test-associations.R
In arules: Mining Association Rules and Frequent Itemsets

set.seed(20070611)

m <- matrix(as.integer(runif(100000) > 0.8), ncol = 20)
dimnames(m) <- list(NULL, paste("item", c(1:20), sep = ""))
t <- as(m, "transactions")
#t
#inspect(t[10])

expect_identical(dim(t), dim(m))

r <-
  apriori(t,
    parameter = list(supp = 0.01, conf = 0.1),
    control = list(verb = FALSE))
#r
#summary(r)
#inspect(r)

ss <- subset(r, subset = lift > 1.4 & lhs %in% "item3")
#inspect(ss)
expect_identical(labels(lhs(ss)), "{item2,item3}")
expect_true(quality(ss)$lift > 1.4)

f <- eclat(t,
  parameter = list(supp = 0.01),
  control = list(verb = FALSE))
#f
#summary(f)
#inspect(f)

ss <- subset(f, subset = items %in% "item7")
#inspect(ss)
expect_identical(labels(ss), grep("item7", labels(ss), value = TRUE))

### create associations manually
lmat <- matrix(rbind(c(1, 1, 0), c(0, 0, 1)), ncol = 3)
rmat <- matrix(rbind(c(1, 0, 0), c(0, 1, 0)), ncol = 3)
colnames(lmat) <- c("a", "b", "c")
colnames(rmat) <- c("c", "a", "b")
# Note: the column names do not agree!

lhs <- as(lmat, "itemMatrix")
rhs <- as(rmat, "itemMatrix")

is <-
  new("itemsets", items = lhs, quality = data.frame(support = c(.1, .1)))
#inspect(is)

expect_equal(labels(is), c("{a,b}", "{c}"))

qual <-
  data.frame(
    support = c(.5, .5),
    confidence = c(.5, .5),
    lift = c(2, 1)
  )

## warning because of the disagreeing labels
# expect_warning(r <- new(
#   "rules",
#   lhs = lhs,
#   rhs = rhs,
#   quality = qual
# ))

expect_warning(r <- rules(lhs, rhs, quality = qual))
#inspect(r)


## subsetting (also tests itemMatrix)
# numeric
take_r <- sample(nrow(t), 10)
take_c <- sample(ncol(t), 10)
expect_equal(dim(sub_n <- t[take_r, take_c]), c(10L, 10L))
expect_equal(dim(t[take_r]), c(10L, ncol(t)))
expect_equal(dim(t[take_r, ]), c(10L, ncol(t)))
expect_equal(dim(t[, take_c]), c(nrow(t), 10L))

# logical
take_rb <- rep(FALSE, nrow(t))
take_rb[take_r] <- TRUE
take_cb <- rep(FALSE, ncol(t))
take_cb[take_c] <- TRUE
expect_equal(dim(sub_b <- t[take_rb, take_cb]), c(10L, 10L))
expect_equal(dim(t[take_rb, ]), c(10L, ncol(t)))
expect_equal(dim(t[take_rb]), c(10L, ncol(t)))
expect_equal(dim(t[, take_cb]), c(nrow(t), 10L))

# Note: transactions and itemLabels are mixed up in numeric subset!
expect_true(setequal(sub_b, recode(sub_n, sub_b)))

# character
take_cc <- itemLabels(t)[take_c]
expect_equal(dim(t[, take_cc]), c(nrow(t), 10L))

# NA
expect_warning(expect_equal(dim(t[NA, NA]), c(0L, 0L)))
expect_warning(expect_equal(dim(t[NA]), c(0L, ncol(t))))
expect_warning(expect_equal(dim(t[, NA]), c(nrow(t), 0L)))

take_rn <- take_r
take_rn[3:4] <- NA
take_cn <- take_c
take_cn[3:4] <- NA
expect_warning(expect_equal(dim(t[take_rn, take_cn]), c(8L, 8L)))

take_rbn <- take_rb
take_rbn[which(take_rbn)[3:4]] <- NA
take_cbn <- take_cb
take_cbn[which(take_cbn)[3:4]] <- NA
expect_warning(expect_equal(dim(t[take_rbn, take_cbn]), c(8L, 8L)))

take_ccn <- take_cc
take_ccn[3:4] <- NA
expect_warning(expect_equal(dim(t[, take_cbn]), c(nrow(t), 8L)))

# rules
r <-
  apriori(t,
    parameter = list(supp = 0.01, conf = 0.1),
    control = list(verb = FALSE))
expect_warning(expect_equal(length(r[NA]), 0L))
expect_warning(expect_equal(length(r[c(1L, NA_integer_)]), 1L))
expect_warning(expect_equal(length(r[c(TRUE, NA, FALSE)]),
  sum(rep(
    c(TRUE, NA, FALSE), length.out = length(r)
  ), na.rm = TRUE))) # recycle

# itemsets
f <- eclat(t,
  parameter = list(supp = 0.01),
  control = list(verb = FALSE))
expect_warning(expect_equal(length(f[NA]), 0L))
expect_warning(expect_equal(length(f[c(1L, NA_integer_)]), 1L))
expect_warning(expect_equal(length(f[c(TRUE, NA, FALSE)]),
  sum(rep(
    c(TRUE, NA, FALSE), length.out = length(f)
  ), na.rm = TRUE))) # recycle

# head and tail
expect_identical(r[1:5], head(r, n = 5))
expect_identical(r[1:6], head(r))
expect_identical(r[1:2], head(r[1:2]))
expect_identical(r[0], head(r, n = 0))
expect_identical(r[1:(length(r) - 10)], head(r, n = -10))
expect_identical(r[1:length(r)], head(r, n = length(r)))
expect_identical(r[1:length(r)], head(r, n = length(r) + 100L))
expect_identical(sort(r, by = "lift")[1:5], head(r, n = 5, by = "lift"))
expect_identical(sort(r, by = "lift", decreasing = FALSE)[1:5],
  head(
    r,
    n = 5,
    by = "lift",
    decreasing = FALSE
  ))
expect_identical(head(r[0]), r[0]) # empty rule set

expect_identical(r[tail(1:length(r), n = 5)], tail(r, n = 5))
expect_identical(r[1:2], tail(r[1:2]))
expect_identical(r[0], tail(r, n = 0))
expect_identical(sort(r, by = "lift")[tail(1:length(r), n = 5)], tail(r, n = 5, by = "lift"))
expect_identical(tail(r[0]), r[0]) # empty rule set

# match, %in%, %pin%
expect_identical(match(r[2:10], r), 2:10)
expect_identical(r[2:10] %in% r, 2:10)
expect_identical(match(f[2:10], f), 2:10)
expect_identical(f[2:10] %in% f, 2:10)

expect_identical(rhs(r[1:10]) %pin% "item1",
  c(FALSE, FALSE, TRUE, TRUE, TRUE,
    TRUE, TRUE, FALSE, FALSE, TRUE))
expect_error(rhs(r[1:10]) %pin% "")
expect_warning(rhs(r[1:10]) %pin% c("1", "2"))