It may take a few minutes to download and install the necessary packages.

Enter the commands

using EigenShow
eigenshow()

(The using command is needed only once per Julia session.) After 20 seconds or so, a new window should open with the demonstrator. It runs independently and can simply be closed when you are done with it.

In EVD mode. Initially you see a vector $x$ on the unit circle and, in a different color, the vector $Ax$ resulting from matrix-vector multiplication using the current matrix $A$ chosen in the selection box. As you move the mouse, $x$ moves around the unit circle and $Ax$ traces out an ellipse (or, in a degenerate case, a line segment). When $Ax$ is parallel to $x$, then $x$ is an eigenvector of $A$, and the (signed) ratio of the vector lengths is the associated eigenvalue. When $x$ is an eigenvector, so is $-x$. The matrix may have zero, one, or two distinct real eigenvectors.

In SVD mode. As you move the mouse, a perpendicular pair of vectors $x,y$ move around the unit circle. In a different color, you also see $Ax$ and $Ay$ for the current matrix $A$ chosen in the selection box. When $Ax$ and $Ay$ are perpendicular to each other, then $x$ and $y$ are right singular vectors of $A$, $Ax$ and $Ay$ are left singular vectors of $A$, and the (unsigned) ratios of lengths of $Ax$ to $x$ and $Ay$ to $y$ are associated singular values. Aside from the trivial duplications $x ↦ -x$ and $y ↦ -y$, every real $2\times 2$ matrix has a unique pair of real right singular vectors.

In either mode, you can click the mouse button to mark a point for future reference.

Acknowledgement

This function is inspired by EIGSHOW.M, which is held in copyright by The MathWorks, Inc and found at:
Cleve Moler (2021), Cleve_Lab, MATLAB Central File Exchange. Retrieved October 25, 2021.

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