Writing MATLAB Scripts
Last updated on 2023-08-21 | Edit this page
Estimated time: 35 minutes
Overview
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, compute
statistics of the data and display some plots about that data. Let’s put
those commands in a script called patient_analysis.m, which
we’ll save in the src directory in our current
folder,matlab-novice-inflammation.
To create a new script we can click the “New script” button on the top left, or use the command:
Matlab will create a file called patient_analysis.m in
the src folder. It is important that we let matlab know
that we want it to find stuff in this folder. To do this, right click on
the folder icon in the file browser and select “Add to Path”.
The MATLAB path
MATLAB knows about files in the current directory, but if we want to run a script saved in a different location, we need to make sure that this file is visible to MATLAB. We do this by adding directories to the MATLAB path. The path is a list of directories MATLAB will search through to locate files.
To add a directory to the MATLAB path, we go to the Home
tab, click on Set Path, and then on
Add with Subfolders.... We navigate to the directory and
add it to the path to tell MATLAB where to look for our files. When you
refer to a file (either code or data), MATLAB will search all the
directories in the path to find it. Alternatively, for data files, we
can provide the relative or absolute file path.
GNU Octave
Octave has only recently gained a MATLAB-like user interface. To
change the path in any version of Octave, including command-line-only
installations, use addpath('path/to/directory')
We can now type the contents of the script:
MATLAB
% Load patient data
patient_data = readmatrix('data/inflammation-01.csv');
% Compute global statistics
g_mean = mean(patient_data(:));
g_max = max(patient_data(:));
g_min = min(patient_data(:));
% Compute patient statistics
p_mean = mean(patient_data(5,:));
p_max = max(patient_data(5,:));
p_min = min(patient_data(5,:));
% Compare patient vs global
disp('Patient 5:')
disp('High mean?')
disp(p_mean > g_mean)
disp('Highest max?')
disp(p_max == g_max)
disp('Lowest min?')
disp(p_min == g_min)Now, before running this script lets clear our workplace so that we can see what is happening.
If you now run the script by clicking “Run” on the graphical user
interface, pressing F5 on the keyboard, or typing the
script’s name patient_analysis on the command line (without
extention), you’ll see a bunch of variables appear on the workspace and
this output:
OUTPUT
Patient 5:
High mean?
0
Highest max?
0
Lowest min?
1Remember, we supressed most outputs with ;, so the only
lines printed are the ones with disp.
As you can see, the script ran every line of code in the script in
order, and created any variable we asked for. Having the code in the
script makes it much easier to follow what we are doing, and also make
changes. For example, if we now want to look at patient 8, all we need
to do is change the number in lines 10, 11 and 12. We can actually do a
bit better, and replace that number for a variable
patient_number. This variable needs to exist before it is
used, so lets insert it before computing the patient statistics, like
so:
MATLAB
% Load patient data
patient_data = readmatrix('data/inflammation-01.csv');
% Compute global statistics
g_mean = mean(patient_data(:));
g_max = max(patient_data(:));
g_min = min(patient_data(:));
patient_number = 8;
% Compute patient statistics
p_mean = mean(patient_data(patient_number,:));
p_max = max(patient_data(patient_number,:));
p_min = min(patient_data(patient_number,:));
% Compare patient vs global
disp('Patient:')
disp(patient_number)
disp('High mean?')
disp(p_mean > g_mean)
disp('Highest max?')
disp(p_max == g_max)
disp('Lowest min?')
disp(p_min == g_min)Note that we also changed the disp commands to show the right patient number.
Getting the results for whichever patient is now as simple as
changing the value of patient_number.
For the case of patient 8, we get:
OUTPUT
Patient 8:
High mean?
1
Highest max?
1
Lowest min?
1Help text
You might have noticed that we described what we want our code to do
using the percent 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.
A comment can appear on any line, but be aware that the first line or
block of comments in a script or function is used by MATLAB as the
help text. When we use the help command,
MATLAB returns the help text. The first help text line (known
as the H1 line) typically includes the name of the
program, and a brief description. The help command works in
just the same way for our own programs as for built-in MATLAB functions.
You should write help text for all of your own scripts and
functions.
Let’s write an H1 line at the top of our script:
MATLAB
% PATIENT_ANALYSIS Computes mean, max and min of a patient and compares to global statistics.We can then get help for our script by running
OUTPUT
patient_analysis Computes mean, max and min of a patient and compares to global statistics.Script for plotting
Of course, our scripts can be as complicated as we like. There were a lot of commands involved with plotting, so lets try and put that in a script.
Create a new script in the current directory called
plot_daily_average.m
In the script, lets recap what we need to do:
MATLAB
% PLOT_DAILY_AVERAGE Plots daily average inflammation accross patients.
% Load patient data
patient_data = readmatrix('data/inflammation-01.csv');
figure
% Plot average inflammation per day
plot(mean(patient_data, 1))
title('Daily average inflammation')
xlabel('Day of trial')
ylabel('Inflammation')Note that we are explicitly creating a new figure window using the
figure command.
Try this on the command line:
MATLAB’s plotting commands only create a new figure window if one doesn’t already exist: the default behaviour is to reuse the current figure window as we saw in the previous episode. Explicitly creating a new figure window in the script avoids any unexpected results from plotting on top of existing figures.
Now lets run the script:
You should see the figure appear.
Let’s modify our plot_daily_average script so that it
creates sub-plots, rather than individual plots.
MATLAB
% PLOT_DAILY_AVERAGE Plots daily average, max and min inflammation accross patients.
% Load patient data
patient_data = readmatrix('data/inflammation-01.csv');
figure
% Plot average inflammation per day
subplot(1, 3, 1)
plot(mean(patient_data, 1))
title('Daily average inflammation')
xlabel('Day of trial')
ylabel('Inflammation')
% Plot max inflammation per day
subplot(1, 3, 2)
plot(max(patient_data, [], 1))
title('Max')
ylabel('Inflammation')
xlabel('Day of trial')
% Plot min inflammation per day
subplot(1, 3, 3)
plot(min(patient_data, [], 1))
title('Min')
ylabel('Inflammation')
xlabel('Day of trial')The script now allows us to create all 3 plots with a single command:
plot_daily_average.
We can ask matlab to save the image too using the print
command. In order to maintain an organised project we’ll save the images
in the results directory:
Callout
Note:
If you have a printer configured on your computer the
print command may send it to the printer. You can instead
use saveas, which requiere two arguments: a figure and a
filename. You can get the current figure with gcf, and
specify the filename with an extension, like so:
When saving plots to disk, it’s sometimes useful to turn off their visibility as MATLAB plots them. For example, we might not want to view (or spend time closing) the figures in MATLAB, and not displaying the figures could make the script run faster.
Let’s add a couple of lines of code to do this.
We can ask MATLAB to create an empty figure window without displaying
it by setting its 'visible' property to 'off',
like so:
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:
Adding these two lines, our finished script looks like this:
MATLAB
% PLOT_DAILY_AVERAGE Saves plot of daily average, max and min inflammation accross patients.
% Load patient data
patient_data = readmatrix('data/inflammation-01.csv');
figure('visible', 'off')
% Plot average inflammation per day
subplot(1, 3, 1)
plot(mean(patient_data, 1))
title('Daily average inflammation')
xlabel('Day of trial')
ylabel('Inflammation')
% Plot max inflammation per day
subplot(1, 3, 2)
plot(max(patient_data, [], 1))
title('Max')
ylabel('Inflammation')
xlabel('Day of trial')
% Plot min inflammation per day
subplot(1, 3, 3)
plot(min(patient_data, [], 1))
title('Min')
ylabel('Inflammation')
xlabel('Day of trial')
% Save plot in 'results' folder as png image:
saveas(gcf,'results/daily_average_01.png')
close()The scripts we’ve written make regenerating plots easier, and looking at individual patient’s data much simpler, but we still need to open the script, change the patient number, save, and run. In contrast, when we have used functions we can provide arguments, which are then used to do something. So, can we create our own functions?
Key Points
- “Save MATLAB code in files with a
.msuffix.”