def combine_per_camera_catalogs(catalogs):
# catalogs is the output of GFA_exposure's all_source_catalogs() method
# which is a dictionary of astropy QTable's, with the keys
# being the GFA camera extension names
# want to add a column to each table giving the GFA camera name, then
# append the all into one per-exposure table
assert(type(catalogs).__name__ == 'dict')
composite_list = []
for extname, tab in catalogs.items():
if tab is not None:
tab['camera'] = extname
tab['petal_loc'] = np.array([common.gfa_extname_to_gfa_number(extname) for extname in tab['camera']], dtype='uint8')
composite_list.append(tab)
# handle case of no sources in any image
if len(composite_list) == 0:
return None
composite = vstack(composite_list)
composite = strip_none_columns(composite)
composite['extname'] = composite['camera']
return composite
def psf_image_header(self, hdu):
hdu.header['EXTNAME'] = self.extname
hdu.header['PETALLOC'] = common.gfa_extname_to_gfa_number(self.extname)
hdu.header['NSTARS'] = self.nstars
hdu.header['FIBFRAC'] = self.fiber_fracflux if np.isfinite(self.fiber_fracflux) else 0.0 # ??
hdu.header['EXPID'] = self.im_header['EXPID']
hdu.header['CBOX'] = self.cbox
hdu.header['CFAILED'] = self.psf_centroiding_failed
if self.cube_index is not None:
hdu.header['CUBE_IND'] = self.cube_index
# guide*.fits.fz GUIDE? extensions apparently don't have NIGHT
# or any other date-related information available
if 'NIGHT' in self.im_header:
hdu.header['NIGHT'] = self.im_header['NIGHT']
def to_hdu(self, primary=False, flavor=''):
# convert this image to an HDU
# currently expect flavor to be one of
# REDUCED - reduced image
# BITMASK - data quality bitmask
# INVVAR - inverse variance image
# DETMAP - detection significance map
# if no flavor is specified then assume ".image" attribute is desired
# data for this HDU
f = (fits.PrimaryHDU if primary else fits.ImageHDU)
if (flavor == '') or (flavor == 'REDUCED'):
hdu = f(self.image.astype('float32'), header=self.header)
elif (flavor == 'BITMASK'):
hdu = f(self.bitmask.astype('int'), header=self.header)
hdu.header = dq_mask.add_dq_bitmask_header_cards(hdu.header)
elif (flavor == 'INVVAR'):
hdu = f(self.ivar_adu.astype('float32'), header=self.header)
elif (flavor == 'DETMAP'):
assert(self.detmap is not None)
hdu = f(self.detmap.astype('float32'), header=self.header)
hdu.header['FLAVOR'] = flavor
gain = common.gfa_camera_gain(self.extname)
hdu.header['GAINA'] = (gain, '[e-/ADU] assumed gain')
hdu.header['BUNIT'] = common.reduced_flavor_to_bunit(flavor)
petal_loc = common.gfa_extname_to_gfa_number(self.extname)
hdu.header['PETALLOC'] = (petal_loc, 'petal number')
return hdu
def assemble_ccds_table(tab, catalog, exp, outdir, proc_obj, cube_index=None,
ps1=None, det_sn_thresh=5.0, sky_mags=True,
minimal=False, mjdrange=None):
nrows = len(tab)
tab['extname'] = tab['camera']
tab['contrast'] = [exp.images[extname].header['CONTRAST'] for extname in tab['camera']]
if minimal:
return tab
if sky_mags:
tab['sky_mag_ab'] = [exp.images[extname].sky_mag for extname in tab['camera']]
tab['sky_mag_ab_subregion'] = [exp.images[extname].sky_mag_upper for extname in tab['camera']]
amps = common.valid_amps_list()
if sky_mags:
sky_mag_ab_per_amp = np.zeros((nrows, len(amps)), dtype='float32') # 4 amps
for i, extname in enumerate(tab['camera']):
for j in range(len(amps)):
_mag = np.nan if exp.images[extname].sky_mag_per_amp is None else exp.images[extname].sky_mag_per_amp[j]
sky_mag_ab_per_amp[i, j] = _mag
tab['sky_mag_ab_per_amp'] = sky_mag_ab_per_amp
tab['petal_loc'] = np.array([common.gfa_extname_to_gfa_number(extname) for extname in tab['camera']], dtype='uint8')
tab['expid'] = [exp.images[extname].header['EXPID'] for extname in tab['camera']]
# should work except if early versions of guide cubes lacked
# MJD information...
tab['mjd'] = [exp.images[extname].try_retrieve_meta_keyword('MJD-OBS', placeholder=0.0) for extname in tab['camera']]
eph = util.load_lst()
tab['lst_deg'] = [util.interp_ephemeris(t['mjd'], eph=eph) for t in tab]
tab['moon_illumination'] = [util.interp_ephemeris(t['mjd'], eph=eph, colname='MPHASE') for t in tab]
tab['program'] = [str(exp.images[extname].try_retrieve_meta_keyword('PROGRAM', placeholder='')) for extname in tab['camera']]
tab['skyra'] = [exp.images[extname].try_retrieve_meta_keyword('SKYRA', placeholder=np.nan) for extname in tab['camera']]
tab['skydec'] = [exp.images[extname].try_retrieve_meta_keyword('SKYDEC', placeholder=np.nan) for extname in tab['camera']]
# zenith distance using approximate center of the field given by SKYRA, SKYDEC
tab['zenith_dist_deg'] = [util._zenith_distance(t['skyra'], t['skydec'], t['lst_deg']) for t in tab]
tab['domshutl'] = np.array(nrows*[exp.try_retrieve_header_card('DOMSHUTL', placeholder='')], dtype='U8')
tab['domshutu'] = np.array(nrows*[exp.try_retrieve_header_card('DOMSHUTU', placeholder='')], dtype='U8')
tab['pmcover'] = exp.try_retrieve_header_card('PMCOVER', placeholder='')
tab['moonra'] = exp.try_retrieve_header_card('MOONRA', placeholder=np.nan)
tab['moondec'] = exp.try_retrieve_header_card('MOONDEC', placeholder=np.nan)
if np.isnan(tab['moonra'][0]):
tab['moonra'] = util.interp_ephemeris(tab['mjd'][0], eph=eph,
colname='MOONRA')
if np.isnan(tab['moondec'][0]):
tab['moondec'] = util.interp_ephemeris(tab['mjd'][0], eph=eph,
colname='MOONDEC')
tab['moon_zd_deg'] = util._zenith_distance(tab['moonra'][0],
tab['moondec'][0],
tab['lst_deg'][0])
tab['t_c_for_dark'] = [exp.images[extname].t_c_for_dark for extname in tab['camera']]
tab['t_c_for_dark_is_guess'] = [int(exp.images[extname].t_c_for_dark_is_guess) for extname in tab['camera']]
tab['time_s_for_dark'] = [exp.images[extname].time_s_for_dark for extname in tab['camera']]
tab['night'] = exp.try_retrieve_header_card('NIGHT', placeholder='')
tab['focus'] = exp.try_retrieve_header_card('FOCUS', placeholder='')
tab['exptime'] = [exp.images[extname].try_retrieve_meta_keyword('EXPTIME', placeholder=np.nan) for extname in tab['camera']]
# hack for acquisition images like guide-00074954-0000.fits.fz
# to make sure their _ccds table ends up listing cube_index 0
# rather than NaN
is_0000_acq_file = proc_obj.fname_in.find('-0000.fits.fz') != -1
if is_0000_acq_file:
tab['cube_index'] = 0
else:
tab['cube_index'] = np.nan if cube_index is None else int(cube_index)
if cube_index == -1:
tab['coadd_index_start'] = [exp.images[extname].coadd_index_range[0] for extname in tab['camera']]
tab['coadd_index_end'] = [exp.images[extname].coadd_index_range[1] for extname in tab['camera']]
tab['coadd_mjdobs_min'] = [exp.bintables[extname]['MJD-OBS'][ind] for extname, ind in zip(tab['camera'], tab['coadd_index_start'])]
tab['coadd_mjdobs_max'] = [exp.bintables[extname]['MJD-OBS'][ind] for extname, ind in zip(tab['camera'], tab['coadd_index_end'])]
tab['racen'] = np.zeros(len(tab), dtype=float)
tab['deccen'] = np.zeros(len(tab), dtype=float)
tab['fname_raw'] = proc_obj.fname_in
tab['gitrev'] = proc_obj.gitrev
tab['fiber_fracflux'] = [(exp.images[extname].psf.fiber_fracflux if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['fiber_fracflux_elg'] = [(exp.images[extname].psf.fiber_fracflux_elg if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['fiber_fracflux_bgs'] = [(exp.images[extname].psf.fiber_fracflux_bgs if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['n_sources_for_psf'] = [(exp.images[extname].psf.nstars if exp.images[extname].psf is not None else 0) for extname in tab['camera']]
# this pertains to aperture _3 which is 1.5 asec radius
tab['aper_corr_fac'] = [(exp.images[extname].psf.aper_corr_fac if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['xcentroid_psf'] = [(exp.images[extname].psf.xcen_flux_weighted if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['ycentroid_psf'] = [(exp.images[extname].psf.ycen_flux_weighted if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['psf_fwhm_pix'] = [(exp.images[extname].psf.moffat_fwhm_pix if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['psf_fwhm_asec'] = [(exp.images[extname].psf.moffat_fwhm_asec if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['psf_centroid_cbox'] = [(float(exp.images[extname].psf.cbox) if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
tab['psf_centroid_failed'] = [(exp.images[extname].psf.psf_centroiding_failed if exp.images[extname].psf is not None else 0) for extname in tab['camera']]
tab['radprof_fwhm_asec'] = [(exp.images[extname].psf.radprof_fwhm_asec if exp.images[extname].psf is not None else np.nan) for extname in tab['camera']]
# is 0 the best placeholder value here when no PSF exists?
tab['psf_centroiding_flag'] = [(exp.images[extname].psf.psf_centroiding_flag if exp.images[extname].psf is not None else 0) for extname in tab['camera']]
tab['psf_asymmetry_ratio'] = [(exp.images[extname].psf.psf_asymmetry_ratio if exp.images[extname].psf is not None else np.float32(np.nan)) for extname in tab['camera']]
tab['psf_asymmetry_numerator'] = [(exp.images[extname].psf.psf_asymmetry_numerator if exp.images[extname].psf is not None else np.float32(np.nan)) for extname in tab['camera']]
tab['psf_asymmetry_denominator'] = [(exp.images[extname].psf.psf_asymmetry_denominator if exp.images[extname].psf is not None else np.float32(np.nan)) for extname in tab['camera']]
tab['psf_total_flux'] = [(exp.images[extname].psf.psf_total_flux if exp.images[extname].psf is not None else np.float32(np.nan)) for extname in tab['camera']]
radprof_ccds_table(tab, exp)
for i, extname in enumerate(tab['camera']):
racen, deccen = ccd_center_radec(exp.images[extname].wcs)
tab['racen'][i] = racen
tab['deccen'][i] = deccen
tab['mountha_header'] = exp.try_retrieve_header_card('MOUNTHA', placeholder=np.nan)
tab['mountdec_header'] = exp.try_retrieve_header_card('MOUNTDEC', placeholder=np.nan)
tab['ha_deg'] = [util._get_ha(t['skyra'], t['lst_deg'], t['mountdec_header']) for t in tab]
tab['ha_deg_per_gfa'] = [util._get_ha(t['racen'], t['lst_deg'], t['mountdec_header']) for t in tab]
tab['moon_sep_deg'] = util.moon_separation(tab['moonra'], tab['moondec'],
tab['racen'], tab['deccen'])
# per-camera zenith distance -- will only be accurate to the extent that
# each camera's WCS recalibration succeeded
tab['zd_deg_per_gfa'] = [util._zenith_distance(t['racen'], t['deccen'], t['lst_deg']) for t in tab]
tab['header_airmass'] = exp.try_retrieve_header_card('AIRMASS', placeholder=np.nan)
# this should make the airmass properly evolve
# with time for guide cube outputs
tab['airmass'] = 1.0/np.cos(tab['zenith_dist_deg']/(180.0/np.pi))
# this per-camera version of airmass should also evolve
# properly with time for guide cube outputs
tab['airmass_per_gfa'] = 1.0/np.cos(tab['zd_deg_per_gfa']/(180.0/np.pi))
tab['zp_adu_per_s'] = [exp.images[extname].compute_zeropoint(ps1) for extname in tab['camera']]
tab['n_stars_for_zp'] = [(np.sum(ps1['use_for_zp'] & (ps1['extname'] == extname)).astype(int) if 'use_for_zp' in ps1.colnames else 0) for extname in tab['camera']]
tab['transparency'] = [util.transparency_from_zeropoint(tab[i]['zp_adu_per_s'], tab[i]['airmass_per_gfa'], tab[i]['camera']) for i in range(len(tab))]
par = common.gfa_misc_params()
tab['kterm'] = np.float32(par['kterm'])
tab['fracflux_nominal_pointsource'] = np.float32(par['fracflux_nominal_pointsource'])
tab['fracflux_nominal_elg'] = np.float32(par['fracflux_nominal_elg'])
tab['fracflux_nominal_bgs'] = np.float32(par['fracflux_nominal_bgs'])
tab['det_sn_thresh'] = det_sn_thresh
prescan_overscan_ccds_table(tab, exp)
high_level_ccds_metrics(tab, catalog, exp)
astrom_ccds_table(tab, exp)
dark_current_ccds_table(tab, exp)
if mjdrange is not None:
tab['req_mjd_min'] = mjdrange[0]
tab['req_mjd_max'] = mjdrange[1]
return tab
def assemble_ccds_table(tab,
catalog,
exp,
outdir,
proc_obj,
cube_index=None,
ps1=None,
det_sn_thresh=5.0,
sky_mags=True,
minimal=False):
nrows = len(tab)
tab['extname'] = tab['camera']
tab['contrast'] = [
exp.images[extname].header['CONTRAST'] for extname in tab['camera']
]
if minimal:
return tab
if sky_mags:
tab['sky_mag_ab'] = [
exp.images[extname].sky_mag for extname in tab['camera']
]
amps = common.valid_amps_list()
if sky_mags:
sky_mag_ab_per_amp = np.zeros((nrows, len(amps)),
dtype='float32') # 4 amps
for i, extname in enumerate(tab['camera']):
for j in range(len(amps)):
_mag = np.nan if exp.images[
extname].sky_mag_per_amp is None else exp.images[
extname].sky_mag_per_amp[j]
sky_mag_ab_per_amp[i, j] = _mag
tab['sky_mag_ab_per_amp'] = sky_mag_ab_per_amp
tab['petal_loc'] = np.array([
common.gfa_extname_to_gfa_number(extname) for extname in tab['camera']
],
dtype='uint8')
tab['expid'] = [
exp.images[extname].header['EXPID'] for extname in tab['camera']
]
# should work except if early versions of guide cubes lacked
# MJD information...
tab['mjd'] = [
exp.images[extname].try_retrieve_meta_keyword('MJD-OBS',
placeholder=0.0)
for extname in tab['camera']
]
eph = util.load_lst()
tab['lst_deg'] = [util.interp_lst(t['mjd'], eph=eph) for t in tab]
tab['program'] = [
str(exp.images[extname].try_retrieve_meta_keyword('PROGRAM',
placeholder=''))
for extname in tab['camera']
]
tab['skyra'] = [
exp.images[extname].try_retrieve_meta_keyword('SKYRA',
placeholder=np.nan)
for extname in tab['camera']
]
tab['skydec'] = [
exp.images[extname].try_retrieve_meta_keyword('SKYDEC',
placeholder=np.nan)
for extname in tab['camera']
]
# zenith distance using approximate center of the field given by SKYRA, SKYDEC
tab['zenith_dist_deg'] = [
util._zenith_distance(t['skyra'], t['skydec'], t['lst_deg'])
for t in tab
]
tab['domshutl'] = np.array(
nrows * [exp.try_retrieve_header_card('DOMSHUTL', placeholder='')],
dtype='U8')
tab['domshutu'] = np.array(
nrows * [exp.try_retrieve_header_card('DOMSHUTU', placeholder='')],
dtype='U8')
tab['pmcover'] = exp.try_retrieve_header_card('PMCOVER', placeholder='')
tab['moonra'] = exp.try_retrieve_header_card('MOONRA', placeholder=np.nan)
tab['moondec'] = exp.try_retrieve_header_card('MOONDEC',
placeholder=np.nan)
tab['t_c_for_dark'] = [
exp.images[extname].t_c_for_dark for extname in tab['camera']
]
tab['t_c_for_dark_is_guess'] = [
int(exp.images[extname].t_c_for_dark_is_guess)
for extname in tab['camera']
]
tab['time_s_for_dark'] = [
exp.images[extname].time_s_for_dark for extname in tab['camera']
]
tab['night'] = exp.try_retrieve_header_card('NIGHT', placeholder='')
tab['focus'] = exp.try_retrieve_header_card('FOCUS', placeholder='')
tab['exptime'] = [
exp.images[extname].try_retrieve_meta_keyword('EXPTIME',
placeholder=np.nan)
for extname in tab['camera']
]
tab['cube_index'] = np.nan if cube_index is None else int(cube_index)
if cube_index == -1:
tab['coadd_index_start'] = [
exp.images[extname].coadd_index_range[0]
for extname in tab['camera']
]
tab['coadd_index_end'] = [
exp.images[extname].coadd_index_range[1]
for extname in tab['camera']
]
tab['racen'] = np.zeros(len(tab), dtype=float)
tab['deccen'] = np.zeros(len(tab), dtype=float)
tab['fname_raw'] = proc_obj.fname_in
tab['gitrev'] = proc_obj.gitrev
tab['fiber_fracflux'] = [(exp.images[extname].psf.fiber_fracflux if
exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['n_sources_for_psf'] = [(exp.images[extname].psf.nstars
if exp.images[extname].psf is not None else 0)
for extname in tab['camera']]
# this pertains to aperture _3 which is 1.5 asec radius
tab['aper_corr_fac'] = [(exp.images[extname].psf.aper_corr_fac if
exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['xcentroid_psf'] = [(exp.images[extname].psf.xcen_flux_weighted if
exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['ycentroid_psf'] = [(exp.images[extname].psf.ycen_flux_weighted if
exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['psf_fwhm_pix'] = [(exp.images[extname].psf.moffat_fwhm_pix
if exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['psf_fwhm_asec'] = [(exp.images[extname].psf.moffat_fwhm_asec if
exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']]
tab['psf_centroid_cbox'] = [
(float(exp.images[extname].psf.cbox)
if exp.images[extname].psf is not None else np.nan)
for extname in tab['camera']
]
tab['psf_centroid_failed'] = [
(exp.images[extname].psf.psf_centroiding_failed
if exp.images[extname].psf is not None else 0)
for extname in tab['camera']
]
for i, extname in enumerate(tab['camera']):
racen, deccen = ccd_center_radec(exp.images[extname].wcs)
tab['racen'][i] = racen
tab['deccen'][i] = deccen
tab['mountha_header'] = exp.try_retrieve_header_card('MOUNTHA',
placeholder=np.nan)
tab['mountdec_header'] = exp.try_retrieve_header_card('MOUNTDEC',
placeholder=np.nan)
tab['ha_deg'] = [
util._get_ha(t['skyra'], t['lst_deg'], t['mountdec_header'])
for t in tab
]
tab['ha_deg_per_gfa'] = [
util._get_ha(t['racen'], t['lst_deg'], t['mountdec_header'])
for t in tab
]
tab['moon_sep_deg'] = util.moon_separation(tab['moonra'], tab['moondec'],
tab['racen'], tab['deccen'])
# per-camera zenith distance -- will only be accurate to the extent that
# each camera's WCS recalibration succeeded
tab['zd_deg_per_gfa'] = [
util._zenith_distance(t['racen'], t['deccen'], t['lst_deg'])
for t in tab
]
tab['header_airmass'] = exp.try_retrieve_header_card('AIRMASS',
placeholder=np.nan)
# this should make the airmass properly evolve
# with time for guide cube outputs
tab['airmass'] = 1.0 / np.cos(tab['zenith_dist_deg'] / (180.0 / np.pi))
# this per-camera version of airmass should also evolve
# properly with time for guide cube outputs
tab['airmass_per_gfa'] = 1.0 / np.cos(tab['zd_deg_per_gfa'] /
(180.0 / np.pi))
tab['zp_adu_per_s'] = [
exp.images[extname].compute_zeropoint(ps1) for extname in tab['camera']
]
tab['transparency'] = [
util.transparency_from_zeropoint(tab[i]['zp_adu_per_s'],
tab[i]['airmass_per_gfa'],
tab[i]['camera'])
for i in range(len(tab))
]
tab['det_sn_thresh'] = det_sn_thresh
prescan_overscan_ccds_table(tab, exp)
high_level_ccds_metrics(tab, catalog, exp)
astrom_ccds_table(tab, exp)
dark_current_ccds_table(tab, exp)
return tab