baseline

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("")

- Data Cleanup