similar to: re-arranging unsorted data for surface/contour plot

I am trying to do a surface profile plot. data is X                  Y(1)             Z(1) 1-jan-02       2002        number 2-jan-02       2002        number . . . 1-jan-03       2003 (Y2)     number Z(2) 2-jan-03       2003 (Y2)     number Z(2) . . . until dec 31 2007.   I used the plot3d funtions to build a scatter point plot. Call rinterface.rrun("library(rgl)") Call

I have carried out a spatial interpolation (Kriging) using surf.gls() The contour plot looks very plausible and the image plot is o.k too. The problem is, hovever, that I need the vectorized isoplethes, as in contour(). Unfortunately, I found no solution to get the internal data from contour(). Is there a possibility to extract contour lines as x-y-polygon from a grid without hacking plot3d.c?

I found it useful to have contour be able to do line widths ... hope that the guts haven't changed an enormous amount in the current development version ... the patches are relatively trivial, mostly going by analogy with lty and col (although in my ignorance it took me a while to figure out what UNPROTECT(2) was and why it should be changed to UNPROTECT(3) ... hope this is useful. Ben

Dear R-list, Is there a way to convert the typical long R data-format to a 1-line per subject format? I have data formatted as: Group subj condition variable 1 1 1 746.36625 2 2 1 1076.152857 1 3 1 1076.152857 2 4 1 657.4263636 1 5 1 854.1266667 2 6 1 1191.676154 1 7 1 1028.175385 1 1 2 46.36625 2 2 2 76.152857 1 3 2 76.152857 2 4 2 57.4263636 1 5 2 54.1266667 2 6 2 191.676154 1 7 2 028.175385

Full_Name: Dominik Heide Version: 2.3.1 OS: Linux (Suse 9.3) Submission from: (NULL) (134.76.220.200) The contour functions has sommewhere (I think in .../main/plot3d.c) a maximum number of line segments that is set using a define. The contour line in my data too long for this and therefore not correct analysed (I get the message 'contour(): circular/long seglist -- bug.report()!').

I am struggling with a contour plot. I want to place a cross over the minimum. alas, I don't seem to be able to map axes appropriately. here is what I mean: N <- 1000 rm <- rnorm(N, mean=0.0, sd=0.4) rx <- rnorm(N, mean=0.0, sd=0.4) rt <- rnorm(N, mean=0.0, sd=0.4) exploss <- function(hdgM,hdgX) { ## this could be any function that is not vectorized losscosts <-

Hi list, I'm using barplot2 form the gplots package to plot a few numbers (I want to add SD bars later). However, I would like the y-axis not to start from 0 but 500. When I add the parameters YLIM, something goes wrong. The graph is not 'cut off' at 500. Instead the bars seems to sink trough the bottom of the graph. Because its a little hard to explain, here is a self-containing

All: Anyone have an idea about how to plot a PLS biplot on the x-y plane under a 3-D surface? Preferably a 3-D surface such as one created with rgl.surface() (meaning, I would love an interactive plot when all is said and done). I have seen examples which combine a 3-d surface with contour plot (e.g.

Hi list, I'm currently processing textual data and I would really appreciate some help with one off my problems. I have a set of strings and I want to count how often each of this strings appears in this set. This is not very difficult and can be done as: TB<-table(my_set) plot(TB) However, I also want to collapse across sub-strings. This is, I want a sub-string ss of string S to be

R-0.99.0a now plots contour labels from contour(), but the values in levels seem to be coerced to integer. Reproduce by: > set.seed(2) > contour(matrix(runif(36),nrow=6), labcex=1.2) and compare with: > set.seed(2) > contour(matrix(10*runif(36),nrow=6), labcex=1.2) Ray Brownrigg -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list --

Hi R help, What is the best way to plots surfaces in 3 dimensions? I also have the following availability problem with "plot3d" and "scatterplot3d", and "wireframe": install.packages("scatterplot3d") Warning: unable to access index for repository http://cran.ch.r-project.org/bin/macosx/leopard/contrib/2.10 Warning message: In getDependencies(pkgs,

Hi, I've used the Mathematica to produce 3D graphics, contour plots of a bivariate normal distribution Now I want make these graphics in R, but i do not know how. I would like to: - Plot a 3D graph for some different variance matrix - Plot the contour plots - Find and try to plot (in the 3d graph ou contour plot) the (1-a)% confidence region based in a chi-square(a) with the degrees of

Hi List, I have a problem plotting data using the lineplot.CI command in the sciplot package. I want to plot the data of 2 experimental cases using different lines (traces). Time is on the X-axis. The tricky thing is that the data collection in the second case started later than for the first case. This is to say: the first n data points for the second case are missing. So far so good. However,

I have the following data table: [,1] [,2] [,3] [,4] [,5] [1,] 2575 1927 1754 581 354 [2,] 1156 810 730 541 237 [3,] 417 297 199 125 110 [4,] 281 132 132 47 58 [5,] 152 84 87 54 19 Each column represents a time interval expressed in nano-seconds Each row represents an energy interval expressed m=n MeV Each table value represents the average gamma rays intensity

Dear list, I have a data frame with a number of events (factor) and the times at which they occurred (continuous variable): event time A 10 A 12 B 15 A 17 C 13 ... Is it possible in R to make a plot against time of the cumulative frequency of occurrence of each event? This would be, a raising line for each factor. Regards, Dieter

You'll find that it is a lot easier to do it in R: # lets first simulate a bivariate normal sample library(MASS) bivn <- mvrnorm(1000, mu = c(0, 0), Sigma = matrix(c(1, .5, .5, 1), 2)) # now we do a kernel density estimate bivn.kde <- kde2d(bivn[,1], bivn[,2], n = 50) # now plot your results contour(bivn.kde) image(bivn.kde) persp(bivn.kde, phi = 45, theta = 30) # fancy contour with

Dear R users, I have a problem in plotting 3 dimensional graph using mixed models. My model is sur_prop ~ afr_c+I(afr_c^2)+I(afr_c^3)+byear_c+I(byear_c^2)+I(byear_c^3)+I(byear_c^4)+(1|Studyparish)+afr_c:byear_c +afr_c:I(byear_c^2)+afr_c:I(byear_c^3)+afr_c:I(byear_c^4)+I(afr_c^2):byear_c+I(afr_c^2):I(byear_c^2)+I(afr_c^2):I(byear_c^3)+I(afr_c^2):I(byear_c^4) This is a study on the effect of

First time user, so sorry if I don't understand protocol.. Anyway, I have created a data frame consisting of pearson's R values at various x and y coordinates and then plotted this using filled.contour. My data is similar to fMRI data except that it is a surface map reconstructed from histological sections. I like the results but would like to know how contours were detected. Google search

The following example just "hangs", i.e. the final contour() does not terminate. x <- pi*(0.5+((-13):12))/36 w <- 0.377*cos(2*x)*sqrt(abs(cos(2*x))) v <- c(rep(-1.47,13),rep(1.722,13))*abs(sin(x))^1.5 cr <- outer(w,w)+outer(v,v) s <- sqrt(diag(cr)) cr <- cr/outer(s,s) contour(cr[1:26,26:1],levels=seq(-1,1,0.1),axes=T) --please do not edit the information below--

Hello, I have a dataset with 4 variables, each consisting of a vector, all with the same length. I start by interpolating the first three variables using the function "interp", and plot the interpolation successfully using "filled.contour". I then interpolate the first two variables and a fourth using "interp" again, but when I try to overlay the contour lines