View source: R/create_palette.R
create_palette | R Documentation |
processes a custom jpeg image producing a palett with a user-defined number of colours
create_palette( image_path = NA, number_of_colors = 40, type_of_variable = NA, filter_on_low_brightness = TRUE, filter_on_high_brightness = TRUE, optimize_palette = TRUE, filter_on_saturation = TRUE )
image_path |
string,default to NA. relative path to the custom image, including .jpeg extension |
type_of_variable |
string, default to 'categorical'. type of variable to be plotted with the building palette |
filter_on_low_brightness |
boolean, default to true. specifies if a filter on colours with low brigthness should be applied to enhance the palette |
filter_on_high_brightness |
boolean, default to true. specifies if a filter on colours with high brigthness should be applied to enhance the palette |
optimize_palette |
boolean, default to true. specifies if palette optimization algorithm should be applied or not |
filter_on_saturation |
boolean, default to ture. specifies if a filter on low saturation should be applied. |
number_of_colours |
integer, default to 40. number of desired colours in the final palette, as specified by the user when calling create_palette |
palette creation and optimization ist started drawing a raw palette of rgb colours from the jpeg image provided. The palette is then optimized applying the following four steps: - conversion to hsv scale in order to easily elavorate on colour order and properties. - filter on colours with a brightness lower than the first quartile of v distribution - filter on colours with a brightness higher or equal to the Tukey's outlier threshold computed on the overall v distribution - subset of the palette according to the type of variable to be plotted: a spaced sample in case of categorical variables, an interpolation between two colours close to the mode of h for continuous variables
Andrea Cirillo
create_palette("data/nascita_venere.jpg",number_of_colors = 20, type_of_variable = "categorical")
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