如何在R ggplot2双分面图表中按因子水平值排序X轴？

我正在制作堆叠条形图，展示20名参与者完成两项相同任务（task）时，使用三种策略（CA.presence：Presence、Possible presence、Absence）的时间占比（Duration），并按task进行分面。使用以下代码生成了图表：

CA_presence %>% ggplot(aes(fill=CA.presence, y= Duration, x= participant, label =    scales::percent(Duration))) + 
geom_bar(width = .7, position="fill", stat="identity") +
scale_y_continuous(labels = scales::label_percent()) +
facet_grid(~task) +
ggtitle("Presence of CA in the dataset") +
theme(plot.title = element_text(size = 15)) +
theme(plot.title = element_text(hjust = 0.5)) +
theme(legend.text = element_text(size = 10)) +
theme(strip.text.x = element_text(size = 13)) +
labs(x = "Participant",
     y = "Proportion of discourse time",
     fill = "CA presence") +
theme(axis.text = element_text(size = 10)) +
theme(axis.title = element_text(size = 10)) +
scale_fill_brewer(palette = "Greens") +
coord_flip()

数据集前几行的dput()输出：

structure(
  list(
    participant = c("L001", "L001", "L002", "L002", "L016", "L016"),
    task = c("T05", "T12", "T05", "T12", "T05", "T12"),
    language = c("French", "French", "French", "French", "French", "French"),
    Duration = c(8823, 46275, 2459, 38193, 20488, 160970),
    CA.presence = c("Presence", "Presence", "Presence", "Presence", "Presence", "Presence")
  ),
  class = c("grouped_df", "tbl_df", "tbl", "data.frame"),
  row.names = c(NA, -6L), groups = structure(
    list(
      participant = c("L001", "L001", "L002", "L002", "L016", "L016"),
      task = c("T05", "T12", "T05", "T12", "T05", "T12"),
      .rows = structure(list(
        1L, 2L, 3L, 4L, 5L, 6L
      ), ptype = integer(0), class = c(
        "vctrs_list_of",
        "vctrs_vctr", "list"
      ))
    ),
    class = c("tbl_df", "tbl", "data.frame"),
    row.names = c(NA, -6L), .drop = TRUE
  )
)

核心需求：如何在该双分面图表中按匹配因子水平的数值对X轴（participant）进行排序？

要实现分面图表中参与者的有序排列，需要先将participant转换为有序因子，排序依据可根据需求选择（如某任务下特定策略的时长、总时长等），分两种场景处理：

场景1：所有分面使用统一排序（基于某一任务的数值） #

比如我们选择T05任务中"Presence"策略的Duration作为排序依据，步骤如下：

1. 预处理数据，生成有序因子 #

library(dplyr)
library(ggplot2)

# 取消原数据的分组状态
CA_presence <- CA_presence %>% ungroup()

# 计算排序参考值：提取T05任务中Presence策略的参与者时长，按时长升序排列
sort_ref <- CA_presence %>%
  filter(task == "T05", CA.presence == "Presence") %>%
  arrange(Duration)  # 若需降序，改为arrange(desc(Duration))

# 将participant转换为有序因子，顺序匹配sort_ref中的排列
CA_presence <- CA_presence %>%
  mutate(participant = factor(participant, levels = sort_ref$participant, ordered = TRUE))

2. 绘制图表（复用原有代码） #

此时participant已按指定顺序排序，直接运行原有绘图代码即可：

CA_presence %>% 
  ggplot(aes(fill = CA.presence, y = Duration, x = participant, label = scales::percent(Duration))) + 
  geom_bar(width = .7, position = "fill", stat = "identity") +
  scale_y_continuous(labels = scales::label_percent()) +
  facet_grid(~task) +
  ggtitle("Presence of CA in the dataset") +
  theme(plot.title = element_text(size = 15, hjust = 0.5),
        legend.text = element_text(size = 10),
        strip.text.x = element_text(size = 13),
        axis.text = element_text(size = 10),
        axis.title = element_text(size = 10)) +
  labs(x = "Participant",
       y = "Proportion of discourse time",
       fill = "CA presence") +
  scale_fill_brewer(palette = "Greens") +
  coord_flip()

场景2：每个分面独立排序（按对应任务的数值） #

若需要T05和T12分面内的参与者各自按该任务下的数值排序，需借助ggh4x包实现自由刻度的分面：

1. 安装并加载依赖包 #

install.packages("ggh4x")
library(ggh4x)

2. 计算每个分面内的排序顺序 #

# 按任务分组，计算每个参与者在该任务下的总时长，生成排序序号
sort_by_task <- CA_presence %>%
  group_by(task, participant) %>%
  summarise(total_duration = sum(Duration), .groups = "drop") %>%
  group_by(task) %>%
  arrange(total_duration) %>%  # 按总时长升序，降序用desc(total_duration)
  mutate(order = row_number())

# 将排序序号合并到原数据
CA_presence_ordered <- CA_presence %>%
  left_join(sort_by_task, by = c("task", "participant"))

3. 绘制分面独立排序的图表 #

CA_presence_ordered %>%
  ggplot(aes(fill = CA.presence, y = Duration, x = order, label = scales::percent(Duration))) + 
  geom_bar(width = .7, position = "fill", stat = "identity") +
  scale_y_continuous(labels = scales::label_percent()) +
  # 使用facet_grid2实现自由x轴刻度
  facet_grid2(~task, scales = "free_x", space = "free_x") +
  # 将x轴刻度替换为参与者编号
  scale_x_continuous(breaks = sort_by_task$order, labels = sort_by_task$participant) +
  ggtitle("Presence of CA in the dataset") +
  theme(plot.title = element_text(size = 15, hjust = 0.5),
        legend.text = element_text(size = 10),
        strip.text.x = element_text(size = 13),
        axis.text = element_text(size = 10),
        axis.title = element_text(size = 10)) +
  labs(x = "Participant",
       y = "Proportion of discourse time",
       fill = "CA presence") +
  scale_fill_brewer(palette = "Greens") +
  coord_flip()

内容的提问来源于stack exchange，提问作者Sébastien