0

当geom_ribbon()与形状美学一起使用时，阴影区域的不透明度似乎有所不同，从而在该区域中创建了块。我重新创建了一个问题，我发现这些不透明度变化仅在包含形状美学时才存在。

数据设置：

alpha <- c("A","B","C","D", "E", "F", "G")
percent <- c(0.012, -0.02, 0.015, -0.01, 0.89, 0.12, -0.25)
flow <- c(-5, 2, -3, 3, 1, 4, -2)
shape <- c("D", "D", "L", "L", "L", "D", "L")

df <- data.frame(alpha,percent,flow, shape)

x_min = min(df$percent)
x_min = round(x_min/0.01)*0.01 - 0.01

x_max = max(df$percent)
x_max = round(x_max/0.01)*0.01 + 0.01

y_min = min(df$flow)
y_min = round(y_min)

y_max = max(df$flow)
y_max = round(y_max)

n_row = nrow(df)

没有形状美学的图表，geom_ribbon() 有效：

df %>%
  ggplot(aes(x = percent, y = flow, label = alpha)) + 
  geom_point() + 
  geom_text_repel(show.legend = FALSE, size = 3) +
  scale_size_continuous(labels = scales::percent) + 
  theme_bw() + 
  scale_x_continuous(labels = scales::percent_format(accuracy = 0.1L)) + 
  scale_y_continuous(labels = scales::dollar_format(negative_parens = TRUE, suffix = "m")) + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = 0, ymax = y_max), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "green") + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = y_min, ymax = 0), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "red")

无形状aes，不透明度很好

具有形状美学的图表，geom_ribbon() 似乎不起作用：

df %>%
  ggplot(aes(x = percent, y = flow, label = alpha, shape = shape)) + 
  geom_point() + 
  geom_text_repel(show.legend = FALSE, size = 3) +
  scale_size_continuous(labels = scales::percent) + 
  theme_bw() + 
  scale_x_continuous(labels = scales::percent_format(accuracy = 0.1L)) + 
  scale_y_continuous(labels = scales::dollar_format(negative_parens = TRUE, suffix = "m")) + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = 0, ymax = y_max), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "green") + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = y_min, ymax = 0), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "red")

包括形状AES，不透明度问题

4

1 回答 1

2

问题是某种过度绘图，并且您添加背景的方式通过geom_ribbon. 基本上，通过添加shape全局美学，您的数据会被分组，并且您的功能区会被多次绘制，每个组一次。要解决此问题shape，请通过将其移动到内部来制作本地 aes geom_point：

library(ggplot2)

ggplot(df, aes(x = percent, y = flow, label = alpha)) + 
  geom_point(aes(shape = shape)) + 
  ggrepel::geom_text_repel(show.legend = FALSE, size = 3) +
  scale_size_continuous(labels = scales::percent) + 
  theme_bw() + 
  scale_x_continuous(labels = scales::percent_format(accuracy = 0.1L)) + 
  scale_y_continuous(labels = scales::dollar_format(negative_parens = TRUE, suffix = "m")) + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = 0, ymax = y_max), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "green") + 
  geom_ribbon(aes(x = seq(x_min, x_max + 0.01, length.out = n_row), ymin = y_min, ymax = 0), alpha = 0.04, linetype = 0, show.legend = FALSE, fill = "red")

但是，geom_ribbon在我看来，您可以通过添加背景矩形来更轻松地获得结果，并且更不容易出错annotate，这取决于您想要的结果，甚至不需要计算最小值和最大值。相反，您可以简单地使用-Infand Inf：

ggplot(df, aes(x = percent, y = flow, label = alpha, shape = shape)) + 
  geom_point() + 
  ggrepel::geom_text_repel(show.legend = FALSE, size = 3) +
  scale_size_continuous(labels = scales::percent) + 
  theme_bw() + 
  scale_x_continuous(labels = scales::percent_format(accuracy = 0.1)) + 
  scale_y_continuous(labels = scales::dollar_format(negative_parens = TRUE, suffix = "m")) + 
  annotate(geom = "rect", xmin = -Inf, xmax = Inf, ymin = 0, ymax = Inf, alpha = 0.04, fill = "green") + 
  annotate(geom = "rect", xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = 0, alpha = 0.04, fill = "red")

于 2022-01-24T08:37:57.703 回答