forked from tidyverse/ggplot2
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathgeom-point.r
146 lines (143 loc) · 5.18 KB
/
geom-point.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
#' Points
#'
#' The point geom is used to create scatterplots. The scatterplot is most
#' useful for displaying the relationship between two continuous variables.
#' It can be used to compare one continuous and one categorical variable, or
#' two categorical variables, but a variation like [geom_jitter()],
#' [geom_count()], or [geom_bin2d()] is usually more
#' appropriate.
#'
#' The \emph{bubblechart} is a scatterplot with a third variable mapped to
#' the size of points. There are no special names for scatterplots where
#' another variable is mapped to point shape or colour, however.
#'
#' @section Overplotting:
#' The biggest potential problem with a scatterplot is overplotting: whenever
#' you have more than a few points, points may be plotted on top of one
#' another. This can severely distort the visual appearance of the plot.
#' There is no one solution to this problem, but there are some techniques
#' that can help. You can add additional information with
#' [geom_smooth()], [geom_quantile()] or
#' [geom_density_2d()]. If you have few unique x values,
#' [geom_boxplot()] may also be useful.
#'
#' Alternatively, you can
#' summarise the number of points at each location and display that in some
#' way, using [geom_count()], [geom_hex()], or
#' [geom_density2d()].
#'
#' Another technique is to make the points transparent (e.g.
#' `geom_point(alpha = 0.05)`) or very small (e.g.
#' `geom_point(shape = ".")`).
#'
#' @eval rd_aesthetics("geom", "point")
#' @inheritParams layer
#' @param na.rm If `FALSE`, the default, missing values are removed with
#' a warning. If `TRUE`, missing values are silently removed.
#' @param ... other arguments passed on to [layer()]. These are
#' often aesthetics, used to set an aesthetic to a fixed value, like
#' `color = "red"` or `size = 3`. They may also be parameters
#' to the paired geom/stat.
#' @inheritParams layer
#' @export
#' @examples
#' p <- ggplot(mtcars, aes(wt, mpg))
#' p + geom_point()
#'
#' # Add aesthetic mappings
#' p + geom_point(aes(colour = factor(cyl)))
#' p + geom_point(aes(shape = factor(cyl)))
#' p + geom_point(aes(size = qsec))
#'
#' # Change scales
#' p + geom_point(aes(colour = cyl)) + scale_colour_gradient(low = "blue")
#' p + geom_point(aes(shape = factor(cyl))) + scale_shape(solid = FALSE)
#'
#' # Set aesthetics to fixed value
#' ggplot(mtcars, aes(wt, mpg)) + geom_point(colour = "red", size = 3)
#'
#' \donttest{
#' # Varying alpha is useful for large datasets
#' d <- ggplot(diamonds, aes(carat, price))
#' d + geom_point(alpha = 1/10)
#' d + geom_point(alpha = 1/20)
#' d + geom_point(alpha = 1/100)
#' }
#'
#' # For shapes that have a border (like 21), you can colour the inside and
#' # outside separately. Use the stroke aesthetic to modify the width of the
#' # border
#' ggplot(mtcars, aes(wt, mpg)) +
#' geom_point(shape = 21, colour = "black", fill = "white", size = 5, stroke = 5)
#'
#' \donttest{
#' # You can create interesting shapes by layering multiple points of
#' # different sizes
#' p <- ggplot(mtcars, aes(mpg, wt, shape = factor(cyl)))
#' p + geom_point(aes(colour = factor(cyl)), size = 4) +
#' geom_point(colour = "grey90", size = 1.5)
#' p + geom_point(colour = "black", size = 4.5) +
#' geom_point(colour = "pink", size = 4) +
#' geom_point(aes(shape = factor(cyl)))
#'
#' # These extra layers don't usually appear in the legend, but we can
#' # force their inclusion
#' p + geom_point(colour = "black", size = 4.5, show.legend = TRUE) +
#' geom_point(colour = "pink", size = 4, show.legend = TRUE) +
#' geom_point(aes(shape = factor(cyl)))
#'
#' # geom_point warns when missing values have been dropped from the data set
#' # and not plotted, you can turn this off by setting na.rm = TRUE
#' mtcars2 <- transform(mtcars, mpg = ifelse(runif(32) < 0.2, NA, mpg))
#' ggplot(mtcars2, aes(wt, mpg)) + geom_point()
#' ggplot(mtcars2, aes(wt, mpg)) + geom_point(na.rm = TRUE)
#' }
geom_point <- function(mapping = NULL, data = NULL,
stat = "identity", position = "identity",
...,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomPoint,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
...
)
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
GeomPoint <- ggproto("GeomPoint", Geom,
required_aes = c("x", "y"),
non_missing_aes = c("size", "shape", "colour"),
default_aes = aes(
shape = 19, colour = "black", size = 1.5, fill = NA,
alpha = NA, stroke = 0.5
),
draw_panel = function(data, panel_params, coord, na.rm = FALSE) {
coords <- coord$transform(data, panel_params)
ggname("geom_point",
pointsGrob(
coords$x, coords$y,
pch = coords$shape,
gp = gpar(
col = alpha(coords$colour, coords$alpha),
fill = alpha(coords$fill, coords$alpha),
# Stroke is added around the outside of the point
fontsize = coords$size * .pt + coords$stroke * .stroke / 2,
lwd = coords$stroke * .stroke / 2
)
)
)
},
draw_key = draw_key_point
)