if (getRversion() >= "4.0.0") {
m1 <- lm(hp ~ ordered(cyl), data = mtcars)
m2 <- lm(hp ~ as.ordered(cyl), data = mtcars)
m3 <- lm(hp ~ as.factor(cyl), data = mtcars)
m4 <- lm(hp ~ factor(cyl), data = mtcars)
test_that("get_datagrid - data from models", {
expect_equal(get_datagrid(m1)$cyl, c(4, 6, 8))
expect_equal(get_datagrid(m2)$cyl, c(4, 6, 8))
expect_equal(get_datagrid(m3)$cyl, c(4, 6, 8))
expect_equal(get_datagrid(m4)$cyl, c(4, 6, 8))
})
# get_datagrid() preserves all factor levels #695
test_that("get_datagrid - preserve factor levels #695", {
dat <<- transform(mtcars, cyl = factor(cyl))
mod <- lm(mpg ~ cyl + am + hp, data = dat)
grid <- get_datagrid(mod, at = "hp")
expect_equal(levels(grid$cyl), c("4", "6", "8"))
})
m <- lm(Sepal.Width ~ Petal.Length + Petal.Width + Species, data = iris)
# adjusted for works
test_that("get_datagrid - adjusted for works", {
dg <- insight::get_datagrid(m, "Species")
expect_equal(attributes(dg)$adjusted_for, c("Petal.Length", "Petal.Width"))
})
# bracket tokens
test_that("get_datagrid - terciles, quartiles, mean-sd", {
dg <- insight::get_datagrid(m, "Petal.Width = [quartiles]")
expect_equal(dg$Petal.Width, unname(quantile(iris$Petal.Width)), tolerance = 1e-4)
expect_equal(attributes(dg)$adjusted_for, c("Petal.Length", "Species"))
dg <- insight::get_datagrid(m, "Petal.Width = [meansd]")
.center <- mean(iris$Petal.Width)
.spread <- sd(iris$Petal.Width)
expect_equal(dg$Petal.Width, .center + c(-1, 0, 1) * .spread, tolerance = 1e-4)
expect_equal(attributes(dg)$adjusted_for, c("Petal.Length", "Species"))
dg <- insight::get_datagrid(m, "Petal.Width = [terciles]")
expect_equal(dg$Petal.Width, unname(quantile(iris$Petal.Width, probs = (1:2) / 3)), tolerance = 1e-4)
expect_equal(attributes(dg)$adjusted_for, c("Petal.Length", "Species"))
})
# bracket tokens
test_that("get_datagrid - range = grid", {
dg <- insight::get_datagrid(m, "Petal.Width", range = "grid")
expect_equal(
dg$Petal.Width,
c(
`-4 SD` = -1.8496, `-3 SD` = -1.0874, `-2 SD` = -0.3251, `-1 SD` = 0.4371,
Mean = 1.1993, `+1 SD` = 1.9616, `+2 SD` = 2.7238, `+3 SD` = 3.486,
`+4 SD` = 4.2483, `+5 SD` = 5.0105
),
tolerance = 1e-3
)
expect_equal(attributes(dg)$adjusted_for, c("Petal.Length", "Species"))
m <- lm(Sepal.Width ~ Petal.Length + Petal.Width * Species, data = iris)
dg <- insight::get_datagrid(m, c("Species", "Petal.Width"), range = "grid", preserve_range = FALSE)
expect_equal(
dg$Petal.Width,
c(
`-1 SD` = 0.4371, Mean = 1.1993, `+1 SD` = 1.9616, `-1 SD` = 0.4371,
Mean = 1.1993, `+1 SD` = 1.9616, `-1 SD` = 0.4371, Mean = 1.1993,
`+1 SD` = 1.9616
),
tolerance = 1e-3
)
expect_equal(attributes(dg)$adjusted_for, "Petal.Length")
})
# order of columns
test_that("get_datagrid - column order", {
m <- lm(Sepal.Width ~ Petal.Length + Petal.Width * Species, data = iris)
dg <- insight::get_datagrid(m, c("Petal.Width", "Species"))
expect_equal(colnames(dg), c("Petal.Width", "Species", "Petal.Length"))
dg <- insight::get_datagrid(m, c("Species", "Petal.Width"))
expect_equal(colnames(dg), c("Species", "Petal.Width", "Petal.Length"))
})
# list-argument
test_that("get_datagrid - list-argument", {
at <- list(Sepal.Length = c(3, 5), Species = c("versicolor", "virginica"))
dg1 <- get_datagrid(iris, at = at)
at <- c("Sepal.Length = c(3, 5)", "Species = c('versicolor', 'virginica')")
dg2 <- get_datagrid(iris, at = at)
expect_equal(dg1, dg2, tolerance = 1e-4)
})
}
if (requiet("bayestestR") && getRversion() >= "4.0.0") {
test_that("get_datagrid - data", {
# Factors
expect_equal(length(get_datagrid(iris$Species)), 3)
expect_equal(length(get_datagrid(c("A", "A", "B"))), 2)
expect_equal(length(get_datagrid(x = iris$Species, at = "c('versicolor')")), 1)
expect_equal(length(get_datagrid(iris$Species, at = "A = c('versicolor')")), 1)
expect_equal(length(get_datagrid(c("A", "A", "B"), at = "dupa = 'A'")), 1)
expect_equal(length(get_datagrid(iris$Species, at = "['versicolor', 'virginica']")), 2)
expect_equal(length(get_datagrid(iris$Species, at = "[versicolor, virginica]")), 2)
# Numerics
expect_equal(length(get_datagrid(x = iris$Sepal.Length)), 10)
expect_equal(length(get_datagrid(x = iris$Sepal.Length, length = 5)), 5)
expect_equal(length(get_datagrid(x = iris$Sepal.Length, length = NA)), length(unique(iris$Sepal.Length)))
expect_equal(min(get_datagrid(x = iris$Sepal.Length, range = "iqr")), as.numeric(quantile(iris$Sepal.Length, 0.025)))
expect_equal(min(get_datagrid(x = iris$Sepal.Length, range = "hdi")), as.numeric(bayestestR::hdi(iris$Sepal.Length, ci = 0.95, verbose = FALSE))[2])
expect_equal(min(get_datagrid(x = iris$Sepal.Length, range = "eti")), as.numeric(bayestestR::eti(iris$Sepal.Length, ci = 0.95, verbose = FALSE))[2])
expect_equal(length(get_datagrid(iris$Sepal.Length, at = "c(1, 3, 4)")), 3)
expect_equal(length(get_datagrid(iris$Sepal.Length, at = "A = c(1, 3, 4)")), 3)
expect_equal(length(get_datagrid(iris$Sepal.Length, at = "[1, 3, 4]")), 3)
expect_equal(length(get_datagrid(iris$Sepal.Length, at = "[1, 4]")), 10)
expect_equal(length(get_datagrid(iris$Sepal.Length, range = "sd", length = 10)), 10)
expect_equal(as.numeric(get_datagrid(iris$Sepal.Length, range = "sd", length = 3)[2]), mean(iris$Sepal.Length))
expect_equal(as.numeric(get_datagrid(iris$Sepal.Length, range = "mad", length = 4)[2]), median(iris$Sepal.Length))
# Dataframes
expect_equal(nrow(get_datagrid(iris, length = 2)), 48)
expect_equal(nrow(get_datagrid(iris, at = "Species", length = 2, numerics = 0)), 3)
expect_equal(nrow(get_datagrid(iris, at = "Sepal.Length", length = 3)), 3)
expect_equal(dim(get_datagrid(iris, at = 1:2, length = 3)), c(9, 5))
expect_equal(dim(get_datagrid(iris, at = 1:2, length = c(3, 2))), c(6, 5))
expect_equal(dim(get_datagrid(iris, at = 1:2, length = c(NA, 2))), c(70, 5))
expect_equal(dim(get_datagrid(iris, at = c("Sepal.Length = c(1, 2)"), length = NA)), c(2, 5))
expect_error(get_datagrid(iris, at = 1:2, length = c(3, 2, 4)))
expect_error(get_datagrid(iris, at = 1:2, length = "yes"))
expect_equal(as.numeric(get_datagrid(iris, at = 1:2, range = c("range", "mad"), length = c(2, 3))[4, "Sepal.Width"]), median(iris$Sepal.Width))
expect_equal(nrow(get_datagrid(data.frame(
X = c("A", "A", "B"),
Y = c(1, 5, 2)
), at = "Y", factors = "mode", length = 5)), 5)
expect_equal(nrow(get_datagrid(iris, at = c("Sepal.Length = 3", "Species"))), 3)
expect_equal(nrow(get_datagrid(iris, at = c("Sepal.Length = c(3, 1)", "Species = 'setosa'"))), 2)
x1 <- get_datagrid(iris, at = c("Species", "Sepal.Length"), length = 30, preserve_range = TRUE)
expect_equal(dim(x1), c(55, 5))
x2 <- get_datagrid(iris[c("Species", "Sepal.Length")], length = 30, preserve_range = TRUE)
expect_equal(dim(x2), c(55, 2))
})
}
if (requiet("gamm4") && getRversion() >= "4.0.0" && requiet("glmmTMB") && requiet("mgcv") && requiet("rstanarm") && requiet("TMB")) {
test_that("get_datagrid - models", {
# GLM
mod <- glm(Petal.Length ~ Petal.Width * Sepal.Length, data = iris)
expect_equal(dim(get_datagrid(mod)), c(100, 2))
mod <- glm(Petal.Length ~ Petal.Width * Species, data = iris)
expect_equal(dim(get_datagrid(mod)), c(10, 2))
# LMER4
mod <- lme4::lmer(Petal.Length ~ Petal.Width + (1 | Species), data = iris)
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(10, 2))
expect_equal(unique(get_datagrid(mod, include_random = FALSE)$Species), 0)
# GLMMTMB
skip_on_os("mac") # error: FreeADFunObject
mod <- suppressWarnings(glmmTMB::glmmTMB(Petal.Length ~ Petal.Width + (1 | Species), data = iris))
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(10, 2))
expect_equal(unique(get_datagrid(mod, include_random = FALSE)$Species), NA)
# MGCV
mod <- mgcv::gam(Petal.Length ~ Petal.Width + s(Sepal.Length), data = iris)
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(100, 2))
expect_equal(dim(get_datagrid(mod, include_smooth = FALSE)), c(10, 1))
expect_equal(dim(get_datagrid(mod, include_smooth = "fixed")), c(10, 2))
mod <- mgcv::gamm(Petal.Length ~ Petal.Width + s(Sepal.Length), random = list(Species = ~1), data = iris)
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(63, 3))
expect_equal(dim(get_datagrid(mod, include_random = FALSE, include_smooth = FALSE)), c(10, 1))
# GAMM4
mod <- gamm4::gamm4(Petal.Length ~ Petal.Width + s(Sepal.Length), random = ~ (1 | Species), data = iris)
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(63, 3))
expect_equal(dim(get_datagrid(mod, include_random = FALSE, include_smooth = "fixed")), c(10, 2))
expect_equal(dim(get_datagrid(mod, include_random = FALSE, include_smooth = FALSE)), c(10, 1))
# MGCV, splines with variables, see #678
data(mtcars)
mod <- mgcv::gam(mpg ~ s(wt, k = 3), data = mtcars)
out1 <- insight::get_datagrid(mod)
k <- 3
mod <- mgcv::gam(mpg ~ s(wt, k = k), data = mtcars)
out2 <- insight::get_datagrid(mod)
expect_equal(out1, out2, ignore_attr = TRUE, tolerance = 1e-4)
# STAN_GAMM4
mod <- suppressWarnings(rstanarm::stan_gamm4(Petal.Length ~ Petal.Width + s(Sepal.Length), random = ~ (1 | Species), data = iris, iter = 100, chains = 2, refresh = 0))
expect_equal(dim(get_datagrid(mod, include_random = TRUE)), c(63, 3))
expect_equal(dim(get_datagrid(mod, include_random = FALSE, include_smooth = "fixed")), c(10, 2))
expect_equal(dim(get_datagrid(mod, include_random = FALSE, include_smooth = FALSE)), c(10, 1))
})
# test if factor levels as reference / non-focal terms works
d <- structure(list(
lfp = structure(c(
2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"no",
"yes"
), class = "factor"), k5 = c(
1L, 0L, 1L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L
),
k618 = c(
0L, 2L, 3L, 3L, 2L, 0L, 2L, 0L, 2L, 2L, 1L, 2L,
0L, 0L, 2L, 1L, 1L, 0L, 0L, 1L, 0L, 0L
), age = c(
32L, 30L,
35L, 34L, 31L, 54L, 37L, 54L, 48L, 39L, 33L, 52L, 50L, 33L,
44L, 41L, 45L, 53L, 53L, 42L, 32L, 56L
), wc = structure(c(
1L,
1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 1L, 2L, 1L
), levels = c("no", "yes"), class = "factor"),
hc = structure(c(
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L
), levels = c(
"no",
"yes"
), class = "factor"), lwg = c(
1.2101647, 0.3285041,
1.5141279, 0.0921151, 1.5242802, 1.5564855, 2.1202636, 2.0596387,
0.7543364, 1.5448993, 1.4019157, 1.1889068, 0.9058391, 1.4934409,
1.4913014, 1.2186279, 0.8697261, 1.0620506, 1.1860113, 0.8703095,
1.2301208, 1.3053159
), inc = c(
10.9100008, 19.5, 12.039999,
6.8000002, 20.1000004, 9.8590002, 9.1520004, 10.9000006,
17.3050003, 12.9250002, 24.3000011, 14.6000004, 21.6000004,
24, 20.8829994, 19.5, 42.7999992, 41.5, 18.9650002, 16.1000004,
14.6999998, 18.7999992
)
), row.names = c(
"1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "11", "500", "501", "502", "503",
"504", "505", "506", "507", "508", "509", "510"
), class = "data.frame")
model <- suppressWarnings(glm(lfp ~ k618 + wc + hc + inc, data = d, family = binomial(link = "logit")))
expect_warning(
insight::get_datagrid(
model,
at = "k618", range = "grid", preserve_range = FALSE,
verbose = TRUE, include_response = FALSE
)
)
grid <- insight::get_datagrid(
model,
at = "k618", range = "grid", preserve_range = FALSE,
verbose = FALSE, include_response = TRUE
)
expect_equal(
sapply(grid, class),
c(
k618 = "numeric", lfp = "factor", wc = "factor", hc = "factor",
inc = "numeric"
)
)
out <- get_modelmatrix(model, data = grid)
expect_equal(
colnames(out),
c("(Intercept)", "k618", "wcyes", "hcyes", "inc")
)
}
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