soil.slot.multiple: Multivariate Soil Profile Slotting

Description

Align several soil properties to a user-defined basis, with data returned in long format.

Usage

soil.slot.multiple(data, g, vars, seg_size=NA, strict=FALSE, user.fun=NULL)

Arguments

data

an input dataframe with 'id' column defining soil profiles, horizon depths must be integers

a character string or vector of length = 1, naming the column in the input dataframe to use as the grouping variable

vars

a character vector with names of columns in the input dataframe that will be aggregated

seg_size

User-degined segment size, default is 1

strict

should horizons be strictly checked for self-consistency? defaults to FALSE

user.fun

User-defined function that should accept a vector and return a scalar. This function should know how to properly deal with unexpected, NA, NULL, or Inf values and trap them accordingly.

Value

A dataframe similar to the output from soil.slot, but with depth-slice information repeated for each requested input variable.

Details

This function is a wrapper to soil.slot, that makes it simpler to "slice" several soil properties at once. The results are in long format; see examples for further processing steps that may be required.

References

http://casoilresource.lawr.ucdavis.edu/

Examples

Run this code

data(sp3)

# add new grouping factor
sp3$group <- 1
sp3$group[as.numeric(sp3$id) > 5] <- 2
sp3$group <- factor(sp3$group)

# slot several variables at once
# within each level of 'group'
# according to 5 cm vertcal increments
a <- soil.slot.multiple(sp3, g='group', vars=c('L','A', 'B'), seg_size=5)

# pre-compute intervals
a$upper <- with(a, p.mean + p.sd)
a$lower <- with(a, p.mean - p.sd)

# check the results
xyplot(
top ~ p.mean | variable, data=a, groups=groups, subscripts=TRUE, 
lower=a$lower, upper=a$upper, ylim=c(125,-5), alpha=0.5,
layout=c(3,1), scales=list(x=list(relation='free')),
panel=panel.depth_function, 
prepanel=prepanel.depth_function
)

# convert mean value for each variable into long format
a.wide <- cast(a, groups + top + bottom ~ variable, value=c('p.mean'))

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