I am using the following with corrplo
t:
require(\"corrplot\") ## needs the corrplot package
corrplot(cor(lpp_axis1, lpp_axis2), method=c(\"number\")
Update2
Actually a real reproducible example is now, thanks to code and data being provided:
d1 <- read.csv(url("http://misterdavis.org/r_wiki/r_results_1231_2010"))
lpp_axis1 <- with(d1, data.frame("Compile Source Code" = Q3A.1,
"View Source Code" = Q3A.2,
"Change Source Code" = Q3A.3,
"Write Documentation" = Q3A.8,
"File Bug Reports"= Q3B.3,
"Ask Questions" = Q3B.5,
"Provide Answers" = Q3B.6,
"Overall Participation" = Q3a3bConsolidated))
lpp_axis2 <- with(d1, data.frame("Identification" = Q1,
"Overall Learning" = Q6Consolidated,
"Learning Programming" = Q6.1,
"Learning about Computers" = Q6.2,
"Learning Teamwork" = Q6.3))
corrplot(cor(lpp_axis1, lpp_axis2), method=c("number"), bg = "grey10",
addgrid.col = "gray50", tl.cex=1,
tl.col = "black",
col = colorRampPalette(c("yellow","green","navyblue"))(100))
dev.new()
corrplot(cor(lpp_axis1, lpp_axis2), method=c("number"), bg = "grey10",
addgrid.col = "gray50", tl.cex=2,
tl.col = "black",
col = colorRampPalette(c("yellow","green","navyblue"))(100))
The dev.new()
allows you to have both on screen at once to compare, without splitting the plotting region into two panels.
The tl.offset
seems to cause more problems than it is worth, so I have left it out. I include the two figures below:
With tl.cex = 1
With tl.cex = 2
As you can see, I can't reproduce the problem you are seeing; tl.cex
is only changing the size of the size of the axis labels. Note this is without using tl.offset
but the rest of the plotting code is the same as yours.
This is what I get from packageDescription()
:
R> packageDescription("corrplot")
Package: corrplot
Type: Package
Title: visualization of a correlation matrix
Version: 0.30
Date: 2010-05-30
Author: Taiyun Wei
Suggests: seriation, cairoDevice, Cairo,
Maintainer: Taiyun Wei
Description: The corrplot package is a graphical display of a
correlation matrix, confidence interval. It also contains some
algorithms to do matrix reordering.
License: GPL-2 | GPL-3
LazyLoad: yes
URL: http://corrplot.r-forge.r-project.org
Repository: CRAN
Repository/R-Forge/Project: corrplot
Repository/R-Forge/Revision: 45
Date/Publication: 2010-05-31 07:44:14
Packaged: 2010-05-30 20:39:16 UTC; rforge
Built: R 2.13.0; ; 2011-04-01 12:33:21 UTC; unix
-- File: /home/gavin/R/libs/corrplot/Meta/package.rds
Compare it with the one on your system and try the example above so we are running exactly the same code for comparison.
Original Example Here is a reproducible example:
require(corrplot)
data(mtcars)
corr <- cor(mtcars)
corrplot(corr, method = "number", tl.cex = 2)
Update
Ok, I see the problem now. With tl.offset
, you push the labels away from the correlation graphic further out into the margins. This seems either a bug on infelicity in corrplot()
as if you don't set tl.offset
it scales the correlation graphic to accommodate the labels. The only solution I can see is to not set tl.offset
at all, or set it to a smaller value Here is an extreme example:
layout(matrix(1:2, ncol = 2))
corrplot(corr, method = "number", tl.cex = 2, tl.offset = 3)
corrplot(corr, method = "number", tl.cex = 2)
layout(1)
You can improve things, by altering the relative dimensions of the plot device - if on screen, increase the width or height (or both) of the plot device window until all the labels are visible. If this is another device (pdf()
or png()
say), then you'll need to alter the dimensions of the device when you create it.
Original Which [The reproducible example] gives:
You aren't clear what the problem with the x and y axis labels, but corrplot()
alters the plot margins to accommodate the labels. You have already stated the relative size of these x and y axis labels by setting argument tl.cex = 2
. If you want the labels bigger, increase this value:
corrplot(corr, method = "number", tl.cex = 4)
and if you want smaller labels, set tl.cex
to a smaller value:
corrplot(corr, method = "number", tl.cex = 0.8)
Given these are the only x and y labels on the plot, does this help? If not, which labels need altering?