library(textrecipes)
library(recipes)

test_data <- tibble(text = c(
  "I would not eat them here or there.",
  "I would not eat them anywhere.",
  "I would not eat green eggs and ham.",
  "I do not like them, Sam-I-am."
))

rec <- recipe(~., data = test_data)

test_that("hashing gives double outputs", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 
  
  rec <- rec %>%
    step_tokenize(text) %>%
    step_texthash(text)

  obj <- rec %>%
    prep()

  expect_true(
    bake(obj, new_data = NULL) %>%
      select(contains("hash")) %>%
      lapply(is.integer) %>%
      unlist() %>%
      all()
  )

  expect_equal(dim(tidy(rec, 2)), c(1, 4))
  expect_equal(dim(tidy(obj, 2)), c(1, 4))
})

test_that("hashing output width changes accordingly with num_terms", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 
  
  rec <- rec %>%
    step_tokenize(text) %>%
    step_texthash(text, num_terms = 256) %>%
    prep()

  expect_equal(
    bake(rec, new_data = NULL) %>%
      select(contains("hash")) %>%
      ncol(),
    256
  )
})

test_that("hashing output width changes accordingly with num_terms", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 

  signed <- recipe(~., data = test_data) %>%
    step_tokenize(all_predictors()) %>%
    step_texthash(all_predictors(), num_terms = 2) %>%
    prep() %>%
    bake(new_data = NULL)

  unsigned <- recipe(~., data = test_data) %>%
    step_tokenize(all_predictors()) %>%
    step_texthash(all_predictors(), num_terms = 2, signed = FALSE) %>%
    prep() %>%
    bake(new_data = NULL)

  all(unsigned$texthash_text_1 == signed$texthash_text_1)
  all(unsigned$texthash_text_2 == signed$texthash_text_2)
  expect_false(all(unsigned$texthash_text_1 == signed$texthash_text_1))
  expect_false(all(unsigned$texthash_text_2 == signed$texthash_text_2))
})

test_that("check_name() is used", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 
  
  dat <- test_data
  dat$texthash_text_0001 <- dat$text
  
  rec <- recipe(~., data = dat) %>%
    step_tokenize(text) %>%
    step_texthash(text)
  
  expect_snapshot(
    error = TRUE,
    prep(rec, training = dat)
  )
})

test_that("tunable", {
  rec <-
    recipe(~., data = mtcars) %>%
    step_texthash(all_predictors())
  rec_param <- tunable.step_texthash(rec$steps[[1]])
  expect_equal(rec_param$name, c("signed", "num_terms"))
  expect_true(all(rec_param$source == "recipe"))
  expect_true(is.list(rec_param$call_info))
  expect_equal(nrow(rec_param), 2)
  expect_equal(
    names(rec_param),
    c("name", "call_info", "source", "component", "component_id")
  )
})

# Infrastructure ---------------------------------------------------------------

test_that("bake method errors when needed non-standard role columns are missing", {
  tokenized_test_data <- recipe(~text, data = test_data) %>%
    step_tokenize(text) %>%
    prep() %>%
    bake(new_data = NULL)
  
  rec <- recipe(tokenized_test_data) %>%
    update_role(text, new_role = "predictor") %>%
    step_texthash(text) %>%
    update_role(text, new_role = "potato") %>%
    update_role_requirements(role = "potato", bake = FALSE)
  
  trained <- prep(rec, training = tokenized_test_data, verbose = FALSE)
  
  expect_error(
    bake(trained, new_data = tokenized_test_data[, -1]),
    class = "new_data_missing_column"
  )
})

test_that("empty printing", {
  rec <- recipe(mpg ~ ., mtcars)
  rec <- step_texthash(rec)
  
  expect_snapshot(rec)
  
  rec <- prep(rec, mtcars)
  
  expect_snapshot(rec)
})

test_that("empty selection prep/bake is a no-op", {
  rec1 <- recipe(mpg ~ ., mtcars)
  rec2 <- step_texthash(rec1)
  
  rec1 <- prep(rec1, mtcars)
  rec2 <- prep(rec2, mtcars)
  
  baked1 <- bake(rec1, mtcars)
  baked2 <- bake(rec2, mtcars)
  
  expect_identical(baked1, baked1)
})

test_that("empty selection tidy method works", {
  rec <- recipe(mpg ~ ., mtcars)
  rec <- step_texthash(rec)
  
  expect <- tibble(
    terms = character(),
    value = logical(),
    length = integer(),
    id = character()
  )
  
  expect_identical(tidy(rec, number = 1), expect)
  
  rec <- prep(rec, mtcars)
  
  expect_identical(tidy(rec, number = 1), expect)
})

test_that("keep_original_cols works", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 
  
  new_names <- paste0("texthash_text_", 1:5)
  
  rec <- recipe(~text, data = test_data) %>%
    step_tokenize(text) %>%
    step_texthash(text, num_terms = 5, keep_original_cols = FALSE)
  
  rec <- prep(rec)
  res <- bake(rec, new_data = NULL)
  
  expect_equal(
    colnames(res),
    new_names
  )
  
  rec <- recipe(~text, data = test_data) %>%
    step_tokenize(text) %>%
    step_texthash(text, num_terms = 5, keep_original_cols = TRUE)
  
  rec <- prep(rec)
  res <- bake(rec, new_data = NULL)
  
  expect_equal(
    colnames(res),
    c("text", new_names)
  )
})

test_that("keep_original_cols - can prep recipes with it missing", {
  rec <- recipe(~text, data = test_data) %>%
    step_tokenize(text) %>%
    step_texthash(text)
  
  rec$steps[[2]]$keep_original_cols <- NULL
  
  expect_snapshot(
    rec <- prep(rec)
  )
  
  expect_error(
    bake(rec, new_data = test_data),
    NA
  )
})

test_that("printing", {
  skip_if_not_installed("text2vec")
  skip_if_not_installed("data.table")
  data.table::setDTthreads(2) # because data.table uses all cores by default 
  
  rec <- rec %>%
    step_tokenize(text) %>%
    step_texthash(text)
  
  expect_snapshot(print(rec))
  expect_snapshot(prep(rec))
})

test_that("tunable is setup to works with extract_parameter_set_dials", {
  skip_if_not_installed("dials")
  rec <- recipe(~., data = mtcars) %>%
    step_texthash(
      all_predictors(),
      signed = hardhat::tune(),
      num_terms = hardhat::tune()
    )
  
  params <- extract_parameter_set_dials(rec)
  
  expect_s3_class(params, "parameters")
  expect_identical(nrow(params), 2L)
})