[R-sig-Geo] Could you add my 'Jenks' method to your classInt package?

[Hisaji ONO]

Hello.

 I've tried to port Java code for Jenks optimization
classification method "natural break" to R, although far
from smart coding.

 My java code was ported Jenks's Basic code and I checked
these results compared to results of ArcView 3.x.

 Jenks method derived from Fischer, but seems to be a
little different in the algorithm.

 My code's results are similar to results of current
ArcGIS's, but not equal to them. Accordindg to Murray, A.
T. & Shyy, T. K.'s papaer (IJGIS, 2000, 14-7, 649-667,
http://geog-www.sbs.ohio-state.edu/faculty/murray/personal/research/crimepubs/murray-shyy2000.pdf),
there are difference between ArcGIS's and MapInfo's. How
about Autodesk's Map Guide Open Source which has employed
Jenks's method as a function.

 Could you try my following code and add this into your
classInt package if you like?


 Regards.





else if (style == "fisher") {
---- cut ---- cut ---- cut ---- cut ---- cut ----
        }
 else if (style == "Jenks") { # Jenks Optimisation Method
            d<- sort(var)
           #work<-matrix(0,k,length(d))
           mat1<-matrix(1,length(d),k)
           mat2<-matrix(0,length(d),k)
           mat2[2:length(d),1:k]<-10000000 #R's max double
value?
           v<-0

           for(l in 2:length(d)){
             s1=s2=w=0
             for(m in 1:l){
               i3 <- l - m + 1
               val <- d[i3]
               s2 <- s2 + val * val
               s1 <- s1 + val
               w<-w+1
               v <- s2 - (s1 * s1) / w
               i4 <- trunc(i3 - 1)

               if(i4 !=0){
                 for(j in 2:k){
                   if(mat2[l,j] >= (v + mat2[i4, j - 1])){
                     mat1[l,j] <- i3
                     mat2[l,j] <- v + mat2[i4, j - 1]
                   }
                 }
               }
             }
             mat1[l,1] <- 1
             mat2[l,1] <- v
           }

           kclass<-1:k
           kclass[k] <-length(d)
           k <- length(d)
           last<-length(d)
           for(j in length(kclass):1){
             id <- trunc(mat1[k,j]) - 1
             kclass[j - 1] <- id
             k <- id #lower
             last <- k -1 #upper
           }
           brks<-d[c(1, kclass)]
         }
         else stop(paste(style, "unknown"))