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# Title : Approximation
# File : R/approximation.R
# Exported : MaxClique
# Valid Algorithms : "GrossoLocatelliPullanMc" (default)
# Runners : GrossoLocatelliPullanMcRunner
# 1) Ensure runner functions run without error and return the "expected
# objects".
test_that("Approximation runner", {
s <- c(1, 2, 3, 4, 5)
t <- c(2, 3, 1, 5, 4)
n <- 5
out <- GrossoLocatelliPullanMcRunner(s, t, n)
expect_true(is.list(out))
expect_length(out, 2)
expect_length(out[[1]], 1)
expect_true(all(out[[2]] %in% s))
})
test_that("Approximation functions", {
s <- c(1, 2, 3, 4, 5)
t <- c(2, 3, 1, 5, 4)
n <- 5
# 2) Ensure exported functions run without error and return the "expected
# objects".
out <- MaxClique(s, t, n)
expect_true(is.list(out))
expect_length(out, 2)
expect_length(out[[1]], 1)
expect_true(all(out[[2]] %in% s))
expect_named(out, c("size", "members"))
# 3) Ensure exported functions with `algorithm=`default runs without error, and
# returns the same if passed no argument
out2 <- MaxClique(s, t, n, algorithm = "GrossoLocatelliPullanMc")
expect_identical(out, out2)
# 4) Ensure exported functions work with all valid algorithms.
# No alternate algorithsm
# 5) Ensure exported functions fail if passed an invalid algorithm.
expect_error(MaxClique(s, t, n, algorithm = "abc"),
"Invalid")
expect_error(MaxClique(s, t, n, algorithm = 1),
"must be a string")
expect_error(MaxClique(s, t, n, algorithm = NULL),
"must be a string")
})
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