NEWS.md
Support comparison of trees with different tips.
Fix caching errors in MapDist() (#98).
Update tests for compatibility with ape 5.7
New functions to measure cluster sizes (see ?"cluster-statistics").
KMeansPP() conducts clustering using K-means++, replacing K-means in app.
New vignette on tree landscape analysis.
New vignette on how to compare tree sets.
PathVector() now treats trees with a root node as rooted.
Fix plot layout in treespace vignette.
Informative failure when not enough memory for consensus_info().
Replace throw with stop in C++.
Correct calculation of trustworthiness and continuity metrics.
Depict strain in minimum spanning trees with StrainCol() and helper function MSTSegments().
Update tests for consistency with “TreeTools” v1.7.
Use lighter Rcpp headers.
Support ConsensusInfo(p > 0.5).
Address hypervolume comparison in vignettes.
Support uniform manifold approximation and projection in app.
Speed improvements, using optimizations suggested by Alexis Stamatakis’ Bioinformatics group.
Support for parallel computation via StartParallel().
Progress bars.
Solaris compatibility.
Modest vignette improvements.
spic/scic abbreviation recognition.
ConsensusInfo() quickly calculates the splitwise information content of the consensus of a set of trees, after Smith (forthcoming).
SplitwiseInfo() and ClusteringInfo() gain a p parameter to reflect the reduced information content of splits with lower support values, and a sum parameter to allow return of individual split information content.
KCDiameter() approximates the diameter of the Kendall-Colijn metric.
Plot3() (experimental) provides pseudo-3D plotting.
Project()/ProjectionQuality() re-named to MapTrees()/MappingQuality().
SpectralClustering() re-named to SpectralEigens().
Diagnose and fix memory leaks, including over-long reported matchings.
Explicitly import shiny/shinyjs functions.
Project() launches ‘shiny’ app for projection and analysis of tree space.
ProjectionQuality() calculates trustworthiness and continuity of tree space mappings.
Faster calculation of Robinson–Foulds distance (using algorithm of Day (1985)) and clustering information distance.
New class ClusterTable to allow faster distance computation with Day (1985) algorithm.
Improve error messages in CalculateTreeDist().
Improvements to vignettes.
Use package ‘vdiffr’ conditionally.
TreeDistance() and related functions now return a dist object when computing all distances between all pairs of trees in a list.
Improve floating-point arithmetic in TreeDistance() functions.
TreeDistance() now returns a distance (as documented), rather than a similarity.
Fix rounding error in NNI ‘Li’ upper estimate, and improve NNI performance.
Reduce precision of LAPJV so rounding errors do not result in interminable run times.
Improvements to NNIDist() in light of Fack et al. (2002).
Add NNIDiameter(): approximate diameter of NNI distance.
Remove vignette ‘Interpreting tree distances’: duplicates https://ms609.github.io/TreeDistData/articles/09-expected-similarity.html.
Remove redundant data object oneOverlap.
Fix an issue when installing on R 3.x (require C++11 to ensure declaration of UINT_FAST16_MAX).
Fix memory-handling bug in lapjv().