Initialise optimisation model (wrapper)

Usage

prepare_model(
  df_list,
  yaml_list = NULL,
  assignment = c("diversity", "preference", "phd", "multirole"),
  w1 = 0.5,
  w2 = 0.5,
  ...
)

df_list: Model input list.
yaml_list: Parameter list from [extract_params_yaml()]. Optional for `assignment = "diversity"` and `assignment = "preference"` for backward compatibility. If supplied, this list is used directly. Ignored for `assignment = "phd"` and `assignment = "multirole"`.
assignment: Character string indicating model type. Must be one of `"diversity"`, `"preference"`, `"phd"`, or `"multirole"`.
w1, w2: Numeric values between 0 and 1. Should sum to 1. Used only for `assignment = "diversity"`.
...: Additional arguments: * For `assignment = "diversity"` when `yaml_list` is `NULL`: supply `n_topics`, `nmin`, `nmax`, `rmin`, and `rmax`. * For `assignment = "preference"` when `yaml_list` is `NULL`: supply `n_topics`, `B`, `nmin`, `nmax`, `rmin`, and `rmax`. * For `assignment = "phd"`: passed to [prepare_phd_model()], including `protected_year` when a cohort other than Year 1 should receive the soft TA-load protection. * For `assignment = "multirole"`: passed to [prepare_multirole_model()]. Multi-role semester capacity is supplied during extraction and read from `df_list$C`.

An ompr model.