在ggplot geom_path中添加轻微曲线（或弯曲）以使路径更易于阅读

Question

此问题是来自之前已回答的问题的新问题：Plot mean of data within same ggplot

正如您在下面的.jpg图片中看到的那样 - 红线geom_path被挤压在一起，使得线条难以解释。有没有办法稍微“弯曲”曲线，以减少重叠/聚合？在点周围进行某种平滑或弯曲，使线条不重叠？

这是我的语法：

orbit.plot <- ggplot(orbit.data, aes(x=OpM, y=INVT, colour=Subj, label=Year)) +
  geom_point(size=7, shape=20) + 
  geom_path(size=1.5) +
  ggtitle("Title Orbits") +
  geom_text(data=subset(orbit.data,Year==2006 | Year==2014), aes(label=Year, vjust=1, hjust=1)) +
  theme(panel.background = element_rect(fill = 'white', colour = 'red'),  
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank()) +
  geom_vline(xintercept=0, size=1) +
  geom_hline(yintercept=7, size=1) +
  scale_y_continuous(limits = c(7, 15), breaks=seq(7,15,1/2))

这是数据集的输入：

structure(list(Year = c(2006L, 2006L, 2007L, 2007L, 2008L, 2008L, 
2009L, 2009L, 2010L, 2010L, 2011L, 2011L, 2012L, 2012L, 2013L, 
2013L, 2014L, 2014L), Subj = structure(c(2L, 1L, 2L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L), .Label = c("TMC", 
"HMC"), class = "factor"), OPM = c(0.088, 0.09, 0.095, 0.078, 
0.085, 0.08, -0.023, 0.019, 0.009, 0.043, 0.025, 0.065, 0.0199, 
0.029, 0.06, 0.055, 0.088, 0.065), Invt = c(14.5, 10.3, 13.8, 
10, 13.3, 9.5, 12.3, 8, 13.5, 8, 14.3, 10, 13.2, 8.5, 13.8, 9.5, 
13.8, 9.75)), .Names = c("Year", "Subj", "OpM", "INVT"
), class = "data.frame", row.names = c(NA, -18L))

谢天谢地。

编辑：更新：基本上，这个图的原因是随着时间的推移显示x / y变量“运动”。在X轴上 - 我正在绘制一个比率（在这种情况下是操作边际）。在Y轴上 - 我显示了一个周期测量（在这种情况下库存转向。）曲线的“弯曲”肯定会“弯曲”数据本身 - 但是使用X / Y测量我正在使用，数据被理解为两（2）个小数 - 因此数据的“轻微”弯曲不会污染数据试图描绘的“本质”。

Answer 1

你可以拼凑它：

library(ggplot2)
orbit.data <- structure(list(Year = 
   c(2006L, 2006L, 2007L, 2007L, 2008L, 2008L,  2009L, 2009L,  2010L, 2010L, 
     2011L, 2011L, 2012L, 2012L, 2013L,  2013L, 2014L, 2014L), 
   Subj = structure(c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
                      2L, 1L, 2L, 1L, 2L, 1L), 
          .Label = c("TMC", "HMC"), class = "factor"), 
   OPM = c(0.088, 0.09, 0.095, 0.078,  0.085, 0.08, -0.023, 0.019, 0.009, 
           0.043, 0.025, 0.065, 0.0199, 0.029, 0.06, 0.055, 0.088, 0.065), 
   Invt = c(14.5, 10.3, 13.8, 10, 13.3, 9.5, 12.3, 8, 13.5, 8, 14.3, 
            10, 13.2, 8.5, 13.8, 9.5, 13.8, 9.75)), 
   .Names = c("Year", "Subj", "OpM", "INVT"), class = "data.frame", 
   row.names = c(NA, -18L))

lsdf <- list()
plot.new()
for (f in unique(orbit.data$Subj)){
  psdf <- orbit.data[orbit.data$Subj==f,]
  newf <- sprintf("%s - xspline",f)
  lsdf[[f]] <- data.frame(xspline(psdf[,c(3:4)], shape=-0.6, draw=F),Subj=newf)
}
sdf <- do.call(rbind,lsdf)   
orbit.plot <- ggplot(orbit.data, aes(x=OpM, y=INVT, colour=Subj, label=Year)) +
  geom_point(size=5, shape=20) + 
  geom_point(data=orbit.data,size=7, shape=20,color="black") + 
  geom_path(size=1) +
  geom_path(data=sdf,aes(x=x,y=y,label="",color=Subj),size=1) + 
  ggtitle("Title Orbits") +
  geom_text(data=subset(orbit.data,Year==2006 | Year==2014), 
             aes(label=Year, vjust=1, hjust=1)) +
  theme(panel.background = element_rect(fill = 'white', colour = 'red'),  
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank()) +
  geom_vline(xintercept=0, size=1) +
  geom_hline(yintercept=7, size=1) +
  scale_y_continuous(limits = c(7, 15), breaks=seq(7,15,1/2))
print(orbit.plot)

给出了：

有很多方法可以做到这一点，我怀疑这是最好的。您可以使用shape调用中的xspline参数进行播放，以获得不同的曲率。