Provides a human-readable assessment of a palette's quality, translating technical metrics into understandable language suitable for presentations or documentation.
Value
A list with class huerd_interpretation containing:
summary: Overall quality assessmentdistinctness: How distinct the colors are from each otheraccessibility: CVD accessibility assessmentrecommendations: Suggestions for improvement (if any)
Examples
pal <- generate_palette(6, progress = FALSE)
interpret_palette_quality(pal)
#>
#> ── Palette Quality Assessment ──
#>
#> This 6-color palette is highly optimized (60% of theoretical maximum).
#> Excellent - colors are highly distinct and easy to differentiate
#>
#>
#> ── Distinctness
#> Excellent - colors are highly distinct and easy to differentiate
#>
#> ── Accessibility
#> Excellent - palette is safe for most color vision deficiencies
