cute_little_R_functions.R 685 KB
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for(i1 in 1:length(data1)){
tempo <- fun_param_check(data = data1[[i1]], data.name = ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), class = "data.frame", na.contain = TRUE, fun.name = function.name) ; eval(ee)
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# reserved word checking
if(any(names(data1[[i1]]) %in% reserved.words)){ # I do not use fun_name_change() because cannot control y before creating "fake_y". But ok because reserved are not that common
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": COLUMN NAMES OF ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), " ARGUMENT CANNOT BE ONE OF THESE WORDS\n", paste(reserved.words, collapse = " "), "\nTHESE ARE RESERVED FOR THE ", function.name, " FUNCTION\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
# end reserved word checking
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# check of geom now because required for y argument
tempo <- fun_param_check(data = geom[[i1]], data.name = ifelse(length(geom) == 1, "geom", paste0("geom NUMBER ", i1)), options = c("geom_point", "geom_line", "geom_path", "geom_hline", "geom_vline"), length = 1, fun.name = function.name) ; eval(ee)
# end check of geom now because required for y argument
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if(is.null(x[[i1]])){
if(all(geom[[i1]] != "geom_hline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ": x ARGUMENT CANNOT BE NULL EXCEPT IF ", ifelse(length(geom) == 1, "x", paste0("geom NUMBER ", i1)), " ARGUMENT IS \"geom_hline\"\nHERE geom ARGUMENT IS: ", paste(geom[[i1]], collapse = " "), "\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}else{
x[[i1]] <- "fake_x"
data1[[i1]] <- cbind(data1[[i1]], fake_x = NA)
data1[[i1]][, "fake_x"] <- as.numeric(data1[[i1]][, "fake_x"])
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL ", ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), " ARGUMENT ASSOCIATED TO ", ifelse(length(geom) == 1, "geom", paste0("geom NUMBER ", i1)), " ARGUMENT ", geom[[i1]], " -> FAKE COLUMN ADDED TO DATA FRAME ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", NAMED \"fake_x\" FOR FINAL DRAWING")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}else{
if(all(geom[[i1]] == "geom_hline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ": x ARGUMENT MUST BE NULL IF ", ifelse(length(geom) == 1, "geom", paste0("geom NUMBER ", i1)), " ARGUMENT IS \"geom_hline\"\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
tempo <- fun_param_check(data = x[[i1]], data.name = ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
}
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if(is.null(y[[i1]])){
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if(all(geom[[i1]] != "geom_vline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ": y ARGUMENT CANNOT BE NULL EXCEPT IF ", ifelse(length(geom) == 1, "y", paste0("geom NUMBER ", i1)), " ARGUMENT IS \"geom_vline\"\nHERE geom ARGUMENT IS: ", paste(geom[[i1]], collapse = " "), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else{
y[[i1]] <- "fake_y"
data1[[i1]] <- cbind(data1[[i1]], fake_y = NA)
data1[[i1]][, "fake_y"] <- as.numeric(data1[[i1]][, "fake_y"])
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL ", ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), " ARGUMENT ASSOCIATED TO ", ifelse(length(geom) == 1, "geom", paste0("geom NUMBER ", i1)), " ARGUMENT ", geom[[i1]], " -> FAKE COLUMN ADDED TO DATA FRAME ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", NAMED \"fake_y\" FOR FINAL DRAWING")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}else{
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if(all(geom[[i1]] == "geom_vline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ": y ARGUMENT MUST BE NULL IF ", ifelse(length(geom) == 1, "geom", paste0("geom NUMBER ", i1)), " ARGUMENT IS \"geom_vline\"\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
tempo <- fun_param_check(data = y[[i1]], data.name = ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
}
if( ! (x[[i1]] %in% names(data1[[i1]]))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), " ARGUMENT MUST BE A COLUMN NAME OF ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
if( ! (y[[i1]] %in% names(data1[[i1]]))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), " ARGUMENT MUST BE A COLUMN NAME OF ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
# na detection and removal (done now to be sure of the correct length of categ)
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if(x[[i1]] == "fake_x" & y[[i1]] == "fake_y"){ # because the code cannot accept to be both "fake_x" and "fake_y" at the same time
tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 2\nTHE CODE CANNOT ACCEPT x AND y TO BE \"fake_x\" AND \"fake_y\" IN THE SAME DATA FRAME ", i1, " \n\n============\n\n"))
stop(tempo.cat)
}
if(any(is.na(data1[[i1]][, c(if(x[[i1]] == "fake_x"){NULL}else{x[[i1]]}, if(y[[i1]] == "fake_y"){NULL}else{y[[i1]]})]))){
tempo.removed.row.nb <- unlist(lapply(lapply(c(data1[[i1]][c(if(x[[i1]] == "fake_x"){NULL}else{x[[i1]]}, if(y[[i1]] == "fake_y"){NULL}else{y[[i1]]})]), FUN = is.na), FUN = which))
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removed.row.nb[[i1]] <- c(removed.row.nb[[i1]], tempo.removed.row.nb)
# report of removed rows will be performed at the very end
data1[[i1]] <- data1[[i1]][-tempo.removed.row.nb, ]
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NA DETECTED IN COLUMN ", if(x[[i1]] == "fake_x"){""}else{ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1))}, if(x[[i1]] != "fake_x" & y[[i1]] != "fake_y"){" AND "}, if(y[[i1]] == "fake_y"){""}else{ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1))}, " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ". CORRESPONDING ROWS HAVE BEEN REMOVED (SEE $removed.row.nb AND $removed.rows)")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
# end na detection and removal (done now to be sure of the correct length of categ)
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tempo <- fun_param_check(data = data1[[i1]][, x[[i1]]], data.name = ifelse(length(x) == 1, "x OF data1", paste0("x NUMBER ", i1, " OF data1 NUMBER ", i1)), class = "vector", mode = "numeric", na.contain = ifelse(x[[i1]] == "fake_x", TRUE, FALSE), fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = data1[[i1]][, y[[i1]]], data.name = ifelse(length(y) == 1, "y OF data1", paste0("y NUMBER ", i1, " OF data1 NUMBER ", i1)), class = "vector", mode = "numeric", na.contain = ifelse(y[[i1]] == "fake_y", TRUE, FALSE), fun.name = function.name) ; eval(ee)
if(( ! is.null(categ)) & ( ! is.null(categ[[i1]]))){ # if categ[[i1]] = NULL, fake_categ will be created later on
tempo <- fun_param_check(data = categ[[i1]], data.name = ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)),, class = "vector", mode = "character", length = 1, fun.name = function.name)
if( ! (categ[[i1]] %in% names(data1[[i1]]))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " ARGUMENT MUST BE A COLUMN NAME OF ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
# na detection and removal (done now to be sure of the correct length of categ)
if(any(is.na(data1[[i1]][, categ[[i1]]]))){
tempo.removed.row.nb <- unlist(lapply(lapply(c(data1[[i1]][categ[[i1]]]), FUN = is.na), FUN = which))
removed.row.nb[[i1]] <- c(removed.row.nb[[i1]], tempo.removed.row.nb)
# report of removed rows will be performed at the very end
data1[[i1]] <- data1[[i1]][-tempo.removed.row.nb, ]
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": IN ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", THE CATEGORY COLUMN:\n", paste(categ[[i1]], collapse = " "), "\nCONTAINS NA")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
# end na detection and removal (done now to be sure of the correct length of categ)
tempo1 <- fun_param_check(data = data1[[i1]][, categ[[i1]]], data.name = ifelse(length(categ) == 1, "categ OF data1", paste0("categ NUMBER ", i1, " OF data1 NUMBER ", i1)), class = "vector", mode = "character", na.contain = FALSE, fun.name = function.name, print = FALSE)
tempo2 <- fun_param_check(data = data1[[i1]][, categ[[i1]]], data.name = ifelse(length(categ) == 1, "categ OF data1", paste0("categ NUMBER ", i1, " OF data1 NUMBER ", i1)), class = "factor", na.contain = FALSE, fun.name = function.name, print = FALSE)
if(tempo1$problem == TRUE & tempo2$problem == TRUE){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(categ) == 1, "categ OF data1", paste0("categ NUMBER ", i1, " OF data1 NUMBER ", i1)), " MUST BE A FACTOR OR CHARACTER VECTOR\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else if(tempo1$problem == FALSE){
data1[[i1]][, categ[[i1]]] <- factor(data1[[i1]][, categ[[i1]]]) # if already a factor, change nothing, if characters, levels according to alphabetical order
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": IN ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", THE CHARACTER COLUMN HAS BEEN CONVERTED TO FACTOR")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))

}
if(geom[[i1]] == "geom_vline" | geom[[i1]] == "geom_hline"){
if(length(unique(data1[[i1]][, categ[[i1]]])) != nrow(data1[[i1]])){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(geom) == 1, "geom OF data1", paste0("geom NUMBER ", i1, " OF data1 NUMBER ", i1)), " ARGUMENT IS ", geom[[i1]], ", MEANING THAT ", ifelse(length(categ) == 1, "categ OF data1", paste0("categ NUMBER ", i1, " OF data1 NUMBER ", i1)), " MUST HAVE A DIFFERENT CLASS PER LINE OF data1 (ONE x VALUE PER CLASS)\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
}
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}else if(( ! is.null(categ)) & is.null(categ[[i1]])){ # if categ[[i1]] = NULL, fake_categ will be created. BEWARE: is.null(categ[[i1]]) means no legend display (see above), because categ has not been precised. This also means a single color for data1[[i1]]
if(length(color[[i1]]) > 1){ # 0 means is.null(color[[i1]]) and 1 is ok -> single color for data1[[i1]]
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " ARGUMENT BUT CORRESPONDING COLORS IN ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " HAS LENGTH OVER 1\n", paste(color[[i1]], collapse = " "), "\nWHICH IS NOT COMPATIBLE WITH NULL CATEG -> COLOR RESET TO A SINGLE COLOR")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
color[[i1]] <- NULL # will provide a single color below
}
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categ[[i1]] <- "fake_categ"
data1[[i1]] <- cbind(data1[[i1]], fake_categ = "")
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# inactivated because give a different color to different "Line_" categ while a single color for all the data1[[i1]] required. Thus, put back after the color management
# if(geom[[i1]] == "geom_hline" | geom[[i1]] == "geom_vline"){
# data1[[i1]][, "fake_categ"] <- paste0("Line_", 1:nrow(data1[[i1]]))
# }else{
data1[[i1]][, "fake_categ"] <- data1[[i1]][, "fake_categ"] # as.numeric("") create a vector of NA but class numeric
# }
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " ARGUMENT -> FAKE COLUMN ADDED TO DATA FRAME ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", NAMED \"fake_categ\" FOR FINAL DRAWING")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
if( ! is.null(legend.name[[i1]])){
tempo <- fun_param_check(data = legend.name[[i1]], data.name = ifelse(length(legend.name) == 1, "legend.name", paste0("legend.name NUMBER ", i1)),, class = "vector", mode = "character", length = 1, fun.name = function.name)
}
if( ! is.null(color)){ # if color is NULL, will be filled later on
# check the nature of color
if(is.null(color[[i1]])){
compart.null.color <- compart.null.color + 1
color[[i1]] <- grey(compart.null.color / 8) # cannot be more than 7 overlays. Thus 7 different greys. 8/8 is excluded because white dots
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL COLOR IN ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", SINGLE COLOR ", paste(color[[i1]], collapse = " "), " HAS BEEN ATTRIBUTED")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
tempo1 <- fun_param_check(data = color[[i1]], data.name = ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), class = "vector", mode = "character", na.contain = TRUE, fun.name = function.name, print = FALSE)
tempo2 <- fun_param_check(data = color[[i1]], data.name = ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), class = "factor", na.contain = TRUE, fun.name = function.name, print = FALSE)
if(tempo1$problem == TRUE & tempo2$problem == TRUE){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " MUST BE A FACTOR OR CHARACTER VECTOR OR INTEGER VECTOR\n\n================\n\n") # integer possible because dealt above
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else if( ! (all(color[[i1]] %in% colors() | grepl(pattern = "^#", color[[i1]])))){ # check that all strings of low.color start by #
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST BE A HEXADECIMAL COLOR VECTOR STARTING BY # AND/OR COLOR NAMES GIVEN BY colors(): ", paste(unique(color[[i1]]), collapse = " "), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
if(any(is.na(color[[i1]]))){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": IN ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", THE COLORS:\n", paste(unique(color[[i1]]), collapse = " "), "\nCONTAINS NA")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
# end check the nature of color
# check the length of color
if(is.null(categ) & length(color[[i1]]) != 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST BE A SINGLE COLOR IF categ IS NULL\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else if( ! is.null(categ)){
# No problem of NA management by ggplot2 because already removed
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if(categ[[i1]] == "fake_categ" & length(color[[i1]]) != 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST BE A SINGLE COLOR IF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IS NULL\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}else if(length(color[[i1]]) == length(unique(data1[[i1]][, categ[[i1]]]))){ # here length(color) is equal to the different number of categ
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data1[[i1]][, categ[[i1]]] <- factor(data1[[i1]][, categ[[i1]]]) # if already a factor, change nothing, if characters, levels according to alphabetical order
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": IN ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", THE FOLLOWING COLORS:\n", paste(color[[i1]], collapse = " "), "\nHAVE BEEN ATTRIBUTED TO THESE CLASSES:\n", paste(levels(factor(data1[[i1]][, categ[[i1]]])), collapse = " "))
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}else if(length(color[[i1]]) == length(data1[[i1]][, categ[[i1]]])){# here length(color) is equal to nrow(data1[[i1]]) -> Modif to have length(color) equal to the different number of categ (length(color) == length(levels(data1[[i1]][, categ[[i1]]])))
data1[[i1]] <- cbind(data1[[i1]], color = color[[i1]])
tempo.check <- unique(data1[[i1]][ , c(categ[[i1]], "color")])
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if( ! (nrow(data1[[i1]]) == length(color[[i1]]) & nrow(tempo.check) == length(unique(data1[[i1]][ , categ[[i1]]])))){
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tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT HAS THE LENGTH OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), " COLUMN VALUES\nBUT IS INCORRECTLY ASSOCIATED TO EACH CLASS OF THIS categ:\n", paste(unique(mapply(FUN = "paste", data1[[i1]][ ,categ[[i1]]], data1[[i1]][ ,"color"])), collapse = "\n"), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else{
data1[[i1]][, categ[[i1]]] <- factor(data1[[i1]][, categ[[i1]]]) # if already a factor, change nothing, if characters, levels according to alphabetical order
color[[i1]] <- unique(color[[i1]][order(data1[[i1]][, categ[[i1]]])]) # Modif to have length(color) equal to the different number of categ (length(color) == length(levels(data1[[i1]][, categ[[i1]]])))
tempo.warning <- paste0(ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT HAS THE LENGTH OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), " COLUMN VALUES\nCOLORS HAVE BEEN RESPECTIVELY ASSOCIATED TO EACH CLASS OF categ AS:\n", paste(levels(factor(data1[[i1]][, categ[[i1]]])), collapse = " "), "\n", paste(color[[i1]], collapse = " "))
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}else if(length(color[[i1]]) == 1){
data1[[i1]][, categ[[i1]]] <- factor(data1[[i1]][, categ[[i1]]]) # if already a factor, change nothing, if characters, levels according to alphabetical order
color[[i1]] <- rep(color[[i1]], length(levels(data1[[i1]][, categ[[i1]]])))
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": IN ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), ", COLOR HAS LENGTH 1 MEANING THAT ALL THE DIFFERENT CLASSES OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), "\n", paste(levels(factor(data1[[i1]][, categ[[i1]]])), collapse = " "), "\nWILL HAVE THE SAME COLOR\n", paste(color[[i1]], collapse = " "))
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}else{
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST BE (1) LENGTH 1, OR (2) THE LENGTH OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), " COLUMN VALUES, OR (3) THE LENGTH OF THE CLASSES IN THIS COLUMN. HERE IT IS COLOR LENGTH ", length(color[[i1]]), " VERSUS CATEG LENGTH ", length(data1[[i1]][, categ[[i1]]]), " AND CATEG CLASS LENGTH ", length(unique(data1[[i1]][, categ[[i1]]])), "\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
}
}
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if((geom[[i1]] == "geom_hline" | geom[[i1]] == "geom_vline") & ! is.null(categ[[i1]])){ # add here after the color management, to deal with the different lines to plot inside any data[[i1]]
if(categ[[i1]] == "fake_categ"){
data1[[i1]][, "fake_categ"] <- paste0("Line_", 1:nrow(data1[[i1]]))
}
}
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tempo <- fun_param_check(data = alpha[[i1]], data.name = ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), prop = TRUE, length = 1, fun.name = function.name) ; eval(ee)
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}
if(length(data1) > 1){
if(length(unique(unlist(x))) > 1){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": THE x ARGUMENT DOES NOT CONTAIN IDENTICAL COLUMN NAMES:\n", paste(unlist(x), collapse = " "), "\nX-AXIS OVERLAYING DIFFERENT VARIABLES?")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}
if(length(data1) > 1){
if(length(unique(unlist(y))) > 1){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": THE y ARGUMENT DOES NOT CONTAIN IDENTICAL COLUMN NAMES:\n", paste(unlist(y), collapse = " "), "\nY-AXIS OVERLAYING DIFFERENT VARIABLES?")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}
if(sum(geom %in% "geom_point") > 3){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": geom ARGUMENT CANNOT HAVE MORE THAN FOUR \"geom_point\" ELEMENTS\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}else if(length(geom) - sum(geom %in% "geom_point") > 3){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": geom ARGUMENT CANNOT HAVE MORE THAN THREE LINE ELEMENTS\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
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}
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tempo <- fun_param_check(data = dot.size, class = "vector", mode = "numeric", length = 1, neg.values = FALSE, fun.name = function.name) ; eval(ee)
tempo <- fun_param_check(data = line.size, class = "vector", mode = "numeric", length = 1, neg.values = FALSE, fun.name = function.name) ; eval(ee)
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if( ! is.null(xlim)){
tempo <- fun_param_check(data = xlim, class = "vector", mode = "numeric", length = 2, fun.name = function.name) ; eval(ee)
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if(tempo$problem == FALSE & any(xlim %in% c(Inf, -Inf))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": xlim ARGUMENT CANNOT CONTAIN -Inf OR Inf VALUES\n\n================\n\n")
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cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
if( ! is.null(xlab)){
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if(all(class(xlab) %in% "expression")){ # to deal with math symbols
tempo <- fun_param_check(data = xlab, class = "expression", length = 1, fun.name = function.name) ; eval(ee)
}else{
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tempo <- fun_param_check(data = xlab, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
}
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}
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tempo <- fun_param_check(data = xlog, options = c("no", "log2", "log10"), length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & xlog != "no"){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": xlog ARGUMENT SET TO ", xlog, ".\nVALUES FROM THE x ARGUMENT COLUMN OF THE data1 DATA FRAME MUST BE ALREADY ", toupper(xlog), " TRANSFORMED, AS THE xlog ARGUMENT JUST MODIFIES THE AXIS SCALE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
if( ! is.null(xlim)){
if(any(xlim <= 0)){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": xlim ARGUMENT CAN SPAN ZERO OR NEGATIVE VALUES IF xlog ARGUMENT IS SET TO ", xlog, " BECAUSE THIS LATTER ARGUMENT DOES NOT TRANSFORM DATA, JUST MODIFIES THE AXIS SCALE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
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}
}
}
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if( ! is.null(x.tick.nb)){
tempo <- fun_param_check(data = x.tick.nb, class = "vector", typeof = "integer", length = 1, double.as.integer.allowed = TRUE, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & x.tick.nb < 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": x.tick.nb ARGUMENT MUST BE A NON NULL POSITIVE INTEGER\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
if( ! is.null(x.inter.tick.nb)){
tempo <- fun_param_check(data = x.inter.tick.nb, class = "vector", typeof = "integer", length = 1, double.as.integer.allowed = TRUE, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & x.inter.tick.nb < 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": x.inter.tick.nb ARGUMENT MUST BE A NON NULL POSITIVE INTEGER\n\n================\n\n")
cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
}
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}
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tempo <- fun_param_check(data = x.left.extra.margin, prop = TRUE, length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_param_check(data = x.right.extra.margin, prop = TRUE, length = 1, fun.name = function.name) ; eval(ee)
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if( ! is.null(ylim)){
tempo <- fun_param_check(data = ylim, class = "vector", mode = "numeric", length = 2, fun.name = function.name) ; eval(ee)
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if(tempo$problem == FALSE & any(ylim %in% c(Inf, -Inf))){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": ylim ARGUMENT CANNOT CONTAIN -Inf OR Inf VALUES\n\n================\n\n")
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cat(tempo.cat)
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arg.check <- c(arg.check, TRUE)
}
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}
if( ! is.null(ylab)){
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if(all(class(ylab) %in% "expression")){ # to deal with math symbols
tempo <- fun_param_check(data = ylab, class = "expression", length = 1, fun.name = function.name) ; eval(ee)
}else{
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tempo <- fun_param_check(data = ylab, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
}
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}
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tempo <- fun_param_check(data = ylog, options = c("no", "log2", "log10"), length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & ylog != "no"){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": ylog ARGUMENT SET TO ", ylog, ".\nVALUES FROM THE y ARGUMENT COLUMN OF THE data1 DATA FRAME MUST BE ALREADY ", toupper(ylog), " TRANSFORMED, AS THE ylog ARGUMENT JUST MODIFIES THE AXIS SCALE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
if( ! is.null(ylim)){
if(any(ylim <= 0)){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": ylim ARGUMENT CAN SPAN ZERO OR NEGATIVE VALUES IF ylog ARGUMENT IS SET TO ", ylog, " BECAUSE THIS LATTER ARGUMENT DOES NOT TRANSFORM DATA, JUST MODIFIES THE AXIS SCALE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
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}
}
}
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if( ! is.null(y.tick.nb)){
tempo <- fun_param_check(data = y.tick.nb, class = "vector", typeof = "integer", length = 1, double.as.integer.allowed = TRUE, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & y.tick.nb < 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": y.tick.nb ARGUMENT MUST BE A NON NULL POSITIVE INTEGER\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
if( ! is.null(y.inter.tick.nb)){
tempo <- fun_param_check(data = y.inter.tick.nb, class = "vector", typeof = "integer", length = 1, double.as.integer.allowed = TRUE, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & y.inter.tick.nb < 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": y.inter.tick.nb ARGUMENT MUST BE A NON NULL POSITIVE INTEGER\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
tempo <- fun_param_check(data = y.top.extra.margin, prop = TRUE, length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_param_check(data = y.bottom.extra.margin, prop = TRUE, length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_param_check(data = xy.include.zero, class = "vector", mode = "logical", length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & ylog == TRUE & xy.include.zero == TRUE){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": BOTH ylog AND xy.include.zero ARGUMENTS SET TO TRUE -> xy.include.zero ARGUMENT RESET TO FALSE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
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tempo <- fun_param_check(data = text.size, class = "vector", mode = "numeric", length = 1, neg.values = FALSE, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = title, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
tempo <- fun_param_check(data = title.text.size, class = "vector", mode = "numeric", length = 1, neg.values = FALSE, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = show.legend, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = classic, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = grid, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = raster, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
if( ! is.null(vectorial.limit)){
tempo <- fun_param_check(data = vectorial.limit, class = "vector", typeof = "integer", neg.values = FALSE, double.as.integer.allowed = TRUE, fun.name = function.name) ; eval(ee)
}
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tempo <- fun_param_check(data = return, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
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tempo <- fun_param_check(data = plot, class = "logical", length = 1, fun.name = function.name) ; eval(ee)
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if( ! is.null(add)){
tempo <- fun_param_check(data = add, class = "vector", mode = "character", length = 1, fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & ! grepl(pattern = "^\\+", add)){ # check that the add string start by +
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": add ARGUMENT MUST START WITH \"+\": ", paste(unique(add), collapse = " "), "\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
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}else if(tempo$problem == FALSE & ! grepl(pattern = "ggplot2::", add)){ #
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tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": add ARGUMENT MUST CONTAIN \"ggplot2::\" IN FRONT OF EACH GGPLOT2 FUNCTION: ", paste(unique(add), collapse = " "), "\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
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}else if(tempo$problem == FALSE & ! grepl(pattern = ")$", add)){ # check that the add string finished by )
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tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": add ARGUMENT MUST FINISH BY \")\": ", paste(unique(add), collapse = " "), "\n\n================\n\n")
cat(tempo.cat)
arg.check <- c(arg.check, TRUE)
}
}
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if( ! is.null(path.lib)){
tempo <- fun_param_check(data = path.lib, class = "vector", mode = "character", fun.name = function.name) ; eval(ee)
if(tempo$problem == FALSE & ! all(dir.exists(path.lib))){
cat(paste0("\n\n============\n\nERROR IN ", function.name, ": \nDIRECTORY PATH INDICATED IN THE path.lib PARAMETER DOES NOT EXISTS: ", path.lib, "\n\n============\n\n"))
arg.check <- c(arg.check, TRUE)
}
}
if(any(arg.check) == TRUE){
stop() # nothing else because print = TRUE by default in fun_param_check()
}
# 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_param_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_param_check()
# end argument checking
# package checking
fun_pack_import(req.package = c("ggplot2"), path.lib = path.lib)
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# packages Cairo and grid tested by fun_gg_point_rast()
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# end package checking
# main code
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# axes management
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if(is.null(xlim)){
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if(any(unlist(mapply(FUN = "[[", data1, x, SIMPLIFY = FALSE)) %in% c(Inf, -Inf))){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": THE x COLUMN IN data1 CONTAINS -Inf OR Inf VALUES THAT WILL NOT BE CONSIDERED IN THE PLOT RANGE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
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xlim <- suppressWarnings(range(unlist(mapply(FUN = "[[", data1, x, SIMPLIFY = FALSE)), na.rm = TRUE, finite = TRUE)) # finite = TRUE removes all the -Inf and Inf except if only this. In that case, whatever the -Inf and/or Inf present, output -Inf;Inf range. Idem with NA only. xlim added here. If NULL, ok if x argument has values
if(suppressWarnings(all(xlim %in% c(Inf, -Inf)))){
if(all(unlist(geom) == "geom_hline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " NOT POSSIBLE TO ONLY DRAW geom_hline KIND OF LINES IF xlim ARGUMENT IS SET TO NULL, SINCE NO X-AXIS DEFINED (", ifelse(length(x) == 1, "x", paste0("x NUMBER ", i1)), " ARGUMENT MUST BE NULL FOR THESE KIND OF LINES)\n\n================\n\n")
stop(tempo.cat)
}else{
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " xlim ARGUMENT MADE OF NA, -Inf OR Inf ONLY: ", paste(xlim, collapse = " "), "\n\n================\n\n")
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stop(tempo.cat)
}
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}
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}
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xlim.order <- order(xlim) # to deal with inverse axis
xlim <- sort(xlim)
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xlim[1] <- xlim[1] - abs(xlim[2] - xlim[1]) * ifelse(diff(xlim.order) > 0, x.right.extra.margin, x.left.extra.margin) # diff(xlim.order) > 0 means not inversed axis
xlim[2] <- xlim[2] + abs(xlim[2] - xlim[1]) * ifelse(diff(xlim.order) > 0, x.left.extra.margin, x.right.extra.margin) # diff(xlim.order) > 0 means not inversed axis
if(xy.include.zero == TRUE){ # no need to check xlog != "no" because done before
xlim <- range(c(xlim, 0), na.rm = TRUE, finite = TRUE) # finite = TRUE removes all the -Inf and Inf except if only this. In that case, whatever the -Inf and/or Inf present, output -Inf;Inf range. Idem with NA only
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}
xlim <- xlim[xlim.order]
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# if(xlog != "no" & any(xlim < 0)){
# tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": FINAL xlim RANGE SPAN NULL OR NEGATIVE VALUES:", paste(xlim, collapse = " "), "\nWHICH IS IMCOMPATIBLE WITH xlog PARAMETER SET TO log10 OR log2\n\n================\n\n")
# stop(tempo.cat)
# }
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if(is.null(ylim)){
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if(any(unlist(mapply(FUN = "[[", data1, y, SIMPLIFY = FALSE)) %in% c(Inf, -Inf))){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": THE y COLUMN IN data1 CONTAINS -Inf OR Inf VALUES THAT WILL NOT BE CONSIDERED IN THE PLOT RANGE")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
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ylim <- suppressWarnings(range(unlist(mapply(FUN = "[[", data1, y, SIMPLIFY = FALSE)), na.rm = TRUE, finite = TRUE)) # finite = TRUE removes all the -Inf and Inf except if only this. In that case, whatever the -Inf and/or Inf present, output -Inf;Inf range. Idem with NA only. ylim added here. If NULL, ok if y argument has values
if(suppressWarnings(all(ylim %in% c(Inf, -Inf)))){ # happen when y is only NULL
if(all(unlist(geom) == "geom_vline")){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " NOT POSSIBLE TO ONLY DRAW geom_vline KIND OF LINES IF ylim ARGUMENT IS SET TO NULL, SINCE NO Y-AXIS DEFINED (", ifelse(length(y) == 1, "y", paste0("y NUMBER ", i1)), " ARGUMENT MUST BE NULL FOR THESE KIND OF LINES)\n\n================\n\n")
stop(tempo.cat)
}else{
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " ylim ARGUMENT MADE OF NA, -Inf OR Inf ONLY: ", paste(ylim, collapse = " "), "\n\n================\n\n")
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stop(tempo.cat)
}
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}
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}
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ylim.order <- order(ylim) # to deal with inverse axis
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ylim <- sort(ylim)
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ylim[1] <- ylim[1] - abs(ylim[2] - ylim[1]) * ifelse(diff(ylim.order) > 0, y.bottom.extra.margin, y.top.extra.margin) # diff(ylim.order) > 0 means not inversed axis
ylim[2] <- ylim[2] + abs(ylim[2] - ylim[1]) * ifelse(diff(ylim.order) > 0, y.top.extra.margin, y.bottom.extra.margin) # diff(ylim.order) > 0 means not inversed axis
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if(xy.include.zero == TRUE){ # no need to check ylog != "no" because done before
ylim <- range(c(ylim, 0), na.rm = TRUE, finite = TRUE) # finite = TRUE removes all the -Inf and Inf except if only this. In that case, whatever the -Inf and/or Inf present, output -Inf;Inf range. Idem with NA only
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}
ylim <- ylim[ylim.order]
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# if(ylog != "no" & any(ylim < 0)){
# tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": FINAL ylim RANGE SPAN NULL OR NEGATIVE VALUES:", paste(ylim, collapse = " "), "\nWHICH IS IMCOMPATIBLE WITH ylog PARAMETER SET TO log10 OR log2\n\n================\n\n")
# stop(tempo.cat)
# }
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# end axes management
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# create a fake categ if NULL to deal with legend display
if(is.null(categ)){
categ <- vector("list", length(data1))
categ[] <- "fake_categ"
for(i2 in 1:length(data1)){
data1[[i2]] <- cbind(data1[[i2]], fake_categ = "")
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if(geom[[i2]] == "geom_hline" | geom[[i2]] == "geom_vline"){
data1[[i2]][, "fake_categ"] <- paste0("Line_", 1:nrow(data1[[i2]]))
}
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}
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL categ ARGUMENT -> FAKE COLUMN ADDED TO EACH DATA FRAME IN data1, NAMED \"fake_categ\" AND FILLED WITH \"\"")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
# end create a fake categ if NULL to deal with legend display
# vector of color with length as in data1
if(is.null(color)){
color <- vector("list", length(data1))
length.categ.list <- lapply(lapply(mapply(FUN = "[[", data1, categ, SIMPLIFY = FALSE), FUN = unique), FUN = function(x){length(x[ ! is.na(x)])})
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length.categ.list[sapply(categ, FUN = "==", "fake_categ")] <- 1 # when is.null(color), a single color for all the dots or lines of data[[i1]] that contain "fake_categ" category
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total.categ.length <- sum(unlist(length.categ.list), na.rm = TRUE)
tempo.color <- fun_gg_palette(total.categ.length)
tempo.count <- 0
for(i3 in 1:length(data1)){
color[[i3]] <- tempo.color[(1:length.categ.list[[i3]]) + tempo.count]
tempo.count <- tempo.count + length.categ.list[[i3]]
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": NULL color ARGUMENT -> COLORS RESPECTIVELY ATTRIBUTED TO EACH CLASS OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i3)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i3)), ":\n", paste(unlist(color), collapse = " "), "\n", paste(names(data1), collapse = " "))
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}
# end vector of color with length as in data1
# last check
for(i1 in 1:length(data1)){
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if(categ[[i1]] != "fake_categ" & length(color[[i1]]) != length(unique(data1[[i1]][, categ[[i1]]]))){
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tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " LAST CHECK: ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST HAVE THE LENGTH OF LEVELS OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), "\nHERE IT IS COLOR LENGTH ", length(color[[i1]]), " VERSUS CATEG LEVELS LENGTH ", length(unique(data1[[i1]][, categ[[i1]]])), "\n\n================\n\n")
stop(tempo.cat)
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}else if(categ[[i1]] == "fake_categ" & length(color[[i1]]) != 1){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " LAST CHECK: ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST HAVE LENGTH 1 WHEN ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IS NULL\nHERE IT IS COLOR LENGTH ", length(color[[i1]]), "\n\n================\n\n")
stop(tempo.cat)
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}
}
# end last check
# conversion of geom_hline and geom_vline
for(i1 in 1:length(data1)){
if(geom[[i1]] == "geom_hline" | geom[[i1]] == "geom_vline"){
final.data.frame <- data.frame()
for(i3 in 1:nrow(data1[[i1]])){
tempo.data.frame <- rbind(data1[[i1]][i3, ], data1[[i1]][i3, ])
if(geom[[i1]] == "geom_hline"){
tempo.data.frame[, x[[i1]]] <- xlim
}else if(geom[[i1]] == "geom_vline"){
tempo.data.frame[, y[[i1]]] <- ylim
}else{
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tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 3\n\n============\n\n"))
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stop(tempo.cat)
}
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# if(is.null(categ[[i1]])){
# data1[, "fake_categ"] <- paste0("Line_", i3)
# } #I put that up
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final.data.frame <- rbind(final.data.frame, tempo.data.frame)
}
data1[[i1]] <- final.data.frame
geom[[i1]] <- "geom_line"
if(length(color[[i1]]) == 1){
color[[i1]] <- rep(color[[i1]], length(unique(data1[[i1]][ , categ[[i1]]])))
}else if(length(color[[i1]]) != length(unique(data1[[i1]][ , categ[[i1]]]))){
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tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, " geom_hline AND geom_vline CONVERSION TO FIT THE XLIM AND YLIM LIMITS OF THE DATA: ", ifelse(length(color) == 1, "color", paste0("color NUMBER ", i1)), " ARGUMENT MUST HAVE THE LENGTH OF LEVELS OF ", ifelse(length(categ) == 1, "categ", paste0("categ NUMBER ", i1)), " IN ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i1)), "\nHERE IT IS COLOR LENGTH ", length(color[[i1]]), " VERSUS CATEG LEVELS LENGTH ", length(unique(data1[[i1]][, categ[[i1]]])), "\n\n================\n\n")
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stop(tempo.cat)
}
}
}
# end conversion of geom_hline and geom_vline
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# kind of geom_point (vectorial or raster)
scatter.kind <- vector("list", length = length(data1)) # list of same length as data1, that will be used to use either ggplot2::geom_point() (vectorial dot layer) or fun_gg_point_rast() (raster dot layer)
fix.ratio <- FALSE
if(is.null(vectorial.limit)){
if(raster == TRUE){
scatter.kind[] <- "fun_gg_point_rast" # not important to fill everything: will be only used when geom == "geom_point"
fix.ratio <- TRUE
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": RASTER PLOT GENERATED -> ASPECT RATIO OF THE PLOT REGION SET TO 1/1 TO AVOID A BUG OF ELLIPSOID DOT DRAWING")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}else{
scatter.kind[] <- "ggplot2::geom_point"
}
}else{
for(i2 in 1:length(data1)){
if(geom[[i2]] == "geom_point"){
if(nrow(data1[[i2]]) <= vectorial.limit){
scatter.kind[[i2]] <- "ggplot2::geom_point"
}else{
scatter.kind[[i2]] <- "fun_gg_point_rast"
fix.ratio <- TRUE
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": ", ifelse(length(data1) == 1, "data1", paste0("data1 NUMBER ", i2)), " LAYER AS RASTER (NOT VECTORIAL)")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}
}
if(any(unlist(scatter.kind) == "fun_gg_point_rast")){
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": RASTER PLOT GENERATED -> ASPECT RATIO OF THE PLOT REGION SET TO 1/1 TO AVOID A BUG OF ELLIPSOID DOT DRAWING")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
}
# end kind of geom_point (vectorial or raster)
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tempo.gg.name <- "gg.indiv.plot."
tempo.gg.count <- 0
# no need loop part
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::ggplot())
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::xlab(if(is.null(xlab)){x[[1]]}else{xlab}))
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::ylab(if(is.null(ylab)){y[[1]]}else{ylab}))
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::ggtitle(title))
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add.check <- TRUE
if( ! is.null(add)){ # if add is NULL, then = 0
if(grepl(pattern = "ggplot2::theme", add) == TRUE){
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tempo.warning <- paste0("FROM FUNCTION ", function.name, ": \"ggplot2::theme\" STRING DETECTED IN THE add ARGUMENT -> INTERNAL GGPLOT2 THEME FUNCTIONS theme() AND theme_classic() HAVE BEEN INACTIVATED, TO BE USED BY THE USER.
\nIT IS RECOMMENDED TO USE \"+ theme(aspect.ratio = 1)\" IF RASTER MODE IS ACTIVATED")
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warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
add.check <- FALSE
}
}
if(add.check == TRUE & classic == TRUE){
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# BEWARE: not possible to add several times theme(). NO message but the last one overwrites the others
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::theme_classic(base_size = text.size))
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if(grid == TRUE){
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), m.gg <- ggplot2::theme(
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text = ggplot2::element_text(size = text.size), 
plot.title = ggplot2::element_text(size = title.text.size), # stronger than text
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line = ggplot2::element_line(size = 0.5), 
axis.line.y.left = ggplot2::element_line(colour = "black"), # draw lines for the y axis
axis.line.x.bottom = ggplot2::element_line(colour = "black"), # draw lines for the x axis
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panel.grid.major.x = ggplot2::element_line(colour = "grey75"),
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panel.grid.major.y = ggplot2::element_line(colour = "grey75"),
aspect.ratio = if(fix.ratio == TRUE){1}else{NULL}
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))
}else{
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), m.gg <- ggplot2::theme(
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text = ggplot2::element_text(size = text.size), 
plot.title = ggplot2::element_text(size = title.text.size), # stronger than text
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line = ggplot2::element_line(size = 0.5), 
axis.line.y.left = ggplot2::element_line(colour = "black"), 
axis.line.x.bottom = ggplot2::element_line(colour = "black"), 
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aspect.ratio = if(fix.ratio == TRUE){1}else{NULL}
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))
}
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}else if(add.check == TRUE & classic == FALSE){
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), m.gg <- ggplot2::theme(
text = ggplot2::element_text(size = text.size), 
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plot.title = ggplot2::element_text(size = title.text.size), # stronger than text
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line = ggplot2::element_line(size = 0.5), 
panel.background = ggplot2::element_rect(fill = "grey95"), 
axis.line.y.left = ggplot2::element_line(colour = "black"), 
axis.line.x.bottom = ggplot2::element_line(colour = "black"), 
panel.grid.major.x = ggplot2::element_line(colour = "grey75"), 
panel.grid.major.y = ggplot2::element_line(colour = "grey75"), 
panel.grid.minor.x = ggplot2::element_blank(), 
panel.grid.minor.y = ggplot2::element_blank(), 
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strip.background = ggplot2::element_rect(fill = "white", colour = "black"), 
aspect.ratio = if(fix.ratio == TRUE){1}else{NULL}
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# do not work -> legend.position = "none" # to remove the legend completely: https://www.datanovia.com/en/blog/how-to-remove-legend-from-a-ggplot/
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))
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}
# end no need loop part
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# loop part
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point.count <- 0
line.count <- 0
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lg.order <- vector(mode = "list", length = 6) # order of the legend
lg.order <- lapply(lg.order, as.numeric) # order of the legend
lg.color <- vector(mode = "list", length = 6) # color of the legend
lg.alpha <- vector(mode = "list", length = 6) # order of the legend
lg.alpha <- lapply(lg.alpha, as.numeric) # alpha of the legend
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for(i1 in 1:length(data1)){
if(geom[[i1]] == "geom_point"){
point.count <- point.count + 1
if(point.count == 1){
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fin.lg.disp[[1]] <- legend.disp[[point.count + line.count]]
lg.order[[1]] <- point.count + line.count
lg.color[[1]] <- color[[i1]]
lg.alpha[[1]] <- alpha[[i1]]
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = scatter.kind[[i1]]))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], fill = categ[[i1]]), size = dot.size, color = color[[i1]][i5], alpha = alpha[[i1]])) # beware: a single color allowed for color argument  outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_fill_manual(name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = color[[i1]], guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], linetype = 0)))) # values are the values of fill. order determines the order in the legend
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}
if(point.count == 2){
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fin.lg.disp[[2]] <- legend.disp[[point.count + line.count]]
lg.order[[2]] <- point.count + line.count
lg.color[[2]] <- color[[i1]]
lg.alpha[[2]] <- alpha[[i1]]
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = scatter.kind[[i1]]))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], shape = categ[[i1]]), size = dot.size, color = color[[i1]][i5], alpha = alpha[[i1]])) # beware: a single color allowed for color argument  outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_shape_manual(name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = rep(19, length(color[[i1]])), guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], linetype = 0)))) # values are the values of shape
}
if(point.count == 3){
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fin.lg.disp[[3]] <- legend.disp[[point.count + line.count]]
lg.order[[3]] <- point.count + line.count
lg.color[[3]] <- color[[i1]]
lg.alpha[[3]] <- alpha[[i1]]
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = scatter.kind[[i1]]))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], stroke = categ[[i1]]), size = dot.size, color = color[[i1]][i5], alpha = alpha[[i1]])) # beware: a single color allowed for color argument  outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_discrete_manual(aesthetics = "stroke", name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = rep(0.5, length(color[[i1]])), guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], linetype = 0)))) # values are the values of stroke
}
}else{
line.count <- line.count + 1
if(line.count == 1){
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fin.lg.disp[[4]] <- legend.disp[[point.count + line.count]]
lg.order[[4]] <- point.count + line.count
lg.color[[4]] <- color[[i1]]
lg.alpha[[4]] <- 1 # to avoid a bug on windows: if alpha argument is different from 1 for lines (transparency), then lines are not correctly displayed in the legend when using the R GUI (bug https://github.com/tidyverse/ggplot2/issues/2452). No bug when using a pdf
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = paste("ggplot2::", geom[[i1]], sep ="")))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], linetype = categ[[i1]]), color = color[[i1]][i5], size = line.size, lineend = "round", alpha = alpha[[i1]])) # beware: a single color allowed for color argument  outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_discrete_manual(aesthetics = "linetype", name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = rep(1, length(color[[i1]])), guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], shape = NA)))) # values are the values of linetype. 1 means solid. Regarding the alpha bug, I have tried different things without success: alpha in guide alone, in geom alone, in both, with different values 
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}
if(line.count == 2){
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fin.lg.disp[[5]] <- legend.disp[[point.count + line.count]]
lg.order[[5]] <- point.count + line.count
lg.color[[5]] <- color[[i1]]
lg.alpha[[5]] <- 1 # to avoid a bug on windows: if alpha argument is different from 1 for lines (transparency), then lines are not correctly displayed in the legend when using the R GUI (bug https://github.com/tidyverse/ggplot2/issues/2452). No bug when using a pdf
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = paste("ggplot2::", geom[[i1]], sep ="")))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], alpha = categ[[i1]]), color = color[[i1]][i5], size = line.size, lineend = "round")) # beware: a single color allowed for color argument outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_discrete_manual(aesthetics = "alpha", name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = rep(alpha[[i1]], length(color[[i1]])), guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], shape = NA)))) # values are the values of linetype. 1 means solid. Regarding the alpha bug, I have tried different things without success: alpha in guide alone, in geom alone, in both, with different values 
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}
if(line.count == 3){
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fin.lg.disp[[6]] <- legend.disp[[point.count + line.count]]
lg.order[[6]] <- point.count + line.count
lg.color[[6]] <- color[[i1]]
lg.alpha[[6]] <- 1 # to avoid a bug on windows: if alpha argument is different from 1 for lines (transparency), then lines are not correctly displayed in the legend when using the R GUI (bug https://github.com/tidyverse/ggplot2/issues/2452). No bug when using a pdf
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class.categ <- levels(factor(data1[[i1]][, categ[[i1]]]))
for(i5 in 1:length(color[[i1]])){ # or length(class.categ). It is the same because already checked that lengths are the same
tempo.data.frame <- data1[[i1]][data1[[i1]][, categ[[i1]]] == class.categ[i5], ]
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), eval(parse(text = paste("ggplot2::", geom[[i1]], sep ="")))(data = tempo.data.frame, mapping = ggplot2::aes_string(x = x[[i1]], y = y[[i1]], size = categ[[i1]]), color = color[[i1]][i5], alpha = alpha[[i1]], lineend = "round")) # beware: a single color allowed for color argument  outside aesthetic, hence the loop # show.legend option do not remove the legend, only the aesthetic of the legend (dot, line, etc.)
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}
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assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_discrete_manual(aesthetics = "size", name = if(is.null(legend.name)){NULL}else{legend.name[[i1]]}, values = rep(line.size, length(color[[i1]])), guide = ggplot2::guide_legend(override.aes = list(colour = color[[i1]], shape = NA)))) # values are the values of linetype. 1 means solid. Regarding the alpha bug, I have tried different things without success: alpha in guide alone, in geom alone, in both, with different values 
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}
}
}
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# end loop part
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# legend display
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::guides(fill = if(fin.lg.disp[[1]] == TRUE){ggplot2::guide_legend(order = lg.order[[1]], override.aes = list(alpha = lg.alpha[[1]], color = lg.color[[1]]))}else{FALSE}, shape = if(fin.lg.disp[[2]] == TRUE){ggplot2::guide_legend(order = lg.order[[2]], override.aes = list(alpha = lg.alpha[[2]], color = lg.color[[2]]))}else{FALSE}, stroke = if(fin.lg.disp[[3]] == TRUE){ggplot2::guide_legend(order = lg.order[[3]], override.aes = list(alpha = lg.alpha[[2]], color = lg.color[[3]]))}else{FALSE}, linetype = if(fin.lg.disp[[4]] == TRUE){ggplot2::guide_legend(order = lg.order[[4]], override.aes = list(alpha = lg.alpha[[4]], color = lg.color[[4]]))}else{FALSE}, alpha = if(fin.lg.disp[[5]] == TRUE){ggplot2::guide_legend(order = lg.order[[5]], override.aes = list(alpha = lg.alpha[[5]], color = lg.color[[5]]))}else{FALSE}, size = if(fin.lg.disp[[6]] == TRUE){ggplot2::guide_legend(order = lg.order[[6]], override.aes = list(alpha = lg.alpha[[6]], color = lg.color[[6]]))}else{FALSE})) # clip = "off" to have secondary ticks outside plot region does not work
# end legend display
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# scale management
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::coord_cartesian(xlim = xlim, ylim = ylim)) # clip = "off" to have secondary ticks outside plot region does not work
# x-axis ticks and inv
tempo.coord <- ggplot2::ggplot_build(eval(parse(text = paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "))))$layout$panel_params[[1]]
tempo.scale <- fun_scale(lim = xlim, n = ifelse(is.null(x.tick.nb), length(tempo.coord$x.major_source), x.tick.nb), log = "no") # "no" because already log transformed
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_x_continuous(
breaks = tempo.scale, 
labels = if(xlog == "log10"){scales::trans_format("identity",  scales::math_format(10^.x))}else if(xlog == "log2"){scales::trans_format("identity",  scales::math_format(2^.x))}else if(xlog == "no"){ggplot2::waiver()}else{tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 4\n\n============\n\n")) ; stop(tempo.cat)}, 
expand = c(0, 0),
limits = NA,
trans = ifelse(diff(xlim) < 0, "reverse", "identity") # equivalent to ggplot2::scale_x_reverse()
))
# end x-axis ticks and inv
# y-axis ticks and inv
tempo.coord <- ggplot2::ggplot_build(eval(parse(text = paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "))))$layout$panel_params[[1]]
tempo.scale <- fun_scale(lim = ylim, n = ifelse(is.null(y.tick.nb), length(tempo.coord$y.major_source), y.tick.nb), log = "no") # "no" because already log transformed
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::scale_y_continuous(
breaks = tempo.scale, 
labels = if(ylog == "log10"){scales::trans_format("identity",  scales::math_format(10^.x))}else if(ylog == "log2"){scales::trans_format("identity",  scales::math_format(2^.x))}else if(ylog == "no"){ggplot2::waiver()}else{tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 5\n\n============\n\n")) ; stop(tempo.cat)}, 
expand = c(0, 0),
limits = NA,
trans = ifelse(diff(ylim) < 0, "reverse", "identity") # equivalent to ggplot2::scale_y_reverse()
))
# end y-axis ticks and inv
# x-axis secondary ticks (after ggplot2::coord_cartesian() or ggplot2::coord_flip())
tempo.coord <- ggplot2::ggplot_build(eval(parse(text = paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "))))$layout$panel_params[[1]]
xlim.order <- order(xlim) # to deal with inverse axis
ylim.order <- order(ylim) # to deal with inverse axis
# no secondary ticks for log2. Play with xlim
if(xlog == "log10"){
y.range <- tempo.coord$y.range
if(diff(ylim.order) < 0){y.range <- -(y.range)}
ini.scipen <- options()$scipen
options(scipen = -1000) # force scientific format
power10.exp <- as.integer(substring(text = 10^xlim, first = (regexpr(pattern = "\\+|\\-", text = 10^xlim)))) # recover the power of 10. Example recover 08 from 1e+08
mantisse <- as.numeric(substr(x = 10^xlim, start = 1, stop = (regexpr(pattern = "\\+|\\-", text = 10^xlim) - 2))) # recover the mantisse. Example recover 1.22 from 1.22e+08
options(scipen = ini.scipen) # restore the initial scientific penalty
tempo.tick.pos <- as.vector(outer(log10(2:10), 10^((power10.exp[1] - ifelse(diff(xlim.order) > 0, 1, -1)):(power10.exp[2] + ifelse(diff(xlim.order) > 0, 1, -1)))))
tempo.tick.pos <- sort(tempo.tick.pos, decreasing = ifelse(diff(xlim.order) > 0, FALSE, TRUE))
tempo.tick.pos <- log10(tempo.tick.pos[tempo.tick.pos >= min(10^xlim) & tempo.tick.pos <= max(10^xlim)])
if(any(is.na(tempo.tick.pos) | ! is.finite(tempo.tick.pos))){ 
tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 6\n\n============\n\n"))
stop(tempo.cat)
}
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::annotate(geom = "segment", x = tempo.tick.pos, xend = tempo.tick.pos, y = y.range[1], yend = y.range[1] + diff(y.range) / 80))
}else if(( ! is.null(x.inter.tick.nb)) & xlog == "no"){
if(x.inter.tick.nb > 0){
x.ticks.pos <- suppressWarnings(as.numeric(tempo.coord$x.labels)) # too difficult to predict the behavior of tempo.coord$x.major_source depending on xlim neg or not, inv or not. Inv is respected
if(any(is.na(x.ticks.pos))){
tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 7\n\n============\n\n"))
stop(tempo.cat)
}
y.range <- tempo.coord$y.range
if(diff(ylim.order) < 0){y.range <- -(y.range)}
tick.dist <- mean(diff(x.ticks.pos), na.rm = TRUE)
minor.tick.dist <- tick.dist / (x.inter.tick.nb + 1)
minor.tick.pos <- seq(x.ticks.pos[1] - tick.dist, x.ticks.pos[length(x.ticks.pos)] + tick.dist, by = minor.tick.dist)
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::annotate(geom = "segment", x = minor.tick.pos, xend = minor.tick.pos, y = y.range[1], yend = y.range[1] + diff(y.range) / 80))
}
}
# end x-axis secondary ticks (after ggplot2::coord_cartesian() or ggplot2::coord_flip())
# y-axis secondary ticks (after ggplot2::coord_cartesian() or ggplot2::coord_flip())
tempo.coord <- ggplot2::ggplot_build(eval(parse(text = paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "))))$layout$panel_params[[1]]
# no secondary ticks for log2. Play with ylim
if(ylog == "log10"){
x.range <- tempo.coord$x.range
if(diff(xlim.order) < 0){x.range <- -(x.range)}
ini.scipen <- options()$scipen
options(scipen = -1000) # force scientific format
power10.exp <- as.integer(substring(text = 10^ylim, first = (regexpr(pattern = "\\+|\\-", text = 10^ylim)))) # recover the power of 10. Example recover 08 from 1e+08
mantisse <- as.numeric(substr(x = 10^ylim, start = 1, stop = (regexpr(pattern = "\\+|\\-", text = 10^ylim) - 2))) # recover the mantisse. Example recover 1.22 from 1.22e+08
options(scipen = ini.scipen) # restore the initial scientific penalty
tempo.tick.pos <- as.vector(outer(log10(2:10), 10^((power10.exp[1] - ifelse(diff(ylim.order) > 0, 1, -1)):(power10.exp[2] + ifelse(diff(ylim.order) > 0, 1, -1)))))
tempo.tick.pos <- sort(tempo.tick.pos, decreasing = ifelse(diff(ylim.order) > 0, FALSE, TRUE))
tempo.tick.pos <- log10(tempo.tick.pos[tempo.tick.pos >= min(10^ylim) & tempo.tick.pos <= max(10^ylim)])
if(any(is.na(tempo.tick.pos) | ! is.finite(tempo.tick.pos))){ 
tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 8\n\n============\n\n"))
stop(tempo.cat)
}
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::annotate(geom = "segment", y = tempo.tick.pos, yend = tempo.tick.pos, x = x.range[1], xend = x.range[1] + diff(x.range) / 80))
}else if(( ! is.null(y.inter.tick.nb)) & ylog == "no"){
if(y.inter.tick.nb > 0){
y.ticks.pos <- suppressWarnings(as.numeric(tempo.coord$y.labels)) # too difficult to predict the behavior of tempo.coord$y.major_source depending on ylim neg or not, inv or not. Inv is respected
if(any(is.na(y.ticks.pos))){
tempo.cat <- (paste0("\n\n============\n\nERROR IN ", function.name, ": CODE INCONSISTENCY 9\n\n============\n\n"))
stop(tempo.cat)
}
x.range <- tempo.coord$x.range
if(diff(xlim.order) < 0){x.range <- -(x.range)}
tick.dist <- mean(diff(y.ticks.pos), na.rm = TRUE)
minor.tick.dist <- tick.dist / (y.inter.tick.nb + 1)
minor.tick.pos <- seq(y.ticks.pos[1] - tick.dist, y.ticks.pos[length(y.ticks.pos)] + tick.dist, by = minor.tick.dist)
assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), ggplot2::annotate(geom = "segment", y = minor.tick.pos, yend = minor.tick.pos, x = x.range[1], xend = x.range[1] + diff(x.range) / 80))
}
}
# end y-axis secondary ticks (after ggplot2::coord_cartesian() or ggplot2::coord_flip())
# end scale management
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if(plot == TRUE){
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suppressWarnings(print(eval(parse(text = paste(paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "),if(is.null(add)){NULL}else{add})))))
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}else{
tempo.warning <- paste0("FROM FUNCTION ", function.name, ": PLOT NOT SHOWN AS REQUESTED")
warning <- paste0(ifelse(is.null(warning), tempo.warning, paste0(warning, "\n\n", tempo.warning)))
}
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if(return == TRUE){
output <- ggplot2::ggplot_build(eval(parse(text = paste(paste0(tempo.gg.name, 1:tempo.gg.count), collapse = " + "))))
if(is.null(unlist(removed.row.nb))){
removed.row.nb <- NULL
removed.rows <- NULL
}else{
for(i3 in 1:length(data1)){
if( ! is.null(removed.row.nb[[i3]])){
removed.row.nb[[i3]] <- sort(removed.row.nb[[i3]])
removed.rows[[i3]] <- data1.ini[[i3]][removed.row.nb[[i3]], ]
}
}
}
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output <- list(data = output$data, removed.row.nb = removed.row.nb, removed.rows = removed.rows, axes = output$layout$panel_params[[1]], warnings = paste0("\n", warning, "\n\n"))
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return(output)
}
}


######## fun_gg_bar_mean() #### ggplot2 mean barplot + overlaid dots if required

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# Check OK: clear to go Apollo
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fun_gg_bar_mean <- function(data1, y, categ, categ.class.order = NULL, categ.legend.name = NULL, categ.color = NULL, bar.width = 0.5, error.disp = NULL, error.whisker.width = 0.5,  dot.color = "same", dot.tidy = FALSE, dot.bin.nb = 30, dot.jitter = 0.25, dot.size = 3, dot.border.size = 0.5, dot.alpha = 0.5, ylim = NULL, ylog = "no", y.tick.nb = NULL, y.inter.tick.nb = NULL, y.include.zero = FALSE, y.top.extra.margin = 0, y.bottom.extra.margin = 0, stat.disp = NULL, stat.size = 4, stat.dist = 2, xlab = NULL, ylab = NULL, vertical = TRUE, text.size = 12, title = "", title.text.size = 8, text.angle = 0, classic = FALSE, grid = FALSE, return = FALSE, plot = TRUE, add = NULL, path.lib = NULL){
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# AIM
# ggplot2 vertical barplot representing mean values with the possibility to add error bars and to overlay dots
# for ggplot2 specifications, see: https://ggplot2.tidyverse.org/articles/ggplot2-specs.html
# WARNINGS
# rows containing NA in data1[, c(y, categ)] will be removed before processing, with a warning (see below)
# if ever bars disappear, see the end of https://github.com/tidyverse/ggplot2/issues/2887
# to have a single bar, create a factor column with a single class and specify the name of this column in categ argument as unique element (no categ2 in categ argument). For a single set of grouped bars, create a factor column with a single class and specify this column in categ argument as first element (categ1). See categ below
# with several single bars (categ argument with only one element), bar.width argument (i.e., width argument of ggplot2::geom_bar()) defines each bar width. The bar.width argument also defines the space between bars by using (1 - bar.width). In addition, xmin and xmax of the fun_gg_bar_mean() output report the bar boundaries (around x-axis unit 1, 2, 3, etc., for each bar)
# with several sets of grouped bars (categ argument with two elements), bar.width argument defines each set of grouped bar width. The bar.width argument also defines the space between set of grouped bars by using (1 - bar.width). In addition, xmin and xmax of the fun_gg_bar_mean() output report the bar boundaries (around x-axis unit 1, 2, 3, etc., for each set of grouped bar)
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# to manually change the 0 base bar into this code, see https://stackoverflow.com/questions/35324892/ggplot2-setting-geom-bar-baseline-to-1-instead-of-zero
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# ARGUMENTS
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# data1: a dataframe containing one column of values (see y argument below) and one or two columns of categories (see categ argument below). Duplicated column names not allowed
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# y: character string of the data1 column name for y-axis (containing numeric values). Numeric values will be averaged by categ to generate the bars and will also be used to plot the dots
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# categ: vector of character strings of the data1 column name for categories (column of characters or factor). Must either be one or two column names. If a single column name (further refered to as categ1), then one bar per class of categ1. If two column names (further refered to as categ1 and categ2), then one bar per class of categ2, which form a group of bars in each class of categ1. BEWARE, categ1 (and categ2 if it exists) must have a single value of y per class of categ1 (and categ2). To have a single bar, create a factor column with a single class and specify the name of this column in categ argument as unique element (no categ2 in categ argument). For a single set of grouped bars, create a factor column with a single class and specify this column in categ argument as first element (categ1)
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# categ.class.order: list indicating the order of the classes of categ1 and categ2 represented on the barplot (the first compartment for categ1 and and the second for categ2). If categ.class.order = NULL, classes are represented according to the alphabetical order. Some compartment can be NULL and other not
# categ.legend.name: character string of the legend title for categ2. If categ.legend.name = NULL, then categ.legend.name <- categ1 if only categ1 is present and categ.legend.name <- categ2 if categ1 and categ2 are present. Write "" if no legend required
# categ.color: vector of character color string for bar filling. If categ.color = NULL, default colors of ggplot2, whatever categ1 and categ2. If categ.color is non null and only categ1 in categ argument, categ.color can be either: (1) a single color string (all the bars will have this color, whatever the classes of categ1), (2) a vector of string colors, one for each class of categ1 (each color will be associated according to categ.class.order of categ1), (3) a vector or factor of string colors, like if it was one of the column of data1 data frame (beware: a single color per class of categ1 and a single class of categ1 per color must be respected). Integers are also accepted instead of character strings, as long as above rules about length are respected. Integers will be processed by fun_gg_palette() using the max integer value among all the integers in categ.color. If categ.color is non null and categ1 and categ2 specified, all the rules described above will apply to categ2 instead of categ1 (colors will be determined for bars inside a group of bars)
# bar.width: numeric value (from 0 to 1) of the bar or set of grouped bar width (see warnings above)
# error.disp: either "SD", "SD.TOP", "SEM" or "SEM.TOP". If NULL, no error bars added
# error.whisker.width: numeric value (from 0 to 1) of the whisker (error bar extremities) width, with 0 meaning no whiskers and 1 meaning a width equal to the corresponding bar width
# dot.color: vector of character string. Idem as categ.color but for dots, except that in the possibility (3), the rule "a single color per class of categ1 and a single class of categ1", cannot be respected (each dot can have a different color). If NULL, no dots plotted
# dot.tidy: logical. Nice dot spreading? If TRUE, use the geom_dotplot() function for a nice representation. If FALSE, dots are randomly spread, using the dot.jitter argument (see below)
# dot.bin.nb: positive integer indicating the number of bins (i.e., nb of separations) of the ylim range. Each dot will then be put in one of the bin, with the size the width of the bin. Not considered if dot.tidy is FALSE
# dot.jitter: numeric value (from 0 to 1) of random dot horizontal dispersion, with 0 meaning no dispersion and 1 meaning a dispersion in the corresponding bar width interval. Not considered if dot.tidy is TRUE
# dot.size: numeric value of dot size. Not considered if dot.tidy is TRUE
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# dot.border.size: numeric value of border dot size. Write zero for no dot border. If dot.tidy is TRUE, value 0 remove the border. Another one leave the border without size control (geom_doplot() feature)
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# dot.alpha: numeric value (from 0 to 1) of dot transparency (full transparent to full opaque, respectively)
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# ylim: 2 numeric values for y-axis range. If NULL, range of y in data1. Order of the 2 values matters (for inverted axis)
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# ylog: Either "no" (values in the y argument column of the data1 data frame are not log), "log2" (values in the y argument column of the data1 data frame are log2 transformed) or "log10" (values in the y argument column of the data1 data frame are log10 transformed). BEWARE: do not tranform the data, but just display ticks in a log scale manner. Thus, negative or zero values allowed. BEWARE: not possible to have horizontal bars with a log axis, due to a bug in ggplot2 (see https://github.com/tidyverse/ggplot2/issues/881)
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# y.tick.nb: approximate number of desired label values on the y-axis (n argument of the the fun_scale() function)
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# y.inter.tick.nb: number of desired secondary ticks between main ticks. Not considered if ylog is other than "no". In that case, play with the ylim and y.tick.nb arguments
# y.include.zero: logical. Does ylim range include 0? BEWARE: if ylog is other than "no", will be automately set to FALSE with a warning message
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# y.top.extra.margin: single proportion (between 0 and 1) indicating if extra margins must be added to ylim. If different from 0, add the range of the axis * y.top.extra.margin (e.g., abs(ylim[2] - ylim[1]) * y.top.extra.margin) to the top of y-axis
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# y.bottom.extra.margin: idem as y.top.extra.margin but to the bottom of y-axis
# stat.disp: add the mean number above the corresponding bar. Either NULL (no number shown), "top" (at the top of the figure region) or "above" (above each bar)
# stat.size: numeric value of the stat size (in points). Increase the value to increase text size
# stat.dist: numeric value of the stat distance. Increase the value to increase the distance
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# xlab: a character string or expression for x-axis legend. If NULL, character string of categ1
# ylab: a character string or expression for y-axis legend. If NULL, character string of the y argument
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# vertical: logical. Vertical bars? BEWARE: will be automatically set to TRUE if ylog argument is other than "no". Indeed, not possible to have horizontal bars with a log axis, due to a bug in ggplot2 (see https://github.com/tidyverse/ggplot2/issues/881)
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# text.size: numeric value of the size of the (1) axis numbers and axis legends, (2) texts in the graphic legend, (3) stats above bars (in points)
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# title: character string of the graph title
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# title.text.size: numeric value of the title size (in points)
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# text.angle: integer value of the text angle for the x-axis labels. Positive values for counterclockwise rotation: 0 for horizontal, 90 for vertical, 180 for upside down etc. Negative values for clockwise rotation: 0 for horizontal, -90 for vertical, -180 for upside down etc.
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# classic: logical. Use the classic theme (article like)?
# grid: logical. draw horizontal lines in the background to better read the bar values? Not considered if classic = FALSE
# return: logical. Return the graph parameters?
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# plot: logical. Plot the graphic? If FALSE and return argument is TRUE, graphical parameters and associated warnings are provided without plotting
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# add: character string allowing to add more ggplot2 features (dots, lines, themes, etc.). BEWARE: (1) must start with "+" just after the simple or double opening quote (no space, end of line, carriage return, etc., allowed), (2) must finish with ")" just before the simple or double closing quote (no space, end of line, carriage return, etc., allowed) and (3) each function must be preceded by "ggplot2::" (for instance: "ggplot2::coord_flip()). If the character string contains the "ggplot2::theme" string, then internal ggplot2 theme() and theme_classic() functions will be inactivated to be reused by add. BEWARE: handle this argument with caution since added functions can create conflicts with the preexisting internal ggplot2 functions
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# path.lib: absolute path of the required packages, if not in the default folders
# REQUIRED PACKAGES
# ggplot2
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# scales
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# REQUIRED FUNCTIONS FROM CUTE_LITTLE_R_FUNCTION
# fun_2D_comp()
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# fun_gg_just()
# fun_gg_palette()
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# fun_name_change()
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# fun_pack_import()
# fun_param_check()
# fun_round()
# fun_scale()
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# RETURN
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# a barplot if plot argument is TRUE
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# a list of the graph info if return argument is TRUE:
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# $stat: the graphic statistics
# $removed.row.nb: which rows have been removed due to NA detection in y and categ columns (NULL if no row removed)
# $removed.rows: removed rows containing NA (NULL if no row removed)
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# $data: the graphic bar and dot coordinates
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# $axes: the x-axis and y-axis info
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# $warnings: the warning messages. Use cat() for proper display. NULL if no warning
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# EXAMPLES
# nice representation (1)
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), categ.class.order = list(NULL, c("B", "A")), categ.legend.name = "LEGEND", categ.color = NULL, bar.width = 0.3, error.disp = "SD.TOP", error.whisker.width = 0.8, dot.color = "same", dot.jitter = 0.5, dot.size = 3.5, dot.border.size = 0.2, dot.alpha = 0.5, ylim = c(10, 25), y.include.zero = TRUE, stat.disp = "above", stat.size = 4, xlab = "GROUP", ylab = "MEAN", text.size = 12, title = "GRAPH1", title.text.size = 8, text.angle = 0, classic = TRUE, grid = TRUE)
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# nice representation (2)
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# set.seed(1) ; obs1 <- data.frame(Time = c(rnorm(24, 0), rnorm(24, -10), rnorm(24, 10), rnorm(24, 20)), Group1 = rep(c("CAT", "DOG"), times = 48), Group2 = rep(c("A", "B", "C", "D"), each = 24)) ; set.seed(NULL) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), categ.class.order = list(NULL, c("B", "A", "D", "C")), categ.legend.name = "LEGEND", categ.color = NULL, bar.width = 0.8, dot.color = "grey50", dot.tidy = TRUE, dot.bin.nb = 60, dot.size = 3.5, dot.border.size = 0.2, dot.alpha = 0.5, ylim= c(-20, 30), stat.disp = "above", stat.size = 4, stat.dist = 1, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, text.size = 12, title = "GRAPH1", title.text.size = 8, text.angle = 45, classic = FALSE)
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# simple example
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1")
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# separate bars. Example (1) of modification of bar color using a single value
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", categ.color = "white")
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# separate bars. Example (2) of modification of bar color using one value par class of categ2
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", categ.color = c("coral", "lightblue"))
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# separate bars. Example (3) of modification of bar color using the bar.color data frame column, with respect of the correspondence between categ2 and bar.color columns
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), bar.color = rep(c("coral", "lightblue"), time = 10)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", categ.color = obs1$bar.color)
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# separate bars. Example (1) of modification of dot color, using the same dot color as the corresponding bar
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = "same")
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# separate bars. Example (2) of modification of dot color, using a single color for all the dots
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = "green")
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# separate bars. Example (3) of modification of dot color, using one value par class of categ2
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = c("green", "brown"))
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# separate bars. Example (4) of modification of dot color, using different colors for each dot
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# obs1 <- data.frame(Time = 1:10, Group1 = rep(c("G", "H"), times = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1)))
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# grouped bars. Simple example
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"))
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# grouped bars. More grouped bars
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# obs1 <- data.frame(Time = 1:24, Group1 = rep(c("G", "H"), times = 12), Group2 = rep(c("A", "B", "C", "D"), each = 6)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"))
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# grouped bars. Example (1) of modification of bar color, using a single value
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), categ.color = "white")
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# grouped bars. Example (2) of modification of bar color, using one value par class of categ2
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), categ.color = c("coral", "lightblue"))
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# grouped bars. Example (3) of modification of bar color, using one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10), bar.color = rep(c("coral", "lightblue"), each = 10)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), categ.color = obs1$bar.color)
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# grouped bars. Example (1) of modification of dot color, using the same dot color as the corresponding bar
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "same")
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# grouped bars. Example (2) of modification of dot color, using a single color for all the dots
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "green")
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# grouped bars. Example (3) of modification of dot color, using one value par class of categ2
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# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = c("green", "brown"))
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# grouped bars. Example (4) of modification of dot color, using different colors for each dot
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# obs1 <- data.frame(Time = 1:10, Group1 = rep(c("G", "H"), times = 5), Group2 = rep(c("A", "B"), each = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1)))
# no dots (y.include.zero set to TRUE to see the lowest bar):
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, y.include.zero = TRUE)
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# bar width. Example (1) with bar.width = 0.25 -> three times more space between single bars than the bar width (y.include.zero set to TRUE to see the lowest bar)
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), each = 500)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = NULL, y.include.zero = TRUE, bar.width = 0.25)
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# bar width. Example (2) with bar.width = 1, no space between single bars
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), each = 500)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = "Group1", dot.color = NULL, y.include.zero = TRUE, bar.width = 1)
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# bar width. Example (3) with bar.width = 0.25 -> three times more space between sets of grouped bars than the set width
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, y.include.zero = TRUE, bar.width = 0.25)
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# bar width. Example (4) with bar.width = 0 -> no space between sets of grouped bars
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, y.include.zero = TRUE, bar.width = 1)
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# error bars
# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, error.disp = "SD.TOP")
# whisker width. Example (1) with error.whisker.width = 1 -> whiskers have the width of the corresponding bar
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, error.disp = "SD", error.whisker.width = 1)
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# whisker width. Example (2) error bars with no whiskers
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = NULL, error.disp = "SD", error.whisker.width = 0)
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# tidy dot distribution. Example (1)
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "same", dot.tidy = TRUE, dot.bin.nb = 100)
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# tidy dot distribution. Example (2) reducing the dot size with dot.bin.nb
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "same", dot.tidy = TRUE, dot.bin.nb = 150)
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# dot jitter. Example (1)
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# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "same", dot.tidy = FALSE, dot.jitter = 1, dot.size = 2)
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# dot jitter. Example (2) with dot.jitter = 1 -> dispersion around the corresponding bar width
# obs1 <- data.frame(Time = 1:1000, Group1 = rep(c("G", "H"), times = 500), Group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "grey", dot.size = 3, dot.alpha = 1,  dot.jitter = 1)
# dot jitter. Example (3) with no dispersion
# obs1 <- data.frame(Time = 1:100, Group1 = rep(c("G", "H"), times = 50), Group2 = rep(LETTERS[1:5], each = 20)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "grey", dot.size = 3, dot.alpha = 1,  dot.jitter = 0)
# dot size, dot border size and dot transparency
# obs1 <- data.frame(Time = 1:100, Group1 = rep(c("G", "H"), times = 50), Group2 = rep(LETTERS[1:5], each = 20)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), dot.color = "grey", dot.size = 4, dot.border.size = 0, dot.alpha = 0.6)
# y-axis limits. Example (1)
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylim = c(-1, 25))
# y-axis limits. Example (2) showing that order matters in ylim argument
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylim = c(25, -1))
# log scale. Example (1). BEWARE: y column must be log, otherwise incoherent scale (see below warning message with the return argument)
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# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10")
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# log scale. Example (2). BEWARE: values of the ylim must be in the corresponding log
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", ylim = c(1,4))
# tick number. Example (1)
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.tick.nb = 10)
# tick number. Example (2) using a log2 scale
# obs1 <- data.frame(Time = log2((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log2", y.tick.nb = 10, ylim = c(1, 16))
# tick number. Example (3) using a log10 scale
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", y.tick.nb = 10)
# tick number. Example (4) using a log10 scale: the reverse y-axis correctly deal with log10 scale
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", y.tick.nb = 10, ylim = c(4, 1))
# secondary tick number. Example (1)
# obs1 <- data.frame(Time = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.inter.tick.nb = 2)
# secondary ticks. Example (2) not for log2 and log10 scales (see below warning message with the return argument)
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", y.inter.tick.nb = 2)
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# include zero in the y-axis
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# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.include.zero = TRUE)
# extra margins. To avoid dot cuts
# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.top.extra.margin = 0.25, y.bottom.extra.margin = 0.25)
# mean diplay. Example (1) at the top of the plot region
# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.top.extra.margin = 0.1, stat.disp = "top", stat.size = 4, stat.dist = 2)
# mean diplay. Example (2) above bars
# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.top.extra.margin = 0.1, stat.disp = "above", stat.size = 4, stat.dist = 2)
# bar orientation.  Example (1) without log scale, showing that the other arguments are still operational
# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), y.tick.nb = 10, y.inter.tick.nb = 2, y.include.zero = TRUE, vertical = FALSE)
# bar orientation. Example (2) with log scale. Horizontal orientation is blocked with log2 and log10 scales because of a bug in ggplot2 (https://github.com/tidyverse/ggplot2/issues/881)
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", vertical = FALSE)
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# classic representation (use grid = TRUE to display the background lines of the y axis ticks)
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# obs1 <- data.frame(Time = (1:20), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), classic = TRUE, grid = FALSE)
# graphic info. Example (1)
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# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), return = TRUE)
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# graphic info. Example (2) of assignation and warning message display
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; warn <- fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), ylog = "log10", return = TRUE) ; cat(warn$warnings)
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# add ggplot2 functions
# obs1 <- data.frame(Time = log10((1:20) * 100), Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "Time", categ = c("Group1", "Group2"), add = "+ggplot2::theme_classic()")
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# all the arguments
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# obs1 <- data.frame(x = 1:20, Group1 = rep(c("G", "H"), times = 10), Group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "x", categ = c("Group1", "Group2"), categ.class.order = list(NULL, c("B", "A")), categ.legend.name = "", categ.color = c("red", "blue"), bar.width = 0.25, error.disp = "SD", error.whisker.width = 0.8, dot.color = "grey", dot.tidy = FALSE, dot.bin.nb = 30, dot.jitter = 1, dot.size = 4, dot.border.size = 0, dot.alpha = 1, ylim = c(0, 25), ylog = "no", y.tick.nb = NULL, y.inter.tick.nb = NULL, y.include.zero = FALSE, y.top.extra.margin = 0.05, y.bottom.extra.margin = 0, stat.disp = "above", stat.size = 4, stat.dist = 2, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, text.size = 12, title = "", title.text.size = 8, text.angle = 45, classic = TRUE, grid = TRUE, return = TRUE, plot = TRUE, add = NULL, path.lib = NULL)
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# DEBUGGING
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# data1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10), bar.color = rep(c("brown", "orange"), each = 10)) ; data1[2:3, 1] <- NA ; data1[7:8, 2] <- NA ; y = names(data1)[1] ; categ = c(names(data1)[2], names(data1)[3]) ; categ.class.order = list(L1 = NULL, L2 = c("B", "A")) ; categ.legend.name = NULL ; categ.color = na.omit(data1)$bar.color ; bar.width = 0.5 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = FALSE ; dot.bin.nb = 30 ; dot.jitter = 0.25 ; dot.size = 3 ; dot.border.size = 0.5 ; dot.alpha = 1 ; ylim = NULL ; ylog = "no" ; y.tick.nb = NULL ; y.inter.tick.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = NULL ; stat.size = 4 ; stat.dist = 2 ; xlab = NULL ; ylab = NULL ; vertical = TRUE ; text.size = 12 ; title = "" ; title.text.size = 8 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE ; plot = TRUE ; add = NULL ; path.lib = NULL
# data1 <-data.frame(a = rep(1:20, 5), group1 = rep(c("G", "H"), times = 50), group2 = rep(LETTERS[1:5], each = 20)) ; y = names(data1)[1] ; categ = c(names(data1)[2], names(data1)[3]) ; categ.class.order = list(L1 = NULL, L2 = c("B", "A", "E", "D", "C")) ; categ.legend.name = NULL ; categ.color = NULL ; bar.width = 0.5 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = TRUE ; dot.bin.nb = 30 ; dot.jitter = 0.25 ; dot.size = 3 ; dot.border.size = 0.5 ; dot.alpha = 1 ; ylim = NULL ; ylog = "no" ; y.tick.nb = NULL ; y.inter.tick.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = NULL ; stat.size = 4 ; stat.dist = 2 ; xlab = NULL ; ylab = NULL ; vertical = TRUE ; text.size = 12 ; title = "" ; title.text.size = 8 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE; plot = TRUE ; add = NULL ; path.lib = NULL
# data1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10), bar.color = rep(c("brown", "orange"), each = 10)) ; data1[2:3, 1] <- NA ; data1[7:8, 2] <- NA ; y = names(data1)[1] ; categ = c(names(data1)[2], names(data1)[3]) ; categ.class.order = list(L1 = NULL, L2 = c("B", "A")) ; categ.legend.name = NULL ; categ.color = na.omit(data1)$bar.color ; bar.width = 0.5 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = TRUE ; dot.bin.nb = 30 ; dot.jitter = 0.25 ; dot.size = 3 ; dot.border.size = 0.5 ; dot.alpha = 1 ; ylim = NULL ; ylog = "no" ; y.tick.nb = NULL ; y.inter.tick.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = "above" ; stat.size = 4 ; stat.dist = 2 ; xlab = NULL ; ylab = NULL ; vertical = TRUE ; text.size = 12 ; title = "" ; title.text.size = 8 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE; plot = TRUE ; add = NULL ; path.lib = NULL
# set.seed(1) ; data1 <- data.frame(a = c(rnorm(25, 0), rnorm(25, -10), rnorm(25, 10), rnorm(25, 20)), group1 = rep(c("G", "H"), times = 50), group2 = rep(c("A", "B", "C", "D"), each = 25)) ; set.seed(NULL) ; y = "Time" ; categ = c("group1", "group2") ; categ.class.order = list(NULL, c("B", "A", "D", "C")) ; categ.legend.name = "LEGEND" ; categ.color = NULL ; bar.width = 0.8 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = TRUE ; dot.bin.nb = 60 ; dot.jitter = 0.25 ; dot.size = 3.5 ; dot.border.size = 0 ; dot.alpha = 1 ; ylim= c(-15, 25) ; ylog = "no" ; y.tick.nb = NULL ; y.inter.tick.nb = NULL ; y.include.zero = "no" ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = "above" ; stat.size = 4 ; stat.dist = 2 ; xlab = "GROUP" ; ylab = "MEAN" ; vertical = FALSE ; text.size = 12 ; title = "" ; title.text.size = 8 ; text.angle = -200 ; classic = FALSE ; grid = FALSE ; return = FALSE; plot = TRUE ; add = NULL ; path.lib = NULL
# set.seed(1) ; data1 <- data.frame(x = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; set.seed(NULL) ; y = "x" ; categ <- c("group1", "group2") ; categ.class.order = list(NULL, c("B", "A", "D", "C", "E")) ; categ.legend.name = "LEGEND" ; categ.color = NULL ; bar.width = 0.8 ; error.disp = "SD" ; error.whisker.width = 1 ; dot.color = NULL ; dot.tidy = FALSE ; dot.bin.nb = 60 ; dot.jitter = 0.25 ; dot.size = 3.5 ; dot.border.size = 0.2 ; dot.alpha = 1 ; ylim= c(1, 4) ; ylog = "log10" ; y.tick.nb = NULL ; y.inter.tick.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0 ; y.bottom.extra.margin = 0 ; stat.disp = "above" ; stat.size = 4 ; stat.dist = 1 ; xlab = "GROUP" ; ylab = "MEAN" ; vertical = TRUE ; text.size = 12 ; title = "" ; title.text.size = 8 ; text.angle = -200 ; classic = FALSE ; grid = FALSE ; return = FALSE; plot = TRUE ; add = NULL ; path.lib = NULL
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# function name
function.name <- paste0(as.list(match.call(expand.dots=FALSE))[[1]], "()")
# end function name
# required function checking
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if(length(find("fun_2D_comp", mode = "function")) == 0){
tempo.cat <- paste0("\n\n================\n\nERROR IN ", function.name, ": REQUIRED fun_2D_comp() FUNCTION IS MISSING IN THE R ENVIRONMENT\n\n================\n\n")
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stop(tempo.cat)
}
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if(length(find("fun_gg_just", mode = "function")) == 0){