On 10/31/2013 03:04 AM, paladini at trustindata.de wrote:
Hi Jim,
thats the second time that you helped me in a short while so thanks a lot!
But it seems to me quite laborious and error-prone to first select all
the relevant countries in this long list and then to create a color vector.
But perhaps I get it all wrong.
For the color vector I first did this
imagecolors<-color.scale(mydata$GPIndex ,c(1,0,0),0,c(0,0,1))
because I wanted the colors to scale from dark red (bad ones) to dark
blue (good ones).
But it went somehow wrong. By the way can you tell me what I did wrong?
Nevertheless I than createt a color vector looking loke this:
eurocol=c("#FF0000FF",8,"#710000FF","#390000FF",8,8,"#390000FF",rep(8,10),"#2F0000FF"
,8,"#000000FF",8,"#000000FF","#000000FF" ,"#000055FF",8,"#000064FF",2,
"#000083FF",8,8,"#00008BFF" ,"#0000F0FF" ,rep(8,20),"#0000F7FF"
,rep(8,18),"#0000FFFF", rep(8,120))
And than
world.map<-map('world', fill = TRUE,col =eurocol
,xlim=c(-12,35),ylim=c(37,70))
Beside the wrong colors it worked okay.
But I am not really happy with this solution.
Did I misapprehend you?
Hi Claudi,
Maybe. You write that the transformation of GPIndex to colors "went
wrong". Let's see:
# make up GPIndex
GPIndex<-c(sample(1:100,33),rep(NA,165))
# transform to colors
eurocol<-color.scale(GPIndex,c(1,0),0,c(0,1))
world.map<-map('world',fill=TRUE,
col=eurocol,xlim=c(-12,35),ylim=c(37,70))
This gives me what I would expect, and checking the colors against
the country names (world.map$names) looks like the correct colors
have been displayed. Obviously I left a lot of areas out (missed UK
and Ireland for example) as I didn't want to overplot individual
countries with areas. Does this look okay to you?
Jim