Hi
The devil is in the detail of the components so here is a toy example
to give you an idea in 2D but 5D
It is somewhat easier to interpret if you condition. You may be able
to visualize in 3D not all can.
3D can be a problem if distinguishing points are 180 degrees apart in
the preferred viewing aspect.
You can see 1 but not the other.
Here is an toy example using lattice and latticeExtra packages
library(lattice)
library(latticeExtra)
set.seed(123)
data = cbind(expand.grid(lat =
rep(1:4,4),long=rep(1:4,each=4),time=month.abb[1:4],direction=c("N","S","E","W")
), speed= rnorm(4096))
useOuterStrips(wireframe(speed~long*lat|time*direction,data))
# or
useOuterStrips(levelplot(speed~long*lat|time*direction,data))
# or
useOuterStrips(contourplot(speed~long*lat|time*direction,data))
# OR
# from http://lmdvr.r-forge.r-project.org/figures/figures.html fig
6.9 Adding useOuterStrips gives more space for panels.
# (code starts from 6.5)
library("locfit")
env <- environmental
env$ozone <- env$ozone^(1/3)
env$Radiation <- equal.count(env$radiation, 4)
fm1.env <- lm(ozone ~ radiation * temperature * wind, env)
fm2.env <-
loess(ozone ~ wind * temperature * radiation, env,
span = 0.75, degree = 1)
fm3.env <-
loess(ozone ~ wind * temperature * radiation, env,
parametric = c("radiation", "wind"),
span = 0.75, degree = 2)
fm4.env <- locfit(ozone ~ wind * temperature * radiation, env)
w.mesh <- with(env, do.breaks(range(wind), 50))
t.mesh <- with(env, do.breaks(range(temperature), 50))
r.mesh <- with(env, do.breaks(range(radiation), 3))
grid <-
expand.grid(wind = w.mesh,
temperature = t.mesh,
radiation = r.mesh)
grid[["fit.linear"]] <- predict(fm1.env, newdata = grid)
grid[["fit.loess.1"]] <- as.vector(predict(fm2.env, newdata = grid))
grid[["fit.loess.2"]] <- as.vector(predict(fm3.env, newdata = grid))
grid[["fit.locfit"]] <- predict(fm4.env, newdata = grid)
useOuterStrips(levelplot(fit.linear + fit.loess.1 + fit.loess.2 +
fit.locfit ~ wind * temperature | radiation, data = grid))
Not knowing if the parameters are continuous makes a difference.
Regards
Duncan
Duncan Mackay
Department of Agronomy and Soil Science
University of New England
Armidale NSW 2351
Email: home: mac...@northnet.com.au
I know you will have more data than this but perhaps a contour plot
At 05:49 17/06/2012, you wrote:
On Jun 16, 2012, at 3:18 PM, Charles Berry wrote:
zoeita <zoe-allcock <at> live.co.uk> writes:
Hi,
I have had a look around the forums and I can't seem to find
anything that
works with my data. I have lats, longs, time, tidal speed and
direction and
need to plot this in an xy plot to determine changes over time.
contour and
cloud have been recommended to me as a way to do this but I can't
figure out
how to get 5 dimensions into this. I want lat and long as my x and
y, time
as my z, direction as w and speed as different colours. I imagine
it's a
lot easier than I think it is - I am very new to R. Could anyone
please
help with a starting point for this?
See
http://blog.revolutionanalytics.com/2012/03/see-the-wind.html
and the links therein.
I suggest looking at 'arrow.plot' in package 'fields'. It will not be
colored, but rather placing oriented arrows whose length is
proportional to velocity. Your request for x, y, time coordinates may
also lead you to the 'rgl' package, or to the 'animation' package.
--
David Winsemius, MD
West Hartford, CT
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and provide commented, minimal, self-contained, reproducible code.
