hz_dissolve: Dissolving horizon boundaries by grouping variables

In aqp: Algorithms for Quantitative Pedology

Dissolving horizon boundaries by grouping variables

Description

This function dissolves or combines horizons that have a common set of grouping variables. It only combines those horizon records that are sequential (e.g. share a horizon boundary). Thus, it can be used to identify discontinuities in the grouping variables along a profile and their unique depths. It is particularly useful for determining the depth to the top or bottom of horizons with a specific category, and should be simpler than previous methods that require aggregating over profiles.

Usage

hz_dissolve(
  object,
  by,
  idcol = "id",
  depthcols = c("top", "bottom"),
  collapse = FALSE,
  order = FALSE
)

dissolve_hz(
  object,
  by,
  id = "idcol",
  hztop = "top",
  hzbot = "bottom",
  collapse = FALSE,
  order = FALSE
)

Arguments

object	a data.frame
by	character: column names, to be used as grouping variables, within the object.
idcol	character: column name of the pedon ID within the object.
depthcols	a character vector of length 2 specifying the names of the horizon depths (e.g. c("top", "bottom")).
collapse	logical: indicating whether to not combine grouping variables before dissolving.
order	logical: indicating whether or not to order the object by the id, hztop, and hzbot columns.
id	deprecated and replaced with idcol.
hztop	deprecated and replaced by depthcols.
hzbot	deprecated and replaced by depthcols.

Details

This function assumes the profiles and horizons within the object follow the logic defined by checkHzDepthLogic (e.g. records are ordered sequentially by id, hztop, and hzbot and without gaps). If the records are not ordered, set the order = TRUE.

Value

A data.frame with the original idcol, by grouping variables, and non-consecutive horizon depths.

Author(s)

Stephen Roecker

See Also

hz_lag(), hz_intersect(), hz_segment() , checkHzDepthLogic()

Examples

# example 1
data(jacobs2000)
spc <- jacobs2000

spc$dep_5 <- spc$depletion_pct >=5
spc$genhz <- generalize.hz(spc$name, c("A", "E", "B", "C"), c("A", "E", "B", "C")) 
h <- horizons(spc)

test <- hz_dissolve(h, by = c("genhz", "dep_5"), idcol = "id", depthcols = c("top", "bottom"))

vars <- c("id", "top", "bottom", "genhz", "dep_5")
h[h$id == "92-1", vars]
test[test$id == "92-1", ]


# example 2
df <- data.frame(
    id = 1,
    top    = c(0, 5,  10, 15, 25, 50), 
    bottom = c(5, 10, 15, 25, 50, 100),
    hzname = c("A1",  "A2",  "E/A", "2Bt1", "2Bt2", "2C"),
    genhz  = c("A",   "A",   "E",   "2Bt",  "2Bt", "2C"),
    texcl  = c("sil", "sil", "sil", "sl",   "sl",   "s")
    )

df

hz_dissolve(df, c("genhz", "texcl"))
hz_dissolve(df, c("genhz", "texcl"), collapse = TRUE)

test <- hz_dissolve(df, "genhz")
subset(test, value == "2Bt")

aqp documentation built on Oct. 19, 2024, 5:06 p.m.