如何将剪贴蒙版应用于ggplot中的geom？

Question

我正在尝试将剪贴蒙版应用到 ggplot 中的几何图形以屏蔽部分数据，但保持轴、网格、其他几何图形和图例可见。我不想创建一个特定的情节，因此我不是在寻找一种解决方法，用多边形掩盖情节的某些部分。

这是我想模仿的那种设计（面具，不一定是主题，我现在怎么做）：

(source)

另见this example

有人可能会争辩说，我可以过滤不包含在定义掩码的多边形中的数据。但是，虽然它适用于点，并且可以适用于多边形/线状对象，但它适用于栅格（边界不会完全遵循非垂直或非水平线）。 所以我尝试了以下方法：

library(ggplot2)
library(gridSVG)
library(grImport)

# Create a plot
p <- ggplot(diamonds[1:300,], aes(carat, price)) + geom_point(aes(colour = cut))

# And a clipping mask
pg <- polygonGrob(c(.7, 0, 0, 1, 1),
              c(0, .7, 1, 1, 0))
cp <- clipPath(pg)

我能够使用包gridSVG 来定义clipping mask，但是我很难将它应用到ggplot 对象上，即使在使用ggplotGrob() 提取grob（参见资源here）之后也是如此。我无法将剪贴蒙版应用到 grob：

g <-  ggplotGrob(p) # store the plot as a grob

registerClipPath("mask", cp)
g_clipped <- clipPath(g)

gridsvg(name = "test_c2.svg")
grid.draw(clipPathGrob(g_clipped, cp)$grob)
dev.off()

我的直觉是应该绘制g_clipped，但我不能grid.draw() 它，因为它是一个clipPath 对象。还有grid.draw() 此处写的行显示未屏蔽的情节。我想我不太了解 clipPath 对象的功能。

函数grobify() 听起来它可以帮助没有gridSVG 的替代方法，请参阅details here，但我不理解非常简约的文档。

由于我什至无法将剪贴蒙版应用于整个情节，因此我的目标还很遥远。

如果您能帮助我了解如何从 gridSVG 应用剪贴蒙版或有其他解决方案将剪贴蒙版应用于特定几何图形，请告诉我。

Answer 1

以下是一个网格解决方案，但在很大程度上是一种变通方法。它展示了如何将非矩形裁剪区域应用于 ggplot，以便裁剪图中的一组点。你的尝试并没有太大的错误。需要注意的几点：

1. 您需要grid.force() ggplotGrob 对象，以便grid 可以看到grobs。
2. 不要将 ggplot grob 定义为剪切路径 - 剪切路径是多边形。
3. 剪切路径应用于 ggplot 绘图面板中的点 grob。这意味着绘图面板中的其他对象、面板背景和网格线不会被剪裁。仅裁剪数据点。

我在绘图中添加了一条蓝线，以表明该线也不需要剪裁；但可以根据需要剪裁。

还有注释的代码行，当不注释时，将绘制剪切区域，并将网格线和点移动到前面（即在较深灰色剪切区域的前面）。

library(ggplot2)
library(gridSVG)
library(grid)

# Open the graphics device
gridsvg(name = "test.svg")

# Create a plot
p <- ggplot(diamonds[1:300, ], aes(carat, price)) + 
       geom_point(aes(colour = cut)) +
       geom_line(data = data.frame(x = c(.3, .9), y = c(500, 2500)), aes(x,y), col = "skyblue", size = 2)
g <- ggplotGrob(p) # Store the plot as a grob


g = grid.force(g)  # So that grid sees all grobs
grid.draw(g)       # Draw the plot

# Define the clipping path
pg <- polygonGrob(c(.7, 0, 0, 1, 1),
                  c(0, .7, 1, 1, 0))
# The clipping path can be nearly any shape you desire. 
# Try this for a circular region
# pg = circleGrob(x = .5, y = .6, r = .5)
cp <- clipPath(pg)

# Add the clipping path to the points grob.
# That is, only the points inside the polygon will be visible,
# but the background and grid lines will not be clipped. 
# Nor will the blue line be clipped.
# grid.ls(g)     # names of the grobs
seekViewport(grep("panel.[0-9]", grid.ls(g)$name, value = TRUE))
grid.clipPath("points", cp, grep = TRUE)   

# To clip the blue line, uncomment the next line
# grid.clipPath("GRID.polyline", cp, grep = TRUE)       

# To show the clipping region,    
# uncomment the next two lines.
# showcp = editGrob(pg, gp = gpar(fill = rgb(0, 0, 0, 0.05), col = "transparent"))
# grid.draw(showcp)

# And to move the grid lines, remaining data points, and blue line in front of the clipping region,
# uncomment the next five lines
# panel = grid.get("panel", grep = TRUE)   # Get the panel, and remove the background grob
# panel = removeGrob(panel, "background", grep = TRUE)

# grid.remove("points", grep = TRUE)     # Remove points and grid lines from the rendered plot
# grid.remove("line", grep = TRUE, global = TRUE)

# grid.draw(panel)     # Draw the edited panel - on top of the clipping region 


# Turn off the graphics device
dev.off()

# Find text.svg in your working directory

编辑使用绘制数据点的坐标系定义剪辑区域。

library(ggplot2)
library(gridSVG)
library(grid)

# Open the graphics device
gridsvg(name = "test.svg")

# Create a plot
p <- ggplot(diamonds[1:300, ], aes(carat, price)) + 
       geom_point(aes(colour = cut)) +
       geom_line(data = data.frame(x = c(.3, .9), y = c(500, 2500)), aes(x,y), col = "skyblue", size = 2)
g <- ggplotGrob(p) # Store the plot as a grob


g = grid.force(g)  # So that grid sees all grobs
grid.draw(g)       # Draw the plot

# Get axis limits (including any expansion)
axis.limits = summarise_layout(ggplot_build(p))[1, c('xmin', 'xmax', 'ymin', 'ymax')]

# Find the 'panel' viewport,
# then push to a new viewport, 
# one that exactly overlaps the 'panel' viewport,
# but with limits on the x and y scales that are the same
# as the limits for the original ggplot. 
seekViewport(grep("panel.[0-9]", grid.ls(g)$name, value = TRUE))
pushViewport(dataViewport(xscale = axis.limits[1, 1:2],
                          yscale = axis.limits[1, 3:4]))

# Define the clipping path
 pg <- polygonGrob(x = c(.6,   0.3, .3,   .8,   1.2), 
                   y = c(500, 1500, 2900, 2900, 1500), 
                   default.units="native")
cp <- clipPath(pg)

# Add the clipping path to the points grob.
# That is, only the points inside the polygon will be visible,
# but the background and grid lines will not be clipped. 
# Nor will the blue line be clipped.
# grid.ls(g)     # names of the grobs

grid.clipPath("points", cp, grep = TRUE)   

# To clip the blue line, uncomment the next line
 grid.clipPath("GRID.polyline", cp, grep = TRUE)       

# To show the clipping region. 
 showcp = editGrob(pg, gp = gpar(fill = rgb(0, 0, 0, 0.05), col = "transparent"))
 grid.draw(showcp)

# And to move the grid lines and remaining data points in front of the clipping region.
 panel = grid.get("panel", grep = TRUE)   # Get the panel, and remove the background grob
 panel = removeGrob(panel, "background", grep = TRUE)

 grid.remove("points", grep = TRUE)     # Remove points and grid lines from the rendered plot
 grid.remove("line", grep = TRUE, global = TRUE)

 grid.draw(panel)     # Draw the edited panel - on top of the clipping region 


# Turn off the graphics device
dev.off()

# Find text.svg in your working directory

Answer 2

由于您从 ggplot 对象开始，将遮罩本身创建为 geom 层可能更简单，而不是将所有内容转换为 grob 并在那里的网格系统中工作。

这里可以使用 ggpolypath 包中的 geom_polypath() 函数。与 ggplot2 中的标准 geom_polygon 不同，它能够处理带孔的多边形（参见 vignette）：

# sample data frame for clipping. The first four x & y coordinates are for the outer ends;
# the next four are for the hole in the polygon.
clipping.df <- data.frame(x = c(0, 1.5, 1.5, 0, 0.2, 1, 0.7, 0.3),
                          y = c(0, 0, 3000, 3000, 250, 2000, 2800, 1500),
                          hole = rep(c(FALSE, TRUE), each = 4),
                          group = rep(c("1", "2"), each = 4))

library(ggpolypath)
p +
  geom_polypath(data = clipping.df,
                aes(x = x, y = y, group = group),
                colour = NA, fill = "black", alpha = 0.5,
                inherit.aes = FALSE) +
  scale_x_continuous(expand = c(0, 0)) + # don't show edges beyond the extent
  scale_y_continuous(expand = c(0, 0))   # of the polygon