Programming with Matlab

Writing MATLAB Scripts

Overview

Teaching: 30 min
Exercises: 0 min
Questions
  • How can I save and re-use my programs?

Objectives
  • Write and save MATLAB scripts.

  • 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('data/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 (print working directory) command:

pwd

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: 4.6148

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 ('average','-dpng')

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 ('patient_data-01','-dpng')

When saving plots to disk, it’s a good idea to turn off their visibility as MATLAB plots them. Let’s add a couple of lines of code to do this:

% 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);

figure('visible', 'off')

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 ('patient_data-01','-dpng')

close()

If we call the figure function without any options, MATLAB will open up an empty figure window. Try this on the command line:

figure()

We can ask MATLAB to create an empty figure window without displaying it by setting its 'visible' property to 'off', like so:

figure('visible', 'off')

When we do this, we have to be careful to manually “close” the figure after we are doing plotting on it - the same as we would “close” an actual figure window if it were open:

close()

Key Points