Blurb::
Surrogate model training data reuse control
Description::
Dakota's global surrogate methods rely on training data, which can
either come from evaluation of a "truth" model, which is generated by
the method specified with
:dakkw:`model-surrogate-global-dace_method_pointer`, from a file of existing
training data, identified by
:dakkw:`model-surrogate-global-import_build_points_file`, or both.

The ``reuse_points`` keyword controls the amount of training data used
in building a surrogate model, either initially, or during iterative
rebuild, as in surrogate-based optimization.  If
:dakkw:`model-surrogate-global-import_build_points_file` is specified,
``reuse_points`` controls how the file contents are used.  If used during
iterative rebuild, it controls what data from previous surrogate
builds is reused in building the current model.



- ``all`` (default for file import) - use all points in the file or available from previous builds


- ``region`` - use only the points falling in the current trust region (see :dakkw:`method-surrogate_based_local`)


- ``none`` (default when no import) - ignore the contents of the file or previous build points, and gather new training data using the specified DACE method
Topics::
surrogate_models
Examples::

Theory::

Faq::

See_Also::
