Changes related the constr.hclust functionality (#34)

* Updates related to constr.hclust version 1.6_4

* Updates related to constr.hclust version 1.6_4

* Updates related to constr.hclust version 1.6_4

DESCRIPTION

@@ -41,5 +41,5 @@ URL: https://github.com/adeverse/adespatial, http://adeverse.github.io/adespatia
 BugReports: https://github.com/adeverse/adespatial/issues
 Encoding: UTF-8
 NeedsCompilation: yes
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 VignetteBuilder: knitr

NAMESPACE

@@ -166,6 +166,7 @@ importFrom(stats,t.test)
 importFrom(stats,var)
 importFrom(stats,weighted.mean)
 importFrom(utils,edit)
+importFrom(utils,head)
 importFrom(utils,modifyList)
 importFrom(utils,tail)
 importFrom(vegan,RsquareAdj)

R/ScotchWhiskey.R

@@ -1,10 +1,12 @@
 ## **************************************************************************
 ##
-##    (c) 2018-2022 Guillaume Guénard
+##    (c) 2018-2024 Guillaume Guénard
 ##        Department de sciences biologiques
 ##        Université de Montréal
 ##        Montreal, QC, Canada
 ##
+##    **Data set: Scotch Whiskey**
+##
 ## **************************************************************************
 ##
 #' Scotch Whiskey Data Set
@@ -13,66 +15,71 @@
 #'
 #' @docType data
 #' 
-#' @keywords Scotch Whiskey datasets
+#' @keywords Scotch Whiskey
 #' 
 #' @name ScotchWhiskey
 #' 
 #' @usage data(ScotchWhiskey)
 #' 
 #' @format A list with 12 members:
 #' \describe{
-#' \item{geo}{A \code{\link{SpatialPointsDataFrame-class}} object containing the
-#' geographic coordinates and other information about the distilleries.}
+#' \item{geo}{A \code{\link[sp]{SpatialPointsDataFrame-class}} object containing
+#' the geographic coordinates and other information about the distilleries.}
 #' \item{colour}{The whiskey colour coded as a 14-level factor.}
 #' \item{nose}{A set of 12 nasal notes (boolean).}
 #' \item{body}{A set of 8 body notes (boolean).}
 #' \item{palate}{A set of 15 palatine notes (boolean).}
 #' \item{finish}{A set of 19 finish (or after-taste) notes (boolean).}
 #' \item{nbChar}{Number of characteristics attributed to each distillery for
 #' each of the four sets of boolean features: nose, body, palate, finish.}
-#' \item{listW}{A \code{listw} object (see \code{\link{nb2listw}})
-#' containing information about the spatial edges (neighbour links) between the distilleries.}
+#' \item{listW}{A \code{listw} object (see \code{\link[spdep]{nb2listw}})
+#' containing information about the spatial edges (neighbour links) between the
+#' distilleries.}
 #' \item{links.mat}{A binary square matrix of the spatial connexions between the
 #' distilleries (contiguity matrix).}
-#' \item{neighbors}{A \code{\link{SpatialLinesDataFrame-class}} object
+#' \item{neighbors}{A \code{\link[sp]{SpatialLinesDataFrame-class}} object
 #' containing geographic information about the spatial links between the
 #' distilleries.}
 #' \item{dist}{A list of distance matrices obtained for each of the four sets of
-#' boolean features.} }
+#' boolean features.}
+#' }
 #' 
 #' @details There are 5 data sets: color, nose, body, palate, and finish. The
-#' binary (0,1) descriptors are in the same order as on p. 239 of the whisky paper.
-#'
+#' binary (0,1) descriptors are in the same order as on p. 239 of the whisky
+#' paper.
+#' 
 #' There are two whiskies in the classification from the Springbank distillery.
 #' One pertains to the Islay group, the other to the Western group.
 #' 
 #' Please let us know of the analyses you have performed with the whiskey data,
 #' especially if you intend to publish them.
-#'
+#' 
 #' The distance matrices were calculated separately as follows for each tasting
 #' data set:
-#'
+#' 
 #' D = (1 - S4)^0.5,
-#'
+#' 
 #' where S4 is the Simple matching coefficient of Sokal & Michener (1958). This
 #' coefficient was called S4 in the Gower & Legendre (1986) paper and S1 in the
-#' Legendre & Legendre (2012) book. In package ade4, coefficient
-#' D = sqrt(1 - S4) is computed by function \code{\link{dist.binary}} using
+#' Legendre & Legendre (2012) book. In package \code{ade4}, coefficient
+#' D = sqrt(1 - S4) is computed by function \code{dist.binary} using
 #' argument \code{"method=2"}.
 #' 
-#' @source Pierre Legendre <pierre.legendre@@umontreal.ca> and François-Joseph
-#' Lapoints <francois-joseph.lapointe@@umontreal.ca>, Département de sciences
+#' @source
+#' Pierre Legendre <pierre.legendre@@umontreal.ca> and François-Joseph
+#' Lapointe <francois-joseph.lapointe@@umontreal.ca>, Département de sciences
 #' biologiques, Université de Montréal, Montréal, Québec, Canada.
 #' 
-#' @references Lapointe, F.-J. and P. Legendre. 1994. A classification of pure
-#' malt Scotch whiskies. Applied Statistics 43: 237-257
-#' <http://www.dcs.ed.ac.uk/home/jhb/whisky/lapointe/text.html>.
-#'
+#' @references
+#' Lapointe, F.-J. and P. Legendre. 1994. A classification of pure malt Scotch
+#' whiskies. Applied Statistics 43: 237-257 \doi{10.2307/2986124}
+#' 
 #' Gower, J.C. and Legendre, P. 1986. Metric and Euclidean properties of
 #' dissimilarity coefficients. Journal of Classification, 3, 5-48.
+#' \doi{10.1007/BF01896809}
 #' 
 #' Legendre, P. and Legendre, L. 2012. Numerical Ecology. 3rd English edition.
-#' Elsevier Science BV, Amsterdam.
+#' Elsevier Science BV, Amsterdam. \doi{10.1016/S0304-3800(00)00291-X}
 #' 
 #' @importFrom sp SpatialPointsDataFrame SpatialLinesDataFrame
 #' 
@@ -82,7 +89,7 @@
 #' ScotchWhiskey$listW  ## attr(ScotchWhiskey$listW,"class")
 #' names(ScotchWhiskey)
 #' names(ScotchWhiskey$dist)
-#' ##
+#' 
 #' plotWhiskey <- function(main) {
 #'     plot(x=ScotchWhiskey$geo@coords[,1L]/1000,
 #'          xlab="Eastings (km)",
@@ -104,42 +111,42 @@
 #'     )
 #'     invisible(NULL)
 #' }
-#' ##
+#' 
 #' plotWhiskey("Scotch whiskey: peat nose")
 #' cols <- c("blue","orange")
 #' points(ScotchWhiskey$geo@coords/1000,pch=21L,
 #'        bg=cols[ScotchWhiskey$nose[,"peat"]+1L])
 #' legend(x=50,y=1000,legend=c("Has a peat nose","Has no peat nose"),
 #'        pch=21L,pt.bg=rev(cols))
-#' ##
+#' 
 #' plotWhiskey("Scotch whiskey: soft body")
 #' cols <- c("red","green")
 #' points(ScotchWhiskey$geo@coords/1000,pch=21L,
 #'        bg=cols[ScotchWhiskey$body[,"soft"]+1L])
 #' legend(x=50,y=1000,legend=c("Has a soft body","Has no soft body"),
 #'        pch=21L,pt.bg=rev(cols))
-#' ##
+#' 
 #' plotWhiskey("Scotch whiskey: spicy palate")
 #' cols <- c("red","green")
 #' points(ScotchWhiskey$geo@coords/1000,pch=21L,
 #'        bg=cols[ScotchWhiskey$palate[,"spice"]+1L])
 #' legend(x=50,y=1000,legend=c("Has a spicy palate","Has no spicy palate"),
 #'        pch=21L,pt.bg=rev(cols))
-#' ##
+#' 
 #' plotWhiskey("Scotch whiskey: sweet finish")
 #' cols <- c("red","green")
 #' points(ScotchWhiskey$geo@coords/1000,pch=21L,
 #'        bg=cols[ScotchWhiskey$finish[,"sweet"]+1L])
 #' legend(x=50,y=1000,legend=c("Has a sweet finish","Has no sweet finish"),
 #'        pch=21L,pt.bg=rev(cols))
-#' ##
-#' ### To visualize (part of) the distance matrices:
+#' 
+#' ## To visualize (part of) the distance matrices:
 #' as.matrix(ScotchWhiskey$dist$nose)[1:5,1:5]
 #' as.matrix(ScotchWhiskey$dist$body)[1:5,1:5]
 #' as.matrix(ScotchWhiskey$dist$palate)[1:5,1:5]
 #' as.matrix(ScotchWhiskey$dist$finish)[1:5,1:5]
-#' ##
-#' ### The data tables:
+#' 
+#' ## The data tables:
 #' ScotchWhiskey$colour
 #' head(ScotchWhiskey$nose)
 #' head(ScotchWhiskey$body)

R/Tiahura.R

@@ -1,10 +1,12 @@
 ## **************************************************************************
 ##
-##    (c) 2018-2022 Guillaume Guénard
+##    (c) 2018-2024 Guillaume Guénard
 ##        Department de sciences biologiques
 ##        Université de Montréal
 ##        Montreal, QC, Canada
 ##
+##    **Tiahura transect fish data set**
+##
 ## **************************************************************************
 ##
 #' Tiahura Transect Fish Data Set
@@ -14,7 +16,7 @@
 #' 
 #' @docType data
 #' 
-#' @keywords Tiahura datasets
+#' @keywords Tiahura
 #' 
 #' @name Tiahura
 #' 
@@ -108,7 +110,7 @@
 #'                               chron=TRUE)
 #' 
 #' ## Plotting the results
-#' oldpar <- par(mfrow=c(3,1))
+#' par(mfrow=c(3,1))
 #' 
 #' ## First graph: constrained clusters
 #' par(mar=c(3,6.5,2,2))
@@ -169,13 +171,13 @@
 #'   axis(2L,at=1:nrow(Tiahura$fish),label=rownames(Tiahura$fish),las=1L)
 #'   invisible(NULL)
 #' }
-#' ##
+#' 
 #' par(mar=c(15,5,2,2))
 #' plot_slice(1L,5L)
 #' ## plot_slice(2L,5L)
 #' ## plot_slice(3L,5L)
 #' ## plot_slice(4L,5L)
 #' ## plot_slice(5L,5L)
-#' par(oldpar)
+#' 
 NULL
 ##

R/constr.hclust-class.R

@@ -1,6 +1,6 @@
 ## **************************************************************************
 ##
-##    (c) 2018-2022 Guillaume Guénard
+##    (c) 2018-2024 Guillaume Guénard
 ##        Department de sciences biologiques,
 ##        Université de Montréal
 ##        Montreal, QC, Canada
@@ -60,6 +60,5 @@
 #' 
 #' @seealso \code{\link{hclust}-class}
 #' 
-#' @returns No return value
-#' 
 NULL
+