.. _method-approximate_control_variate-model_pointer:

"""""""""""""
model_pointer
"""""""""""""


Identifier for model block to be used by a method



**Topics**


block_pointer


.. toctree::
   :hidden:
   :maxdepth: 1



**Specification**

- *Alias:* None

- *Arguments:* STRING

- *Default:* method use of last model parsed (or use of default model if none parsed)


**Description**


The ``model_pointer`` is used to specify which :dakkw:`model` block will be
used to perform the function evaluations needed by the Dakota method.

*Default Behavior*

If not specified, a Dakota method will use the last model block
parsed.  If specified, there must be a :dakkw:`model` block in the Dakota
input file that has a corresponding ``id_model`` with the same name.

*Usage Tips*

When doing advanced analyses that involve using multiple methods and
multiple models, defining a ``model_pointer`` for each method is
imperative.

See :ref:`topic-block_pointer` for details about pointers.



**Examples**



.. code-block::

    environment
      tabular_data
      method_pointer = 'UQ'
    
    method
      id_method = 'UQ'
      model_pointer = 'SURR'
      sampling,
        samples = 10
        seed = 98765 rng rnum2
        response_levels = 0.1 0.2 0.6
                          0.1 0.2 0.6
                                0.1 0.2 0.6
        sample_type lhs
        distribution cumulative
    
    model
      id_model = 'SURR'
        surrogate global,
        dace_method_pointer = 'DACE'
        polynomial quadratic
    
    method
      id_method = 'DACE'
        model_pointer = 'DACE_M'
        sampling sample_type lhs
        samples = 121 seed = 5034 rng rnum2
    
    model
      id_model = 'DACE_M'
      single
      interface_pointer = 'I1'
    
    variables
      uniform_uncertain = 2
        lower_bounds =  0.   0.
        upper_bounds =  1.   1.
        descriptors  = 'x1' 'x2'
    
    interface
      id_interface = 'I1'
      system asynch evaluation_concurrency = 5
        analysis_driver = 'text_book'
    
    responses
      response_functions = 3
      no_gradients
      no_hessians