路径：操作父-子'中的事件列表；节点'；在R

我感兴趣的是根据预先指定的事件列表（例如诊断、手术、治疗1、治疗2、死亡）可视化患者的路径

测试数据集可能如下所示：

df <- structure(list(ID = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L), .Label = c("a", "b", "c"), class = "factor"), 
    Event = structure(c(2L, 3L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 
    5L, 1L), .Label = c("death", "diagnosis", "surgery", "treatment1", 
    "treatment2"), class = "factor"), date = structure(c(14610, 
    14619, 16667, 14975, 14976, 14977, 15074, 15084, 15006, 15050, 
    15051, 15053), class = "Date")), .Names = c("ID", "Event", 
"date"), row.names = c(NA, 12L), class = "data.frame")

> df
   ID      Event       date
1   a  diagnosis 2010-01-01
2   a    surgery 2010-01-10
3   a      death 2015-08-20
4   b  diagnosis 2011-01-01
5   b    surgery 2011-01-02
6   b treatment1 2011-01-03
7   b treatment2 2011-04-10
8   b      death 2011-04-20
9   c  diagnosis 2011-02-01
10  c    surgery 2011-03-17
11  c treatment2 2011-03-18
12  c      death 2011-03-20

（请注意，datediff列中的数字不是实际数字） i、 e.一系列具有日期差异的父子节点

这将允许我绘制节点，并对事件之间的时间进行进一步的描述性分析

我发现了一个用于绘制节点的包（见下文），但是，如果有人知道一种允许箭头宽度反映父子组合数量的方法/包，那就太棒了

 require(igraph) # possible package to use
 parents<-c("A","A","A","A","A","A","C","C","F","F","H","I")
 children<-c("I","I","I","I","B","A","D","H","G","H","I","J")
 begats<-data.frame(parents=parents,children=children)
 graph_begats<-graph.data.frame(begats)
 tkplot(graph_begats)

require（igraph）#可使用的软件包
家长将数据折叠起来，给出每个家长-孩子组合及其发生次数的计数，例如：

# put the previous event against the current event, and drop the rows before the first event:
df$Event <- as.character(df$Event)
df$PreEvent <- with(df, ave(Event,ID,FUN=function(x) c(NA,head(x,-1)) ) )
result <- df[!is.na(df$PreEvent),c("ID","PreEvent","Event")]

# aggregate the combos by how often they occur:
result <- aggregate(list(count=rownames(result)),result[c("PreEvent","Event")],FUN=length)
#    PreEvent      Event count
#1    surgery      death     1
#2 treatment2      death     2
#3  diagnosis    surgery     3
#4    surgery treatment1     1
#5    surgery treatment2     1
#6 treatment1 treatment2     1

# plot in igraph, adjusting the edge.width to account for how many cases of each
# parent-child combo exist:
library(igraph)
g <- graph.data.frame(result)
plot(g,edge.width=result$count)

#将上一个事件与当前事件相对，并删除第一个事件前的行：
df$事件
# put the previous event against the current event, and drop the rows before the first event:
df$Event <- as.character(df$Event)
df$PreEvent <- with(df, ave(Event,ID,FUN=function(x) c(NA,head(x,-1)) ) )
result <- df[!is.na(df$PreEvent),c("ID","PreEvent","Event")]

# aggregate the combos by how often they occur:
result <- aggregate(list(count=rownames(result)),result[c("PreEvent","Event")],FUN=length)
#    PreEvent      Event count
#1    surgery      death     1
#2 treatment2      death     2
#3  diagnosis    surgery     3
#4    surgery treatment1     1
#5    surgery treatment2     1
#6 treatment1 treatment2     1

# plot in igraph, adjusting the edge.width to account for how many cases of each
# parent-child combo exist:
library(igraph)
g <- graph.data.frame(result)
plot(g,edge.width=result$count)