context("Test implementation of sorensen 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_sorensen_dist <- function(P, Q) { if (sum((P) + (Q) > 0)) { return(sum(abs((P) - (Q))) / sum((P) + (Q))) } else { return(NAN) } } test_that("distance(method = 'sorensen') computes the correct distance value.", { expect_equal(as.vector(philentropy::distance(rbind(P, Q), method = "sorensen")), test_sorensen_dist(P, Q)) # 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 = "sorensen") expect_equal(dist.vals[lower.tri(dist.vals, diag = FALSE)], test_dist_matrix(distMat, FUN = test_sorensen_dist)) }) test_that("Correct sorensen 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) distMat <- rbind(P1,Q1,P2,Q2) dist.vals <- distance(distMat, method = "sorensen") expect_equal(dist.vals[lower.tri(dist.vals, diag = FALSE)], test_dist_matrix(distMat, FUN = test_sorensen_dist)) })