这是一个通过改变线条透明度的快速绘图。

dft$x <- dft$time
levels(dft$x) <- 0:3
dft$x <- as.numeric(dft$x)
ggplot(dft, aes(x, value, group=line)) + geom_line(size=1, alpha=0.15)

我想出了一个粗糙的解决方案，使用规则的情节。如果有人有一个解决方案，使一个更好的情节，例如。有了ggplot，我真的很乐意学习。也许ggplot中不同级别的透明度可以做到这一点。

df<-ddply(transitions,.(generation,t0,t1),nrow)
levels(df$generation) <- c(0,1,2,3)
df$generationnr <- as.numeric(as.character(df$generation))

plot(1:1, 1:1, lwd = 1, type = 'l', xlim = c(0,3), ylim = c(0,1))
for (item in 1:nrow(df))
  lines(c(df$generationnr[item],(df$generationnr[item]+1)),+
              c(df$t0[item],df$t1[item]),lwd=df$V1[item] )

使用更真实的数据，这个粗糙的解决方案变得有点不稳定，线宽难以感知。

我也被这个问题绊倒了。我用ggplot用频率作为线段的宽度来解决它。

dft <- data.frame(
  line = c(rep("X1", 4), rep("X2", 4), rep("X3", 4)), 
  time = rep(c("t1","t2","t3","t4"), 3), 
  value = c(0,1,1,1,0,0.5,1,1,0,0,1,1))

# you need a data frame with each transition and the frequency for it
dft_wide <- dft %>% pivot_wider( names_from = "time", values_from = "value")
# which columns are the different time transitions
t <- 2:5
t_seq <- paste(t, t+1, sep = ":")[-length(t)]
timeseq <- 1:4

# add the frequency for each transition
freqtable <- data.frame()
for (i in 1:length(t_seq)){
  temp <- eval(parse(text = paste0("dft_wide[", t_seq[[i]],"]"))) %>% group_by_all %>% count()
  names(temp) <- c("from", "to", "n")
  freqtable <- rbind.data.frame(freqtable, 
                                cbind.data.frame(temp, 
                                                 trans = t_seq[[i]],
                                                 tstart = timeseq[[i]], 
                                                 tend = timeseq[[i+1]]))
}

#draw the transition as separate segments and use the frequency as line width 
freqtable %>%
  ggplot(aes ( x = tstart, xend = tend, y = from, yend = to ))+
  geom_segment(aes(lwd = n))

如果您只有两个时间点，则更简单：

dft_2 <- data.frame(t1 = c(0,1,0,0,2, 1, 1), t2 = c(1,1,1,2,1,1,1))

data.frame(table(dft_2$t1, dft_2$t2)) %>%
  mutate(transition = paste(Var1, Var2))%>%
  pivot_longer(cols = c(Var1, Var2), names_to = "x", values_to = "y")%>%
  filter(Freq != 0 & !grepl("NA", transition )) %>%
  ggplot(aes ( x = x, y = y, group = transition ))+
    geom_point()+
    geom_line(aes(lwd = Freq, ))

如果这被认为是“一个更好的情节”，这是个人的判断。