search for: grey30

...fferent, the legend gets "scrambled", in that the order of the colours does not match the labels. My code is below. Can anyone tell me how to get around this? (R 2.2.6 for Windows, ggplot2 version 2_0.5.7) Thanks, Pedro library(ggplot2) Data: > plotdata2 x y group 1 1 0.1 grey30 2 2 0.2 grey30 3 3 0.3 grey10 4 4 0.4 grey90 5 1 0.1 grey30 6 2 0.2 grey60 7 3 0.3 grey60 8 4 0.4 grey90 9 1 0.1 grey60 10 2 0.2 grey10 11 3 0.3 grey90 12 4 0.4 grey30 13 1 0.1 grey90 14 2 0.2 grey60 15 3 0.3 grey10 16 4 0.4 grey10 > levels(plotdata2$group) [1] "grey10" "...

...g code, but it does not work: barplot(cs.not.log.bp[c(1:2),], xlab = "Conservation status", ylab = "Number of species", col = c("grey90","grey80"),names = cs.names, ylim = c(0,250), space = 2) barplot(cs.not.log.bp[c(3:4),], col = c("grey60","grey30"), beside = T,add = T,names.arg = NA) legend("topright",c("IUCN Terrestrial","IUCN Marine","National CS Terrestrial","National CS Marine"), col = c("grey90","grey80","grey60","grey30"), pch = 15) What...

...ge y.high=rnorm(length(age),250,25)+10*age plot(age,y.high,type='n',ylim=c(100,400),ylab='Y Range',xlab='Age (years)') lines(age,y.low,col='grey') lines(age,y.high,col='grey') Is it possible to fill the area between the 2 lines filled with, for example, 'grey30' ? thanks very much in advance, David Freedman ----- David Freedman Atlanta -- View this message in context: http://www.nabble.com/fill-in-area-between-2-lines-with-a-color-tp18556096p18556096.html Sent from the R help mailing list archive at Nabble.com.

...;,ylab="",type="p", data=ordinate) abline(v=0,h=0) par(new=TRUE) # Define cars vector with 8 values cars <- c(1,1,1,1,1,1,1,1) # Define colors in each sector color1 <- c("grey80","grey80","grey80","grey80","gray80","grey30","grey20","gray10" ) ## gray10=<0.0001, gray20<0.001, gray30<0.01, gray40=<0.05, gray 80=>0.05 # Putting sector levels car_labels <- c(1,2,3,4,5,6,7,8) car_labels <- paste(car_labels,sep="") # Create a pie chart with defined heading and custo...

...but it does not work: barplot(cs.not.log.bp[c(1:2),], xlab = "Conservation status", ylab = "Number of species", col = c("grey90","grey80"), names = cs.names, ylim = c(0,250), space = 2) barplot(cs.not.log.bp[c(3:4),], col = c("grey60","grey30"), beside = T,add = T,names.arg = NA) legend("topright",c("IUCN Terrestrial","IUCN Marine","National CS Terrestrial","National CS Marine"), col = c("grey90","grey80","grey60","grey30"), pch = 15)...

...#39;, 'JA', 'SR', 'PC', 'JS', 'CB', 'AG') colors=gray.colors(length(rownames(data))) rang <- c(1:length(rownames(data))) plot(serie0, serie1, pch=rang, col='black', xlab='ABK', ylab='CMJ') abline(lm(serie1 ~ serie0),col='grey30') legend('bottomright' ,legend=rownames(data), pch=rang, col='black', cex=.7) title(main='IUB (abk-cmj)/cmj *100 (XY)', sub=paste('correlation:',cor(serie0,serie1)), cex.sub=0.75, font.sub=3, col.sub='grey30') ¿cómo podría identificar de forma automatiza...

...ng, col='black', xlab='ABK', ylab='CMJ') legend('bottomright' ,legend=rownames(data), pch=rang, col='black', cex=.7) title(main='IUB (abk-cmj)/cmj *100 (XY)', sub=paste('correlation:',cor(serie0,serie1)), cex.sub=0.75, font.sub=3, col.sub='grey30') mylm<-lm(serie1~serie0) abline(mylm,col="red") newx<-seq(min(serie0),max(serie0),length.out=length(serie0)) prd<-predict(mylm,newdata=data.frame(serie0=newx),interval = c("confidence"), level = 0.90,type="response") lines(newx,prd[,3],col="red&qu...

Number of subjects = 25 Mean of Sample = 77 Standard Deviation (s) = 12 sem = 2.4 df = 24 The claim is that population mean is less than 80 * > 80 So our H0 (null hupotheis) is * > 80 > qt(.95,24) [1] 1.710882 > qt(0.05, 24) [1] -1.710882 tstat = -1.25 on t24 falls between 1.711 (.95,24) and *1.711 (.005,24) How Could I sketch t curve for the above data where my * would be at the

...i=c(2,0.2,1.8,0.2), mai=c(0.4, 0.4, 0.5, 0.1) ) my.input <- read.table("input.data", header=FALSE, sep="\t") my.input.exp <- read.table("exp.data", header=FALSE, sep="\t") hist(my.input.exp[,2], breaks=40,freq = FALSE,xlab="", border = "grey30", ylab="", main="") hist(my.input[,2], breaks=40,freq = FALSE,xlab="", ylab="", main="", border = "red",add =TRUE) mtext("Fraction", side=2, line=2, cex=0.7) box() ====================================================== -- V...

...try + pressofficer|period, data=graph5, as.table=T, xlim=c(0,150), layout=c(3,1), par.strip.text=list(cex=1.5), scales = list(alternating = 3, cex=1.2, tick.number=5), xlab="", col=c("grey15","grey75","grey30","grey90","grey45","grey0","grey60","grey100"), #col=c(grey(100:1/100), grey(50:1/100), grey(0:1/100)), stack=T) Unfortunately, in the first two periods there are much less data, hence the bars are much shorter in those two p...

...95.n4.nabble.com/file/n4648669/step_plot_in_default_color.png> [version 2- producing wrong colour] #try greyScale, didn't work all <-qry_r3_AFF0_CumRate_pooled all <- subset(all, trt_label %in% c('ace','ctrlAM','met')) greyScale <-c("grey15","grey30","grey45") ggplot(all, aes(x=AFF0, y=cum_rate_AFF0_pooled, group=trt_label))+ geom_step(direction="hv", size=3.0)+ scale_y_continuous("Rates of initiating first orientation flight", limits=c(0,0.6), expand=c(0,0), breaks=c(0,0.2,0.4,0.6)) + scal...

...0]) #Draw outlines of Strata polygon(strlong,strlat,border=T,density=0) par(cex=.8) legend(-61.7,42.6, c("Below 2.0","2.0 to 4.0","4.0 to 6.0","6.0 to 8.0","8.0 to 10.0","10 & Above"), fill=c('grey5','grey12','grey30','grey45','grey62','grey99'),ncol=2,bty="o", bg='white') text(-61.7,42.6,"Temperature Anomaly",adj=c(0,0)) ##############Coding used for grey background issue. require(grid) library(lattice) background<-trellis.par.get("background...

The data is of two forms, ie one numeric and another ordinal ie 1.5 and <.5. The X Value is a factor. I'm trying to create a lattice conditioned plot with the following characteristics: 1) The plot is conditioned using the form (Conductivity~Day|Valve) 2) The plot should use a barplot for the ordinal (<.5) and dots for the numeric (1.5) 3) A line should be created specifying a

Hi, I have a question which is a little off-topic but then again, it should stay in the boundaries of what can be done with available R functions. Has anyone pointers to tutorials or the like where one can get inspiration on how to visualize some "spatial" statistics? I want to analyze different statistics of 60 counties in a country. I have a shape file for those counties thus I can

...31.25 55 13.75 330 DS 19 0.5 2 6/8/2002 Six_Foot 6 23.75 58.75 17.5"),header=T) closeAllConnections() library(plotrix) soil.texture(soil.dat[,c(9,10,11)],main='',show.lines=TRUE,show.names=TRUE,pch=soil.dat$Region_Num,cex=soil.dat$Region_Sym,col.names="grey10",col.lines="grey30",col.symbols=soil.dat$Region_Col) legend(x=0.10,y=0.9,c("Upstream","Downstream"),pch=c(1,20),col=c("blue","red"),bty="o",bg="white",box.col="white") title(main="Soil Texture",line=-1,cex=2.5) -- View this message...

...3B3B3B", "grey24", "#3D3D3D", "grey25", "#404040", "grey26", "#424242", "grey27", "#454545", "grey28", "#474747", "grey29", "#4A4A4A", "grey30", "#4D4D4D", "grey31", "#4F4F4F", "grey32", "#525252", "grey33", "#545454", "grey34", "#575757", "grey35", "#595959", "grey36", "#5C5C5C&q...