# Exits
if (!requireNamespace("rpart", quietly = TRUE)) {
exit_file("Package rpart missing")
}
# # Load required packages
# suppressMessages({
# library(rpart)
# })
# Generate Friedman benchmark data
friedman1 <- gen_friedman(seed = 101)
# Fit model(s)
fit <- rpart::rpart(y ~ ., data = friedman1)
no_splits <- rpart::rpart(y ~ ., data = friedman1, minsplit = 1e06)
# Compute VI scores
vis <- vi_model(fit)
# Expectations for `vi_model()`
expect_identical(
current = vis$Importance,
target = unname(fit$variable.importance)
)
expect_error(vi(no_splits))
# Expectations for `get_training_data()`
expect_identical(
current = vip:::get_training_data.default(fit),
target = friedman1
)
# Expectations for `get_feature_names()`
expect_identical(
current = vip:::get_feature_names.rpart(fit),
target = paste0("x", 1L:10L)
)
# Call `vip::vip()` directly
p <- vip(fit, method = "model", type = 1, include_type = TRUE)
# Expect `p` to be a `"gg" "ggplot"` object
expect_identical(
current = class(p),
target = c("gg", "ggplot")
)
# Display VIPs side by side
grid.arrange(
vip(vis, include_type = TRUE),
p,
nrow = 1
)
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