.. _method-vector_parameter_study: """""""""""""""""""""" vector_parameter_study """""""""""""""""""""" Samples variables along a user-defined vector **Topics** parameter_studies .. toctree:: :hidden: :maxdepth: 1 method-vector_parameter_study-final_point method-vector_parameter_study-step_vector method-vector_parameter_study-num_steps method-vector_parameter_study-model_pointer **Specification** - *Alias:* None - *Arguments:* None **Child Keywords:** +-------------------------+--------------------+--------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+====================+=============================================+ | Required (Choose One) | Step Control | `final_point`__ | Final variable values defining vector in | | | | | vector parameter study | | | +--------------------+---------------------------------------------+ | | | `step_vector`__ | Size of step for each variable | +-------------------------+--------------------+--------------------+---------------------------------------------+ | Required | `num_steps`__ | Number of sampling steps along the vector | | | | in a vector parameter study | +----------------------------------------------+--------------------+---------------------------------------------+ | Optional | `model_pointer`__ | Identifier for model block to be used by a | | | | method | +----------------------------------------------+--------------------+---------------------------------------------+ .. __: method-vector_parameter_study-final_point.html __ method-vector_parameter_study-step_vector.html __ method-vector_parameter_study-num_steps.html __ method-vector_parameter_study-model_pointer.html **Description** Dakota's vector parameter study computes response data sets at selected intervals along a vector in parameter space. It is often used for single-coordinate parameter studies (to study the effect of a single variable on a response set), but it can be used more generally for multiple coordinate vector studies (to investigate the response variations along some n-dimensional vector such as an optimizer search direction). *Default Behavior* By default, the vector parameter study operates over all types of variables. *Expected Outputs* A vector parameter study produces a set of responses for each parameter set that is generated. *Expected HDF5 Output* If Dakota was built with HDF5 support and run with the :dakkw:`environment-results_output-hdf5` keyword, this method writes the following results to HDF5: - :ref:`hdf5_results-pstudies` *Usage Tips* *Group 1* is used to define the vector along which the parameters are varied. Both cases also rely on the variables specification of an initial value, through: - the :dakkw:`variables-continuous_design-initial_point` keyword - the :dakkw:`variables-continuous_state-initial_state` keyword - relying on the default initial value, based on the rest of the variables specification From the initial value, the vector can be defined using one of the two keyword choices. Once the vector is defined, the samples are then fully specifed by :dakkw:`method-vector_parameter_study-num_steps`. **Examples** The following example is a good comparison to the examples on :dakkw:`method-multidim_parameter_study` and :dakkw:`method-centered_parameter_study`. .. code-block:: # tested on Dakota 6.0 on 140501 environment tabular_data tabular_data_file = 'rosen_vector.dat' method vector_parameter_study num_steps = 10 final_point = 2.0 2.0 model single variables continuous_design = 2 initial_point = -2.0 -2.0 descriptors = 'x1' "x2" interface analysis_driver = 'rosenbrock' fork responses response_functions = 1 no_gradients no_hessians