The function is used in the depths to map parameter inputs to the parameters of a model. One application is to get the search space as a vector, matching with the free parameters of a model. Other applications map, for example, mean values to the free parameters of a model. Relevant when users use the "default parameters" approach where they only specify the parameter labels and assume the package figures out how each parameter relates across conditions (see simulate_data). This comes in handy, when freeing a parameter across conditions, while the search space remains the same (otherwise, a user would always have to adapt the vectors for lower/upper to match with x2prms_vals)
Usage
get_parameters_smart(
drift_dm_obj,
input_a,
input_b = NULL,
labels = TRUE,
is_l_u = TRUE,
fill_up_with = NULL
)
Arguments
- drift_dm_obj
an object of type drift_dm
- input_a, input_b
either a atomic vector or list (see create_matrix_smart)
- labels
optional logical, if
TRUE
, then the returned vectors have the unique parameter labels according to prm_cond_combo_2_labels.- is_l_u
optional logical, if
TRUE
, a warning is thrown wheninput_a
leads to larger values thaninput_b
. Useful wheninput_a
andinput_b
span a (search) space.- fill_up_with
optional values used to fill up the returned vectors for all parameters that are not specified in
input_a
orinput_b
(requires at least one parameter to specified).
Value
a list with two entries named vec_a/vec_b
. The length and names
(if requested) matches with coef(model, select_unique = TRUE). When
input_a
and/or input_b
is NULL
, the respective entry for
vec_a
/vec_b
will be NULL
as well.
Details
The function first gets all unique parameters across conditions using
prms_cond_combo. The unique parameter labels are then forwarded
to create_matrix_smart, together with all (!) the conditions in the
model and the input_a
/input_b
arguments. Subsequently, the created matrices
are wrangled into vectors in accordance with prms_cond_combo. The
vectors are then passed back.