[R] Smooth contour of a map

Pierre Bruyer pbruyer at agaetis.fr
Wed May 18 14:27:53 CEST 2011


I've pratically resolved my problem (the code is under that), but a last thing is not perfect:
when I use the function plot to call after the function polygon, there is a marge between my raster and the window. I think it's the axis of the function "plot()", but I have not found how delete it. Someone have a solution please?

Pierre Bruyer

##smooth contour
	
	contours <- contourLines(V2b,levels=paliers)

	
	par(mar=c(0,0,0,0))
	plot(1,col="white",main="polygon()", asp = 1, axes = FALSE, ann = FALSE,xlim=c(0,1), ylim = c(0,1),type = "n", method = c("image"))
	for (i in seq_along(contours)) {
 		 x <- contours[[i]]$x
 		 y <- contours[[i]]$y
 		 c <- contours[[i]]$level
 		 j <- 1
 		 tmp <- 0 
 		 while(j < length(level[,1]) && tmp == 0){
 		 	if(level[j,1] == c){
 		 		tmp <- j
 		 	}
 		 	j <- j+1 
 		}	

 		polygon( spline( seq_along(x), x)$y, spline( seq_along(y), y)$y ,col = colgraph[tmp+1], border = NA)
	}



Le 17 mai 2011 à 16:44, Pierre Bruyer a écrit :

> The result is good, thanks a lot, but how can I with this method fill my raster to color?
> 
> Le 17 mai 2011 à 15:43, Duncan Murdoch a écrit :
> 
>> I don't think filled.contour gives you access to the contour lines.  If you use contourLines() to compute them, then you can draw them using code like this:
>> 
>> contours <- contourLines(V2b,levels=paliers)
>> for (i in seq_along(contours)) {
>>  x <- contours[[i]]$x
>>  y <- contours[[i]]$y
>>  lines( splines( seq_along(x), x)$y, splines( seq_along(y), y)$y )
>> }
>> 
>> but as I said, you won't get great results.  A better way is to use a finer grid, e.g. by fitting a smooth surface to your set of points and using predictions from the model to interpolate.
>> 
>> Duncan Murdoch
>> 
>> 
>> On 17/05/2011 9:35 AM, Pierre Bruyer wrote:
>>> 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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