Merge branch 'master' into collapseHz

.github/workflows/R-CMD-check.yaml

@@ -34,10 +34,9 @@ jobs:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
       RSPM: ${{ matrix.config.rspm }}
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
-
+      
     steps:
-      - uses: actions/checkout@v4
-
+      - uses: actions/checkout@v4        
       - uses: r-lib/actions/setup-r@v2
         with:
           r-version: ${{ matrix.config.r }}
@@ -52,15 +51,8 @@ jobs:
           brew install --cask xquartz
           
       - uses: r-lib/actions/setup-r-dependencies@v2
-        if: matrix.config.r == '3.6'
         with:
-          extra-packages: any::rcmdcheck, soiltexture=?ignore-before-r=4.3.0, markovchain=?ignore-before-r=4.0.0, Hmisc=?ignore
-          needs: check
-
-      - uses: r-lib/actions/setup-r-dependencies@v2
-        if: matrix.config.r != '3.6'
-        with:
-          extra-packages: any::rcmdcheck, markovchain=?ignore-before-r=4.0.0
+          extra-packages: any::rcmdcheck, soiltexture=?ignore-before-r=4.3.0, sf=?ignore-before-r=4.0.0, markovchain=?ignore-before-r=4.0.0, Hmisc=?ignore, knitr=?ignore-before-r=4.0.0, rmarkdown=?ignore-before-r=4.0.0, testthat=?ignore-before-r=4.0.0,
           needs: check
 
       - name: Install soilDB from r-universe (R-devel only)
@@ -70,6 +62,14 @@ jobs:
         shell: Rscript {0}
 
       - uses: r-lib/actions/check-r-package@v2
+        if: matrix.config.r != '3.6'
+        with:
+          upload-snapshots: true
+
+      - uses: r-lib/actions/check-r-package@v2
+        if: matrix.config.r == '3.6'
         with:
+          args: 'c("--no-manual", "--as-cran", "--ignore-vignettes", "--no-tests")'
+          build_args: 'c("--no-manual", "--no-build-vignettes")'
           upload-snapshots: true
 

CITATION.cff

@@ -19,7 +19,7 @@ abstract: The Algorithms for Quantitative Pedology (AQP) project was started in
   the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>.
   These functions and data structures have been extensively tested and documented,
   applied to projects involving hundreds of thousands of soil profiles, and deeply
-  integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>.
+  integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>.
   Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve
   an important role in routine data analysis within the USDA-NRCS Soil Science Division.
   The AQP suite of R packages offer a convenient platform for bridging the gap between

DESCRIPTION

@@ -1,20 +1,20 @@
 Package: aqp
-Version: 2.0.3
+Version: 2.1.0
 Title: Algorithms for Quantitative Pedology
 Authors@R: c(person(given="Dylan", family="Beaudette", role = c("aut", "cre"), email = "[email protected]"), person(given="Pierre", family="Roudier", email="[email protected]", role = c("aut", "ctb")), person(given="Andrew", family="Brown", email="[email protected]", role = c("aut", "ctb")))
 Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]
 Maintainer: Dylan Beaudette <[email protected]>
 Depends: R (>= 3.5.0)
-Imports: grDevices, graphics, stats, utils, methods, grid, lattice, cluster, sp, stringr, data.table, farver
-Suggests: colorspace, ape, soilDB, sf, latticeExtra, tactile, compositions, sharpshootR, markovchain, xtable, testthat, Gmedian, Hmisc, tibble, RColorBrewer, scales, digest, MASS, mpspline2, soiltexture, gower, knitr, rmarkdown, plyr
-Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
+Imports: grDevices, graphics, stats, utils, methods, grid, lattice, cluster, stringr, data.table, farver
+Suggests: mvtnorm, colorspace, ape, soilDB, sp, sf, latticeExtra, tactile, compositions, sharpshootR, markovchain, xtable, testthat, Gmedian, Hmisc, tibble, RColorBrewer, scales, digest, MASS, mpspline2, soiltexture, gower, knitr, rmarkdown, plyr
+Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
 License: GPL (>= 3)
 LazyLoad: yes
 Repository: CRAN
 URL: https://github.com/ncss-tech/aqp, https://ncss-tech.github.io/AQP/
 BugReports: https://github.com/ncss-tech/aqp/issues
 Language: en-US
 Encoding: UTF-8
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.2
 Roxygen: list(markdown = TRUE)
 VignetteBuilder: knitr

NAMESPACE

@@ -96,7 +96,13 @@ export(hzOffset)
 export(hzTopographyCodeToLineType)
 export(hzTopographyCodeToOffset)
 export(hzTransitionProbabilities)
+export(hz_dissolve)
+export(hz_intersect)
+export(hz_lag)
+export(hz_segment)
+export(hz_to_taxpartsize)
 export(invertLabelColor)
+export(lookup_taxpartsize)
 export(lunique)
 export(maxDepthOf)
 export(minDepthOf)
@@ -139,6 +145,7 @@ export(slice.fast)
 export(slicedHSD)
 export(soilColorSignature)
 export(soilPalette)
+export(soilTextureColorPal)
 export(spc_in_sync)
 export(spec2Munsell)
 export(splitLogicErrors)
@@ -152,6 +159,7 @@ export(texmod_to_fragvoltot)
 export(textureTriangleSummary)
 export(texture_to_taxpartsize)
 export(texture_to_texmod)
+export(thicknessOf)
 export(thompson.bell.darkness)
 export(unroll)
 export(warpHorizons)
@@ -169,6 +177,7 @@ exportMethods("horizons<-")
 exportMethods("hzID<-")
 exportMethods("hzdesgnname<-")
 exportMethods("hzidname<-")
+exportMethods("hzmetaname<-")
 exportMethods("hztexclname<-")
 exportMethods("initSpatial<-")
 exportMethods("metadata<-")
@@ -201,6 +210,7 @@ exportMethods(hzID)
 exportMethods(hzMetadata)
 exportMethods(hzdesgnname)
 exportMethods(hzidname)
+exportMethods(hzmetaname)
 exportMethods(hztexclname)
 exportMethods(idname)
 exportMethods(isEmpty)
@@ -233,8 +243,6 @@ exportMethods(trunc)
 exportMethods(unique)
 exportMethods(validSpatialData)
 import(data.table)
-importClassesFrom(sp,SpatialPoints)
-importClassesFrom(sp,SpatialPointsDataFrame)
 importFrom(cluster,daisy)
 importFrom(cluster,pam)
 importFrom(cluster,silhouette)
@@ -298,11 +306,6 @@ importFrom(methods,setOldClass)
 importFrom(methods,setReplaceMethod)
 importFrom(methods,slot)
 importFrom(methods,slotNames)
-importFrom(sp,"coordinates<-")
-importFrom(sp,"proj4string<-")
-importFrom(sp,SpatialPoints)
-importFrom(sp,coordinates)
-importFrom(sp,proj4string)
 importFrom(stats,TukeyHSD)
 importFrom(stats,aggregate)
 importFrom(stats,aov)
@@ -311,6 +314,7 @@ importFrom(stats,as.dist)
 importFrom(stats,as.formula)
 importFrom(stats,cmdscale)
 importFrom(stats,complete.cases)
+importFrom(stats,cov)
 importFrom(stats,dist)
 importFrom(stats,formula)
 importFrom(stats,median)

NEWS.md

@@ -1,6 +1,22 @@
-# aqp 2.0.3 (2023-12-19)
- * performance improvements in `profileInformationIndex()`
+# aqp 2.1.0 (2024-10-10)
+ * added Munsell values of 8.5 and 9.5 to Munsell look up table and (interpolated) reference spectra (#318)
+ * `munsell2rgb()` now safely selects the closest Munsell value and chroma to those available in the package LUT 
+ * new function `soilTextureColorPal()` for suggesting a color palette suitable for soil texture class
+ * **Breaking Change**: `@sp` slot of the SoilProfileCollection object, and dependency on sp package, has been removed. 
+  * Any SoilProfileCollection objects previously written to file (.rda, .rds) with aqp <2.1.x will need to be rebuilt using `rebuildSPC()` due to changes to S4 object structure
+
+# aqp 2.0.4 (2024-07-30)
+ * CRAN release
+ * ragged bottom lines in `plotSPC()` now adjusted as function of number of profiles and device width
+ * additional metadata from `plotSPC()` saved to `last_spc_plot` in `aqp.env`
+
+# aqp 2.0.3 (2024-04-18)
+ * CRAN release
+ * `simulateColor()` gains new method `mvnorm` for simulating plausible colors
+   - package mvtnorm added to SUGGESTS
+ * performance improvements in `profileInformationIndex()`, `dice()`, `slab()`, `spc2mpspline()`, `fillHzGaps()`, and `flagOverlappingHz()`
  * aesthetic improvements in `huePositionCircle()`
+ * new function `thicknessOf()` used for calculating thickness of horizons within each profile of a `SoilProfileCollection` based on horizon-level logical expressions encoded in a function. Default behavior uses pattern matching on the horizon designation name.
 
 # aqp 2.0.2 (2023-11-18)
  * CRAN release
@@ -598,7 +614,7 @@ Incremental changes, should have no effect on previous code:
 
 # aqp 1.0 (2012-03-26)
    * 1.0 release, still missing condensed vignettes- should be ready soon
-   * see http://casoilresource.lawr.ucdavis.edu/drupal/taxonomy/term/56 for samples
+   * see https://casoilresource.lawr.ucdavis.edu/drupal/taxonomy/term/56 for samples
    * A small bug in profile_compare() was fixed, where slices were evaluated as 'soil' based on the bottom depth of the profile, and NOT on the presence of actual data. See ?profile_compare for details. This change will have a minor affect on profile comparisons in cases where Cr or R horizons (usually missing most characterization data) have been extended down to some arbitrary depth (usually 150 or 200 cm) AND a maximum depth of evaluation (max_d) was set beyond the actual depth of most profiles in the collection.
 
 # aqp 0.99-9.8 (2012-03-02)

R/AAAA.R

@@ -5,7 +5,6 @@ aqp.env <- new.env(hash = TRUE, parent = parent.frame())
 # register options for later use
 .onLoad <- function(libname, pkgname) {
   options(.aqp.show.n.cols = 10)
-
 }
 
 # no longer needed since it is imported

R/Class-SoilProfileCollection.R

@@ -9,28 +9,24 @@
 #' @slot metadata list.
 #' @slot horizons data.frame.
 #' @slot site data.frame.
-#' @slot sp SpatialPoints.
 #' @slot diagnostic data.frame.
 #' @slot restrictions data.frame.
+#' 
+#' @details
+#' After aqp 2.0.2, the `@sp` slot was removed from the SoilProfileCollection object. If you run into errors related to old object definitions, use `rebuildSPC()` on the problematic object.
+#' 
 #' @aliases SoilProfileCollection-class
 #' @rdname SoilProfileCollection-class
-#' @importFrom sp SpatialPoints proj4string coordinates proj4string<- coordinates<-
-#' @importClassesFrom sp SpatialPoints SpatialPointsDataFrame
 setClass(
   Class = 'SoilProfileCollection',
   representation = representation(
     idcol = 'character', # column name containing IDs
     hzidcol = 'character', # column name containing unique horizon IDs
     depthcols = 'character', # 2 element vector with column names for hz top, bottom
-
     metadata = 'list', # list with key-value mapping
-
     horizons = 'data.frame', # all horizons sorted by ID & top depth
-
     site = 'data.frame', # data about the sampling sites
-
-    sp = 'SpatialPoints', # spatial data stored here, initialized as 'empty' sp object
-
+    # sp = 'NULL', # no longer used, formerly 'empty' sp object
     diagnostic = 'data.frame',# (optional) diagnostic horizons are stored here
     restrictions = 'data.frame' # (optional) restrictions are stored here
   ),
@@ -47,7 +43,7 @@ setClass(
                           top = numeric(0), bottom = numeric(0),
                           stringsAsFactors = FALSE),
     site = data.frame(id = character(0), stringsAsFactors = FALSE),
-    sp = sp::SpatialPoints(data.frame(x = 0, y = 0))[-1, ],
+    # sp = NULL, 
     diagnostic = data.frame(stringsAsFactors = FALSE),
     restrictions = data.frame(stringsAsFactors = FALSE)
   ),
@@ -61,18 +57,18 @@ setClass(
 # c/o: https://gis.stackexchange.com/questions/291069/creating-empty-spatialpoints-or-spatialpointsdataframe-in-r
 # old: new('SpatialPoints')
 # new: SpatialPoints(data.frame(x = 0, y = 0))[-1,]
+# new new: NULL
 
 #' Constructor for the SoilProfileCollection object
 #'
-#' @param idcol character Profile ID Column Name
-#' @param hzidcol character Horizon ID Column Name
-#' @param depthcols character, length 2 Top and Bottom Depth Column Names
-#' @param metadata list, metadata including data.frame class in use and depth units
-#' @param horizons data.frame An object inheriting from data.frame containing Horizon data.
-#' @param site data.frame An object inheriting from data.frame containing Site data.
-#' @param sp SpatialPoints A SpatialPoints object. No longer used in aqp 2+, see `?initSpatial`
-#' @param diagnostic data.frame An object inheriting from data.frame containing diagnostic feature data. Must contain profile ID. See \code{diagnostic_hz()}
-#' @param restrictions data.frame An object inheriting from data.frame containing restrictive feature data. Must contain profile ID. See \code{restrictions()}
+#' @param idcol character. Profile ID Column Name
+#' @param hzidcol character. Horizon ID Column Name
+#' @param depthcols character. length 2 Top and Bottom Depth Column Names
+#' @param metadata list. metadata including data.frame class in use and depth units
+#' @param horizons data.frame. An object inheriting from data.frame containing Horizon data.
+#' @param site data.frame. An object inheriting from data.frame containing Site data.
+#' @param diagnostic data.frame. An object inheriting from data.frame containing diagnostic feature data. Must contain profile ID. See \code{diagnostic_hz()}
+#' @param restrictions data.frame. An object inheriting from data.frame containing restrictive feature data. Must contain profile ID. See \code{restrictions()}
 #'
 #' @description In general, one should use \code{depths()} to initiate a SoilProfileCollection object from data. However, sometimes there are instances where either an empty, or very specific, object is needed. If that is the case, the general constructor \code{SoilProfileCollection} is available.
 #'
@@ -184,7 +180,7 @@ setClass(
              stringsAsFactors = FALSE
            ),
            site = data.frame(id = character(0), stringsAsFactors = FALSE),
-           sp = new('SpatialPoints'),
+           # sp = NULL, 
            diagnostic = data.frame(stringsAsFactors = FALSE),
            restrictions = data.frame(stringsAsFactors = FALSE)) {
 
@@ -200,16 +196,9 @@ setClass(
       aqp_hzdesgn = "",
       aqp_hztexcl = "",
       depth_units = 'cm',
-      stringsAsFactors = FALSE,
-
-      # calculate data order (original)
-      original.order = order(as.character(horizons[[idcol]]),
-                             horizons[[depthcols[1]]])
+      stringsAsFactors = FALSE
     )
 
-    # the target order to check/maintain is the default for a new SPC
-    # metadata$target.order <- metadata$original.order
-
     # add any custom metadata
     metadata <- c(metadata,
                   new.metadata[!names(new.metadata) %in% names(metadata)])
@@ -234,7 +223,7 @@ setClass(
       metadata = metadata,
       horizons = .as.data.frame.aqp(horizons, hzclass),
       site = .as.data.frame.aqp(site, hzclass),
-      sp = sp,
+      # sp = sp,
       diagnostic = .as.data.frame.aqp(diagnostic, hzclass),
       restrictions = .as.data.frame.aqp(restrictions, hzclass)
     )
@@ -955,10 +944,12 @@ setMethod("site", signature(object = "SoilProfileCollection"),
 setGeneric("diagnostic_hz", function(object, ...)
   standardGeneric("diagnostic_hz"))
 
-#' Retrieve diagnostic data from SoilProfileCollection
-#'
-#' @description Get diagnostic feature data from SoilProfileCollection. Result is returned in the same \code{data.frame} class used to initially construct the SoilProfileCollection.
+#' Get or Set Diagnostic Horizon data in a SoilProfileCollection
 #'
+#' @description Diagnostic horizons describe features of the soil relevant to taxonomic classification. A single profile may have multiple diagnostic features or horizons, each of which may be comprised of multiple horizons.
+#' 
+#'  - `diagnostic_hz()` (get method): Get diagnostic feature data from a SoilProfileCollection. 
+#'  
 #' @param object a SoilProfileCollection
 #'
 #' @docType methods
@@ -975,9 +966,11 @@ setMethod(f = 'diagnostic_hz', signature(object = 'SoilProfileCollection'),
 setGeneric("restrictions", function(object, ...)
   standardGeneric("restrictions"))
 
-#' Retrieve restriction data from SoilProfileCollection
+#' Get or Set Restriction data in a SoilProfileCollection
 #'
-#' @description Get restriction data from SoilProfileCollection. Result is returned in the same \code{data.frame} class used to initially construct the SoilProfileCollection.
+#' @description Restrictions describe root-limiting features in the soil. A single profile may have multiple restrictions.
+#' 
+#'  - `restrictions()` (get method): Get restriction data from a SoilProfileCollection. 
 #'
 #' @param object a SoilProfileCollection
 #' @docType methods

R/L1_profiles.R

@@ -86,9 +86,9 @@
 L1_profiles <- function(x, fm, basis = 1, method = c('regex', 'simple', 'constant'), maxDepthRule = c('max', 'min'), maxDepthConstant = NULL) {
 
   # sanity check, need this for L1 median
-  if(!requireNamespace('Gmedian'))
-    stop('package `Gmedian` is required', call.=FALSE)
-
+  if(!requireNamespace('Gmedian')) {
+    stop('package `Gmedian` is required', call. = FALSE)
+  }
 
   # sanity checks: is this an SPC?
   if(! inherits(x, 'SoilProfileCollection')) {

R/SoilProfileCollection-coercion.R

@@ -12,7 +12,7 @@
 #' @docType methods
 #' @rdname coercion-methods
 #'
-#' @examples 
+#' @examples
 #' # load example data stored as SoilProfileCollection
 #' data(sp5)
 #' 
@@ -30,11 +30,19 @@
 #' sp5$x <- sp5$y <- rnorm(length(sp5))
 #' initSpatial(sp5, crs = "OGC:CRS84") <- ~ x + y
 #' 
-#' # SpatialPointsDataFrame output
-#' str(as(sp5, 'SpatialPointsDataFrame'))
+#' if (requireNamespace("sf")) {
+#' 
+#'   # sf output
+#'   str(as(sp5, 'sf'))
+#' 
+#'   # SpatialPointsDataFrame output
+#'   str(as(sp5, 'SpatialPointsDataFrame'))
+#' 
+#'   # SpatialPoints output
+#'   str(as(sp5, 'SpatialPoints'))
+#'   
+#' }
 #' 
-#' # SpatialPoints output
-#' str(as(sp5, 'SpatialPoints'))
 setAs("SoilProfileCollection", "list", function(from) {
 
   # get slot names from prototype