Write a DSSAT experimental file (X file) — write_exp

Creates a DSSAT experiment file from already prepared experiment metadata, planting information, soil/weather links, irrigation flags and fertilization inputs. This is the low-level writer used after experiment data have been tidied into one row per DSSAT treatment setup.

Usage

write_exp_dssat(
  path,
  id_name,
  crop,
  cultivar,
  soil,
  wth_station,
  planting_details,
  irri,
  fert_in,
  start_date,
  planting_date,
  emergence_date,
  treatments_number
)

Arguments

path: Character. Directory where the DSSAT experiment file will be written.
id_name: Character vector used to build the DSSAT experiment name and output file name. The first element is the site or experiment identifier.
crop: Character. DSSAT crop name, for example "rice", "maize", "barley", "sorghum", "wheat", "bean", "fababean", or "teff".
cultivar: Character vector of DSSAT cultivar codes, one per treatment when multiple treatments are written.
soil: Character vector of DSSAT soil profile identifiers.
wth_station: Character vector of DSSAT weather station identifiers.
planting_details: List or data frame with DSSAT planting details such as PPOP, PPOE, PLME, PLDS, PLRS, PLRD, and PLDP.
irri: Logical. TRUE for irrigated experiments and FALSE for rainfed experiments.
fert_in: Data frame or NULL. Fertilization schedule with DSSAT fields such as FDATE, FMCD, FACD, FDEP, FAMN, FAMP, FAMK, FAMC, FAMO, FOCD, and FERNAME.
start_date: Date. Simulation start date.
planting_date: Date vector. Planting date for each treatment.
emergence_date: Date vector or NULL. Emergence date for each treatment.
treatments_number: Integer. Number of DSSAT treatments to write.

Value

Character vector with the path of the DSSAT experiment file created.

Details

Use tidy_exp_dssat() to prepare the row-wise inputs consumed by this writer.

Examples

if (FALSE) { # \dontrun{
# Experimental tidy data
tidy_exp_data <- tidy_exp_dssat(agro, phenol, fertil, path = tempdir())

# Write DSSAT experimental files
exp_files_created <- tidy_exp_data %>%
  mutate(file = pmap_chr(., write_exp_dssat)) %>%
  pull(file)

exp_files_created
file.remove(exp_files_created)
} # }