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初衷 在这次疫情处理过程中，了解到在梳理传播链的过程中，很多时候仍然是手工在powerpoint等软件绘制传播链的。采用这种方式的优点能够在图中根据设计者需要加入较多的信息，比如：人员大致位置分布，接触的途径和强度等信息。不足之处在于，在链条上节点（感染者）较少的时候还能够梳理得很明确，但一旦节点达到一定数量，其中关系复杂度将呈几何倍数增加（比如1人传多个，1人与多个感染者有接触之类）。 在这种情况下。单纯的手工整理，将耗费非常多的脑力。最严重的缺点是，当现场流调信息变更，对链条进行修订的时，其中一个节点或链接的变化，会因连锁作用导致整个链条的变化。节点越多，变化的影响范围越大，越复杂，就像整理线头一样。当感染者人数上升到一定数量时，手动整理已经变成了一件难以完成的事情。由于本人对R的热衷，探索了一下能不能使用软件自动化链就是自己懒嘛的方式绘制传播，使用igraph，ggraph和networkD3最终效果如下面几张图,个人觉得还是networkD3炫酷的互动效果最好。 具体制作过程 参见我使用的3个包的说明。。。。。详细步骤待补充。 数据 节点数据 节点数据里面只需要包含所有感染者的基本信息，比如编号，姓名，类别等等。 边数据 边数据最基础的要求为，节点数据左右感染者的对应关系，简单说就像Excel两列，第一列from， 第二列to，代表每一行两个感染者的关系，从谁传播到谁，当然这些资料需要辛苦在现场的流调专家们提供。 可视化 igraph 首先使用graph_from_data_frame(d =line, vertices = node, directed = T)将节点和边转换成igraph，就可以直接plot第一张图, 参数自己可以调节。 netwokd3 个人最喜欢的效果，使用igraph_to_networkD3命令，将igraph数据转换一下，就可以使用simpleNetwork,forceNetwork，sankeyNetwork(画出交互性网络图了。试验了下，手机浏览器一样可以互动，包括拖动节点，放大，移动等，非常棒的体验。 {"x":{"links":{"source":[2,8,10,12,3,7,56,2,14,13,1,56,0,2,2,2,2,3,4,5,6,7,7,1,56,1,9,2,11,6,24,3,56,7,12,12,1,12,12,6,7,10,15,15,7,28,30,12,7,56,16,14,14,17,37,18,53,2,56,1,5,3,6],"target":[10,11,12,12,13,14,15,16,17,18,19,19,1,20,21,22,23,24,25,26,27,28,29,2,2,30,31,32,33,34,35,35,36,37,38,39,3,40,41,42,43,44,45,46,47,47,47,48,49,4,50,51,52,53,53,54,55,5,6,7,8,9,9],"value":[8,4,8,3,8,8,4,8,8,4,8,3,3,8,8,8,8,8,8,8,8,8,8,8,3,4,8,8,8,8,3,8,4,8,6,8,3,8,8,8,8,8,8,8,8,3,3,8,8,4,8,8,8,8,3,8,4,8,4,4,8,4,2],"colour":["#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666","#666"]},"nodes":{"name":["0号","1号","2号","3号","4号","5号","6号","7号","8号","9号","10号","11号","12号","13号","14号","15号","16号","17号","18号","19号","20号","21号","22号","23号","24号","25号","26号","27号","28号","29号","30号","31号","32号","33号","34号","35号","36号","37号","38号","39号","40号","41号","42号","43号","44号","45号","46号","47号","48号","49号","50号","51号","52号","53号","54号","55号","56号"],"group":[2,2,2,1,7,2,1,6,5,1,2,5,8,4,3,9,2,3,4,2,2,2,2,2,1,7,2,1,6,6,6,1,2,5,1,1,2,3,8,8,8,8,1,6,2,9,9,6,8,6,2,3,3,3,4,3,2],"nodesize":[200,150,30.6,34,35.6,43.1,40.5,10.8,46.9,44.5,42.8,46.8,22.8,27.3,25.4,18.7,11,14.2,23.1,12.4,31.3,11.1,21.7,11.6,11.2,1.3,24,48.2,33.1,2.9,29.2,15.5,45.1,38,23.8,44.4,32.7,15,36,41.2,4.8,22.9,1.6,38.9,41.1,38.6,43.3,9.9,2.1,46.1,12,42.3,1.8,18.9,40.6,27.9,20]},"options":{"NodeID":"name","Group":"group","colourScale":"d3.scaleOrdinal(d3.schemeCategory20);","fontSize":12,"fontFamily":"serif","clickTextSize":30,"linkDistance":50,"linkWidth":"function(d) { return Math.sqrt(d.value); }","charge":-30,"opacity":2,"zoom":true,"legend":false,"arrows":true,"nodesize":true,"radiusCalculation":" Math.sqrt(d.nodesize)+6","bounded":false,"opacityNoHover":1,"clickAction":null}},"evals":[],"jsHooks":[]} {"x":{"links":{"source":[2,8,10,12,3,7,56,2,14,13,1,56,0,2,2,2,2,3,4,5,6,7,7,1,56,1,9,2,11,6,24,3,56,7,12,12,1,12,12,6,7,10,15,15,7,28,30,12,7,56,16,14,14,17,37,18,53,2,56,1,5,3,6],"target":[10,11,12,12,13,14,15,16,17,18,19,19,1,20,21,22,23,24,25,26,27,28,29,2,2,30,31,32,33,34,35,35,36,37,38,39,3,40,41,42,43,44,45,46,47,47,47,48,49,4,50,51,52,53,53,54,55,5,6,7,8,9,9],"value":[8,4,8,3,8,8,4,8,8,4,8,3,3,8,8,8,8,8,8,8,8,8,8,8,3,4,8,8,8,8,3,8,4,8,6,8,3,8,8,8,8,8,8,8,8,3,3,8,8,4,8,8,8,8,3,8,4,8,4,4,8,4,2]},"nodes":{"name":["0号","1号","2号","3号","4号","5号","6号","7号","8号","9号","10号","11号","12号","13号","14号","15号","16号","17号","18号","19号","20号","21号","22号","23号","24号","25号","26号","27号","28号","29号","30号","31号","32号","33号","34号","35号","36号","37号","38号","39号","40号","41号","42号","43号","44号","45号","46号","47号","48号","49号","50号","51号","52号","53号","54号","55号","56号"],"group":["0号","1号","2号","3号","4号","5号","6号","7号","8号","9号","10号","11号","12号","13号","14号","15号","16号","17号","18号","19号","20号","21号","22号","23号","24号","25号","26号","27号","28号","29号","30号","31号","32号","33号","34号","35号","36号","37号","38号","39号","40号","41号","42号","43号","44号","45号","46号","47号","48号","49号","50号","51号","52号","53号","54号","55号","56号"]},"options":{"NodeID":"name","NodeGroup":"name","LinkGroup":null,"colourScale":"d3.scaleOrdinal(d3.schemeCategory20);","fontSize":16,"fontFamily":null,"nodeWidth":15,"nodePadding":10,"units":"Letter(s)","margin":{"top":null,"right":null,"bottom":null,"left":null},"iterations":20,"sinksRight":true}},"evals":[],"jsHooks":[]} ggraph ggraph基本研用了ggplot2绘图的方式，画出来的图也相对更漂亮。首先使用tidygraph包将igraph类型的数据转换为ggraph更合适的元数据。然后可以愉快地使用ggplot2的方式画图了。

对于一个公卫狗来说，很多工作都在分析数据、撰写报告总结的内容。这些文档有周报、月报、季报、年报。在使用R之前，经常会对同样架构的不同时间的的数据进行重复的分析和撰写。Rmarkdwon提供了非常便利的可重复复文档，简单来说就是根据跟新的数据库一键生成同样格式的文档。文档的类型可以是PDF和WORD。非常的便利。 1 Rmarkdown基础 1.1 markdown Markdown是一种轻量级标记语言，排版语法简洁，让人们更多地关注内容本身而非排版。它使用易读易写的纯文本格式编写文档，可与HTML混编，可导出HTML、PDF以及本身的.md格式的文件。因简洁、高效、易读、易写，Markdown被大量使用，如Github、Wikipedia、简书等。 Markdown已经是一种轻量化的语言，他的不足在于当需要转换为PDF或者WORD格式时有点力不从心了。针对这问题，目前供职与Rstudio的谢益辉大神在Markdown的基础上开发了rmarkdwon包。Rmarkdown的优点有： 具备markdown简单的文本标记语言； 相较于markdown有更丰富的文档排版能力； 可以在生成文档时直接运行插入的代码块，并将运行结果输出在最终文档中。 1.2 基本语法 Rmarkdown的基本语法与markdwon相同，几乎所有markdown能用的语法都可以在其中使用。 常用的markdown语法见表1.1，更详细的语法请参考Markdown官方教程 表1.1: Rmarkdown的优点 输入 结果 普通文本 普通文本 *斜体文本* 斜体文本 **加粗文本** 加粗文本 ***斜体加粗文本*** 斜体加粗文本 ~~删除线文本~~ 删除线文本 上标^文本^ 上标文本 `代码文本` 代码文本 # 一级标题 1.3 建立Rmarkdwon文件 在RStudio选择文件-新建-Rmarkdown就可以建立一个最简单的rmarkdown的模板。（图 1.1） 图1.1: 新建rmarkdown文件 新建文件后会弹出新的窗口，如图1.2所示。窗口中可以设置标题、作者和输出文件类型。在左边栏选择”From Template”会有更多的模板更选择。你也可以安装相应的R包扩展更多的模板。 图1....

加载常用的包 library(tidyverse) library(readxl) library(openxlsx) library(lubridate) 1 R基础相关 1.1 基础命令 1.1.1 set_names命令 set_names()命令可以很方便的创建带名称的向量，set_names(x, nm = x, ...)其中x表示需要赋名的变量，nm表示向量的名称，示例： set_names(1:4, letters[1:4]) # a b c d # 1 2 3 4 1.1.2 交集并集 interesect()求交集，union()并集,setdiff()补，结果如图1.1： 图1.1: R集合运算命令 1.2 数学公式测试 行内公式\(x^2+y^2=z^2\) 行间公式:\[f(x)=ax+b\] 1.3 逻辑运算符号 R中基础逻辑运算符号有（=;!=;>;<;>=;<=），返回的值是true和false，也可分别作为为数字1和0进行数学运算： x <- c(1, 2, 3, 4, 5, 6) x > 3 # [1] FALSE FALSE FALSE TRUE TRUE TRUE sum(x > 3) # [1] 3 1....