/
ph2co_required_sn.py
168 lines (134 loc) · 6.1 KB
/
ph2co_required_sn.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
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
"""
Simple proposal-writing experiment: For a given signal-to-noise in a line, what
signal-to-noise do you get in a derived parameter (e.g., temperature)?
"""
import pyradex
import pylab as pl
import numpy as np
import matplotlib
import astropy.units as u
import os
# for pretty on-screen plots
if os.path.exists('/Users/adam/.matplotlib/ggplotrc'):
matplotlib.rc_file('/Users/adam/.matplotlib/ggplotrc')
# Download the data file if it's not here already
if not os.path.exists('ph2co-h2.dat'):
import urllib
urllib.urlretrieve('http://home.strw.leidenuniv.nl/~moldata/datafiles/ph2co-h2.dat')
# Formatting tool
def latex_float(f):
float_str = "{0:.1g}".format(f)
if "e" in float_str:
base, exponent = float_str.split("e")
return r"{0} \times 10^{{{1}}}".format(base, int(exponent))
else:
return float_str
# Define the grid parameters
ntemp = 75
tmin = 10
tmax = 300
temperatures = np.linspace(tmin,300,ntemp)
# initial density; will be modified later
density = 1e4
deltav = 1.0 # km/s
for abundance in (10**-8.5,10**-9):
for nh2 in (1e22,1e23):
R = pyradex.Radex(species='ph2co-h2',
abundance=abundance,
collider_densities={'oH2':density,'pH2':0},
deltav=1.0,
column=None,
temperature=temperatures[0],
h2column=nh2)
pl.figure(1)
pl.clf()
Swcs = pyradex.synthspec.FrequencyArray(218.2*u.GHz, 218.8*u.GHz, npts=1000)
for temperature in [10,50,100,200,300]:
R.temperature = temperature
R.run_radex()
S = pyradex.synthspec.SyntheticSpectrum.from_RADEX(Swcs, R, linewidth=10*u.km/u.s)
S.plot(label='%i K' % temperature, linewidth=2, alpha=0.5)
pl.legend(loc='best')
pl.savefig("pH2CO_synthspectra_N=%1.0e_X=%0.1e_n=%0.1e_opr=0.pdf" % (nh2,abundance,density),bbox_inches='tight')
# create a small grid...
densities = [10**x for x in xrange(4,7)]
ratio1 = {d:[] for d in densities}
ratio2 = {d:[] for d in densities}
f1 = {d:[] for d in densities}
f2 = {d:[] for d in densities}
f3 = {d:[] for d in densities}
for density in densities:
R.density = {'oH2': density, 'pH2':0}
for temperature in temperatures:
R.temperature = temperature
print R.run_radex(),
F1 = R.T_B[2] # 218.222192 3_0_3
F2 = R.T_B[12] # 218.760066 3_2_1
F3 = R.T_B[9] # 218.475632 3_2_2
ratio1[density].append(F2/F1)
ratio2[density].append(F3/F1)
f3[density].append(F3)
f2[density].append(F2)
f1[density].append(F1)
print
f1 = {d:np.array([x.value for x in f1[d]]) for d in densities}
f2 = {d:np.array([x.value for x in f2[d]]) for d in densities}
f3 = {d:np.array([x.value for x in f3[d]]) for d in densities}
ratio1 = {d:np.array(ratio1[d]) for d in densities}
ratio2 = {d:np.array(ratio2[d]) for d in densities}
ratio = ratio1
pl.figure(2)
pl.clf()
for d in densities:
pl.plot(ratio[d],temperatures,label='$n=10^{%i}$' % (np.log10(d)))
m = 1/((ratio[d][15]-ratio[d][5])/(temperatures[15]-temperatures[5]))
b = temperatures[5]-ratio[d][5]*m
line=(m,b)
print d,m,b
pl.plot(ratio[d],ratio[d]*line[0]+line[1],'--')
pl.ylabel("Temperature")
pl.xlabel("$S(3_{2,1}-2_{2,0})/S(3_{0,3}-2_{0,2})$")
pl.legend(loc='best',fontsize=14)
pl.title("$N(H_2) = %s$ cm$^{-2}$, X(p-H$_2$CO)$=10^{%0.1f}$" % (latex_float(nh2),np.log10(abundance)))
pl.axis([0,0.5,tmin,tmax,])
pl.savefig("pH2CO_ratio_vs_temperature_N=%1.0e_X=%0.1e.pdf" % (nh2,abundance),bbox_inches='tight')
pl.figure(3)
pl.clf()
for d in densities:
L, = pl.plot(temperatures,f2[d],label='$n=10^{%i}$' % (np.log10(d)))
pl.plot(temperatures,f1[d],'--',color=L.get_color())
pl.xlabel("Temperature")
pl.ylabel("$T_B(3_{2,1}-2_{2,0})$ (solid), $T_B(3_{0,3}-2_{0,2})$ (dashed)")
ax = pl.gca()
#pl.plot(ax.get_xlim(),[1.5,1.5],'k--',label='S/N$=5$, $\sigma=0.3$ K')
#pl.plot(ax.get_xlim(),[2.5,2.5],'k:',label='S/N$=5$, $\sigma=0.5$ K')
#pl.plot(ax.get_xlim(),[0.25,0.25],'k-.',label='S/N$=5$, $\sigma=0.05$ K')
ax.axis([tmin,tmax,0,5.2])
pl.legend(loc='best',fontsize=14)
pl.title("$N(H_2) = %s$ cm$^{-2}$, X(p-H$_2$CO)$=10^{%0.1f}$" % (latex_float(nh2),np.log10(abundance)))
pl.savefig("pH2CO_321-220_vs_temperature_N=%1.0e_X=%0.1e.pdf" % (nh2,abundance),bbox_inches='tight')
pl.figure(4,figsize=(10,10))
pl.clf()
ax1= pl.subplot(2,1,1)
for d in densities:
pl.plot(temperatures,ratio[d],label='$n=10^{%i}$' % (np.log10(d)))
#pl.xlabel("Temperature")
pl.ylabel("$S(3_{2,1}-2_{2,0})/S(3_{0,3}-2_{0,2})$")
pl.legend(loc='upper left',fontsize=18)
pl.title("$N(H_2) = %s$ cm$^{-2}$, X(p-H$_2$CO)$=10^{%0.1f}$" % (latex_float(nh2),np.log10(abundance)))
ax1.set_xticks([])
pl.subplots_adjust(hspace=0.0)
ax2 = pl.subplot(2,1,2)
for d in densities:
L, = pl.plot(temperatures,f2[d],dashes=[2,2],label='$n=10^{%i}$' % (np.log10(d)))
pl.plot(temperatures,f1[d],'--',color=L.get_color())
pl.xlabel("Temperature")
pl.ylabel("$T_B$")
ax2.axis([tmin,tmax,0,5.2])
pl.legend((pl.Line2D([0],[0],dashes=[2,2],color='k'),pl.Line2D([0],[0],linestyle='--',color='k')),
("$3_{2,1}-2_{2,0}$","$3_{0,3}-2_{0,2}$"),
fontsize=16,
loc='center right',
bbox_to_anchor=[1,1.2])
#pl.savefig("pH2CO_321-220_vs_temperature_N=%1.0e_X=%0.1e.pdf" % (nh2,abundance),bbox_inches='tight')
pl.savefig("pH2CO_flux_and_ratio_vs_temperature_N=%1.0e_X=%0.1e.pdf" % (nh2,abundance),bbox_inches='tight')