如何为ggplot的scale_colour_binned添加更多颜色调色板？

用ggplot2和ggOceanMaps绘制地图时，通过scale_colour_binned()实现日期的颜色分箱效果，尝试将type参数改为"magma"等调色板时，报错提示仅支持"viridis"或"gradient"，如何为scale_colour_binned()添加更多可用调色板？

原代码：

library(ggOceanMaps)
library(tidyverse)
library(lubridate)

df_map <- df_map %>%
  mutate(date_numeric = as.numeric(date))

basemap(data = df_map, limits = c(min(df_map$Lon) - 0.5,max(df_map$Lon) + 0.5,min(df_map$Lat) - 0.5,max(df_map$Lat) + 0.5), bathymetry = TRUE,
        # bathy.style = "rcb" proper raster
) + # a synonym: basemap(dt)
  ggspatial::geom_spatial_point(data = df_map, aes(x = Lon, y = Lat, color = date_numeric), size = 2) + 
  # scale_colour_distiller(labels = \(x) as.POSIXct(x, origin = lubridate::origin) |>
  #                          format(format ="%b %d"), n.breaks = length(unique(df_map$station))/2, palette = "Spectral")
  scale_colour_binned(type = "magma", name="Date",
                      breaks = seq(min(df_map$date_numeric), max(df_map$date_numeric), length.out = length(unique(df_map$date_numeric))),
                      labels = \(x) as.POSIXct(x, origin = lubridate::origin) |>
                        format(format = "%b %d"))

解决方法 #

1. 使用scale_colour_stepsn()自定义分箱调色板 #

这是最灵活的方案，支持所有调色板（包括viridis系列、RColorBrewer、自定义颜色），直接指定颜色向量即可实现分箱渐变。

需要先加载viridis包获取magma调色板：

library(ggOceanMaps)
library(tidyverse)
library(lubridate)
library(viridis)

df_map <- df_map %>%
  mutate(date_numeric = as.numeric(date))

basemap(data = df_map, 
        limits = c(min(df_map$Lon) - 0.5,max(df_map$Lon) + 0.5,
                   min(df_map$Lat) - 0.5,max(df_map$Lat) + 0.5), 
        bathymetry = TRUE) +
  ggspatial::geom_spatial_point(data = df_map, aes(x = Lon, y = Lat, color = date_numeric), size = 2) +
  scale_colour_stepsn(
    name = "Date",
    # 从magma调色板提取对应数量的颜色
    colours = magma(n = length(unique(df_map$date_numeric))),
    breaks = seq(min(df_map$date_numeric), max(df_map$date_numeric), 
                 length.out = length(unique(df_map$date_numeric))),
    labels = \(x) as.POSIXct(x, origin = lubridate::origin) |>
      format(format = "%b %d")
  )

2. 结合scale_colour_binned()与gradient类型 #

如果坚持使用scale_colour_binned()，可以将type设为"gradient"，通过low/high指定渐变两端，或用colors传入完整颜色向量：

方式A：指定渐变首尾颜色

basemap(data = df_map, 
        limits = c(min(df_map$Lon) - 0.5,max(df_map$Lon) + 0.5,
                   min(df_map$Lat) - 0.5,max(df_map$Lat) + 0.5), 
        bathymetry = TRUE) +
  ggspatial::geom_spatial_point(data = df_map, aes(x = Lon, y = Lat, color = date_numeric), size = 2) +
  scale_colour_binned(
    type = "gradient",
    name = "Date",
    # 从magma调色板取首尾颜色
    low = magma(10)[1],
    high = magma(10)[10],
    breaks = seq(min(df_map$date_numeric), max(df_map$date_numeric), 
                 length.out = length(unique(df_map$date_numeric))),
    labels = \(x) as.POSIXct(x, origin = lubridate::origin) |>
      format(format = "%b %d")
  )

方式B：使用调色板函数生成颜色

借助viridis_pal()生成指定类型的调色板函数，配合scale_colour_binned()的palette参数：

basemap(data = df_map, 
        limits = c(min(df_map$Lon) - 0.5,max(df_map$Lon) + 0.5,
                   min(df_map$Lat) - 0.5,max(df_map$Lat) + 0.5), 
        bathymetry = TRUE) +
  ggspatial::geom_spatial_point(data = df_map, aes(x = Lon, y = Lat, color = date_numeric), size = 2) +
  scale_colour_binned(
    type = "gradient",
    name = "Date",
    palette = viridis_pal(option = "magma"),
    breaks = seq(min(df_map$date_numeric), max(df_map$date_numeric), 
                 length.out = length(unique(df_map$date_numeric))),
    labels = \(x) as.POSIXct(x, origin = lubridate::origin) |>
      format(format = "%b %d")
  )

示例数据 #

df_map = structure(list(Lat = c(78.6585508333333, 78.6585508333333, 78.6585508333333,
78.6585508333333, 78.6585508333333, 78.6585508333333, 78.6585508333333,
78.6585508333333, 78.7585508333333, 78.7585508333333, 78.7585508333333,
79.6585508333333, 79.6585508333333, 79.6585508333333, 79.6585508333333,
79.7585508333333, 79.7585508333333, 79.7585508333333, 80.6585508333333,
80.6585508333333, 75.0000000000000, 75.1000000000000, 73.9994955166667, 73.9994955166667, 73.9994955166667,
73.9994955166667, 73.9994955166667), Lon = c(24.6500727416667, 24.6500727416667,
24.6500727416667, 24.6500727416667, 24.6500727416667, 24.6500727416667,
24.6500727416667, 24.6500727416667, 24.6500727416667, 24.6500727416667,
24.6500727416667, 24.6500727416667, 24.6500727416667, 24.6500727416667,
23.6500727416667, 23.6500727416667, 23.6500727416667, 25.7500727416667,
25.7500727416667, 25.7500727416667, 30.9864643333333, 30.8874643333333, 35.9974643333333,
35.9974643333333, 35.9974643333333, 35.9974643333333, 35.9974643333333), date = structure(c(1690042620,
1690042620, 1690042620, 1690042620, 1690042620, 1690042620, 1690042620,
1690042620, 1690042620, 1690042620, 1690192620, 1690192620, 1690192620,
1690192620, 1690192620, 1690392620, 1690392620, 1690542620, 1690542620,
1690542620, 1691056620, 1691056620, 1691686620, 1691686620, 1691686620, 1691686620,
1691686620), class = c("POSIXct", "POSIXt"), tzone = "UTC")), row.names = c(NA,
27L), class = "data.frame")

内容的提问来源于stack exchange，提问作者C. Guff