similar to: Ggplot2: saving a grid with multiple plots

I need to plot two graphics just like the example below but for some reason your example crashes. Using facet_wrap seems to be the cause: library(ggplot2) upper <- with(economics, data.frame(date,value = psavert, position = "upper")) upper lower <- with(economics, data.frame(date,value = unemploy,position = "lower")) lower #upper$date <-

I have data that plots over time with four different variables. I would like to combine them in one plot using facet_grid, where each variable gets its own sub-plot. The following code resembles my data require(ggplot2) require(reshape2) subm <- melt(economics, id='date', c('psavert','uempmed','unemploy')) mcsm <- melt(data.frame(date=economics$date,

Dear all, One of the functions that I wrote (ggsave.latex) extents the functionality of a function (ggsave) in another package (ggplot2). Instead of copying all the information I would like to create a link in the helpfile of ggsave.latex to the helpfile of ggsave. I tried \code{\link{ggsave}} and \code{\link{ggplot2::ggsave}}, but neither worked. Both cases gave a 'missing link' warning.

Hello, I am having trouble specifying a suitable nlme model. My data structure is described by gd <- groupedData(ppath ~ lcut | exp, outer = ~ bait, inner = ~ weight, data = d) i.e. the response (ppath) of several subjects (sub) was measured at levels of a continuous variable (lcut). Subjects were given either of one level of a factor (bait), and all subjects were measured at two levels

is there a way to label points in a graph using text(locator(1),"text") after ggplot() or qplot() ? > qplot(date, psavert, data = economics, geom = "line",main="jhdjd")->p > p+opts(text(locator(1),"HHHH"),new=T) does not work. -- View this message in context: http://www.nabble.com/text%28%29-to-label-points-in-ggplot-tp23545135p23545135.html Sent

I just updated to R 2.14 with ggplot2 0.9 and am finding bugs. > ggplot2 "GPL-2" "2.14.0" This example is taken from pg 101 in the ggplot book. > plot <- qplot(date, psavert, data = economics, geom = "line") + > ylab("Personal savings rate") + geom_hline(xintercept = 0, colour = > "grey50")' > plot +

Dear all, I am struggling with a problem and I am hoping that somebody could point me in the right direction. I am trying to match the locations of two peak patterns. A is the true pattern. B is the measured pattern. Hence A and B have a very strong linear relationship. The problem is that B can contain false positives: peaks due to noise instead of the true pattern from A. An additional problem

Dear all, Is there an elegant way to add citations of packages when using Sweave? Ideally I'd like a function which creates a Bibtex-file with the packagenames as keys. The idea is to use \cite{packagename} or \cite{R} in LaTeX. I know you can get the Bibtex entry with toBibtex(citation("packagename")). But after updating R or a package one needs to update the bib-file too. When

Dear all, I'm using Roxygen for the first time and I'm getting a rather cryptic error message. I must be doing something wrong but I have no clue what is it. Any suggestions? Regards, Thierry roxygenize("AFLP", roxygen.dir = "AFLP", copy.package = FALSE, unlink.target = FALSE) Writing AFLP.outlier to AFLP/man/AFLP.outlier.Rd Writing AFLP.outlier to

I'm a newbie to LLVM and I've really been struggling to write a pass which changes the behavior of the following function: #include<stdlib.h>#include<stdio.h>#include<string.h>void foo(char* bar){const char* path;path=getenv(<SOME_ENV_VAR>); if (path!=NULL){strcpy(bar,path);}else{printf("env_var not set!");}} In the pass, I hope to invoke

Dear all, Could someone point me to a function or algorithm to generate random bivariate binomial data? Some details about what I'm trying to do. I have a dataset of trees who were categorised as not damaged or damaged. Each tree is measured twice (once in two consecutive years). The trees can recover from the damage but the data is clearly correlated. As a (un)damaged tree is more likely

Dear all, I'm plotting some points on a graph where both axes need to have the same scale. See the example below. Coord_equal does that trick but in this case it wastes a lot of space on the y-axis. Setting the limits of the y-axis myself was no avail. Any suggestions to solve this problem? library(ggplot2) ds <- data.frame(x = runif(1000, min = 0, max = 300000), y = runif(1000, min =

Hi All, I Am new to Wine, and I try to get Office 97 to work, but the M$ Office installer dosen't work yet. Se bug 150 on:

Hi all! I am having some problems with PowerPoint 2000 running in a wine 0.0.20050725-1 debian package. It works fine when I am creating a new presentation, but when I am opening old presentations it freezes after displaying the first slide and I am unable to even exit from ppoint. The console shows the following: err:syslevel:_EnterSysLevel (0x7f117380, level 2): Holding 0x7fb1fea0, level 3.

Dear all, Is it possible to incorporate a nested design in GEE? I have measurements on trees that where measured in two years. The trees are nested in plots. Each plot contains 24 trees. The number of plots is 72. Hence we would expect 2 * 24 * 72 = 3456 data points. A few are missing, so we end up wih 3431 data points. This is what I have tried until now. #assuming independence between trees

Code for this post is shown below.   Two issues: (1) grid.gedit doesn't work from source file Reproduce - copy the code shown below into an R source file, and of course save off in the appropriate location.  Then copy the the first line "source("C:/TestCode.R")" into R and run. Notice that you get the following error:Error in editDLfromGPath(gPath, specs, strict, grep,

Text is really small and legend boxes are huge in this plot when saved to .png with ggsave. Plot is correct (i.e. looks the same as the screen) when saved with dev.print. Saving to .pdf with ggsave give the correct output. I'm a noob at ggplot2 so this may be user error rather than a bug. However the interface to ggsave seems simple enough to exclude many possibilities for screwing this up

Dear all, I'm using zeroinfl() from the pscl-package for zero inflated Poisson regression. I would like to calculate (aproximate) prediction intervals for the fitted values. The package itself does not provide them. Can this be calculated analyticaly? Or do I have to use bootstrap? What I tried until now is to use bootstrap to estimate these intervals. Any comments on the code are welcome.

Two different ways: library(ggplot2) x=5 size=50 A=data.frame(X=sample(x, size, replace=T), Y=sample(x, size, replace=T),a=rep(1:2,each=25));A # Facetting qplot(X,Y,data=A) + geom_jitter(position=position_jitter(width=.03)) + facet_grid(.~a) # Or with vp p=qplot(X, Y, data=A) + geom_jitter(position=position_jitter(width=.03)) ggsave(p, file='main.png') p1=qplot(X, Y, data=A) +

Estimado Linis, Si estás bajo Windows y no has cambiado las rutas (también dentro de las funciones) es posible que no funcionen bien. Por ejemplo la sentencia paste('img/',plotName,'.png', sep='') deberías cambiarla por: paste('img\',plotName,'.png', sep='') o incluso por paste('img\\',plotName,'.png', sep='')