| simcol | R Documentation | 
simcol finds and shows colors 
from a palette of color candidates col_candidates that are similar 
to some target color col_target.
simcol(
  col_target,
  col_candidates = colors(),
  tol = c(25, 50, 75),
  distinct = TRUE,
  plot = TRUE
)
| col_target | A (required) target color. | 
| col_candidates | A palette of color candidates to be considered. 
Default:  | 
| tol | Numeric tolerance value(s) 
(either 1 or 3 numeric values, in the RGB range from 0 to 255).
Values are considered in the order of the RGB value rank in  | 
| distinct | Boolean: Return only visually distinct colors? 
Default:  | 
| plot | Boolean: Plot the output (using  | 
simcol returns a vector of the (named) colors or color values in 
col_candidates (set to colors() of grDevices per default) 
that are similar to the specified target color col_target. 
If plot = TRUE, simcol also visualizes the detected colors  
(by passing its result to seecol, as a side-effect).
Color similarity is defined in terms of the distance between colors' RGB values, 
which must be within the numeric tolerance threshold(s) specified by tol 
(with 0 <= tol <= 255). 
Higher tol values correspond to more permissive similarity judgments.  
If tol is a scalar, the values of all three RGB dimensions 
of col_candidates must be within the corresponding values of 
col_target to be judged as 'similar'. 
If tol contains three values, the three RGB dimension are compared 
in order of the dimensions' rank in col_target 
(i.e., the primary dimension must be within tol[1], etc.). 
Thus, providing three tol values allows for 
more fine-grained similarity matching.
A named vector of colors or color values.
seecol for plotting/seeing color palettes; 
usecol for using color palettes; 
newpal for defining new color palettes; 
grepal for finding named colors; 
shades_of to defining shades of a given color; 
ac for adjusting color transparency.
Other color functions: 
ac(),
demopal(),
grepal(),
newpal(),
seecol(),
shades_of(),
usecol()
# Basic uses:
simcol(col_target = "red")
simcol("tan", tol = 15)
simcol(Seeblau, tol = c(20, 30, 40))
simcol("blue", col_candidates = pal_unikn_pref, tol = 120)
# Fine-tuning the range of color matching:
simcol(Seeblau, tol = 30)  # = simcol(Seeblau, tol = c(30, 30, 30))
simcol(Seeblau, tol = c(20, 20, 80))
# Increasing tolerance widens range:
simcol("grey", c("white", "grey", "black"), tol = 255, distinct = FALSE, plot = FALSE)
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