# batch-calculate

    library(agena.ai)

# 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)