tests/testthat/test_dist_data_cdf.R

In csgillespie/poweRlaw: Analysis of Heavy Tailed Distributions

test_that("Testing dist_data_cdf function", {

  x = c(1, 1, 2, 4, 5, 5)
  mt = displ$new(x)
  expect_equal(dist_data_cdf(mt), c(1 / 3, 1 / 2, 4 / 6, 1), tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), c(1 / 4, 1 / 2, 1), tol = 1e-4)

  ##Discrete log normal
  x = c(1, 1, 2, 4, 5, 5)
  mt = dislnorm$new(x)
  expect_equal(dist_data_cdf(mt), c(1 / 3, 1 / 2, 4 / 6, 1), tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), c(1 / 4, 1 / 2, 1), tol = 1e-4)

  ##Discrete Poisson
  x = c(1, 1, 2, 4, 5, 5)
  mt = dispois$new(x)
  expect_equal(dist_data_cdf(mt), c(1 / 3, 1 / 2, 4 / 6, 1), tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), c(1 / 4, 1 / 2, 1), tol = 1e-4)

  ##I don't think this is correct
  ##But it's what clausett does
  ##Need to check
  ##CTN power-law
  x = c(1, 1, 2, 4, 5)
  mt = conpl$new(x)
  expect_equal(dist_data_cdf(mt), 0:4 / 5, tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), 0:2 / 3, tol = 1e-4)

  ##CTN power-law
  x = c(1, 1, 2, 4, 5)
  mt = conpl$new(x)
  expect_equal(dist_data_cdf(mt), 0:4 / 5, tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), 0:2 / 3, tol = 1e-4)

  ##CTN lognormal
  x = c(1, 1, 2, 4, 5)
  mt = conlnorm$new(x)
  expect_equal(dist_data_cdf(mt), 0:4 / 5, tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), 0:2 / 3, tol = 1e-4)


  ##CTN Exp
  x = c(1, 1, 2, 4, 5)
  mt = conexp$new(x)
  expect_equal(dist_data_cdf(mt), 0:4 / 5, tol = 1e-4)
  mt$setXmin(2)
  expect_equal(dist_data_cdf(mt), 0:2 / 3, tol = 1e-4)

}
)