# Prints NLME metamodel template file and token json file using given options, filepaths and data This function generates and writes the model template and tokens files based on the provided inputs. ```r write_ModelTemplateTokens( TemplateFilePath = "template.txt", TokensFilePath = "tokens.json", Description = "", Author = "", DataFilePath, DataMapping = NULL, ColDef = "", PMLParametersSets, EstArgs = specify_EngineParams(), SimArgs = "", Tables = list(), AppendixRows = "", OmegaSearchBlocks = list() ) ``` ## Arguments - `TemplateFilePath`: TemplateFilePath NLME template file path to be written (usually txt). - `TokensFilePath`: json file path to be written (usually json). - `Description`: A problem name to be outputted in Description section. - `Author`: The author information for the model to be outputted in Author section. - `DataFilePath`: A data file path used by NLME. - `DataMapping`: Mapping of model terms to data column names, which can be: * A named character vector : Used when `PMLParametersSets` contains a single parameter set. Maps model terms to data columns. * A named list of named character vectors : Used when `PMLParametersSets` contains multiple parameter sets. Each element corresponds to a parameter set, with list names matching the names of `PMLParametersSets`. - `ColDef`: A character string specifying additional column definitions in NLME column definition format. See Phoenix NLME documentation for details. [https://onlinehelp.certara.com/phoenix/8.6/index.html#t=Phoenix_UserDocs%2FPML%2FColumn_mappings.htm](https://onlinehelp.certara.com/phoenix/8.6/index.html#t=Phoenix_UserDocs%2FPML%2FColumn_mappings.htm) - `PMLParametersSets`: A list of PML parameters sets (`PMLModels` class instance). - `EstArgs`: Estimation arguments for the model template. Please use `specify_EngineParams` to specify the arguments passed to NLME. - `SimArgs`: Simulation arguments for the model template. Please use `specify_SimParams` to specify the arguments passed to NLME. - `Tables`: A list of `Table` class instances specifying properties of the tables to be generated after fitting or during simulation. - `AppendixRows`: Additional rows to include in the model template appendix in NLME column definition format. See Phoenix NLME documentation for details. [https://onlinehelp.certara.com/phoenix/8.6/index.html#t=Phoenix_UserDocs%2FPML%2FColumn_mappings.htm](https://onlinehelp.certara.com/phoenix/8.6/index.html#t=Phoenix_UserDocs%2FPML%2FColumn_mappings.htm) - `OmegaSearchBlocks`: A list of character vectors representing omega names to try to build block omegas. ## Returns A list containing statements written to template and tokens files. ## Details Mapping Details: **Basic Mapping:** Maps a model variable name (e.g., `CObs`) to a column name in your data file (e.g., `"Concentration"`). **Shorthand Mapping:** If an element is unnamed, the Model Term is assumed to be the same as the Data Column Term. Example: `c(ID = "Subject", "Age", Weight = "WT")` is equivalent to `c(ID = "Subject", Age = "Age", Weight = "WT")`. **Multiple ID/Grouping Levels:** Model terms matching the pattern `ID[0-9]?` (i.e., `ID`, `ID0`, `ID1`, `ID2`, `ID3`, `ID4`), case-insensitive, are automatically recognized by `Certara.RsNLME` as NLME sort keys/grouping levels. You can map up to 5 such levels. The function uses these to structure the model execution. **Covariates:** If not explicitly mapped, the function attempts to map them using data column names that match covariate names in the model. **Mapping a List:** When using a list, each vector must map terms specific to its parameter set, and the list length must equal the number of parameter sets. **Special Terms:** * Terms `\_Duration` or `\_Rate` could be used to map rate/duration columns for the corresponding dosepoints (e.g., `A1_Rate = "InfRate"`). Term `\BQL` could be used to map a BQL flag column for the corresponding observation (e.g., `CObsBQL = "ConcBQL"`). * The generic `AMT` term can be used to map the dose amount column; the function will automatically associate it with the primary absorption compartment (e.g., `A1` for zero-order/bolus, `Aa` for first-order) for each parameter set. * Generic `Duration` or `Rate` terms can be mapped (e.g., `Rate = "InfRate"`); the function will associate them with the dose mapped via `AMT`. If a specific mapping like `A1_Rate` exists, it overrides the generic `Rate` mapping for that dosepoint (`A1`). ## Examples ```r # Write model template and tokens files PMLParametersSets <- create_ModelPK(CompartmentsNumber = c(1,2)) # write test data frame TempFolder <- tempdir() TemplateFilePath <- file.path(TempFolder, "template.txt") TokensFilePath <- file.path(TempFolder, "tokens.json") DataFilePath <- file.path(TempFolder, "Data.csv") # Ensure data file has columns matching the DataMapping values write.csv(data.frame(Subject = 'id_1', # Column for ID StudyDay = 1, # Column for ID1 time = 0, # Column for time DoseAmt = 100, # Column for AMT Concentration = 10.5, # Column for CObs SubjectAge = 45, # Column for Age Weight = 70, # Column for Weight ConcBQL = 0), # Column for CObsBQL DataFilePath, row.names = FALSE) # Use row.names=FALSE write_ModelTemplateTokens( TemplateFilePath = TemplateFilePath, TokensFilePath = TokensFilePath, Description = "1-2Cpts try with Multi-ID and Shorthand", Author = "Certara", DataFilePath = DataFilePath, DataMapping = c(ID = "Subject", # Map ID model term to Subject column ID1 = "StudyDay", # Map ID1 model term to StudyDay column time = "time", # Map time model term to time column CObs = "Concentration", # Map CObs to Concentration AMT = "DoseAmt", # Map generic AMT to DoseAmt "SubjectAge", # Shorthand: Map Age model term to SubjectAge column Weight = "Weight",# Map Weight model term to Weight column CObsBQL = "ConcBQL"), # Map BQL flag ColDef = "", PMLParametersSets = PMLParametersSets, EstArgs = specify_EngineParams(method = "QRPEM"), SimArgs = specify_SimParams(numReplicates = 1000L), Tables = list(Table(Name = "simtable1.csv", KeepSource = TRUE, VariablesList = "C", ForSimulation = TRUE)), OmegaSearchBlocks = list(c("nCl", "nV"), c("nCl2", "nV2"))) # Multiple parameter sets PMLParametersSets <- create_ModelPK(Absorption =c("Intravenous", "Weibull")) DataMapping <- list( c(ID = "Subject", time = "time", Aa = "DoseAmt", CObs = "Concentration"), c(ID = "Subject", time = "time", A1 = "DoseAmt", CObs = "Concentration") ) names(DataMapping) <- names(PMLParametersSets) write_ModelTemplateTokens( TemplateFilePath = TemplateFilePath, TokensFilePath = TokensFilePath, Description = "1 Cpt Weibull and First-Order", Author = "Certara", DataFilePath = DataFilePath, DataMapping = DataMapping, PMLParametersSets = PMLParametersSets) ``` ## See Also `specify_EngineParams()`, `specify_SimParams()`, `Table()`

write_ModelTemplateTokens function