如何在R的ggplot中绘制波数不匹配的两个FTIR光谱到同一图

方法一：直接叠加线条（最简单快捷） #

不需要合并数据集，直接在同一个ggplot对象中依次添加两个geom_line，分别指定各自的数据集，并通过颜色区分两组数据：

library(readxl)
library(ggplot2)

# 读取两个数据集
sacola57 <- read_excel("57.xlsx", sheet = 1)
PADRAO <- read_excel("padrao.xlsx", sheet = 1)

# 绘制对比图
ggplot() +
  # 添加第一个光谱线条
  geom_line(data = sacola57, aes(x = Wavenumber, y = Absorbance, color = "sacola57")) +
  # 添加第二个光谱线条
  geom_line(data = PADRAO, aes(x = Wavenumber, y = Absorbance, color = "PADRAO")) +
  # 设置主题，移除网格线
  theme_bw() +
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
  # 自定义图例标题和颜色
  labs(color = "样本类型") +
  scale_color_manual(values = c("sacola57" = "#1f77b4", "PADRAO" = "#ff7f0e"))

方法二：插值对齐波数后用长格式绘图 #

如果希望用tidy数据格式绘图，可以先通过插值将两个数据集的波数对齐，再合并成统一数据集：

library(readxl)
library(ggplot2)
library(dplyr)
library(tidyr)

# 读取数据
sacola57 <- read_excel("57.xlsx", sheet = 1)
PADRAO <- read_excel("padrao.xlsx", sheet = 1)

# 生成统一的波数序列：覆盖两个数据集的全部波数范围，步长设为1
min_wavenum <- min(sacola57$Wavenumber, PADRAO$Wavenumber)
max_wavenum <- max(sacola57$Wavenumber, PADRAO$Wavenumber)
common_wavenum <- seq(from = min_wavenum, to = max_wavenum, by = 1)

# 对两个数据集分别进行线性插值，匹配统一波数
sacola_interp <- tibble(
  Wavenumber = common_wavenum,
  Absorbance = approx(sacola57$Wavenumber, sacola57$Absorbance, xout = common_wavenum)$y,
  Sample = "sacola57"
)

padrao_interp <- tibble(
  Wavenumber = common_wavenum,
  Absorbance = approx(PADRAO$Wavenumber, PADRAO$Absorbance, xout = common_wavenum)$y,
  Sample = "PADRAO"
)

# 合并成长格式数据集
combined_data <- bind_rows(sacola_interp, padrao_interp)

# 绘制对比图
ggplot(combined_data, aes(x = Wavenumber, y = Absorbance, color = Sample)) +
  geom_line() +
  theme_bw() +
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
  labs(color = "样本类型") +
  scale_color_manual(values = c("sacola57" = "#1f77b4", "PADRAO" = "#ff7f0e"))

说明 #

• 方法一适合快速出图，不需要修改原始数据；
• 方法二通过插值对齐波数，适合后续需要对数据进行统一分析的场景，approx函数默认使用线性插值，能较好保留FTIR光谱的趋势。

内容的提问来源于stack exchange，提问作者oceanpath