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#' Atomic Jitter plot
#'
#' @inheritParams common_args
#' @param x A character string of the column name to plot on the x-axis.
#' A character/factor column is expected. If multiple columns are provided, the columns will be concatenated with `x_sep`.
#' @param x_sep A character string to concatenate the columns in `x`, if multiple columns are provided.
#' When `in_form` is "wide", `x` columns will not be concatenated.
#' @param y A character string of the column name to plot on the y-axis. A numeric column is expected.
#' When `in_form` is "wide", `y` is not required. The values under `x` columns will be used as y-values.
#' @param in_form A character string to specify the input data type. Either "long" or "wide".
#' @param sort_x A character string to specify the sorting of x-axis, chosen from "none", "mean_asc", "mean_desc", "mean", "median_asc", "median_desc", "median".
#' * `none` means no sorting (as-is).
#' * `mean_asc` sorts the x-axis by ascending mean of y-values.
#' * `mean_desc` sorts the x-axis by descending mean of y-values.
#' * `mean` is an alias for `mean_asc`.
#' * `median_asc` sorts the x-axis by ascending median of y-values.
#' * `median_desc` sorts the x-axis by descending median of y-values.
#' * `median` is an alias for `median_asc`.
#' @param flip A logical value to flip the plot.
#' @param keep_empty A logical value to keep the empty levels in the x-axis.
#' @param group_by A character string to dodge the points.
#' @param group_by_sep A character string to concatenate the columns in `group_by`, if multiple columns are provided.
#' @param group_name A character string to name the legend of dodge.
#' @param add_bg A logical value to add background to the plot.
#' @param bg_palette A character string to specify the palette of the background.
#' @param bg_palcolor A character vector to specify the colors of the background.
#' @param bg_alpha A numeric value to specify the transparency of the background.
#' @param shape A numeric value to specify the point shape.
#' Shapes 21–25 have borders; border behavior is controlled by `border`.
#' @param border A logical or character value to specify the border of points when the shape has border (21–25).
#' If TRUE, border color follows the point color (same as fill). If a color string, uses that constant border color.
#' If FALSE, no border.
#' @param size_by A numeric column name or a single numeric value for the point size.
#' When a column, sizes are scaled (see scatter plots).
#' @param size_name Legend title for size when `size_by` is a column.
#' @param size_trans A function or a name of a global function to transform `size_by` (when `size_by` is a column).
#' The legend shows original (untransformed) values.
#' @param alpha Point transparency.
#' @param jitter_width,jitter_height Jitter parameters.
#' @param y_max,y_min Numeric or quantile strings ("q95", "q5") for y limits computation (used for fixed coord).
#' @param y_trans,y_nbreaks Axis settings.
#' @param labels A vector of row names or indices to label the points.
#' @param label_by A character column name to use as the label text. If NULL, rownames are used.
#' @param nlabel Number of points to label per x-group when `labels` is NULL (top by y^2 + size^2).
#' @param order_by A string of expression passed to `dplyr::arrange()` to order the data to get the
#' top `nlabel` points for labeling. Default is `-({y}^2 + {size_by}^2)` (similar to VolcanoPlot).
#' @param label_size,label_fg,label_bg,label_bg_r Label aesthetics.
#' @param add_hline Add one or more horizontal reference lines at the given y-value(s).
#' @param hline_type The line type for the horizontal reference line(s).
#' @param hline_width The line width for the horizontal reference line(s).
#' @param hline_color The color for the horizontal reference line(s).
#' @param hline_alpha The alpha for the horizontal reference line(s).
#' @param highlight,highlight_color,highlight_size,highlight_alpha Highlighted point options.
#' @return A ggplot object
#' @keywords internal
#' @importFrom stats median quantile
#' @importFrom rlang sym syms parse_expr %||%
#' @importFrom dplyr mutate ungroup first
#' @importFrom ggplot2 geom_point labs theme element_line element_text coord_flip
#' @importFrom ggplot2 position_jitterdodge scale_fill_manual scale_color_manual scale_y_continuous scale_size_area guide_legend guide_colorbar
#' @importFrom ggrepel geom_text_repel
JitterPlotAtomic <- function(
data, x, x_sep = "_", y = NULL, in_form = c("long", "wide"),
sort_x = c("none", "mean_asc", "mean_desc", "mean", "median_asc", "median_desc", "median"),
flip = FALSE, keep_empty = FALSE, group_by = NULL, group_by_sep = "_", group_name = NULL,
x_text_angle = 0, order_by = "-({y}^2 + {size_by}^2)",
theme = "theme_this", theme_args = list(), palette = "Paired", palcolor = NULL, alpha = 1,
aspect.ratio = NULL, legend.position = "right", legend.direction = "vertical",
shape = 21, border = "black",
size_by = 2, size_name = NULL, size_trans = NULL, y_nbreaks = 4,
jitter_width = 0.5, jitter_height = 0, y_max = NULL, y_min = NULL, y_trans = "identity",
add_bg = FALSE, bg_palette = "stripe", bg_palcolor = NULL, bg_alpha = 0.2,
add_hline = NULL, hline_type = "solid", hline_width = 0.5, hline_color = "black", hline_alpha = 1,
labels = NULL, label_by = NULL, nlabel = 5, label_size = 3, label_fg = "black", label_bg = "white", label_bg_r = 0.1,
highlight = NULL, highlight_color = "red2", highlight_size = 1, highlight_alpha = 1,
facet_by = NULL, facet_scales = "fixed", facet_ncol = NULL, facet_nrow = NULL, facet_byrow = TRUE,
title = NULL, subtitle = NULL, xlab = NULL, ylab = NULL, seed = 8525, ...
) {
set.seed(seed)
ggplot <- if (getOption("plotthis.gglogger.enabled", FALSE)) gglogger::ggplot else ggplot2::ggplot
in_form <- match.arg(in_form)
if (in_form == "wide") {
data <- data %>% tidyr::pivot_longer(cols = x, names_to = ".x", values_to = ".y")
x <- ".x"; y <- ".y"
}
x <- check_columns(data, x, force_factor = TRUE, allow_multi = TRUE, concat_multi = TRUE, concat_sep = x_sep)
y <- check_columns(data, y)
group_by <- check_columns(data, group_by, force_factor = TRUE, allow_multi = TRUE, concat_multi = TRUE, concat_sep = group_by_sep)
facet_by <- check_columns(data, facet_by, force_factor = TRUE, allow_multi = TRUE)
sort_x <- match.arg(sort_x)
data <- data %>%
dplyr::group_by(!!!syms(unique(c(x, group_by, facet_by)))) %>%
mutate(.y_mean = mean(!!sym(y)), .y_median = median(!!sym(y))) %>%
ungroup()
values <- data[[y]][is.finite(data[[y]])]
if (is.character(y_max)) {
q_max <- as.numeric(sub("(^q)(\\d+)", "\\2", y_max)) / 100
y_max_use <- stats::quantile(values, q_max, na.rm = TRUE)
} else {
y_max_use <- max(values, na.rm = TRUE)
}
if (is.null(y_min)) {
y_min_use <- min(values, na.rm = TRUE)
} else if (is.character(y_min)) {
q_min <- as.numeric(sub("(^q)(\\d+)", "\\2", y_min)) / 100
y_min_use <- stats::quantile(values, q_min, na.rm = TRUE)
} else {
y_min_use <- y_min
}
rm(values)
# Highlight flag
if (!is.null(highlight)) {
if (isTRUE(highlight)) {
data$.highlight <- TRUE
} else if (is.numeric(highlight)) {
data$.highlight <- 1:nrow(data) %in% highlight
} else if (is.character(highlight) && length(highlight) == 1) {
data <- dplyr::mutate(data, .highlight = !!parse_expr(highlight))
} else if (is.null(rownames(data))) {
stop("No row names in the data, please provide a vector of indexes to highlight.")
} else {
data$.highlight <- rownames(data) %in% highlight
}
} else {
data$.highlight <- FALSE
}
# Labels (similar to VolcanoPlot)
# Labels using distance = y^2 + size^2
data$.label <- if (is.null(label_by)) rownames(data) else data[[label_by]]
data$.show_label <- FALSE
if (!is.null(labels)) {
data[labels, ".show_label"] <- TRUE
} else if (nlabel > 0) {
if (!is.null(facet_by)) {
data <- data %>% dplyr::group_by(!!!syms(facet_by), !!sym(x)) %>%
dplyr::arrange(!!rlang::parse_expr(glue::glue(order_by))) %>%
dplyr::mutate(.show_label = dplyr::row_number() <= nlabel) %>%
dplyr::ungroup()
} else {
data <- data %>% dplyr::group_by(!!sym(x)) %>%
dplyr::arrange(!!rlang::parse_expr(glue::glue(order_by))) %>%
dplyr::mutate(.show_label = dplyr::row_number() <= nlabel) %>%
dplyr::ungroup()
}
}
data <- as.data.frame(data)
if (sort_x == "mean" || sort_x == "mean_asc") {
data[[x]] <- stats::reorder(data[[x]], data$.y_mean)
} else if (sort_x == "mean_desc") {
data[[x]] <- stats::reorder(data[[x]], -data$.y_mean)
} else if (sort_x == "median" || sort_x == "median_asc") {
data[[x]] <- stats::reorder(data[[x]], data$.y_median)
} else if (sort_x == "median_desc") {
data[[x]] <- stats::reorder(data[[x]], -data$.y_median)
}
if (isTRUE(flip)) {
data[[x]] <- factor(data[[x]], levels = rev(levels(data[[x]])))
aspect.ratio <- 1 / aspect.ratio
if (length(aspect.ratio) == 0 || is.na(aspect.ratio)) aspect.ratio <- NULL
}
# Base
p <- ggplot(data, aes(x = !!sym(x), y = !!sym(y)))
if (isTRUE(add_bg)) {
p <- p + bg_layer(data, x, bg_palette, bg_palcolor, bg_alpha, keep_empty, facet_by)
}
# Positioner (jitter + optional dodge)
pos <- position_jitterdodge(
jitter.width = jitter_width, jitter.height = jitter_height,
dodge.width = ifelse(is.null(group_by), 0, 0.9), seed = seed
)
# Build point layer, color by x
has_fill <- shape %in% 21:25
point_args <- list(
shape = shape, position = pos, alpha = alpha
)
mapping <- list(aes())
if (has_fill) {
mapping[[length(mapping) + 1]] <- aes(fill = !!sym(x))
# border handling
if (isTRUE(border)) {
mapping[[length(mapping) + 1]] <- aes(color = !!sym(x))
} else if (is.character(border) && length(border) == 1) {
point_args$color <- border
} else {
point_args$color <- NA
}
} else {
# shapes without fill
mapping[[length(mapping) + 1]] <- aes(color = !!sym(x))
}
# size handling
if (is.numeric(size_by)) {
point_args$size <- size_by
} else {
size_by <- check_columns(data, size_by)
# transform size values while keeping original values for legend labels
f <- if (is.null(size_trans)) {
identity
} else if (is.function(size_trans)) {
size_trans
} else {
get(as.character(size_trans), inherits = TRUE)
}
data$.size_raw <- data[[size_by]]
data$.size_mapped <- f(data$.size_raw)
mapping[[length(mapping) + 1]] <- aes(size = !!sym(".size_mapped"))
}
# Group for dodging only (no legend)
if (!is.null(group_by)) {
mapping[[length(mapping) + 1]] <- aes(group = !!sym(group_by))
}
modify_list <- utils::getFromNamespace("modify_list", "ggplot2")
point_args$mapping <- Reduce(modify_list, mapping)
point_args$data <- data
p <- p + do.call(geom_point, point_args)
# Discrete color/fill scales by x
x_levels <- levels(data[[x]])
if (has_fill) {
p <- p + scale_fill_manual(
name = x, values = palette_this(x_levels, palette = palette, palcolor = palcolor), drop = !keep_empty
)
if (isTRUE(border)) {
p <- p + scale_color_manual(
values = palette_this(x_levels, palette = palette, palcolor = palcolor), guide = "none", drop = !keep_empty
)
}
} else {
p <- p + scale_color_manual(
name = x, values = palette_this(x_levels, palette = palette, palcolor = palcolor), drop = !keep_empty
)
}
# Size scale when mapped
if (!is.numeric(size_by)) {
# compute breaks on raw, but use transformed positions for sizes
f <- if (is.null(size_trans)) {
identity
} else if (is.function(size_trans)) {
size_trans
} else {
get(as.character(size_trans), inherits = TRUE)
}
raw_vals <- data$.size_raw
raw_breaks <- unique(scales::pretty_breaks(n = 4)(raw_vals))
mapped_breaks <- tryCatch(f(raw_breaks), error = function(e) raw_breaks)
p <- p + scale_size_area(max_size = 6, breaks = mapped_breaks, labels = raw_breaks) +
guides(size = guide_legend(
title = size_name %||% size_by,
override.aes = list(fill = "grey30", shape = shape), order = 1
))
}
# Highlight overlay on top (does not affect legends)
if (any(data$.highlight)) {
hi_df <- data[data$.highlight, , drop = FALSE]
if (has_fill) {
p <- p + geom_point(
data = hi_df,
mapping = if (!is.null(group_by)) {
aes(x = !!sym(x), y = !!sym(y), group = !!sym(group_by))
} else {
aes(x = !!sym(x), y = !!sym(y))
},
shape = shape, fill = highlight_color, color = "transparent",
position = pos, size = if (is.numeric(size_by)) highlight_size else highlight_size, alpha = highlight_alpha
)
} else {
p <- p + geom_point(
data = hi_df,
mapping = if (!is.null(group_by)) {
aes(x = !!sym(x), y = !!sym(y), group = !!sym(group_by))
} else {
aes(x = !!sym(x), y = !!sym(y))
},
shape = shape, color = highlight_color,
position = pos, size = if (is.numeric(size_by)) highlight_size else highlight_size, alpha = highlight_alpha
)
}
}
# Labels layer
if (any(data$.show_label)) {
p <- p + geom_text_repel(
data = data[data$.show_label, , drop = FALSE],
mapping = aes(label = !!sym(".label")),
color = label_fg, bg.color = label_bg, bg.r = label_bg_r,
size = label_size, min.segment.length = 0, segment.color = "grey40",
max.overlaps = 100
)
}
# Optional horizontal reference lines
if (!is.null(add_hline)) {
p <- p + ggplot2::geom_hline(
yintercept = add_hline,
linetype = hline_type, linewidth = hline_width, color = hline_color, alpha = hline_alpha
)
}
just <- calc_just(x_text_angle)
p <- p +
scale_x_discrete(drop = !keep_empty) +
scale_y_continuous(trans = y_trans, n.breaks = y_nbreaks) +
labs(title = title, subtitle = subtitle, x = xlab %||% x, y = ylab %||% y)
height <- width <- 0
if (!identical(legend.position, "none")) {
if (legend.position %in% c("right", "left")) {
width <- width + 1
} else if (legend.direction == "horizontal") {
height <- height + 1
} else {
height <- height + 2
}
}
x_maxchars <- max(nchar(levels(data[[x]])))
nx <- nlevels(data[[x]])
nd <- ifelse(is.null(group_by), 1, nlevels(data[[group_by]]))
facet_free <- !is.null(facet_by) && (
identical(facet_scales, "free") ||
(!flip && identical(facet_scales, "free_y")) ||
(flip && identical(facet_scales, "free_x"))
)
if (isTRUE(flip)) {
strip_position <- "top"
p <- p + ggplot2::theme(
strip.text.y = element_text(angle = 0),
panel.grid.major.y = element_line(color = "grey", linetype = 2)
)
if (facet_free) p <- p + coord_flip() else p <- p + coord_flip(ylim = c(y_min_use, y_max_use))
width <- max(3, width + 2.2 + x_maxchars * 0.05)
height <- height + nx * nd * 0.3
} else {
strip_position <- "top"
p <- p + ggplot2::theme(
strip.text.x = element_text(angle = 0),
panel.grid.major.x = element_line(color = "grey", linetype = 2)
)
if (!facet_free) p <- p + ggplot2::coord_cartesian(ylim = c(y_min_use, y_max_use))
height <- max(3, height + 2 + x_maxchars * 0.05)
width <- width + nx * nd * 0.3
}
p <- p +
do.call(theme, theme_args) +
ggplot2::theme(
aspect.ratio = aspect.ratio,
axis.text.x = element_text(angle = x_text_angle, hjust = just$h, vjust = just$v),
legend.position = legend.position,
legend.direction = legend.direction
)
attr(p, "height") <- height
attr(p, "width") <- max(width, height)
facet_plot(p, facet_by, facet_scales, facet_nrow, facet_ncol, facet_byrow,
strip.position = strip_position, legend.position = legend.position,
legend.direction = legend.direction
)
}
#' Jitter Plot
#'
#' @description
#' Jittered point plot with optional background, highlight, labels and faceting.
#' @rdname jitterplot
#' @return The Jitter plot(s).
#' When `split_by` is not provided, it returns a ggplot object.
#' When `split_by` is provided, it returns a object of plots wrapped by `patchwork::wrap_plots` if `combine = TRUE`;
#' otherwise, it returns a list of ggplot objects.
#' @export
#' @inheritParams JitterPlotAtomic
#' @inheritParams common_args
#' @examples
#' \donttest{
#' set.seed(8525)
#' n <- 200
#' x <- sample(LETTERS[1:5], n, replace = TRUE)
#' group <- sample(c("G1", "G2"), n, replace = TRUE)
#' size <- rexp(n, rate = 1)
#' id <- paste0("pt", seq_len(n))
#' y <- rnorm(n, mean = ifelse(group == "G1", 0.5, -0.5)) +
#' as.numeric(factor(x, levels = LETTERS[1:5]))/10
#' df <- data.frame(
#' x = factor(x, levels = LETTERS[1:5]),
#' y = y,
#' group = group,
#' size = size,
#' id = id
#' )
#'
#' # Basic
#' JitterPlot(df, x = "x", y = "y")
#'
#' # Map size with transform; legend shows original values
#' JitterPlot(df, x = "x", y = "y", size_by = "size", size_name = "Abundance",
#' size_trans = sqrt, order_by = "-y^2")
#'
#' # Dodge by group and add a horizontal line
#' JitterPlot(df, x = "x", y = "y", group_by = "group",
#' add_hline = 0, hline_type = "dashed", hline_color = "red2")
#'
#' # Label top points by distance (y^2 + size^2)
#' JitterPlot(df, x = "x", y = "y", size_by = "size", label_by = "id", nlabel = 3)
#'
#' # Flip axes
#' JitterPlot(df, x = "x", y = "y", flip = TRUE)
#' }
JitterPlot <- function(
data, x, x_sep = "_", y = NULL, in_form = c("long", "wide"),
split_by = NULL, split_by_sep = "_",
sort_x = c("none", "mean_asc", "mean_desc", "mean", "median_asc", "median_desc", "median"),
flip = FALSE, keep_empty = FALSE, group_by = NULL, group_by_sep = "_", group_name = NULL,
x_text_angle = 0, order_by = "-({y}^2 + {size_by}^2)",
theme = "theme_this", theme_args = list(), palette = "Paired", palcolor = NULL, alpha = 1,
aspect.ratio = NULL, legend.position = "right", legend.direction = "vertical",
shape = 21, border = "black",
size_by = 2, size_name = NULL, size_trans = NULL, y_nbreaks = 4,
jitter_width = 0.5, jitter_height = 0, y_max = NULL, y_min = NULL, y_trans = "identity",
add_bg = FALSE, bg_palette = "stripe", bg_palcolor = NULL, bg_alpha = 0.2,
add_hline = NULL, hline_type = "solid", hline_width = 0.5, hline_color = "black", hline_alpha = 1,
labels = NULL, label_by = NULL, nlabel = 5, label_size = 3, label_fg = "black", label_bg = "white", label_bg_r = 0.1,
highlight = NULL, highlight_color = "red2", highlight_size = 1, highlight_alpha = 1,
facet_by = NULL, facet_scales = "fixed", facet_ncol = NULL, facet_nrow = NULL, facet_byrow = TRUE,
title = NULL, subtitle = NULL, xlab = NULL, ylab = NULL, seed = 8525,
combine = TRUE, nrow = NULL, ncol = NULL, byrow = TRUE,
axes = NULL, axis_titles = axes, guides = NULL, design = NULL, ...
) {
validate_common_args(seed)
theme <- process_theme(theme)
split_by <- check_columns(data, split_by, force_factor = TRUE, allow_multi = TRUE, concat_multi = TRUE, concat_sep = split_by_sep)
if (!is.null(split_by)) {
datas <- split(data, data[[split_by]])
datas <- datas[levels(data[[split_by]])]
} else {
datas <- list(data); names(datas) <- "..."
}
palette <- check_palette(palette, names(datas))
palcolor <- check_palcolor(palcolor, names(datas))
legend.direction <- check_legend(legend.direction, names(datas), "legend.direction")
legend.position <- check_legend(legend.position, names(datas), "legend.position")
plots <- lapply(
names(datas), function(nm) {
default_title <- if (length(datas) == 1 && identical(nm, "...")) NULL else nm
if (is.function(title)) {
title <- title(default_title)
} else {
title <- title %||% default_title
}
JitterPlotAtomic(
datas[[nm]],
x = x, x_sep = x_sep, y = y, in_form = in_form,
sort_x = sort_x, flip = flip, keep_empty = keep_empty, group_by = group_by, group_by_sep = group_by_sep, group_name = group_name,
x_text_angle = x_text_angle, theme = theme, theme_args = theme_args, palette = palette[[nm]], palcolor = palcolor[[nm]], alpha = alpha,
aspect.ratio = aspect.ratio, legend.position = legend.position[[nm]], legend.direction = legend.direction[[nm]],
shape = shape, border = border, order_by = order_by,
size_by = size_by, size_name = size_name, size_trans = size_trans, y_nbreaks = y_nbreaks,
jitter_width = jitter_width, jitter_height = jitter_height, y_max = y_max, y_min = y_min, y_trans = y_trans,
add_bg = add_bg, bg_palette = bg_palette, bg_palcolor = bg_palcolor, bg_alpha = bg_alpha,
add_hline = add_hline, hline_type = hline_type, hline_width = hline_width, hline_color = hline_color, hline_alpha = hline_alpha,
labels = labels, label_by = label_by, nlabel = nlabel, label_size = label_size, label_fg = label_fg, label_bg = label_bg, label_bg_r = label_bg_r,
highlight = highlight, highlight_color = highlight_color, highlight_size = highlight_size, highlight_alpha = highlight_alpha,
facet_by = facet_by, facet_scales = facet_scales, facet_ncol = facet_ncol, facet_nrow = facet_nrow, facet_byrow = facet_byrow,
title = title, subtitle = subtitle, xlab = xlab, ylab = ylab, seed = seed, ...
)
}
)
combine_plots(plots, combine = combine, nrow = nrow, ncol = ncol, byrow = byrow,
axes = axes, axis_titles = axis_titles, guides = guides, design = design)
}
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