build_cell_names_r {ggdmcModel} | R Documentation |
Find All Possible Conditions
Description
Constructs all possible condition combinations (i.e., cells) based on experimental factors, parameter mappings, and response definitions. Returns both cell names and sorted factor definitions.
Usage
build_cell_names_r(parameter_map_r, factors_r, responses_r)
Arguments
parameter_map_r |
An Rcpp::List where each element is a character vector mapping parameters to conditions. Names should correspond to parameters. |
factors_r |
An Rcpp::List where each element is a character vector of factor levels. Names should correspond to factor names. |
responses_r |
A character vector (std::vector<std::string>) of response/accumulator names. |
Details
The function:
Converts R lists to 'C++' maps for efficient processing
Generates all condition combinations via Cartesian product
Handles special parameter mappings (like mapping accumulators to conditions)
Returns both cell names and the factor structure used
Value
An Rcpp::List with two elements:
-
cell_names
: Character vector of all possible condition combinations -
sortedFactors
: The processed factor structure used to generate cells
Typical Workflow
This function is typically used to:
Establish the full experimental design space
Verify factor/parameter compatibility
Generate condition labels for model specification
This function primarily is to debug the internal process of model building.
Examples
# A simple example
p_map <- list(A = "1", B = "1", t0 = "1", mean_v = "M", sd_v = "1",
st0 ="1")
factors <- list(S = c("s1", "s2"))
responses <- c("r1", "r2")
result <- build_cell_names_r(p_map, factors, responses)
# cat("B (2 factors), t0, mean_v (3 factors), sd_v (2 factors)")
p_map <- list(
A = "H", B = c("S", "G"), t0 = "E", mean_v = c("D", "H", "M"),
sd_v = c("D", "M"), st0 = "1"
)
factors <- list(
S = c("s1", "s2", "s3"), D = c("d1", "d2"), E = c("e1", "e2"),
G = c("g1", "g2", "g3"), H = c("h1", "h2", "h3", "h4", "h5")
)
responses <- c("r1", "r2", "r3")
result <- build_cell_names_r(p_map, factors, responses)