R Under development (unstable) (2015-07-07 r68640) -- "Unsuffered Consequences"
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> #### Interface to intermediate level Fortran Routines
> #### Purpose : explore different versions of  dysta(), dysta3(), .. in
> ####	       Fortran code.
> 
> library(cluster)
> 
> dysta <- function(x, kind = c("euclidean","manhattan", "SqEuclidean"),
+                   dystaK = "dysta")
+ {
+     ## Purpose:
+     ## -------------------------------------------------------------------------
+     ## Arguments:
+     ## -------------------------------------------------------------------------
+     ## Author: Martin Maechler, Date:  3 Sep 2002, 08:21
+ 
+     kind <- match.arg(kind)
+     ndyst <- which(kind == eval(formals()$kind))# 1, 2, or 3
+     n <- nrow(x <- as.matrix(x))
+     p <- ncol(x)
+     storage.mode(x) <- "double"
+     hasNA <- apply(is.na(x), 2, any) # == apply(x, 2, anyNA)
+     if(any(hasNA)) {
+ 	ina <- is.na(x)
+ 	x[ina] <- valmd <- -1.1*max(abs(range(x, na.rm = TRUE)))
+ 	valmd <- rep(valmd, p)
+     } else valmd <- 0.
+ 
+     dys <- double(1 + n*(n-1)/2)
+     jtmd <- as.integer(ifelse(hasNA, -1, 1))
+ 
+     r <-
+         if(dystaK == "dysta3") {
+             .C(cluster:::dysta3,
+                n,
+                jp = p,
+                x,
+                dys= dys,
+                ndyst= ndyst,
+                jtmd=  jtmd,
+                valmd= valmd,
+ 	       jhalt= integer(1))[c("dys", "jhalt")]
+         } else {
+             .Fortran(cluster:::dysta,
+                      n,
+                      jp = p,
+                      x,
+                      dys= dys,
+                      ndyst= ndyst,
+                      jtmd=  jtmd,
+                      valmd= valmd,
+ 		     jhalt= integer(1))[c("dys", "jhalt")]
+         }
+     if(r$jhalt) {
+ 	cat("'jhalt' was ", r$jhalt,
+ 	    " -- some dissimilarities will be missing.\n")
+ 	r$dys[r$dys == -1.] <- NA
+     }
+     r$dys
+ }
> 
> (x <- cbind(c(0:6,NA), c(1,2,NA,7,NA,8:9,8)))
     [,1] [,2]
[1,]    0    1
[2,]    1    2
[3,]    2   NA
[4,]    3    7
[5,]    4   NA
[6,]    5    8
[7,]    6    9
[8,]   NA    8
> dysta(x)
'jhalt' was  1  -- some dissimilarities will be missing.
 [1]  0.000000  1.414214  2.828427  1.414214  6.708204  5.385165  1.414214
 [8]  5.656854  4.242641  2.828427  1.414214  8.602325  7.211103  4.242641
[15]  2.236068  1.414214 10.000000  8.602325  5.656854  3.605551  2.828427
[22]  1.414214  9.899495  8.485281        NA  1.414214        NA  0.000000
[29]  1.414214
> (d1 <- dysta(x, kind = "m"))
'jhalt' was  1  -- some dissimilarities will be missing.
 [1]  0  2  4  2  9  7  2  8  6  4  2 12 10  6  3  2 14 12  8  5  4  2 14 12 NA
[26]  2 NA  0  2
> (d3 <- dysta(x, kind = "m",dystaK = "dysta3"))
'jhalt' was  1  -- some dissimilarities will be missing.
 [1]  2  4  9  8 12 14 14  2  7  6 10 12 12  2  4  6  8 NA  2  3  5  2  2  4 NA
[26]  2  0  2  0
> 
> identical(sort(d1), sort(d3)) # TRUE
[1] TRUE
> cbind(d1=d1[-1], d3=d3[-length(d3)],
+       dist=dist(x,"manhattan"), daisy= daisy(x,"manhattan"))
      d1 d3 dist daisy
 [1,]  2  2    2     2
 [2,]  4  4    4     4
 [3,]  2  9    9     9
 [4,]  9  8    8     8
 [5,]  7 12   12    12
 [6,]  2 14   14    14
 [7,]  8 14   14    14
 [8,]  6  2    2     2
 [9,]  4  7    7     7
[10,]  2  6    6     6
[11,] 12 10   10    10
[12,] 10 12   12    12
[13,]  6 12   12    12
[14,]  3  2    2     2
[15,]  2  4    4     4
[16,] 14  6    6     6
[17,] 12  8    8     8
[18,]  8 NA   NA    NA
[19,]  5  2    2     2
[20,]  4  3    3     3
[21,]  2  5    5     5
[22,] 14  2    2     2
[23,] 12  2    2     2
[24,] NA  4    4     4
[25,]  2 NA   NA    NA
[26,] NA  2    2     2
[27,]  0  0    0     0
[28,]  2  2    2     2
> 
> identical(d3[-length(d3)],
+ 	  c(dist(x,"manhattan")))# !
[1] TRUE
> identical(c(daisy(x,"manhattan")), c(dist(x,"manhattan")))
[1] TRUE
> identical(c(daisy(x,"euclidean")), c(dist(x,"euclidean")))
[1] TRUE
> identical(dysta(x, dystaK="dysta3")[-length(d3)],
+ 	  c(dist(x,"euclidean")))# !
'jhalt' was  1  -- some dissimilarities will be missing.
[1] TRUE
> 
> proc.time()
   user  system elapsed 
  0.179   0.060   0.265