.. _model-active_subspace-truncation_method-energy:

""""""
energy
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Truncate the subspace based on eigenvalue energy


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

   model-active_subspace-truncation_method-energy-truncation_tolerance


**Specification**

- *Alias:* None

- *Arguments:* None


**Child Keywords:**

+-------------------------+--------------------+--------------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword           | Dakota Keyword Description                    |
|                         | Group              |                          |                                               |
+=========================+====================+==========================+===============================================+
| Optional                                     | `truncation_tolerance`__ | Specify the maximum percentage (as a decimal) |
|                                              |                          | of the eigenvalue energy not captured by the  |
|                                              |                          | active subspace representation.               |
+----------------------------------------------+--------------------------+-----------------------------------------------+

.. __: model-active_subspace-truncation_method-energy-truncation_tolerance.html



**Description**


Uses a criterion based on the derivative matrix eigenvalue energy.

*Usage Tips*

This subspace truncation method may work best when working with non-normally
distributed uncertain variables. If this automated diagnostic does not yield
desirable results, consider using the explicit :dakkw:`model-active_subspace-dimension` truncation option or
one of the other truncation methods.



**Theory**


Using the eigenvalue energy truncation metric, the subspace size is determined using the following equation:

.. math:: n = \inf \left\lbrace d \in \mathbf{Z} \quad\middle|\quad 1 \le d \le N \quad \wedge\quad 1 - \frac{\sum_{i = 1}^{d} \lambda_i}{\sum_{i = 1}^{N} \lambda_i} \,<\, \epsilon \right\rbrace 

where :math:`\epsilon`  is the :dakkw:`model-active_subspace-truncation_method-energy-truncation_tolerance`, :math:`n`  is the estimated subspace size, :math:`N`  is the size of the full space, and :math:`\lambda_i`  are the eigenvalues of the derivative matrix.