{"id":30620407,"url":"https://github.com/jingyuexing/mathlib","last_synced_at":"2025-08-30T13:36:56.720Z","repository":{"id":48914431,"uuid":"174944104","full_name":"jingyuexing/MathLib","owner":"jingyuexing","description":"The Math 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MathLib\n在calculus中有微积分为微积分实现方法,目前还未进行实现 在`statistics`中包含统计学相关的算法,如协方差，方差，求中位数,平均值,分位数图计算\n### statistics\n- ----`index`：[当前库的主要导出文件](statistics/TypeScript/src/index.ts)\n- ----`Variance`：[方差实现方法](statistics/TypeScript/src/Variance.ts) [python](statistics/python/src/var.py)\n- ----`weigth_variance`:[加权平均数实现方法](statistics/TypeScript/src/weigth_variance.ts)\n- ----`QuantilePlot`:[分位数图](statistics/TypeScript/src/src/QuantilePlot.ts)\n- ----`Covariance`：[协方差](statistics/TypeScript/src/Covariance.ts)\n- ----`Mean`：[平均值](statistics/TypeScript/src/Mean.ts) [py](statistics/python/src/Mean.py)\n- ----`harmonic`：[调和数](statistics/TypeScript/src/harmonic.ts)\n- ----`LeastSquare`：[二乘法](statistics/TypeScript/src/LeastSquare.ts)\n- ----`Media`:[中位数](statistics/TypeScript/src/Median.ts) [py](statistics/python/src/Median.py)\n- ----`Matrix`:[矩阵类](statistics/TypeScript/src/Matrix.ts) [C](statistics/C/src/matrix.c) [py](statistics/python/src/Matrix.py) [haxe](statistics/Haxe/src/mathlib/Matrix.hx),实现矩阵的计算,诸如相加,相减,矩阵的逆,矩阵转置\n- ----`rank`：[排序](statistics/TypeScript/src/Rank.ts) [py](statistics/python/src/Rnak.py) 的实现(未完全实现)\n- ----`StandardDeviation`:[标准差](statistics/TypeScript/src/Standard_Deviation.ts)\n- ----`vector`:[向量](statistics/TypeScript/src/vector.ts)的运算 [py](statistics/python/src/Vector.py)\n- ----`Permutations`：[阶乘](statistics/TypeScript/src/Permutations.ts)\n- ----`expetation`：[期望值](statistics/TypeScript/src/expetation.ts)\n- ----`sigmoid`:[激活函数](statistics/TypeScript/src/sigmoid.ts) [py](statistics/python/src/sigmoid.py)\n- ----`angule`:[角度和弧度转换](statistics/TypeScript/src/angule.ts)\n- ----`gcd`:[求最大公约数](statistics/TypeScript/src/gcd.ts)\n- ----`Factorial`:[求n的阶乘](statistics/TypeScript/src/Factorial.ts)\n- ----`softmax`:[softmax](statistics/TypeScript/src/softmax.ts) [py](statistics/python/src/softmax.py)\n\n---\n增加链式调用,Matrix类以及Vector类\n\n----\n用法:\n* ***Variance***\n此方法求取数据的方差,返回的是方差值,若需要标准差,只需要将该方法返回值开方即可\n```js\n//Variance([...value]:Array\u003cnumber\u003e);\nconsole.log(Variance([2,3,5,7,8,9,12,40,66,92,103,88]));//NaN,unknow Error\n```\n* ***weigth_variance***\n此方法返回加权平均值\n函数第一个参数数组为数据,第二个数组参数为权重值\n```js\n//weigthVariance([...numberData]: Array \u003c number \u003e , [...weigth]: Array \u003c number \u003e )\nconsole.log(weigthVariance([2,3,5,8,9,12,44],[1,1,1,2,3,2,1]))\n```\n\n### todolist\n- ☐ 完成Matrix算法的 C 实现\n- ☐ 完成Matrix算法的 CPP 实现\n- ☐ 完成Matrix算法的 CS 实现\n- ☐ 完成Matrix算法的 JS 实现\n- ☐ 完成Matrix算法的 GO 实现\n- ☐ 完成Matrix算法的 Haxe 实现\n- ☐ 完成Matrix算法的 Java 实现\n- ☐ 完成Matrix算法的 Python 实现\n- ☐ 完成link链表的 CPP 的实现\n- ☐ 完成link链表的 JS 的实现\n- ☐ 完成link链表的 Haxe 的实现\n- ☐ 完成link链表的 Java 的实现\n- ☐ 完成link链表的 Python 的实现\n- ☐ 完成Vector向量 C 的实现\n- ☐ 完成Vector向量 CPP 的实现\n- ☐ 完成Vector向量 CS 的实现\n- ☐ 完成Vector向量 JS 的实现\n- ☐ 完成Vector向量 Go 的实现\n- ☐ 完成Vector向量 Haxe 的实现\n- ☐ 完成Vector向量 Java 的实现\n- ☐ 完成Rank排序 C 的算法的实现\n- ☐ 完成Rank排序 CPP 的算法的实现\n- ☐ 完成Rank排序 JS 的算法的实现\n- ☐ 完成Rank排序 Go 的算法的实现\n- ☐ 完成Rank排序 Haxe 的算法的实现\n- ☐ 完成Rank排序 Java 的算法的实现\n- ☐ 完成Sgmoid算法的 C 实现\n- ☐ 完成Sgmoid算法的 CPP 实现\n- ☐ 完成Sgmoid算法的 JS 实现\n- ☐ 完成Sgmoid算法的 TS 实现\n- ☐ 完成Sgmoid算法的 Go 实现\n- ☐ 完成Sgmoid算法的 Haxe 实现\n- ☐ 完成Sgmoid算法的 Java 实现\n- ☐ 完成Softmax算法的 C 实现\n- ☐ 完成Softmax算法的 CPP 实现\n- ☐ 完成Softmax算法的 JS 实现\n- ☐ 完成Softmax算法的 GO 实现\n- ☐ 完成Softmax算法的 Haxe 实现\n- ☐ 完成Softmax算法的 Java 实现\n- ☐ 完成Rank排序各类语言算法的实现\n- ☐ 完成Sgmoid算法的各类语言实现\n- ☐ 完成Vector各类语言的实现\n- ☐ 完成link链表的各类语言的实现\n- ☐ 完成Matrix算法的各类语言实现\n\n---\n\nArchive:\n- ✔ 完成List链表的 Go 的实现 @done (21-08-07 11:31)\n- ✔ 完成link链表的 Go 的实现 @done (21-08-07 11:29)\n- ✔ 完成link链表的 C 的实现 @done (20-12-08 20:38)\n- ✔ 完成Sgmoid算法的 CS 实现 @done (20-12-04 12:12)\n- ✔ 完成link链表的 CS 的实现 @done (20-12-04 12:03)\n- ✔ 完成Softmax算法的 CS 实现 @done (20-12-04 11:17)\n- ✔ 完成Sgmoid算法的 CS 实现 @done (20-12-04 11:16)\n- ✔ 完成Vector向量 Python 的实现 @done (20-12-03 14:41)\n- ✔ 完成Softmax算法的 Python 实现 @done (20-12-03 14:41)\n- ✔ 完成Softmax算法的 TS 实现 @done (20-12-03 14:28)\n- ✔ 完成link链表的 TS 的实现 @done (20-12-03 14:27)\n- ✔ 完成Vector向量 TS 的实现 @done (20-12-03 14:27)\n- ✔ 完成Rank排序 TS 的算法的实现 @done (20-12-03 14:27)\n- ✔ 完成Rank排序 Python 的算法的实现 @done (20-12-03 14:27)\n- ✔ 完成Matrix算法的 TS 实现 @done (20-12-03 14:27)\n- ✔ 完成Sgmoid算法的 Python 实现 @done (20-12-03 14:26)\n\n---\n关于这个数学库如果有意见可以和我[一起修改我的github仓库](https://github.com/jingyuexing/MathLib)\n你也可以到[gitee码云](https://gitee.com/jingyuexing/MathLib)查询这个库的镜像\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjingyuexing%2Fmathlib","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjingyuexing%2Fmathlib","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjingyuexing%2Fmathlib/lists"}