如何用grid.arrange排列shapviz的sv_dependence图：统一尺寸且仅显示一次色条

尝试使用grid.arrange()将shapviz包中的三个sv_importance()绘图排列在一行，仅在第三个图显示特征值颜色刻度（色条），但当前第三个图因色条占据额外宽度，导致三个图的主体绘图区域尺寸不一致。需要让三个图的主体区域尺寸相同，同时保留第三个图的色条。

可复现代码：

library(shapviz)
library(ggplot2)
library(gridExtra)

set.seed(1)

X_train <- data.matrix(`colnames<-`(replicate(26, rnorm(100)), LETTERS))
dtrain <- xgboost::xgb.DMatrix(X_train, label = rnorm(100))
fit <- xgboost::xgb.train(data = dtrain, nrounds = 50)
shp <- shapviz(fit, X_pred = X_train)

p_a <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_b <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_c <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15)
grid.arrange(p_a,p_b,p_c,nrow=1)

方法1：使用patchwork包（推荐） #

patchwork对ggplot对象的布局控制更灵活，能自动对齐绘图区域，同时可以统一管理图例显示。

代码示例：

library(shapviz)
library(ggplot2)
library(patchwork)

set.seed(1)

X_train <- data.matrix(`colnames<-`(replicate(26, rnorm(100)), LETTERS))
dtrain <- xgboost::xgb.DMatrix(X_train, label = rnorm(100))
fit <- xgboost::xgb.train(data = dtrain, nrounds = 50)
shp <- shapviz(fit, X_pred = X_train)

p_a <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_b <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_c <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15)

# 排列并对齐绘图区域，仅保留一个色条
p_a + p_b + p_c + 
  plot_layout(nrow = 1, guides = "collect") +
  theme(legend.position = "right")

方法2：使用gridExtra结合gtable调整宽度 #

如果坚持使用gridExtra，可以通过gtable对象手动调整前两个图的宽度，让它们预留出色条空间，与第三个图对齐。

代码示例：

library(shapviz)
library(ggplot2)
library(gridExtra)
library(gtable)

set.seed(1)

X_train <- data.matrix(`colnames<-`(replicate(26, rnorm(100)), LETTERS))
dtrain <- xgboost::xgb.DMatrix(X_train, label = rnorm(100))
fit <- xgboost::xgb.train(data = dtrain, nrounds = 50)
shp <- shapviz(fit, X_pred = X_train)

p_a <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_b <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15, color_bar_title=NULL)
p_c <- sv_importance(shp, kind = "beeswarm", show_numbers = TRUE, max_display = 15)

# 转换为gtable对象
gt_a <- ggplotGrob(p_a)
gt_b <- ggplotGrob(p_b)
gt_c <- ggplotGrob(p_c)

# 让前两个图的宽度与第三个图（含色条）一致
gt_a$widths <- gt_c$widths
gt_b$widths <- gt_c$widths

# 排列调整后的图形
grid.arrange(gt_a, gt_b, gt_c, nrow = 1)

内容的提问来源于stack exchange，提问作者kris