context("Test implementation of chebyshev distance ...") P <- 1:10 / sum(1:10) Q <- 20:29 / sum(20:29) V <- -10:10 W <- -20:0 # function to test distance matrix functionality # for different distance measures test_dist_matrix <- function(x, FUN) { dist.fun <- match.fun(FUN) res.dist.matrix <- matrix(NA_real_, nrow(x), nrow(x)) for (i in 1:nrow(x)) { for (j in 1:nrow(x)) { res.dist.matrix[i, j] <- dist.fun(x[i, ], x[j, ]) } } return(res.dist.matrix[lower.tri(res.dist.matrix, diag = FALSE)]) } test_that("distance(method = 'chebyshev') computes the correct distance value.", { expect_equal(as.vector(philentropy::distance(rbind(P, Q), method = "chebyshev")), max(abs((P) - (Q)))) expect_equal(as.vector(philentropy::distance(rbind(P, Q), method = "chebyshev")), as.vector(stats::dist(base::rbind(P, Q), method = "maximum"))) # test correct computation of distance matrix distMat <- rbind(rep(0.2, 5), rep(0.1, 5), c(5, 1, 7, 9, 5)) dist.vals <- distance(distMat, method = "chebyshev") expect_equal(dist.vals[lower.tri(dist.vals, diag = FALSE)], as.vector(dist(distMat, method = "maximum"))) }) test_that("Correct chebyshev distance is computed when vectors contain 0 values ...", { P1 <- c(1,0) P2 <- c(0.5, 0.5) Q1 <- c(0.5,0.5) Q2 <- c(1,0) expect_equal(as.vector(philentropy::distance(rbind(P1, Q1), method = "chebyshev")), as.vector(stats::dist(base::rbind(P1, Q1), method = "maximum"))) expect_equal(as.vector(philentropy::distance(rbind(P2, Q2), method = "chebyshev")), as.vector(stats::dist(base::rbind(P2, Q2), method = "maximum"))) })