In our previous post we reviewed how to apply the DRY principle (don’t repeat yourself) to our code and we learned how to create Python modules to avoid repeating ourselves (i.e. cutting-and-pasting code) across scripts and programs. In this post we will see how we can use our modules as a stand-alone program as well as useful functions that can
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We previously learned to create our own Python functions to reduce how much we repeat ourselves in our code. In this post we see another example of the DRY principle (don’t repeat yourself) and we will learn how to ensure we don’t repeat ourselves between the different programs we write. A typical (bad) script to process data Below is an
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Learning to program is not easy. We have to learn a new language and a new way of thinking. We have to learn the grammatical rules of the programming language we are learning, and the logic of our program, how it will work its way through the code and hopefully give us the answer we expect. In this post we
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Sometimes when we plot data we want to indicate a relevant feature or have a user select a section of the data. For example, if we record electromyography (EMG) and force signals, we might want to have the user mark the baseline EMG level so that it can be removed, and determine the amount of EMG produced during a maximum
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We had a short intro to functions and understand that a function works with variables defined inside or outside it. Now, let’s write a function to help with data analysis. I needed to analyse data from 3 people who had a stroke. The way these data are structured can be typical of experimental studies (on humans): each subject has a
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We last saw how to write a function in Python. Let’s take a step back to consider how a function works with variables provided to it. Functions can accept input values and return new values. In Python, input values are passed into the function using local variables inserted in the parentheses (). For example, the fahr_to_kelvin() function below receives the
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Scientifically Sound 