Blurb::
Truncate the subspace based on eigenvalue energy
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.
Topics::

Examples::

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.
Faq::

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