z02-colorSchemes: Color Schemes for Images and Heat Maps
In oompaBase: Class Unions, Matrix Operations, and Color Schemes for OOMPA

Description Usage Arguments Details Value BUGS Author(s) See Also Examples

Create a vector of N contiguous colors.

redscale(N)
greenscale(N)
bluescale(N)
blueyellow(N)
cyanyellow(N)
redgreen(N)
jetColors(N)
grayscale(N)
greyscale(N)
wheel(N, sat = 1)

`N`	an integer; the number of distinct levels in the color map
`sat`	a real number between 0 and 1; the saturation amount

The color maps that ship with R (see, for example, terrain.colors) do not include the most common color maps used in publications in the microarray literature. This collection of color maps expands the available options. The functions redscale, greenscale, and bluescale each range from pure black for low values to a pure primary color for high values. The synonyms graysale and greysale range from pure black to pure white.

The redgreen color map ranges from pure green at the low end, through black in the middle, to pure red at the high end. Although this is the most common color map used in the microarray literature, it will prove problematic for individuals with red-green color-blindness.

The blueyellow color map ranges from pure blue at the low end, through gray in the middle, to pure yellow at the high end.

The jetColors map tries to reproduce the default "jet" color map from MATLAB.

The cyanyellow color map was added to provide a divergent map that should be usable by the majority of individuals whose vision has a color deficit. It ranges from cyan (a mixture of blue and green) at the low to yellow (a mixture of red and green) at the high end. Since the vast majority of color deficits arise because an individual lacks cones for one of the three primary colors (red, green, or blue), this colormap should stil provide adequate contrasts.

A character vector 'cv' of color names. This can be used to create a user-defined color palette for subsequent graphics by 'palette(cv)' or directly in a 'col=' specification in 'par' or in graphics functions such as 'image' or 'heatmap'.

The names redgreen and blueyellow are inconsistent with respect to which color represents low values and which color represents high values. It is too late to fix this.

Kevin R. Coombes <krc@silicovore.com>

rainbow, topo.colors, terrain.colors, heat.colors, rgb, image, heatmap, palette.

data <- matrix(1:1024, nrow=1024)
image(data, col=bluescale(64))
image(data, col=redgreen(32))
image(data, col=redscale(128))
image(data, col=blueyellow(64))
image(data, col=jetColors(64))
image(data, col=grayscale(64))
image(data, col=cyanyellow(64))
rm(data) # cleanup