{"id":22663405,"url":"https://github.com/efjerryyang/computational-methods","last_synced_at":"2025-06-12T13:03:50.975Z","repository":{"id":41855200,"uuid":"467388448","full_name":"efJerryYang/computational-methods","owner":"efJerryYang","description":"Computational Methods 哈尔滨工业大学（深圳）计算方法实验","archived":false,"fork":false,"pushed_at":"2023-03-08T02:15:34.000Z","size":732629,"stargazers_count":5,"open_issues_count":3,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-26T02:35:01.172Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/efJerryYang.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-03-08T06:19:15.000Z","updated_at":"2024-03-21T10:43:03.000Z","dependencies_parsed_at":"2023-02-18T05:31:07.827Z","dependency_job_id":null,"html_url":"https://github.com/efJerryYang/computational-methods","commit_stats":null,"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/efJerryYang%2Fcomputational-methods","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/efJerryYang%2Fcomputational-methods/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/efJerryYang%2Fcomputational-methods/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/efJerryYang%2Fcomputational-methods/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/efJerryYang","download_url":"https://codeload.github.com/efJerryYang/computational-methods/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248531118,"owners_count":21119700,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-09T12:18:52.436Z","updated_at":"2025-04-12T07:22:27.834Z","avatar_url":"https://github.com/efJerryYang.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 哈尔滨工业大学（深圳）计算方法实验\n\n该仓库内容主要为哈尔滨工业大学祖传的计算方法实验，如果实验指导书有更新，可能内容将不再适用\n\n我们实验时编程语言不限，故我选择使用 Julia 语言完成该实验\n\n如果这个项目对你有帮助，请在右上角点一下 star ~\n\n\u003e 这只是个想骗星星的仓库罢了 :(\n\n## 项目结构\n\n\u003e 因实验首先用 Julia 在 Jupyter Notebook 上完成，而后因为提交验收问题，不得已改为 Julia 脚本。而提交的实验报告 PDF 由 Jupyter Notebook 导出的 Markdown 转换而来，故 Notebook 所撰写的报告部分内容可能没有更新，但实验结果应当是正确的。\n\n- `docs` 目录下包含完整的作业和实验的 PDF 提交文档，代码和源文件在 `hws` 和 `labs` 目录下查看\n- `hws` 目录下包含作业的源 Markdown 文件，各班作业内容有差别，仅供参考\n- `labs` 目录为实验目录，包括实验代码和报告源 Markdown 文件\n  - `handout` 为实验指导书等内容\n  - `julia` 为 `*.jl` 脚本文件，运行需要 `julia` 环境和相关包的依赖\n  - `jupyer` 为 `*.ipynb` 笔记本，执行代码需要在笔记本安装 IJulia 核\n  - `matlab` 为 `.m` 格式的 MATLAB 脚本文件，运行需要安装 MATLAB （当前实现为 ChatGPT 翻译 Julia 代码，可能无法执行）\n  - `reports` 目录下为实验报告的源 Markdown 文件，包括实验报告所用的图片等，如仅需参考报告，建议查看 `docs` 目录下排版完整的 PDF 文件\n    - `lab1-lagrange` 为拉格朗日插值实验报告\n    - `lab2-romberg` 为龙贝格积分实验报告\n    - `lab3-runge-kutta` 为龙格-库塔方法实验报告\n    - `lab4-newton` 为牛顿插值实验报告\n    - `lab5-gauss` 为高斯消元法实验报告\n\n完整目录结构如下所示：\n\n```bash\n.\n|-- archive\n|-- docs\n|   |-- homework-pdfs\n|   `-- lab-reports\n|-- hws\n|   `-- assets\n`-- labs\n    |-- handout\n    |-- julia\n    |-- jupyter\n    |-- matlab\n    `-- reports\n        |-- lab1-lagrange\n        |-- lab2-romberg\n        |-- lab3-runge-kutta\n        |   `-- assets\n        |-- lab4-newton\n        `-- lab5-gauss\n```\n\n## 安装使用\n\n### Jupyter Notebook\n\n如果你有 Jupyter Notebook 环境，添加了 IJulia 核之后，可以直接打开 `labs/jupyter` 目录下的 `*.ipynb` 文件，运行代码即可。运行报错时，根据提示安装需要的第三方包。\n\n### Julia\n\nJulia 脚本运行需要解释器，可以在 [Julia 官网](https://julialang.org/) 下载安装包，或者使用包管理器安装。国内安装有中文官网，可以参考 [Julia 中文官网](https://cn.julialang.org/)。\n\n### MATLAB\n\nMATLAB 脚本的运行需要安装 MATLAB\n\n\u003e 注意：当前的 MATLAB 实现为 Julia 代码通过 ChatGPT 生成，尚未验证可执行性，但因两者的语法相似（数组、向量等的下标起点为 1 ，列优先保存等，如果是参考算法二者实现的差异不大）\n\n### Release Binary\n\n如果使用 Release 版本的二进制文件，因执行时编译运行的耗时，其执行效率较低，且只适用于 Windows 平台\n\n## 参考资料\n\n\u003e 具体的参考资料引用已在各个实验报告中给出，这里不再列出\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fefjerryyang%2Fcomputational-methods","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fefjerryyang%2Fcomputational-methods","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fefjerryyang%2Fcomputational-methods/lists"}