I need different-width facets; the left plot shows the dynamic range of an experiment, and the right has the test conditions. Is there a way to have both free x and y scales with facet_wrap? It is possible in facet_grid, but even with scale="free", there is a fixed y scale. facet_wrap allows free y scale, but the x scale seems fixed. The same question was posted on a google page a few years back, but the answer is unsatisfactory.
https://groups.google.com/forum/#!topic/ggplot2/1RwkCcTRBAw
Sorry if this is a repeat here too; any help would be hugely appreciated!
mdf <- read.table(text="
strain val type
1 1 0.0000 sample
2 1 0.0140 sample
3 1 0.0175 sample
4 2 0.0025 sample
5 2 0.0260 sample
6 2 0.0105 sample
7 3 0.0190 sample
8 3 0.0725 sample
9 3 0.0390 sample
10 4 0.0560 sample
11 4 0.0695 sample
12 4 0.0605 sample
13 5 0.0735 sample
14 5 0.1065 sample
15 5 0.0890 sample
16 6 0.1135 sample
17 6 0.2105 sample
18 6 0.1410 sample
19 7 0.1360 sample
20 7 0.2610 sample
21 7 0.1740 sample
22 8 0.3850 control
23 8 0.7580 control
24 8 0.5230 control
25 9 0.5230 control
26 9 0.5860 control
27 9 0.7240 control")
library(ggplot2)
p<-ggplot(mdf, aes(reorder(strain, val), val))+
labs(x="Strain", y="intensity")+
geom_boxplot()+
geom_point()+
facet_grid(~type, scales ="free", space="free_x")
p
## free x, fixed y. why?
q<-ggplot(mdf, aes(reorder(strain, val), val))+
labs(x="Strain", y="intensity")+
geom_boxplot()+
geom_point()+
facet_wrap(~type, scales ="free")
q
## free y, fixed x. why?
I can't be absolutely certain, but I think the answer is no - with ggplot2 commands. I don't think it's a good idea either because it might not be obvious to a reader that the scales on the y-axes are different. Nevertheless, if you must have the plot, you can adjust the widths of the panels of your q plot using the ggplot grob layout. Note that the first panel has two x-values, and the second panel has seven x-values. Therefore change the default widths of the panels to 2null and 7null respectively.
Edit: Updating to ggplot2 2.2.0
library(ggplot2)
library(grid)
# get mdf data frame from the question
# Your q plot
q <- ggplot(mdf, aes(factor(strain), val)) +
labs(x = "Strain", y = "intensity") +
geom_boxplot() +
geom_point() +
facet_wrap( ~ type, scales = "free")
q
# Get the ggplot grob
gt = ggplotGrob(q)
# Check for the widths - you need to change the two that are set to 1null
gt$widths
# The required widths are 4 and 8
# Replace the default widths with relative widths:
gt$widths[4] = unit(2, "null")
gt$widths[8] = unit(7, "null")
# Draw the plot
grid.newpage()
grid.draw(gt)
# I think it is better to have some extra space between the two panels
gt$widths[5] = unit(1, "cm")
grid.newpage()
grid.draw(gt)
Or, get R to determine the relative widths and the panels.
gt = ggplotGrob(q)
# From 'dfm', get the number of 'strain' for each 'type'.
# That is, the number x-breaks in each panel.
library(dplyr)
N <- mdf %>% group_by(type) %>%
summarise(count = length(unique(strain))) %>%
`[[`(2)
# Get the column index in the gt layout corresponding to the panels.
panelI <- gt$layout$l[grepl("panel", gt$layout$name)]
# Replace the default panel widths with relative heights.
gt$widths[panelI] <- unit(N, "null")
# Add extra width between panels (assuming two panels)
gt$widths[panelI[1] + 1] = unit(1, "cm")
## Draw gt
grid.newpage()
grid.draw(gt)
Also, for those trying to use @Sandy's answer with dplyr:
library(dplyr)
N<-mdf%>% group_by(type)%>% summarise(count = length(unique(strain)))
# Get the column index in the gt layout corresponding to the panels.
panelI <- gt$layout$l[grepl("panel", gt$layout$name)]
# Replace the default panel widths with relative heights.
gt$widths[panelI] <- lapply(N$count, unit, "null")