tests/testthat/test_2_5_textPredict.R

In OscarKjell/text: Analyses of Text using Transformers Models from HuggingFace, Natural Language Processing and Machine Learning

library(testthat)
library(text)
library(tibble)
library(dplyr)

context("Prediction")

test_that("textPredictTest t-test and bootstrapped test", {
  skip_on_cran()
  set.seed(1)

  # Test data
  y1 <- runif(10)
  yhat1 <- runif(10)
  y2 <- runif(10)
  yhat2 <- runif(10)

  boot_test <- text::textPredictTest(y1,
                                     yhat1,
                                     y2,
                                     yhat2,
                                     method = "bootstrap",
                                     bootstraps_times = 10
  )

  testthat::expect_that(boot_test, testthat::is_a("list"))
  testthat::expect_equal(boot_test$overlapp_p_value, 0.7398745, tolerance = 0.0001)

  boot_test2 <- text::textPredictTest(
    y1 = y1,
    yhat1,
    y2 = NULL,
    yhat2,
    method = "t-test"
  )

  testthat::expect_that(boot_test2, testthat::is_a("list"))
  testthat::expect_equal(boot_test2$Test$statistic[[1]], 0.233267, tolerance = 0.0001)
  testthat::expect_equal(boot_test2$Effect_size, 0.06198192, tolerance = 0.0001)


  # Test data
  set.seed(1)
  y1 <- sample(c(1, 2), 20, replace = T)
  yhat1 <- runif(20)

  y2 <- sample(c(1, 2), 20, replace = T)
  yhat2 <- runif(20)


  boot_test_auc1 <- text::textPredictTest(
    y1 = y1,
    yhat1,
    y2 = y2,
    yhat2,
    method = "bootstrap",
    statistic = "auc",
    times = 10
  )

  testthat::expect_equal(boot_test_auc1$overlapp_p_value, 0.4530578, tolerance = 0.0001)


  boot_test_auc2 <- text::textPredictTest(
    y1 = y1,
    yhat1,
    y2 = y1,
    yhat2,
    method = "bootstrap",
    statistic = "auc",
    bootstraps_times = 10
  )

  testthat::expect_equal(boot_test_auc2$overlapp_p_value, 0.5782996, tolerance = 0.0001)
})