I work with large datasets (10000 points) so I can't post them , but my 
function is :

create_map <- function(grd, level ,map_output, format = c("jpeg"), width_map = 
150, height_map = 150,...)
{       
                
        ##sp <- spline(x = grd[,1], y = grd[,2])

        grd2 <- matrix(grd[,3], nrow = sqrt(length(grd[,3])), ncol = 
sqrt(length(grd[,3])), byrow = FALSE)
        
        V2b <- grd2

        
        ##creation of breaks for colors
        i<-1    
        paliers <- c(-1.0E300)
        while(i<=length(level[,1]))
        {
                paliers <- c(paliers,level[i,1])
                i <- i+1
        }
        paliers <- c(paliers, 1.0E300)
                
        ##scale color creation
        i <- 1
        colgraph <- c(rgb(255,255,255, maxColorValue = 255))
        while(i<=length(level[,2]))
        {
                colgraph <- c(colgraph, rgb(level[i,2],level[i,3],level[i,4], 
maxColorValue = 255))
                i <- i +1
        }

        ##user can choose the output format (default is jpeg)
        switch(format, 
                png = png(map_output, width = width_map, height = height_map) ,
                jpeg = jpeg(map_output, width = width_map, height = height_map, 
quality = 100),
                bmp = bmp(map_output, width = width_map, height = height_map),
                tiff = tiff(map_output, width = width_map, height = height_map),
                jpeg(map_output, width = width_map, height = height_map))

        ## drawing map
        
        ##delete marge
        par(mar=c(0,0,0,0))
        filled.contour(V2b, col = colgraph, levels = paliers, asp = 1, axes = 
FALSE, ann = FALSE)
        dev.off()               

}

where grd is a xyz data frame, 
map_output is the path+name of the output image file,
and level is a matrix like this :


level <- matrix(0,10,4)
level[1,1] <- 1.0000E+00
level[2,1] <- 3.0000E+00
level[3,1] <- 5.0000E+00
level[4,1] <- 1.0000E+01
level[5,1] <- 1.5000E+01
level[6,1] <- 2.0000E+01
level[7,1] <- 3.0000E+01
level[8,1] <- 4.0000E+01
level[9,1] <- 5.0000E+01
level[10,1] <- 7.5000E+01


level[1,2] <- 102
level[2,2] <- 102
level[3,2] <- 102
level[4,2] <- 93
level[5,2] <- 204
level[6,2] <- 248
level[7,2] <- 241
level[8,2] <- 239
level[9,2] <- 224
level[10,2] <- 153

level[1,3] <- 153
level[2,3] <- 204
level[3,3] <- 204
level[4,3] <- 241
level[5,3] <- 255
level[6,3] <- 243
level[7,3] <- 189
level[8,3] <- 126
level[9,3] <- 14
level[10,3] <- 0

level[1,4] <- 153
level[2,4] <- 204
level[3,4] <- 153
level[4,4] <- 107
level[5,4] <- 102
level[6,4] <- 33
level[7,4] <- 59
level[8,4] <- 63
level[9,4] <- 14
level[10,4] <- 51 

Le 17 mai 2011 à 15:17, Duncan Murdoch a écrit :

> On 17/05/2011 8:24 AM, Pierre Bruyer wrote:
>> Thank you for your answer, but the function spline() (and a lot of other 
>> function in R)  can't take in its parameters the original contour which are 
>> define by a vector, i.e. :
>> 
> 
> If you post some reproducible code to generate the contours, someone will 
> show you how to use splines to interpolate them.
> 
> Duncan Murdoch
> 
>>      ##creation of breaks for colors
>>      i<-1    
>>      paliers<- c(-1.0E300)
>>      while(i<=length(level[,1]))
>>      {
>>              paliers<- c(paliers,level[i,1])
>>              i<- i+1
>>      }
>>      paliers<- c(paliers, 1.0E300)
>> 
>> 
>> 
>> Le 17 mai 2011 à 13:05, Duncan Murdoch a écrit :
>> 
>> >  On 11-05-17 5:58 AM, Pierre Bruyer wrote:
>> >>  I'm a French developer (so I am sorry if my english is not perfect). I 
>> >> have a problem to smooth the contours of a map. I have a dataset with 3 
>> >> columns, x, y and z, where x and y are the coordinates of my points and z 
>> >> is evaluate to a qualitative elevation and his representation is a set of 
>> >> colors, which is define by levels.
>> >>
>> >>  The problem is the curve of my contour is so linear, and I would like a 
>> >> more continuous contour. I use the function fitted.contour to draw my map.
>> >
>> >  If you use a finer grid of x,y values you'll get shorter segments and 
>> > they will look smoother.
>> >
>> >  You might be able to use a smooth interpolator (e.g. spline()) rather 
>> > than linear interpolation, but those occasionally do strange things e.g.
>> >
>> >  x<- c(1:4, 5.9, 6:10)
>> >  y<- c(1:4,   7, 6:10)
>> >  plot(spline(x,y, n=200), type="l")
>> >  points(x,y)
>> >
>> >  where one point is out of line with the others, but the curve 
>> > overcompensates in order to stay smooth.
>> >
>> >  Duncan Murdoch
>> 
> 

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