tests/testthat/test_myetruncnorm.R

In stephens999/ashr: Methods for Adaptive Shrinkage, using Empirical Bayes

context("my_etruncnorm")

test_that("my_etruncnorm returns expected results", {
  expect_equal(-100,my_etruncnorm(-Inf,-100,0,1),tolerance=0.01)
  expect_equal(-100,my_etruncnorm(-Inf,-100,0,0))
  expect_equal(30,my_etruncnorm(30,100,0,0))
  real = c(-100,-100,30)
  a=c(-Inf,-Inf,30)
  b=c(-100,-100,100)
  m=c(0,0,0)
  sd=c(1,0,0)
  expect_equal(real,my_etruncnorm(a,b,m,sd),tolerance=0.01)
  real = matrix(real,3,4)
  m = matrix(m,3,4)
  sd = matrix(sd,3,4)
  expect_equal(real,my_etruncnorm(a,b,m,sd),tolerance=0.01)
  a=c(0,0)
  b=c(1,2)
  m = rbind(c(0,2,4),c(0,0,0))
  sd = 0
  real = rbind(c(0,1,1),c(0,0,0))
  expect_equal(real,my_etruncnorm(a,b,m,sd))
  
  expect_equal(my_etruncnorm(0,99,-2,3),truncnorm::etruncnorm(0,99,-2,3))
  expect_equal(my_etruncnorm(0,9999,-2,3),my_etruncnorm(0,Inf,-2,3),tol=1e-3)
  expect_error(my_etruncnorm(0, 1:2, mean = 0, sd = 1))
  expect_error(my_etruncnorm(1, 0, mean = 0, sd = 1))
})

context("my_vtruncnorm")

test_that("my_vtruncnorm returns expected results", {
  expect_equal(0, my_vtruncnorm(-Inf, -100), tolerance = 0.01)
  expect_equal(0, my_vtruncnorm(-Inf, -100, sd = 0))
  expect_equal(0, my_vtruncnorm(30, 100, sd = 0))
  real = c(0, 0, 0)
  a = c(-Inf, -Inf, 30)
  b = c(-100, -100, 100)
  m = c(0, 0, 0)
  sd = c(1, 0, 0)
  expect_equal(real, my_vtruncnorm(a, b, m, sd), tolerance = 0.01)
  real = matrix(real, 3, 4)
  m = matrix(m, 3, 4)
  sd = matrix(sd, 3, 4)
  expect_equal(real, my_vtruncnorm(a, b, m, sd), tolerance = 0.01)
  a = c(0, 0)
  b = c(1, 2)
  m = rbind(c(0, 2, 4), c(0, 0, 0))
  sd = 0
  real = rbind(c(0, 0, 0), c(0, 0, 0))
  expect_equal(real, my_vtruncnorm(a,b,m,sd))
  
  expect_equal(my_vtruncnorm(-2, 3), truncnorm::vtruncnorm(-2, 3))
  expect_equal(my_vtruncnorm(6, 7, sd = 9), truncnorm::vtruncnorm(6, 7, sd = 9))
  expect_equal(my_vtruncnorm(0, 9999, -2, 3),
               my_vtruncnorm(0, Inf, -2, 3), tol = 1e-3)
})