据 AlphaMoat 统计,截至 2026-09,MATLAB 累计下载 3,663 次、获 3 个星标,在全部 5,078 个 AI 技能中排名第 2,959 位,在「开发编程」分类(577 个)中排名第 385 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 53 | 1,851 | 3 | - |
| SkillHub ↗ | 344 | 3,663 | 3 | — |
各平台的计数口径不同,统计时间不一致。
涵盖矩阵与逐元素运算、向量方向、预分配、扩展、缺失值、元胞、函数和调试。技能本身是指导资料而非可执行代码。建议需匹配项目 MATLAB 版本与工具箱,运行或验证代码前确认已安装且有许可的 MATLAB 环境。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,663 | — | 3 |
| 2026-08 | 2,636 | +15.7% | 3 |
| 2026-07 | 2,279 | +15.9% | 3 |
| 2026-06 | 1,967 | +11.2% | 3 |
| 2026-05 | 1,769 | — | 3 |
| 2026-03 | 1,141 | — | 3 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
name: MATLAB
description: Avoid common MATLAB mistakes — indexing traps, matrix vs element-wise ops, and vectorization pitfalls.
metadata: {"clawdbot":{"emoji":"📐","requires":{"bins":["matlab"]},"os":["linux","darwin","win32"]}}
---
## Indexing
- 1-based indexing — first element is `A(1)`, not `A(0)`
- `end` keyword for last index — `A(end)`, `A(end-1)`, works in any dimension
- Linear indexing on matrices — `A(5)` accesses 5th element column-major order- Logical indexing returns vector — `A(A > 0)` gives 1D result regardless of A's shape
## Matrix vs Element-wise
- `*` is matrix multiplication — `.*` for element-wise
- `/` solves `A*x = B` — `./` for element-wise division
- `^` is matrix power — `.^` for element-wise power
- Forgetting the dot is silent bug — dimensions might accidentally match
## Vector Shape Matters
- Row vector: `[1 2 3]` or `[1, 2, 3]` — shape is 1×3
- Column vector: `[1; 2; 3]` — shape is 3×1
- Transpose with `'` (conjugate) or `.'` (non-conjugate) — for complex, they differ
- `*` between row and column gives scalar or matrix — depending on order
## Array Preallocation
- Growing arrays in loops is slow — preallocate: `A = zeros(1000, 1)`
- `zeros`, `ones`, `nan` for preallocation — specify size upfront
- Cell arrays: `cell(n, m)` — preallocate cells too
## Broadcasting
- Implicit expansion since R2016b — `A + b` works if dimensions compatible
- Singleton dimensions expand — `[1;2;3] + [10 20]` gives 3×2
- Before R2016b needed `bsxfun` — legacy code may still use it
## NaN Handling
- `NaN ~= NaN` is true — use `isnan()` to check
- Most operations propagate NaN — `sum([1 NaN 3])` is NaN
- Use `'omitnan'` flag — `sum(A, 'omitnan')`, `mean(A, 'omitnan')`
## Cell Arrays vs Matrices
- `{}` for cell arrays — hold mixed types, different sizes
- `()` indexing returns cell — `C(1)` is 1×1 cell
- `{}` indexing extracts content — `C{1}` is the actual value
- Comma-separated list from `C{:}` — useful for function arguments
## Common Mistakes
- `=` for assignment, `==` for comparison — `if x = 5` is error in MATLAB
- Semicolon suppresses output — forget it and flood command window
- `clear` removes all variables — use `clearvars` for selective, `close all` for figures
- `i` and `j` are imaginary unit — don't use as loop variables, or reassign explicitly
- String vs char: `"text"` vs `'text'` — double quotes are string arrays (R2017a+)
## Functions
- Anonymous functions: `f = @(x) x^2` — quick inline functions
- Multiple outputs: `[a, b] = func()` — must capture or use `~` to ignore
- `nargin`/`nargout` for optional args — check how many inputs/outputs provided
- `varargin`/`varargout` for variable args — cell array of extra arguments
## Debugging
- `dbstop if error` — breakpoint on any error
- `keyboard` in code pauses execution — enter debug mode at that line
- `whos` shows variable sizes — `size(A)` for specific variable
用 gh 命令行工具查看 GitHub 上的 PR 检查、工作流运行与 API 查询的技能。
聚合 16 个搜索引擎、无需 API Key 的检索技能。
用命令行直接列出、配置、授权并调用 MCP 服务与工具。
生成有效的 Mermaid 图表,如流程图、时序图、思维导图、ER 图、用户旅程等。
用受管 OAuth 访问 YouTube Data API,检索视频并管理频道内容。
通过受管的 OAuth 连接访问 GitHub REST API。
覆盖规划、实现、验证与测试的编码工作流技能。
整理 Docker 常用命令与容器工作流的技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在保留公式、格式与工作簿结构的前提下创建、检查并修改 Excel 文件的技能。
处理 Word 与 DOCX 文档的作业规范,重点是改完之后样式、编号与版式不跑偏。
把数据库、表格与导出的原始数据变成可决策结论的数据分析技能。
改 PPT 之前先看清结构的一套规范,目标是改完还能干净渲染。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。