cute_little_R_functions.R 568 KB
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row.name <- dimnames(data1)[[1]]
}
# row names
any.id.row.name <- FALSE
if(any(dimnames(data1)[[1]] %in% dimnames(data2)[[1]])){
any.id.row.name <- TRUE
same.row.name.pos1 <- which(dimnames(data1)[[1]] %in% dimnames(data2)[[1]])
}
if(any(dimnames(data2)[[1]] %in% dimnames(data1)[[1]])){
any.id.row.name <- TRUE
same.row.name.pos2 <- which(dimnames(data2)[[1]] %in% dimnames(data1)[[1]])
}
if(any.id.row.name == TRUE){
common.row.names <- unique(c(dimnames(data1)[[1]][same.row.name.pos1], dimnames(data2)[[1]][same.row.name.pos2]))
}
# col names
any.id.col.name <- FALSE
if(any(dimnames(data1)[[2]] %in% dimnames(data2)[[2]])){
any.id.col.name <- TRUE
same.col.name.pos1 <- which(dimnames(data1)[[2]] %in% dimnames(data2)[[2]])
}
if(any(dimnames(data2)[[2]] %in% dimnames(data1)[[2]])){
any.id.col.name <- TRUE
same.col.name.pos2 <- which(dimnames(data2)[[2]] %in% dimnames(data1)[[2]])
}
if(any.id.col.name == TRUE){
common.col.names <- unique(c(dimnames(data1)[[2]][same.col.name.pos1], dimnames(data2)[[2]][same.col.name.pos2]))
}
if( ! identical(dimnames(data1)[[2]], dimnames(data2)[[2]])){
same.col.name <- FALSE
# col names remain NULL
}else{
same.col.name <- TRUE
col.name <- dimnames(data1)[[2]]
}
}
# identical row and col content
if(all(class(data1) == "table")){
as.data.frame(matrix(data1, ncol = ncol(data1)), stringsAsFactors = FALSE)
}else if(all(class(data1) == "matrix")){
data1 <- as.data.frame(data1, stringsAsFactors = FALSE)
}else if(all(class(data1) == "data.frame")){
data1 <- data.frame(lapply(data1, as.character), stringsAsFactors=FALSE)
}
if(all(class(data2) == "table")){
as.data.frame(matrix(data2, ncol = ncol(data2)), stringsAsFactors = FALSE)
}else if(all(class(data2) == "matrix")){
data2 <- as.data.frame(data2, stringsAsFactors = FALSE)
}else if(all(class(data2) == "data.frame")){
data2 <- data.frame(lapply(data2, as.character), stringsAsFactors=FALSE)
}
row.names(data1) <- paste0("A", 1:nrow(data1))
row.names(data2) <- paste0("A", 1:nrow(data2))
if(same.col.nb == TRUE){ # because if not the same col nb, the row cannot be identical
same.row.pos1 <- which(c(as.data.frame(t(data1), stringsAsFactors = FALSE)) %in% c(as.data.frame(t(data2), stringsAsFactors = FALSE)))
same.row.pos2 <- which(c(as.data.frame(t(data2), stringsAsFactors = FALSE)) %in% c(as.data.frame(t(data1), stringsAsFactors = FALSE)))
names(same.row.pos1) <- NULL
names(same.row.pos2) <- NULL
if(all(is.na(same.row.pos1))){
same.row.pos1 <- NULL
}else{
same.row.pos1 <- same.row.pos1[ ! is.na(same.row.pos1)]
any.id.row <- TRUE
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}
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if(all(is.na(same.row.pos2))){
same.row.pos2 <- NULL
}else{
same.row.pos2 <- same.row.pos2[ ! is.na(same.row.pos2)]
any.id.row <- TRUE
}
if(is.null(same.row.pos1) & is.null(same.row.pos2)){
any.id.row <- FALSE
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}
}else{
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any.id.row <- FALSE
# same.row.pos1 and 2 remain NULL
}
if(same.row.nb == TRUE){ # because if not the same row nb, the col cannot be identical
same.col.pos1 <- which(c(data1) %in% c(data2))
same.col.pos2 <- which(c(data2) %in% c(data1))
names(same.col.pos1) <- NULL
names(same.col.pos2) <- NULL
if(all(is.na(same.col.pos1))){
same.col.pos1 <- NULL
}else{
same.col.pos1 <- same.col.pos1[ ! is.na(same.col.pos1)]
any.id.col <- TRUE
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if(all(is.na(same.col.pos2))){
same.col.pos2 <- NULL
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same.col.pos2 <- same.col.pos2[ ! is.na(same.col.pos2)]
any.id.col <- TRUE
}
if(is.null(same.col.pos1) & is.null(same.col.pos2)){
any.id.col <- FALSE
}
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}else{
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any.id.col <- FALSE
# same.col.pos1 and 2 remain NULL
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}
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if(same.dim == TRUE & ! all(is.null(same.row.pos1), is.null(same.row.pos2), is.null(same.col.pos1), is.null(same.col.pos2))){ # same.dim == TRUE means that same.row.nb == TRUE and same.col.nb == TRUE, meaning that row.nb != NULL and col.nb != NULL. Thus, no need to include these checkings
if(identical(same.row.pos1, 1:row.nb) & identical(same.row.pos2, 1:row.nb) & identical(same.col.pos1, 1:col.nb) & identical(same.col.pos2, 1:col.nb)){
identical.content <- TRUE
}else{
identical.content <- FALSE
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}
}else{
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identical.content <- FALSE
}
}
output <- list(same.class = same.class, class = class, same.dim = same.dim, dim = dim, same.row.nb = same.row.nb, row.nb = row.nb, same.col.nb = same.col.nb , col.nb = col.nb, same.row.name = same.row.name, row.name = row.name, any.id.row.name = any.id.row.name, same.row.name.pos1 = same.row.name.pos1, same.row.name.pos2 = same.row.name.pos2, common.row.names = common.row.names, same.col.name = same.col.name, col.name = col.name,any.id.col.name = any.id.col.name, same.col.name.pos1 = same.col.name.pos1, same.col.name.pos2 = same.col.name.pos2, common.col.names = common.col.names, any.id.row = any.id.row, same.row.pos1 = same.row.pos1, same.row.pos2 = same.row.pos2, any.id.col = any.id.col, same.col.pos1 = same.col.pos1, same.col.pos2 = same.col.pos2, identical.object = identical.object, identical.content = identical.content)
return(output)
}


######## fun_comp_list() #### comparison of two lists


# Check OK: clear to go Apollo
fun_comp_list <- function(data1, data2){
# AIM
# compare two lists. Check and report in a list if the 2 datasets have:
# same length
# common names
# common compartments
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# none
# ARGUMENTS
# data1: list
# data2: list
# RETURN
# a list containing:
# $same.length: logical. Are number of elements identical?
# $length: number of elements in the 2 datasets (NULL otherwise)
# $same.name: logical. Are element names identical ?
# $name: name of elements of the 2 datasets if identical (NULL otherwise)
# $any.id.name: logical. Is there any element names identical ?
# $same.name.pos1: position, in data1, of the element names identical in data2
# $same.name.pos2: position, in data2, of the compartment names identical in data1
# $any.id.compartment: logical. is there any identical compartments ?
# $same.compartment.pos1: position, in data1, of the compartments identical in data2
# $same.compartment.pos2: position, in data2, of the compartments identical in data1
# $identical.object: logical. Are objects identical (kind of object, compartment names and content)?
# $identical.content: logical. Are content objects identical (identical compartments excluding compartment names)?
# EXAMPLES
# obs1 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) ; obs2 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) ; fun_comp_list(obs1, obs2)
# obs1 = list(1:5, LETTERS[1:2]) ; obs2 = list(a = 1:5, b = LETTERS[1:2]) ; fun_comp_list(obs1, obs2)
# obs1 = list(b = 1:5, c = LETTERS[1:2]) ; obs2 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) ; fun_comp_list(obs1, obs2)
# obs1 = list(b = 1:5, c = LETTERS[1:2]) ; obs2 = list(LETTERS[5:9], matrix(1:6), 1:5) ; fun_comp_list(obs1, obs2)
# DEBUGGING
# data1 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) ; data2 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) # for function debugging
# data1 = list(a = 1:5, b = LETTERS[1:2]) ; data2 = list(a = 1:5, b = LETTERS[1:2], d = matrix(1:6)) # for function debugging
# function name
function.name <- paste0(as.list(match.call(expand.dots=FALSE))[[1]], "()")
# end function name
# argument checking
if( ! any(class(data1) %in% "list")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 ARGUMENT MUST BE A LIST\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
if( ! any(class(data2) %in% "list")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data2 ARGUMENT MUST BE A LIST\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
# source("C:/Users/Gael/Documents/Git_versions_to_use/debugging_tools_for_r_dev-v1.2/r_debugging_tools-v1.2.R") ; eval(parse(text = str_basic_arg_check_dev)) # activate this line and use the function to check arguments status
# end argument checking
# main code
same.length <- NULL
length <- NULL
same.name <- NULL
name <- NULL
any.id.name <- NULL
same.name.pos1 <- NULL
same.name.pos2 <- NULL
any.id.compartment <- NULL
same.compartment.pos1 <- NULL
same.compartment.pos2 <- NULL
identical.object <- NULL
identical.content <- NULL
if(identical(data1, data2)){
same.length <- TRUE
length <- length(data1)
if( ! is.null(names(data1))){
same.name <- TRUE
name <- names(data1)
any.id.name <- TRUE
same.name.pos1 <- 1:length(data1)
same.name.pos2 <- 1:length(data2)
}
any.id.compartment <- TRUE
same.compartment.pos1 <- 1:length(data1)
same.compartment.pos2 <- 1:length(data2)
identical.object <- TRUE
identical.content <- TRUE
}else{
identical.object <- FALSE
if( ! identical(length(data1), length(data2))){
same.length<- FALSE
}else{
same.length<- TRUE
length <- length(data1)
}
if( ! (is.null(names(data1)) & is.null(names(data2)))){
if( ! identical(names(data1), names(data2))){
same.name <- FALSE
}else{
same.name <- TRUE
name <- names(data1)
}
any.id.name <- FALSE
if(any(names(data1) %in% names(data2))){
any.id.name <- TRUE
same.name.pos1 <- which(names(data1) %in% names(data2))
}
if(any(names(data2) %in% names(data1))){
any.id.name <- TRUE
same.name.pos2 <- which(names(data2) %in% names(data1))
}
}
names(data1) <- NULL
names(data2) <- NULL
any.id.compartment <- FALSE
if(any(data1 %in% data2)){
any.id.compartment <- TRUE
same.compartment.pos1 <- which(data1 %in% data2)
}
if(any(data2 %in% data1)){
any.id.compartment <- TRUE
same.compartment.pos2 <- which(data2 %in% data1)
}
if(same.length == TRUE & ! all(is.null(same.compartment.pos1), is.null(same.compartment.pos2))){
if(identical(same.compartment.pos1, same.compartment.pos2)){
identical.content <- TRUE
}else{
identical.content <- FALSE
}
}else{
identical.content <- FALSE
}
}
output <- list(same.length = same.length, length = length, same.name = same.name, name = name, any.id.name = any.id.name, same.name.pos1 = same.name.pos1, same.name.pos2 = same.name.pos2, any.id.compartment = any.id.compartment, same.compartment.pos1 = same.compartment.pos1, same.compartment.pos2 = same.compartment.pos2, identical.object = identical.object, identical.content = identical.content)
return(output)
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}


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######## fun_test() #### test combinations of argument values of a function
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# add traceback https://stackoverflow.com/questions/47414119/how-to-read-a-traceback-in-r

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# Check OK: clear to go Apollo
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tempo    
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fun_test <- function(fun, arg, val, expect.error = NULL, thread.nb = NULL, print.count = 10, plot.fun = FALSE, export = FALSE, res.path = NULL, lib.path = NULL, cute.path = "C:\\Users\\Gael\\Documents\\Git_projects\\cute_little_R_functions\\cute_little_R_functions.R"){
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# AIM
# test combinations of argument values of a function
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# WARNING
# Limited to 43 arguments with at least 2 values each. The total number of arguments tested can be more if the additional arguments have a single value. The limit is due to nested "for" loops (https://stat.ethz.ch/pipermail/r-help/2008-March/157341.html), but it should not be a problem since the number of tests would be 2^43 > 8e12
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# ARGUMENTS
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# fun: character string indicating the name of the function tested (without brackets)
# arg: vector of character strings of arguments of fun. At least arguments that do not have default values must be present in this vector
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# val: list with number of compartments equal to length of arg, each compartment containing values of the corresponding argument in arg. Each different value must be in a list or in a vector. For instance, argument 3 in arg is a logical argument (values accepted TRUE, FALSE, NA). Thus, compartment 3 of val can be either list(TRUE, FALSE, NA), or c(TRUE, FALSE, NA)
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# expect.error: list of exactly the same structure as val argument, but containing FALSE or TRUE, depending on whether error is expected (TRUE) or not (FALSE) for each corresponding value of val. A message is returned depending on discrepancies between the expected and observed errors. Ignored if NULL
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# thread.nb: numeric value indicating the number of available threads. Write NULL if no parallelization wanted
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# print.count: interger value. Print a working progress message every print.count during loops. BEWARE: can increase substentially the time to complete the process using a small value, like 10 for instance. Use Inf is no loop message desired
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# plot.fun: logical. Plot the plotting function tested for each test?
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# export: logical. Export the results into a .RData file and into a .txt file? If FALSE, return a list into the console (see below). BEWARE: will be automatically set to TRUE if thread.nb is not NULL. This means that when using parallelization, the results are systematically exported, not returned into the console
# res.path: character string indicating the absolute pathway of folder where the txt results and pdfs, containing all the plots, will be saved. Several txt and pdf, one per thread, if parallelization. Ignored if export is FALSE. Must be specified if thread.nb is not NULL or if export is TRUE
# lib.path: character string indicating the absolute path of the required packages, if not in the default folders
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# cute.path: character string indicating the absolute path of the cute.R file. Will be remove when cute will be a package. Not considered if thread.nb is NULL
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# REQUIRED PACKAGES
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# lubridate
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# parallel if thread.nb argument is not NULL
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# if the tested function is in a package, this package must be imported first (no parallelization) or must be in the classical R package folder indicated by the lib.path argument (parallelization)
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# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_check()
# fun_get_message()
# fun_pack()
# RETURN
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# if export is FALSE a list containing:
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# $fun: the tested function
# $data: a data frame of all the combination tested, containing the following columns:
# the different values tested, named by arguments
# $kind: a vector of character strings indicating the kind of test result: either "ERROR", or "WARNING", or "OK"
# $problem: a logical vector indicating if error or not
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# $expected.error: optional logical vector indicating the expected error specified in the expect.error argument
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# $message: either NULL if $kind is always "OK", or the messages
# $instruction: the initial instruction
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# $sys.info: system and packages info
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# if export is TRUE 1) the same list object into a .RData file, 2) also the $data data frame into a .txt file, and 3) if expect.error is non NULL and if any discrepancy, the $data data frame into a .txt file but containing only the rows with discrepancies between expected and observed errors
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# one or several pdf if a plotting function is tested and if the plot.fun argument is TRUE
# EXAMPLES
# fun_test(fun = "unique", arg = c("x", "incomparables"), val = list(x = list(1:10, c(1,1,2,8), NA), incomparable = c(TRUE, FALSE, NA)))
# fun_test(fun = "fun_round", arg = c("data", "dec.nb", "after.lead.zero"), val = list(L1 = list(c(1, 1.0002256, 1.23568), "a", NA), L2 = list(2, c(1,3), NA), L3 = c(TRUE, FALSE, NA)))
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# fun_test(fun = "plot", arg = c("x", "y"), val = list(x = list(1:10, 12:13, NA, (1:10)^2), y = list(1:10, NA, NA)),  expect.error = list(x = list(FALSE, TRUE, TRUE, FALSE), y = list(FALSE, TRUE, TRUE)), thread.nb = NULL, plot.fun = TRUE, res.path = "C:\\Users\\Gael\\Desktop\\", lib.path = NULL)
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# fun_test(fun = "plot", arg = c("x", "y"), val = list(x = list(1:10, 12:13, NA, (1:10)^2), y = list(1:10, NA, NA)), thread.nb = 4, plot.fun = TRUE, res.path = "C:\\Users\\Gael\\Desktop\\", lib.path = "C:\\Program Files\\R\\R-3.6.1\\library\\")
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# set.seed(1) ; obs1 <- data.frame(Time = c(rnorm(10), rnorm(10) + 2), Group1 = rep(c("G", "H"), each = 10)) ; fun_test(fun = "fun_gg_boxplot", arg = c("data1", "y", "categ"), val = list(L1 = list(L1 = obs1), L2 = list(L1 = "Time"), L3 = list(L1 = "Group1")))
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# set.seed(1) ; obs1 <- data.frame(Time = c(rnorm(10), rnorm(10) + 2), Group1 = rep(c("G", "H"), each = 10)) ; fun_test(fun = "fun_gg_boxplot", arg = c("data1", "y", "categ"), val = list(L1 = list(obs1), L2 = "Time", L3 = "Group1"), thread.nb = NULL, plot.fun = TRUE, res.path = "C:\\Users\\Gael\\Desktop\\", lib.path = "C:\\Program Files\\R\\R-3.6.1\\library\\")
# library(ggplot2) ; fun_test(fun = "geom_histogram", arg = c("data", "mapping"), val = list(x = list(data.frame(X = "a")), y = list(ggplot2::aes(x = X))), thread.nb = NULL, plot.fun = TRUE, res.path = "C:\\Users\\Gael\\Desktop\\", lib.path = "C:\\Program Files\\R\\R-3.6.1\\library\\") # BEWARE: ggplot2::geom_histogram does not work
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# DEBUGGING
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# fun = "unique" ; arg = "x" ; val = list(x = list(1:10, c(1,1,2,8), NA)) ; expect.error = list(x = list(FALSE, FALSE, TRUE)) ; thread.nb = NULL ; plot.fun = FALSE ; export = FALSE ; res.path = "C:\\Users\\Gael\\Desktop\\" ; lib.path = NULL ; print.count = 1 ; cute.path = "C:\\Users\\Gael\\Documents\\Git_projects\\cute_little_R_functions\\cute_little_R_functions.R" # for function debugging
# fun = "unique" ; arg = c("x", "incomparables") ; val = list(x = list(1:10, c(1,1,2,8), NA), incomparable = c(TRUE, FALSE, NA)) ; expect.error = NULL ; thread.nb = 2 ; plot.fun = FALSE ; export = TRUE ; res.path = "C:\\Users\\Gael\\Desktop\\" ; lib.path = NULL ; print.count = 10 ; cute.path = "C:\\Users\\Gael\\Documents\\Git_projects\\cute_little_R_functions\\cute_little_R_functions.R" # for function debugging
# fun = "plot" ; arg = c("x", "y") ; val = list(x = list(1:10, 12:13, NA), y = list(1:10, NA, NA)) ; expect.error = list(x = list(FALSE, FALSE, TRUE, FALSE), y = list(FALSE, TRUE, TRUE)) ; print.count = 10 ; thread.nb = NULL ; plot.fun = TRUE ; export = TRUE ; res.path = "C:\\Users\\Gael\\Desktop\\" ; lib.path = NULL # for function debugging
# set.seed(1) ; obs1 <- data.frame(Time = c(rnorm(10), rnorm(10) + 2), Group1 = rep(c("G", "H"), each = 10)) ; fun = "fun_gg_boxplot" ; arg = c("data1", "y", "categ") ; val = list(L1 = list(L1 = obs1), L2 = list(L1 = "Time"), L3 = list(L1 = "Group1")) ; expect.error = NULL ; print.count = 10 ; thread.nb = NULL ; plot.fun = TRUE ; export = TRUE ; res.path = "C:\\Users\\Gael\\Desktop\\" ; lib.path = NULL # for function debugging
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# function name
function.name <- paste0(as.list(match.call(expand.dots=FALSE))[[1]], "()")
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instruction <- match.call()
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# end function name
# required function checking
req.function <- c(
"fun_check", 
"fun_get_message", 
"fun_pack"
)
for(i1 in req.function){
if(length(find(i1, mode = "function")) == 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": REQUIRED ", i1, "() FUNCTION IS MISSING IN THE R ENVIRONMENT\n\n================\n\n")
stop(tempo.cat)
}
}
# end required function checking
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# argument primary checking
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# arg with no default values
if(any(missing(fun) | missing(arg) | missing(val))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ARGUMENTS fun, arg AND val HAVE NO DEFAULT VALUE AND REQUIRE ONE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
# end arg with no default values
# using fun_check()
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arg.check <- NULL #
text.check <- NULL #
checked.arg.names <- NULL # for function debbuging: used by r_debugging_tools
ee <- expression(arg.check <- c(arg.check, tempo$problem) , text.check <- c(text.check, tempo$text) , checked.arg.names <- c(checked.arg.names, tempo$fun.name))
tempo <- fun_check(data = fun, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
if(grepl(x = fun, pattern = "()$")){ # remove ()
fun <- sub(x = fun, pattern = "()$", replacement = "")
}
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if( ! exists(fun)){
tempo.cat <- paste0("ERROR IN ", function.name, ": CHARACTER STRING IN fun ARGUMENT DOES NOT EXIST IN THE R WORKING ENVIRONMENT: ", paste(fun, collapse = "\n"))
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text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
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}else if( ! all(class(get(fun)) == "function")){
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tempo.cat <- paste0("ERROR IN ", function.name, ": fun ARGUMENT IS NOT CLASS \"function\" BUT: ", paste(class(get(fun)), collapse = "\n"), "\nCHECK IF ANY CREATED OBJECT WOULD HAVE THE NAME OF THE TESTED FUNCTION")
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text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
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tempo <- fun_check(data = arg, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
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if(tempo$problem == FALSE & length(arg) == 0){
tempo.cat <- paste0("ERROR IN ", function.name, ": arg ARGUMENT CANNOT BE LENGTH 0")
text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
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tempo <- fun_check(data = val, class = "list", fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
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for(i2 in 1:length(val)){
tempo1 <- fun_check(data = val[[i2]], class = "vector", na.contain = TRUE, fun.name = function.name, print = FALSE)
tempo2 <- fun_check(data = val[[i2]], class = "list", na.contain = TRUE, fun.name = function.name, print = FALSE)
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if(tempo1$problem == TRUE & tempo2$problem == TRUE){
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tempo.cat <- paste0("ERROR IN ", function.name, ": COMPARTMENT ", i2, " OF val ARGUMENT MUST BE A VECTOR OR A LIST")
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text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}else if(tempo1$problem == FALSE){ # vector split into list compartments
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val[[i2]] <- split(x = val[[i2]], f = 1:length(val[[i2]]))
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}
}
}
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if( ! is.null(expect.error)){
tempo <- fun_check(data = expect.error, class = "list", fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
for(i3 in 1:length(expect.error)){
tempo1 <- fun_check(data = expect.error[[i3]], class = "vector",  mode = "logical", fun.name = function.name, print = FALSE)
tempo2 <- fun_check(data =  expect.error[[i3]], class = "list", fun.name = function.name, print = FALSE)
if(tempo1$problem == TRUE & tempo2$problem == TRUE){
tempo.cat <- paste0("ERROR IN ", function.name, ": COMPARTMENT ", i3, " OF expect.error ARGUMENT MUST BE TRUE OR FALSE")
text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}else if(tempo1$problem == FALSE){ # vector split into list compartments
expect.error[[i3]] <- split(x = expect.error[[i3]], f = 1:length(expect.error[[i3]]))
}
}
}
}
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if( ! is.null(thread.nb)){
tempo <- fun_check(data = thread.nb, typeof = "integer", double.as.integer.allowed = TRUE, neg.values = FALSE, length = 1, fun.name = "SLITHERINE") ; eval(ee)
if(tempo$problem == FALSE & thread.nb < 1){
tempo.cat <- paste0("ERROR IN ", function.name, ": thread.nb PARAMETER MUST EQUAL OR GREATER THAN 1: ", thread.nb)
text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
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tempo <- fun_check(data = print.count, class = "vector", typeof = "integer", length = 1, double.as.integer.allowed = TRUE, neg.values = FALSE, fun.name = function.name) ; eval(ee)
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tempo <- fun_check(data = plot.fun, class = "vector", mode = "logical", length = 1, fun.name = function.name) ; eval(ee)
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tempo <- fun_check(data = export, class = "vector", mode = "logical", length = 1, fun.name = function.name) ; eval(ee)
if( ! is.null(res.path)){
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tempo <- fun_check(data = res.path, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
if( ! all(dir.exists(res.path))){ # separation to avoid the problem of tempo$problem == FALSE and res.path == NA
tempo.cat <- paste0("ERROR IN ", function.name, ": DIRECTORY PATH INDICATED IN THE res.path ARGUMENT DOES NOT EXISTS:\n", paste(res.path, collapse = "\n"))
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text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
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}
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if( ! is.null(lib.path)){
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tempo <- fun_check(data = lib.path, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
if( ! all(dir.exists(lib.path))){ # separation to avoid the problem of tempo$problem == FALSE and lib.path == NA
tempo.cat <- paste0("ERROR IN ", function.name, ": DIRECTORY PATH INDICATED IN THE lib.path ARGUMENT DOES NOT EXISTS:\n", paste(lib.path, collapse = "\n"))
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text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
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}
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if( ! is.null(thread.nb)){
tempo <- fun_check(data = cute.path, class = "vector", typeof = "character", length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE){
if( ! file.exists(cute.path)){
tempo.cat <- paste0("ERROR IN ", function.name, ": FILE PATH INDICATED IN THE cute.path PARAMETER DOES NOT EXISTS:\n", cute.path)
text.check <- c(text.check, tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
}
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if(any(arg.check) == TRUE){
stop(paste0("\n\n================\n\n", paste(text.check[arg.check], collapse = "\n"), "\n\n================\n\n"), call. = FALSE) #
}
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# end using fun_check()
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# source("C:/Users/Gael/Documents/Git_versions_to_use/debugging_tools_for_r_dev-v1.2/r_debugging_tools-v1.2.R") ; eval(parse(text = str_basic_arg_check_dev)) ; eval(parse(text = str_arg_check_with_fun_check_dev)) # activate this line and use the function (with no arguments left as NULL) to check arguments status and if they have been checked using fun_check()
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# end argument primary checking
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# second round of checking and data preparation
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# dealing with NA
if(any(is.na(fun)) | any(is.na(arg)) | any(is.na(expect.error)) | any(is.na(thread.nb)) | any(is.na(print.count)) | any(is.na(plot.fun)) | any(is.na(export)) | any(is.na(res.path)) | any(is.na(lib.path))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": NO ARGUMENT EXCEPT val CAN HAVE NA VALUES\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
# end dealing with NA
# dealing with NULL
if(is.null(fun) | is.null(arg) | is.null(val) | is.null(print.count) | is.null(plot.fun) | is.null(export)){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THESE ARGUMENTS fun, arg, val, print.count, plot.fun AND export CANNOT BE NULL\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
# end dealing with NULL
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if(length(arg) != length(val)){
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tempo.cat <- paste0("ERROR IN ", function.name, ": LENGTH OF arg ARGUMENT MUST BE IDENTICAL TO LENGTH OF val ARGUMENT:\nHERE IT IS: ", length(arg), " VERSUS ", length(val))
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stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
}
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args <- names(formals(get(fun)))
if( ! all(arg %in% args)){
tempo.cat <- paste0("ERROR IN ", function.name, ": SOME OF THE STRINGS IN arg ARE NOT ARGUMENTS OF fun\nfun ARGUMENTS: ", paste(args, collapse = " "),"\nPROBLEMATIC STRINGS IN arg: ", paste(arg[ ! arg %in% args], collapse = " "))
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stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
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}
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if(sum(sapply(val, FUN = length) > 1) > 43){
tempo.cat <- paste0("ERROR IN ", function.name, ": CANNOT TEST MORE THAN 43 ARGUMENTS IF THEY ALL HAVE AT LEAST 2 VALUES EACH\nHERE THE NUMBER IS: ", sum(sapply(val, FUN = length) > 1))
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stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
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}
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if( ! is.null(expect.error)){
if(length(val) != length(expect.error)){
tempo.cat <- paste0("ERROR IN ", function.name, ": LENGTH OF val ARGUMENT MUST BE IDENTICAL TO LENGTH OF expect.error ARGUMENT:\nHERE IT IS: ", length(val), " VERSUS ", length(expect.error))
stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
}
}
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if( ! is.null(thread.nb) & is.null(res.path)){
tempo.cat <- paste0("ERROR IN ", function.name, ": res.path ARGUMENT MUST BE SPECIFIED IF thread.nb ARGUMENT IS NOT NULL")
stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
}
if(is.null(res.path) & export == TRUE){
tempo.cat <- paste0("ERROR IN ", function.name, ": res.path ARGUMENT MUST BE SPECIFIED IF export ARGUMENT TRUE")
stop(paste0("\n\n================\n\n", tempo.cat, "\n\n================\n\n"), call. = FALSE)
}
if( ! is.null(thread.nb) & export == FALSE){
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export <- TRUE
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tempo.cat <- paste0("WARNING FROM ", function.name, ": export ARGUMENT CONVERTED TO TRUE BECAUSE thread.nb ARGUMENT IS NOT NULL")
warning(paste0("\n", tempo.cat, "\n"), call. = FALSE)
}
# end second round of checking and data preparation
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# package checking
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fun_pack(req.package = c("lubridate"), lib.path = lib.path)
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if( ! is.null(thread.nb)){
fun_pack(req.package = c("parallel"), lib.path = lib.path)
}
# end package checking
# declaration of special plot functions
sp.plot.fun <- c("fun_gg_scatter", "fun_gg_bar", "fun_gg_boxplot")
# end declaration of special plot functions
# main code
cat("\nfun_test JOB IGNITION\n")
ini.date <- Sys.time()
ini.time <- as.numeric(ini.date) # time of process begin, converted into seconds
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if(export == TRUE){
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res.path <- paste0(res.path, "/fun_test_res_", trunc(ini.time))
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if(dir.exists(res.path)){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": FOLDER ALREADY EXISTS\n", res.path, "\nPLEASE RERUN ONCE\n\n============\n\n")
stop(tempo.cat, call. = FALSE)
}else{
dir.create(res.path)
}
}
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total.comp.nb <- prod(sapply(val, FUN = "length"))
cat(paste0("\nTHE TOTAL NUMBER OF TESTS IS: ", total.comp.nb, "\n"))
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# creation of the txt instruction that includes several loops
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loop.string <- NULL
end.loop.string <- NULL
fun.args <- NULL
fun.args2 <- NULL
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error.values <- NULL
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arg.values <- "list("
for(i1 in 1:length(arg)){
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if(is.null(thread.nb)){
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if(length(val[[i1]]) > 1){ # loop only if more than one value in length(val[[i1]])
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loop.string <- paste0(loop.string, "for(i", i1, " in 1:", length(val[[i1]]), "){")
end.loop.string <- paste0(end.loop.string, "}")
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}
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}else{
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loop.string <- "for(i in x){"
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end.loop.string <- "}"
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}
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fun.args <- paste0(
fun.args, 
ifelse(i1 == 1, "", ", "), 
arg[i1], 
" = val[[", 
i1, 
"]][[", 
if(is.null(thread.nb)){
if(length(val[[i1]]) > 1){
paste0("i", i1)
}else{
"1" # a unique element in val[[i1]]
}
}else{
paste0("i.list[[", i1, "]][i]")
}, 
"]]"
)
fun.args2 <- paste0(
fun.args2, 
ifelse(i1 == 1, "", ", "), 
arg[i1], 
" = val[[", 
i1, 
"]][[', ", 
if(is.null(thread.nb)){
if(length(val[[i1]]) > 1){
paste0("i", i1)
}else{
"1" # a unique element in val[[i1]]
}
}else{
paste0("i.list[[", i1, "]][i]")
}, 
", ']]"
)
arg.values <- paste0(
arg.values, 
"val[[", i1, "]][[", 
if(is.null(thread.nb)){
if(length(val[[i1]]) > 1){
paste0("i", i1)
}else{
"1" # a unique element in val[[i1]]
}
}else{
paste0("i.list[[", i1, "]][i]")
}, 
"]]", 
ifelse(i1 == length(arg), "", ", ")
)
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error.values <- paste0(
error.values, 
ifelse(i1 == 1, "", " | "), 
"expect.error[[", i1, "]][[", 
if(is.null(thread.nb)){
if(length(expect.error[[i1]]) > 1){
paste0("i", i1)
}else{
"1" # a unique element in expect.error[[i1]]
}
}else{
paste0("i.list[[", i1, "]][i]")
}, 
"]]"
)
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}
arg.values <- paste0(arg.values, ")")
fun.test <- paste0(fun, "(", fun.args, ")")
fun.test2 <- paste0("paste0('", fun, "(", fun.args2, ")')")
# plot title for special plot functions
if(plot.fun == TRUE){
plot.kind <- "classic"
if(fun %in% sp.plot.fun){
plot.kind <- "special"
if(any(arg %in% "title")){ # this is for the special functions
tempo.match <- regmatches(x = fun.test, m = regexpr(text = fun.test, pattern = "title = .+[,)]"))
tempo.match <- substring(tempo.match , 1, nchar(tempo.match) - 1)
fun.test <- sub(x = fun.test, pattern = tempo.match, replacement = paste0(tempo.match, "\ntempo.title"))
}else{
fun.test <- sub(x = fun.test, pattern = ")$", replacement = ", title = tempo.title)")
}
}
}
# end plot title for special plot functions
kind <- character()
problem <- logical()
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expected.error <- logical()
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res <- character()
count <- 0
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print.count.loop <- 0
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plot.count <- 0
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if(length(arg) == 1){
data <- data.frame()
}else{ # length(arg) == 0 already tested above
data <- data.frame(t(vector("character", length(arg))), stringsAsFactors = FALSE)[-1, ] # -1 to remove the single row created and to have an empty data frame with length(arg) columns
}
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code <- paste(
loop.string, '
count <- count + 1
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print.count.loop <- print.count.loop + 1
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data <- rbind(data, as.character(sapply(eval(parse(text = arg.values)), FUN = "paste", collapse = " ")), stringsAsFactors = FALSE) # each colum is a test
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tempo.try.error <- fun_get_message(data = eval(parse(text = fun.test2)), kind = "error", header = FALSE, env = get(env.name)) # data argument needs a character string but eval(parse(text = fun.test2)) provides it (eval parse replace the i1, i2, etc., by the correct values, meaning that only val is required in the env.name environment)
tempo.try.warning <- fun_get_message(data = eval(parse(text = fun.test2)), kind = "warning", header = FALSE, env = get(env.name), print.no = TRUE) # data argument needs a character string but eval(parse(text = fun.test2)) provides it (eval parse replace the i1, i2, etc., by the correct values, meaning that only val is required in the env.name environment)
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if( ! is.null(expect.error)){
expected.error <- c(expected.error, eval(parse(text = error.values)))
}
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if( ! is.null(tempo.try.error)){
kind <- c(kind, "ERROR")
problem <- c(problem, TRUE)
res <- c(res, tempo.try.error)
}else{
if( ! is.null(tempo.try.warning)){
kind <- c(kind, "WARNING")
problem <- c(problem, FALSE)
res <- c(res, tempo.try.warning)
}else{
kind <- c(kind, "OK")
problem <- c(problem, FALSE)
res <- c(res, "")
}
if(plot.fun == TRUE){
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dev.set(window.nb)
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plot.count <- plot.count + 1
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tempo.title <- paste0("test_", sprintf(paste0("%0", nchar(total.comp.nb), "d"), ifelse(is.null(thread.nb), count, x[count])))
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if(plot.kind == "classic"){
eval(parse(text = fun.test))
tempo <- fun_post_plot(corner.text = tempo.title)
}else if(plot.kind == "special"){
eval(parse(text = fun.test))
}else{
tempo.cat <- paste0("\n\n================\n\nINTERNAL CODE ERROR 1 IN ", function.name, ": CODE HAS TO BE MODIFIED\n\n============\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
}
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if(print.count.loop == print.count){
print.count.loop <- 0
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tempo.time <- as.numeric(Sys.time())
tempo.lapse <- round(lubridate::seconds_to_period(tempo.time - ini.time))
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final.loop <- (tempo.time - ini.time) / count * ifelse(is.null(thread.nb), total.comp.nb, length(x)) # intra nb.compar loop lapse: time lapse / cycles done * cycles remaining
final.exp <- as.POSIXct(final.loop, origin = ini.date)
cat(paste0(ifelse(is.null(thread.nb), "\n", paste0("\nIN PROCESS ", process.id, " | ")), "LOOP ", format(count, big.mark=","), " / ", format(ifelse(is.null(thread.nb), total.comp.nb, length(x)), big.mark=","), " | TIME SPENT: ", tempo.lapse, " | EXPECTED END: ", final.exp))
}
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if(count == ifelse(is.null(thread.nb), total.comp.nb, length(x))){
tempo.time <- as.numeric(Sys.time())
tempo.lapse <- round(lubridate::seconds_to_period(tempo.time - ini.time))
cat(paste0(ifelse(is.null(thread.nb), "\nLOOP PROCESS ENDED | ", paste0("\nPROCESS ", process.id, " ENDED | ")), "LOOP ", format(count, big.mark=","), " / ", format(ifelse(is.null(thread.nb), total.comp.nb, length(x)), big.mark=","), " | TIME SPENT: ", tempo.lapse, "\n\n"))
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}
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', 
end.loop.string
)
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# end creation of the txt instruction that includes several loops
if( ! is.null(thread.nb)){
# list of i numbers that will be split
i.list <- vector("list", length(val)) # positions to split in parallel jobs
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for(i2 in 1:length(arg)){
if(i2 == 1){
tempo.divisor <- total.comp.nb / length(val[[i2]])
i.list[[i2]] <- rep(1:length(val[[i2]]), each = as.integer(tempo.divisor))
tempo.multi <- length(val[[i2]])
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}else{
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tempo.divisor <- tempo.divisor / length(val[[i2]])
i.list[[i2]] <- rep(rep(1:length(val[[i2]]), each = as.integer(tempo.divisor)), time = as.integer(tempo.multi))
tempo.multi <- tempo.multi * length(val[[i2]])
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}
}
# end list of i numbers that will be split
tempo.cat <- paste0("PARALLELIZATION INITIATED AT: ", ini.date)
cat(paste0("\n", tempo.cat, "\n"))
tempo.thread.nb = parallel::detectCores(all.tests = FALSE, logical = TRUE) # detect the number of threads
if(tempo.thread.nb < thread.nb){
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thread.nb <- tempo.thread.nb
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}
tempo.cat <- paste0("NUMBER OF THREADS USED: ", thread.nb)
cat(paste0("\n    ", tempo.cat, "\n"))
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Clust <- parallel::makeCluster(thread.nb, outfile = paste0(res.path, "/fun_test_parall_log.txt")) # outfile to print or cat during parallelization (only possible in a file, outfile = "" do not work on windows)
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tempo.cat <- paste0("SPLIT OF TEST NUMBERS IN PARALLELISATION:")
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cat(paste0("\n    ", tempo.cat, "\n"))
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cluster.list <- parallel::clusterSplit(Clust, 1:total.comp.nb) # split according to the number of cluster
str(cluster.list) # using print(str()) add a NULL below the result
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cat("\n")
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paral.output.list <- parallel::clusterApply( # paral.output.list is a list made of thread.nb compartments, each made of n / thread.nb (mat theo column number) compartment. Each compartment receive the corresponding results of fun_permut(), i.e., data (permuted mat1.perm), warning message, cor (final correlation) and count (number of permutations)
cl = Clust,
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x = cluster.list,
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function.name = function.name, 
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instruction = instruction, 
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thread.nb = thread.nb, 
print.count = print.count, 
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total.comp.nb = total.comp.nb, 
sp.plot.fun = sp.plot.fun,
i.list = i.list, 
fun.tested = fun,
arg.values = arg.values,
fun.test = fun.test,
fun.test2 = fun.test2,
kind = kind,
problem = problem,
res = res,
count = count,
plot.count = plot.count,
data = data,
code = code,
plot.fun = plot.fun, 
res.path = res.path, 
lib.path = lib.path, 
cute.path = cute.path, 
fun = function(
x, 
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function.name, 
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instruction, 
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thread.nb, 
print.count, 
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total.comp.nb, 
sp.plot.fun, 
i.list, 
fun.tested, 
arg.values, 
fun.test, 
fun.test2, 
kind, 
problem, 
res, 
count, 
plot.count, 
data, 
code, 
plot.fun, 
res.path, 
lib.path, 
cute.path
){
# check again: very important because another R
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process.id <- Sys.getpid()
cat(paste0("\nPROCESS ID ", process.id, " -> TESTS ", x[1], " TO ", x[length(x)], "\n"))
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source(cute.path, local = .GlobalEnv)
fun_pack(req.package = "lubridate", lib.path = lib.path, load = TRUE) # load = TRUE to be sure that functions are present in the environment. And this prevent to use R.lib.path argument of fun_python_pack()
# end check again: very important because another R
# plot management
if(plot.fun == TRUE){
pdf(file = paste0(res.path, "/plots_from_fun_test_", x[1], ifelse(length(x) == 1, ".pdf", paste0("-", x[length(x)], ".pdf"))))
}else{
pdf(file = NULL) # send plots into a NULL file, no pdf file created
}
window.nb <- dev.cur()
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dev.set(window.nb)
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# end plot management
# new environment
env.name <- paste0("env", ini.time)
if(exists(env.name, where = -1)){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ENVIRONMENT env.name ALREADY EXISTS. PLEASE RERUN ONCE\n\n============\n\n")
stop(tempo.cat, call. = FALSE)
}else{
assign(env.name, new.env())
assign("var", var, envir = get(env.name))
}
# end new environment
ini.date <- Sys.time()
ini.time <- as.numeric(ini.date) # time of process begin, converted into 
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print.count.loop <- 0
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suppressMessages(suppressWarnings(eval(parse(text = code))))
colnames(data) <- arg
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if( ! is.null(expect.error)){
data <- data.frame(data, kind = kind, problem = problem, expected.error = expected.error, message = res, stringsAsFactors = FALSE)
}else{
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data <- data.frame(data, kind = kind, problem = problem, message = res, stringsAsFactors = FALSE)
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}
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row.names(data) <- paste0("test_", sprintf(paste0("%0", nchar(total.comp.nb), "d"), x))
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sys.info <- sessionInfo()
invisible(dev.off(window.nb))
rm(env.name) # optional, because should disappear at the end of the function execution
# output
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output <- list(fun = fun, data = data, instruction = instruction, sys.info = sys.info)
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save(output, file = paste0(res.path, "/fun_test_", x[1], ifelse(length(x) == 1, ".RData", paste0("-", x[length(x)], ".RData"))))
if(plot.fun == TRUE & plot.count == 0){
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warning(paste0("\nWARNING FROM ", function.name, " IN PROCESS ", process.id, ": NO PDF PLOT BECAUSE ONLY ERRORS REPORTED\n"), call. = FALSE)
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file.remove(paste0(res.path, "/plots_from_fun_test_", x[1], ifelse(length(x) == 1, ".pdf", paste0("-", x[length(x)], ".pdf"))))
}
table.out <- as.matrix(output$data)
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# table.out[table.out == ""] <- " " # does not work # because otherwise read.table() converts "" into NA
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table.out <- gsub(table.out, pattern = "\n", replacement = " ")
write.table(table.out, file = paste0(res.path, "/table_from_fun_test_", x[1], ifelse(length(x) == 1, ".txt", paste0("-", x[length(x)], ".txt"))), row.names = TRUE, col.names = NA, append = FALSE, quote = FALSE, sep = "\t", eol = "\n")
}
)
parallel::stopCluster(Clust)
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# txt files assembly
if(length(cluster.list) > 1){
for(i2 in 1:length(cluster.list)){
tempo.name <- paste0(res.path, "/table_from_fun_test_", min(cluster.list[[i2]], na.rm = TRUE), ifelse(length(cluster.list[[i2]]) == 1, ".txt", paste0("-", max(cluster.list[[i2]], na.rm = TRUE), ".txt")))
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tempo <- read.table(file = tempo.name, header = TRUE, stringsAsFactors = FALSE, sep = "\t", row.names = 1, comment.char = "", colClasses = "character") #  row.names = 1 (1st column) because now read.table() adds a NA in the header if the header starts by a tabulation, comment.char = "" because colors with #, colClasses = "character" otherwise convert "" (from NULL) into NA
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file.remove(tempo.name)
if(i2 == 1){
final.file <- tempo
}else{
final.file <- rbind(final.file, tempo)
}
}
write.table(final.file, file = paste0(res.path, "/table_from_fun_test_1-", total.comp.nb, ".txt"), row.names = TRUE, col.names = NA, append = FALSE, quote = FALSE, sep = "\t", eol = "\n")
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if( ! is.null(expect.error)){
final.file <- final.file[ ! final.file$problem == final.file$expected.error, ]
if(nrow(final.file) == 0){
cat(paste0("NO DISCREPANCY BETWEEN EXPECTED AND OBSERVED ERRORS\n\n"))
}else{
cat(paste0("DISCREPANCIES BETWEEN EXPECTED AND OBSERVED ERRORS (SEE THE discrepancy_table_from_fun_test_1-", total.comp.nb, ".txt FILE)\n\n"))
write.table(final.file, file = paste0(res.path, "/discrepancy_table_from_fun_test_1-", total.comp.nb, ".txt"), row.names = TRUE, col.names = NA, append = FALSE, quote = FALSE, sep = "\t", eol = "\n")
}
}
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}
# end txt files assembly
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}else{
# plot management
if(plot.fun == TRUE){
pdf(file = paste0(res.path, "/plots_from_fun_test_1", ifelse(total.comp.nb == 1, ".pdf", paste0("-", total.comp.nb, ".pdf"))))
}else{
pdf(file = NULL) # send plots into a NULL file, no pdf file created
}
window.nb <- dev.cur()
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dev.set(window.nb)
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# end plot management
# new environment
env.name <- paste0("env", ini.time)
if(exists(env.name, where = -1)){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ENVIRONMENT env.name ALREADY EXISTS. PLEASE RERUN ONCE\n\n============\n\n")
stop(tempo.cat, call. = FALSE)
}else{
assign(env.name, new.env())
assign("var", var, envir = get(env.name))
}
# end new environment
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suppressMessages(suppressWarnings(eval(parse(text = code))))
colnames(data) <- arg
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expect.data <- data.frame()
if( ! is.null(expect.error)){
data <- data.frame(data, kind = kind, problem = problem, expected.error = expected.error, message = res, stringsAsFactors = FALSE)
}else{
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data <- data.frame(data, kind = kind, problem = problem, message = res, stringsAsFactors = FALSE)
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}
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row.names(data) <- paste0("test_", sprintf(paste0("%0", nchar(total.comp.nb), "d"), 1:total.comp.nb))
sys.info <- sessionInfo()
invisible(dev.off(window.nb))
rm(env.name) # optional, because should disappear at the end of the function execution
# output
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output <- list(fun = fun, data = data, instruction = instruction, sys.info = sys.info)
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if(plot.fun == TRUE & plot.count == 0){
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warning(paste0("\nWARNING FROM ", function.name, ": NO PDF PLOT BECAUSE ONLY ERRORS REPORTED\n"), call. = FALSE)
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file.remove(paste0(res.path, "/plots_from_fun_test_1", ifelse(total.comp.nb == 1, ".pdf", paste0("-", total.comp.nb, ".pdf"))))
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}
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if( ! is.null(expect.error)){
expect.data <- output$data[ ! output$data$problem == output$data$expected.error, ]
if(nrow(expect.data) == 0){
cat(paste0("NO DISCREPANCY BETWEEN EXPECTED AND OBSERVED ERRORS\n\n"))
}else{
cat(paste0("DISCREPANCIES BETWEEN EXPECTED AND OBSERVED ERRORS (SEE THE ", if(export == TRUE){paste0("discrepancy_table_from_fun_test_1", ifelse(total.comp.nb == 1, "", paste0("-", total.comp.nb)), ".txt FILE")}else{"$data RESULT"}, ")\n\n"))
if(export == TRUE){
expect.data <- as.matrix(expect.data)
expect.data <- gsub(expect.data, pattern = "\n", replacement = "  ")
write.table(expect.data, file = paste0(res.path, "/discrepancy_table_from_fun_test_1", ifelse(total.comp.nb == 1, ".txt", paste0("-", total.comp.nb, ".txt"))), row.names = TRUE, col.names = NA, append = FALSE, quote = FALSE, sep = "\t", eol = "\n")
}
}
}
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if(export == TRUE){
save(output, file = paste0(res.path, "/fun_test_1", ifelse(total.comp.nb == 1, ".RData", paste0("-", total.comp.nb, ".RData"))))
table.out <- as.matrix(output$data)
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table.out <- gsub(table.out, pattern = "\n", replacement = "  ")
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write.table(table.out, file = paste0(res.path, "/table_from_fun_test_1", ifelse(total.comp.nb == 1, ".txt", paste0("-", total.comp.nb, ".txt"))), row.names = TRUE, col.names = NA, append = FALSE, quote = FALSE, sep = "\t", eol = "\n")
}else{
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return(output)
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}
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}
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end.date <- Sys.time()
end.time <- as.numeric(end.date)
total.lapse <- round(lubridate::seconds_to_period(end.time - ini.time))
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cat(paste0("fun_test JOB END\n\nTIME: ", end.date, "\n\nTOTAL TIME LAPSE: ", total.lapse, "\n\n\n"))
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}
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################ Object modification


######## fun_name_change() #### check a vector of character strings and modify any string if present in another vector


# Check OK: clear to go Apollo
fun_name_change <- function(data1, data2, added.string = "_modif"){
# AIM
# this function allow to check if a vector of character strings, like column names of a data frame, has elements present in another vector (vector of reserved words or column names of another data frame before merging)
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_check()
# ARGUMENTS
# data1: vector of character strings to check and modify
# data2: reference vector of character strings
# added.string: string added at the end of the modified string in data1 if present in data2
# RETURN
# a list containing
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# $data: the modified data1 (in the same order as in the initial data1)
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# $ini: the initial elements before modification. NULL if no modification
# $post: the modified elements in the same order as in ini. NULL if no modification
# EXAMPLES
# obs1 <- c("A", "B", "C", "D") ; obs2 <- c("A", "C") ; fun_name_change(obs1, obs2)
# obs1 <- c("A", "B", "C", "C_modif1", "D") ; obs2 <- c("A", "A_modif1", "C") ; fun_name_change(obs1, obs2) # the function checks that the new names are neither in obs1 nor in obs2 (increment the number after the added string)
# DEBUGGING
# data1 = c("A", "B", "C", "D") ; data2 <- c("A", "C") ; added.string = "_modif" # for function debugging
# function name
function.name <- paste0(as.list(match.call(expand.dots=FALSE))[[1]], "()")
# end function name
# required function checking
if(length(utils::find("fun_check", mode = "function")) == 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": REQUIRED fun_check() FUNCTION IS MISSING IN THE R ENVIRONMENT\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
# end required function checking
# argument checking
arg.check <- NULL #
text.check <- NULL #
checked.arg.names <- NULL # for function debbuging: used by r_debugging_tools
ee <- expression(arg.check <- c(arg.check, tempo$problem) , text.check <- c(text.check, tempo$text) , checked.arg.names <- c(checked.arg.names, tempo$fun.name))
tempo <- fun_check(data = data1, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
tempo <- fun_check(data = data2, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
tempo <- fun_check(data = added.string, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
if(any(arg.check) == TRUE){
stop(paste0("\n\n================\n\n", paste(text.check[arg.check], collapse = "\n"), "\n\n================\n\n"), call. = FALSE) #
}
# source("C:/Users/Gael/Documents/Git_versions_to_use/debugging_tools_for_r_dev-v1.2/r_debugging_tools-v1.2.R") ; eval(parse(text = str_basic_arg_check_dev)) ; eval(parse(text = str_arg_check_with_fun_check_dev)) # activate this line and use the function (with no arguments left as NULL) to check arguments status and if they have been checked using fun_check()
# end argument checking
# main code
ini <- NULL
post <- NULL
if(any(data1 %in% data2)){
tempo.names <- data1[data1 %in% data2]
ini <- NULL
post <- NULL
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for(i2 in 1:length(tempo.names)){
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count <- 0
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tempo <- tempo.names[i2]
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while(any(tempo %in% data2) | any(tempo %in% data1)){
count <- count + 1
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tempo <- paste0(tempo.names[i2], "_modif", count)
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}
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data1[data1 %in% tempo.names[i2]] <- paste0(tempo.names[i2], "_modif", count)
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if(count != 0){
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ini <- c(ini, tempo.names[i2])
post <- c(post, paste0(tempo.names[i2], "_modif", count))
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}
}
data <- data1
}else{
data <- data1
}
output <- list(data = data, ini = ini, post = post)
return(output)
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}


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######## fun_df_remod() #### remodeling a data frame to have column name as a qualitative values and vice-versa
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# Check OK: clear to go Apollo
fun_df_remod <- function(data, quanti.col.name = "quanti", quali.col.name = "quali"){
# AIM
# if the data frame is made of numeric columns, a new data frame is created, with the 1st column gathering all the numeric values, and the 2nd column being the name of the columns of the initial data frame. If row names were present in the initial data frame, then a new ini_rowname column is added with the names of the rows
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# If the data frame is made of one numeric column and one character or factor column, a new data frame is created, with the new columns corresponding to the split numeric values (according to the character column). NA are added a the end of each column to have the same number of rows. BEWARE: in such data frame, rows are not individuals. This means that in the example below, values 10 and 20 are associated on the same row but that means nothing in term of association
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# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_check()
# ARGUMENTS
# data: data frame to convert
# quanti.col.name: optional name for the quanti column of the new data frame
# quali.col.name: optional name for the quali column of the new data frame
# RETURN
# the modified data frame
# EXAMPLES
# obs <- data.frame(col1 = (1:4)*10, col2 = c("A", "B", "A", "A")) ; obs ; fun_df_remod(obs)
# obs <- data.frame(col1 = (1:4)*10, col2 = 5:8) ; obs ; fun_df_remod(obs, quanti.col.name = "quanti", quali.col.name = "quali")
# obs <- data.frame(col1 = (1:4)*10, col2 = 5:8) ; rownames(obs) <- paste0("row", 1:4) ; obs ; fun_df_remod(obs, quanti.col.name = "quanti", quali.col.name = "quali")
# DEBUGGING
# data = data.frame(a = 1:3, b = 4:6) ; quanti.col.name = "quanti" ; quali.col.name = "quali" # for function debugging
# data = data.frame(a = 1:3, b = 4:6, c = 11:13) ; quanti.col.name = "quanti" ; quali.col.name = "quali" # for function debugging
# data = data.frame(a = 1:3, b = letters[1:3]) ; quanti.col.name = "quanti" ; quali.col.name = "quali" # for function debugging
# data = data.frame(a = 1:3, b = letters[1:3]) ; quanti.col.name = "TEST" ; quali.col.name = "quali" # for function debugging