no_scrambling

Do not scramble this digital net

Specification

• Alias: None

• Arguments: None

Description

The digital net should preserve the structure of the points after randomization. This can be achieved by scrambling the digital net. Scrambling can also improve the rate of convergence of a method that uses these scrambled points to compute the mean of the model response. Owen’s scrambling [Owe98] is the most well-known scrambling technique. A particular variant is linear matrix scrambling, which is implemented in Dakota [Matouvsek98]. In linear matrix scrambling, we left-multiply each generating matrix with a lower-triangular random scramble matrix. The number of rows in the scramble matrix can be set with the keyword t_scramble.

Usage tips

When this keyword is provided, the digital net points will not be scrambled. Unscrambled digital net points are generally less performant compared to their scrambled counterparts, so it is highly recommended to not use this keyword, unless you’re absolutely sure you know what you’re doing.

Examples

environment
  tabular_data
    tabular_data_file = 'samples.dat'
    freeform

method
  sampling
    samples 32
    sample_type
      low_discrepancy
        digital_net
          generating_matrices inline
            1 2 4 8 16
            # this encodes the generating matrix
            # 1 0 0 0 0
            # 0 1 0 0 0
            # 0 0 1 0 0
            # 0 0 0 1 0
            # 0 0 0 0 1
            1 3 5 15 17
            # this encodes the generating matrix
            # 1 1 1 1 1
            # 0 1 0 1 0
            # 0 0 1 1 0
            # 0 0 0 1 0
            # 0 0 0 0 1
          m_max 5
          t_max 5
          no_scrambling
          no_digital_shift

variables
  uniform_uncertain = 2
    lower_bounds 0.0 0.0
    upper_bounds 1.0 1.0

interface
  analysis_drivers = 'genz'
  analysis_components = 'cp1'
  direct

responses
  response_functions = 1
  no_gradients
  no_hessians