3. Functions

Functions are one of the most useful programming facilities that you will run into because they allow you to make your code more modular. We have seen functions already, for example functions to print stuff to the screen like print() in Python, and disp() in MATLAB, functions for mathematics like sqrt(), and so on. The advantage of putting things like these into functions is that we avoid the need to write everything from scratch each time we want to repeat a common operation. Imagine if every time we wanted to take the square root of a number, we had to write an entire algorithm (like Newton's method) to do so. It would be ridiculous. By encapsulating this operation into a function, all we need to do is write sqrt() and the program goes and looks up the definition of that function, and executes that code, without us having to type it in again, and again.

Here we will be going through how to write our own functions to encapsulate our own operations, whatever they may be.

You can even imagine a series of functions that you write to perform the various steps of your data analysis, so that each time you collect more data in your experiment, you simply have to type:

go_my_analysis()

… and all of your data analysis will be repeated, including the incorporation of any new data that may be residing in your data directory. Of course you have to define what happens inside of go_my_analysis() for this to be useful. Maybe inside your go_my_analysis() function you have defined other functions like:

load_all_data()
filter_data()
average_across_subjects()
perform_statistics()
generate_plots()
save_processed_data()

You get the idea.

The other situation where modularity in your code is useful, is for when you want to share code with other people (or use someone else's code). If you (or someone else) has a specific input/output functionality in mind, then you can swap in and out one of many potential functions that claim to achieve the desired functionality, as long as it preserves the input/output relationship(s) that you specify.

For example, let's say you discover that as part of your data analysis you will need to compute the square root of a number, and let's pretend that you don't have a function to do so built in to your language. (In fact you do of course … but for the purpose of this thought experiment let's imagine you don't.) The input/output requirements for your square root function are that it takes as input a single floating-point number and returns a single floating point number. Now you can go shopping, among your friends, colleagues, or on the internet, for an implementation of the square root function, and you can simply plug it in to your program and use it, as long as it takes a single floating-point number as input, and returns a single floating-point number as output. This specification is sometimes called the function prototype. You might find that several functions that you have found work equally well in terms of returning the correct answer, but that one in particular is way faster than the rest (perhaps it was written by a mathematician who knows some clever numerical tricks).

Concepts that you should focus on in your readings, and that we will talk about in class, include:

• how to define a function in your language of choice
• specifying input arguments
• specifying output arguments (return value(s))
• variable scope
• recursion