ggasym轻松给热图添加多个图例

R语言数据分析指南

发布于 2023-08-18 13:37:55

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发布于 2023-08-18 13:37:55

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❝本节了介绍一款R包「ggasym」其主要作用为绘制热图时根据数据添加多个连续型图例，以往遇到热图需要多个图例的问题小编都是分批绘制，使用「ggasym」可以看到代码过程明显有所简化，感兴趣的朋友欢迎分享转发，「更多详细内容请参考作者官方文档」 ❞

官方文档

❝https://jhrcook.github.io/ggasym/index.html ❞

加载R包

devtools::install_github("jhrcook/ggasym")
# install.packages("ggasym")

library(tidyverse)
library(ggasym)

构建数据

tib <- tibble(
  g1 = c("A", "A", "A", "A", "B", "B", "B", "C", "C", "D"),
  g2 = c("B", "C", "D", "E", "C", "D", "E", "D", "E", "E"),
  val_1 = seq(1, 10, 1),
  val_2 = rnorm(10, mean = 0, sd = 3)
)

案例 1

tib <- asymmetrise(tib, g1, g2)
tib$val_3 <- runif(nrow(tib))
ggplot(tib, aes(x = g1, y = g2)) +
  geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
  scale_fill_tl_gradient(low = "lightpink", high = "tomato") +
  scale_fill_br_gradient(low = "lightblue1", high = "dodgerblue") +
  scale_fill_diag_gradient(low = "yellow", high = "orange3")+
  theme_bw()

案例 2

ggplot(tib, aes(x = g1, y = g2)) +
  geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
  scale_fill_tl_gradient(low = "lightpink", high = "tomato") +
  scale_fill_br_gradient2(low = "orange", mid = "white", high = "dodgerblue") +
  scale_fill_diag_gradientn(colors = rainbow(25))

案例 3

ggplot(tib, aes(x = g1, y = g2)) +
  geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
  scale_fill_tl_gradient(
    low = "lightpink", high = "tomato",
    guide = guide_colourbar(
      direction = "horizontal",
      order = 1,
      title.position = "top"
    )
  ) +
  scale_fill_br_gradient2(
    low = "orange", mid = "white", high = "dodgerblue",
    guide = guide_colourbar(
      direction = "horizontal",
      order = 3,
      title.position = "top"
    )
  ) +
  scale_fill_diag_gradientn(
    colors = rainbow(25),
    guide = guide_colourbar(
      direction = "horizontal",
      order = 2,
      title.position = "top"
    )
  )

案例4 分面操作

tib <- tibble(
  g1 = rep(c("A", "A", "B"), 2),
  g2 = rep(c("B", "C", "C"), 2),
  val_1 = seq(1, 6),
  val_2 = rnorm(6),
  grps = c(1, 1, 1, 2, 2, 2))

tib <- tib %>%
  group_by(grps) %>%
  asymmetrise(g1, g2) %>%
  ungroup()
tib <- tib %>% mutate(val_3 = ifelse(g1 == g2, runif(nrow(tib)), NA))

ggplot(tib, aes(x = g1, y = g2)) +
  geom_asymmat(aes(
    fill_tl = log(val_1),
    fill_br = val_2,
    fill_diag = val_3
  )) +
  scale_fill_tl_gradient(
    low = "lightpink", high = "tomato",
    guide = guide_colourbar(
      direction = "horizontal",
      order = 1,
      title.position = "top"
    )
  ) +
  scale_fill_br_gradient(
    low = "lightblue1", high = "dodgerblue",
    guide = guide_colourbar(
      direction = "horizontal",
      order = 3,
      title.position = "top"
    )
  ) +
  scale_fill_diag_gradient(
    low = "grey80", high = "grey20",
    guide = guide_colourbar(
      direction = "horizontal",
      order = 2,
      title.position = "top"
    )
  ) +
  labs(
    fill_tl = "top-left fill",
    fill_br = "bottom-right fill",
    fill_diag = "diagonal fill",
    title = "Example of faceting with ggasym"
  ) +
  theme_bw() +
  theme(
    axis.title = element_blank(),
    plot.title = element_text(hjust = 0.5),
    panel.background = element_rect(fill = "grey70"),
    panel.grid = element_blank()
  ) +
  scale_x_discrete(expand = c(0, 0)) +
  scale_y_discrete(expand = c(0, 0)) +
  facet_grid(. ~ grps)

tib <- ggplot2::txhousing %>%
  filter(city == "Austin") %>%
  mutate(year = as.character(year))
aov_res <- aov(median ~ year, data = tib)
broom::tidy(aov_res)

案例 5

asymmat_tib <- asymmetrise_stats(TukeyHSD(aov_res))

ggplot(asymmat_tib, aes(x = x, y = y)) +
  geom_asymmat(aes(
    fill_tl = estimate,
    fill_br = -log10(adj.p.value + 0.0000001)
  )) +
  scale_fill_tl_gradient2(low = "dodgerblue", high = "tomato") +
  scale_fill_br_distiller(type = "seq", palette = "Greens", direction = 1) +
  labs(
    title = "Median House Prices in Austin",
    fill_tl = "diff. in\nmean values",
    fill_br = "-log10( adj. p-value )"
  ) +
  theme(
    panel.background = element_rect(fill = "grey75"),
    panel.grid = element_blank()
  ) +
  scale_x_discrete(expand = c(0, 0)) +
  scale_y_discrete(expand = c(0, 0))