FCE_GRID_INPUT_TEXT <- '<p align="justify">Set the range and the granularity of the results.
The table will show function values that have been reached within evenly
spaced evaluation budgets.</p>'
RT_TAR_LABEL <- HTML('<p>\\(B:\\) Budget value</p>')
RT_MIN_LABEL <- HTML('<p>\\(B_{\\text{min}}:\\) Smallest budget value</p>')
RT_MAX_LABEL <- HTML('<p>\\(B_{\\text{max}}:\\) Largest budget value</p>')
RT_STEP_LABEL <- HTML('<p>\\(\\Delta B:\\) Granularity (step size)</p>')
F_TAR_LABEL <- HTML('Target function value <p>\\(f_{\\text{target}}:\\)</p>')
F_MIN_LABEL <- HTML('<p>\\(f_{\\text{min}}:\\) Smallest target value</p>')
F_MAX_LABEL <- HTML('<p>\\(f_{\\text{max}}:\\) Largest target value</p>')
F_STEP_LABEL <- HTML('<p>\\(\\Delta f:\\) Granularity (step size)</p>')
Pdsc_info <- "Practical Deep Comparison uses this
as a threshold parameter to determine when two performance measure values are
equal or different from a practical point of view.
Since the practical significance
is handled with preprocessing using the predefined threshold in sequential order of
the obtained runs, to make more robust analysis a Monte-Carlo simulation is required."
Pdsc_mc_info <- "Practical Deep Comparison uses this
to determine the number of monte-carlo simulations to perform.
The Monte-Carlo simulation involves preprocessing done with different orders of the
independent runs before comparing the distribution of the data.
This only has effect if threshold for practical significance > 0"
HTML_P <- function(s) HTML(paste0('<p align="left" style="font-size:120%;">', s, '</p>'))
alg_select_info <- "Use this option to select which IDs to plot.
This will have an effect the dowloaded plot,
as opposed to using the legend-entries to show or hide algorithms.
The attributes which define the ID can be changed in the settings."
custom_icon <- function(name = NULL){
if (is.null(name)) name <- "info-circle"
htmltools::tags$a(shiny::icon(name = name), href = "javascript:void(0);")
}
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