Setting the working directory to where we have the Models folder if needed

#setwd("/Users/user/repos/api-r")

Importing an existing model from a .cmpx file

model <- from_cmpx("CarCosts.cmpx")
network <- model$networks[[1]]

Creating an empty csv file template with all the networks and nodes in the model

create_csv_template(model)

The dataset csv is manually prepared and filled in outside the R environment

In this example, it now includes five scenarios with different observations, and only the columns about the observed variables are kept

inputData <- "CarCosts_DataSet_Modified.csv"

Creating batch cases, this function creates a new .json model file in the working directory with dataSets representing all the rows in the input data

create_batch_cases(model, inputData)

It is possible to import the new model file back to R to work with it

model_with_cases <- from_cmpx("Car Costs_0 Model_Batch_Cases.json")

Now model_with_cases is an R model object containing both the dataSets already existing in the model and a new dataSet for each row in the input data and it is ready to be used for calculation purposes

Running the local API batch calculate function to update the model object with all the results

local_api_batch_calculate(model_with_cases)