Color

This library provides a wide array of functions for dealing with color. This includes conversion between colorspaces, measuring distance between colors, simulating color blindness, and generating color scales for graphics, among other things.

Colorspaces

What follows is a synopsis of every colorspace implemented in Color.jl. Any color value can be converted to a similar value in any other colorspace using the convert function.

E.g.

convert(RGB, HSL(270, 0.5, 0.5))

Depending on the source and destination colorspace, this may not be perfectly lossless.

RGB

The sRGB colorspace.

immutable RGB <: ColorValue
    r::Float64 # Red in [0,1]
    g::Float64 # Green in [0,1]
    b::Float64 # Blue in [0,1]
end

HSV

Hue-Saturation-Value. A common projection of RGB to cylindrical coordinates. This is also sometimes called "HSB" for Hue-Saturation-Brightness.

immutable HSV <: ColorValue
    h::Float64 # Hue in [0,360]
    s::Float64 # Saturation in [0,1]
    v::Float64 # Value in [0,1]
end

HSL

Hue-Saturation-Lightness. Another common projection of RGB to cylindrical coordinates.

immutable HSL <: ColorValue
    h::Float64 # Hue in [0,360]
    s::Float64 # Saturation in [0,1]
    l::Float64 # Lightness in [0,1]
end

XYZ

The XYZ colorspace standardized by the CIE in 1931, based on experimental measurements of color perception culminating in the CIE standard observer (see cie_color_match)

immutable XYZ <: ColorValue
    x::Float64
    y::Float64
    z::Float64
end

LAB

A percuptually uniform colorpsace standardized by the CIE in 1976. See also LUV, a similar colorspace standardized the same year.

immutable LAB <: ColorValue
    l::Float64 # Luminance in approximately [0,100]
    a::Float64 # Red/Green
    b::Float64 # Blue/Yellow
end

LUV

A percuptually uniform colorpsace standardized by the CIE in 1976. See also LAB, a similar colorspace standardized the same year.

immutable LUV <: ColorValue
    l::Float64 # Luminance
    u::Float64 # Red/Green
    v::Float64 # Blue/Yellow
end

LCHab

The LAB colorspace reparameterized using cylindrical coordinates.

immutable LCHab <: ColorValue
    l::Float64 # Luminance in [0,100]
    c::Float64 # Chroma
    h::Float64 # Hue in [0,360]
end

LCHuv

The LUV colorspace reparameterized using cylindrical coordinates.

immutable LCHuv <: ColorValue
    l::Float64 # Luminance
    c::Float64 # Chroma
    h::Float64 # Hue

LMS

Long-Medium-Short cone response values. Multiple methods of converting to LMS space have been defined. Here the CAT02 chromatic adaptation matrix is used.

immutable LMS <: ColorValue
    l::Float64 # Long
    m::Float64 # Medium
    s::Float64 # Short
end

RGB24

An RGB color represented as 8-bit values packed into a 32-bit integer.

immutable RGB24 <: ColorValue
    color::Uint32
end

Color Parsing

color(desc::String)

Parse a CSS color specification. It will parse any CSS color syntax with the exception of transparent, rgba(), hsla() (since this library has no notion of transparency), and currentColor.

All CSS/SVG named colors are supported, in addition to X11 named colors, when their definitions do not clash with SVG.

A RGB color is returned, except when the hsl() syntax is used, which returns a HSL value.

CIE Standard Observer

cie_color_match(wavelen::Real)

The CIE defines a standard observer, defining typical frequency response curve for each of the three human cones. This function returns an XYZ color corresponding to a wavelength specified in nanometers.

Chromatic Adaptation (white balance)

whitebalance{T <: ColorValue}(c::T, src_white::ColorValue, ref_white::ColorValue)

Convert a color c viewed under conditions with a given source whitepoint src_whitepoint, to appear the same under a different conditions specified by a reference whitepoint ref_white.

Color Difference

colordiff(a::ColorValue, b::ColorValue)

Evaluate the CIEDE2000 color difference formula. This gives an approximate measure of the perceptual difference between two colors to a typical viewer. A large number is returned for increasingly distinguishable colors.

Simulation of color blindness

protanopic(c::ColorValue)
deuteranopic(c::ColorValue)
tritanopic(c::ColorValue)

Three functions are provided that map colors to a reduced gamut to simulate different types of dichromacy, the loss one the three types of human photopigments. Protanopia, deuteranopia, and tritanopia are the loss of long, middle, and short wavelength photopigment, respectively.

These functions take a color and return a new, altered color is the same colorspace .

protanopic(c::ColorValue, p::Float64)
deuteranopic(c::ColorValue, p::Float64)
tritanopic(c::ColorValue, p::Float64)

Also provided are versions of these functions with an extra parameter p in [0,1], giving the degree of photopigment loss. Where 1.0 is a complete loss, and 0.0 is no loss at all.

Color Scales

distinguishable_colors(n::Integer, transform::Function, seed::ColorValue, ls::Vector{Float64}, cs::Vector{Float64}, hs::Vector{Float64})

Generate n maximally distinguishable colors in LCHab space.

The algorithm builds up the palette starting from a color seed, and choosing the other n-1 over the Cartesian product of provided possible lightness (ls), chroma (cs), and hue (hs) values.

Distinguishability is maximized with respect to the CIEDE2000 color difference formula (see colordiff), after first applying a transformation function (transform). I.e. the difference between two colors a and b is computed as colordiff(transform(a), transform(b)).

linspace(c1::ColorValue, c2::ColorValue, n=100)

Generates n colors in a linearly interpolated ramp from c1 to c2, inclusive, returning an Array of colors

weighted_color_mean(w1::Real, c1::ColorValue, c2::ColorValue)

Returns a color that is the weighted mean of c1 and c2, where c1 has a weight 0 ≤ w1 ≤ 1.

References

What perceptually uniform colorspaces are and why you should be using them:

• Ihaka, R. (2003). Colour for Presentation Graphics. In K Hornik, F Leisch, A Zeileis (eds.), Proceedings of the 3rd International Workshop on Distributed Statistical Computing, Vienna, Austria. ISSN 1609-395X
• Zeileis, A., Hornik, K., and Murrell, P. (2009). Escaping RGBland: Selecting colors for statistical graphics. Computational Statistics and Data Analysis, 53(9), 3259–3270. doi:10.1016/j.csda.2008.11.033

Functions in this library were mostly implemented according to:

• Schanda, J., ed. Colorimetry: Understanding the CIE system. Wiley-Interscience, 2007.
• Sharma, G., Wu, W., and Dalal, E. N. (2005). The CIEDE2000 color‐difference formula: Implementation notes, supplementary test data, and mathematical observations. Color Research & Application, 30(1), 21–30. doi:10.1002/col
• Ihaka, R., Murrel, P., Hornik, K., Fisher, J. C., and Zeileis, A. (2013). colorspace: Color Space Manipulation. R package version 1.2-1.
• Lindbloom, B. (2013). Useful Color Equations