search for: bplot

Hello! I have created a bplot-figure using this code: *file <- "2dcali_red.ttt" ux<-as.matrix(read.table(file, dec = ",")) mode(ux)<-'numeric' vel<-ux[,1] ang<-ux[,2] x<-ux[,3] y<-ux[,4] dat<- data.frame(ang=ang, x=x,y=y) require(rms) ddist2 <- datadist(dat) options...

Hi, I'm trying to customize a window with 2 graphs. I'm able to do the first one with something like this general example par(mfrow=c(1,2),cex.axis=0.85,cex.lab=0.80,mai=c(1.3,1,0.5,0),las=3) bplot<-barplot(bar.values,names.arg=cf.names,width=0.5,ylab="% Area held") abline(h=0.3,lty=3,col="red") abline(h=0.1,lty=3,col="blue") points(bplot,target$target/xi[nrow(xi),],pch=20) text(bplot,target$target/xi[nrow(xi),],paste(target$target,"ha"),adj=c(-0.3,...

...gt; Now, trying the examples shown via the r-help mailing list I am trying to make a plot where each of the groups gets displayed in a histogram-like fashion upwards with the number 0.1, 0.2 and so forth underneath the group. What I do is the following: > par(mar = c(6, 4, 4, 2) + 0.1) > bplot = barplot(lsu, beside=TRUE, col=colors[1:length(lsu[,1])], ylim = c(0,1.0), xaxt = "n", xlab = "") > axis(side=1,at=bplot, labels=FALSE, tick=TRUE) NULL > nam=rep("a",10) > text(bplot, par("usr")[3] - 1.5, srt = 45, adj = 1, labels = nam, xpd = TRUE)...

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: requiere(rms) n <- 1000 # define sample size set.seed(17) # so can reproduce the results age...

...s routines to make them more modular, to use lattice graphics, and to make it easier to use ggplot2 graphics. Defaults for confidence bands are now gray scale-shaded polygons. The most visable change for the user is the replacement of the plot.Design function with the Predict, plot.Predict, and bplot functions. plot.Predict is used for bivariate graphics (using lattice), and bplot is used for 3-d graphics using base graphics functions image, contour, and persp. Note that multi-panel lattice graphics are usually better than 3-d graphics for showing the effects of multiple predictors varyin...

...s routines to make them more modular, to use lattice graphics, and to make it easier to use ggplot2 graphics. Defaults for confidence bands are now gray scale-shaded polygons. The most visable change for the user is the replacement of the plot.Design function with the Predict, plot.Predict, and bplot functions. plot.Predict is used for bivariate graphics (using lattice), and bplot is used for 3-d graphics using base graphics functions image, contour, and persp. Note that multi-panel lattice graphics are usually better than 3-d graphics for showing the effects of multiple predictors varyin...

..."spacing" of the symbol being plotted. In other words, I don't want > to plot the "1" at every data point, but only at every kth point (things > get too cluttered when there are many data points). Thanks in advance! > > -- > Wolfgang Viechtbauer See function bplot defined below. Peter Wolf "bplot"<- function(x,y,k,pch="*",space.size=1/70,space.bg="white",pch.col="black",...){ # plot of x and y, type "b" with symbols at every k-th points pw 10/02 # pch: characters to be plotted # space.si...

...internally (calibrate.cph, calibrate.psm) validating a survival model with right-censored data. The polspline package is used to estimate the survival probability at a fixed time point as a function of the predicted survival probability. Some user-requested plotting features have been added to bplot and plot.Predict. Changes in version 2.1-0 * Made Predict not return invisibly if predictors not specified * New option nlines for plot.Predict for getting line plots with 2 categorical predictors * Added rename option to rbind.Predict to handle case where predictor name has changed...

...ictor=NA to Predict, summary, nomogram, survplot, gendata, you just specify the name of the predictor. For example, to get predictions for the default range of x1 and for just 2 values of x2 you might specify Predict(fit, x1, x2=c(1,3)). The next major change is the use of lattice graphics in bplot, so that now you can easily make multi-panel 3-D displays of effects in the fitted model. The package's web site is http://biostat.mc.vanderbilt.edu/rms Here is what's new: * Added levels.only option to survplot.* to remove variablename= from curve labels * Added digits argumen...

...internally (calibrate.cph, calibrate.psm) validating a survival model with right-censored data. The polspline package is used to estimate the survival probability at a fixed time point as a function of the predicted survival probability. Some user-requested plotting features have been added to bplot and plot.Predict. Changes in version 2.1-0 * Made Predict not return invisibly if predictors not specified * New option nlines for plot.Predict for getting line plots with 2 categorical predictors * Added rename option to rbind.Predict to handle case where predictor name has changed...

...ar All, The following code save my graphs as pdf: pdf("j:/mix.pdf", width = 18, height = 16) grid.newpage() pushViewport(viewport(layout = grid.layout(3,1))) vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y) print(Aplot, vp = vplayout(1, 1)) print(Bplot, vp = vplayout(2, 1)) print(Cplot, vp = vplayout(3, 1)) dev.off() How can I save it in PNG and maintain the same graph structure? Thanks -- View this message in context: http://r.789695.n4.nabble.com/ggplot2-grid-viewport-and-PNG-tp3790866p3790866.html Sent from the R help mailing list archiv...

....png") x <- table(General$PTA.Support, General$Grade.Level) #x <- table(x, exclude=NULL) #names(x) <- r ("Yes","No") yrange <- range(x,na.rm=TRUE)*1.2 if (yrange[1]>0) yrange[1] <- 0 if (yrange[2]<0) yrange[2] <- 0 bplot <- barplot(x,col=rainbow(if(is.matrix(x)) dim(x) else length(x)),beside=TRUE,legend.text=TRUE,ylim=yrange, main ="Barplot of PTA Support in Grade Levels") text(bplot,x,labels=x,pos=3,offset=.5)

...ictor=NA to Predict, summary, nomogram, survplot, gendata, you just specify the name of the predictor. For example, to get predictions for the default range of x1 and for just 2 values of x2 you might specify Predict(fit, x1, x2=c(1,3)). The next major change is the use of lattice graphics in bplot, so that now you can easily make multi-panel 3-D displays of effects in the fitted model. The package's web site is http://biostat.mc.vanderbilt.edu/rms Here is what's new: * Added levels.only option to survplot.* to remove variablename= from curve labels * Added digits argumen...

...sFeature <- as.numeric(BoxplotsFeature)     BoxplotsData <- as.numeric(which(PCIList == BoxplotsFeature))     BoxplotsData <- TotalIntensityList[BoxplotsData,]     BoxplotsHeading <- paste("Tukey boxplot (including outliers) for PCI ", BoxplotsFeature , sep = "")     bplot(as.numeric(BoxplotsData), GroupingList, style = "tukey", outlier = TRUE,   col="red", main = BoxplotsHeading,     xlab = "Groups", ylab = "Normalised Intensity", plot = TRUE)     BoxplotsFilename <- paste(BoxplotsFeature, "_Boxplot", sep = &quot...

Dear All, I would like to plot a scalar (e.g. a temperature) on a non-rectangular domain (or even better: I would simply like to be able to draw a contour plot on an arbitrary 2D domain). I wonder if there is any tool to achieve that with R. I did some online search in particular on the list archives, found several queries similar to this one but was not able to find any conclusive answer. I

...ame(x=x,y=y,times=times) #I want to recreate something like coplot with lattice coplot(y~x|times,data=df) #this doesn't work, which is an issue with co.intervals breaks<-equal.count(times) #this does work breaks<-equal.count(unclass(times)) #In the lattice book there is this outline bPlot<-plot(breaks) dPlot<-xyplot(y~x|breaks, data=df) plot(bPlot, position=c(0,0.65,1,1)) plot(dPlot, position=c(0,0,1,0.65),newpage=FALSE) #The plot is ok, but the xaxis is in numeric and not date ######################################### Jon Loehrke Graduate Research Assistant Department of Fi...

...html latex example Wtransform.sim text html latex example arrow.plot text html latex example as.image text html latex example as.surface text html latex example bplot text html latex example bplot.xy text html latex example cover.design text html latex example exp.cov text html latex example fields-internal...

...rms uses generic functions defined in other packages. For example there is a latex method in the Hmisc package, and rms has a latex method for objects of class "anova.rms" so there are anova.rms and latex.anova.rms functions in rms. I use: export(asis,bj,bjplot,bootBCa,bootcov,bootplot,bplot,calibrate,cph,catg,combineRelatedPredictors,confplot,contrast,coxphFit,cph,cr.setup,datadist,effective.df,fastbw,formatNP,gendata,gIndex,GiniMd,Glm,Gls,groupkm,Hazard,hazard.ratio.plot,histdensity,"%ia%",ie.setup,interactions.containing,legend.nomabbrev,lm.pfit,lrm,lrtest,lsp,matinv,matrx...

...idation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if conf='bands' and labelc was FALSE) * In survfit.cph, fixed bug by which n wasn't always defined * In cph, put survival::: on exact fit call * Quit ignoring zlim argument in bplot; added xlabrot argument * Added caption argument for latex.anova.rms * Changed predab to not print summaries of variables selected if bw=TRUE * Changed predab to pass force argument to fastbw * fastbw: implemented force argument * Added force argument to validate.lrm, validate.b...

...idation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if conf='bands' and labelc was FALSE) * In survfit.cph, fixed bug by which n wasn't always defined * In cph, put survival::: on exact fit call * Quit ignoring zlim argument in bplot; added xlabrot argument * Added caption argument for latex.anova.rms * Changed predab to not print summaries of variables selected if bw=TRUE * Changed predab to pass force argument to fastbw * fastbw: implemented force argument * Added force argument to validate.lrm, validate.b...