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colfun.R
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colfun.R
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.data <- t(array(c(
0, 0, 0,
2, 31, 64,
5, 48, 97,
23, 62, 132,
33, 102, 172,
67, 147, 195,
146, 197, 222,
209, 229, 240,
253, 253, 253,
253, 219, 199,
244, 165, 130,
214, 96, 77,
178, 24, 43,
138, 14, 33,
103, 0, 31,
68, 0, 28,
0, 0, 0),
dim=c(3,17)))/255
.hsurf <- t(array(c(
60, 179, 113,
157, 210, 156,
207, 229, 174,
242, 244, 193,
230, 226, 148,
216, 211, 114,
165, 152, 72,
121, 79, 31,
81, 63, 22),
dim=c(3,9)))/255
.hsurf2 <- t(array(c(
80, 140, 30,
120, 164, 48,
140, 188, 56,
255, 250, 110,
231, 202, 62,
207, 154, 14,
183, 106, 0,
159, 58, 0,
135, 10, 0,
111, 0, 0,
87, 0, 0,
20, 0, 0),
dim=c(3,9)))/255
.gpcc <- t(array(c(
255, 252, 127,
255, 250, 0,
132, 250, 127,
22, 247, 0,
18, 194, 0,
15, 165, 0,
14, 162, 255,
9, 109, 255,
0, 39, 255,
139, 50, 222,
159, 31, 161,
189, 37, 191,
218, 43, 221,
253, 0, 255),
dim=c(3,14)))/255
.ngauges <- t(array(c(
255, 255, 255,
255, 250, 0,
132, 250, 127,
22, 247, 0,
18, 194, 0,
15, 165, 0,
14, 162, 255,
9, 109, 255,
0, 39, 255,
139, 50, 222,
159, 31, 161,
189, 37, 191,
218, 43, 221,
253, 0, 255),
dim=c(3,14)))/255
.cordex_t2m_diff <- t(array(c(
0, 0, 121,
0, 0, 255,
0, 130, 255,
100, 180, 250,
201, 227, 240,
255, 255, 255,
255, 150, 0,
255, 100, 0,
255, 0, 0,
200, 0, 0,
100, 0, 0),
dim=c(3,11)))/255
.cordex_t2m_diff_uni <- t(array(c(
255, 255, 255,
255, 200, 0,
255, 100, 0,
255, 0, 0,
200, 0, 0,
100, 0, 0),
dim=c(3,6)))/255
.cordex_t2m <- t(array(c(
160, 0, 200,
130, 0, 220,
30, 60, 255,
0, 160, 255,
0, 200, 200,
0, 210, 140,
0, 220, 0,
160, 230, 50,
230, 220, 50,
230, 175, 45,
240, 130, 40,
250, 60, 60),
dim=c(3,12)))/255
# 240, 0, 130),
# define the standard colour bars
.bluewhite <- .data[1:9,]
.redwhite <- .data[17:9,]
.greenwhite <- .data[17:9,c(2,1,3)]
.brownwhite <- .data[1:9,c(3,2,1)]
.water <- '#7caaff'
rm(.data)
.getval <- function(ind, val, predind, smooth) {
# Function to get smoothed values in the interval 0 - 1
#
# Arguments:
# ind An index specifying the spacing of the values (0 - 1)
# val The values to which a smoothed spline is fitted
# predind The location for which the smoothed spline function
# is evaluated (0 - 1)
# smooth the smoothing as 'spar' in smooth.spline
#
# Author jonas.bhend -at- gkss.de
#
fitfun <- smooth.spline(ind, val, spar=smooth)
fitval <- predict(fitfun, predind)$y
if (min(fitval) < 0) fitval <- fitval - min(fitval)
if (max(fitval) > 1) fitval <- fitval / max(fitval)
fitval
}
.colseq <- function(x, tmp, start=0, stop=1, log=FALSE, smooth=0.4){
# .colseq computes a color sequence of x rgb colors along the indicated
# colors by tmp (Attention: 'ind' is set to .spacing to match the
# colours provided by .bluewhite, etc.)
#
# Arguments:
# x Number of colors
# tmp Array of rgb values (dim=c(ncolors,3)) along which
# the color sequence is interpolated
# start/stop the range for which colours should be interpolated (0 - 1)
# log logical, defaults to FALSE, interval between start
# and stop is divided linearly
# smooth smoothing for smooth.spline in .getval
#
# Author jonas.bhend -at- gkss.de
#
ind <- seq(0,1,length=dim(tmp)[1])
predind <- seq(start, stop, length=x)
if (log & min(predind) > 0){
predind <- log(predind)
mini <- min(predind)
maxi <- max(predind)
predind <- (predind - mini)/(maxi-mini)*(stop-start) + start
}
r <- .getval(ind, tmp[,1], predind, smooth=smooth)
g <- .getval(ind, tmp[,2], predind, smooth=smooth)
b <- .getval(ind, tmp[,3], predind, smooth=smooth)
colour <- rgb(r,g,b)
colour
}
rbfun <- function(x, start=0.4, log=FALSE){
# rbfun computes a symmetric redblue color scale with x colors
#
# Arguments:
# x number of colors
# start 'Darkness' of the darkest colours (0=black, 1=white)
# log logical, defaults to FALSE, if true, colors around the
# center of the color scale get brighter
#
# Author jonas.bhend -at- gkss.de
#
numx <- floor(x/2)
if (2*numx == x){
colour <- c(.colseq((numx+1), .bluewhite, start=start, log=log)[1:numx],
rev(.colseq((numx+1), .redwhite, start=start, log=log)[1:numx]))
} else {
colour <- c(.colseq((numx+1), .bluewhite, start=start, log=log),
rev(.colseq((numx+1), .redwhite, start=start, log=log)[1:numx]))
}
colour
}
rbfuninv <- function(x, start=0.4, log=FALSE){
# rbfun computes a symmetric redblue color scale with x colors
#
# Arguments:
# x number of colors
# start 'Darkness' of the darkest colours (0=black, 1=white)
# log logical, defaults to FALSE, if true, colors around the
# center of the color scale get brighter
#
# Author jonas.bhend -at- gkss.de
#
numx <- floor(x/2)
if (2*numx == x){
colour <- c(.colseq((numx+1), .redwhite, start=start, log=log)[1:numx],
rev(.colseq((numx+1), .bluewhite, start=start, log=log)[1:numx]))
} else {
colour <- c(.colseq((numx+1), .redwhite, start=start, log=log),
rev(.colseq((numx+1), .bluewhite, start=start, log=log)[1:numx]))
}
colour
}
gbfun <- function(x, start=0.4, log=FALSE){
# rbfun computes a symmetric greenbrown color scale with x colors
#
# Arguments:
# x number of colors
# start 'Darkness' of the darkest colours (0=black, 1=white)
# log logical, defaults to FALSE, if true, colors around the
# center of the color scale get brighter
#
# Author jonas.bhend -at- gkss.de
#
numx <- floor(x/2)
if (2*numx == x){
colour <- c(.colseq((numx+1), .brownwhite, start=start, log=log)[1:numx],
rev(.colseq((numx+1), .greenwhite, start=start, log=log)[1:numx]))
} else {
colour <- c(.colseq((numx+1), .brownwhite, start=start, log=log),
rev(.colseq((numx+1), .greenwhite, start=start, log=log)[1:numx]))
}
colour
}
.soil <- c('#E6FAFF','white', 'grey', gbfun(6)[c(3:1,4:6)], .water)