# library(testthat) # testthat::test_file("tests/testthat/test-select_rate.R") # covr::file_coverage("R/select_rate.R", "tests/testthat/test-select_rate.R") # Sys.setenv(NOT_CRAN = "true") # cvr <- covr::package_coverage() # covr::report(cvr) # Sys.setenv(NOT_CRAN = "false") capture.output({ ## stops printing outputs on assigning skip_on_cran() ## objects for testing ## convert_rate-from-auto_rate object ## contains both negative and positive rates { suppressWarnings(conv_rt_ar_obj <- inspect(intermittent.rd) %>% auto_rate(plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955)) ## for testing with zero/non-zero change a couple to zero conv_rt_ar_obj_w_0 <- conv_rt_ar_obj conv_rt_ar_obj_w_0$rate[3] <- 0 conv_rt_ar_obj_w_0$summary$rate[3] <- 0 conv_rt_ar_obj_w_0$rate[9] <- 0 conv_rt_ar_obj_w_0$summary$rate[9] <- 0 ## make subset by method test objects suppressWarnings(conv_rt_ar_subset_pos <- select_rate(conv_rt_ar_obj, method = "positive")) suppressWarnings(conv_rt_ar_subset_neg <- select_rate(conv_rt_ar_obj, method = "negative")) suppressWarnings(conv_rt_ar_subset_nonzero <- select_rate(conv_rt_ar_obj_w_0, method = "nonzero")) suppressWarnings(conv_rt_ar_subset_zero <- select_rate(conv_rt_ar_obj_w_0, method = "zero")) ## objects to test subsetting of different auto_rate methods conv_rt_ar_obj_high <- auto_rate(urchins.rd[,1:2], method = "highest") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_low <- auto_rate(urchins.rd[,1:2], method = "lowest") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_maximum <- auto_rate(urchins.rd[,1:2], method = "maximum") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_minimum <- auto_rate(urchins.rd[,1:2], method = "minimum") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_max <- suppressWarnings(auto_rate(urchins.rd[,1:2], method = "max")) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_min <- suppressWarnings(auto_rate(urchins.rd[,1:2], method = "min")) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_int <- auto_rate(urchins.rd[,1:2], method = "interval") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) conv_rt_ar_obj_high_sub <- select_rate(conv_rt_ar_obj_high, method = "rsq", n = c(0.96,1)) # large object conv_rt_ar_low_obj <- inspect(sardine.rd) %>% auto_rate(method = "lowest", plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) # intermittent-flow test data # regular reps - 10 reps from this dataset dt.reg.insp <- subset_data(zeb_intermittent.rd, from = 5840, to = 5840 + 6599, by = "row") %>% inspect(legend = F, plot = T) # 10 reps, 1 rank in each conv_rt_ar.int_obj <- dt.reg.insp %>% calc_rate.int(starts = 660, by = "time", plot = F) %>% convert_rate(oxy.unit = "mg/L", time.unit = "secs", output.unit = "mg/h/g", volume = 0.12, mass = 0.0009) # 10 reps, multiple ranks in each conv_rt_ar.int_obj_mult_ranks <- dt.reg.insp %>% auto_rate.int(starts = 660, wait = 120, measure = 360, by = "row", plot = F, n = 5, width = 0.4) %>% convert_rate(oxy.unit = "mg/L", time.unit = "secs", output.unit = "mg/h/g", volume = 0.12, mass = 0.0009) } # General checks ---------------------------------------------------------- test_that("select_rate - works with convert_rate-from-auto_rate input", { expect_error(select_rate(conv_rt_ar_obj, method = "positive"), regexp = NA) }) test_that("select_rate - works with convert_rate-from-auto_rate input that has already been subset", { expect_error(select_rate(conv_rt_ar_subset_pos, method = "positive"), regexp = NA) }) test_that("select_rate - stops if input is not a convert_rate object", { expect_error(select_rate(calc_rate(intermittent.rd, from = 0, to = 1000, by = "row")), regexp = "select_rate: Input is not a 'convert_rate' or 'convert_rate.ft' object") expect_error(select_rate(545), regexp = "select_rate: Input is not a 'convert_rate' or 'convert_rate.ft' object") }) test_that("select_rate - stops if wrong method", { expect_error(select_rate(conv_rt_ar_subset_pos, method = "blah"), regexp = "select_rate: 'method' input not recognised") }) test_that("select_rate - output inherits convert_rate and convert_rate_select class", { expect_is(conv_rt_ar_subset_pos, "convert_rate") expect_is(conv_rt_ar_subset_pos, "convert_rate_select") }) test_that("select_rate - outputs can be plotted (as convert_rate objects)", { ## (checking all here) for(i in 1:length(conv_rt_ar_subset_pos$rate.output)) expect_output(plot(conv_rt_ar_subset_pos, pos = i)) }) test_that("select_rate - summary and print generics work", { expect_output(summary(conv_rt_ar_subset_pos)) expect_output(print(conv_rt_ar_subset_pos)) }) test_that("select_rate - works with pipes", { suppressMessages(piped_conv_rt_ar_subset_obj <- inspect(intermittent.rd) %>% auto_rate(plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) %>% select_rate(method = "positive")) expect_equal(piped_conv_rt_ar_subset_obj$rate, conv_rt_ar_subset_pos$rate) }) test_that("select_rate - works chained by multiple pipes", { chain <- select_rate(conv_rt_ar_obj_w_0, method = "nonzero") %>% select_rate(method = "positive") %>% select_rate(method = "row", n = c(2000, 4100)) %>% select_rate(method = "highest", n = 2) expect_length(chain$rate.output, 2) expect_equal(chain$rate.output[1], 0.02212841) }) test_that("select_rate - output has saved original convert_rate input", { expect_equal(conv_rt_ar_subset_neg$original, conv_rt_ar_obj) }) test_that("select_rate - output has saved subset calls", { expect_equal(as.character(conv_rt_ar_subset_neg$select_calls[[1]]), c("select_rate", "conv_rt_ar_obj", "negative")) }) test_that("select_rate - works with convert_rate-from-auto_rate method = highest object", { expect_error(select_rate(conv_rt_ar_obj_high, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_high, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = lowest object", { expect_error(select_rate(conv_rt_ar_obj_low, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_low, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = maximum object", { expect_error(select_rate(conv_rt_ar_obj_maximum, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_maximum, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = minimum object", { expect_error(select_rate(conv_rt_ar_obj_minimum, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_minimum, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = max object (OLD METHOD", { expect_error(select_rate(conv_rt_ar_obj_max, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_max, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = min object (OLD METHOD)", { expect_error(select_rate(conv_rt_ar_obj_min, method = "rsq", n = c(0.96,1)), regexp = NA) ## should be 38 remaining expect_equal(length(select_rate(conv_rt_ar_obj_min, method = "rsq", n = c(0.96,1))$rate.output), 38) }) test_that("select_rate - works with convert_rate-from-auto_rate method = interval object (OLD METHOD", { expect_error(select_rate(conv_rt_ar_obj_int, method = "rsq", n = c(0.90,0.95)), regexp = NA) ## should be 3 remaining - IN INTERVAL CASE ONLY expect_equal(length(select_rate(conv_rt_ar_obj_int, method = "rsq", n = c(0.90,0.95))$rate.output), 3) }) test_that("select_rate - works with empty objects", { empty_obj <- select_rate(conv_rt_ar_obj, method = "rate", n = c(0.1, 1)) empty_obj$summary empty_obj$rate.output # works with S3 expect_output(print(empty_obj)) expect_message(print(empty_obj), "No rates found in convert_rate object.") expect_output(summary(empty_obj)) expect_message(summary(empty_obj), "No rates found in convert_rate object.") expect_output(mean(empty_obj)) expect_message(mean(empty_obj), "No rates found in convert_rate object.") # subsetting expect_error(select_rate(empty_obj, method = "rsq", n = c(0.90,0.95)), regexp = NA) expect_message(select_rate(empty_obj, method = "rsq", n = c(0.90,0.95)), regexp = "----- Selection complete. 0 rate\\(s) removed, 0 rate\\(s) remaining -----") # reordering expect_error(select_rate(empty_obj, method = "rsq", n = NULL), regexp = NA) expect_message(select_rate(empty_obj, method = "rsq", n = NULL), regexp = "----- Reordering complete. 0 rate\\(s) reordered by 'rsq' method -----") }) # Check NULL stops fn -------------------------------------------- test_that("select_rate - method = NULL - correct message", { expect_error(conv_rt_ar_obj_uniq <- select_rate(conv_rt_ar_obj_high), regexp = "select_rate: Please specify a 'method'") }) # Check "positive" method ------------------------------------------------- test_that("select_rate: method = positive - all output rates are positive", { expect_true(all(conv_rt_ar_subset_pos$rate.output > 0)) }) test_that("select_rate: method = positive - check n rates are subset", { expect_length(conv_rt_ar_subset_pos$rate.output, 11) }) test_that("select_rate: method = positive - check some exact values", { expect_equal(conv_rt_ar_subset_pos$rate.output[4], convert_rate(0.0009992067, oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955)$rate.output) }) test_that("select_rate: method = positive - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "positive"), "select_rate: Selecting all positive rate values. 'n' input ignored...") }) # Check "negative" method ------------------------------------------------- test_that("select_rate: method = negative - all output rates are negative", { expect_true(all(conv_rt_ar_subset_neg$rate.output < 0)) }) test_that("select_rate: method = negative - check n rates are subset", { expect_length(conv_rt_ar_subset_neg$rate.output, 5) }) test_that("select_rate: method = negative - check some exact values", { expect_equal(conv_rt_ar_subset_neg$rate.output[4], convert_rate(-0.0005949222, oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955)$rate.output) }) test_that("select_rate: method = negative - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "negative"), "Selecting all negative rate values. 'n' input ignored.") }) # Check "nonzero" method -------------------------------------------------- test_that("select_rate: method = nonzero - NO rates should be zero", { expect_true(all(conv_rt_ar_subset_nonzero$rate.output != 0)) }) test_that("select_rate: method = nonzero - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "nonzero"), "Selecting all non-zero rate values. 'n' input ignored.") }) # Check "zero" method ----------------------------------------------------- test_that("select_rate: method = zero - ALL rates should be zero", { expect_true(all(conv_rt_ar_subset_zero$rate.output == 0)) }) test_that("select_rate: method = zero - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "zero"), "Selecting all zero rate values. 'n' input ignored.") }) # Check "lowest" method --------------------------------------------------- test_that("select_rate: method = lowest - errors", { expect_error(select_rate(conv_rt_ar_obj, method = "lowest", n = 7), regexp = "Object contains both negative and positive rates.") expect_error(select_rate(conv_rt_ar_obj_min, method = "lowest", n = 7.1), regexp = "select_rate: For 'lowest' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_obj_min, method = "lowest", n = -1), regexp = "select_rate: For 'lowest' method 'n' must contain only positive integers.") expect_message(select_rate(conv_rt_ar_obj_min, method = "lowest", n = 1000), regexp = "select_rate: 'n' input is greater than number of rates in \\$summary. Nothing to remove.") }) test_that("select_rate: method = lowest - check n rates extracted for positive rates", { conv_rt_ar_subset_low_pos <- select_rate(conv_rt_ar_subset_pos, method = "lowest", n = 3) expect_equal(length(conv_rt_ar_subset_low_pos$rate.output), 3) }) test_that("select_rate: method = lowest - check they are LOWEST numerically for positive rates", { conv_rt_ar_subset_low_pos <- select_rate(conv_rt_ar_subset_pos, method = "lowest", n = 3) expect_equal(head(sort(conv_rt_ar_subset_pos$rate.output), 3), ## head to get lowest sort(conv_rt_ar_subset_low_pos$rate.output)) }) test_that("select_rate: method = lowest - check n rates extracted for negative rates", { conv_rt_ar_subset_low_neg <- select_rate(conv_rt_ar_subset_neg, method = "lowest", n = 3) expect_equal(length(conv_rt_ar_subset_low_neg$rate.output), 3) }) test_that("select_rate: method = lowest - check they are HIGHEST numerically for negative rates", { conv_rt_ar_subset_low_neg <- select_rate(conv_rt_ar_subset_neg, method = "lowest", n = 3) expect_equal(tail(sort(conv_rt_ar_subset_neg$rate.output), 3), ## tail to get lowest sort(conv_rt_ar_subset_low_neg$rate.output)) }) test_that("select_rate: method = lowest - check message", { expect_message(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = 3), "Selecting lowest") }) # Check "highest" method -------------------------------------------------- test_that("select_rate: method = highest - errors", { expect_error(select_rate(conv_rt_ar_obj, method = "highest", n = 7), regexp = "Object contains both negative and positive rates.") expect_error(select_rate(conv_rt_ar_obj_min, method = "highest", n = 7.1), regexp = "select_rate: For 'highest' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_obj_min, method = "highest", n = -1), regexp = "select_rate: For 'highest' method 'n' must contain only positive integers.") expect_message(select_rate(conv_rt_ar_obj_min, method = "highest", n = 1000), regexp = "select_rate: 'n' input is greater than number of rates in \\$summary. Nothing to remove.") }) test_that("select_rate: method = highest - check n rates extracted for positive rates", { conv_rt_ar_subset_high_pos <- select_rate(conv_rt_ar_subset_pos, method = "highest", n = 3) expect_equal(length(conv_rt_ar_subset_high_pos$rate.output), 3) }) test_that("select_rate: method = highest - check they are HIGHEST numerically for positive rates", { conv_rt_ar_subset_high_pos <- select_rate(conv_rt_ar_subset_pos, method = "highest", n = 3) expect_equal(tail(sort(conv_rt_ar_subset_pos$rate.output), 3), ## tail to get highest sort(conv_rt_ar_subset_high_pos$rate.output)) }) test_that("select_rate: method = highest - check n rates extracted for negative rates", { conv_rt_ar_subset_high_neg <- select_rate(conv_rt_ar_subset_neg, method = "highest", n = 3) expect_equal(length(conv_rt_ar_subset_high_neg$rate.output), 3) }) test_that("select_rate: method = highest - check they are LOWEST numerically for negative rates", { conv_rt_ar_subset_high_neg <- select_rate(conv_rt_ar_subset_neg, method = "highest", n = 3) expect_equal(head(sort(conv_rt_ar_subset_neg$rate.output), 3), ## head to get lowest sort(conv_rt_ar_subset_high_neg$rate.output)) }) test_that("select_rate: method = highest - check message", { expect_message(select_rate(conv_rt_ar_subset_pos, method = "highest", n = 3), "Selecting highest") }) # Check "lowest_percentile" method ---------------------------------------- test_that("select_rate: method = lowest_percentile - errors", { expect_error(select_rate(conv_rt_ar_obj, method = "lowest_percentile", n = 7), regexp = "Object contains both negative and positive rates.") expect_error(select_rate(conv_rt_ar_obj_min, method = "lowest_percentile", n = 7.1), regexp = "select_rate: For 'percentile' methods 'n' must be between 0 and 1.") expect_error(select_rate(conv_rt_ar_obj_min, method = "lowest_percentile", n = -1), regexp = "select_rate: For 'percentile' methods 'n' must be between 0 and 1.") }) test_that("select_rate: method = lowest_percentile - these should match", { conv_rt_ar_subset_pos_flip <- conv_rt_ar_subset_pos conv_rt_ar_subset_pos_flip$rate.output <- conv_rt_ar_subset_pos_flip$rate.output * -1 conv_rt_ar_subset_pos_flip$summary$rate.output <- conv_rt_ar_subset_pos_flip$summary$rate.output * -1 expect_equal(select_rate(conv_rt_ar_subset_pos, method = "lowest_percentile", n = 0.1)$rate.output, select_rate(conv_rt_ar_subset_pos_flip, method = "lowest_percentile", n = 0.1)$rate.output *-1) }) # Check "highest_percentile" method --------------------------------------- test_that("select_rate: method = highest_percentile - errors", { expect_error(select_rate(conv_rt_ar_obj, method = "highest_percentile", n = 7), regexp = "Object contains both negative and positive rates.") expect_error(select_rate(conv_rt_ar_obj_min, method = "highest_percentile", n = 7.1), regexp = "select_rate: For 'percentile' methods 'n' must be between 0 and 1.") expect_error(select_rate(conv_rt_ar_obj_min, method = "highest_percentile", n = -1), regexp = "select_rate: For 'percentile' methods 'n' must be between 0 and 1.") }) test_that("select_rate: method = highest_percentile - these should match", { conv_rt_ar_subset_pos_flip <- conv_rt_ar_subset_pos conv_rt_ar_subset_pos_flip$rate.output <- conv_rt_ar_subset_pos_flip$rate.output * -1 conv_rt_ar_subset_pos_flip$summary$rate.output <- conv_rt_ar_subset_pos_flip$summary$rate.output * -1 expect_equal(select_rate(conv_rt_ar_subset_pos, method = "highest_percentile", n = 0.1)$rate.output, select_rate(conv_rt_ar_subset_pos_flip, method = "highest_percentile", n = 0.1)$rate.output *-1) }) # Check "minimum" method -------------------------------------------------- conv_rt_ar_subset_min_n <- select_rate(conv_rt_ar_obj, method = "minimum", n = 4) test_that("select_rate: method = minimum - errors", { expect_error(select_rate(conv_rt_ar_subset_min_n, method = "minimum", n = 7.1), regexp = "select_rate: For 'minimum' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_subset_min_n, method = "minimum", n = -1), regexp = "select_rate: For 'minimum' method 'n' must contain only positive integers.") expect_message(select_rate(conv_rt_ar_subset_min_n, method = "minimum", n = 7000), regexp = "select_rate: 'n' input is greater than number of rates in \\$summary. Nothing to remove.") }) test_that("select_rate: method = minimum - check n rates extracted", { expect_length(conv_rt_ar_subset_min_n$rate.output, 4) }) test_that("select_rate: method = minimum - check they are LOWEST n rates", { expect_equal(head(sort(conv_rt_ar_obj$rate.output), 4), ## head to get lowest sort(conv_rt_ar_subset_min_n$rate.output)) }) test_that("select_rate: method = minimum - check some exact values", { expect_equal(conv_rt_ar_subset_min_n$rate.output[2], convert_rate(-0.0005968452, oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955)$rate.output) }) test_that("select_rate: method = minimum - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "minimum", n = 4), "Selecting minimum") }) # Check "maximim" method -------------------------------------------------- conv_rt_ar_subset_max_n <- select_rate(conv_rt_ar_obj, method = "maximum", n = 4) test_that("select_rate: method = maximum - errors", { expect_error(select_rate(conv_rt_ar_subset_max_n, method = "maximum", n = 7.1), regexp = "select_rate: For 'maximum' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_subset_max_n, method = "maximum", n = -1), regexp = "select_rate: For 'maximum' method 'n' must contain only positive integers.") expect_message(select_rate(conv_rt_ar_subset_max_n, method = "maximum", n = 7000), regexp = "select_rate: 'n' input is greater than number of rates in \\$summary. Nothing to remove.") }) test_that("select_rate: method = maximum - check n rates extracted", { expect_length(conv_rt_ar_subset_max_n$rate.output, 4) }) test_that("select_rate: method = maximum - check they are HIGHEST n rates", { expect_equal(tail(sort(conv_rt_ar_obj$rate.output), 4), sort(conv_rt_ar_subset_max_n$rate.output)) }) test_that("select_rate: method = maximum - check some exact values", { expect_equal(conv_rt_ar_subset_max_n$rate.output[2], convert_rate(0.001605693, oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955)$rate.output) }) test_that("select_rate: method = maximum - check message", { expect_message(select_rate(conv_rt_ar_obj, method = "maximum", n = 4), "Selecting maximum") }) # Check "minimum_percentile" method ------------------------------------------- conv_rt_ar_subset_min_perc <- select_rate(conv_rt_ar_obj, method = "minimum_percentile", n = 0.1) test_that("select_rate: method = minimum_percentile - these should match (in this case)", { expect_equal(conv_rt_ar_subset_min_perc$rate.output, select_rate(conv_rt_ar_obj, method = "minimum", n = 2)$rate.output) }) test_that("select_rate: method = minimum_percentile - check stops with n not between 0-1", { expect_error(select_rate(conv_rt_ar_obj, method = "minimum_percentile", n = 4), regexp = "For 'percentile' methods 'n' must be between 0 and 1.") }) # Check "maximum_percentile" method ------------------------------------------- conv_rt_ar_subset_max_perc <- select_rate(conv_rt_ar_obj, method = "maximum_percentile", n = 0.1) test_that("select_rate: method = maximum_percentile - these should match (in this case)", { expect_equal(conv_rt_ar_subset_max_perc$rate.output, select_rate(conv_rt_ar_obj, method = "maximum", n = 2)$rate.output) }) test_that("select_rate: method = maximum_percentile - check stops with n not between 0-1", { expect_error(select_rate(conv_rt_ar_obj, method = "maximum_percentile", n = 4), regexp = "For 'percentile' methods 'n' must be between 0 and 1.") }) # Check "rate" method ----------------------------------------------------- conv_rt_ar_select_rate <- select_rate(conv_rt_ar_obj, method = "rate", n = c(-0.012, 0.02)) test_that("select_rate: method = rate - check all within n rate values", { sapply(conv_rt_ar_select_rate$rate.output, function(x) expect_gte(x, -0.012)) sapply(conv_rt_ar_select_rate$rate.output, function(x) expect_lte(x, 0.02)) }) test_that("select_rate: method = rate - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "rate", n = 4), regexp = "For 'rate' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "rate", n = c(1,2,3)), regexp = "For 'rate' method 'n' must be a vector of two values.") }) test_that("select_rate: method = rate - works if n entered either way round", { expect_equal(select_rate(conv_rt_ar_obj, method = "rate", n = c(0.0010, 0.0015))$rate.output, select_rate(conv_rt_ar_obj, method = "rate", n = c(0.0015, 0.0010))$rate.output) }) # Check "slope" method ----------------------------------------------------- conv_rt_ar_select_slope <- select_rate(conv_rt_ar_obj, method = "slope", n = c(-0.0006, 0.001)) test_that("select_slope: method = slope - check all within n slope values", { sapply(conv_rt_ar_select_slope$summary$slope_b1, function(x) expect_gte(x, -0.0006)) sapply(conv_rt_ar_select_slope$summary$slope_b1, function(x) expect_lte(x, 0.001)) }) test_that("select_slope: method = slope - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "slope", n = 4), regexp = "For 'slope' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "slope", n = c(1,2,3)), regexp = "For 'slope' method 'n' must be a vector of two values.") }) test_that("select_slope: method = slope - works if n entered either way round", { expect_equal(select_rate(conv_rt_ar_obj, method = "slope", n = c(-0.0006, 0.001))$rate.output, select_rate(conv_rt_ar_obj, method = "slope", n = c(-0.0006, 0.001))$rate.output) }) # Check "intercept" method ----------------------------------------------------- conv_rt_ar_select_intercept <- select_rate(conv_rt_ar_obj, method = "intercept", n = c(3, 7.2)) test_that("select_intercept: method = intercept - check all within n intercept values", { sapply(conv_rt_ar_select_intercept$summary$intercept_b0, function(x) expect_gte(x, 3)) sapply(conv_rt_ar_select_intercept$summary$intercept_b0, function(x) expect_lte(x, 7.2)) }) test_that("select_intercept: method = intercept - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "intercept", n = 4), regexp = "For 'intercept' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "intercept", n = c(1,2,3)), regexp = "For 'intercept' method 'n' must be a vector of two values.") }) test_that("select_intercept: method = intercept - works if n entered either way round", { expect_equal(select_rate(conv_rt_ar_obj, method = "intercept", n = c(3, 7.2))$rate.output, select_rate(conv_rt_ar_obj, method = "intercept", n = c(3, 7.2))$rate.output) }) # Check "rsq" method ------------------------------------------------------ conv_rt_ar_subset_rsq <- select_rate(conv_rt_ar_obj, method = "rsq", n = c(0.7, 0.993)) test_that("select_rate: method = rsq - check all within rsq n range", { sapply(conv_rt_ar_subset_rsq$summary$rsq, function(x) expect_gte(x, 0.7)) sapply(conv_rt_ar_subset_rsq$summary$rsq, function(x) expect_lte(x, 0.993)) }) test_that("select_rate: method = rsq - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "rsq", n = 4), regexp = "For 'rsq' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "rsq", n = c(1,2,3)), regexp = "For 'rsq' method 'n' must be a vector of two values.") }) test_that("select_rate: method = rsq - works if n entered either way round", { expect_equal(select_rate(conv_rt_ar_obj, method = "rsq", n = c(0.6, 0.7))$rate.output, select_rate(conv_rt_ar_obj, method = "rsq", n = c(0.7, 0.6))$rate.output) }) # Check "row" method ------------------------------------------------------ conv_rt_ar_subset_row <- select_rate(conv_rt_ar_obj, method = "row", n = c(2000, 4100)) test_that("select_rate: method = row - check all within row n range", { sapply(conv_rt_ar_subset_row$summary$row, function(x) expect_gte(x, 2000)) sapply(conv_rt_ar_subset_row$summary$endrow, function(x) expect_lte(x, 4100)) }) test_that("select_rate: method = row - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "row", n = 4), regexp = "For 'row' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "row", n = c(1,2,3)), regexp = "For 'row' method 'n' must be a vector of two values.") }) test_that("select_rate: method = row - check stops with n out of range", { expect_error(select_rate(conv_rt_ar_obj, method = "row", n = c(1,5000)), regexp = "select_rate: Input for 'n': row inputs out of data frame range.") }) # Check "row_omit" method ------------------------------------------------- test_that("select_rate: works with method = row_omit and a single n input", { expect_error(conv_rt_ar_subset_row_omit <- select_rate(conv_rt_ar_obj, method = "row_omit", n = 2201), regexp = NA) expect_equal(nrow(select_rate(conv_rt_ar_obj, method = "row_omit", n = 2201)$summary), 9) }) test_that("select_rate: with method = row_omit correctly omits rates with single n input", { conv_rt_ar_subset_row_omit <- select_rate(conv_rt_ar_obj, method = "row_omit", n = 2201) ## check omitted row not within rows for each regression apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(2201 %in% x[6]:x[7])) }) test_that("select_rate: works with method = row_omit and n input of multiple values", { expect_error(conv_rt_ar_subset_row_omit <- select_rate(conv_rt_ar_obj, method = "row_omit", n = c(1000,2000,3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(1000 %in% x[6]:x[7])) apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(2000 %in% x[6]:x[7])) apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(3000 %in% x[6]:x[7])) }) test_that("select_rate: works with method = row_omit and n input of range of values", { skip_on_cran() expect_error(conv_rt_ar_subset_row_omit <- select_rate(conv_rt_ar_obj, method = "row_omit", n = c(1000:3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(1000 %in% x[6]:x[7])) apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(2000 %in% x[6]:x[7])) apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(3000 %in% x[6]:x[7])) }) test_that("select_rate: works with method = row_omit and n input of two values", { skip_on_cran() expect_error(conv_rt_ar_subset_row_omit <- select_rate(conv_rt_ar_obj, method = "row_omit", n = c(2000,3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(2000 %in% x[6]:x[7])) apply(conv_rt_ar_subset_row_omit$summary, 1, function(x) expect_false(3000 %in% x[6]:x[7])) }) test_that("select_rate: works with method = row_omit and n input not used - i.e. does not remove any results", { skip_on_cran() expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "row_omit", n = 100)$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "row_omit", n = 98:100)$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) }) test_that("select_rate: stops with method = row_omit and n input malformed", { ## check stops with n not numeric or integer expect_error(select_rate(conv_rt_ar_obj, method = "row_omit", n = "string"), regexp = "select_rate: For 'row_omit' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_obj, method = "row_omit", n = 1.2), regexp = "select_rate: For 'row_omit' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar_obj, method = "row_omit", n = c(1.2, 2.5)), regexp = "select_rate: For 'row_omit' method 'n' must contain only positive integers.") ## check stops when out of range expect_error(select_rate(conv_rt_ar_obj, method = "row_omit", n = 5000), regexp = "select_rate: Input for 'n': row inputs out of data frame range.") }) # Check "time" method ----------------------------------------------------- test_that("select_rate: method = time - check all rates are within time range", { conv_rt_ar_subset_time <- select_rate(conv_rt_ar_obj, method = "time", n = c(2000,3500)) sapply(conv_rt_ar_subset_time$summary$time, function(x) expect_gte(x, 2000)) sapply(conv_rt_ar_subset_time$summary$endtime, function(x) expect_lte(x, 3500)) }) test_that("select_rate: method = time - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "time", n = 4), regexp = "For 'time' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "time", n = c(1,2,3)), regexp = "For 'time' method 'n' must be a vector of two values.") }) test_that("select_rate: stops with method = time and n input malformed", { ## check stops when out of range expect_error(select_rate(conv_rt_ar_obj, method = "time", n = c(1,5000)), regexp = "select_rate: Input for 'n': time inputs out of time data range.") }) # Check "time_omit" method ------------------------------------------------- test_that("select_rate: works with method = time_omit and a single n input", { expect_error(conv_rt_ar_subset_time_omit <- select_rate(conv_rt_ar_obj, method = "time_omit", n = 2201), regexp = NA) expect_equal(nrow(select_rate(conv_rt_ar_obj, method = "time_omit", n = 2201)$summary), 9) }) test_that("select_rate: with method = time_omit correctly omits rates with single n input", { conv_rt_ar_subset_time_omit <- select_rate(conv_rt_ar_obj, method = "time_omit", n = 2201) ## check omitted row not within rows for each regression apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(2201 %in% x[8]:x[9])) }) test_that("select_rate: works with method = time_omit and n input of multiple values", { expect_error(conv_rt_ar_subset_time_omit <- select_rate(conv_rt_ar_obj, method = "time_omit", n = c(1000,2000,3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(1000 %in% x[8]:x[9])) apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(2000 %in% x[8]:x[9])) apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(3000 %in% x[8]:x[9])) }) test_that("select_rate: works with method = time_omit and n input of range of values", { skip_on_cran() expect_error(conv_rt_ar_subset_time_omit <- select_rate(conv_rt_ar_obj, method = "time_omit", n = c(1000:3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(1000 %in% x[8]:x[9])) apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(2000 %in% x[8]:x[9])) apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(3000 %in% x[8]:x[9])) }) test_that("select_rate: works with method = time_omit and n input of two values", { expect_error(conv_rt_ar_subset_time_omit <- select_rate(conv_rt_ar_obj, method = "time_omit", n = c(2000,3000)), regexp = NA) ## check omitted rows not within rows for each regression apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(2000 %in% x[8]:x[9])) apply(conv_rt_ar_subset_time_omit$summary, 1, function(x) expect_false(3000 %in% x[8]:x[9])) }) test_that("select_rate: works with method = time_omit and n input not used - i.e. does not remove any results", { skip_on_cran() expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "time_omit", n = 6000)$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "time_omit", n = 5998:6000)$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) }) test_that("select_rate: stops with method = time_omit and n input malformed", { ## check stops with n not numeric expect_error(select_rate(conv_rt_ar_obj, method = "time_omit", n = "string"), regexp = "select_rate: For 'time_omit' method 'n' must contain only numeric values of time.") ## check stops when out of range expect_error(select_rate(conv_rt_ar_obj, method = "time_omit", n = 5000), regexp = "select_rate: Input for 'n': time inputs out of time data range.") }) # Check "rank" method ------------------------------------------------------ conv_rt_ar_subset_rank <- select_rate(conv_rt_ar_obj, method = "rank", n = c(4, 10)) test_that("select_rate: method = rank - messages", { expect_message(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank", n = 4), "select_rate: Note there are multiple replicates present in these results, which may have multiple ranks \\*within\\* them.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank", n = 7.1), regexp = "select_rate: For 'rank' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank", n = 1000), regexp = "select_rate: Input for 'n': One or more 'rank' inputs out of range of 'summary\\$rank' values.") }) test_that("select_rate: method = rank - check all within rank n range", { expect_equal(unique(conv_rt_ar_subset_rank$summary$rank), c(4,10)) }) test_that("select_rate: method = rank - correctly selects from intermittent-flow multiple ranks per rep ", { #conv_rt_ar.int_obj #conv_rt_ar.int_obj_mult_ranks # should not remove any rates expect_equal(nrow(select_rate(conv_rt_ar.int_obj, method = "rank", n = 1)$summary), 10) # should remove all ranks except 1 expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank", n = 1)$summary), 10) # another check expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank", n = 1:2)$summary), 20) }) test_that("select_rate: method = rank - accepts multiple length vectors", { expect_error(select_rate(conv_rt_ar_obj, method = "rank", n = 4), NA) expect_error(select_rate(conv_rt_ar_obj, method = "rank", n = c(1,2)), NA) expect_error(select_rate(conv_rt_ar_obj, method = "rank", n = c(1,2,3)), NA) }) # Check "rank_omit" method ------------------------------------------------------ conv_rt_ar_subset_rank <- select_rate(conv_rt_ar_obj, method = "rank_omit", n = c(4, 10)) test_that("select_rate: method = rank - messages", { expect_message(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 4), "select_rate: Note there are multiple replicates present in these results, which may have multiple ranks \\*within\\* them.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 7.1), regexp = "select_rate: For 'rank_omit' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 1000), regexp = "select_rate: Input for 'n': One or more 'rank_omit' inputs out of range of 'summary\\$rank' values.") }) test_that("select_rate: method = rank_omit - check all within rank n range", { expect_equal(unique(conv_rt_ar_subset_rank$summary$rank), c(1:3,5:9,11:16)) }) test_that("select_rate: method = rank_omit - correctly selects from intermittent-flow multiple ranks per rep ", { #conv_rt_ar.int_obj #conv_rt_ar.int_obj_mult_ranks # should remove all rates expect_equal(nrow(select_rate(conv_rt_ar.int_obj, method = "rank_omit", n = 1)$summary), 0) # expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 1)$summary), 31) expect_equal(unique(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 1)$summary$rank), 2:5) expect_equal(unique(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rank_omit", n = 1:3)$summary$rank), 4:5) }) test_that("select_rate: method = rank - accepts multiple length vectors", { expect_error(select_rate(conv_rt_ar_obj, method = "rank_omit", n = 4), NA) expect_error(select_rate(conv_rt_ar_obj, method = "rank_omit", n = c(1,2)), NA) expect_error(select_rate(conv_rt_ar_obj, method = "rank_omit", n = c(1,2,3)), NA) }) # Check "rep" method ------------------------------------------------------ #conv_rt_ar.int_obj #conv_rt_ar.int_obj_mult_ranks # conv_rt_ar_subset_rep <- select_rate(conv_rt_ar.int_obj, method = "rep", n = c(4, 10)) test_that("select_rate: method = rep - messages", { expect_error(select_rate(conv_rt_ar_obj, method = "rep", n = 1), regexp = "select_rate: All 'rep' are NA so nothing to select!") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = 7.1), regexp = "select_rate: For 'rep' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = 1000), regexp = "select_rate: Input for 'n': One or more 'rep' inputs out of range of 'summary\\$rep' values.") }) test_that("select_rate: method = rep - check all within rep n range", { expect_equal(unique(conv_rt_ar_subset_rep$summary$rep), c(4,10)) }) test_that("select_rate: method = rep - correctly selects from intermittent-flow multiple reps per rep ", { # expect_equal(nrow(select_rate(conv_rt_ar.int_obj, method = "rep", n = 1)$summary), 1) # expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = 1)$summary), 4) # another check expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = 1:2)$summary), 9) }) test_that("select_rate: method = rep - accepts multiple length vectors", { expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = 1), NA) expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = c(1,2)), NA) expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep", n = c(1,2,3)), NA) }) # Check "rep_omit" method ------------------------------------------------------ #conv_rt_ar.int_obj #conv_rt_ar.int_obj_mult_ranks conv_rt_ar_subset_rep <- select_rate(conv_rt_ar.int_obj, method = "rep_omit", n = c(4, 10)) test_that("select_rate: method = rep - messages", { expect_error(select_rate(conv_rt_ar_obj, method = "rep_omit", n = 1), regexp = "select_rate: All 'rep' are NA so nothing to select!") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 7.1), regexp = "select_rate: For 'rep_omit' method 'n' must contain only positive integers.") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 1000), regexp = "select_rate: Input for 'n': One or more 'rep_omit' inputs out of range of 'summary\\$rep' values.") }) test_that("select_rate: method = rep_omit - check all within rep n range", { expect_equal(unique(conv_rt_ar_subset_rep$summary$rep), c(1:3,5:9)) }) test_that("select_rate: method = rep_omit - correctly selects from intermittent-flow multiple reps per rep ", { #conv_rt_ar.int_obj #conv_rt_ar.int_obj_mult_ranks # should remove all rates expect_equal(nrow(select_rate(conv_rt_ar.int_obj, method = "rep_omit", n = 1)$summary), 9) # expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 1)$summary), 37) expect_equal(unique(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 1)$summary$rep), 2:10) expect_equal(unique(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 1:3)$summary$rep), 4:10) }) test_that("select_rate: method = rep - accepts multiple length vectors", { expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = 4), NA) expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = c(1,2)), NA) expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "rep_omit", n = c(1,2,3)), NA) }) # Check "oxygen" method ---------------------------------------------------- conv_rt_ar_subset_oxy <- select_rate(conv_rt_ar_obj_high, method = "oxygen", c(7.35, 7)) # this doesn't strictly check proper functonality, in that the method checks # *ALL* oxygen values in the original regression test_that("select_rate: method = oxygen - check all within oxygen n range", { sapply(conv_rt_ar_subset_oxy$summary$endoxy, function(x) expect_gte(x, 7)) sapply(conv_rt_ar_subset_oxy$summary$oxy, function(x) expect_lte(x, 7.35)) }) test_that("select_rate: method = oxygen - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "oxygen", n = 4), regexp = "For 'oxygen' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "oxygen", n = c(1,2,3)), regexp = "For 'oxygen' method 'n' must be a vector of two values.") }) test_that("select_rate: works with method = oxygen_omit and n input not used - i.e. does not remove any results", { skip_on_cran() expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "oxygen", n = c(3.5, 7.7))$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) }) # Check "oxygen_omit" method ---------------------------------------------------- conv_rt_ar_subset_oxy_om <- select_rate(conv_rt_ar_obj, method = "oxygen_omit", c(7.00)) # this doesn't strictly check proper functonality, in that the method checks # *ALL* oxygen_omit values in the original regression test_that("select_rate: method = oxygen_omit - no remaining results have ommitted value", { for(z in 1:nrow(conv_rt_ar_subset_oxy_om$summary)) { mapply(function(p,q) expect_false(any((conv_rt_ar_subset_oxy_om$dataframe$y[p:q] == 7.35))), p = conv_rt_ar_subset_oxy_om$summary$row, q = conv_rt_ar_subset_oxy_om$summary$endrow) } }) test_that("select_rate: works with method = oxygen_omit and n input of multiple values", { expect_error(conv_rt_ar_subset_oxygen_omit <- select_rate(conv_rt_ar_obj, method = "oxygen_omit", n = c(7, 6.9, 6.8)), regexp = NA) }) test_that("select_rate: works with method = oxygen_omit and n input of range of values", { expect_error(conv_rt_ar_subset_oxygen_omit <- select_rate(conv_rt_ar_obj, method = "oxygen_omit", n = c(7:5)), regexp = NA) }) test_that("select_rate: works with method = oxygen_omit and n input of two values", { expect_error(conv_rt_ar_subset_oxygen_omit <- select_rate(conv_rt_ar_obj, method = "oxygen_omit", n = c(7,6)), regexp = NA) }) test_that("select_rate: works with method = oxygen_omit and n input not used - i.e. does not remove any results", { skip_on_cran() expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "oxygen_omit", n = 3.5)$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) expect_equal(nrow(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "oxygen_omit", n = c(3.2, 3.3, 3.5))$summary), nrow(conv_rt_ar.int_obj_mult_ranks$summary)) }) test_that("select_rate: stops with method = oxygen_omit and n input malformed", { ## check stops with n not numeric expect_error(select_rate(conv_rt_ar_obj, method = "oxygen_omit", n = "string"), regexp = "select_rate: For 'oxygen_omit' method 'n' must contain only numeric values of oxygen.") }) # Check "manual" method ----------------------------------------------------- test_that("select_rate: method = manual - subsets a single rate", { conv_rt_ar_subset_man <- select_rate(conv_rt_ar_obj, method = "manual", n = 1) expect_equal(length(conv_rt_ar_subset_man$rate.output), 1) expect_equal(conv_rt_ar_obj$rate.output[1], conv_rt_ar_subset_man$rate.output[1]) }) test_that("select_rate: method = manual - subsets multiple consecutive rates", { conv_rt_ar_subset_man <- select_rate(conv_rt_ar_obj, method = "manual", n = c(3,2)) expect_equal(length(conv_rt_ar_subset_man$rate.output), 2) expect_equal(conv_rt_ar_obj$rate.output[2:3], conv_rt_ar_subset_man$rate.output) }) test_that("select_rate: method = manual - subsets multiple non-consecutive rates", { conv_rt_ar_subset_man <- select_rate(conv_rt_ar_obj, method = "manual", n = c(1,5,9)) expect_equal(length(conv_rt_ar_subset_man$rate.output), 3) expect_equal(conv_rt_ar_obj$rate.output[c(1,5,9)], conv_rt_ar_subset_man$rate.output) }) test_that("select_rate: method = manual - check stops with n out of range", { expect_error(select_rate(conv_rt_ar_obj, method = "manual", n = 17), regexp = "For 'manual' method: 'n' values are out of range of ") }) # Check "manual_omit" method ------------------------------------------------------ conv_rt_ar_subset_rank <- select_rate(conv_rt_ar_obj, method = "manual_omit", n = c(4, 10)) test_that("select_rate: method = rank - messages", { expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "manual_omit", n = 7.1), regexp = "select_rate: For 'manual' method: 'n' values are out of range of \\$summary data.frame rows...") expect_error(select_rate(conv_rt_ar.int_obj_mult_ranks, method = "manual_omit", n = 1000), regexp = "select_rate: For 'manual' method: 'n' values are out of range of \\$summary data.frame rows...") }) test_that("select_rate: method = manual_omit - check all within rank n range", { expect_equal(unique(conv_rt_ar_subset_rank$summary$rank), c(1:3,5:9,11:16)) }) test_that("select_rate: method = rank - accepts multiple length vectors", { expect_error(select_rate(conv_rt_ar_obj, method = "manual_omit", n = 4), NA) expect_error(select_rate(conv_rt_ar_obj, method = "manual_omit", n = c(1,2)), NA) expect_error(select_rate(conv_rt_ar_obj, method = "manual_omit", n = c(1,2,3)), NA) }) # Check "density" method -------------------------------------------------- conv_rt_ar_subset_density <- select_rate(conv_rt_ar_obj, method = "density", n = c(300, 7500)) test_that("select_rate: method = density - check all within density n range", { sapply(conv_rt_ar_subset_density$summary$density, function(x) expect_gte(x, 300)) sapply(conv_rt_ar_subset_density$summary$density, function(x) expect_lte(x, 7500)) }) test_that("select_rate: method = density - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "density", n = 4), regexp = "For 'density' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "density", n = c(1,2,3)), regexp = "For 'density' method 'n' must be a vector of two values.") }) test_that("select_rate: method = density - check stops with auto_rate objects not of 'linear' KDE method", { skip_on_cran() obj <- inspect(intermittent.rd) %>% auto_rate(method = "maximum") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) expect_error(select_rate(obj, method = "density", n = c(300,7500)), regexp = "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") obj <- inspect(intermittent.rd) %>% auto_rate(method = "interval") %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 2.379, mass = 0.006955) expect_error(select_rate(obj, method = "density", n = c(300,7500)), regexp = "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") }) # Check "duration" method ------------------------------------------------- test_that("select_rate: method = duration - check stops with n not length 2 vector", { expect_error(select_rate(conv_rt_ar_obj, method = "duration", n = 4), regexp = "For 'duration' method 'n' must be a vector of two values.") expect_error(select_rate(conv_rt_ar_obj, method = "duration", n = c(1,2,3)), regexp = "For 'duration' method 'n' must be a vector of two values.") }) test_that("select_rate: method = duration - subsets max duration (zero to something) correctly", { conv_rt_ar_subset_dur1 <- select_rate(conv_rt_ar_obj, method = "duration", n = c(0,1000)) ## should be 11 matches expect_equal(length(conv_rt_ar_subset_dur1$rate.output), 11) }) test_that("select_rate: method = duration - min duration (something to something large) correctly", { conv_rt_ar_subset_dur2 <- select_rate(conv_rt_ar_obj, method = "duration", n = c(1000, 5000)) ## should be 5 matches expect_equal(length(conv_rt_ar_subset_dur2$rate.output), 5) }) test_that("select_rate: method = duration - Test all possible durations match to original", { conv_rt_ar_subset_dur1 <- select_rate(conv_rt_ar_obj, method = "duration", n = c(0,999)) conv_rt_ar_subset_dur2 <- select_rate(conv_rt_ar_obj, method = "duration", n = c(1000, Inf)) expect_equal(length(conv_rt_ar_subset_dur1$rate.output) + length(conv_rt_ar_subset_dur2$rate.output), length(conv_rt_ar_obj$rate.output)) }) # Check "overlap" method -------------------------------------------------- test_that("select_rate: method = overlap - applies n = NULL default of 0", { expect_message(select_rate(conv_rt_ar_obj, method = "overlap", n = NULL), "select_rate: 'overlap' method - applying default 'n = 0', no overlapping permitted.") }) test_that("select_rate: method = overlap - stops when n is outside 0 to 1", { expect_error(select_rate(conv_rt_ar_obj, method = "overlap", n = 2), "For 'overlap' method 'n' must be between 0 and 1 inclusive.") }) test_that("select_rate: method = overlap - outputs 4 rates with these inputs", { expect_equal(length(select_rate(conv_rt_ar_obj, method = "overlap", n = 0.5)$rate.output), 4) }) test_that("select_rate: method = overlap - outputs 4 rates with these inputs", { expect_equal(length(select_rate(conv_rt_ar_obj, method = "overlap", n = 0.5)$rate.output), 4) }) # Reordering checks ------------------------------------------------------- ## put conv_rt_ar_obj results in a random order conv_rt_ar_obj_mixed_lin <- conv_rt_ar_obj new_order_lin <- c(10, 9, 14, 13, 5, 2, 1 , 3, 8, 16, 6, 15, 7, 4, 12, 11) conv_rt_ar_obj_mixed_lin$summary <- conv_rt_ar_obj_mixed_lin$summary[new_order_lin,] conv_rt_ar_obj_mixed_lin$rate.output <- conv_rt_ar_obj_mixed_lin$summary$rate.output # same with other auto_rate method that's not linear conv_rt_ar_obj_mixed_high <- conv_rt_ar_obj_high new_order_high <- sample(1:nrow(conv_rt_ar_obj_mixed_high$summary)) conv_rt_ar_obj_mixed_high$summary <- conv_rt_ar_obj_mixed_high$summary[new_order_high,] conv_rt_ar_obj_mixed_high$rate.output <- conv_rt_ar_obj_mixed_high$summary$rate.output # empty object empty_obj <- select_rate(conv_rt_ar_obj, method = "rate", n = c(0.1, 1)) # method = "rolling" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = rolling - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = 1), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = 1:10), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = 1), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = 1:10), regexp = "select_rate: Reordering results by 'rolling' method. 'n' input ignored...") }) test_that("select_rate: method = rolling - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "rolling", n = NULL), NA) expect_message(select_rate(empty_obj, method = "rolling", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'rolling' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL)$summary$row, sort(conv_rt_ar_obj$summary$row)) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL)$summary$row, sort(conv_rt_ar_obj_high$summary$row)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, row)$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, row)$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "rolling", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "rolling", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "row" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = row - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL), regexp = "select_rate: Reordering results by 'row' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL), regexp = "select_rate: Reordering results by 'row' method.") }) test_that("select_rate: method = row - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "row", n = NULL), NA) expect_message(select_rate(empty_obj, method = "row", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'row' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL)$summary$row, sort(conv_rt_ar_obj$summary$row)) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL)$summary$row, sort(conv_rt_ar_obj_high$summary$row)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, row)$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, row)$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "row", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "row", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "time" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = time - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL), regexp = "select_rate: Reordering results by 'time' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL), regexp = "select_rate: Reordering results by 'time' method.") }) test_that("select_rate: method = time - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "time", n = NULL), NA) expect_message(select_rate(empty_obj, method = "time", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'time' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL)$summary$time, sort(conv_rt_ar_obj$summary$time)) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL)$summary$time, sort(conv_rt_ar_obj_high$summary$time)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, time)$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, time)$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "time", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "time", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "linear" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = linear - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL), regexp = "select_rate: Reordering results by 'linear' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = 1), regexp = "select_rate: Reordering results by 'linear' method. 'n' input ignored...") expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = 1:10), regexp = "select_rate: Reordering results by 'linear' method. 'n' input ignored...") # highest object expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "linear", n = NULL), regexp = "select_rate: The 'linear' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") }) test_that("select_rate: method = linear - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "linear", n = NULL), NA) expect_message(select_rate(empty_obj, method = "linear", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'linear' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL)$summary$density, (conv_rt_ar_obj$summary$density)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(density))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "linear", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) }) # method = "density" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = density - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL), regexp = "select_rate: Reordering results by 'density' method.") }) test_that("select_rate: method = density - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "density", n = NULL), NA) expect_message(select_rate(empty_obj, method = "density", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'density' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL)$summary$density, (conv_rt_ar_obj$summary$density)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(density))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "density", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) }) # method = "rank" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = rank - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL), regexp = "select_rate: Reordering results by 'rank' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL), regexp = "select_rate: Reordering results by 'rank' method.") }) test_that("select_rate: method = rank - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "rank", n = NULL), NA) expect_message(select_rate(empty_obj, method = "rank", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'rank' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL)$summary$rank, (conv_rt_ar_obj$summary$rank)) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL)$summary$rank, (conv_rt_ar_obj_high$summary$rank)) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, rank)$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, rank)$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "rank", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "rank", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "rsq" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = rsq - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL), regexp = "select_rate: Reordering results by 'rsq' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL), regexp = "select_rate: Reordering results by 'rsq' method.") }) test_that("select_rate: method = rsq - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "rsq", n = NULL), NA) expect_message(select_rate(empty_obj, method = "rsq", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'rsq' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL)$summary$rsq, rev(sort(conv_rt_ar_obj$summary$rsq))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL)$summary$rsq, rev(sort(conv_rt_ar_obj_high$summary$rsq))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL)$summary$rate.output) # expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL)$rate.output, # conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(rsq))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, desc(rsq))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "rsq", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "rsq", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "slope" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = slope - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL), regexp = "select_rate: Reordering results by 'slope' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL), regexp = "select_rate: Reordering results by 'slope' method.") }) test_that("select_rate: method = slope - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "slope", n = NULL), NA) expect_message(select_rate(empty_obj, method = "slope", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'slope' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL)$summary$slope, (sort(conv_rt_ar_obj$summary$slope))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL)$summary$slope, (sort(conv_rt_ar_obj_high$summary$slope))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL)$summary$rate.output) # expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL)$rate.output, # conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(slope))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, (slope_b1))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "slope", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "slope", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "intercept" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = intercept - correct message", { # linear object expect_message(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL), regexp = "select_rate: Reordering results by 'intercept' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL), regexp = "select_rate: Reordering results by 'intercept' method.") }) test_that("select_rate: method = intercept - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "intercept", n = NULL), NA) expect_message(select_rate(empty_obj, method = "intercept", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'intercept' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL)$summary$intercept, (sort(conv_rt_ar_obj$summary$intercept))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL)$summary$intercept, (sort(conv_rt_ar_obj_high$summary$intercept))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL)$summary$rate.output) # expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL)$rate.output, # conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(intercept))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, (intercept_b0))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "intercept", n = NULL)$rate.output), length(conv_rt_ar_obj$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "intercept", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "lowest" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = lowest - correct message", { # linear object expect_message(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL), regexp = "select_rate: Reordering results by 'lowest' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL), regexp = "select_rate: Reordering results by 'lowest' method.") # mixed sign object expect_error(select_rate(conv_rt_ar_obj, method = "lowest", n = NULL), regexp = "select_rate: Object contains both negative and positive rates.") }) test_that("select_rate: method = lowest - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "lowest", n = NULL), NA) expect_message(select_rate(empty_obj, method = "lowest", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'lowest' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL)$summary$lowest, rev(sort(conv_rt_ar_obj$summary$lowest))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL)$summary$lowest, rev(sort(conv_rt_ar_obj_high$summary$lowest))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL)$rate.output, select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL)$summary$rate.output) # expect_identical(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL)$rate.output, # conv_rt_ar_subset_pos$rate.output[dplyr::arrange(conv_rt_ar_subset_pos$summary, desc(rate))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, desc(rate))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_subset_pos, method = "lowest", n = NULL)$rate.output), length(conv_rt_ar_subset_pos$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "lowest", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "highest" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = highest - correct message", { # linear object expect_message(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL), regexp = "select_rate: Reordering results by 'highest' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL), regexp = "select_rate: Reordering results by 'highest' method.") # mixed sign object expect_error(select_rate(conv_rt_ar_obj, method = "highest", n = NULL), regexp = "select_rate: Object contains both negative and positive rates.") }) test_that("select_rate: method = highest - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "highest", n = NULL), NA) expect_message(select_rate(empty_obj, method = "highest", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'highest' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL)$summary$highest, rev(sort(conv_rt_ar_obj$summary$highest))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL)$summary$highest, rev(sort(conv_rt_ar_obj_high$summary$highest))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL)$rate.output, select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL)$summary$rate.output) # expect_identical(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL)$rate.output, # conv_rt_ar_subset_pos$rate.output[dplyr::arrange(conv_rt_ar_subset_pos$summary, desc(rate))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, (rate))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_subset_pos, method = "highest", n = NULL)$rate.output), length(conv_rt_ar_subset_pos$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "highest", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "minimum" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = minimum - correct message", { # linear object expect_message(select_rate(conv_rt_ar_subset_pos, method = "minimum", n = NULL), regexp = "select_rate: Reordering results by 'minimum' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL), regexp = "select_rate: Reordering results by 'minimum' method.") }) test_that("select_rate: method = minimum - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "minimum", n = NULL), NA) expect_message(select_rate(empty_obj, method = "minimum", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'minimum' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL)$summary$minimum, rev(sort(conv_rt_ar_obj$summary$minimum))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL)$summary$minimum, rev(sort(conv_rt_ar_obj_high$summary$minimum))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, (rate))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, (rate))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "minimum", n = NULL)$rate.output), length(conv_rt_ar_obj_mixed_lin$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "minimum", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # method = "maximum" ----------------------------------------------------- # "rolling" and "linear" methods ignore 'n', all others it must be NULL to reorder # So for others only need top test here test_that("select_rate: method = maximum - correct message", { # linear object expect_message(select_rate(conv_rt_ar_subset_pos, method = "maximum", n = NULL), regexp = "select_rate: Reordering results by 'maximum' method.") # highest object expect_message(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL), regexp = "select_rate: Reordering results by 'maximum' method.") }) test_that("select_rate: method = maximum - works and correctly reorders results", { skip_on_cran() # works expect_error(select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL), NA) expect_error(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL), NA) # can be plotted reorder_obj_lin <- select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL) expect_error(plot(reorder_obj_lin), regex = NA) reorder_obj_high <- select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL) expect_error(plot(reorder_obj_high), regex = NA) # no error with empty object expect_error(select_rate(empty_obj, method = "maximum", n = NULL), NA) expect_message(select_rate(empty_obj, method = "maximum", n = NULL), "----- Reordering complete. 0 rate\\(s) reordered by 'maximum' method -----") # works with S3 expect_output(print(reorder_obj_lin)) expect_output(summary(reorder_obj_lin)) expect_output(mean(reorder_obj_lin)) expect_output(print(reorder_obj_high)) expect_output(summary(reorder_obj_high)) expect_output(mean(reorder_obj_high)) # summary table correctly ordered for this method expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL)$summary$maximum, rev(sort(conv_rt_ar_obj$summary$maximum))) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL)$summary$maximum, rev(sort(conv_rt_ar_obj_high$summary$maximum))) # $rate.output element correctly ordered expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL)$rate.output, conv_rt_ar_obj$rate.output[dplyr::arrange(conv_rt_ar_obj$summary, desc(rate))$rank]) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL)$rate.output, select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL)$summary$rate.output) expect_identical(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL)$rate.output, conv_rt_ar_obj_high$rate.output[dplyr::arrange(conv_rt_ar_obj_high$summary, desc(rate))$rank]) # $subset_regs element correct length expect_identical(length(select_rate(conv_rt_ar_obj_mixed_lin, method = "maximum", n = NULL)$rate.output), length(conv_rt_ar_obj_mixed_lin$rate.output)) expect_identical(length(select_rate(conv_rt_ar_obj_mixed_high, method = "maximum", n = NULL)$rate.output), length(conv_rt_ar_obj_high$rate.output)) }) # Numerics checks --------------------------------------------------------- # Single numeric test_that("select_rate: single numerics work", { num_sing <- -0.03 %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should NOT remove the only rate expect_error(select_rate(num_sing, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(num_sing, method = "rate", n = c(-0.4, -0.3))$rate.output, 1) # should remove the only rate expect_error(select_rate(num_sing, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(num_sing, method = "rate", n = c(-0.3, -0.2))$rate.output, 0) # Works piped expect_error( num_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (num_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # should stop expect_error( num_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rsq", n = NULL), "select_rate: The 'rsq' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "density", n = NULL), "select_rate: The 'density' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "plot.convert_rate: Plot is not available for 'convert_rate' objects containing rates converted from numeric values.") }) # Multiple numerics test_that("select_rate: multiple numerics work", { num_mult <- c(-0.03, -0.025, -0.021,- 0.051, -0.04) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should remove 3 of 5 rates expect_error(select_rate(num_mult, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(num_mult, method = "rate", n = c(-0.4, -0.3))$rate.output, 2) # should remove 4 of 5 rates expect_error(select_rate(num_mult, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(num_mult, method = "rate", n = c(-0.3, -0.2))$rate.output, 1) # Works piped expect_error( num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # should stop expect_error( num_mult %>% select_rate(method = "rsq", n = NULL), "select_rate: The 'rsq' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "oxygen", n = c(8,7)), "select_rate: The 'oxygen' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "plot.convert_rate: Plot is not available for 'convert_rate' objects containing rates converted from numeric values.") }) # Single numeric that has been adjusted test_that("select_rate: Single numeric that has been adjusted work", { num_sing_adj <- -0.03 %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove single rate expect_error(select_rate(num_sing_adj, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(num_sing_adj, method = "rate", n = c(-0.4, -0.3))$rate.output, 1) # should remove single rates expect_error(select_rate(num_sing_adj, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(num_sing_adj, method = "rate", n = c(-0.3, -0.2))$rate.output, 0) # Works piped expect_error( num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # should stop expect_error( num_sing_adj %>% select_rate(method = "rsq", n = NULL), "select_rate: The 'rsq' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "oxygen", n = c(8,7)), "select_rate: The 'oxygen' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "plot.convert_rate: Plot is not available for 'convert_rate' objects containing rates converted from numeric values.") }) # Multiple numeric that has been adjusted test_that("select_rate: Multiple numeric that has been adjusted work", { num_mult_adj <- c(-0.03, -0.025, -0.021,- 0.051, -0.04) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should remove 2 of 5 rates expect_error(select_rate(num_mult_adj, method = "rate", n = c(-0.4, -0.2)), NA) expect_length(select_rate(num_mult_adj, method = "rate", n = c(-0.4, -0.2))$rate.output, 3) # Works piped expect_error( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.2)) %>% select_rate(method = "rank", n = c(1,2)), NA) expect_length( (num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.2)) %>% select_rate(method = "rank", n = c(1,2)))$rate.output, 2) # Works with reordering expect_error( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # should stop expect_error( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "linear", n = c(8,7)), "select_rate: The 'linear' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "oxygen", n = c(8,7)), "select_rate: The 'oxygen' method is not accepted for 'convert_rate' objects which have been created using numeric inputs.") # should stop expect_error( num_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "plot.convert_rate: Plot is not available for 'convert_rate' objects containing rates converted from numeric values.") }) # calc_rate-to-convert_rate object checks --------------------------------- # Single rate test_that("select_rate: calc_rate-to-convert_rate object with single rate works", { cr_sing <- urchins.rd[,1:2] %>% calc_rate(50, 150, "row", plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove single rate expect_error(select_rate(cr_sing, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(cr_sing, method = "rate", n = c(-0.4, -0.3))$rate.output, 1) # should remove single rates expect_error(select_rate(cr_sing, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(cr_sing, method = "rate", n = c(-0.3, -0.2))$rate.output, 0) # Works piped expect_error( cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr_sing %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr_sing %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), NA) expect_output( cr_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot()) }) # Multiple rates test_that("select_rate: calc_rate-to-convert_rate object with multiple rates works", { cr_mult <- urchins.rd[,1:2] %>% calc_rate(seq(10, 100, 10), seq(110, 200, 10), "row", plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(cr_mult, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(cr_mult, method = "rate", n = c(-0.4, -0.3))$rate.output, 10) # should remove all rates expect_error(select_rate(cr_mult, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(cr_mult, method = "rate", n = c(-0.3, -0.2))$rate.output, 0) # should remove some rates expect_error(select_rate(cr_mult, method = "rate", n = c(-0.35, -0.381)), NA) expect_length(select_rate(cr_mult, method = "rate", n = c(-0.35, -0.381))$rate.output, 4) # Works piped expect_error( cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr_mult %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr_mult %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), NA) expect_output( cr_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot()) }) # Single adjusted rate test_that("select_rate: calc_rate-to-adjust_rate-to-convert_rate object with single rate works", { cr_sing_adj <- urchins.rd[,1:2] %>% calc_rate(50, 150, "row", plot = FALSE) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove single rate expect_error(select_rate(cr_sing_adj, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(cr_sing_adj, method = "rate", n = c(-0.4, -0.3))$rate.output, 1) # should remove single rates expect_error(select_rate(cr_sing_adj, method = "rate", n = c(-0.3, -0.2)), NA) expect_length(select_rate(cr_sing_adj, method = "rate", n = c(-0.3, -0.2))$rate.output, 0) # Works piped expect_error( cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr_sing_adj %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr_sing_adj %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), NA) expect_output( cr_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot()) }) # Multiple adjusted rates test_that("select_rate: calc_rate-to-adjust_rate-to-convert_rate object with multiple rates works", { cr_mult_adj <- urchins.rd[,1:2] %>% calc_rate(seq(10, 100, 10), seq(110, 200, 10), "row", plot = FALSE) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(cr_mult_adj, method = "rate", n = c(-0.4, -0.25)), NA) expect_length(select_rate(cr_mult_adj, method = "rate", n = c(-0.4, -0.25))$rate.output, 10) # should remove all rates expect_error(select_rate(cr_mult_adj, method = "rate", n = c(-0.4, -0.5)), NA) expect_length(select_rate(cr_mult_adj, method = "rate", n = c(-0.4, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(cr_mult_adj, method = "rate", n = c(-0.28, -0.316)), NA) expect_length(select_rate(cr_mult_adj, method = "rate", n = c(-0.28, -0.316))$rate.output, 4) # Works piped expect_error( cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr_mult_adj %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr_mult_adj %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), NA) expect_output( cr_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot()) }) # calc_rate.int checks ---------------------------------------------------- # Multiple adjusted rates test_that("select_rate: calc_rate.int-to-adjust_rate-to-convert_rate object with multiple rates works", { cr.int_mult_adj <- intermittent.rd %>% inspect(plot = FALSE)%>% calc_rate.int(starts = c(1, 2101, 3901), wait = 500, measure = 500, by = "row", plot = FALSE) %>% adjust_rate(by = -0.00005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "s", output.unit = "mg/h/g", mass = 0.006955, volume = 2.379) # should not remove any rates expect_error(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.6, -0.8)), NA) expect_length(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.6, -0.8))$rate.output, 3) # should remove all rates expect_error(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.4, -0.5)), NA) expect_length(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.4, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.7, -0.8)), NA) expect_length(select_rate(cr.int_mult_adj, method = "rate", n = c(-0.7, -0.8))$rate.output, 1) # Works piped expect_error( cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr.int_mult_adj %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr.int_mult_adj %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( cr.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( cr.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate.int checks ---------------------------------------------------- # Multiple adjusted rates test_that("select_rate: auto_rate.int-to-adjust_rate-to-convert_rate object with multiple rates works", { ar.int_mult_adj <- intermittent.rd %>% inspect(plot = FALSE)%>% auto_rate.int(starts = c(1, 2101, 3901), measure = c(1900, 3550, 4831) - c(1, 2101, 3901), width = 500, plot = FALSE) %>% adjust_rate(by = -0.00005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "s", output.unit = "mg/h/g", mass = 0.006955, volume = 2.379) #summary(ar.int_mult_adj) # should not remove any rates expect_error(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.6, -0.8)), NA) expect_length(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.6, -0.8))$rate.output, 3) # should remove all rates expect_error(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.4, -0.5)), NA) expect_length(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.4, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.7, -0.8)), NA) expect_length(select_rate(ar.int_mult_adj, method = "rate", n = c(-0.7, -0.8))$rate.output, 1) # Works piped expect_error( ar.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar.int_mult_adj %>% select_rate(method = "rsq", n = NULL), NA) ar.int_low_mult_adj <- intermittent.rd %>% inspect(plot = FALSE)%>% auto_rate.int(starts = c(1, 2101, 3901), measure = c(1900, 3550, 4831) - c(1, 2101, 3901), width = 500, method = "lowest", plot = FALSE) %>% adjust_rate(by = -0.00005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "s", output.unit = "mg/h/g", mass = 0.006955, volume = 2.379) # should stop expect_error( ar.int_low_mult_adj %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( ar.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar.int_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate checks -------------------------------------------------------- # auto_rate-to-convert_rate object with single rate test_that("select_rate: auto_rate-to-convert_rate object with single rates works", { ar_sing <- urchins.rd[,1:2] %>% auto_rate(width = 220, plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_sing, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(ar_sing, method = "rate", n = c(-0.4, -0.3))$rate.output, 1) # should remove all rates expect_error(select_rate(ar_sing, method = "rate", n = c(-0.4, -0.5)), NA) expect_length(select_rate(ar_sing, method = "rate", n = c(-0.4, -0.5))$rate.output, 0) # should remove some rates # expect_error(select_rate(ar_sing, method = "rate", n = c(-0.7, -0.8)), # NA) # expect_length(select_rate(ar_sing, method = "rate", n = c(-0.7, -0.8))$rate.output, # 2) # Works piped expect_error( ar_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_sing %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_sing %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_sing %>% select_rate(method = "rsq", n = NULL), NA) # should NOT stop - this accepts density method expect_error( ar_sing %>% select_rate(method = "density", n = c(8,7)), NA) # should plot expect_error( ar_sing %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_sing %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_sing %>% select_rate(method = "rate", n = c(-0.5, -0.4)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate-to-adjust_rate-to-convert_rate object with single rate test_that("select_rate: auto_rate-to-adjust_rate-to-convert_rate object with single rates works", { ar_sing_adj <- urchins.rd[,1:2] %>% auto_rate(width = 220, plot = FALSE) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_sing_adj, method = "rate", n = c(-0.2, -0.3)), NA) expect_length(select_rate(ar_sing_adj, method = "rate", n = c(-0.2, -0.3))$rate.output, 1) # should remove all rates expect_error(select_rate(ar_sing_adj, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(ar_sing_adj, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates # expect_error(select_rate(ar_sing_adj, method = "rate", n = c(-0.7, -0.8)), # NA) # expect_length(select_rate(ar_sing_adj, method = "rate", n = c(-0.7, -0.8))$rate.output, # 2) # Works piped expect_error( ar_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_sing_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_sing_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_sing_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_sing_adj %>% select_rate(method = "rsq", n = NULL), NA) # should NOT stop - this accepts density method expect_error( ar_sing_adj %>% select_rate(method = "density", n = c(8,7)), NA) # should plot expect_error( ar_sing_adj %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_sing_adj %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_sing_adj %>% select_rate(method = "rate", n = c(-0.5, -0.4)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate-to-convert_rate object with multiple rates test_that("select_rate: auto_rate-to-convert_rate object with multiple rates works", { ar_mult <- urchins.rd[,1:2] %>% auto_rate(width = 0.2, plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_mult, method = "rate", n = c(-0.5, -0.3)), NA) expect_length(select_rate(ar_mult, method = "rate", n = c(-0.5, -0.3))$rate.output, 4) # should remove all rates expect_error(select_rate(ar_mult, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(ar_mult, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(ar_mult, method = "rate", n = c(-0.4, -0.3)), NA) expect_length(select_rate(ar_mult, method = "rate", n = c(-0.4, -0.3))$rate.output, 2) # Works piped expect_error( ar_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_mult %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_mult %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_mult %>% select_rate(method = "rsq", n = NULL), NA) # should NOT stop - this accepts density method expect_error( ar_mult %>% select_rate(method = "density", n = c(8,7)), NA) # should plot expect_error( ar_mult %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_mult %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_mult %>% select_rate(method = "rate", n = c(-0.9, -1)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate-to-adjust_rate-to-convert_rate object with multiple rates test_that("select_rate: auto_rate-to-adjust_rate-to-convert_rate object with multiple rates works", { ar_mult_adj <- urchins.rd[,1:2] %>% auto_rate(width = 0.2, plot = FALSE) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_mult_adj, method = "rate", n = c(-0.2, -0.4)), NA) expect_length(select_rate(ar_mult_adj, method = "rate", n = c(-0.2, -0.4))$rate.output, 4) # should remove all rates expect_error(select_rate(ar_mult_adj, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(ar_mult_adj, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(ar_mult_adj, method = "rate", n = c(-0.32, -0.36)), NA) expect_length(select_rate(ar_mult_adj, method = "rate", n = c(-0.32, -0.36))$rate.output, 2) # Works piped expect_error( ar_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_mult_adj %>% select_rate(method = "rsq", n = NULL), NA) # should NOT stop - this accepts density method expect_error( ar_mult_adj %>% select_rate(method = "density", n = c(8,7)), NA) # should plot expect_error( ar_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_mult_adj %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_mult_adj %>% select_rate(method = "rate", n = c(-0.5, -0.4)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate-to-convert_rate object with multiple rates and NOT linear method test_that("select_rate: auto_rate-to-convert_rate object with multiple rates and NOT linear method works", { ar_mult_low <- urchins.rd[,1:2] %>% auto_rate(width = 0.2, method = "lowest", plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_mult_low, method = "rate", n = c(-0.5, -0.3)), NA) expect_length(select_rate(ar_mult_low, method = "rate", n = c(-0.5, -0.3))$rate.output, 218) # should remove all rates expect_error(select_rate(ar_mult_low, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(ar_mult_low, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(ar_mult_low, method = "rate", n = c(-0.4, -0.39)), NA) expect_length(select_rate(ar_mult_low, method = "rate", n = c(-0.4, -0.39))$rate.output, 27) # Works piped expect_error( ar_mult_low %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_mult_low %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_mult_low %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_mult_low %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_mult_low %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( ar_mult_low %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( ar_mult_low %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_mult_low %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_mult_low %>% select_rate(method = "rate", n = c(-0.9, -1)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # auto_rate-to-adjust_rate-to-convert_rate object with multiple rates and NOT linear method test_that("select_rate: auto_rate-to-adjust_rate-to-convert_rate object with multiple rates and NOT linear method works", { ar_mult_low_adj <- urchins.rd[,1:2] %>% auto_rate(width = 0.2, method = "lowest", plot = FALSE) %>% adjust_rate(by = -0.005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h/g", volume = 1.09, mass = 0.005) # should not remove any rates expect_error(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.2, -0.4)), NA) expect_length(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.2, -0.4))$rate.output, 218) # should remove all rates expect_error(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.3, -0.35)), NA) expect_length(select_rate(ar_mult_low_adj, method = "rate", n = c(-0.3, -0.35))$rate.output, 113) # Works piped expect_error( ar_mult_low_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (ar_mult_low_adj %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( ar_mult_low_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( ar_mult_low_adj %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( ar_mult_low_adj %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( ar_mult_low_adj %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") # should plot expect_error( ar_mult_low_adj %>% select_rate(method = "rsq", n = NULL) %>% plot(), NA) expect_output( ar_mult_low_adj %>% select_rate(method = "rsq", n = NULL) %>% plot()) # should NOT plot expect_message( ar_mult_low_adj %>% select_rate(method = "rate", n = c(-0.5, -0.4)) %>% plot(), "convert_rate: Nothing to plot! No rates found in object.") }) # calc_rate.bg checks ----------------------------------------------------- # calc_rate.bg-to-convert_rate object with single rate test_that("select_rate: calc_rate.bg-to-convert_rate object with single rate works", { cr.bg_sing <- urchins.rd[,c(1,18)] %>% calc_rate.bg(plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h", volume = 1.09) # should not remove any rates expect_error(select_rate(cr.bg_sing, method = "rate", n = c(-0.04, -0.06)), NA) expect_length(select_rate(cr.bg_sing, method = "rate", n = c(-0.04, -0.06))$rate.output, 1) # should remove all rates expect_error(select_rate(cr.bg_sing, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(cr.bg_sing, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # # should remove some rates # expect_error(select_rate(cr.bg_sing, method = "rate", n = c(-0.3, -0.35)), # NA) # expect_length(select_rate(cr.bg_sing, method = "rate", n = c(-0.3, -0.35))$rate.output, # 113) # Works piped expect_error( cr.bg_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr.bg_sing %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr.bg_sing %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr.bg_sing %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr.bg_sing %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr.bg_sing %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") expect_error( cr.bg_sing %>% select_rate(method = "oxygen", n = c(8,7)), "select_rate: The 'oxygen' method is not accepted for 'calc_rate.bg' objects because rates may come from different columns of the dataframe.") # should NOT plot expect_error( cr.bg_sing %>% select_rate(method = "rsq", n = NULL) %>% plot(), "plot.convert_rate: Plot is not available for converted 'calc_rate.bg' objects") # expect_output( # cr.bg_sing %>% # select_rate(method = "rsq", n = NULL) %>% # plot()) # should NOT plot # expect_output( # cr.bg_sing %>% # select_rate(method = "rate", n = c(-0.5, -0.4)) %>% # plot()) # expect_message( # cr.bg_sing %>% # select_rate(method = "rate", n = c(-0.5, -0.4)) %>% # plot(), # "convert_rate: Nothing to plot! No rates found in object.") }) # calc_rate.bg-to-convert_rate object with multiple rates test_that("select_rate: calc_rate.bg-to-convert_rate object with multiple rates works", { suppressWarnings(cr.bg_mult <- urchins.rd %>% inspect(1,18:19, plot = FALSE) %>% calc_rate.bg(plot = FALSE) %>% convert_rate(oxy.unit = "mg/l", time.unit = "min", output.unit = "mg/h", volume = 1.09)) # should not remove any rates expect_error(select_rate(cr.bg_mult, method = "rate", n = c(-0.04, -0.06)), NA) expect_length(select_rate(cr.bg_mult, method = "rate", n = c(-0.04, -0.06))$rate.output, 2) # should remove all rates expect_error(select_rate(cr.bg_mult, method = "rate", n = c(-0.6, -0.5)), NA) expect_length(select_rate(cr.bg_mult, method = "rate", n = c(-0.6, -0.5))$rate.output, 0) # should remove some rates expect_error(select_rate(cr.bg_mult, method = "rate", n = c(-0.03, -0.052)), NA) expect_length(select_rate(cr.bg_mult, method = "rate", n = c(-0.03, -0.052))$rate.output, 1) # Works piped expect_error( cr.bg_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)), NA) expect_length( (cr.bg_mult %>% select_rate(method = "rate", n = c(-0.4, -0.3)) %>% select_rate(method = "rate", n = c(-0.3, -0.2)))$rate.output, 0) # Works with reordering expect_error( cr.bg_mult %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), NA) expect_message( cr.bg_mult %>% select_rate(method = "rsq", n = NULL) %>% select_rate(method = "rank", n = NULL), "select_rate: Reordering results by 'rank' method.") # Works with a method that doesn't work on numerics expect_error( cr.bg_mult %>% select_rate(method = "rsq", n = NULL), NA) # should stop expect_error( cr.bg_mult %>% select_rate(method = "density", n = c(8,7)), "select_rate: The 'density' method is only accepted for rates determined in 'auto_rate' via the 'linear' method.") expect_error( cr.bg_mult %>% select_rate(method = "oxygen_omit", n = c(8,7)), "select_rate: The 'oxygen_omit' method is not accepted for 'calc_rate.bg' objects because rates may come from different columns of the dataframe.") # should NOT plot expect_error( cr.bg_mult %>% select_rate(method = "rsq", n = NULL) %>% plot(), "plot.convert_rate: Plot is not available for converted 'calc_rate.bg' objects") # expect_output( # cr.bg_mult %>% # select_rate(method = "rsq", n = NULL) %>% # plot()) # should NOT plot # expect_output( # cr.bg_mult %>% # select_rate(method = "rate", n = c(-0.5, -0.4)) %>% # plot()) # expect_message( # cr.bg_mult %>% # select_rate(method = "rate", n = c(-0.5, -0.4)) %>% # plot(), # "convert_rate: Nothing to plot! No rates found in object.") }) # Misc S3 Checks ---------------------------------------------------------- test_that("select_rate: empty summary tables don't stop pipes during reordering", { cr.int_mult_adj <- intermittent.rd %>% inspect(plot = FALSE)%>% calc_rate.int(starts = c(1, 2101, 3901), from = 500, to = 1000, by = "row", plot = FALSE) %>% adjust_rate(by = -0.00005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "s", output.unit = "mg/h/g", mass = 0.006955, volume = 2.379) # should not remove any rates expect_error(cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.5)) %>% select_rate(method = "time", n = NULL) %>% select_rate(method = "rsq", n = NULL), NA) expect_length((cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.5)) %>% select_rate(method = "time", n = NULL) %>% select_rate(method = "rsq", n = NULL))$rate.output, 0) }) test_that("select_rate: empty summary tables don't stop pipes during subsetting", { cr.int_mult_adj <- intermittent.rd %>% inspect(plot = FALSE)%>% calc_rate.int(starts = c(1, 2101, 3901), from = 500, to = 1000, by = "row", plot = FALSE) %>% adjust_rate(by = -0.00005) %>% convert_rate(oxy.unit = "mg/l", time.unit = "s", output.unit = "mg/h/g", mass = 0.006955, volume = 2.379) # should not remove any rates expect_error(cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.5)) %>% select_rate(method = "time", n = c(1,100)) %>% select_rate(method = "rsq", n = c(0.95,1)), NA) expect_length((cr.int_mult_adj %>% select_rate(method = "rate", n = c(-0.4, -0.5)) %>% select_rate(method = "time", n = c(1,100)) %>% select_rate(method = "rsq", n = c(0.95,1)))$rate.output, 0) }) # Remove plot pdf --------------------------------------------------------- ## this may cause problems with cmd-check.... ## .... but apparently not! suppressWarnings(file.remove("Rplots.pdf")) }) ## end capture.output