Blurb::
Specify predefined generating matrices

Description::
Dakota provides two predefined generating vectors:

- :dakkw:`method-sampling-sample_type-low_discrepancy-digital_net-generating_matrices-predefined-joe_kuo` (default): generates up to 2\ :sup:`32` points in up to 250 dimensions :cite:p:`Joe08`
- :dakkw:`method-sampling-sample_type-low_discrepancy-digital_net-generating_matrices-predefined-sobol_order_2`: generates up to 2\ :sup:`32` points in up to 1024 dimensions :cite:p:`QMCPy`

Topics::

Examples::

.. code-block::

    environment
      tabular_data
        tabular_data_file = 'samples.dat'
        freeform

    method
      sampling
        samples 1024
        sample_type
          low_discrepancy
            digital_net
              generating_matrices predefined joe_kuo

    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

Theory::

Faq::

See_Also::
