Section 7.3 Multidimensional Arrays
In the first two sections of this chapter on arrays, we’ve encountered one-dimensional arrays (sometimes referred to as vectors), and two-dimensional arrays (often referred to as matrices). Arrays are important structures in mathematics and also in computing. We’ve spent our time focused on operations which can be done with arrays and some example implementations of algorithms that compute those operations. We’ve ignored the technical aspects of arrays from a computer science perspective since you’ll get that exposure in computer science coursework.
Before we exit this chapter, its worth mentioning that multidimensional arrays (arrays with more than just rows and columns) exist and find lots of uses in the real world. For example, a three-dimensional array is requird to define the colors of the pixels on your computer monitor right now. You can think of such an array as containing a matrix for the red channel, another matrix for the green channel, and a third matrix for the blue channel. Perhaps there is a fourth matrix governing the opacity (equivalently, the level of transparency) of the pixel. This is often referred to as an alpha channel.
These multidimensional arrays find uses elsewhere too. Perhaps you’ve heard of machine learning, where some classes of model, like Long Short-Term Memory (LSTM) models, require these multidimensional arrays (sometimes called tensors) as inputs. Arrays are important data structures, and you’ll be making lots of use of them in your future coursework and computing endeavours.
