diff --git a/examples_alone.txt b/examples_alone.txt index 6362918c34ba4b2c4a6a935d8b6baeefeeabf690..591c49f5c0c19bfa7f7e799fc2cabaaee63d78be 100644 --- a/examples_alone.txt +++ b/examples_alone.txt @@ -327,87 +327,113 @@ set.seed(1) ; obs1 <- data.frame(km = rnorm(1000, 10, 3), time = rnorm(1000, 10, ######## fun_gg_bar_mean() # 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) +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) # 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) +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, title = "GRAPH1", text.size = 20, text.angle = 45, classic = FALSE) # 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 +# 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 +# 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 +# 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 +# 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 +# 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 +# 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 +# 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 +# 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 +# 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 +# grouped 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), 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 +# grouped 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), 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 +# 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 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 +# 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 +# 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 +# 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 +# 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) +# 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 +# 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 +# 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 +# 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 +# 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 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 +# 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) +# 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 +# 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 +# dot jitter. 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 = 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) +# 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) +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") +# 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) +# include zero in the y-axis +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) # 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 = (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) 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) +# 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) +# 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()") +# 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 = 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, title = "GRAPH1", text.size = 14, text.angle = 45, classic = TRUE, grid = TRUE, return = TRUE, plot = TRUE, add = NULL, path.lib = NULL)