Nothing
## ----chunk_options, include=FALSE---------------------------------------------
if (requireNamespace("pkgdown", quietly = TRUE) && pkgdown::in_pkgdown()) {
tiny_width = 5.5
tiny_height = 3 + 2/3
small_width = med_width = 6.75
small_height = med_height = 4.5
large_width = 8
large_height = 5.25
} else {
tiny_width = 5
tiny_height = 3 + 1/3
small_width = 5
small_height = 3 + 1/3
med_width = 5
med_height = 3 + 1/3
large_width = 5.5
large_height = 2/3
}
knitr::opts_chunk$set(
fig.width = small_width,
fig.height = small_height
)
if (capabilities("cairo") && Sys.info()[['sysname']] != "Darwin") {
knitr::opts_chunk$set(
dev = "png",
dev.args = list(type = "cairo")
)
}
## ----setup, message = FALSE, warning = FALSE----------------------------------
library(dplyr)
library(tidyr)
library(distributional)
library(ggdist)
library(ggplot2)
library(patchwork)
library(palmerpenguins)
theme_set(theme_ggdist())
## ----hidden_options, include=FALSE------------------------------------------------------------------------------------
.old_options = options(width = 120)
## ----dotsinterval_components, echo=FALSE, fig.height=4.15, fig.width=6.5----------------------------------------------
red_ = "#d95f02"
green_ = "#1b9e77"
blue_ = "#7570b3"
bracket_ = function(..., x, xend = x, y, yend = y, color = red_) {
annotate("segment",
arrow = arrow(angle = 90, ends = "both", length = unit(3, "points")),
color = color, linewidth = 0.75,
x = x, xend = xend, y = y, yend = yend,
...
)
}
thickness_ = function(x) dnorm(x,4,1) * 0.9 / dnorm(4,4,1)
refline_ = function(..., x, xend = x, y, yend = y, color = red_, linetype = "solid", alpha = 0.5) {
annotate("segment",
color = color, linetype = linetype, alpha = alpha, linewidth = 0.75,
x = x, xend = xend, y = y, yend = yend,
...
)
}
label_ = function(..., hjust = 0, color = red_) {
annotate("text",
color = color, hjust = hjust, lineheight = 1,
size = 3.25,
...
)
}
arrow_ = function(..., curvature = 0, x, xend = x, y, yend = y) {
annotate("curve",
color = red_, arrow = arrow(angle = 45, length = unit(3, "points"), type = "closed"),
curvature = curvature,
x = x, xend = xend, y = y, yend = yend
)
}
tibble(dist = dist_normal(4, 1.2)) %>%
ggplot(aes(y = 0, xdist = dist)) +
geom_hline(yintercept = 0:1, color = "gray95") +
stat_dotsinterval(
aes(linewidth = NULL),
slab_color = "gray50",
.width = 1 - 2*pnorm(-1, sd = 1.2),
fill = "gray75",
point_size = 5,
shape = 22,
slab_shape = 21,
stroke = 1.5,
linewidth = 5,
slab_linewidth = 1.5
) +
# height
refline_(x = 0, xend = 8.4, y = 1) +
bracket_(x = 8.4, y = 0, yend = 1) +
label_(label = "height", x = 8.6, y = 1) +
# scale
refline_(x = 4, xend = 8.6, y = 0.9) +
bracket_(x = 8.6, y = 0, yend = 0.9) +
label_(label = "scale = 0.9", x = 8.8, y = 0.9) +
# slab line properties
label_(x = 2.5, y = 0.7,
label = 'slab_color = "gray50"\nslab_linewidth = 1.5',
vjust = 1, hjust = 1
) +
arrow_(x = 2.52, xend = 3, y = 0.67, yend = thickness_(3.1) + 0.03, curvature = -0.2) +
# slab fill
label_(x = 5.5, y = 0.7,
label = 'slab_fill = fill = "gray75"\nslab_alpha = alpha = 1\nslab_shape = 21',
vjust = 1,
) +
arrow_(x = 5.48, xend = 4.81, y = 0.67, yend = thickness_(3.1) + 0.01, curvature = 0.2) +
# xmin / x / xmax
arrow_(x = 2.65, xend = 3, y = -0.1, yend = -0.01, curvature = -0.2) +
label_(x = 2.7, y = -0.1, label = "xmin", hjust = 1, vjust = 1) +
arrow_(x = 4, y = -0.1, yend = -0.05) +
label_(x = 4, y = -0.1, label = "x", hjust = 0.5, vjust = 1) +
arrow_(x = 5.35, xend = 5, y = -0.1, yend = -0.01, curvature = 0.2) +
label_(x = 5.3, y = -0.1, label = "xmax", hjust = 0, vjust = 1) +
# interval properties
label_(x = 3.5, y = -0.2,
label = 'interval_color = color = "black"\ninterval_alpha = alpha = 1\ninterval_linetype = linetype = "solid"\nlinewidth = size = 5',
vjust = 1, hjust = 1
) +
arrow_(x = 3.3, xend = 3.4, y = -0.18, yend = -0.015, curvature = -0.1) +
# point properties
label_(x = 4.5, y = -0.2,
label = 'point_fill = fill = "gray75"\npoint_color = color = "black"\npoint_alpha = alpha = 1\npoint_size = size = 5\nshape = 22\nstroke = 1.5',
vjust = 1, hjust = 0
) +
arrow_(x = 4.55, xend = 4.2, y = -0.18, yend = -0.03, curvature = 0.2) +
coord_cartesian(xlim = c(-1, 10), ylim = c(-0.6, 1)) +
labs(subtitle = "Properties of geom_dotsinterval", x = NULL, y = NULL)
## ----dots_components, echo=FALSE, fig.height=3.04, fig.width=6.5------------------------------------------------------
tibble(dist = dist_normal(4, 1.2)) %>%
ggplot(aes(y = 0, xdist = dist)) +
geom_hline(yintercept = 0:1, color = "gray95") +
stat_dots(
aes(linewidth = NULL),
color = "gray50",
fill = "gray75",
linewidth = 1.5,
shape = 21
) +
# height
refline_(x = 0, xend = 8.4, y = 1) +
bracket_(x = 8.4, y = 0, yend = 1) +
label_(label = "height", x = 8.6, y = 1) +
# scale
refline_(x = 4, xend = 8.6, y = 0.9) +
bracket_(x = 8.6, y = 0, yend = 0.9) +
label_(label = "scale = 0.9", x = 8.8, y = 0.9) +
# slab line properties
label_(x = 2.5, y = 0.7,
label = 'color = "gray50"\nlinewidth = 1.5',
vjust = 1, hjust = 1
) +
arrow_(x = 2.52, xend = 3, y = 0.67, yend = thickness_(3.1) + 0.03, curvature = -0.2) +
# slab fill
label_(x = 5.5, y = 0.7,
label = 'fill = "gray75"\nalpha = 1\nshape = 21',
vjust = 1,
) +
arrow_(x = 5.48, xend = 4.81, y = 0.67, yend = thickness_(3.1) + 0.01, curvature = 0.2) +
coord_cartesian(xlim = c(-1, 10), ylim = c(-0.05, 1)) +
labs(subtitle = "Properties of geom_dots", x = NULL, y = NULL)
## ----layout_params, echo=FALSE, fig.height=3.7, fig.width=6-----------------------------------------------------------
data.frame(x = c(.4, .7, .7, 1, 1, 1)) %>%
# data.frame(x = c(.4, rep(.7, 2), rep(1, 3))) %>%
ggplot(aes(x = x)) +
geom_hline(yintercept = 0:1, color = "gray95") +
# binwidth
refline_(x = seq(.25, 1.15, by = .3), y = -0.025, yend = 0.9, color = green_) +
bracket_(x = .25, xend = .55, y = -0.025, color = green_) +
label_(
label = "binwidth = NA\n=> binwidth = 0.3\n(auto-selected so that\n the tallest stack is \u2264 scale)",
x = 0.55, y = -0.08, vjust = 1, hjust = 1, color = green_
) +
geom_dots(scale = 0.9, dotsize = 1, alpha = 0.5) +
# height
refline_(x = 0, xend = 2, y = 1) +
bracket_(x = 2, y = 0, yend = 1) +
label_(label = "height", x = 2.05, y = 1) +
# scale
refline_(x = 0.25, xend = 2.1, y = 0.9) +
bracket_(x = 2.1, y = 0, yend = 0.9) +
label_(label = "scale = 0.9", x = 2.15, y = 0.9) +
# stackratio
refline_(x = 1, xend = 1.3, y = c(.15, .45)) +
bracket_(x = 1.3, y = .15, yend = .45) +
label_(label = "stackratio = 1", x = 1.35, y = .3) +
# dotsize
refline_(x = c(.85, 1.15), y = 0.15, yend = -0.025, color = blue_, linetype = "22", alpha = 1) +
bracket_(x = .85, xend = 1.15, y = -0.025, color = blue_) +
label_(
label = "dotsize = 1\n(relative to binwidth)",
x = 0.85, y = -0.08, vjust = 1, hjust = 0, color = blue_
) +
scale_x_continuous(limits = c(-0.1, 2.35)) +
scale_y_continuous(limits = c(-0.35, 1)) +
coord_fixed() +
labs(subtitle = "Layout parameters for dots geoms", x = NULL, y = NULL)
## ----horizontal_side, fig.width = small_width, fig.height = small_width/2---------------------------------------------
set.seed(1234)
x = rnorm(100)
side_plot = function(...) {
expand.grid(
x = x,
side = c("topright", "both", "bottomleft"),
stringsAsFactors = FALSE
) %>%
ggplot(aes(side = side, ...)) +
geom_dots() +
facet_grid(~ side, labeller = "label_both") +
labs(x = NULL, y = NULL) +
theme(panel.border = element_rect(color = "gray75", fill = NA))
}
side_plot(x = x) +
labs(title = "Horizontal geom_dots() with different values of side") +
scale_y_continuous(breaks = NULL)
## ----vertical_side, fig.width = small_width, fig.height = small_width/2-----------------------------------------------
side_plot(y = x) +
labs(title = "Vertical geom_dots() with different values of side") +
scale_x_continuous(breaks = NULL)
## ----layout_top, fig.width = small_width, fig.height = small_height---------------------------------------------------
layout_plot = function(layout, side, ...) {
data.frame(
x = x
) %>%
ggplot(aes(x = x)) +
geom_dots(layout = layout, side = side, stackratio = if (layout == "hex") 0.9 else 1) +
labs(
subtitle = paste0("layout = ", deparse(layout), if (layout == "hex") " with stackratio = 0.9"),
x = NULL,
y = NULL
) +
scale_y_continuous(breaks = NULL) +
theme(panel.border = element_rect(color = "gray75", fill = NA))
}
(layout_plot("bin", side = "top") +
layout_plot("hex", side = "top")) /
(layout_plot("weave", side = "top") +
layout_plot("swarm", side = "top")) +
plot_annotation(title = 'geom_dots() layouts with side = "top"')
## ----layout_both, fig.width = small_width, fig.height = small_height--------------------------------------------------
(layout_plot("bin", side = "both") +
layout_plot("hex", side = "both")) /
(layout_plot("weave", side = "both") +
layout_plot("swarm", side = "both")) +
plot_annotation(title = 'geom_dots() layouts with side = "both"')
## ----beeswarm_bin, fig.width = small_width, fig.height = small_height-------------------------------------------------
set.seed(1234)
abc_df = data.frame(
value = rnorm(300, mean = c(1,2,3), sd = c(1,2,2)),
abc = c("a", "b", "c")
)
abc_df %>%
ggplot(aes(x = abc, y = value)) +
geom_dots(side = "both") +
ggtitle('geom_dots(side = "both")')
## ----beeswarm_hex, fig.width = small_width, fig.height = small_height-------------------------------------------------
abc_df %>%
ggplot(aes(x = abc, y = value)) +
geom_dots(side = "both", layout = "hex", stackratio = 0.92) +
ggtitle('geom_dots(side = "both", layout = "hex")')
## ----geom_weave, fig.width = small_width, fig.height = small_height---------------------------------------------------
set.seed(1234)
swarm_data = data.frame(
y = rnorm(300, c(1,4)),
g = c("a","b")
)
swarm_plot = swarm_data %>%
ggplot(aes(x = g, y = y)) +
geom_swarm(linewidth = 0, alpha = 0.75) +
labs(title = "geom_swarm()")
weave_plot = swarm_data %>%
ggplot(aes(x = g, y = y)) +
geom_weave(linewidth = 0, alpha = 0.75) +
labs(title = "geom_weave()")
swarm_plot + weave_plot
## ----beeswarm_dodge, fig.width = small_width, fig.height = small_height-----------------------------------------------
set.seed(12345)
abcc_df = data.frame(
value = rnorm(300, mean = c(1,2,3,4), sd = c(1,2,2,1)),
abc = c("a", "b", "c", "c"),
hi = c("h", "h", "h", "i")
)
abcc_df %>%
ggplot(aes(y = value, x = abc, fill = hi)) +
geom_weave(position = "dodge", linewidth = 0, alpha = 0.75) +
scale_fill_brewer(palette = "Dark2") +
ggtitle(
'geom_weave(position = "dodge")',
'aes(fill = hi, shape = hi)'
)
## ----beeswarm_shape_color_together, fig.width = small_width, fig.height = small_height--------------------------------
abcc_df %>%
ggplot(aes(y = value, x = abc, fill = hi, group = NA)) +
geom_dots(linewidth = 0) +
scale_color_brewer(palette = "Dark2") +
ggtitle(
'geom_dots()',
'aes(fill = hi, group = NA)'
)
## ----beeswarm_shape_color_together_stacked, fig.width = small_width, fig.height = small_height------------------------
abcc_df %>%
ggplot(aes(y = value, x = abc, fill = hi, group = NA, order = hi)) +
geom_dots(linewidth = 0) +
scale_color_brewer(palette = "Dark2") +
ggtitle(
'geom_dots()',
'aes(fill = hi, group = NA, order = hi)'
)
## ----beeswarm_shape_color_continuous, fig.width = small_width, fig.height = small_height------------------------------
abcc_df %>%
arrange(hi) %>%
ggplot(aes(y = value, x = abc, shape = abc, color = value)) +
geom_dots() +
ggtitle(
'geom_dots()',
'aes(color = value)'
)
## ----large_sample_min_binwidth, fig.width = small_width, fig.height = small_width/2-----------------------------------
set.seed(1234)
x = rnorm(2000)
ggplot() +
geom_dots(aes(x), binwidth = unit(c(1.5, Inf), "mm"), overflow = "compress", alpha = 0.5) +
labs(
title = 'geom_dots()',
subtitle = 'binwidth = unit(c(1.5, Inf), "mm"), overflow = "compress")'
)
## ----large_sample_smooth, fig.width = small_width, fig.height = small_width/2-----------------------------------------
ggplot() +
geom_dots(aes(x), smooth = "unbounded") +
labs(
title = 'geom_dots() with 2000 dots',
subtitle = 'smooth = "unbounded"',
x = NULL
) +
scale_y_continuous(breaks = NULL)
## ----smooth_bounded_versus_unbounded, fig.width = small_width, fig.height = small_height------------------------------
set.seed(1234)
x = rbeta(2000, 0.5, 0.5)
ggplot(data.frame(x), aes(x)) +
geom_dots(aes(y = "bounded"), smooth = smooth_bounded(bounds = c(0, 1))) +
geom_dots(aes(y = "unbounded"), smooth = "unbounded") +
geom_vline(xintercept = c(0, 1), alpha = 0.25) +
scale_x_continuous(breaks = c(0, 0.5, 1)) +
labs(
title = "geom_dots(smooth = ...) on x ~ Beta(0.5, 0.5)",
y = "smooth ="
)
## ----discrete_dots_too_small, fig.width = small_width, fig.height = small_height--------------------------------------
set.seed(1234)
abcd_df = data.frame(
x = sample(c("a", "b", "c", "d"), 1000, replace = TRUE, prob = c(0.27, 0.6, 0.03, 0.005)),
g = c("a","b")
)
abcd_df %>%
ggplot(aes(x = x)) +
geom_dots() +
scale_y_continuous(breaks = NULL) +
labs(
title = "geom_dots()",
subtitle = "on a large discrete sample"
)
## ----discrete_dots_rect, fig.width = small_width, fig.height = small_height-------------------------------------------
abcd_df %>%
ggplot(aes(x = x)) +
geom_dots(smooth = "discrete") +
scale_y_continuous(breaks = NULL) +
labs(
title = 'geom_dots(smooth = "discrete")',
subtitle = "on a large discrete sample"
)
## ----discrete_dots_bar, fig.width = small_width, fig.height = small_height--------------------------------------------
abcd_df %>%
ggplot(aes(x = x, fill = g, order = g)) +
geom_dots(layout = "bar", group = NA, color = NA) +
scale_y_continuous(breaks = NULL) +
labs(
title = 'geom_dots(aes(fill = g), layout = "bar", group = NA)',
subtitle = "on a large discrete sample"
)
## ----discrete_dots_ep, fig.width = small_width, fig.height = small_height---------------------------------------------
abcd_df %>%
ggplot(aes(x = x)) +
geom_dots(smooth = smooth_discrete(kernel = "ep"), side = "both") +
scale_y_continuous(breaks = NULL) +
labs(
title = 'geom_dots(smooth = smooth_discrete(kernel = "ep"), side = "both")',
subtitle = "on a large discrete sample"
)
## ----dotsinterval_dist, fig.width = small_width, fig.height = small_height--------------------------------------------
dist_df = tibble(
dist = c(dist_normal(1,0.25), dist_beta(3,3), dist_gamma(5,5)),
dist_name = format(dist)
)
dist_df %>%
ggplot(aes(y = dist_name, xdist = dist)) +
stat_dotsinterval() +
ggtitle(
"stat_dotsinterval()",
"aes(y = dist_name, xdist = dist)"
)
## ----dotsinterval_dist_1000_level_color, fig.width = small_width, fig.height = small_height---------------------------
dist_df %>%
ggplot(aes(y = dist_name, xdist = dist, slab_fill = after_stat(level))) +
stat_dotsinterval(quantiles = 1000, point_interval = mode_hdci, layout = "weave", slab_color = NA) +
scale_color_manual(values = scales::brewer_pal()(3)[-1], aesthetics = "slab_fill") +
ggtitle(
"stat_dotsinterval(quantiles = 1000, point_interval = mode_hdci)",
"aes(y = dist_name, xdist = dist, slab_fill = after_stat(level))"
)
## ----dotsinterval_dist_color, fig.width = small_width, fig.height = small_height--------------------------------------
dist_df %>%
ggplot(aes(y = dist_name, xdist = dist, slab_color = after_stat(x))) +
stat_dotsinterval(slab_shape = 19, quantiles = 500) +
scale_color_distiller(aesthetics = "slab_color", guide = "colorbar2") +
ggtitle(
"stat_dotsinterval(slab_shape = 19, quantiles = 500)",
'aes(slab_color = after_stat(x)) +\nscale_color_distiller(aesthetics = "slab_color", guide = "colorbar2")'
)
## ----dist_dots_weave, fig.width = small_width, fig.height = small_height----------------------------------------------
ab_df = tibble(
ab = c("a", "b"),
mean = c(5, 7),
sd = c(1, 1.5)
)
ab_df %>%
ggplot(aes(y = ab, xdist = dist_normal(mean, sd), fill = after_stat(x < 6))) +
stat_dots(position = "dodge", color = NA, layout = "weave") +
labs(
title = 'stat_dots(layout = "weave")',
subtitle = "aes(fill = after_stat(x < 6))"
) +
geom_vline(xintercept = 6, alpha = 0.25) +
scale_x_continuous(breaks = 2:10)
## ----halfeye_dotplot, fig.width = small_width, fig.height = small_height----------------------------------------------
set.seed(12345) # for reproducibility
data.frame(
abc = c("a", "b", "b", "c"),
value = rnorm(200, c(1, 8, 8, 3), c(1, 1.5, 1.5, 1))
) %>%
ggplot(aes(y = abc, x = value, fill = abc)) +
stat_slab(aes(thickness = after_stat(pdf*n)), scale = 0.7) +
stat_dotsinterval(side = "bottom", scale = 0.7, slab_linewidth = NA) +
scale_fill_brewer(palette = "Set2") +
ggtitle(paste0(
'stat_slab(aes(thickness = after_stat(pdf*n)), scale = 0.7) +\n',
'stat_dotsinterval(side = "bottom", scale = 0.7, slab_linewidth = NA)'
),
'aes(fill = abc)'
)
## ----gentoo_raw, fig.width = med_width, fig.height = med_height-------------------------------------------------------
gentoo = penguins %>%
filter(species == "Gentoo", !is.na(sex))
gentoo %>%
ggplot(aes(x = body_mass_g, y = sex, side = sex)) +
geom_dots(scale = 0.5) +
scale_side_mirrored(guide = "none") +
ggtitle(
"geom_dots(scale = 0.5)",
'aes(side = sex) + scale_side_mirrored()'
)
## ----m_gentoo---------------------------------------------------------------------------------------------------------
m = glm(sex == "male" ~ body_mass_g, data = gentoo, family = binomial)
m
## ----logit_dotplot, fig.width = med_width, fig.height = med_height/1.5------------------------------------------------
# construct a prediction grid for the fit line
prediction_grid = with(gentoo,
data.frame(body_mass_g = seq(min(body_mass_g), max(body_mass_g), length.out = 100))
)
prediction_grid %>%
bind_cols(predict(m, ., se.fit = TRUE)) %>%
mutate(
# distribution describing uncertainty in log odds
log_odds = dist_normal(fit, se.fit),
# inverse-logit transform the log odds to get
# distribution describing uncertainty in Pr(sex == "male")
p_male = dist_transformed(log_odds, plogis, qlogis)
) %>%
ggplot(aes(x = body_mass_g)) +
geom_dots(
aes(y = as.numeric(sex == "male"), side = sex),
scale = 0.4,
data = gentoo
) +
stat_lineribbon(
aes(ydist = p_male), alpha = 1/4, fill = "#08306b"
) +
scale_side_mirrored(guide = "none") +
coord_cartesian(ylim = c(0, 1)) +
labs(
title = "logit dotplot: stat_dots() with stat_lineribbon()",
subtitle = 'aes(side = sex) + scale_side_mirrored()',
x = "Body mass (g) of Gentoo penguins",
y = "Pr(sex = male)"
)
## ----reset_options, include=FALSE---------------------------------------------
options(.old_options)
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