具有形狀美學的geom_ribbon()會導致不透明度的差異

當geom_ribbon()與形狀美學一起使用時，陰影區域的不透明度似乎有所不同，從而在該區域中創建了塊。我重新創建了一個問題，我發現這些不透明度變化僅在包含形狀美學時才存在。

資料設定：

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)

沒有形狀美學的圖表，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")

具有形狀美學的圖表，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")

uj5u.com熱心網友回復：

問題是某種過度繪圖，并且您添加背景的方式通過geom_ribbon. 基本上，通過添加shape全域美學，您的資料會被分組，并且您的功能區會被多次繪制，每個組一次。要解決此問題shape，請通過將其移動到內部來制作本地 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在我看來，您可以通過添加背景矩形來更輕松地獲得結果，并且更不容易出錯annotate，這取決于您想要的結果，甚至不需要計算最小值和最大值。相反，您可以簡單地使用-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")

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