r - ggplot2::coord_cartesian 在方面
问题描述
coord_cartesian
不允许设置每个方面的坐标,并且使用其他范围限制往往会在特定极端上产生一条直线。由于我们有广泛变化的 y 范围,我们不能对所有方面都设置相同的限制;geom_line
在 plot 之前限制数据对/ geom_path
( https://stackoverflow.com/a/27319786/3358272 )不友好,因为插入数据以到达边缘然后插入NA
s 以打破上线。(最终,获得所需结果的唯一方法就是这样做,这对于其他数据可能有点繁琐。)
https://gist.github.com/burchill/d780d3e8663ad15bcbda7869394a348a中建议了一种解决方法,它以
test_data %>%
ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
geom_line(size=2) +
geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2)
在以前的版本中ggplot2
,该要点定义coord_panel_ranges
并能够控制每个方面的坐标。右侧的两个方面应缩小到 1-6(ish)的 y 轴,以便爆炸置信区间脱离屏幕并允许方面主要关注数据的“正常范围”。(注意:test_data
这个 vis 不是我的,它取自要点。虽然我的需求有些相似,但我认为最好留在要点的数据和代码的范围内。)
不幸的是,这对我来说现在失败了ggplot2-3.3.0
。与最近丢失的 相关的初始错误ggplot2::scale_range
,我试图通过对 burchill 代码(使用其他ggplot2:::
内部函数)的这种改编来减轻这些错误:
UniquePanelCoords <- ggplot2::ggproto(
"UniquePanelCoords", ggplot2::CoordCartesian,
num_of_panels = 1,
panel_counter = 1,
panel_ranges = NULL,
setup_layout = function(self, layout, params) {
self$num_of_panels <- length(unique(layout$PANEL))
self$panel_counter <- 1
layout
},
setup_panel_params = function(self, scale_x, scale_y, params = list()) {
if (!is.null(self$panel_ranges) & length(self$panel_ranges) != self$num_of_panels)
stop("Number of panel ranges does not equal the number supplied")
train_cartesian <- function(scale, limits, name, given_range = NULL) {
if (is.null(given_range)) {
expansion <- ggplot2:::default_expansion(scale, expand = self$expand)
range <- ggplot2:::expand_limits_scale(scale, expansion,
coord_limits = self$limits[[name]])
} else {
range <- given_range
}
out <- scale$break_info(range)
out$arrange <- scale$axis_order()
names(out) <- paste(name, names(out), sep = ".")
out
}
cur_panel_ranges <- self$panel_ranges[[self$panel_counter]]
if (self$panel_counter < self$num_of_panels)
self$panel_counter <- self$panel_counter + 1
else
self$panel_counter <- 1
c(train_cartesian(scale_x, self$limits$x, "x", cur_panel_ranges$x),
train_cartesian(scale_y, self$limits$y, "y", cur_panel_ranges$y))
}
)
coord_panel_ranges <- function(panel_ranges, expand = TRUE, default = FALSE, clip = "on") {
ggplot2::ggproto(NULL, UniquePanelCoords, panel_ranges = panel_ranges,
expand = expand, default = default, clip = clip)
}
但这仍然失败
test_data %>%
ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
geom_line(size=2) +
geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2) +
coord_panel_ranges(panel_ranges = list(
list(x=c(8,64), y=c(1,4)), # Panel 1
list(x=c(8,64), y=c(1,6)), # Panel 2
list(NULL), # Panel 3, an empty list falls back on the default values
list(x=c(8,64), y=c(1,7)) # Panel 4
))
# Error in panel_params$x$break_positions_minor() :
# attempt to apply non-function
我对扩展不是很熟悉ggplot2
,我怀疑 ggproto 中缺少一些东西。以下是 proto 的返回值:
str(c(train_cartesian(scale_x, self$limits$x, "x", cur_panel_ranges$x),
train_cartesian(scale_y, self$limits$y, "y", cur_panel_ranges$y)))
# List of 14
# $ x.range : num [1:2] 8 64
# $ x.labels : chr [1:3] "20" "40" "60"
# $ x.major : num [1:3] 0.214 0.571 0.929
# $ x.minor : num [1:6] 0.0357 0.2143 0.3929 0.5714 0.75 ...
# $ x.major_source: num [1:3] 20 40 60
# $ x.minor_source: num [1:6] 10 20 30 40 50 60
# $ x.arrange : chr [1:2] "secondary" "primary"
# $ y.range : num [1:2] 1 4
# $ y.labels : chr [1:4] "1" "2" "3" "4"
# $ y.major : num [1:4] 0 0.333 0.667 1
# $ y.minor : num [1:7] 0 0.167 0.333 0.5 0.667 ...
# $ y.major_source: num [1:4] 1 2 3 4
# $ y.minor_source: num [1:7] 1 1.5 2 2.5 3 3.5 4
# $ y.arrange : chr [1:2] "primary" "secondary"
我是否需要一个x
至少包含一个break_positions_minor
函数的列表元素,或者是否需要继承其他东西以确保panel_params$x$break_positions_minor
存在或使用合理的默认值?
数据:
test_data <- structure(list(DataType = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), class = "factor"),
ExpType = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("X", "Y"), class = "factor"),
EffectSize = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("15", "35"
), class = "factor"), Nsubjects = c(8, 16, 32, 64, 8, 16,
32, 64, 8, 16, 32, 64, 8, 16, 32, 64, 8, 16, 32, 64, 8, 16,
32, 64, 8, 16, 32, 64, 8, 16, 32, 64), Odds = c(1.06248116259846,
1.09482076720863, 1.23086993413208, 1.76749340505612, 1.06641831731573,
1.12616954196688, 1.48351814320987, 3.50755080416964, 1.11601399761081,
1.18352602009495, 1.45705466646283, 2.53384744810515, 1.13847061762186,
1.24983742407086, 1.97075900741022, 6.01497152563726, 1.02798821372378,
1.06297006279249, 1.19432835697453, 1.7320754674107, 1.02813271730924,
1.09355953747203, 1.44830680332583, 3.4732692664923, 1.06295915758305,
1.12008443626365, 1.3887632112682, 2.46321037334, 1.06722652223114,
1.1874936754725, 1.89870184372054, 5.943747409114), Upper = c(1.72895843644471,
2.09878774769559, 2.59771794965346, 5.08513435549015, 1.72999898901071,
1.8702196882561, 3.85385388850167, 5.92564404180303, 1.99113042576373,
2.61074135841984, 3.45852331828636, 4.83900142207583, 1.57897154221764,
1.8957409107653, 10, 75, 2.3763918424135, 2.50181951057562,
3.45037180395673, 3.99515276392065, 2.04584535265976, 2.39317394040066,
2.832526733659, 5.38414183471915, 1.40569501856836, 2.6778044191832,
2.98023068052396, 4.75934650422069, 1.54116883311054, 2.50647989271592,
3.48517589981551, 100), Lower = c(0.396003888752214, 0.0908537867216577,
-0.135978081389309, -1.55014754537791, 0.40283764562075,
0.382119395677663, -0.88681760208193, 1.08945756653624, 0.240897569457892,
-0.243689318229938, -0.544413985360706, 0.228693474134466,
0.69796969302609, 0.603933937376415, 0.183548809738402, 3.57236968943798,
-0.320415414965949, -0.375879384990643, -1.06171509000767,
-0.531001829099242, 0.010420081958713, -0.206054865456611,
0.0640868729926525, 1.56239669826544, 0.720223296597732,
-0.437635546655903, -0.202704257987574, 0.167074242459314,
0.593284211351745, -0.131492541770921, 0.312227787625573,
3.76692741957876)), .Names = c("DataType", "ExpType", "EffectSize",
"Nsubjects", "Odds", "Upper", "Lower"), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -32L))
解决方案
我修改了函数train_cartesian
以匹配(在此处view_scales_from_scale
定义)的输出格式,这似乎有效:
train_cartesian <- function(scale, limits, name, given_range = NULL) {
if (is.null(given_range)) {
expansion <- ggplot2:::default_expansion(scale, expand = self$expand)
range <- ggplot2:::expand_limits_scale(scale, expansion,
coord_limits = self$limits[[name]])
} else {
range <- given_range
}
out <- list(
ggplot2:::view_scale_primary(scale, limits, range),
sec = ggplot2:::view_scale_secondary(scale, limits, range),
arrange = scale$axis_order(),
range = range
)
names(out) <- c(name, paste0(name, ".", names(out)[-1]))
out
}
p <- test_data %>%
ggplot(aes(x=Nsubjects, y = Odds, color=EffectSize)) +
facet_wrap(DataType ~ ExpType, labeller = label_both, scales="free") +
geom_line(size=2) +
geom_ribbon(aes(ymax=Upper, ymin=Lower, fill=EffectSize, color=NULL), alpha=0.2)
p +
coord_panel_ranges(panel_ranges = list(
list(x=c(8,64), y=c(1,4)), # Panel 1
list(x=c(8,64), y=c(1,6)), # Panel 2
list(NULL), # Panel 3, an empty list falls back on the default values
list(x=c(8,64), y=c(1,7)) # Panel 4
))
原始答案
我以前曾欺骗过类似的问题。
# alternate version of plot with data truncated to desired range for each facet
p.alt <- p %+% {test_data %>%
mutate(facet = as.integer(interaction(DataType, ExpType, lex.order = TRUE))) %>%
left_join(data.frame(facet = 1:4,
ymin = c(1, 1, -Inf, 1), # change values here to enforce
ymax = c(4, 6, Inf, 7)), # different axis limits
by = "facet") %>%
mutate_at(vars(Odds, Upper, Lower), list(~ ifelse(. < ymin, ymin, .))) %>%
mutate_at(vars(Odds, Upper, Lower), list(~ ifelse(. > ymax, ymax, .))) }
# copy alternate version's panel parameters to original plot & plot the result
p1 <- ggplot_build(p)
p1.alt <- ggplot_build(p.alt)
p1$layout$panel_params <- p1.alt$layout$panel_params
p2 <- ggplot_gtable(p1)
grid::grid.draw(p2)
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