R-Studio 中的组合绘图轴标签

Question

我尝试创建一个具有共享轴标签的绘图。问题是，我希望我的图例位于我的地块下，因为否则我的地块会太压缩。我没能用 Eggpackage 创建一个好的图，因为我的 x 轴标签在我的图例下。

所以我想我可以尝试一下解决办法，并询问了 ChatGPT。问题是，下面的代码切断了我的 x 轴标签的最后一部分。我是 R Studio 的新手，不知道我是否犯了一个明显的错误。我不知道我用最小的、可重现的例子是否做对了。 感谢您的帮助！

编辑：我更新了我的 MRE，我无法将它提供的 3 个图合并到一个图中，因为这将包括 12 条线和我的原始数据。

set.seed(123)
spy <- data.frame(
  UG_100 = runif(10, 0, 100),
  UG_500 = runif(10, 0, 100),
  UG_1000 = runif(10, 0, 100),
  SK_0_disap = rbinom(10, 1, 0.5),
  SK_Z_disap = rbinom(10, 1, 0.5),
  SB_Z_disap = rbinom(10, 1, 0.5),
  SB_0_disap = rbinom(10, 1, 0.5)
)
# packages 
library(ggplot2)
library(viridis)
library(patchwork)
library(cowplot)

# Plots 
combined_plot1 <- ggplot(spy, aes(x = UG_100)) +
  geom_point(aes(y = SK_0_disap, color = "SK_0_disap")) +
  geom_smooth(aes(y = SK_0_disap, color = "SK_0_disap", fill = "SK_0_disap"), method = "glm", se = TRUE, method.args = list(family = binomial), alpha = 0.2) +
  theme_classic() +
  labs(x = NULL, y = "Disappearance") +
  scale_color_viridis_d(name = "Food Type", labels = c("sunflower seeds \nwithout cinnamon")) +
  scale_fill_viridis_d(name = "Food Type", labels = c("SK_0_disap"), guide = FALSE)

combined_plot_500_1 <- ggplot(spy, aes(x = UG_500)) +
  geom_point(aes(y = SK_0_disap, color = "SK_0_disap")) +
  geom_smooth(aes(y = SK_0_disap, color = "SK_0_disap", fill = "SK_0_disap"), method = "glm", se = TRUE, method.args = list(family = binomial), alpha = 0.2) +
  theme_classic() +
  labs(x = "Percentage of impervious surface cover", y = NULL) +
  theme(axis.title.x = element_text(margin = margin(t = 20))) +
  scale_color_viridis_d(name = "Food Type", labels = c("sunflower seeds \nwithout cinnamon")) +
  scale_fill_viridis_d(name = "Food Type", labels = c("SK_0_disap"), guide = FALSE)

combined_plot_1000 <- ggplot(spy, aes(x = UG_1000)) +
  geom_point(aes(y = SK_0_disap, color = "SK_0_disap")) +
  geom_smooth(aes(y = SK_0_disap, color = "SK_0_disap", fill = "SK_0_disap"), method = "glm", se = TRUE, method.args = list(family = binomial), alpha = 0.2) +
  theme_classic() +
  labs(x = NULL, y = NULL) +
  scale_color_viridis_d(name = "Food Type", labels = c("sunflower seeds \nwithout cinnamon")) +
  scale_fill_viridis_d(name = "Food Type", labels = c("SK_0_disap"), guide = FALSE)

# Plot patchwork
combined_plot_all <- (combined_plot1 | combined_plot_500_1 | combined_plot_1000) + 
  plot_layout(guides = "collect") &
  theme(legend.position = "bottom")


final_plot <- combined_plot_all +
  plot_annotation(
    tag_levels = 'a',
    theme = theme(plot.tag = element_text(size = 14, face = "bold"))
  ) &
  plot_annotation(
    title = NULL,
    subtitle = NULL,
    caption = NULL,
    tag_levels = c('a', 'b', 'c'),
    theme = theme(plot.tag = element_text(size = 14, face = "bold"))
  ) 

print(final_plot)

Answer 1

这里有两个选项可以实现您想要的结果。首先，正如我在评论中已经提到的，您可能会考虑使用分面，这需要将数据重塑很长，但允许创建一个由

UG

分面的图。

library(tidyverse)

spy_long <- spy |>
  tidyr::pivot_longer(starts_with("UG"), names_to = "ug", values_to = "value") |>
  mutate(ug = factor(ug, paste0("UG_", c(100, 500, 1000))))

ggplot(spy_long, aes(x = value, y = SK_0_disap)) +
  geom_point(aes(color = "SK_0_disap")) +
  geom_smooth(
    aes(color = "SK_0_disap", fill = "SK_0_disap"),
    method = "glm", se = TRUE, method.args = list(family = binomial), alpha = 0.2
  ) +
  scale_color_viridis_d(
    name = "Food Type", labels = c("sunflower seeds \nwithout cinnamon"),
    aesthetics = c("color", "fill")
  ) +
  facet_wrap(~ug) +
  theme_classic() +
  theme(legend.position = "bottom") +
  labs(x = "Percentage of impervious surface cover", y = "Disappearance")
#> `geom_smooth()` using formula = 'y ~ x'

其次，如果你想坚持使用单独的图，例如因为您想要有标签，那么您仍然可以使用

axes="collect"

来获取共享轴，其工作方式与

guides="collect"

类似。但与后者一样，收集仅在轴相同时才有效，这意味着轴应该具有相同的名称、标签、中断和限制，即您必须为每个图添加相同的轴标题，并且重要的是确保所有 x 轴共享相同的

limits=

。此外，我避免为每个图重复代码，而是指定整个补丁的大部分图层，这需要使用

patchwork

的

&

运算符而不是

ggplot2

的

+

添加图层。

注意：如果您只需要共享 x 轴，也可以使用

axes="collect_x"

仅收集 x 轴。

combined_plot_100 <- ggplot(spy, aes(x = UG_100, y = SK_0_disap))
combined_plot_500 <- ggplot(spy, aes(x = UG_500, y = SK_0_disap))
combined_plot_1000 <- ggplot(spy, aes(x = UG_1000, y = SK_0_disap))

library(patchwork)

(combined_plot_100 | combined_plot_500 | combined_plot_1000) +
  plot_layout(guides = "collect", axes = "collect") +
  plot_annotation(
    tag_levels = "a",
    theme = theme(plot.tag = element_text(size = 14, face = "bold"))
  ) &
  geom_point(aes(color = "SK_0_disap")) &
  geom_smooth(aes(color = "SK_0_disap", fill = "SK_0_disap"),
    method = "glm", se = TRUE, method.args = list(family = binomial), alpha = 0.2
  ) &
  scale_x_continuous(limits = c(0, 100)) &
  scale_color_viridis_d(
    name = "Food Type", labels = c("sunflower seeds \nwithout cinnamon"),
    aesthetics = c("color", "fill")
  ) &
  theme_classic() &
  theme(
    axis.title.x = element_text(margin = margin(t = 20)),
    legend.position = "bottom"
  ) &
  labs(x = "Percentage of impervious surface cover", y = "Disappearance")
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'