library(loo) options(mc.cores=1) options(loo.cores=NULL) set.seed(123) context("tis and is") LLarr <- example_loglik_array() LLmat <- example_loglik_matrix() LLvec <- LLmat[, 1] chain_id <- rep(1:2, each = dim(LLarr)[1]) r_eff_arr <- relative_eff(exp(LLarr)) r_eff_vec <- relative_eff(exp(LLvec), chain_id = chain_id) psis1 <- psis(log_ratios = -LLarr, r_eff = r_eff_arr) tis1 <- tis(log_ratios = -LLarr, r_eff = r_eff_arr) is1 <- sis(log_ratios = -LLarr, r_eff = r_eff_arr) test_that("tis and is runs", { LLvec[1] <- -10 expect_silent(tis1 <- tis(log_ratios = -LLvec, r_eff = r_eff_vec)) expect_silent(is1 <- sis(log_ratios = -LLvec, r_eff = r_eff_vec)) expect_failure(expect_equal(tis1$log_weights, is1$log_weights)) expect_failure(expect_equal(tis1$log_weights, psis1$log_weights)) }) test_that("tis() and sis() returns object with correct structure for tis/sis", { expect_false(is.psis(tis1)) expect_false(is.psis(is1)) expect_true(is.tis(tis1)) expect_false(is.tis(is1)) expect_false(is.sis(tis1)) expect_true(is.sis(is1)) expect_false(is.loo(tis1)) expect_false(is.loo(is1)) expect_false(is.psis_loo(tis1)) expect_false(is.psis_loo(is1)) expect_named(tis1, c("log_weights", "diagnostics")) expect_named(is1, c("log_weights", "diagnostics")) expect_named(tis1$diagnostics, c("pareto_k", "n_eff", "r_eff")) expect_named(is1$diagnostics, c("pareto_k", "n_eff", "r_eff")) expect_equal(dim(tis1), dim(LLmat)) expect_equal(dim(is1), dim(LLmat)) expect_length(tis1$diagnostics$pareto_k, dim(psis1)[2]) expect_length(is1$diagnostics$pareto_k, dim(psis1)[2]) expect_length(tis1$diagnostics$n_eff, dim(psis1)[2]) expect_length(is1$diagnostics$n_eff, dim(psis1)[2]) expect_equal(attr(psis1, "method")[1], "psis") expect_equal(attr(tis1, "method")[1], "tis") expect_equal(attr(is1, "method")[1], "sis") }) test_that("psis methods give same results", { tis2 <- suppressWarnings(tis(-LLmat, r_eff = r_eff_arr)) expect_identical(tis1, tis2) tisvec <- suppressWarnings(tis(-LLvec, r_eff = r_eff_vec)) tismat <- suppressWarnings(tis(-LLmat[, 1], r_eff = r_eff_vec)) expect_identical(tisvec, tismat) is2 <- suppressWarnings(sis(-LLmat, r_eff = r_eff_arr)) expect_identical(is1, is2) isvec <- suppressWarnings(sis(-LLvec, r_eff = r_eff_vec)) ismat <- suppressWarnings(sis(-LLmat[, 1], r_eff = r_eff_vec)) expect_identical(isvec, ismat) }) test_that("tis throws correct errors and warnings", { # r_eff default no warnings expect_silent(tis(-LLarr)) expect_silent(tis(-LLmat)) expect_silent(tis(-LLmat[, 1])) # r_eff=NULL no warnings expect_silent(tis(-LLarr, r_eff = NULL)) expect_silent(tis(-LLmat, r_eff = NULL)) expect_silent(tis(-LLmat[,1], r_eff = NULL)) # r_eff=NA no warnings expect_silent(tis(-LLarr, r_eff = NA)) expect_silent(tis(-LLmat, r_eff = NA)) expect_silent(tis(-LLmat[,1], r_eff = NA)) # r_eff default and r_eff=NA give same answer expect_equal( suppressWarnings(tis(-LLarr)), tis(-LLarr, r_eff = NA) ) # r_eff=NULL and r_eff=NA give same answer expect_equal( suppressWarnings(tis(-LLarr, r_eff = NULL)), tis(-LLarr, r_eff = NA) ) # r_eff scalar is fine expect_silent(tis(-LLarr, r_eff = r_eff_arr[1])) # r_eff wrong length is error expect_error(tis(-LLarr, r_eff = r_eff_arr[-1]), "one value per observation") # r_eff has some NA values causes error r_eff_arr[2] <- NA expect_error(tis(-LLarr, r_eff = r_eff_arr), "mix NA and not NA values") # no NAs or non-finite values allowed LLmat[1,1] <- NA expect_error(tis(-LLmat), "NAs not allowed in input") LLmat[1,1] <- 1 LLmat[10, 2] <- Inf expect_error(tis(-LLmat), "All input values must be finite") # no lists allowed expect_error(expect_warning(tis(as.list(-LLvec)), "List not allowed as input")) # if array, must be 3-D array dim(LLarr) <- c(2, 250, 2, 32) expect_error( tis(-LLarr), "length(dim(log_ratios)) == 3 is not TRUE", fixed = TRUE ) }) test_that("explict test of values for 'sis' and 'tis'", { lw <- 1:16 expect_silent(tis_true <- tis(log_ratios = lw, r_eff = NA)) expect_equal(as.vector(weights(tis_true, log = TRUE, normalize = FALSE)), c(-14.0723, -13.0723, -12.0723, -11.0723, -10.0723, -9.0723, -8.0723, -7.0723, -6.0723, -5.0723, -4.0723, -3.0723, -2.0723, -1.0723, -0.0723, 0.) + 15.07238, tol = 0.001) expect_silent(is_true <- sis(log_ratios = lw, r_eff = NA)) expect_equal(as.vector(weights(is_true, log = TRUE, normalize = FALSE)), lw, tol = 0.00001) lw <- c(0.7609420, 1.3894140, 0.4158346, 2.5307927, 4.3379119, 2.4159240, 2.2462172, 0.8057697, 0.9333107, 1.5599302) expect_silent(tis_true <- tis(log_ratios = lw, r_eff = NA)) expect_equal(as.vector(weights(tis_true, log = TRUE, normalize = FALSE)), c(-2.931, -2.303, -3.276, -1.161, 0, -1.276, -1.446, -2.886, -2.759, -2.132) + 3.692668, tol = 0.001) expect_silent(is_true <- sis(log_ratios = lw, r_eff = NA)) expect_equal(as.vector(weights(is_true, log = TRUE, normalize = FALSE)), lw, tol = 0.00001) }) test_that("tis_loo and sis_loo are returned", { LLmat <- example_loglik_matrix() loo_psis <- suppressWarnings(loo(LLmat, r_eff = NA, is_method = "psis")) loo_tis <- suppressWarnings(loo(LLmat, r_eff = NA, is_method = "tis")) loo_sis <- suppressWarnings(loo(LLmat, r_eff = NA, is_method = "sis")) expect_s3_class(loo_tis, "tis_loo") expect_s3_class(loo_sis, "sis_loo") expect_s3_class(loo_tis, "importance_sampling_loo") expect_s3_class(loo_sis, "importance_sampling_loo") expect_output(print(loo_tis), regexp = "tis_loo") expect_output(print(loo_sis), regexp = "sis_loo") })