## code to prepare `Vascular_Abundances_Clod` dataset goes here
# Empty the environment
rm(list = ls())
# Source cleaning function
source("R/data.cleaning.R")
source("R/add.treatments.R")
library(tidyverse)
# Import dataset containing thermal conductivity measurements -------------------------
ThermalK <- readr::read_csv("data-raw/Soil/Thermal_Conductivity_Horizons.csv")
## Clean horizons characters
ThermalK_clean <- data.cleaning(ThermalK)
# Import dataset containing soil physical properties ----------------------
load("data/Soil_Physic_mm.rda")
## Compute the mean predicted thermal conductivity at 5 cm
Horizon_5 <- Soil_Physic_mm %>%
filter(Depth < 8 & Depth > 2) %>%
group_by(Parcelle, Traitement, Exclos) %>%
summarise_at(vars(Volume:ThermDiff), .funs = mean) %>%
mutate(Profondeur = 5)
## Compute the mean predicted thermal conductivity at 10 cm
Horizon_10 <- Soil_Physic_mm %>%
filter(Depth < 13 & Depth > 7) %>%
group_by(Parcelle, Traitement, Exclos) %>%
summarise_at(vars(Volume:ThermDiff), .funs = mean) %>%
mutate(Profondeur = 10)
## Compute the mean predicted thermal conductivity at 10 cm
Horizon_15 <- Soil_Physic_mm %>%
filter(Depth < 18 & Depth > 12) %>%
group_by(Parcelle, Traitement, Exclos) %>%
summarise_at(vars(Volume:ThermDiff), .funs = mean) %>%
mutate(Profondeur = 15)
Horizon <- bind_rows(Horizon_5, Horizon_10, Horizon_15)
# Create final data set ---------------------------------------------------
Soil_ThermalConductivity_Horizon <- ThermalK_clean %>%
### Average the repetitions
group_by(Date, Parcelle, Traitement, Exclos, Grazing, Profondeur) %>%
summarise(Conductivite_thermique = mean(Conductivite_thermique, na.rm = T),
mean_Temp = mean(Temp_moy, na.rm = T)) %>%
ungroup() %>%
left_join(Horizon)
# Add Treatments variables
Soil_ThermalConductivity_Horizon <- Soil_ThermalConductivity_Horizon %>%
rename(Depth = Profondeur,
K_measured = Conductivite_thermique,
Temp_mean = mean_Temp) %>%
add.treatments()
usethis::use_data(Soil_ThermalConductivity_Horizon, overwrite = TRUE)
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