def build_template(in_files, slits, wv_cuts, binspec, outroot,
lowredux=True, ifiles=None, det_cut=None, chk=False):
"""
Generate a full_template for a given instrument
Args:
in_files:
slits:
wv_cuts:
binspec:
outroot:
lowredux:
ifiles:
det_cut:
chk:
Returns:
"""
# Load xidl file
# Grab it
# Load and splice
yvals = []
lvals = []
if not isinstance(in_files,list):
in_files = [in_files]
ifiles = [0]*len(slits)
for kk, slit in enumerate(slits):
in_file = in_files[ifiles[kk]]
if lowredux:
wv_vac, spec = xidl_arcspec(in_file, slit)
else:
wv_vac, spec = pypeit_arcspec(in_file, slit)
# Cut
if len(slits) > 1:
if kk == 0:
llow = 0.
lhi = wv_cuts[0]
elif kk == len(slits)-1:
llow = wv_cuts[kk-1]
lhi = 1e9
else:
llow = wv_cuts[kk-1]
lhi = wv_cuts[kk]
#
gdi = (wv_vac > llow) & (wv_vac < lhi)
else:
gdi = np.arange(spec.size).astype(int)
# Append
yvals.append(spec[gdi])
lvals.append(wv_vac[gdi])
# Concatenate
nwspec = np.concatenate(yvals)
nwwv = np.concatenate(lvals)
# Check
if chk:
debugger.plot1d(nwwv, nwspec)
# Generate the table
write_template(nwwv, nwspec, binspec, outpath, outroot, det_cut=det_cut)
def show_sensfunc(self):
"""
Plot the sensitivity function
"""
if self.sens_dict is None:
msgs.warn("You need to generate the sens_dict first!")
return None
# Generate from model
#wave = np.linspace(self.sens_dict['wave_min'], self.sens_dict['wave_max'], 1000)
#mag_func = utils.func_val(self.sens_dict['c'], wave, self.sens_dict['func'])
#sens = 10.0**(0.4*mag_func)
# Plot
debugger.plot1d(self.sens_dict['wave'],
self.sens_dict['sensfunc'],
xlbl='Wavelength',
ylbl='Sensitivity Function')
def show_sensfunc(self):
"""
Plot the sensitivity function
"""
if self.sens_dict is None:
msgs.warn("You need to generate the sens_dict first!")
return None
# Generate from model
#wave = np.linspace(self.sens_dict['wave_min'], self.sens_dict['wave_max'], 1000)
#mag_func = utils.func_val(self.sens_dict['c'], wave, self.sens_dict['func'])
#sens = 10.0**(0.4*mag_func)
# Plot
if self.spectrograph.pypeline == 'Echelle':
for iord in range(len(self.std)):
sord = str(iord)
debugger.plot1d(self.sens_dict[sord]['wave'],
self.sens_dict[sord]['sensfunc'],
xlbl='Wavelength',
ylbl='Sensitivity Function')
else:
debugger.plot1d(self.sens_dict['0']['wave'],
self.sens_dict['0']['sensfunc'],
xlbl='Wavelength',
ylbl='Sensitivity Function')
def build_template(in_files, slits, wv_cuts, binspec, outroot, outdir=None,
normalize=False, subtract_conti=False, wvspec=None,
lowredux=True, ifiles=None, det_cut=None, chk=False,
miny=None, overwrite=True):
"""
Generate a full_template for a given instrument
Args:
in_files (list or str):
Wavelength solution files, XIDL or PypeIt
slits (list):
Slits in the archive files to use
wv_cuts (list):
Wavelengths to cut each slit at
binspec (int):
Spectral binning of the archived spectrum
outroot (str):
Name of output archive
outdir (str):
Name of output directory
lowredux (bool, optional):
If true, in_files are from LowRedux
wvspec (ndarray, optional):
Manually input the wavelength values
ifiles (list, optional):
Ordering of the in_files. Default is np.arange(len(in_files))
det_cut (dict, optional):
Cut the detector into pieces. Important for long detectors with wavelengths on one side
chk (bool, optional):
Show a plot or two
miny (float):
Impose a minimum value
normalize (bool, optional):
If provided multiple in_files, normalize each
snippet to have the same maximum amplitude.
subtract_conti (bool, optional):
Subtract the continuum for the final archive
"""
if outdir is None:
outdir = outpath
# Load xidl file
# Grab it
# Load and splice
yvals = []
lvals = []
if not isinstance(in_files,list):
in_files = [in_files]
ifiles = [0]*len(slits)
for kk, slit in enumerate(slits):
if wvspec is None:
in_file = in_files[ifiles[kk]]
if lowredux:
wv_vac, spec = xidl_arcspec(in_file, slit)
else:
wv_vac, spec = pypeit_arcspec(in_file, slit)
else:
wv_vac, spec = wvspec['wv_vac'], wvspec['spec']
# Cut
if len(slits) > 1:
if kk == 0:
llow = 0.
lhi = wv_cuts[0]
elif kk == len(slits)-1:
llow = wv_cuts[kk-1]
lhi = 1e9
else:
llow = wv_cuts[kk-1]
lhi = wv_cuts[kk]
#
gdi = (wv_vac > llow) & (wv_vac < lhi)
else:
gdi = np.arange(spec.size).astype(int)
# Append
yvals.append(spec[gdi])
lvals.append(wv_vac[gdi])
# Continuum
if subtract_conti:
for kk,spec in enumerate(yvals):
_, _, _, _, spec_cont_sub = wvutils.arc_lines_from_spec(spec)
yvals[kk] = spec_cont_sub
# Normalize?
if normalize:
norm_val = 10000.
# Max values
maxs = []
for kk,spec in enumerate(yvals):
mx = np.max(spec)
spec = spec * norm_val / mx
yvals[kk] = spec
# Concatenate
nwspec = np.concatenate(yvals)
nwwv = np.concatenate(lvals)
# Min y?
if miny is not None:
nwspec = np.maximum(nwspec, miny)
# Check
if chk:
debugger.plot1d(nwwv, nwspec)
embed(header='123')
# Generate the table
write_template(nwwv, nwspec, binspec, outdir, outroot, det_cut=det_cut, overwrite=overwrite)
