Exploring the magnetic susceptibility data from Boomplas

magnetic-susceptibility-data.R

library(tidyverse) # you may need to install.packages("tidyverse") in the console
library(googlesheets4) # ditto

# change to your own UW email
gs4_auth("bmarwick@uw.edu")

# Get our google sheet of information about the location of each point
ms_data <- 
  read_sheet("https://docs.google.com/spreadsheets/d/1rDyfJQ6OnWJktIWMZfnLe8YRtCiW1PVrP9nKW1kERN4/edit?pli=1#gid=0") 

# compute the mean values of our measurements, and then the LF and FD mass values
ms_data_computed <- 
  ms_data %>% 
  rowwise() %>%
  mutate(
    mean_lf = mean(c_across(starts_with("MS_LF")), na.rm = TRUE),
    mean_hf = mean(c_across(starts_with("MS_HF")), na.rm = TRUE)
  ) %>%
  ungroup() %>% 
  select(`Sample ID`,
         mean_lf, 
         mean_hf,
         MS_empty_pot_mass_g,
         MS_pot_and_sediment_mass_g ) %>% 
  # χ = low frequency measured value x (10/sample mass)
  mutate(lf = mean_lf * (10/(MS_pot_and_sediment_mass_g -  MS_empty_pot_mass_g )),
         hf = mean_hf * (10/(MS_pot_and_sediment_mass_g -  MS_empty_pot_mass_g ))) %>% 
  # χFD % = 100 x ((χLF - χHF) / χLF)
  mutate(fd = 100 * (lf - hf) / lf)

# draw a plot
lf_plot <- 
ggplot(ms_data_computed) +
  aes(`Sample ID`, 
      lf,
      label = `Sample ID`) +
  geom_line() +
  geom_point() +
  coord_flip() +
  theme_minimal() +
  ylab(bquote('χ m'~(m^3~kg^-1)))

fd_plot <- 
ggplot(ms_data_computed) +
  aes(`Sample ID`, 
      fd,
      label = `Sample ID`) +
  geom_line() +
  geom_point() +
  coord_flip() +
  theme_minimal() +
  # remove labels to fit nicely on the right side of the panel
  theme(axis.text.y = element_blank(),
        axis.title.y = element_blank()) +
  ylab("χ fd %")

# draw the two plots together
library(cowplot)
plot_grid(lf_plot,
          fd_plot)