MATLAB

Introduction to Matlab (Code)

intro.m

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% Introduction to Matlab

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 (1) Basics

The symbol "%" is used to indicate a comment (for the remainder of the line).When writing a long Matlab statement that becomes to long for a single line use "..." at the end of the line to continue on the next line. E.g.

A = [1, 2; ... 3, 4];

A semicolon at the end of a statement means that Matlab will not display the result of the evaluated statement. If the ";" is omitted then Matlab will display the result. This is also useful for printing the value of variables, e.g. A

Matlab's command line is a little like a standard shell:

- Use the up arrow to recall commands without retyping them (and down arrow to go forward in the command history). 

 - C-a moves to beginning of line (C-e for end), C-f moves forward a character and C-b moves back (equivalent to the left and right arrow keys), C-d deletes a character, C-k deletes the rest of the  line to the right of the cursor, C-p goes back through the  command history and C-n goes forward (equivalent to up and down arrows), Tab tries to complete a command.

 Simple debugging:

 If the command "dbstop if error" is issued before running a script or a function that causes a run-time error, the execution will stop  at the point where the error occurred. Very useful for tracking down errors.

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 (2) Basic types in Matlab

(A) The basic types in Matlab are scalars (usually double-precision floating point), vectors, and matrices:

A = [1 2; 3 4];                           %Creates a 2x2 matrix

B = [1,2; 3,4];                   

The simplest way to create a matrix is to list its entries in square brackets. The ";" symbol separates rows; the (optional) "," separates columns.

N = 5          % A scalar

v = [1 0 0]    % A row vector

v = [1; 2; 3]  % A column vector

v = v'  

Transpose a vector (row to column or column to row)

v = 1:.5:3  % A vector filled in a specified range:

v = pi*[-4:4]/4  % [start:stepsize:end]

 (brackets are optional)

v = []  % Empty vector

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(B) Creating special matrices: 1ST parameter is ROWS, 2ND parameter is COLS 

m = zeros(2, 3)  % Creates a 2x3 matrix of zeros

v = ones(1, 3)  % Creates a 1x3 matrix (row vector) of ones

m = eye(3)  % Identity matrix (3x3)

v = rand(3, 1)  % Randomly filled 3x1 matrix (column vector); see also randn But watch out:

m = zeros(3)  % Creates a 3x3 matrix (!) of zeros

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(C) Indexing vectors and matrices.

Warning: Indices always start at 1 and *NOT* at 0!

v = [1 2 3];

v(3)  % Access a vector element

m = [1 2 3 4; 5 7 8 8; 9 10 11 12; 13 14 15 16]

m(1, 3)  % Access a matrix element matrix(ROW #, COLUMN #)

m(2, :)  % Access a whole matrix row (2nd row)

m(:, 1)  % Access a whole matrix column (1st column)

m(1, 1:3)  % Access elements 1 through 3 of the 1st row

m(2:3, 2)  % Access elements 2 through 3 of the 2nd column

m(2:end, 3)  % Keyword "end" accesses the remainder of a column or row

m = [1 2 3; 4 5 6]

size(m)  % Returns the size of a matrix

size(m, 1)  % Number of rows

size(m, 2)  % Number of columns

m1 = zeros(size(m))  % Create a new matrix with the size of m

who  % List variables in workspace

whos  % List variables w/ info about size, type, etc.

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(3) Simple operations on vectors and matrices

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 (A) Element-wise operations:

These operations are done "element by element". If two vectors/matrices are to be added, subtracted, or element-wise multiplied or divided, they must have the same size.

a = [1 2 3 4]';  % A column vector

2 * a  % Scalar multiplication

a / 4  % Scalar division

b = [5 6 7 8]';  % Another column vector

a + b  % Vector addition

a - b  % Vector subtraction

a .^ 2  % Element-wise squaring (note the ".")

a .* b  % Element-wise multiplication (note the ".")

a ./ b  % Element-wise division (note the ".")

log([1 2 3 4])  % Element-wise logarithm

round([1.5 2; 2.2 3.1])   

Element-wise rounding to nearest integer Other element-wise arithmetic operations include e.g. : floor, ceil, ...

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(B) Vector Operations

 Built-in Matlab functions that operate on vectors

a = [1 4 6 3]  % A row vector

sum(a)  % Sum of vector elements

mean(a)  % Mean of vector elements

var(a)  % Variance of elements

std(a)  % Standard deviation

max(a)  % Maximum

min(a)  % Minimum

If a matrix is given, then these functions will operate on each column of the matrix and return a row vector as result

a = [1 2 3; 4 5 6]  % A matrix

mean(a)  % Mean of each column

max(a)  % Max of each column

max(max(a))  % Obtaining the max of a matrix

mean(a, 2)  % Mean of each row (second argument specifies  dimension along which operation is taken)

[1 2 3] * [4 5 6]' 

1x3 row vector times a 3x1 column vector results in a scalar. Known as dot product or inner product. Note the absence of "."

[1 2 3]' * [4 5 6]   

3x1 column vector times a 1x3 row vector results in a 3x3 matrix. Known as outer

% product. Note the absence of "."

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(C) Matrix Operations:

a = rand(3,2)  % A 3x2 matrix

b = rand(2,4)  % A 2x4 matrix

c = a * b  % Matrix product results in a 3x4 matrix

a = [1 2; 3 4; 5 6];  % A 3x2 matrix

b = [5 6 7];  % A 1x3 row vector

b * a  % Vector-matrix product results in a 1x2 row vector

c = [8; 9];  % A 2x1 column vector

a * c  % Matrix-vector product results in a 3x1 column vector

a = [1 3 2; 6 5 4; 7 8 9];  % A 3x3 matrix

inv(a)  % Matrix inverse of a

eig(a)  % Vector of eigenvalues of a

[V, D] = eig(a)  % D matrix with eigenvalues on diagonal; V matrix of eigenvectors

Example for multiple return values!

[U, S, V] = svd(a)  % Singular value decomposition of a.
 a = U * S * V', singular values are stored in S Other matrix operations: det, norm, rank, ...

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(D) Reshaping and assembling matrices:

a = [1 2; 3 4; 5 6];  % A 3x2 matrix

b = a(:)  % Make 6x1 column vector by stacking up columns of a

sum(a(:))  % Useful: sum of all elements

a = reshape(b, 2, 3)  % Make 2x3 matrix out of vector elements (column-wise)

a = [1 2]; b = [3 4];  % Two row vectors

c = [a b]  % Horizontal concatenation (see horzcat)

a = [1; 2; 3];  % Column vector

c = [a; 4]  % Vertical concatenation (see vertcat)

a = [eye(3) rand(3)]  % Concatenation for matrices

b = [eye(3); ones(1, 3)]

b = repmat(5, 3, 2)  % Create a 3x2 matrix of fives

b = repmat([1 2; 3 4], 1, 2) % Replicate the 2x2 matrix twice in column direction; makes 2x4 matrix

b = diag([1 2 3])  % Create 3x3 diagonal matrix with given diagonal elements

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(4) Control statements & vectorization

 Syntax of control flow statements:

for VARIABLE = EXPR

 STATEMENT

 ...

STATEMENT

end

EXPR is a vector here, e.g. 1:10 or -1:0.5:1 or [1 4 7]

 while EXPRESSION

STATEMENTS

 end

if EXPRESSION

STATEMENTS

elseif EXPRESSION

 STATEMENTS

else

 STATEMENTS

 end

 (elseif and else clauses are optional, the "end" is required)

 EXPRESSIONs are usually made of relational clauses, e.g. a < b The operators are <, >, <=, >=, ==, ~= (almost like in C(++))

 Warning:

Loops run very slowly in Matlab, because of interpretation overhead. This has gotten somewhat better in version 6.5, but you should nevertheless try to avoid them by "vectorizing" the computation, i.e. by rewriting the code in form of matrix operations. This is illustrated in some examples below.

 Examples:

fori=1:2:7  % Loop from 1 to 7 in steps of 2

i  % Print i

end

fori=[5 13 -1]  % Loop over given vector

if(i > 10)  % Sample if statement

disp('Larger than 10')  % Print given string

elseifi < 0  % Parentheses are optional

disp('Negative value')

else

disp('Something else')

end

end

 Here is another example: given an mxn matrix A and a 1xn vector v, we want to subtract v from every row of A.

m = 50; n = 10; A = ones(m, n); v = 2 * rand(1, n); 

Implementation using loops:

fori=1:m

A(i,:) = A(i,:) - v;

end

We can compute the same thing using only matrix operations

A = ones(m, n) - repmat(v, m, 1);  % This version of the code runs much faster!!!

We can vectorize the computation even when loops contain conditional statements.

Example: given an mxn matrix A, create a matrix B of the same size containing all zeros, and then copy into B the elements of A that are greater than zero.

Implementation using loops:

B = zeros(m,n);

fori=1:m

forj=1:n

ifA(i,j)>0

B(i,j) = A(i,j);

end

end

end

All this can be computed w/o any loop!

B = zeros(m,n);

ind = find(A > 0);  % Find indices of positive elements of A

B(ind) = A(ind);  % Copies into B only the elements of A that are > 0

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(5) Saving your work

save myfile  % Saves all workspace variables into file myfile.mat

save myfile a b  % Saves only variables a and b

clear a b  % Removes variables a and b from the workspace

clear  % Clears the entire workspace

load myfile  % Loads variable(s) from myfile.mat

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(6) Creating scripts or functions using m-files:

 Matlab scripts are files with ".m" extension containing Matlab commands. 

 Variables in a script file are global and will change the value of variables of the same name in the environment of the current Matlab session. A script with name "script1.m" can be invoked by typing "script1" in the command window. 

 Functions are also m-files. The first line in a function file must be of this form: 

function [outarg_1, ..., outarg_m] = myfunction(inarg_1, ..., inarg_n)

The function name should be the same as that of the file (i.e. function "myfunction" should be saved in file "myfunction.m"). Have a look at myfunction.m and myotherfunction.m for examples.

Functions are executed using local workspaces: there is no risk of conflicts with the variables in the main workspace. At the end of a function execution only the output arguments will be visible in the main workspace.

a = [1 2 3 4];  % Global variable a

b = myfunction(2 * a)  % Call myfunction which has local

% variable a

a  % Global variable a is unchanged

[c, d] = ...

myotherfunction(a, b)  % Call myotherfunction with two return values

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(7) Plotting

x = [0 1 2 3 4];  % Basic plotting

plot(x);  % Plot x versus its index values

pause  % Wait for key press

plot(x, 2*x);  % Plot 2*x versus x

axis([0 8 0 8]);  % Adjust visible rectangle

figure;  % Open new figure

x = pi*[-24:24]/24;

plot(x, sin(x));

xlabel('radians');  % Assign label for x-axis

ylabel('sin value');  % Assign label for y-axis

title('dummy');  % Assign plot title

figure;

subplot(1, 2, 1);  % Multiple functions in separate graphs

plot(x, sin(x));  % (see "help subplot")

axis square;  % Make visible area square

subplot(1, 2, 2);

plot(x, 2*cos(x));

axis square;

figure;

plot(x, sin(x));

hold on;  % Multiple functions in single graph

plot(x, 2*cos(x), '--');  % '--' chooses different line pattern

legend('sin', 'cos');  % Assigns names to each plot

hold off;  % Stop putting multiple figures in current graph

figure;  % Matrices vs. images

m = rand(64,64);

imagesc(m)  % Plot matrix as image

colormap gray;  % Choose gray level colormap

axis image;  % Show pixel coordinates as axes

axis off;  % Remove axes

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(8) Working with (gray level) images

I = imread('cit.png');  % Read a PNG image

figure

imagesc(I)  % Display it as gray level image

colormap gray;

colorbar  % Turn on color bar on the side

pixval  % Display pixel values interactively

truesize  % Display at resolution of one screen pixel per image pixel

truesize(2*size(I))  % Display at resolution of two screen pixels per image pixel

I2 = imresize(I, 0.5, 'bil'); % Resize to 50% using bilinear interpolation

I3 = imrotate(I2, 45, ...% Rotate 45 degrees and crop to

'bil', 'crop'); % original size

I3 = double(I2);  % Convert from uint8 to double, to allow math operations

imagesc(I3.^2)  % Display squared image (pixel-wise)

imagesc(log(I3))  % Display log of image (pixel-wise)

I3 = uint8(I3);  % Convert back to uint8 for writing

imwrite(I3, 'test.png')  % Save image as PNG

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myfunction.m

functiony = myfunction(x)

Function of one argument with one return value

a = [-2 -1 0 1];  % Have a global variable of the same name

y = a + x;

myotherfunction.m

function[y, z] = myotherfunction(a, b)

Function of two arguments with two return values

y = a + b;

z = a - b;