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## For different cluster versions
require(cluster)
if(interactive()) print(packageDescription("cluster"))
## trivial cases should 'work':
daisy(cbind(1))
(d10 <- daisy(matrix(0., 1,0))); str(d10)
d01 <- daisy(matrix(0., 0,1))
if(paste(R.version$major, R.version$minor, sep=".") >= "2.1.0")
print(d01)
str(d01)
d32 <- data.frame(eins=c("A"=1,"B"=1,"C"=1), zwei=c(2,2,2))
daisy(d32)
daisy(d32, stand = TRUE)
daisy(d32, type = list(ordratio="zwei"))
str(d5 <- data.frame(a= c(0, 0, 0,1,0,0, 0,0,1, 0,NA),
b= c(NA,0, 1,1,0,1, 0,1,0, 1,0),
c= c(0, 1, 1,0,1,NA,1,0,1, 0,NA),
d= c(1, 1, 0,1,0,0, 0,0,0, 1,0),
e= c(1, NA,0,1,0,0, 0,0,NA,1,1)))
(d0 <- daisy(d5))
(d1 <- daisy(d5, type = list(asymm = 1:5)))
(d2 <- daisy(d5, type = list(symm = 1:2, asymm= 3:5)))
(d2.<- daisy(d5, type = list( asymm= 3:5)))
stopifnot(identical(c(d2), c(d2.)))
(dS <- daisy(d5, stand = TRUE))# gave error in some versions
stopifnot(all.equal(as.vector(summary(c(dS), digits=9)),
c(0, 2.6142638, 3.4938562, 3.2933687, 4.0591077, 5.5580177),
tol = 1e-7))# 7.88e-9
d5[,4] <- 1 # binary with only one instead of two values
(d0 <- daisy(d5))
(d1 <- daisy(d5, type = list(asymm = 1:5)))# 2 NAs
(d2 <- daisy(d5, type = list(symm = 1:2, asymm= 3:5)))
(d2.<- daisy(d5, type = list( asymm= 3:5)))
## better leave away the constant variable: it has no effect:
stopifnot(identical(c(d1), c(daisy(d5[,-4], type = list(asymm = 1:4)))))
###---- Trivial "binary only" matrices (not data frames) did fail:
x <- matrix(0, 2, 2)
dimnames(x)[[2]] <- c("A", "B")## colnames<- is missing in S+
daisy(x, type = list(symm= "B", asymm="A"))
daisy(x, type = list(symm= "B"))# 0 too
x2 <- x; x2[2,2] <- 1
daisy(x2, type= list(symm = "B"))# |-> 0.5 (gives 1 in S+)
daisy(x2, type= list(symm = "B", asymm="A"))# 1
x3 <- x; x3[] <- diag(2)
daisy(x3) # warning: both as interval scaled -> sqrt(2)
daisy(x3, type= list(symm="B", asymm="A"))# 1
daisy(x3, type= list(symm =c("B","A"))) # 1, S+: sqrt(2)
daisy(x3, type= list(asymm=c("B","A"))) # 1, S+ : sqrt(2)
x4 <- rbind(x3, 1)
daisy(x4, type= list(symm="B", asymm="A"))# 1 0.5 0.5
daisy(x4, type= list(symm=c("B","A"))) # dito; S+ : 1.41 1 1
daisy(x4, type= list(asymm=c("A","B"))) # dito, dito
## ----------- example(daisy) -----------------------
data(flower)
data(agriculture)
## Example 1 in ref:
## Dissimilarities using Euclidean metric and without standardization
(d.agr <- daisy(agriculture, metric = "euclidean", stand = FALSE))
(d.agr2 <- daisy(agriculture, metric = "manhattan"))
## Example 2 in ref
(dfl0 <- daisy(flower))
stopifnot(identical(c(dfl0),
c(daisy(flower, type = list(symm = 1)))) &&
identical(c(dfl0),
c(daisy(flower, type = list(symm = 2)))) &&
identical(c(dfl0),
c(daisy(flower, type = list(symm = 3)))) &&
identical(c(dfl0),
c(daisy(flower, type = list(symm = c(1,3)))))
)
(dfl1 <- daisy(flower, type = list(asymm = 3)))
(dfl2 <- daisy(flower, type = list(asymm = c(1, 3), ordratio = 7)))
(dfl3 <- daisy(flower, type = list(asymm = 1:3)))
## --- animals
data(animals)
d0 <- daisy(animals)
d1 <- daisy(animals - 1, type=list(asymm=c(2,4)))
(d2 <- daisy(animals - 1, type=list(symm = c(1,3,5,6), asymm=c(2,4))))
stopifnot(c(d1) == c(d2))
d3 <- daisy(2 - animals, type=list(asymm=c(2,4)))
(d4 <- daisy(2 - animals, type=list(symm = c(1,3,5,6), asymm=c(2,4))))
stopifnot(c(d3) == c(d4))
pairs(cbind(d0,d2,d4),
main = "Animals -- symmetric and asymm. dissimilarities")
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