def return_astropy_table(Source_dict,
fiberweights=False,
return_fiber_info=False):
"""Returns an astropy table fom a source dictionary"""
id_arr = []
shotid_arr = []
wave_arr = []
spec_arr = []
spec_err_arr = []
weights_arr = []
fiber_weights_arr = []
fiber_info_arr = []
gal_flag_arr = []
meteor_flag_arr = []
amp_flag_arr = []
flag_arr = []
config = HDRconfig()
bad_amps_table = Table.read(config.badamp)
galaxy_cat = Table.read(config.rc3cat, format="ascii")
# loop over every ID/observation combo:
for ID in Source_dict.keys():
for shotid in Source_dict[ID].keys():
wave_rect = 2.0 * np.arange(1036) + 3470.0
spec = Source_dict[ID][shotid][0]
spec_err = Source_dict[ID][shotid][1]
weights = Source_dict[ID][shotid][2]
if fiberweights:
fiber_weights = Source_dict[ID][shotid][3]
# get fiber info to make masks
try:
fiber_info = Source_dict[ID][shotid][4]
except:
fiber_info = None
if Source_dict[ID][shotid][5] is None:
amp_flag = True
gal_flag = True
meteor_flag = True
flag = True
else:
meteor_flag, gal_flag, amp_flag, flag = Source_dict[ID][shotid][5]
sel = np.isfinite(spec)
if np.sum(sel) > 0:
id_arr.append(ID)
shotid_arr.append(shotid)
wave_arr.append(wave_rect)
spec_arr.append(spec)
spec_err_arr.append(spec_err)
weights_arr.append(weights)
if fiberweights:
fiber_weights_arr.append(fiber_weights)
fiber_info_arr.append(fiber_info)
flag_arr.append(flag)
amp_flag_arr.append(amp_flag)
meteor_flag_arr.append(meteor_flag)
gal_flag_arr.append(gal_flag)
output = Table()
fluxden_u = 1e-17 * u.erg * u.s ** (-1) * u.cm ** (-2) * u.AA ** (-1)
output.add_column(Column(id_arr), name="ID")
output.add_column(Column(shotid_arr), name="shotid")
output.add_column(Column(wave_arr, unit=u.AA, name="wavelength"))
output.add_column(Column(spec_arr, unit=fluxden_u, name="spec"))
output.add_column(Column(spec_err_arr, unit=fluxden_u, name="spec_err"))
output.add_column(Column(weights_arr), name="weights")
output.add_column(Column(flag_arr, name='flag', dtype=int))
output.add_column(Column(gal_flag_arr, name='gal_flag', dtype=int))
output.add_column(Column(amp_flag_arr, name='amp_flag', dtype=int))
output.add_column(Column(meteor_flag_arr, name='meteor_flag', dtype=int))
if fiberweights:
output.add_column(Column(fiber_weights_arr), name="fiber_weights")
if return_fiber_info:
output.add_column(Column(fiber_info_arr, name="fiber_info"))
return output
def __init__(
self,
coords=None,
detectid=None,
survey="hdr2.1",
aperture=3.0 * u.arcsec,
cutout_size=5.0 * u.arcmin,
zoom=3,
):
self.survey = survey.lower()
self.detectid = detectid
self.aperture = aperture
self.cutout_size = cutout_size
self.zoom = zoom
config = HDRconfig(survey=survey)
self.fileh5dets = tb.open_file(config.detecth5, "r")
self.catlib = catalogs.CatalogLibrary()
if coords:
self.coords = coords
self.detectid = 1000000000
elif detectid:
self.detectid = detectid
self.update_det_coords()
else:
self.coords = SkyCoord(191.663132 * u.deg,
50.712696 * u.deg,
frame="icrs")
self.detectid = 2101848640
# initialize the image widget from astrowidgets
self.imw = ImageWidget(image_width=600, image_height=600)
self.survey_widget = widgets.Dropdown(
options=["HDR1", "HDR2", "HDR2.1"],
value=self.survey.upper(),
layout=Layout(width="10%"),
)
self.detectbox = widgets.BoundedIntText(
value=self.detectid,
min=1000000000,
max=3000000000,
step=1,
description="DetectID:",
disabled=False,
)
self.im_ra = widgets.FloatText(
value=self.coords.ra.value,
description="RA (deg):",
layout=Layout(width="20%"),
)
self.im_dec = widgets.FloatText(
value=self.coords.dec.value,
description="DEC (deg):",
layout=Layout(width="20%"),
)
self.pan_to_coords = widgets.Button(description="Pan to coords",
disabled=False,
button_style="success")
self.marking_button = widgets.Button(description="Mark Sources",
button_style="success")
self.reset_marking_button = widgets.Button(description="Reset",
button_style="success")
self.extract_button = widgets.Button(description="Extract Object",
button_style="success")
self.marker_table_output = widgets.Output(
layout={"border": "1px solid black"})
# self.spec_output = widgets.Output(layout={'border': '1px solid black'})
self.spec_output = widgets.Tab(description="Extracted Spectra:",
layout={"border": "1px solid black"})
self.textimpath = widgets.Text(description="Source: ",
value="",
layout=Layout(width="90%"))
self.topbox = widgets.HBox([
self.survey_widget,
self.detectbox,
self.im_ra,
self.im_dec,
self.pan_to_coords,
])
self.leftbox = widgets.VBox([self.imw, self.textimpath],
layout=Layout(width="800px"))
self.rightbox = widgets.VBox(
[
widgets.HBox([
self.marking_button,
self.reset_marking_button,
self.extract_button,
]),
self.marker_table_output,
self.spec_output,
],
layout=Layout(width="800px"),
)
self.bottombox = widgets.Output(layout={"border": "1px solid black"})
self.load_image()
self.all_box = widgets.VBox([
self.topbox,
widgets.HBox([self.leftbox, self.rightbox]),
#self.spec_output,
self.bottombox
])
display(self.all_box)
self.detectbox.observe(self.on_det_change)
self.pan_to_coords.on_click(self.pan_to_coords_click)
self.marking_button.on_click(self.marking_on_click)
self.reset_marking_button.on_click(self.reset_marking_on_click)
self.extract_button.on_click(self.extract_on_click)
self.survey_widget.observe(self.on_survey_change)
def return_flux_limit_model(flim_model, cache_sim_interp=True, verbose=False):
"""
Return the noise -> 50% completeness
scaling and a function for the
completeness curves
"""
# old models for legacy support
if flim_model in ["hdr1", "hdr2pt1"]:
if verbose:
print("Using flim model: {:s}".format(flim_model))
return return_flux_limit_model_old(flim_model)
models = {
"one_sigma_nearest_pixel":
ModelInfo("curves_v1", [1.0],
None,
False,
False,
snlow=0.999999,
snhigh=1.000001),
"one_sigma_interpolate":
ModelInfo("curves_v1", [1.0],
None,
True,
False,
snlow=0.999999,
snhigh=1.000001),
"hdr2pt1pt1":
ModelInfo(
"curves_v1",
[2.76096687e-03, 2.09732448e-02, 7.21681512e-02, 3.36040017e+00],
None, False, False),
"hdr2pt1pt3":
ModelInfo(
"curves_v1",
[6.90111625e-04, 5.99169372e-02, 2.92352510e-01, 1.74348070e+00],
None, False, False),
"v1":
ModelInfo("curves_v1", [
-8.80650683e-02, 2.03488098e+00, -1.73733048e+01, 6.56038443e+01,
-8.84158092e+01
], None, False, True),
"v1.1":
ModelInfo("curves_v1", [
-8.80650683e-02, 2.03488098e+00, -1.73733048e+01, 6.56038443e+01,
-8.84158092e+01
], None, True, True),
"v2":
ModelInfo("curves_v1", [1.0, 0.0], [
-1.59395767e-14, 3.10388106e-10, -2.26855051e-06, 7.38507004e-03,
-8.06953973e+00
],
False,
True,
lw_scaling=linewidth_f50_scaling_v1)
}
default = "v2"
if not flim_model:
flim_model = default
model = models[flim_model]
if verbose:
print("Using flim model: {:s}".format(flim_model))
if flim_model_cache.cached_model == flim_model and cache_sim_interp:
sinterp = flim_model_cache.cached_sim_interp
else:
conf = HDRconfig()
fdir = conf.flim_sim_completeness
fdir = join(fdir, model.snfile_version)
sinterp = SimulationInterpolator(fdir,
model.dont_interp_to_zero,
snmode=False,
verbose=verbose)
# save model in cache
if cache_sim_interp:
flim_model_cache.cached_model = flim_model
flim_model_cache.cached_sim_interp = sinterp
def f50_from_noise(noise, lambda_, sncut, linewidth=None):
"""
Return the 50% completeness
flux given noise and S/N cut.
Parameters
----------
noise : float
the noise from the
sensitivity cubes
sncut : float
the signal to noise
cut to assume
linewidth : float
the linewidth in A,
only used with supported
models
Returns
-------
f50s : array
the fluxes at 50%
completeness
"""
try:
if sncut < model.snlow or sncut > model.snhigh:
print("WARNING: model {:s} not calibrated for this S/N range".
format(flim_model))
except ValueError:
if any(sncut < 4.5) or any(ncut > 7.5):
print("WARNING: model {:s} not calibrated for this S/N range".
format(flim_model))
bad = noise > 998
if model.wavepoly:
noise = noise * polyval(model.wavepoly, lambda_)
if type(linewidth) != type(None):
if type(model.lw_scaling) != type(None):
lw_scale = model.lw_scaling(linewidth, sncut)
else:
raise NoLineWidthModel(
"Linewidth dependence not available for this flim model")
noise = noise * lw_scale
snmult = polyval(model.snpoly, sncut)
f50 = snmult * noise
# keep bad values unscaled
try:
f50[bad] = 999
except TypeError:
if bad:
f50 = 999
return f50
return f50_from_noise, sinterp, model.interp_sigmas
def __init__(self,
datevshot,
release=None,
flim_model=None,
rad=3.5,
ffsky=False,
wavenpix=3,
d25scale=3.0,
verbose=False,
sclean_bad=True,
log_level="WARNING"):
self.conf = HDRconfig()
self.extractor = Extract()
self.shotid = int(datevshot.replace("v", ""))
self.date = datevshot[:8]
self.rad = rad
self.ffsky = ffsky
self.wavenpix = wavenpix
self.sclean_bad = sclean_bad
logger = logging.getLogger(name="ShotSensitivity")
logger.setLevel(log_level)
if verbose:
raise DeprecationWarning(
"Using verbose is deprecated, set log_level instead")
logger.setLevel("DEBUG")
logger.info("shotid: {:d}".format(self.shotid))
if not release:
self.release = self.conf.LATEST_HDR_NAME
else:
self.release = release
logger.info("Data release: {:s}".format(self.release))
self.survey = Survey(survey=self.release)
# Set up flux limit model
self.f50_from_noise, self.sinterp, interp_sigmas \
= return_flux_limit_model(flim_model,
cache_sim_interp=False,
verbose=verbose)
# Generate astrometry for this shot
survey_sel = (self.survey.shotid == self.shotid)
self.shot_pa = self.survey.pa[survey_sel][0]
self.shot_ra = self.survey.ra[survey_sel][0]
self.shot_dec = self.survey.dec[survey_sel][0]
rot = 360.0 - (self.shot_pa + 90.)
self.tp = TangentPlane(self.shot_ra, self.shot_dec, rot)
#Set up masking
logger.info("Using d25scale {:f}".format(d25scale))
self.setup_mask(d25scale)
# Set up spectral extraction
if release == "hdr1":
fwhm = self.survey.fwhm_moffat[survey_sel][0]
else:
fwhm = self.survey.fwhm_virus[survey_sel][0]
logger.info("Using Moffat PSF with FWHM {:f}".format(fwhm))
self.moffat = self.extractor.moffat_psf(fwhm, 3. * rad, 0.25)
self.extractor.load_shot(self.shotid, fibers=True, survey=self.release)
# Set up the focal plane astrometry
fplane_table = self.extractor.shoth5.root.Astrometry.fplane
# Bit of a hack to avoid changing pyhetdex
with NamedTemporaryFile(mode='w') as tpf:
for row in fplane_table.iterrows():
tpf.write(
"{:03d} {:8.5f} {:8.5f} {:03d} {:03d} {:03d} {:8.5f} {:8.5f}\n"
.format(row['ifuslot'], row['fpx'], row['fpy'],
row['specid'], row['specslot'], row['ifuid'],
row['ifurot'], row['platesc']))
tpf.seek(0)
self.fplane = FPlane(tpf.name)
def main(argv=None):
""" Main Function """
# Call initial parser from init_utils
parser = ap.ArgumentParser(description="""Create HDF5 Astrometry file.""",
add_help=True)
parser.add_argument(
"-sdir",
"--shotdir",
help="""Directory for shot H5 files to ingest""",
type=str,
default="/scratch/03946/hetdex/hdr3/reduction/data",
)
parser.add_argument(
"-sl",
"--shotlist",
help="""Text file of DATE OBS list""",
type=str,
default="hdr3.shotlist",
)
parser.add_argument(
"-of",
"--outfilename",
type=str,
help="""Relative or absolute path for output HDF5
file.""",
default=None,
)
parser.add_argument("-survey", "--survey", type=str, default="hdr3")
parser.add_argument(
"-m",
"--month",
type=int,
default=None,
help="""Create FiberIndex for a single month""",
)
parser.add_argument(
"--merge",
"-merge",
help="""Boolean trigger to merge all 2*.fits files in cwd""",
default=False,
required=False,
action="store_true",
)
args = parser.parse_args(argv)
args.log = setup_logging()
fileh = tb.open_file(args.outfilename,
mode="w",
title=args.survey.upper() + " Fiber Index file ")
shotlist = Table.read(args.shotlist,
format="ascii.no_header",
names=["date", "obs"])
tableFibers = fileh.create_table(
fileh.root,
"FiberIndex",
VIRUSFiberIndex,
"Survey Fiber Coord Info",
expectedrows=300000000,
)
if args.merge:
files = glob.glob("mfi*h5")
for file in files:
args.log.info("Appending detect H5 file: %s" % file)
fileh_i = tb.open_file(file, "r")
tableFibers_i = fileh_i.root.FiberIndex.read()
tableFibers.append(tableFibers_i)
tableFibers.cols.healpix.create_csindex()
tableFibers.cols.ra.create_csindex()
tableFibers.cols.shotid.create_csindex()
tableFibers.flush()
fileh.close()
args.log.info("Completed {}".format(args.outfilename))
sys.exit()
# set up HEALPIX options
Nside = 2**15
hp.max_pixrad(Nside, degrees=True) * 3600 # in unit of arcsec
config = HDRconfig(survey=args.survey)
badshot = np.loadtxt(config.badshot, dtype=int)
if args.month is not None:
args.log.info("Working on month {}".format(args.month))
# if working on a single month downselect
shotlist["month"] = np.array(shotlist["date"] / 100, dtype=int)
sel_month = shotlist["month"] == args.month
shotlist = shotlist[sel_month]
for shotrow in shotlist:
datevshot = str(shotrow["date"]) + "v" + str(shotrow["obs"]).zfill(3)
shotid = int(str(shotrow["date"]) + str(shotrow["obs"]).zfill(3))
date = shotrow["date"]
try:
args.log.info("Ingesting %s" % datevshot)
file_obs = tb.open_file(op.join(args.shotdir, datevshot + ".h5"),
"r")
tableFibers_i = file_obs.root.Data.FiberIndex
for row_i in tableFibers_i:
row_main = tableFibers.row
for col in tableFibers_i.colnames:
row_main[col] = row_i[col]
fiberid = row_i["fiber_id"]
try:
row_main["healpix"] = hp.ang2pix(Nside,
row_i["ra"],
row_i["dec"],
lonlat=True)
except:
row_main["healpix"] = 0
row_main["shotid"] = shotid
row_main["date"] = date
row_main["datevobs"] = datevshot
row_main["specid"] = fiberid[20:23]
row_main["ifuslot"] = fiberid[24:27]
row_main["ifuid"] = fiberid[28:31]
row_main["amp"] = fiberid[32:34]
row_main.append()
file_obs.close()
except:
if shotid in badshot:
pass
else:
args.log.error("could not ingest %s" % datevshot)
tableFibers.cols.healpix.create_csindex()
tableFibers.cols.ra.create_csindex()
tableFibers.cols.shotid.create_csindex()
tableFibers.flush()
fileh.close()
args.log.info("Completed {}".format(args.outfilename))
"/work/03946/hetdex/hdr2.1/detect/image_db",
"/work/03261/polonius/hdr2.1/detect/image_db"
],
}
#
# add paths from hetdex_api to search (place in first position)
#
for v in DICT_DB_PATHS.keys():
try:
release_number = v/10.0
if v % 10 == 0:
release_string = "hdr{:d}".format(int(release_number))
else:
release_string = "hdr{:2.1f}".format(release_number)
DICT_DB_PATHS[v].insert(0,op.join(HDRconfig(survey=release_string).elix_dir))
except:# Exception as e:
#print(e)
continue
def get_elixer_report_db_path(detectid,report_type="report"):
"""
Return the top (first found) path to database file based on the detectid (assumes the HDR version is part of the
prefix, i.e. HDR1 files are 1000*, HDR2 are 2000*, and so on)
:param detectid:
:param report_type: choose one of "report" (normal ELiXer report image) [default]
"nei" (ELiXer neighborhood image)
"mini" (ELiXer mini-report image for phone app)
:return: None or database filename
"""
def main(argv=None):
''' Main Function '''
# Call initial parser from init_utils
parser = ap.ArgumentParser(description="""Create HDF5 file.""",
add_help=True)
parser.add_argument("-d", "--date",
help='''Date, e.g., 20170321, YYYYMMDD''',
type=str, default=None)
parser.add_argument("-o", "--observation",
help='''Observation number, "00000007" or "7"''',
type=str, default=None)
parser.add_argument("-r", "--rootdir",
help='''Root Directory for Reductions''',
type=str, default='/data/00115/gebhardt/calfits/')
parser.add_argument('-of', '--outfilename', type=str,
help='''Relative or absolute path for output HDF5
file.''', default=None)
parser.add_argument("-survey", "--survey", help='''{hdr1, hdr2, hdr2.1}''',
type=str, default='hdr2.1')
args = parser.parse_args(argv)
args.log = setup_logging()
calfiles = get_cal_files(args)
datestr = '%sv%03d' % (args.date, int(args.observation))
shotid = int(str(args.date) + str(args.observation).zfill(3))
#check if shotid is in badlist
config = HDRconfig(args.survey)
badshots = np.loadtxt(config.badshot, dtype=int)
badshotflag = False
if shotid in badshots:
badshotflag = True
if len(calfiles) == 0:
if badshotflag:
args.log.warning("No calfits file to append for %s" % datestr)
else:
args.log.error("No calfits file to append for %s" % datestr)
sys.exit('Exiting cal append script for %s' % datestr)
if op.exists(args.outfilename):
fileh = tb.open_file(args.outfilename, 'a')
else:
args.log.error('Problem opening : ' + args.outfilename)
sys.exit('Exiting Script')
args.log.info('Appending calibrated fiber arrays to ' + args.outfilename)
fibtable = fileh.root.Data.Fibers
for calfile in calfiles:
multi = calfile[49:60]
try:
cal_table = get_cal_table(calfile)
except:
continue
args.log.error('Could not ingest calfile: %s' % calfile)
args.log.info('Working on IFU ' + multi )
for amp_i in ['LL','LU','RL','RU']:
multiframe_i = 'multi_'+ multi + '_' + amp_i
for fibrow in fibtable.where('multiframe == multiframe_i'):
idx = (cal_table['expnum'] == fibrow['expnum']) * (cal_table['multiframe'] == fibrow['multiframe'].decode()) * (cal_table['fibidx'] == fibrow['fibidx'])
if np.sum(idx) >= 1:
fibrow['calfib'] = cal_table['calfib'][idx]
fibrow['calfibe'] = cal_table['calfibe'][idx]
fibrow['calfib_counts'] = cal_table['calfib_counts'][idx]
fibrow['calfibe_counts'] = cal_table['calfibe_counts'][idx]
fibrow['spec_fullsky_sub'] = cal_table['spec_fullsky_sub'][idx]
fibrow.update()
#else:
# args.log.warning("No fiber match for %s" % fibrow['fiber_id'])
args.log.info('Flushing and closing H5 file')
fibtable.flush()
fileh.close()
