Add a Matrix Diagonalization node (

) under
Definitions >
Variable Utilities (if
Group by Type is active; otherwise, directly under
Definitions) to define variables representing the diagonalization of a symmetric 3-by-3 input matrix. You add it by right-clicking the
Definitions node and choosing
Variable Utilities >
Matrix Diagonalization or by right-clicking the
Variable Utilities node and choosing
Matrix Diagonalization.
You can also add a global Matrix Diagonalization under
Global Definitions >
Variable Utilities (if
Group by Type is active; otherwise, directly under
Global Definitions). In the global context, the
Matrix Diagonalization node has no selection. The eigenvalue and eigenvector variables are defined globally but the diagonalization is done locally, for each point where the variables are evaluated. The input matrix therefore does not have to depend only on constants and global variables. Its expressions will be evaluated at each evaluation point.
You can define a Label for the node, and a namespace for variables using the
Name field. For the
Geometric Entity Selection, see
About Selecting Geometric Entities.
In addition, the Settings window for a
Matrix Diagonalization node contains the following sections:
Select the Compute exponential checkbox to compute also the matrix
eT, where
T is the input matrix.
Select the Ignore Jacobian contributions checkbox (selected by default) to ignore any solution dependencies during the solution process.
The principal values become available as variables <name>.e<i>, where
<name> is the namespace set in the
Name field, and
<i> is the principal component index, ordered from largest to smallest absolute value. Components of the corresponding principal vectors are called
<name>.e<i><j>, where
<j> are integer indices. If
Compute exponential was selected, the result can be evaluated as a list of variables with names
<name>.expT<i><j>. The input matrix with names
<name>.T<i><j>, as well as its determinant
<name>.detT are also made available. Note that the determinant is not computed for matrices of size 4-by-4 or larger; if required, use a
Matrix Decomposition node instead.
You can use individual components where variable expressions are allowed, but also evaluate complete vectors and matrices at once using a matrix evaluation node under Derived Values. For example, to evaluate the first principal vector, select
matdiag1.e1_vec under
Model >
Component 1 >
Definitions >
Matrix Diagonalization 1 >
Principal vector 1 if the node has been defined as
Matrix Diagonalization 1 with the name
matdiag1 in
Component 1.