tests/testthat/test_makeSpatialization.R

In pokyah/agrometeoR: Spatial interpolation for Agromet project @ CRA-W

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## unit tests for makeSpatialization
## to run these tests, use : devtools::test(filter= "makeSpatialization")
## in case you want to debug on of these tests, place browser() where yo uwant the code execution to stop

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## library and context.
library(testthat)
context("Testing makeSpatialization")

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## definition of the various function inputs that are tested.
## the objects used in these function inputs definition comes precompiled. See folder data-raw for their source file

groups = list(
  good = list(
    all_good = list(
      model = ex_makeModel$output$value$trained,
      pred.grid = ex_grid
    )),
  bad = list(
    bad_grid = list(
      model = ex_makeModel$output$value$trained,
      pred.grid = ex_bad_grid
    ),
    bad_model = list(
      model = "bad_model",
      pred.grid = ex_grid
    )
  ))

#####
## definition of the unit tests

# test1
test_outputStrucure = function(){test_that("Output has the good structure whatever the inputs", {
  for (group in 1:length(groups)) {
    for (case in 1:length(group)) {
      object = do.call(what = makeSpatialization, args = groups[[group]][[case]])

      expect_is(object, class = "list")
      expect_named(object, c("snitch", "output"))
      expect_named(object$output, c("value", "condition"))
    }
  }
})
}

# test2
test_badInput = function(){test_that("Good behaviour in case of bad parameters", {
  for (group in 1:length(groups)) {
    if (names(groups[group]) == "bad") {
      for (case in 1:length(group)) {
        object = do.call(what = makeSpatialization, args = groups[[group]][[case]])

        browser()

        expect_false(object$snitch)
        expect_equal(object$output$condition$type, "error")
        expect_null(object$output$value)
      }
    }
  }
})}

# test3
test_goodInput = function(){test_that("Good behaviour in case of good parameter", {
  for (group in 1:length(groups)) {
    if (names(groups[group]) == "good") {
      for (case in 1:length(group)) {
        object = do.call(what = makeSpatialization, args = groups[[group]][[case]])

        # the snitch is at TRUE
        expect_true(object$snitch)
        # the returned object at slot value is of class list
        expect_is(object$output$value, "list")
        # the returned object at slot value summary and value spatialized are of class data.frame
        expect_is(object$output$value$summary, "data.frame")
        expect_is(object$output$value$spatialized, "data.frame")
        # the number of spatilized points is equal the size of the spatialization grid
        expect_identical(nrow(object$output$value$spatialized), nrow(ex_grid))
        # the px ids are equa
        expect_identical(unique(object$output$value$spatialized$px), unique(ex_grid$px))
      }
    }
  }
})}


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## execution of the tests. If you want to skip a test, simply comment it :)

test_outputStrucure()
# test_badInput()
test_goodInput()