diff --git a/cute_little_R_functions.R b/cute_little_R_functions.R index bb201efe56565733cfba37c769dbf7f83a48bed2..f36c4a3501c990b6f78f82efff749d998051b7b3 100644 --- a/cute_little_R_functions.R +++ b/cute_little_R_functions.R @@ -3935,6 +3935,8 @@ return(output) ######## fun_gg_bar_mean() #### ggplot2 mean barplot + overlaid dots if required +# nice breaks + @@ -4010,71 +4012,87 @@ fun_gg_bar_mean <- function(data1, y, categ, categ.class.order = NULL, categ.leg # 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", title = "GRAPH1", text.size = 20, text.angle = 0, classic = TRUE, grid = TRUE, return = TRUE) # nice representation (2) # 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 = "same", dot.tidy = TRUE, dot.bin.nb = 60, dot.size = 3.5, dot.border.size = 0.2, dot.alpha = 1, ylim= c(-20, 25), stat.disp = "above", stat.size = 4, stat.dist = 1, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, title = "GRAPH1", text.size = 20, text.angle = 45, classic = FALSE, return = TRUE) -# separate bars, modification of bar color (1) (a single value) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = "white") -# separate bars, modification of bar color (2) (one value par class of categ2) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = c("red", "blue")) -# separate bars, modification of bar color (3) (one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), bar.color = rep(c("brown", "orange"), time = 10)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = obs1$bar.color) -# separate bars, modification of dot color (1) (same dot color as the corresponding bar) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = "same") -# separate bars, modification of dot color (2) (single color for all the dots) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = "green") -# separate bars, modification of dot color (3) (one value par class of categ2) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = c("green", "brown")) -# separate bars, modification of dot color 4 (any color for each dot) -# obs1 <- data.frame(a = 1:10, group1 = rep(c("G", "H"), times = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1))) -# grouped bars, default arguments -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2")) -# more grouped bars -# obs1 <- data.frame(a = 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 = "a", categ = c("group1", "group2"), return = TRUE) -# grouped bars, log scale. Beware, y column must be log, otherwise incoherent scale -# obs1 <- data.frame(a = 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 = "a", categ = c("group1", "group2"), ylog = TRUE) -# grouped bars, no dots (y.include.zero = TRUE to see the lowest bar) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, y.include.zero = TRUE) -# grouped bars, modification of bar color (1) (a single value) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = "white") -# grouped bars, modification of bar color (2) (one value par class of categ2) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = c("red", "blue")) -# grouped bars, modification of bar color (3) (one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns) -# obs1 <- 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)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = obs1$bar.color) -# grouped bars, modification of dot color (1) (same dot color as the corresponding bar) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "same") -# grouped bars, modification of dot color (2) (single color for all the dots) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "green") -# grouped bars, modification of dot color (3) (one value par class of categ2) -# obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = c("green", "brown")) -# grouped bars, modification of dot color (4) (any color for each dot) -# obs1 <- data.frame(a = 1:10, group1 = rep(c("G", "H"), times = 5), group2 = rep(c("A", "B"), each = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1))) -# width example. With bar.width = 0.25, three times more space between single bars than the bar width -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), each = 500)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = NULL, bar.width = 0.25, y.include.zero = TRUE) -# width example. With bar.width = 1, no space between single bars -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), each = 500)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = NULL, bar.width = 1, y.include.zero = TRUE) -# width example. With bar.width = 0.25, three times more space between sets of grouped bars than the set width -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, bar.width = 0.25, y.include.zero = TRUE) -# width example. With bar.width = 0, no space between sets of grouped bars -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, bar.width = 1, y.include.zero = TRUE) -# width example. With error.whisker.width = 1, whiskers have the width of the corresponding bar -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, error.disp = "SD", error.whisker.width = 1) -# width example. No whiskers -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, error.disp = "SD", error.whisker.width = 0) -# width example. With dot.jitter = 1, dispersion around the corresponding bar width -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "grey", dot.size = 3, dot.alpha = 1, dot.jitter = 1) -# width example. No dispersion -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "grey", dot.size = 3, dot.alpha = 1, dot.jitter = 0) -# tidy dot example -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "same", dot.tidy = TRUE, dot.bin.nb = 100) -# tidy dot example. Comparison with random spreading -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "same", dot.tidy = FALSE, dot.jitter = 1, dot.size = 2) -# orientation example. Beware: log scale automatically set to FALSE for horizontal display, because of a bug in ggplot2 (https://github.com/tidyverse/ggplot2/issues/881) -# obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "grey", dot.size = 3, dot.alpha = 1, dot.jitter = 1, vertical = FALSE) -# many arguments -# 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.jitter = 1, dot.size = 4, dot.border.size = 0, dot.alpha = 1, ylim = NULL, ylog = FALSE, y.break.nb = NULL, y.include.zero = FALSE, y.top.extra.margin = 0.05, y.bottom.extra.margin = 0, stat.disp = "above", stat.size = 4, xlab = "GROUP", ylab = "MEAN", vertical = TRUE, title = "GRAPH1", text.size = 14, text.angle = 45, classic = TRUE, grid = TRUE, return = TRUE, path.lib = NULL) +# 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") +# separate bars: example (1) of modification of bar color using a single value +# 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") +# separate bars: example (2) of modification of bar color using one value par class of categ2 +# 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")) +# 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 +# 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) +# separate bars: example (1) of modification of dot color, using the same dot color as the corresponding bar +# 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") +# separate bars: example (2) of modification of dot color, using a single color for all the dots +# 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") +# separate bars: example (3) of modification of dot color, using one value par class of categ2 +# 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")) +# separate bars: example (4) of modification of dot color, using different colors for each dot +# 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))) +# grouped bars: 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 = c("Group1", "Group2")) +# grouped bars: more grouped bars +# 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")) +# grouped bars: example (1) of modification of bar color (1), using a single value +# 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") +# grouped bars: example (2) of modification of bar color (2), using one value par class of categ2 +# 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")) +# grouped bars: example (3) of modification of bar color (3), using one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns +# 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) +# grouped bars: example (1) of modification of dot color, using the same dot color as the corresponding 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 = "same") +# grouped bars: example (2) of modification of dot color, using a single color for all the dots +# 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") +# grouped bars: example (3) of modification of dot color, using one value par class of categ2 +# 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")) +# grouped bars: example (4) of modification of dot color, using different colors for each dot +# 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) +# 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) +# 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) +# bar width: example (2) with bar.width = 1, no space between single bars +# 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) +# bar width: example (3) with bar.width = 0.25 -> three times more space between sets of grouped bars than the set 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 = NULL, y.include.zero = TRUE, bar.width = 0.25) +# bar width: example (4) with bar.width = 0 -> no space between sets of grouped 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, y.include.zero = TRUE, bar.width = 1) +# whisker width: example (1) with error.whisker.width = 1 -> whiskers have the width of the corresponding bar +# 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) +# whisker width: example (2) error bars with no whiskers +# 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) +# dot jitter: example (1) 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 (2) 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) +# tidy dot distribution: example (1) +# 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) +# tidy dot distribution: example (2) reducing the dot size with dot.bin.nb +# 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) +# tidy dot distribution: comparison with random spreading +# 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) +# log scale: beware, y column must be log, otherwise incoherent 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 = TRUE) +# break number: (make nice) +# 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"), y.break.nb = 10) +# extra margins for the plot region: to avoid dot cuts +# 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"), 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 = 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"), stat.disp = "top", stat.size = 4, stat.dist = 2) +# mean diplay: example (2) above bars +# 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"), stat.disp = "above", stat.size = 4, stat.dist = 2) +# label orientation: beware, log scale automatically set to FALSE for horizontal display, 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"), vertical = FALSE) +# graphic info: +# 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) +# all the arguments: +# 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 = NULL, ylog = FALSE, y.break.nb = NULL, y.include.zero = FALSE, y.top.extra.margin = 0.05, y.bottom.extra.margin = 0.05, stat.disp = "above", stat.size = 4, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, title = "GRAPH1", text.size = 14, text.angle = 45, classic = TRUE, grid = TRUE, return = TRUE, path.lib = NULL) # DEBUGGING # 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)$bar.color ; bar.width = 0.5 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = FALSE ; dot.bin.nb = 30 ; dot.jitter = 0.25 ; dot.size = 3 ; dot.border.size = 0.5 ; dot.alpha = 1 ; ylim = NULL ; ylog = FALSE ; y.break.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = NULL ; stat.size = 4 ; stat.dist = 2 ; xlab = NULL ; ylab = NULL ; vertical = TRUE ; title = "" ; text.size = 12 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE ; path.lib = NULL # data1 <-data.frame(a = rep(1:20, 5), group1 = rep(c("G", "H"), times = 50), group2 = rep(LETTERS[1:5], each = 20)) ; y = names(data1)[1] ; categ = c(names(data1)[2], names(data1)[3]) ; categ.class.order = list(L1 = NULL, L2 = c("B", "A", "E", "D", "C")) ; categ.legend.name = NULL ; categ.color = NULL ; bar.width = 0.5 ; error.disp = "SD" ; error.whisker.width = 0.5 ; dot.color = "same" ; dot.tidy = TRUE ; dot.bin.nb = 30 ; dot.jitter = 0.25 ; dot.size = 3 ; dot.border.size = 0.5 ; dot.alpha = 1 ; ylim = NULL ; ylog = FALSE ; y.break.nb = NULL ; y.include.zero = FALSE ; y.top.extra.margin = 0.05 ; y.bottom.extra.margin = 0 ; stat.disp = NULL ; stat.size = 4 ; stat.dist = 2 ; xlab = NULL ; ylab = NULL ; vertical = TRUE ; title = "" ; text.size = 12 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE ; path.lib = NULL # data1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10), bar.color = rep(c("brown", "orange"), each = 10)) ; data1[2:3, 1] <- NA ; data1[7:8, 2] <- NA ; y = names(data1)[1] ; categ = c(names(data1)[2], names(data1)[3]) ; categ.class.order = list(L1 = NULL, L2 = c("B", "A")) ; categ.legend.name = NULL ; categ.color = na.omit(data1)$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 = FALSE ; y.break.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 ; title = "" ; text.size = 12 ; text.angle = 0 ; classic = FALSE ; grid = FALSE ; return = FALSE ; 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 = "a" ; 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 = 0.2 ; dot.alpha = 1 ; ylim= c(-15, 25) ; ylog = FALSE ; y.break.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 ; title = "GRAPH1" ; text.size = 20 ; classic = FALSE ; grid = FALSE ; return = FALSE ; 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 = FALSE ; y.break.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 ; title = "GRAPH1" ; text.size = 20 ; text.angle = -200 ; classic = FALSE ; grid = FALSE ; return = FALSE ; 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(-15, 25) ; ylog = FALSE ; y.break.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 = 1 ; xlab = "GROUP" ; ylab = "MEAN" ; vertical = TRUE ; title = "GRAPH1" ; text.size = 20 ; text.angle = -200 ; classic = FALSE ; grid = FALSE ; return = FALSE ; path.lib = NULL # function name function.name <- paste0(as.list(match.call(expand.dots=FALSE))[[1]], "()") @@ -4539,7 +4557,8 @@ assign(paste0(tempo.gg.name, tempo.gg.count <- tempo.gg.count + 1), m.gg <- ggpl 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 -panel.grid.major.y = ggplot2::element_line(colour = "grey75"), +panel.grid.major.x = if(vertical == TRUE){NULL}else{ggplot2::element_line(colour = "grey75")}, +panel.grid.major.y = if(vertical == TRUE){ggplot2::element_line(colour = "grey75")}else{NULL}, axis.text.x = if(vertical == TRUE){ggplot2::element_text(angle = tempo.just$angle, hjust = tempo.just$hjust, vjust = tempo.just$vjust)}else{NULL}, axis.text.y = if(vertical == TRUE){NULL}else{ggplot2::element_text(angle = tempo.just$angle, hjust = tempo.just$hjust, vjust = tempo.just$vjust)} )) @@ -4816,7 +4835,9 @@ return(output) ######## fun_gg_boxplot() #### ggplot2 boxplot + background dots if required + # http://www.sthda.com/english/wiki/ggplot2-box-plot-quick-start-guide-r-software-and-data-visualization +# Exmaple of boxplots: https://github.com/IndrajeetPatil/ggstatsplot fun_gg_boxplot <- function(data1, y, categ, class.order = NULL, legend.name = NULL, categ.color = NULL, dot.color = "same", box.width = 0.5, whisker.width = 0.5, jitter = 0.25, ylim = NULL, ylog = FALSE, y.include.zero = FALSE, top.extra.margin = 0.05, bottom.extra.margin = 0, xlab = NULL, ylab = NULL, pt.size = 3, pt.border.size = 0.5, alpha = 0.5, show.stat = NULL, stat.size = 4, title = "", text.size = 12, break.nb = NULL, classic = FALSE, grid = FALSE, return = FALSE, path.lib = NULL){ # AIM diff --git a/cute_little_R_functions.docx b/cute_little_R_functions.docx index 91021fbde300606b2043c094ba88a92bf1cc7cac..8f082141a38cdebb929c6c82e33b263639aea46f 100644 Binary files a/cute_little_R_functions.docx and b/cute_little_R_functions.docx differ diff --git a/examples_alone.txt b/examples_alone.txt index 357c9e453e72d382b4cffb8b99ec7da8e68fde68..57ed2003ed39a1716ab096918edfd922fae5b5e0 100644 --- a/examples_alone.txt +++ b/examples_alone.txt @@ -226,32 +226,88 @@ data1 <- list(L1 = data.frame(a = 1:6, b = (1:6)^2, group = c("A1", "A2", "A3", ######## fun_gg_bar_mean() -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = "white") # separate bars, modification of bar color 1 (a single value) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = c("red", "blue")) # separate bars, modification of bar color 2 (one value par class of categ2) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), bar.color = rep(c("brown", "orange"), time = 10)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", categ.color = obs1$bar.color) # separate bars, modification of bar color 3 (one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = "same") # separate bars, modification of dot color 1 (same dot color as the corresponding bar) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = "green") # separate bars, modification of dot color 2 (single color for all the dots) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = c("green", "brown")) # separate bars, modification of dot color 3 (one value par class of categ2) -obs1 <- data.frame(a = 1:10, group1 = rep(c("G", "H"), times = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1))) # separate bars, modification of dot color 4 (any color for each dot) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2")) # grouped bars, default arguments -obs1 <- data.frame(a = 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 = "a", categ = c("group1", "group2"), return = TRUE) # more grouped bars -obs1 <- data.frame(a = 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 = "a", categ = c("group1", "group2"), ylog = TRUE) # grouped bars, log scale. Beware, y column must be log, otherwise incoherent scale -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL) # grouped bars, no dots -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = "white") # grouped bars, modification of bar color 1 (a single value) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = c("red", "blue")) # grouped bars, modification of bar color 2 (one value par class of categ2) -obs1 <- 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)) ; obs1 ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), categ.color = obs1$bar.color) # grouped bars, modification of bar color 3 (one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "same") # grouped bars, modification of dot color 1 (same dot color as the corresponding bar) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "green") # grouped bars, modification of dot color 2 (single color for all the dots) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = c("green", "brown")) # grouped bars, modification of dot color 3 (one value par class of categ2) -obs1 <- data.frame(a = 1:10, group1 = rep(c("G", "H"), times = 5), group2 = rep(c("A", "B"), each = 5)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = hsv(h = (1:nrow(obs1)) / nrow(obs1))) # grouped bars, modification of dot color 4 (any color for each dot) -obs1 <- data.frame(a = 1:20, group1 = rep(c("G", "H"), times = 10), group2 = rep(c("A", "B"), each = 10)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), class.order = list(NULL, c("B", "A")), legend.name = "", categ.color = c("red", "blue"), dot.color = "grey", error.bar = "SD", bar.width = 0.25, error.bar.width = 0.8, jitter = 1, ylim = c(10, 30), y.include.zero = FALSE, top.extra.margin = 0.5, bottom.extra.margin = 1, xlab = "GROUP", ylab = "MEAN", pt.size = 4, pt.border.size = 0, alpha = 1, show.stat = "above", stat.size = 4, title = "GRAPH1", text.size = 20, return = TRUE, break.nb = 10, classic = TRUE, grid = TRUE) # grouped bars, all the argumentsobs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = NULL, bar.width = 0.25) # width example. With bar.width = 0.25, three times more space between single bars than the bar width -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = "group1", dot.color = NULL, bar.width = 1) # width example. With bar.width = 1, no space between single bars -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, bar.width = 0.25) # width example. With bar.width = 0.25, three times more space between sets of grouped bars than the set width -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, bar.width = 1) # width example. With bar.width = 0, no space between sets of grouped bars -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, error.bar = "SD", error.bar.width = 1) # width example. With error.bar.width = 1, whiskers have the width of the corresponding bar -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = NULL, error.bar = "SD", error.bar.width = 0) # width example. No whiskers -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "grey", pt.size = 3, alpha = 1, jitter = 1) # width example. With jitter = 1, dispersion around the corresponding bar width -obs1 <- data.frame(a = 1:1000, group1 = rep(c("G", "H"), times = 500), group2 = rep(LETTERS[1:5], each = 200)) ; fun_gg_bar_mean(data1 = obs1, y = "a", categ = c("group1", "group2"), dot.color = "grey", pt.size = 3, alpha = 1, jitter = 0) # width example. No dispersion +# nice representation (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"), 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", title = "GRAPH1", text.size = 20, text.angle = 0, classic = TRUE, grid = TRUE, return = TRUE) +# nice representation (2) +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 = "same", dot.tidy = TRUE, dot.bin.nb = 60, dot.size = 3.5, dot.border.size = 0.2, dot.alpha = 1, ylim= c(-20, 25), stat.disp = "above", stat.size = 4, stat.dist = 1, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, title = "GRAPH1", text.size = 20, text.angle = 45, classic = FALSE, return = TRUE) +# 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") +# separate bars: example (1) of modification of bar color using a single value +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") +# separate bars: example (2) of modification of bar color using one value par class of categ2 +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")) +# 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 +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) +# separate bars: example (1) of modification of dot color, using the same dot color as the corresponding bar +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") +# separate bars: example (2) of modification of dot color, using a single color for all the dots +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") +# separate bars: example (3) of modification of dot color, using one value par class of categ2 +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")) +# separate bars: example (4) of modification of dot color, using different colors for each dot +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))) +# grouped bars: 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 = c("Group1", "Group2")) +# grouped bars: more grouped bars +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")) +# grouped bars: example (1) of modification of bar color (1), using a single value +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") +# grouped bars: example (2) of modification of bar color (2), using one value par class of categ2 +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")) +# grouped bars: example (3) of modification of bar color (3), using one value per line of obs1, with respect of the correspondence between categ2 and bar.color columns +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) +# grouped bars: example (1) of modification of dot color, using the same dot color as the corresponding 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 = "same") +# grouped bars: example (2) of modification of dot color, using a single color for all the dots +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") +# grouped bars: example (3) of modification of dot color, using one value par class of categ2 +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")) +# grouped bars: example (4) of modification of dot color, using different colors for each dot +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) +# 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) +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) +# bar width: example (2) with bar.width = 1, no space between single bars +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) +# bar width: example (3) with bar.width = 0.25 -> three times more space between sets of grouped bars than the set 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 = NULL, y.include.zero = TRUE, bar.width = 0.25) +# bar width: example (4) with bar.width = 0 -> no space between sets of grouped 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, y.include.zero = TRUE, bar.width = 1) +# whisker width: example (1) with error.whisker.width = 1 -> whiskers have the width of the corresponding bar +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) +# whisker width: example (2) error bars with no whiskers +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) +# dot jitter: example (1) 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 (2) 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) +# tidy dot distribution: example (1) +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) +# tidy dot distribution: example (2) reducing the dot size with dot.bin.nb +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) +# tidy dot distribution: comparison with random spreading +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) +# log scale: beware, y column must be log, otherwise incoherent 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 = TRUE) +# break number: (make nice) +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"), y.break.nb = 10) +# extra margins for the plot region: to avoid dot cuts +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"), 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 = 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"), stat.disp = "top", stat.size = 4, stat.dist = 2) +# mean diplay: example (2) above bars +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"), stat.disp = "above", stat.size = 4, stat.dist = 2) +# label orientation: beware, log scale automatically set to FALSE for horizontal display, 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"), vertical = FALSE) +# classic representation (use grid = TRUE to display the background lines of the y axis ticks) +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"), classic = TRUE, grid = FALSE) +# graphic info: +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) +# all the arguments: +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 = NULL, ylog = FALSE, y.break.nb = NULL, y.include.zero = FALSE, y.top.extra.margin = 0.05, y.bottom.extra.margin = 0.05, stat.disp = "above", stat.size = 4, xlab = "GROUP", ylab = "MEAN", vertical = FALSE, title = "GRAPH1", text.size = 14, text.angle = 45, classic = TRUE, grid = TRUE, return = TRUE, path.lib = NULL)