context("Check plot() function for broken object")
HR_data <- breakDown::HR_data
wine <- breakDown::wine
model_classif_rf <- randomForest::randomForest(factor(left)~., data = breakDown::HR_data, ntree = 50)
model_regr_lm <- lm(quality~., data = breakDown::wine)
model_classif_glm <- glm(factor(left)~., data = breakDown::HR_data, family = "binomial")
predict_function_rf <- function(model, x) predict(model, x, type = "prob")[,2]
predict_function_glm <- function(model, x) predict(model, x, type = "response")
new_observation_classif <- HR_data[11,-7]
new_observation_regr <- wine[8,-12]
broken_rf_classif <- broken(model_classif_rf, new_observation_classif, data = HR_data[,-7],
predict.function = predict_function_rf, direction = "down")
broken_rf_classif_extended <- broken(model_classif_rf, new_observation_classif, data = HR_data[,-7],
predict.function = predict_function_rf, direction = "down", keep_distributions=TRUE)
broken_lm_regr <- broken(model_regr_lm, new_observation_regr, data = wine[,-12], direction = "up")
broken_lm_regr_extended <- broken(model_regr_lm, new_observation_regr, data = wine[,-12], direction = "up", keep_distributions=TRUE)
broken_glm_classif <- broken(model_classif_glm, new_observation_classif, data = HR_data[,-7], direction = "up")
test_that("Output format", {
expect_is(plot(broken_rf_classif), "gg")
expect_is(plot(broken_lm_regr), "gg")
expect_is(plot(broken_glm_classif), "gg")
expect_is(plot(broken_rf_classif, top_features = 3), "gg")
expect_is(plot(broken_lm_regr, min_delta = 0.1), "gg")
expect_is(plot(broken_lm_regr, min_delta = 10, top_features = 20), "gg")
expect_is(plot(broken_glm_classif, top_features = 3, min_delta = 0.1), "gg")
expect_length(plot(broken_rf_classif), length(ggplot()))
expect_length(plot(broken_lm_regr), length(ggplot()))
expect_length(plot(broken_glm_classif), length(ggplot()))
expect_is(plot(broken_rf_classif_extended, plot_distributions=TRUE, add_contributions = FALSE), "gg")
expect_is(plot(broken_rf_classif_extended, plot_distributions=TRUE), "gg")
})
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