# rm(list=ls()) # library(testthat) # test_file("tests/testthat/test-auto_rate.int.R") # covr::file_coverage("R/auto_rate.int.R", "tests/testthat/test-auto_rate.int.R") # cvr <- covr::package_coverage() # covr::report(cvr) # covr::report(covr::package_coverage()) capture.output({ ## stops printing outputs on assigning if (!identical(Sys.getenv("NOT_CRAN"), "true")) return() skip_on_cran() # create testing objects suppressWarnings({ # in secs dt.sec <- intermittent.rd %>% subset_data(from = 1) # removes first value at 0 time because of annoying messages during adjustments dt.sec.insp <- inspect(dt.sec, plot = F) # in mins - 2 dec places dt.min.2 <- intermittent.rd %>% subset_data(from = 1) dt.min.2[[1]] <- round(dt.min.2[[1]]/60, 2) dt.min.2.insp <- inspect(dt.min.2, plot = F) # in mins - 1 dec places dt.min.1 <- intermittent.rd %>% subset_data(from = 1) dt.min.1[[1]] <- round(dt.min.1[[1]]/60, 1) dt.min.1.insp <- inspect(dt.min.1, plot = F) # in hrs - 2 dec places dt.hr <- intermittent.rd %>% subset_data(from = 1) dt.hr[[1]] <- round(dt.hr[[1]]/60/60, 3) dt.hr.insp <- inspect(dt.hr, plot = F) sts <- c(1,2100,3899) # different from help file because first row removed above sts.min <- c(0.02,35,65) # starts in minutes sts.hr <- round(c(0.02,35,65)/60, 3) # starts in hr ens.actual <- c(2099,3898,4830) #actual ends including flush ens.measure <- c(1899,3549,4830) # ends excluding flush # 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 = F) }) # x input tests -------------------------------------------------- # stops if x not df or inspect obj test_that("auto_rate.int - stops with wrong 'x' inputs", { expect_error(auto_rate.int(dt.sec[[1]], starts = sts, width = 100, plot = F), "auto_rate.int: Input must be a 'data.frame' or 'inspect' object.") expect_error(auto_rate.int(inspect.ft(dt.sec, plot = F), starts = sts, width = 100, plot = F), "auto_rate.int: Input must be a 'data.frame' or 'inspect' object.") expect_error(auto_rate.int(12, starts = sts, width = 100, plot = F), "auto_rate.int: Input must be a 'data.frame' or 'inspect' object.") }) # accepts df and inspect objs test_that("auto_rate.int - accepts 'data.frame' 'x' inputs", { expect_error(auto_rate.int(dt.sec, starts = sts, width = 100, plot = F), NA) }) test_that("auto_rate.int - accepts 'inspect' 'x' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, width = 100, plot = F), NA) }) test_that("auto_rate.int - correctly extracts dataframe from 'inspect' objects", { ar.int <- auto_rate.int(dt.sec.insp, starts = sts, width = 100, plot = F) expect_identical(ar.int$dataframe, dt.sec.insp$dataframe) expect_is(ar.int$dataframe, "data.table") }) test_that("auto_rate.int - message with multicolumn 'x' inputs", { expect_message(auto_rate.int(sardine.rd, starts = sts, width = 100, plot = F), "auto_rate.int: Multi-column dataset detected in input. Selecting first two columns by default.") }) # starts input tests ----------------------------------------------------- # required, numeric, integer, within df row range test_that("auto_rate.int - stops with wrong 'starts' inputs", { # NULL expect_error(auto_rate.int(dt.sec.insp, starts = NULL, width = 100, plot = F), "auto_rate.int: 'starts' - input is required.") # Non-integer(s) expect_error(auto_rate.int(dt.sec.insp, starts = c(1, 100.1, 500), width = 100, plot = F), "auto_rate.int: 'starts' - one or more inputs are not integers.") }) # Accepts multiple and single inputs test_that("auto_rate.int - accepts correct 'starts' inputs", { skip_on_cran() expect_error(auto_rate.int(dt.sec.insp, starts = sts, width = 100, by = "row", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = 1000, width = 100, by = "row", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = sts, width = 100, by = "time", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = 1000, width = 100, by = "time", plot = F), NA) }) # wait input tests ----------------------------------------------------- # required, numeric, integer, within df row range test_that("auto_rate.int - stops with wrong 'wait' inputs", { # NULL - is ok expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = NULL, width = 100, by = "row", plot = F), NA) # string expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = "text", width = 100, by = "row", plot = F), "auto_rate.int: 'wait' - input is not numeric.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = "text", width = 100, by = "time", plot = F), "auto_rate.int: 'wait' - input is not numeric.") # Non-integer(s) for row expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 100.1, width = 100, by = "row", plot = F), "auto_rate.int: 'wait' - one or more inputs are not integers.") # Non-integer(s) for time is ok expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 100.1, width = 100, by = "time", plot = F), NA) # Outside range expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = c(300,400, 5000), width = 100, by = "row", plot = F), "auto_rate.int: 'wait' - one or more inputs are outside the range of allowed values.") # by = "time" - there is no range test # Wrong length expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 100:103, width = 100, by = "row", plot = F), "auto_rate.int: For a vector input 'wait' should be the same length as 'starts'.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 100:103, width = 100, by = "time", plot = F), "auto_rate.int: For a vector input 'wait' should be the same length as 'starts'.") }) # Accepts multiple and single inputs test_that("auto_rate.int - accepts correct length 'wait' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, width = 100, by = "row", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50:52, width = 100, by = "row", plot = F), NA) }) # if wait = NULL all start rows should be equal to subset start rows test_that("auto_rate.int - properly parses 'wait = NULL'", { # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = NULL, measure = 1000, width = 500, by = "row", method = "rolling", n = 1, plot = F) #summary(ar.int.obj.3reps) # locs expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]]), ar.int.obj.3reps$summary$row) # ends should be this plus width expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]])+500-1, ar.int.obj.3reps$summary$endrow) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses single 'wait' values", { # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = 100, measure = 1000, width = 500, by = "row", method = "rolling", n = 1, plot = F) #summary(ar.int.obj.3reps) # locs expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]]), ar.int.obj.3reps$summary$row - 100) # ends should be this plus width expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]])+500-1, ar.int.obj.3reps$summary$endrow - 100) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses multiple 'wait' values", { # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = c(100, 120, 140), measure = 1000, width = 500, by = "row", method = "rolling", n = 1, plot = F) #summary(ar.int.obj.3reps) # locs expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]]), ar.int.obj.3reps$summary$row - c(100, 120, 140)) # ends should be this plus width expect_equal(sapply(ar.int.obj.3reps$subsets, function(z) z[[1,1]])+500-1, ar.int.obj.3reps$summary$endrow - c(100, 120, 140)) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) # measure input tests ----------------------------------------------------- test_that("auto_rate.int - message with NULL 'measure' input", { expect_message(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = NULL, width = 100, plot = F), "auto_rate.int: The `measure` input is NULL. Calculating rate to the end of the replicate.") }) # required, numeric, integer, within df row range test_that("auto_rate.int - stops with wrong 'measure' inputs", { # string expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = "text", width = 100, by = "row", plot = F), "auto_rate.int: 'measure' - input is not numeric.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = "text", width = 100, by = "time", plot = F), "auto_rate.int: 'measure' - input is not numeric.") # Non-integer(s) for row expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 200.1, width = 100, by = "row", plot = F), "auto_rate.int: 'measure' - one or more inputs are not integers.") # Non-integer(s) for time is ok expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 200.1, width = 100, by = "time", plot = F), NA) # Outside range expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = c(300,400, 5000), width = 100, by = "row", plot = F), "auto_rate.int: 'measure' - one or more inputs are outside the range of allowed values.") # by = "time" - there is no range test # Wrong length expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 100:103, width = 100, by = "row", plot = F), "auto_rate.int: For a vector input 'measure' should be the same length as 'starts'.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 100:103, width = 100, by = "time", plot = F), "auto_rate.int: For a vector input 'measure' should be the same length as 'starts'.") }) # Accepts multiple and single inputs test_that("auto_rate.int - accepts correct length 'measure' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "row", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500:502, width = 100, by = "row", plot = F), NA) }) test_that("auto_rate.int - properly parses 'measure = NULL'", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = NULL, measure = NULL, width = 500, by = "row", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates of this width last endrow should be last row of data expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[2]-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[3]-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 3333) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses single 'measure' values", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = 100, measure = 1000, width = 500, by = "row", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+1000-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+100+1000-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 1335) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses multiple 'measure' values", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = 100, measure = c(800, 900, 1000), width = 500, by = "row", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+800-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+100+900-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 1035) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses multiple 'measure' values with multiple wait values", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = c(100, 150, 200), measure = c(800, 900, 1000), width = 500, by = "row", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+800-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+150+900-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 935) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "row")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses 'measure = NULL' and by = 'time'", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = NULL, measure = NULL, width = 500, by = "time", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates of this width last endrow should be last row of data expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[2]-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[3]-1) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future # This is 1 less per rep than by = "row" prob for minor reasons expect_equal(nrow(ar.int.obj.3reps$summary), 3330) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses single 'measure' values and by = 'time'", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = 100, measure = 1000, width = 500, by = "time", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+1000) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+100+1000) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 1334) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses multiple 'measure' values and by = 'time'", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = 100, measure = c(800, 900, 1000), width = 500, by = "time", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+800) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+100+900) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 1034) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) test_that("auto_rate.int - properly parses multiple 'measure' values with multiple wait values and by = 'time'", { skip_on_cran() # by row ar.int.obj.3reps <- auto_rate.int(x = dt.sec.insp, starts = sts, wait = c(100, 150, 200), measure = c(800, 900, 1000), width = 500, by = "time", method = "rolling", n = 10000, plot = F) #summary(ar.int.obj.3reps) # locs # If we calc all possible rates with this measure last endrows should be starts + wait + measure expect_equal(nrow(dt.sec.insp$dataframe), ar.int.obj.3reps$summary$endrow[nrow(ar.int.obj.3reps$summary)]) # last endrow of each rep should be last row of each rep expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 1], 1), sts[1]+100+800) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 2], 1), sts[2]+150+900) expect_equal(tail(ar.int.obj.3reps$summary$endrow[ar.int.obj.3reps$summary$rep == 3], 1), nrow(dt.sec.insp$dataframe)) # sould be this many result rows - just leaving this here in case this changes for some reason in future expect_equal(nrow(ar.int.obj.3reps$summary), 934) # check raw data matches for these rows expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$row,], ar.int.obj.3reps$summary[,c(9,11)]) expect_equivalent(dt.sec.insp$dataframe[ar.int.obj.3reps$summary$endrow,], ar.int.obj.3reps$summary[,c(10,12)]) # check rate calcs for these rows expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) expect_equal(calc_rate(dt.sec.insp, from = ar.int.obj.3reps$summary$row, to = ar.int.obj.3reps$summary$endrow, by = "time")$rate, ar.int.obj.3reps$summary$rate) }) # 'by' input tests ------------------------------------------------------- test_that("auto_rate.int - accepts correct 'by' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "row", plot = F), NA) expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "time", plot = F), NA) }) test_that("auto_rate.int - stops with incorrect 'by' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = NULL, plot = F), "auto_rate.int: 'by' input is required.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "oxygen", plot = F), "auto_rate.int: 'by' input not valid or not recognised.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "sometext", plot = F), "auto_rate.int: 'by' input not valid or not recognised.") }) # 'width' input tests ----------------------------------------------------- test_that("auto_rate.int - stops with NULL 'width' inputs", { expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = NULL, by = "row", plot = F), "auto_rate.int: Please enter a 'width'. This should be in the 'by' input of number of rows.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = NULL, by = "time", plot = F), "auto_rate.int: Please enter a 'width'. This should be in the 'by' input of a time duration in the correct units.") }) test_that("auto_rate.int - stops with incorrect 'width' inputs", { # numeric expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = "text", by = "row", plot = F), "auto_rate.int: 'width' - input is not numeric.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = "text", by = "time", plot = F), "auto_rate.int: 'width' - input is not numeric.") # integer of 1 if by = row expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 1, by = "row", plot = F), "auto_rate.int: 'width' - one or more inputs are outside the range of allowed values.") # 0 to 1 non-integers ok with by = "row" expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 0.5, by = "row", plot = F), NA) # non-integers ok with by = "time" expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100.1, by = "time", plot = F), NA) # out of range expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 5000, by = "row", plot = F), "auto_rate.int: 'width' - one or more inputs are outside the range of allowed values.") # no range test for by = "time" }) test_that("auto_rate.int - message if 'width' input between 0 and 1 and by = 'time'", { expect_message(auto_rate.int(dt.hr, starts = sts.hr, wait = 0.01, measure = 0.4, width = 0.05, by = "time", plot = F), "auto_rate.int: 'width' input is between 0 and 1. Check this value is what you intend.") }) # 'n' input tests --------------------------------------------------------- test_that("auto_rate.int - stops with incorrect 'n' inputs", { # required expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "row", n = NULL, plot = F), "auto_rate.int: 'n' - input is required.") # numeric expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "row", n = "text", plot = F), "auto_rate.int: 'n' - input is not numeric.") expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "time", n = "text", plot = F), "auto_rate.int: 'n' - input is not numeric.") # integer expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 100, by = "row", n = 1.1, plot = F), "auto_rate.int: 'n' - one or more inputs are not integers.") # single value expect_error(auto_rate.int(dt.sec.insp, starts = sts, wait = 50, measure = 500, width = 5000, by = "time", n = 1:2, plot = F), "auto_rate.int: 'n' - only 1 inputs allowed.") }) # 'starts' correctly parsed ----------------------------------------------- test_that("single 'starts' inputs are correctly parsed to correct number and locations of reps",{ # by row # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.sec.insp, starts = 1000, wait = 50, measure = 500, width = 100, by = "row", n = 1, plot = F) # n reps expect_equal(nrow(ar.int.obj.5reps$summary), 5) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[[1,1]]), c(1,1001,2001,3001,4001)) # by time # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.sec.insp, starts = 1000, wait = 50, measure = 500, width = 100, by = "time", n = 1, plot = F) # n reps expect_equal(nrow(ar.int.obj.5reps$summary), 5) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[[1,1]]), c(1,1001,2001,3001,4001)) # by time - different units # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.min.2.insp, starts = 1000/60, wait = 1, measure = 6, width = 1, by = "time", n = 1, plot = F) # n reps expect_equal(nrow(ar.int.obj.5reps$summary), 5) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[[1,1]]), round(c(1,1001,2001,3001,4001)/60),2) # by time - different units and n greater than 1 # should be 5 reps ar.int.obj.15reps <- auto_rate.int(dt.min.2.insp, starts = 1000/60, wait = 1, measure = 6, width = 1, by = "time", n = 3, plot = F) # n reps expect_equal(nrow(ar.int.obj.15reps$summary), 15) # locs - this should not change with different n expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[[1,1]]), round(c(1,1001,2001,3001,4001)/60),2) # Regular reps # should be 10 reps ar.int.obj.10reps <- auto_rate.int(dt.reg.insp, starts = 660, wait = 50, measure = 300, width = 100, by = "row", n = 1, plot = F) # n reps expect_equal(nrow(ar.int.obj.10reps$summary), 10) # locs expect_equal(sapply(ar.int.obj.10reps$subsets, function(z) z[[1,1]]), seq(5840, 5840 + 6599, 660)) # Regular reps # should be 10 reps ar.int.obj.10reps <- auto_rate.int(dt.reg.insp, starts = 660, wait = 50, measure = 300, width = 100, by = "time", n = 1, plot = F) # n reps expect_equal(nrow(ar.int.obj.10reps$summary), 10) # locs expect_equal(sapply(ar.int.obj.10reps$subsets, function(z) z[[1,1]]), seq(5840, 5840 + 6599, 660)) }) # rep ends correctly parsed ----------------------------------------------- test_that("single 'starts' inputs are correctly parsed to correct number and locations of reps",{ # by row # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.sec.insp, starts = 1000, wait = 50, measure = 500, width = 100, by = "row", n = 1, plot = F) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[1,nrow(z)]), c(1000,1000,1000,1000,830)) # by time # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.sec.insp, starts = 1000, wait = 50, measure = 500, width = 100, by = "time", n = 1, plot = F) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[1,nrow(z)]), c(1000,1000,1000,1000,830)) # by time - different units # should be 5 reps ar.int.obj.5reps <- auto_rate.int(dt.min.2.insp, starts = 1000/60, wait = 1, measure = 6, width = 1, by = "time", n = 1, plot = F) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[1,nrow(z)]), c(1000,1000,1000,1000,830)) # by time - different units and n greater than 1 # should be 5 reps ar.int.obj.15reps <- auto_rate.int(dt.min.2.insp, starts = 1000/60, wait = 1, measure = 6, width = 1, by = "time", n = 3, plot = F) # locs expect_equal(sapply(ar.int.obj.5reps$subsets, function(z) z[1,nrow(z)]), c(1000,1000,1000,1000,830)) # Regular reps # should be 10 reps ar.int.obj.10reps <- auto_rate.int(dt.reg.insp, starts = 660, wait = 50, measure = 300, width = 100, by = "row", n = 1, plot = F) # locs expect_equal(sapply(ar.int.obj.10reps$subsets, function(z) z[1,nrow(z)]), rep(660, 10)) # Regular reps # should be 10 reps ar.int.obj.10reps <- auto_rate.int(dt.reg.insp, starts = 660, wait = 50, measure = 300, width = 100, by = "time", n = 1, plot = F) # locs expect_equal(sapply(ar.int.obj.10reps$subsets, function(z) z[1,nrow(z)]), rep(660, 10)) }) # Expected results --------------------------------------- # # Since it's running auto_rate we use it to get results to test against # by = "time" tests ------------------------------------------------------- test_that("auto_rate.int - expected results with method = 'linear'", { skip_on_cran() # Whole replicate #auto_rate object ar.obj.rep1 <- auto_rate(dt.sec[sts[1]:ens.actual[1],], width = 400, by = "row", plot = F) ar.obj.rep2 <- auto_rate(dt.sec[sts[2]:ens.actual[2],], width = 400, by = "row", plot = F) ar.obj.rep3 <- auto_rate(dt.sec[sts[3]:ens.actual[3],], width = 400, by = "row", plot = F) #auto_rate.int object ar.int.obj <- auto_rate.int(dt.sec.insp, starts = sts, width = 400, by = "row", plot = F) # test # first rows of summary should match # except these columns: rep, rank, row, endrow # so just use final few columns expect_equal(ar.obj.rep1$summary[1,9:ncol(ar.obj.rep1$summary)], ar.int.obj$summary[1,9:ncol(ar.int.obj$summary)]) expect_equal(ar.obj.rep2$summary[1,9:ncol(ar.obj.rep2$summary)], ar.int.obj$summary[2,9:ncol(ar.int.obj$summary)]) expect_equal(ar.obj.rep3$summary[1,9:ncol(ar.obj.rep3$summary)], ar.int.obj$summary[3,9:ncol(ar.int.obj$summary)]) }) test_that("auto_rate.int - expected results with method = 'lowest' and excluded flushes", { skip_on_cran() # Whole replicate #auto_rate object ar.obj.rep1 <- auto_rate(dt.sec[sts[1]:ens.measure[1],], method = "lowest", width = 300, by = "time", plot = F) ar.obj.rep2 <- auto_rate(dt.sec[sts[2]:ens.measure[2],], method = "lowest", width = 300, by = "time", plot = F) ar.obj.rep3 <- auto_rate(dt.sec[sts[3]:ens.measure[3],], method = "lowest", width = 300, by = "time", plot = F) #auto_rate.int object ar.int.obj <- auto_rate.int(dt.sec.insp, starts = sts, measure = ens.measure - sts +1, method = "lowest", width = 300, by = "time", plot = F) # test # first rows of summary should match # except these columns: rep, rank, row, endrow # so just use final few columns expect_equal(ar.obj.rep1$summary[1,9:ncol(ar.obj.rep1$summary)], ar.int.obj$summary[1,9:ncol(ar.int.obj$summary)]) expect_equal(ar.obj.rep2$summary[1,9:ncol(ar.obj.rep2$summary)], ar.int.obj$summary[2,9:ncol(ar.int.obj$summary)]) expect_equal(ar.obj.rep3$summary[1,9:ncol(ar.obj.rep3$summary)], ar.int.obj$summary[3,9:ncol(ar.int.obj$summary)]) }) test_that("auto_rate.int - correctly populates $rep and $rank columns", { # We know this produces specific results, with different numbers of rresults in each rep # so we just test these 2 columns ar.int.obj <- auto_rate.int(dt.sec.insp, starts = c(1, 2101, 3751), measure = ens.measure - sts +1, method = "linear", width = 800, by = "row", n = 6, plot = F) # test expect_equal(ar.int.obj$summary$rep, c(rep(1, 6), rep (2, 5), rep(3, 3))) expect_equal(ar.int.obj$summary$rank, c(1:6, 1:5, 1:3)) }) test_that("auto_rate.int - with replicates of regularly spaced reps", { # Regular replicates - Whole replicate #auto_rate object ar.int.obj <- auto_rate.int(dt.reg.insp, starts = 660, width = 400, by = "row", plot = F) #auto_rate.int object expect_error(auto_rate.int(dt.reg.insp, starts = 660, width = 400, by = "row", plot = F), NA) # test # should be 10 rows expect_equal(nrow(ar.int.obj$summary), 10) # should be 20 rows when n = 2 expect_equal(nrow(auto_rate.int(dt.reg.insp, starts = 660, width = 400, by = "row", n = 2, plot = F)$summary), 20) }) # General tests ----------------------------------------------------------- test_that("auto_rate.int - outputs object of class auto_rate.int", { skip_on_cran() ar.int <- auto_rate.int(dt.sec.insp, starts = sts, width = 400, by = "row", plot = F) expect_is(ar.int, "auto_rate.int") }) test_that("auto_rate.int - S3 generics work", { skip_on_cran() # plots from within function expect_output(auto_rate.int(dt.sec.insp, starts = sts, width = 400, by = "row", plot = TRUE)) expect_error(auto_rate.int(dt.sec.insp, starts = sts, width = 400, by = "row", plot = TRUE), NA) ar.int <- auto_rate.int(dt.sec.insp, starts = sts, width = 400, by = "row", plot = F) expect_output(print(ar.int)) expect_output(summary(ar.int)) expect_output(plot(ar.int)) expect_output(mean(ar.int)) # multiple rates and 'pos' expect_output(print(ar.int, pos = 2)) expect_error(print(ar.int, pos = 2:3), "print.auto_rate.int: 'pos' must be a single value. To examine multiple results use summary().") expect_error(print(ar.int, pos = 30), "print.auto_rate.int: Invalid 'pos' input: only 3 rates found.") expect_output(summary(ar.int, pos = 2:3)) expect_error(summary(ar.int, pos = 40), "summary.auto_rate.int: Invalid 'pos' input: only 3 rates found.") expect_is(summary(ar.int, pos = 2:3, export = TRUE), "data.frame") expect_output(mean(ar.int, pos = 1)) expect_message(mean(ar.int, pos = 1), "Only 1 rate found. Returning mean rate anyway...") expect_output(mean(ar.int, pos = 2:3)) expect_error(mean(ar.int, pos = 40), "mean.auto_rate.int: Invalid 'pos' input: only 3 rates found.") expect_is(mean(ar.int, pos = 2:3, export = TRUE), "numeric") expect_equal(mean(ar.int, pos = 2:3, export = TRUE), mean(ar.int$rate[2:3])) # pos default applied expect_output(plot(ar.int, pos = NULL)) expect_output(plot(ar.int, pos = 1)) expect_output(plot(ar.int, pos = 3)) expect_error(plot(ar.int, pos = 50), "plot.auto_rate.int: Invalid 'pos' input: only 3 rates found.") # plot types produce output expect_output(plot(ar.int, type = "rep")) expect_output(plot(ar.int, type = "rep", pos = 2:3)) expect_output(plot(ar.int, type = "full")) expect_output(plot(ar.int, type = "full", pos = 2:3)) expect_output(plot(ar.int, type = "ar")) expect_output(plot(ar.int, type = "ar", pos = 2:3)) expect_error(plot(ar.int, type = "test"), "plot.auto_rate.int: 'type' input not recognised.") }) test_that("auto_rate.int - row numbers are output correctly", { #auto_rate.int object ar.int.obj <- auto_rate.int(x = dt.sec.insp, starts = sts, by = "time", method = "linear", width = 10, wait = c(100,200,300), n = 2, measure = c(500,500,400), plot = F, type = "rep") %>% summary() ar.int.obj$dataframe[ar.int.obj$summary$row,] # test - if we use row numbers in calc_rate results should match #calc_rate object cr.obj <- calc_rate(dt.sec.insp, from = ar.int.obj$summary$row, to = ar.int.obj$summary$endrow, by = "row", plot = F) %>% summary() expect_equal(ar.int.obj$rate, cr.obj$rate) }) test_that("auto_rate.int - 'pos' inputs work", { ar.int <- auto_rate.int(x = dt.sec.insp, starts = sts, by = "time", method = "linear", width = 10, wait = c(100,200,300), n = 2, measure = c(500,500,400), plot = F, type = "rep") # multiple rates and 'pos' expect_output(print(ar.int, pos = 2)) expect_error(print(ar.int, pos = 2:3), "print.auto_rate.int: 'pos' must be a single value. To examine multiple results use summary().") expect_error(print(ar.int, pos = 30), "print.auto_rate.int: Invalid 'pos' input: only 5 rates found.") expect_output(summary(ar.int, pos = 2:3)) expect_error(summary(ar.int, pos = 40), "summary.auto_rate.int: Invalid 'pos' input: only 5 rates found.") expect_is(summary(ar.int, pos = 2:3, export = TRUE), "data.frame") expect_output(mean(ar.int, pos = 2:3)) expect_error(mean(ar.int, pos = 40), "mean.auto_rate.int: Invalid 'pos' input: only 5 rates found.") expect_is(mean(ar.int, pos = 2:3, export = TRUE), "numeric") expect_equal(mean(ar.int, pos = 2:3, export = TRUE), mean(ar.int$rate[2:3])) # works if legend used expect_output(plot(ar.int, pos = 1, legend = TRUE)) # pos default applied expect_output(plot(ar.int, pos = NULL)) expect_output(plot(ar.int, pos = 1)) expect_output(plot(ar.int, pos = 3)) expect_error(plot(ar.int, pos = 50), "plot.auto_rate.int: Invalid 'pos' input: only 5 rates found.") # works with multiple pos up to and past 20 dt.reg.insp.30 <- subset_data(zeb_intermittent.rd, from = 5840, to = 5840 + 19797, by = "row") %>% inspect(legend = F, plot = F) # should be 30 reps ar.int.obj.30reps <- auto_rate.int(dt.reg.insp.30, starts = 660, wait = 50, measure = 300, width = 100, by = "row", n = 1, plot = F) expect_output(plot(ar.int.obj.30reps, pos = 1)) expect_output(plot(ar.int.obj.30reps, pos = 1:2)) expect_output(plot(ar.int.obj.30reps, pos = 1:4)) expect_output(plot(ar.int.obj.30reps, pos = 1:6)) expect_output(plot(ar.int.obj.30reps, pos = 1:9)) expect_output(plot(ar.int.obj.30reps, pos = 1:12)) expect_output(plot(ar.int.obj.30reps, pos = 1:16)) expect_output(plot(ar.int.obj.30reps, pos = 1:20)) expect_output(plot(ar.int.obj.30reps, pos = 1:25)) expect_message(plot(ar.int.obj.30reps, pos = 1:25), "plot.auto_rate.int: Plotting first 20 selected rates only. To plot others modify 'pos' input.") # plot types produce output expect_output(plot(ar.int, type = "rep")) expect_output(plot(ar.int, type = "rep", pos = 2:3)) expect_output(plot(ar.int, type = "full")) expect_output(plot(ar.int, type = "full", pos = 2:3)) expect_output(plot(ar.int, type = "ar")) expect_output(plot(ar.int, type = "ar", pos = 2:3)) expect_error(plot(ar.int, type = "test"), "plot.auto_rate.int: 'type' input not recognised.") }) # Expected results with adjust_rate --------------------------------------- test_that("auto_rate.int - works as expected with adjust_rate method = 'value'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) # "value" method by <- -0.0001 ar.int.adj <- adjust_rate(ar.int, by = by, method = "value") expect_equal(ar.int$rate - by, ar.int.adj$rate.adjusted) }) test_that("auto_rate.int - works as expected with adjust_rate method = 'mean'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) # "mean" method by <- c(-0.0001, -0.00008, -0.00005) ar.int.adj <- adjust_rate(ar.int, by = by, method = "mean") expect_equal(ar.int$rate - mean(by), ar.int.adj$rate.adjusted) }) test_that("auto_rate.int - works as expected with adjust_rate method = 'paired'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) # "paired" method by <- c(-0.0001, -0.00008, -0.00005) ar.int.adj <- adjust_rate(ar.int, by = by, method = "paired") # ar.int.adj$summary expect_equal(ar.int$rate - by, ar.int.adj$rate.adjusted) }) test_that("auto_rate.int - works as expected with adjust_rate method = 'concurrent'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) # "concurrent" method # subset these data to the same length by <- background_con.rd %>% subset_data(1, 4830, "time", quiet = TRUE) %>% calc_rate.bg(plot = F) ar.int.adj <- adjust_rate(ar.int, by = by, method = "concurrent") # ar.int.adj$summary rt <- calc_rate(by$dataframe, from = ar.int$summary$row, to = ar.int$summary$endrow, by = "row")$rate expect_equal(ar.int$rate - rt, ar.int.adj$rate.adjusted) }) test_that("auto_rate.int - works as expected with adjust_rate method = 'linear'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) #summary(ar.int) # "linear" method # subset these data to the same length by1 <- background_con.rd %>% subset_data(1, 800, "time") %>% calc_rate.bg() by2 <- background_exp.rd %>% subset_data(5000, 15000, "time") %>% calc_rate.bg() ar.int.adj <- adjust_rate(ar.int, by = by1, by2 = by2, method = "linear") # runs without error expect_error(adjust_rate(ar.int, by = by1, by2 = by2, method = "linear"), NA) # ar.int.adj$summary # ar.int.adj$summary$adjustment # For now just test the known values in case they change in future expect_equal(c(-0.00006102753, -0.00009158973, -0.00013826320), ar.int.adj$summary$adjustment) }) test_that("auto_rate.int - works as expected with adjust_rate method = 'exponential'", { skip_on_cran() ar.int <- auto_rate.int(dt.sec, starts = sts, width = 100, plot = F) # "exponential" method # subset these data to the same length by1 <- background_con.rd %>% subset_data(1, 800, "time") %>% calc_rate.bg() by2 <- background_exp.rd %>% subset_data(5000, 15000, "time") %>% calc_rate.bg() ar.int.adj <- adjust_rate(ar.int, by = by1, by2 = by2, method = "exponential") # runs without error expect_error(adjust_rate(ar.int, by = by1, by2 = by2, method = "exponential"), NA) # ar.int.adj$summary # ar.int.adj$summary$adjustment # For now just test the known values in case they change in future expect_equal(c(-0.00005483333, -0.00007021938, -0.00010244557), ar.int.adj$summary$adjustment) }) }) ## end capture output