HTML=isTRUE(Sys.getenv("ART_GENERATE_HTML") == "TRUE") # Set with Sys.setenv(ART_GENERATE_HTML = "TRUE") overwrite = FALSE # Use TRUE when creating new tests that need new *_epected data. test_that("amExample2 results from pg 8 in allelematchSuppDoc.pdf 2.5.3 compatible", code = { # Prepare for printing large snapshot files: withr::local_options(width=200) # Allow longer lines for the summaries: # Follow the instructions from allelematchSuppDoc.pdf, pg: data("amExample2") example2 <- amDataset(amExample2, indexColumn="sampleId", metaDataColumn="knownIndividual", missingCode="-99") { # Ensure that the result is still the same as that from 2.5.3: expect_snapshot_value(example2, style="deparse") } output = capture.output( amUniqueProfile(example2, doPlot=TRUE) ) { # Check that the output to STDOUT is still the same as that from 2.5.3: testthat::expect_match(output, "missing data load for input dataset is 0.046 ", fixed=TRUE, all=FALSE) testthat::expect_match(output, "allelic diversity for input dataset is 7.9 ", fixed=TRUE, all=FALSE) testthat::expect_match(output, "Best guess for optimal parameter at alleleMismatch=3 OR matchThreshold=0.85 OR cutHeight=0.15$", all=FALSE) testthat::expect_match(output, "Best guess for unique profile morphology: ZeroSecondMinimum$", all=FALSE) } output = capture.output( uniqueExample2 <- amUnique(example2, alleleMismatch=3) ) { # Check that the output to STDOUT is still the same as that from 2.5.3: testthat::expect_match(output, "allelematch: assuming genotype columns are in pairs, representing 10 loci$", all=FALSE) # Ensure that the result is still the same as that from 2.5.3: expect_snapshot_value(uniqueExample2, style="deparse") # Generate a summary file: summary.amUnique(uniqueExample2, csv=summaryFile <- tempfile("example2_1.csv")) # Ensure that the result is still the same as that from 2.5.3 expect_snapshot_value(read.csv(file=summaryFile, colClasses="character"), style="deparse") file.remove(summaryFile) } if(HTML) { summary.amUnique(uniqueExample2, html=helpHtml("example2_1.html")) } output = capture.output( uniqueExample2 <- amUnique(example2, alleleMismatch=3, doPsib="all") ) { testthat::expect_match(output, "allelematch: assuming genotype columns are in pairs, representing 10 loci$", all=FALSE) # Ensure that the result is still the same as that from 2.5.3: expect_snapshot_value(uniqueExample2, style="deparse") # Generate a summary file: summary.amUnique(uniqueExample2, csv=summaryFile <- tempfile("example2_2.csv")) # Ensure that the result is still the same as that from 2.5.3 expect_snapshot_value(read.csv(file=summaryFile, colClasses="character"), style="deparse") file.remove(summaryFile) } if(HTML) { summary.amUnique(uniqueExample2, html=helpHtml("example2_2.html")) } # Copied from test of amExample1: example2chk <- amDataset(amExample2, indexColumn="sampleId", metaDataColumn="knownIndividual", missingCode="-99") { # Ensure that the result is still the same as that from 2.5.3: expect_snapshot_value(example2chk, style="deparse") } output = capture.output( uniqueExample2chk <- amUnique(example2chk, alleleMismatch=2) ) { testthat::expect_match(output, "allelematch: assuming genotype columns are in pairs, representing 10 loci$", all=FALSE) # Ensure that the result is still the same as that from 2.5.3: expect_snapshot_value(uniqueExample2chk, style="deparse") } })