Parameter Frequency and Density Plot

Source: R/sampling_frequency.R

Frequency or density plot that depicts the sampling performed by irace across the iterations of the configuration process. For categorical parameters a frequency plot is created, while for numerical parameters a histogram and density plots are created. The plots are shown in groups of maximum 9, the parameters included in the plot can be specified by setting the param_names argument.

sampling_frequency(
  configurations,
  parameters,
  param_names = NULL,
  n = NULL,
  filename = NULL
)

Arguments

configurations

(data.frame())
Configurations in irace format. Example: iraceResults$allConfigurations.

parameters

(list())
Parameters object in irace format. If this argument is missing, the first parameter is taken as the iraceResults data generated when loading the .Rdata file created by irace and configurations=iraceResults$allConfigurations and parameters = iraceResults$scenario$parameters.

param_names

(character()) Parameters to be included in the plot. Example: c("algorithm","alpha","rho","q0","rasrank").

n

Numeric, for scenarios with large parameter sets, it selects a subset of 9 parameters. For example, n=1 selects the first 9 (1 to 9) parameters, n=2 selects the next 9 (10 to 18) parameters and so on.

filename

(character(1)) File name to save the plot, for example "~/path/example/filename.png".

Value

Frequency and/or density plot

Note

If there are more than 9 parameters, a pdf file extension is recommended as it allows to create a multi-page document. Otherwise, you can use the n argument of the function to generate the plot of a subset of the parameters.

Examples

# Either use iraceResults
iraceResults <- read_logfile(system.file(package="iraceplot", "exdata",
                                         "guide-example.Rdata", mustWork = TRUE))
sampling_frequency(iraceResults)


# \donttest{ 
sampling_frequency(iraceResults, n = 2)

#> TableGrob (2 x 1) "arrange": 2 grobs
#>   z     cells    name           grob
#> 1 1 (1-1,1-1) arrange gtable[layout]
#> 2 2 (2-2,1-1) arrange gtable[layout]
sampling_frequency(iraceResults, param_names = c("alpha"))

sampling_frequency(iraceResults, param_names = c("algorithm", "alpha", "rho", "q0", "rasrank"))

#> TableGrob (3 x 2) "arrange": 5 grobs
#>   z     cells    name           grob
#> 1 1 (1-1,1-1) arrange gtable[layout]
#> 2 2 (1-1,2-2) arrange gtable[layout]
#> 3 3 (2-2,1-1) arrange gtable[layout]
#> 4 4 (2-2,2-2) arrange gtable[layout]
#> 5 5 (3-3,1-1) arrange gtable[layout]
# }
# Or explicitly specify the configurations and parameters.
parameters <- iraceResults$scenario$parameters
sampling_frequency(iraceResults$allConfigurations, parameters)


# \donttest{ 
sampling_frequency(iraceResults$allConfigurations, parameters, n = 2)

#> TableGrob (2 x 1) "arrange": 2 grobs
#>   z     cells    name           grob
#> 1 1 (1-1,1-1) arrange gtable[layout]
#> 2 2 (2-2,1-1) arrange gtable[layout]
sampling_frequency(iraceResults$allConfigurations, parameters, 
                    param_names = c("alpha"))

sampling_frequency(iraceResults$allConfigurations, parameters, 
                    param_names = c("algorithm", "alpha", "rho", "q0", "rasrank"))

#> TableGrob (3 x 2) "arrange": 5 grobs
#>   z     cells    name           grob
#> 1 1 (1-1,1-1) arrange gtable[layout]
#> 2 2 (1-1,2-2) arrange gtable[layout]
#> 3 3 (2-2,1-1) arrange gtable[layout]
#> 4 4 (2-2,2-2) arrange gtable[layout]
#> 5 5 (3-3,1-1) arrange gtable[layout]
# }