# DAKOTA INPUT FILE - dakota_uq_ishigami_dste_exp.in

environment,    
	  tabular_data    
	  method_pointer = 'EPISTEMIC'

#################################
# begin EPISTEMIC specification #
#################################
method,									 
        id_method = 'EPISTEMIC'
        model_pointer = 'EPIST_M'
     	local_evidence		        #s0
#	global_evidence ego	        #s1,#s2,#s3
#         gaussian_process dakota       #s1
#         gaussian_process surfpack     #s2,#s3
#	  seed = 627431			#s1,#s2,#s3
          response_levels = 1. 5. 100.
	  output verbose

model,
        id_model = 'EPIST_M'
        nested
          variables_pointer  = 'EPIST_V'
          sub_method_pointer = 'ALEATORY'
          responses_pointer  = 'EPIST_R'
          primary_variable_mapping = 'x1'
          primary_response_mapping = 1. 0. 

variables,
        id_variables = 'EPIST_V'
        continuous_interval_uncertain = 1				
	  num_intervals   = 4.                                   
          interval_probs  = 0.25 0.25 0.25 0.25
	  lower_bounds    = 0.0  0.5  0.9  1.6
	  upper_bounds    = 0.5  1.5  2.0  1.8 

responses,
        id_responses = 'EPIST_R'
        response_functions = 1
        analytic_gradients		#s0	
#	no_gradients			#s1,#s2,#s3
        no_hessians
  
################################
# begin ALEATORY specification #
################################
method,
        id_method = 'ALEATORY'
        model_pointer = 'ALEAT_M'
	stoch_collocation askey
	  quadrature_order = 10

model,
        id_model = 'ALEAT_M'
        single
          variables_pointer = 'ALEAT_V'
          interface_pointer = 'ALEAT_I'
          responses_pointer = 'ALEAT_R'

##########################################################################
# Test 3 is the case where a combined expansion is performed.            # 
# The other tests involve an expansion only over the aleatory variables. #
##########################################################################

variables,
        id_variables = 'ALEAT_V'
#	active all			#s3
	continuous_design = 1
	  initial_point 1
	  lower_bounds 	0.
	  upper_bounds  2. 
	  descriptors  'x1'
	uniform_uncertain = 2
	  lower_bounds 	0.  0.
	  upper_bounds  2.  2. 
	  descriptors  'x2' 'x3'
		
interface,
        id_interface = 'ALEAT_I'
        direct
          analysis_driver = 'sobol_ishigami'

responses,
        id_responses = 'ALEAT_R'
        response_functions = 1
	analytic_gradients		
        no_hessians