def vanilla_pypeit_file(pypeit_file,
root,
spectrograph,
extension='.fits'):
"""
Write a vanilla PypeIt file.
Args:
pypeit_file (str):
Name of PypeIt file to be generated
root (str):
spectrograph (str):
Name of spectrograph
extension (str, optional):
File extension
Returns:
"""
# Generate
dfname = os.path.join(root, '*{0}*'.format(extension)) \
if os.path.isdir(root) else '{0}*{1}*'.format(root, extension)
# configuration lines
cfg_lines = ['[rdx]']
cfg_lines += [' spectrograph = {0}'.format(spectrograph)]
# cfg_lines += [' sortroot = {0}'.format(root)]
make_pypeit_file(pypeit_file,
spectrograph, [dfname],
cfg_lines=cfg_lines,
setup_mode=True)
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 test_initialization():
""" Load input PYPIT file
"""
# 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(''))
# Test
assert spectrograph.spectrograph == 'shane_kast_blue'
assert len(fitstbl) == 2
assert par['calibrations']['arcframe']['number'] == 1
def test_initialization():
""" Load input PypeIt file
"""
# 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(''))
# Test
assert spectrograph.name == 'shane_kast_blue'
assert len(fitstbl) == 8
# Clean-up
os.remove(data_path('test.calib'))
os.remove(data_path('test.pypeit'))
def main(args):
"""
This setups PypeIt files for fluxing, coadding and telluric corrections.
It will produce three files named as your_spectragraph.flux, your_spectragraph.coadd1d,
and your_spectragraph.tell
"""
allfiles = os.listdir(args.sci_path)
allfiles = np.sort(allfiles)
spec1dfiles = []
spec2dfiles = []
spec1dinfos = []
for ifile in allfiles:
if ('spec1d' in ifile) and ('.fits' in ifile):
spec1dfiles.append(ifile)
elif ('spec2d' in ifile) and ('.fits' in ifile):
spec2dfiles.append(ifile)
elif ('spec1d' in ifile) and ('.txt' in ifile):
spec1dinfos.append(ifile)
else:
msgs.warn('{:} is not a standard PypeIt output.'.format(ifile))
if len(spec2dfiles) > len(spec1dfiles):
msgs.warn('The following exposures do not have 1D extractions:')
for ii in range(len(spec2dfiles)):
if not os.path.exists(
os.path.join(args.sci_path, spec2dfiles[ii].replace(
'spec2d', 'spec1d'))):
msgs.info('\t {:}'.format(spec2dfiles[ii]))
if len(spec1dfiles) > 0:
par = io.fits_open(os.path.join(args.sci_path, spec1dfiles[0]))
## fluxing pypeit file
spectrograph = par[0].header['PYP_SPEC']
pypeline = par[0].header['PYPELINE']
flux_file = '{:}.flux'.format(spectrograph)
cfg_lines = ['[fluxcalib]']
cfg_lines += [
' extinct_correct = False # Set to True if your SENSFUNC derived with the UVIS algorithm\n'
]
cfg_lines += [
'# Please add your SENSFUNC file name below before running pypeit_flux_calib'
]
make_pypeit_file(flux_file,
spectrograph,
spec1dfiles,
cfg_lines=cfg_lines,
setup_mode=True)
fin = open(flux_file, "rt")
data = fin.read()
data = data.replace('spec1d_', os.path.join(args.sci_path, 'spec1d_'))
data = data.replace('data', 'flux')
fin.close()
fin = open(flux_file, "wt")
fin.write(data)
fin.close()
## coadd1d pypeit file
coadd1d_file = '{:}.coadd1d'.format(spectrograph)
cfg_lines = ['[coadd1d]']
cfg_lines += [
' coaddfile = YOUR_OUTPUT_FILE_NAME # Please set your output file name'
]
cfg_lines += [
' sensfuncfile = YOUR_SENSFUNC_FILE # Please set your SENSFUNC file name'
]
if pypeline == 'Echelle':
cfg_lines += [
' wave_method = velocity # creates a uniformly space grid in log10(lambda)\n'
]
else:
cfg_lines += [
' wave_method = linear # creates a uniformly space grid in lambda\n'
]
cfg_lines += ['# This file includes all extracted objects. You need to figure out which object you want to \n'+\
'# coadd before running pypeit_coadd_1dspec!!!']
spec1d_info = []
for ii in range(len(spec1dfiles)):
meta_tbl = Table.read(os.path.join(args.sci_path,
spec1dfiles[ii]).replace(
'.fits', '.txt'),
format='ascii.fixed_width')
_, indx = np.unique(meta_tbl['name'], return_index=True)
objects = meta_tbl[indx]
for jj in range(len(objects)):
spec1d_info.append(spec1dfiles[ii] + ' ' + objects['name'][jj])
make_pypeit_file(coadd1d_file,
spectrograph,
spec1d_info,
cfg_lines=cfg_lines,
setup_mode=True)
fin = open(coadd1d_file, "rt")
data = fin.read()
data = data.replace('spec1d_', os.path.join(args.sci_path, 'spec1d_'))
data = data.replace('data', 'coadd1d')
fin.close()
fin = open(coadd1d_file, "wt")
fin.write(data)
fin.close()
## tellfit pypeit file
tellfit_file = '{:}.tell'.format(spectrograph)
cfg_lines = ['[tellfit]']
if args.objmodel == 'qso':
cfg_lines += [' objmodel = qso']
cfg_lines += [' redshift = 0.0']
cfg_lines += [' bal_wv_min_max = 10000.,11000.']
elif args.objmodel == 'star':
cfg_lines += [' objmodel = star']
cfg_lines += [' star_type = A0']
cfg_lines += [' star_mag = 0.0']
elif args.objmodel == 'poly':
cfg_lines += [' objmodel = poly']
cfg_lines += [' polyorder = 5']
cfg_lines += [' fit_wv_min_max = 17000.0,22000.0']
with open(tellfit_file, 'w') as f:
f.write('# Auto-generated PypeIt file\n')
f.write('# {0}\n'.format(
time.strftime("%a %d %b %Y %H:%M:%S", time.localtime())))
f.write("\n")
f.write("# User-defined execution parameters\n")
f.write(
"# This is only an example. Make sure to change the following parameters accordingly.\n"
)
f.write('\n'.join(cfg_lines))
f.write('\n')
f.write('\n')
msgs.info('PypeIt file written to: {0}'.format(tellfit_file))
def run_on_science(pargs, script_Utils, calib_pypeit_file, ps_sci):
"""
Process a science frame
Args:
pargs (argparse.ArgumentParser):
Command line arguments
script_Utils:
calib_pypeit_file (str):
ps_sci (:class:`pypeit.pypeitsetup.PypeItSetup`):
"""
# Load up and slurp PypeIt file
ps = PypeItSetup.from_pypeit_file(calib_pypeit_file)
# Parse science file info
science_file = os.path.join(pargs.full_rawpath, pargs.science)
science_pypeit = calib_pypeit_file.replace('calib', 'science')
# Add to file list, it not present
if science_file not in ps.file_list:
ps.file_list += [science_file]
# Add to usrdata
new_row = {}
for key in ps.usrdata.keys():
new_row[key] = ps_sci.fitstbl[key][0]
ps.usrdata.add_row(new_row)
# Build
_ = ps.build_fitstbl()
# Remove any extraneous science files in the folder
gd_files = (ps.usrdata['filename'] == os.path.basename(science_file)) | (
ps.usrdata['frametype'] != 'science')
# Update
#ps.fitstbl.table = ps.fitstbl.table[gd_files]
#ps.file_list = np.array(ps.file_list)[gd_files].tolist()
ps.usrdata = ps.usrdata[gd_files]
# Generate PypeIt file
# TODO -- Generalize this with metadata.write_pypeit()
# Write the file
setup_lines = yaml.dump(utils.yamlify(ps.setup_dict)).split('\n')[:-1]
with io.StringIO() as ff:
ps.usrdata.write(ff, format='ascii.fixed_width')
data_lines = ff.getvalue().split('\n')[:-1]
paths = [os.path.dirname(item) for item in ps.file_list]
paths = np.unique(paths)
# Add to configs
if pargs.slit_spat is not None:
# Remove detnum
for kk, item in enumerate(ps.user_cfg):
if 'detnum' in item:
ps.user_cfg.pop(kk)
ridx = ps.user_cfg.index('[rdx]')
ps.user_cfg.insert(ridx + 1,
' slitspatnum = {0}'.format(pargs.slit_spat))
# this is to avoid that the default detnum (which was introduced for mosaic)
# will be passed to the reduction and crash it
ps.user_cfg.insert(ridx + 2, ' detnum = None')
else:
raise NotImplementedError('NOT READY: 118 of ql_deimos')
# Do it
make_pypeit_file(science_pypeit,
script_Utils.spectrograph.name, [],
cfg_lines=ps.user_cfg,
setup_lines=setup_lines,
sorted_files=data_lines,
paths=paths)
# Run me!
redux_path = os.path.dirname(science_pypeit) # Path to PypeIt file
run_pargs = run_pypeit.RunPypeIt.parse_args([
science_pypeit,
'-r={}'.format(redux_path),
])
run_pypeit.RunPypeIt.main(run_pargs)