-
Notifications
You must be signed in to change notification settings - Fork 0
/
act.yml
152 lines (133 loc) · 3.05 KB
/
act.yml
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
debug: False
timing: True
# Run with bandpass corrections
likelihood:
# The 100 mJy likelihood
act_pylike.act100:
stop_at_error: True
bandpass: True
# Optional line to do some debugging with an input theory curve
#theory_debug: data/actpol_2f_full_s1316_2flux_fin/data/cosmo2017_10K_acc3_lensedCls.dat
# The 15 mJy likelihood
act_pylike.act15:
stop_at_error: True
bandpass: True
# Optional line to do some debugging with an input theory curve
#theory_debug: data/actpol_2f_full_s1316_2flux_fin/data/cosmo2017_10K_acc3_lensedCls.dat
params:
theta_MC_100:
prior:
min: 0.5
max: 10
ref:
dist: norm
loc: 1.04109
scale: 0.0004
proposal: 0.0002
latex: 100\theta_\mathrm{MC}
drop: true
renames: theta
cosmomc_theta:
value: 'lambda theta_MC_100: 1.e-2*theta_MC_100'
derived: false
logA:
prior:
min: 2
max: 4
ref:
dist: norm
loc: 3.1
scale: 0.001
proposal: 0.001
drop: True
latex: \log(10^{10} A_\mathrm{s})
As:
value: "lambda logA: 1e-10*np.exp(logA)"
latex: A_\mathrm{s}
ns:
prior:
min: 0.8
max: 1.2
ref:
dist: norm
loc: 0.96
scale: 0.004
proposal: 0.002
latex: n_\mathrm{s}
ombh2:
prior:
min: 0.005
max: 0.1
ref:
dist: norm
loc: 0.0221
scale: 0.0001
proposal: 0.0001
latex: \Omega_\mathrm{b}h^2
omch2:
prior:
min: 0.001
max: 0.99
ref:
dist: norm
loc: 0.12
scale: 0.001
proposal: 0.0005
latex: \Omega_\mathrm{c}h^2
tau:
prior:
min: 0.01
max: 0.8
ref:
dist: norm
loc: 0.065
scale: 0.01
proposal: 0.005
latex: \tau_\mathrm{reio}
H0:
latex: H_0
sigma8:
latex: \sigma_8
prior:
tau_prior: "lambda tau: stats.norm.logpdf(tau, loc=0.065, scale=0.015)"
a_c_prior: "lambda a_c: stats.norm.logpdf(a_c, loc=4.9, scale=0.9)"
a_p_tt_100_prior: "lambda a_p_tt_100: stats.norm.logpdf(a_p_tt_100, loc=22.5, scale=3.0)"
a_p_tt_15_prior: "lambda a_p_tt_15: stats.norm.logpdf(a_p_tt_15, loc=3.1, scale=0.4)"
theory:
camb:
stop_at_error: False
extra_args:
lens_potential_accuracy: 1
theta_H0_range:
- 20
- 100
sampler:
# Example for evaluating at a specific point
# evaluate:
# override:
# a_c: 4.9
# a_d: 6.9
# a_tsz: 3.3
# a_ksz: 4.950210
# xi: 1.654936e-2
# a_p_tt_15: 3.1
# a_p_tt_100: 24.6
# a_p_ee: 0.0
# a_p_te: 0.1
# beta_CIB : 2.2
# yp_95: 1
# yp_150: 1
# Example MCMC run
mcmc:
burn_in: 100
max_samples: .inf
max_tries: 400
learn_proposal: True
drag: True
# Optionally use a covmat with the right theta convention
covmat: 'data/ACTPol_b5_new_cosmomc_theta2.covmat'
# Example for running the minimizer
# minimize:
# covmat: 'data/ACTPol_b5_new_cosmomc_theta2.covmat'
output: chains/bandpass_run_test
resume: True