-
Notifications
You must be signed in to change notification settings - Fork 2k
/
geom-boxplot.R
398 lines (369 loc) · 14.6 KB
/
geom-boxplot.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
#' A box and whiskers plot (in the style of Tukey)
#'
#' The boxplot compactly displays the distribution of a continuous variable.
#' It visualises five summary statistics (the median, two hinges
#' and two whiskers), and all "outlying" points individually.
#'
#' @eval rd_orientation()
#'
#' @section Summary statistics:
#' The lower and upper hinges correspond to the first and third quartiles
#' (the 25th and 75th percentiles). This differs slightly from the method used
#' by the [boxplot()] function, and may be apparent with small samples.
#' See [boxplot.stats()] for more information on how hinge
#' positions are calculated for [boxplot()].
#'
#' The upper whisker extends from the hinge to the largest value no further than
#' 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance
#' between the first and third quartiles). The lower whisker extends from the
#' hinge to the smallest value at most 1.5 * IQR of the hinge. Data beyond the
#' end of the whiskers are called "outlying" points and are plotted
#' individually.
#'
#' In a notched box plot, the notches extend `1.58 * IQR / sqrt(n)`.
#' This gives a roughly 95% confidence interval for comparing medians.
#' See McGill et al. (1978) for more details.
#'
#' @eval rd_aesthetics("geom", "boxplot")
#'
#' @seealso [geom_quantile()] for continuous `x`,
#' [geom_violin()] for a richer display of the distribution, and
#' [geom_jitter()] for a useful technique for small data.
#' @inheritParams layer
#' @inheritParams geom_bar
#' @param geom,stat Use to override the default connection between
#' `geom_boxplot()` and `stat_boxplot()`. For more information about
#' overriding these connections, see how the [stat][layer_stats] and
#' [geom][layer_geoms] arguments work.
#' @param outliers Whether to display (`TRUE`) or discard (`FALSE`) outliers
#' from the plot. Hiding or discarding outliers can be useful when, for
#' example, raw data points need to be displayed on top of the boxplot.
#' By discarding outliers, the axis limits will adapt to the box and whiskers
#' only, not the full data range. If outliers need to be hidden and the axes
#' needs to show the full data range, please use `outlier.shape = NA` instead.
#' @param outlier.colour,outlier.color,outlier.fill,outlier.shape,outlier.size,outlier.stroke,outlier.alpha
#' Default aesthetics for outliers. Set to `NULL` to inherit from the
#' data's aesthetics.
#' @param whisker.colour,whisker.color,whisker.linetype,whisker.linewidth
#' Default aesthetics for the whiskers. Set to `NULL` to inherit from the
#' data's aesthetics.
#' @param median.colour,median.color,median.linetype,median.linewidth
#' Default aesthetics for the median line. Set to `NULL` to inherit from the
#' data's aesthetics.
#' @param staple.colour,staple.color,staple.linetype,staple.linewidth
#' Default aesthetics for the staples. Set to `NULL` to inherit from the
#' data's aesthetics. Note that staples don't appear unless the `staplewidth`
#' argument is set to a non-zero size.
#' @param box.colour,box.color,box.linetype,box.linewidth
#' Default aesthetics for the boxes. Set to `NULL` to inherit from the
#' data's aesthetics.
#' @param notch If `FALSE` (default) make a standard box plot. If
#' `TRUE`, make a notched box plot. Notches are used to compare groups;
#' if the notches of two boxes do not overlap, this suggests that the medians
#' are significantly different.
#' @param notchwidth For a notched box plot, width of the notch relative to
#' the body (defaults to `notchwidth = 0.5`).
#' @param staplewidth The relative width of staples to the width of the box.
#' Staples mark the ends of the whiskers with a line.
#' @param varwidth If `FALSE` (default) make a standard box plot. If
#' `TRUE`, boxes are drawn with widths proportional to the
#' square-roots of the number of observations in the groups (possibly
#' weighted, using the `weight` aesthetic).
#' @note In the unlikely event you specify both US and UK spellings of colour,
#' the US spelling will take precedence.
#'
#' @export
#' @references McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of
#' box plots. The American Statistician 32, 12-16.
#' @examples
#' p <- ggplot(mpg, aes(class, hwy))
#' p + geom_boxplot()
#' # Orientation follows the discrete axis
#' ggplot(mpg, aes(hwy, class)) + geom_boxplot()
#'
#' p + geom_boxplot(notch = TRUE)
#' p + geom_boxplot(varwidth = TRUE)
#' p + geom_boxplot(fill = "white", colour = "#3366FF")
#' # By default, outlier points match the colour of the box. Use
#' # outlier.colour to override
#' p + geom_boxplot(outlier.colour = "red", outlier.shape = 1)
#' # Remove outliers when overlaying boxplot with original data points
#' p + geom_boxplot(outlier.shape = NA) + geom_jitter(width = 0.2)
#'
#' # Boxplots are automatically dodged when any aesthetic is a factor
#' p + geom_boxplot(aes(colour = drv))
#'
#' # You can also use boxplots with continuous x, as long as you supply
#' # a grouping variable. cut_width is particularly useful
#' ggplot(diamonds, aes(carat, price)) +
#' geom_boxplot()
#' ggplot(diamonds, aes(carat, price)) +
#' geom_boxplot(aes(group = cut_width(carat, 0.25)))
#' # Adjust the transparency of outliers using outlier.alpha
#' ggplot(diamonds, aes(carat, price)) +
#' geom_boxplot(aes(group = cut_width(carat, 0.25)), outlier.alpha = 0.1)
#'
#' \donttest{
#' # It's possible to draw a boxplot with your own computations if you
#' # use stat = "identity":
#' set.seed(1)
#' y <- rnorm(100)
#' df <- data.frame(
#' x = 1,
#' y0 = min(y),
#' y25 = quantile(y, 0.25),
#' y50 = median(y),
#' y75 = quantile(y, 0.75),
#' y100 = max(y)
#' )
#' ggplot(df, aes(x)) +
#' geom_boxplot(
#' aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
#' stat = "identity"
#' )
#' }
geom_boxplot <- function(mapping = NULL, data = NULL,
stat = "boxplot", position = "dodge2",
...,
outliers = TRUE,
outlier.colour = NULL,
outlier.color = NULL,
outlier.fill = NULL,
outlier.shape = NULL,
outlier.size = NULL,
outlier.stroke = 0.5,
outlier.alpha = NULL,
whisker.colour = NULL,
whisker.color = NULL,
whisker.linetype = NULL,
whisker.linewidth = NULL,
staple.colour = NULL,
staple.color = NULL,
staple.linetype = NULL,
staple.linewidth = NULL,
median.colour = NULL,
median.color = NULL,
median.linetype = NULL,
median.linewidth = NULL,
box.colour = NULL,
box.color = NULL,
box.linetype = NULL,
box.linewidth = NULL,
notch = FALSE,
notchwidth = 0.5,
staplewidth = 0,
varwidth = FALSE,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE) {
# varwidth = TRUE is not compatible with preserve = "total"
if (is.character(position)) {
if (varwidth == TRUE) position <- position_dodge2(preserve = "single")
} else {
if (identical(position$preserve, "total") & varwidth == TRUE) {
cli::cli_warn("Can't preserve total widths when {.code varwidth = TRUE}.")
position$preserve <- "single"
}
}
outlier_gp <- list(
colour = outlier.color %||% outlier.colour,
fill = outlier.fill,
shape = outlier.shape,
size = outlier.size,
stroke = outlier.stroke,
alpha = outlier.alpha
)
whisker_gp <- list(
colour = whisker.color %||% whisker.colour,
linetype = whisker.linetype,
linewidth = whisker.linewidth
)
staple_gp <- list(
colour = staple.color %||% staple.colour,
linetype = staple.linetype,
linewidth = staple.linewidth
)
median_gp <- list(
colour = median.color %||% median.colour,
linetype = median.linetype,
linewidth = median.linewidth
)
box_gp <- list(
colour = box.color %||% box.colour,
linetype = box.linetype,
linewidth = box.linewidth
)
check_number_decimal(staplewidth)
check_bool(outliers)
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomBoxplot,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list2(
outliers = outliers,
outlier_gp = outlier_gp,
whisker_gp = whisker_gp,
staple_gp = staple_gp,
median_gp = median_gp,
box_gp = box_gp,
notch = notch,
notchwidth = notchwidth,
staplewidth = staplewidth,
varwidth = varwidth,
na.rm = na.rm,
orientation = orientation,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
GeomBoxplot <- ggproto("GeomBoxplot", Geom,
# need to declare `width` here in case this geom is used with a stat that
# doesn't have a `width` parameter (e.g., `stat_identity`).
extra_params = c("na.rm", "width", "orientation", "outliers"),
setup_params = function(data, params) {
params$flipped_aes <- has_flipped_aes(data, params)
params
},
setup_data = function(data, params) {
data$flipped_aes <- params$flipped_aes
data <- flip_data(data, params$flipped_aes)
data$width <- data$width %||%
params$width %||% (resolution(data$x, FALSE, TRUE) * 0.9)
if (isFALSE(params$outliers)) {
data$outliers <- NULL
}
if (!is.null(data$outliers)) {
suppressWarnings({
out_min <- vapply(data$outliers, min, numeric(1))
out_max <- vapply(data$outliers, max, numeric(1))
})
data$ymin_final <- pmin(out_min, data$ymin)
data$ymax_final <- pmax(out_max, data$ymax)
}
# if `varwidth` not requested or not available, don't use it
if (is.null(params) || is.null(params$varwidth) || !params$varwidth || is.null(data$relvarwidth)) {
data$xmin <- data$x - data$width / 2
data$xmax <- data$x + data$width / 2
} else {
# make `relvarwidth` relative to the size of the largest group
data$relvarwidth <- data$relvarwidth / max(data$relvarwidth)
data$xmin <- data$x - data$relvarwidth * data$width / 2
data$xmax <- data$x + data$relvarwidth * data$width / 2
}
data$width <- NULL
if (!is.null(data$relvarwidth)) data$relvarwidth <- NULL
flip_data(data, params$flipped_aes)
},
draw_group = function(self, data, panel_params, coord, lineend = "butt",
linejoin = "mitre", fatten = 2, outlier_gp = NULL,
whisker_gp = NULL, staple_gp = NULL, median_gp = NULL,
box_gp = NULL, notch = FALSE, notchwidth = 0.5,
staplewidth = 0, varwidth = FALSE, flipped_aes = FALSE) {
data <- check_linewidth(data, snake_class(self))
data <- flip_data(data, flipped_aes)
# this may occur when using geom_boxplot(stat = "identity")
if (nrow(data) != 1) {
cli::cli_abort(c(
"Can only draw one boxplot per group.",
"i"= "Did you forget {.code aes(group = ...)}?"
))
}
common <- list(fill = fill_alpha(data$fill, data$alpha), group = data$group)
whiskers <- data_frame0(
x = c(data$x, data$x),
xend = c(data$x, data$x),
y = c(data$upper, data$lower),
yend = c(data$ymax, data$ymin),
colour = rep(whisker_gp$colour %||% data$colour, 2),
linetype = rep(whisker_gp$linetype %||% data$linetype, 2),
linewidth = rep(whisker_gp$linewidth %||% data$linewidth, 2),
alpha = c(NA_real_, NA_real_),
!!!common,
.size = 2
)
whiskers <- flip_data(whiskers, flipped_aes)
box <- transform(
data,
y = middle,
ymax = upper,
ymin = lower,
ynotchlower = ifelse(notch, notchlower, NA),
ynotchupper = ifelse(notch, notchupper, NA),
notchwidth = notchwidth
)
box <- flip_data(box, flipped_aes)
if (!is.null(data$outliers) && length(data$outliers[[1]]) >= 1) {
outliers <- data_frame0(
y = data$outliers[[1]],
x = data$x[1],
colour = outlier_gp$colour %||% data$colour[1],
fill = outlier_gp$fill %||% data$fill[1],
shape = outlier_gp$shape %||% data$shape[1] %||% 19,
size = outlier_gp$size %||% data$size[1] %||% 1.5,
stroke = outlier_gp$stroke %||% data$stroke[1] %||% 0.5,
fill = NA,
alpha = outlier_gp$alpha %||% data$alpha[1],
.size = length(data$outliers[[1]])
)
outliers <- flip_data(outliers, flipped_aes)
outliers_grob <- GeomPoint$draw_panel(outliers, panel_params, coord)
} else {
outliers_grob <- NULL
}
if (staplewidth != 0) {
staples <- data_frame0(
x = rep((data$xmin - data$x) * staplewidth + data$x, 2),
xend = rep((data$xmax - data$x) * staplewidth + data$x, 2),
y = c(data$ymax, data$ymin),
yend = c(data$ymax, data$ymin),
linetype = rep(staple_gp$linetype %||% data$linetype, 2),
linewidth = rep(staple_gp$linewidth %||% data$linewidth, 2),
colour = rep(staple_gp$colour %||% data$colour, 2),
alpha = c(NA_real_, NA_real_),
!!!common,
.size = 2
)
staples <- flip_data(staples, flipped_aes)
staple_grob <- GeomSegment$draw_panel(
staples, panel_params, coord,
lineend = lineend
)
} else {
staple_grob <- NULL
}
ggname("geom_boxplot", grobTree(
outliers_grob,
staple_grob,
GeomSegment$draw_panel(whiskers, panel_params, coord, lineend = lineend),
GeomCrossbar$draw_panel(
box,
fatten = fatten,
panel_params,
coord,
lineend = lineend,
linejoin = linejoin,
flipped_aes = flipped_aes,
middle_gp = median_gp,
box_gp = box_gp
)
))
},
draw_key = draw_key_boxplot,
default_aes = aes(
weight = 1, colour = from_theme(col_mix(ink, paper, 0.2)),
fill = from_theme(paper), size = from_theme(pointsize),
alpha = NA, shape = from_theme(pointshape), linetype = from_theme(bordertype),
linewidth = from_theme(borderwidth)
),
required_aes = c("x|y", "lower|xlower", "upper|xupper", "middle|xmiddle", "ymin|xmin", "ymax|xmax"),
rename_size = TRUE
)