context("filterClusters")
test_that("valid input parameters", {
data <- fullDataMapped
blank <- c()
brokenData <- data.table::copy(data)
brokenData[,Collapsed_Peptide := NULL]
brokenData[,Collapsed_Peptide := NULL]
cutoff_1 <- 1
cutoff_0 <- 0
cutoff_tooBig <- 1.5
cutoff_tooSmall <- -1
testthat::expect_error(filterClusters(blank),
"The provided input table is not a data.table. Please provide an output table from mapClusters.")
testthat::expect_error(filterClusters(brokenData),
"The provided input table does not contain all required columns. Please provide an output table from mapClusters.")
testthat::expect_error(filterClusters(data,cutoff_tooBig),
"The provided min_main_cluster_freq value is not valid. Please choose a value between 0 and 1.")
testthat::expect_error(filterClusters(data,cutoff_tooSmall),
"The provided min_main_cluster_freq value is not valid. Please choose a value between 0 and 1.")
testData <- subset(data,Collapsed_Peptide=="SLSGISSSDLTESGALLHDR(2P)")
testthat::expect_equal(nrow(filterClusters(testData)),196)
testthat::expect_equal(nrow(filterClusters(testData,cutoff_1)),0)
testthat::expect_equal(nrow(filterClusters(testData,cutoff_0)),196)
dataFiltered <- filterClusters(data,0.6)
testthat::expect_true(all(dataFiltered$new_cluster==dataFiltered$main_cluster_of_tg))
testthat::expect_gte(min(dataFiltered$main_cluster_tg_freq),0.6)
})
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