人们经常忽略的一个选项是，只要您可以用多边形表示，您几乎可以在 ggplot2 中绘制任何东西。缺点是工作量大很多。
以下方法模仿了我在此处给出的答案，但稍作调整以更一致地适用于多种密度。它完全放弃了 {ggridges} 方法。
下面的函数可用于沿 y 位置对任意多边形进行切片。
library(ggplot2)
library(ggridges)
library(polyclip)
fade_polygon <- function(x, y, yseq = seq(min(y), max(y), length.out = 100)) {
poly <- data.frame(x = x, y = y)
# Create bounding-box edges
xlim <- range(poly$x) + c(-1, 1)
# Pair y-edges
grad <- cbind(head(yseq, -1), tail(yseq, -1))
# Add vertical ID
grad <- cbind(grad, seq_len(nrow(grad)))
# Slice up the polygon
grad <- apply(grad, 1, function(range) {
# Create bounding box
bbox <- data.frame(x = c(xlim, rev(xlim)),
y = c(range[1], range[1:2], range[2]))
# Do actual slicing
slice <- polyclip::polyclip(poly, bbox)
# Format as data.frame
for (i in seq_along(slice)) {
slice[[i]] <- data.frame(
x = slice[[i]]$x,
y = slice[[i]]$y,
value = range[3],
id = c(1, rep(0, length(slice[[i]]$x) - 1))
)
}
slice <- do.call(rbind, slice)
})
# Combine slices
grad <- do.call(rbind, grad)
# Create IDs
grad$id <- cumsum(grad$id)
return(grad)
}
接下来，我们需要手动计算每个月的密度，并为每个密度应用上面的函数。
# Split by month and calculate densities
densities <- split(lincoln_weather, lincoln_weather$Month)
densities <- lapply(densities, function(df) {
dens <- density(df$`Mean Temperature [F]`)
data.frame(x = dens$x, y = dens$y)
})
# Extract x/y positions
x <- lapply(densities, `[[`, "x")
y <- lapply(densities, `[[`, "y")
# Make sequence to max density
ymax <- max(unlist(y))
yseq <- seq(0, ymax, length.out = 100) # 100 can be any large enough number
# Apply function to all densities
polygons <- mapply(fade_polygon, x = x, y = y, yseq = list(yseq),
SIMPLIFY = FALSE)
接下来，我们需要将有关月份的信息添加回数据中。
# Count number of observations in each of the polygons
rows <- vapply(polygons, nrow, integer(1))
# Combine all of the polygons
polygons <- do.call(rbind, polygons)
# Assign month information
polygons$month_id <- rep(seq_along(rows), rows)
最后，我们用 vanilla ggplot2 绘制这些多边形。与ggridges(y / ymax) * scale所做的缩放类似，并且month_id每个月相互添加偏移量。
scale <- 3
ggplot(polygons, aes(x, (y / ymax) * scale + month_id,
fill = value, group = interaction(month_id, id))) +
geom_polygon(aes(colour = after_scale(fill)), size = 0.3) +
scale_y_continuous(
name = "Month",
breaks = seq_along(rows),
labels = names(rows)
) +
scale_fill_viridis_c()
由reprex 包于 2021-09-12 创建(v2.0.1)
