GHA run for more-leaves branch

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

@@ -93,6 +93,7 @@ jobs:
         run: |
           install.packages("pak")
           install.packages("pkgdepends")
+          pak::pkg_install("ms609/TreeTools@more-leaves")
         shell: Rscript {0}
 
       - name: pak bug workaround - install TreeDist (CRAN)

.github/workflows/memcheck.yml

@@ -87,6 +87,7 @@ jobs:
 
       - name: Install dependencies
         run: |
+          remotes::install_github("ms609/TreeTools", "more-leaves")
           remotes::install_deps(dependencies = TRUE)
           remotes::install_cran("devtools")
         shell: Rscript {0}

DESCRIPTION

@@ -1,4 +1,4 @@
-Package: TreeDist
+Package: BigTreeDist
 Type: Package
 Title: Calculate and Map Distances Between Phylogenetic Trees
 Version: 2.6.3.9001
@@ -48,7 +48,7 @@ Imports:
   Rdpack (>= 0.7),
   shiny,
   shinyjs,
-  TreeTools (>= 1.7.2),
+  BigTreeTools (>= 1.7.2),
 Suggests:
   bookdown,
   cluster,
@@ -77,7 +77,9 @@ Suggests:
   vdiffr (>= 1.0.0),
 LinkingTo: 
   Rcpp,
-  TreeTools,
+  BigTreeTools,
+Remotes:
+  ms609/TreeTools@more-leaves
 RdMacros: Rdpack
 VignetteBuilder: knitr
 Config/Needs/check: rcmdcheck

NAMESPACE

@@ -118,33 +118,33 @@ export(TreeDistPlot)
 export(TreeDistance)
 export(TreesConsistentWithTwoSplits)
 export(VisualizeMatching)
+importFrom(BigTreeTools,AllAncestors)
+importFrom(BigTreeTools,KeepTip)
+importFrom(BigTreeTools,LnRooted.int)
+importFrom(BigTreeTools,LnTreesMatchingSplit)
+importFrom(BigTreeTools,Log2Rooted.int)
+importFrom(BigTreeTools,Log2TreesMatchingSplit)
+importFrom(BigTreeTools,Log2Unrooted)
+importFrom(BigTreeTools,Log2Unrooted.int)
+importFrom(BigTreeTools,MSTEdges)
+importFrom(BigTreeTools,MSTLength)
+importFrom(BigTreeTools,NRooted)
+importFrom(BigTreeTools,NSplits)
+importFrom(BigTreeTools,NTip)
+importFrom(BigTreeTools,PectinateTree)
+importFrom(BigTreeTools,Postorder)
+importFrom(BigTreeTools,Preorder)
+importFrom(BigTreeTools,RenumberTips)
+importFrom(BigTreeTools,RootOnNode)
+importFrom(BigTreeTools,SplitInformation)
+importFrom(BigTreeTools,SplitsInBinaryTree)
+importFrom(BigTreeTools,TipLabels)
+importFrom(BigTreeTools,TipsInSplits)
+importFrom(BigTreeTools,TreeIsRooted)
+importFrom(BigTreeTools,TreesMatchingSplit)
+importFrom(BigTreeTools,as.ClusterTable)
+importFrom(BigTreeTools,as.Splits)
 importFrom(Rdpack,reprompt)
-importFrom(TreeTools,AllAncestors)
-importFrom(TreeTools,KeepTip)
-importFrom(TreeTools,LnRooted.int)
-importFrom(TreeTools,LnTreesMatchingSplit)
-importFrom(TreeTools,Log2Rooted.int)
-importFrom(TreeTools,Log2TreesMatchingSplit)
-importFrom(TreeTools,Log2Unrooted)
-importFrom(TreeTools,Log2Unrooted.int)
-importFrom(TreeTools,MSTEdges)
-importFrom(TreeTools,MSTLength)
-importFrom(TreeTools,NRooted)
-importFrom(TreeTools,NSplits)
-importFrom(TreeTools,NTip)
-importFrom(TreeTools,PectinateTree)
-importFrom(TreeTools,Postorder)
-importFrom(TreeTools,Preorder)
-importFrom(TreeTools,RenumberTips)
-importFrom(TreeTools,RootOnNode)
-importFrom(TreeTools,SplitInformation)
-importFrom(TreeTools,SplitsInBinaryTree)
-importFrom(TreeTools,TipLabels)
-importFrom(TreeTools,TipsInSplits)
-importFrom(TreeTools,TreeIsRooted)
-importFrom(TreeTools,TreesMatchingSplit)
-importFrom(TreeTools,as.ClusterTable)
-importFrom(TreeTools,as.Splits)
 importFrom(ape,Nnode.phylo)
 importFrom(ape,drop.tip)
 importFrom(ape,edgelabels)
@@ -182,4 +182,4 @@ importFrom(stats,sd)
 importFrom(stats,setNames)
 importFrom(stats,var)
 importFrom(utils,combn)
-useDynLib(TreeDist, .registration = TRUE)
+useDynLib(BigTreeDist, .registration = TRUE)

R/TreeDist-package.R → R/BigTreeDist-package.R

@@ -112,21 +112,21 @@
 #' 
 #' @references
 #' 
-#' - \insertRef{Bocker2013}{TreeDist}
+#' - \insertRef{Bocker2013}{BigTreeDist}
 #' 
-#' - \insertRef{Bogdanowicz2012}{TreeDist}
+#' - \insertRef{Bogdanowicz2012}{BigTreeDist}
 #' 
-#' - \insertRef{Kendall2016}{TreeDist}
+#' - \insertRef{Kendall2016}{BigTreeDist}
 #' 
-#' - \insertRef{Li1996}{TreeDist}
+#' - \insertRef{Li1996}{BigTreeDist}
 #' 
-#' - \insertRef{Lin2012}{TreeDist}
+#' - \insertRef{Lin2012}{BigTreeDist}
 #' 
-#' - \insertRef{Nye2006}{TreeDist}
+#' - \insertRef{Nye2006}{BigTreeDist}
 #' 
-#' - \insertRef{SmithDist}{TreeDist}
+#' - \insertRef{SmithDist}{BigTreeDist}
 #' 
-#' - \insertRef{SmithSpace}{TreeDist}
+#' - \insertRef{SmithSpace}{BigTreeDist}
 #' 
 #' @encoding UTF-8
 #' @keywords internal

R/Information.R

@@ -22,7 +22,7 @@
 #' trees consistent with two splits.
 #' 
 #' `SplitSharedInformation()` returns the phylogenetic information that two splits
-#' have in common \insertCite{Meila2007}{TreeDist}, in bits.
+#' have in common \insertCite{Meila2007}{BigTreeDist}, in bits.
 #' 
 #' `SplitDifferentInformation()` returns the amount of phylogenetic information
 #' distinct to one of the two splits, in bits.
@@ -47,7 +47,7 @@
 #' @references \insertAllCited{}
 #' 
 #' @family information functions
-#' @importFrom TreeTools Log2TreesMatchingSplit Log2Unrooted
+#' @importFrom BigTreeTools Log2TreesMatchingSplit Log2Unrooted
 #' @export
 SplitSharedInformation <- function(n, A1, A2 = A1) {
   Log2Unrooted(n) +
@@ -57,7 +57,7 @@ SplitSharedInformation <- function(n, A1, A2 = A1) {
 }
 
 #' @describeIn SplitSharedInformation Different information between two splits.
-#' @importFrom TreeTools SplitInformation
+#' @importFrom BigTreeTools SplitInformation
 #' @export
 SplitDifferentInformation <- function(n, A1, A2 = A1) {
   Log2TreesMatchingSplit(A1, n - A1) +
@@ -69,10 +69,10 @@ SplitDifferentInformation <- function(n, A1, A2 = A1) {
 #' Use variation of clustering information to compare pairs of splits
 #' 
 #' Compare a pair of splits viewed as clusterings of taxa, using the variation
-#' of clustering information proposed by \insertCite{Meila2007}{TreeDist}.
+#' of clustering information proposed by \insertCite{Meila2007}{BigTreeDist}.
 #' 
 #' This is equivalent to the mutual clustering information
-#' \insertCite{Vinh2010}{TreeDist}.
+#' \insertCite{Vinh2010}{BigTreeDist}.
 #' For the total information content, multiply the VoI by the number of leaves.
 #' 
 #' @template split12Params
@@ -146,8 +146,8 @@ MeilaMutualInformation <- function(split1, split2) {
 #' Variation of information for all split pairings
 #' 
 #' Calculate the variation of clustering information
-#' \insertCite{Meila2007}{TreeDist} for each possible pairing of
-#' non-trivial splits on _n_ leaves \insertCite{SmithDist}{TreeDist},
+#' \insertCite{Meila2007}{BigTreeDist} for each possible pairing of
+#' non-trivial splits on _n_ leaves \insertCite{SmithDist}{BigTreeDist},
 #' tabulating the number of pairings with each similarity.
 #' 
 #' @param n Integer specifying the number of leaves in a tree.
@@ -211,8 +211,8 @@ AllSplitPairings <- memoise(function(n) {
 #' two groups.
 #' Further details are available in a 
 #' [vignette](https://ms609.github.io/TreeDist/articles/information.html),
-#' \insertCite{Mackay2003;textual}{TreeDist} and
-#' \insertCite{Meila2007;textual}{TreeDist}.
+#' \insertCite{Mackay2003;textual}{BigTreeDist} and
+#' \insertCite{Meila2007;textual}{BigTreeDist}.
 #' 
 #' @template split12Params
 #' 
@@ -259,7 +259,7 @@ SplitEntropy <- function(split1, split2 = split1) {
 
 #' @describeIn SplitSharedInformation Number of trees consistent with two 
 #' splits.
-#' @importFrom TreeTools TreesMatchingSplit NRooted
+#' @importFrom BigTreeTools TreesMatchingSplit NRooted
 #' @export
 TreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
 
@@ -306,7 +306,7 @@ TreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
 
 #' @describeIn SplitSharedInformation Natural logarithm of 
 #' `TreesConsistentWithTwoSplits()`.
-#' @importFrom TreeTools LnTreesMatchingSplit LnRooted.int
+#' @importFrom BigTreeTools LnTreesMatchingSplit LnRooted.int
 #' @export
 LnTreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
   smallSplit <- min(A1, A2)
@@ -326,7 +326,7 @@ LnTreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
 
 #' @describeIn SplitSharedInformation Base two logarithm of 
 #' `TreesConsistentWithTwoSplits()`.
-#' @importFrom TreeTools Log2TreesMatchingSplit Log2Rooted.int
+#' @importFrom BigTreeTools Log2TreesMatchingSplit Log2Rooted.int
 #' @export
 Log2TreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
   smallSplit <- min(A1, A2)
@@ -346,7 +346,7 @@ Log2TreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
 
 #' @describeIn SplitSharedInformation Base 2 logarithm of 
 #' `TreesConsistentWithTwoSplits()`.
-#' @importFrom TreeTools Log2TreesMatchingSplit Log2Rooted.int
+#' @importFrom BigTreeTools Log2TreesMatchingSplit Log2Rooted.int
 #' @export
 Log2TreesConsistentWithTwoSplits <- function(n, A1, A2 = A1) {
   smallSplit <- min(A1, A2)

R/RcppExports.R

@@ -2,54 +2,54 @@
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
 COMCLUST <- function(trees) {
-    .Call(`_TreeDist_COMCLUST`, trees)
+    .Call(`_BigTreeDist_COMCLUST`, trees)
 }
 
 consensus_info <- function(trees, phylo, p) {
-    .Call(`_TreeDist_consensus_info`, trees, phylo, p)
+    .Call(`_BigTreeDist_consensus_info`, trees, phylo, p)
 }
 
 robinson_foulds_all_pairs <- function(tables) {
-    .Call(`_TreeDist_robinson_foulds_all_pairs`, tables)
+    .Call(`_BigTreeDist_robinson_foulds_all_pairs`, tables)
 }
 
 lapjv <- function(x, maxX) {
-    .Call(`_TreeDist_lapjv`, x, maxX)
+    .Call(`_BigTreeDist_lapjv`, x, maxX)
 }
 
 cpp_mast <- function(edge1, edge2, nTip) {
-    .Call(`_TreeDist_cpp_mast`, edge1, edge2, nTip)
+    .Call(`_BigTreeDist_cpp_mast`, edge1, edge2, nTip)
 }
 
 cpp_nni_distance <- function(edge1, edge2, nTip) {
-    .Call(`_TreeDist_cpp_nni_distance`, edge1, edge2, nTip)
+    .Call(`_BigTreeDist_cpp_nni_distance`, edge1, edge2, nTip)
 }
 
 cpp_robinson_foulds_distance <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_robinson_foulds_distance`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_robinson_foulds_distance`, x, y, nTip)
 }
 
 cpp_robinson_foulds_info <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_robinson_foulds_info`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_robinson_foulds_info`, x, y, nTip)
 }
 
 cpp_matching_split_distance <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_matching_split_distance`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_matching_split_distance`, x, y, nTip)
 }
 
 cpp_jaccard_similarity <- function(x, y, nTip, k, allowConflict) {
-    .Call(`_TreeDist_cpp_jaccard_similarity`, x, y, nTip, k, allowConflict)
+    .Call(`_BigTreeDist_cpp_jaccard_similarity`, x, y, nTip, k, allowConflict)
 }
 
 cpp_msi_distance <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_msi_distance`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_msi_distance`, x, y, nTip)
 }
 
 cpp_mutual_clustering <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_mutual_clustering`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_mutual_clustering`, x, y, nTip)
 }
 
 cpp_shared_phylo <- function(x, y, nTip) {
-    .Call(`_TreeDist_cpp_shared_phylo`, x, y, nTip)
+    .Call(`_BigTreeDist_cpp_shared_phylo`, x, y, nTip)
 }
 

R/cluster_stats.R

@@ -255,7 +255,7 @@ MeanMSTEdge.numeric <- function(x, cluster = 1) {
          numeric(1))
 }
 
-#' @importFrom TreeTools MSTLength
+#' @importFrom BigTreeTools MSTLength
 .MeanMSTEdge <- function(x) {
   n <- dim(x)[1]
   # Return:

R/kmeanspp.R

@@ -1,11 +1,11 @@
 #' k-means++ clustering
 #'
-#' k-means++ clustering \insertCite{Arthur2007}{TreeDist} improves the speed and
+#' k-means++ clustering \insertCite{Arthur2007}{BigTreeDist} improves the speed and
 #' accuracy of standard \code{\link[stats]{kmeans}} clustering
-#' \insertCite{Hartigan1979}{TreeDist} by preferring initial cluster centres 
+#' \insertCite{Hartigan1979}{BigTreeDist} by preferring initial cluster centres 
 #' that are far from others.
 #' A scalable version of the algorithm has been proposed for larger data sets
-#' \insertCite{Bahmani2012}{TreeDist}, but is not implemented here.
+#' \insertCite{Bahmani2012}{BigTreeDist}, but is not implemented here.
 #' 
 #' @param x Numeric matrix of data, or an object that can be coerced to such a
 #' matrix (such as a numeric vector or a data frame with all numeric columns).

R/lap.R

@@ -1,14 +1,14 @@
 #' Solve linear assignment problem using LAPJV
 #'
-#' Use the algorithm of \insertCite{Jonker1987;textual}{TreeDist} to solve the 
+#' Use the algorithm of \insertCite{Jonker1987;textual}{BigTreeDist} to solve the 
 #' [Linear Sum Assignment Problem](
 #' http://www.assignmentproblems.com/doc/LSAPIntroduction.pdf).
 #' 
 #' The Linear Assignment Problem seeks to match each row of a matrix with a 
 #' column, such that the cost of the matching is minimized.
 #' 
 #' The Jonker & Volgenant approach is a faster alternative to the Hungarian
-#' algorithm \insertCite{Munkres1957}{TreeDist}, which is implemented in 
+#' algorithm \insertCite{Munkres1957}{BigTreeDist}, which is implemented in 
 #' `clue::solve_LSAP()`.
 #' 
 #' Note: the JV algorithm expects integers. In order to apply the function

R/median.R

@@ -56,7 +56,7 @@
 #' 
 #' @seealso Consensus methods:
 #'   [`ape::consensus()`],
-#'   [`TreeTools::ConsensusWithout()`]
+#'   [`BigTreeTools::ConsensusWithout()`]
 #'   
 #' @importFrom stats median
 #' @family tree space functions

R/plot.R

@@ -104,7 +104,7 @@ TreeDistPlot <- function(tr, title = NULL, bold = NULL, leaveRoom = FALSE,
 #' @importFrom ape nodelabels edgelabels plot.phylo
 #' @importFrom colorspace qualitative_hcl sequential_hcl
 #' @importFrom graphics par
-#' @importFrom TreeTools as.Splits
+#' @importFrom BigTreeTools as.Splits
 #' 
 #' @examples 
 #' tree1 <- TreeTools::BalancedTree(6)
@@ -270,14 +270,14 @@ VisualizeMatching <- function(Func, tree1, tree2, setPar = TRUE,
 #' 
 #' To identify strain in a multidimensional scaling of distances, it can be
 #' useful to plot a minimum spanning tree
-#' \insertCite{Gower1966,SmithSpace}{TreeDist}.  Colouring each edge of the
+#' \insertCite{Gower1966,SmithSpace}{BigTreeDist}.  Colouring each edge of the
 #' tree according to its strain can identify areas where the mapping is
 #' stretched or compressed.
 #' 
 #' @param mapping Two-column matrix giving _x_ and _y_ coordinates of plotted
 #' points.
 #' @param mstEnds Two-column matrix identifying rows of `mapping` at end of
-#' each edge of the MST, as output by [`TreeTools::MSTEdges()`].
+#' each edge of the MST, as output by [`BigTreeTools::MSTEdges()`].
 #' @param distances Matrix or `dist` object giving original distances between
 #' each pair of points.
 #' @param palette Vector of colours with which to colour edges.
@@ -323,7 +323,7 @@ MSTSegments <- function(mapping, mstEnds, ...) {
 #' early in `palette` assigned to edges in which the ratio of mapped
 #' distance to original distance is small.
 #' @importFrom grDevices hcl.colors
-#' @importFrom TreeTools MSTEdges
+#' @importFrom BigTreeTools MSTEdges
 #' @export
 StrainCol <- function(distances, mapping, mstEnds = MSTEdges(distances),
                       palette = rev(hcl.colors(256L, "RdYlBu"))) {