def test_gen_sensfunc():
kastb = load_spectrograph('shane_kast_blue')
# Load a random spectrum for the sensitivity function
sfile = data_path('spec1d_r153-J0025-0312_KASTr_2015Jan23T025323.850.fits')
specobjs = load.load_specobjs(sfile)
# telescope = telescopes.ShaneTelescopePar()
fitstbl = dummy_fitstbl()
RA = '05:06:36.6'
DEC = '52:52:01.0'
# Get the sensitivity function
sens_dict = flux.generate_sensfunc(specobjs[0][0].boxcar['WAVE'],
specobjs[0][0].boxcar['COUNTS'],
specobjs[0][0].boxcar['COUNTS_IVAR'],
fitstbl['airmass'][4],
fitstbl['exptime'][4],
kastb.telescope['longitude'],
kastb.telescope['latitude'],
ra=RA,
dec=DEC)
# Test
assert isinstance(sens_dict, dict)
assert isinstance(sens_dict['wave_min'], units.Quantity)
def ech_generate_sensfunc(stdframe,spectrograph=None, telluric=True, star_type=None,
star_mag=None, ra=None, dec=None, std_file = None, BALM_MASK_WID=5., nresln=None,debug=False):
if spectrograph is None:
std_specobjs, std_header = ech_load_specobj(stdframe, order=0)
spectrograph = std_header['INSTRUME']
msgs.info('You are working on {:s}'.format(spectrograph))
ext_final = fits.getheader(stdframe, -1)
norder = 5
#norder = ext_final['ORDER'] + 1
sens_dicts = {}
for iord in range(norder):
std_specobjs, std_header = ech_load_specobj(stdframe, order=iord)
std_idx = flux.find_standard(std_specobjs)
std = std_specobjs[std_idx]
wavemask = std.boxcar['WAVE']>1000.0*units.AA
wave,counts,ivar = std.boxcar['WAVE'][wavemask],std.boxcar['COUNTS'][wavemask],std.boxcar['COUNTS_IVAR'][wavemask]
sens_dict = flux.generate_sensfunc(wave,counts,ivar,std_header['AIRMASS'],std_header['EXPTIME'],
spectrograph,star_type=star_type,star_mag=star_mag,
telluric=telluric,ra=ra,dec=dec,BALM_MASK_WID=BALM_MASK_WID,
nresln=nresln,std_file=std_file,debug=debug)
sens_dict['ech_orderindx'] = iord
sens_dicts[str(iord)] = sens_dict
sens_dicts['norder'] = norder
return sens_dicts
def generate_sensfunc(self):
"""
Generate the senstivity function
Wrapper to flux.generate_sensfunc
Requires self.std has been set
Returns
-------
self.sensfunc : dict
"""
# Check internals
if self.std is None:
msgs.warn('First identify the star first (with find_standard).')
return None
if self.std_header is None:
msgs.warn(
'First set std_header with a dict-like object holding RA, DEC, '
'AIRMASS, EXPTIME.')
return None
self.sens_dict = {}
try:
this_wave = self.std.optimal['WAVE_GRID']
except KeyError:
this_wave = self.std.optimal['WAVE']
sens_dict_long = flux.generate_sensfunc(
this_wave,
self.std.optimal['COUNTS'],
self.std.optimal['COUNTS_IVAR'],
self.std_header['AIRMASS'],
self.std_header['EXPTIME'],
self.spectrograph.telescope['longitude'],
self.spectrograph.telescope['latitude'],
BALM_MASK_WID=self.par['balm_mask_wid'],
telluric=self.telluric,
ra=self.std_ra,
dec=self.std_dec,
std_file=self.std_file,
debug=self.debug)
self.sens_dict['0'] = sens_dict_long
self.sens_dict['nslits'] = 1
# Step
self.steps.append(inspect.stack()[0][3])
# Return
return self.sens_dict
def ech_generate_sensfunc(stdframe,
spectrograph=None,
telluric=True,
star_type=None,
star_mag=None,
ra=None,
dec=None,
std_file=None,
BALM_MASK_WID=5.,
nresln=None,
debug=False):
if spectrograph is None:
std_specobjs, std_header = ech_load_specobj(stdframe, order=0)
spectrograph = std_header['INSTRUME']
msgs.info('You are working on {:s}'.format(spectrograph))
ext_final = fits.getheader(stdframe, -1)
norder = 5
#norder = ext_final['ORDER'] + 1
sens_dicts = {}
for iord in range(norder):
std_specobjs, std_header = ech_load_specobj(stdframe, order=iord)
std_idx = flux.find_standard(std_specobjs)
std = std_specobjs[std_idx]
wavemask = std.boxcar['WAVE'] > 1000.0 * units.AA
wave, counts, ivar = std.boxcar['WAVE'][wavemask], std.boxcar[
'COUNTS'][wavemask], std.boxcar['COUNTS_IVAR'][wavemask]
sens_dict = flux.generate_sensfunc(wave,
counts,
ivar,
std_header['AIRMASS'],
std_header['EXPTIME'],
spectrograph,
star_type=star_type,
star_mag=star_mag,
telluric=telluric,
ra=ra,
dec=dec,
BALM_MASK_WID=BALM_MASK_WID,
nresln=nresln,
std_file=std_file,
debug=debug)
sens_dict['ech_orderindx'] = iord
sens_dicts[str(iord)] = sens_dict
sens_dicts['norder'] = norder
return sens_dicts
def generate_sensfunc(self):
"""
Generate the senstivity function
Wrapper to flux.generate_sensfunc
Requires self.std has been set
Returns
-------
self.sensfunc : dict
"""
# Check internals
# if self.std is None:
# msgs.warn('First identify the star first (with find_standard).')
# return None
if self.std_header is None:
msgs.warn('First set std_header with a dict-like object holding RA, DEC, '
'AIRMASS, EXPTIME.')
return None
ext_final = fits.getheader(self.std_spec1d_file, -1)
norder = ext_final['ORDER'] + 1
self.sens_dict = {}
for iord in range(norder):
std_specobjs, std_header = load.ech_load_specobj(self.std_spec1d_file, order=iord)
std_idx = flux.find_standard(std_specobjs)
std = std_specobjs[std_idx]
wavemask = std.boxcar['WAVE'] > 1000.0 * units.AA
wave, counts, ivar = std.boxcar['WAVE'][wavemask], std.boxcar['COUNTS'][wavemask], \
std.boxcar['COUNTS_IVAR'][wavemask]
sens_dict_iord = flux.generate_sensfunc(wave, counts, ivar, std_header['AIRMASS'], std_header['EXPTIME'],
self.spectrograph, star_type=self.star_type, star_mag=self.star_mag,
telluric=self.telluric, ra=self.std_ra, dec=self.std_dec,
BALM_MASK_WID=self.BALM_MASK_WID,
nresln=self.nresln, std_file=self.std_file, debug=self.debug)
sens_dict_iord['ech_orderindx'] = iord
self.sens_dict[str(iord)] = sens_dict_iord
self.sens_dict['norder'] = norder
# Step
self.steps.append(inspect.stack()[0][3])
# Return
return self.sens_dict
def generate_sensfunc(self):
"""
Generate the senstivity function
Wrapper to flux.generate_sensfunc
Requires self.std has been set
Returns
-------
self.sensfunc : dict
"""
# Check internals
if self.std is None:
msgs.warn('First identify the star first (with find_standard).')
return None
if self.std_header is None:
msgs.warn(
'First set std_header with a dict-like object holding RA, DEC, '
'AIRMASS, EXPTIME.')
return None
ext_final = fits.getheader(self.par['std_file'], -1)
norder = ext_final['ECHORDER'] + 1
self.sens_dict = {}
for iord in range(norder):
std_specobjs, std_header = load.load_specobjs(self.par['std_file'],
order=iord)
std_idx = flux.find_standard(std_specobjs)
std = std_specobjs[std_idx]
try:
wavemask = std.optimal['WAVE_GRID'] > 0.0 #*units.AA
except KeyError:
wavemask = std.optimal['WAVE'] > 1000.0 * units.AA
this_wave = std.optimal['WAVE'][wavemask]
else:
this_wave = std.optimal['WAVE_GRID'][wavemask]
counts, ivar = std.optimal['COUNTS'][wavemask], std.optimal[
'COUNTS_IVAR'][wavemask]
sens_dict_iord = flux.generate_sensfunc(
this_wave,
counts,
ivar,
float(self.std_header['AIRMASS']),
self.std_header['EXPTIME'],
self.spectrograph.telescope['longitude'],
self.spectrograph.telescope['latitude'],
star_type=self.star_type,
star_mag=self.star_mag,
telluric=self.telluric,
ra=self.std_ra,
dec=self.std_dec,
resolution=self.resolution,
BALM_MASK_WID=self.BALM_MASK_WID,
std_file=self.std_file,
poly_norder=self.poly_norder,
polycorrect=self.polycorrect,
debug=self.debug)
sens_dict_iord['ech_orderindx'] = iord
self.sens_dict[str(iord)] = sens_dict_iord
## add some keys to be saved into primary header in masterframe
for key in [
'wave_max', 'exptime', 'airmass', 'std_file', 'std_ra',
'std_dec', 'std_name', 'cal_file'
]:
try:
self.sens_dict[key] = sens_dict_iord[key]
except:
pass
self.sens_dict['meta'] = {}
self.sens_dict['meta']['nslits'] = norder
self.sens_dict['wave_min'] = self.sens_dict['0']['wave_min']
# Step
self.steps.append(inspect.stack()[0][3])
# Return
return self.sens_dict