#@ s*: Label=FastTest
#@ s0: DakotaConfig=HAVE_DOT
#@ s1: DakotaConfig=HAVE_DOT
#@ s2: DakotaConfig=HAVE_DOT
#@ s3: DakotaConfig=HAVE_DOT
#@ s4: DakotaConfig=HAVE_DOT
#@ s5: DakotaConfig=HAVE_DOT
#@ s6: DakotaConfig=HAVE_DOT
#@ s7: DakotaConfig=HAVE_DOT
#@ s8: DakotaConfig=HAVE_DOT
#@ s9: UserMan=textbook_opt_conmin
## DAKOTA INPUT FILE - dakota_textbook.in     #s8
## Dakota Input File: textbook_opt_conmin.in	#s9
# This tester populates a test matrix of fork/system vs. synch/asynch
# vs. temporary/named files for the 1 piece interface.
# s10-s11: test correct traits coverage of various Minimizer TPLs

environment
#  tabular_data                                     #s9
#    tabular_data_file = 'textbook_opt_conmin.dat'  #s9
#   top_method_pointer = 'SBGO'                     #s10
#   method_pointer = 'SBLO'                         #s11

method
  dot_mmfd,                       #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8
## dot_mmfd #DOT performs better but may not be available     #s9
#  conmin_mfd			                              #s9
    max_iterations = 50           #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
    convergence_tolerance = 1e-4  #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
# id_method = 'SBGO'              #s10
# surrogate_based_global          #s10
# model_pointer = 'SURROGATE'     #s10
# method_pointer = 'MOGA'         #s10
# replace_points                  #s10
# id_method = 'SBLO'              #s11
# surrogate_based_local           #s11
# model_pointer = 'SURROGATE'     #s11
# approx_method_pointer = 'NLP'   #s11
# max_iterations = 50             #s11
# trust_region                    #s11
#   initial_size = 0.10           #s11
#   contraction_factor = 0.5      #s11
#   expansion_factor   = 1.50     #s11

# method                                              #s10
#     id_method = 'MOGA'                              #s10
#     moga                                            #s10
#         seed = 10983                                #s10
#     population_size = 20                            #s10
#     max_function_evaluations = 200                  #s10
#     initialization_type unique_random               #s10
#     crossover_type shuffle_random                   #s10
#         num_offspring = 2 num_parents = 2           #s10
#         crossover_rate = 0.8                        #s10
#     mutation_type replace_uniform                   #s10
#         mutation_rate = 0.1                         #s10
#     fitness_type domination_count                   #s10
#     replacement_type below_limit = 6                #s10
#         shrinkage_percentage = 0.9                  #s10
#     niching_type distance 0.05 0.05                 #s10
#     postprocessor_type                              #s10
#         orthogonal_distance 0.05 0.05               #s10
#     convergence_type metric_tracker                 #s10
#         percent_change = 0.05 num_generations = 10  #s10
#     output silent                                   #s10

#     method,     #s11
#       id_method = 'NLP'                   #s11
#       conmin_mfd                          #s11
#         max_iterations = 50               #s11
#         convergence_tolerance = 1e-4      #s11


# model                                     #s10,#s11
#     id_model = 'SURROGATE'                #s10,#s11
#     responses_pointer = 'SURROGATE_RESP'  #s10,#s11
#     surrogate global                      #s10,#s11
#         dace_method_pointer = 'SAMPLING'  #s10,#s11
#         polynomial quadratic              #s10,#s11

variables
  continuous_design = 2
    initial_point    0.9    1.1
    upper_bounds     5.8    2.9
    lower_bounds     0.5   -2.9
    descriptors      'x1'   'x2'
#   linear_equality_constraint_matrix = 2. 1.       #s10,#s11
#   linear_equality_targets = 4.0                   #s10,#s11
#   linear_inequality_constraint_matrix = 1. 1.     #s10,#s11
#   linear_inequality_upper_bounds = 5.0            #s10,#s11

interface                                 #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  analysis_drivers =       'text_book'    #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
    fork                                  #s0,#s1,#s2,#s3
#    system 				                      #s4,#s5,#s6,#s7
#    direct				                        #s8,#s9
#      parameters_file=        'tb.in'    #s1,#s3,#s5,#s7
#      results_file=           'tb.out'	  #s1,#s3,#s5,#s7
       labeled                            #s0,#s1,#s2,#s3
#      file_tag				                    #s3,#s7
#  asynchronous			                      #s2,#s3,#s6,#s7

# responses,                              #s10,#s11
#   id_responses = 'SURROGATE_RESP'       #s10,#s11
#   objective_functions = 1               #s10,#s11
#   nonlinear_inequality_constraints = 1  #s10,#s11
#   nonlinear_equality_constraints = 1    #s10,#s11
#   no_gradients                          #s10
#   numerical_gradients                   #s11
#     method_source dakota                #s11
#     interval_type forward               #s11
#     fd_gradient_step_size = .0001       #s11
#   no_hessians                           #s10,#s11

# method                        #s10,#s11
#     id_method = 'SAMPLING'    #s10,#s11
#     sampling                  #s10,#s11
#       samples = 100           #s10,#s11
#       seed = 531              #s10,#s11
#       sample_type lhs         #s10,#s11
#     model_pointer = 'TRUTH'   #s10,#s11

# model                                 #s10,#s11
#     id_model = 'TRUTH'                #s10,#s11
#     single                            #s10,#s11
#       interface_pointer = 'TRUE_FN'   #s10,#s11
#     responses_pointer = 'TRUE_RESP'   #s10,#s11

# interface,                          #s10,#s11
#   direct                            #s10,#s11
#   id_interface = 'TRUE_FN'          #s10,#s11
#     analysis_driver = 'text_book'   #s10,#s11

# responses,                              #s10,#s11
#   id_responses = 'TRUE_RESP'            #s10,#s11
#   objective_functions = 1               #s10,#s11
#   nonlinear_inequality_constraints = 1  #s10,#s11
#   nonlinear_equality_constraints = 1    #s10,#s11
#   no_gradients                          #s10,#s11  
#   no_hessians                           #s10,#s11


responses                                 #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  objective_functions = 1                 #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  nonlinear_inequality_constraints = 2    #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  descriptors 'f' 'c1' 'c2'               #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  numerical_gradients                     #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
    method_source dakota                  #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
    interval_type central                 #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
    fd_step_size = 1.e-4                  #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9
  no_hessians                             #s0,#s1,#s2,#s3,#s4,#s5,#s6,#s7,#s8,#s9