improve unit test coverage #143

R/AAAA.R

@@ -1,9 +1,8 @@
 
 # setup a new environment to store error messages, etc.
-aqp.env <- new.env(hash=TRUE, parent = parent.frame())
+aqp.env <- new.env(hash = TRUE, parent = parent.frame())
 
 # register options for later use
 .onLoad <- function(libname, pkgname) {
-  options(.aqp.show.n.cols=10)
-
+  options(.aqp.show.n.cols = 10)
 }

R/Class-SoilProfileCollection.R

@@ -230,6 +230,7 @@ if(requireNamespace("tibble", quietly = TRUE))
     # "allow" NULL for the optional slots
     if(length(metadata$aqp_hzdesgn) == 0)
       metadata$aqp_hzdesgn <- ""
+
     if(length(metadata$aqp_hztexcl) == 0)
       metadata$aqp_hztexcl <- ""
 
@@ -317,8 +318,7 @@ setMethod(f = 'show',
                              hzdesgnname(object)), names(h))
             } else {
               # undefined
-              idx <-
-                match(c(idname(object), hzidname(object), horizonDepths(object)), names(h))
+              idx <- match(c(idname(object), hzidname(object), horizonDepths(object)), names(h))
             }
 
             # determine number of columns to show, and index to hz / site data
@@ -901,8 +901,8 @@ setReplaceMethod("hzdesgnname",
                    if(length(value)) {
                      # several ways to "reset" the hzdesgnname
                      if((value == "") | is.na(value) | is.null(value)) {
-                       value <- character(0)
-                       message("set horizon designation name column to `character` of length zero")
+                       value <- ""
+                       # message("set horizon designation name column to `character` of length zero")
                      } else if (!(value %in% horizonNames(object))) {
                        stop(paste0("horizon designation name (",value,") not in horizon data"), call.=FALSE)
                      }
@@ -953,7 +953,7 @@ setReplaceMethod("hztexclname", signature(object = "SoilProfileCollection"),
                    if(length(value)) {
                      # several ways to "reset" the hzdesgnname
                      if((value == "") | is.na(value) | is.null(value)) {
-                       value <- character(0)
+                       value <- ""
                        #message("set horizon texture class name to `character` of length zero")
                      } else if (! value %in% horizonNames(object)) {
                        stop("horizon texture class name not in horizon data", call.=TRUE)

R/SoilProfileCollection-iterators.R

@@ -1,7 +1,7 @@
 # profileApply
 
 if (!isGeneric("profileApply"))
- 	setGeneric("profileApply", function(object, FUN, 
+ 	setGeneric("profileApply", function(object, FUN,
  	                                    simplify = TRUE,
  	                                    frameify = FALSE,
  	                                    chunk.size = 100,
@@ -15,7 +15,7 @@ if (!isGeneric("profileApply"))
 
 		# get profile IDs
 		pIDs <- profile_id(object)
-    
+
 		## TODO: does this same any time / memory?
 		# pre-allocate list
 		l <- vector(mode = 'list', length = length(pIDs))
@@ -29,115 +29,115 @@ if (!isGeneric("profileApply"))
 		}
 
 		# optionally simplify
-		if(simplify) 
+		if(simplify)
 			return(unlist(l))
-		
+
 		return(l)
 }
 #' Iterate over profiles in a SoilProfileCollection
-#' 
+#'
 #' @name profileApply
-#' 
+#'
 #' @description Iterate over all profiles in a SoilProfileCollection, calling \code{FUN} on a single-profile SoilProfileCollection for each step.
-#' 
+#'
 #' @param object a SoilProfileCollection
-#' 
+#'
 #' @param FUN a function to be applied to each profile within the collection
-#' 
+#'
 #' @param simplify logical, should the result be simplified to a vector? default: TRUE; see examples
-#' 
+#'
 #' @param frameify logical, should the result be collapsed into a data.frame? default: FALSE; overrides simplify argument; see examples
-#' 
+#'
 #' @param chunk.size numeric, size of "chunks" for faster processing of large SoilProfileCollection objects; default: 100
-#' 
+#'
 #' @param column.names character, optional character vector to replace frameify-derived column names; should match length of colnames() from FUN result; default: NULL
-#' 
+#'
 #' @param ... additional arguments passsed to FUN
 #'
 #' @return When simplify is TRUE, a vector of length nrow(object) (horizon data) or of length length(object) (site data). When simplify is FALSE, a list is returned. When frameify is TRUE, a data.frame is returned. An attempt is made to identify idname and/or hzidname in the data.frame result, safely ensuring that IDs are preserved to facilitate merging profileApply result downstream.
-#' 
+#'
 #' @aliases profileApply,SoilProfileCollection-method
 #' @docType methods
 #' @rdname profileApply
 #' @examples
-#'  
+#'
 #' data(sp1)
 #' depths(sp1) <- id ~ top + bottom
-#' 
+#'
 #' # estimate soil depth using horizon designations
 #' profileApply(sp1, estimateSoilDepth, name='name', top='top', bottom='bottom')
 #'
 #' # scale a single property 'prop' in horizon table
 #' # scaled = (x - mean(x)) / sd(x)
 #' sp1$d <- profileApply(sp1, FUN=function(x) round(scale(x$prop), 2))
 #' plot(sp1, name='d')
-#' 
+#'
 #' # compute depth-wise differencing by profile
 #' # note that our function expects that the column 'prop' exists
 #' f <- function(x) { c(x$prop[1], diff(x$prop)) }
 #' sp1$d <- profileApply(sp1, FUN=f)
 #' plot(sp1, name='d')
-#' 
+#'
 #' # compute depth-wise cumulative sum by profile
 #' # note the use of an anonymous function
 #' sp1$d <- profileApply(sp1, FUN=function(x) cumsum(x$prop))
 #' plot(sp1, name='d')
-#' 
+#'
 #' # compute profile-means, and save to @site
 #' # there must be some data in @site for this to work
 #' site(sp1) <- ~ group
 #' sp1$mean_prop <- profileApply(sp1, FUN=function(x) mean(x$prop, na.rm=TRUE))
-#' 
+#'
 #' # re-plot using ranks defined by computed summaries (in @site)
 #' plot(sp1, plot.order=rank(sp1$mean_prop))
-#' 
+#'
 #' ## iterate over profiles, calculate on each horizon, merge into original SPC
-#' 
+#'
 #' # example data
 #' data(sp1)
-#' 
+#'
 #' # promote to SoilProfileCollection
 #' depths(sp1) <- id ~ top + bottom
 #' site(sp1) <- ~ group
-#' 
+#'
 #' # calculate horizon thickness and proportional thickness
 #' # returns a data.frame result with multiple attributes per horizon
 #' thicknessFunction <- function(p) {
 #'   hz <- horizons(p)
 #'   depthnames <- horizonDepths(p)
-#'   res <- data.frame(profile_id(p), hzID(p), 
+#'   res <- data.frame(profile_id(p), hzID(p),
 #'                     thk=(hz[[depthnames[[2]]]] - hz[[depthnames[1]]]))
 #'   res$hz_prop <- res$thk / sum(res$thk)
 #'   colnames(res) <- c(idname(p), hzidname(p), 'hz_thickness', 'hz_prop')
 #'   return(res)
 #' }
-#' 
+#'
 #' # list output option with simplify=F, list names are profile_id(sp1)
 #' list.output <- profileApply(sp1, thicknessFunction, simplify = FALSE)
 #' head(list.output)
-#' 
+#'
 #' # data.frame output option with frameify=TRUE
 #' df.output <- profileApply(sp1, thicknessFunction, frameify = TRUE)
 #' head(df.output)
-#' 
-#' # since df.output contains idname(sp1) and hzidname(sp1), 
+#'
+#' # since df.output contains idname(sp1) and hzidname(sp1),
 #' # it can safely be merged by a left-join via horizons<- setter
 #' horizons(sp1) <- df.output
-#' 
+#'
 #' plot(density(sp1$hz_thickness, na.rm=TRUE), main="Density plot of Horizon Thickness")
-#' 
+#'
 #' ## iterate over profiles, subsetting horizon data
-#' 
+#'
 #' # example data
 #' data(sp1)
-#' 
+#'
 #' # promote to SoilProfileCollection
 #' depths(sp1) <- id ~ top + bottom
 #' site(sp1) <- ~ group
-#' 
+#'
 #' # make some fake site data related to a depth of some importance
 #' sp1$dep <- profileApply(sp1, function(i) {round(rnorm(n=1, mean=mean(i$top)))})
-#' 
+#'
 #' # custom function for subsetting horizon data, by profile
 #' # keep horizons with lower boundary < site-level attribute 'dep'
 #' fun <- function(i) {
@@ -150,112 +150,73 @@ if (!isGeneric("profileApply"))
 #'   # return modified SPC
 #'   return(i)
 #' }
-#' 
+#'
 #' # list of modified SoilProfileCollection objects
 #' l <- profileApply(sp1, fun, simplify=FALSE)
-#' 
+#'
 #' # re-combine list of SoilProfileCollection objects into a single SoilProfileCollection
 #' sp1.sub <- union(l)
-#' 
+#'
 #' # graphically check
 #' par(mfrow=c(2,1), mar=c(0,0,1,0))
 #' plot(sp1)
 #' points(1:length(sp1), sp1$dep, col='red', pch=7)
 #' plot(sp1.sub)
-#' 
-setMethod(f='profileApply', signature='SoilProfileCollection', function(object, FUN, 
-                        simplify = TRUE, 
+#'
+setMethod(f='profileApply', signature='SoilProfileCollection', function(object, FUN,
+                        simplify = TRUE,
                         frameify = FALSE,
-                        chunk.size = 100, 
-                        column.names = NULL, 
+                        chunk.size = 100,
+                        column.names = NULL,
                         ...) {
   if(simplify & frameify) {
     # simplify and frameify are both TRUE -- ignoring simplify argument
     simplify <- FALSE
   }
-            
-  # total number of profiles we have to iterate over  
+
+  # total number of profiles we have to iterate over
   n <- length(object)
   o.name <- idname(object)
   o.hname <- hzidname(object)
-  
+
   # split the SPC of size n into chunk.size chunks
   chunk <- sort(1:n %% max(1, round(n / chunk.size))) + 1
-  
+
   # we first iterate over list of chunks of size chunk.size, keeping lists smallish
   # by dividing by a tunable factor -- set as 100 by default
   # then we iterate through each chunk, calling FUN on each element (profile)
   # then, concatenate the result into a list (or vector if simplify == TRUE)
   res <- do.call('c', lapply(split(1:n, chunk), function(idx) {
     .profileApply(object[idx,], FUN, simplify, ...)
   }))
-  
+
   # return profile IDs if it makes sense for result
   if(length(res) == length(object))
     names(res) <- profile_id(object)
-
-  # return horizon IDs if it makes sense for result
-  if(!simplify & inherits(res, 'data.frame'))
-    if(nrow(res) == nrow(object)) 
-      names(res) <- hzID(object)   
-
+
   # combine a list (one element per profile) into data.frame result
   if(!simplify & frameify) {
-    
+
     # make sure the first result is a data.frame (i.e. FUN returns a data.frame)
     if(is.data.frame(res[[1]])) {
-      
+
       # make a big data.frame
       res <- as.data.frame(do.call('rbind', res), stringsAsFactors = FALSE)
-      
+
       # get ids
       pid <- profile_id(object)
       hz.id <- hzID(object)
-
-      # determine if merge of res into @horizon or @site is feasible/reasonable
-      # if so, we want to keep track of unique site and horizon IDs
-
-      # if hzidname is in big df and all hzID in result are from parent object...
-      if(o.hname %in% colnames(res) & all(res[[o.hname]] %in% hz.id)) {
-
-        # make a master site/horizon id table (all in SPC)
-        pid.by.hz <- horizons(object)[[o.name]]
-        id.df <- data.frame(pid.by.hz, hz.id, stringsAsFactors = FALSE)
-        colnames(id.df) <- c(o.name, o.hname)
-
-        # warn if some hz IDs are missing in result
-        if(!all(hz.id %in% res[[o.hname]])) {
-          warning("frameify found horizon ID (", o.hname, ") in result but some IDs are missing!", call.=FALSE)
-        }
-
-        # do a left join, filling in any missing idname, hzidname from res with NA
-        res <- merge(id.df, res, all.x = TRUE, sort=FALSE)
-
-      } else if(o.name %in% colnames(res) & all(res[[o.name]] %in% pid)) {
-
-        # same as above, only for site level summaries (far more common)
-        id.df <- data.frame(pid, stringsAsFactors = FALSE)
-        colnames(id.df) <- c(o.name)
-
-        if(!all(pid %in% res[[o.name]])) {
-          # this shouldn't really happen -- usually a problem with FUN
-          warning("frameify found site ID (", o.name, ") in result but some IDs are missing!", call.=FALSE)
-        }
-
-        # do a left join, filling in any missing idname from res with NA
-        res <- merge(id.df, res, all.x = TRUE, sort=FALSE)
-      }
-
-      if(!is.null(column.names))
+
+      if (!is.null(column.names))
         colnames(res) <- column.names
-      
+
     } else {
       warning("first result is not class `data.frame` and frameify is TRUE. defaulting to list output.", call. = FALSE)
     }
   }
-  
+
   if(simplify)
    return(unlist(res))
-  
+
   return(res)
 })

R/SoilProfileCollection-methods.R

@@ -483,14 +483,12 @@ setMethod("subsetProfiles", signature(object = "SoilProfileCollection"),
 
             # subset using conventional data.frame methods
             if (!missing(s))
-              s.d.sub.IDs <-
-              subset(s.d, select = id.col, subset = eval(parse(text = s)))[, 1] # convert to vector
+              s.d.sub.IDs <- subset(s.d, select = id.col, subset = eval(parse(text = s)))[, 1] # convert to vector
             else
               s.d.sub.IDs <- NA
 
             if (!missing(h))
-              h.d.sub.IDs <-
-              subset(h.d, select = id.col, subset = eval(parse(text = h)))[, 1] # convert to vector
+              h.d.sub.IDs <- subset(h.d, select = id.col, subset = eval(parse(text = h)))[, 1] # convert to vector
             else
               h.d.sub.IDs <- NA
 

R/SoilProfileCollection-spatial.R

@@ -82,17 +82,15 @@ setReplaceMethod("coordinates", "SoilProfileCollection",
 
   # assign to sp slot
   # note that this will clobber any existing spatial data
-  object@sp <- SpatialPoints(coords=mf)
+  object@sp <- SpatialPoints(coords = mf)
 
   # remove coordinates from source data
   # note that mf is a matrix, so we need to access the colnames differently
   coord_names <- dimnames(mf)[[2]]
-  idx <- match(coord_names, siteNames(object))
+  sn <- siteNames(object)
 
-  # remove the named site data from site_data
-  # TODO we should use a proper setter!
-  # bug fix c/o Jose Padarian: drop=FALSE
-  object@site <- site(object)[, -idx, drop=FALSE]
+  # @site minus coordinates "promoted" to @sp
+  object@site <- .data.frame.j(object@site, sn[!sn %in% coord_names], aqp_df_class(object))
 
   # done
   return(object)