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MATLAB Syntax

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1. Overview

2. Syntax

3. Shortcuts

1. Overview

⑴ MATLAB stands for matrix laboratory

⑵ A commercial license (paid) is required to use MATLAB commercially: Contrasts with free Python

⑶ Comparison with Python

① 1-indexed

② Range end is inclusive

③ Uses “()” instead of “[]”

④ Functions do not require return: Output variables are returned automatically

2. Syntax

○ ; (semicolon): Executes the code but does not display the output. Can be used to write multiple commands in one line

○ [v d] = version

○ %: Comment

○ help plot: Outputs documentation related to plot

○ disp(x): Displays x

○ clear: Clears the workspace

○ clc: Clears the command window

○ a1 = [1 2 3 4 5]

○ a2 = 1:100

○ a3 = 0:5:100

○ .*: element-wise multiplication

○ .^: element-wise power

○ c1 = [1; 3; 5; 7; 9]: column vector

○ m1 = [1 2 3 ; 4 5 6 ; 7 8 9]

○ m2 = zeros(3, 2)

○ m3 = ones(3, 2)

○ m4 = rand(3, 2): Creates a 3 × 2 matrix by randomly sampling from a uniform range [0, 1]

○ m5 = randn(3, 2): Creates a 3 × 2 matrix by randomly sampling from a normal distribution N(0, 1)

○ m6 = eye(3)

○ inv(m1): Inverse of m1

○ m1': Transpose of m1

○ size(m6): Returns the shape of matrix m6

○ a /b: Unlike a / b, results in an error

○ length(m1): Outputs the largest dimension

○ numel(m1): Number of elements in m1

○ m1(:): Flattens the m1 matrix

○ data(data > 0): Outputs elements greater than 0 in data

○ find(data > 0): Outputs indices of elements greater than 0 in data

○ hold on: Used before plotting new graphs to display multiple graphs at once

○ subplot(2,2,2): Specifies the number of rows, number of columns, and index to display multiple subplots simultaneously

○ save('data.mat','data','w','x','y','t'): Saves multiple variables into a file named data.mat at once

○ save('data.mat','b','-append'): Updates existing data.mat with a new variable b

○ load('data.mat'): Loads a saved file

○ fft(y): Fourier Transform of signal y

○ lowpass(y, cutoff_frequency, sampling_frequency): Applies a lowpass filter to signal y

○ highpass(y, cutoff_frequency, sampling_frequency): Applies a highpass filter to signal y

○ bandpass(y, [low_cutoff_frequency high_cutoff_frequency], sampling_frequency): Applies a bandpass filter to signal y

○ gray_image = imread('dark_woods.tif'): Reads an image file

○ imshow(gray_image): Visualizes the image

○ gray_image_equalized = histeq(gray_image): Histogram equalization function. Widens the distribution of pixel intensity, improving image contrast

○ colored_image_eq = cat(3, red_channel_eq, green_channel_eq, blue_channel_eq): Concatenate

○ rng(42): Random seed setting

○ cv = cvpartition(y, 'Holdout', 0.2): Partition data into 80:20

○ X_train = X(training(cv), :)

○ y_train = y(training(cv))

○ X_test = X(test(cv), :)

○ y_test = y(test(cv))

3. Shortcuts

○ Use Ctrl + - (Windows/Linux) or Cmd + - (macOS) to reduce font size

Input: 2024.08.26 17:14