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# context("counter factuals") deprecated
library(BART)
library(dplyr)
library(tidyr)
# set up counter factual values
md_cf <- bartmodel1_modelmatrix
md_cf[, "z"] <- 1 - md_cf[, "z"] # 0 -> 1, 1 -> 0
# rows = MCMC samples, cols = observations
check_matrix <- predict(bartmodel1, newdata = md_cf)
colnames(check_matrix) <- 1:ncol(check_matrix)
check_df <- check_matrix %>%
as_tibble() %>%
mutate(.draw = 1:n()) %>%
pivot_longer(
cols = all_of(1:ncol(check_matrix)),
names_to = ".row",
values_to = "cf_check"
) %>%
mutate(.row = as.integer(.row))
test_that("Counter factuals calculated correctly", {
td_cf <- tidytreatment:::fitted_with_counter_factual_draws(bartmodel1, treatment = "z", newdata = suhillsim1$data, subset = "all")
comp_df <- td_cf %>% full_join(check_df, by = c(".row", ".draw"))
expect_equal(comp_df$cfactual, comp_df$cf_check)
})
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