ami3/" + output)
fitsdiff_default_kwargs['atol'] = 1e-5
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert diff.identical, diff.report()
def test_miri_lrs_slitless_tso3_x1dints(run_tso3_pipeline, rtdata_module,
fitsdiff_default_kwargs):
"""Compare the output of a MIRI LRS slitless calwebb_tso3 pipeline."""
rtdata = rtdata_module
output_filename = f"{PRODUCT_NAME}_x1dints.fits"
rtdata.output = output_filename
rtdata.get_truth(f"truth/test_miri_lrs_slitless_tso3/{output_filename}")
diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
assert 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()
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 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_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_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
