Faheem Mitha
2013-05-12 11:48:37 UTC
Hello,
I've posted a ggplot2 question to Stack Overflow,
http://stackoverflow.com/q/16501999/350713. I've reproduced the text of
that question below. The SO question also contains an image.
Is there some way to disable email sending by Google groups? I can
read replies via Gmane.
Regards, Faheem
###################################################################
I have a plot generated by ggplot2, which contains two legends. The
placing of the legends is not ideal, so I would like to adjust
them. I've been trying to imitate the method shown in [the answer to
"How do I position two legends independently in
ggplot"](http://stackoverflow.com/a/13327793/350713). The example
shown in that answer works. However, I can't get the method described
to work for my situation.
'm using R 2.15.3 (2013-03-01), ggplot2_0.9.3.1, lattice_0.20-13, gtable_0.1.2, gridExtra_0.9.1 on Debian squeeze.
Consider the plot generated by `minimal.R`. This is similar to
my actual plot.
########################
minimal.R
########################
get_stat <- function()
{
n = 20
q1 = qnorm(seq(3, 17)/20, 14, 5)
q2 = qnorm(seq(1, 19)/20, 65, 10)
Stat = data.frame(value = c(q1, q2),
pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
variable = c(rep('true', length(q1)), rep('data', length(q2))))
return(Stat)
}
stat_all<- function()
{
library(ggplot2)
library(gridExtra)
stathuman = get_stat()
stathuman$dataset = "human"
statmouse = get_stat()
statmouse$dataset = "mouse"
stat = merge(stathuman, statmouse, all=TRUE)
return(stat)
}
simplot <- function()
{
Stat = stat_all()
Pvalue = subset(Stat, variable=="true")
pdf(file = "CDF.pdf", width = 5.5, height = 2.7)
stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type",
labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))
print(stat)
dev.off()
}
simplot()
This results in the following plot. As can be seen, the `Data type`
and `Pvalue` legends are not well positioned. I modified this code to
`minimal2.R`.
With Version 1, which should put the legend on the top, the code runs
without error, but no legend is shown.
EDIT: There are two boxes displayed, one on top of the other. The top
one is blank. If I do not set the heights in grid.arrange(), as
suggeted by @baptiste, then the legend and the plot are both placed in
the bottom box. If I set the height as shown, then I don't see the
legend.
With Version 2, I get this error.
Error in UseMethod("grid.draw") :
no applicable method for 'grid.draw' applied to an object of class "c('gg', 'ggplot')"
Calls: simplot -> grid.draw
EDIT: If I use print(plotNew) as suggested by @baptiste, then I get the following error
Error in if (empty(data)) { : missing value where TRUE/FALSE needed
Calls: simplot ... facet_map_layout -> facet_map_layout.grid ->
locate_grid.
I tried to figure out what is going on here, but I could not find much
relevant information.
NOTES:
1. I'm not sure why I'm getting the staircase effect for the empirical
CDF. I'm sure there is an obvious explanation. Please enlighten me if
you know.
2. I'm willing to consider alternatives to this code and even ggplot2 for
producing this graph, if anyone can suggest alternatives,
e.g. matplotlib, which I have never seriously experimented with.
3. Adding
print(ggplot_gtable(ggplot_build(stat2)))
to `minimal2.R` gives me
TableGrob (7 x 7) "layout": 12 grobs
z cells name grob
1 0 (1-7,1-7) background rect[plot.background.rect.186]
2 1 (3-3,4-4) strip-top absoluteGrob[strip.absoluteGrob.135]
3 2 (3-3,6-6) strip-top absoluteGrob[strip.absoluteGrob.141]
4 5 (4-4,3-3) axis-l absoluteGrob[GRID.absoluteGrob.129]
5 3 (4-4,4-4) panel gTree[GRID.gTree.155]
6 4 (4-4,6-6) panel gTree[GRID.gTree.169]
7 6 (5-5,4-4) axis-b absoluteGrob[GRID.absoluteGrob.117]
8 7 (5-5,6-6) axis-b absoluteGrob[GRID.absoluteGrob.123]
9 8 (6-6,4-6) xlab text[axis.title.x.text.171]
10 9 (4-4,2-2) ylab text[axis.title.y.text.173]
11 10 (4-4,4-6) guide-box gtable[guide-box]
12 11 (2-2,4-6) title text[plot.title.text.184]
I don't understand this breakdown. Can anyone explain? Does
guide-box correspond to the legend, and how does one know this?
########################
minimal2.R
########################
get_stat <- function()
{
n = 20
q1 = qnorm(seq(3, 17)/20, 14, 5)
q2 = qnorm(seq(1, 19)/20, 65, 10)
Stat = data.frame(value = c(q1, q2),
pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
variable = c(rep('true', length(q1)), rep('data', length(q2))))
return(Stat)
}
stat_all<- function()
{
library(ggplot2)
library(gridExtra)
library(gtable)
stathuman = get_stat()
stathuman$dataset = "human"
statmouse = get_stat()
statmouse$dataset = "mouse"
stat = merge(stathuman, statmouse, all=TRUE)
return(stat)
}
simplot <- function()
{
Stat = stat_all()
Pvalue = subset(Stat, variable=="true")
pdf(file = "CDF.pdf", width = 5.5, height = 2.7)
## only include data type legend
stat1 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)
## Extract data type legend
dataleg <- gtable_filter(ggplot_gtable(ggplot_build(stat1)), "guide-box")
## only include pvalue legend
stat2 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))
## Extract pvalue legend
pvalleg <- gtable_filter(ggplot_gtable(ggplot_build(stat2)), "guide-box")
## no legends
stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)
## Add data type legend: version 1 (data type legend should be on top)
## plotNew <- arrangeGrob(dataleg, stat, heights = unit.c(dataleg$height, unit(1, "npc") - dataleg$height), ncol = 1)
## Add data type legend: version 2 (data type legend should be somewhere in the interior)
## plotNew <- stat + annotation_custom(grob = dataleg, xmin = 7, xmax = 10, ymin = 0, ymax = 4)
grid.newpage()
grid.draw(plotNew)
dev.off()
}
simplot()
--
I've posted a ggplot2 question to Stack Overflow,
http://stackoverflow.com/q/16501999/350713. I've reproduced the text of
that question below. The SO question also contains an image.
Is there some way to disable email sending by Google groups? I can
read replies via Gmane.
Regards, Faheem
###################################################################
I have a plot generated by ggplot2, which contains two legends. The
placing of the legends is not ideal, so I would like to adjust
them. I've been trying to imitate the method shown in [the answer to
"How do I position two legends independently in
ggplot"](http://stackoverflow.com/a/13327793/350713). The example
shown in that answer works. However, I can't get the method described
to work for my situation.
'm using R 2.15.3 (2013-03-01), ggplot2_0.9.3.1, lattice_0.20-13, gtable_0.1.2, gridExtra_0.9.1 on Debian squeeze.
Consider the plot generated by `minimal.R`. This is similar to
my actual plot.
########################
minimal.R
########################
get_stat <- function()
{
n = 20
q1 = qnorm(seq(3, 17)/20, 14, 5)
q2 = qnorm(seq(1, 19)/20, 65, 10)
Stat = data.frame(value = c(q1, q2),
pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
variable = c(rep('true', length(q1)), rep('data', length(q2))))
return(Stat)
}
stat_all<- function()
{
library(ggplot2)
library(gridExtra)
stathuman = get_stat()
stathuman$dataset = "human"
statmouse = get_stat()
statmouse$dataset = "mouse"
stat = merge(stathuman, statmouse, all=TRUE)
return(stat)
}
simplot <- function()
{
Stat = stat_all()
Pvalue = subset(Stat, variable=="true")
pdf(file = "CDF.pdf", width = 5.5, height = 2.7)
stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type",
labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))
print(stat)
dev.off()
}
simplot()
This results in the following plot. As can be seen, the `Data type`
and `Pvalue` legends are not well positioned. I modified this code to
`minimal2.R`.
With Version 1, which should put the legend on the top, the code runs
without error, but no legend is shown.
EDIT: There are two boxes displayed, one on top of the other. The top
one is blank. If I do not set the heights in grid.arrange(), as
suggeted by @baptiste, then the legend and the plot are both placed in
the bottom box. If I set the height as shown, then I don't see the
legend.
With Version 2, I get this error.
Error in UseMethod("grid.draw") :
no applicable method for 'grid.draw' applied to an object of class "c('gg', 'ggplot')"
Calls: simplot -> grid.draw
EDIT: If I use print(plotNew) as suggested by @baptiste, then I get the following error
Error in if (empty(data)) { : missing value where TRUE/FALSE needed
Calls: simplot ... facet_map_layout -> facet_map_layout.grid ->
locate_grid.
I tried to figure out what is going on here, but I could not find much
relevant information.
NOTES:
1. I'm not sure why I'm getting the staircase effect for the empirical
CDF. I'm sure there is an obvious explanation. Please enlighten me if
you know.
2. I'm willing to consider alternatives to this code and even ggplot2 for
producing this graph, if anyone can suggest alternatives,
e.g. matplotlib, which I have never seriously experimented with.
3. Adding
print(ggplot_gtable(ggplot_build(stat2)))
to `minimal2.R` gives me
TableGrob (7 x 7) "layout": 12 grobs
z cells name grob
1 0 (1-7,1-7) background rect[plot.background.rect.186]
2 1 (3-3,4-4) strip-top absoluteGrob[strip.absoluteGrob.135]
3 2 (3-3,6-6) strip-top absoluteGrob[strip.absoluteGrob.141]
4 5 (4-4,3-3) axis-l absoluteGrob[GRID.absoluteGrob.129]
5 3 (4-4,4-4) panel gTree[GRID.gTree.155]
6 4 (4-4,6-6) panel gTree[GRID.gTree.169]
7 6 (5-5,4-4) axis-b absoluteGrob[GRID.absoluteGrob.117]
8 7 (5-5,6-6) axis-b absoluteGrob[GRID.absoluteGrob.123]
9 8 (6-6,4-6) xlab text[axis.title.x.text.171]
10 9 (4-4,2-2) ylab text[axis.title.y.text.173]
11 10 (4-4,4-6) guide-box gtable[guide-box]
12 11 (2-2,4-6) title text[plot.title.text.184]
I don't understand this breakdown. Can anyone explain? Does
guide-box correspond to the legend, and how does one know this?
########################
minimal2.R
########################
get_stat <- function()
{
n = 20
q1 = qnorm(seq(3, 17)/20, 14, 5)
q2 = qnorm(seq(1, 19)/20, 65, 10)
Stat = data.frame(value = c(q1, q2),
pvalue = c(dnorm(q1, 14, 5)/max(dnorm(q1, 14, 5)), d = dnorm(q2, 65, 10)/max(dnorm(q2, 65, 10))),
variable = c(rep('true', length(q1)), rep('data', length(q2))))
return(Stat)
}
stat_all<- function()
{
library(ggplot2)
library(gridExtra)
library(gtable)
stathuman = get_stat()
stathuman$dataset = "human"
statmouse = get_stat()
statmouse$dataset = "mouse"
stat = merge(stathuman, statmouse, all=TRUE)
return(stat)
}
simplot <- function()
{
Stat = stat_all()
Pvalue = subset(Stat, variable=="true")
pdf(file = "CDF.pdf", width = 5.5, height = 2.7)
## only include data type legend
stat1 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=guide_legend(override.aes = list(size = 2))) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)
## Extract data type legend
dataleg <- gtable_filter(ggplot_gtable(ggplot_build(stat1)), "guide-box")
## only include pvalue legend
stat2 = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""))
## Extract pvalue legend
pvalleg <- gtable_filter(ggplot_gtable(ggplot_build(stat2)), "guide-box")
## no legends
stat = ggplot() + stat_ecdf(data=Stat, n=1000, aes(x=value, colour = variable)) +
theme(legend.key = element_blank(), legend.background = element_blank(), legend.position=c(.9, .25), legend.title = element_text(face = "bold")) +
scale_x_continuous("Negative log likelihood") +
scale_y_continuous("Proportion $<$ x") +
facet_grid(~ dataset, scales='free') +
scale_colour_manual(values = c("blue", "red"), name="Data type", labels=c("Gene segments", "Model"), guide=FALSE) +
geom_area(data=Pvalue, aes(x=value, y=pvalue, fill=variable), position="identity", alpha=0.5) +
scale_fill_manual(values = c("gray"), name="Pvalue", labels=c(""), guide=FALSE)
## Add data type legend: version 1 (data type legend should be on top)
## plotNew <- arrangeGrob(dataleg, stat, heights = unit.c(dataleg$height, unit(1, "npc") - dataleg$height), ncol = 1)
## Add data type legend: version 2 (data type legend should be somewhere in the interior)
## plotNew <- stat + annotation_custom(grob = dataleg, xmin = 7, xmax = 10, ymin = 0, ymax = 4)
grid.newpage()
grid.draw(plotNew)
dev.off()
}
simplot()
--