在R语言中重现目标学术热图的配色方案

我正在使用R语言开发，在一篇论文中发现了心仪的热图，想要尝试重现。参考教程模拟数据后编写了如下R代码：

library(ggplot2)
library(reshape2)
library(metR)

set.seed(123)  
Biomass <- seq(0, 10, length.out = 100)
variable <- seq(0, 10, length.out = 100)

con <- data.frame(matrix(ncol = length(variable), nrow = length(Biomass)))

for (i in 1:length(Biomass)) {
    for (j in 1:length(variable)) {
        con[i, j] <- sin(Biomass[i]) + cos(variable[j])  # adjust this as needed
    }
}

rownames(con) <- Biomass

con <- cbind(Biomass = rownames(con), con)
rownames(con) <- NULL

con$Biomass <- as.numeric(con$Biomass)

conm = melt(con, id = "Biomass")
conm$variable <- gsub("X", "", conm$variable)
conm$variable = as.numeric(conm$variable)
gg = ggplot(conm, aes(x = variable, y = Biomass)) + 
    geom_raster(aes(fill = value)) + 
    geom_contour(aes(z = value), colour = "white", size = 0.2, alpha = 0.5) + 
    geom_text_contour(aes(z = value),  colour = "white" ) +
    labs(x = "Filtered light intensity (umol photons/m2/s)", 
         y = "Dry Biomass Concentration (g/L)", 
         fill = "Productivity (umol O2/g biomass/s)") + 
    theme(legend.title = element_text(size = 10, face = "bold"), 
          legend.position = "top", panel.background = element_blank(), 
          axis.text = element_text(colour = "black", size = 10, face = "bold"), 
          axis.title = element_text(size = 12, face = "bold"), 
          legend.text = element_text(size = 11), legend.key = element_blank()) + 
    scale_fill_continuous(low = "#BFE1B0", high = "#137177") + 
    scale_y_continuous(expand = c(0,0)) +
    scale_x_continuous(expand = c(0,0)) 

gg

当前生成的热图：

请问是否可以重现目标热图的配色方案？

当然可以重现目标热图的配色方案，以下是几种可行的实现方式：

1. 提取目标热图的颜色值 #

使用取色工具（比如系统自带取色器）从目标热图中提取关键渐变节点的十六进制色值，然后通过scale_fill_gradientn指定多色渐变，或替换scale_fill_continuous的low和high参数：

# 示例：假设提取的颜色为浅橙到深褐的渐变
scale_fill_gradientn(colors = c("#FFE8CC", "#FFB74D", "#E67E22", "#8E44AD"))

2. 使用专业配色包匹配风格 #

如果目标热图采用科研领域常用配色体系，可借助R配色包快速实现：

• 暖色调渐变（适配高对比度科研热图）：

library(RColorBrewer)
scale_fill_distiller(palette = "YlOrRd", direction = 1)

• 冷色调渐变（适配蓝绿系专业热图）：

library(viridis)
scale_fill_viridis(option = "mako")

3. 直接修改现有代码的配色 #

针对你当前的代码，只需替换scale_fill_continuous中的色值参数即可，将现有配色替换为目标热图的深浅色：

# 替换为从目标图提取的浅色调和深色调
scale_fill_continuous(low = "#你的浅色调十六进制值", high = "#你的深色调十六进制值")

内容的提问来源于stack exchange，提问作者stats_noob