data <- list( c("A", "B"), c("A", "B", "C", "G"), c("C", "D"), c("E", "F"), c("A", "B", "C", "D") ) ### is.superset / is.subset is <- new("itemsets", items = as(data, "itemMatrix")) ### find supersets in is ss <- is.superset(is, is) expect_identical(colnames(ss), labels(is)) expect_identical(rownames(ss), labels(is)) expect_equal(unname(diag(ss)), rep(TRUE, nrow(ss))) ss2 <- is.superset(is) expect_identical(ss, ss2) ss <- is.superset(is, is, proper = TRUE) expect_equal(unname(diag(ss)), rep(FALSE, nrow(ss))) ss <- is.superset(is[5], is) expect_equal(unname(as(ss, "matrix")), t(c(T, F, T, F, T))) ### sparse (should all be true) expect_equal(as.matrix(is.superset(is, is)), is.superset(is, is, sparse = FALSE)) expect_equal(as.matrix(is.superset(is)), is.superset(is, sparse = FALSE)) expect_equal( as.matrix(is.superset(is[5], is)), is.superset(is[5], is, sparse = FALSE) ) expect_equal( as.matrix(is.superset(is, is, proper = TRUE)), is.superset(is, is, proper = TRUE, sparse = FALSE) ) ### find subsets in is ss <- is.subset(is, is) expect_identical(colnames(ss), labels(is)) expect_identical(rownames(ss), labels(is)) expect_equal(unname(diag(ss)), rep(TRUE, nrow(ss))) ss <- is.subset(is, is, proper = TRUE) expect_identical(colnames(ss), labels(is)) expect_identical(rownames(ss), labels(is)) expect_equal(unname(diag(ss)), rep(FALSE, nrow(ss))) ss <- is.subset(is[1], is) expect_equal(unname(as(ss, "matrix")), t(c(T, T, F, F, T))) ### is.maximal quality(is)$isMaximal <- is.maximal(is) # inspect(is) expect_equal(quality(is)$isMaximal, c(F, T, F, T, T)) ### is.closed db <- as(data, "transactions") is <- eclat(db, parameter = list(supp = 0), control = list(verbose = FALSE)) quality(is) <- cbind(quality(is), isClosed = is.closed(is)) # inspect(is) expect_equal(quality(is)$isClosed[1:5], c(T, T, F, F, F)) ### union, intersection, setequal, setdiff, is.element rules <- apriori(data, control = list(verbose = FALSE)) r1 <- rules[1:10] r2 <- rules[6:20] expect_equal(length(union(r1, r2)), 20L) expect_equal(length(intersect(r1, r2)), 5L) expect_false(setequal(r1, r2)) expect_true(setequal(r1, r1)) expect_true(setequal(r1, c(rules[5:10], rules[1:5]))) expect_equal(length(setdiff(r1, r2)), 5L) expect_equal(length(setdiff(r2, r1)), 10L) expect_true(is.element(rules[5], r1)) expect_false(is.element(rules[15], r1)) # union(setA,setB)= setA + setB - intersect(setA,setB) expect_equal(length(union(r1, r2)), length(c(r1, r2)) - length(intersect(r1, r2))) # Test setequal with incompatible itemMatrices containing the same itemsets d1 <- as(data, "itemMatrix") expect_true(setequal(d1, d1)) d2 <- merge(d1[, 6:7], d1[, 1:5]) compatible(d1, d2) expect_warning(expect_true(setequal(d1, d2))) expect_warning(expect_true(setequal(union(d1, d2), intersect(d1, d2))))