-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathpilot MCMC chains 1000 iterations.txt
199 lines (196 loc) · 8.94 KB
/
pilot MCMC chains 1000 iterations.txt
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
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
Click the Refresh button to see progress of the chains
starting worker pid=17136 on localhost:11721 at 16:00:41.416
starting worker pid=15488 on localhost:11721 at 16:00:41.654
starting worker pid=10792 on localhost:11721 at 16:00:41.886
SAMPLING FOR MODEL 'ctsm' NOW (CHAIN 1).
SAMPLING FOR MODEL 'ctsm' NOW (CHAIN 2).
SAMPLING FOR MODEL 'ctsm' NOW (CHAIN 3).
Chain 1:
Chain 1: Gradient evaluation took 0.097 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 970 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 3:
Chain 3: Gradient evaluation took 0.128 seconds
Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 1280 seconds.
Chain 3: Adjust your expectations accordingly!
Chain 3:
Chain 3:
Chain 2:
Chain 2: Gradient evaluation took 0.132 seconds
Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 1320 seconds.
Chain 2: Adjust your expectations accordingly!
Chain 2:
Chain 2:
Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup)
Chain 3: Iteration: 1 / 1000 [ 0%] (Warmup)
Chain 2: Iteration: 1 / 1000 [ 0%] (Warmup)
Chain 3: Iteration: 20 / 1000 [ 2%] (Warmup)
Chain 2: Iteration: 20 / 1000 [ 2%] (Warmup)
Chain 1: Iteration: 20 / 1000 [ 2%] (Warmup)
Chain 3: Iteration: 40 / 1000 [ 4%] (Warmup)
Chain 1: Iteration: 40 / 1000 [ 4%] (Warmup)
Chain 2: Iteration: 40 / 1000 [ 4%] (Warmup)
Chain 3: Iteration: 60 / 1000 [ 6%] (Warmup)
Chain 1: Iteration: 60 / 1000 [ 6%] (Warmup)
Chain 2: Iteration: 60 / 1000 [ 6%] (Warmup)
Chain 3: Iteration: 80 / 1000 [ 8%] (Warmup)
Chain 1: Iteration: 80 / 1000 [ 8%] (Warmup)
Chain 2: Iteration: 80 / 1000 [ 8%] (Warmup)
Chain 3: Iteration: 100 / 1000 [ 10%] (Warmup)
Chain 2: Iteration: 100 / 1000 [ 10%] (Warmup)
Chain 1: Iteration: 100 / 1000 [ 10%] (Warmup)
Chain 2: Iteration: 120 / 1000 [ 12%] (Warmup)
Chain 3: Iteration: 120 / 1000 [ 12%] (Warmup)
Chain 1: Iteration: 120 / 1000 [ 12%] (Warmup)
Chain 2: Iteration: 140 / 1000 [ 14%] (Warmup)
Chain 1: Iteration: 140 / 1000 [ 14%] (Warmup)
Chain 3: Iteration: 140 / 1000 [ 14%] (Warmup)
Chain 2: Iteration: 160 / 1000 [ 16%] (Warmup)
Chain 1: Iteration: 160 / 1000 [ 16%] (Warmup)
Chain 3: Iteration: 160 / 1000 [ 16%] (Warmup)
Chain 1: Iteration: 180 / 1000 [ 18%] (Warmup)
Chain 2: Iteration: 180 / 1000 [ 18%] (Warmup)
Chain 3: Iteration: 180 / 1000 [ 18%] (Warmup)
Chain 3: Iteration: 200 / 1000 [ 20%] (Warmup)
Chain 2: Iteration: 200 / 1000 [ 20%] (Warmup)
Chain 1: Iteration: 200 / 1000 [ 20%] (Warmup)
Chain 2: Iteration: 220 / 1000 [ 22%] (Warmup)
Chain 3: Iteration: 220 / 1000 [ 22%] (Warmup)
Chain 1: Iteration: 220 / 1000 [ 22%] (Warmup)
Chain 2: Iteration: 240 / 1000 [ 24%] (Warmup)
Chain 1: Iteration: 240 / 1000 [ 24%] (Warmup)
Chain 3: Iteration: 240 / 1000 [ 24%] (Warmup)
Chain 3: Iteration: 260 / 1000 [ 26%] (Warmup)
Chain 2: Iteration: 260 / 1000 [ 26%] (Warmup)
Chain 1: Iteration: 260 / 1000 [ 26%] (Warmup)
Chain 3: Iteration: 280 / 1000 [ 28%] (Warmup)
Chain 2: Iteration: 280 / 1000 [ 28%] (Warmup)
Chain 1: Iteration: 280 / 1000 [ 28%] (Warmup)
Chain 3: Iteration: 300 / 1000 [ 30%] (Warmup)
Chain 2: Iteration: 300 / 1000 [ 30%] (Warmup)
Chain 1: Iteration: 300 / 1000 [ 30%] (Warmup)
Chain 3: Iteration: 320 / 1000 [ 32%] (Warmup)
Chain 2: Iteration: 320 / 1000 [ 32%] (Warmup)
Chain 1: Iteration: 320 / 1000 [ 32%] (Warmup)
Chain 3: Iteration: 340 / 1000 [ 34%] (Warmup)
Chain 2: Iteration: 340 / 1000 [ 34%] (Warmup)
Chain 1: Iteration: 340 / 1000 [ 34%] (Warmup)
Chain 3: Iteration: 360 / 1000 [ 36%] (Warmup)
Chain 2: Iteration: 360 / 1000 [ 36%] (Warmup)
Chain 1: Iteration: 360 / 1000 [ 36%] (Warmup)
Chain 3: Iteration: 380 / 1000 [ 38%] (Warmup)
Chain 2: Iteration: 380 / 1000 [ 38%] (Warmup)
Chain 1: Iteration: 380 / 1000 [ 38%] (Warmup)
Chain 3: Iteration: 400 / 1000 [ 40%] (Warmup)
Chain 1: Iteration: 400 / 1000 [ 40%] (Warmup)
Chain 2: Iteration: 400 / 1000 [ 40%] (Warmup)
Chain 3: Iteration: 420 / 1000 [ 42%] (Warmup)
Chain 2: Iteration: 420 / 1000 [ 42%] (Warmup)
Chain 1: Iteration: 420 / 1000 [ 42%] (Warmup)
Chain 3: Iteration: 440 / 1000 [ 44%] (Warmup)
Chain 3: Iteration: 460 / 1000 [ 46%] (Warmup)
Chain 1: Iteration: 440 / 1000 [ 44%] (Warmup)
Chain 2: Iteration: 440 / 1000 [ 44%] (Warmup)
Chain 3: Iteration: 480 / 1000 [ 48%] (Warmup)
Chain 1: Iteration: 460 / 1000 [ 46%] (Warmup)
Chain 2: Iteration: 460 / 1000 [ 46%] (Warmup)
Chain 3: Iteration: 500 / 1000 [ 50%] (Warmup)
Chain 3: Iteration: 501 / 1000 [ 50%] (Sampling)
Chain 1: Iteration: 480 / 1000 [ 48%] (Warmup)
Chain 2: Iteration: 480 / 1000 [ 48%] (Warmup)
Chain 3: Iteration: 520 / 1000 [ 52%] (Sampling)
Chain 2: Iteration: 500 / 1000 [ 50%] (Warmup)
Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup)
Chain 2: Iteration: 501 / 1000 [ 50%] (Sampling)
Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling)
Chain 3: Iteration: 540 / 1000 [ 54%] (Sampling)
Chain 2: Iteration: 520 / 1000 [ 52%] (Sampling)
Chain 1: Iteration: 520 / 1000 [ 52%] (Sampling)
Chain 3: Iteration: 560 / 1000 [ 56%] (Sampling)
Chain 2: Iteration: 540 / 1000 [ 54%] (Sampling)
Chain 1: Iteration: 540 / 1000 [ 54%] (Sampling)
Chain 3: Iteration: 580 / 1000 [ 58%] (Sampling)
Chain 2: Iteration: 560 / 1000 [ 56%] (Sampling)
Chain 1: Iteration: 560 / 1000 [ 56%] (Sampling)
Chain 3: Iteration: 600 / 1000 [ 60%] (Sampling)
Chain 2: Iteration: 580 / 1000 [ 58%] (Sampling)
Chain 3: Iteration: 620 / 1000 [ 62%] (Sampling)
Chain 3: Iteration: 640 / 1000 [ 64%] (Sampling)
Chain 3: Iteration: 660 / 1000 [ 66%] (Sampling)
Chain 1: Iteration: 580 / 1000 [ 58%] (Sampling)
Chain 2: Iteration: 600 / 1000 [ 60%] (Sampling)
Chain 3: Iteration: 680 / 1000 [ 68%] (Sampling)
Chain 1: Iteration: 600 / 1000 [ 60%] (Sampling)
Chain 2: Iteration: 620 / 1000 [ 62%] (Sampling)
Chain 3: Iteration: 700 / 1000 [ 70%] (Sampling)
Chain 3: Iteration: 720 / 1000 [ 72%] (Sampling)
Chain 3: Iteration: 740 / 1000 [ 74%] (Sampling)
Chain 3: Iteration: 760 / 1000 [ 76%] (Sampling)
Chain 3: Iteration: 780 / 1000 [ 78%] (Sampling)
Chain 3: Iteration: 800 / 1000 [ 80%] (Sampling)
Chain 3: Iteration: 820 / 1000 [ 82%] (Sampling)
Chain 3: Iteration: 840 / 1000 [ 84%] (Sampling)
Chain 3: Iteration: 860 / 1000 [ 86%] (Sampling)
Chain 3: Iteration: 880 / 1000 [ 88%] (Sampling)
Chain 3: Iteration: 900 / 1000 [ 90%] (Sampling)
Chain 1: Iteration: 620 / 1000 [ 62%] (Sampling)
Chain 2: Iteration: 640 / 1000 [ 64%] (Sampling)
Chain 3: Iteration: 920 / 1000 [ 92%] (Sampling)
Chain 2: Iteration: 660 / 1000 [ 66%] (Sampling)
Chain 2: Iteration: 680 / 1000 [ 68%] (Sampling)
Chain 2: Iteration: 700 / 1000 [ 70%] (Sampling)
Chain 3: Iteration: 940 / 1000 [ 94%] (Sampling)
Chain 2: Iteration: 720 / 1000 [ 72%] (Sampling)
Chain 1: Iteration: 640 / 1000 [ 64%] (Sampling)
Chain 3: Iteration: 960 / 1000 [ 96%] (Sampling)
Chain 3: Iteration: 980 / 1000 [ 98%] (Sampling)
Chain 2: Iteration: 740 / 1000 [ 74%] (Sampling)
Chain 1: Iteration: 660 / 1000 [ 66%] (Sampling)
Chain 2: Iteration: 760 / 1000 [ 76%] (Sampling)
Chain 3: Iteration: 1000 / 1000 [100%] (Sampling)
Chain 3:
Chain 3: Elapsed Time: 33751.8 seconds (Warm-up)
Chain 3: 15111.6 seconds (Sampling)
Chain 3: 48863.3 seconds (Total)
Chain 3:
Chain 2: Iteration: 780 / 1000 [ 78%] (Sampling)
Chain 1: Iteration: 680 / 1000 [ 68%] (Sampling)
Chain 2: Iteration: 800 / 1000 [ 80%] (Sampling)
Chain 1: Iteration: 700 / 1000 [ 70%] (Sampling)
Chain 2: Iteration: 820 / 1000 [ 82%] (Sampling)
Chain 2: Iteration: 840 / 1000 [ 84%] (Sampling)
Chain 1: Iteration: 720 / 1000 [ 72%] (Sampling)
Chain 2: Iteration: 860 / 1000 [ 86%] (Sampling)
Chain 1: Iteration: 740 / 1000 [ 74%] (Sampling)
Chain 2: Iteration: 880 / 1000 [ 88%] (Sampling)
Chain 1: Iteration: 760 / 1000 [ 76%] (Sampling)
Chain 2: Iteration: 900 / 1000 [ 90%] (Sampling)
Chain 1: Iteration: 780 / 1000 [ 78%] (Sampling)
Chain 2: Iteration: 920 / 1000 [ 92%] (Sampling)
Chain 1: Iteration: 800 / 1000 [ 80%] (Sampling)
Chain 2: Iteration: 940 / 1000 [ 94%] (Sampling)
Chain 1: Iteration: 820 / 1000 [ 82%] (Sampling)
Chain 2: Iteration: 960 / 1000 [ 96%] (Sampling)
Chain 2: Iteration: 980 / 1000 [ 98%] (Sampling)
Chain 1: Iteration: 840 / 1000 [ 84%] (Sampling)
Chain 2: Iteration: 1000 / 1000 [100%] (Sampling)
Chain 2:
Chain 2: Elapsed Time: 35971.5 seconds (Warm-up)
Chain 2: 22193.2 seconds (Sampling)
Chain 2: 58164.6 seconds (Total)
Chain 2:
Chain 1: Iteration: 860 / 1000 [ 86%] (Sampling)
Chain 1: Iteration: 880 / 1000 [ 88%] (Sampling)
Chain 1: Iteration: 900 / 1000 [ 90%] (Sampling)
Chain 1: Iteration: 920 / 1000 [ 92%] (Sampling)
Chain 1: Iteration: 940 / 1000 [ 94%] (Sampling)
Chain 1: Iteration: 960 / 1000 [ 96%] (Sampling)
Chain 1: Iteration: 980 / 1000 [ 98%] (Sampling)
Chain 1: Iteration: 1000 / 1000 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 36019 seconds (Warm-up)
Chain 1: 26251 seconds (Sampling)
Chain 1: 62270 seconds (Total)
Chain 1: