1. Introduction to MATLAB
Session 1
Getting started
Mihaela Duta
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

2. Recommended bibliography
“Matlab Guide” – D. Higham and N. Higham,
“Matlab primer” – A. Davis
“A Guide to MATLAB: For Beginners and Experienced Users”, B. Hunt, R. Lipsman and J. Rosenberg
“Essential MATLAB for Scientists and Engineers” – B.Hahn
“Numerical Methods in Finance: A MATLAB-based Introduction ”, P. Brandimarte
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

3. Need more help? mihaela.duta@maths.ox.ac.uk www.mathworks.com
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

4. Today’s topics Programming basics MATLAB background
Development environment
Scripts and functions
Data types
Matrices
Arithmetical operators
Interfacing with the OS
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

5. Programming language
An artificial language used to control the behaviour of a computer, in order to manipulate information and express algorithms.
Structure and meaning is determined with
syntactic rules
semantic rules
respectively.
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

6. Semantics/syntax Semantics reflects the meaning of programs Syntax:
the set of allowed reserved words and possible order of instructions in a program
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

7. Algorithm
A procedure defined as a finite set of well-defined instructions for accomplishing some task – recipe
Implemented as functions
They often have
iterations - repetitions of a process: loops
conditionals - execution choices based on a given condition: conditional statements
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

8. MATLAB background Very powerful tool for technical computing
Integrates
Computation
Visualisation
Programming
Interactive and easy to use
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

9. MATLAB short history Cleve Moler invented MATLAB in late ’70s
Very popular within the applied maths community
Joined by Jack Little and Steve Bangart to
rewrite MATLAB in C
found Mathworks in 1984
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

10. Application Program Interface (API)
Overview
Development Environment
Command window
Editor/Debugger
Browsers (help etc)
Application Program Interface (API)
The MATLAB system
Graphics
Talk through the slide
The MATLAB language
Function library
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

11. The development environment
Collection of graphical windows
Command line window
Editor/Debugger
Browsers for help, workspace, commands history, directory
Apart from command line window, all the other are optional – everything can be done in the command window
Let’s have a look now at what has MATLAB environment to offer.
Open MATLAB
Discuss initial desktop configuration
Name and describe briefly each visible window
Show how you can type commands
Show how one can customize the desktop by adding/removing windows
Open the browser and point out that the studentsare supposed to make full use of help when solving the exercises
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

12. The Workspace Accumulates variables handled in a session
Can be manipulated from
Workspace browser
Command line
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

13. Scripts Collection of MATLAB statements Stored in a .m file
They runs in the same memory area with the main MATLAB session:
Use variables from the workspace
Changes made to the workspace remain after script finishes
Give operators example.
Show workspace contents before and after
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

14. Functions Collections of MATLAB statements Syntax for declaration
function [output args] = fname(input args)
Run in a separate memory space than the main MATLAB session:
does not have access to the callers workspace
changes made to variables are local
variables passed via input/output arguments
Same example with operators
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

15. Code comments Any text starting following %
Recommend – document all code while implementing it
Example:
function umax = exmax(u1,u2)
% function exmax(u1,u2)
% analytic extension of real max function
sw = real(u1) > real(u2);
umax = sw.*u1 + (1-sw).*u2;
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

16. Data types Basic: Numerical Logical Strings Advanced: Cell arrays
stored floating-point double-precision ( “double ) – a format that occupies two storage locations in computer memory
e.g. >> a = 3.14;
format: controls the way numerical variables are echoed in the command window
Logical
>> a = true;
Strings
>> a = 'Some text' ;
Advanced:
Cell arrays
>> a = {'Text' , [1 2 3], [true false]};
Structures
>> a.location = 'Oxford'; a.date = '12-Oct-05';
Objects
No need to declare the variables
a = 1; whos
a = ‘text’ whos
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

17. MATRIX The fundamental two-dimensional data storage unit
Created with matrix creator operator [ ]
>> a = [ ]; % one-dimensional array (vector, array)
>> b = [1 2; 3 4]; % two-dimensional matrix
Element separator: space, column separator: ;
Access elements with numerical indices
>> c = a(1);
>> i = 2; d = a(i);
Concatenate
>> a = [1 2]; b= [3 4];
>> c = [a b];
Selectively display rows/columns
>> a = [1 2; 3 4; 5 6];
>> b = a(2, :);
Empty matrix
>> c = [];
Delete rows/columns
>> a(2) = [];
Bring back the previous examples a = 1; whos
Show formats
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

18. Arithmetical operators
+, -, *, /
>> a=[1 2]; b = [3 4]; c = a+b;
their element-wise counterparts .* , ./
>> a=[10 20;30 40]; b=[1 2; 3 4]; c = a./b; d = a/b;
^ (raise to the power of); also .^
>> a = [10 20; 30 40]; b = a.^2; c = a^2;
' (transpose)
>> a = [1 2 3]; b = a';
\ (left division) – A\B: If A is a square matrix, A\B is roughly the same as inv(A)*B, except it is computed in a different way.
Give extensive examples
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

19. ( * vs .* ) , (/ vs ./ ), (^ vs .^ ) ( * vs .* ) , (/ vs ./ ) vs
matrix multiplication element-wise
(^ vs .^ )
matrix power element-wise
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

20. Strings Arrays of alpha-numeric elements
Elements accessed like array elements
Can be concatenated
Useful functions
strcmp/strcmpi
strfind/findstr
sprintf/sscanf
num2str/str2num
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

21. Structures A data unit made up of containers called fields
The fields can be any data type
Compact way of storing data
<struct_name>.<fieldX>
Build a structure by
assigning values to its fields: >> a.location = 'Oxford';
struct function: >> a = struct(‘location’, ‘Oxford’);
rmfield/isfield
Can be used to build matrices
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

22. Cell arrays
A way of storing a miscellaneous collection of data in matrix form
{} – cell arrays constructor operator
>> a = {'Text' , [1 2 3], [true false]};
Indices for elements given in {}
>> a = {2}
can be concatenated
sort/size apply if these operations make sense for the elements of the cell array
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1

23. Interface with the OS
Run OS commands from MATLAB prompt with preceding them with the character !
e.g. >> !dir
Manipulate files and directories using MATLAB functions:
path
pwd cd
copyfile/movefile/delete
mkdir/rmdir
MSc in Mathematical and Computational Finance Introduction to MATLAB
Session 1