diff --git a/articles/Introduction-to-SoilProfileCollection-Objects.html b/articles/Introduction-to-SoilProfileCollection-Objects.html index 5fb655b8..07ea4c58 100644 --- a/articles/Introduction-to-SoilProfileCollection-Objects.html +++ b/articles/Introduction-to-SoilProfileCollection-Objects.html @@ -258,7 +258,6 @@

Rapid Templating hz.depths = TRUE )

-
#> [1] 0.1223958
@@ -362,7 +361,7 @@

Horizon and Site Data

Assignment of new data to existing or new attributes can proceed as follows.

-
+
 
#>  [1] 21 27 32 55 25 34  3 15 27 32 25 31 33 13 21 23 15 17 12 19 14 14 22 25 40 51 67 24 25 32

-
+
 sp4$elevation # vector of simulated elevation (site data)

 
#>  [1]  789.9935 1038.2976  634.4105  999.1643 1093.2329 1172.2617  726.7274  962.9012  963.3701
 #> [10]  957.5942

-
+
 # unit-length value explicitly targeting site data
 site(sp4)$collection_id <- 1
 
@@ -394,7 +393,7 @@ 
Horizon and Site DataSoilProfileCollection.

-
+
 # extract horizon data to data.frame
 h <- horizons(sp4)
 
@@ -457,7 +456,7 @@ 
Diagnostic Horizons
+
 dh <- data.frame(
   id = 'colusa',
   kind = 'argillic',
@@ -497,7 +496,7 @@ 
Root Restrictive FeaturesThe example data sp4 does not describe the restrictive
 features, so we will simulate some at the bottom of each profile +
 20cm.

-
+
 # get the depth of each profile
 rf.top <- profileApply(sp4, max)
 rf.bottom <- rf.top + 20
@@ -536,7 +535,7 @@ 
Object Metadata
 
SoilProfileCollection metadata can be extracted and set using the
 metadata() and metadata<- methods.

-
+
 # metadata structure
 str(metadata(sp4))

 
#> List of 6
@@ -546,7 +545,7 @@ 
Object Metadata#>  $ aqp_hztexcl     : chr ""
 #>  $ depth_units     : chr "cm"
 #>  $ stringsAsFactors: logi FALSE

-
+
 # alter the depth unit metadata attribute
 depth_units(sp4) <- 'inches' # units are really 'cm'
 
@@ -567,7 +566,7 @@ 
Object Metadata#>  $ describer       : chr "DGM"
 #>  $ date            : Date[1:1], format: "2009-01-01"
 #>  $ citation        : chr "McGahan, D.G., Southard, R.J, Claassen, V.P. 2009. Plant-Available Calcium Varies Widely in Soils on Serpentini"| __truncated__

-
@@ -582,7 +581,7 @@ 
Spatial Data
+
 # generate some fake coordinates as site level attributes
 sp4$x <- rnorm(n = length(sp4), mean = 354000, sd = 100)
 sp4$y <- rnorm(n = length(sp4), mean = 4109533, sd = 100)
@@ -603,14 +602,14 @@ 
Spatial Data#>  [8,] 354057.8 4109801
 #>  [9,] 354011.8 4109497
 #> [10,] 353808.8 4109554

-
+
 # get/set spatial reference system using prj()<-
 prj(sp4) <- '+proj=utm +zone=11 +datum=NAD83'
 
 # return CRS information
 prj(sp4)

 
#> [1] "+proj=utm +zone=11 +datum=NAD83"

-
+
 # extract spatial data + site level attributes in new spatial object
 sp4.sp <- as(sp4, 'SpatialPointsDataFrame')
 sp4.sf <- as(sp4, 'sf')

@@ -630,12 +629,12 @@ 
Validity and Horizon Logichttps://github.com/ncss-tech/aqp/issues

 
checkSPC() returns TRUE for a SoilProfileCollection that
 contains all slots defined in the class prototype.

-
+
 checkSPC(sp4)

 
spc_in_sync() is used as the validity method for the
 SoilProfileCollection, it determines if some reordering of the horizon
 data relative to the unique profile ID / site order has occurred.

-
+
 
#>   nSites relativeOrder valid
 #> 1   TRUE          TRUE  TRUE

@@ -643,7 +642,7 @@ 
Validity and Horizon Logic
-
+
 
checkHzDepthLogic() has the ability to perform logical
 tests on whole profiles or individual horizons. Four different tests are
@@ -654,7 +653,7 @@ 
Validity and Horizon Logic
missing (NA) top or bottom depth

 
  • gap or overlap between adjacent horizons
    • 
 
-
    +
 
    #>                id valid depthLogic sameDepth missingDepth overlapOrGap
 #> 1          colusa  TRUE      FALSE     FALSE        FALSE        FALSE
@@ -667,7 +666,7 @@ 
    Validity and Horizon Logic#> 8          shasta  TRUE      FALSE     FALSE        FALSE        FALSE
 #> 9  shasta-trinity  TRUE      FALSE     FALSE        FALSE        FALSE
 #> 10         tehama  TRUE      FALSE     FALSE        FALSE        FALSE
    
-
    +
     checkHzDepthLogic(sp4, byhz = TRUE)
    
 
    #>                id top bottom valid hzID depthLogic sameDepth missingDepth overlapOrGap
 #> 1          colusa   0      3  TRUE    1      FALSE     FALSE        FALSE           NA
@@ -708,7 +707,7 @@ 
    Coerciondata.frame, list and
 SpatialPointsDataFrame (when spatial slot has been set
 up):
    
-
    +
     # check our work by viewing the internal structure
 str(sp4)
 
@@ -744,7 +743,7 @@ 
    ProfilesUsing the i index, select one or more profiles by numeric
 index. An index greater than the number of profiles will return an empty
 SoilProfileCollection object.
    
-
    +
     # explicit string matching
 idx <- which(sp4$group == 'A')
 
@@ -758,7 +757,7 @@ 
    Profilessp4[idx, ]
    
 
    In an interactive session, it is often simpler to use
 subset() directly:
    
-
    +
     subset(sp4, group == 'A')
 subset(sp4, elevation < 1000)
 subset(sp4, grepl('shasta', id, ignore.case = TRUE))
    
@@ -769,7 +768,7 @@ 
    Horizons by Index
    +
     sp4[, 2]
    
 
    
 
    
@@ -779,7 +778,7 @@ 
    Horizons by Keyword
    +
     sp4[, , .FIRST]
 sp4[, , .LAST]
    
 
    
@@ -794,7 +793,7 @@ 
    Splitting, Dupli
 SoilProfileCollection. Manually subset the example data
 into 3 pieces, compile into a list, and then combine back
 together.
    
-
    +
     # subset data into chunks
 s1 <- sp4[1:2, ]
 s2 <- sp4[4, ]
@@ -809,7 +808,7 @@ 
    Splitting, Dupli
 with different internal structure. The final object will contain the all
 site and horizon columns from the inputs, possibly creating sparse
 tables. IDs and horizon depth names are taken from the first object.
    
-
    +
     # sample data as data.frame objects
 data(sp1)
 data(sp3)
@@ -854,7 +853,7 @@ 
    Splittingcombine() is split():
 subsets of the SoilProfileCollection are split into list
 elements, each containing a new SoilProfileCollection.
    
-
    +
     # continuing from above
 # split subsets of x into a list of SoilProfileCollection objects using site-level attribute 'g'
 res <- split(x, 'g')
@@ -866,17 +865,16 @@ 
    Duplication
    +
     d <- duplicate(sp4[1, ], times = 8)
 par(mar = c(0, 2, 0, 1))
 plotSPC(d, color = 'ex_Ca_to_Mg')
    
 
    
-
    #> [1] 0.5067568
    
 
    
 
    
 
    Selecting Unique Profiles
 
    
-
    +
     # an example soil profile  
 x <- data.frame(
   id = 'A',
@@ -908,19 +906,16 @@ 
    Selecting Unique Profiles        name.style = 'center-center',
         width = 0.15)
    
 
    
-
    #> [1] 0.03216912
    
-
    +
     # "uniqueness" is a function of variables selected to consider
 plotSPC(unique(x.sim, vars = c('top', 'bottom')),
         name.style = 'center-center')
    
 
    
-
    #> [1] 0.1617973
    
-
    +
     plotSPC(unique(x.sim, vars = c('name')),
         name.style = 'center-center',
         width = 0.15)
    
 
    
-
    #> [1] 0.03235947
    
 
    
 
    
 
    
@@ -954,39 +949,39 @@ 
    Making AdjustmentsexplainPlotSPC() function is helpful for adjusting
 some of the more obscure arguments to plotSPC().
    
 
    A basic plot with debugging information overlaid:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name')
    
 
    
 
    Make sketches wider:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', width = 0.3)
    
 
    
 
    Move soil surface at 0cm “down” 5cm:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', y.offset = 5)
    
 
    
 
    Move soil surface at 0cm “up” 10cm; useful for sketches of shallow
 profiles:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', y.offset = -10)
    
 
    
 
    Scale depths by 50%:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', scaling.factor = 0.5)
    
 
    
 
    A graphical explanation of how profiles are re-arranged via
 plot.order argument:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', plot.order = length(sp4):1)
    
 
    
 
    Leave room for an additional 2 profile sketches:
    
-
    +
     par(mar = c(4, 3, 2, 2))
 explainPlotSPC(sp4, name = 'name', n = length(sp4) + 2)
    
 
    
@@ -1009,30 +1004,27 @@ 
    Small SoilProfileCollections
    +
     data(osd)
 x <- osd
    
 
    Using 5x6 inch output device:
    
-
    +
     par(mar = c(0, 2, 0, 4), xpd = NA)
 plotSPC(x[1, ], cex.names = 1)
    
 
    
-
    #> [1] 0.2330044
    
 
    Using 7x6 inch output device, slight adjustments to
 width usually required:
    
-
    +
     # set margins and turn off clipping
 par(mar = c(0, 2, 0, 4), xpd = NA)
 plotSPC(x[1:2, ], cex.names = 1, width = 0.25)
    
 
    
-
    #> [1] 0.3259698
    
 
    Using 8x6 inch output device, slight adjustments to are usually
 required:
    
-
    +
     par(mar = c(0, 2, 0, 4), xpd = NA)
 plotSPC(x, cex.names = 1, depth.axis = list(line = -0.1), width = 0.3)
    
 
    
-
    #> [1] 0.3661152
    
 
    
 
    
 
    
@@ -1040,7 +1032,7 @@ 
    Horizon Depth Labeling
 
    Horizon depths can be labeled for each profile as an alternative to a
 single depth axis.
    
-
    +
     par(mar = c(0, 0, 1, 1))
 plotSPC(
   x,
@@ -1052,7 +1044,6 @@ 
    Horizon Depth Labeling  hz.depths.offset = 0.08
 )
    
 
    
-
    #> [1] 0.3191774
    
 
    As of aqp version 1.41, it is possible to “fix” overlapping horizon
 depth labels with the new fixLabelCollisions argument. This
 approach to labeling depths works best when moving horizon designations
@@ -1069,7 +1060,7 @@ 
    Relative Horizontal Positioningplot.order but be careful:
 relative.pos must be specified in the final
 ordering of profiles. See ?plotSPC for details.
    
-
    +
     par(mar = c(4, 3, 2, 2))
 pos <- jitter(1:length(sp4))
 explainPlotSPC(sp4, name = 'name', relative.pos = pos)
    
@@ -1077,7 +1068,7 @@ 
    Relative Horizontal PositioningRelative positioning works well when the vector of positions is close
 to the default spacing along an integer sequence, but not when positions
 are closer than the width of a profile sketch.
    
-
    +
     par(mar = c(4, 3, 2, 2))
 pos <- c(1, 1.2, 3, 4, 5, 5.2, 7, 8, 9, 10)
 explainPlotSPC(sp4, name = 'name', relative.pos = pos)
    
@@ -1089,7 +1080,7 @@ 
    Relative Horizontal Positioningset.seed().
    
-
    +
     par(mar = c(4, 3, 2, 2))
 new.pos <- fixOverlap(pos)
 explainPlotSPC(sp4, name = 'name', relative.pos = new.pos)
    
@@ -1097,7 +1088,7 @@ 
    Relative Horizontal PositioningThere are several parameters available for optimizing horizontal
 position in the presence of overlap. See ?fixOverlap for
 details and further examples.
    
-
    +
     par(mar = c(4, 3, 2, 2))
 new.pos <- fixOverlap(pos, thresh = 0.7)
 explainPlotSPC(sp4, name = 'name', relative.pos = new.pos)
    
@@ -1110,16 +1101,15 @@ 
    Thematic Sketches
    +
     par(mar = c(0, 0, 3, 0))
 plotSPC(sp4,
         name = 'name',
         color = 'clay',
         col.label = 'Clay Content (%)')
    
 
    
-
    #> [1] 0.4882812
    
 
    Use a different set of colors:
    
-
    +
     par(mar = c(0, 0, 3, 0)) 
 plotSPC(
   sp4,
@@ -1129,11 +1119,10 @@ 
    Thematic Sketches= 'Clay Content (%)'
 )
    
 
    
-
    #> [1] 0.4882812
    
 
    Categorical properties can also be used to make a thematic sketch.
 Colors are interpolated when there are more classes than colors provided
 by col.palette:
    
-
    +
     par(mar = c(0, 0, 3, 0))
 plotSPC(
   sp4,
@@ -1143,10 +1132,9 @@ 
    Thematic Sketches= 'Original Horizon Name'
 )
    
 
    
-
    #> [1] 0.4882812
    
 
    Try with generalized
 horizon labels:
    
-
    +
     par(mar = c(0, 0, 3, 0)) 
 
 # generalize horizon names into 3 groups
@@ -1160,21 +1148,19 @@ 
    Thematic Sketches= 'Generalized Horizon Name'
 )
    
 
    
-
    #> [1] 0.4882812
    
 
    Horizon-level attributes that represent a volume fraction
 (e.g. coarse-fragment percentage) can be added to an existing figure.
 See ?addVolumeFraction for adding layers to an existing
 plot based on these attributes.
    
-
    +
     par(mar = c(0, 0, 3, 0)) 
 # convert coarse rock fragment proportion to percentage
 sp4$frag_pct <- sp4$CF * 100
 
 # label horizons with fragment percent
-plotSPC(sp4, name = 'frag_pct', color = 'frag_pct')
    
-
    #> [1] 0.4882812
    
-
    -# symbolize volume fraction data
+plotSPC(sp4, name = 'frag_pct', color = 'frag_pct')
+
+# symbolize volume fraction data
 addVolumeFraction(sp4, colname = 'frag_pct')
    
 
    
 
    
@@ -1185,7 +1171,7 @@ 
    Depth IntervalsdepthOf()
 function. See ?depthOf for more details.
    
-
    +
     # extract top/bottom depths associated with all A horizons
 tops <- minDepthOf(sp4, pattern = '^A', hzdesgn = 'name', top = TRUE)
 bottoms <- maxDepthOf(sp4, pattern = '^A', hzdesgn = 'name', top = FALSE)
@@ -1208,21 +1194,19 @@ 
    Depth Intervals#> 8          shasta   0      3
 #> 9  shasta-trinity   0     12
 #> 10         tehama   0      3
    
-
    +
     par(mar = c(0, 0, 0, 0))
-plotSPC(sp4)
    
-
    #> [1] 0.4882812
    
-
    -# annotate A horizon depth interval with brackets
+plotSPC(sp4)
+
+# annotate A horizon depth interval with brackets
 addBracket(a, col = 'red', offset = -0.4)
    
 
    
 
    Add labels:
    
-
    +
     par(mar = c(0, 0, 0, 0))
-plotSPC(sp4, name = 'name')
    
-
    #> [1] 0.4882812
    
-
    -# addBracket() looks for a column `label`; add a ID for each bracket
+plotSPC(sp4, name = 'name')
+
+# addBracket() looks for a column `label`; add a ID for each bracket
 a$label <- site(sp4)$id
 
 # note that depth brackets "knows which profiles to use" via profile ID
@@ -1236,38 +1220,30 @@ 
    Depth Intervals
    
 
    It is possible to arrange profile sketches by site-level grouping
 variable:
    
-
    +
     par(mar = c(0, 0, 0, 0)) 
-groupedProfilePlot(sp4, groups = 'group')
    
-
    #> [1] 0.4882812
    
-
    -addBracket(a, col = 'red', offset = -0.4)
    
+groupedProfilePlot(sp4, groups = 'group')
+addBracket(a, col = 'red', offset = -0.4)
    
 
    
 
    There need not be brackets for all profiles in a collection:
    
-
    +
     par(mar = c(0, 0, 0, 0))
 a.sub <- a[1:4,]
-groupedProfilePlot(sp4, groups = 'group')
    
-
    #> [1] 0.4882812
    
-
    -addBracket(a.sub, col = 'red', offset = -0.4)
    
+groupedProfilePlot(sp4, groups = 'group')
+addBracket(a.sub, col = 'red', offset = -0.4)
    
 
    
 
    When bottom depths are missing an arrow is used:
    
-
    +
     a$bottom <- NA
 par(mar = c(0, 0, 0, 0))
-groupedProfilePlot(sp4, groups = 'group')
    
-
    #> [1] 0.4882812
    
-
    -addBracket(a, col = 'red', offset = -0.4)
    
+groupedProfilePlot(sp4, groups = 'group')
+addBracket(a, col = 'red', offset = -0.4)
    
 
    
 
    Manually define bottom depth:
    
-
    +
     par(mar = c(0, 0, 0, 0))
-groupedProfilePlot(sp4, groups = 'group')
    
-
    #> [1] 0.4882812
    
-
    -addBracket(
+groupedProfilePlot(sp4, groups = 'group')
+addBracket(
   a,
   col = 'red',
   label.cex = 0.75,
@@ -1276,12 +1252,11 @@ 
    Depth Intervals)
    
 
    
 
    Further customization of brackets:
    
-
    +
     par(mar = c(0, 0, 0, 0))
-plotSPC(sp4, max.depth = 75)
    
-
    #> [1] 0.4882812
    
-
    -# copy root-restricting features
+plotSPC(sp4, max.depth = 75)
+
+# copy root-restricting features
 a <- restrictions(sp4)
 
 # add a label: restrictive feature 'kind'
@@ -1314,7 +1289,7 @@ 
    SVG Output for Use in Page Layo
 with most software titles. WMF output is compatible with MS Office tools
 and can be written with the win.metafile() function.
    
 
-
    +
     # library(svglite)
 # svglite(filename = 'e:/temp/fig.svg', width = 7, height = 6, pointsize = 12)
 # 
@@ -1334,7 +1309,7 @@ 
    Iterating Over Profiles in a Co
 for each profile in the collection, typically returning a single value
 per profile. In this case, the ordering of the results would match the
 ordering of values in the site level attribute table.
    
-
    +
     # max() returns the depth of a soil profile
 sp4$soil.depth <- profileApply(sp4, FUN = max)
 
@@ -1354,7 +1329,7 @@ 
    Iterating Over Profiles in a Co
 to create new horizon-level attributes. For example, the change in clay
 content by horizon depth (delta.clay, below) could be
 calculated as:
    
-
    +
     # save as horizon-level attribute
 sp4$delta.clay <- profileApply(sp4, FUN = function(i) c(NA, diff(i$clay)))
 
@@ -1377,7 +1352,7 @@ 
    Iterating Over Profiles in a Co
 custom function can be combined into a single
 SoilProfileCollection object via
 combine().
    
-
    +
     # compute hz-thickness weighted mean exchangeable-Ca:Mg
 wt.mean.ca.mg <- function(i) {
   # use horizon thickness as a weight
@@ -1394,7 +1369,7 @@ 
    Iterating Over Profiles in a Co
 
    In this case profiles are ordered based on the horizon-thickness
 weighted mean, exchangeable Ca:Mg values. Horizons are colored by
 exchangeable Ca:Mg values.
    
-
    +
     # plot the data using our new order based on Ca:Mg weighted average
 # the result is an index of rank 
 new.order <- order(sp4$wt.mean.ca.to.mg)
@@ -1403,10 +1378,9 @@ 
    Iterating Over Profiles in a Co
 plotSPC(sp4,
         name = 'name',
         color = 'ex_Ca_to_Mg',
-        plot.order = new.order)
    
-
    #> [1] 0.4882812
    
-
    -# add an axis labeled with the sorting criteria
+        plot.order = new.order)
+
+# add an axis labeled with the sorting criteria
 axis(1, at = 1:length(sp4), labels = round(sp4$wt.mean.ca.to.mg, 3), cex.axis = 0.75)
 mtext(1, line = 2.25, text = 'Horizon Thickness Weighted Mean Ex. Ca:Mg', cex = 0.75)
    
 
    
@@ -1421,7 +1395,7 @@ 
    Slicing Horizons: dice()dice() function. The
 slicing structure and variables of interest are defined via formula
 notation:
    
-
    +
     # slice select horizon-level attributes
 seq ~ var.1 + var.2 + var.3 + ...
 # slice all horizon-level attributes
@@ -1435,7 +1409,7 @@ 
    Slicing Horizons: dice()
    +
     # resample to 1cm slices
 s <- dice(sp4, fm = 0:15 ~ sand + silt + clay + name + ex_Ca_to_Mg)
 
@@ -1444,15 +1418,14 @@ 
    Slicing Horizons: dice()#> [1] "SoilProfileCollection"
 #> attr(,"package")
 #> [1] "aqp"
    
-
    +
     # plot sliced data
 par(mar = c(0, 0, 3, 0)) # tighten figure margins
 plotSPC(s, color = 'ex_Ca_to_Mg')
    
 
    
-
    #> [1] 0.4882812
    
 
    Once soil profile data have been sliced, it is simple to extract
 “chunks” of data by depth interval via [-subsetting:
    
-
    +
     # slice from 0 to max depth in the collection
 s <- dice(sp4, fm= 0:max(sp4) ~ sand + silt + clay + name + ex_Ca_to_Mg)
 
@@ -1469,43 +1442,39 @@ 
    Slicing Horizons: dice()Ragged Extraction: glom()
 
    
 
    Select all horizons that overlap the interval of 5-15cm:
    
-
    +
     # truncate to the interval 5-15cm
 clods <- glom(sp4, z1 = 5, z2 = 15)
 
 # plot outlines of original profiles
 par(mar = c(0, 0, 3, 1.5)) 
-plotSPC(sp4, color = NA, name = NA, print.id = FALSE, depth.axis = FALSE, lwd = 0.5)
    
-
    #> [1] 0.5073052
    
-
    -# overlay glom() depth criteria
+plotSPC(sp4, color = NA, name = NA, print.id = FALSE, depth.axis = FALSE, lwd = 0.5)
+
+# overlay glom() depth criteria
 rect(xleft = 0.5, ybottom = 15, xright = length(sp4) + 0.5, ytop = 5, lty = 2)
 
 # add SoilProfileCollection with selected horizons
 plotSPC(clods, add = TRUE, cex.names = 0.6, name = 'name', color = 'ex_Ca_to_Mg', name.style = 'center-center')
    
 
    
-
    #> [1] 0.5999729
    
 
    
 
    
 
    Truncation: trunc()
 
    
 
    Truncate the SPC to the interval of 5-15cm:
    
-
    +
     # truncate to the interval 5-15cm
 sp4.truncated <- trunc(sp4, 5, 15)
 
 # plot outlines of original profiles
 par(mar = c(0, 0, 3, 1.5)) 
-plotSPC(sp4, color = NA, name = NA, print.id = FALSE, lwd = 0.5)
    
-
    #> [1] 0.5073052
    
-
    -# overlay truncation criteria
+plotSPC(sp4, color = NA, name = NA, print.id = FALSE, lwd = 0.5)
+
+# overlay truncation criteria
 rect(xleft = 0.5, ybottom = 15, xright = length(sp4) + 0.5, ytop = 5, lty = 2)
 
 # add truncated SoilProfileCollection
 plotSPC(sp4.truncated, depth.axis = FALSE, add = TRUE, cex.names = 0.6, name = 'name', color = 'ex_Ca_to_Mg', name.style = 'center-center')
    
 
    
-
    #> [1] 0.5999729
    
 
    
 
    
 
    Change of Support
@@ -1539,7 +1508,7 @@ 
    Aggregation over “slabs”c(0, 5, 10, 50, 100)): data are aggregated over the
 depths spanning 0–5, 5–10, 10–50, 50–100 units
 
-
    +
     # aggregate a couple of the horizon-level attributes, 
 # across the entire collection, 
 # from 0--10 cm
@@ -1555,7 +1524,7 @@ 
    Aggregation over “slabs”#> 1     sand            1 47.63                     1   0     10
 #> 2     silt            1 31.15                     1   0     10
 #> 3     clay            1 21.11                     1   0     10
    
-
    +
     # again, this time within groups defined by a site-level attribute:
 slab(
   sp4,
@@ -1571,7 +1540,7 @@ 
    Aggregation over “slabs”#> 4     silt     B 30.78                     1   0     10
 #> 5     clay     A 20.30                     1   0     10
 #> 6     clay     B 21.92                     1   0     10
    
-
    +
     # again, this time over several depth ranges
 slab(
   sp4,
@@ -1590,7 +1559,7 @@ 
    Aggregation over “slabs”#> 7     clay            1 21.11000             1.0000000   0     10
 #> 8     clay            1 28.10687             0.8733333  10     25
 #> 9     clay            1 36.26966             0.5933333  25     40
    
-
    +
     # again, this time along 1-cm slices, computing quantiles
 agg <- slab(sp4, fm = ~ Mg + Ca + ex_Ca_to_Mg + CEC_7 + clay)
 
@@ -1603,7 +1572,7 @@ 
    Aggregation over “slabs”#> 4       Mg            1 6.195 13.175 21.05 25.050 30.73                     1   3      4
 #> 5       Mg            1 6.195 13.175 21.05 25.050 30.73                     1   4      5
 #> 6       Mg            1 6.195 13.175 21.05 26.250 31.72                     1   5      6
    
-
    +
     # plot median +/i bounds defined by the 25th and 75th percentiles
 # this is lattice graphics, syntax is a little rough
 xyplot(top ~ p.q50 | variable, data = agg, ylab = 'Depth', 
@@ -1624,7 +1593,7 @@ 
    Aggregation over “slabs”
    
 
    Depth-wise aggregation can be useful for visual evaluation of
 multivariate similarity among groups of profiles.
    
-
    +
     # processing the "napa" and tehama profiles
 idx <- which(profile_id(sp4) %in% c('napa', 'tehama'))
 napa.and.tehama <- slab(sp4[idx,], fm = ~ Mg + Ca + ex_Ca_to_Mg + CEC_7 + clay)
@@ -1658,7 +1627,7 @@ 
    Aggregation over “slabs”
    
 
    The following example is based on a set of 9 randomly generated
 profiles, re-aligned to the Global Soil Map (GSM) standard depths.
    
-
    +
     library(data.table)
 library(RColorBrewer)
 
@@ -1699,7 +1668,7 @@ 
    Aggregation over “slabs”A simple graphical comparison of the original and re-aligned soil
 profile data, after converting slab() result from long
 -> wide format with {data.table} dcast():
    
-
    +
     # reshape to wide format
 # this scales to > 1 aggregated variables
 d.gsm.pedons <- data.table::dcast(
@@ -1718,14 +1687,10 @@ 
    Aggregation over “slabs”
 # compare original and aggregated
 par(mar = c(1, 0, 3, 3), mfrow = c(2, 1))
-plotSPC(d, color = 'p1')
    
-
    #> [1] 0.06138393
    
-
    -mtext('original depths', side = 2, line = -1.5)
-plotSPC(d.gsm.pedons, color = 'p1')
    
-
    #> [1] 0.06138393
    
-
    -mtext('GSM depths', side = 2, line = -1.5)
    
+plotSPC(d, color = 'p1')
+mtext('original depths', side = 2, line = -1.5)
+plotSPC(d.gsm.pedons, color = 'p1')
+mtext('GSM depths', side = 2, line = -1.5)
    
 
    
 
    Note that re-aligned data may not represent reality (and should
 therefore be used with caution) when the original soil depth is
@@ -1733,7 +1698,7 @@ 
    Aggregation over “slabs”contributing_fraction metric returned by
 slab() can be useful for assessing how much real
 data were used to generate the new set of re-aligned data.
    
-
    +
     # reshape to wide format
 d.gsm.pedons.2 <- data.table::dcast(
   data.table(d.gsm), 
@@ -1746,10 +1711,8 @@ 
    Aggregation over “slabs”
 # compare original and aggregated
 par(mar = c(1, 0, 3, 3), mfrow = c(2, 1))
-plotSPC(d.gsm.pedons, name = '', color = 'p1')
    
-
    #> [1] 0.06138393
    
-
    -mtext('GSM depths', side = 2, line = -1.5)
+plotSPC(d.gsm.pedons, name = '', color = 'p1')
+mtext('GSM depths', side = 2, line = -1.5)
 
 plotSPC(
   d.gsm.pedons.2,
@@ -1757,10 +1720,8 @@ 
    Aggregation over “slabs”  color = 'p1',
   col.label = 'Contributing Fraction',
   col.palette = RColorBrewer::brewer.pal(10, 'Spectral')
-)
    
-
    #> [1] 0.06138393
    
-
    -mtext('GSM depths', side = 2, line = -1.5)
    
+)
+mtext('GSM depths', side = 2, line = -1.5)
    
 
    
 
    
 
    
@@ -1778,7 +1739,7 @@ 
    Pair-Wise Dissimilarity: NCSP()See the function
 manual page and this paper for
 details.
    
-
    +
     library(cluster)
 library(sharpshootR)
 
@@ -1805,7 +1766,7 @@ 
    Pair-Wise Dissimilarity: NCSP()#> shasta           17.2  13.6   8.7     17.6      17.6 34.8       23.3                      
 #> shasta-trinity    6.4  16.9  22.3      9.6      17.0 30.9       28.3   23.3               
 #> tehama           30.1  23.9  29.2     28.6      20.8  9.0       15.3   32.7           29.2
    
-
    +
     # visualize dissimilarity matrix via divisive hierarchical clustering
 d.diana <- diana(d)
 
@@ -1825,7 +1786,6 @@ 
    Pair-Wise Dissimilarity: NCSP()  depth.axis = FALSE
 )
    
 
    
-
    #> [1] 0.5322917
    
 
    Some additional examples can be found in:
    
 
    
 
    
-
    #> [1] 1.052334
    
 
    Subgroup level classification (encoded as an un-ordered factor) will
 be used as a site-level attribute for computing pair-wise distances.
 Quickly review the grouping structure with
 groupedProfilePlot().
    
-
    +
     # encode as a factor for distance calculation
 z$subgroup <- factor(z$subgroup)
 
 par(mar = c(0, 0, 1, 1))
 groupedProfilePlot(z, groups = 'subgroup', group.name.offset = -10, break.style = 'arrow', group.line.lty = 1, group.line.lwd = 1)
    
 
    
-
    #> [1] 1.052334
    
 
    Horizon designation, grouped into “generalized
 horizon labels” will be used as the horizon-level attribute for
 computing pair-wise distances. REGEX pattern matching is used to apply
@@ -190,7 +188,7 @@ 
    A Simple Example
-
    +
     # assign GHL
 z$genhz <- generalize.hz(
   z$hzname, new = c('A', 'E', 'Bt', 'C'), 
@@ -201,13 +199,12 @@ 
    A Simple Examplepar(mar = c(0, 0, 3, 1))
 groupedProfilePlot(z, groups = 'subgroup', group.name.offset = -10, break.style = 'arrow', group.line.lty = 1, group.line.lwd = 1, color = 'genhz')
    
 
    
-
    #> [1] 1.052334
    
 
    Define weights and compute separately horizon and site level distance
 matrices. In this case, the site-level distances are give double the
 weight as the horizon-level distances. See the manual pages
 (?NCSP and ?compareSites) for additional
 arguments that can be used to further customize the comparison.
    
-
    +
     # horizon-level distance matrix weight
 w1 <- 1
 # perform NCSP using only the GHL (ordered factors) to a depth of 185cm
@@ -229,16 +226,15 @@ 
    A Simple Example
-
    +
     # divisive hierarchical clustering
 h <- as.hclust(diana(D))
 
 # hang soil profile sketches from resulting dendrogram
 par(mar = c(1, 0, 0, 1))
-plotProfileDendrogram(z, clust = h, scaling.factor = 0.0075, y.offset = 0.15, width = 0.33, color = 'genhz', name = NA)
    
-
    #> [1] 1.052334
    
-
    -# annotate dendorgram with subgroup classification
+plotProfileDendrogram(z, clust = h, scaling.factor = 0.0075, y.offset = 0.15, width = 0.33, color = 'genhz', name = NA)
+
+# annotate dendorgram with subgroup classification
 # this handy function provided by the {ape} package
 tiplabels(pch = 15, col = c(2, 3)[z$subgroup], cex = 1.5, offset = 0.05)
 
diff --git a/articles/label-placement.html b/articles/label-placement.html
index 47b2608a..9f70fd2d 100644
--- a/articles/label-placement.html
+++ b/articles/label-placement.html
@@ -118,7 +118,6 @@ 
    Introduction
    
-
    #> [1] 0.2265625
    
 
    Version 2.0 of the {aqp} package provides two algorithms for avoiding
 overlapping annotation, available in plotSPC() for the
 adjustment of horizon depth annotation, and for general use via
@@ -130,7 +129,7 @@ 
    Introduction
    +
     library(aqp)
 
 # soil profile template
@@ -151,9 +150,8 @@ 
    Introduction# create 3 copies of each simulation
 s <- duplicate(s, times = 3)
    
 
    Overlapping horizon depth labels are clear. Note that there are three
-copies of each simulated variation on the original template.
    
-
    #> [1] 0.6210938
    
-
    
+copies of each simulated variation on the original template.
+
    
 
    Selecting the optimal label-adjustment methods and parameters will
 depend on the collection of profiles, horizonation, profile height, font
 sizes, and graphics device settings (figure height, resolution).
    
@@ -183,7 +181,6 @@ 
    Electrostatic SimulationelectroStatics_1D(). The most common adjustment is via
 charge density (q). See comparisons below.
    
-
    #> [1] 0.6210938
    
 
    
 
    
 
    
@@ -199,9 +196,8 @@ 
    Simulated AnnealingSANN_1D() via fixOverlap().
    
 
    Note that each solution, within duplicate profiles, is slightly
-different.
    
-
    #> [1] 0.6210938
    
-
    
+different.
+
    
 
    
 
    
 
    
@@ -209,7 +205,7 @@ 
    Quick Comparison
 
    Create a very busy profile with lots of possible overlapping horizon
 depth labels.
    
-
    +
     x <- quickSPC(
   "SPC:Oi|Oe|AAA|E1|E2|E3|BhsBhsBhsBhs|Bt1|Bt2|Bt3Bt3|CCCCCC|Ab1|Ab2|2C2C2C2C2C2C|2Cr|2R2R2R2R2R2R2R2R", 
   interval = 1
@@ -218,7 +214,7 @@ 
    Quick Comparisonx$z <- as.numeric(x$hzID)
    
 
    Set arguments to plotSPC() and define a custom function
 to demonstrate various label adjustment settings.
    
-
    +
     # pretty colors
 .bluecolors <- hcl.colors(n = 25, palette = 'Blues')[-25]
 
@@ -259,48 +255,32 @@ 
    Quick Comparisonset.seed().
    
-
    +
     par(mar = c(1, 0, 0, 0), mfcol = c(1, 8))
 
-testIt(x, fixLabelCollisions = FALSE)
    
-
    #> [1] 0.4010417
    
-
    -title('No\nAdjustment', line = -3.5, adj = 0.5)
+testIt(x, fixLabelCollisions = FALSE)
+title('No\nAdjustment', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'S'))
    
-
    #> [1] 0.4010417
    
-
    -title('SANN\nsim 1', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'S'))
+title('SANN\nsim 1', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'S'))
    
-
    #> [1] 0.4010417
    
-
    -title('SANN\nsim 2', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'S'))
+title('SANN\nsim 2', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'S'))
    
-
    #> [1] 0.4010417
    
-
    -title('SANN\nsim 3', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'S'))
+title('SANN\nsim 3', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'E', q = 1.5))
    
-
    #> [1] 0.4010417
    
-
    -title('Electrostatic\nq = 1.5', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'E', q = 1.5))
+title('Electrostatic\nq = 1.5', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'E', q = 1))
    
-
    #> [1] 0.4010417
    
-
    -title('Electrostatic\nq = 1', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'E', q = 1))
+title('Electrostatic\nq = 1', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'E', q = 0.5))
    
-
    #> [1] 0.4010417
    
-
    -title('Electrostatic\nq = 0.5', line = -3.5, adj = 0.5)
+testIt(x, fixOverlapArgs = list(method = 'E', q = 0.5))
+title('Electrostatic\nq = 0.5', line = -3.5, adj = 0.5)
 
-testIt(x, fixOverlapArgs = list(method = 'E', q = 0.25))
    
-
    #> [1] 0.4010417
    
-
    -title('Electrostatic\nq = 0.25', line = -3.5, adj = 0.5)
    
+testIt(x, fixOverlapArgs = list(method = 'E', q = 0.25))
+title('Electrostatic\nq = 0.25', line = -3.5, adj = 0.5)
    
 
    
 
 
    
 
    
@@ -383,7 +339,7 @@ 
    General CasesplotSPC(). The function overlapMetics() can
 be used to determine overlap within a vector of positions based on a
 given distance threshold.
    
-
    +
     x <- c(1, 2, 3, 3.4, 3.5, 5, 6, 10)
 
 overlapMetrics(x, thresh = 0.5)
    
@@ -398,7 +354,7 @@ 
    General CasesfixOverlap() for additional details.
    
-
    +
     # vector of positions, typically labels but could be profile sketch alignment on the x-axis
 s <- c(1, 2, 2.3, 4, 5, 5.5, 7)
 
@@ -408,7 +364,7 @@ 
    General Cases#> [1] 1.000000 2.198432 2.775781 4.000000 5.000000 5.500000 7.000000
 #> attr(,"converged")
 #> [1] TRUE
    
-
    +
@@ -424,7 +380,7 @@ 
    Compare Algorithms
    +
     evalMethods <- function(x, thresh, q, ...) {
   
   cols <- hcl.colors(n = 9, palette = 'Zissou 1', rev = TRUE)
@@ -483,7 +439,7 @@ 
    Compare Algorithms
    +
 
    
-
    +
     # ok, but now most label positions are affected
 evalMethods(x, thresh = 5, q = 1.8)
    
 
    
-
    +
     # too high, wasting time on more iterations
 evalMethods(x, thresh = 5, q = 3)
    
 
    
-
    +
     # far too high, wasting more time with little gain
 evalMethods(x, thresh = 5, q = 4)
    
 
    
-
    +
     # chaos and failure to converge
 evalMethods(x, thresh = 5, q = 5)
    
 
    
 
    Additional examples to tinker with.
    
-
    +
     # threshold too large
 evalMethods(x, thresh = 10, q = 3)
 
@@ -560,7 +516,7 @@ 
    Learning More about the SANN Alg
 
    
 
    Define a custom function for visualizing the extended output from
 fixOverlap(..., method = 'S', trace = TRUE).
    
-
    +
 
    A relatively challenging example.
    
-
    +
     x <- c(0, 1, 2, 2.2, 2.8, 3.5, 6, 8, 10, 10.1, 12.8, 13, 14.8, 15, 15.5)
 
 # fix overlap, return debugging information
 set.seed(10101)
 z <- fixOverlap(x, thresh = 0.73, method = 'S', trace = TRUE)
    
 
    #> 160 iterations
    
-
    +
     # check convergence
 z$converged
    
 
    #> [1] TRUE
    
-
    +
     # inspect algorithm trace
 tracePlot(x, z)
    
 
    
-
    +
     # trace log
 # B: boundary condition violation
 # O: rank (order) violation
@@ -647,7 +603,7 @@ 
    Learning More about the SANN Alg
 #>  B  O  +  - 
 #> 22 71 64  2
    
 
    A very challenging example.
    
-
    +
     # fix overlap, return debugging information
 set.seed(101010)
 x <- sort(runif(10, min = 2.5, max = 3.5))
@@ -655,16 +611,16 @@ 
    Learning More about the SANN Alg
 # widen boundary conditions
 z <- fixOverlap(x, thresh = 0.2, trace = TRUE, min.x = 0, max.x = 10, maxIter = 2000, adj = 0.05)
    
 
    #> 1203 iterations
    
-
    +
     # check convergence
 z$converged
    
 
    #> [1] TRUE
    
-
    +
     # inspect algorithm trace
 tracePlot(x, z)
    
 
    
 
    Cleanup.
    
-
    +
     # reset plotSPC() options
 options(.aqp.plotSPC.args = NULL)
    
 
    
diff --git a/articles/missing-data.html b/articles/missing-data.html
index f0f3ab5b..74cff3cc 100644
--- a/articles/missing-data.html
+++ b/articles/missing-data.html
@@ -117,20 +117,17 @@ 
    Missing Data
    
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'time_saturated')
    
 
    
-
    #> [1] 0.3289879
    
-
    +
     # missing some data
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'concentration_color')
    
 
    
-
    #> [1] 0.3289879
    
-
    +
     # very nearly complete
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'matrix_color')
    
 
    
-
    #> [1] 0.3289879
    
-
    +
     # variables to consider
 v <- c('time_saturated', 'concentration_color', 'matrix_color')
 
@@ -166,8 +163,7 @@ 
    Missing Data
    
   cex.names = 0.8, color = 'hz.data.complete'
 )
    
 
    
-
    #> [1] 0.3289879
    
-
    +
     # rank on profile completeness
 new.order <- order(jacobs2000$data.complete)
 
@@ -176,10 +172,9 @@ 
    Missing Data
    
   jacobs2000, name.style = 'center-center', 
   cex.names = 0.8, color = 'hz.data.complete', 
   plot.order = new.order
-)
    
-
    #> [1] 0.3289879
    
-
    -# add relative completeness axis
+)
+
+# add relative completeness axis
 # note re-ordering of axis labels
 axis(
   side = 1, at = 1:length(jacobs2000), 
@@ -198,57 +193,47 @@ 
    Missing Data
    
 mtext('Relative\nCompleteness', side = 1, at = 0.25, line = 0.25, cex = 0.8)
 mtext('Absolute\nCompleteness (cm)', side = 1, at = 0.25, line = 2.75, cex = 0.8)
    
 
    
-
    +
     x <- fetchKSSL(series = 'pierre')
 par(mar = c(0, 0, 3, 2))
 
 plotSPC(x, color = 'clay', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
 
    
-
    #> [1] 0.1507675
    
-
    +
     plotSPC(x, color = 'cec7', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
 
    
-
    #> [1] 0.1507675
    
-
    +
     plotSPC(x, color = 'estimated_oc', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
 
    
-
    #> [1] 0.1507675
    
-
    +
     plotSPC(x, color = 'ph_h2o', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
 
    
-
    #> [1] 0.1507675
    
-
    +
     plotSPC(x, color = 'db_13b', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
 
    
-
    #> [1] 0.1507675
    
-
    +
     par(mar = c(1, 0, 3, 2))
-plotSPC(x, color = 'ph_h2o', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
    
-
    #> [1] 0.1507675
    
-
    -.b <- x[, , .LAST, .BOTTOM]
+plotSPC(x, color = 'ph_h2o', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index')
+
+.b <- x[, , .LAST, .BOTTOM]
 text(x = 1:length(x), y = .b, labels = x$pi, cex = 0.85, pos = 1)
 mtext('Profile Information Index (bytes)', side = 1, line = -0.5)
    
 
    
-
    +
     v <- c('clay', 'db_13b', 'cec7', 'ph_h2o')
 x$rel.not.missing <- evalMissingData(x, vars = v, method = 'relative')
 x$abs.not.missing <- evalMissingData(x, vars = v, method = 'absolute')
 x$hz.not.missing <- evalMissingData(x, vars = v, method = 'horizon')
 
 o <- order(x$rel.not.missing)
-plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o)
    
-
    #> [1] 0.1507675
    
-
    -text(x = 1:length(x), y = .b[o], labels = round(x$rel.not.missing[o], 2), cex = 0.85, pos = 1)
+plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o)
+text(x = 1:length(x), y = .b[o], labels = round(x$rel.not.missing[o], 2), cex = 0.85, pos = 1)
 mtext('Relative Non-Missing Fraction', side = 1, line = -0.5)
    
 
    
-
    +
     o <- order(x$abs.not.missing)
-plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o)
    
-
    #> [1] 0.1507675
    
-
    -text(x = 1:length(x), y = .b[o], labels = x$abs.not.missing[o], cex = 0.85, pos = 1)
+plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o)
+text(x = 1:length(x), y = .b[o], labels = x$abs.not.missing[o], cex = 0.85, pos = 1)
 mtext('Absolute Non-Missing (cm)', side = 1, line = -0.5)
    
 
    
   
    
diff --git a/pkgdown.yml b/pkgdown.yml
index 3acab798..e1e76fe1 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -9,5 +9,5 @@ articles:
   Munsell-color-conversion: Munsell-color-conversion.html
   NCSP: NCSP.html
   new-in-aqp-2: new-in-aqp-2.html
-last_built: 2024-06-15T01:02Z
+last_built: 2024-06-25T19:40Z
 
diff --git a/reference/SoilProfileCollection-class.html b/reference/SoilProfileCollection-class.html
index 8d069952..3793e0ff 100644
--- a/reference/SoilProfileCollection-class.html
+++ b/reference/SoilProfileCollection-class.html
@@ -222,7 +222,6 @@ 
    Examples
    
 depths(d) <- id ~ top + bottom
 plot(d)
 
-#> [1] 0.1407658
 
 # split into new SoilProfileCollection objects by index
 d.1 <- d[1, ]
@@ -234,7 +233,6 @@ 
    Examples
    
 d.new <- c(d.345, d.1, d.2)
 plot(d.new)
 
-#> [1] 0.07678133
 
 data(sp1)
 
diff --git a/reference/SoilProfileCollection-plotting-methods.html b/reference/SoilProfileCollection-plotting-methods.html
index 1cadf58d..46002520 100644
--- a/reference/SoilProfileCollection-plotting-methods.html
+++ b/reference/SoilProfileCollection-plotting-methods.html
@@ -428,13 +428,11 @@ 
    Examples
    
 # plot profiles without horizon-line divisions
 plotSPC(sp1, divide.hz = FALSE)
 
-#> [1] 0.3799805
 
 # diagonal lines encode horizon boundary distinctness
 sp1$hzD <- hzDistinctnessCodeToOffset(sp1$bound_distinct)
 plotSPC(sp1, hz.distinctness.offset = 'hzD', name.style = 'center-center')
 
-#> [1] 0.3799805
 
 # plot horizon color according to some property
 data(sp4)
@@ -442,7 +440,6 @@ 
    Examples
    
 hzdesgnname(sp4) <- 'name'
 plotSPC(sp4, color = 'clay')
 
-#> [1] 0.6817383
 
 # another example
 data(sp2)
@@ -455,13 +452,11 @@ 
    Examples
    
 plotSPC(sp2, label = 'surface', plot.order = order(sp2$surface), 
 max.depth = 400)
 
-#> [1] 2.074414
 
 # example using a categorical attribute
 plotSPC(sp2, color = "plasticity", 
 max.depth = 400)
 
-#> [1] 0.9719401
 
 # plot two SPC objects in the same figure
 par(mar = c(1,1,1,1))
@@ -469,12 +464,10 @@ 
    Examples
    
 # plot the first SPC object and
 # allocate space for the second SPC object
 plotSPC(sp1, n = length(sp1) + length(sp2))
-#> [1] 0.4042345
 
 # plot the second SPC, starting from the first empty space
 plotSPC(sp2, x.idx.offset = length(sp1), add = TRUE)
 
-#> [1] 1.033979
 
 
 ##
@@ -492,7 +485,6 @@ 
    Examples
    
   cex.names = 0.8
 )
 
-#> [1] 0.4472448
 
 # shrink horizon names in "thin" horizons
 plotSPC(
@@ -504,7 +496,6 @@ 
    Examples
    
   cex.names = 0.8,
 )
 
-#> [1] 0.4472448
 
 
 ##
@@ -524,12 +515,10 @@ 
    Examples
    
 # note that the legend is split into 2 rows when length(classes) > n.legend argument
 plotSPC(sp3, color='fake.data', name='fake.data', cex.names=0.8)
 
-#> [1] 0.1893726
 
 # make enough room in a single legend row
 plotSPC(sp3, color='fake.data', name='fake.data', cex.names=0.8, n.legend=15)
 
-#> [1] 0.1893726
 
 
 ##
@@ -552,12 +541,10 @@ 
    Examples
    
 # y-offset at 0
 plotSPC(x, color = 'matrix_color', cex.names = 0.66)
 
-#> [1] 0.3687043
 
 # constant adjustment to y-offset
 plotSPC(x, color = 'matrix_color', cex.names = 0.66, y.offset = 50)
 
-#> [1] 0.3687043
 
 # attempt using invalid y.offset
 # warning issued and default value of '0' used
@@ -577,7 +564,6 @@ 
    Examples
    
   fixLabelCollisions = TRUE,
   name.style = 'center-center'
 )
-#> [1] 0.3942057
 #> depth axis is disabled when more than 1 unique y offsets are supplied
 
 
@@ -598,7 +584,6 @@ 
    Examples
    
         hz.depths = TRUE, 
         name.style = 'center-center'
 )
-#> [1] 0.346582
 #> depth axis is disabled when more than 1 unique y offsets are supplied
 
 
@@ -621,7 +606,6 @@ 
    Examples
    
         hz.depths = TRUE, 
         name.style = 'center-center'
 )
-#> [1] 0.3573011
 #> depth axis is disabled when more than 1 unique y offsets are supplied
 
 box()
diff --git a/reference/accumulateDepths.html b/reference/accumulateDepths.html
index ce1bee74..dfe425c5 100644
--- a/reference/accumulateDepths.html
+++ b/reference/accumulateDepths.html
@@ -172,7 +172,6 @@ 
    Examples
    
                        hzdatum = 5 * 1:length(sp4))
 plot(hz)
 
-#> [1] 0.8375163
   
 # example using old-style O horizons
 hz <- read.table(text = "peiidref hzdept hzdepb hzname seqnum phiid
@@ -210,10 +209,8 @@ 
    Examples
    
 
 par(mfrow=c(2,1), mar=c(0,0,3,2))
 plotSPC(origO, max.depth = 25)
-#> [1] 0.07757092
 plotSPC(fixedO, max.depth = 25)
 
-#> [1] 0.07757092
 
 
    
     
    
diff --git a/reference/addBracket.html b/reference/addBracket.html
index dc786e3b..da97180e 100644
--- a/reference/addBracket.html
+++ b/reference/addBracket.html
@@ -155,7 +155,6 @@ 
    Examples
    
 par(mar = c(0, 0, 0, 1))
 plotSPC(sp1, width = 0.3)
 
-#> [1] 0.3917324
 
 # extract min--max depths associated with all A horizons
 # result is a single-row data.frame / profile
@@ -203,7 +202,6 @@ 
    Examples
    
 
 # plot in reverse order
 plotSPC(sp1, plot.order = rev(1:length(sp1)), width = 0.25)
-#> [1] 0.3917324
 
 # note that plotting order is derived from the call to `plotSPC(sp1)`
 addBracket(b1, col='red', offset = -0.35)
@@ -211,7 +209,6 @@ 
    Examples
    
 
 # plot in reverse order
 plotSPC(sp1, plot.order = rev(1:length(sp1)), width = 0.25)
-#> [1] 0.3917324
 
 # note that plotting order is derived from the call to `plotSPC(sp1)`
 addBracket(b2, col='red', offset = -0.35)
diff --git a/reference/alignTransect.html b/reference/alignTransect.html
index d9ff1c9e..bbd6bd69 100644
--- a/reference/alignTransect.html
+++ b/reference/alignTransect.html
@@ -136,14 +136,12 @@ 
    Examples
    
 plotSPC(g, width=0.25, name.style='center-center', 
         cex.names=0.75, 
         relative.pos = g.p$relative.pos, plot.order = g.p$order)
-#> [1] 0.7214442
 
 axis(1, at = g.p$relative.pos, labels = g.p$grad, line = -1.5)
 
 plotSPC(a, width=0.25, name.style='center-center', 
         cex.names=0.75, 
         relative.pos = a.p$relative.pos, plot.order = a.p$order)
-#> [1] 0.5329192
 
 axis(1, at = a.p$relative.pos, labels = a.p$grad, line = -1.5)
 
diff --git a/reference/allocate.html b/reference/allocate.html
index 415ea04c..7e163439 100644
--- a/reference/allocate.html
+++ b/reference/allocate.html
@@ -226,7 +226,6 @@ 
    Examples
    
 
 plotSPC(sp3)
 
-#> [1] 0.1407658
 
 allocate(
   sp3, 
@@ -261,7 +260,6 @@ 
    Examples
    
 
 plotSPC(x)
 
-#> [1] 0.1407658
 
 allocate(
   x, 
diff --git a/reference/depthOf.html b/reference/depthOf.html
index c86c8a88..155aa20b 100644
--- a/reference/depthOf.html
+++ b/reference/depthOf.html
@@ -88,7 +88,7 @@ 
    Get top or bottom depths of horizons matching a regular expression pattern  pattern,
   FUN = NULL,
   top = TRUE,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   no.contact.depth = NULL,
   no.contact.assigned = NA_real_,
   na.rm = TRUE,
@@ -99,7 +99,7 @@ 
    Get top or bottom depths of horizons matching a regular expression pattern  p,
   pattern,
   top = TRUE,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   no.contact.depth = NULL,
   no.contact.assigned = NA,
   na.rm = TRUE,
@@ -110,7 +110,7 @@ 
    Get top or bottom depths of horizons matching a regular expression pattern  p,
   pattern,
   top = TRUE,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   no.contact.depth = NULL,
   no.contact.assigned = NA,
   na.rm = TRUE,
diff --git a/reference/depths.html b/reference/depths.html
index 57fa08d7..8ec68374 100644
--- a/reference/depths.html
+++ b/reference/depths.html
@@ -194,7 +194,6 @@ 
    Examples
    
 # plot
 plot(sp1)
 
-#> [1] 0.4668065
 
 # number of profiles
 length(sp1)
diff --git a/reference/duplicate.html b/reference/duplicate.html
index b587bb88..60260d10 100644
--- a/reference/duplicate.html
+++ b/reference/duplicate.html
@@ -125,7 +125,6 @@ 
    Examples
    
 par(mar = c(0, 0, 3, 1))
 plotSPC(d, color = 'Ca', width = 0.25)
 
-#> [1] 1.963394
 
 
    
     
    
diff --git a/reference/estimatePSCS.html b/reference/estimatePSCS.html
index 384d6983..5f6a80de 100644
--- a/reference/estimatePSCS.html
+++ b/reference/estimatePSCS.html
@@ -87,9 +87,9 @@ 
    Estimate boundaries of the particle size control section (U.S Soil Taxonomy;
     
    
     
    estimatePSCS(
   p,
-  hzdesgn = "hzname",
-  clay.attr = "clay",
-  texcl.attr = "texcl",
+  hzdesgn = hzdesgnname(p, required = TRUE),
+  clay.attr = hzmetaname(p, "clay", required = TRUE),
+  texcl.attr = hztexclname(p, required = TRUE),
   tax_order_field = "tax_order",
   bottom.pattern = "Cr|R|Cd",
   simplify = TRUE,
@@ -179,10 +179,13 @@ 
    Examples
    
 depths(sp1) <- id ~ top + bottom
 site(sp1) <- ~ group
 
-p <- sp1
-attr <- 'prop' # clay contents
-foo <- estimatePSCS(p, hzdesgn='name', clay.attr = attr, texcl.attr="texture")
-foo
+# set required metadata
+hzdesgnname(sp1) <- 'name'
+hztexclname(sp1) <- 'texture'
+hzmetaname(sp1, 'clay') <- 'prop'
+
+x <- estimatePSCS(sp1)
+x
 #>     id pscs_top pscs_bottom
 #> 1 P001       49          89
 #> 2 P002       30          59
@@ -193,8 +196,6 @@ 
    Examples
    
 #> 7 P007       25         100
 #> 8 P008       27         102
 #> 9 P009       28         103
-
-
 
    
     
    
   
    
diff --git a/reference/estimateSoilDepth.html b/reference/estimateSoilDepth.html
index 311f5ee3..187f8343 100644
--- a/reference/estimateSoilDepth.html
+++ b/reference/estimateSoilDepth.html
@@ -166,7 +166,6 @@ 
    Examples
    
 par(mar = c(0, 0, 0, 2))
 plotSPC(d, hz.depths = TRUE, name.style = 'center-center', cex.names = 1, width = 0.1)
 
-#> [1] 0.02219775
 
 # top of the first Cd
 estimateSoilDepth(d, name = 'name')
@@ -212,7 +211,6 @@ 
    Examples
    
 par(mar=c(1,1,1,2))
 # adjust default y-offset and depth scaling for following examples
 plotSPC(sp1, y.offset=10, scaling.factor=0.5)
-#> [1] 0.417561
 
 # get plotting parameters for profile widths and depth scaling factors
 lsp <- get("last_spc_plot", envir = aqp.env)
diff --git a/reference/evalMissingData.html b/reference/evalMissingData.html
index a45499b4..3eadbdc1 100644
--- a/reference/evalMissingData.html
+++ b/reference/evalMissingData.html
@@ -135,19 +135,16 @@ 
    Examples
    
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'time_saturated')
 
-#> [1] 0.5164744
 
 # missing some data
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'concentration_color')
 
-#> [1] 0.5164744
 
 # very nearly complete
 plotSPC(jacobs2000, name.style = 'center-center', 
         cex.names = 0.8, color = 'matrix_color')
 
-#> [1] 0.5164744
 
 
 # variables to consider
@@ -185,7 +182,6 @@ 
    Examples
    
   cex.names = 0.8, color = 'hz.data.complete'
 )
 
-#> [1] 0.5164744
 
 
 # rank on profile completeness
@@ -197,7 +193,6 @@ 
    Examples
    
   cex.names = 0.8, color = 'concentration_color', 
   plot.order = new.order
 )
-#> [1] 0.5164744
 
 # add relative completeness axis
 # note re-ordering of axis labels
diff --git a/reference/fillHzGaps.html b/reference/fillHzGaps.html
index 6c43a8dc..7bc71486 100644
--- a/reference/fillHzGaps.html
+++ b/reference/fillHzGaps.html
@@ -159,7 +159,6 @@ 
    Examples
    
 name = 'hzID', name.style = 'center-center', cex.names = 0.8,
 cex.id = 0.66)
 
-#> [1] 0.7976646
 
 # fill gaps left by HzDepthLogicSubset()
 z <- fillHzGaps(x, flag = TRUE)
@@ -169,18 +168,15 @@ 
    Examples
    
 show.legend = FALSE, name.style = 'center-center', cex.names = 0.8,
 cex.id = 0.66)
 
-#> [1] 0.7976646
 
 # fill top to 0 cm
 z2 <- fillHzGaps(x, flag = TRUE, to_top = 0)
 plotSPC(z2, width = 0.3, color = '.filledGap', name = 'hzID', show.legend = FALSE)
 
-#> [1] 0.7252535
 
 # fill bottom to max(SPC)
 z3 <- fillHzGaps(x, flag = TRUE, to_top = 0, to_bottom = max(x))
 plotSPC(z3, width = 0.3, color = '.filledGap', name = 'hzID', show.legend = FALSE)
-#> [1] 0.7252535
 
 ## another example
 data(sp4)
@@ -200,10 +196,8 @@ 
    Examples
    
 #> filling gaps left by HzDepthLogicSubset
 plotSPC(d, color = 'Ca', show.legend = FALSE)
 
-#> [1] 0.7252535
 plotSPC(d, color = '.filledGap', show.legend = FALSE)
 
-#> [1] 0.7252535
 
 
    
     
    
diff --git a/reference/fixOverlap.html b/reference/fixOverlap.html
index 4797f70f..03305fb6 100644
--- a/reference/fixOverlap.html
+++ b/reference/fixOverlap.html
@@ -184,27 +184,21 @@ 
    Examples
    
 op <- par(mar = c(0, 0, 0, 0), mfcol = c(1, 6))
 
 testIt(x)
-#> [1] 0.3894531
 title('ES (defaults)', line = -3)
 
 testIt(x, fixOverlapArgs = list(method = 'S'))
-#> [1] 0.3894531
 title('SANN (defaults)', line = -3)
 
 testIt(x, fixOverlapArgs = list(method = 'E', q = 1.5))
-#> [1] 0.3894531
 title('ES (q = 1.5)', line = -3)
 
 testIt(x, fixOverlapArgs = list(method = 'E', q = 1))
-#> [1] 0.3894531
 title('ES (q = 1)', line = -3)
 
 testIt(x, fixOverlapArgs = list(method = 'E', q = 0.5))
-#> [1] 0.3894531
 title('ES (q = 0.5)', line = -3)
 
 testIt(x, fixOverlapArgs = list(method = 'E', q = 0.1))
-#> [1] 0.3894531
 title('ES (q = 0.1)', line = -3)
 
 
diff --git a/reference/flagOverlappingHz.html b/reference/flagOverlappingHz.html
index ab9e10f3..b878a1ff 100644
--- a/reference/flagOverlappingHz.html
+++ b/reference/flagOverlappingHz.html
@@ -131,7 +131,6 @@ 
    Examples
    
 plotSPC(z, color = '.overlapFlag', hz.depths = TRUE, 
 depth.axis = FALSE, cex.names = 0.85)
 
-#> [1] 0.06850334
 
 
    
     
    
diff --git a/reference/getArgillicBounds.html b/reference/getArgillicBounds.html
index 8696c08c..cf742446 100644
--- a/reference/getArgillicBounds.html
+++ b/reference/getArgillicBounds.html
@@ -85,9 +85,9 @@ 
    Estimate upper and lower boundary of argillic diagnostic subsurface horizon<
     
    
     
    getArgillicBounds(
   p,
-  hzdesgn = "hzname",
-  clay.attr = "clay",
-  texcl.attr = "texcl",
+  hzdesgn = hzdesgnname(p, required = TRUE),
+  clay.attr = hzmetaname(p, "clay", required = TRUE),
+  texcl.attr = hztexclname(p, required = TRUE),
   require_t = TRUE,
   bottom.pattern = "Cr|R|Cd",
   lower.grad.pattern = "^[2-9]*B*CB*[^rtd]*[1-9]*$",
@@ -169,10 +169,13 @@ 
    Examples
    
 depths(sp1) <- id ~ top + bottom
 site(sp1) <- ~ group
 
-p <- sp1
-attr <- 'prop' # clay contents
-foo <- getArgillicBounds(p, hzdesgn='name', clay.attr = attr, texcl.attr="texture")
-foo
+# set required metadata
+hzdesgnname(sp1) <- 'name'
+hztexclname(sp1) <- 'texture'
+hzmetaname(sp1, 'clay') <- 'prop'
+
+x <- getArgillicBounds(sp1)
+x
 #>     id ubound lbound
 #> 1 P001     49     89
 #> 2 P002     NA     NA
diff --git a/reference/getCambicBounds.html b/reference/getCambicBounds.html
index aeb27bdc..c8ab4d88 100644
--- a/reference/getCambicBounds.html
+++ b/reference/getCambicBounds.html
@@ -85,9 +85,9 @@ 
    Find all intervals that are potentially part of a Cambic horizon
    
     
    
     
    getCambicBounds(
   p,
-  hzdesgn = guessHzDesgnName(p, required = TRUE),
-  texcl.attr = guessHzTexClName(p, required = TRUE),
-  clay.attr = guessHzAttrName(p, attr = "clay", c("total", "_r")),
+  hzdesgn = hzdesgnname(p, required = TRUE),
+  texcl.attr = hztexclname(p, required = TRUE),
+  clay.attr = hzmetaname(p, "clay", required = TRUE),
   argi_bounds = NULL,
   d_value = "d_value",
   m_value = "m_value",
@@ -165,12 +165,14 @@ 
    Examples
    
 
 # promote to SoilProfileCollection
 depths(spc) <- id ~ hzdept + hzdepb
+
+# set required metadata
 hzdesgnname(spc) <- 'hzname'
 hztexclname(spc) <- 'texcl'
+hzmetaname(spc, 'clay') <- 'clay'
 
 # print results in table
 getCambicBounds(spc)
-#> guessing horizon attribute 'clay' is stored in `clay`
 #>   id cambic_top cambic_bottom cambic_index
 #> 1  1         32            49            1
 
diff --git a/reference/getSurfaceHorizonDepth.html b/reference/getSurfaceHorizonDepth.html
index 26fdf878..112479d9 100644
--- a/reference/getSurfaceHorizonDepth.html
+++ b/reference/getSurfaceHorizonDepth.html
@@ -84,20 +84,20 @@ 
    Determine thickness of horizons (continuous from surface) matching a pattern
     
    getSurfaceHorizonDepth(
   p,
   pattern,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   simplify = TRUE
 )
 
 getMineralSoilSurfaceDepth(
   p,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   pattern = "O",
   simplify = TRUE
 )
 
 getPlowLayerDepth(
   p,
-  hzdesgn = guessHzDesgnName(p),
+  hzdesgn = hzdesgnname(p, required = TRUE),
   pattern = "^Ap[^b]*",
   simplify = TRUE
 )
    
@@ -114,7 +114,7 @@ 
    Arguments
    
 
 
 
    hzdesgn
    
-
    column name containing horizon designation. Default: guessHzDesgnName(p, required = TRUE).
    
+
    column name containing horizon designation. Default: hzdesgnname(p, required = TRUE).
    
 
 
 
    simplify
    
diff --git a/reference/glom.html b/reference/glom.html
index f7cc46eb..30c07bc9 100644
--- a/reference/glom.html
+++ b/reference/glom.html
@@ -192,7 +192,6 @@ 
    Examples
    
 # inspect graphically
 par(mar = c(1,1,3,1))
 plot(p, color = "prop", max.depth = 200)
-#> [1] 1.215197
 #> [P001:4] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 abline(h = c(25, 100), lty = 2)
@@ -209,7 +208,6 @@ 
    Examples
    
 # inspect graphically
 par(mar = c(1,1,3,1))
 plot(p2, color = "prop", max.depth = 200)
-#> [1] 1.215197
 #> [P001:4] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 abline(h = c(25, 100), lty = 2)
@@ -226,7 +224,6 @@ 
    Examples
    
 # inspect graphically
 par(mar = c(1,1,3,1))
 plot(p3, color = "prop", max.depth = 200)
-#> [1] 1.215197
 abline(h = c(25, 100), lty = 2)
 
 
@@ -243,7 +240,6 @@ 
    Examples
    
 par(mar = c(1,1,3,1))
 plot(p4, color = "prop", max.depth = 200)
 
-#> [1] 1.215197
 
 
 # load sample data
@@ -259,12 +255,10 @@ 
    Examples
    
 
 # full profiles
 plot(sp3)
-#> [1] 0.3444661
 
 # trunc'd profiles
 plot(trunc(sp3, 0, 25))
 
-#> [1] 0.3444661
 
    
     
    
   
    
diff --git a/reference/glomApply.html b/reference/glomApply.html
index ead96188..1c95cd75 100644
--- a/reference/glomApply.html
+++ b/reference/glomApply.html
@@ -157,33 +157,27 @@ 
    Examples
    
 # constant depths, whole horizon returns by default
 plot(glomApply(sp3, function(p) c(25,100)))
 
-#> [1] 0.4231771
 
 # constant depths, truncated
 #(see aqp::trunc for helper function)
 plot(glomApply(sp3, function(p) c(25,30), truncate = TRUE))
 
-#> [1] 0.4231771
 
 # constant depths, inverted
 plot(glomApply(sp3, function(p) c(25,100), invert = TRUE))
 
-#> [1] 0.4231771
 
 # constant depths, inverted + truncated (same as above)
 plot(glomApply(sp3, function(p) c(25,30), invert = TRUE, truncate=TRUE))
 
-#> [1] 0.4231771
 
 # random boundaries in each profile
 plot(glomApply(sp3, function(p) round(sort(runif(2, 0, max(sp3))))))
 
-#> [1] 0.3847064
 
 # random boundaries in each profile (truncated)
 plot(glomApply(sp3, function(p) round(sort(runif(2, 0, max(sp3)))), truncate = TRUE))
 
-#> [1] 0.3847064
 
 # calculate some boundaries as site level attribtes
 sp3$glom_top <- profileApply(sp3, getMineralSoilSurfaceDepth)
@@ -195,7 +189,6 @@ 
    Examples
    
 # use site level attributes for glom intervals for each profile
 plot(glomApply(sp3, function(p) return(c(p$glom_top, p$glom_bottom))))
 
-#> [1] 0.4231771
 
 
    
     
    
diff --git a/reference/guessHzAttrName.html b/reference/guessHzAttrName.html
index 6d03e19b..c8c5ff6d 100644
--- a/reference/guessHzAttrName.html
+++ b/reference/guessHzAttrName.html
@@ -1,8 +1,8 @@
 
 Guess Horizon Slot Column Names — guessHzAttrName • aqp
@@ -82,8 +82,8 @@ 
    Guess Horizon Slot Column Names
    
     
    
     
    guessHzAttrName(): Guess the horizon column name where possible/preferred formative elements are known. There is a preference for records where more optional requirements are met to handle cases where there will be many matches. For example, working with soil data one might have "low, RV and high" total clay, as well as clay fractions. One could distinguish between these different measurements using standard formative elements for column names from the database of interest. Result is the first match in horizonNames(x) with the most required plus optional patterns matched.
    
 
    e.g. guessHzAttrName(x, attr="clay", optional=c("total", "_r")) matches (claytotal_r == totalclay_r) over (clay_r == claytotal == totalclay) over clay.
    
-
    guessHzDesgnName(): This follows the historic convention used by aqp::plotSPC() looking for "hzname" or other column names containing the regular expression "name". If the pattern "name" is not found, the pattern "desgn" is searched as a fallback, as "hzdesgn" or "hz_desgn" are other common column naming schemes for horizon designation name.
    
-
    guessHzTexClName(): This function is used to provide a texture class attribute column name to functions. It will use regular expressions to match "texcl" which is typically the texture of the fine earth fraction, without modifiers or in-lieu textures. Alternately, it will match "texture" for cases where "texcl" is absent (e.g. in NASIS Component Horizon).
    
+
    guessHzDesgnName(): DEPRECATED This follows the historic convention used by aqp::plotSPC() looking for "hzname" or other column names containing the regular expression "name". If the pattern "name" is not found, the pattern "desgn" is searched as a fallback, as "hzdesgn" or "hz_desgn" are other common column naming schemes for horizon designation name.
    
+
    guessHzTexClName(): DEPRECATED This function is used to provide a texture class attribute column name to functions. It will use regular expressions to match "texcl" which is typically the texture of the fine earth fraction, without modifiers or in-lieu textures. Alternately, it will match "texture" for cases where "texcl" is absent (e.g. in NASIS Component Horizon).
    
     
    
 
     
    
@@ -101,15 +101,15 @@ 
    Arguments
    
 
 
 
    attr
    
-
    A regular expression containing required formative element of attribute name.
    
+
    character. A regular expression containing required formative element of attribute name.
    
 
 
 
    optional
    
-
    A character vector of regular expression(s) containing optional formative elements of attribute name.
    
+
    character. Vector of regular expression(s) containing optional formative elements of attribute name.
    
 
 
 
    verbose
    
-
    A boolean value for whether to produce message output about guesses.
    
+
    logical. Produce message output about guesses? Default: TRUE
    
 
 
 
    required
    
@@ -160,28 +160,6 @@ 
    Examples
    
 #> guessing horizon attribute 'clay' is stored in `totalclay_r`
 #> [1] "totalclay_r"
 
-
-a <- data.frame(id = 1, top = c(0,10), bottom=c(10,40), horizonname=c("A","Bw"))
-depths(a) <- id ~ top + bottom
-
-# store guess in metadata
-hzdesgnname(a) <- guessHzDesgnName(a)
-
-# inspect result
-hzdesgnname(a)
-#> [1] "horizonname"
-
-
-a <- data.frame(id = 1, top = c(0,10), bottom=c(10,40), texture=c("A","Bw"))
-depths(a) <- id ~ top + bottom
-
-# store guess in metadata
-hztexclname(a) <- guessHzTexClName(a)
-
-# inspect result
-hztexclname(a)
-#> [1] "texture"
-
 
    
     
    
   
    
diff --git a/reference/harden.melanization.html b/reference/harden.melanization.html
index 43f7fdd0..8d084bf2 100644
--- a/reference/harden.melanization.html
+++ b/reference/harden.melanization.html
@@ -164,7 +164,6 @@ 
    Examples
    
         plot.order = jacobs2000$melanorder,
         max.depth = 250
         )
-#> [1] 1.030629
 
 segments(
   x0 = 0.5, 
diff --git a/reference/harden.rubification.html b/reference/harden.rubification.html
index bfdb1c53..2aadb0ad 100644
--- a/reference/harden.rubification.html
+++ b/reference/harden.rubification.html
@@ -176,7 +176,6 @@ 
    Examples
    
 plot.order = jacobs2000$rubiforder,
 max.depth = 250
 )
-#> [1] 1.030629
 
 segments(
   x0 = 0.5, 
diff --git a/reference/harmonize-SoilProfileCollection-method.html b/reference/harmonize-SoilProfileCollection-method.html
index 5d1d4f78..a9ce5c40 100644
--- a/reference/harmonize-SoilProfileCollection-method.html
+++ b/reference/harmonize-SoilProfileCollection-method.html
@@ -137,12 +137,10 @@ 
    Examples
    
 # inspect result
 plotSPC(h1, color = "foo")
 
-#> [1] 5.59328
 
 # filter with calculated "harmonized group" to get just RV profiles
 plotSPC(subset(h1, hgroup == "q50"), color="foo")
 
-#> [1] 1.864427
 
 ### single source, two properties at once; with common labels: "method1" "method2"
 
@@ -152,10 +150,8 @@ 
    Examples
    
                                     bar = c(method1 = "p3", method2 = "p4")))
 plotSPC(h3, color = "foo")
 
-#> [1] 6.935273
 plotSPC(h3, color = "bar")
 
-#> [1] 6.935273
 head(horizons(h3))
 #>           id top bottom       foo      bar hzID
 #> 1 10_method1   0     20 -12.83190 10.08068    1
@@ -170,20 +166,16 @@ 
    Examples
    
                                     bar = c(method2 = "p3", method3 = "p4")))
 plotSPC(h3, color = "foo") # note the pattern of values missing for foo (*_method3)
 
-#> [1] 10.40291
 plotSPC(h3, color = "bar") #  likewise for bar (*_method1)
 
-#> [1] 10.40291
 
 #' the new labels need not match across harmonizations -- not sure how useful this is but it works
 h3 <- harmonize(spc, x.names = list(foo = c(method1 = "p1", method2 = "p2"),
                                     bar = c(method3 = "p3", method4 = "p4")))
 plotSPC(h3, color = "foo") # note the pattern of values missing for foo (*_method 3 + 4)
 
-#> [1] 13.87055
 plotSPC(h3, color = "bar") #  likewise for bar (*_method 1 + 2)
 
-#> [1] 13.87055
 
 ### two-source harmonization
 
@@ -197,7 +189,6 @@ 
    Examples
    
 # same property with different name in two different datasets
 plotSPC(h4, color = "foo")
 
-#> [1] 3.656111
 
 ### many source harmonization
 
@@ -224,7 +215,6 @@ 
    Examples
    
 # inspect a subset
 plotSPC(bigspc[1:30,], color = "foo")
 
-#> [1] 3.252649
 
 
    
     
    
diff --git a/reference/horizonColorIndices.html b/reference/horizonColorIndices.html
index 5eec5375..737e4960 100644
--- a/reference/horizonColorIndices.html
+++ b/reference/horizonColorIndices.html
@@ -141,17 +141,14 @@ 
    Examples
    
 # visualize
 par(mar = c(0, 1, 3, 1))
 plotSPC(sp1, color='hurst_redness', name = 'm')
-#> [1] 1.215197
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
 plotSPC(sp1, color='barron_torrent_redness', name = 'm')
-#> [1] 1.215197
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
 plotSPC(sp1, color='buntley_westin', name = 'm')
-#> [1] 1.215197
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
diff --git a/reference/hzDistinctnessCodeToOffset.html b/reference/hzDistinctnessCodeToOffset.html
index be2616df..45a78cab 100644
--- a/reference/hzDistinctnessCodeToOffset.html
+++ b/reference/hzDistinctnessCodeToOffset.html
@@ -150,7 +150,6 @@ 
    Examples
    
 
 # sketches, adjust width, adjust text size, include coded hz distinctness offsets
 plotSPC(sp1, width=0.3, cex.names=0.75, hz.distinctness.offset = 'hzdo')
-#> [1] 0.5979017
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
diff --git a/reference/hz_segment.html b/reference/hz_segment.html
index a271cf07..26a3db04 100644
--- a/reference/hz_segment.html
+++ b/reference/hz_segment.html
@@ -144,15 +144,12 @@ 
    Examples
    
 par(mar = c(0, 0, 3, 1))
 plotSPC(z, color = 'segment_id', width = 0.3)
 
-#> [1] 1.177614
 
 # highlight new horizon records
 par(mar = c(0, 0, 2, 1))
 plotSPC(z, color = NA, default.color = NA, width = 0.3, lwd = 1)
-#> [1] 1.177614
 plotSPC(sp1, color = NA, default.color = NA, 
 width = 0.3, lwd = 3, add = TRUE, name = NA, print.id = FALSE)
-#> [1] 1.177614
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 legend('top', horiz = TRUE, 
diff --git a/reference/hz_to_taxpartsize.html b/reference/hz_to_taxpartsize.html
index 63c706e0..923b4f6c 100644
--- a/reference/hz_to_taxpartsize.html
+++ b/reference/hz_to_taxpartsize.html
@@ -171,6 +171,11 @@ 
    Examples
    
 
 depths(h) <- id ~ top + bottom
 
+# set required metadata for estimatePSCS()
+hzdesgnname(h) <- "hzname"
+hztexclname(h) <- "texcl"
+hzmetaname(h, "clay") <- "clay"
+
 pscs <- data.frame(id = h$id, rbind(estimatePSCS(h)))
 names(pscs)[2:3] <- c("top", "bottom")
 
diff --git a/reference/hzmetaname.html b/reference/hzmetaname.html
new file mode 100644
index 00000000..ebad6264
--- /dev/null
+++ b/reference/hzmetaname.html
@@ -0,0 +1,200 @@
+
+Get or Set Horizon Metadata Column Name — hzmetaname • aqp
+    
+
+    
    
+      
    
+
+      
+
+      
    
+  
    
+    
    
+    
    Get or Set Horizon Metadata Column Name
    
+    Source: R/SoilProfileCollection-metadata.R
+    
+    
    
+
+    
    
+    
    hzmetaname(): Get column name containing horizon data of interest
    
+
    hzmetaname<-: Set horizon designation column name
    
+    
    
+
+    
    
+    
    # S4 method for SoilProfileCollection
+hzmetaname(object, attr, required = FALSE)
+
+# S4 method for SoilProfileCollection
+hzmetaname(object, attr, required = FALSE) <- value
    
+    
    
+
+    
    
+    
    Arguments
    
+    
    object
    
+
    A SoilProfileCollection
    
+
+
+
    attr
    
+
    character. Base name for attribute to be stored in metadata. This is prefixed with "aqp_hz" for horizon-level metadata for column attributes. e.g. attr="clay" results in metadata value retrieved from "aqp_hzclay".
    
+
+
+
    required
    
+
    logical. Is this attribute required? If it is, set to TRUE to trigger error on invalid value.
    
+
+
+
    value
    
+
    character. Name of horizon-level column containing  data corresponding to attr.
    
+
+
    
+    
    
+    
    Details
    
+    
    Store the column name containing a specific type of horizon data in the metadata slot of the SoilProfileCollection.
    
+    
    
+    
    
+    
    See also
    
+    
    guessHzAttrName()
    
+    
    
+
+    
    
+    
    Examples
    
+    
    
+data(sp1)
+
+# promote to SPC
+depths(sp1) <- id ~ top + bottom
+
+# set important metadata columns
+hzdesgnname(sp1) <- "name"
+hztexclname(sp1) <- "texture"
+
+# set custom horizon property (clay content) column
+hzmetaname(sp1, "clay") <- "prop"
+
+# inspect metadata list
+metadata(sp1)
+#> $aqp_df_class
+#> [1] "data.frame"
+#> 
+#> $aqp_group_by
+#> [1] ""
+#> 
+#> $aqp_hzdesgn
+#> [1] "name"
+#> 
+#> $aqp_hztexcl
+#> [1] "texture"
+#> 
+#> $depth_units
+#> [1] "cm"
+#> 
+#> $stringsAsFactors
+#> [1] FALSE
+#> 
+#> $aqp_hzclay
+#> [1] "prop"
+#> 
+
+# get horizon clay content column
+hzmetaname(sp1, "clay")
+#> [1] "prop"
+
+# uses hzdesgname(), hztexclname(), hzmetaname(attr="clay") in function definition
+estimatePSCS(sp1)
+#>     id pscs_top pscs_bottom
+#> 1 P001       49          89
+#> 2 P002       30          59
+#> 3 P003        2          52
+#> 4 P004       32          62
+#> 5 P005        5          55
+#> 6 P006       31         106
+#> 7 P007       25         100
+#> 8 P008       27         102
+#> 9 P009       28         103
+
    
+    
    
+  
    
+  
+
    
+
+
+      
    
+  
    Developed by Dylan Beaudette, Pierre Roudier, Andrew Brown.
    
+
    
+
+
    
+  
    Site built with pkgdown 2.0.9.
    
+
    
+
+      
    
+
+  
+
+
+  
+
+  
+
diff --git a/reference/index.html b/reference/index.html
index 8c18274e..e73626cf 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -538,6 +538,10 @@ 
    All functions `hzidname<-`(<SoilProfileCollection>) hzidname(<SoilProfileCollection>) 
    
         
         
    Set horizon ID column name
    
+      
+          
    hzmetaname(<SoilProfileCollection>) `hzmetaname<-`(<SoilProfileCollection>) 
    
+        
+        
    Get or Set Horizon Metadata Column Name
    
       
           
    hztexclname(<SoilProfileCollection>) `hztexclname<-`(<SoilProfileCollection>) 
    
         
diff --git a/reference/jacobs2000.html b/reference/jacobs2000.html
index f0a06311..8c5d64ee 100644
--- a/reference/jacobs2000.html
+++ b/reference/jacobs2000.html
@@ -113,7 +113,6 @@ 
    Examples
    
 # basic plot
 par(mar=c(0, 1, 3, 1.5))
 plotSPC(jacobs2000, name='name', color='matrix_color', width=0.3)
-#> [1] 0.8523367
 # add concentrations
 addVolumeFraction(jacobs2000, 'concentration_pct',
 col = jacobs2000$concentration_color, pch = 16, cex.max = 0.5)
@@ -121,7 +120,6 @@ 
    Examples
    
 
 # add depletions
 plotSPC(jacobs2000, name='name', color='matrix_color', width=0.3)
-#> [1] 0.8523367
 addVolumeFraction(jacobs2000, 'depletion_pct',
 col = jacobs2000$depletion_color, pch = 16, cex.max = 0.5)
 
@@ -129,7 +127,6 @@ 
    Examples
    
 # time saturated
 plotSPC(jacobs2000, color='time_saturated', cex.names=0.8, col.label = 'Time Saturated')
 
-#> [1] 0.4544975
 
 # color contrast: matrix vs. concentrations
 cc <- colorContrast(jacobs2000$matrix_color_munsell, jacobs2000$concentration_munsell)
diff --git a/reference/mollic.thickness.requirement.html b/reference/mollic.thickness.requirement.html
index e7470783..f25c62ab 100644
--- a/reference/mollic.thickness.requirement.html
+++ b/reference/mollic.thickness.requirement.html
@@ -83,9 +83,9 @@ 
    Calculate the minimum thickness requirement for Mollic epipedon
    
     
    
     
    mollic.thickness.requirement(
   p,
-  hzdesgn = guessHzDesgnName(p),
-  texcl.attr = guessHzTexClName(p),
-  clay.attr = guessHzAttrName(p, "clay", c("total", "_r")),
+  hzdesgn = hzdesgnname(p, required = TRUE),
+  texcl.attr = hztexclname(p, required = TRUE),
+  clay.attr = hzmetaname(p, "clay", required = TRUE),
   truncate = TRUE
 )
    
     
    
diff --git a/reference/munsell2spc-SoilProfileCollection-method.html b/reference/munsell2spc-SoilProfileCollection-method.html
index f3bc2693..7c3040b9 100644
--- a/reference/munsell2spc-SoilProfileCollection-method.html
+++ b/reference/munsell2spc-SoilProfileCollection-method.html
@@ -191,12 +191,10 @@ 
    Examples
    
 # plot rgb "R" coordinate by horizon
 plot(sp3, color = "rgb_R")
 
-#> [1] 0.4231771
 
 # plot lab "A" coordinate by horizon
 plot(sp3, color = "lab_A")
 
-#> [1] 0.4231771
 
 # note that `lab_A` values do not exactly match the original `A` values
 # this is because `lab_A` was computed from the (field determined) Munsell color notation,
diff --git a/reference/pbindlist.html b/reference/pbindlist.html
index eec1d671..67e9e195 100644
--- a/reference/pbindlist.html
+++ b/reference/pbindlist.html
@@ -133,7 +133,6 @@ 
    Examples
    
 # check
 plot(z)
 
-#> [1] 2.934726
 
    
     
    
   
    
diff --git a/reference/perturb.html b/reference/perturb.html
index d7fad6c4..32327c86 100644
--- a/reference/perturb.html
+++ b/reference/perturb.html
@@ -178,7 +178,6 @@ 
    Examples
    
 # plot
 par(mfrow = c(2, 1), mar = c(0, 0, 0, 0))
 plot(sim.1)
-#> [1] 2.815755
 mtext(
   'SD = 2',
   side = 2,
@@ -187,7 +186,6 @@ 
    Examples
    
   cex = 0.75
 )
 plot(sim.2)
-#> [1] 2.815755
 mtext(
   'SD = c(1, 2, 5, 5, 5, 10, 3)',
   side = 2,
diff --git a/reference/profileApply.html b/reference/profileApply.html
index b036d97a..a2e7f5ed 100644
--- a/reference/profileApply.html
+++ b/reference/profileApply.html
@@ -150,7 +150,6 @@ 
    Examples
    
 # scaled = (x - mean(x)) / sd(x)
 sp1$d <- profileApply(sp1, FUN=function(x) round(scale(x$prop), 2))
 plot(sp1, name='d')
-#> [1] 1.403299
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
@@ -160,7 +159,6 @@ 
    Examples
    
 f <- function(x) { c(x$prop[1], diff(x$prop)) }
 sp1$d <- profileApply(sp1, FUN=f)
 plot(sp1, name='d')
-#> [1] 1.403299
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
@@ -169,7 +167,6 @@ 
    Examples
    
 # note the use of an anonymous function
 sp1$d <- profileApply(sp1, FUN=function(x) cumsum(x$prop))
 plot(sp1, name='d')
-#> [1] 1.403299
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
@@ -181,7 +178,6 @@ 
    Examples
    
 
 # re-plot using ranks defined by computed summaries (in @site)
 plot(sp1, plot.order=rank(sp1$mean_prop))
-#> [1] 1.403299
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
@@ -319,13 +315,11 @@ 
    Examples
    
 # graphically check
 par(mfrow=c(2,1), mar=c(0,0,1,0))
 plot(sp1)
-#> [1] 1.142285
 #> [P001:6] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 points(1:length(sp1), sp1$dep, col='red', pch=7)
 plot(sp1.sub)
 
-#> [1] 1.142285
 
 
    
     
    
diff --git a/reference/profileGroupLabels.html b/reference/profileGroupLabels.html
index db1aac17..f84e37b5 100644
--- a/reference/profileGroupLabels.html
+++ b/reference/profileGroupLabels.html
@@ -175,7 +175,6 @@ 
    Examples
    
 # plot 2 SoilProfileCollection objects on the same axis
 par(mar=c(1,1,1,1))
 plotSPC(sp3, n = n.pedons)
-#> [1] 0.3664533
 plotSPC(sp4, add = TRUE, x.idx.offset = group.ends[1], 
 depth.axis = FALSE, id.style = 'side')
 
diff --git a/reference/profileInformationIndex.html b/reference/profileInformationIndex.html
index ae12b248..c334c381 100644
--- a/reference/profileInformationIndex.html
+++ b/reference/profileInformationIndex.html
@@ -187,7 +187,6 @@ 
    Examples
    
 # visual check
 par(mar = c(1, 0, 3, 3))
 plotSPC(z, color = 'p', name.style = 'center-center', cex.names = 0.8, max.depth = 110)
-#> [1] 0.09175395
 
 # factor version of horizon name
 z$fname <- factor(z$name)
diff --git a/reference/quickSPC.html b/reference/quickSPC.html
index 50077650..8275a438 100644
--- a/reference/quickSPC.html
+++ b/reference/quickSPC.html
@@ -149,7 +149,6 @@ 
    Examples
    
 s <- quickSPC(x)
 plotSPC(s, name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.0526272
 
 # character template, mode 1
 # horizon thickness is generated at random (uniform [5,20])
@@ -158,7 +157,6 @@ 
    Examples
    
 s <- quickSPC(x)
 plotSPC(s, name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.1835554
 
 
 # multiple templates
@@ -172,7 +170,6 @@ 
    Examples
    
 s <- quickSPC(x)
 plotSPC(s, name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.6017337
 
 
 # optionally specify profile IDs using "ID:" prefix
@@ -185,7 +182,6 @@ 
    Examples
    
 s <- quickSPC(x)
 plotSPC(s, name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.1578816
 
 
 # optionally specify:
@@ -199,7 +195,6 @@ 
    Examples
    
 s <- quickSPC(x)
 plotSPC(s, name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.3094048
 
 # use newline character as delimiter, more compact
 x <- 'Oe,10,10YR 2/2
@@ -211,7 +206,6 @@ 
    Examples
    
 
 plotSPC(quickSPC(x), name.style = 'center-center', cex.names = 1)
 
-#> [1] 0.1865946
 
 
 # character template, mode 2
@@ -232,7 +226,6 @@ 
    Examples
    
         hz.depths = TRUE
 )
 
-#> [1] 0.5846978
 
 # each horizon label is '5' depth-units
 s <- quickSPC(x, interval = 5)
@@ -241,7 +234,6 @@ 
    Examples
    
         hz.depths = TRUE
 )
 
-#> [1] 0.600454
 
 # optionally specify some / all profile IDs with "ID:" prefix
 x <- c(
@@ -256,7 +248,6 @@ 
    Examples
    
         hz.depths = TRUE
 )
 
-#> [1] 0.3052458
 
 
 # make a NODATA profile, with a random hash ID
@@ -268,7 +259,6 @@ 
    Examples
    
         cex.names = 1, depth.axis = FALSE, 
         hz.depths = TRUE)
 
-#> [1] 0.2012711
 
 
 
    
diff --git a/reference/random_profile.html b/reference/random_profile.html
index e9278ef3..e3662eb4 100644
--- a/reference/random_profile.html
+++ b/reference/random_profile.html
@@ -214,7 +214,6 @@ 
    Examples
    
 opar <- par(mar=c(0,0,3,2))
 plotSPC(d, color='p1', name='name', cex.names=0.75)
 
-#> [1] 0.1832267
 par(opar)
 
 # simulate horizon boundary distinctness codes:
@@ -226,7 +225,6 @@ 
    Examples
    
 opar <- par(mar=c(0,0,3,2))
 plotSPC(d, name='name', color='p1', hz.distinctness.offset='HzD')
 
-#> [1] 0.3664533
 par(opar)
 
 
@@ -239,7 +237,6 @@ 
    Examples
    
 
 # plot
 plotSPC(d.1, name='name', color='p1', col.label = 'LPP Defaults')
-#> [1] 0.3444661
 
 
 # do this again, this time set all of the LPP parameters
@@ -250,7 +247,6 @@ 
    Examples
    
 # plot
 plotSPC(d.2, name='name', color='p1', col.label = 'Custom LPP Parameters')
 
-#> [1] 0.3444661
 
 
 # reset plotting defaults
diff --git a/reference/repairMissingHzDepths.html b/reference/repairMissingHzDepths.html
index 493c8576..11e73b9f 100644
--- a/reference/repairMissingHzDepths.html
+++ b/reference/repairMissingHzDepths.html
@@ -125,7 +125,6 @@ 
    Examples
    
 
 # inspect data before repairs
 plotSPC(h)
-#> [1] 0.1154119
 #> [1:3] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 #> [2:4] horizon with top == bottom, cannot fix horizon depth overlap
@@ -141,7 +140,6 @@ 
    Examples
    
 # inspect
 plotSPC(g)
 
-#> [1] 0.1154119
 
 # no adj, max.depth only
 f <- repairMissingHzDepths(h, adj = NA, max.depth = 200)
@@ -149,7 +147,6 @@ 
    Examples
    
 #> [1] TRUE
 plotSPC(f)
 
-#> [1] 0.1154119
 
 # max.depth defaults to max(x) if too small
 f$bottom[c(3,7)] <- NA
@@ -159,7 +156,6 @@ 
    Examples
    
 #> [1] TRUE
 plotSPC(d)
 
-#> [1] 0.1154119
 
 
    
     
    
diff --git a/reference/rowley2019.html b/reference/rowley2019.html
index 65f31be7..41fb7a9f 100644
--- a/reference/rowley2019.html
+++ b/reference/rowley2019.html
@@ -275,16 +275,13 @@ 
    Examples
    
 par(mar=c(1,1,3,1))
 plotSPC(rowley2019, color='Feo_Fed', name='name', cex.names=0.85)
 
-#> [1] 0.2308428
 
 plotSPC(rowley2019, color='Ca_exch', name='name', cex.names=0.85)
-#> [1] 0.2308428
 
 # grouped plot
 groupedProfilePlot(rowley2019, groups = 'group', color='Ca_exch',
 name='name', cex.names=0.85, group.name.offset = -10)
 
-#> [1] 0.2308428
 
 # aggregate over 1cm slices, for select properties
 a <- slab(rowley2019, group ~ Reactive_carbonate + Ca_exch + pH + K_Feldspar + Na_Plagioclase + Al)
diff --git a/reference/sierraTransect.html b/reference/sierraTransect.html
index 04d87e84..af706634 100644
--- a/reference/sierraTransect.html
+++ b/reference/sierraTransect.html
@@ -122,7 +122,6 @@ 
    Examples
    
 # quick sketch
 plotSPC(sierraTransect, name.style = 'center-center', width=0.3)
 
-#> [1] 2.358138
 
 # split by transect
 par(mar=c(0,0,1,1))
@@ -132,7 +131,6 @@ 
    Examples
    
 name.style='center-center'
 )
 
-#> [1] 2.43107
 
 # thematic
 groupedProfilePlot(
@@ -141,7 +139,6 @@ 
    Examples
    
 name.style='center-center', color='Fe_o_to_Fe_d'
 )
 
-#> [1] 2.43107
 
 # horizon boundary viz
 sierraTransect$hzd <- hzDistinctnessCodeToOffset(substr(sierraTransect$hz_boundary, 0, 1))
@@ -151,7 +148,6 @@ 
    Examples
    
 width=0.3, name.style='center-center', color='Fe_o_to_Fe_d',
 hz.distinctness.offset='hzd')
 
-#> [1] 2.43107
 
 
 # split transects
@@ -164,11 +160,9 @@ 
    Examples
    
 # order (left -> right) by elevation
 par(mar=c(2,0,0,2), mfrow=c(2,1))
 plot(g, width=0.3, name.style='center-center', cex.names=0.75, plot.order=g.order)
-#> [1] 0.7214442
 axis(1, at=1:length(g), labels=g$elev[g.order], line=-1.5)
 
 plot(a, width=0.3, name.style='center-center', cex.names=0.75, plot.order=a.order)
-#> [1] 0.5329192
 axis(1, at=1:length(a), labels=a$elev[a.order], line=-1.5)
 
 
diff --git a/reference/slice.html b/reference/slice.html
index f9c60bf7..ed8c09c6 100644
--- a/reference/slice.html
+++ b/reference/slice.html
@@ -203,7 +203,6 @@ 
    Examples
    
 par(mar=c(0,1,0,1))
 plotSPC(s)
 
-#> [1] 1.032732
 
 # generate slices from 0 - 11 cm, for all variables
 s <- dice(d, fm = 0:10 ~ .)
diff --git a/reference/sp1.html b/reference/sp1.html
index e33b6d46..f136e001 100644
--- a/reference/sp1.html
+++ b/reference/sp1.html
@@ -159,7 +159,6 @@ 
    Examples
    
 # plot, note slices
 plot(s)
 
-#> [1] 1.403299
 
 
 # aggregate all profiles along 1 cm depth slices,
diff --git a/reference/sp2.html b/reference/sp2.html
index fe36033b..f8479a59 100644
--- a/reference/sp2.html
+++ b/reference/sp2.html
@@ -185,14 +185,12 @@ 
    Examples
    
 par(mar=c(1,0,3,0))
 plot(sp2, plot.order=p.order)
 
-#> [1] 2.922331
 
 # setup multi-figure output
 par(mfrow=c(2,1), mar=c(0,0,1,0))
 
 # truncate plot to 200 cm depth
 plot(sp2, plot.order=p.order, max.depth=200)
-#> [1] 2.922331
 abline(h=200, lty=2, lwd=2)
 
 # compute numerical distances between profiles
diff --git a/reference/sp3.html b/reference/sp3.html
index a9f2bba9..dec705a7 100644
--- a/reference/sp3.html
+++ b/reference/sp3.html
@@ -273,13 +273,11 @@ 
    Examples
    
 #>  $ contributing_fraction: num  0.89 1 1 1 1 1 0.9 0.9 0.58 0.15 ...
 #>  $ top                  : int  0 10 20 30 40 50 60 70 80 90 ...
 #>  $ bottom               : int  10 20 30 40 50 60 70 80 90 100 ...
-#> [1] 0.7949667
 #> Computing dissimilarity matrices from 13 profiles
 #>  [0.3 Mb]
 
 
 
-#> [1] 0.2290074
 
    
     
    
   
    
diff --git a/reference/sp4.html b/reference/sp4.html
index 593cdafc..71f46012 100644
--- a/reference/sp4.html
+++ b/reference/sp4.html
@@ -409,7 +409,6 @@ 
    Examples
    
 
 # basic plot method, highly customizable: see manual page ?plotSPC
 plot(sp4)
-#> [1] 2.517548
 # inspect plotting area, very simple to overlay graphical elements
 abline(v=1:length(sp4), lty=3, col='blue')
 # profiles are centered at integers, from 1 to length(obj)
@@ -423,10 +422,8 @@ 
    Examples
    
 par(mar=c(0,0,4,0))
 plot(sp4, color='clay')
 
-#> [1] 2.049284
 plot(sp4, color='CF')
 
-#> [1] 2.049284
 
 # apply a function to each profile, returning a single value per profile,
 # in the same order as profile_id(sp4)
@@ -464,7 +461,6 @@ 
    Examples
    
 par(mar=c(0,0,0,0))
 plot(sp4, plot.order=new.order)
 
-#> [1] 2.049284
 
 # deconstruct SoilProfileCollection into a data.frame, with horizon+site data
 as(sp4, 'data.frame')
diff --git a/reference/sp6.html b/reference/sp6.html
index 9daf25ed..f8d42ee8 100644
--- a/reference/sp6.html
+++ b/reference/sp6.html
@@ -156,27 +156,22 @@ 
    Examples
    
   # profile sketches
   par(mar=c(0,0,3,0))
   plot(sp6, color='soil_color')
-#> [1] 0.50625
 #> [A-1:12] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
   plot(sp6, color='Mn')
-#> [1] 0.50625
 #> [A-1:12] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
   plot(sp6, color='Fe')
-#> [1] 0.50625
 #> [A-1:12] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
   plot(sp6, color='pH')
-#> [1] 0.50625
 #> [A-1:12] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
   plot(sp6, color='texture')
-#> [1] 0.50625
 #> [A-1:12] horizon with top == bottom, cannot fix horizon depth overlap
 #>  consider using repairMissingHzDepths()
 
diff --git a/reference/spc2mpspline-SoilProfileCollection-method.html b/reference/spc2mpspline-SoilProfileCollection-method.html
index bddca74c..fcbf6365 100644
--- a/reference/spc2mpspline-SoilProfileCollection-method.html
+++ b/reference/spc2mpspline-SoilProfileCollection-method.html
@@ -150,7 +150,6 @@ 
    Examples
    
   plotSPC(res[1:5,], color = "prop_spline", divide.hz = FALSE)
 }
 
-#> [1] 0.7796104
 
    
     
    
   
    
diff --git a/reference/subsetHz-SoilProfileCollection-method.html b/reference/subsetHz-SoilProfileCollection-method.html
index c27a3658..e1c8a300 100644
--- a/reference/subsetHz-SoilProfileCollection-method.html
+++ b/reference/subsetHz-SoilProfileCollection-method.html
@@ -120,7 +120,6 @@ 
    Examples
    
 # show just horizons with 10YR hues
 plot(subsetHz(sp3, hue == '10YR'))
 
-#> [1] 0.3462358
 
 
    
     
    
diff --git a/reference/subsetProfiles.html b/reference/subsetProfiles.html
index 7740a44d..a7cba35c 100644
--- a/reference/subsetProfiles.html
+++ b/reference/subsetProfiles.html
@@ -134,20 +134,17 @@ 
    Examples
    
 # subset by integer index, note that this does not re-order the profiles
 plot(sp2[1:5, ])
 
-#> [1] 1.044266
 
 # generate an integer index via pattern-matching
 idx <- grep('modesto', sp2$surface, ignore.case=TRUE)
 plot(sp2[idx, ])
 
-#> [1] 1.578496
 
 # generate in index via profileApply:
 # subset those profiles where: min(ph) < 5.6
 idx <- which(profileApply(sp2, function(i) min(i$field_ph, na.rm=TRUE) < 5.6))
 plot(sp2[idx, ])
 
-#> [1] 0.8661893
 
 
    
     
    
diff --git a/reference/thompson.bell.darkness.html b/reference/thompson.bell.darkness.html
index 6d5a8ed1..cf99b3d3 100644
--- a/reference/thompson.bell.darkness.html
+++ b/reference/thompson.bell.darkness.html
@@ -83,7 +83,7 @@ 
    Thompson-Bell (1996) Index
    
     
    
     
    thompson.bell.darkness(
   p,
-  name = guessHzDesgnName(p, required = TRUE),
+  name = hzdesgnname(p, required = TRUE),
   pattern = "^A",
   value = "m_value",
   chroma = "m_chroma"
diff --git a/reference/unique.html b/reference/unique.html
index 2add8980..eb9a68fc 100644
--- a/reference/unique.html
+++ b/reference/unique.html
@@ -133,23 +133,18 @@ 
    Examples
    
   # graphical check
   plotSPC(x.dupes, name.style = 'center-center')
 
-#> [1] 0.7134265
   plotSPC(x.sim, name.style = 'center-center')
 
-#> [1] 0.7134265
   
   # inspect unique results
   plotSPC(unique(x.dupes, vars = c('top', 'bottom')), name.style = 'center-center')
 
-#> [1] 0.1426853
   
   # uniqueness is a function of variable selection
   plotSPC(unique(x.sim, vars = c('top', 'bottom')), name.style = 'center-center')
 
-#> [1] 0.7134265
   plotSPC(unique(x.sim, vars = c('name')), name.style = 'center-center')
 
-#> [1] 0.1426853
   
 
 
diff --git a/reference/warpHorizons.html b/reference/warpHorizons.html
index 1dfd542d..ee9749b0 100644
--- a/reference/warpHorizons.html
+++ b/reference/warpHorizons.html
@@ -150,7 +150,6 @@ 
    Examples
    
   depth.axis = list(line = -3), 
   y.offset = .yoff
 )
-#> [1] 0.1062791
 #> depth axis is disabled when more than 1 unique y offsets are supplied
 
 # illustrate warping with arrows
@@ -195,7 +194,6 @@ 
    Examples
    
   depth.axis = list(line = -2)
 )
 
-#> [1] 0.3265414
 
 
 
    
diff --git a/reference/wilson2022.html b/reference/wilson2022.html
index fa5c7dfa..50ac5a01 100644
--- a/reference/wilson2022.html
+++ b/reference/wilson2022.html
@@ -135,7 +135,6 @@ 
    Examples
    
 cex.names = 0.66, cex.id = 0.66, width = 0.3, 
 depth.axis = FALSE, hz.depths = TRUE)
 
-#> [1] 1.189991
 
 groupedProfilePlot(wilson2022, groups = 'biome', 
 group.name.offset = -15, label = 'pm', 
@@ -143,7 +142,6 @@ 
    Examples
    
 cex.names = 0.66, cex.id = 0.66, width = 0.3, 
 depth.axis = FALSE, hz.depths = TRUE)
 
-#> [1] 1.02759
 
 
    
     
    
diff --git a/sitemap.xml b/sitemap.xml
index f02eff82..4ad94b71 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -381,6 +381,9 @@
   
     /reference/hzidname.html
   
+  
+    /reference/hzmetaname.html
+  
   
     /reference/hztexclname.html