# Test smooth_estimates() dat <- data_sim("eg1", n = 400, seed = 1) m1 <- gam(y ~ s(x0) + s(x1, bs = "cr") + s(x2, bs = "ps") + s(x3, bs = "bs"), data = dat, method = "REML" ) m2 <- gamm(y ~ s(x0) + s(x1, bs = "cr") + s(x2, bs = "ps") + s(x3, bs = "bs"), data = dat, method = "REML" ) m_t2 <- gam(y ~ t2(x0, x1, x2), data = dat, method = "REML") m_ti <- gam(y ~ s(x0) + s(x1) + ti(x0, x1), data = dat, method = "REML") dat_2d_by <- data_sim("eg4", n = 400, seed = 42) m_2d_by <- gam(y ~ fac + s(x0, x1, by = fac), data = dat_2d_by) ## simulate example... from ?mgcv::factor.smooth.interaction sim_fs <- function(n = 500, nf = 10) { f0 <- function(x) 2 * sin(pi * x) f1 <- function(x, a = 2, b = -1) exp(a * x) + b f2 <- function(x) { 0.2 * x^11 * (10 * (1 - x))^6 + 10 * (10 * x)^3 * (1 - x)^10 } n <- 500 nf <- 10 fac <- sample(1:nf, n, replace = TRUE) x0 <- runif(n) x1 <- runif(n) x2 <- runif(n) a <- rnorm(nf) * .2 + 2 b <- rnorm(nf) * .5 f <- f0(x0) + f1(x1, a[fac], b[fac]) + f2(x2) fac <- factor(fac) y <- f + rnorm(n) * 2 df <- data.frame(y = y, x0 = x0, x1 = x1, x2 = x2, fac = fac) df } dat_fs <- withr::with_seed(0, sim_fs()) m_fs <- gam(y ~ s(x1, fac, bs = "fs", k = 5), method = "ML", data = dat_fs) obj_nms <- c(".smooth", ".type", ".by", ".estimate", ".se") test_that("smooth_estimates works for a GAM", { sm <- smooth_estimates(m1, "s(x2)") expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") }) test_that("smooth_estimates works with more than one term", { sm <- smooth_estimates(m1, c("s(x1)", "s(x2)")) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") }) test_that("smooth_estimates throws error if smooth not found", { expect_error(smooth_estimates(m1, select = "s(z)"), "Failed to match any smooths in model `m1`", fixed = TRUE ) }) test_that("smooth is deprecated in smooth_estimates", { expect_warning(smooth_estimates(m_gam, smooth = "s(x1)"), "deprecated") }) test_that("smooth_estimates works for a GAMM", { sm <- smooth_estimates(m2, "s(x2)") expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") }) test_that("smooth_estimates works with a bivariate TPRS smooth", { expect_silent(sm <- smooth_estimates(su_m_bivar, "s(x,z)", n = 50)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 2500L) expect_named(sm, c(obj_nms, "x", "z")) }) test_that("smooth_estimates works with a bivariate TPRS smooth with dist", { expect_silent(sm <- smooth_estimates(su_m_bivar, "s(x,z)", n = 50, dist = 0.1 )) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 2500L) expect_named(sm, c(obj_nms, "x", "z")) }) test_that("smooth_estimates works with a bivariate te smooth", { expect_silent(sm <- smooth_estimates(su_m_bivar_te, "te(x,z)", n = 50)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 2500L) expect_named(sm, c(obj_nms, "x", "z")) }) test_that("smooth_estimates works with a bivariate te smooth with dist", { expect_silent(sm <- smooth_estimates(su_m_bivar_te, "te(x,z)", n = 50, dist = 0.1 )) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 2500L) expect_named(sm, c(obj_nms, "x", "z")) }) test_that("smooth_estimates works with a trivariate smooth", { expect_silent(sm <- smooth_estimates(su_m_trivar, "s(x0,x1,x2)", n = 25)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 10000L) expect_named(sm, c(obj_nms, "x0", "x1", "x2")) }) test_that("smooth_estimates works with a trivariate tensor product smooth", { expect_silent(sm <- smooth_estimates(su_m_trivar_te, "te(x0,x1,x2)", n = 25)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 10000L) expect_named(sm, c(obj_nms, "x0", "x1", "x2")) }) test_that("smooth_estimates works with a trivariate t2 tensor product smooth", { expect_silent(sm <- smooth_estimates(m_t2, "t2(x0,x1,x2)", n = 25)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 10000L) expect_named(sm, c(obj_nms, "x0", "x1", "x2")) }) test_that("smooth_estimates works with a tensor product interaction smooth", { expect_silent(sm <- smooth_estimates(m_ti, "ti(x0,x1)", n = 25)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 625L) expect_named(sm, c(obj_nms, "x0", "x1")) }) test_that("smooth_estimates works", { expect_silent(sm <- smooth_estimates(rm1, select = "s(fac)")) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), length(levels(su_re[["fac"]]))) expect_named(sm, c(obj_nms, "fac")) }) test_that("smooth_estimates works when passed data", { expect_silent(sm <- smooth_estimates(rm1, select = "s(fac)", data = su_re )) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), nrow(su_re)) expect_named(sm, c(obj_nms, "fac")) }) test_that("check_user_data fails if smooth var not in data", { id <- which(names(dat) == "x0") expect_error(check_user_data(data = dat[, -id], "x0"), "Variable(s) 'x0' not found in 'data'.", fixed = TRUE ) }) test_that("smooth_estimates works with vector data", { sm1 <- smooth_estimates(m_1_smooth, "s(x0)", data = dat[, "x0"]) sm2 <- smooth_estimates(m_1_smooth, "s(x0)", data = dat) expect_s3_class(sm1, "smooth_estimates") expect_equal(sm1, sm2) }) test_that("smooth_estimates fails if data is not data frame or numeric", { expect_error(smooth_estimates(m1, "s(x0)", data = list(x0 = dat[, "x0"])), "'data', if supplied, must be a numeric vector or data frame.", fixed = TRUE ) }) test_that("smooth_estimates works for a 2d factor by smooth", { expect_silent(sm <- smooth_estimates(m_2d_by, "s(x0,x1)", partial_match = TRUE )) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") }) test_that("smooth_estimates works for a factor smooth", { expect_silent(sm <- smooth_estimates(m_fs)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), 1000L) # 100 n * 10 levels expect_named(sm, c(obj_nms, "x1", "fac")) newdf <- data.frame(x1 = dat_fs$x1, fac = dat_fs$fac) expect_silent(sm <- smooth_estimates(m_fs, "s(x1,fac)", data = newdf)) expect_s3_class(sm, "smooth_estimates") expect_s3_class(sm, "tbl_df") expect_s3_class(sm, "data.frame") expect_identical(nrow(sm), nrow(newdf)) expect_named(sm, c(obj_nms, "x1", "fac")) newdf <- data.frame(x4 = 1:10, fac = factor(2, levels = 1:10)) expect_error(smooth_estimates(m_fs, "s(x1,fac)", data = newdf), "Variable(s) 'x1' not found in 'data'.", fixed = TRUE ) expect_error( smooth_estimates(m_fs, "s(x1,fac)", data = dat_fs[, !names(dat_fs) == "fac"] ), "Variable(s) 'fac' not found in 'data'.", fixed = TRUE ) }) ## check_user_data test_that("check_user_data throws error when passed a vector with vars >1", { expect_error(check_user_data(1:10, vars = c("x1", "x2")), "'smooth' requires multiple data vectors but only 1 provided.", fixed = TRUE ) }) test_that("check_user_data errors when passed a non-numeric vector", { expect_error(check_user_data(LETTERS, vars = "x1"), "'data', if supplied, must be a numeric vector or a data frame.", fixed = TRUE ) }) test_that("check_user_data works when passed a vector with 1 var", { expect_silent(df <- check_user_data(1:10, vars = "x1")) expect_s3_class(df, c("tbl_df", "tbl", "data.frame")) }) test_that("smooth_estimates works for m_gamm4", { expect_silent(sm <- smooth_estimates(m_gamm4, "s(x2)")) expect_s3_class(sm, c("smooth_estimates", "tbl_df", "tbl", "data.frame")) expect_identical(ncol(sm), 6L) expect_identical(nrow(sm), 100L) expect_named(sm, c(obj_nms, "x2")) }) test_that("smooth_estimates works for GAM with sz smooth single factor", { skip_if_not_installed("mgcv", minimum_version = "1.8.41") expect_silent(sm <- smooth_estimates(m_sz, "s(fac,x2)")) expect_s3_class(sm, c("smooth_estimates", "tbl_df", "tbl", "data.frame")) expect_identical(ncol(sm), 7L) expect_identical(nrow(sm), 300L) expect_named(sm, c(obj_nms, "fac", "x2")) }) test_that("smooth_estimates works for GAM with sz smooth two factors", { skip_if_not_installed("mgcv", minimum_version = "1.8.41") expect_silent(sm <- smooth_estimates(m_sz_2f, "s(f1,f2,x)")) expect_s3_class(sm, c("smooth_estimates", "tbl_df", "tbl", "data.frame")) expect_identical(ncol(sm), 8L) expect_identical(nrow(sm), 600L) expect_named(sm, c(obj_nms, "f1", "f2", "x")) }) test_that("check_all_vars errors if smooths not numeric or list", { skip_on_cran() expect_error(check_all_vars(m_gam, data = su_eg1, smooths = "a"), "Do not know how to handle supplied `smooths`." ) }) test_that("check_all_vars errors if smooths numeric out of bounds", { skip_on_cran() expect_error(check_all_vars(m_gam, data = su_eg1, smooths = 18), "do not inherit from class `mgcv.smooth`." ) }) test_that("check_all_vars works if smooths is null", { skip_on_cran() expect_silent(check_all_vars(m_gam, data = su_eg1)) })