为了返回您概述的情节，还有很多事情要做。此外，您还没有提供所需输出的详细示例，但基于您给出的示例，希望这接近您想要的。
在这个方法中，其中一个标签的位置有问题，我无法解决这个问题，所以我最终手动纠正了它。如果有人能看到错误，请在下面评论。

library(dplyr)
library(ggplot2)

# A dataframe of your matrix
df <- data.frame(matrix(c(1,rep(2,4),rep(3,6),rep(4,4),5,
                          139.17365,136.27613,139.01464,
                          135.47032,98.02343,136.28064,
                          132.31289,135.26496,96.62991,
                          97.49587,90.17913,132.25711,
                          96.01838,88.87682,89.06218,87.65776),16,2,
                        byrow=F))

colnames(df) <- c("id", "value")

# Get max value of value column
max_value <- max(df[,2])

# Prepare data for plotting
df1 <- df %>%
  # Your "percentage decrease based on magnitude" formula
  mutate(perc_all = round((max(value) - value) * 100 / max(value), 1)) %>%
  group_by(id) %>%
  # Assign value for original order (and for barplot labels)
  mutate(ord = paste0("x", 1:n())) %>%
  # Sort data in descending order
  arrange(id, desc(perc_all)) %>%
  # Create vector of barplot labels
  mutate(label_text =  paste0(ord,"=", round(perc_all, 1), "%")) %>%
  # Add one row to each group for absent data
  group_modify(~ add_row(.x,.before = 0)) %>%
  # Add value to new rows so each column adds up to max_value
  mutate(perc_all = ifelse(is.na(perc_all),
                           max_value - sum(perc_all, na.rm = TRUE), perc_all),
         # Add "x" value to new rows
         ord = ifelse(is.na(ord),
                      paste0("x", n()), ord),
         # Calculate label locations for barplot labels
         label_loc = cumsum(lag(perc_all, default = 0))) %>% 
  # Return only the plot data
  filter(id %in% 2:5) %>%
  ungroup()

# Label placement of x3 for id group 3 is incorrect, could not work out why,
# so have to manually edit it
df1[11,6] <- df1[11,6] - 2

# Running this will return a warning, which you can ignore, it just means
# there are NA values in the label_text column
ggplot() +
  geom_bar(data = df1,
           aes(x = id, 
               y = perc_all,
               fill = ord,
               group = ord),
           stat = "identity",
           show.legend = FALSE) +
  geom_text(data = df1,
            aes(x = id,
                y = label_loc,
                label = label_text),
            vjust = -0.1,
            colour = "black",
            size = 2)

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的数据

这就是你想要的吗

mat.all=matrix(c(1,rep(2,4),rep(3,6),rep(4,4),5,139.17365,136.27613,139.01464,135.47032,98.02343,136.28064,132.31289,135.26496,96.62991, 97.49587,90.17913,132.25711,96.01838,88.87682,89.06218,87.65776),16,2,byrow=F)

library(ggplot2)

# Convert the matrix to a data frame
df <- data.frame(mat.all)
perc.all=round(((mat.all[1,2]-mat.all[1:16,2])*100/mat.all[1,2]),1)
# Add a column for percentage decrease
df$perc.decrease <- perc.all

# Plot the stacked bar chart
ggplot(df, aes(x = factor(X1), y = X2, fill = factor(X1))) +
  geom_bar(stat = "identity") +
  geom_text(aes(label = paste0(perc.decrease, "%")),
            position = position_stack(vjust = 0.5), size = 3) +
  #scale_y_continuous(labels = scales::comma) +  # Optional, format y-axis labels
  labs(title = "Stacked Bar Chart with Percentage Decrease",
       x = "Category",
       y = "Magnitude") +
  theme_minimal()

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