Iterate over all profiles in a SoilProfileCollection, calling FUN on a single-profile SoilProfileCollection for each step.

# S4 method for SoilProfileCollection
profileApply(
  object,
  FUN,
  simplify = TRUE,
  frameify = FALSE,
  chunk.size = 100,
  column.names = NULL,
  ...
)

Arguments

object

a SoilProfileCollection

FUN

a function to be applied to each profile within the collection

simplify

logical, should the result be simplified to a vector? default: TRUE; see examples

frameify

logical, should the result be collapsed into a data.frame? default: FALSE; overrides simplify argument; see examples

chunk.size

numeric, size of "chunks" for faster processing of large SoilProfileCollection objects; default: 100

column.names

character, optional character vector to replace frameify-derived column names; should match length of colnames() from FUN result; default: NULL

...

additional arguments passed to FUN

Value

When simplify is TRUE, a vector of length nrow(object) (horizon data) or of length length(object) (site data). When simplify is FALSE, a list is returned. When frameify is TRUE, a data.frame is returned. An attempt is made to identify idname and/or hzidname in the data.frame result, safely ensuring that IDs are preserved to facilitate merging profileApply result downstream.

Examples


data(sp1)
depths(sp1) <- id ~ top + bottom

# estimate soil depth using horizon designations
profileApply(sp1, estimateSoilDepth, name='name')
#> P001 P002 P003 P004 P005 P006 P007 P008 P009 
#>   89   59   67   62   68  200  233  200  240 

# scale a single property 'prop' in horizon table
# scaled = (x - mean(x)) / sd(x)
sp1$d <- profileApply(sp1, FUN=function(x) round(scale(x$prop), 2))
plot(sp1, name='d')


# compute depth-wise differencing by profile
# note that our function expects that the column 'prop' exists
f <- function(x) { c(x$prop[1], diff(x$prop)) }
sp1$d <- profileApply(sp1, FUN=f)
plot(sp1, name='d')


# compute depth-wise cumulative sum by profile
# note the use of an anonymous function
sp1$d <- profileApply(sp1, FUN=function(x) cumsum(x$prop))
plot(sp1, name='d')


# compute profile-means, and save to @site
# there must be some data in @site for this to work
site(sp1) <- ~ group
sp1$mean_prop <- profileApply(sp1, FUN=function(x) mean(x$prop, na.rm=TRUE))

# re-plot using ranks defined by computed summaries (in @site)
plot(sp1, plot.order=rank(sp1$mean_prop))


## iterate over profiles, calculate on each horizon, merge into original SPC

# example data
data(sp1)

# promote to SoilProfileCollection
depths(sp1) <- id ~ top + bottom
#> This is already a SoilProfileCollection-class object, doing nothing.
site(sp1) <- ~ group
#> Error in eval(predvars, data, env): object 'group' not found

# calculate horizon thickness and proportional thickness
# returns a data.frame result with multiple attributes per horizon
thicknessFunction <- function(p) {
  hz <- horizons(p)
  depthnames <- horizonDepths(p)
  res <- data.frame(profile_id(p), hzID(p),
                    thk=(hz[[depthnames[[2]]]] - hz[[depthnames[1]]]))
  res$hz_prop <- res$thk / sum(res$thk)
  colnames(res) <- c(idname(p), hzidname(p), 'hz_thickness', 'hz_prop')
  return(res)
}

# list output option with simplify=F, list names are profile_id(sp1)
list.output <- profileApply(sp1, thicknessFunction, simplify = FALSE)
head(list.output)
#> $P001
#>     id hzID hz_thickness    hz_prop
#> 1 P001    1            2 0.02247191
#> 2 P001    2           12 0.13483146
#> 3 P001    3           35 0.39325843
#> 4 P001    4            8 0.08988764
#> 5 P001    5           32 0.35955056
#> 6 P001    6            0 0.00000000
#> 
#> $P002
#>     id hzID hz_thickness    hz_prop
#> 1 P002    7            5 0.08474576
#> 2 P002    8           14 0.23728814
#> 3 P002    9           14 0.23728814
#> 4 P002   10           26 0.44067797
#> 
#> $P003
#>     id hzID hz_thickness    hz_prop
#> 1 P003   11            2 0.02985075
#> 2 P003   12           11 0.16417910
#> 3 P003   13           22 0.32835821
#> 4 P003   14           18 0.26865672
#> 5 P003   15           14 0.20895522
#> 
#> $P004
#>     id hzID hz_thickness    hz_prop
#> 1 P004   16            2 0.03225806
#> 2 P004   17           11 0.17741935
#> 3 P004   18           19 0.30645161
#> 4 P004   19           11 0.17741935
#> 5 P004   20           19 0.30645161
#> 
#> $P005
#>     id hzID hz_thickness    hz_prop
#> 1 P005   21            5 0.07352941
#> 2 P005   22           25 0.36764706
#> 3 P005   23           15 0.22058824
#> 4 P005   24           23 0.33823529
#> 
#> $P006
#>      id hzID hz_thickness hz_prop
#> 1  P006   25            6   0.030
#> 2  P006   26           11   0.055
#> 3  P006   27           32   0.160
#> 4  P006   28           14   0.070
#> 5  P006   29           27   0.135
#> 6  P006   30           40   0.200
#> 7  P006   31           20   0.100
#> 8  P006   32           10   0.050
#> 9  P006   33           10   0.050
#> 10 P006   34           30   0.150
#> 

# data.frame output option with frameify=TRUE
df.output <- profileApply(sp1, thicknessFunction, frameify = TRUE)
head(df.output)
#>     id hzID hz_thickness    hz_prop
#> 1 P001    1            2 0.02247191
#> 2 P001    2           12 0.13483146
#> 3 P001    3           35 0.39325843
#> 4 P001    4            8 0.08988764
#> 5 P001    5           32 0.35955056
#> 6 P001    6            0 0.00000000

# since df.output contains idname(sp1) and hzidname(sp1),
# it can safely be merged by a left-join via horizons<- setter
horizons(sp1) <- df.output

plot(density(sp1$hz_thickness, na.rm=TRUE), main="Density plot of Horizon Thickness")


## iterate over profiles, subsetting horizon data

# example data
data(sp1)

# promote to SoilProfileCollection
depths(sp1) <- id ~ top + bottom
#> This is already a SoilProfileCollection-class object, doing nothing.
site(sp1) <- ~ group
#> Error in eval(predvars, data, env): object 'group' not found

# make some fake site data related to a depth of some importance
sp1$dep <- profileApply(sp1, function(i) {round(rnorm(n=1, mean=mean(i$top)))})

# custom function for subsetting horizon data, by profile
# keep horizons with lower boundary < site-level attribute 'dep'
fun <- function(i) {
  # extract horizons
  h <- horizons(i)
  # make an expression to subset horizons
  exp <- paste('bottom < ', i$dep, sep='')
  # subset horizons, and write-back into current SPC
  slot(i, 'horizons') <- subset(h, subset=eval(parse(text=exp)))
  # return modified SPC
  return(i)
}

# list of modified SoilProfileCollection objects
l <- profileApply(sp1, fun, simplify=FALSE)

# re-combine list of SoilProfileCollection objects into a single SoilProfileCollection
sp1.sub <- pbindlist(l)

# graphically check
par(mfrow=c(2,1), mar=c(0,0,1,0))
plot(sp1)
points(1:length(sp1), sp1$dep, col='red', pch=7)
plot(sp1.sub)