1# DAKOTA INPUT FILE - dakota_uq_textbook_adaptsampling.in
2# This sampling input file demonstrates adaptive sampling.
3
4method,
5	adaptive_sampling,
6	  initial_samples = 20
7	  seed = 1234
8	  # rng mt19937
9
10          response_levels =  10.0
11          samples_on_emulator = 400
12          max_iterations = 50
13          refinement_samples = 2
14          batch_selection = naive
15          fitness_metric = predicted_variance
16          #fitness_metric = distance
17          #fitness_metric = gradient
18          # previous implementation with misc_options:
19          # misc_options  'sample_design=sampling_lhs'
20          # 'approx_type=global_kriging'
21          # 'candidate_size=400' 'rounds=50' 'score_type=alm'
22          # 'batch_size=2' 'batch_environment=naive'
23
24variables,
25	uniform_uncertain = 2
26          descriptors  = 'x1' 'x2'
27	  lower_bounds =  -2.0   -2.0
28	  upper_bounds =  2.0   2.0
29
30interface,
31        direct
32	  analysis_driver = 'text_book'
33
34responses,
35	response_functions = 1
36	no_gradients
37	no_hessians
38