def test_select_detectors():
# Generate a PYPIT file
pypit_file = data_path('test.pypeit')
make_pypeit_file(pypit_file,
'shane_kast_blue', [data_path('b*fits.gz')],
setup_mode=True)
# Perform the setup
setup = pypeitsetup.PypeItSetup.from_pypeit_file(pypit_file)
par, spectrograph, fitstbl = setup.run(sort_dir=data_path(''))
assert PypeIt.select_detectors(detnum=par['rdx']['detnum'], ndet=spectrograph.ndet) == [1], \
'Incorrect detectors selected.'
# Clean-up
os.remove(data_path('test.calib'))
os.remove(data_path('test.pypeit'))
assert np.array_equal(PypeIt.select_detectors(),
[1]), 'Incorrect detectors selected.'
assert np.array_equal(PypeIt.select_detectors(detnum=3, ndet=5), [3]), \
'Incorrect detectors selected.'
assert np.array_equal(PypeIt.select_detectors(ndet=5), [1,2,3,4,5]), \
'Incorrect detectors selected.'
assert np.array_equal(PypeIt.select_detectors(detnum=[1,3]), [1,3]), \
'Incorrect detectors selected.'
def main(args):
""" Executes 2d coadding
"""
# Load the file
if args.file is not None:
spectrograph, config_lines, spec2d_files = read_coadd2d_file(args.file)
# Parameters
# TODO: Shouldn't this reinstantiate the same parameters used in
# the PypeIt run that extracted the objects? Why are we not
# just passing the pypeit file?
spectrograph_def_par = spectrograph.default_pypeit_par()
par = par.PypeItPar.from_cfg_lines(
cfg_lines=spectrograph_def_par.to_config(),
merge_with=config_lines)
elif args.obj is not None:
# TODO: This needs to define the science path
spec2d_files = glob.glob('./Science/spec2d_*' + args.obj + '*')
head0 = fits.getheader(spec2d_files[0])
spectrograph_name = head0['SPECTROG']
spectrograph = load_spectrograph(spectrograph_name)
par = spectrograph.default_pypeit_par()
else:
msgs.error(
'You must either input a coadd2d file with --file or an object name with --obj'
)
# If detector was passed as an argument override whatever was in the coadd2d_file
if args.det is not None:
msgs.info("Restricting reductions to detector={}".format(args.det))
par['rdx']['detnum'] = int(args.det)
# Get headers and base names
spec1d_files = [
files.replace('spec2d', 'spec1d') for files in spec2d_files
]
head1d = fits.getheader(spec1d_files[0])
head2d = fits.getheader(spec2d_files[0])
if args.basename is None:
filename = os.path.basename(spec2d_files[0])
basename = filename.split('_')[1]
else:
basename = args.basename
# Write the par to disk
par_outfile = basename + '_coadd2d.par'
print("Writing the parameters to {}".format(par_outfile))
par.to_config(par_outfile)
# Now run the coadds
skysub_mode = head2d['SKYSUB']
ir_redux = True if 'DIFF' in skysub_mode else False
# Print status message
msgs_string = 'Reducing target {:s}'.format(basename) + msgs.newline()
msgs_string += 'Performing coadd of frames reduce with {:s} imaging'.format(
skysub_mode)
msgs_string += msgs.newline(
) + 'Combining frames in 2d coadd:' + msgs.newline()
for file in spec2d_files:
msgs_string += '{0:s}'.format(os.path.basename(file)) + msgs.newline()
msgs.info(msgs_string)
# TODO: This needs to be added to the parameter list for rdx
redux_path = os.getcwd()
master_dirname = os.path.basename(head2d['PYPMFDIR']) + '_coadd'
master_dir = os.path.join(redux_path, master_dirname)
# Make the new Master dir
if not os.path.isdir(master_dir):
msgs.info(
'Creating directory for Master output: {0}'.format(master_dir))
os.makedirs(master_dir)
# Instantiate the sci_dict
sci_dict = OrderedDict() # This needs to be ordered
sci_dict['meta'] = {}
sci_dict['meta']['vel_corr'] = 0.
sci_dict['meta']['ir_redux'] = ir_redux
# Find the detectors to reduce
detectors = PypeIt.select_detectors(detnum=par['rdx']['detnum'],
ndet=spectrograph.ndet)
if len(detectors) != spectrograph.ndet:
msgs.warn('Not reducing detectors: {0}'.format(' '.join([
str(d) for d in set(np.arange(spectrograph.ndet)) - set(detectors)
])))
# Loop on detectors
for det in detectors:
msgs.info("Working on detector {0}".format(det))
sci_dict[det] = {}
# Read in the images stacks and other clibration/meta data for this detector
stack_dict = coadd2d.load_coadd2d_stacks(spec2d_files, det)
sci_dict[det]['sciimg'], sci_dict[det]['sciivar'], sci_dict[det]['skymodel'], \
sci_dict[det]['objmodel'], sci_dict[det]['ivarmodel'], sci_dict[det]['outmask'], \
sci_dict[det]['specobjs'] \
= coadd2d.extract_coadd2d(stack_dict, master_dir, det, ir_redux=ir_redux,
par=par, show=args.show, show_peaks=args.peaks,
std=args.std, samp_fact=args.samp_fact)
# Make the new Science dir
# TODO: This needs to be defined by the user
scipath = os.path.join(redux_path, 'Science_coadd')
if not os.path.isdir(scipath):
msgs.info('Creating directory for Science output: {0}'.format(scipath))
os.makedirs(scipath)
# Save the results
save.save_all(sci_dict, stack_dict['master_key_dict'], master_dir,
spectrograph, head1d, head2d, scipath, basename)
def main(args):
import time
import os
import numpy as np
from pypeit.spectrographs.util import load_spectrograph
from pypeit import traceimage, edgetrace, biasframe
from pypeit.pypeit import PypeIt
from pypeit.core import parse
from IPython import embed
if args.pypeit_file is not None:
pypeit_file = args.pypeit_file
if not os.path.isfile(pypeit_file):
raise FileNotFoundError(
'File does not exist: {0}'.format(pypeit_file))
pypeit_file = os.path.abspath(pypeit_file)
redux_path = os.path.abspath(
os.path.split(pypeit_file)[0] if args.redux_path is None else args.
redux_path)
rdx = PypeIt(pypeit_file, redux_path=redux_path)
# Save the spectrograph
spec = rdx.spectrograph
# Get the calibration group to use
group = np.unique(
rdx.fitstbl['calib'])[0] if args.group is None else args.group
if group not in np.unique(rdx.fitstbl['calib']):
raise ValueError(
'Not a valid calibration group: {0}'.format(group))
# Find the rows in the metadata table with trace frames in the
# specified calibration group
tbl_rows = rdx.fitstbl.find_frames('trace',
calib_ID=int(group),
index=True)
# Master keyword
master_key_base = '_'.join(
rdx.fitstbl.master_key(tbl_rows[0]).split('_')[:2])
# Save the binning
binning = rdx.fitstbl['binning'][tbl_rows[0]]
# Save the full file paths
files = rdx.fitstbl.frame_paths(tbl_rows)
# Trace image processing parameters
proc_par = rdx.caliBrate.par['traceframe']
# Slit tracing parameters
trace_par = rdx.caliBrate.par['slitedges']
# Get the bias files, if requested
bias_rows = rdx.fitstbl.find_frames('bias',
calib_ID=int(group),
index=True)
bias_files = rdx.fitstbl.frame_paths(bias_rows)
bias_par = rdx.caliBrate.par['biasframe']
# Set the QA path
qa_path = rdx.qa_path
else:
spec = load_spectrograph(args.spectrograph)
master_key_base = 'A_1'
binning = '1,1' if args.binning is None else args.binning
if not os.path.isfile(args.trace_file):
raise FileNotFoundError('File does not exist: {0}'.format(
args.trace_file))
files = [os.path.abspath(args.trace_file)]
redux_path = os.path.abspath(
os.path.split(files[0])[0] if args.redux_path is None else args.
redux_path)
par = spec.default_pypeit_par()
proc_par = par['calibrations']['traceframe']
trace_par = par['calibrations']['slitedges']
bias_files = None
bias_par = None
# Set the QA path
qa_path = os.path.join(os.path.abspath(os.path.split(files[0])[0]),
'QA')
detectors = np.arange(spec.ndet) + 1 if args.detector is None else [
args.detector
]
master_dir = os.path.join(redux_path, args.master_dir)
for det in detectors:
# Master keyword for output file name
master_key = '{0}_{1}'.format(master_key_base, str(det).zfill(2))
# Get the bias frame if requested
if bias_files is None:
proc_par['process']['bias'] = 'skip'
msbias = None
else:
biasFrame = biasframe.BiasFrame(spec,
files=bias_files,
det=det,
par=bias_par,
master_key=master_key,
master_dir=master_dir)
msbias = biasFrame.build_image()
msbpm = spec.bpm(files[0], det)
# Build the trace image
traceImage = traceimage.TraceImage(spec,
files=files,
det=det,
par=proc_par,
bias=msbias)
traceImage.build_image(bias=msbias, bpm=msbpm)
# Trace the slit edges
t = time.perf_counter()
edges = edgetrace.EdgeTraceSet(spec,
trace_par,
master_key=master_key,
master_dir=master_dir,
img=traceImage,
det=det,
bpm=msbpm,
auto=True,
debug=args.debug,
show_stages=args.show,
qa_path=qa_path)
print('Tracing for detector {0} finished in {1} s.'.format(
det,
time.perf_counter() - t))
edges.save()
return 0
def main(args):
""" Executes 2d coadding
"""
msgs.warn('PATH =' + os.getcwd())
# Load the file
if args.file is not None:
spectrograph, config_lines, spec2d_files = read_coadd2d_file(args.file)
# Parameters
# TODO: Shouldn't this reinstantiate the same parameters used in
# the PypeIt run that extracted the objects? Why are we not
# just passing the pypeit file?
# JFH: The reason is that the coadd2dfile may want different reduction parameters
spectrograph_def_par = spectrograph.default_pypeit_par()
parset = par.PypeItPar.from_cfg_lines(cfg_lines=spectrograph_def_par.to_config(),
merge_with=config_lines)
elif args.obj is not None:
# TODO: We should probably be reading the pypeit file and using those parameters here rather than using the
# default parset.
# TODO: This needs to define the science path
spec2d_files = glob.glob('./Science/spec2d_*' + args.obj + '*')
head0 = fits.getheader(spec2d_files[0])
spectrograph_name = head0['SPECTROG']
spectrograph = load_spectrograph(spectrograph_name)
parset = spectrograph.default_pypeit_par()
else:
msgs.error('You must either input a coadd2d file with --file or an object name with --obj')
# Update with configuration specific parameters (which requires science file) and initialize spectrograph
spectrograph_cfg_lines = spectrograph.config_specific_par(spec2d_files[0]).to_config()
parset = par.PypeItPar.from_cfg_lines(cfg_lines=spectrograph_cfg_lines, merge_with=parset.to_config())
# If detector was passed as an argument override whatever was in the coadd2d_file
if args.det is not None:
msgs.info("Restricting reductions to detector={}".format(args.det))
parset['rdx']['detnum'] = int(args.det)
# Get headers (if possible) and base names
spec1d_files = [files.replace('spec2d', 'spec1d') for files in spec2d_files]
head1d = None
for spec1d_file in spec1d_files:
if os.path.isfile(spec1d_file):
head1d = fits.getheader(spec1d_file)
break
if head1d is None:
msgs.warn("No 1D spectra so am generating a dummy header for output")
head1d = io.initialize_header()
head2d = fits.getheader(spec2d_files[0])
if args.basename is None:
filename = os.path.basename(spec2d_files[0])
basename = filename.split('_')[2]
else:
basename = args.basename
# Write the par to disk
par_outfile = basename+'_coadd2d.par'
print("Writing the parameters to {}".format(par_outfile))
parset.to_config(par_outfile)
# Now run the coadds
skysub_mode = head2d['SKYSUB']
ir_redux = True if 'DIFF' in skysub_mode else False
# Print status message
msgs_string = 'Reducing target {:s}'.format(basename) + msgs.newline()
msgs_string += 'Performing coadd of frames reduce with {:s} imaging'.format(skysub_mode)
msgs_string += msgs.newline() + 'Combining frames in 2d coadd:' + msgs.newline()
for file in spec2d_files:
msgs_string += '{0:s}'.format(os.path.basename(file)) + msgs.newline()
msgs.info(msgs_string)
# TODO: This needs to be added to the parameter list for rdx
redux_path = os.getcwd()
master_dirname = os.path.basename(head2d['PYPMFDIR']) + '_coadd'
master_dir = os.path.join(redux_path, master_dirname)
# Make the new Master dir
if not os.path.isdir(master_dir):
msgs.info('Creating directory for Master output: {0}'.format(master_dir))
os.makedirs(master_dir)
# Instantiate the sci_dict
sci_dict = OrderedDict() # This needs to be ordered
sci_dict['meta'] = {}
sci_dict['meta']['vel_corr'] = 0.
sci_dict['meta']['ir_redux'] = ir_redux
# Find the detectors to reduce
detectors = PypeIt.select_detectors(detnum=parset['rdx']['detnum'], ndet=spectrograph.ndet)
if len(detectors) != spectrograph.ndet:
msgs.warn('Not reducing detectors: {0}'.format(' '.join([str(d) for d in
set(np.arange(spectrograph.ndet) + 1) - set(detectors)])))
# Loop on detectors
for det in detectors:
msgs.info("Working on detector {0}".format(det))
sci_dict[det] = {}
# Instantiate Coadd2d
coadd = coadd2d.CoAdd2D.get_instance(spec2d_files, spectrograph, parset, det=det,
offsets=parset['coadd2d']['offsets'],
weights=parset['coadd2d']['weights'],
ir_redux=ir_redux,
debug_offsets=args.debug_offsets, debug=args.debug,
samp_fact=args.samp_fact)
# Coadd the slits
coadd_dict_list = coadd.coadd(only_slits=None) # TODO implement only_slits later
# Create the psuedo images
psuedo_dict = coadd.create_psuedo_image(coadd_dict_list)
# Reduce
msgs.info('Running the extraction')
sci_dict[det]['sciimg'], sci_dict[det]['sciivar'], sci_dict[det]['skymodel'], sci_dict[det]['objmodel'], \
sci_dict[det]['ivarmodel'], sci_dict[det]['outmask'], sci_dict[det]['specobjs'] = coadd.reduce(
psuedo_dict, show = args.show, show_peaks = args.peaks)
# Save psuedo image master files
coadd.save_masters(master_dir)
# Make the new Science dir
# TODO: This needs to be defined by the user
scipath = os.path.join(redux_path, 'Science_coadd')
if not os.path.isdir(scipath):
msgs.info('Creating directory for Science output: {0}'.format(scipath))
os.makedirs(scipath)
# Save the results
save.save_all(sci_dict, coadd.stack_dict['master_key_dict'], master_dir, spectrograph, head1d,
head2d, scipath, basename)#, binning=coadd.binning)
def main(args):
""" Executes 2d coadding
"""
msgs.warn('PATH =' + os.getcwd())
# Load the file
if args.file is not None:
spectrograph_name, config_lines, spec2d_files = io.read_spec2d_file(
args.file, filetype="coadd2d")
spectrograph = load_spectrograph(spectrograph_name)
# Parameters
# TODO: Shouldn't this reinstantiate the same parameters used in
# the PypeIt run that extracted the objects? Why are we not
# just passing the pypeit file?
# JFH: The reason is that the coadd2dfile may want different reduction parameters
spectrograph_def_par = spectrograph.default_pypeit_par()
parset = par.PypeItPar.from_cfg_lines(
cfg_lines=spectrograph_def_par.to_config(),
merge_with=config_lines)
elif args.obj is not None:
# TODO: We should probably be reading the pypeit file and using those parameters here rather than using the
# default parset.
# TODO: This needs to define the science path
spec2d_files = glob.glob('./Science/spec2d_*' + args.obj + '*')
head0 = fits.getheader(spec2d_files[0])
spectrograph_name = head0['PYP_SPEC']
spectrograph = load_spectrograph(spectrograph_name)
parset = spectrograph.default_pypeit_par()
else:
msgs.error(
'You must either input a coadd2d file with --file or an object name with --obj'
)
# Update with configuration specific parameters (which requires science file) and initialize spectrograph
spectrograph_cfg_lines = spectrograph.config_specific_par(
spec2d_files[0]).to_config()
parset = par.PypeItPar.from_cfg_lines(cfg_lines=spectrograph_cfg_lines,
merge_with=parset.to_config())
# If detector was passed as an argument override whatever was in the coadd2d_file
if args.det is not None:
msgs.info("Restricting reductions to detector={}".format(args.det))
parset['rdx']['detnum'] = int(args.det)
# Get headers (if possible) and base names
spec1d_files = [
files.replace('spec2d', 'spec1d') for files in spec2d_files
]
head1d = None
for spec1d_file in spec1d_files:
if os.path.isfile(spec1d_file):
head1d = fits.getheader(spec1d_file)
break
if head1d is None:
msgs.warn("No 1D spectra so am generating a dummy header for output")
head1d = io.initialize_header()
head2d = fits.getheader(spec2d_files[0])
if args.basename is None:
filename = os.path.basename(spec2d_files[0])
basename = filename.split('_')[2]
else:
basename = args.basename
# Write the par to disk
par_outfile = basename + '_coadd2d.par'
print("Writing the parameters to {}".format(par_outfile))
parset.to_config(par_outfile)
# Now run the coadds
skysub_mode = head2d['SKYSUB']
ir_redux = True if 'DIFF' in skysub_mode else False
# Print status message
msgs_string = 'Reducing target {:s}'.format(basename) + msgs.newline()
msgs_string += 'Performing coadd of frames reduce with {:s} imaging'.format(
skysub_mode)
msgs_string += msgs.newline(
) + 'Combining frames in 2d coadd:' + msgs.newline()
for file in spec2d_files:
msgs_string += '{0:s}'.format(os.path.basename(file)) + msgs.newline()
msgs.info(msgs_string)
# TODO: This needs to be added to the parameter list for rdx
redux_path = os.getcwd()
master_dirname = os.path.basename(head2d['PYPMFDIR']) + '_coadd'
master_dir = os.path.join(redux_path, master_dirname)
# Make the new Master dir
if not os.path.isdir(master_dir):
msgs.info(
'Creating directory for Master output: {0}'.format(master_dir))
os.makedirs(master_dir)
# Instantiate the sci_dict
sci_dict = OrderedDict() # This needs to be ordered
sci_dict['meta'] = {}
sci_dict['meta']['vel_corr'] = 0.
sci_dict['meta']['ir_redux'] = ir_redux
# Find the detectors to reduce
detectors = PypeIt.select_detectors(detnum=parset['rdx']['detnum'],
ndet=spectrograph.ndet)
if len(detectors) != spectrograph.ndet:
msgs.warn('Not reducing detectors: {0}'.format(' '.join([
str(d)
for d in set(np.arange(spectrograph.ndet) + 1) - set(detectors)
])))
# Loop on detectors
for det in detectors:
msgs.info("Working on detector {0}".format(det))
sci_dict[det] = {}
# Instantiate Coadd2d
coadd = coadd2d.CoAdd2D.get_instance(
spec2d_files,
spectrograph,
parset,
det=det,
offsets=parset['coadd2d']['offsets'],
weights=parset['coadd2d']['weights'],
ir_redux=ir_redux,
debug_offsets=args.debug_offsets,
debug=args.debug,
samp_fact=args.samp_fact)
# Coadd the slits
coadd_dict_list = coadd.coadd(
only_slits=None) # TODO implement only_slits later
# Create the pseudo images
pseudo_dict = coadd.create_pseudo_image(coadd_dict_list)
# Reduce
msgs.info('Running the extraction')
# TODO -- This should mirror what is in pypeit.extract_one
# TODO -- JFH :: This ought to return a Spec2DObj and SpecObjs which would be slurped into
# AllSpec2DObj and all_specobsj, as below.
# TODO -- JFH -- Check that the slits we are using are correct
sci_dict[det]['sciimg'], sci_dict[det]['sciivar'], sci_dict[det]['skymodel'], sci_dict[det]['objmodel'], \
sci_dict[det]['ivarmodel'], sci_dict[det]['outmask'], sci_dict[det]['specobjs'], sci_dict[det]['detector'], \
sci_dict[det]['slits'], sci_dict[det]['tilts'], sci_dict[det]['waveimg'] = coadd.reduce(
pseudo_dict, show = args.show, show_peaks = args.peaks)
# Save pseudo image master files
#coadd.save_masters()
# Make the new Science dir
# TODO: This needs to be defined by the user
scipath = os.path.join(redux_path, 'Science_coadd')
if not os.path.isdir(scipath):
msgs.info('Creating directory for Science output: {0}'.format(scipath))
os.makedirs(scipath)
# THE FOLLOWING MIMICS THE CODE IN pypeit.save_exposure()
# TODO -- These lines should be above once reduce() passes back something sensible
all_specobjs = specobjs.SpecObjs()
for det in detectors:
all_specobjs.add_sobj(sci_dict[det]['specobjs'])
# Write
outfile1d = os.path.join(scipath, 'spec1d_{:s}.fits'.format(basename))
subheader = spectrograph.subheader_for_spec(head2d, head2d)
all_specobjs.write_to_fits(subheader, outfile1d)
# 2D spectra
# TODO -- These lines should be above once reduce() passes back something sensible
all_spec2d = spec2dobj.AllSpec2DObj()
all_spec2d['meta']['ir_redux'] = ir_redux
for det in detectors:
all_spec2d[det] = spec2dobj.Spec2DObj(
det=det,
sciimg=sci_dict[det]['sciimg'],
ivarraw=sci_dict[det]['sciivar'],
skymodel=sci_dict[det]['skymodel'],
objmodel=sci_dict[det]['objmodel'],
ivarmodel=sci_dict[det]['ivarmodel'],
scaleimg=np.array([1.0], dtype=np.float),
bpmmask=sci_dict[det]['outmask'],
detector=sci_dict[det]['detector'],
slits=sci_dict[det]['slits'],
waveimg=sci_dict[det]['waveimg'],
tilts=sci_dict[det]['tilts'],
sci_spat_flexure=None,
sci_spec_flexure=None,
vel_corr=None,
vel_type=None)
# Build header
outfile2d = os.path.join(scipath, 'spec2d_{:s}.fits'.format(basename))
pri_hdr = all_spec2d.build_primary_hdr(
head2d,
spectrograph,
subheader=subheader,
# TODO -- JFH :: Decide if we need any of these
redux_path=None,
master_key_dict=None,
master_dir=None)
# Write
all_spec2d.write_to_fits(outfile2d, pri_hdr=pri_hdr)
def main(args):
import time
import os
import numpy as np
from pypeit.spectrographs.util import load_spectrograph
from pypeit import edgetrace
from pypeit import slittrace
from pypeit.pypeit import PypeIt
from pypeit.images import buildimage
from pypeit import masterframe
from IPython import embed
if args.pypeit_file is not None:
pypeit_file = args.pypeit_file
if not os.path.isfile(pypeit_file):
raise FileNotFoundError('File does not exist: {0}'.format(pypeit_file))
pypeit_file = os.path.abspath(pypeit_file)
redux_path = os.path.abspath(os.path.split(pypeit_file)[0]
if args.redux_path is None else args.redux_path)
rdx = PypeIt(pypeit_file, redux_path=redux_path)
detectors = rdx.par['rdx']['detnum'] if args.detector is None else args.detector
# Save the spectrograph
spec = rdx.spectrograph
# Get the calibration group to use
group = np.unique(rdx.fitstbl['calib'])[0] if args.group is None else args.group
if group not in np.unique(rdx.fitstbl['calib']):
raise ValueError('Not a valid calibration group: {0}'.format(group))
# Find the rows in the metadata table with trace frames in the
# specified calibration group
tbl_rows = rdx.fitstbl.find_frames('trace', calib_ID=int(group), index=True)
# Master keyword
master_key_base = '_'.join(rdx.fitstbl.master_key(tbl_rows[0]).split('_')[:2])
# Save the binning
binning = rdx.fitstbl['binning'][tbl_rows[0]]
# Save the full file paths
files = rdx.fitstbl.frame_paths(tbl_rows)
# Trace image processing parameters
proc_par = rdx.par['calibrations']['traceframe']
# Slit tracing parameters
trace_par = rdx.par['calibrations']['slitedges']
# Get the bias files, if requested
bias_rows = rdx.fitstbl.find_frames('bias', calib_ID=int(group), index=True)
bias_files = rdx.fitstbl.frame_paths(bias_rows)
bias_par = rdx.par['calibrations']['biasframe']
if len(bias_files) == 0:
bias_files = None
# Get the dark files, if requested
dark_rows = rdx.fitstbl.find_frames('dark', calib_ID=int(group), index=True)
dark_files = rdx.fitstbl.frame_paths(dark_rows)
dark_par = rdx.par['calibrations']['darkframe']
if len(dark_files) == 0:
dark_files = None
# Set the QA path
qa_path = rdx.qa_path
else:
detectors = args.detector
spec = load_spectrograph(args.spectrograph)
master_key_base = 'A_1'
binning = '1,1' if args.binning is None else args.binning
if not os.path.isfile(args.trace_file):
raise FileNotFoundError('File does not exist: {0}'.format(args.trace_file))
files = [os.path.abspath(args.trace_file)]
redux_path = os.path.abspath(os.path.split(files[0])[0]
if args.redux_path is None else args.redux_path)
par = spec.default_pypeit_par()
proc_par = par['calibrations']['traceframe']
trace_par = par['calibrations']['slitedges']
bias_files = None
bias_par = None
dark_files = None
dark_par = None
# Set the QA path
qa_path = os.path.join(os.path.abspath(os.path.split(files[0])[0]), 'QA')
if detectors is None:
detectors = np.arange(spec.ndet)+1
elif isinstance(detectors, (int, tuple)):
detectors = [detectors]
elif any([isinstance(d,str) for d in detectors]):
detectors = [eval(d) for d in detectors]
master_dir = os.path.join(redux_path, args.master_dir)
for det in detectors:
# Master keyword for output file name
master_key = f'{master_key_base}_{spec.get_det_name(det)}'
# Get the bias frame if requested
if bias_files is None:
proc_par['process']['use_biasimage'] = False
msbias = None
else:
msbias = buildimage.buildimage_fromlist(spec, det, bias_par, bias_files)
# Get the dark frame if requested
if dark_files is None:
proc_par['process']['use_darkimage'] = False
msdark = None
else:
msdark = buildimage.buildimage_fromlist(spec, det, dark_par, dark_files)
msbpm = spec.bpm(files[0], det)
# Build the trace image
traceImage = buildimage.buildimage_fromlist(spec, det, proc_par, files, bias=msbias,
bpm=msbpm, dark=msdark)
# Trace the slit edges
t = time.perf_counter()
edges = edgetrace.EdgeTraceSet(traceImage, spec, trace_par, auto=True,
debug=args.debug, show_stages=args.show,
qa_path=qa_path)
print('Tracing for detector {0} finished in {1} s.'.format(det, time.perf_counter()-t))
# Write the MasterEdges file
edge_masterframe_name = masterframe.construct_file_name(edgetrace.EdgeTraceSet,
master_key,
master_dir=master_dir)
edges.to_master_file(edge_masterframe_name)
# Write the MasterSlits file
slit_masterframe_name = masterframe.construct_file_name(slittrace.SlitTraceSet,
master_key,
master_dir=master_dir)
edges.get_slits().to_master_file(slit_masterframe_name)
return 0
