Nothing
test_that("Test internals", {
testthat::skip_on_cran()
## since below we are testing internal functions that use `.throw_error()`
## and `.throw_warning()`, we need to treat this block as a function
## definition and set the function name
.set_function_name("test")
on.exit(.unset_function_name(), add = TRUE)
# .expand_parameters() ------------------------------------------------------
##create empty function ... reminder
##this is an internal function, the first object is always discarded, it
##might be a list of RLum.Analysis objects is might be super large
f <- function(object, a, b = 1, c = list(), d = NULL) {
Luminescence:::.expand_parameters(len = 3)
}
##test some functions
##missing arguments must be identified
expect_error(f(), "Argument 'a' missing, with no default")
##check whether the objects are properly recycled
expect_type(f(object, a = 1), "list")
expect_length(f(object, a = 1, c = list(a = 1, b = 2, c = 3))$c, 3)
expect_length(f(object, a = (1), c = list(a = 1, b = 2, c = 3))$c, 3)
expect_equal(f(object, a = (1 + 10), c = list(a = 1, b = 2, c = 3))$a[[1]], 11)
# .calc_HPDI() ------------------------------------------------------------
set.seed(1234)
test <- expect_type(Luminescence:::.calc_HPDI(rnorm(100), plot = TRUE), "double")
expect_equal(round(sum(test),2), 0.20, tolerance = 1)
##create a case where the value cannot be calculated
expect_type(.calc_HPDI(rlnorm(n = 100, meanlog = 10, sdlog = 100)), type = "logical")
# .warningCatcher() ---------------------------------------------------------------------------
expect_warning(Luminescence:::.warningCatcher(for(i in 1:5) warning("test")),
regexp = "\\(1\\) test\\: This warning occurred 5 times\\!")
# .smoothing ----------------------------------------------------------------------------------
expect_silent(Luminescence:::.smoothing(runif(100), k = 5, method = "median"))
expect_silent(.smoothing(runif(200), method = "median"))
expect_silent(.smoothing(runif(100), k = 4, method = "mean"))
expect_silent(.smoothing(runif(100), k = 4, method = "median"))
expect_error(.smoothing(runif(100), method = "error"),
"'method' should be one of 'mean' or 'median'")
expect_error(.smoothing(runif(100), align = "error"),
"'align' should be one of 'right', 'center' or 'left'")
## .normalise_curve() -----------------------------------------------------
data <- runif(100)
expect_equal(data, .normalise_curve(data, FALSE))
expect_equal(.normalise_curve(data, TRUE), .normalise_curve(data, "max"))
expect_silent(.normalise_curve(data, "last"))
expect_silent(.normalise_curve(data, "huot"))
data[100] <- 0
expect_warning(.normalise_curve(data, "last"),
"Curve normalisation produced Inf/NaN values, values replaced")
# fancy_scientific ()--------------------------------------------------------------------------
plot(seq(1e10, 1e20, length.out = 10),1:10, xaxt = "n")
expect_silent(axis(1, at = axTicks(1),labels = Luminescence:::fancy_scientific(axTicks(1))))
# .add_fancy_log_axis() -----------------------------------------------------
y <- c(0.1, 0.001, 0.0001)
plot(1:length(y), y, yaxt = "n", log = "y")
expect_silent(Luminescence:::.add_fancy_log_axis(side = 2, las = 1))
expect_null(.add_fancy_log_axis(side = 1, las = 1))
# .get_keyword_coordinates() ----------------------------------------------
xlim <- c(0, 5)
ylim <- c(2, 10)
coords <- .get_keyword_coordinates(xlim = xlim, ylim = ylim)
expect_type(coords, "list")
expect_named(coords, c("pos", "adj"))
expect_length(coords, 2)
expect_equal(coords$pos,
c(0, 10))
expect_equal(.get_keyword_coordinates(pos = c(1, 2), xlim, ylim)$pos,
c(1, 2))
expect_equal(.get_keyword_coordinates(pos = "topleft", xlim, ylim)$pos,
c(0, 10))
expect_equal(.get_keyword_coordinates(pos = "top", xlim, ylim)$pos,
c(2.5, 10))
expect_equal(.get_keyword_coordinates(pos = "topright", xlim, ylim)$pos,
c(5, 10))
expect_equal(.get_keyword_coordinates(pos = "left", xlim, ylim)$pos,
c(0, 6))
expect_equal(.get_keyword_coordinates(pos = "center", xlim, ylim)$pos,
c(2.5, 6))
expect_equal(.get_keyword_coordinates(pos = "right", xlim, ylim)$pos,
c(5, 6))
expect_equal(.get_keyword_coordinates(pos = "bottomleft", xlim, ylim)$pos,
c(0, 2))
expect_equal(.get_keyword_coordinates(pos = "bottom", xlim, ylim)$pos,
c(2.5, 2))
expect_equal(.get_keyword_coordinates(pos = "bottomright", xlim, ylim)$pos,
c(5, 2))
# .create_StatisticalSummaryText() ------------------------------------------------------------
stats <- calc_Statistics(data.frame(1:10,1:10))
expect_silent(Luminescence:::.create_StatisticalSummaryText())
expect_equal(.create_StatisticalSummaryText(stats,
keywords = "mean"),
"mean = 5.5")
expect_equal(.create_StatisticalSummaryText(stats,
keywords = "unweighted$mean"),
"mean = 5.5")
expect_equal(.create_StatisticalSummaryText(stats,
keywords = "weighted$mean"),
"weighted$mean = 1.89")
# .unlist_RLum() ------------------------------------------------------------------------------
expect_length(Luminescence:::.unlist_RLum(list(a = list(b = list(c = list(d = 1, e = 2))))), 2)
# .rm_nonRLum() -----------------------------------------------------------
expect_type(
Luminescence:::.rm_nonRLum(c(list(set_RLum("RLum.Analysis"), set_RLum("RLum.Analysis")), 2)),
"list")
expect_type(
Luminescence:::.rm_nonRLum(
c(list(set_RLum("RLum.Analysis"), set_RLum("RLum.Analysis")), 2), class = "RLum.Analysis"),
"list")
# .rm_NULL_elements() -----------------------------------------------------------
expect_type(.rm_NULL_elements(list("a", NULL)),
"list")
t <- expect_type(.rm_NULL_elements(list(NULL, NULL)),
"list")
expect_length(t, 0)
# .matrix_binning() ---------------------------------------------------------------------------
m <- matrix(data = c(rep(1:20, each = 20)), ncol = 20, nrow = 20)
rownames(m) <- 1:nrow(m)
colnames(m) <- 1:ncol(m)
##crash the function
expect_error(Luminescence:::.matrix_binning("none matrix"),
"'m' should be of class 'matrix'")
##test operation modes and arguments
expect_type(Luminescence:::.matrix_binning(m, bin_size = 4, bin_col = FALSE), "integer")
expect_type(Luminescence:::.matrix_binning(m, bin_size = 4, bin_col = TRUE), "integer")
##test row / column renaming options
expect_type(Luminescence:::.matrix_binning(m, bin_size = 2, bin_col = FALSE, names = "groups"),
"integer")
expect_type(Luminescence:::.matrix_binning(m, bin_size = 2, bin_col = FALSE, names = "mean"),
"integer")
expect_type(Luminescence:::.matrix_binning(m, bin_size = 2, bin_col = FALSE, names = "sum"),
"integer")
expect_type(Luminescence:::.matrix_binning(m, bin_size = 2, bin_col = FALSE, names = c("test1", "test2")),
"integer")
##clean-up
rm(m)
# .download_file() --------------------------------------------------------
## returns just NULL (no URL detected)
expect_null(.download_file(url = "_url"))
## attempts download but fails
url.404 <- "https://raw.githubusercontent.com/R-Lum/rxylib/master/inst/extg"
expect_message(
expect_message(
expect_message(expect_null(.download_file(url = url.404)),
"URL detected:"),
"Attempting download ..."),
"FAILED")
## attempts download and succeeds
url.ok <- "https://raw.githubusercontent.com/R-Lum/rxylib/master/codecov.yml"
suppressMessages( # silence other messages already tested above
expect_message(expect_type(.download_file(url = url.ok),
"character"),
"OK")
)
# .get_named_list_element ------------------------------------------------
## create random named list element
l <- list(
a = list(x = 1:10),
b = list(x = 1:10)
)
t <- expect_type(.get_named_list_element(l, element = "x"), type = "list")
expect_equal(sum(unlist(t)), expected = 110)
## .throw_error() ---------------------------------------------------------
fun.int <- function() {
.set_function_name("fun.int")
on.exit(.unset_function_name(), add = TRUE)
.throw_error("Error message")
}
fun.ext <- function() fun.int()
fun.docall <- function() do.call(fun.ext, args = list())
fun.docall_do <- function() fun.docall()
expect_error(fun.int(),
"[fun.int()] Error message", fixed = TRUE)
expect_error(fun.ext(),
"[fun.int()] Error message", fixed = TRUE)
expect_error(fun.docall(),
"[fun.int()] Error message", fixed = TRUE)
expect_error(fun.docall_do(),
"[fun.int()] Error message", fixed = TRUE)
## .throw_warning() -------------------------------------------------------
fun.int <- function() {
.set_function_name("fun.int")
on.exit(.unset_function_name(), add = TRUE)
.throw_warning("Warning message")
}
fun.ext <- function() fun.int()
fun.docall <- function() do.call(fun.ext, args = list())
fun.docall_do <- function() fun.docall()
expect_warning(fun.int(),
"[fun.int()] Warning message", fixed = TRUE)
expect_warning(fun.ext(),
"[fun.int()] Warning message", fixed = TRUE)
expect_warning(fun.docall(),
"[fun.int()] Warning message", fixed = TRUE)
expect_warning(fun.docall_do(),
"[fun.int()] Warning message", fixed = TRUE)
## SW() ------------------------------------------------------------------
expect_silent(SW(cat("silenced message")))
expect_silent(SW(message("silenced message")))
expect_silent(SW(warning("silenced message")))
expect_silent(SW(.throw_warning("silenced message")))
expect_error(SW(stop("error message")),
"error message")
expect_error(SW(.throw_error("error message")),
"error message")
## .validate_args() -------------------------------------------------------
fun1 <- function(arg) {
.validate_args(arg, c("val1", "val2", "val3"), null.ok = TRUE)
}
expect_silent(fun1(NULL))
expect_equal(fun1(arg = "val1"), "val1")
expect_equal(fun1(arg = c("val1", "val2")), "val1")
expect_equal(fun1(arg = c("val3", "val2")), "val3")
expect_error(fun1(arg = c("error", "val1")),
"[test()] 'arg' contains multiple values but not all of them",
fixed = TRUE)
expect_error(fun1(arg = "error"),
"[test()] 'arg' should be one of 'val1', 'val2', 'val3' or NULL",
fixed = TRUE)
fun2 <- function(arg = c("val1", "val2", "val3")) {
.validate_args(arg, c("val1", "val2", "val3"), name = "other_name")
}
expect_equal(fun2(), "val1")
expect_error(fun2(arg = NULL),
"[test()] 'other_name' should be one of 'val1', 'val2' or 'val3'",
fixed = TRUE)
expect_error(fun2(arg = "error"),
"[test()] 'other_name' should be one of 'val1', 'val2' or 'val3'",
fixed = TRUE)
fun3 <- function(arg) {
.validate_args(arg, c("val1", "val2"),
extra = "'other.val'", null.ok = FALSE)
}
expect_error(fun3(arg = "error"),
"[test()] 'arg' should be one of 'val1', 'val2' or 'other.val'",
fixed = TRUE)
fun4 <- function(arg) {
.validate_args(arg, c("val1", "val2"),
extra = "'other.val'", null.ok = TRUE)
}
expect_error(fun4(arg = "error"),
"[test()] 'arg' should be one of 'val1', 'val2', 'other.val' or NULL",
fixed = TRUE)
fun.err <- function(arg) {
.validate_args(arg)
}
expect_error(fun.err("val1"),
"is missing, with no default")
## .validate_class() ------------------------------------------------------
fun1 <- function(arg) {
.validate_class(arg, "data.frame")
}
fun2 <- function(arg) {
.validate_class(arg, "data.frame", throw.error = FALSE)
}
expect_true(fun1(iris))
expect_true(.validate_class(iris, c("data.frame", "integer")))
expect_true(.validate_class(iris, c("data.frame", "integer"),
throw.error = FALSE))
expect_warning(expect_false(.validate_class(arg <- NULL, "data.frame",
throw.error = FALSE)),
"'arg' should be of class 'data.frame'")
expect_error(fun1(),
"'arg' should be of class 'data.frame'")
expect_error(fun1(NULL),
"'arg' should be of class 'data.frame'")
expect_error(.validate_class(test <- 1:5),
"is missing, with no default")
expect_error(.validate_class(test <- 1:5, "data.frame"),
"'test' should be of class 'data.frame'")
expect_error(.validate_class(test <- 1:5, c("list", "data.frame", "numeric")),
"'test' should be of class 'list', 'data.frame' or 'numeric'")
expect_error(.validate_class(test <- 1:5, c("list", "data.frame")),
"'test' should be of class 'list' or 'data.frame'")
expect_error(.validate_class(test <- 1:5, c("list", "data.frame"),
extra = "another type"),
"'test' should be of class 'list', 'data.frame' or another")
expect_error(.validate_class(test <- 1:5, c("list", "data.frame"),
name = "'other_name'"),
"'other_name' should be of class 'list' or 'data.frame'")
expect_warning(fun2(),
"'arg' should be of class 'data.frame'")
## .validate_not_empty() --------------------------------------------------
expect_true(.validate_not_empty(letters, "vector"))
expect_error(.validate_not_empty(test <- c(), "vector"),
"'test' cannot be an empty vector")
expect_error(.validate_not_empty(test <- list()),
"'test' cannot be an empty list")
expect_error(.validate_not_empty(test <- numeric(0)),
"'test' cannot be an empty numeric")
expect_error(.validate_not_empty(test <- data.frame()),
"'test' cannot be an empty data.frame")
expect_error(.validate_not_empty(iris[0, ]),
"'iris' cannot be an empty data.frame")
expect_error(.validate_not_empty(iris[, 0]),
"'iris' cannot be an empty data.frame")
expect_error(.validate_not_empty(test <- matrix(NA, 0, 5)),
"'test' cannot be an empty matrix")
expect_error(.validate_not_empty(test <- matrix(NA, 5, 0)),
"'test' cannot be an empty matrix")
expect_error(.validate_not_empty(test <- set_RLum("RLum.Analysis")),
"'test' cannot be an empty RLum.Analysis")
expect_error(.validate_not_empty(list(), "list", name = "'other_name'"),
"'other_name' cannot be an empty list")
expect_warning(expect_false(.validate_not_empty(test <- list(), "list",
throw.error = FALSE)),
"'test' cannot be an empty list")
## .validate_length() -----------------------------------------------------
expect_true(.validate_length(letters, 26))
expect_error(.validate_length(letters),
"is missing, with no default")
expect_error(.validate_length(letters, 25),
"'letters' should have length 25")
expect_error(.validate_length(letters, 25, name = "'other_name'"),
"'other_name' should have length 25")
expect_warning(expect_false(.validate_length(letters, 25, throw.error = FALSE)),
"'letters' should have length 25")
## .validate_positive_scalar() --------------------------------------------
expect_silent(.validate_positive_scalar(int = TRUE))
expect_silent(.validate_positive_scalar(1.3))
expect_silent(.validate_positive_scalar(2, int = TRUE))
expect_silent(.validate_positive_scalar(NULL, int = TRUE, null.ok = TRUE))
expect_error(.validate_positive_scalar(test <- "a"),
"'test' should be a positive scalar")
expect_error(.validate_positive_scalar(test <- NULL),
"'test' should be a positive scalar")
expect_error(.validate_positive_scalar(iris),
"'iris' should be a positive scalar")
expect_error(.validate_positive_scalar(1:2, name = "'var'"),
"'var' should be a positive scalar")
expect_error(.validate_positive_scalar(0, name = "'var'"),
"'var' should be a positive scalar")
expect_error(.validate_positive_scalar(-1, name = "'var'"),
"'var' should be a positive scalar")
expect_error(.validate_positive_scalar(1.5, int = TRUE, name = "'var'"),
"'var' should be a positive integer")
expect_error(.validate_positive_scalar(NA, int = TRUE, name = "The variable"),
"The variable should be a positive integer")
## .validate_logical_scalar() ---------------------------------------------
expect_silent(.validate_logical_scalar())
expect_silent(.validate_logical_scalar(TRUE))
expect_silent(.validate_logical_scalar(FALSE))
expect_silent(.validate_logical_scalar(NULL, null.ok = TRUE))
expect_error(.validate_logical_scalar(test <- "a"),
"'test' should be a single logical value")
expect_error(.validate_logical_scalar(test <- NULL),
"'test' should be a single logical value")
expect_error(.validate_logical_scalar(iris),
"'iris' should be a single logical value")
expect_error(.validate_logical_scalar(c(TRUE, FALSE), name = "'var'"),
"'var' should be a single logical value")
expect_error(.validate_logical_scalar(0, name = "'var'"),
"'var' should be a single logical value")
expect_error(.validate_logical_scalar(NA, name = "The variable"),
"The variable should be a single logical value")
## .require_suggested_package() -------------------------------------------
expect_true(.require_suggested_package("utils"))
expect_error(.require_suggested_package("error"),
"This function requires the 'error' package: to install it")
expect_error(.require_suggested_package("error",
reason = "Reporting a good error"),
"Reporting a good error requires the 'error' package")
expect_warning(
expect_false(.require_suggested_package("error", throw.error = FALSE),
"This function requires the 'error' package: to install it"))
## .listify() -------------------------------------------------------------
expect_equal(.listify(1, length = 3),
list(1, 1, 1))
expect_equal(.listify(letters, length = 5),
.listify(list(letters), length = 5))
## .collapse() ------------------------------------------------------------
expect_equal(.collapse(1:3),
"'1', '2', '3'")
expect_equal(.collapse(1:3, quote = FALSE),
"1, 2, 3")
expect_equal(.collapse(NULL), "")
## .shorten_filename() ----------------------------------------------------
expect_equal(.shorten_filename("/path/to/filename"),
"/path/to/filename")
expect_equal(.shorten_filename("/path/to/a_somewhat_longer_filename",
max.width = 27),
"/path/…what_longer_filename")
## C++ code ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
##
# src_create_RLumDataCurve_matrix -------------------------------------------------------------
##RLum.Data.Curve() ... test src_create_RLumDataCurve_matrix()
expect_output(
Luminescence:::src_create_RLumDataCurve_matrix(
DATA = 1:100,
VERSION = 4,
NPOINTS = 100,
LTYPE = "TL",
LOW = 0,
HIGH = 500,
AN_TEMP = 0,
TOLDELAY = 0,
TOLON = 0,
TOLOFF = 0
)
)
## cover NA case
expect_type(
Luminescence:::src_create_RLumDataCurve_matrix(
DATA = 1:100,
VERSION = 4,
NPOINTS = 0,
LTYPE = "OSL",
LOW = 0,
HIGH = 500,
AN_TEMP = 0,
TOLDELAY = 0,
TOLON = 0,
TOLOFF = 0), type = "double")
## case for a delayed hit ramp start
expect_type(
Luminescence:::src_create_RLumDataCurve_matrix(
DATA = 1:100,
VERSION = 4,
NPOINTS = 0,
LTYPE = "OSL",
LOW = 0,
HIGH = 500,
AN_TEMP = 0,
TOLDELAY = 10,
TOLON = 0,
TOLOFF = 0), type = "double")
## case for a delayed hit ramp start
expect_type(
Luminescence:::src_create_RLumDataCurve_matrix(
DATA = 1:100,
VERSION = 4,
NPOINTS = 0,
LTYPE = "OSL",
LOW = 0,
HIGH = 500,
AN_TEMP = 100,
TOLDELAY = 0,
TOLON = 0,
TOLOFF = 0), type = "double")
## generate strange curve and more tests
expect_type(Luminescence:::src_create_RLumDataCurve_matrix(
DATA = 1:100,
VERSION = 4,
NPOINTS = 100,
LTYPE = "TL",
LOW = 0,
HIGH = 500,
AN_TEMP = 200,
TOLDELAY = 10,
TOLON = 10,
TOLOFF = 400), type = "double")
})
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