def linename_to_restwl(linelistfile = '/Users/adam/work/IRAS05358/code/linelist.txt',outfile='/Users/adam/work/IRAS05358/code/newlinelist.txt'):
lines = readcol.readcol(linelistfile,fsep='|',twod=False,dtype='S')
outf = open(outfile,'w')
for line in transpose(lines):
name = line[0]
jre = re.compile('\(([0-9]*)\)').search(name)
if jre == None:
print >>outf, "%10s|%10s" % (line[0],line[1])
continue
else:
jl = int( jre.groups()[0] )
if name[4] == 'S':
ju = jl + 2
elif name[4] == 'Q':
ju = jl
elif name[4] == 'O':
ju = jl - 2
else:
print >>outf, "%10s|%10s" % (line[0],line[1])
continue
vu = int( name[0] )
vl = int( name[2] )
rwl = restwl(vu,vl,ju,jl)
if rwl == 0:
rwl = float(line[1])
print >>outf,"%10s|%10.8f" % (name,rwl)
def readspec(image,noiseimage,
linelistfile = '/Users/adam/work/IRAS05358/code/linelist.txt',
path_obs='/Users/adam/work/IRAS05358/spectra/nearir/', #'/Users/adam/observations/IRAS05358/UT090108/',
noiseaperture=[0,10],
aperture=[],
nameregex='2-1 S\(1\)|1-0 S\([1379028]\)|1-0 Q\([1234]\)|3-2 S\([35]\)|4-3 S\(5\)',
apname='',
vlsrcorr=0):
regex = re.compile(nameregex)
im = pyfits.open(path_obs+image)
noiseim = pyfits.open(path_obs+noiseimage)
wlA = im[0].header['CRVAL1'] + im[0].header['CD1_1'] * ( arange(im[0].data.shape[1]) - im[0].header['CRPIX1'] + 1)
data = im[0].data
atmospec = median(noiseim[0].data[noiseaperture[0]:noiseaperture[1]],axis=0)
countsperflux = 2.25e18
stdatmo = noiseim[0].data[noiseaperture[0]:noiseaperture[1]].std(axis=0) # std. dev. of non-backsubtracted data
poisserr = sqrt(abs(noiseim[0].data).mean(axis=0) * countsperflux) / countsperflux # Poisson noise (very approximate correction)
errspec = sqrt( stdatmo**2 + 2*poisserr**2 ) # poisson statistics - once for estimation of the noise, once for the subtraction
errspec /= atmotrans_vect(wlA)**2 # Weight by inverse of atmospheric transmission^2
lines = readcol.readcol(linelistfile,fsep='|',twod=False,dtype='S')
lines[1] = asarray(lines[1],dtype='float')*1e4 # convert microns to angstroms
specsegments=[]
for line in transpose(lines):
wl = float(line[1])
name = line[0]
if wl > wlA.min() and wl < wlA.max() and regex.search(name) != None:
closest = argmin(abs(wlA-wl))
minind = closest-7
maxind = closest+7
if len(aperture) != 0:
savedata = data[aperture[0]:aperture[1],minind:maxind].sum(axis=0)
else:
savedata = data[:,minind:maxind]
specsegments.append({
'name':name,
'apname':apname,
'linewl':wl,
'index':closest,
'minind':minind,
'maxind':maxind,
'vlsrcorr':vlsrcorr,
'wavelength':wlA[minind:maxind],
'data':savedata,
'noback':atmospec[minind:maxind],
'err':errspec[minind:maxind],
'model':data[0,minind:maxind]*0
# 'smoothdata':convolve( data[:,minind:maxind] , hanning(3) , 'same')
})
print "Done finding lines"
return specsegments
def readspexspec(image,
linelistfile = '/Users/adam/work/IRAS05358/code/linelist.txt',
path_obs='/Users/adam/work/IRAS05358/spectra/nearir/', #'/Users/adam/observations/IRAS05358/UT090108/',
nameregex='2-1 S\(1\)|1-0 S\([1379028]\)|1-0 Q\([1234]\)|3-2 S\([35]\)|4-3 S\(5\)',
vlsrcorr=0,
backsub=False,
**kwargs):
regex = re.compile(nameregex)
im = pyfits.open(path_obs+image)
wlA = im[0].data[0,:] * 1e4
data = im[0].data[1,:]
countsperflux = 2.25e18
errspec = im[0].data[2,:]
lines = readcol.readcol(linelistfile,fsep='|',twod=False,dtype='S')
lines[1] = asarray(lines[1],dtype='float')*1e4 # convert microns to angstroms
specsegments=[]
for line in transpose(lines):
wl = float(line[1])
name = line[0]
if wl > wlA.min() and wl < wlA.max() and regex.search(name) != None:
closest = argmin(abs(wlA-wl))
minind = closest-7
maxind = closest+7
savedata = data[minind:maxind]
if backsub:
savedata -= median(savedata[savedata<median(savedata)])
specsegments.append({
'name':name,
'linewl':wl,
'index':closest,
'minind':minind,
'maxind':maxind,
'vlsrcorr':vlsrcorr,
'wavelength':wlA[minind:maxind],
'data':savedata,
'noback':data[minind:maxind]*0,
'err':errspec[minind:maxind],
'model':data[minind:maxind]*0
})
print "Done finding lines"
return specsegments
http://webbook.nist.gov/cgi/cbook.cgi?ID=C1333740&Units=SI&Mask=1000#Diatomic
(see the bottom of the table)
"""
We=4401.21
Be=60.853
WeXe=121.33
De=.0471
Ae=3.062
re=.74144
return h * c * (We*(V+0.5) + Be*(J*(J+1)) - WeXe*(V+.5)**2 - De*J**2*(J+1)**2 - Ae*(V+.5)*(J+1)*J)
# read in rest energies before calling function
tablepath='/Users/adam/work/IRAS05358/code/'
resten = readcol.readcol(tablepath+'dalgarno1984_table5.txt',verbose=0)
def restwl(vu,vl,ju,jl):
""" Uses energy levels measured by Dalgarno, Can J. Physics, 62,1639,1984
vu,vl - upper and lower vibrational states
ju,jl - upper and lower rotational states
returns wavelength in microns"""
if ju >= resten.shape[0] or vu >= resten.shape[1]:
return 0
dl = .01/(resten[ju][vu]-resten[jl][vl])
return dl * 1e6
def linename_to_restwl(linelistfile = '/Users/adam/work/IRAS05358/code/linelist.txt',outfile='/Users/adam/work/IRAS05358/code/newlinelist.txt'):
lines = readcol.readcol(linelistfile,fsep='|',twod=False,dtype='S')
outf = open(outfile,'w')