#@ s2: Restart=write
#@ s3: Restart=read DependsOn=s2
#
# Batch sampling with multiple distribution types
# (based on dakota_uq_rosenbrock_verify, test s5)
#   0: generate 700 D-optimal points
#   1: single study to generate 400 + 200 + 100 D-optimal points
#   2: initial study to generate 400 D-optimal points
#   3: restarted study to generate (400) + 200 + 100 D-optimal points
#      (should be identical to 1)

environment,
#  tabular_data                                     #s1,#s3
#    tabular_data_file = 'samples_700.dat'          #s1
#    tabular_data_file = 'samples_700_restart.dat'  #s3

method,
	sampling
    sample_type random
    seed = 12347
    samples = 700                                   #s0
#    initial_samples = 400                          #s1,#s2,#s3
#      refinement_samples = 200 100                 #s1,#s3
      d_optimal                                     
        candidate_designs = 50
	  response_levels = .1 1. 50. 100. 500. 1000.
	  output silent

variables,
	normal_uncertain = 1
      	  means             =  0.
	  std_deviations    =  1.
	  descriptors       = 'x1'
	uniform_uncertain = 1
      	  lower_bounds      = -2.
	  upper_bounds      =  2.
	  descriptors       = 'x2'
	exponential_uncertain = 1
	  betas             =  2.
	  descriptors       = 'x3'
	beta_uncertain = 1
	  alphas            =  1.5
	  betas             =  2.
      	  lower_bounds      = -2.
	  upper_bounds      =  2.
	  descriptors       = 'x4'
	gamma_uncertain = 1
	  alphas           =  2.5
	  betas            =  2.
	  descriptors      = 'x5'

interface,
	direct
	  analysis_driver = 'generalized_rosenbrock'
#	  deactivate evaluation_cache restart_file

responses,
	response_functions = 1
	no_gradients
	no_hessians