# LUCID - five omics, normal outcome test_that("check the summary function of LUCID with normal outcome (K = 2,2,2,2,2)", { # run LUCID model i <- 1008 set.seed(i) G <- matrix(rnorm(500), nrow = 100) Z1 <- matrix(rnorm(1000),nrow = 100) Z2 <- matrix(rnorm(1000), nrow = 100) Z3 <- matrix(rnorm(1000), nrow = 100) Z4 <- matrix(rnorm(1000), nrow = 100) Z5 <- matrix(rnorm(1000), nrow = 100) Z <- list(Z1 = Z1, Z2 = Z2, Z3 = Z3, Z4 = Z4, Z5 = Z5) Z_e = matrix(rnorm(1000), nrow = 100) Y <- rnorm(100) CoY <- matrix(rnorm(200), nrow = 100) CoG <- matrix(rnorm(200), nrow = 100) # i <- sample(1:2000, 1) # cat(paste("test1 - seed =", i, "\n")) ## early invisible(capture.output(fit1 <- lucid(G = G, Z = Z_e, Y = Y, K = 2:5, CoG = CoG, CoY = CoY, lucid_model = "early", family = "normal", seed = i, useY = TRUE))) sum_fit1 = summary_lucid(fit1) print.sumlucid(sum_fit1) ## parallel invisible(capture.output(fit2 <- lucid(G = G, Z = Z, Y = Y, K = list(3, 2:3, 3:4, 2:3, 2), CoG = CoG, CoY = CoY, lucid_model = "parallel", family = "normal", seed = i, useY = TRUE))) sum_fit2 = summary_lucid(fit2) print.sumlucid(sum_fit2) Z <- list(Z1 = Z1, list(Z2 = Z2, Z3 = Z3), Z4 = Z4, Z5 = Z5) invisible(capture.output(fit3 <- lucid(G = G, Z = Z, Y = Y, K = list(2,list(2:3,2),2:4,2), lucid_model = "serial", family = "normal", seed = i, CoG = CoG, CoY = CoY, useY = TRUE))) sum_fit3 = summary_lucid(fit3) print.sumlucid(sum_fit3) })