Soil Profile Information Index

A simple index of "information" content associated with individuals in a SoilProfileCollection object. Information content is quantified by number of bytes after compression via memCompress().

profileInformationIndex(
  x,
  vars,
  method = c("joint", "individual"),
  baseline = FALSE,
  numericDigits = 8,
  padNA = FALSE,
  scaleNumeric = FALSE,
  compression = "gzip"
)

Arguments

x

SoilProfileCollection object

vars

character vector of site or horizon level attributes to consider

method

character, 'individual' or 'joint' complexity

baseline

logical, compute ratio to "baseline" information content, see details

numericDigits

integer, number of significant digits to retain in numeric -> character conversion

padNA

logical, pad depths to max(x), supplied to dice(fill = padNA)

scaleNumeric

logical, scale() each numeric variable, causing "profile information" to vary based on other profiles in the collection

compression

character, compression method as used by memCompress(): 'gzip', 'bzip2', 'xz', 'none'

Value

a numeric vector of the same length as length(x) and in the same order, suitable for direct assignment to a new site-level attribute

Details

Information content via compression (gzip) is the central assumption behind this function: the values associated with a simple soil profile having few horizons and little variation between horizons (isotropic depth-functions) will compress to a much smaller size than a complex profile (many horizons, strong anisotropy). Information content is evaluated a profile at a time, over each site or horizon level attribute specified in vars. The baseline argument invokes a comparison to the simplest possible representation of each depth-function:

• numeric: replication of the mean value to match the number of horizons with non-NA values

• character or factor: replication of the most frequent value to match the number of horizons with non-NA values

The ratios computed against a "simple" baseline represent something like "information gain". Larger baseline ratios suggest more complexity (more information) associated with a soil profile's depth-functions. Alternatively, the total quantity of information (in bytes) can be determined by setting baseline = FALSE.

Author

D.E. Beaudette

Examples

# single horizon, constant value
p1 <- data.frame(id = 1, top = 0, bottom = 100, p = 5, name = 'H')

# multiple horizons, constant value
p2 <- data.frame(
  id = 2, top = c(0, 10, 20, 30, 40, 50),
  bottom = c(10, 20, 30, 40, 50, 100),
  p = rep(5, times = 6),
  name = c('A1', 'A2', 'Bw', 'Bt1', 'Bt2', 'C')
)

# multiple horizons, random values
p3 <- data.frame(
  id = 3, top = c(0, 10, 20, 30, 40, 50),
  bottom = c(10, 20, 30, 40, 50, 100),
  p = c(1, 5, 10, 35, 6, 2),
  name = c('A1', 'A2', 'Bw', 'Bt1', 'Bt2', 'C')
)

# multiple horizons, mostly NA
p4 <- data.frame(
  id = 4, top = c(0, 10, 20, 30, 40, 50),
  bottom = c(10, 20, 30, 40, 50, 100),
  p = c(1, NA, NA, NA, NA, NA),
  name = c('A1', 'A2', 'Bw', 'Bt1', 'Bt2', 'C')
)

# shallower version of p1
p5 <- data.frame(id = 5, top = 0, bottom = 50, p = 5, name = 'H')

# combine and upgrade to SPC
z <- rbind(p1, p2, p3, p4, p5)
depths(z) <- id ~ top + bottom
hzdesgnname(z) <- 'name'

z <- fillHzGaps(z)

# visual check
par(mar = c(1, 0, 3, 3))
plotSPC(z, color = 'p', name.style = 'center-center', cex.names = 0.8, max.depth = 110)

# factor version of horizon name
z$fname <- factor(z$name)

vars <- c('p', 'name')
# result is total bytes
pi <- profileInformationIndex(z, vars = vars, method = 'joint', baseline = FALSE)

text(x = 1:5, y = 105, labels = pi, cex = 0.85)
mtext('Profile Information Index (bytes)', side = 1, line = -1)