This helper function is a wrapper for findCols to extract classes from a "classInterval" object and assign colours from a palette created by colorRampPalette from the two or more colours given in the pal argument. It also returns two attributes for use in constructing a legend.

findColours(clI, pal, under="under", over="over", between="-",
 digits = getOption("digits"), cutlabels=TRUE)

Arguments

clI

a "classIntervals" object

pal

a character vector of at least two colour names; colorRampPalette is used internally to create the required number of colours

under

character string value for "under" in legend if cutlabels=FALSE

over

character string value for "over" in legend if cutlabels=FALSE

between

character string value for "between" in legend if cutlabels=FALSE

digits

minimal number of significant digits in legend

cutlabels

use cut-style labels in legend

Value

a character vector of colours with attributes: "table", a named frequency table; "palette", a character vector of colours corresponding to the specified breaks.

See also

Examples

if (!require("spData", quietly=TRUE)) { message("spData package needed for examples") run <- FALSE } else { run <- TRUE } if (run) { data(jenks71, package="spData") mypal <- c("wheat1", "red3") h5 <- classIntervals(jenks71$jenks71, n=5, style="hclust", method="complete") print(findColours(h5, mypal)) }
#> [1] "#FFE7BA" "#E6735D" "#E6735D" "#F2AD8B" "#E6735D" "#E6735D" "#E6735D" #> [8] "#E6735D" "#D9392E" "#CD0000" "#D9392E" "#D9392E" "#E6735D" "#E6735D" #> [15] "#F2AD8B" "#E6735D" "#E6735D" "#E6735D" "#E6735D" "#D9392E" "#F2AD8B" #> [22] "#E6735D" "#F2AD8B" "#F2AD8B" "#E6735D" "#F2AD8B" "#F2AD8B" "#F2AD8B" #> [29] "#F2AD8B" "#E6735D" "#F2AD8B" "#FFE7BA" "#F2AD8B" "#F2AD8B" "#F2AD8B" #> [36] "#F2AD8B" "#FFE7BA" "#FFE7BA" "#F2AD8B" "#F2AD8B" "#FFE7BA" "#F2AD8B" #> [43] "#F2AD8B" "#FFE7BA" "#F2AD8B" "#F2AD8B" "#FFE7BA" "#F2AD8B" "#FFE7BA" #> [50] "#FFE7BA" "#F2AD8B" "#F2AD8B" "#FFE7BA" "#F2AD8B" "#F2AD8B" "#FFE7BA" #> [57] "#F2AD8B" "#F2AD8B" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [64] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [71] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [78] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [85] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [92] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> [99] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#FFE7BA" #> attr(,"palette") #> [1] "#FFE7BA" "#F2AD8B" "#E6735D" "#D9392E" "#CD0000" #> attr(,"table") #> [15.57,54.81) [54.81,74.405) [74.405,105.95) [105.95,143.4) [143.4,155.3] #> 55 27 15 4 1
if (run) { print(findColours(getHclustClassIntervals(h5, k=7), mypal)) }
#> [1] "#F6C09B" "#E6735D" "#E6735D" "#EE9A7C" "#E6735D" "#E6735D" "#E6735D" #> [8] "#DD4D3E" "#D5261F" "#CD0000" "#D5261F" "#D5261F" "#DD4D3E" "#E6735D" #> [15] "#EE9A7C" "#DD4D3E" "#E6735D" "#E6735D" "#E6735D" "#D5261F" "#EE9A7C" #> [22] "#E6735D" "#EE9A7C" "#EE9A7C" "#E6735D" "#EE9A7C" "#EE9A7C" "#EE9A7C" #> [29] "#EE9A7C" "#DD4D3E" "#EE9A7C" "#F6C09B" "#EE9A7C" "#EE9A7C" "#EE9A7C" #> [36] "#EE9A7C" "#F6C09B" "#F6C09B" "#EE9A7C" "#EE9A7C" "#F6C09B" "#EE9A7C" #> [43] "#EE9A7C" "#F6C09B" "#EE9A7C" "#EE9A7C" "#F6C09B" "#EE9A7C" "#F6C09B" #> [50] "#F6C09B" "#EE9A7C" "#EE9A7C" "#F6C09B" "#EE9A7C" "#EE9A7C" "#F6C09B" #> [57] "#EE9A7C" "#EE9A7C" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" #> [64] "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" #> [71] "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" #> [78] "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" "#F6C09B" #> [85] "#F6C09B" "#F6C09B" "#F6C09B" "#FFE7BA" "#F6C09B" "#FFE7BA" "#FFE7BA" #> [92] "#F6C09B" "#F6C09B" "#FFE7BA" "#FFE7BA" "#FFE7BA" "#F6C09B" "#FFE7BA" #> [99] "#FFE7BA" "#FFE7BA" "#FFE7BA" "#F6C09B" #> attr(,"palette") #> [1] "#FFE7BA" "#F6C09B" "#EE9A7C" "#E6735D" "#DD4D3E" "#D5261F" "#CD0000" #> attr(,"table") #> [15.57,29.84) [29.84,54.81) [54.81,74.405) [74.405,90.16) [90.16,105.95) #> 10 45 27 11 4 #> [105.95,143.4) [143.4,155.3] #> 4 1
if (run) { h5Colours <- findColours(h5, mypal) plot(h5, mypal, main="Complete hierarchical clustering") legend(c(95, 155), c(0.12, 0.4), fill=attr(h5Colours, "palette"), legend=names(attr(h5Colours, "table")), bg="white") }
if (run) { h5tab <- attr(h5Colours, "table") legtext <- paste(names(h5tab), " (", h5tab, ")", sep="") plot(h5, mypal, main="Complete hierarchical clustering (with counts)") legend(c(95, 165), c(0.12, 0.4), fill=attr(h5Colours, "palette"), legend=legtext, bg="white") }