Wednesday, July 25, 2012

So long as my eigenvalue is always 1, just fine.

How well do you function in a matrixed environment?

Before I get to talking about eigenvalues and eigenvectors, I suggest checking out 27 Agile Things to Do Before You're Fired.  Great list.  I don't know that I can agree with all of them working for a big company, but every single one of them at least creates discussion around why things are the way they are, and how they could be better.  When it comes to offices, I'm not a fan.  I try to give mine away as often as I can and sit in the colocated areas with the developers and ops.

If you're unfamiliar with an eigenvalue, Wikipedia has a good entry.  "The eigenvectors of a square matrix are the non-zero vectors that, after being multiplied by the matrix, remain parallel to the original vector. For each eigenvector, the corresponding eigenvalue is the factor by which the eigenvector is scaled when multiplied by the matrix."

Oof, not much clearer for the clear speaking.  I think it sums it up nicely when it gets to: "In such cases, the concept of direction loses its ordinary meaning."  That's almost a punchline all by itself.

But to get to the gist of this humor, which was created by my co-snarkist:
"As a special case, the identity matrix I is the matrix that leaves all vectors unchanged: Ix = 1x = x.  Every non-zero vector x is an eigenvector of the identity matrix with eigenvalue 1."

And if you still don't get it (hopefully my wife doesn't find me condescending), the real problem with matrixed (matriced) environments is that a.) your eigenvalue is never one and b.) your output trends closer to 0.  I recommend Brooks' Mythical Man Month even to non-development folks.

Title: So long as my eigenvalue is always 1, just fine.
Snarky: How well do you function in a matrixed environment?

1 comment:

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