Skip to content

Latest commit

 

History

History
118 lines (91 loc) · 3.17 KB

02-scripts.md

File metadata and controls

118 lines (91 loc) · 3.17 KB
layout title subtitle minutes
page
Programming with MATLAB
Writing MATLAB Scripts
30

Learning Objectives {.objectives}

  • Learn how to write and save MATLAB scripts.
  • Learn how to save MATLAB plots to disk.

So far, we've typed in commands one-by-one on the command line to get MATLAB to do things for us. But what if we want to repeat our analysis? Sure, it's only a handful of commands, and typing them in shouldn't take us more than a few minutes. But if we forget a step or make a mistake, we'll waste time rewriting commands. Also, we'll quickly find ourselves doing more complex analyses, and we'll need our results to be more easily reproducible.

In addition to running MATLAB commands one-by-one on the command line, we can also write several commands in a script. A MATLAB script is just a text file with a .m extension. We've written commands to load data from a .csv file and displays some statistics about that data. Let's put those commands in a script called analyze.m:

% script analyze.m

patient_data = csvread('inflammation-01.csv');

disp(['Analyzing "inflammation-01.csv": '])
disp(['Maximum inflammation: ', num2str(max(patient_data(:)))]);
disp(['Minimum inflammation: ', num2str(min(patient_data(:)))]);
disp(['Standard deviation: ', num2str(std(patient_data(:)))]);

Before we can use it, we need to make sure that this file is visible to MATLAB. MATLAB doesn't know about all the files on your computer, but it keeps an eye on several directories. The most convenient of these directories is generally the "working directory", or "current directory". To find out the working directory, use the pwd command:

pwd

As you might have guessed, pwd stands for "print working directory".

Once you have a script saved in a location that MATLAB knows about, you can get MATLAB to run those commands by typing in the name of the script (without the .m) in the MATLAB command line:

analyze
Maximum inflammation: 20
Minimum inflammation: 0
Standard deviation: 4.7219

We've also written commands to create plots:

ave_inflammation = mean(patient_data, 1);

plot(ave_inflammation);
ylabel('average')

MATLAB let's us save those as images on disk:

% save plot to disk as png image:
print -dpng 'average.png'

You might have noticed that we described what we want our code to do using the %-sign. This is another plus of writing scripts: you can comment your code to make it easier to understand when you come back to it after a while.

Let's extend our analyze script with commands to create and save plots:

% script analyze.m

patient_data = csvread('inflammation-01.csv');

disp(['Maximum inflammation: ', num2str(max(patient_data(:)))]);
disp(['Minimum inflammation: ', num2str(min(patient_data(:)))]);
disp(['Standard deviation: ', num2str(std(patient_data(:)))]);

ave_inflammation = mean(patient_data, 1);

subplot(1, 3, 1);
plot(ave_inflammation);
ylabel('average')

subplot(1, 3, 2);
plot(max(patient_data, [], 1));
ylabel('max')

subplot(1, 3, 3);
plot(min(patient_data, [], 1));
ylabel('min')

% save plot to disk as png image:
print -dpng 'patient_data-01.png'