Technical Art Math Series: An Introduction and Overview.

The Big Lie

Let's talk about one of the biggest lies in programming. At least one that I've heard in my career quite a lot. "You don't need to know, or be good at, math in order to write code." This was the hook I heard constantly from all of my programming instructors in college. I can definitely understand why this is the case. Math can be an intimidating subject to tackle. One of my favorite memories in college was walking into my academic advisor's office and asking to be enrolled in the Linear Algebra class, even though it wasn't required for me. The bewildered look on my advisor's face was priceless.

Obligatory anecdotes aside. There is good news for those of us that aren't so great at math. We don't need to know how to apply L'Hôpital's rule. We don't even need to know every intricate detail of Principle Component Analysis. As long as we have working knowledge of the math concepts, we can make the software do most of the hard work for us.

That being said. I thought it would be an interesting idea to delve into some different math concepts. I will be writing a series of articles that will explore fundamental math concepts and how they're applied to technical art. We'll start small with the language of math, and how Maya is based on set and graph theory. Then we'll work our way up to to more complex applications such as Matrix math.

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Let's let's look at the timeline. So we can see the progression of things to come.

The Language of Math and Maya

1. Part I: Set Theory

2. Part II: Graph Theory

3. Part II: More Graph Theory (Maya's Lazy Evaluation.)

Applied Vector Math and Maya

1. Part I: Basic Vector Math & Auto Rigging Applications.

2. Part II: Vector Dot Product Applications.

3. Part III: Vector Cross Product Applications.

Applied Trigonometry

1. Part I: Using Trig Functions in Maya

2. Part II: Euler to Quaternion

Applied Matrix Math

1. Part I: Maya's 4x4 Matrix

2. Part II: Understanding Matrix Rotations

3. Part III: Matrix Node Applications I

4. Part IV: Matrix Node Applications II

Quaternions: The Hypercomplex Rotation

1. Part I: The Fundamentals of Rotation

2. Part II: Quaternion Applications

Applied Advanced Matrix Math:

1. Part I: Matrix multiplication: A∙X = B

It's going to be an interesting journey writing these articles. As well as re teaching myself some of these concepts on a deeper level. Perhaps this is just an extremely elaborate excuse to teach myself more math even after college.