On Aug 13, 2010, at 11:25 PM, Duncan Mackay wrote:
Hi David
I do not know if you have done something like this.
I had tried a few efforts like that, starting with an examination of
str(bp.plot) as you demonstrate.
I tried str(bp.plot) which gave the section about the regions (for
colours) as:
$ panel.args.common:List of 8
..$ x : num [1:2500] 27 28 29 29.9 30.9 ...
..$ y : num [1:2500] 141 141 141 141 141 ...
..$ z : num [1:2500] -1.43 -1.41 -1.39 -1.36 -1.34 ...
..$ at : num [1:10] -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
..$ region : logi FALSE
..$ zlab :List of 3
.. ..$ label: chr "log odds"
.. ..$ rot : num 90
.. ..$ cex : num 1
..$ labels : logi TRUE
..$ contour: logi TRUE
I tried (with a bplot object named "bldLT40"):
bldLT40$legend$right$args$key$at <- c(-0.233, seq(.50, 2.25,
by=0.25),
seq(2.5, 5.0, by=0.5), 6:10)
... and then tried
bldLT40$panel.args$at <- c(-0.233, seq(.50, 2.25, by=0.25), seq(2.5,
5.0, by=0.5), 6:10)
Neither of these efforts changed the boundaries beteen colors in the
plot area. The first effort changed the legend scal,e but that just
created a "misalignment" of the colors of plot area and the legend. I
would be interested in either a strategy that lets one alter the
color
level changes of the z variable (which in bplot-created objects is
"zhat", or lets one specify the values at which contour lines are
drawn in contourplot.
Thanks for your efforts.
--
David.
I added the col.region and colours from a plot levelplot that I had
done to see what would occur to the trellis parameters. No colours
were produced when plotted.
bp.plot <- bplot(p, lfun=contourplot, color.key = TRUE, col.regions
=
c
("#FFFFFF
","#00FFFF","#A9E2FF","#8080FF","#0000FF","#FFD18F","#FF0000") )
$ panel.args.common:List of 10
..$ x : num [1:2500] 27 28 29 29.9 30.9 ...
..$ y : num [1:2500] 141 141 141 141 141 ...
..$ z : num [1:2500] -1.43 -1.41 -1.39 -1.36 -1.34 ...
..$ at : num [1:10] -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
..$ region : logi FALSE
..$ color.key : logi TRUE
..$ zlab :List of 3
.. ..$ label: chr "log odds"
.. ..$ rot : num 90
.. ..$ cex : num 1
..$ labels : logi TRUE
..$ contour : logi TRUE
..$ col.regions: chr [1:7] "#FFFFFF" "#00FFFF" "#A9E2FF"
"#8080FF" ...
So it has been added to the panel.args.common, whether you can
access these are another matter.
I then tried
bp.plot <- bplot(p, lfun=contourplot, par.settings = list(axis.text
= list(cex = 0.65)), color.key = TRUE, col.regions =
c
("#FFFFFF
","#00FFFF","#A9E2FF","#8080FF","#0000FF","#FFD18F","#FF0000") )
which changed the size of the axis text so it may be the case of
having to add the col.regions etc to the appropriate list in
par.settings
I'll leave you to amend and access the colours.
You may have to add values for the wireframe/levelplot arguments
like "at" etc. and col.regions (I think that is the function) to
produce an appropriate colour range of your choice
It is a while since I have delved into these sorts of plots.
Need some sustenance.
Regards
Duncan
Duncan Mackay
Department of Agronomy and Soil Science
University of New England
ARMIDALE NSW 2351
Email home: mac...@northnet.com.au
At 10:33 14/08/2010, you wrote:
I have a plot produced by function bplot (package = rms) that is
really a lattice plot (class="trellis"). It is similar to this plot
produced by a very minor modification of the first example on the
bplot help page:
require(rms)
n <- 1000 # define sample size
set.seed(17) # so can reproduce the results
age <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol <- rnorm(n, 200, 25)
sex <- factor(sample(c('female','male'), n,TRUE))
label(age) <- 'Age' # label is in Hmisc
label(cholesterol) <- 'Total Cholesterol'
label(blood.pressure) <- 'Systolic Blood Pressure'
label(sex) <- 'Sex'
units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc
units(blood.pressure) <- 'mmHg'
# Specify population model for log odds that Y=1
L <- .4*(sex=='male') + .045*(age-50) +
(log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
# Simulate binary y to have Prob(y=1) = 1/[1+exp(-L)]
y <- ifelse(runif(n) < plogis(L), 1, 0)
ddist <- datadist(age, blood.pressure, cholesterol, sex)
options(datadist='ddist')
fit <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)),
x=TRUE, y=TRUE)
p <- Predict(fit, age, cholesterol, sex='male', np=50) # vary sex
last
bp.plot <- bplot(p, lfun=contourplot)
bp.plot
I have tried a variety of efforts at using update (which I assume
is a
lattice function although I can find no help page for it. It does
appear in some of the lattice hep pages and my understanding is
that
it pushes objects onto the list structure of a plot object. I've
also
tried adding to it with llines()
#-------------
Oh, never mind. I recovered a memory that I had seen a solution on
rhelp and had saved it. Turns out it was from Peter Ehlers, to
whom I
offer thanks. I was trying to add a step function: ht and weight
from
a dataframe, "bld":
trellis.focus("panel", 1, 1)
panel.lines(x=bld$inches, y=bld$BMI28, type='s')
trellis.unfocus()
Success!
Now... how do I control the color levels in levelplot or
contourplot???
David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
