```
# NOT RUN {
### show available proximities
summary(pr_DB)
### get more information about a particular one
pr_DB$get_entry("Jaccard")
### binary data
x <- matrix(sample(c(FALSE, TRUE), 8, rep = TRUE), ncol = 2)
dist(x, method = "Jaccard")
### for real-valued data
dist(x, method = "eJaccard")
### for positive real-valued data
dist(x, method = "fJaccard")
### cross distances
dist(x, x, method = "Jaccard")
### pairwise (diagonal)
dist(x, x, method = "Jaccard",
pairwise = TRUE)
### this is the same but less efficient
as.matrix(stats::dist(x, method = "binary"))
### numeric data
x <- matrix(rnorm(16), ncol = 4)
## test inheritance of names
rownames(x) <- LETTERS[1:4]
colnames(x) <- letters[1:4]
dist(x)
dist(x, x)
## custom distance function
f <- function(x, y) sum(x * y)
dist(x, f)
## working with lists
z <- unlist(apply(x, 1, list), recursive = FALSE)
(d <- dist(z))
dist(z, z)
## subsetting
d[[1:2]]
subset(d, c(1,3,4))
d[[c(1,2,2)]] # duplicate index gets ignored
## transformations and self-proximities
as.matrix(as.simil(d, function(x) exp(-x)), diag = 1)
## row and column indexes
row.dist(d)
col.dist(d)
# }
```

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