Read NetLogo BehaviorSpace Experiment output

read_experiment() reads NetLogo BehaviorSpace experiment output files as tidy data frames. It automatically detects the output format (Table, Spreadsheet, Lists, or Stats) and parses the data accordingly. The function also extracts metadata from the files.

Only version 2.0 (NetLogo 6.4 and later) of BehaviorSpace output files is supported.

Usage

read_experiment(file, tidy_output = TRUE)

Arguments

file: A character string specifying the path to the BehaviorSpace output CSV file.
tidy_output: (optional) A logical flag indicating whether to tidy the output data frames. If TRUE, output data frames are arranged according to tidy data principles. If FALSE, only the default transformations from read_delim() and clean_names() are applied to the output data (default: TRUE).

Value

A list containing the experiment results. The list includes the following elements, depending on the output file provided:

metadata: A list with metadata about the experiment run (present in all cases).
table: A tibble with the results of the table output.
spreadsheet: A list with the results of the spreadsheet output containing two elements:
- statistics: A tibble with data from the output first section.
- data: A tibble with data from the output second section.
lists: A tibble with the results of the lists output.
statistics: A tibble with the results of the statistics output.

Examples

file <- tempfile()

c(
  'BehaviorSpace results (NetLogo 7.0.3), "Table version 2.0"',
  paste0(
    '"/opt/NetLogo 7-0-3/models/',
    'IABM Textbook/chapter 4/Wolf Sheep Simple 5.nlogox"'
  ),
  '"Wolf Sheep Simple Model Analysis"',
  '"01/05/2026 06:37:48:683 -0300"',
  '"min-pxcor","max-pxcor","min-pycor","max-pycor"',
  '"-17","17","-17","17"',
  paste0(
    '"[run number]","number-of-sheep","number-of-wolves",',
    '"movement-cost","grass-regrowth-rate","energy-gain-from-grass",',
    '"energy-gain-from-sheep","[step]","count wolves","count sheep"'
  ),
  '"3","500","5","0.5","0.3","2","5","0","5","500"',
  '"5","500","5","0.5","0.3","2","5","0","5","500"',
  '"4","500","5","0.5","0.3","2","5","0","5","500"',
  '"6","500","5","0.5","0.3","2","5","0","5","500"',
  '"1","500","5","0.5","0.3","2","5","0","5","500"',
  '"8","500","5","0.5","0.3","2","5","0","5","500"',
  '"9","500","5","0.5","0.3","2","5","0","5","500"',
  '"2","500","5","0.5","0.3","2","5","0","5","500"'
) |>
  writeLines(file)

read_experiment(file)
#> $metadata
#> $metadata$timestamp
#> [1] "2026-01-05 09:37:48 -03"
#> 
#> $metadata$netlogo_version
#> [1] "7.0.3"
#> 
#> $metadata$output_version
#> [1] "2.0"
#> 
#> $metadata$model_file
#> [1] "Wolf Sheep Simple 5.nlogox"
#> 
#> $metadata$experiment_name
#> [1] "Wolf Sheep Simple Model Analysis"
#> 
#> $metadata$world_dimensions
#> min-pxcor max-pxcor min-pycor max-pycor 
#>       -17        17       -17        17 
#> 
#> 
#> $table
#> # A tibble: 8 × 10
#>   run_number number_of_sheep number_of_wolves movement_cost grass_regrowth_rate
#>        <dbl>           <dbl>            <dbl>         <dbl>               <dbl>
#> 1          1             500                5           0.5                 0.3
#> 2          2             500                5           0.5                 0.3
#> 3          3             500                5           0.5                 0.3
#> 4          4             500                5           0.5                 0.3
#> 5          5             500                5           0.5                 0.3
#> 6          6             500                5           0.5                 0.3
#> 7          8             500                5           0.5                 0.3
#> 8          9             500                5           0.5                 0.3
#> # ℹ 5 more variables: energy_gain_from_grass <dbl>,
#> #   energy_gain_from_sheep <dbl>, step <dbl>, count_wolves <dbl>,
#> #   count_sheep <dbl>
#>

Usage

Arguments

Value

See also

Examples