def test_slitdark_in_calservice(self, get_or_create_tmpdir, do_slit_dark):
"""
Check that:
- A bias slit calibrator exists in the local calibrations dir;
- It can be retrieved using a getProcessedSlitBias call.
"""
# Ensure the slit dark reduction has been done
_, _, _ = do_slit_dark
_, cal_service = get_or_create_tmpdir
# import pdb; pdb.set_trace()
assert len(glob.glob(os.path.join(
os.getcwd(), 'calibrations', 'processed_dark', '*dark*slit*.fits'
))) == 1, "Couldn't find the stored slit bias in the calibrations " \
"system OR found multiples\n " \
"(calibration ls: {})\n" \
"(caldb contents: {})".format(
glob.glob(os.path.join(os.getcwd(), 'calibrations',
'processed_dark', '*')),
[_ for _ in cal_service.list_files()],
)
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
# Use one of the 'dark slit' files to try and retrieve the slit bias
reduce.files = glob.glob(
os.path.join(os.getcwd(), 'flat95*MEF_2x2_slit.fits'))
reduce.mode = [
'test',
]
reduce.recipename = 'recipeRetrieveSlitDarkTest'
# reduce.mode = ['sq', ]
reduce.logfile = os.path.join(os.getcwd(),
'reduce_slitdark_retrieve.log')
reduce.logmode = 'quiet'
reduce.suffix = '_testSlitDarkRetrieve'
# FIXME cal_service will hopefully find the calibration itself later
# reduce.ucals = normalize_ucals(reduce.files, [
# 'processed_dark:{}'.format(
# glob.glob(os.path.join(
# 'calibrations',
# 'processed_dark',
# '*slit*dark*.fits'))[0]),
# ])
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
try:
reduce.runr()
except IOError as e:
assert 0, 'Calibration system could not locate the slit bias ' \
'frame ({})'.format(e.message)
finally:
# Teardown code
for _ in glob.glob(
os.path.join(os.getcwd(),
'*{}.fits'.format(reduce.suffix)), ):
os.remove(_)
def do_overscan_subtract(self, get_or_create_tmpdir, request):
"""
Run overscan correction on the main data.
.. note::
Fixture.
"""
# Copy the raw data file into here
rawfilename = 'bias*{}*.fits'.format(request.param)
tmpsubdir, cal_service = get_or_create_tmpdir
# Make sure we're working inside the temp dir
# rawfiles = glob.glob(os.path.join(
# os.path.dirname(os.path.abspath(__file__)),
# 'testdata',
# rawfilename))
# shutil.copy(
# rawfiles[0],
# os.path.join(tmpsubdir.dirname, tmpsubdir.basename))
rawfile = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
rawfilename))[0]
# Do the overscan subtraction
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = [
rawfile,
]
reduce.mode = [
'test',
]
reduce.recipename = 'recipeBiasRemoveOverscan'
reduce.logfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
'reduce_overscancorrect.log')
reduce.logmode = 'quiet'
reduce.suffix = '_testOverscanCorrect'
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
reduce.runr()
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
'*' + reduce.suffix + '.fits')
corrfilename = glob.glob(corrfilename)[0]
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Return filenames of raw, subtracted files
yield rawfile, corrfile
# Execute teardown code
for _ in glob.glob(
os.path.join(os.getcwd(), '*{}.fits'.format(reduce.suffix))):
os.remove(_)
def test_slitbias_in_calservice(self, get_or_create_tmpdir):
"""
Check that:
- A bias slit calibrator exists in the local calibrations dir;
- It can be retrieved using a getProcessedSlitBias call.
"""
assert len(glob.glob(os.path.join(
os.getcwd(), 'calibrations', 'processed_bias', '*bias*slit*.fits'
))) == 1, "Couldn't find the stored slit bias in the calibrations " \
"system OR found multiples"
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
# Use one of the 'dark slit' files to try and retrieve the slit bias
reduce.files = [
os.path.join(os.getcwd(), 'dark95_1_MEF_2x2_slit.fits'),
]
reduce.mode = [
'test',
]
reduce.recipename = 'recipeRetrieveSlitBiasTest'
# reduce.mode = ['sq', ]
# reduce.recipename = 'makeProcessedBias'
reduce.logfile = os.path.join(os.getcwd(),
'reduce_slitbias_retrieve.log')
# FIXME cal_service will hopefully find the calibration itself later
reduce.ucals = normalize_ucals(reduce.files, [
'processed_bias:{}'.format(
glob.glob(
os.path.join('calibrations', 'processed_bias',
'*slit*bias*.fits'))[0]),
])
reduce.logmode = 'quiet'
reduce.suffix = '_testSlitBiasRetrieve'
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
try:
reduce.runr()
except IOError as e:
assert 0, 'Calibration system could not locate the slit bias ' \
'frame ({})'.format(e.message)
finally:
# Teardown code
for _ in glob.glob(
os.path.join(os.getcwd(),
'*{}.fits'.format(reduce.suffix)), ):
os.remove(_)
def do_slit_bias(self, get_or_create_tmpdir):
"""
Reduce the bias slit test data.
.. note::
Fixture.
"""
rawfilename = 'bias*slit*.fits'
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
# Find all the relevant files
rawfiles = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename, rawfilename))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = rawfiles
reduce.mode = [
'test',
]
reduce.recipename = 'recipeSlitBiasTest'
reduce.logfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
'reduce_slitbias.log')
reduce.logmode = 'quiet'
reduce.suffix = '_testSlitBias'
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
reduce.runr()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Return filenames of raw, subtracted files
yield rawfiles, corrfile
# Execute teardown code
for _ in glob.glob(
os.path.join(
os.getcwd(),
# rawfilename,
corrfilename,
)):
os.remove(_)
def do_slit_arc(self, request, get_or_create_tmpdir):
"""
Reduce the test slit arc data.
.. note::
Fixture.
"""
# import pdb; pdb.set_trace()
# rawfilename = '{}*slit*.fits'.format(slit_type)
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
slit_type, res = request.param
filenames = glob.glob('{}*{}*slit.fits'.format(slit_type, res))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.mode = ['test', ]
reduce.recipename = 'recipeSlitArcTest' if slit_type == 'arc' \
else 'recipeSlitTest'
# Make sure refresh is used for all primitives
reduce.upars = ['refresh=True', ]
# FIXME cal_service will hopefully find the calibration itself later
calibs = {
'processed_bias': glob.glob(os.path.join(
'calibrations',
'processed_bias',
'*slit*bias*.fits'))[0],
'processed_dark': glob.glob(os.path.join(
'calibrations',
'processed_dark',
'*slit*dark*.fits'))[0],
'processed_slitflat': glob.glob(os.path.join(
'calibrations',
'processed_slitflat',
'*{}*slit*slitflat*.fits'.format(res, )))[0]
}
reduce.logfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
'reduce_slit{}.log'.format(slit_type))
reduce.logmode = 'standard'
reduce.suffix = '_{}_testSlit'.format(slit_type)
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
corrfiles = []
for filename in filenames:
reduce.files = [filename, ]
reduce.ucals = normalize_ucals(reduce.files, [
'{}:{}'.format(k, v) for k, v in calibs.items()
])
reduce.runr()
# import pdb; pdb.set_trace()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
corrfiles.append(corrfile)
# Return filenames of raw, subtracted files
yield filenames, corrfiles, calibs
# import pdb; pdb.set_trace()
# Execute teardown code
for _ in glob.glob(os.path.join(
os.getcwd(),
# rawfilename,
corrfilename,
)):
os.remove(_)
def do_master_flat(self, get_or_create_tmpdir, request):
"""
Run the recipeFlatCreateMaster recipe.
.. note::
Fixture.
"""
arm, res = request.param
rawfilename = 'flat*{}*{}*.fits'.format(res, arm)
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
# Find all the relevant files
# rawfiles = glob.glob(os.path.join(os.path.dirname(
# os.path.abspath(__file__)),
# 'testdata',
# rawfilename))
# for f in rawfiles:
# shutil.copy(f, os.path.join(tmpsubdir.dirname, tmpsubdir.basename))
rawfiles = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename, rawfilename))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = rawfiles
reduce.mode = [
'test',
]
reduce.recipename = 'recipeFlatCreateMaster'
# reduce.mode = ['sq', ]
# reduce.recipename = 'makeProcessedBias'
reduce.logfile = os.path.join(
tmpsubdir.dirname, tmpsubdir.basename,
'reduce_masterflat_{}_{}.log'.format(res, arm))
reduce.logmode = 'quiet'
reduce.suffix = '_{}_{}_testMasterFlat'.format(res, arm)
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
# import pdb; pdb.set_trace()
calibs = {
'processed_bias':
glob.glob(
os.path.join('calibrations', 'processed_bias',
'bias*{}*.fits'.format(arm)))[0],
'processed_dark':
glob.glob(
os.path.join('calibrations', 'processed_dark',
'dark*{}*.fits'.format(arm)))[0],
'processed_slitflat':
glob.glob(
os.path.join('calibrations', 'processed_slitflat',
'flat*{}*slitflat*.fits'.format(res)))[0],
}
reduce.ucals = normalize_ucals(
reduce.files, ['{}:{}'.format(k, v) for k, v in calibs.items()])
reduce.runr()
if res == 'std' and arm == 'red':
pass
# import pdb;
# pdb.set_trace()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Return filenames of raw, subtracted files
yield rawfiles, corrfile, calibs
# Execute teardown code
pass
def do_slit_dark(self, get_or_create_tmpdir):
"""
Reduce the test slit dark data.
.. note::
Fixture.
"""
rawfilename = 'dark*slit*.fits'
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
# Find all the relevant files
rawfiles = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename, rawfilename))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = rawfiles
reduce.mode = [
'test',
]
reduce.recipename = 'recipeSlitDarkTest'
# Make sure refresh is used for all primitives
reduce.upars = [
'refresh=True',
]
# FIXME cal_service will hopefully find the calibration itself later
calibs = {
'processed_bias':
glob.glob(
os.path.join('calibrations', 'processed_bias',
'*slit*bias*.fits'))[0],
}
reduce.ucals = normalize_ucals(
reduce.files, ['{}:{}'.format(k, v) for k, v in calibs.items()])
reduce.logfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
'reduce_slitdark.log')
reduce.logmode = 'standard'
reduce.suffix = '_testSlitDark'
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
reduce.runr()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Return filenames of raw, subtracted files
yield rawfiles, corrfile, calibs
# import pdb; pdb.set_trace()
# Execute teardown code
for _ in glob.glob(
os.path.join(
os.getcwd(),
# rawfilename,
corrfilename,
)):
os.remove(_)
def do_master_bias(self, get_or_create_tmpdir, request):
"""
Perform bias subtraction on the main data.
.. note::
Fixture.
"""
rawfilename = 'bias*{}*.fits'.format(request.param)
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
# Find all the relevant files
# rawfiles = glob.glob(os.path.join(os.path.dirname(
# os.path.abspath(__file__)),
# 'testdata',
# rawfilename))
# for f in rawfiles:
# shutil.copy(f, os.path.join(tmpsubdir.dirname, tmpsubdir.basename))
rawfiles = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename, rawfilename))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = rawfiles
reduce.mode = [
'test',
]
reduce.recipename = 'recipeBiasCreateMaster'
reduce.upars = [
'refresh=True',
]
# reduce.mode = ['sq', ]
# reduce.recipename = 'makeProcessedBias'
reduce.logfile = os.path.join(
tmpsubdir.dirname, tmpsubdir.basename,
'reduce_masterbias_{}.log'.format(request.param))
reduce.logmode = 'quiet'
reduce.suffix = '_{}_testMasterBias'.format(request.param)
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
reduce.runr()
# import pdb; pdb.set_trace()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Find the overscan-corrected bias files
rawfiles = glob.glob(
os.path.join(
tmpsubdir.dirname,
tmpsubdir.basename,
rawfilename.split('.')[0] + '*_overscanCorrect*.fits',
))
# Return filenames of raw, subtracted files
yield rawfiles, corrfile
# Execute teardown code
pass
def do_bias_subtract(self, get_or_create_tmpdir, request):
"""
Perform basic bias subtraction on the dark frame.
.. note::
Fixture.
"""
rawfilename = 'dark*{}*.fits'.format(request.param)
# Copy the raw data file into here
tmpsubdir, cal_service = get_or_create_tmpdir
# Find all the relevant files
# rawfiles = glob.glob(os.path.join(os.path.dirname(
# os.path.abspath(__file__)),
# 'testdata',
# rawfilename))
# for f in rawfiles:
# shutil.copy(f, os.path.join(tmpsubdir.dirname, tmpsubdir.basename))
rawfiles = glob.glob(
os.path.join(tmpsubdir.dirname, tmpsubdir.basename, rawfilename))
# Do the master bias generation
reduce = Reduce()
reduce.drpkg = 'ghostdr'
reduce.files = rawfiles[0]
reduce.mode = [
'test',
]
reduce.recipename = 'recipeDarkBiasCorrect'
# reduce.mode = ['sq', ]
# reduce.recipename = 'makeProcessedBias'
reduce.logfile = os.path.join(
tmpsubdir.dirname, tmpsubdir.basename,
'reduce_biascorrect_{}.log'.format(request.param))
reduce.logmode = 'quiet'
reduce.suffix = '_{}_testBiasCorrect'.format(request.param)
logutils.config(file_name=reduce.logfile, mode=reduce.logmode)
# import pdb; pdb.set_trace()
calibs = {
'processed_bias':
glob.glob(
os.path.join('calibrations', 'processed_bias',
'bias*{}*.fits'.format(request.param)))[0],
}
reduce.ucals = normalize_ucals(
reduce.files, ['{}:{}'.format(k, v) for k, v in calibs.items()])
# import pdb;
# pdb.set_trace()
reduce.runr()
corrfilename = '*' + reduce.suffix + '.fits'
corrfilename = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
glob.glob(corrfilename)[0])
corrfile = os.path.join(tmpsubdir.dirname, tmpsubdir.basename,
corrfilename)
# Return filenames of raw, subtracted files
yield rawfiles, corrfile, calibs
# Execute teardown code
for _ in glob.glob(
os.path.join(os.getcwd(), '*{}.fits'.format(reduce.suffix))):
os.remove(_)