| aggregateColor {aqp} | R Documentation |
Summarize soil color data, weighted by occurrence and horizon thickness.
aggregateColor(x, groups = "genhz", col = "soil_color")
x |
a |
groups |
the name of a horizon or site attribute used to group horizons, see examples |
col |
the name of a horizon-level attribute with soil color specified in hexadecimal (i.e. "#rrggbb") |
Weights are computed by:
w_i = sqrt(sum(thickness_i)) * n_i
where w_i is the weight associated with color i, thickness_i is the total thickness of all horizons associated with the color i, and n_i is the number of horizons associated with color i. Weights are computed within groups specified by groups.
A list with the following components:
scaled.data |
a list of colors and associated weights, one item for each generalized horizon label with at least one color specified in the source data |
aggregate.data |
a data.frame of weighted-mean colors, one row for each generalized horizon label with at least one color specified in the source data |
D.E. Beaudette
# load some example data
data(sp1, package='aqp')
# upgrade to SoilProfileCollection and convert Munsell colors
sp1$soil_color <- with(sp1, munsell2rgb(hue, value, chroma))
depths(sp1) <- id ~ top + bottom
site(sp1) <- ~ group
# generalize horizon names
n <- c('O', 'A', 'B', 'C')
p <- c('O', 'A', 'B', 'C')
sp1$genhz <- generalize.hz(sp1$name, n, p)
# aggregate colors over horizon-level attribute: 'genhz'
a <- aggregateColor(sp1, 'genhz')
# aggregate colors over site-level attribute: 'group'
a <- aggregateColor(sp1, 'group')
# aggregate colors over depth-slices
s <- slice(sp1, c(5, 10, 15, 25, 50, 100, 150) ~ soil_color)
s$slice <- paste0(s$top, ' cm')
a <- aggregateColor(s, 'slice')
## Not run:
##D # optionally plot with helper function
##D if(require(sharpshootR))
##D aggregateColorPlot(a)
## End(Not run)
# a more interesting example
## Not run:
##D data(loafercreek, package = 'soilDB')
##D
##D # generalize horizon names using REGEX rules
##D n <- c('Oi', 'A', 'BA','Bt1','Bt2','Bt3','Cr','R')
##D p <- c('O', '^A$|Ad|Ap|AB','BA$|Bw',
##D 'Bt1$|^B$','^Bt$|^Bt2$','^Bt3|^Bt4|CBt$|BCt$|2Bt|2CB$|^C$','Cr','R')
##D loafercreek$genhz <- generalize.hz(loafercreek$hzname, n, p)
##D
##D # remove non-matching generalized horizon names
##D loafercreek$genhz[loafercreek$genhz == 'not-used'] <- NA
##D loafercreek$genhz <- factor(loafercreek$genhz)
##D
##D a <- aggregateColor(loafercreek, 'genhz')
##D
##D # plot results with helper function
##D par(mar=c(1,4,4,1))
##D aggregateColorPlot(a, print.n.hz = TRUE)
##D
##D # inspect aggregate data
##D a$aggregate.data
## End(Not run)