revdep/checks.noindex/pmml/old/pmml.Rcheck/tests/testthat/test_pmml.nnet.R

In gbm-developers/gbm: Generalized Boosted Regression Models

library(nnet)
data(iris)

# teardown({detach("package:nnet", unload=TRUE)})

test_that("error when object is not nnet", {
  expect_error(pmml.nnet("foo"), "Not a legitimate nnet object")
})

test_that("No error for formula input", {
  fit_3 <- nnet(Species ~ ., data = iris, size = 4, trace = FALSE)
  expect_error(pmml.nnet(fit_3), NA)
})

test_that("No error when number of output neurons is 1", {
  fit_4 <- nnet(Sepal.Width ~ Petal.Length + Petal.Width,
    data = iris,
    size = 3, trace = FALSE
  )
  expect_error(pmml.nnet(fit_4), NA)
})


test_that("No error for matrix input", {
  ir <- rbind(iris3[, , 1], iris3[, , 2], iris3[, , 3])
  targets <- class.ind(c(rep("s", 50), rep("c", 50), rep("v", 50)))
  set.seed(1)
  samp <- c(sample(1:50, 25), sample(51:100, 25), sample(101:150, 25))
  fit <- nnet(ir[samp, ], targets[samp, ],
    size = 2, rang = 0.1,
    decay = 5e-4, maxit = 5, trace = FALSE
  )

  expect_error(pmml(fit), NA)
})

test_that("No error for data.frame input", {
  ir <- as.data.frame(rbind(iris3[, , 1], iris3[, , 2], iris3[, , 3]))
  targets <- as.data.frame(class.ind(c(rep("s", 50), rep("c", 50), rep("v", 50))))
  set.seed(2)
  samp <- c(sample(1:50, 25), sample(51:100, 25), sample(101:150, 25))
  fit_2 <- nnet(ir[samp, ], targets[samp, ],
    size = 2, rang = 0.1,
    decay = 5e-4, maxit = 6, trace = FALSE
  )

  expect_error(pmml(fit_2), NA)
})