forked from djeff1887/SgrB2DS-CH3OH
-
Notifications
You must be signed in to change notification settings - Fork 0
/
makesyntheticspectra.py
152 lines (115 loc) · 5.01 KB
/
makesyntheticspectra.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
import numpy as np
import astropy.units as u
from astropy.wcs import WCS
from spectral_cube import SpectralCube as sc
import matplotlib.pyplot as plt
from astroquery.splatalogue import utils, Splatalogue
import scipy.constants as cnst
from scipy.optimize import curve_fit as cf
from astropy.io import fits
import glob
import radio_beam
from astropy.modeling import models, fitting#Fittable1DModel, Parameter, fitting
from utilities import *#Q_rot_asym,mulu,vradio,t_rad,nupper_estimated,opticaldepth,qngrabber
import matplotlib as mpl
#from cubecoretexmap import t_rad,nupper_estimated,opticaldepth
Splatalogue.QUERY_URL= 'https://splatalogue.online/c_export.php'
mpl.interactive(True)
plt.close('all')
linelist='JPL'
'''Collect constants for N_tot and N_upper calculations'''
source='SgrB2S'
c=cnst.c*u.m/u.s
k=cnst.k*u.J/u.K
h=cnst.h*u.J*u.s
sigma_sb=cnst.sigma*u.W/((u.m)**(2)*(u.K)**(4))
b_0=24679.98*u.MHz
a_0=127484*u.MHz
c_0=23769.70*u.MHz
m=b_0**2/(a_0*c_0)
Tbg=2.7355*u.K
testT=300*u.K
qrot_partfunc=Q_rot_asym(testT).to('')
testntot=1e17*u.cm**-2
R_i=1
kappa=((2*b_0)-a_0-c_0)/(a_0-c_0)
f=1
dopplershifts={'SgrB2S':0.000234806,'DSi':0.000186431,'DSv':0.000186431}#:0.000190713}/old doppler S: 0.0002306756533745274
z=dopplershifts[source]
files=glob.glob('/blue/adamginsburg/d.jeff/SgrB2DSminicubes/SgrB2S/OctReimage_K/*.fits')
imgnames=['spw0','spw1','spw2','spw3']
datacubes=[]
for spew in imgnames:
for f1 in files:
if spew in f1:
datacubes.append(f1)
continue
assert 'spw0' in datacubes[0], 'Cube list out of order'
#imgnum=0
testline=0
#cube=sc.read(datacubes[imgnum])
#targetworldcrd=[[0,0,0],[266.8316149,-28.3972040,0]]#DSi
#targetworldcrd=[[0,0,0],[266.8321311,-28.3976633,0]]#DSv
#targetworldcrd=[[0,0,0],[2.66835339e+02, -2.83961660e+01, 0]]#SgrB2S
for datacube, img in zip(datacubes,imgnames):
print('Getting ready - '+img)
cube=sc.read(datacube)
cube.allow_huge_operations=True
cube_w=cube.wcs#WCS(files[imgnum])
targetworldcrd=[[0,0,0],[2.66835339e+02, -2.83961660e+01, 0]]#SgrB2S
targetpixcrd=cube_w.all_world2pix(targetworldcrd,1,ra_dec_order=True)
freqs=cube.spectral_axis
freqflip=False
if freqs[0] > freqs[1]:
freqs=freqs[::-1]
freqflip=True
print('Corrected decreasing frequency axis')
else:
pass
freq_min=freqs[0]*(1+z)#215*u.GHz
freq_max=freqs[(len(freqs)-1)]*(1+z)#235*u.GHz
assert freq_max > freq_min, 'Decreasing frequency axis'
linewidth=0.00485*u.GHz#Half of original 0.0097GHz
lw2=linewidth/8
originallinewidth=(11231152.36688232*u.Hz/2)
'''Generate methanol table for contaminant search'''
methanol_table= Splatalogue.query_lines(freq_min, freq_max, chemical_name=' CH3OH ', energy_max=1840, energy_type='eu_k', line_lists=['JPL'], show_upper_degeneracy=True)
minmethtable=utils.minimize_table(methanol_table)
mlines=(minmethtable['Freq']*10**9)/(1+z)*u.Hz
mqns=minmethtable['QNs']
meuks=minmethtable['EU_K']*u.K
meujs=[]
for euk in meuks:
meujs.append(KtoJ(euk))
mdegs=methanol_table['Upper State Degeneracy']
mlog10aijs=minmethtable['log10_Aij']
maijs=10**mlog10aijs*u.s**-1
#zeros=np.zeros(cube.shape[0])
#baseline=np.array(list(zip(plot.value,zeros)))#np.vstack((plot,zeros))
baseline=models.Linear1D(slope=(0*(u.K/u.Hz)),intercept=0*u.K)
baseline.bounding_box=(freqs[0],freqs[(len(freqs)-1)])
modelspec=baseline
print('Begin model loops')
plot=np.linspace(freqs[0],freqs[(len(freqs)-1)],cube.shape[0]).to('GHz')
modelgaus=models.Gaussian1D(mean=freqs[0], stddev=11 * u.MHz, amplitude=0*u.K)
for line,deg,euj,aij,qn in zip(mlines,mdegs,meujs,maijs,mqns):
print(f'Transition: {qn} @ {line.to("GHz")}')
restline=line*(1+z)
est_nupper=nupper_estimated(testntot,deg,qrot_partfunc,euj,testT).to('cm-2')
est_tau=opticaldepth(aij,restline,testT,est_nupper,originallinewidth).to('')
trad=t_rad(f,est_tau,restline,testT).to('K')
modelline=models.Gaussian1D(mean=line, stddev=1 * u.MHz, amplitude=trad)
#modelgaus+=modelline
modelspec+=modelline
print('Plotting model spectra')
#plot=np.linspace(freqs[0],freqs[(len(freqs)-1)],cube.shape[0])
cube[:,int(round(targetpixcrd[1][1])),int(round(targetpixcrd[1][0]))].quicklook()
plt.plot(freqs,modelspec(freqs),drawstyle='steps',color='red')
#plt.plot(plot,cube[:,int(round(targetpixcrd[1][1])),int(round(targetpixcrd[1][0]))].value,color='black',drawstyle='steps')
plt.xlabel(r'$\nu$ (Hz)')
plt.ylabel('T$_b$ (K)')
print('Overplotting axvlines and transition annotations')
for line,qn in zip(mlines,mqns):
plt.axvline(x=line.value,linestyle='--',color='yellow',ymin=0.25)
plt.annotate(qn, (line.value, 0), (line.value-0.002,40),rotation=90)
plt.show()