slice.fast(object, fm, top.down = TRUE, just.the.data = FALSE, strict = TRUE)

library(aqp)

# simulate some data, IDs are 1:20
d <- lapply(1:20, random_profile)
d <- do.call('rbind', d)

# init SoilProfileCollection object
depths(d) <- id ~ top + bottom
head(horizons(d))

# generate single slice at 10 cm
# output is a SoilProfileCollection object
s <- slice(d, 10 ~ name + p1 + p2 + p3)

# generate single slice at 10 cm, output data.frame
s <- slice(d, 10 ~ name + p1 + p2 + p3, just.the.data=TRUE)

# generate integer slices from 0 - 26 cm
# note that slices are specified by default as "top-down"
# e.g. the lower depth will always by top + 1
s <- slice(d, 0:25 ~ name + p1 + p2 + p3)
par(mar=c(0,1,0,1))
plot(s)

# generate slices from 0 - 11 cm, for all variables
s <- slice(d, 0:10 ~ .)
print(s)

# note that pct missing is computed for each slice,
# if all vars are missing, then NA is returned
d$p1[1:10] <- NA
s <- slice(d, 10 ~ ., just.the.data=TRUE)
print(s)

## Not run: 
##
## check sliced data
##

# test that mean of 1 cm slices property is equal to the
# hz-thickness weighted mean value of that property
data(sp1)
depths(sp1) <- id ~ top + bottom

# get the first profile
sp1.sub <- sp1[which(profile_id(sp1) == 'P009'), ]

# compute hz-thickness wt. mean
hz.wt.mean <- with(
  horizons(sp1.sub),
  sum((bottom - top) * prop) / sum(bottom - top)
)

# hopefully the same value, calculated via slice()
s <- slice(sp1.sub, 0:max(sp1.sub) ~ prop)
hz.slice.mean <- mean(s$prop, na.rm=TRUE)

# same?
if(!all.equal(hz.slice.mean, hz.wt.mean))
  stop('there is a bug in slice() !!!')

## End(Not run)