The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

Introduction to Arena2R

Pedro Nascimento de Lima

2018-10-15

Exporting Arena Report Database

This is a basic example which shows you how to get your Arena results quickly into R. The basic idea is to run different scenarios and save each of them to a separate csv file. (Yes, you could use Process Analyzer (PAN) to run all scenarios, but to my knowledge, there’s no way to get your data out of the PAN easily).

Follow these steps to get Arena simulation results to R:

Using the Shiny App

If you’re not familiar to R, you can run this command on R Console and use the example app.


runArenaApp()

After running this command, the app screen will pop up. You can upload your csv files and play around with the Confidence Interval and Scatter Plots.

Using the Package with an R Script

# Load the library:

library(arena2r)

# Define the path to your folder with Arena csv files. In my case, it's here:

my_path = system.file("extdata", package = "arena2r")

# Then, get a tidy results data.frame out of your files!
results = arena2r::get_simulation_results(my_path)

You can also play around with the arena_results dataset included in the package. To use it, follow these steps:


library(arena2r)

# Load the example dataset:
data("arena_results")

# Let's call it results
results = arena_results

knitr::kable(head(results))
Scenario Statistic Replication Value
SCENARIO 1 Entity 1.NumberIn 1 233
SCENARIO 1 Entity 1.NumberIn 2 247
SCENARIO 1 Entity 1.NumberIn 3 239
SCENARIO 1 Entity 1.NumberIn 4 261
SCENARIO 1 Entity 1.NumberIn 5 264
SCENARIO 1 Entity 1.NumberIn 6 266

After these steps, now you have a tidy data.frame with your results. Let’s get into possible visualizations. Usually, you’ll be interested in the mean confidence interval for some response variable, across scenarios.


# Plot a Statistic confidence interval across scenarios for a response variable.

arena2r::plot_confint(sim_results = results, response_variable = "Entity 1.NumberOut")

Now let’s explore the relationship between two variables, across scenarios and replications:


# Now let's plot analyse the relationship between two variables:

arena2r::plot_scatter(sim_results = results, x_variable = "Entity 1.NumberIn", y_variable = "Entity 1.NumberOut")

Finally, let’s summarise every statistic across all scenarios.


statistics_summary = arena2r::get_statistics_summary(sim_results = results, confidence = 0.95)

knitr::kable(head(statistics_summary[,1:6]))
Scenario Statistic Mean SD Min Max
SCENARIO 1 Entity 1.NumberIn 241.03333 15.773140 209.000000 276.0000
SCENARIO 1 Entity 1.NumberOut 225.13333 7.735870 205.000000 240.0000
SCENARIO 1 Entity 1.NVATime 0.00000 0.000000 0.000000 0.0000
SCENARIO 1 Entity 1.OtherTime 0.00000 0.000000 0.000000 0.0000
SCENARIO 1 Entity 1.TotalTime 11.15272 4.850762 5.161059 25.2438
SCENARIO 1 Entity 1.TranTime 0.00000 0.000000 0.000000 0.0000

I hope you enjoyed the package.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.