test_that("RecruitmentCorrection", {
# Import data
library(data.table)
data(TestData)
# Create test data
MatrixData <- as.matrix(TestData)
NoDBHData <- TestData[, !c("Diameter")]
NoDBHCorData <- TestData
setnames(TestData, "Diameter", "Diameter_TreeDataCor")
# Check the function argument
expect_error(RecruitmentCorrection(MatrixData),
regexp = "Data must be a data.frame or data.table")
expect_error(RecruitmentCorrection(TestData, MinDBH = c(5, 10, 20), PositiveGrowthThreshold = TRUE),
regexp = "The 'MinDBH' and 'PositiveGrowthThreshold'' arguments
of the 'RecruitmentCorrection' function must be 1 numeric value each")
expect_error(RecruitmentCorrection(TestData, InvariantColumns = c(1:3)),
regexp = "'InvariantColumns' argument must be of character class")
expect_error(RecruitmentCorrection(TestData,
DetectOnly = "no"),
regexp = "The 'DetectOnly' argument
of the 'RecruitmentCorrection' function must be logicals")
expect_error(RecruitmentCorrection(NoDBHData),
regexp = "column does't exist in the dataset.")
expect_error(RecruitmentCorrection(TestData, InvariantColumns = "a"),
regexp = "InvariantColumns argument must contain one or several column names")
# Check the function works
Rslt <- RecruitmentCorrection(TestData,
InvariantColumns = c("Site",
"Genus",
"Species",
"Family",
"ScientificName"))
})
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