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