model_selection

Select the models that write evaluation data to HDF5

Topics

dakota_output

Specification

• Alias: None

• Arguments: None

Child Keywords:

Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
Required (Choose One)	Model Evaluation Storage Selection	top_method	Write evaluation data only for the top-level method’s model to HDF5
		none	Write evaluation data for no models to HDF5
		all_methods	Write evaluation data to HDF5 for all models that belong directly to methods
		all	Write evaluation data to HDF5 for all models

Description

By default, when HDF5 output is enabled, Dakota writes evaluation data only for the model that belongs to the top-level method. This keyword group is used to override the default.

HDF5 output is an experimental feature, and the contents and organization of the output file is subject to change. The current organization and a brief explanation of HDF5 is provided in the hdf5_output section of this manual.

The example below will be used to explain the effect of each keyword.

Examples

environment
  results_output
      hdf5
       # model_selection
       #  top_method
       #  all_methods
       #  all
       #  none
      results_output_file 'my_results'  # The .h5 extension will be added

   method_pointer 'opt'

method
  id_method 'opt'
    optpp_q_newton
  model_pointer 'surr'

model
  id_model 'surr'
  surrogate global gaussian_process surfpack
  dace_method_pointer 'training'

method
  id_method 'training'
  sampling
    seed 1234
    samples 20
  model_pointer 'truth_m'

model
  id_model 'truth_m'
  simulation

interface
  id_interface 'truth'
  direct
    analysis_drivers 'text_book'

variables
  continuous_design 2
    descriptors 'x1' 'x2'
    lower_bounds -2.0 -2.0
    upper_bounds  2.0  2.0

responses
  objective_functions 2
    descriptors 'f1' 'f2'
  analytic_gradients
  no_hessians