Repeating With Loops
Overview
Teaching: 40 min
Exercises: 10 minQuestions
How can I repeat the same operations on multiple values?
Objectives
Explain what a for loop does.
Correctly write for loops that repeat simple commands.
Trace changes to a loop variable as the loops runs.
Use a for loop to process multiple files
Recall that we have to do this analysis for every one of our dozen datasets, and we need a better way than typing out commands for each one, because we’ll find ourselves writing a lot of duplicate code. Remember, code that is repeated in two or more places will eventually be wrong in at least one. Also, if we make changes in the way we analyze our datasets, we have to introduce that change in every copy of our code. To avoid all of this repetition, we have to teach MATLAB to repeat our commands, and to do that, we have to learn how to write loops.
Suppose we want to print each character in the word “lead” on
a line of its own. One way is to use four disp
statements:
%LOOP_DEMO Demo script to explain loops
word = 'lead';
disp(word(1))
disp(word(2))
disp(word(3))
disp(word(4))
l
e
a
d
But this is a bad approach for two reasons:
-
It doesn’t scale: if we want to print the characters in a string that’s hundreds of letters long, we’d be better off typing them in.
-
It’s fragile: if we change
word
to a longer string, it only prints part of the data, and if we change it to a shorter one, it produces an error, because we’re asking for characters that don’t exist.
%LOOP_DEMO Demo script to explain loops
word = 'tin';
disp(word(1))
disp(word(2))
disp(word(3))
disp(word(4))
error: A(I): index out of bounds; value 4 out of bound 3
There’s a better approach:
%LOOP_DEMO Demo script to explain loops
word = 'lead';
for letter = 1:4
disp(word(letter))
end
l
e
a
d
This improved version uses a for loop to repeat an operation—in this case, printing to the screen—once for each element in an array.
The general form of a for loop is:
for variable = collection
do things with variable
end
The for loop executes the commands in the
loop body
for every value in the array collection
.
This value is called the loop variable,
and we can call it whatever we like.
In our example, we gave it the name letter
.
We have to terminate the loop body with the end
keyword,
and we can have as many commands as we like in the loop body.
But, we have to remember
that they will all be repeated as many times as
there are values in collection
.
Our for loop has made our code more scalable, and less fragile. There’s still one little thing about it that should bother us. For our loop to deal appropriately with shorter or longer words, we have to change the first line of our loop by hand:
%LOOP_DEMO Demo script to explain loops
word = 'tin';
for letter = 1:3
disp(word(letter))
end
t
i
n
Although this works, it’s not the best way to write our loop:
-
We might update
word
and forget to modify the loop to reflect that change. -
We might make a mistake while counting the number of letters in
word
.
Fortunately, MATLAB provides us with a convenient function to write a better loop:
%LOOP_DEMO Demo script to explain loops
word = 'aluminum';
for letter = 1:length(word)
disp(word(letter))
end
a
l
u
m
i
n
u
m
This is much more robust code,
as it can deal identically with
words of arbitrary length.
Here’s another loop that
repeatedly updates the variable len
:
%LOOP_DEMO Demo script to explain loops
len = 0
for vowel = 'aeiou'
len = len + 1;
end
disp(['Number of vowels: ', num2str(len)])
It’s worth tracing the execution of this little program step by step.
The debugger
We can use the MATLAB debugger to trace the execution of a program.
The first step is to set a break point by clicking just to the right of a line number on the
-
symbol. A red circle will appear — this is the break point, and when we run the script, MATLAB will pause execution at that line.A green arrow appears, pointing to the next line to be run. To continue running the program one line at a time, we use the
step
button.We can then inspect variables in the workspace or by hovering the cursor over where they appear in the code, or get MATLAB to evaluate expressions in the command window (notice the prompt changes to
K>>
).This process is useful to check your understanding of a program, in order to correct mistakes.
This process is illustrated below:
Since there are five characters in “aeiou”,
the loop body will be executed five times.
When we enter the loop, len
is zero -
the value assigned to it beforehand.
The first time through,
the loop body adds 1 to the old value of len
,
producing 1,
and updates len
to refer to that new value.
The next time around,
vowel
is e
,
and len
is 1,
so len
is updated to 2.
After three more updates,
len
is 5;
since there’s nothing left in aeiou
for MATLAB to process,
the loop finishes and the disp
statement tells us our final answer.
Note that a loop variable is just a variable that’s being used to record progress in a loop. It still exists after the loop is over, and we can re-use variables previously defined as loop variables as well:
>> disp(vowel)
u
Performing Exponentiation
MATLAB uses the caret (
^
) to perform exponentiation:>> disp(5^3)
125
You can also use a loop to perform exponentiation. Remember that
b^x
is justb*b*b*
…x
times.Let a variable
b
be the base of the number andx
the exponent. Write a loop to computeb^x
. Check your result forb = 4
andx = 5
.Solution
% Loop to perform exponentiation b = 4; % base x = 5; % exponent result=1; for i = 1:x result = result * b; end disp([num2str(b), '^', num2str(x), ' = ', num2str(result)])
Incrementing with Loops
Write a loop that spells the word “aluminum,” adding one letter at a time:
a al alu alum alumi alumin aluminu aluminum
Solution
% spell a string adding one letter at a time using a loop word = 'aluminium'; for letter = 1:length(word) disp(word(1:letter)) end
Looping in Reverse
In MATLAB, the colon operator (
:
) accepts a stride or skip argument between the start and stop:>> disp(1:3:11)
1 4 7 10
>> disp(11:-3:1)
11 8 5 2
Using this, write a loop to print the letters of “aluminum” in reverse order, one letter per line.
m u n i m u l a
Solution
% Spell a string in reverse using a loop word = 'aluminium'; for letter = length(word):-1:1 disp(word(letter)) end
Analyzing patient data from multiple files
We now have almost everything we need to process
multiple data files with our analyze
script.
We need to generate a list of data files to process, and then we can use a loop to repeat the analysis for each file.
We can use the dir
command to return a structure array containing
the names of the files in the data
directory.
Each element in this structure array is a structure, containing
information about a single file in the form of named fields.
>> files = dir('data/inflammation-*.csv')
files =
12×1 struct array with fields:
name
folder
date
bytes
isdir
datenum
To access the name field of the first file, we can use the following syntax:
>> filename = files(1).name;
>> disp(filename)
inflammation-01.csv
To get the modification date of the third file, we can do:
>> mod_date = files(3).date;
>> disp(mod_date)
26-Jul-2015 22:24:31
A good first step towards processing multiple files is to write a loop which prints
the name of each of our files.
Let’s write this in a temporary script temp.m
so that it’s easier to develop further:
%TEMP Developing code to automate inflammation analysis
files = dir('data/inflammation-*.csv');
for i = 1:length(files)
file_name = files(i).name;
disp(file_name)
end
>> temp
inflammation-01.csv
inflammation-02.csv
inflammation-03.csv
inflammation-04.csv
inflammation-05.csv
inflammation-06.csv
inflammation-07.csv
inflammation-08.csv
inflammation-09.csv
inflammation-10.csv
inflammation-11.csv
inflammation-12.csv
Another task is to generate the file names for the figures we’re going to save.
Let’s name the output file after the data file used to generate the figure.
So for the data set inflammation-01.csv
we will call the figure inflammation-01.png
.
We can use the replace
command for this purpose.
The syntax for the replace
command is like this:
NEWSTR = replace(STR, OLD, NEW)
So for example if we have the string big_shark
and want to get the string
terror_shark
, we can execute the following command:
>> new_string = replace('big_shark', 'big', 'terror');
>> disp(new_string)
terror_shark
GNU Octave
In Octave, the
replace
function doesn’t exist, but thestrrep
function is a direct replacement. The above example becomes>> new_string = strep('big_shark', 'big', 'terror') terror_shark
Recall that we’re saving our figures to the results
directory.
The best way to generate a path to a file in MATLAB is by using the fullfile
command.
This generates a file path with the correct separators for the platform you’re using
(i.e. forward slash for Linux and macOS, and backslash for Windows).
This makes your code more portable which is great for collaboration.
Putting these concepts together, we can now generate the paths for the data files, and the image files we want to save:
%TEMP Developing code to automate inflammation analysis
files = dir('data/inflammation-*.csv');
for i = 1:length(files)
file_name = files(i).name;
% Generate string for image name
img_name = replace(file_name, '.csv', '.png');
% Generate path to data file and image file
file_name = fullfile('data', file_name);
img_name = fullfile('results',img_name);
disp(file_name)
disp(img_name)
end
data/inflammation-01.csv
results/inflammation-01.png
data/inflammation-02.csv
results/inflammation-02.png
data/inflammation-03.csv
results/inflammation-03.png
data/inflammation-04.csv
results/inflammation-04.png
data/inflammation-05.csv
results/inflammation-05.png
data/inflammation-06.csv
results/inflammation-06.png
data/inflammation-07.csv
results/inflammation-07.png
data/inflammation-08.csv
results/inflammation-08.png
data/inflammation-09.csv
results/inflammation-09.png
data/inflammation-10.csv
results/inflammation-10.png
data/inflammation-11.csv
results/inflammation-11.png
data/inflammation-12.csv
results/inflammation-12.png
We’re now ready to modify analyze.m
to process multiple data files:
%ANALYZE Print statistics for all patients.
% Save plots of statistics to disk.
files = dir('data/inflammation-*.csv');
% Process each file in turn
for i = 1:length(files)
file_name = files(i).name;
% Generate strings for image names:
img_name = replace(file_name, '.csv', '.png');
% Generate path to data file and image file
file_name = fullfile('data', file_name);
img_name = fullfile('results', img_name);
patient_data = csvread(file_name);
% Create figures
figure('visible', 'off')
subplot(2, 2, 1)
plot(mean(patient_data, 1))
title('Average')
ylabel('Inflammation')
xlabel('Day')
subplot(2, 2, 2)
plot(max(patient_data, [], 1))
title('Max')
ylabel('Inflammation')
xlabel('Day')
subplot(2, 2, 3)
plot(min(patient_data, [], 1))
title('Min')
ylabel('Inflammation')
xlabel('Day')
print(img_name, '-dpng')
close()
end
We run the modified script using its name in the Command Window:
>> analyze
The first three figures output to the results
directory are as shown below:
Sure enough, the maxima of these data sets show exactly the same ramp as the first, and their minima show the same staircase structure.
We’ve now automated the analysis and have confirmed that all the data files we have looked at show the same artifact. This is what we set out to test, and now we can just call one script to do it. With minor modifications, this script could be re-used to check all our future data files.
Key Points
Use
for
to create a loop that repeats one or more operations.