search for: grey50

...(not my choice!) in Windows Vista. The problem is that I want to use stat_smooth() to add an fitted linear model line along with its 95% confidence band, but I cannot seem to get the confidence band in a format that would import into Word. I have read the documentation and am using the fill="grey50" argument to eliminate transparency as a potential problem. But still, I have tried nearly all export formats and the only one that correctly shows the confidence band is PDF, which I cannot import into Word as a vector graphic. This makes me wonder if the fill="grey50" option is w...

...2,15,22,34,21) y2 <- c(40, 130, 150, 145, 40, 30) par(las=1, mar=c(4, 4, 2, 4)) plot.new() #plot.window(range(x1), c(0, 12)) plot.window(range(x2), c(0, 170)) plot.window lines(x1, y1) lines(x2, y2) points(x1, y1, pch=16, cex=2) points(x2, y2, pch=21, bg="white", cex=2) par(col="grey50", fg="grey50", col.axis="grey50") axis(1, at=seq(0, 16, 4)) axis(2, at=seq(0, 170, 10)) axis(3, at=seq(0, 70, 10)) axis(4, at=seq(0, 170, 10)) box(bty="u") mtext("k", side=1, line=2, cex=0.8) mtext("GO terms", side=2, line=2, las=0, cex=0.8...

Like this? # example using qplot library(ggplot2) meanprice <- tapply(diamonds$price, diamonds$cut, mean);meanprice cut <- factor(levels(diamonds$cut), levels = levels(diamonds$cut)) qplot(cut, meanprice, geom="bar", stat="identity", fill = I("grey50")) dev.new() # create a new graph to compare with qplot # Example using ggplot ggdata <- data.frame(meanprice,cut);ggdata ggplot(ggdata,aes(y=meanprice,x=cut)) + geom_bar(fill="grey50",stat='identity') Felipe D. Carrillo Supervisory Fishery Biologist Department of th...

...st(fun = key1), vertical = TRUE ) ##set some parameters for the plot #---------------------------------------------------------------------------------------- trellis.par.set( dot.line=list(col = "grey90", lty="dashed"), axis.line=list(col = "grey50"), axis.text=list(col ="grey50", cex=0.8), panel.background=list(col="transparent"), par.xlab.text= list(col="grey50"), ) ## Create the dot plot #---------------------------------------------------------------------------------------- with(Cal_dat, dotplo...

...3 + X4 + X5 + X6 + X7, data=graph4, xlim=c(0,130), #scales = list(alternating = 1, cex=1.2), xlab="", panel = function (x,y) { stack=F groups=country panel.barchart(x,y, col=c("grey20","grey100","grey50","grey83","grey33","grey67","grey0")) panel.abline(v = 20, lty = 2, col = "blue") } ) But now I would like to add vertical lines at certain values (20, 40, etc.), but because I couldn't make the abline command w...

...or VT 2-utskrivning 51.97531 bwplot(Medelvärde ~ Skalor| Kön , kt, panel = "panel.superpose", groups = Tillfälle,scales = list(x = list(rot = 45),cex=0.7,alternating=2), panel.groups = "panel.linejoin",lty=c(1:3),lwd=3,col=c("steelblue","grey50","green4"), ylab = list(label = "skalpoäng (0-100)", cex = 0.8), xlab = list(label = "skalor", cex = 0.8), key = list(lines = Rows(list(col=c("steelblue","grey50","green4"),lty=c(1:3)), c(1:3, 0)),...

Hi, I am newbie user of ggplot and would like some assistance in implementing time series plots. I'd like to know how the tsdiag plot can be made in ggplot? Thanks Harsh Singhal Decisions Systems, Mu Sigma Inc.

...t(levels(Cal_dat$Commodity)), title="Ore type", points=list(pch=21,cex=1.3,fill=col.pat,col="black") ) ##set some parameters for the dotplot trellis.par.set( dot.line=list(col = "transparent"), axis.line=list(col = "grey90"), axis.text=list(col ="grey50", cex=0.8), panel.background=list(col="grey98"), par.xlab.text= list(col="grey50") ) ## Create the dot plot dotplot(reorder(Mine, Resc_Gt)~ Resc_Gt,groups=Commodity, data=Cal_dat, cex=1.2, pch=21, aspect=2.0, key=plot.key, col="black", fill=col.pa...

...st(fun = key1), vertical = TRUE ) ##set some parameters for the plot #---------------------------------------------------------------------------------------- trellis.par.set( dot.line=list(col = "grey90", lty="dashed"), axis.line=list(col = "grey50"), axis.text=list(col ="grey50", cex=0.8), panel.background=list(col="transparent"), par.xlab.text= list(col="grey50"), ) ## Create the dot plot #---------------------------------------------------------------------------------------- with(Cal_dat, dotplo...

...e * 0.8), legend.title = theme_text(size = base_size * 0.8, face = "bold", hjust = 0), legend.position = "right", panel.background = theme_rect(fill = "white", colour = NA), panel.border = theme_rect(fill = NA, colour = "grey50"), panel.grid.major = theme_line(colour = "black", size = 0.2), panel.grid.minor = theme_line(colour = "black", size = 0.5), panel.margin = unit(0.25, "lines"), strip.background = theme_rect(fill = "grey80", colour...

...list(fun = key1), vertical = FALSE ) ##set some parameters for the plot #---------------------------------------------------------------------------------------- trellis.par.set( dot.line=list(col = "grey95", lty=1), axis.line=list(col = "grey50"), axis.text=list(col ="grey50", cex=0.8), panel.background=list(col="transparent") ) ## Create the dot plot #---------------------------------------------------------------------------------------- # some mean values for reference lines first ave_dat<-aggregate(Cal_...

Dear list,   I made boxplots using ggplot and want to control for x- and yaxis. Using "plot" I can do it by setting cex.axis equally to any size but can't figure out how to do it with ggplot.     ggplot(dat, aes(x = factor(time), y = volume)) + opts(axis.title.x=theme_text(size=8),axis.title.y=theme_text(size=8)) + geom_boxplot() + geom_jitter(aes(colour = id))+labs(x =

...black", size = 0.5, linetype = 1),? ? ? text = ? ? ? ? ? ? ? element_text(family = base_family, face = "plain", colour = "black", size = base_size, hjust = 0.5, vjust = 0.5, angle = 0, lineheight = 0.9),? ? ? axis.text = ? ? ? ? ?element_text(size = rel(0.8), colour = "grey50"),? ? ? strip.text = ? ? ? ? element_text(size = rel(0.8)), ? ? ? axis.line = ? ? ? ? ?element_blank(),? ? ? axis.text.x = ? ? ? ?element_text(family = base_family, size = base_size * 0.7, lineheight = 0.8, vjust = 1.2),? ? ? axis.text.y = ? ? ? ?element_text(family = base_family, size = base_...

...",] # male trap catches w<-Hecke[Hecke$m_w=="w",] # female trap catches barplot(m$trapcatch, ylab="Y", space=0.5, col=c("grey0"), ylim=c(0,450), las=2, cex.lab=0.9, cex.axis=0.9, cex.names=0.9) barplot(w$trapcatch,space=0.5, add=TRUE, beside=FALSE, col=c("grey50"), xaxt="n", yaxt="n") Thanks a lot Sibylle [[alternative HTML version deleted]]

Can't installe packag maDB or limma. Error is shown as Using R version 2.13.1, biocinstall version 2.8.4. Installing Bioconductor version 2.8 packages: Is there any other way to draw volcano plot ? Thanks [[alternative HTML version deleted]]

My question is related to plot( ) in the mgcv package. Before modelling the data, a few predictors were transformed to normalize them. Therefore, the x-axes in the plots show transformed predictor values. How do I back-transform the predictors so that the plots are easier to interpret? Thanks in advance, Suzan -- Suzan Pool Oregon State University Cooperative Institute for Marine

...but the output does not seem good. Poly<read.table("C:\\Users\\Momadou\\Documents\\AreaMonthly.csv",sep=";",dec=",",header=TRUE) Poly y <-MeanArea x <-SdArea z <-Date matplot(x,cbind(y,z),type="n") polygon(c(x,rev(x)),c(y,rev(z)),col="grey50") Thank you in advance -- View this message in context: http://r.789695.n4.nabble.com/Polygon-tp4186283p4186283.html Sent from the R help mailing list archive at Nabble.com.

...> 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 + scale_x_date(major = "10 years") Error in continuous_scale(aesthetics, "date", identity, breaks = breaks, : unused argument(s) (major = "10 years")> plot + scale_x_date(limits = as.Date(c("2004-01-01", "2005-01-01")),fo...

...is what bg="transparent" would mean for a screen device. I think it should mean "white", but the difference would emerge if the device was copied. An alternative for the windows() device (which can have a canvas larger than the device region) would be the canvas colour (default grey50). In that case one might want a default of "white". Clearly some thought would be needed to get the png devices to handle transparency, but it should be doable. Brian -- Brian D. Ripley, ripley@stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.u...

...ill=rgb) + scale_y_continuous(name=" ",breaks=" ") + scale_x_continuous(name=" ",breaks=" ") + scale_fill_identity() + coord_cartesian() + opts(aspect.ratio = .75) + facet_grid(unitX ~ unitY,margins=FALSE) The result is a plot where all tiles are filled with grey50, and not the data values. I've also tried this variation with the same results: ggplot(data = somdf, mapping = aes(x = pixX, y = pixY)) + geom_tile(data = somdf, fill=rgb) + scale_y_continuous(name=" ",breaks=" ") + scale_x_continuous(name=" ",breaks=" "...