def test_io_qa_frame(self):
nspec = 3
nwave = 10
wave = np.arange(nwave)
flux = np.random.uniform(size=(nspec, nwave))
ivar = np.ones(flux.shape)
frame = Frame(wave, flux, ivar, spectrograph=0)
frame.meta = dict(CAMERA='b0', FLAVOR='dark', NIGHT='20160607', EXPID=1)
#- Init
qaframe = QA_Frame(frame)
qaframe.init_skysub()
# Write
desio_qa.write_qa_frame(self.testyfile, qaframe)
# Read
xqaframe = desio_qa.read_qa_frame(self.testyfile)
# Check
self.assertTrue(qaframe.qa_data['SKYSUB']['PARAM']['PCHI_RESID'] == xqaframe.qa_data['SKYSUB']['PARAM']['PCHI_RESID'])
self.assertTrue(qaframe.flavor == xqaframe.flavor)
def make_frameqa(self, make_plots=False, clobber=True):
""" Work through the Production and make QA for all frames
Parameters:
make_plots: bool, optional
Remake the plots too?
clobber: bool, optional
Returns:
"""
# imports
from desispec.io import meta
from desispec.io.qa import load_qa_frame, write_qa_frame
from desispec.io.fiberflat import read_fiberflat
from desispec.io.sky import read_sky
from desispec.io.fluxcalibration import read_flux_calibration
from desispec.qa import qa_plots
from desispec.io.fluxcalibration import read_stdstar_models
# Loop on nights
path_nights = glob.glob(self.specprod_dir + '/exposures/*')
nights = [ipathn[ipathn.rfind('/') + 1:] for ipathn in path_nights]
for night in nights:
for exposure in get_exposures(night,
specprod_dir=self.specprod_dir):
# Object only??
frames_dict = get_files(filetype=str('frame'),
night=night,
expid=exposure,
specprod_dir=self.specprod_dir)
for camera, frame_fil in frames_dict.items():
# Load frame
frame = read_frame(frame_fil)
spectro = int(frame.meta['CAMERA'][-1])
if frame.meta['FLAVOR'] in ['flat', 'arc']:
qatype = 'qa_calib'
else:
qatype = 'qa_data'
qafile = meta.findfile(qatype,
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
if (not clobber) & os.path.isfile(qafile):
log.info(
"qafile={:s} exists. Not over-writing. Consider clobber=True"
.format(qafile))
continue
# Load
qaframe = load_qa_frame(qafile,
frame,
flavor=frame.meta['FLAVOR'])
# Flat QA
if frame.meta['FLAVOR'] in ['flat']:
fiberflat_fil = meta.findfile(
'fiberflat',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
fiberflat = read_fiberflat(fiberflat_fil)
qaframe.run_qa('FIBERFLAT', (frame, fiberflat),
clobber=clobber)
if make_plots:
# Do it
qafig = meta.findfile(
'qa_flat_fig',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
qa_plots.frame_fiberflat(qafig, qaframe, frame,
fiberflat)
# SkySub QA
if qatype == 'qa_data':
sky_fil = meta.findfile('sky',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
skymodel = read_sky(sky_fil)
qaframe.run_qa('SKYSUB', (frame, skymodel))
if make_plots:
qafig = meta.findfile(
'qa_sky_fig',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
qa_plots.frame_skyres(qafig, frame, skymodel,
qaframe)
# FluxCalib QA
if qatype == 'qa_data':
# Standard stars
stdstar_fil = meta.findfile(
'stdstars',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir,
spectrograph=spectro)
model_tuple = read_stdstar_models(stdstar_fil)
flux_fil = meta.findfile(
'calib',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
fluxcalib = read_flux_calibration(flux_fil)
qaframe.run_qa(
'FLUXCALIB',
(frame, fluxcalib, model_tuple)) #, indiv_stars))
if make_plots:
qafig = meta.findfile(
'qa_flux_fig',
night=night,
camera=camera,
expid=exposure,
specprod_dir=self.specprod_dir)
qa_plots.frame_fluxcalib(qafig, qaframe, frame,
fluxcalib, model_tuple)
# Write
write_qa_frame(qafile, qaframe)
def make_frameqa(self, make_plots=False, clobber=True):
""" Work through the Production and make QA for all frames
Parameters:
make_plots: bool, optional
Remake the plots too?
clobber: bool, optional
Returns:
"""
# imports
from desispec.io import meta
from desispec.io.qa import load_qa_frame, write_qa_frame
from desispec.io.fiberflat import read_fiberflat
from desispec.io.sky import read_sky
from desispec.io.fluxcalibration import read_flux_calibration
from desispec.qa import qa_plots
from desispec.io.fluxcalibration import read_stdstar_models
# Loop on nights
path_nights = glob.glob(self.specprod_dir+'/exposures/*')
nights = [ipathn[ipathn.rfind('/')+1:] for ipathn in path_nights]
for night in nights:
for exposure in get_exposures(night, specprod_dir = self.specprod_dir):
# Object only??
frames_dict = get_files(filetype = str('frame'), night = night,
expid = exposure, specprod_dir = self.specprod_dir)
for camera,frame_fil in frames_dict.items():
# Load frame
frame = read_frame(frame_fil)
spectro = int(frame.meta['CAMERA'][-1])
if frame.meta['FLAVOR'] in ['flat','arc']:
qatype = 'qa_calib'
else:
qatype = 'qa_data'
qafile = meta.findfile(qatype, night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
if (not clobber) & os.path.isfile(qafile):
log.info("qafile={:s} exists. Not over-writing. Consider clobber=True".format(qafile))
continue
# Load
qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
# Flat QA
if frame.meta['FLAVOR'] in ['flat']:
fiberflat_fil = meta.findfile('fiberflat', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
fiberflat = read_fiberflat(fiberflat_fil)
qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber)
if make_plots:
# Do it
qafig = meta.findfile('qa_flat_fig', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
# SkySub QA
if qatype == 'qa_data':
sky_fil = meta.findfile('sky', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
skymodel = read_sky(sky_fil)
qaframe.run_qa('SKYSUB', (frame, skymodel))
if make_plots:
qafig = meta.findfile('qa_sky_fig', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
# FluxCalib QA
if qatype == 'qa_data':
# Standard stars
stdstar_fil = meta.findfile('stdstars', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir,
spectrograph=spectro)
model_tuple=read_stdstar_models(stdstar_fil)
flux_fil = meta.findfile('calib', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
fluxcalib = read_flux_calibration(flux_fil)
qaframe.run_qa('FLUXCALIB', (frame, fluxcalib, model_tuple))#, indiv_stars))
if make_plots:
qafig = meta.findfile('qa_flux_fig', night=night, camera=camera, expid=exposure, specprod_dir=self.specprod_dir)
qa_plots.frame_fluxcalib(qafig, qaframe, frame, fluxcalib, model_tuple)
# Write
write_qa_frame(qafile, qaframe)
def qaframe_from_frame(frame_file,
specprod_dir=None,
make_plots=False,
qaprod_dir=None,
output_dir=None,
clobber=True):
""" Generate a qaframe object from an input frame_file name (and night)
Write QA to disk
Will also make plots if directed
Args:
frame_file: str
specprod_dir: str, optional
qa_dir: str, optional -- Location of QA
make_plots: bool, optional
output_dir: str, optional
Returns:
"""
import glob
import os
from desispec.io import read_frame
from desispec.io import meta
from desispec.io.qa import load_qa_frame, write_qa_frame
from desispec.io.qa import qafile_from_framefile
from desispec.io.frame import search_for_framefile
from desispec.io.fiberflat import read_fiberflat
from desispec.fiberflat import apply_fiberflat
from desispec.qa import qa_plots
from desispec.io.sky import read_sky
from desispec.io.fluxcalibration import read_flux_calibration
from desispec.qa import qa_plots_ql
if '/' in frame_file: # If present, assume full path is used here
pass
else: # Find the frame file in the desispec hierarchy?
frame_file = search_for_framefile(frame_file)
# Load frame
frame = read_frame(frame_file)
frame_meta = frame.meta
night = frame_meta['NIGHT'].strip()
camera = frame_meta['CAMERA'].strip()
expid = frame_meta['EXPID']
spectro = int(frame_meta['CAMERA'][-1])
# Filename
qafile, qatype = qafile_from_framefile(frame_file,
qaprod_dir=qaprod_dir,
output_dir=output_dir)
if os.path.isfile(qafile) and (not clobber):
write = False
else:
write = True
qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
# Flat QA
if frame_meta['FLAVOR'] in ['flat']:
fiberflat_fil = meta.findfile('fiberflat',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
try: # Backwards compatibility
fiberflat = read_fiberflat(fiberflat_fil)
except FileNotFoundError:
fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
path, basen = os.path.split(fiberflat_fil)
path, _ = os.path.split(path)
fiberflat_fil = os.path.join(path, basen)
fiberflat = read_fiberflat(fiberflat_fil)
if qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber):
write = True
if make_plots:
# Do it
qafig = meta.findfile('qa_flat_fig',
night=night,
camera=camera,
expid=expid,
qaprod_dir=qaprod_dir,
specprod_dir=specprod_dir,
outdir=output_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
# SkySub QA
if qatype == 'qa_data':
sky_fil = meta.findfile('sky',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
fiberflat_fil = meta.findfile('fiberflatnight',
night=night,
camera=camera)
if not os.path.exists(fiberflat_fil):
# Backwards compatibility (for now)
dummy_fiberflat_fil = meta.findfile(
'fiberflat',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir) # This is dummy
path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
fiberflat_files = glob.glob(
os.path.join(path, '*', 'fiberflat-' + camera + '*.fits'))
if len(fiberflat_files) == 0:
path = path.replace('exposures', 'calib2d')
path, _ = os.path.split(path) # Remove night
fiberflat_files = glob.glob(
os.path.join(path, 'fiberflat-' + camera + '*.fits'))
# Sort and take the first (same as old pipeline)
fiberflat_files.sort()
fiberflat_fil = fiberflat_files[0]
fiberflat = read_fiberflat(fiberflat_fil)
apply_fiberflat(frame, fiberflat)
# Load sky model and run
try:
skymodel = read_sky(sky_fil)
except FileNotFoundError:
warnings.warn(
"Sky file {:s} not found. Skipping..".format(sky_fil))
else:
if qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber):
write = True
if make_plots:
qafig = meta.findfile('qa_sky_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir,
qaprod_dir=qaprod_dir)
qafig2 = meta.findfile('qa_skychi_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir,
qaprod_dir=qaprod_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
#qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)
# S/N QA on cframe
if qatype == 'qa_data':
# cframe
cframe_file = frame_file.replace('frame-', 'cframe-')
cframe = read_frame(cframe_file)
if qaframe.run_qa('S2N', (cframe, ), clobber=clobber):
write = True
# Figure?
if make_plots:
s2n_dict = copy.deepcopy(qaframe.qa_data['S2N'])
qafig = meta.findfile('qa_s2n_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir,
qaprod_dir=qaprod_dir)
#badfibs = np.where(np.isnan(s2n_dict['METRICS']['MEDIAN_SNR']))[0].tolist()
#sci_idx = s2n_dict['METRICS']['OBJLIST'].index('SCIENCE')
coeff = s2n_dict['METRICS']['FITCOEFF_TGT'] #[sci_idx]
# Add an item or two for the QL method
s2n_dict['CAMERA'] = camera
s2n_dict['EXPID'] = expid
s2n_dict['PANAME'] = 'SNRFit'
s2n_dict['METRICS']['RA'] = frame.fibermap['FIBER_RA']
s2n_dict['METRICS']['DEC'] = frame.fibermap['FIBER_DEC']
objlist = s2n_dict['METRICS']['OBJLIST']
# Deal with YAML list instead of ndarray
s2n_dict['METRICS']['MEDIAN_SNR'] = np.array(
s2n_dict['METRICS']['MEDIAN_SNR'])
# Generate
if (not os.path.isfile(qafig)) or clobber:
qa_plots_ql.plot_SNR(s2n_dict, qafig, objlist,
[[]] * len(objlist), coeff)
# FluxCalib QA
if qatype == 'qa_data':
# Standard stars
stdstar_fil = meta.findfile('stdstars',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
spectrograph=spectro)
# try:
# model_tuple=read_stdstar_models(stdstar_fil)
# except FileNotFoundError:
# warnings.warn("Standard star file {:s} not found. Skipping..".format(stdstar_fil))
# else:
flux_fil = meta.findfile('calib',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
try:
fluxcalib = read_flux_calibration(flux_fil)
except FileNotFoundError:
warnings.warn(
"Flux file {:s} not found. Skipping..".format(flux_fil))
else:
if qaframe.run_qa(
'FLUXCALIB', (frame, fluxcalib),
clobber=clobber): # , model_tuple))#, indiv_stars))
write = True
if make_plots:
qafig = meta.findfile('qa_flux_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir,
qaprod_dir=qaprod_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_fluxcalib(qafig, qaframe, frame,
fluxcalib) # , model_tuple)
# Write
if write:
write_qa_frame(qafile, qaframe, verbose=True)
return qaframe
def qaframe_from_frame(frame_file,
specprod_dir=None,
make_plots=False,
qaprod_dir=None,
output_dir=None,
clobber=True):
""" Generate a qaframe object from an input frame_file name (and night)
Write QA to disk
Will also make plots if directed
Args:
frame_file: str
specprod_dir: str, optional
qa_dir: str, optional -- Location of QA
make_plots: bool, optional
output_dir: str, optional
Returns:
"""
import glob
import os
from desispec.io import read_frame
from desispec.io import meta
from desispec.io.qa import load_qa_frame, write_qa_frame
from desispec.io.qa import qafile_from_framefile
from desispec.io.frame import search_for_framefile
from desispec.io.fiberflat import read_fiberflat
from desispec.fiberflat import apply_fiberflat
from desispec.qa import qa_plots
from desispec.io.sky import read_sky
from desispec.io.fluxcalibration import read_flux_calibration
if '/' in frame_file: # If present, assume full path is used here
pass
else: # Find the frame file in the desispec hierarchy?
frame_file = search_for_framefile(frame_file)
# Load frame
frame = read_frame(frame_file)
frame_meta = frame.meta
night = frame_meta['NIGHT'].strip()
camera = frame_meta['CAMERA'].strip()
expid = frame_meta['EXPID']
spectro = int(frame_meta['CAMERA'][-1])
# Filename
qafile, qatype = qafile_from_framefile(frame_file,
qaprod_dir=qaprod_dir,
output_dir=output_dir)
qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
# Flat QA
if frame_meta['FLAVOR'] in ['flat']:
fiberflat_fil = meta.findfile('fiberflat',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
try: # Backwards compatibility
fiberflat = read_fiberflat(fiberflat_fil)
except FileNotFoundError:
fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
path, basen = os.path.split(fiberflat_fil)
path, _ = os.path.split(path)
fiberflat_fil = os.path.join(path, basen)
fiberflat = read_fiberflat(fiberflat_fil)
qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber)
if make_plots:
# Do it
qafig = meta.findfile('qa_flat_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir)
qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
# SkySub QA
if qatype == 'qa_data':
sky_fil = meta.findfile('sky',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
fiberflat_fil = meta.findfile('fiberflatnight',
night=night,
camera=camera)
if not os.path.exists(fiberflat_fil):
# Backwards compatibility (for now)
dummy_fiberflat_fil = meta.findfile(
'fiberflat',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir) # This is dummy
path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
fiberflat_files = glob.glob(
os.path.join(path, '*', 'fiberflat-' + camera + '*.fits'))
if len(fiberflat_files) == 0:
path = path.replace('exposures', 'calib2d')
path, _ = os.path.split(path) # Remove night
fiberflat_files = glob.glob(
os.path.join(path, 'fiberflat-' + camera + '*.fits'))
# Sort and take the first (same as old pipeline)
fiberflat_files.sort()
fiberflat_fil = fiberflat_files[0]
fiberflat = read_fiberflat(fiberflat_fil)
apply_fiberflat(frame, fiberflat)
# Load sky model and run
try:
skymodel = read_sky(sky_fil)
except FileNotFoundError:
warnings.warn(
"Sky file {:s} not found. Skipping..".format(sky_fil))
else:
qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber)
if make_plots:
qafig = meta.findfile('qa_sky_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir)
qafig2 = meta.findfile('qa_skychi_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir)
qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
#qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)
# FluxCalib QA
if qatype == 'qa_data':
# Standard stars
stdstar_fil = meta.findfile('stdstars',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
spectrograph=spectro)
# try:
# model_tuple=read_stdstar_models(stdstar_fil)
# except FileNotFoundError:
# warnings.warn("Standard star file {:s} not found. Skipping..".format(stdstar_fil))
# else:
flux_fil = meta.findfile('calib',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir)
try:
fluxcalib = read_flux_calibration(flux_fil)
except FileNotFoundError:
warnings.warn(
"Flux file {:s} not found. Skipping..".format(flux_fil))
else:
qaframe.run_qa(
'FLUXCALIB',
(frame, fluxcalib)) # , model_tuple))#, indiv_stars))
if make_plots:
qafig = meta.findfile('qa_flux_fig',
night=night,
camera=camera,
expid=expid,
specprod_dir=specprod_dir,
outdir=output_dir)
qa_plots.frame_fluxcalib(qafig, qaframe, frame,
fluxcalib) # , model_tuple)
# Write
write_qa_frame(qafile, qaframe, verbose=True)
return qaframe
def qaframe_from_frame(frame_file, specprod_dir=None, make_plots=False, qaprod_dir=None,
output_dir=None, clobber=True):
""" Generate a qaframe object from an input frame_file name (and night)
Write QA to disk
Will also make plots if directed
Args:
frame_file: str
specprod_dir: str, optional
qa_dir: str, optional -- Location of QA
make_plots: bool, optional
output_dir: str, optional
Returns:
"""
import glob
import os
from desispec.io import read_frame
from desispec.io import meta
from desispec.io.qa import load_qa_frame, write_qa_frame
from desispec.io.qa import qafile_from_framefile
from desispec.io.frame import search_for_framefile
from desispec.io.fiberflat import read_fiberflat
from desispec.fiberflat import apply_fiberflat
from desispec.qa import qa_plots
from desispec.io.sky import read_sky
from desispec.io.fluxcalibration import read_flux_calibration
from desispec.qa import qa_plots_ql
if '/' in frame_file: # If present, assume full path is used here
pass
else: # Find the frame file in the desispec hierarchy?
frame_file = search_for_framefile(frame_file)
# Load frame
frame = read_frame(frame_file)
frame_meta = frame.meta
night = frame_meta['NIGHT'].strip()
camera = frame_meta['CAMERA'].strip()
expid = frame_meta['EXPID']
spectro = int(frame_meta['CAMERA'][-1])
# Filename
qafile, qatype = qafile_from_framefile(frame_file, qaprod_dir=qaprod_dir, output_dir=output_dir)
if os.path.isfile(qafile) and (not clobber):
write = False
else:
write = True
qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
# Flat QA
if frame_meta['FLAVOR'] in ['flat']:
fiberflat_fil = meta.findfile('fiberflat', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir)
try: # Backwards compatibility
fiberflat = read_fiberflat(fiberflat_fil)
except FileNotFoundError:
fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
path, basen = os.path.split(fiberflat_fil)
path,_ = os.path.split(path)
fiberflat_fil = os.path.join(path, basen)
fiberflat = read_fiberflat(fiberflat_fil)
if qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber):
write = True
if make_plots:
# Do it
qafig = meta.findfile('qa_flat_fig', night=night, camera=camera, expid=expid,
qaprod_dir=qaprod_dir, specprod_dir=specprod_dir, outdir=output_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
# SkySub QA
if qatype == 'qa_data':
sky_fil = meta.findfile('sky', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir)
fiberflat_fil = meta.findfile('fiberflatnight', night=night, camera=camera)
if not os.path.exists(fiberflat_fil):
# Backwards compatibility (for now)
dummy_fiberflat_fil = meta.findfile('fiberflat', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir) # This is dummy
path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
fiberflat_files = glob.glob(os.path.join(path,'*','fiberflat-'+camera+'*.fits'))
if len(fiberflat_files) == 0:
path = path.replace('exposures', 'calib2d')
path,_ = os.path.split(path) # Remove night
fiberflat_files = glob.glob(os.path.join(path,'fiberflat-'+camera+'*.fits'))
# Sort and take the first (same as old pipeline)
fiberflat_files.sort()
fiberflat_fil = fiberflat_files[0]
fiberflat = read_fiberflat(fiberflat_fil)
apply_fiberflat(frame, fiberflat)
# Load sky model and run
try:
skymodel = read_sky(sky_fil)
except FileNotFoundError:
warnings.warn("Sky file {:s} not found. Skipping..".format(sky_fil))
else:
if qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber):
write=True
if make_plots:
qafig = meta.findfile('qa_sky_fig', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
qafig2 = meta.findfile('qa_skychi_fig', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
#qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)
# S/N QA on cframe
if qatype == 'qa_data':
# cframe
cframe_file = frame_file.replace('frame-', 'cframe-')
cframe = read_frame(cframe_file)
if qaframe.run_qa('S2N', (cframe,), clobber=clobber):
write=True
# Figure?
if make_plots:
s2n_dict = copy.deepcopy(qaframe.qa_data['S2N'])
qafig = meta.findfile('qa_s2n_fig', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
#badfibs = np.where(np.isnan(s2n_dict['METRICS']['MEDIAN_SNR']))[0].tolist()
#sci_idx = s2n_dict['METRICS']['OBJLIST'].index('SCIENCE')
coeff = s2n_dict['METRICS']['FITCOEFF_TGT']#[sci_idx]
# Add an item or two for the QL method
s2n_dict['CAMERA'] = camera
s2n_dict['EXPID'] = expid
s2n_dict['PANAME'] = 'SNRFit'
s2n_dict['METRICS']['RA'] = frame.fibermap['FIBER_RA']
s2n_dict['METRICS']['DEC'] = frame.fibermap['FIBER_DEC']
objlist = s2n_dict['METRICS']['OBJLIST']
# Deal with YAML list instead of ndarray
s2n_dict['METRICS']['MEDIAN_SNR'] = np.array(s2n_dict['METRICS']['MEDIAN_SNR'])
# Generate
if (not os.path.isfile(qafig)) or clobber:
qa_plots_ql.plot_SNR(s2n_dict, qafig, objlist, [[]]*len(objlist), coeff)
# FluxCalib QA
if qatype == 'qa_data':
# Standard stars
stdstar_fil = meta.findfile('stdstars', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir,
spectrograph=spectro)
# try:
# model_tuple=read_stdstar_models(stdstar_fil)
# except FileNotFoundError:
# warnings.warn("Standard star file {:s} not found. Skipping..".format(stdstar_fil))
# else:
flux_fil = meta.findfile('calib', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir)
try:
fluxcalib = read_flux_calibration(flux_fil)
except FileNotFoundError:
warnings.warn("Flux file {:s} not found. Skipping..".format(flux_fil))
else:
if qaframe.run_qa('FLUXCALIB', (frame, fluxcalib), clobber=clobber): # , model_tuple))#, indiv_stars))
write = True
if make_plots:
qafig = meta.findfile('qa_flux_fig', night=night, camera=camera, expid=expid,
specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
if (not os.path.isfile(qafig)) or clobber:
qa_plots.frame_fluxcalib(qafig, qaframe, frame, fluxcalib) # , model_tuple)
# Write
if write:
write_qa_frame(qafile, qaframe, verbose=True)
return qaframe