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## SANITIZING FUNCTIONS
## Checking the class of an object and returning an error message if != class
check.class <- function(object, class, msg, errorif = FALSE, report) {
## Get call
match_call <- match.call()
## class_object variable initialisation
class_object <- class(object)[1]
## class_length variable initialisation
length_class <- length(class)
## Get the report argument
if(missing(report)) {
report <- 1:length_class
}
## Set msg if missing
if(missing(msg)) {
if(length_class != 1) {
msg <- paste(" must be of class ", paste(class[report], collapse = " or "), ".", sep = "")
} else {
msg <- paste(" must be of class ", class, ".", sep = "")
}
}
## check if object is class.
if(length_class != 1) {
## check if object is class in a cascade (class[1] else class[2] else class[3], etc..)
## returns error only if object is not of any class
error <- NULL
for(counter in 1:length_class) {
if(errorif != TRUE) {
if(class_object != class[counter]) {
error <- c(error, TRUE)
} else {
error <- c(error, FALSE)
}
} else {
if(class_object == class[counter]) {
error <- c(error, TRUE)
} else {
error <- c(error, FALSE)
}
}
}
## If function did not return, class is not matching
if(!any(!error)) {
stop(match_call$object, msg, call. = FALSE)
} else {
return(class_object)
}
} else {
if(errorif != TRUE) {
if(class_object != class) {
stop(match_call$object, msg , call. = FALSE)
}
} else {
if(class_object == class) {
stop(match_call$object, msg , call. = FALSE)
}
}
}
}
## Checking the class of an object and returning an error message if != class
check.length <- function(object, length, msg, errorif = FALSE) {
match_call <- match.call()
if(errorif != TRUE) {
if(length(object) != length) {
stop(match_call$object, msg , call. = FALSE)
}
} else {
if(length(object) == length) {
stop(match_call$object, msg , call. = FALSE)
}
}
}
## Checking if a method matches the authorized method
check.method <- function(argument, all_arguments, msg, condition = all) {
if(condition(is.na(match(argument, all_arguments)))) {
stop(paste(msg, " must be one of the following: ", paste(all_arguments, collapse = ", "), ".", sep = ""), call. = FALSE)
}
}
## Checking if a matrix is a distance matrix
check.dist.matrix <- function(matrix, method, just.check = FALSE, ...) {
## Is distance
was_dist <- FALSE
## Check if distance
if(is(matrix, "dist")) {
return(list(matrix, "was_dist" = TRUE))
}
## Is the matrix square?
if(dim(matrix)[1] == dim(matrix)[2] &&
all(diag(as.matrix(matrix)) == 0) &&
all(matrix[upper.tri(matrix)] == matrix[rev(lower.tri(matrix))], na.rm = TRUE)) {
## It was a distance matrix!
was_dist <- TRUE
}
if(just.check) {
## Simply return the check
return(was_dist)
} else {
## Return a matrix
if(was_dist) {
return(list(stats::as.dist(matrix), "was_dist" = TRUE))
} else {
return(list(vegan::vegdist(matrix, method = method, ...), "was_dist" = FALSE))
}
}
}
## Stop with call message wrapper function
stop.call <- function(call, msg, msg.pre = "") {
stop(paste0(msg.pre, as.expression(call), msg), call. = FALSE)
}
## Check through a list
check.list <- function(list, check.fun, condition, ...) {
## Run the checks
check_results <- lapply(list, check.fun, ...)
## Apply the condition
if(!missing(condition)) {
return(unlist(lapply(check_results, condition)))
} else {
return(unlist(check_results))
}
}
## Function for test results with rounding
expect_equal_round <- function(x, y, digits) {
testthat::expect_equal(round(x, digits), round(y, digits))
}
## Function for automatically add rownames (used in both branches below)
add.rownames <- function(x) {
rownames(x) <- seq(1:nrow(x))
return(x)
}
## Checks whether the data is a matrix or a list
check.data <- function(data, match_call) {
## Multi toggle
is_multi <- FALSE
## Check class
data_class <- check.class(data, c("matrix", "data.frame", "list"))
## If data.frame, change to matrix
if(data_class == "data.frame") {
data <- as.matrix(data)
}
## Adding rownames
row_warning <- paste0("Row names have been automatically added to ", as.expression(match_call$data), ".")
## Switch between cases
if(data_class == "list") {
## Error message
is_error <- " must be matrix or a list of matrices with the same dimensions and unique row names."
## Check the classes
all_classes <- unique(unlist(lapply(data, class)))
if(!all(all_classes %in% c("matrix", "array"))) {
stop.call(match_call$data, is_error)
}
## Check the columns
if(length(unique(unlist(lapply(data, ncol)))) > 1) {
stop.call(match_call$data, is_error)
}
## Check the rownames
if(is.null(unlist(lapply(data, rownames)))) {
## If no rownames, add them
data <- lapply(data, add.rownames)
warning(row_warning)
}
## Find the rows that are not in common between matrices
rows <- unique(unlist(lapply(data, rownames)))
unmatch <- unlist(lapply(data, function(x, rows) return(rows[!rows %in% rownames(x)]), rows = rows))
if(length(unmatch) > 0) {
## Warning rows
warning(paste0("The following elements are not present in all matrices: ", paste0(unmatch, collapse = ", "), ". The matrices will be treated as separate trait-spaces."), call. = FALSE)
## Toggle multi
is_multi <- TRUE
} else {
## Reorder the rows to match the first matrix
data <- lapply(data, function(x, order) x[order, , drop = FALSE], order = rownames(data[[1]]))
}
} else {
## Eventually add rownames
if(is.null(rownames(data))) {
data <- add.rownames(data)
warning(row_warning)
}
data <- list(data)
}
return(list(matrix = data, multi = is_multi))
}
## Checks whether the tree is in the correct format
check.tree <- function(tree, data, bind.trees = FALSE, match_call) {
## multi toggle
is_multi <- FALSE
## Check class
tree_class <- check.class(tree, c("phylo", "multiPhylo"))
## Convert into a list (not multiPhylo if it's a single tree)
if(tree_class == "phylo") {
tree <- list(tree)
class(tree) <- "multiPhylo"
}
## Bind tree auto-toggle
if(length(tree) != 1 && (length(tree) == length(data$matrix))) {
bind.trees <- TRUE
}
## Inc.nodes toggle
inc.nodes <- unique(unlist(lapply(tree, function(x) !is.null(x$node.label))))
if(length(inc.nodes) > 1) {
stop("All trees should have node labels or no node labels.", call. = FALSE)
}
## Double check the inc.nodes
if(inc.nodes) {
## ignore node labels if no overlap
inc.nodes <- any(unlist(mapply(function(x, y) any(rownames(x) %in% y$node.label), data$matrix, tree, SIMPLIFY = FALSE)))
}
## Make the data into "dispRity" format for testing
if(!missing(data) && is.array(data) || is.null(names(data))) {
if(!is(data, "dispRity")) {
data <- list(matrix = list(data))
}
}
## Match with the data
if(!missing(data) && !is.null(data$matrix[[1]])) {
## Match the data and the trees?
pass.fun <- function(cleaned) return(!all(is.na(cleaned$dropped_tips), is.na(cleaned$dropped_rows)))
if(!bind.trees) {
if(length(tree) != length(data$matrix)) {
## Check multi trees
dropped <- check.multi.tree(tree, data, inc.nodes)
## Toggle multi
is_multi <- !all(unlist(lapply(tree, function(x, y) all(c(x$node.label, x$tip.label) %in% c(y$node.label, y$tip.label)), y = tree[[1]])))
if(length(dropped) > 0) {
## Warning
warning(paste0("The following elements are not present in all trees: ", paste0(dropped, collapse = ", "), ". Some analyses downstream might not work because of this (you can use ?clean.data to match both data and tree if needed)."), call. = FALSE)
}
## Done for here
return(list(tree = tree, multi = is_multi))
} else {
## Normal cleaning check
options(warn = -1)
cleanings <- lapply(data$matrix, clean.data, tree, inc.nodes = inc.nodes)
options(warn = 0)
}
} else {
if(length(tree) != length(data$matrix)) {
stop("The number of matrices and trees must be the same to bind them.", call. = FALSE)
}
## Clean
cleanings <- mapply(clean.data, data$matrix, tree, MoreArgs = list(inc.nodes = inc.nodes), SIMPLIFY = FALSE)
}
if(any(not_pass <- unlist(lapply(cleanings, pass.fun)))) {
## Stop!
stop("The data is not matching the tree labels (you can use ?clean.data to match both data and tree).", call. = FALSE)
}
}
return(list(tree = tree, multi = is_multi))
}
## Check the match between multiple trees and data
check.multi.tree <- function(tree, data, inc.nodes) {
## Get all the labels from the matrices and make a dummy one
all_elements <- unique(unlist(lapply(data$matrix, rownames)))
dummy_data <- matrix(1, nrow = length(all_elements), dimnames = list(all_elements))
## Make a dummy matrix with these
cleanings <- lapply(tree, function(tree, data, inc.nodes) clean.data(data, tree, inc.nodes), data = dummy_data, inc.nodes = inc.nodes)
dropped <- unique(unlist(lapply(cleanings, function(x) return(c(x$dropped_rows, x$dropped_tips)))))
if(any(is.na(dropped))) {
dropped <- dropped[-which(is.na(dropped))]
}
return(dropped)
}
## Wrapper function for checking the data
check.dispRity.data <- function(data = NULL, tree = NULL, bind.trees = FALSE, returns = c("matrix", "tree", "multi")) {
match_call <- match.call()
is_multi <- FALSE
## Checking the data
if(!is.null(data) && !is(data, "dispRity")) {
data <- check.data(data, match_call)
is_multi <- any(is_multi, data$multi)
data$multi <- NULL
}
## Checking the tree
if(!is.null(tree)) {
tree <- check.tree(tree, data, bind.trees, match_call)
is_multi <- any(is_multi, tree$multi)
}
## Sort the output
output <- list()
if("matrix" %in% returns) {
output$matrix <- data$matrix
}
if("tree" %in% returns) {
output$tree <- tree$tree
}
if("multi" %in% returns) {
output$multi <- is_multi
}
## Output
if(length(returns) == 1) {
return(output[[1]])
} else {
return(output)
}
}
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