def build_wv_calib(self, arccen, method, skip_QA=False):
"""
Main routine to generate the wavelength solutions in a loop over slits
Wrapper to arc.simple_calib or arc.calib_with_arclines
self.maskslits is updated for slits that fail
Args:
method : str
'simple' -- arc.simple_calib
'arclines' -- arc.calib_with_arclines
'holy-grail' -- wavecal.autoid.HolyGrail
'reidentify' -- wavecal.auotid.ArchiveReid
'full_template' -- wavecal.auotid.full_template
skip_QA (bool, optional)
Returns:
dict: self.wv_calib
"""
# Obtain a list of good slits
ok_mask = np.where(~self.maskslits)[0]
# Obtain calibration for all slits
if method == 'simple':
lines = self.par['lamps']
line_lists = waveio.load_line_lists(lines)
self.wv_calib = arc.simple_calib_driver(
self.msarc,
line_lists,
arccen,
ok_mask,
nfitpix=self.par['nfitpix'],
IDpixels=self.par['IDpixels'],
IDwaves=self.par['IDwaves'])
elif method == 'semi-brute':
# TODO: THIS IS CURRENTLY BROKEN
debugger.set_trace()
final_fit = {}
for slit in ok_mask:
# HACKS BY JXP
self.par['wv_cen'] = 8670.
self.par['disp'] = 1.524
# ToDO remove these hacks and use the parset in semi_brute
best_dict, ifinal_fit \
= autoid.semi_brute(arccen[:, slit], self.par['lamps'], self.par['wv_cen'],
self.par['disp'], match_toler=self.par['match_toler'],
func=self.par['func'], n_first=self.par['n_first'],
sigrej_first=self.par['n_first'],
n_final=self.par['n_final'],
sigrej_final=self.par['sigrej_final'],
sigdetect=self.par['sigdetect'],
nonlinear_counts= self.nonlinear_counts)
final_fit[str(slit)] = ifinal_fit.copy()
elif method == 'basic':
final_fit = {}
for slit in ok_mask:
status, ngd_match, match_idx, scores, ifinal_fit = \
autoid.basic(arccen[:, slit], self.par['lamps'], self.par['wv_cen'],
self.par['disp'], nonlinear_counts=self.nonlinear_counts)
final_fit[str(slit)] = ifinal_fit.copy()
if status != 1:
self.maskslits[slit] = True
elif method == 'holy-grail':
# Sometimes works, sometimes fails
arcfitter = autoid.HolyGrail(arccen, par=self.par, ok_mask=ok_mask)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'reidentify':
# Now preferred
# Slit positions
arcfitter = autoid.ArchiveReid(arccen,
self.spectrograph,
self.par,
ok_mask=ok_mask,
slit_spat_pos=self.slit_spat_pos)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'full_template':
# Now preferred
if self.binspectral is None:
msgs.error(
"You must specify binspectral for the full_template method!"
)
final_fit = autoid.full_template(arccen,
self.par,
ok_mask,
self.det,
self.binspectral,
nsnippet=self.par['nsnippet'])
else:
msgs.error(
'Unrecognized wavelength calibration method: {:}'.format(
method))
self.wv_calib = final_fit
# Remake mask (*mainly for the QA that follows*)
self.maskslits = self.make_maskslits(len(self.maskslits))
ok_mask = np.where(~self.maskslits)[0]
# QA
if not skip_QA:
for slit in ok_mask:
outfile = qa.set_qa_filename(self.master_key,
'arc_fit_qa',
slit=slit,
out_dir=self.qa_path)
autoid.arc_fit_qa(self.wv_calib[str(slit)], outfile=outfile)
# Return
self.steps.append(inspect.stack()[0][3])
return self.wv_calib
def build_wv_calib(self, arccen, method, skip_QA=False):
"""
Main routine to generate the wavelength solutions in a loop over slits
Wrapper to arc.simple_calib or arc.calib_with_arclines
self.maskslits is updated for slits that fail
Args:
method : str
'simple' -- arc.simple_calib
'arclines' -- arc.calib_with_arclines
'holy-grail' -- wavecal.autoid.HolyGrail
'reidentify' -- wavecal.auotid.ArchiveReid
'identify' -- wavecal.identify.Identify
'full_template' -- wavecal.auotid.full_template
skip_QA (bool, optional)
Returns:
dict: self.wv_calib
"""
# Obtain a list of good slits
ok_mask_idx = np.where(np.invert(self.wvc_bpm))[0]
# Obtain calibration for all slits
if method == 'simple':
lines = self.par['lamps']
line_lists = waveio.load_line_lists(lines)
final_fit = arc.simple_calib_driver(
line_lists,
arccen,
ok_mask_idx,
n_final=self.par['n_final'],
sigdetect=self.par['sigdetect'],
IDpixels=self.par['IDpixels'],
IDwaves=self.par['IDwaves'])
elif method == 'holy-grail':
# Sometimes works, sometimes fails
arcfitter = autoid.HolyGrail(
arccen,
par=self.par,
ok_mask=ok_mask_idx,
nonlinear_counts=self.nonlinear_counts)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'identify':
final_fit = {}
# Manually identify lines
msgs.info("Initializing the wavelength calibration tool")
embed(header='line 222 wavecalib.py')
for slit_idx in ok_mask_idx:
arcfitter = Identify.initialise(arccen,
self.slits,
slit=slit_idx,
par=self.par)
final_fit[str(slit_idx)] = arcfitter.get_results()
arcfitter.store_solution(final_fit[str(slit_idx)],
"",
self.binspectral,
specname=self.spectrograph.name,
gratname="UNKNOWN",
dispangl="UNKNOWN")
elif method == 'reidentify':
# Now preferred
# Slit positions
arcfitter = autoid.ArchiveReid(
arccen,
self.spectrograph,
self.par,
ok_mask=ok_mask_idx,
#slit_spat_pos=self.spat_coo,
orders=self.orders,
nonlinear_counts=self.nonlinear_counts)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'full_template':
# Now preferred
if self.binspectral is None:
msgs.error(
"You must specify binspectral for the full_template method!"
)
final_fit = autoid.full_template(
arccen,
self.par,
ok_mask_idx,
self.det,
self.binspectral,
nonlinear_counts=self.nonlinear_counts,
nsnippet=self.par['nsnippet'])
else:
msgs.error(
'Unrecognized wavelength calibration method: {:}'.format(
method))
# Build the DataContainer
# Loop on WaveFit items
tmp = []
for idx in range(self.slits.nslits):
item = final_fit.pop(str(idx))
if item is None: # Add an empty WaveFit
tmp.append(wv_fitting.WaveFit(self.slits.spat_id[idx]))
else:
# This is for I/O naming
item.spat_id = self.slits.spat_id[idx]
tmp.append(item)
self.wv_calib = WaveCalib(
wv_fits=np.asarray(tmp),
arc_spectra=arccen,
nslits=self.slits.nslits,
spat_ids=self.slits.spat_id,
PYP_SPEC=self.spectrograph.name,
)
# Update mask
self.update_wvmask()
#TODO For generalized echelle (not hard wired) assign order number here before, i.e. slits.ech_order
# QA
if not skip_QA:
ok_mask_idx = np.where(np.invert(self.wvc_bpm))[0]
for slit_idx in ok_mask_idx:
outfile = qa.set_qa_filename(
self.master_key,
'arc_fit_qa',
slit=self.slits.slitord_id[slit_idx],
out_dir=self.qa_path)
#
#autoid.arc_fit_qa(self.wv_calib[str(self.slits.slitord_id[slit_idx])],
# outfile=outfile)
autoid.arc_fit_qa(
self.wv_calib.wv_fits[slit_idx],
#str(self.slits.slitord_id[slit_idx]),
outfile=outfile)
# Return
self.steps.append(inspect.stack()[0][3])
return self.wv_calib
def build_wv_calib(self, arccen, method, skip_QA=False):
"""
Main routine to generate the wavelength solutions in a loop over slits
Wrapper to arc.simple_calib or arc.calib_with_arclines
self.maskslits is updated for slits that fail
Args:
method : str
'simple' -- arc.simple_calib
'arclines' -- arc.calib_with_arclines
'holy-grail' -- wavecal.autoid.HolyGrail
'reidentify' -- wavecal.auotid.ArchiveReid
'identify' -- wavecal.identify.Identify
'full_template' -- wavecal.auotid.full_template
skip_QA (bool, optional)
Returns:
dict: self.wv_calib
"""
# Obtain a list of good slits
ok_mask = np.where(np.invert(self.maskslits))[0]
# Obtain calibration for all slits
if method == 'simple':
lines = self.par['lamps']
line_lists = waveio.load_line_lists(lines)
final_fit = arc.simple_calib_driver(
line_lists,
arccen,
ok_mask,
n_final=self.par['n_final'],
sigdetect=self.par['sigdetect'],
IDpixels=self.par['IDpixels'],
IDwaves=self.par['IDwaves'])
elif method == 'semi-brute':
# TODO: THIS IS CURRENTLY BROKEN
embed()
final_fit = {}
for slit in ok_mask:
# HACKS BY JXP
self.par['wv_cen'] = 8670.
self.par['disp'] = 1.524
# ToDO remove these hacks and use the parset in semi_brute
best_dict, ifinal_fit \
= autoid.semi_brute(arccen[:, slit], self.par['lamps'], self.par['wv_cen'],
self.par['disp'], match_toler=self.par['match_toler'],
func=self.par['func'], n_first=self.par['n_first'],
sigrej_first=self.par['n_first'],
n_final=self.par['n_final'],
sigrej_final=self.par['sigrej_final'],
sigdetect=self.par['sigdetect'],
nonlinear_counts= self.nonlinear_counts)
final_fit[str(slit)] = ifinal_fit.copy()
elif method == 'basic':
final_fit = {}
for slit in ok_mask:
status, ngd_match, match_idx, scores, ifinal_fit = \
autoid.basic(arccen[:, slit], self.par['lamps'], self.par['wv_cen'],
self.par['disp'], nonlinear_counts=self.nonlinear_counts)
final_fit[str(slit)] = ifinal_fit.copy()
if status != 1:
self.maskslits[slit] = True
elif method == 'holy-grail':
# Sometimes works, sometimes fails
arcfitter = autoid.HolyGrail(arccen, par=self.par, ok_mask=ok_mask)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'identify':
final_fit = {}
# Manually identify lines
msgs.info("Initializing the wavelength calibration tool")
# TODO: Move this loop to the GUI initalise method
embed()
for slit in ok_mask:
arcfitter = gui_identify.initialise(arccen,
slit=slit,
par=self.par)
final_fit[str(slit)] = arcfitter.get_results()
if final_fit[str(slit)] is not None:
ans = 'y'
# ans = ''
# while ans != 'y' and ans != 'n':
# ans = input("Would you like to store this wavelength solution in the archive? (y/n): ")
if ans == 'y' and final_fit[str(
slit)]['rms'] < self.par['rms_threshold']:
# Store the results in the user reid arxiv
specname = self.spectrograph.spectrograph
gratname = "UNKNOWN" # input("Please input the grating name: ")
dispangl = "UNKNOWN" # input("Please input the dispersion angle: ")
templates.pypeit_identify_record(
final_fit[str(slit)], self.binspectral, specname,
gratname, dispangl)
msgs.info("Your wavelength solution has been stored")
msgs.info(
"Please consider sending your solution to the PYPEIT team!"
)
elif method == 'reidentify':
# Now preferred
# Slit positions
arcfitter = autoid.ArchiveReid(arccen,
self.spectrograph,
self.par,
ok_mask=ok_mask,
slit_spat_pos=self.slit_spat_pos)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'full_template':
# Now preferred
if self.binspectral is None:
msgs.error(
"You must specify binspectral for the full_template method!"
)
final_fit = autoid.full_template(arccen,
self.par,
ok_mask,
self.det,
self.binspectral,
nsnippet=self.par['nsnippet'])
else:
msgs.error(
'Unrecognized wavelength calibration method: {:}'.format(
method))
self.wv_calib = final_fit
# Remake mask (*mainly for the QA that follows*)
self.maskslits = self.make_maskslits(len(self.maskslits))
ok_mask = np.where(np.invert(self.maskslits))[0]
# QA
if not skip_QA:
for slit in ok_mask:
outfile = qa.set_qa_filename(self.master_key,
'arc_fit_qa',
slit=slit,
out_dir=self.qa_path)
autoid.arc_fit_qa(self.wv_calib[str(slit)], outfile=outfile)
# Return
self.steps.append(inspect.stack()[0][3])
return self.wv_calib
def build_wv_calib(self, arccen, method, skip_QA=False):
"""
Main routine to generate the wavelength solutions in a loop over slits
Wrapper to arc.simple_calib or arc.calib_with_arclines
self.maskslits is updated for slits that fail
Args:
method : str
'simple' -- arc.simple_calib
'arclines' -- arc.calib_with_arclines
'holy-grail' -- wavecal.autoid.HolyGrail
'reidentify' -- wavecal.auotid.ArchiveReid
'identify' -- wavecal.identify.Identify
'full_template' -- wavecal.auotid.full_template
skip_QA (bool, optional)
Returns:
dict: self.wv_calib
"""
# Obtain a list of good slits
ok_mask_idx = np.where(np.invert(self.wvc_bpm))[0]
# Obtain calibration for all slits
if method == 'simple':
lines = self.par['lamps']
line_lists = waveio.load_line_lists(lines)
final_fit = arc.simple_calib_driver(
line_lists,
arccen,
ok_mask_idx,
n_final=self.par['n_final'],
sigdetect=self.par['sigdetect'],
IDpixels=self.par['IDpixels'],
IDwaves=self.par['IDwaves'])
# elif method == 'basic':
# final_fit = {}
# for slit in ok_mask:
# status, ngd_match, match_idx, scores, ifinal_fit = \
# autoid.basic(arccen[:, slit], self.par['lamps'], self.par['wv_cen'],
# self.par['disp'], nonlinear_counts=self.nonlinear_counts)
# final_fit[str(slit)] = ifinal_fit.copy()
# if status != 1:
# self.maskslits[slit] = True
elif method == 'holy-grail':
# Sometimes works, sometimes fails
arcfitter = autoid.HolyGrail(
arccen,
par=self.par,
ok_mask=ok_mask_idx,
nonlinear_counts=self.nonlinear_counts)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'identify':
final_fit = {}
# Manually identify lines
msgs.info("Initializing the wavelength calibration tool")
# TODO: Move this loop to the GUI initalise method
embed()
for slit_idx in ok_mask_idx:
arcfitter = gui_identify.initialise(arccen,
slit=slit_idx,
par=self.par)
final_fit[str(slit_idx)] = arcfitter.get_results()
if final_fit[str(slit_idx)] is not None:
ans = 'y'
# ans = ''
# while ans != 'y' and ans != 'n':
# ans = input("Would you like to store this wavelength solution in the archive? (y/n): ")
if ans == 'y' and final_fit[str(
slit_idx)]['rms'] < self.par['rms_threshold']:
# Store the results in the user reid arxiv
specname = self.spectrograph.spectrograph
gratname = "UNKNOWN" # input("Please input the grating name: ")
dispangl = "UNKNOWN" # input("Please input the dispersion angle: ")
templates.pypeit_identify_record(
final_fit[str(slit_idx)], self.binspectral,
specname, gratname, dispangl)
msgs.info("Your wavelength solution has been stored")
msgs.info(
"Please consider sending your solution to the PYPEIT team!"
)
elif method == 'reidentify':
# Now preferred
# Slit positions
arcfitter = autoid.ArchiveReid(
arccen,
self.spectrograph,
self.par,
ok_mask=ok_mask_idx,
slit_spat_pos=self.spat_coo,
nonlinear_counts=self.nonlinear_counts)
patt_dict, final_fit = arcfitter.get_results()
elif method == 'full_template':
# Now preferred
if self.binspectral is None:
msgs.error(
"You must specify binspectral for the full_template method!"
)
final_fit = autoid.full_template(
arccen,
self.par,
ok_mask_idx,
self.det,
self.binspectral,
nonlinear_counts=self.nonlinear_counts,
nsnippet=self.par['nsnippet'])
else:
msgs.error(
'Unrecognized wavelength calibration method: {:}'.format(
method))
# Convert keys to spatial system
self.wv_calib = {}
tmp = copy.deepcopy(final_fit)
for idx in range(self.slits.nslits):
if str(idx) in final_fit.keys():
self.wv_calib[str(self.slits.slitord_id[idx])] = final_fit.pop(
str(idx))
# Update mask
self.update_wvmask()
#TODO For generalized echelle (not hard wired) assign order number here before, i.e. slits.ech_order
# QA
if not skip_QA:
ok_mask_idx = np.where(np.invert(self.wvc_bpm))[0]
for slit_idx in ok_mask_idx:
outfile = qa.set_qa_filename(
self.master_key,
'arc_fit_qa',
slit=self.slits.slitord_id[slit_idx],
out_dir=self.qa_path)
autoid.arc_fit_qa(self.wv_calib[str(
self.slits.slitord_id[slit_idx])],
outfile=outfile)
# Return
self.steps.append(inspect.stack()[0][3])
return self.wv_calib