baseline • measure

Let’s use the meats data from {modeldata} to demonstrate baseline correction.

library(tidyverse)
library(tidymodels)
library(measure)
tidymodels_prefer()
theme_set(theme_light())

Data Cleanup

Before we can perform baseline correction, we need to reshape the data. It is in a wide format where the columns represent the wavelength and the value is transmittance. The step_baseline() function operates on long format data. We can reshape this data with tidyr.

meats2 <- 
  meats |>
  rowid_to_column(var = "id") |> 
  pivot_longer(cols = starts_with("x_"),
               names_to = "channel",
               values_to = "transmittance") |> 
  mutate(channel = str_extract(channel, "[:digit:]+") |> as.integer())

meats2 |>
  ggplot(aes(x = channel, y = transmittance, group = id)) + 
  geom_line(alpha = 0.5) + theme_light()

meats2 |> 
  group_by(id) |> 
  subtract_rf_baseline(yvar = transmittance, span = 0.8) |> 
  ggplot(aes(x = channel, color = water, group = id)) + 
  geom_line(aes(y = transmittance), alpha = 0.5) +
  scale_color_viridis_c() + 
  ggtitle("")