cute_little_R_functions.R 675 KB
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################################################################
##                                                            ##
##     CUTE FUNCTIONS v6.0.0                                  ##
##                                                            ##
##     Gael A. Millot                                         ##
##                                                            ##
##     Compatible with R v3.6.1                               ##
##                                                            ##
################################################################
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# https://usethis.r-lib.org/ and usethat also
# BEWARE: do not forget to save the modifications in the .R file (through RSTUDIO for indentation)
# add print warning argument using warning(warnings)
# update graphic examples with good comment, as in barplot
#is there any interest to be able to source elsewhere ? If yes, but may be interesting to put it into a new environement just above .GlobalEnv environment. See https://stackoverflow.com/questions/9002544/how-to-add-functions-in-an-existing-environment
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# Make a first round check for each function if required
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# Update all argument description, saying, character vector, etc.
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# check all the functions using fun_test
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# Templates: https://prettydoc.statr.me/themes.html
# # package: http://r-pkgs.had.co.nz/
# https://pkgdown.r-lib.org/
# https://rdrr.io/github/gastonstat/cointoss/
# doc:https://www.sphinx-doc.org/en/master/man/sphinx-autogen.html considering that https://www.ericholscher.com/blog/2014/feb/11/sphinx-isnt-just-for-python/
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################################ OUTLINE ################################
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################ Object analysis    2
######## fun_check() #### check class, type, length, etc., of objects   2
######## fun_info() #### recover object information 8
######## fun_head() #### head of the left or right of big 2D objects    10
######## fun_tail() #### tail of the left or right of big 2D objects    11
######## fun_comp_1d() #### comparison of two 1D datasets (vectors, factors, 1D tables) 13
######## fun_comp_2d() #### comparison of two 2D datasets (row & col names, dimensions, etc.)   17
######## fun_comp_list() #### comparison of two lists   23
######## fun_test() #### test combinations of argument values of a function 25
################ Object modification    28
######## fun_name_change() #### check a vector of character strings and modify any string if present in another vector  28
######## fun_df_remod() #### remodeling a data frame to have column name as a qualitative values and vice-versa 29
######## fun_merge() #### merge the columns of two 2D objects, by common rows   32
######## fun_round() #### rounding number if decimal present    36
######## fun_mat_rotate() #### 90° clockwise matrix rotation    38
######## fun_mat_num2color() #### convert a numeric matrix into hexadecimal color matrix    39
######## fun_mat_op() #### assemble several matrices with operation 42
######## fun_mat_inv() #### return the inverse of a square matrix   44
######## fun_mat_fill() #### fill the empty half part of a symmetric square matrix  45
######## fun_permut() #### progressively breaks a vector order  49
################ Graphics management    59
######## fun_width() #### window width depending on classes to plot 59
######## fun_open() #### open a GUI or pdf graphic window   61
######## fun_prior_plot() #### set graph param before plotting (erase axes for instance)    64
######## fun_scale() #### select nice label numbers when setting number of ticks on an axis 68
######## fun_post_plot() #### set graph param after plotting (axes redesign for instance)   73
######## fun_close() #### close specific graphic windows    84
################ Standard graphics  85
######## fun_empty_graph() #### text to display for empty graphs    86
################ gg graphics    87
######## fun_gg_palette() #### ggplot2 default color palette    87
######## fun_gg_just() #### ggplot2 justification of the axis labeling, depending on angle  89
######## fun_gg_point_rast() #### ggplot2 raster scatterplot layer  91
######## fun_gg_scatter() #### ggplot2 scatterplot + lines (up to 6 overlays totally)   94
######## fun_gg_bar() #### ggplot2 mean barplot + overlaid dots if required 130
######## fun_gg_boxplot() #### ggplot2 boxplot + background dots if required    165
######## fun_gg_prop() #### ggplot2 proportion barplot  165
######## fun_gg_strip() #### ggplot2 stripchart + mean/median   165
######## fun_gg_dot() #### ggplot2 categorial dotplot + mean/median 165
######## fun_gg_violin() #### ggplot2 violins   165
######## fun_gg_line() #### ggplot2 lines + background dots and error bars  165
######## fun_gg_heatmap() #### ggplot2 heatmap + overlaid mask if required  168
######## fun_gg_empty_graph() #### text to display for empty graphs 181
################ Graphic extraction 183
######## fun_trim() #### display values from a quantitative variable and trim according to defined cut-offs 183
######## fun_segmentation() #### segment a dot cloud on a scatterplot and define the dots from another cloud outside the segmentation   191
################ Import 223
######## fun_pack() #### check if R packages are present and import into the working environment    223
######## fun_python_pack() #### check if python packages are present    225
################ Print / Exporting results (text & tables)  227
######## fun_report() #### print string or data object into output file 227
######## fun_get_message() #### return messages of an expression (that can be exported) 230
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################################ FUNCTIONS ################################
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################ Object analysis


######## fun_check() #### check class, type, length, etc., of objects


# Check OK: clear to go Apollo
fun_check <- function(data, data.name = NULL, class = NULL, typeof = NULL, mode = NULL, length = NULL, prop = FALSE, double.as.integer.allowed = FALSE, options = NULL, all.options.in.data = FALSE, na.contain = FALSE, neg.values = TRUE, print = FALSE, fun.name = NULL){
# AIM
# check the class, type, mode and length of the data argument
# mainly used to check the arguments of other functions
# check also other kind of data parameters, is it a proportion? Is it type double but numbers without decimal part?
# if options = NULL, then at least class or type or mode or length must be non null
# if options is non null, then class, type and mode must be NULL, and length can be NULL or specified
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# none
# ARGUMENTS
# data: object to test
# data.name: name of the object to test. If NULL, use the name of the object assigned to the data argument
# class: one of the class() result or "vector"
# typeof: one of the typeof() result
# mode: one of the mode() result (for non vector object)
# length: length of the object
# prop: logical, are the numeric values between 0 and 1 (proportion)? If TRUE, can be used alone, without considering class, etc.
# double.as.integer.allowed: logical. If TRUE, no error is reported if argument is set to typeof = "integer" or class = "integer", while the reality is typeof = "double" or class = "numeric" but the numbers have a zero as modulo (remainder of a division). This means that i<-1 , which is typeof(i) -> "double" is considered as integer with double.as.integer.allowed = TRUE
# options: a vector of possible values for data
# all.options.in.data: If TRUE, all of the options must be present at least once in data, and nothing else. If FALSE, some of the options must be present in data, and nothing else
# na.contain: can data contains NA?
# neg.values: are negative numeric values authorized? BEWARE: only considered if set to FALSE, to check for non negative values when class is set to "numeric", "matrix", "array", "data.frame", "table", or typeof is set to "double", "integer", or mode is set to "numeric"
# print: print the error message if $problem is TRUE? See the example section
# fun.name: name of the function when fun_check() is used to check its argument. If non NULL, name will be added into the error message returned by fun_check()
# RETURN
# a list containing:
# $problem: logical. Is there any problem detected ?
# $text: the problem detected
# $fun.name: name of the checked parameter
# EXAMPLES
# test <- 1:3 ; fun_check(data = test, data.name = NULL, print = TRUE, options = NULL, all.options.in.data = FALSE, class = NULL, typeof = NULL, mode = NULL, prop = TRUE, double.as.integer.allowed = FALSE, length = NULL)
# test <- 1:3 ; fun_check(data = test, print = TRUE, class = "numeric", typeof = NULL, double.as.integer.allowed = FALSE)
# test <- 1:3 ; fun_check(data = test, print = TRUE, class = "vector", mode = "numeric")
# argument print with and without assignation
# test <- 1:3 ; tempo <- fun_check(data = test, print = TRUE, class = "vector", mode = "character")
# test <- 1:3 ; tempo <- fun_check(data = test, print = FALSE, class = "vector", mode = "character") # the assignation allows to recover a problem without printing it
# test <- 1:3 ; fun_check(data = test, print = TRUE, class = "vector", mode = "character")
# test <- matrix(1:3) ; fun_check(data = test, print = TRUE, class = "vector", mode = "numeric")
# DEBUGGING
# data = expression(TEST) ; data.name = NULL ; class = "vector" ; typeof = NULL ; mode = NULL ; length = 1 ; prop = FALSE ; double.as.integer.allowed = FALSE ; options = NULL ; all.options.in.data = FALSE ; na.contain = FALSE ; neg.values = TRUE ; print = TRUE ; fun.name = NULL
# function name: no used in this function for the error message, to avoid env colliding
# argument checking
if( ! is.null(data.name)){
if( ! (length(data.name) == 1 & class(data.name) == "character")){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): data.name ARGUMENT MUST BE A SINGLE CHARACTER ELEMENT AND NOT ", paste(data.name, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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}
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if(is.null(prop) | is.null(double.as.integer.allowed) | is.null(all.options.in.data) | is.null(na.contain) | is.null(neg.values) | is.null(print)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THESE ARGUMENTS prop, double.as.integer.allowed, all.options.in.data, na.contain, neg.values AND print CANNOT BE NULL\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if(is.null(options) & is.null(class) & is.null(typeof) & is.null(mode) &  prop == FALSE & is.null(length)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): AT LEAST ONE OF THE options, class, typeof, mode, prop, OR length ARGUMENT MUST BE SPECIFIED (I.E, TRUE FOR prop)\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! is.null(options) & ( ! is.null(class) | ! is.null(typeof) | ! is.null(mode) | prop == TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE class, typeof, mode ARGUMENTS MUST BE NULL, AND prop FALSE, IF THE option ARGUMENT IS SPECIFIED\nTHE option ARGUMENT MUST BE NULL IF THE class AND/OR typeof AND/OR mode AND/OR prop ARGUMENT IS SPECIFIED\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! (all(class(neg.values) == "logical") & length(neg.values) == 1 & any(is.na(neg.values)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE neg.values ARGUMENT MUST BE TRUE OR FALSE ONLY\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if(neg.values == FALSE & is.null(class) & is.null(typeof) & is.null(mode)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE neg.values ARGUMENT CANNOT BE SWITCHED TO FALSE IF class, typeof AND mode ARGUMENTS ARE NULL\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! is.null(class)){
if( ! all(class %in% c("vector", "logical", "integer", "numeric", "complex", "character", "matrix", "array", "data.frame", "list", "factor", "table", "expression", "name", "symbol", "function", "uneval", "environment") & any(is.na(class)) != TRUE)){ # not length == 1 here because ordered factors are class "factor" "ordered" (length == 2)
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): class ARGUMENT MUST BE ONE OF THESE VALUE:\n\"vector\", \"logical\", \"integer\", \"numeric\", \"complex\", \"character\", \"matrix\", \"array\", \"data.frame\", \"list\", \"factor\", \"table\", \"expression\", \"name\", \"symbol\", \"function\", \"environment\"\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if(neg.values == FALSE & ! any(class %in% c("vector", "numeric", "integer", "matrix", "array", "data.frame", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): class ARGUMENT CANNOT BE OTHER THAN \"vector\", \"numeric\", \"integer\", \"matrix\", \"array\", \"data.frame\", \"table\" IF neg.values ARGUMENT IS SWITCHED TO FALSE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! is.null(typeof)){
if( ! (all(typeof %in% c("logical", "integer", "double", "complex", "character", "list", "expression", "name", "symbol", "closure", "special", "builtin", "environment")) & length(typeof) == 1 & any(is.na(typeof)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): typeof ARGUMENT MUST BE ONE OF THESE VALUE:\n\"logical\", \"integer\", \"double\", \"complex\", \"character\", \"list\", \"expression\", \"name\", \"symbol\", \"closure\", \"special\", \"builtin\", \"environment\"\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if(neg.values == FALSE & ! typeof %in% c("double", "integer")){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): typeof ARGUMENT CANNOT BE OTHER THAN \"double\" OR \"integer\" IF neg.values ARGUMENT IS SWITCHED TO FALSE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! is.null(mode)){
if( ! (all(mode %in% c("logical", "numeric", "complex", "character", "list", "expression", "name", "symbol", "function", "environment")) & length(mode) == 1 & any(is.na(mode)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): mode ARGUMENT MUST BE ONE OF THESE VALUE:\n\"logical\", \"numeric\", \"complex\", \"character\", \"list\", \"expression\", \"name\", \"symbol\", \"function\", \"environment\"\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if(neg.values == FALSE & mode != "numeric"){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): mode ARGUMENT CANNOT BE OTHER THAN \"numeric\" IF neg.values ARGUMENT IS SWITCHED TO FALSE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! is.null(length)){
if( ! (is.numeric(length) & length(length) == 1 & ! grepl(length, pattern = "\\.") & any(is.na(length)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): length ARGUMENT MUST BE A SINGLE INTEGER VALUE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! (is.logical(prop) | length(prop) == 1 & any(is.na(prop)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): prop ARGUMENT MUST BE TRUE OR FALSE ONLY\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}else if(prop == TRUE){
if( ! is.null(class)){
if( ! any(class %in% c("vector", "numeric", "integer", "matrix", "array", "data.frame", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): class ARGUMENT CANNOT BE OTHER THAN \"vector\", \"numeric\", \"integer\", \"matrix\", \"array\", \"data.frame\", \"table\" IF prop ARGUMENT IS TRUE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! is.null(mode)){
if(mode != "numeric"){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): mode ARGUMENT CANNOT BE OTHER THAN \"numeric\" IF prop ARGUMENT IS TRUE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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if( ! is.null(typeof)){
if(typeof != "double"){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): typeof ARGUMENT CANNOT BE OTHER THAN \"double\" IF prop ARGUMENT IS TRUE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
}
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if( ! (all(class(double.as.integer.allowed) == "logical") & length(double.as.integer.allowed) == 1 & any(is.na(double.as.integer.allowed)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE double.as.integer.allowed ARGUMENT MUST BE TRUE OR FALSE ONLY: ", paste(double.as.integer.allowed, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! (is.logical(all.options.in.data) & length(all.options.in.data) == 1 & any(is.na(all.options.in.data)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): all.options.in.data ARGUMENT MUST BE A SINGLE LOGICAL VALUE (TRUE OR FALSE ONLY): ", paste(all.options.in.data, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! (all(class(na.contain) == "logical") & length(na.contain) == 1 & any(is.na(na.contain)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE na.contain ARGUMENT MUST BE TRUE OR FALSE ONLY: ", paste(na.contain, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! (all(class(print) == "logical") & length(print) == 1 & any(is.na(print)) != TRUE)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE print ARGUMENT MUST BE TRUE OR FALSE ONLY: ", paste(print, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
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if( ! is.null(fun.name)){
if( ! (class(fun.name) == "character" & length(fun.name) == 1)){
tempo.cat <- paste0("\n\n================\n\nERROR IN fun_check(): THE fun.name ARGUMENT MUST BE A CHARACTER VECTOR OF LENGTH 1: ", paste(fun.name, collapse = " "), "\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
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}
}
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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)) # activate this line and use the function to check arguments status
# end argument checking
# main code
if(is.null(data.name)){
data.name <- deparse(substitute(data))
}
problem <- FALSE
text <- paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER")
if( ! is.null(options)){
text <- ""
if( ! all(data %in% options)){
problem <- TRUE
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE ", data.name, " PARAMETER MUST BE SOME OF THESE OPTIONS: ", paste(options, collapse = " "), "\nTHE PROBLEMATIC ELEMENTS OF ", data.name, " ARE: ", paste(unique(data[ ! (data %in% options)]), collapse = " "))
}
if(all.options.in.data == TRUE){
if( ! all(options %in% data)){
problem <- TRUE
if(text == ""){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE ", data.name, " PARAMETER MUST BE SOME OF THESE OPTIONS: ", paste(options, collapse = " "), "\nTHE PROBLEMATIC ELEMENTS OF ", data.name, " ARE: ", unique(data[ ! (data %in% options)]))
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}else{
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text <- paste0(text, "\n", ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE ", data.name, " PARAMETER MUST BE SOME OF THESE OPTIONS: ", paste(options, collapse = " "), "\nTHE PROBLEMATIC ELEMENTS OF ", data.name, " ARE: ", unique(data[ ! (data %in% options)]))
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}
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}
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}
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if( ! is.null(length)){
if(length(data) != length){
problem <- TRUE
if(text == ""){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE LENGTH OF ", data.name, " MUST BE ", length, " AND NOT ", length(data))
}else{
text <- paste0(text, "\n", ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE LENGTH OF ", data.name, " MUST BE ", length, " AND NOT ", length(data))
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}
}
}
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if(text == ""){
text <- paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER")
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}
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}
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arg.names <- c("class", "typeof", "mode", "length")
if(is.null(options)){
for(i2 in 1:length(arg.names)){
if( ! is.null(get(arg.names[i2]))){
# script to execute
tempo.script <- '
problem <- TRUE ;
if(identical(text, paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER"))){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": THE ", data.name, " PARAMETER MUST BE ") ;
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}else{
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text <- paste0(text, " AND "); 
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}
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text <- paste0(text, toupper(arg.names[i2]), " ", get(arg.names[i2]))
'
# end script to execute
if(typeof(data) == "double" & double.as.integer.allowed == TRUE & ((arg.names[i2] == "class" & get(arg.names[i2]) == "integer") | (arg.names[i2] == "typeof" & get(arg.names[i2]) == "integer"))){
if( ! all(data%%1 == 0)){ # to check integers (use %%, meaning the remaining of a division): see the precedent line. isTRUE(all.equal(data%%1, rep(0, length(data)))) not used because we strictly need zero as a result
eval(parse(text = tempo.script)) # execute tempo.script
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}else if(get(arg.names[i2]) != "vector" & eval(parse(text = paste0(arg.names[i2], "(data)"))) != get(arg.names[i2])){
eval(parse(text = tempo.script)) # execute tempo.script
}else if(arg.names[i2] == "class" & get(arg.names[i2]) == "vector" & ! (class(data) == "numeric" | class(data) == "integer" | class(data) == "character" | class(data) == "logical")){
eval(parse(text = tempo.script)) # execute tempo.script
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}
}
}
}
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if(prop == TRUE){
if(any(data < 0 | data > 1, na.rm = TRUE)){
problem <- TRUE
if(identical(text, paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER"))){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": ")
}else{
text <- paste0(text, " AND ")
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}
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text <- paste0(text, "THE ", data.name, " PARAMETER MUST BE DECIMAL VALUES BETWEEN 0 AND 1")
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}
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}
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if(all(class(data) %in% "expression")){
data <- as.character(data) # to evaluate the presence of NA
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}
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if(na.contain == FALSE & ! (class(data) %in% c("function", "environment"))){
if(any(is.na(data)) == TRUE){ # not on the same line because when data is class envir or function , do not like that
problem <- TRUE
if(identical(text, paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER"))){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": ")
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}else{
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text <- paste0(text, " AND ")
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}
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text <- paste0(text, "THE ", data.name, " PARAMETER CONTAINS NA WHILE NOT AUTHORIZED (na.contain ARGUMENT SET TO FALSE)")
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}
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}
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if(neg.values == FALSE){
if(any(data < 0, na.rm = TRUE)){
problem <- TRUE
if(identical(text, paste0(ifelse(is.null(fun.name), "", paste0("IN ", fun.name, ": ")), "NO PROBLEM DETECTED FOR THE ", data.name, " PARAMETER"))){
text <- paste0(ifelse(is.null(fun.name), "ERROR", paste0("ERROR IN ", fun.name)), ": ")
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}else{
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text <- paste0(text, " AND ")
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}
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text <- paste0(text, "THE ", data.name, " PARAMETER MUST BE NON NEGATIVE NUMERIC VALUES")
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}
}
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if(print == TRUE & problem == TRUE){
cat(paste0("\n\n================\n\n", text, "\n\n================\n\n"))
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}
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output <- list(problem = problem, text = text, fun.name = data.name)
return(output)
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}
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######## fun_info() #### recover object information


# Check OK: clear to go Apollo
fun_info <- function(data){
# AIM
# provide a full description of an object
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# none
# ARGUMENTS
# data: object to test
# RETURN
# a list containing information, depending on the class and type of data
# if data is made of numerics, provide range, sum, mean, number of NA and number of Inf
# please, use names(fun_info()) and remove what can be too big for easy analysis
# EXAMPLES
# fun_info(data = 1:3)
# fun_info(data.frame(a = 1:2, b = ordered(factor(c("A", "B")))))
# fun_info(list(a = 1:3, b = ordered(factor(c("A", "B")))))
# DEBUGGING
# data = NULL # for function debugging
# data = 1:3 # for function debugging
# data = matrix(1:3) # for function debugging
# data = data.frame(a = 1:2, b = c("A", "B")) # for function debugging
# data = factor(c("b", "a")) # for function debugging
# data = ordered(factor(c("b", "a"))) # for function debugging
# data = list(a = 1:3, b = factor(c("A", "B"))) # for function debugging
# data = list(a = 1:3, b = ordered(factor(c("A", "B")))) # for function debugging
# function name: no need because no check and no message
# argument checking
# 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
data.name <- deparse(substitute(data))
output <- list("NAME" = data.name)
tempo <- list("CLASS" = class(data))
output <- c(output, tempo)
tempo <- list("TYPE" = typeof(data))
output <- c(output, tempo)
tempo <- list("LENGTH" = length(data))
output <- c(output, tempo)
if(all(typeof(data) %in% c("integer", "numeric", "double"))){
tempo <- list("RANGE" = range(data[ ! is.infinite(data)], na.rm = TRUE))
output <- c(output, tempo)
tempo <- list("SUM" = sum(data[ ! is.infinite(data)], na.rm = TRUE))
output <- c(output, tempo)
tempo <- list("MEAN" = mean(data[ ! is.infinite(data)], na.rm = TRUE))
output <- c(output, tempo)
tempo <- list("NA.NB" = sum(is.na(data)))
output <- c(output, tempo)
tempo <- list("INF.NB" = sum(is.infinite(data)))
output <- c(output, tempo)
}
tempo <- list("HEAD" = head(data))
output <- c(output, tempo)
if( ! is.null(data)){
tempo <- list("TAIL" = tail(data))
output <- c(output, tempo)
if( ! is.null(dim(data))){
tempo <- list("DIMENSION" = dim(data))
names(tempo[[1]]) <- c("NROW", "NCOL")
output <- c(output, tempo)
}
tempo <- list("SUMMARY" = summary(data))
output <- c(output, tempo)
}
if(all(class(data) == "data.frame" | class(data) == "matrix")){
tempo <- list("ROW_NAMES" = dimnames(data)[[1]])
output <- c(output, tempo)
tempo <- list("COLUM_NAMES" = dimnames(data)[[2]])
output <- c(output, tempo)
}
if(all(class(data) == "data.frame")){
tempo <- list("STRUCTURE" = ls.str(data)) # str() print automatically, ls.str() not but does not give the order of the data.frame
output <- c(output, tempo)
tempo <- list("COLUMN_TYPE" = sapply(data, FUN = "typeof"))
if(any(sapply(data, FUN = "class") %in% "factor")){ # if an ordered factor is present, then sapply(data, FUN = "class") return a list but works with any(sapply(data, FUN = "class") %in% "factor") 
tempo.class <- sapply(data, FUN = "class")
if(any(unlist(tempo.class) %in% "ordered")){
tempo2 <- sapply(tempo.class, paste, collapse = " ") # paste the "ordered" factor" in "ordered factor"
}else{
tempo2 <- unlist(tempo.class)
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}
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tempo[["COLUMN_TYPE"]][grepl(x = tempo2, pattern = "factor")] <- tempo2[grepl(x = tempo2, pattern = "factor")]
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}
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output <- c(output, tempo)
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}
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if(all(class(data) == "list")){
tempo <- list("COMPARTMENT_NAMES" = names(data))
output <- c(output, tempo)
tempo <- list("COMPARTMENT_TYPE" = sapply(data, FUN = "typeof"))
if(any(unlist(sapply(data, FUN = "class")) %in% "factor")){ # if an ordered factor is present, then sapply(data, FUN = "class") return a list but works with any(sapply(data, FUN = "class") %in% "factor") 
tempo.class <- sapply(data, FUN = "class")
if(any(unlist(tempo.class) %in% "ordered")){
tempo2 <- sapply(tempo.class, paste, collapse = " ") # paste the "ordered" factor" in "ordered factor"
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}else{
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tempo2 <- unlist(tempo.class)
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}
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tempo[["COMPARTMENT_TYPE"]][grepl(x = tempo2, pattern = "factor")] <- tempo2[grepl(x = tempo2, pattern = "factor")]
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}
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output <- c(output, tempo)
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}
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return(output)
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}
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######## fun_head() #### head of the left or right of big 2D objects


# Check OK: clear to go Apollo
fun_head <- function(data1, n = 6, side = "l"){
# AIM
# as head() but display the left or right head of big 2D objects
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_check()
# ARGUMENTS
# data1: any object but more dedicated for matrix, data frame or table
# n: as in head() but for for matrix, data frame or table, number of dimension to print (10 means 10 rows and columns)
# side: either "l" or "r" for the left or right side of the 2D object (only for matrix, data frame or table)
# BEWARE: other arguments of head() not used
# RETURN
# the head
# EXAMPLES
# obs1 = matrix(1:30, ncol = 5, dimnames = list(letters[1:6], LETTERS[1:5])) ; obs1 ; fun_head(obs1, 3)
# obs1 = matrix(1:30, ncol = 5, dimnames = list(letters[1:6], LETTERS[1:5])) ; obs1 ; fun_head(obs1, 3, "right")
# DEBUGGING
# data1 = matrix(1:30, ncol = 5) # for function debugging
# data1 = matrix(1:30, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # 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)
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}
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# 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 = n, class = "vector", typeof = "integer", double.as.integer.allowed = TRUE, length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_check(data = side, options = c("l", "r"), 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) #
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}
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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()
# end argument checking
# main code
if( ! any(class(data1) %in% c("matrix", "data.frame", "table"))){
return(head(data1, n))
}else{
obs.dim <- dim(data1)
row <- 1:ifelse(obs.dim[1] < n, obs.dim[1], n)
if(side == "l"){
col <- 1:ifelse(obs.dim[2] < n, obs.dim[2], n)
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}
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if(side == "r"){
col <- ifelse(obs.dim[2] < n, 1, obs.dim[2] - n + 1):obs.dim[2]
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}
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return(data1[row, col])
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}
}


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######## fun_tail() #### tail of the left or right of big 2D objects


# Check OK: clear to go Apollo
fun_tail <- function(data1, n = 10, side = "l"){
# AIM
# as tail() but display the left or right head of big 2D objects
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_check()
# ARGUMENTS
# data1: any object but more dedicated for matrix, data frame or table
# n: as in tail() but for for matrix, data frame or table, number of dimension to print (10 means 10 rows and columns)
# side: either "l" or "r" for the left or right side of the 2D object (only for matrix, data frame or table)
# BEWARE: other arguments of tail() not used
# RETURN
# the tail
# EXAMPLES
# obs1 = matrix(1:30, ncol = 5, dimnames = list(letters[1:6], LETTERS[1:5])) ; obs1 ; fun_tail(obs1, 3)
# obs1 = matrix(1:30, ncol = 5, dimnames = list(letters[1:6], LETTERS[1:5])) ; obs1 ; fun_tail(obs1, 3, "r")
# DEBUGGING
# data1 = matrix(1:10, ncol = 5) # for function debugging
# data1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # 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 = n, class = "vector", typeof = "integer", double.as.integer.allowed = TRUE, length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_check(data = side, options = c("l", "r"), 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
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# main code
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if( ! any(class(data1) %in% c("matrix", "data.frame", "table"))){
return(tail(data1, n))
}else{
obs.dim <- dim(data1)
row <- ifelse(obs.dim[1] < n, 1, obs.dim[1] - n + 1):obs.dim[1]
if(side == "l"){
col <- 1:ifelse(obs.dim[2] < n, obs.dim[2], n)
}
if(side == "r"){
col <- ifelse(obs.dim[2] < n, 1, obs.dim[2] - n + 1):obs.dim[2]
}
return(data1[row, col])
}
}
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######## fun_comp_1d() #### comparison of two 1D datasets (vectors, factors, 1D tables)
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# Check OK: clear to go Apollo
fun_comp_1d <- function(data1, data2){
# AIM
# compare two 1D datasets (vector of factor or 1D table) of the same class or not. Check and report in a list if the 2 datasets have:
# same class
# common elements
# common element names (except factors)
# common levels (factors only)
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# none
# ARGUMENTS
# data1: vector or factor or 1D table
# data2: vector or factor or 1D table
# RETURN
# a list containing:
# $same.class: logical. Are class identical?
# $class: class of the 2 datasets (NULL otherwise)
# $same.length: logical. Are number of elements identical?
# $length: number of elements in the 2 datasets (NULL otherwise)
# $same.levels: logical. Are levels identical? (NULL if data1 and data2 are not factors)
# $levels: levels of the 2 datasets if identical (NULL otherwise or NULL if data1 and data2 are not factors)
# $any.id.levels: logical. Is there any identical levels? (NULL if data1 and data2 are not factors)
# $same.levels.pos1: position, in data1, of the levels identical in data2 (NULL if data1 and data2 are not factors)
# $same.levels.pos2: position, in data2, of the levels identical in data1 (NULL if data1 and data2 are not factors)
# $common.levels: common levels between data1 and data2 (can be a subset of $levels or not). NULL if no common levels or if data1 and data2 are not factors
# $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 elements names identical in data1
# $common.names: common element names between data1 and data2 (can be a subset of $name or not). NULL if no common element names
# $any.id.element: logical. is there any identical elements ?
# $same.element.pos1: position, in data1, of the elements identical in data2
# $same.element.pos2: position, in data2, of the elements identical in data1
# $common.elements: common elements between data1 and data2. NULL if no common elements
# $identical.object: logical. Are objects identical (kind of object, element names and content)?
# $identical.content: logical. Are content objects identical (identical elements excluding kind of object and element names)?
# EXAMPLES
# obs1 = 1:5 ; obs2 = 1:5 ; names(obs1) <- LETTERS[1:5] ; names(obs2) <- LETTERS[1:5] ; fun_comp_1d(obs1, obs2)
# obs1 = 1:5 ; obs2 = 1:5 ; names(obs1) <- LETTERS[1:5] ; fun_comp_1d(obs1, obs2)
# obs1 = 1:5 ; obs2 = 3:6 ; names(obs1) <- LETTERS[1:5] ; names(obs2) <- LETTERS[1:4] ; fun_comp_1d(obs1, obs2)
# obs1 = factor(LETTERS[1:5]) ; obs2 = factor(LETTERS[1:5]) ; fun_comp_1d(obs1, obs2)
# obs1 = factor(LETTERS[1:5]) ; obs2 = factor(LETTERS[10:11]) ; fun_comp_1d(obs1, obs2)
# obs1 = factor(LETTERS[1:5]) ; obs2 = factor(LETTERS[4:7]) ; fun_comp_1d(obs1, obs2)
# obs1 = 1:5 ; obs2 = factor(LETTERS[1:5]) ; fun_comp_1d(obs1, obs2)
# obs1 = 1:5 ; obs2 = 1.1:6.1 ; fun_comp_1d(obs1, obs2)
# obs1 = as.table(1:5); obs2 = as.table(1:5) ; fun_comp_1d(obs1, obs2)
# obs1 = as.table(1:5); obs2 = 1:5 ; fun_comp_1d(obs1, obs2)
# DEBUGGING
# data1 = 1:5 ; data2 = 1:5 ; names(data1) <- LETTERS[1:5] ; names(data2) <- LETTERS[1:5] # 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% c("logical", "integer", "numeric", "character", "factor", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 ARGUMENT MUST BE A NON NULL VECTOR, FACTOR OR 1D TABLE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}else if(all(class(data1) %in% "table")){
if(length(dim(data1)) > 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 ARGUMENT MUST BE A 1D TABLE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
}
if( ! any(class(data2) %in% c("logical", "integer", "numeric", "character", "factor", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data2 ARGUMENT MUST BE A NON NULL VECTOR, FACTOR OR 1D TABLE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}else if(all(class(data2) %in% "table")){
if(length(dim(data2)) > 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data2 ARGUMENT MUST BE A 1D TABLE\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.class <- NULL
class <- NULL
same.length <- NULL
length <- NULL
same.levels <- NULL
levels <- NULL
any.id.levels <- NULL
same.levels.pos1 <- NULL
same.levels.pos2 <- NULL
common.levels <- NULL
same.name <- NULL
name <- NULL
any.id.name <- NULL
same.name.pos1 <- NULL
same.name.pos2 <- NULL
common.names <- NULL
any.id.element <- NULL
same.element.pos1 <- NULL
same.element.pos2 <- NULL
common.elements <- NULL
identical.object <- NULL
identical.content <- NULL
if(identical(data1, data2)){
same.class <- TRUE
class <- class(data1)
same.length <- TRUE
length <- length(data1)
if(any(class(data1) %in% "factor")){
same.levels <- TRUE
levels <- levels(data1)
any.id.levels <- TRUE
same.levels.pos1 <- 1:length(levels(data1))
same.levels.pos2 <- 1:length(levels(data2))
common.levels <- levels(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)
common.names <- names(data1)
}
any.id.element <- TRUE
same.element.pos1 <- 1:length(data1)
same.element.pos2 <- 1:length(data2)
common.elements <- data1
identical.object <- TRUE
identical.content <- TRUE
}else{
identical.object <- FALSE
if( ! identical(class(data1), class(data2))){
same.class <- FALSE
}else{
same.class <- TRUE
class <- class(data1)
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if( ! identical(length(data1), length(data2))){
same.length<- FALSE
}else{
same.length<- TRUE
length <- length(data1)
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if(any(class(data1) %in% "factor") & any(class(data2) %in% "factor")){
if( ! identical(levels(data1), levels(data2))){
same.levels <- FALSE
}else{
same.levels <- TRUE
levels <- levels(data1)
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any.id.levels <- FALSE
if(any(levels(data1) %in% levels(data2))){
any.id.levels <- TRUE
same.levels.pos1 <- which(levels(data1) %in% levels(data2))
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if(any(levels(data2) %in% levels(data1))){
any.id.levels <- TRUE
same.levels.pos2 <- which(levels(data2) %in% levels(data1))
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if(any.id.levels == TRUE){
common.levels <- unique(c(levels(data1)[same.levels.pos1], levels(data2)[same.levels.pos2]))
}
}
if(any(class(data1) %in% "factor")){ # to compare content
data1 <- as.character(data1)
}
if(any(class(data2) %in% "factor")){ # to compare content
data2 <- as.character(data2)
}
if( ! (is.null(names(data1)) & is.null(names(data2)))){
if( ! identical(names(data1), names(data2))){
same.name <- FALSE
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}else{
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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))
}
if(any.id.name == TRUE){
common.names <- unique(c(names(data1)[same.name.pos1], names(data2)[same.name.pos2]))
}
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any.id.element <- FALSE
if(any(data1 %in% data2)){
any.id.element <- TRUE
same.element.pos1 <- which(data1 %in% data2)
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if(any(data2 %in% data1)){
any.id.element <- TRUE
same.element.pos2 <- which(data2 %in% data1)
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if(any.id.element == TRUE){
common.elements <- unique(c(data1[same.element.pos1], data2[same.element.pos2]))
}
if(same.length == TRUE & ! all(is.null(same.element.pos1), is.null(same.element.pos2))){
names(same.element.pos1) <- NULL
names(same.element.pos2) <- NULL
if(identical(same.element.pos1, same.element.pos2)){
identical.content <- TRUE
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identical.content <- FALSE
}
}else{
identical.content <- FALSE
}
}
output <- list(same.class = same.class, class = class, same.length = same.length, length = length, same.levels = same.levels, levels = levels, any.id.levels = any.id.levels, same.levels.pos1 = same.levels.pos1, same.levels.pos2 = same.levels.pos2, common.levels = common.levels, same.name = same.name, name = name, any.id.name = any.id.name, same.name.pos1 = same.name.pos1, same.name.pos2 = same.name.pos2, common.names = common.names, any.id.element = any.id.element, same.element.pos1 = same.element.pos1, same.element.pos2 = same.element.pos2, common.elements = common.elements, identical.object = identical.object, identical.content = identical.content)
return(output)
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}


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######## fun_comp_2d() #### comparison of two 2D datasets (row & col names, dimensions, etc.)


# Check OK: clear to go Apollo
fun_comp_2d <- function(data1, data2){
# AIM
# compare two 2D datasets of the same class or not. Check and report in a list if the 2 datasets have:
# same class
# common row names
# common column names
# same row number
# same column number
# potential identical rows between the 2 datasets
# potential identical columns between the 2 datasets
# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# none
# ARGUMENTS
# data1: matrix, data frame or table
# data2: matrix, data frame or table
# RETURN
# a list containing:
# $same.class: logical. Are class identical ?
# $class: classes of the 2 datasets (NULL otherwise)
# $same.dim: logical. Are dimension identical ?
# $dim: dimension of the 2 datasets (NULL otherwise)
# $same.row.nb: logical. Are number of rows identical ?
# $row.nb: nb of rows of the 2 datasets if identical (NULL otherwise)
# $same.col.nb: logical. Are number of columns identical ?
# $col.nb: nb of columns of the 2 datasets if identical (NULL otherwise)
# $same.row.name: logical. Are row names identical ? NULL if no row names in the two 2D datasets
# $row.name: name of rows of the 2 datasets if identical (NULL otherwise)
# $any.id.row.name: logical. Is there any row names identical ? NULL if no row names in the two 2D datasets
# $same.row.name.pos1: position, in data1, of the row names identical in data2
# $same.row.name.pos2: position, in data2, of the row names identical in data1
# $common.row.names: common row names between data1 and data2 (can be a subset of $name or not). NULL if no common row names
# $same.col.name: logical. Are column names identical ? NULL if no col names in the two 2D datasets
# $col.name: name of columns of the 2 datasets if identical (NULL otherwise)
# $any.id.col.name: logical. Is there any column names identical ? NULL if no col names in the two 2D datasets
# $same.col.name.pos1: position, in data1, of the column names identical in data2
# $same.col.name.pos2: position, in data2, of the column names identical in data1
# $common.col.names: common column names between data1 and data2 (can be a subset of $name or not). NULL if no common column names
# $any.id.row: logical. is there identical rows (not considering row names) ?
# $same.row.pos1: position, in data1, of the rows identical in data2 (not considering row names)
# $same.row.pos2: position, in data2, of the rows identical in data1 (not considering row names)
# $any.id.col: logical. is there identical columns (not considering column names)?
# $same.col.pos1: position in data1 of the cols identical in data2 (not considering column names)
# $same.col.pos2: position in data2 of the cols identical in data1 (not considering column names)
# $identical.object: logical. Are objects identical (including row & column names)?
# $identical.content: logical. Are content objects identical (identical excluding row & column names)?
# EXAMPLES
# obs1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; obs2 = as.data.frame(matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5]))) ; obs1 ; obs2 ; fun_comp_2d(obs1, obs2)
# obs1 = matrix(101:110, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; obs2 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; obs1 ; obs2 ; fun_comp_2d(obs1, obs2)
# obs1 = matrix(1:10, byrow = TRUE, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; obs2 = matrix(c(1:5, 101:105, 6:10), byrow = TRUE, ncol = 5, dimnames = list(c("a", "z", "b"), c(LETTERS[1:2], "k", LETTERS[5:4]))) ; obs1 ; obs2 ; fun_comp_2d(obs1, obs2)
# obs1 = t(matrix(1:10, byrow = TRUE, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5]))) ; obs2 = t(matrix(c(1:5, 101:105, 6:10), byrow = TRUE, ncol = 5, dimnames = list(c("a", "z", "b"), c(LETTERS[1:2], "k", LETTERS[5:4])))) ; obs1 ; obs2 ; fun_comp_2d(obs1, obs2)
# DEBUGGING
# data1 = matrix(1:10, ncol = 5) ; data2 = matrix(1:10, ncol = 5) # for function debugging
# data1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; data2 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # for function debugging
# data1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; data2 = matrix(1:10, ncol = 5) # for function debugging
# data1 = matrix(1:15, byrow = TRUE, ncol = 5, dimnames = list(letters[1:3], LETTERS[1:5])) ; data2 = matrix(1:10, byrow = TRUE, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # for function debugging
# data1 = matrix(1:15, ncol = 5, dimnames = list(letters[1:3], LETTERS[1:5])) ; data2 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # for function debugging
# data1 = matrix(1:15, ncol = 5, dimnames = list(paste0("A", letters[1:3]), LETTERS[1:5])) ; data2 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # for function debugging
# data1 = matrix(1:15, ncol = 5, dimnames = list(letters[1:3], LETTERS[1:5])) ; data2 = matrix(1:12, ncol = 4, dimnames = list(letters[1:3], LETTERS[1:4])) # for function debugging
# data1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; data2 = matrix(101:110, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) # for function debugging
# data1 = data.frame(a = 1:3, b= letters[1:3], row.names = LETTERS[1:3]) ; data2 = data.frame(A = 1:3, B= letters[1:3]) # for function debugging
# data1 = matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; data2 = as.data.frame(matrix(1:10, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5]))) # for function debugging
# data1 = matrix(1:10, byrow = TRUE, ncol = 5, dimnames = list(letters[1:2], LETTERS[1:5])) ; data2 = matrix(c(1:5, 101:105, 6:10), byrow = TRUE, ncol = 5, dimnames = list(c("a", "z", "b"), c(LETTERS[1:2], "k", LETTERS[5:4]))) # for function debugging
# data1 = table(Exp1 = c("A", "A", "A", "B", "B", "B"), Exp2 = c("A1", "B1", "A1", "C1", "C1", "B1")) ; data2 = data.frame(A = 1:3, B= letters[1:3]) # 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% c("matrix", "data.frame", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 ARGUMENT MUST BE A MATRIX, DATA FRAME OR TABLE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
if( ! any(class(data2) %in% c("matrix", "data.frame", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data2 ARGUMENT MUST BE A MATRIX, DATA FRAME OR TABLE\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.class <- NULL
class <- NULL
same.dim <- NULL
dim <- NULL
same.row.nb <- NULL
row.nb <- NULL
same.col.nb <- NULL
col.nb <- NULL
same.row.name <- NULL
row.name <- NULL
any.id.row.name <- NULL
same.row.name.pos1 <- NULL
same.row.name.pos2 <- NULL
common.row.names <- NULL
same.col.name <- NULL
any.id.col.name <- NULL
same.col.name.pos1 <- NULL
same.col.name.pos2 <- NULL
common.col.names <- NULL
col.name <- NULL
any.id.row <- NULL
same.row.pos1 <- NULL
same.row.pos2 <- NULL
any.id.col <- NULL
same.col.pos1 <- NULL
same.col.pos2 <- NULL
identical.object <- NULL
identical.content <- NULL
if(identical(data1, data2) & any(class(data1) %in% c("matrix", "data.frame", "table"))){
same.class <- TRUE
class <- class(data1)
same.dim <- TRUE
dim <- dim(data1)
same.row.nb <- TRUE
row.nb <- nrow(data1)
same.col.nb <- TRUE
col.nb <- ncol(data1)
same.row.name <- TRUE
row.name <- dimnames(data1)[[1]]
any.id.row.name <- TRUE
same.row.name.pos1 <- 1:row.nb
same.row.name.pos2 <- 1:row.nb
common.row.names <- dimnames(data1)[[1]]
same.col.name <- TRUE
col.name <- dimnames(data1)[[2]]
any.id.col.name <- TRUE
same.col.name.pos1 <- 1:col.nb
same.col.name.pos2 <- 1:col.nb
common.col.names <- dimnames(data1)[[2]]
any.id.row <- TRUE
same.row.pos1 <- 1:row.nb
same.row.pos2 <- 1:row.nb
any.id.col <- TRUE
same.col.pos1 <- 1:col.nb
same.col.pos2 <- 1:col.nb
identical.object <- TRUE
identical.content <- TRUE
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}else{
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identical.object <- FALSE
if(all(class(data1) == "table") & length(dim(data1)) == 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 ARGUMENT IS A 1D TABLE. USE THE fun_comp_1d FUNCTION\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
if(all(class(data2) == "table") & length(dim(data2)) == 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data2 ARGUMENT IS A 1D TABLE. USE THE fun_comp_1d FUNCTION\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}
if( ! identical(class(data1), class(data2))){
same.class <- FALSE
}else if( ! any(class(data1) %in% c("matrix", "data.frame", "table"))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": THE data1 AND data2 ARGUMENTS MUST BE EITHER MATRIX, DATA FRAME OR TABLE\n\n================\n\n")
stop(tempo.cat, call. = FALSE)
}else{
same.class <- TRUE
class <- class(data1)
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if( ! identical(dim(data1), dim(data2))){
same.dim <- FALSE
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}else{
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same.dim <- TRUE
dim <- dim(data1)
}
if( ! identical(nrow(data1), nrow(data2))){
same.row.nb <- FALSE
}else{
same.row.nb <- TRUE
row.nb <- nrow(data1)
}
if( ! identical(ncol(data1), ncol(data2))){
same.col.nb <- FALSE
}else{
same.col.nb <- TRUE
col.nb <- ncol(data1)
}
# row and col names
if(is.null(dimnames(data1)) & is.null(dimnames(data2))){
same.row.name <- NULL
same.col.name <- NULL
# row and col names remain NULL
}else if((is.null(dimnames(data1)) & ! is.null(dimnames(data2))) | ( ! is.null(dimnames(data1)) & is.null(dimnames(data2)))){
same.row.name <- FALSE
same.col.name <- FALSE
# row and col names remain NULL
}else{
if( ! identical(dimnames(data1)[[1]], dimnames(data2)[[1]])){
same.row.name <- FALSE
# row names remain NULL
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}else{
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same.row.name <- TRUE
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
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