-
Notifications
You must be signed in to change notification settings - Fork 0
/
params_ppd.ini
181 lines (160 loc) · 5.57 KB
/
params_ppd.ini
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
169
170
171
172
173
174
175
176
177
178
179
180
181
%include fiducial/params.ini
[runtime]
sampler = test
root = ${COSMOSIS_SRC_DIR}
pre_script =
; pre_script = ;${Y3METHODS_DIR}/cosmosis/pre_script.sh
[DEFAULT]
BASELINE_DIR=.
2PT_DATA_SETS = ERROR ;xip xim gammat wtheta
2PT_DATA_SETS_D = ERROR ;xip xim gammat wtheta
2PT_DATA_SETS_DPRIME = ERROR ;xip xim gammat wtheta
RUN_NAME_PPD = ERROR
; use as the last item in the pipeline to switch between 2pt_like and save_2pt
ACTION = ERROR
[output]
filename= ppd/%(RUN_NAME_PPD)s/ppd_chain_${RUNNAME}_%(RUN_NAME_PPD)s.txt
; [test]
; save_dir=%(RUN_NAME_PPD)s/test_${DATAFILE}_%(RUN_NAME_PPD)s
[listppd]
; filename = trimmed_chains/chain_%(RUN_NAME)s.txt ;%(RUN_NAME_PPD)s/chain_%(RUN_NAME_PPD)s_${DATAFILE}_${SCALE_CUTS}_${DEMODEL}.txt
filename = /project/projectdirs/des/www/y3_chains/3x2pt/final_paper_chains/chain_%(RUN_NAME)s.txt
ppd_output_file_basename = ppd/%(RUN_NAME_PPD)s/ppd_${RUNNAME}_%(RUN_NAME_PPD)s
[pipeline]
quiet=F
timing=T
debug=F
fast_slow=F
modules = consistency bbn_consistency camb halofit extrapolate fits_nz lens_photoz_width lens_photoz_bias source_photoz_bias fast_pt IA pk_to_cl_gg pk_to_cl add_magnification add_intrinsic add_eb shear_2pt_eplusb shear_2pt_eminusb choose_xip 2pt_gal 2pt_gal_shear shear_m_bias add_pm smallratio_like 2pt_like 2pt_d_like 2pt_dprime_like 2pt_xip_like 2pt_xim_like 2pt_1x2_like 2pt_gammat_like 2pt_wtheta_like 2pt_2x2_like ppd
; priors = ppd/%(RUN_NAME_PPD)s/priors.ini
; values = ppd/%(RUN_NAME_PPD)s/values.ini
extra_output = cosmological_parameters/sigma_8 cosmological_parameters/sigma_12 data_vector/2pt_chi2 data_vector/2pt_d_chi2 data_vector/2pt_dprime_chi2 data_vector/2pt_xip_chi2 data_vector/2pt_xim_chi2 data_vector/2pt_1x2_chi2 data_vector/2pt_gammat_chi2 data_vector/2pt_wtheta_chi2 data_vector/2pt_2x2_chi2 ppd/chi2_dprime_data ppd/chi2_dprime_realization ppd/chi2_d_data ppd/chi2_xip_data ppd/chi2_xip_realization ppd/chi2_xim_data ppd/chi2_xim_realization ppd/chi2_1x2_data ppd/chi2_1x2_realization ppd/chi2_gammat_data ppd/chi2_gammat_realization ppd/chi2_wtheta_data ppd/chi2_wtheta_realization ppd/chi2_2x2_data ppd/chi2_2x2_realization ppd/chi2_dprime_comp_avg ppd/chi2_xip_comp_avg ppd/chi2_xim_comp_avg ppd/chi2_1x2_comp_avg ppd/chi2_gammat_comp_avg ppd/chi2_wtheta_comp_avg ppd/chi2_2x2_comp_avg
likelihoods = 2pt ;smallratio
; [smallratio_like]
; measured_ratio_filename = ${Y3METHODS_DIR}/cosmosis/shear_ratio_data/ratios/v.40/redmagic/ratios_ss.npy ; for data
[2pt_like]
; file = cosmosis-standard-library/likelihood/2pt/2pt_like_allmarg.py
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
;;; The following lines are the options used in the fiducial params.ini file.
; do_pm_marg = True
; do_pm_sigcritinv = True
; sigma_a=10000.0
; no_det_fac = False
; data_file = %(2PT_FILE)s
data_sets = %(2PT_DATA_SETS)s
; make_covariance=F
; covmat_name=COVMAT
;;; PPD changes
like_name = 2pt
%include ppd/${SCALEFILE}_2pt_like
[2pt_d_like]
; file = cosmosis-standard-library/likelihood/2pt/2pt_like_allmarg.py
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = %(2PT_DATA_SETS_D)s
make_covariance=F
covmat_name=COVMAT
;;; PPD changes
like_name = 2pt_d
%include ppd/${SCALEFILE}_2pt_d_like
[2pt_dprime_like]
; file = cosmosis-standard-library/likelihood/2pt/2pt_like_allmarg.py
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = %(2PT_DATA_SETS_DPRIME)s
make_covariance=F
covmat_name=COVMAT
;;; PPD changes
like_name = 2pt_dprime
%include ppd/${SCALEFILE}_2pt_dprime_like
##################### Likelihood for separate obs + 1x2 and 2x2 #######################
[2pt_xip_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = xip
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_xip
%include ppd/${SCALEFILE}_2pt_xip_like
[2pt_xim_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = xim
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_xim
%include ppd/${SCALEFILE}_2pt_xim_like
[2pt_1x2_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = xip xim
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_1x2
%include ppd/${SCALEFILE}_2pt_1x2_like
[2pt_gammat_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = gammat
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_gammat
%include ppd/${SCALEFILE}_2pt_gammat_like
[2pt_wtheta_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = wtheta
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_wtheta
%include ppd/${SCALEFILE}_2pt_wtheta_like
[2pt_2x2_like]
file = ${PWD}/ppd/2pt/2pt_like_allmarg.py
do_pm_marg = True
do_pm_sigcritinv = True
sigma_a=10000.0
no_det_fac = False
data_file = %(2PT_FILE)s
data_sets = gammat wtheta
make_covariance=F
covmat_name=COVMAT
like_name = 2pt_2x2
%include ppd/${SCALEFILE}_2pt_2x2_like
##################### PPD module ##########################
[ppd]
file=${PWD}/ppd/ppd/ppd.py
statistic = chi2
ppd_d_names = %(2PT_DATA_SETS_D)s
ppd_dprime_names = %(2PT_DATA_SETS_DPRIME)s
condition_on_d = ERROR
; use_like_cuts = -1
use_like_cuts = 2
ndraws = 100