my ggplot R-code works perfectly ok with my other datasets but I'm stumbled with why it's not working for one particular data set. See image below where the filled confidence interval stops at 0.10:

For reproducing the problem:

library(nlme)
library(ggeffects)
library(ggplot2)
SurfaceCoverage <- c(0.02,0.04,0.06,0.08,0.1,0.12,0.02,0.04,0.06,0.08,0.1,0.12)
SpecificSurfaceEnergy <- c(18.0052997,15.9636971,14.2951057,13.0263081,13.0816591,13.3825573,2.9267577,2.2889628,1.8909175,1.0083036,0.5683574,0.1681063)
sample <- c(1,1,1,1,1,1,2,2,2,2,2,2)

highW <- data.frame(sample,SurfaceCoverage,SpecificSurfaceEnergy)

highW$sample <- sub("^", "Wettable", highW$sample)
highW$RelativeHumidity <- "High relative humidity"; highW$group <- "Wettable"
highW$sR <- paste(highW$sample,highW$RelativeHumidity)

dfhighW <- data.frame(
  "y"=c(highW$SpecificSurfaceEnergy),
  "x"=c(highW$SurfaceCoverage),
  "b"=c(highW$sample),
  "sR"=c(highW$sR)
)

mixed.lme <- lme(y~log(x),random=~1|b,data=dfhighW)
pred.mmhighW <- ggpredict(mixed.lme, terms = c("x"))

(ggplot(pred.mmhighW)   
    geom_line(aes(x = x, y = predicted))            # slope
    geom_ribbon(aes(x = x, ymin = predicted - std.error, ymax = predicted   std.error), 
                fill = "lightgrey", alpha = 0.5)    # error band
    geom_point(data = dfhighW,                      # adding the raw data (scaled values)
               aes(x = x, y = y, shape = b))   
    xlim(0.01,0.2)   
    ylim(0,30)  
    labs(title = "")   
    ylab(bquote('Specific Surface Energy ' (mJ/m^2)))  
    xlab(bquote('Surface Coverage ' (n/n[m]) ))  
    theme_minimal()
)

Can someone advise me how to fix this? Thanks.

CodePudding user response：

The last part of your ribbon has disappeared because you have excluded it from the plot. The lower edge of your ribbon is the following vector:

pred.mmhighW$predicted - pred.mmhighW$std.error
#> [1]  3.91264018  2.37386628  1.47061258  0.82834206  0.32935718 -0.07886245

Note the final value is a small negative number, but you have set the y axis limits with:

ylim(0, 30)

So anything negative will be cut off. If you change to

ylim(-2, 30)

You get

CodePudding user response：

I don't know whether this is already answered previously, but coord_cartesian and scales::squish are two solutions to this problem.

• coord_cartesian adjusts the viewport without adjusting the spacing of grid lines etc. (unlike xlim()/scale_*_continuous(limits = ...), which will "zoom")
• scales::squish() is suboptimal if you are "squishing" lines and points, not just edgeless polygons (in the case of fill/polygons, squishing and clipping produce the same results)

gg0 <- (ggplot(pred.mmhighW) 
      geom_ribbon(aes(x = x, ymin = predicted - std.error,
                      ymax = predicted   std.error), 
                  fill = "lightgrey", alpha = 0.5)
      theme_minimal()
)

## set lower limit to 5 for a more obvious effect
gg0   coord_cartesian(ylim = c(5, 30))
gg0   scale_y_continuous(limits = c(5, 30),
                         ## oob = "out of bounds" behaviour
                         oob = scales::squish)