背景
我一直在使用ggplot和冲积包装创建一个冲积图(类似于Sankey图)来可视化随时间变化的频率差异以及它们的起源。
举个例子,我创建了一个简单的数据集,包含100个假想的病人,并对新冠肺炎进行筛选。基线时,所有患者新冠肺炎均为阴性。假设1周后,所有患者都再次进行检测:现在,30例阳性,65例阴性,5例结果不确定。再过一周,30例阳性患者仍为阳性,10例由阴性转为阳性,其余均为阴性。
data <- data.frame(analysis = as.factor(rep(c("time0", "time1", "time2"), each = 4)),
freq = rep(c(30, 10, 55, 5), 3),
track = rep(1:4, 3),
response = c("neg","neg","neg","neg", "pos", "neg", "neg", "inconc", "pos", "pos", "neg", "neg"))
# analysis freq track response
#1 time0 30 1 neg
#2 time0 10 2 neg
#3 time0 55 3 neg
#4 time0 5 4 neg
#5 time1 30 1 pos
#6 time1 10 2 neg
#7 time1 55 3 neg
#8 time1 5 4 inconc
#9 time2 30 1 pos
#10 time2 10 2 pos
#11 time2 55 3 neg
#12 time2 5 4 neg目标
其目的是创建一个冲积图,使这些患者的“轨迹”(即典故)在一段时间内可视化,从而在两周后可视化结果的起源。类似于:

尝试
我设法完成了这个数字的主要部分:
library(tidyverse)
library(ggalluvial)
ggplot(data, aes(x = analysis, stratum = response, alluvium = track, y = freq, fill = response), col = "black") +
geom_flow(stat = "alluvium") +
geom_stratum(alpha = .5) +
scale_fill_manual(values = c("grey", "green", "red"))

问题
然而,我却不能清楚地分辨出这些阶层。现在,它们都是相邻的,这导致了一个完全“填充”的矩形。
如何在冲积图中使用ggalluvial包( R )中的地层/冲积层空间?
发布于 2021-04-15 18:24:58
https://stackoverflow.com/questions/67113888
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