# Matlab

MATLAB and GNU Octave numerical computing for matrix operations, data analysis...

- Repository: https://github.com/zLanqing/codex-claude-academic-skills (5550 stars)
- Category: Data and ML
- License: MIT
- Last updated: 2026-05-14
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add zLanqing/codex-claude-academic-skills --skill matlab -g -a claude-code -y`
Codex: `npx skills add zLanqing/codex-claude-academic-skills --skill matlab -g -a codex -y`
Cursor: `npx skills add zLanqing/codex-claude-academic-skills --skill matlab -g -a cursor -y`
Gemini CLI: `npx skills add zLanqing/codex-claude-academic-skills --skill matlab -g -a gemini-cli -y`

## Description

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MATLAB/Octave Scientific Computing

MATLAB is a numerical computing environment optimized for matrix operations and scientific computing. GNU Octave is a free, open-source alternative with high MATLAB compatibility.

## Quick Start

**Running MATLAB scripts:**
```bash
# MATLAB (commercial)
matlab -nodisplay -nosplash -r "run('script.m'); exit;"

# GNU Octave (free, open-source)
octave script.m
```

**Install GNU Octave:**
```bash
# macOS
brew install octave

# Ubuntu/Debian
sudo apt install octave

# Windows - download from https://octave.org/download
```

## Core Capabilities

### 1. Matrix Operations

MATLAB operates fundamentally on matrices and arrays:

```matlab
% Create matrices
A = [1 2 3; 4 5 6; 7 8 9];  % 3x3 matrix
v = 1:10;                     % Row vector 1 to 10
v = linspace(0, 1, 100);      % 100 points from 0 to 1

% Special matrices
I = eye(3);          % Identity matrix
Z = zeros(3, 4);     % 3x4 zero matrix
O = ones(2, 3);      % 2x3 ones matrix
R = rand(3, 3);      % Random uniform
N = randn(3, 3);     % Random normal

% Matrix operations
B = A';              % Transpose
C = A * B;           % Matrix multiplication
D = A .* B;          % Element-wise multiplication
E = A \ b;           % Solve linear system Ax = b
F = inv(A);          % Matrix inverse
```

For complete matrix operations, see [references/matrices-arrays.md](references/matrices-arrays.md).

### 2. Linear Algebra

```matlab
% Eigenvalues and eigenvectors
[V, D] = eig(A);     % V: eigenvectors, D: diagonal eigenvalues

% Singular value decomposition
[U, S, V] = svd(A);

% Matrix decompositions
[L, U] = lu(A);      % LU decomposition
[Q, R] = qr(A);      % QR decomposition
R = chol(A);         % Cholesky (symmetric positive definite)

% Solve linear systems
x = A \ b;           % Preferred method
x = linsolve(A, b);  % With options
x = inv(A) * b;      % Less efficient
```

For comprehensive linear algebra, see [references/mathematics.md](references/mathematics.md).

The rest: https://github.com/zLanqing/codex-claude-academic-skills/blob/HEAD/scientific-toolkit-skill/references/scientific-skills/matlab/SKILL.md