def moogsynth(*args,**kwargs):
"""
NAME:
moogsynth
PURPOSE:
Run a MOOG synthesis (direct interface to the MOOG code; use 'synth' for a general routine that generates the non-continuum-normalized spectrum, convolves withe LSF and macrotubulence, and optionally continuum normalizes the output)
INPUT ARGUMENTS:
lists with abundances (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
SYNTHEIS KEYWORDS:
isotopes= ('solar') use 'solar' or 'arcturus' isotope ratios; can also be a dictionary with isotope ratios (e.g., isotopes= {'108.00116':'1.001','606.01212':'1.01'})
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
doflux= (False) if True, calculate the continuum flux instead
LINELIST KEYWORDS:
linelist= (None) linelist to use; if this is None, the code looks for a weed-out version of the linelist appropriate for the given model atmosphere; otherwise can be set to the path of a linelist file or to the name of an APOGEE linelist
ATMOSPHERE KEYWORDS:
Either:
(a) modelatm= (None) can be set to the filename of a model atmosphere (needs to end in .mod)
(b) specify the stellar parameters for a grid point in model atm by
- lib= ('kurucz_filled') spectral library
- teff= (4500) grid-point Teff
- logg= (2.5) grid-point logg
- metals= (0.) grid-point metallicity
- cm= (0.) grid-point carbon-enhancement
- am= (0.) grid-point alpha-enhancement
- dr= return the path corresponding to this data release
vmicro= (2.) microturbulence (km/s) (only used if the MOOG-formatted atmosphere file doesn't already exist)
OUTPUT:
(wavelengths,spectra (nspec,nwave)) for synth driver
(wavelengths,continuum spectr (nwave)) for doflux driver
HISTORY:
2015-02-13 - Written - Bovy (IAS)
"""
doflux= kwargs.pop('doflux',False)
# Get the spectral synthesis limits
wmin= kwargs.pop('wmin',_WMIN_DEFAULT)
wmax= kwargs.pop('wmax',_WMAX_DEFAULT)
dw= kwargs.pop('dw',_DW_DEFAULT)
width= kwargs.pop('width',_WIDTH_DEFAULT)
linelist= kwargs.pop('linelist',None)
# Parse isotopes
isotopes= kwargs.pop('isotopes','solar')
if isinstance(isotopes,str) and isotopes.lower() == 'solar':
isotopes= {'108.00116':'1.001',
'606.01212':'1.01',
'606.01213':'90',
'606.01313':'180',
'607.01214':'1.01',
'607.01314':'90',
'607.01215':'273',
'608.01216':'1.01',
'608.01316':'90',
'608.01217':'1101',
'608.01218':'551',
'114.00128':'1.011',
'114.00129':'20',
'114.00130':'30',
'101.00101':'1.001',
'101.00102':'1000',
'126.00156':'1.00'}
elif isinstance(isotopes,str) and isotopes.lower() == 'arcturus':
isotopes= {'108.00116':'1.001',
'606.01212':'0.91',
'606.01213':'8',
'606.01313':'81',
'607.01214':'0.91',
'607.01314':'8',
'607.01215':'273',
'608.01216':'0.91',
'608.01316':'8',
'608.01217':'1101',
'608.01218':'551',
'114.00128':'1.011',
'114.00129':'20',
'114.00130':'30',
'101.00101':'1.001',
'101.00102':'1000',
'126.00156':'1.00'}
elif not isinstance(isotopes,dict):
raise ValueError("'isotopes=' input not understood, should be 'solar', 'arcturus', or a dictionary")
# Get the filename of the model atmosphere
modelatm= kwargs.pop('modelatm',None)
if not modelatm is None:
if isinstance(modelatm,str) and os.path.exists(modelatm):
modelfilename= modelatm
elif isinstance(modelatm,str):
raise ValueError('modelatm= input is a non-existing filename')
else:
raise ValueError('modelatm= in moogsynth should be set to the name of a file')
else:
modelfilename= appath.modelAtmospherePath(**kwargs)
# Check whether a MOOG version exists
if not os.path.exists(modelfilename.replace('.mod','.org')):
# Convert to MOOG format
convert_modelAtmosphere(modelatm=modelfilename,**kwargs)
modeldirname= os.path.dirname(modelfilename)
modelbasename= os.path.basename(modelfilename)
# Get the name of the linelist
if linelist is None:
linelistfilename= modelbasename.replace('.mod','.lines')
if not os.path.exists(os.path.join(modeldirname,linelistfilename)):
raise IOError('No linelist given and no weed-out version found for this atmosphere; either specify a linelist or run weedout first')
linelistfilename= os.path.join(modeldirname,linelistfilename)
elif os.path.exists(linelist):
linelistfilename= linelist
else:
linelistfilename= appath.linelistPath(linelist,
dr=kwargs.get('dr',None))
# We will run in a subdirectory of the relevant model atmosphere
tmpDir= tempfile.mkdtemp(dir=modeldirname)
shutil.copy(linelistfilename,tmpDir)
# Cut the linelist to the desired wavelength range
with open(os.path.join(tmpDir,'cutlines.awk'),'w') as awkfile:
awkfile.write('$1>%.3f && $1<%.3f\n' %(wmin-width,wmax+width))
keeplines= open(os.path.join(tmpDir,'lines.tmp'),'w')
stderr= open('/dev/null','w')
try:
subprocess.check_call(['awk','-f','cutlines.awk',
os.path.basename(linelistfilename)],
cwd=tmpDir,stdout=keeplines,stderr=stderr)
keeplines.close()
shutil.copy(os.path.join(tmpDir,'lines.tmp'),
os.path.join(tmpDir,os.path.basename(linelistfilename)))
except subprocess.CalledProcessError:
print("Removing unnecessary linelist entries failed ...")
finally:
os.remove(os.path.join(tmpDir,'cutlines.awk'))
os.remove(os.path.join(tmpDir,'lines.tmp'))
stderr.close()
# Also copy the strong lines
stronglinesfilename= appath.linelistPath('stronglines.vac',
dr=kwargs.get('dr',None))
if not os.path.exists(stronglinesfilename):
download.linelist('stronglines.vac',dr=kwargs.get('dr',None))
shutil.copy(stronglinesfilename,tmpDir)
# Now write the script file
if len(args) == 0: #special case that there are *no* differences
args= ([26,0.],)
nsynths= numpy.array([len(args[ii])-1 for ii in range(len(args))])
nsynth= numpy.amax(nsynths) #Take the longest abundance list
if nsynth > 5:
raise ValueError("MOOG only allows five syntheses to be run at the same time; please reduce the number of abundance values in the apogee.modelspec.moog.moogsynth input")
nabu= len(args)
with open(os.path.join(tmpDir,'synth.par'),'w') as parfile:
if doflux:
parfile.write('doflux\n')
else:
parfile.write('synth\n')
parfile.write('terminal x11\n')
parfile.write('plot 1\n')
parfile.write("standard_out std.out\n")
parfile.write("summary_out '../synth.out'\n")
parfile.write("smoothed_out '/dev/null'\n")
parfile.write("strong 1\n")
parfile.write("damping 0\n")
parfile.write("stronglines_in stronglines.vac\n")
parfile.write("model_in '../%s'\n" % modelbasename.replace('.mod','.org'))
parfile.write("lines_in %s\n" % os.path.basename(linelistfilename))
parfile.write("atmosphere 1\n")
parfile.write("molecules 2\n")
parfile.write("lines 1\n")
parfile.write("flux/int 0\n")
# Write the isotopes
niso= len(isotopes)
parfile.write("isotopes %i %i\n" % (niso,nsynth))
for iso in isotopes:
isotopestr= iso
for ii in range(nsynth):
isotopestr+= ' '+isotopes[iso]
parfile.write(isotopestr+'\n')
# Abundances
parfile.write("abundances %i %i\n" % (nabu,nsynth))
for ii in range(nabu):
abustr= '%i' % args[ii][0]
for jj in range(nsynth):
try:
abustr+= ' %.3f' % args[ii][jj+1]
except IndexError:
abustr+= ' 0.0'
parfile.write(abustr+"\n")
# Synthesis limits
parfile.write("synlimits\n") # Add 0.001 to make sure wmax is included
parfile.write("%.3f %.3f %.3f %.3f\n" % (wmin,wmax+0.001,dw,width))
# Now run synth
sys.stdout.write('\r'+"Running MOOG synth ...\r")
sys.stdout.flush()
try:
p= subprocess.Popen(['moogsilent'],
cwd=tmpDir,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p.stdin.write('synth.par\n')
stdout, stderr= p.communicate()
except subprocess.CalledProcessError:
print("Running synth failed ...")
finally:
if os.path.exists(os.path.join(tmpDir,'synth.par')):
os.remove(os.path.join(tmpDir,'synth.par'))
if os.path.exists(os.path.join(tmpDir,'std.out')):
os.remove(os.path.join(tmpDir,'std.out'))
if os.path.exists(os.path.join(tmpDir,
os.path.basename(linelistfilename))):
os.remove(os.path.join(tmpDir,os.path.basename(linelistfilename)))
if os.path.exists(os.path.join(tmpDir,'stronglines.vac')):
os.remove(os.path.join(tmpDir,'stronglines.vac'))
os.rmdir(tmpDir)
sys.stdout.write('\r'+download._ERASESTR+'\r')
sys.stdout.flush()
# Now read the output
wavs= numpy.arange(wmin,wmax+dw,dw)
if wavs[-1] > wmax+dw/2.: wavs= wavs[:-1]
if doflux:
contdata= numpy.loadtxt(os.path.join(modeldirname,'synth.out'),
converters={0:lambda x: x.replace('D','E'),
1:lambda x: x.replace('D','E')},
usecols=[0,1])
# Wavelength in summary file appears to be wrong from comparing to
# the standard output file
out= contdata[:,1]
out/= numpy.nanmean(out) # Make the numbers more manageable
else:
with open(os.path.join(modeldirname,'synth.out')) as summfile:
out= numpy.empty((nsynth,len(wavs)))
for ii in range(nsynth):
# Skip to beginning of synthetic spectrum
while True:
line= summfile.readline()
if line[0] == 'M': break
summfile.readline()
tout= []
while True:
line= summfile.readline()
if not line or line[0] == 'A': break
tout.extend([float(s) for s in line.split()])
out[ii]= numpy.array(tout)
os.remove(os.path.join(modeldirname,'synth.out'))
if doflux:
return (wavs,out)
else:
return (wavs,1.-out)
def synth(*args,**kwargs):
"""
NAME:
synth
PURPOSE:
Generate model APOGEE spectra using MOOG: this is a general routine that generates the non-continuum-normalized spectrum, convolves with the LSF and macrotubulence, and optionally continuum normalizes the output; use 'moogsynth' for a direct interface to MOOG
INPUT ARGUMENTS:
lists with abundances wrt the atmosphere (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
INPUT KEYWORDS:
LSF:
lsf= ('all') LSF to convolve with; output of apogee.spec.lsf.eval; sparsify for efficiency; if 'all' or 'combo' a pre-computed version will be downloaded from the web
Either:
xlsf= (None) pixel offset grid on which the LSF is computed (see apogee.spec.lsf.eval); unnecessary if lsf=='all' or 'combo'
dxlsf= (None) spacing of pixel offsets
vmacro= (6.) macroturbulence to apply
CONTINUUM:
cont= ('aspcap') continuum-normalization to apply:
None: no continuum normalization
'true': Use the true continuum
'aspcap': Use the continuum normalization method of ASPCAP DR12
'cannon': Normalize using continuum pixels derived from the Cannon
SYNTHESIS:
linelist= (None) linelist to use; can be set to the path of a linelist file or to the name of an APOGEE linelist
run_weedout= (False) if True, run MOOG weedout on the linelist first
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
lib= ('kurucz_filled') spectral library
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere or to a model-atmosphere instance (if filename, needs to end in .mod)
(b) parameters of a KURUCZ model atmosphere:
(1) teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
(2) fparam= standard ASPCAP output format
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found) (can also be part of fparam)
MISCELLANEOUS:
dr= return the path corresponding to this data release
OUTPUT:
spectra (nspec,nwave)
HISTORY:
2015-03-15 - Written - Bovy (IAS)
"""
run_weedout= kwargs.pop('run_weedout',False)
# Check that we have the LSF and store the relevant keywords
lsf= kwargs.pop('lsf','all')
if isinstance(lsf,str):
xlsf, lsf= aplsf._load_precomp(dr=kwargs.get('dr',None),fiber=lsf)
dxlsf= None
else:
xlsf= kwargs.pop('xlsf',None)
dxlsf= kwargs.pop('dxlsf',None)
if xlsf is None and dxlsf is None: raise ValueError('xlsf= or dxlsf= input needs to be given if the LSF is given as an array')
vmacro= kwargs.pop('vmacro',6.)
# Parse continuum-normalization keywords
cont= kwargs.pop('cont','aspcap')
# Setup the model atmosphere
modelatm= kwargs.pop('modelatm',None)
tmpModelAtmDir= False
# Parse fparam, if present
fparam= kwargs.pop('fparam',None)
if not fparam is None:
kwargs['teff']= fparam[paramIndx('TEFF')]
kwargs['logg']= fparam[paramIndx('LOGG')]
kwargs['metals']= fparam[paramIndx('METALS')]
kwargs['am']= fparam[paramIndx('ALPHA')]
kwargs['cm']= fparam[paramIndx('C')]
kwargs['vm']= 10.**fparam[paramIndx('LOG10VDOP')]
if modelatm is None: # Setup a model atmosphere
modelatm= atlas9.Atlas9Atmosphere(teff=kwargs.get('teff',4500.),
logg=kwargs.get('logg',2.5),
metals=kwargs.get('metals',0.),
am=kwargs.get('am',0.),
cm=kwargs.get('cm',0.),
dr=kwargs.get('dr',None))
if isinstance(modelatm,str) and os.path.exists(modelatm):
modelfilename= modelatm
elif isinstance(modelatm,str):
raise ValueError('modelatm= input is a non-existing filename')
else: # model atmosphere instance
# Need to write this instance to a file; we will run in a temp
# subdirectory of the current directory
tmpDir= tempfile.mkdtemp(dir=os.getcwd())
tmpModelAtmDir= True # need to remove this later
modelfilename= os.path.join(tmpDir,'modelatm.mod')
modelatm.writeto(modelfilename)
kwargs['modelatm']= modelfilename
try:
# Check whether a MOOG version of the model atmosphere exists
if not os.path.exists(modelfilename.replace('.mod','.org')):
# Convert to MOOG format
convert_modelAtmosphere(**kwargs)
# Run weedout on the linelist first if requested
if run_weedout:
linelistfilename= modelfilename.replace('.mod','.lines')
if not os.path.exists(linelistfilename):
weedout(**kwargs)
kwargs['linelist']= linelistfilename
# Run MOOG synth for all abundances
if len(args) == 0: #special case that there are *no* differences
args= ([26,0.],)
nsynths= numpy.array([len(args[ii])-1 for ii in range(len(args))])
nsynth= numpy.amax(nsynths) #Take the longest abundance list
nmoogwav= int((kwargs.get('wmax',_WMAX_DEFAULT)\
-kwargs.get('wmin',_WMIN_DEFAULT))\
/kwargs.get('dw',_DW_DEFAULT)+1)
out= numpy.empty((nsynth,nmoogwav))
# Check whether the number of syntheses is > 5 and run multiple
# MOOG instances if necessary, bc MOOG only does 5 at a time
ninstances= int(numpy.ceil(nsynth/5.))
for ii in range(ninstances):
newargs= ()
for jj in range(len(args)):
tab= [args[jj][0]]
if len(args[jj][5*ii+1:5*(ii+1)+1]) > 0:
tab.extend(args[jj][5*ii+1:5*(ii+1)+1])
newargs= newargs+(tab,)
out[5*ii:5*(ii+1)]= moogsynth(*newargs,**kwargs)[1]
# We'll grab the wavelength grid from the continuum below
# Now compute the continuum and multiply each c-norm spectrum with it
mwav, cflux= moogsynth(doflux=True,**kwargs)
except: raise
finally:
if tmpModelAtmDir: # need to remove this temporary directory
os.remove(modelfilename)
moogmodelfilename= modelfilename.replace('.mod','.org')
if os.path.exists(moogmodelfilename):
os.remove(moogmodelfilename)
if run_weedout:
os.remove(modelfilename.replace('.mod','.lines'))
os.rmdir(tmpDir)
out*= numpy.tile(cflux,(nsynth,1))
# Now convolve with the LSF
out= aplsf.convolve(mwav,out,
lsf=lsf,xlsf=xlsf,dxlsf=dxlsf,vmacro=vmacro)
# Now continuum-normalize
if cont.lower() == 'true':
# Get the true continuum on the apStar wavelength grid
apWave= apStarWavegrid()
baseline= numpy.polynomial.Polynomial.fit(mwav,cflux,4)
ip= interpolate.InterpolatedUnivariateSpline(mwav,
cflux/baseline(mwav),
k=3)
cflux= baseline(apWave)*ip(apWave)
# Divide it out
out/= numpy.tile(cflux,(nsynth,1))
elif not cont is None:
cflux= apcont.fit(out,numpy.ones_like(out),type=cont)
out[cflux > 0.]/= cflux[cflux > 0.]
out[cflux <= 0.]= numpy.nan
return out
def weedout(**kwargs):
"""
NAME:
weedout
PURPOSE:
Weed-out unnecessary lines from the linelist for a given atmosphere
INPUT:
linelist= (None) linelist to use; can be set to the path of a linelist file or to the name of an APOGEE linelist
keepratio= (0.00001) Eliminate lines weaker than keepratio where keepratio = kapnu/kaplam at the approximate line wavelength, calculated at a continuue optical depth of 0.5
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere (needs to end in .mod)
( b) parameters of a KURUCZ model atmosphere:
teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found)
OUTPUT:
(none; just weeds out lines)
HISTORY:
2015-02-13 - Written - Bovy (IAS)
"""
# Get the name of the linelist
linelist= kwargs.pop('linelist','moog.201312161124.vac')
if os.path.exists(linelist):
linelistfilename= linelist
else:
linelistfilename= appath.linelistPath(linelist,
dr=kwargs.get('dr',None))
# Get the spectral synthesis limits
wmin= kwargs.pop('wmin',_WMIN_DEFAULT)
wmax= kwargs.pop('wmax',_WMAX_DEFAULT)
dw= kwargs.pop('dw',_DW_DEFAULT)
width= kwargs.pop('width',_WIDTH_DEFAULT)
# Ratio of lines to keep
keepratio= kwargs.pop('keepratio',0.00001)
# Get the filename of the model atmosphere
modelatm= kwargs.pop('modelatm',None)
if not modelatm is None:
if isinstance(modelatm,str) and os.path.exists(modelatm):
modelfilename= modelatm
elif isinstance(modelatm,str):
raise ValueError('modelatm= input is a non-existing filename')
else:
raise ValueError('modelatm= in moogsynth should be set to the name of a file')
else:
modelfilename= appath.modelAtmospherePath(**kwargs)
# Check whether a MOOG version exists
if not os.path.exists(modelfilename.replace('.mod','.org')):
# Convert to MOOG format
convert_modelAtmosphere(modelatm=modelfilename,**kwargs)
modeldirname= os.path.dirname(modelfilename)
modelbasename= os.path.basename(modelfilename)
outname= modelbasename.replace('.mod','.lines')
# We will run in a subdirectory of the relevant model atmosphere
tmpDir= tempfile.mkdtemp(dir=modeldirname)
shutil.copy(linelistfilename,tmpDir)
# Now write the script file
with open(os.path.join(tmpDir,'weedout.par'),'w') as parfile:
parfile.write('weedout\n')
parfile.write('terminal x11\n')
parfile.write('plot 0\n')
parfile.write("standard_out '/dev/null'\n")
parfile.write("keeplines_out '../%s'\n" % outname)
parfile.write("tosslines_out 'toss.out'\n")
parfile.write("summary_out '/dev/null'\n")
parfile.write("smoothed_out '/dev/null'\n")
parfile.write("damping 0\n")
parfile.write("model_in '../%s'\n" % modelbasename.replace('.mod','.org'))
parfile.write("lines_in %s\n" % os.path.basename(linelistfilename))
parfile.write("atmosphere 1\n")
parfile.write("molecules 2\n")
parfile.write("lines 1\n")
parfile.write("flux/int 0\n")
parfile.write("synlimits\n")
parfile.write("%.3f %.3f %.3f %.3f\n" % (wmin,wmax,dw,width))
# Now run weedout
sys.stdout.write('\r'+"Running MOOG weedout ...\r")
sys.stdout.flush()
try:
p= subprocess.Popen(['moogsilent'],
cwd=tmpDir,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p.stdin.write('weedout.par\n')
p.stdin.write('%g\n' % keepratio)
stdout, stderr= p.communicate()
except subprocess.CalledProcessError:
print("Running weedout failed ...")
finally:
if os.path.exists(os.path.join(tmpDir,'weedout.par')):
os.remove(os.path.join(tmpDir,'weedout.par'))
if os.path.exists(os.path.join(tmpDir,'toss.out')):
os.remove(os.path.join(tmpDir,'toss.out'))
if os.path.exists(os.path.join(tmpDir,
os.path.basename(linelistfilename))):
os.remove(os.path.join(tmpDir,os.path.basename(linelistfilename)))
os.rmdir(tmpDir)
sys.stdout.write('\r'+"Running MOOG weedout ...\r")
sys.stdout.flush()
return None
def windows(*args,**kwargs):
"""
NAME:
windows
PURPOSE:
Generate model APOGEE spectra using MOOG in selected wavelength windows (but the whole APOGEE spectral range is returned): this is a general routine that generates the non-continuum-normalized spectrum, convolves with the LSF and macrotubulence, and optionally continuum normalizes the output; use 'moogsynth' for a direct interface to MOOG
INPUT ARGUMENTS:
Windows specification: Provide one of
(1) Element string: the APOGEE windows for this element will be loaded
(2) startindxs, endindxs= start and end indexes of the windows on the apStar wavelength grid
(3) startlams, endlams= start and end wavelengths in \AA
lists with abundance differences wrt the atmosphere (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
INPUT KEYWORDS:
BASELINE: you can specify the baseline spectrum to not always re-compute it
baseline= baseline c-normalized spectrum on MOOG wavelength grid (obtained from moogsynth)
mwav= MOOG wavelength grid (obtained from moogsynth)
cflux= continuum flux from MOOG
Typically, you can obtain these three keywords by doing (kwargs are the keywords you provide to this function as well)
>>> baseline= moogsynth(**kwargs)[1]
>>> mwav, cflux= moogsynth(doflux=True,**kwargs)
LSF:
lsf= ('all') LSF to convolve with; output of apogee.spec.lsf.eval; sparsify for efficiency; if 'all' or 'combo' a pre-computed version will be downloaded from the web
Either:
xlsf= (None) pixel offset grid on which the LSF is computed (see apogee.spec.lsf.eval); unnecessary if lsf=='all' or 'combo'
dxlsf= (None) spacing of pixel offsets
vmacro= (6.) macroturbulence to apply
CONTINUUM:
cont= ('aspcap') continuum-normalization to apply:
None: no continuum normalization
'true': Use the true continuum
'aspcap': Use the continuum normalization method of ASPCAP DR12
'cannon': Normalize using continuum pixels derived from the Cannon
SYNTHESIS:
linelist= (None) linelist to use; if this is None, the code looks for a weed-out version of the linelist appropriate for the given model atmosphere
run_weedout= (False) if True, run MOOG weedout on the linelist first
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits *for the whole spectrum* (not just the windows), step, and width of calculation (see MOOG)
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere or to a model-atmosphere instance (if filename, needs to end in .mod)
(b) parameters of a KURUCZ model atmosphere:
(1) teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
(2) fparam= standard ASPCAP output format (
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found) (can also be part of fparam)
MISCELLANEOUS:
dr= return the path corresponding to this data release
OUTPUT:
spectra (nspec,nwave)
HISTORY:
2015-03-18 - Written - Bovy (IAS)
"""
# Pop some kwargs
run_weedout= kwargs.pop('run_weedout',False)
baseline= kwargs.pop('baseline',None)
mwav= kwargs.pop('mwav',None)
cflux= kwargs.pop('cflux',None)
# Check that we have the LSF and store the relevant keywords
lsf= kwargs.pop('lsf','all')
if isinstance(lsf,str):
xlsf, lsf= aplsf._load_precomp(dr=kwargs.get('dr',None),fiber=lsf)
dxlsf= None
else:
xlsf= kwargs.pop('xlsf',None)
dxlsf= kwargs.pop('dxlsf',None)
if xlsf is None and dxlsf is None: raise ValueError('xlsf= or dxlsf= input needs to be given if the LSF is given as an array')
vmacro= kwargs.pop('vmacro',6.)
# Parse continuum-normalization keywords
cont= kwargs.pop('cont','aspcap')
# Parse the wavelength regions
apWave= apStarWavegrid()
if isinstance(args[0],str): #element string given
si,ei= apwindow.waveregions(args[0],pad=3,asIndex=True)
args= args[1:]
else:
if isinstance(args[0][0],int): # assume index
si,ei= args[0], args[1]
else: # assume wavelengths in \AA
sl,el= args[0], args[1]
# Convert to index
si, ei= [], []
for s,e in zip(sl,el):
# Find closest index into apWave
si.append(numpy.argmin(numpy.fabs(s-apWave)))
ei.append(numpy.argmin(numpy.fabs(e-apWave)))
args= args[2:]
# Setup the model atmosphere
modelatm= kwargs.pop('modelatm',None)
tmpModelAtmDir= False
# Parse fparam, if present
fparam= kwargs.pop('fparam',None)
if not fparam is None:
kwargs['teff']= fparam[0,paramIndx('TEFF')]
kwargs['logg']= fparam[0,paramIndx('LOGG')]
kwargs['metals']= fparam[0,paramIndx('METALS')]
kwargs['am']= fparam[0,paramIndx('ALPHA')]
kwargs['cm']= fparam[0,paramIndx('C')]
kwargs['vm']= 10.**fparam[0,paramIndx('LOG10VDOP')]
if modelatm is None: # Setup a model atmosphere
modelatm= atlas9.Atlas9Atmosphere(teff=kwargs.get('teff',4500.),
logg=kwargs.get('logg',2.5),
metals=kwargs.get('metals',0.),
am=kwargs.get('am',0.),
cm=kwargs.get('cm',0.),
dr=kwargs.get('dr',None))
if isinstance(modelatm,str) and os.path.exists(modelatm):
modelfilename= modelatm
elif isinstance(modelatm,str):
raise ValueError('modelatm= input is a non-existing filename')
else: # model atmosphere instance
# Need to write this instance to a file; we will run in a temp
# subdirectory of the current directory
tmpDir= tempfile.mkdtemp(dir=os.getcwd())
tmpModelAtmDir= True # need to remove this later
modelfilename= os.path.join(tmpDir,'modelatm.mod')
modelatm.writeto(modelfilename)
kwargs['modelatm']= modelfilename
try:
# Check whether a MOOG version of the model atmosphere exists
if not os.path.exists(modelfilename.replace('.mod','.org')):
# Convert to MOOG format
convert_modelAtmosphere(**kwargs)
# Run weedout on the linelist first if requested
if run_weedout:
linelistfilename= modelfilename.replace('.mod','.lines')
if not os.path.exists(linelistfilename):
weedout(**kwargs)
kwargs['linelist']= linelistfilename
# Run MOOG synth for the whole wavelength range as a baseline, also contin
if baseline is None:
baseline= moogsynth(**kwargs)[1]
elif isinstance(baseline,tuple): #probably accidentally gave wav as well
baseline= baseline[1]
if mwav is None or cflux is None:
mwav, cflux= moogsynth(doflux=True,**kwargs)
# Convert the apStarWavegrid windows to moogWavegrid regions
sm,em= [], []
for start,end in zip(si,ei):
sm.append(numpy.argmin(numpy.fabs(apWave[start]-mwav)))
em.append(numpy.argmin(numpy.fabs(apWave[end]-mwav)))
# Run MOOG synth for all abundances and all windows
if len(args) == 0: #special case that there are *no* differences
args= ([26,0.],)
nsynths= numpy.array([len(args[ii])-1 for ii in range(len(args))])
nsynth= numpy.amax(nsynths) #Take the longest abundance list
out= numpy.tile(baseline,(nsynth,1))
# Run all windows
for start, end in zip(sm,em):
kwargs['wmin']= mwav[start]
kwargs['wmax']= mwav[end]
# Check whether the number of syntheses is > 5 and run multiple
# MOOG instances if necessary, bc MOOG only does 5 at a time
ninstances= int(numpy.ceil(nsynth/5.))
for ii in range(ninstances):
newargs= ()
for jj in range(len(args)):
tab= [args[jj][0]]
if len(args[jj][5*ii+1:5*(ii+1)+1]) > 0:
tab.extend(args[jj][5*ii+1:5*(ii+1)+1])
newargs= newargs+(tab,)
out[5*ii:5*(ii+1),start:end+1]= moogsynth(*newargs,**kwargs)[1]
except: raise
finally:
if tmpModelAtmDir: # need to remove this temporary directory
os.remove(modelfilename)
moogmodelfilename= modelfilename.replace('.mod','.org')
if os.path.exists(moogmodelfilename):
os.remove(moogmodelfilename)
if run_weedout:
os.remove(modelfilename.replace('.mod','.lines'))
os.rmdir(tmpDir)
# Now multiply each continuum-normalized spectrum with the continuum
out*= numpy.tile(cflux,(nsynth,1))
# Now convolve with the LSF
out= aplsf.convolve(mwav,out,
lsf=lsf,xlsf=xlsf,dxlsf=dxlsf,vmacro=vmacro)
# Now continuum-normalize
if cont.lower() == 'true':
# Get the true continuum on the apStar wavelength grid
apWave= apStarWavegrid()
baseline= numpy.polynomial.Polynomial.fit(mwav,cflux,4)
ip= interpolate.InterpolatedUnivariateSpline(mwav,
cflux/baseline(mwav),
k=3)
cflux= baseline(apWave)*ip(apWave)
# Divide it out
out/= numpy.tile(cflux,(nsynth,1))
elif not cont is None:
cflux= apcont.fit(out,numpy.ones_like(out),type=cont)
out[cflux > 0.]/= cflux[cflux > 0.]
out[cflux <= 0.]= numpy.nan
return out
def moogsynth(*args, **kwargs):
"""
NAME:
moogsynth
PURPOSE:
Run a MOOG synthesis (direct interface to the MOOG code; use 'synth' for a general routine that generates the non-continuum-normalized spectrum, convolves withe LSF and macrotubulence, and optionally continuum normalizes the output)
INPUT ARGUMENTS:
lists with abundances (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
SYNTHEIS KEYWORDS:
isotopes= ('solar') use 'solar' or 'arcturus' isotope ratios; can also be a dictionary with isotope ratios (e.g., isotopes= {'108.00116':'1.001','606.01212':'1.01'})
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
doflux= (False) if True, calculate the continuum flux instead
LINELIST KEYWORDS:
linelist= (None) linelist to use; if this is None, the code looks for a weed-out version of the linelist appropriate for the given model atmosphere; otherwise can be set to the path of a linelist file or to the name of an APOGEE linelist
ATMOSPHERE KEYWORDS:
Either:
(a) modelatm= (None) can be set to the filename of a model atmosphere (needs to end in .mod)
(b) specify the stellar parameters for a grid point in model atm by
- lib= ('kurucz_filled') spectral library
- teff= (4500) grid-point Teff
- logg= (2.5) grid-point logg
- metals= (0.) grid-point metallicity
- cm= (0.) grid-point carbon-enhancement
- am= (0.) grid-point alpha-enhancement
- dr= return the path corresponding to this data release
vmicro= (2.) microturbulence (km/s) (only used if the MOOG-formatted atmosphere file doesn't already exist)
OUTPUT:
(wavelengths,spectra (nspec,nwave)) for synth driver
(wavelengths,continuum spectr (nwave)) for doflux driver
HISTORY:
2015-02-13 - Written - Bovy (IAS)
"""
doflux = kwargs.pop('doflux', False)
# Get the spectral synthesis limits
wmin = kwargs.pop('wmin', _WMIN_DEFAULT)
wmax = kwargs.pop('wmax', _WMAX_DEFAULT)
dw = kwargs.pop('dw', _DW_DEFAULT)
width = kwargs.pop('width', _WIDTH_DEFAULT)
linelist = kwargs.pop('linelist', None)
# Parse isotopes
isotopes = kwargs.pop('isotopes', 'solar')
if isinstance(isotopes, str) and isotopes.lower() == 'solar':
isotopes = {
'108.00116': '1.001',
'606.01212': '1.01',
'606.01213': '90',
'606.01313': '180',
'607.01214': '1.01',
'607.01314': '90',
'607.01215': '273',
'608.01216': '1.01',
'608.01316': '90',
'608.01217': '1101',
'608.01218': '551',
'114.00128': '1.011',
'114.00129': '20',
'114.00130': '30',
'101.00101': '1.001',
'101.00102': '1000',
'126.00156': '1.00'
}
elif isinstance(isotopes, str) and isotopes.lower() == 'arcturus':
isotopes = {
'108.00116': '1.001',
'606.01212': '0.91',
'606.01213': '8',
'606.01313': '81',
'607.01214': '0.91',
'607.01314': '8',
'607.01215': '273',
'608.01216': '0.91',
'608.01316': '8',
'608.01217': '1101',
'608.01218': '551',
'114.00128': '1.011',
'114.00129': '20',
'114.00130': '30',
'101.00101': '1.001',
'101.00102': '1000',
'126.00156': '1.00'
}
elif not isinstance(isotopes, dict):
raise ValueError(
"'isotopes=' input not understood, should be 'solar', 'arcturus', or a dictionary"
)
# Get the filename of the model atmosphere
modelatm = kwargs.pop('modelatm', None)
if not modelatm is None:
if isinstance(modelatm, str) and os.path.exists(modelatm):
modelfilename = modelatm
elif isinstance(modelatm, str):
raise ValueError('modelatm= input is a non-existing filename')
else:
raise ValueError(
'modelatm= in moogsynth should be set to the name of a file')
else:
modelfilename = appath.modelAtmospherePath(**kwargs)
# Check whether a MOOG version exists
if not os.path.exists(modelfilename.replace('.mod', '.org')):
# Convert to MOOG format
convert_modelAtmosphere(modelatm=modelfilename, **kwargs)
modeldirname = os.path.dirname(modelfilename)
modelbasename = os.path.basename(modelfilename)
# Get the name of the linelist
if linelist is None:
linelistfilename = modelbasename.replace('.mod', '.lines')
if not os.path.exists(os.path.join(modeldirname, linelistfilename)):
raise IOError(
'No linelist given and no weed-out version found for this atmosphere; either specify a linelist or run weedout first'
)
linelistfilename = os.path.join(modeldirname, linelistfilename)
elif os.path.exists(linelist):
linelistfilename = linelist
else:
linelistfilename = appath.linelistPath(linelist,
dr=kwargs.get('dr', None))
if not os.path.exists(linelistfilename):
raise RuntimeError(
"Linelist %s not found; download linelist w/ apogee.tools.download.linelist (if you have access)"
% linelistfilename)
# We will run in a subdirectory of the relevant model atmosphere
tmpDir = tempfile.mkdtemp(dir=modeldirname)
shutil.copy(linelistfilename, tmpDir)
# Cut the linelist to the desired wavelength range
with open(os.path.join(tmpDir, 'cutlines.awk'), 'w') as awkfile:
awkfile.write('$1>%.3f && $1<%.3f\n' % (wmin - width, wmax + width))
keeplines = open(os.path.join(tmpDir, 'lines.tmp'), 'w')
stderr = open('/dev/null', 'w')
try:
subprocess.check_call(
['awk', '-f', 'cutlines.awk',
os.path.basename(linelistfilename)],
cwd=tmpDir,
stdout=keeplines,
stderr=stderr)
keeplines.close()
shutil.copy(os.path.join(tmpDir, 'lines.tmp'),
os.path.join(tmpDir, os.path.basename(linelistfilename)))
except subprocess.CalledProcessError:
print("Removing unnecessary linelist entries failed ...")
finally:
os.remove(os.path.join(tmpDir, 'cutlines.awk'))
os.remove(os.path.join(tmpDir, 'lines.tmp'))
stderr.close()
# Also copy the strong lines
stronglinesfilename = appath.linelistPath('stronglines.vac',
dr=kwargs.get('dr', None))
if not os.path.exists(stronglinesfilename):
try:
download.linelist('stronglines.vac', dr=kwargs.get('dr', None))
except:
raise RuntimeError(
"Linelist stronglines.vac not found or downloading failed; download linelist w/ apogee.tools.download.linelist (if you have access)"
)
finally:
if os.path.exists(os.path.join(tmpDir, 'synth.par')):
os.remove(os.path.join(tmpDir, 'synth.par'))
if os.path.exists(os.path.join(tmpDir, 'std.out')):
os.remove(os.path.join(tmpDir, 'std.out'))
if os.path.exists(
os.path.join(tmpDir, os.path.basename(linelistfilename))):
os.remove(
os.path.join(tmpDir, os.path.basename(linelistfilename)))
if os.path.exists(os.path.join(tmpDir, 'stronglines.vac')):
os.remove(os.path.join(tmpDir, 'stronglines.vac'))
os.rmdir(tmpDir)
shutil.copy(stronglinesfilename, tmpDir)
# Now write the script file
if len(args) == 0: #special case that there are *no* differences
args = ([26, 0.], )
nsynths = numpy.array([len(args[ii]) - 1 for ii in range(len(args))])
nsynth = numpy.amax(nsynths) #Take the longest abundance list
if nsynth > 5:
raise ValueError(
"MOOG only allows five syntheses to be run at the same time; please reduce the number of abundance values in the apogee.modelspec.moog.moogsynth input"
)
nabu = len(args)
with open(os.path.join(tmpDir, 'synth.par'), 'w') as parfile:
if doflux:
parfile.write('doflux\n')
else:
parfile.write('synth\n')
parfile.write('terminal x11\n')
parfile.write('plot 1\n')
parfile.write("standard_out std.out\n")
parfile.write("summary_out '../synth.out'\n")
parfile.write("smoothed_out '/dev/null'\n")
parfile.write("strong 1\n")
parfile.write("damping 0\n")
parfile.write("stronglines_in stronglines.vac\n")
parfile.write("model_in '../%s'\n" %
modelbasename.replace('.mod', '.org'))
parfile.write("lines_in %s\n" % os.path.basename(linelistfilename))
parfile.write("atmosphere 1\n")
parfile.write("molecules 2\n")
parfile.write("lines 1\n")
parfile.write("flux/int 0\n")
# Write the isotopes
niso = len(isotopes)
parfile.write("isotopes %i %i\n" % (niso, nsynth))
for iso in isotopes:
isotopestr = iso
for ii in range(nsynth):
isotopestr += ' ' + isotopes[iso]
parfile.write(isotopestr + '\n')
# Abundances
parfile.write("abundances %i %i\n" % (nabu, nsynth))
for ii in range(nabu):
abustr = '%i' % args[ii][0]
for jj in range(nsynth):
try:
abustr += ' %.3f' % args[ii][jj + 1]
except IndexError:
abustr += ' 0.0'
parfile.write(abustr + "\n")
# Synthesis limits
parfile.write("synlimits\n") # Add 0.001 to make sure wmax is included
parfile.write("%.3f %.3f %.3f %.3f\n" %
(wmin, wmax + 0.001, dw, width))
# Now run synth
sys.stdout.write('\r' + "Running MOOG synth ...\r")
sys.stdout.flush()
try:
p = subprocess.Popen(['moogsilent'],
cwd=tmpDir,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p.stdin.write('synth.par\n')
stdout, stderr = p.communicate()
except subprocess.CalledProcessError:
print("Running synth failed ...")
finally:
if os.path.exists(os.path.join(tmpDir, 'synth.par')):
os.remove(os.path.join(tmpDir, 'synth.par'))
if os.path.exists(os.path.join(tmpDir, 'std.out')):
os.remove(os.path.join(tmpDir, 'std.out'))
if os.path.exists(
os.path.join(tmpDir, os.path.basename(linelistfilename))):
os.remove(os.path.join(tmpDir, os.path.basename(linelistfilename)))
if os.path.exists(os.path.join(tmpDir, 'stronglines.vac')):
os.remove(os.path.join(tmpDir, 'stronglines.vac'))
os.rmdir(tmpDir)
sys.stdout.write('\r' + download._ERASESTR + '\r')
sys.stdout.flush()
# Now read the output
wavs = numpy.arange(wmin, wmax + dw, dw)
if wavs[-1] > wmax + dw / 2.: wavs = wavs[:-1]
if doflux:
contdata = numpy.loadtxt(os.path.join(modeldirname, 'synth.out'),
converters={
0: lambda x: x.replace('D', 'E'),
1: lambda x: x.replace('D', 'E')
},
usecols=[0, 1])
# Wavelength in summary file appears to be wrong from comparing to
# the standard output file
out = contdata[:, 1]
out /= numpy.nanmean(out) # Make the numbers more manageable
else:
with open(os.path.join(modeldirname, 'synth.out')) as summfile:
out = numpy.empty((nsynth, len(wavs)))
for ii in range(nsynth):
# Skip to beginning of synthetic spectrum
while True:
line = summfile.readline()
if line[0] == 'M': break
summfile.readline()
tout = []
while True:
line = summfile.readline()
if not line or line[0] == 'A': break
tout.extend([float(s) for s in line.split()])
out[ii] = numpy.array(tout)
os.remove(os.path.join(modeldirname, 'synth.out'))
if doflux:
return (wavs, out)
else:
return (wavs, 1. - out)
def weedout(**kwargs):
"""
NAME:
weedout
PURPOSE:
Weed-out unnecessary lines from the linelist for a given atmosphere
INPUT:
linelist= (None) linelist to use; can be set to the path of a linelist file or to the name of an APOGEE linelist
keepratio= (0.00001) Eliminate lines weaker than keepratio where keepratio = kapnu/kaplam at the approximate line wavelength, calculated at a continuue optical depth of 0.5
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere (needs to end in .mod)
( b) parameters of a KURUCZ model atmosphere:
teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found)
OUTPUT:
(none; just weeds out lines)
HISTORY:
2015-02-13 - Written - Bovy (IAS)
"""
# Get the name of the linelist
linelist = kwargs.pop('linelist', 'moog.201312161124.vac')
if os.path.exists(linelist):
linelistfilename = linelist
else:
linelistfilename = appath.linelistPath(linelist,
dr=kwargs.get('dr', None))
if not os.path.exists(linelistfilename):
raise RuntimeError(
"Linelist %s not found; download linelist w/ apogee.tools.download.linelist (if you have access)"
% linelistfilename)
# Get the spectral synthesis limits
wmin = kwargs.pop('wmin', _WMIN_DEFAULT)
wmax = kwargs.pop('wmax', _WMAX_DEFAULT)
dw = kwargs.pop('dw', _DW_DEFAULT)
width = kwargs.pop('width', _WIDTH_DEFAULT)
# Ratio of lines to keep
keepratio = kwargs.pop('keepratio', 0.00001)
# Get the filename of the model atmosphere
modelatm = kwargs.pop('modelatm', None)
if not modelatm is None:
if isinstance(modelatm, str) and os.path.exists(modelatm):
modelfilename = modelatm
elif isinstance(modelatm, str):
raise ValueError('modelatm= input is a non-existing filename')
else:
raise ValueError(
'modelatm= in moogsynth should be set to the name of a file')
else:
modelfilename = appath.modelAtmospherePath(**kwargs)
# Check whether a MOOG version exists
if not os.path.exists(modelfilename.replace('.mod', '.org')):
# Convert to MOOG format
convert_modelAtmosphere(modelatm=modelfilename, **kwargs)
modeldirname = os.path.dirname(modelfilename)
modelbasename = os.path.basename(modelfilename)
outname = modelbasename.replace('.mod', '.lines')
# We will run in a subdirectory of the relevant model atmosphere
tmpDir = tempfile.mkdtemp(dir=modeldirname)
shutil.copy(linelistfilename, tmpDir)
# Now write the script file
with open(os.path.join(tmpDir, 'weedout.par'), 'w') as parfile:
parfile.write('weedout\n')
parfile.write('terminal x11\n')
parfile.write('plot 0\n')
parfile.write("standard_out '/dev/null'\n")
parfile.write("keeplines_out '../%s'\n" % outname)
parfile.write("tosslines_out 'toss.out'\n")
parfile.write("summary_out '/dev/null'\n")
parfile.write("smoothed_out '/dev/null'\n")
parfile.write("damping 0\n")
parfile.write("model_in '../%s'\n" %
modelbasename.replace('.mod', '.org'))
parfile.write("lines_in %s\n" % os.path.basename(linelistfilename))
parfile.write("atmosphere 1\n")
parfile.write("molecules 2\n")
parfile.write("lines 1\n")
parfile.write("flux/int 0\n")
parfile.write("synlimits\n")
parfile.write("%.3f %.3f %.3f %.3f\n" % (wmin, wmax, dw, width))
# Now run weedout
sys.stdout.write('\r' + "Running MOOG weedout ...\r")
sys.stdout.flush()
try:
p = subprocess.Popen(['moogsilent'],
cwd=tmpDir,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p.stdin.write('weedout.par\n')
p.stdin.write('%g\n' % keepratio)
stdout, stderr = p.communicate()
except subprocess.CalledProcessError:
print("Running weedout failed ...")
finally:
if os.path.exists(os.path.join(tmpDir, 'weedout.par')):
os.remove(os.path.join(tmpDir, 'weedout.par'))
if os.path.exists(os.path.join(tmpDir, 'toss.out')):
os.remove(os.path.join(tmpDir, 'toss.out'))
if os.path.exists(
os.path.join(tmpDir, os.path.basename(linelistfilename))):
os.remove(os.path.join(tmpDir, os.path.basename(linelistfilename)))
os.rmdir(tmpDir)
sys.stdout.write('\r' + "Running MOOG weedout ...\r")
sys.stdout.flush()
return None
def synth(*args, **kwargs):
"""
NAME:
synth
PURPOSE:
Generate model APOGEE spectra using MOOG: this is a general routine that generates the non-continuum-normalized spectrum, convolves with the LSF and macrotubulence, and optionally continuum normalizes the output; use 'moogsynth' for a direct interface to MOOG
INPUT ARGUMENTS:
lists with abundances wrt the atmosphere (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
INPUT KEYWORDS:
LSF:
lsf= ('all') LSF to convolve with; output of apogee.spec.lsf.eval; sparsify for efficiency; if 'all' or 'combo' a pre-computed version will be downloaded from the web
Either:
xlsf= (None) pixel offset grid on which the LSF is computed (see apogee.spec.lsf.eval); unnecessary if lsf=='all' or 'combo'
dxlsf= (None) spacing of pixel offsets
vmacro= (6.) macroturbulence to apply
CONTINUUM:
cont= ('aspcap') continuum-normalization to apply:
None: no continuum normalization
'true': Use the true continuum
'aspcap': Use the continuum normalization method of ASPCAP DR12
'cannon': Normalize using continuum pixels derived from the Cannon
SYNTHESIS:
linelist= (None) linelist to use; can be set to the path of a linelist file or to the name of an APOGEE linelist
run_weedout= (False) if True, run MOOG weedout on the linelist first
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits, step, and width of calculation (see MOOG)
lib= ('kurucz_filled') spectral library
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere or to a model-atmosphere instance (if filename, needs to end in .mod)
(b) parameters of a KURUCZ model atmosphere:
(1) teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
(2) fparam= standard ASPCAP output format
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found) (can also be part of fparam)
MISCELLANEOUS:
dr= return the path corresponding to this data release
OUTPUT:
spectra (nspec,nwave)
HISTORY:
2015-03-15 - Written - Bovy (IAS)
"""
run_weedout = kwargs.pop('run_weedout', False)
# Check that we have the LSF and store the relevant keywords
lsf = kwargs.pop('lsf', 'all')
if isinstance(lsf, str):
xlsf, lsf = aplsf._load_precomp(dr=kwargs.get('dr', None), fiber=lsf)
dxlsf = None
else:
xlsf = kwargs.pop('xlsf', None)
dxlsf = kwargs.pop('dxlsf', None)
if xlsf is None and dxlsf is None:
raise ValueError(
'xlsf= or dxlsf= input needs to be given if the LSF is given as an array'
)
vmacro = kwargs.pop('vmacro', 6.)
# Parse continuum-normalization keywords
cont = kwargs.pop('cont', 'aspcap')
# Setup the model atmosphere
modelatm = kwargs.pop('modelatm', None)
tmpModelAtmDir = False
# Parse fparam, if present
fparam = kwargs.pop('fparam', None)
if not fparam is None:
kwargs['teff'] = fparam[paramIndx('TEFF')]
kwargs['logg'] = fparam[paramIndx('LOGG')]
kwargs['metals'] = fparam[paramIndx('METALS')]
kwargs['am'] = fparam[paramIndx('ALPHA')]
kwargs['cm'] = fparam[paramIndx('C')]
kwargs['vm'] = 10.**fparam[paramIndx('LOG10VDOP')]
if modelatm is None: # Setup a model atmosphere
modelatm = atlas9.Atlas9Atmosphere(teff=kwargs.get('teff', 4500.),
logg=kwargs.get('logg', 2.5),
metals=kwargs.get('metals', 0.),
am=kwargs.get('am', 0.),
cm=kwargs.get('cm', 0.),
dr=kwargs.get('dr', None))
if isinstance(modelatm, str) and os.path.exists(modelatm):
modelfilename = modelatm
elif isinstance(modelatm, str):
raise ValueError('modelatm= input is a non-existing filename')
else: # model atmosphere instance
# Need to write this instance to a file; we will run in a temp
# subdirectory of the current directory
tmpDir = tempfile.mkdtemp(dir=os.getcwd())
tmpModelAtmDir = True # need to remove this later
modelfilename = os.path.join(tmpDir, 'modelatm.mod')
modelatm.writeto(modelfilename)
kwargs['modelatm'] = modelfilename
try:
# Check whether a MOOG version of the model atmosphere exists
if not os.path.exists(modelfilename.replace('.mod', '.org')):
# Convert to MOOG format
convert_modelAtmosphere(**kwargs)
# Run weedout on the linelist first if requested
if run_weedout:
linelistfilename = modelfilename.replace('.mod', '.lines')
if not os.path.exists(linelistfilename):
weedout(**kwargs)
kwargs['linelist'] = linelistfilename
# Run MOOG synth for all abundances
if len(args) == 0: #special case that there are *no* differences
args = ([26, 0.], )
nsynths = numpy.array([len(args[ii]) - 1 for ii in range(len(args))])
nsynth = numpy.amax(nsynths) #Take the longest abundance list
nmoogwav= int((kwargs.get('wmax',_WMAX_DEFAULT)\
-kwargs.get('wmin',_WMIN_DEFAULT))\
/kwargs.get('dw',_DW_DEFAULT)+1)
out = numpy.empty((nsynth, nmoogwav))
# Check whether the number of syntheses is > 5 and run multiple
# MOOG instances if necessary, bc MOOG only does 5 at a time
ninstances = int(numpy.ceil(nsynth / 5.))
for ii in range(ninstances):
newargs = ()
for jj in range(len(args)):
tab = [args[jj][0]]
if len(args[jj][5 * ii + 1:5 * (ii + 1) + 1]) > 0:
tab.extend(args[jj][5 * ii + 1:5 * (ii + 1) + 1])
newargs = newargs + (tab, )
out[5 * ii:5 * (ii + 1)] = moogsynth(*newargs, **kwargs)[1]
# We'll grab the wavelength grid from the continuum below
# Now compute the continuum and multiply each c-norm spectrum with it
mwav, cflux = moogsynth(doflux=True, **kwargs)
except:
raise
finally:
if tmpModelAtmDir: # need to remove this temporary directory
os.remove(modelfilename)
moogmodelfilename = modelfilename.replace('.mod', '.org')
if os.path.exists(moogmodelfilename):
os.remove(moogmodelfilename)
if run_weedout:
os.remove(modelfilename.replace('.mod', '.lines'))
os.rmdir(tmpDir)
out *= numpy.tile(cflux, (nsynth, 1))
# Now convolve with the LSF
out = aplsf.convolve(mwav,
out,
lsf=lsf,
xlsf=xlsf,
dxlsf=dxlsf,
vmacro=vmacro)
# Now continuum-normalize
if cont.lower() == 'true':
# Get the true continuum on the apStar wavelength grid
apWave = apStarWavegrid()
baseline = numpy.polynomial.Polynomial.fit(mwav, cflux, 4)
ip = interpolate.InterpolatedUnivariateSpline(mwav,
cflux / baseline(mwav),
k=3)
cflux = baseline(apWave) * ip(apWave)
# Divide it out
out /= numpy.tile(cflux, (nsynth, 1))
elif not cont is None:
cflux = apcont.fit(out, numpy.ones_like(out), type=cont)
out[cflux > 0.] /= cflux[cflux > 0.]
out[cflux <= 0.] = numpy.nan
return out
def windows(*args, **kwargs):
"""
NAME:
windows
PURPOSE:
Generate model APOGEE spectra using MOOG in selected wavelength windows (but the whole APOGEE spectral range is returned): this is a general routine that generates the non-continuum-normalized spectrum, convolves with the LSF and macrotubulence, and optionally continuum normalizes the output; use 'moogsynth' for a direct interface to MOOG
INPUT ARGUMENTS:
Windows specification: Provide one of
(1) Element string: the APOGEE windows for this element will be loaded
(2) startindxs, endindxs= start and end indexes of the windows on the apStar wavelength grid
(3) startlams, endlams= start and end wavelengths in \AA
lists with abundance differences wrt the atmosphere (they don't all have to have the same length, missing ones are filled in with zeros):
[Atomic number1,diff1_1,diff1_2,diff1_3,...,diff1_N]
[Atomic number2,diff2_1,diff2_2,diff2_3,...,diff2_N]
...
[Atomic numberM,diffM_1,diffM_2,diffM_3,...,diffM_N]
INPUT KEYWORDS:
BASELINE: you can specify the baseline spectrum to not always re-compute it
baseline= baseline c-normalized spectrum on MOOG wavelength grid (obtained from moogsynth)
mwav= MOOG wavelength grid (obtained from moogsynth)
cflux= continuum flux from MOOG
Typically, you can obtain these three keywords by doing (kwargs are the keywords you provide to this function as well)
>>> baseline= moogsynth(**kwargs)[1]
>>> mwav, cflux= moogsynth(doflux=True,**kwargs)
LSF:
lsf= ('all') LSF to convolve with; output of apogee.spec.lsf.eval; sparsify for efficiency; if 'all' or 'combo' a pre-computed version will be downloaded from the web
Either:
xlsf= (None) pixel offset grid on which the LSF is computed (see apogee.spec.lsf.eval); unnecessary if lsf=='all' or 'combo'
dxlsf= (None) spacing of pixel offsets
vmacro= (6.) macroturbulence to apply
CONTINUUM:
cont= ('aspcap') continuum-normalization to apply:
None: no continuum normalization
'true': Use the true continuum
'aspcap': Use the continuum normalization method of ASPCAP DR12
'cannon': Normalize using continuum pixels derived from the Cannon
SYNTHESIS:
linelist= (None) linelist to use; if this is None, the code looks for a weed-out version of the linelist appropriate for the given model atmosphere
run_weedout= (False) if True, run MOOG weedout on the linelist first
wmin, wmax, dw, width= (15000.000, 17000.000, 0.10000000, 7.0000000) spectral synthesis limits *for the whole spectrum* (not just the windows), step, and width of calculation (see MOOG)
MODEL ATMOSPHERE PARAMETERS:
Specify one of the following:
(a) modelatm= (None) can be set to the filename of a model atmosphere or to a model-atmosphere instance (if filename, needs to end in .mod)
(b) parameters of a KURUCZ model atmosphere:
(1) teff= (4500) Teff
logg= (2.5) logg
metals= (0.) metallicity
cm= (0.) carbon-enhancement
am= (0.) alpha-enhancement
(2) fparam= standard ASPCAP output format (
lib= ('kurucz_filled') model atmosphere library
dr= (None) use model atmospheres from this data release
vmicro= (2.) microturbulence (only used if the MOOG-formatted atmosphere is not found) (can also be part of fparam)
MISCELLANEOUS:
dr= return the path corresponding to this data release
OUTPUT:
spectra (nspec,nwave)
HISTORY:
2015-03-18 - Written - Bovy (IAS)
"""
# Pop some kwargs
run_weedout = kwargs.pop('run_weedout', False)
baseline = kwargs.pop('baseline', None)
mwav = kwargs.pop('mwav', None)
cflux = kwargs.pop('cflux', None)
# Check that we have the LSF and store the relevant keywords
lsf = kwargs.pop('lsf', 'all')
if isinstance(lsf, str):
xlsf, lsf = aplsf._load_precomp(dr=kwargs.get('dr', None), fiber=lsf)
dxlsf = None
else:
xlsf = kwargs.pop('xlsf', None)
dxlsf = kwargs.pop('dxlsf', None)
if xlsf is None and dxlsf is None:
raise ValueError(
'xlsf= or dxlsf= input needs to be given if the LSF is given as an array'
)
vmacro = kwargs.pop('vmacro', 6.)
# Parse continuum-normalization keywords
cont = kwargs.pop('cont', 'aspcap')
# Parse the wavelength regions
apWave = apStarWavegrid()
if isinstance(args[0], str): #element string given
si, ei = apwindow.waveregions(args[0], pad=3, asIndex=True)
args = args[1:]
else:
if isinstance(args[0][0], int): # assume index
si, ei = args[0], args[1]
else: # assume wavelengths in \AA
sl, el = args[0], args[1]
# Convert to index
si, ei = [], []
for s, e in zip(sl, el):
# Find closest index into apWave
si.append(numpy.argmin(numpy.fabs(s - apWave)))
ei.append(numpy.argmin(numpy.fabs(e - apWave)))
args = args[2:]
# Setup the model atmosphere
modelatm = kwargs.pop('modelatm', None)
tmpModelAtmDir = False
# Parse fparam, if present
fparam = kwargs.pop('fparam', None)
if not fparam is None:
kwargs['teff'] = fparam[0, paramIndx('TEFF')]
kwargs['logg'] = fparam[0, paramIndx('LOGG')]
kwargs['metals'] = fparam[0, paramIndx('METALS')]
kwargs['am'] = fparam[0, paramIndx('ALPHA')]
kwargs['cm'] = fparam[0, paramIndx('C')]
kwargs['vm'] = 10.**fparam[0, paramIndx('LOG10VDOP')]
if modelatm is None: # Setup a model atmosphere
modelatm = atlas9.Atlas9Atmosphere(teff=kwargs.get('teff', 4500.),
logg=kwargs.get('logg', 2.5),
metals=kwargs.get('metals', 0.),
am=kwargs.get('am', 0.),
cm=kwargs.get('cm', 0.),
dr=kwargs.get('dr', None))
if isinstance(modelatm, str) and os.path.exists(modelatm):
modelfilename = modelatm
elif isinstance(modelatm, str):
raise ValueError('modelatm= input is a non-existing filename')
else: # model atmosphere instance
# Need to write this instance to a file; we will run in a temp
# subdirectory of the current directory
tmpDir = tempfile.mkdtemp(dir=os.getcwd())
tmpModelAtmDir = True # need to remove this later
modelfilename = os.path.join(tmpDir, 'modelatm.mod')
modelatm.writeto(modelfilename)
kwargs['modelatm'] = modelfilename
try:
# Check whether a MOOG version of the model atmosphere exists
if not os.path.exists(modelfilename.replace('.mod', '.org')):
# Convert to MOOG format
convert_modelAtmosphere(**kwargs)
# Run weedout on the linelist first if requested
if run_weedout:
linelistfilename = modelfilename.replace('.mod', '.lines')
if not os.path.exists(linelistfilename):
weedout(**kwargs)
kwargs['linelist'] = linelistfilename
# Run MOOG synth for the whole wavelength range as a baseline, also contin
if baseline is None:
baseline = moogsynth(**kwargs)[1]
elif isinstance(baseline,
tuple): #probably accidentally gave wav as well
baseline = baseline[1]
if mwav is None or cflux is None:
mwav, cflux = moogsynth(doflux=True, **kwargs)
# Convert the apStarWavegrid windows to moogWavegrid regions
sm, em = [], []
for start, end in zip(si, ei):
sm.append(numpy.argmin(numpy.fabs(apWave[start] - mwav)))
em.append(numpy.argmin(numpy.fabs(apWave[end] - mwav)))
# Run MOOG synth for all abundances and all windows
if len(args) == 0: #special case that there are *no* differences
args = ([26, 0.], )
nsynths = numpy.array([len(args[ii]) - 1 for ii in range(len(args))])
nsynth = numpy.amax(nsynths) #Take the longest abundance list
out = numpy.tile(baseline, (nsynth, 1))
# Run all windows
for start, end in zip(sm, em):
kwargs['wmin'] = mwav[start]
kwargs['wmax'] = mwav[end]
# Check whether the number of syntheses is > 5 and run multiple
# MOOG instances if necessary, bc MOOG only does 5 at a time
ninstances = int(numpy.ceil(nsynth / 5.))
for ii in range(ninstances):
newargs = ()
for jj in range(len(args)):
tab = [args[jj][0]]
if len(args[jj][5 * ii + 1:5 * (ii + 1) + 1]) > 0:
tab.extend(args[jj][5 * ii + 1:5 * (ii + 1) + 1])
newargs = newargs + (tab, )
out[5 * ii:5 * (ii + 1),
start:end + 1] = moogsynth(*newargs, **kwargs)[1]
except:
raise
finally:
if tmpModelAtmDir: # need to remove this temporary directory
os.remove(modelfilename)
moogmodelfilename = modelfilename.replace('.mod', '.org')
if os.path.exists(moogmodelfilename):
os.remove(moogmodelfilename)
if run_weedout:
os.remove(modelfilename.replace('.mod', '.lines'))
os.rmdir(tmpDir)
# Now multiply each continuum-normalized spectrum with the continuum
out *= numpy.tile(cflux, (nsynth, 1))
# Now convolve with the LSF
out = aplsf.convolve(mwav,
out,
lsf=lsf,
xlsf=xlsf,
dxlsf=dxlsf,
vmacro=vmacro)
# Now continuum-normalize
if cont.lower() == 'true':
# Get the true continuum on the apStar wavelength grid
apWave = apStarWavegrid()
baseline = numpy.polynomial.Polynomial.fit(mwav, cflux, 4)
ip = interpolate.InterpolatedUnivariateSpline(mwav,
cflux / baseline(mwav),
k=3)
cflux = baseline(apWave) * ip(apWave)
# Divide it out
out /= numpy.tile(cflux, (nsynth, 1))
elif not cont is None:
cflux = apcont.fit(out, numpy.ones_like(out), type=cont)
out[cflux > 0.] /= cflux[cflux > 0.]
out[cflux <= 0.] = numpy.nan
return out