MATLAB - Arrays

MATLAB - Arrays and Data Containers

The fundamental data structure in MATLAB is the array. Every variable, from a single number (a 1x1 array) to a complex dataset, is stored as a multidimensional array. Understanding how to create, manipulate, and choose the right type of array is key to writing efficient and effective MATLAB code.

Fundamental Array Creation

MATLAB provides a rich set of functions for creating common types of arrays:

% A 3x4 matrix of all zeros
A = zeros(3, 4);

% A 5x5 square matrix of all ones
B = ones(5);

% A 4x4 identity matrix
I = eye(4);

% A 2x5 matrix of uniformly distributed random numbers between 0 and 1
R_uniform = rand(2, 5);

% A 3x3 matrix of normally distributed random numbers
R_normal = randn(3);

% A vector with 100 points evenly spaced from 0 to 10
V = linspace(0, 10, 100);

Multidimensional Arrays

Arrays can have more than two dimensions. These are often used for image data (height x width x color channels) or for representing data over a 3D grid. You can create them by extending an existing 2D array or by using creation functions with more than two dimension arguments.

% Start with a 2x3 matrix (Page 1)
A = [1 2 3; 4 5 6];

% Add a second 'page' to create a 2x3x2 array
A(:, :, 2) = [7 8 9; 10 11 12];

% Access the element at row 1, col 3, page 2
element = A(1, 3, 2); % This will be 9

% Create a 4x3x2 array of random numbers directly
B = rand(4, 3, 2);

Essential Array Manipulation Functions

Instead of a long list, here are some of the most critical functions for working with arrays:

• Size and Shape: size(A) returns the dimensions of array A. numel(A) returns the total number of elements. length(A) returns the size of the longest dimension.
• Reshaping: reshape(A, new_dims) changes the dimensions of an array without changing its elements. For example, reshape(1:6, 2, 3) creates a 2x3 matrix.
• Sorting: sort(V) sorts a vector. For a matrix M, sort(M, 1) sorts each column, and sort(M, 2) sorts each row.
• Finding Elements: find(A > 5) returns the linear indices of all elements in A that are greater than 5.

Modern Data Containers

For more complex or structured data, modern MATLAB offers specialized data containers that are often more efficient and convenient than basic numeric arrays.

String Arrays (Recommended for Text)

For handling text, modern MATLAB introduced string arrays, created with double quotes (""). They are more flexible and powerful than traditional character arrays (single quotes '').

% Modern String Array (Recommended)
names_str = ["Alice", "Bob", "Charlie"];
names_str(2) % Accesses the full string "Bob"

% Old Character Array (Avoid if possible)
names_char = ['Alice'; 'Bob  '; 'Charlie']; % Requires padding with spaces to be rectangular

Cell Arrays (For Heterogeneous Data)

A cell array is a container where each element (a cell) can hold any type of data, including numbers, text, or even other arrays. This is useful for grouping dissimilar data together.

Use parentheses () to index the cells themselves, and curly braces {} to access the content inside a cell.

% Create a 2x3 cell array
C = {10, 'some text', [1 2; 3 4]; ...
     @(x) x^2, "a string", {1; 2}};

% Get the cell at (1, 3) (which is a cell containing a matrix)
cell_subset = C(1, 3); % Returns a 1x1 cell array

% Get the CONTENT of the cell at (1, 3) (the matrix itself)
matrix_content = C{1, 3}; % Returns the 2x2 matrix [1 2; 3 4]

Tables (For Tabular Data)

A table is the best choice for storing mixed-type columnar data, like you would find in a spreadsheet or database table. Each column can have a different data type, but all data within a column must be of the same type. Tables are highly recommended for data analysis.

% Create data for the table
LastName = ["Smith"; "Jones"; "Williams"];
Age = [38; 29; 45];
Smoker = [true; false; true];
Height = [71; 69; 64];

% Create the table
patients = table(LastName, Age, Smoker, Height);
disp(patients);

% Access data using dot notation (very convenient)
mean_age = mean(patients.Age);
fprintf('Mean patient age: %.1f\n', mean_age);

% Access all data for smokers
smoker_data = patients(patients.Smoker, :);
disp(smoker_data);