在 ggridge 中选择 NaN 的联合带宽

Question

我正在尝试生成像 here 中描述的那样的脊线图，但错误“选择 NaN 的联合带宽”不断出现。这有什么问题吗？感谢任何指针，提示。最佳

toplot = structure(list(Year = c("2000", "2000", "2001", "2001", "2002", 
"2002", "2003", "2003", "2004", "2004", "2005", "2005", "2006", 
"2006", "2007", "2007", "2008", "2008", "2009", "2009", "2010", 
"2010", "2011", "2011", "2012", "2012", "2013", "2013", "2014", 
"2014", "2015", "2015", "2016", "2016", "2017", "2017", "2018", 
"2018", "2019", "2019", "2020", "2020", "2021", "2021"), genes = c("DAO", 
"IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", 
"DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", 
"IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", 
"DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", 
"IDH2", "DAO", "IDH2", "DAO", "IDH2", "DAO", "IDH2"), n = c(2L, 
0L, 2L, 0L, 2L, 0L, 3L, 0L, 5L, 0L, 5L, 0L, 4L, 0L, 6L, 0L, 2L, 
0L, 4L, 0L, 13L, 0L, 7L, 0L, 7L, 0L, 169L, 1L, 182L, 0L, 215L, 
56L, 147L, 11L, 165L, 115L, 10L, 62L, 13L, 74L, 14L, 59L, 67L, 
44L)), row.names = c(NA, -44L), class = c("tbl_df", "tbl", "data.frame"
))


toplot %>%
  mutate(YearFct = fct_rev(as.factor(Year))) %>%
  ggplot(aes(y = YearFct)) +
  geom_density_ridges(
    aes(x = n, fill = paste(YearFct, genes)), 
    alpha = .8
  ) +
  labs(
    x = "No_Patent",
    y = "Year"
  ) +
  scale_y_discrete(expand = c(0, 0)) +
  scale_x_continuous(expand = c(0, 0)) +
  coord_cartesian(clip = "off") +
  theme_ridges(grid = FALSE)

Answer 1

你的代码没问题。您只是没有足够的数据来绘制此类图。每年每个基因只有一次测量。因此，您试图每年根据一个点创建密度估计，但这是行不通的。您每年至少需要两分才能获得自动带宽选择。

如果您模拟大量数据，您会发现您的代码运行良好。

set.seed(1)

toplot <- data.frame(Year = rep(2000:2021, each = 20),
                     genes = rep(c("DAO", "IDH2"), 220),
                     n = round(rexp(440, rep(c(0.9, 0.05), 220))))

library(tidyverse)
library(ggridges)

toplot %>%
  mutate(YearFct = fct_rev(as.factor(Year))) %>%
  ggplot(aes(y = YearFct)) +
  geom_density_ridges(
    aes(x = n, fill = genes), 
    alpha = .8
  ) +
  labs(
    x = "No_Patent",
    y = "Year"
  ) +
  scale_y_discrete(expand = c(0, 0)) +
  scale_x_continuous(expand = c(0, 0)) +
  coord_cartesian(clip = "off") +
  theme_ridges(grid = FALSE)
#> Picking joint bandwidth of 3.71

一种可能的解决方案是使用 dnorm 创建您自己的密度曲线，其中 n 是平均值，分组标准差是 sd。这使您对所涉及的不确定性有所了解。它确实至少产生了一个 kind-of 信息图，尽管可能不如简单的闪避条形图诚实，这将是绘制此数据集的明显方法

toplot %>%
  group_by(genes) %>%
  mutate(sd = sd(n)) %>%
  group_by(Year, genes) %>%
  summarise(x = seq(0, 300, length = 1000),
            dens = dnorm(x, n, sd),
            dens = dens/max(dens)) %>%
  mutate(YearFct = fct_rev(as.factor(Year))) %>%
  ggplot(aes(y = YearFct, x = x)) +
  geom_ridgeline(
    aes(height = dens, fill = genes), 
    alpha = .8
  ) +
  labs(
    x = "No_Patent",
    y = "Year"
  ) +
  scale_y_discrete(expand = c(0, 0)) +
  scale_x_continuous(expand = c(0, 0)) +
  coord_cartesian(clip = "off") +
  theme_ridges(grid = FALSE)

我认为这比简单的线图更难解释，更不诚实，而且可以说更没有吸引力。

toplot %>%
  ggplot(aes(factor(Year), n, color = genes, group = genes)) +
  geom_line(size = 1.5) +
  geom_point(size = 4, shape = 21, fill = "white") +
  scale_color_manual(values = c("deepskyblue4", "orange")) +
  labs(x = "Year") +
  theme_light(base_size = 16)

^{由 reprex package (v2.0.1)}

于 2022-04-24 创建

在 ggridge 中选择 NaN 的联合带宽

Picking joint bandwidth of NaN within ggridge

r

ggplot2

ggridges