tests/testthat/test-generics.R

In FrankPortman/bayesAB: Fast Bayesian Methods for AB Testing

library(bayesAB)
context('generics')

A_data <- rlnorm(100)
B_data <- rlnorm(100)

priors <- c('mu' = 5, 'lambda' = 3, 'alpha' = 3, 'beta' = 2)

x <- bayesTest(A_data, B_data, priors = priors, distribution = 'lognormal')

A_binom<- rbinom(100, 1, .5)
B_binom <- rbinom(100, 1, .6)

AB3 <- bayesTest(A_binom, B_binom, 
                 priors = c('alpha' = 1, 'beta' = 1), distribution = 'bernoulliC')

AB4 <- bayesTest(A_binom, B_binom, 
                 priors = c('alpha' = 1, 'beta' = 1), distribution = 'bernoulli')

test_that("Failures based on inputs", {
  
  expect_error(plot(x, percentLift = 0), "Must supply a 'percentLift' for every parameter with a posterior distribution.")
  
  expect_error(plot(x, priors = FALSE, posteriors = FALSE, samples = FALSE), "Must specifiy at least one plot to make.")
  
  expect_error(summary(x, percentLift = 0), "Must supply a 'percentLift' for every parameter with a posterior distribution.")
  
  expect_error(summary(x, credInt = 0), "Must supply a 'credInt' for every parameter with a posterior distribution.")
  
  expect_error(c(x, AB4), "Unable to concatenate. Mismatches in (A_data, B_data, priors, distribution). All inputs must be the same (except n_samples).",
               fixed = TRUE)

  expect_error(plot(AB3), "Can't plot 'closed form' bayesTest.", fixed = TRUE)

  expect_error(summary(x, credInt = c(5, 5, 5, 5)), "Credible interval width must be in (0, 1).", fixed = TRUE)

})

test_that("Success", {
  
  expect_silent(plot(x))
  expect_silent(plot(x, rep(.5, 4)))
  expect_equal(length(plot(x, posteriors = FALSE, samples = FALSE)$priors), 1)
  expect_equal(names(plot(x, posteriors = FALSE, samples = FALSE)$priors), c('NormalInvGamma'))
  
  expect_silent(print(plot(x)))
  expect_silent(print(plot(x, rep(.5, 4))))
  
  expect_output(print(x), "Distribution used")
  
  expect_silent(summary(x))
  expect_silent(summary(x, rep(.5, 4)))
  expect_silent(summary(x, rep(.5, 4), rep(.5, 4)))
  
  expect_output(print(summary(x)), 'P(A > B)', fixed = TRUE)
  expect_output(print(summary(AB3)), 'P(A > B)', fixed = TRUE)
  
  expect_is(c(x, x), "bayesTest")
  expect_identical(rep(x$posteriors$Mu$A, 2), c(x, x)$posteriors$Mu$A)
  expect_identical(rep(x$posteriors$Mu$B, 2), c(x, x)$posteriors$Mu$B)
  expect_identical(rep(x$posteriors$Mu$A, 3), c(x, x, x)$posteriors$Mu$A)
  
})